CHIMERAS

Young or old it doesn't matter: we need them both

2012-03-15T05:32:00.001-07:00

To honor Brain Awareness Week I thought I'd try and discuss a neuroscience paper this week. It's not my field, so you'll have to be patient with me (and you experts out there are more than welcome to pitch in). I found a really fascinating story in the latest issue of Science [1] on the differences in information processing between "young" and "old" neurons. In order to understand the story, I had to take a couple of steps back and review a few things about the brain.

The hippocampus is the part of the brain that's responsible for learning, storing memories and associating them with feelings and emotions. Within the hippocampus lies the dentate gyrus, which is where adult neurogenesis takes place -- the formation of new neurons throughout adulthood. The middle layer of the dentate gyrus contains a type of neurons called granule cells. These are constantly generated and take a few weeks to develop and integrate in the dentate gyrus network. In [1], Marin-Burgin et al. asked the following question:

"Is it solely the continuous addition of new neurons to the network that is important, or are there specific functional properties only attributable to new granule cells (GCs) that are relevant to information processing?"

In order to answer the question, the researchers compared immature granule cells to mature ones in mouse hippocampus. The part that fascinates me the most about these experiments is that in order to "see" the different cells, these neurons are "retrovirally labeled to express red fluorescent protein." What this means is that a genetically engineered retrovirus that preferentially infects this type of cells is used to "infect" them and deliver the fluorescent proteins so that the neural activity can be visualized. Pretty cool, right?

Marin-Burgin et al. found that the dentate gyrus is made of a heterogeneous population of granule cells of different ages and that the different subpopulations have distinct activation thresholds. When given both excitatory and inhibitory input, the ratio of excitation to inhibition favors inhibition in mature granule cells, whereas immature cells have fewer inhibitory inputs (hehe, sounds familiar don't you think?). In other words, younger cells respond more easily and broadly, whereas older cells tend to be more specific. The fact that both are present at all times suggests that this range in different responses is needed for the correct functionality of the dentate gyrus, in particular for the correct storing and integration of novel information.

[1] Marin-Burgin, A., Mongiat, L., Pardi, M., & Schinder, A. (2012). Unique Processing During a Period of High Excitation/Inhibition Balance in Adult-Born Neurons Science, 335 (6073), 1238-1242 DOI: 10.1126/science.1214956

Human Immunodeficiency Virus model

2012-03-12T21:26:00.000-07:00

Human Immunodeficiency Virus model

This is so darn cool! Well, okay, for an HIV scientist like me... But still, click on the link: it'll give you all the inside views of the virus, and then, if you click on "view labels" on the upper left corner, it tells you what you're looking at and the reference to the paper that describes it. So awesome to have it all conveniently in one picture!

How nucleosomes "protect" our DNA

2012-03-12T06:54:00.001-07:00

Did you know that not all mutations happen at an equal rate? There are several kinds of mutations: substitutions, insertions, deletions, etc. Insertions and deletions happen when bits of DNA are either inserted or deleted, whereas substitutions happen when the overall length of the DNA locus doesn't change, but a base is substituted for another. As you all know, we have 4 nucleotides (A, C, G, and T), however, not all possible changes are equally likely. The most frequent substitutions are As with Gs and Cs with Ts.

Mutations happen because of errors in DNA replications or because of DNA lesions. These are chemical processes that are more or less likely depending on the circumstances. For example, DNA is "stronger" when it's a double helix, although occasionally the bonds between the two helices can locally denature, opening up a chance for a mutation to happen.

In all nucleated cells DNA is packaged inside the nucleus in units called nucleosomes: threads of DNA (~147 base pairs) wrap around "spools" formed by 8 protein units called histones. When the DNA is packed into nucleosomes it is more resistant and less prone to mutations. At the same time, chromatin, the assembly of all nucleosomes inside the nucleus, is hardly ever static. See this post where I discuss how nucleosomes are reassembled in order to promote the expression of certain genes versus others (a phenomenon called "chromatin remodeling"). A new study [1] published in the latest issue of Science investigates how the structure and assembly of DNA inside the cells affects the likelihood of certain mutations versus others. They found that nucleosomes act as regulators for substitution mutations, protecting DNA from damage. For example, compared to other DNA states, nucleosomal DNA undergoes 50% less C -> T mutations.

"Furthermore, the rates of G -> T and A -> T mutations were also about two-fold suppressed by nucleosomes. On the basis of these results, we conclude that nucleosome-dependent mutation spectra affect eukaryotic genome structure and evolution and may have implications for understanding the origin of mutations in cancers and in induced pluripotent stem cells."

Without getting into too many technical details, Chen et al. looked at the initial nucleosome profile from two replicates of the yeast Saccharomyces cerevisiae strain Y55, and then tracked subsequent mutations. They also looked at SNPs (single-nucleotide polymorphisms) in the germline of the Japanese killifish medaka. Germline cells are cells that give rise to oocytes and spermatocytes, hence mutations in this line are of evolutionary importance since they get carried on to subsequent generations.

We have revealed that nucleosomes, the most abundant eukaryotic protein-DNA complexes, likely function as a major regulator of substitution mutations in eukaryotes. Binding of proteins to DNA to suppress DNA breathing or to exclude endogenous mutagens may be how cells protect their DNA. However, DNA repair, which often works with varied efficiency between nucleosomal DNA and naked DNA, may also shape the base-specific mutation spectrum."

Chen, X., Chen, Z., Chen, H., Su, Z., Yang, J., Lin, F., Shi, S., & He, X. (2012). Nucleosomes Suppress Spontaneous Mutations Base-Specifically in Eukaryotes Science, 335 (6073), 1235-1238 DOI: 10.1126/science.1217580

Photo: light reflections (or is it refractions?) on a soap bubble. Shutter speed 1/125, focal length 100mm, F-stop f5, ISO speed 100.

GP 120!

2012-03-11T10:36:00.003-07:00

I took the above photo yesterday. As I was processing it, I suddenly froze and thought, "GP 120!"

Check it out:

GP120 is the protein that sits on the outer shell (envelope) of HIV and binds to target cells. A trimer of three gp120 (together with three gp41, another protein) bound together forms the "spike" you see in the above picture.

Something tells me I've been working too hard if I suddenly see gp120 in tulips.
Fascinating, though, how these trimeric structures come up in nature, don't you think?

How are new viruses made?

2012-03-08T06:21:00.004-08:00

I'm sure you are all familiar with H1N1, the influenza strain that emerged in 2009 and which contained genetic elements from four different strains: two swine flu strains, one avian flu strain, and one human flu strain.

How did this incredible mix-up happen?

One thing I've learned in the five years I've spent studying viruses is that these little things are genetic brewing machines (I just made that expression up, please don't quote me!). They can carry genetic material from different organisms, they can integrate in the host's genome, they can transport genetic material from one organism to another. The viral genome of a flu virus in particular is split in different portions called segments. Now suppose an avian flu virus and a swine flu virus infect the same hosts, and two viral particles coinfect the same cell inside the host. Yes, you've guessed it: the genetic segments from the two distinct viruses can indeed "reshuffle" and create a completely new virus. In the case of H1N1, this pattern of coinfection and "reshuffling" (called segment reassortment) happened more than once and across three different hosts: birds, pigs, and humans.

Reassortment of segmented viruses happens when two genetically distinct viral species coinfect the same cell and exchange genomic segments, a mechanism that ensures rapid novel virus creation. In the past, novel influenza strains have appeared when the virus's genomic segments reasserted with non-human flu genomic segments. The host's immune system may be prepared to recognize either strain but not a combination of both, hence the new virus can, potentially, evade adaptive immunity.

An interesting bit of the puzzle is that this reassortment does not appear to be random: there is a "reassortment bias", in other words, not all possible "reshufflings" of the genomic segments are equally likely to happen. There are constraints in terms of the genetic information that needs to be exchanged across the segments in order to make a new virus. The ability to predict which reassortments are most likely can help us be prepared for future outbreaks like H1N1.

In a recent PNAS paper [1], Greenbaum et al. use the mathematical framework of information theory to infer the viral populations produced by a coinfection out of the possible repertoire of progeny viruses. They look at quantities like entropy and mutual information to measure the genetic variation, predict which segments share relevant genetic information, and derive general segregation rules of how reassortment may happen.

"We study, for influenza and other segmented viruses, the extent to which a virus’s segments can communicate strain information across an infection and among one another. Our approach goes beyond previous association studies and quantifies how much the diversity of emerging strains is altered by patterns in reassortment, whether biases are consistent across multiple strains and cell types, and if significant information is shared among more than two segments. [1]"

Mutual information gives an upper bound on how much information strains can exchange. Pushing the rate of reassortment past this bound would disrupt viral segment communication and stop the creation of new virus. This is something I've heard about viral mutation rates, as well. Rapid turnover in genetic diversity is an advantage for tiny organisms like viruses and bacteria because it allows them to quickly develop escapes to the immune system: it's the Red Queen Effect I've talked about in the previous post. However, if this turnover it's too quick you get the opposite effect: when you go past the limit and start accumulating too much diversity, the population rapidly goes extinct because deleterious mutations happen more frequently than advantageous ones. This suggests that tweaking the diversity increase beyond this limit may be a novel defense strategy.

"Understanding how much these segments transfer information about their strain of origin, and to what extent this is possible, can ultimately lead to novel antiviral strategies."

Greenbaum, B., Li, O., Poon, L., Levine, A., & Rabadan, R. (2012). From the Cover: Viral reassortment as an information exchange between viral segments Proceedings of the National Academy of Sciences, 109 (9), 3341-3346 DOI: 10.1073/pnas.1113300109

It takes all the running you can do to keep in the same place

2012-03-05T05:40:00.014-08:00

"Now, here, you see, it takes all the running you can do, to keep in the same place. If you want to get somewhere else, you must run at least twice as fast as that!"
~Lewis Carroll, Through the Looking Glass

The Red Queen Effect is a genetic effect named after Lewis Carroll's famous quote, "It takes all the running you can do to keep in the same place." As it turns out, Carroll's witty and paradoxical thinking fits viral host evolution: out of the whole viral population, only a few manage to infect new hosts -- these are the viruses that are fit enough to overcome the first hurdle (bottleneck) of "jumping" into a new host. Once there, though, these viral particles are not necessarily fit to survive the new host's environment because the defenses they have developed have been selected for in the previous host (this in genetics is called "fitness cost"). Therefore, they must mutate rapidly in order to acquire new defenses that will allow them to escape the new immune system.

Do you see why Carroll's Red Queen applies? A virus has to do all the running (mutating) it takes in order to keep (survive) in the same place (host).

Variety in hosts' immune responses is ensured by the MHC genes, the major histocompatibility complex genes in vertebrates. These genes, which are the most polymorphic among vertebrates, encode molecules found on all cell surfaces that mediate antigen presentation: when an antigen (any object, either a molecule or another organism, that is recognized as a "non-self" by the body) enters a cell, it is broken up and the bits of proteins are transported to the cell surface for "presentation" to the immune system. High variability in this class of molecules ensures that a wide range of antigens can be recognized and hence trigger the immune response. The high variability found in the MHC genes is the reason for the high variation in disease susceptibility in the population, for example, why a particular flu strain can keep one person in bed for a whole week, while another only gets a mild cold for a couple of days.

Just like the virus needs to do a lot of running in order to overcome the immune system, the immune system itself is at an advantage the more antigens it is able to recognize. So, you see, the Red Queen Effect, applies to both the host and the pathogen, leading to an antagonistic coevolution that ensures diversity in the MHC genes in the population.

A recent PNAS paper [1] investigates how this mechanism is maintained:

"One leading explanation, antagonistic coevolution (also known as the Red Queen), postulates a never-ending molecular arms race where pathogens evolve to evade immune recognition by common MHC alleles, which in turn provides a selective advantage to hosts carrying rare MHC alleles. This cyclical process leads to negative frequency-dependent selection and promotes MHC diversity if two conditions are met: (i) pathogen adaptation must produce trade-offs that result in pathogen fitness being higher in familiar (i.e., host MHC genotype adapted to) vs. unfamiliar host MHC genotypes; and (ii) this adaptation must produce correlated patterns of virulence (i.e., disease severity)."

In [1], Kubinak et al. describe how they repeatedly transmitted the same pathogen through different hosts (groups of genetically identical mice, each group carrying a different MHC family) and observed patterns of pathogen adaptation.

"Results from our experiments demonstrate that pathogen adaptation is host MHC genotype-specific. We conclude that pathogen adaptation to the familiar host MHC genotype produces trade-offs in pathogen fitness by reducing the reproductive output of adapted viruses when infecting hosts carrying unfamiliar MHC genotypes. Although previous work has shown that interactions between host and pathogen genotypes are important for determining patterns of pathogen fitness and virulence associated with infection, our dataset is unique in that it provides direct experimental support for fitness trade-offs associated with a pathogen’s adaptation to specific host MHC genotypes, thus confirming the first major assumption of the antagonistic coevolution model of MHC evolution."

With their experiment, Kubinak and colleagues proved that diversity in the MCH gene complex is maintained through the antagonistic coevolution between pathogen and host. This does not exclude other factors such as the heterozygote advantage and mating preferences, which have also been considered as likely explanations of the high variability in this gene family. As it often happens in genetics, the likely explanation is an interaction between all these phenomena and the hardest thing is to disentangle each contribution.

The authors conclude with one final thought, as their results suggest that populations with low MHC genetic diversity are likely to select for more virulent pathogens.

"If this suggestion is true, many livestock breeds and endangered species that exhibit reduced genetic diversity may be particularly sensitive to the consequences of rapid pathogen adaptation. Additionally, the prophylactic use of antibiotics on domesticated livestock places a selective pressure on pathogen populations to evolve antibiotic resistance, and as a consequence has been implicated in the emergence of antibiotic-resistant strains of human pathogens."

[1] Kubinak, J., Ruff, J., Hyzer, C., Slev, P., & Potts, W. (2012). From the Cover: Experimental viral evolution to specific host MHC genotypes reveals fitness and virulence trade-offs in alternative MHC types Proceedings of the National Academy of Sciences, 109 (9), 3422-3427 DOI: 10.1073/pnas.1112633109

MicroRNAs found for the first time in a retrovirus

2012-03-01T08:00:00.003-08:00

MicroRNAs (miRNAs) are small non-coding RNAs that play a regulatory role in many cellular processes such as immune function, apoptosis and tumorigenesis. MicroRNAs are about 22 nucleotide long (on average) and they typically derive from primary transcripts "snipped" during a process called "endonucleolytic cleavage," which involves a protein that recognizes a double-helix RNA and cleaves the nucleotides in halves for degradation. MicroRNAs are post-transcriptional regulators, meaning they regulate what genes get transcripted by binding to their complementary RNA transcripts and thus preventing them to produce proteins.

Most eukaryotes, as well as many viruses, encode miRNAs. As you know, there are two kinds of viruses, depending on whether they carry DNA or RNA, and until now miRNAs had been found in DNA viruses only.

"Although limited studies exist, a preliminary model suggests that DNA viruses will use miRNAs for varied activities, including: regulation of latent/persistent infection, evasion of the innate and adaptive immune responses, and promotion of cell viability [1]."

A new study published in last week's issue of PNAS [1] reports the finding of miRNA in a retrovirus, namely the bovine leukemia virus (BLV), a virus that is associated with B-cell tumors both in cattle and sheep. How the virus initiates these tumors remains a mystery.

"Essentially all tumor cells are positive for the viral genome; however, very little, if any, viral mRNAs and proteins are detected in most cells [1]."

The finding that BLV encodes miRNAs is quite surprising because the general thought was that it would be deleterious for a retrovirus to encode miRNA, since it would have to come from the cleavage process I described above, and this could potentially affect the viral genome. In their study, Kincaid et al. identify a cluster of five miRNAs expressed from the BLV genome and also describe the mechanism by which these transcripts escape cleavage. Interestingly, one of the five miRNAs is functional and identical to the target portion in the host. The researchers demonstrate that the two miRNAs, the viral one and the host's, target transcripts that have been previously associated with B-cell cancerogenesis in mice, thus shedding new light on how the virus could initiate the cancer in the host.

"In summary, we demonstrate that an RNA virus expresses abundant, evolutionarily conserved miRNAs, including at least one that functions as an analog to a host oncogenic miRNA. These findings open up a role for noncoding RNAs in retroviral-associated tumorigenesis, and suggest the possibility that other retro- viruses exist that use noncoding RNAs in their infectious cycles."

Kincaid, R., Burke, J., & Sullivan, C. (2012). From the Cover: RNA virus microRNA that mimics a B-cell oncomiR Proceedings of the National Academy of Sciences, 109 (8), 3077-3082 DOI: 10.1073/pnas.1116107109

Mendelian puzzles

2012-02-27T06:24:00.001-08:00

A Mendelian disorder is a disease caused by a single-gene mutation that's usually inherited according to Mendel's laws. Despite being for the most part quite debilitating, they persist in the population, though at a very low prevalence. This is due in part to the effect called heterozygote advantage. Recessive mutations bear no symptoms and are carried on from one generation to the next until an individual with both mutated alleles is born.

A Perspective in the latest issue of Science [1] gives a good review of Mendelian disorders and the puzzles yet to unravel around them. The mystery is two-fold: first, given a disorder, not all subjects carry the specific mutation; second, given the specific mutation, not all subjects are affected in the same way, and in fact, some aren't affected at all.

The first puzzle (an affected person who doesn't carry the mutation) can easily be attributed to the fact that the specific disease could indeed have many causes. Just because it has been found to be monogenic (caused by one gene), it doesn't mean that it has one cause only. Environmental factors could be playing a role too, for example, as well as additional interactions between genes. Different environmental exposures could also explain the other side of the puzzle, i.e. why carriers of the same mutations can be affected in such different ways, from no symptoms at all to severe conditions. Ultimately, things like gene-to-gene interactions and variation in an individual's regulatory sequences could explain both puzzles.

DNA transcription is controlled by proteins called transcription factors. These proteins bind to the region "upstream" from the gene, and this is the non-coding region called "regulatory sequence" because it affects whether the gene is silenced or expressed.

"For an autosomal dominant disorder in which individuals harbor one normal (wild-type) and one mutant gene copy (allele), additional variants at a physically close silencer or enhancer can modulate the wild-type versus mutant transcripts so as to yield more or less mutant transcript and protein, thus leading to more severe or less severe disease. The specific outcomes depend on the function of the regulatory sequence and whether the regulatory variant is physically linked to the wild-type or the mutant allele.

In the Science review, Chakravarti and Kapoor hypothesize that mutations in the regulatory sequences are far more common than mutations in the adjacent structural gene that code for the affected transcript or protein, and it is the combination of the two that could explain the wide range of disease penetrance we observe. Furthermore, while disease mutations are kept at a low prevalence by strong selection, selection is much weaker on regulatory sequences. As a consequence, mutations that arise in these regions have a higher chance to become common in the population.

"The combination of rare coding mutations with common regulatory variants can lead to complex patterns of inheritance and thus provide a singular mechanistic explanation of Mendelian families that do not carry a mutation in the coding gene associated with the disease, as well as variable disease penetrance in individuals that carry the Mendelian gene mutation."

Photo: waves in La Jolla, CA. I took 500 shots and not a single one had a straight horizon. It's official: I've now lived up in the mountains for too long.

[1] Chakravarti, A., & Kapoor, A. (2012). Mendelian Puzzles Science, 335 (6071), 930-931 DOI: 10.1126/science.1219301

Modifying gene expression through riboswitches

2012-02-23T20:52:00.001-08:00

Messenger RNA (mRNA), the RNA transcribed from a DNA template in order to make proteins, contains elements able to sense and bind to specific targeting molecules (metabolites or metal ions). In bacteria, fungi and plants, these binding mechanisms are used to control gene expression, and therefore act as genetic "switches", which is why these RNA elements are called "riboswitches". They are often found at the 5' end of the mRNA, in the untranslated region (the stretch that precedes the start codon): this way, they are the first domain to be synthesized and can therefore influence expression before the entire mRNA is created.

Riboswitches have two components: the domain that binds to the ligand is called "aptamer" and it's highly conserved from an evolutionary point of view, as it has to "sense" a precise type of molecule. The other component, called "expression platform," is what regulates gene expression, and, contrary to the aptamer, it can vary greatly in order to affect the different processes of transcription, translation, and RNA processing.

In order to understand how riboswitches bind to their specific ligands, it is vital to decipher their "secondary structure," in other words, the way they fold and assume a 3-D structure that allows them to "sense" and "capture" the targeting molecules. Common elements of RNA secondary structures are "helices" (similar to those found in DNA), and "hairpins," which take place when the RNA folds back onto itself. "Some riboswitches are surprisingly complex, and they rival protein factors in their structural and functional sophistication [1]."

The following figure, from this Scitable article, illustrates the kind of changes in secondary (3D) structure a riboswitch can undergo before and after binding to a molecule.

A riboswitch can adopt different secondary structures to effect gene regulation depending on whether ligand is bound. This schematic is an example of a riboswitch that controls transcription. When metabolite is not bound (-M), the expression platform incorporates the switching sequence into an antiterminator stem-loop (AT) and transcription proceeds through the coding region of the mRNA. When metabolite binds (+M), the switching sequence is incorporated into the aptamer domain, and the expression platform folds into a terminator stem-loop (T), causing transcription to abort. aptamer domain (red), switching sequence (purple), and expression platform (blue).

Because they affect gene expression, particularly genes involved in biosynthetic pathways, riboswitches are natural targets for drug development.

"First, many riboswitches repress the expression of genes whose protein products are involved in the transport or biosynthesis of essential metabolites. Therefore, compounds that trick riboswitches by mimicking the natural ligand might inhibit bacterial growth by starving the cells for that essential metabolite. Second, medicinal chemists already have a ‘‘hit’’ compound (the natural ligand) for each validated riboswitch class that they can begin to chemically alter to create new antibiotics. In this regard, riboswitches are almost unique among noncoding RNAs classes because they have evolved pockets to purposefully bind a small molecule, and therefore should be more easily drugged [1]."

From the Scitable article:

"Their role in regulating transcription in bacteria makes them enticing targets for the development of novel antibiotics aimed at stopping bacterial pathogens from flourishing inside the people they infect. Because riboswitches control genes essential for bacterial survival, or genes that control the ability of bacteria to succeed at infection, a drug designed to affect a riboswitch could be a powerful tool for shutting down pathogenic bacteria."

Synthetic riboswitches have been developed and shown to activate or repress gene expression in bacteria [2]. While I couldn't find any studies done in humans yet (though if you guys know of some, please let me know!), I did find a Nature letter reporting the first ever human RNA switch analogous to riboswitches [3].

[1] Breaker, R. (2011). Prospects for Riboswitch Discovery and Analysis Molecular Cell, 43 (6), 867-879 DOI: 10.1016/j.molcel.2011.08.024

[2] Topp, S., Reynoso, C., Seeliger, J., Goldlust, I., Desai, S., Murat, D., Shen, A., Puri, A., Komeili, A., Bertozzi, C., Scott, J., & Gallivan, J. (2010). Synthetic Riboswitches That Induce Gene Expression in Diverse Bacterial Species Applied and Environmental Microbiology, 76 (23), 7881-7884 DOI: 10.1128/AEM.01537-10

[3] Ray, P., Jia, J., Yao, P., Majumder, M., Hatzoglou, M., & Fox, P. (2008). A stress-responsive RNA switch regulates VEGFA expression Nature, 457 (7231), 915-919 DOI: 10.1038/nature07598

Is cancer contagious? Sometimes. But it may not be a bad thing.

2012-02-20T05:54:00.001-08:00

About 15% of all cancers worldwide are caused by infectious pathogens such as viruses, bacteria, or parasites [1]. Viruses that are capable of inducing cancer are called oncoviruses -- HPV is an example. The pathogen is transmitted from a donor to a recipient, starts the infection, and the infection eventually causes the cancer. But did you know there existed such a thing as a transmissible cancer? In this case, it's not the pathogen, but the cancer cell line itself that gets transmitted from one individual to another.

Yes, it's scary, but there are some good news.

For one thing, "relatively common" cases have been observed in animals only. Canine transmissible venereal tumor (CTVT) is quite common in dogs. It's transmitted during mating and eventually rejected by the host dog who then acquires lifelong immunity.

"In man, only scattered case reports exist about such communicable cancers, most often in the setting of organ or hematopoietic stem cell transplants and cancers arising during pregnancy that are transmitted to the fetus. In about one third of cases, transplant recipients develop cancers from donor organs from individuals who were found to harbor malignancies after the transplantation. The fact that two thirds of the time cancer does not develop, along with the fact that cancer very rarely is transmitted from person to person, supports the notion that natural immunity prevents such cancers from taking hold in man. These observations might hold invaluable clues to the immunobiology and possible immunotherapy of cancer [1]."

CTVT is particularly interesting to study because it has evolved some ingenious mechanisms to escape the immune system. Every nucleated cell has a class of molecules, called MHC, which have the function to display fragments of proteins that are "flags" as to whether the cell is healthy or harbors some pathogen. Once in the host, CTVT

"downregulates its MHC I expression, thereby reducing its initial visibility to the host's immune system. This allows it to not only to escape T-cell mediated immunity (which would occur if MHC I were fully expressed) but also natural killer cells (which would eradicate the cells were they completely devoid of MHC I)."

Despite this type of "defense", eventually the dog's immune system recognizes the pathogen and clears it, and understanding this mechanism is of interest for a possible cancer vaccine (I talked about cancer vaccines here).

A recent study published in Science [2] looked at two regions in the mitochondrial genome (mtDNA) from 37 CTVT samples, and compared them with sequences from the mtDNA of 15 hosts. Through phylogenetic analysis Rebbeck et al. showed a high variability in the sequenced regions, suggesting that CTVT periodically acquires mtDNA from infected hosts. The reason for this, the researchers hypothesize, is that CTVT mitochondria, due to a high metabolic rate, tend to accumulate deleterious mutations and therefore, transfers of mtDNA from the host may have the benefit of restoring CTVT mitochondrial function.

[1] Welsh, J. (2011). Contagious Cancer The Oncologist, 16 (1), 1-4 DOI: 10.1634/theoncologist.2010-0301

[2] Rebbeck, C., Leroi, A., & Burt, A. (2011). Mitochondrial Capture by a Transmissible Cancer Science, 331 (6015), 303-303 DOI: 10.1126/science.1197696

Avian influenza, ferrets, and bioterrorism: fear versus science

2012-02-17T13:17:00.002-08:00

I learned about this last week, when Science published a short article on how the National Science Advisory Board for Biosecurity had recommended two research groups NOT to publish details on how avian influenza strains were modified in order to make them transmissible through aerosol in ferrets.

You can read that story here.

The first thing that struck me was: is this censorship? Because for as long as I've been a scientist I've known that the great bulk of scientific progress is made through the free exchange of ideas and results. The very core of scientific validation is in the reproducibility of an experiment, and you can't reproduce an experiment unless who conducted it shares the details.

Why then the recommendation?

The World Health Organization currently lists the case fatality of avian influenza (H5) somewhere between 50% and 80%. This is the percentage of all cases that report in a hospital and have been confirmed through labwork. Currently, it is transmissible through fluids by coming in contact with infected birds. The two studies under the radar here, by Ron Fouchier at Erasmus Medical Center in Rotterdam and by Yoshihiro Kawaoka at the University of Wisconsin, have been submitted but not yet published to Science and Nature respectively. Though different, they both prove that it takes a relatively small number of mutations for the virus to become transmissible through aerosol in ferrets.

Why the fear? With a fatality rate anywhere above 50%, if you can make the virus transmissible through aerosol, you've got a deadly weapon. But is it so obvious one can make it?

First, ferrets are not humans and currently we have no way to predict whether what has been observed in ferrets is likely to happen in humans. For example, there are many strains of avian influenza, and they all have been circulating in birds for many decades. However, of all these strains, only three (H1, H2, and H3) have been able to circulate in humans. There is a natural bottleneck in the way a virus is able to adapt from one organism to another.

One may object we don't know for sure, so, theoretically, it could be possible. But in that case, is censorship the answer? I honestly don't think so and I was quite happy to find a PNAS paper [1] in complete agreement with my thoughts:

"Why Is it Important to Have the Full Data Published? With respect to the specific papers by Fouchier and Kawaoka, it would be important for other scientists to replicate portions of these works to test new vaccines/therapeutic agents and for continued studies on the molecular aspects of influenza transmission, a topic that is extremely important yet relatively poorly understood."

And, most importantly:

"It would be very difficult for a bioterrorist to come up with a human virus strain that is transmissible and still highly virulent. Under natural conditions, however, there is virtually unlimited allowance for generation of capable viruses, the opportunities for infection of humans are plentiful, and the evolutionary pressures of selection are great. If anyone could do it, Nature could."

And that's exactly why we need to be prepared. And the way we are prepared is by sharing results and having multiple groups worldwide brainstorm and join forces to find a vaccine.

What do you guys think?

Palese, P., & Wang, T. (2012). H5N1 influenza viruses: Facts, not fear Proceedings of the National Academy of Sciences, 109 (7), 2211-2213 DOI: 10.1073/pnas.1121297109

Large intergenic noncoding RNAs affect gene expression

2012-02-16T05:30:00.000-08:00

I learned this amazing fact from a talk I went to last week: currently, somewhere between 70% and 90% of DNA is estimated to be transcribed into RNA but not translated into proteins. So, the question is: if it's not making proteins, what's all this non-coding RNA doing?

In mammalians in particular, more than a thousand large (over 5 kb) intergenic noncoding RNAs (lincRNA) have been identified [1] and, by looking at expression patterns, researchers were able to see that they are involved in many different biological processes. They are evolutionary conserved across species, indicating that they are indeed functional, yet very little is known of their function. Two 2009 papers [1,2] investigated whether lincRNA are involved in the establishment of chromatin states by creating "genome-wide chromatin-state maps."

We need a refresher here. I discussed chromatin (the package of DNA and proteins inside the nucleus) in this post. The structure and topology of the chromatin changes from cell line to cell line and also during a cell's life, allowing for different genes to be activated or deactivated as needed (for example during cell differentiation). These modifications in the way the DNA is packaged are called chromatin states and are key to understand how and which genes are expressed inside the cell. In particular, there exists a whole family of proteins, called chromatin-modifying complexes, that modify the structure of chromatin to promote or inhibit access genes.

in [1], Guttman et al. looked at a particular genome domain called K4-K36 in genome-wide chromatin-state maps in 4 mouse cell lines. This chromatin signature marks actively transcribed genes, hence, they were able to find lincRNAs "by identifying K4-K36 structures that reside outside protein-coding gene loci."

"These lincRNAs show similar expression levels as protein-coding genes, but lack any protein-coding capacity. Importantly, lincRNAs show significant evolutionary conservation relative to neutral sequences, providing strong evidence that they have been functional in the mammalian lineage [2]."

In [2], Khalil et al. extended the results found in [1] by mapping the K4-K36 domain to 6 human cell types. They found 1,703 new human lincRNA genes and estimated the total number of human lincRNAs to be roughly 4,500. Of all newly discovered lincRNAs, a substantial fraction was found to be associated with PCR2, one of the chromatin-modifying complexes I mentioned above.

"Collectively, these results suggest that many lincRNAs collaborate with chromatin-modifying proteins to repress gene expression at specific loci. [...] Our results suggest an intriguing hypothesis that lincRNAs bind to chromatin-modifying complexes to guide them to specific locations in the genome. [...] Under our model, differentially expressed lincRNAs could bind to these complexes and help establish cell type specific epigenetic states."

The specific experiments conducted by Khalil et al. identified associations with chromatin-modifying complexes that have a repressive role, but the researchers suggest that, with different experiments, one could find additional lincRNA that instead are associated with activating chromatin-modifying complexes.

[1] Guttman, M., Amit, I., Garber, M., French, C., Lin, M., Feldser, D., Huarte, M., Zuk, O., Carey, B., Cassady, J., Cabili, M., Jaenisch, R., Mikkelsen, T., Jacks, T., Hacohen, N., Bernstein, B., Kellis, M., Regev, A., Rinn, J., & Lander, E. (2009). Chromatin signature reveals over a thousand highly conserved large non-coding RNAs in mammals Nature, 458 (7235), 223-227 DOI: 10.1038/nature07672

[2] Khalil, A., Guttman, M., Huarte, M., Garber, M., Raj, A., Rivea Morales, D., Thomas, K., Presser, A., Bernstein, B., van Oudenaarden, A., Regev, A., Lander, E., & Rinn, J. (2009). Many human large intergenic noncoding RNAs associate with chromatin-modifying complexes and affect gene expression Proceedings of the National Academy of Sciences, 106 (28), 11667-11672 DOI: 10.1073/pnas.0904715106

The "not-so-universal" genetic code, its origin and its evolution

2012-02-13T05:05:00.000-08:00

From [1]:

"Until relatively recently, the [genetic] code was thought to be invariable, frozen, in all organisms, because of the way in which any change would produce widespread alteration in the amino acid sequences of proteins. The universality of the genetic code was first challenged in 1979, when mammalian mitochondria were found to use a code that deviated somewhat from the universal."

A brief refresher: proteins are chains of amino acids. They are made from messenger RNA by assigning each triplet of RNA nucleotides (a codon) to one amino acid. For example, in the sequence AUGCCCAAGCUG each triplet codes an amino acid: AUG becomes M, CCC becomes P, AAG becomes K, and CUG becomes L. All together: AUG|CCC|AAG|CUG -> MPKL.

So, what does "universal" mean in the above quote? It means that the above sequence gets translated into the same amino acids in every organism, from bacteria to humans. Is this true? Not always.

Take a stop codon, for example. A stop codon is a triplet of RNA nucleotides that end the translation. Think of it as a flag that says, "The protein code ends here." If the genetic code were a universal one, a stop codon would always be a stop codon, in all organisms. The first exception to this was discovered in 1985, when the stop codon UGA was found to be actually coding an amino acid in the bacteria Mycoplasma capricolum. More exceptions to the "universal" conception (other triplets that coded different amino acids instead of always the same one) were later found in other organisms and in mitochondrial DNA as well. A more realistic theory is that, being DNA dynamical, when codons "disappear" the old codons can undergo reassignments and take on a new meaning.

The "universal" view has prevailed for many years on the basis that present time proteins are so evolved that changes would most likely be lethal. The first deviations from universality were found in the late 'seventies in mitochondrial DNA. It was argued that mtDNA is considerably smaller than nuclear DNA and hence it had a better tolerance to changes.

In [1], Ohama et al. list various code changes reported in the nuclear DNA in the past three decades, and then discuss the origin of the genetic code:

"The theories to explain the early evolution of the genetic code are numerous, all of which include speculations that the coding system arose with one or a limited number of amino acids, and that others were added until a total of 20 was reached. Most of these theories are aesthetically pleasing but cannot be verified."

They assume that the most ancient genetic code had to have a minimum number of codons made of all 20 amino acids and a minimum number of corresponding tRNAs -- transfer RNA molecules that act as mediators between the mRNA and the amino acids. This first genetic code had to have very little tolerance for change. However, with the time, the development of synonymous codons (different triplets code the same amino acid), allowed for flexibility and therefore resulted in an advantageous addition.

Finally, they conclude:

"It should be stressed however that there are no organisms which use the genetic code system for more than, or less than, 20 amino acids. What were frozen are 20 amino acids (magic 20!) and not the genetic code that assigns them. Thus the genetic code is still in the state of evolution."

I'm including below a second reference [2] that goes a bit more in depth on how these codon reassignments happen, for those of you who might be interested. In this case, the authors looked at the evolution of the genetic code in yeast.

[1] Ohama T, Inagaki Y, Bessho Y, & Osawa S (2008). Evolving genetic code. Proceedings of the Japan Academy. Series B, Physical and biological sciences, 84 (2), 58-74 PMID: 18941287

[2] Miranda, I., Silva, R., & Santos, M. (2006). Evolution of the genetic code in yeasts Yeast, 23 (3), 203-213 DOI: 10.1002/yea.1350

Happy Darwin Day!

2012-02-12T07:33:00.000-08:00

Happy Darwin Day everybody!

Charles Darwin was born on this day in 1809, and ... well, I don't need to tell you who Darwin was, right?

The International Darwin Day Foundation has a collection of links to Darwin lectures happening all over the world this month. If you live in a big city, chances are, there's something going on near by and you may want to check it out.

Whatever you do today, please keep one thing in mind: Charles Darwin was a great scientist and a great man and he left us an immense legacy. This is not a religious debate. And it's not political either. Anybody who mentions either religion or politics when discussing evolution is missing the point. As the Poet once said, "Non ragioniam di lor ma guarda e passa."

I leave you with Carl Sagan's hymn to evolution:

Migrating genes

2012-02-10T05:09:00.000-08:00

I've been talking quite a lot about mitochondria lately. The fact that these organelles contain their own DNA (called mtDNA) and were the result of a horizontal gene transfer during evolution is simply fascinating. And I know many of you agree, as proved by the wonderful questions my last post on mitochondria sparked (thank you Hollis and Marleen!)

Plastids, plant organelles that are responsible for photosynthesis, also have a circular, double-stranded DNA molecule (called ptDNA). Like mitochondria, plastids originated through endosymbiosis and, in most plants, are inherited from one parent only. Now, here's another fascinating fact:

"During the early phase of organelle evolution, organelle-to-nucleus DNA transfer resulted in a massive relocation of functional genes to the nucleus: in yeast, as many as 75% of all nuclear genes could derive from protomitochondria, whereas ~4500 genes in the nucleus of Arabidopsis are of plastid descent. Cases of present-day organelle-to-nucleus DNA transfer, revealed by the presence of NUMTs and NUPTs [the fraction of nuclear DNA that derives from mitochondria and plastids respectively], are known in most species studied so far. [...] Mitochondrial chromosomes contain segments homologous to chloroplast sequences, as well as sequences of nuclear origin, providing indirect evidence for plastid-to-mitochondrion and nucleus-to-mitochondrion transfer of DNA [1]."

Throughout evolution transfers of genes between plastids and mitochondria have been documented, although in present organisms these transfers gave rise to non-functional sequences. In plants, the transfer of genes from organelles to nucleus seems to be still active, as documented by the RPS10 gene, which is present in the mitochondria of some angiosperms, and in the nucleus of other plants [Henze and Martin, 2001]. In fact, orgenelle-to-DNA gene transfers have been studied extensively in plants: their cells have both plastids and mitochondria and, as a consequence, they are in general more informative than animal eukaryotes.

In [1], Leister revises studies that show that mtDNA in Homo sapiens integrates continuously into the nuclear genome, as both de novo and pre-existing nuclear insertions of mtDNA have been documented. Recent acquisition of nuclear mtDNA have been documented by comparison with chimpanzee genomes.

So, how do these transfers happen? Though it was originally thought that genes would migrate as RNA transcripts, new studies have shown that it's the DNA itself that "escapes" the organelle:

"Escape of organelle DNA and its uptake into the nucleus has been experimentally demonstrated in yeast and tobacco."

Once these bits of DNA arrive to the nucleus, however, they are subject to a much lower mutation rate than they were in their original location. What this means is that mutations appear more rarely in the nucleus than they do in the organelles. As a consequence, they become "conserved," undergo very little changes, and, at all effects, become "molecular fossils," allowing researchers to retrace phylogenies between species.

"Moreover, nuclear organelle DNA insertion polymorphisms, as a subclass of insertion-deletion polymorphisms, are valuable markers for population and evolutionary studies."

Since the process of migration from organelle to nucleus is a constant one, studies have been directed at measuring the rate of continued colonization of organelle DNA into the germline. The rate in humans has been found to be of the order of 10e-05, and even though these insertions in the past had been thought to be essentially harmless, recent studies have confirmed associations with certain types of hereditary diseases. As I was discussing last week, more studies are in the way to investigate possible associations between nuclear mitochondrial polymorphisms and certain types of cancers.

[1] Leister, D. (2005). Origin, evolution and genetic effects of nuclear insertions of organelle DNA Trends in Genetics, 21 (12), 655-663 DOI: 10.1016/j.tig.2005.09.004

You're being watched. That's okay, though, we do it for your own benefit. Or so we'd like you to think...

2012-02-08T16:40:00.000-08:00

Starting March 1st Google's much anticipated new privacy policy will take place. Of course, how much it will or will not affect your life depends upon your own personal choices. It strikes me, though, how much the Internet has become a place like those Italian marketplaces I used to love growing up: lots to see, stands full of goodies, lots of people, lots of entertaining distractions, yet if you don't keep a constant eye on your wallet next thing you know it'll be gone.

What can you lose on the Internet?

Well, privacy, of course. It's a subtle question. Google offers me a service, and in a way, they have a right to access certain information that, by accepting their services, I am voluntarily giving up. Where's the boundary, though? For one thing, I'm bugged by the fact that they present it as yet another service they are offering me: they gather information so they can make my searches easier and provide me with a better service, tailored to my needs.

Please. It's called marketing, and we all know it.

I am indeed grateful for all the services Google is offering me. I love the Blogger platform, and, as I have stated before, I am thrilled with G+ and the community there. I also understand that no service is ever free, rather it comes at a cost. Having said that, I think it's worth giving the whole thing some thought because, as a Google user, I feel I have to make a choice of how much of my information I want to share.

Check-out what Leonhardt and Magee had to say back in 1998 (Remember 1998? Gmail didn't even exist back then!):

"[...] location services will often become repositories of potentially sensitive personal and corporate information. Where you are and who you are with are closely correlated with what you are doing. To leave this information unprotected for everybody to see is clearly undesirable. People would feel uncomfortable if their every move could be watched anonymously [1]."

Do you like to be watched anonymously?
From Google's new privacy policy:

"Location data: Google offers location-enabled services, such as Google Maps and Latitude. If you use those services, Google may receive information about your actual location (such as GPS signals sent by a mobile device) or information that can be used to approximate a location (such as a cell ID)."

You may argue it's a machine, not a person watching you. You're still being watched, though, and the way it's done -- as I understand it -- is not that you choose what to make public and what not to. Email or GPS signals are not something people typically post publicly, yet those pieces of info are apparently up for grabs as well. And that, to me, doesn't sound right.

Leonhardt and Magee predicted the future when they wrote:

"We are especially concerned with the balance between security imposed by the system (mandatory security), and security specified by individuals (discretionary security). [...] We expect that [a global location] service would be provided by a network of loosely cooperating providers, very similar to today's mobile telephone system. Customers would subscribe to one or more service providers. The providers would have roaming agreements with each other. [...] Further, there is scope for third-party location-aware services. For example, such a service might be responsible to automatically inform emergency services when a distress signal from a subscriber is received. On the other hand, users will often have to trust the service providers to obey the security policy laid down in the service contract."

Another quote, from a 2006 paper this time (yes, I did a lot of research on this!):

"These technologies can be applied for private and public goals, and can be used in private and public situations. Although it is possible to make a distinction between private and public on an analytical level, in reality, it is difficult to draw a clear line between private and public situations, and between private and public goals [2]."

That's exactly the issue here. Where do we draw the line between public service, hence available, and private data, hence "hands-off"? What are the dangers of not being able to draw such line? In the above paper, titled "Privacy invasions," philosophy professor Karsten Weber explains:

"In principle, leaving a physical place means leaving it forever; by contrast, being in cyberspace means being there forever, because all of an individual's actions are stored immediately, and can be tracked and analyzed. [...] The technology could be used to track individuals and monitor related characteristics, such as whether the person gathers in groups or prefers solitude. Even if the reader cannot imagine a use for such information, rest assured that marketing experts would find it highly valuable."

Some people seem not to be bothered by any of this. And most likely tomorrow I'll wake up and I'll no longer be bothered by it either. Still. I find it paradoxical that I live in a country where once kids are in college parents no longer have access to their grades or where one can't access the health record of an elderly relative because of privacy issues. Maybe next time you need to access any of that data you should ask Google.

[1] Leonhardt, U., & Magee, J. (1998). Security Considerations for a Distributed Location Service Journal of Network and Systems Management, 6 (1), 51-70 DOI: 10.1023/A:1018777802208

[2] Weber, K. (2006). Privacy invasions: New technology that can identify anyone anywhere challenges how we balance individuals' privacy against public goals EMBO reports, 7 DOI: 10.1038/sj.embor.7400684

The first tree of life

2012-02-06T05:22:00.000-08:00

I came to learn the meaning of the word phylogenetics in 2006, when I started working on HIV. With a highly variable virus like HIV, it is convenient to be able to reconstruct its molecular evolution through a graph called phylogenetic tree. It gives researchers a visual sense of the genetic diversity found in the sample of viral sequences and infer what the infecting strain (the "patriarch", so to speak) might have looked like.

These trees are not specific to virology. In fact, they are used in all fields of evolutionary biology to infer genealogical and evolutionary relationships. A recent paper in PNAS [1] discusses the "Scientific, historical, and conceptual significance of the first tree of life." From the abstract:

"In 1977, Carl Woese and George Fox published a brief paper in PNAS [2] that established, for the first time, that the overall phylogenetic structure of the living world is tripartite. We describe the way in which this monumental discovery was made, its context within the historical development of evolutionary thought, and how it has impacted our understanding of the emergence of life and the characterization of the evolutionary process in its most general form."

By comparing molecular sequences of different organisms, Woese and Fox constructed the very first tree of life and showed that all species are phylogenetically related. Using the tree, they divided all cellular life into three major groups: eukaryotes (organisms whose cells have a nucleus), eubacteria (non-nucleated cells, or prokaryotes), and archaebacteria (a kind of prokaryote that shares similarities with eukaryotes -- I know, it gets complicated!). Interestingly, the paper went almost unnoticed at first, and then, when it did get noticed, it was highly criticized, as often revolutionary thinking is:

"The manuscript received severe criticisms when it was submitted to PNAS in the summer of 1977. One reviewer recommended that it not be published on methodological grounds that their claim for a tripartite division of the microbial world was as unfounded as their claims in regard to symbiosis and the origin of eukaryotic organelles."

It should be said that comparing genetic sequences back then wasn't as straightforward as today (hence the skepticism), and that, though not systematically proven, the general belief prior to this paper had been that life could be divided in two, not three, major groups.

Woese realized very early that the only way to quantify evolutionary change was to study the conservation and variation of molecular sequences across different organisms. So, together with Fox, they looked at small subunit ribosomal RNA from different organisms. In all cells protein synthesis is carried out in the ribosomes, which create proteins reading the information from the messenger RNA (mRNA). Ribosomes have an RNA component and a protein component, and ribosomal RNA, or rRNA, as you may have already guessed by now, is the RNA component of the ribosome.

Woese and Fox set the foundations that, years later, led to the discovery that the root of the tree of life was to be found in the eubacterial line and settled the question of whether chloroplast and mitochondria originated from a symbiotic event. Pace et al. conclude in [2]:

"Modern versions of the techniques used by Woese and Fox are now routinely used to sample environments as varied as geothermal hot springs and gastrointestinal microbiomes, providing unprecedented insight into community structure and dynamics. The results challenged the foundations of classical evolutionary theory, requiring new modes of evolution to be considered, indicating the presence of an unexpectedly large microbial pangenome (field of genes‚ to use Woese's favorite phrase), and forcing us to reconsider basic concepts such as the nature of species. Perhaps no other paper in evolutionary biology has left a richer legacy of accomplishments and promise for the future."

[1] Pace, N., Sapp, J., & Goldenfeld, N. (2012). Classic Perspective: Phylogeny and beyond: Scientific, historical, and conceptual significance of the first tree of life Proceedings of the National Academy of Sciences, 109 (4), 1011-1018 DOI: 10.1073/pnas.1109716109

[2] Woese, C., & Fox, G. (1977). Phylogenetic structure of the prokaryotic domain: The primary kingdoms Proceedings of the National Academy of Sciences, 74 (11), 5088-5090 DOI: 10.1073/pnas.74.11.5088

Missing heritability: the humble opinion of a mathematician

2012-02-02T05:44:00.001-08:00

Tomorrow, February 3, is Eric Lander's birthday, the director of the Broad Institute (the well-known MIT/Harvard genomic research center), and the first author of the historic 2001 Nature paper that marked the completion of the Human Genome Project [1]. I heard him once speak at USC and without ever getting technical he managed to engage the whole audience and share his passion for genetics. As you know, I've been honoring famous geneticists by discussing one of their papers on their birthday and today I'm facing a conundrum. You see, the natural choice would be to pick the latest PNAS paper titled "The mystery of genetic heritability" [2]. I want to talk about this paper and at the same time I don't want to talk about this paper.

I'm not a geneticist. I'm a computational biologist, which means my background is mostly analytical, not biological. I used to work on SNP associations and cancer epidemiology and now I work on HIV. I am NOT one of the players in this game. Hence, what does my opinion count when it comes to a highly debated paper as this one?

The thing is, this paper resonates with me. It makes a great point about a mathematical model that's been "assumed" for years now in the world of genetics. Often people don't get mathematical models. They don't get that mathematical models are tools, not the truth. Hence when one says "I present this model," you get two possible reactions: those who have seen data concordant with your model will smile and happily welcome your model. Those who instead have seen the opposite will boo you and challenge you. Problem is, models are neither right or wrong. Models are tools. Do they help describe what we see? Fine, we keep the model. When they don't, we go back to the data and try to understand which of our assumptions failed. We use the model to discern the situations that meet the assumptions stated in the model from those that don't. Models help us shape our thinking, not the data! For example, evolution is a model, too. Go tell that to creationists and followers of intelligent design. They can challenge evolution as much as they want, but until they hand me a model that explains the genetic diversity we observe today better than evolution does, I will stick with evolution.

Back to the PNAS paper. It's a hot topic right now, and I'm kind of late discussing this particular paper in the blogosphere. Razib Khan discussed it here, Luke Jostins here and here, and I'm sure many others whom I don't know have talked about it too.

So, what is the missing heritability? Since I've already defined it in an earlier post of mine, for the time being, let me just quote Razib Khan:

"The issue is basically that there are traits where patterns of inheritance within the population strongly imply that most of the variation is due to genes, but attempts to ascertain which specific genetic variants are responsible for this variation have failed to yield much. For example, with height you have a trait which is ~80-90 percent heritable in Western populations, which means that the substantial majority of the population wide variation is attributable to genes. But geneticists feel very lucky if they detect a variant which can account for 1 percent of the variance."

The implications of this are clear: we want to find risk alleles to predict common diseases, but given the missing heritability, we can't predict common diseases.

Is this surprising?

Given the reactions I saw on the internet, apparently it is. People claim we still haven't found all variants and that's where the missing heritability's hiding. Maybe. However, after reading so much about epigenetics, RNA editing, and epistasis, allow me to be skeptical. Traits (proteins, diseases, etc.) are not genes. The path from genes to traits is long and convoluted.

So, what's Lander's point in this PNAS paper? Something I've also previously discussed: epistasis, or the way genes interact together. We're missing heritability because we think of risks as additive, but additivity doesn't count for interactions. If you take into account interactions between genes, the total heritability is much smaller than anticipated and hence the percentage of what the variants are explaining (all together) much larger.

"Quantitative geneticists have long known that genetic interactions can affect heritability calculations. However, human genetic studies of missing heritability have paid little attention to the potential impact of genetic interactions."

Now here's the beauty of this paper. They do not deny the additive risk model. They extend it:

"We thus introduce the limiting pathway (LP) model, in which a trait depends on the rate-limiting value of k inputs, each of which is a strictly additive trait that depends on a set of variants (that may be common or rare). When k = 1, the LP model is simply a standard additive trait. For k > 1, we show that LP(k) traits can have substantial phantom heritability."

Again, mathematician thinking here, but that's exactly what models are for: some traits may very well be additive. However, the model does not fit all the data we observe it. Hence we need a better model, one that encompasses the old one and at the same time goes beyond it. Gene-gene interactions need not explain all missing heritability. But since they've been observed, we need to account for them in those situations where they may be real.

"The potential magnitude of phantom heritability can be illustrated by considering Crohn's disease, for which GWAS have so far identified 71 risk associated loci (13). Under the usual assumption that the disease arises from a strictly additive genetic architecture, these loci explain only 21.5% of the estimated heritability. However, if Crohn's disease instead follows an LP(3) model, the phantom heritability is 62.8%, thus genetic interactions could account for 80% of the currently missing heritability."

"In short, genetic interactions may greatly inflate the apparent heritability without being readily detectable by standard methods. Thus, current estimates of missing heritability are not meaningful, because they ignore genetic interactions."

"The results show that mistakenly assuming that a trait is additive can seriously distort inferences about missing heritability. From a biological standpoint, there is no a priori reason to expect that traits should be additive. Biology is filled with nonlinearity: The saturation of enzymes with substrate concentration and receptors with ligand concentration yields sigmoid response curves; cooperative binding of proteins gives rise to sharp transitions; the outputs of pathways are constrained by rate-limiting inputs; and genetic networks exhibit bistable states."

Mother Nature did not create mathematics. We created mathematics to describe Mother Nature. We start with a simple model and build up on it. The data is always the reality check, we should never forget that.

[1] Lander, E., Linton, L., Birren, B., Nusbaum, C., Zody, M., Baldwin, J., Devon, K., Dewar, K., Doyle, M., FitzHugh, W., Funke, R., Gage, D., Harris, K., et al. (2001). Initial sequencing and analysis of the human genome Nature, 409 (6822), 860-921 DOI: 10.1038/35057062

[2] Zuk, O., Hechter, E., Sunyaev, S., & Lander, E. (2012). The mystery of missing heritability: Genetic interactions create phantom heritability Proceedings of the National Academy of Sciences, 109 (4), 1193-1198 DOI: 10.1073/pnas.1119675109

The wondrous mitochondrion and its proteome

2012-01-30T05:11:00.000-08:00

The sequencing of human mitochondrial DNA, a circular DNA molecule contained in mitochondria, was completed in 1981, and, since then, roughly 150 mutations have been found that are associated with maternally inherited diseases (if you don't remember why mtDNA is inherited from the mother and not the father, check out this earlier post of mine). Despite this, the majority of human mitochondrial syndromes are actually caused by defects in the nuclear genome. This is sort of obvious if you think about it, given that human mitochondrial proteome consists of an estimated 1,100-1,400 distinct proteins, of which 13 are encoded by the mitochondrial DNA. The majority of proteins targeted at the mitochondria are actually encoded by nuclear genes. In fact

"The 13 proteins encoded by mammalian mtDNA are all components of the respiratory chain, which generates the majority of cellular ATP via oxidative phosphorylation (OXPHOS). However, the remaining respiratory chain subunits are encoded by nuclear genes, as are all proteins required for the transcription, translation, modification, and assembly of the 13 mtDNA proteins. All the components of numerous other mitochondrial pathways are also nuclear en- coded, including the tricarboxylic acid (TCA) cycle, protein import, fatty acid and amino acid oxidation, apoptosis, and biosynthesis of ketone bodies, pyrimidines, heme, and urea. Furthermore, during the decades following the sequencing of the mtDNA, it became clear that maternally inherited mitochondrial disorders represent only 20% of all inherited human mitochondrial disorders [1]."

Mitochondria are amazing organelles. Roughly half of mitochondrial proteins are ubiquitous and found across all organs, while the rest are tissue specific, meaning that their function and structure varies across cell lines. For example, when comparing mitochondria across different tissues, researchers found about a 75% overlap. In addition to this cell-type specificity, some of the mitochondrial proteins are expressed at very low levels or only during certain specific developmental stages, making the characterization of the mitochondrial proteome a challenging task. Today, a little over 1,000 of all mitochondrial proteins have been identified, mainly through large-scale proteomics, microscopy, and computation.

The first half of Calvo and Mootha's review [1] is an detailed report on the progress made so far in extensively classifying the mitochondrial proteome. They then proceed to discuss how the inventory of mitochondrial proteins has lead to the better understanding of mitochondrial disorders as well as the discovery of new disease genes.

"Traditionally, mitochondrial disease has referred primarily to disorders of oxidative ATP production, as discussed above. However the breadth of the mitochondrial proteome now implicates a large number of additional phenotypes, such as soft tissue tumors (paragangliomas) and diabetes mellitus. The discovery of new disease genes will further expand the clinical phenotypes associated with mitochondrial defects."

[1] Calvo, S., & Mootha, V. (2010). The Mitochondrial Proteome and Human Disease Annual Review of Genomics and Human Genetics, 11 (1), 25-44 DOI: 10.1146/annurev-genom-082509-141720

Have you been blogging lately?

2012-01-27T05:19:00.000-08:00

I have to admit I'm obsessed with social networking. I have a love-hate relationship with the whole thing. Until last year I would've sworn I'd never jump the "networking" fence. My thoughts: "There's enough background noise already on the Internet." And: "I've got nothing interesting today."

Whether my posts are background noise or not, I'll leave it to you guys to decide, but I'm myself appalled by the fact that I've been blogging since last July and recently surpassed the threshold of 100 posts. That's not bad for somebody who thought they had nothing to say!

I can't help but wonder, though: what makes social networking so appealing? And how do people behave on the Internet? I've myself been on a couple of boards and found quite different behaviors, ranging from extremely aggressive to extremely supportive (yes, I love my G+ friends, absolutely love you guys!) From what I read about these things, the trend seems to be towards supportive. In fact, websites like Wikipedia and Foldit count on collaborative learning and crowdsourcing through networks based on the assumption that shared knowledge can rise over the background noise and provide meaningful advancements. A new research field has risen in order to analyze the huge amounts of data now available through the Internet.

It's mind boggling, isn't it?

All this to say that, much like I did in this post, I continue to avidly browse the literature looking for more info on social networks. Back when I wrote that post I hypothesized that "likes" on Facebook spread like viruses. My own experiment tells me that's not the case, but guess what? I did find something in the literature that mentions networks and viruses! Check it out:

"The user-generated content showed interesting viral-spreading patterns within blogs. Topical content such as news and political commentary spreads quickly by the hour and then quickly disappears, while non-topical content such as music and entertainment propagates slowly over a much long period of time [1]."

Ha! I knew I was right! Okay, I had the wrong "target." What's viral here is not the "likes" on Facebook, but blog content: for this particular study Cha et al. [1] analyzed 8.7 million posts from 1.1 million blogs -- wow, that's a lot!

Now, while I'm morbidly curious about these things, people smarter than me keep an eye on these data because of their economic value:

"Sentiments embedded in short text updates in social media have been shown to effectively predict and even precede the daily stock price variation (Bollen et al. 2011). Likewise, the blogosphere has been shown effective in capturing up-to-date news (Leskovec et al. 2009). In fact, a non-negligible fraction of news items shared in these social media are known faster than the traditional, authoritative news sources."

The paper lists several findings. First, when hey looked at the network structure of blogs, they saw a heavy-tailed distribution. Apparently, this is common to most network data: when you graph users vs. the amount of use/contribution to the network, you see few individuals contributing a lot (a spike in the graph), then a steep decline and a long tail indicating that the vast majority of the users contributes occasionally. Same with tweets, wikipedia edits, etc. However, unlike most other networks, blogs show much less reciprocity. That's understandable, as blogs are more intended as a means to publish content rather than exchange, giving rise to much less bidirectional nodes when you look at the blog graphs compared to posts on Facebook or Twitter.

The researchers also found that

"media content spreads according to two broad patterns: flash floods and ripples. The first group includes topical content such as news, political commentary, and opinion. Like flash floods, these types of content spread quickly by the hour and then quickly disappear. This demonstrates the role of blogs as a social medium that helps and influences how opinions form and spread on current issues. The second group includes non-topical content such as music and entertainment. Like ripples, old content (produced more than a year ago) can get rediscovered and again start gaining the attention of bloggers, albeit at a slow rate."

[1] Cha, M., Pérez, J., & Haddadi, H. (2011). The spread of media content through blogs Social Network Analysis and Mining DOI: 10.1007/s13278-011-0040-x

Surfing the wave of genetics: the man who invented genetic landscapes

2012-01-25T04:02:00.000-08:00

Today is the 90th birthday of the one and only Luigi Luca Cavalli-Sforza, professor emeritus at Stanford University and a pillar in population genetics. Oh, and in case you couldn't tell by the name, he's Italian, too. Not that I'm biased, mind you.

Cavalli-Sforza is best known for his book The History and Geography of Human Genes, in which he reconstructs the history of human migrations by mapping the distribution of gene alleles and correlating gene frequencies in populations with the geographic distances between them.

I had an interesting discussion a few months ago and it occurred to me then that many people outside the field of genetics still think that all traits are selected through evolution. This is not true. If you remember, another famous population geneticist came up with a mathematical model according to which it would take 300 generations for a trait under constant selection pressure to completely take over. That lead to Haldane's dilemma and the fact that such time scale was too slow to explain all genetic variation observed today.

The fact that Haldane's model didn't fit the observations eventually lead to the neutral theory of molecular evolution, and one of the greatest players in this new thinking was Motoo Kimura. Kimura's theory of "random genetic drift" is based on the assumption that most mutations are free of selective effects, and hence the rate of molecular evolution is determined by the mutation rate. This is backed up by the fact that most mutations we see are "silent" (which means they bear no effect on the proteins) and that most of the DNA in eukaryotes is non-coding.

Genetic drift is the change in allele frequencies due to chance. Under selection, some individuals pass their genes onto the next generation because they are "fitter." However, if not all traits are under selection, the vast majority is driven by chance. Some individuals will have offsprings, others won't, and each generation represents a new random drawing in the gene pool. When a random mutation arises in a population, assuming the mutation is neutral (in other words it doesn't affect the fitness of the individuals), the chance that it will get fixed in the population by random drift is 1/N where N is the population size. Therefore, the smaller the population, the greater the chance that a random mutation becomes prevalent by "chance" (and not selection!).

To celebrate Cavalli-Sforza's birthday, I chose a paper published in 2009 [1] that looks at genetic diversity in the Y chromosome and compares it to the expected variation under neutral drift. From the abstract:

"We observe geographic peculiarities with some Y chromosome mutants, most probably due to a drift-related phenomenon called the surfing effect. We also compare the overall genetic diversity in Y chromosome DNA data with that of other chromosomes and their expectations under drift and natural selection, as well as the rate of fall of diversity within populations known as the serial founder effect during the recent ‘‘Out of Africa’’ expansion of modern humans to the whole world. All these observations are difficult to explain without accepting a major relative role for drift in the course of human expansions."

The surfing effect is a really interesting phenomenon: mutations that arise in the wave front of an expanding population have an advantage over mutations that arise in individuals who are left behind with respect to the migrating portion of the population. This is because the front of the migration is a local, temporarily smaller population, and since the probability of a mutation to get fixed is inversely proportional to the population size, the fact that the mutants arise in a smaller population puts them at an advantage. Furthermore,

"The faster the population expansion, the greater the probability of success of a mutant that arises in the wave front, because then the wave front is longer."

In the paper, Chiaroni et al. look at the 18 major haplogroups (genetically similar groups that can be thought of as originating from the same ancestor) of Y chromosome genotypes and inferr their place of origin.

"If migrations were random, the geographic distribution of individuals with a specific haplogroup would be approximately normal (Gaussian) around the place of origin of the oldest mutation defining the haplogroup, apart from irregularities due to vagaries of the environment: obstacles, like mountains and deserts, or favored routes, like coasts and rivers."

The interesting finding in the paper is that while the expected genetic diversity for chromosome X more or less matches the observed one, the expected diversity of chromosome Y is significantly higher than the observed one indicating that, on average, there is more natural selection acting on X and the other autosome chromosomes than on the Y chromosome.

The authors conclude:

"The increasing role of human creativity and the fast diffusion of inventions seem to have favored cultural solutions for many of the problems encoun- tered in the expansion. We suggest that cultural evolution has been subrogating biologic evolution in providing natural selection advan- tages and reducing our dependence on genetic mutations, especially in the last phase of transition from food collection to food production."

[1] Chiaroni, J., Underhill, P., & Cavalli-Sforza, L. (2009). Y chromosome diversity, human expansion, drift, and cultural evolution Proceedings of the National Academy of Sciences, 106 (48), 20174-20179 DOI: 10.1073/pnas.0910803106

Mapping HIV-human protein to protein interaction reveals new targets for better drug design

2012-01-22T06:54:00.000-08:00

HIV has a small genome (roughly 9,000 bases) and it survives by using the host's proteins and DNA. Understanding how these proteins come in contact and interact with one another is crucial in order to unravel the mechanisms by which HIV hijacks the cellular machinery and proliferates. A comprehensive work [1] by a group of researchers at UCSF lead by Nevan Krogan looked at two human cell lines in particular and identified 497 HIV-human protein-protein interactions between 16 HIV proteins and 435 human factors. The study, published in the last issue of Nature, is the first one to look at protein-protein interactions in a host-pathogen system, and it opens up new possible targets for drug design.

The researchers devised a score to classify the strength of the interactions, which they statistically validated through random reshuffling. They identified 196 interactions in both cell types, while 150 and 151 were specific to each line (HEK293 and Jurkat cells respectively, two human cell lines that were isolated in the '70s and are used today in experiments). Interestingly, the proteins identified in both cell lines had stronger evolutionary signatures than the others, something the researchers were able to identify using comparative genomics between human and rhesus macaque.

Besides revealing an enrichment for host proteins that the virus recruits in order to replicate, the study unveiled proteins that have an inhibitory role during the infection. For example, they knocked down ten interactors using RNAi and observed an increase in HIV infection, suggesting that those factors may play a role in inhibiting replication.

"Ultimately, our analysis of the host factors co-opted by different viruses using the same proteomic pipeline will allow for the identification of protein complexes routinely targeted by different pathogens, which may rep- resent better therapeutic targets for future studies."

[1] Jäger, S., Cimermancic, P., Gulbahce, N., Johnson, J., McGovern, K., Clarke, S., Shales, M., Mercenne, G., Pache, L., Li, K., Hernandez, H., Jang, G., Roth, S., Akiva, E., Marlett, J., Stephens, M., D’Orso, I., Fernandes, J., Fahey, M., Mahon, C., O’Donoghue, A., Todorovic, A., Morris, J., Maltby, D., Alber, T., Cagney, G., Bushman, F., Young, J., Chanda, S., Sundquist, W., Kortemme, T., Hernandez, R., Craik, C., Burlingame, A., Sali, A., Frankel, A., & Krogan, N. (2011). Global landscape of HIV–human protein complexes Nature DOI: 10.1038/nature10719

Photo: I'm crazy about soap bubbles this week. The macro lens can enlarge all the pretty color patterns and they are so, so beautiful. More bubble awesomeness to come later!

Regenerating tissue through autologous cells: a personal appeal

2012-01-18T20:14:00.000-08:00

The trachea is one of the most challenging organs to transplant, with a high risk of necrosis and infection due to inadequate graft revascularization and the fact that it's constantly exposed to airborne elements. Transplants requires lifelong immunosuppression, which also carry high risks. Prosthesis can rupture, generate infection, and cause injury.

What to do then? One answer is tissue engineering.

Dr. Paolo Macchiarini is one of the pioneers in this techniques. In a recent paper [1] he and his co-authors

"describe in detail the tissue engineering approach used for tracheal construction, with a focus on the mobilization, isolation, and in vitro culture of cell types with high potential for use in bioengineering."

The technique is highly sophisticated and I'm sure I'm doing a poor job here in trying to explain it in simple terms. The starting point is a scaffold that should provide the basic characteristics of the trachea. As Macchiarini and colleagues state in the paper,

"Despite intensive research in this field, no solution has been proposed as being optimal; currently both natural and synthetic grafts are being used."

In one case study in particular, they used as scaffold a decellularized cadaveric organ from a human donor trachea, and then colonized it by epithelial cells and MSC-derived chondrocytes cultured from autologous cells taken from the patient. They aspirated bone marrow from the patient to obtain marrow mononuclear cells. These contain a class of repair cells called multipotent mesenchymal stem/progenitor cells, cells that are able to differentiate and hence can be used to regenerate tissue. The researchers separated the cells, differentiated them, and then seeded them along a scaffold:

"We then expanded and differentiated these cells toward chondrocytes and seeded the cells into the exterior spongy layer of the scaffold, where they formed the cartilaginous component. For generating the inner epithelial lining of the trachea, we seeded the surface of the scaffold with nasal epithelial cells, after in vitro expansion to obtain sufficient numbers for seeding the graft."

Above: The entire concept of the regenerative approach to tracheal transplantation using natural scaffolds. MNC, mononuclear cell.

While ex-vivo, the tissue is maintained through a perfusion system called bioreactor. Once implanted, several pharmacologic intervention are prescribed to minimize the risk of necrosis, infection, and cell migration. Despite the non-trivial risks, the result is incredible:

"Since 2008, nine patients (ranging in age from 11 to 73 years), with either benign or malignant conditions, were treated using this decellularized scaffold. To date, the new in vivo engineered transplanted tracheas have been shown to be viable and to possess a good epithelial coating, are characterized by immediate vascularization, and, above all, maintain a constantly open lumen for air passage."

Please help Rachel Breathe

Now, to most of us, what I've discussed above is fascinating science. To some, is hope for a new life. Rachel Phillips was a ballet dancer with Royal Ballet in London, the Kirov in St. Petersburg, Russia and other major companies in the US and abroad. Today, with over 90% of her airways collapsed, Rachel is fighting for her life. She suffers from a genetic disorder called Ehlers–Danlos syndrome, which is caused by mutations in a number of genes involved in either the structure, the production, or the processing of collagen. Collagen is essential in all connective tissues in the body. Because of this Rachel needs a new trachea and Dr. Macchiarini's tissue regeneration technique can give her one but she needs our help.

Please visit Rachel's website at helprachelbreathe.com/ and help her out with a donation. This is not just science. It's life!

Thank you.

[1] Jungebluth, P., Moll, G., Baiguera, S., & Macchiarini, P. (2011). Tissue-Engineered Airway: A Regenerative Solution Clinical Pharmacology & Therapeutics, 91 (1), 81-93 DOI: 10.1038/clpt.2011.270

Introns, exons, and stop codons: how antisense oligonucleotides can fix frameshift mutations

2012-01-17T06:05:00.000-08:00

DMD is the largest gene in nature, covering roughly 2.4 mega bases of the X chromosome. It encodes the dystrophin protein, a component of the protein complex that connects the cytoskeleton to the extra-cellular matrix.

DMD is a very complex gene. Its RNA transcripts are differentially spliced, which means that the gene produces different transcripts, encoding a large set of protein isoforms. A refresher: every gene is composed of coding parts, called exons, interspersed with non-coding bits, called introns. When the gene is transcribed into RNA, a process called RNA splicing, the introns are removed and the exons (grr… my auto-correct keeps turning all my "exons" into "eons"!) reassembled to form the RNA transcript that will be used to form proteins. Some proteins, like dystrophin, have different isoforms (some specific to different cell types), and those are obtained through different splicing forms of the RNA, originated by maintaining a different number of exons in the final transcript.

This video is a good illustration of RNA splicing:

All this to give you an idea of how complex this gene is. So, when it carries a mutation, things get very complicated, and the consequences devastating. Mutations in the DMD gene are responsible for several forms of muscular dystrophy (MD), and because the gene is on the X chromosomes, the prevalence is usually higher in boys than girls. (This is because girls carry two X chromosomes, hence if one allele only is mutated, the other will compensate.)

The most common mutations causing muscular dystrophy cause the transcription process to stop too early, producing incomplete, and therefore non-functional, RNA transcripts. I discussed reading frames in this post: in layman terms, the reading frame of a gene is how you split the bases in triplets so that each triplet codes one amino acid (the building blocks of proteins). Mutations that cause a shift in the reading frame basically disrupt the translation into amino acid, often resulting in the early termination of the transcription process (when the frameshift causes the random appearance of an early stop codon). When not enough functional dystrophin is produced, individuals experience a significant loss in muscle function and muscle degeneration.

How to counteract the action of frameshifting mutations?

One way is to use antisense oligonucleotides, buts of RNA that bind to a splicing site on the pre-mRNA causing the deleterious exons to be skipped and thus restoring the "functional frame." What does this mean? Remember, RNA is one-stranded. From DNA to RNA there are several steps: pre-messenger RNA and messenger RNA, or mRNA. The deleterious mutations are on the gene and they cause a misread when going from DNA to pre-mRNA. Now the mutations are on the pre-mRNA. Suppose you can devise a "bandage" that literally covers the bit of bases causing the framshift. If the bandage works, the bit won't be read when the pre-mRNA is turned into mRNA thus effectively canceling the frameshift and restoring the original RNA transcript. These "bandages" are bits of antisense RNA specifically made to bind to the "bad" parts of pre-mRNA. I covered this kind of therapy in an earlier post on gene therapy.

Does it work? So far, enough to give hope.

Goemans et al. [1] recruited 12 patients with Duchenne's muscular distrophy. Over the course of 12 weeks, the patients received weekly, dose-escalating

"weekly abdominal subcutaneous injections of PRO051 (from 0.5 to 10 mg per kilogram of body weight, with 3 patients receiving each dose) for 5 weeks. The specific increases in dose were determined after analysis of safety and dystrophin levels in muscle-biopsy specimens."

The lowest dose of 0.5 mg per kilogram showed no effect on RNA or protein expression. Exon-skipping RNA was instead observed in the higher-dose patients. Muscle biopsies were sampled at the end of the high-dose period and new dystrophin expression was observed starting from week 2, with increased signal as time and dose progressed. By the end of the twelve weeks the average distance walked in six minutes across all patients had increased by 35 meters, with some patients able to walk 65 meters farther than at baseline. Patients were also tested 2 and 7 weeks after the treatment, and most still showed similar dystrophin expression levels as right after the treatment.

Though a lot still needs to be done in order to defeat this disease, these results certainly set a much needed step forward.

[1] Goemans, N., Tulinius, M., van den Akker, J., Burm, B., Ekhart, P., Heuvelmans, N., Holling, T., Janson, A., Platenburg, G., Sipkens, J., Sitsen, J., Aartsma-Rus, A., van Ommen, G., Buyse, G., Darin, N., Verschuuren, J., Campion, G., de Kimpe, S., & van Deutekom, J. (2011). Systemic Administration of PRO051 in Duchenne's Muscular Dystrophy New England Journal of Medicine, 364 (16), 1513-1522 DOI: 10.1056/NEJMoa1011367

This picture was a "Rule of Thirds" exercise: find an interesting background, and have the main subject of your photo cover one third of the picture only, instead of positioning it in the middle. You can see how it immediately makes both subject and background more interesting. Focal length 26mm, shutter speed 1/25, ISO speed 100, F-stop 7.1

Tackling the mysteries of evolution: Peter Watts talks about consciousness, publishing, and his Hugo nominated novel Blindsight

2012-01-16T07:36:00.000-08:00

One of the things I enjoy the most about running this blog is getting to know writers. I also get to learn about the infinitely many faces of the publishing world, like the new and ever-growing realm of self-publishing. Today, though, I have a story that is even more amazing, because amazing is the person I talked to: marine biologist Peter Watts is the author of the Hugo nominated novel Blindsight, as well as the Rifters Trilogy Starfish, Maelstrom, and Behemoth. Publisher's Weekly gave Blindsight a starred review, defining it an

"Intellectually challenging hard science fiction ... Watts puts a terrifying and original spin on the familiar alien contact story. Combines riveting action and a fascinating alien environment with a stimulating exploration of the nature of consciousness."

Peter is one of the most interesting writers I've talked to, so without further ado, please join me in welcoming Peter to the blog today!

EEG: For starters I'd like to know more about your research: I love marine biology, can you tell me a bit about what you do?

PW: Research-wise, these days, zippo. I used to work on the distributional/biophysical ecology of marine mammals, but that was before I ran screaming from academia in reaction to the inevitable craven political bullshit involved. For a while I worked for a research consortium investigating why marine mammal populations in the North Pacific/Bering had collapsed a few years after the US fishing industry moved into their feeding grounds. Turned out most of our funding came from the US fishing industry; what could possibly go wrong? I also worked for a private research association funded by the International Fund for Animal Welfare. Turned out I wasn't allowed to say anything that might reflect negatively on the animal welfare movement.

I'm told that somewhere, in some far-off land, scientists are not whores with data sets. Somewhere, people like me get to follow the data wherever they lead. I remain skeptical. If such a utopian realm exists, it does not lie within the bounds of marine mammalogy. So these days I'm pretty much a full-time writer. I still do the occasional bit of biostatistical analysis as an independent consultant -- migratory waterfowl stuff, mainly -- but it's been years since that was my primary source of income. At least with science fiction, you're supposed to make shit up.

EEG: LOL. I see. I guess I'm lucky, then, to be working on viruses instead of mammals. Though a decade ago saying that AIDS was caused by HIV was also something highly frowned upon.

Let's talk about your books. Blindsight is a fascinating read that touches on many scientific and philosophical concepts. Can you tell me how the story was born? Was it one concept in particular that intrigued you or a scene or... ?

PW: The question of consciousness -- not what it is so much as what it's good for, in a Darwinian sense -- has been rattling around in the back of my head ever since 1991, when I read an offhand comment Richard Dawkins made in an afterword to an anthology of ecology essays he'd edited. I can't remember what that book was called -- it had a pale blue cover with a picture of a wasp's nest on the front, if that's any help -- but Dawkins tossed off this remark to the effect that it was very easy to imagine a nonconscious meat robot that could do pretty much everything we do, so the functional utility of consciousness is thus one of the great mysteries of biology.

He obviously wasn't the first person to raise that issue; his iteration just happened to be the one I read at an impressionable age. As thought-fodder, it was both profoundly inspiring and profoundly limiting. Inspiring, obviously because sapience seems to be at the heart of what we are as a cognitive species, and we have no damn idea how it works. But limiting, too, because the question "What is it good for?" implies that it is, in fact, good for something. The question itself puts you in a box. Obviously self-awareness serves a purpose to the organism; surely natural selection would have weeded out anything so metabolically expensive if it didn't serve some vital purpose, yes?

So I went for years trying to think of what that vital purpose was. Finally I realized that nobody asks how a parasite benefits its host; the very question would betray an ignorance of what parasites are. And then it occurred to me that the very absence of function -- the idea that the core of what we most exalt about ourselves might in fact be an impediment, that the little guy behind the eyes is actually a tapeworm that the system would be better off without -- well, that's a much more dramatic punchline than the realization that, Oh, of course, we need self-awareness because we couldn't do X particular thing without it. So that's what I went with; it was consistent with the limited research I'd done, it was beautifully nihilistic, it would make a memorable point that readers could argue about. But I didn't really believe it. I figured there was some obvious function that just hadn't occurred to a dabbler like myself, and that any real real expert would shoot down that punchline in an instant.

It wasn't until I got to the copy-editing stage that it began to dawn on me that a significant number of those experts were coming to exactly the same conclusion. Lucky coincidence, eh?

I'd just add here that, having broken out of the "Must be good for something" box, there's a follow-up question that I find very helpful when dealing with those papers that do argue for useful sapience. Some are really ingenious; perhaps my favorite was a piece by a dude named Ezequiel Morsella, who claims that consciousness exists to mediate conflicting motor commands to the skeletal musculature. The question I always ask myself when such a mechanism is presented is "Okay, but is it possible to imagine a nonconscious agent that does the same thing?" I'm perfectly willing to accept that we use consciousness for a variety of tasks-- evolution is always grabbing whatever's at hand and repurposing it to some other task. So maybe we do use self-awareness for logical deduction, or muscle mediation, or the aesthetic appreciation of grapes for all I know. But to me, a more interesting question is always, can we imagine something that does all that nonconsciously? Would its solution to the problem be more efficient than ours? And would it kick our asses if the two of us ever ended up on an island with limited resources?

EEG: That's fascinating and indeed one of the hardest problems ever tackled by both science and philosophy. Though if I may add my two cents, I think the heart of the problem is that the question "What is it for?" in science is ill-posed. Take genetics, for example. So much work has been done looking for "causative" loci, attributing function X to locus Y, when in fact it's like trying to answer the question of why a stream chose exactly one path to come down from the mountain, out of a million possible paths.

Back to consciousness, I was quite intrigued, last September, by your observation on Too Hard for Science? that if you split the brain down the middle you get a split in consciousness with different tastes and opinions.

Which sort of brings me to the next question... In your bio you write: "Peter Watts has spent much of his adult life trying to decide whether to be a writer or a scientist, ending up as a marginal hybrid of both." Can you elaborate more on how the two worlds, science and writing, coexist in you?

PW: I've wanted to write SF (age seven) almost as long as I wanted to be a marine biologist (age five). To me, both pursuits are flip sides of the same coin: both involve experiments of a sort. You start with a premise, and (here it comes again) follow the data. The difference, of course, is that there are fewer constraints when writing SF: you don't have to spend ten years developing real-world expertise in your subject; you don't have to fellate NSERC or the NSC for funding; peer-review -- such as it is -- is generally a lot more forgiving. You're not saying "This is"; you're asking "What if it was?" But in both cases you're exploring questions about the way the universe works.

Of course in science fiction your answers are more likely to be wrong, because you generally don't have the requisite fine-scale expertise and nobody can predict the future. But in real science, your answers are less likely to be deep, because most science is step-by-step trudgery and the filling in of a million little holes in the knowledge base. It doesn't matter whether your data are more reliable: "What if the lachrymal secretions of herring gulls can be used as an index of heavy-metal contamination" just doesn't have the same zing as "What if the Internet developed a sex drive?"

(I'd also add here than I'm increasingly convinced that too much scientific expertise actually makes one a worse SF writer, simply because every time you have a cool idea, your own expertise squashes it flat with all the reasons why it would never work. You become strait-jacketed by your own knowledge of the state of the art.)

EEG: Ah, we're on the same page on this one. I've written in another interview that I truly believe that writing a story (any story, in fact, not just SF) is like solving a system of equations. Your variables are the characters, your initial conditions the premises, and then you just sit down and solve it.

Let me warp up with one last question: I'm curious as to why you have a free version of Blindsight on your website when the book is on the market...

PW: I myself went the Creative Commons route for two reasons. Short stories, out-of-print titles in my backlist had stopped earning money anyway. I was giving up nothing by posting them online, and by setting them free I was increasing my exposure to potential fans who might go on to buy my next book if they liked what they read. At the very least it would cost me nothing, and at most it could significantly increase my readership.

I set Blindsight free, however, while it was still in print (just a couple of months after it was released, in fact) and for entirely different reasons. It's pretty obvious that Tor had written it off as a failure even before it was released: one of the two largest retail distributors on the continent had chosen not to preorder any copies, so Tor slapped on a cheap-ass cover and put out a very small print run. Then the critics started raving about it, but of course because so few copies had been printed nobody could buy the damn thing; Blindsight was the weekly #1 bestseller in at least a couple of stores that didn't even have any copies‚ the greatest number of their orders was for a book they didn't even have in stock, because not enough copies had been printed to meet the demand!

You'd think at this point that Tor would've hustled out another print run, and they did in fact start talking about it. But then they decided to wait until all the physical stock had left their warehouses. Then, once that that happened, they changed their minds and decided to wait until the back orders had built up. They kept moving the goalposts.

At this point I had pretty much come to the conclusion that Blindsight was going to fail commercially no matter how many good reviews it got, simply because there were so few copies for sale. So I had a choice: it could fail commercially and be read by no one, or it could fail commercially and at least be freely available to anyone who wanted it. There was no "succeed commercially" option that I could see. So, with nothing to lose, I put it out in the Creative Commons‚Äî and hardcover sales nearly tripled the very next week. The rest is history: strong sales, numerous award nominations, multiple hardcover printings, and widespread overseas translations. Blindsight is being used as a required textbook in a couple of university philosophy courses, and even as a core text in a neuropsych course at the University of Miami. It's been a commercial and critical success beyond anyone's expectations, and there's no doubt in my mind that none of that would have happened if I hadn't resorted to a Creative Commons release.

It's important to recognize, though, that it wasn't the CC release per se that caused the boost in sales, it was the publicity that resulted from the CC release. My actions were covered by boingboing, and by high-profile bloggers like John Scalzi and Kathryn Cramer. If those folks hadn't taken notice, Blindsight would have languished. But giving one's stuff away is still a pretty rare strategy, and that makes it newsworthy, and that's why my strategy worked.

That's also why it won't work for very much longer. As more and more people jump on the CC bandwagon, this kind of move will become a lot less noteworthy. We'll have to come up with some other way of drawing attention to our work. But for now, and in this case, the Creative Commons did more than just boost my sales and get me wider recognition; it literally saved my career as a writer.

EEG: I'm really glad it worked because you totally deserved the success. Thank you so much for being with us today and for sharing your experience with us.

To find out more about Peter's books and work, check-out his website and his blog, where he muses about writing, publishing, and yes, of course, science, too.

Sickle cell anemia, malaria, and the heterozygote advantage

2012-01-13T05:51:00.000-08:00

Hemoglobin is the oxygen-carrying protein found in the red cells of our blood. Patients with sickle cell anemia have a sickle form of hemoglobin. While healthy red cells are shaped like a disk pinched in the middle (a doughnut without a whole), in patients affected by the disease the sickle hemoglobin forms strands which cause the red cells to be shaped like a crescent. This causes all sorts of complications and risks: the sickle red cells are more rigid and increase the risk of ischemia and necrosis; the drop in hemoglobin can cause painful enlargement of the spleen, anemia, tachycardia.

Sickle cell anemia is caused by a single-base polymorphism, SNP rs334, in the hemoglobin gene. The "normal" allele is A, whereas the mutated one is T. As you know, we all carry two copies of each genes, so the vast majority of the population has AA at this locus, a few carry AT and very few TT. Heterozygous carriers of the SNP (people who carry the AT form) are, for the most part, not affected by the disease. The healthy gene allele produces enough healthy hemoglobin to compensate for the sickly one.

This is not uncommon in genetics: another example of disease that's only expressed when both gene copies are mutated is cystic fibrosis. You may carry the "mutated SNP", but so long as you have only one copy, you're not affected by the disease. The problem is when both parents are carriers: if the child inherits both mutated alleles, she will develop the disease. Now the question is: if this allele causes such a devastating disease, why has it not been wiped out by natural selection and/or genetic drift?

The answer lies in a concept called heterozygote advantage: if the one allele turns out to be advantageous in certain circumstances, then it will still be prevalent at a certain frequency in the population. For example, the allele that causes cystic fibrosis has been hypothesized to protect against cholera, typhoid, and diarrhea. In the case of RS334, the sickle cell anemia SNP, the mutant has been proven to confer an advantage against malaria:

"These deleterious mutations are maintained in the population in a state of balanced polymorphism because of the protective effect against severe forms of malaria conferred by the heterozygous states. [...] However, it is not clear what happens to these polymorphisms in areas where the selective pressure has become relaxed or is nonexistent altogether. In some cases, as in the Caribbean, the HbS mutation has been shown to continue to exist with unaltered frequency, despite the near eradication of malaria more than half a century ago [1].

In [1] Salih et al. looked at the prevalence of malaria in the population from two African villages, Hausa and Massalit. The two populations were of different ethnic origins, and in both malaria was endemic but mostly mild. Within the two populations, they looked at the genotype frequencies of the sickle cell polymorphism and used a simulation to predict its behavior. Although the sickle cell SNP conferred significant protection from malaria in both populations, they found a trend for a decrease of the RS334 allele frequency in Hausa and an increase of frequency in Massalit. They conclude that this effect may be due to the fact that

"In the Hausa village, this seems to be likely due to the low clinical burden of the disease, the population effect (possibly under drift) in addition to the deleterious impact of the homozygous allele, both conspiring against the maintenance of balancing selection. In the Massalit village, the relatively higher episodes of clinical malaria, in addition to a potential impact from visceral leishmaniasis (a disease with a higher fatality rate), may be responsible for the different selection profile."

[1]Salih NA, Hussain AA, Almugtaba IA, Elzein AM, Elhassan IM, Khalil EA, Ishag HB, Mohammed HS, Kwiatkowski D, & Ibrahim ME (2010). Loss of balancing selection in the betaS globin locus. BMC medical genetics, 11 PMID: 20128890

Blinding pain, simple truth: a professor of mathematics heals himself through Buddhist meditation

2012-01-12T10:58:00.000-08:00

Husband, father, grandfather, and teacher, Richard S. Ellis is a professor of mathematics and an adjunct professor of Judaic studies at the University of Massachusetts Amherst. And, for the past few years, a promoter of Buddhist meditation through his book, Blinding Pain, Simple Truth.

How did a professor of mathematics end up writing a book on Buddhist meditation? It’s a fascinating story, one that I was lucky enough to hear in person since I’ve known Richard for over ten years now, and I was thrilled when he graciously accepted to share it here on Chimeras.

EEG: I know you’ve always been writing: papers, essays, novels, and more. Do you find that the writer in you is an essential part of the scientist, or are the two completely separate?

RSE: I love writing, and I’d like to put it in a wider context. My area of research in mathematics is the theory of large deviations, which studies random events having small probability and often significant effect. More broadly, a large deviation is any event defying expectation: a surprise, a revelation, a miracle. My activities as a scientist and as a writer have their roots in this theory because my life has been a large deviation in numerous ways, Jewish, literary, spiritual, and mathematical. A major example is the casual conversation at a bat mitzvah in 1981 that inspired my family and me to spend a sabbatical the next year in Israel, a visit that changed my life by putting me on a spiritual journey through Judaism, Torah, literature, and Buddhism that still continues.

The writer in me is definitely an essential part of the scientist. I don’t see a big difference between writing about mathematics and writing about literature or spirituality because in essence it’s all text. As I continue to write and discover new fields and new connections, I feel as if I am building a palace of mirrors in which everything reflects back on everything else. In this sense writing is an act of creation that brings light where there was darkness, order where there was chaos, and connections that previously were not seen.

EEG: You have so many interests. You are a professor of mathematics, an adjunct professor of Judaic studies, and you have published and taught courses in mathematics, literature, and Bible studies. What inspires your writing the most?

RSE: Let me answer by referring to the poem “so you want to be a writer?” by Charles Bukowski. In it he gives one view of the writing process: “if it doesn’t come bursting out of you / in spite of everything, / don’t do it.” This poem certainly expresses the initial, exhilarating inspiration that I have always felt while writing, the sense that I have something new and important and even life-altering to say. However, the poem minimizes the painstaking work required to polish a piece. I first felt “it” bursting out of me when I was an undergraduate at Harvard, writing an honors thesis on the figures of Apollo and Buddha in the New Poems of Rainer Maria Rilke. Under Rilke’s inspiration, I filled notebooks with my own poetry and published a few.

I continue to be inspired by the same feeling of exhilaration whether I discover a beautiful solution of a difficult problem in mathematics or understand a resonance between a poem of Emily Dickinson and a passage in the Torah or so quiet my mind that the deep spirituality of a Psalm of David reveals itself to me. The inspiration bursts forth, and I start to write in ever-widening circles, each new section putting previous sections in a new light, and I revise, motivated by the insight that language is inherently linear while what I am trying to capture is nonlinear. Finally, after much work, it crystallizes as I finally see how all the pieces interconnect and find the words to express these interconnections.

EEG: Please tell us how you discovered Buddhist meditation and how your book, Blinding Pain, Simple Truth, came to be.

RSE: The short answer is that I discovered meditation because of pain. In 1980 a therapist introduced me to relaxation techniques based on Buddhist meditation to deal with tension headaches. These techniques were miraculously effective. However, as soon as the headaches were healed, I stopped meditating and stopped listening to the wisdom of the headaches as I threw myself into an ambitious project of a research-level math book. Headaches returned twenty years later, in February 2000, and this time they were much worse, nearly destroying my career. Desperately seeking help from doctors but unable to find relief from the many pills they prescribed, I dealt with the pain by anger, avoidance, and fear, which only compounded my suffering.

After suffering for two and half years, in September 2002 I sought help from Jean Colucci, a psychologist who based her therapy on meditation and Buddhist teachings. My work with her set the stage for a transformative experience in the summer of 2003. At a meditation retreat I experienced the truth about the headaches and the suffering they had caused. This truth is so simple, yet so deep: it is not the pain that causes suffering, but the mental state associated with the pain. Through meditation I learned not to push the pain away, or to react to the pain with anger and fear, but rather to accept it. Accepting the headaches allowed them to become my best teacher, a wise guide who constantly reveals new insights about life and pain and suffering and letting go and love.

The wisdom about pain, suffering, and healing that the headaches revealed is the subject of my recently published book, Blinding Pain, Simple Truth: Changing Your Life Through Buddhist Meditation. My goal in writing it is to empower people who suffer from physical and emotional pain to heal their suffering and embrace their lives with equanimity, gratitude, and joy.

I started writing the book at the suggestion of a literary agent, who found me on the internet in 2003. My experiences with the headaches had been so profound that, as Charles Bukowski describes, the inspiration for the book burst out of my heart and my mind and my mouth and my gut. However, revising and polishing the manuscript took years. In 2007 the literary agent announced, without explanation, that she could no longer represent the book. After much effort and further revision, I was able to place the manuscript with Rainbow Books, which published it in 2011. As I have often joked, the quest to write a book on Buddhist teachings and find a publisher requires the full wisdom of Buddhist teachings to lead one through the labyrinths and past the ego-traps that make this quest such a challenge.

As the book describes, every day I am blessed by the gifts of infinite worth that meditation has bestowed upon me: it calms my mind, enables me to connect with the wisdom of my body and the wisdom of the present moment, allows my body’s natural healing powers to flourish, and has freed me from the prison of chronic pain into a vast landscape of equanimity and peace. The book is also an invitation to begin meditating. It is a practice with potentially infinite rewards that can become an all-encompassing approach to people’s lives as it has become with mine.

EEG: That is truly amazing. Thank you, Richard, for sharing your story with us and for spreading the word through your book.

Richard S. Ellis has published numerous papers in mathematics and is the author of two research-level math books. He has also published poetry and articles on the Torah, literature, art, and anti-Semitism and the Holocaust. To learn more about his recently published book, Blinding Pain, Simple Truth: Changing Your Life Through Buddhist Meditation, check out his website at RichardSEllis.com. You can also email Richard at rsellis (at) math.umass.edu. Information about his work and interests is available at his webpage.

Having kids wears you out? Same holds for telomeres. In zebra finches.

2012-01-10T16:00:00.000-08:00

One of my most popular posts on the blog has been The Immortality Paradox, in which I discuss telomeres, aging, and cancer. Telomeres are the ends of he chromosomes, a bit of non-coding DNA that naturally wears off as cells divide and as we age. Once the telomeres reach a certain critical length the cell stops dividing and eventually dies. As a consequence, telomeres length varies across age groups but, even within the same age group, it varies from individual to individual. So, it becomes natural to ask: is this variation in telomeres length correlated to longevity?

A new study published in PNAS [1] seems to indicate that it is. Now, my personal disclaimer is that I'm always a little skeptical about associations with longevity because there are so many factors and confounders that it's really hard to extrapolate meaningful p-values. However, this study was done in birds (Taeniopygia guttata, or zebra finches), which makes it less prone to bias than a human study. In fact, the authors cite various studies that attempted to correlate telomeres length an longevity in humans but yielded mixed results. Most importantly, these earlier studies had not monitored telomeres length since an early stage in life, something that is critical in order to account for environmental factors that have been shown to accelerate telomere shortening.

In this study, Hedinger et al.

"examined telomere length in red blood cell samples from early in life (at 25 days) and at various points thereafter in a group of zebra finches (n = 99) that were allowed to live out their natural lifespan (ranging from 210 days to 8.7 years). We also examined the effect of reproduction on adult telomere length, by experimentally manipulating whether, and how often, individuals were allowed to breed. These data enabled us to uniquely examine the relationship between telomere dynamics from early in life and total lifespan and reveal that telomere length in early life is a highly significant predictor of the age of death."

While they found no differences between genders, Heidinger et al. did record a decrease in telomere length with age, which was most marked during the first year of life. Interestingly, they also found that telomere shortening was accelerated in birds engaging in reproduction. (When parents say kids make them age faster, they mean it!!) The effect, though, did not persist, and at the next time point the effect of reproduction on telomere length had weaned. Of course, the most interesting result was the significant correlation between telomere length in early life and lifespan. It is important to note that the highly significant correlation was with the measurement taken early in life: length measured at later time points didn't have such a strong predictive effect.

"We found telomere length at 25 days to be a very strong predictor of realized lifespan (P < 0.001); those individuals living longest had relatively long telomeres at all points at which they were measured. Reproduction increased adult telomere loss, but this effect appeared transient and did not influence survival. Our results provide the strongest evidence available of the relationship between telomere length and lifespan and emphasize the importance of understanding factors that determine early life telomere length."

The authors underline what still remains to be seen:

"Whether telomere length change itself plays a directly causative role in determining the pace of decline and age of death is an active area of research. Several mechanistic routes have been identified, mainly from in vitro studies, whereby shortened telomeres can accelerate aging and reduce longevity, primarily involving activation of cellular checkpoints of apoptosis, cell cycle arrest, and impaired stem cell and tissue function."

One thing is certain: any analogous study to be carried in humans should measure telomere length very early in life because, as this study shows, if individuals with shorter lengths die earlier, a sample of lengths measured later in life would already be skewed towards longer length (since individuals with shorter length would have already died) and hence the results would be inconclusive.

[1] Heidinger, B., Blount, J., Boner, W., Griffiths, K., Metcalfe, N., & Monaghan, P. (2012). Telomere length in early life predicts lifespan Proceedings of the National Academy of Sciences DOI: 10.1073/pnas.1113306109

Can you write with... light?

2012-01-10T06:27:00.000-08:00

I discovered a new game I can play with my macro lens...

It's called lightwriting. Usually you move the light in front of the camera, but this time I did the opposite. Moved the camera in front of the light and kept the shutter open between 5 and 10 seconds. Fun! You can do it with any lens, but I like it better with the macro because you can use smaller lights like the tiny light on the laptop, mouse, an alarm clock, etc.

Chaperon proteins do more than... chaperon

2012-01-09T06:10:00.000-08:00

The full human genome was typed for the first time in 2003. Ever since, there has been a "hunt" for mutations and, more in general, associations between genotypes and phenotypes. As I have pointed out multiple times on this blog, things have turned out more complicated than originally anticipated: what happens between DNA and proteins (what we could consider the "end" product) is still very much a "black box" in which epigenetic changes and RNA editing can completely turn around the outcome. Furthermore, the interaction between genes and mutated loci can either increase or decrease the likelihood of certain phenotypes, given the genotype.

Take molecular chaperones, for example. These are proteins that assist the folding and unfolding of other macromolecules. They are typically involved in protein folding, but they also assist the assembly of nucleosomes from folded histones and DNA in the nucleus (see this earlier post on chromatin) and thus, by changing the topology of the nucleus, they play an important role in regulating gene expression.

A study published in the last issue of Science [1] looks at the role of chaperon proteins in compensating for deleterious mutations in Caenorhabditis elegans. Casanueva et al. found that worms with higher expression of protective chaperon genes were more resistant to deleterious mutations: worms with a potentially deadly mutation received a mild heat stress when still larvae. The heat stress promoted the expression of protective chaperon genes, and in some of the worms this prevented the deleterious misfolding of proteins, resulting in a 35% increase in chance of survival.

"We subjected animals to a transient heat shock as larvae to induce a stress response, allowed them to develop to adults, and examined the proportion of individuals affected by late-acting mutations. When a mutation was chaperone-dependent, a mild environmental challenge stimulated a reduction in penetrance."

Paradoxically, they also found that individuals with higher chaperon expression reproduced less. Why, if the higher expression seems advantageous and protective? Casanueva et al. hypothesize that the net effect is to maintain a heterogeneous population in levels of expression, and this is more advantageous to the survival of the population than homogeneous levels of gene expression. In other words, what is advantageous to the individual is not necessarily advantageous to the species.

From the paper abstract:

"The induced mutation buffering varies across isogenic individuals because of interindividual differences in stress signaling. This variation has important consequences in wild-type animals, producing some individuals with higher stress resistance but lower reproductive fitness and other individuals with lower stress resistance and higher reproductive fitness. This may be beneficial in an unpredictable environment, acting as a “bet-hedging” strategy to diversify risk. These results illustrate how transient environmental stimuli can induce protection against mutations, how environmental responses can underlie variable mutation buffering, and how a fitness trade-off may make variation in stress signaling advantageous."

Of course, it's not clear how this could apply to humans. However, it does prompt caution when treating a person's full genome as a key to disease risks. We are still far from unraveling the complete interactions between genome, epigenome, and proteome, and, as I've often said before, Mother Nature has made us far more complex than any of our models can predict.

[1] Casanueva, M., Burga, A., & Lehner, B. (2011). Fitness Trade-Offs and Environmentally Induced Mutation Buffering in Isogenic C. elegans Science, 335 (6064), 82-85 DOI: 10.1126/science.1213491

Photo: it's not what it looks like! This is eggs, water and vegetable oil all mixed in a blue bowl to make brownies. Seriously. You just set the bowl under a lamp and suddenly it behaves like a mirror. Eventually the mix turned into brownies, but not before my daughter and I had a little fun shooting pictures.

The curse of drug-resistant TB strains

2012-01-06T05:46:00.000-08:00

Tuberculosis (TB) is a disease caused by a number of strains of mycobacteria. It affects mostly the lungs with chronic, bloody cough and fever. It can remain asymptomatic as a latent infection, though about 10% of these latent infections eventually progress to active disease.

The two most common drugs used to treat TB are isoniazid and rifampicin, but unfortunately new mycobacteria strains (called MDR strains, which stands for multi-drug resistant) have emerged that are resistant to both these powerful drugs. In other words, the pathogens have developed certain mutations that make them "immune" to the drugs. As with HIV, common thought is that these drug-resistant strains emerge during the course of the treatment in single individuals as a result of the selection pressure induced by the drugs. This is also reinforced by the fact that typically drug-resistant mutations confer a cost of fitness: though able to escape the drugs, the mutated strains tend to reproduce less quickly and/or are not able to be transmitted.

Unfortunately, that's not always true. A study published by Nature Genetics in December [1] showed that MDR TB strains do not show a fitness cost and that the most common drug-resistant mutation is present in the population with a wide variety of compensatory mutations. These are additional mutations that compensate for the loss of fitness by working in antagonistic epistasis to lessen the structural and functional instability of the affected proteins.

Comas et al. compared

"the genome sequences of ten paired clinical rifampicin-resistant isolates to the genomes of the corresponding rifampicin-susceptible isolates recovered from the same infected individual at an earlier time point. We identified all nonsynonymous and intergenic mutations found only in the rifampicin-resistant genomes. In addition, we experimentally evolved six laboratory-derived rifampicin-resistant mutants from rifampicin-susceptible ancestors during 45 weeks of serial subculture in the absence of rifampicin."

They showed that

"The high frequency of compensatory mutations in strains from Abkhazia/Georgia, Uzbekistan and Kazakhstan is consistent with the success of MDR strains in these regions, where up to 50% of individuals with TB are estimated to carry MDR strains compared to a global average of only 3%."

These findings are particularly relevant for TB treatment policies: isoniazid and rifampicin have been used not only to treat infected patients, but also as a preventive measure for people visiting countries with high TB prevalence (as for example peace corps). Furthermore, people are treated as soon as they become TB positive, but for the most part these infection are latent and all genetic information we have on TB is from active infections. There's no way to know if these drugs are effective until the infection becomes active. If these MTR strains are not only fit but also transmissible, the persistent use of these drugs will have the net effect of allowing breeding and spreading drug-resistant strains, resulting in a rise of non-treatable infections.

"In conclusion, our results suggest that the acquisition over time of particular mutations in rpoA and rpoC in rifampicin-resistant M. tuberculosis strains leads to the emergence of MDR strains with high fitness. Furthermore, our data show that these mutations occur at high frequencies in clinical settings, particularly in hotspot regions of MDR TB9. Additional studies are needed to determine whether MDR strains of M. tuberculosis with mutations in rpoA or rpoC have increased transmission rates and how these mutations contribute to the success of these strains. Use of targeted genotyping of these mutations will enable TB control programs to focus on the most transmissible MDR strains. Our findings also suggest that mathematical models that aim at predicting the future of the global MDR TB epidemic should take into account the effects of compensatory mutations as well as the time necessary for such mutations to emerge."

[1] Comas, I., Borrell, S., Roetzer, A., Rose, G., Malla, B., Kato-Maeda, M., Galagan, J., Niemann, S., & Gagneux, S. (2011). Whole-genome sequencing of rifampicin-resistant Mycobacterium tuberculosis strains identifies compensatory mutations in RNA polymerase genes Nature Genetics, 44 (1), 106-110 DOI: 10.1038/ng.1038

Photo: making progress with my macro lens! Canon 40D, focal length 100mm, shutter speed 1/100, F-stop 14, ISO speed 100.

Stories born in the ER: best-selling author CJ Lyons talks about writing and her decision to self-publish

2012-01-04T06:38:00.000-08:00

She's been called a "master within the genre" (Pittsburgh Magazine) and her work has been praised as "breathtakingly fast-paced" and "riveting" (Publishers Weekly) with "characters with beating hearts and three dimensions" (Newsday). New York Times Bestseller CJ Lyons is the author of many cutting edge thrillers, including the award-winning, critically acclaimed Angels of Mercy series (LIFELINES, WARNING SIGNS, URGENT CARE, and CRITICAL CONDITION). Where does she get the inspiration for all these stories? In the ER, of course! Quoting from her bio:

A trained in Pediatric Emergency Medicine, CJ has assisted police and prosecutors with cases involving child abuse, rape, homicide and Munchausen by Proxy. She has worked in numerous trauma centers, on the Navajo reservation, as a crisis counselor, victim advocate, as well as a flight physician for Life Flight and Stat Medevac.

I'm so excited to have CJ as my guest today!

EEG: How much of your fiction was inspired by your work in the ER?

CJ: All of the characters in my work are fictional, but the medical cases and the emotions surrounding trauma, violence, and loss are real. Well, as real as you can get and still be entertaining. It always surprises me when an editor cuts something because no one would believe it but it's something that really happened. I guess truth really is stranger than fiction.

EEG: Can you share more about what happened when, during your residency, a fellow intern was murdered and how this inspired you to turn to crime fiction? (You hint to it in your bio).

CJ: Halfway through my internship year at Childrens Hospital of Pittsburgh one of my fellow interns was killed in a very horrendous way. The police apprehended the killer, thanks to good forensic work and cooperation of several agencies. But we interns were still traumatized and left to mourn and make sense of this terrible thing while simultaneously caring for infants and children entrusted to our care and trying to help families cope.

For me, writing helped me to heal. I wrote my first crime fiction novel, a romantic thriller called BORROWED TIME (which recently hit the USA TODAY Bestseller list). Before I'd always written SF/F, but after Jeff died I needed to explore good/evil, justice/truth more than I needed the escapism my previous novels provided me.

EEG: Wow, that's chilling. I noticed that many of your recent titles are self-published. I'm curious as to what prompted you to turn to self-publication and how it's turning out for you.

CJ: After signing with a NYC publisher I thought I had it made. But after my first book came out I realized my readers wanted more books faster than NYC could publish them. So late 2009 I began to self-publish via Kindle and then Smashwords and Barnes and Noble.

At first it was a way to use those e-books as promotional tools. It was easier to give them away than print books and I could adjust the price. Then a year later, everything changed. E-books grew exponentially, my fans were loving the new books, and I was on track to make more money than I was making from my NYC published books, despite their being bestsellers.

A win/win for all… in fact, I believe the future of publishing will be a partnership between traditional publishers creating books that are events, keepers that readers treasure and display on their bookshelves, agents selling subrights, booksellers handselling both print and e-books, and writers giving their fans what they want and making a living wage. It's a true Renaissance for writers and book-lovers everywhere!

EEG: That is so interesting! The publishing world is indeed changing, and faster than we realize. Thanks so much for sharing your experience with us. And yes, it's absolutely fantastic to be able to click and one second later read. Makes you want more!

To find out more about CJ and her "Thrillers with a Heart," check out her website at www.cjlyons.com.

A lot happens in the blink of an eye!

2012-01-03T06:06:00.000-08:00

Do you have recurrent nightmares? I do, especially when I'm under a lot of stress. I often dream of missing a train. The setting, location, company and place I need to reach change every time, but the common factor is always the frightening sense of having missed the train and not being able to make it. Another recurrent nightmare I have is that the light is so bright I can't keep my eyes open. So I start blinking faster and faster but I can't see a thing and end up missing something very important.

Blinking seems to be such an important task that our body takes care of constantly, as important and essential as breathing. And yet we hardly ever think about it. Under normal conditions, we blink spontaneously 10 to 15 times a minute. We blink both eyes at the same time, which may seem obvious but (maybe you already knew this, I didn't!) it's unique to mammals. Birds, for example, blink one eye at the time and this prevents loss of visual information. In fact, blinking causes a momentary loss of vision that lasts lasts 100 to 150 milliseconds -- a mini black-out that happens constantly as we stare at things and yet we hardly ever notice it, in ourselves, or in others.

Another thing our eyes smoothly cope with is saccades, quick, simultaneous movements of both eyes. When I rapidly move my camera and press the shutter, not matter how fast the shutter speed, I get a blur. However, our eyes move all the time and yet what we perceive is a constant, flowing image.

We compensate these visual disruptions with two similar mechanisms: blinking suppression and saccadic suppression -- basically, visual sensitivity is suppressed immediately prior to and during both blinking and saccades. The two mechanisms are often coordinated in order to minimize downtime in visual processing. Unfortunately,

They are challenging to study because any brain-activity changes resulting from an extra-retinal signal associated with the blink motor command are potentially masked by profound neural-activity changes caused by the retinal-illumination reduction that results from occlusion of the pupil by the eyelid [1].

In order to measure the neural consequences of blinks on visual function one has to bypass the physical consequences of eyelid closure. In other words, you want to stimulate the retinae maintaining the eyes open. How? Via the mouth, as Volkmann et al. [2] showed in 1980: you insert a light probe in the mouth, the light passes through the palate and stimulates the retinae without forcing eyelid closure.

In [1], Bristow et al. use the same technique to stimulate both retinae while measuring brain activity through fMRI. They also used opaque goggles to ensure that retinal illumination remained constant throughout the experiment, whether the eyelids were open or closed. By doing this, they could see what parts of the brain were responding to the retinal stimulation independently from the change in illumination caused by eyelid closure. They find that

Whereas it might have been supposed that blink suppression is a purely low-level visual phenomenon, mediated solely by retinotopic visual areas, our whole-brain analysis surprisingly revealed that activity evoked by retinal stimulation in parietal and frontal cortices was also suppressed by blinking.

Thus, one possible interpretation of our findings is that the observed suppression of these parietal and prefrontal regions during blinking represents a neural mechanism underlying the lack of awareness of the changes in visual input that normally occur during a blink. Specifically, it may account for the lack of awareness of the percept of the eyelid descending across the pupil and the resulting reduction in retinal illumination.

Their experiment also proves the deep connection between saccade suppression and blinking suppression, as they conclude:

In summary, our data demonstrate that responses to retinal illumination are suppressed by blinking in retino-topic visual area V3 and in parietal and prefrontal cortices, whereas in the absence of retinal stimulation, we identified a positive blink-related signal in early visual areas LGN–V3. We propose that these findings represent a neural signature of blinking associated with the blink motor command and may go some way toward explaining both the neural mechanisms underlying the visual-sensitivity loss, known as blink suppression, that occurs during blinks, and why they go unnoticed. Our findings parallel recent observations of saccade-related changes in activity in visual cortex during saccades, suggesting that blink suppression and saccadic suppression may indeed share common neural mechanisms.

Finally, I'd like to mention a more recent paper by Bonfiglio et al. [3], which used EEGs to look at brain waves during blinking. Brain EEGs typically show oscillations that are classified based on their frequency. Spontaneous blinking modulates two oscillations in particular, alpha and delta, which are thought to be involved in the automatic mechanism of maintaining visual awareness. In their study, Bonfiglio et al. studied the alpha oscillations and postulated that

a) an early blink-related synchronization represents the short-term memory maintenance of the last visually perceived trace of the surroundings; b) the alpha blink-related desynchronization is associated with the comparison between the newly perceived image of the environment and its mnestic representation.

[1] Bristow, D., Haynes, J., Sylvester, R., Frith, C., & Rees, G. (2005). Blinking Suppresses the Neural Response to Unchanging Retinal Stimulation Current Biology, 15 (14), 1296-1300 DOI: 10.1016/j.cub.2005.06.025

[2] Volkmann FC, Riggs LA, & Moore RK (1980). Eyeblinks and visual suppression. Science (New York, N.Y.), 207 (4433), 900-2 PMID: 7355270

[3] Bonfiglio L, Sello S, Carboncini MC, Arrighi P, Andre P, & Rossi B (2011). Reciprocal dynamics of EEG alpha and delta oscillations during spontaneous blinking at rest: a survey on a default mode-based visuo-spatial awareness. International journal of psychophysiology : official journal of the International Organization of Psychophysiology, 80 (1), 44-53 PMID: 21238505

Photo: trees in downtown illuminated over the holidays. It was freezing cold, but the sky was so pretty and I just couldn't stop shooting. I could hardly feel my hands when I got home.

What better way to start the new year than... with a carnival?

2012-01-02T07:28:00.000-08:00

...and not just any carnival: the Molecular Biology Carnival!

Happy New Year, everyone! I'm starting off the new year by hosting the January edition of the Molecular Biology Carnival -- what a great honor! And a very special edition indeed, with lots of my favorite things: vaccines, viruses, proteins, bacteria, and more!

Let's start off with James Byrne's holiday-themed post (Merry) Christmas Disease, where the ailment is not some kind of viral disease you might catch on Christmas eve, but a rare form of hemophilia named after a patient diagnosed with it, Mr. Stephen Christmas.

We all know vaccines are delivered through viral vectors, but what about... parasites? Zoonotica explains how a group of researchers genetically modified a trypanosome parasite to vaccinate cattle from redwater fever.

Talking about parasites, did you know that viruses have their own share, too? These "viral" parasites are called virophages, and they can only reproduce in cells that have already been infected by a helper virus. In his post Virophages and the evolution of transposable elements, Habib Maroon discusses a new virophage recently discovered, called Mavirus, which amazingly sheds light on the origin of an intriguing DNA element, the transposons (yes, the "jumping genes" I've covered in an earlier post).

Let's stick with viruses and ask the following question: how come some viruses are degraded by our immune system's sentinels, the T-cells and B-cells, and others, like measles and HIV instead have developed a mechanism to infect those very same cells that are supposed to destroy them? Connor Bamford, in his post Viruses at the crossroads of infection looks at a paper that suggests the answer may be hidden in the virus's sugar coating.

And in another great post from his Rule of 6ix blog, Connor talks about the influenza virus and dendritic cells: immune response or Trojan horse?

From viruses to bacteria and, in particular, bacterial genes: Gemma Atkinson, in her post Bacterial genes in eukaryotes - function and phylogeny presents two papers that look at bacterial genes in eukaryotes.

Still from the amazing world of bacteria, S. E. Gould reports of a new group of magnetic bacteria, better known as magnetotactic bacteria. As S.E. Gould explains, these organisms "contain small nanoparticles of magnetic material which allow them to swim along magnetic field lines." How cool is that?

And yet another bacteria marvel: off the coast of Costa Rica, white and hairy crabs known as Yeti crabs farm bacteria on their claws, as Lucas Brouwers explains in his post Yeti Crabs grow bacteria on their hairy claws.

Finally, DNA Testing presents DNA Paternity Testing on the Rise posted at DNA Testing Blog - DNA Paternity, Sibling, & Biological Family Testing.

That's all for this edition. Don't forget to submit your entry for the next edition of the molbio carnival using the carnival submission form. Past posts and future hosts can be found on the blog carnival index page.

Photo: "Beam me up, Spock!" A.K.A.: a "zoom blur" (zoom while the shutter's open) of a decorated tree in downtown.

Happy New Year!

2012-01-01T01:33:00.000-08:00

Happy New Year, everyone!!
No fireworks here, so had to do with what I had at home: a Christmas tree, a Canon on the tripod, and a zoom! :)

May the new year bring you all joy, peace and serenity. Thanks for being an active part of CHIMERAS.

Beta blockers and genetic variation

2011-12-29T07:02:00.000-08:00

It's happening again.
I'm sitting in a meeting, and suddenly I feel my hands prickling. My heart thumps faster. I can't concentrate on what people around me are saying. My head is buzzing, and cold sweat trickles down my neck. I feel the tingling of panic biting at the tip of my fingers. My muscles tense, adrenaline spikes. Every cell of my body screams, "Danger!"

Now, part of me wants to take out my notebook and jot everything down for my next high-adrenaline, action-packed story.

The other (more sensible) part of me, wants to run out of the room, pick up the phone, dial my doctor's office number, and yell, "I NEED THE BETA BLOCKERS AGAIN!!!!!"

In case you didn't know, beta blockers are a wonderful drug. I'm told you can't take them during Olympic competitions, but that's okay, I've given up my Olympic dreams a long time ago. They are considered performance enhancers because they fend off the action of adrenaline and hence prevent stage freight and all sorts of anxieties. In other words, they make you happy. Olympics aside, they are prescribed in clinical cases with a high risk of infarction myocardial ischemia, or, as in my case, when the thyroid acts up and starts producing too much thyroid hormones. (I've actually been feeling really well for the past year, knock on wood!)

They block the beta-adrenergic receptors (hence the name), which are the receptors that are stimulated by adrenaline, the hormone produced by the adrenal glands. When adrenaline is released, it binds to the beta-adrenergic receptors and this causes a bunch of things to happen: the heart starts pumping faster in order to better oxygenate the muscles; blood flow is diverted from non-essential organs to the muscles; pupils and airways dilate; vessels narrow. Basically, the body is getting ready to "either fight or flight."

So here comes the beautiful, casually charming and nonchalantly laid-back, beta-blocker -- our hero. He sits right on the receptor and when the adrenaline comes, he smiles, puffs out some smoke, and, talking around a charred cigarette butt, says, "So long, babe. Spot's taken."

Yeah. Been reading too much Chandler.

I've been quite happy with beta-blockers, though my problem was not of a cardiac nature. So, I was quite surprised to find out that

"Recent evidence suggests that there is substantial inter-individual difference in how patients respond to beta-blockers: Some patients experience strong side effects such as excessive hypotension and bradycardia, whereas others experience no measurable response. Several lines of evidence suggest that the individual genetic background is responsible for these observed response differences [1]."

In order to understand this, one needs to understand how drugs are metabolized within the body. A cytochrome enzyme is an enzyme involved in the canalization of organic substances, and, as a consequence, in drug metabolism. The enzyme responsible for the metabolism of most beta-blockers is, CYP2D6. Now, here's the interesting part: the corresponding gene shows a large variability due to genetic polymorphisms (any variant that's at least 5% prevalent in the population). In other words, different individuals may present different alleles, and the frequency of these variants varies across ethnic groups. In [1], Nagele and Liggett discuss the most important SNPs and gene variants within adrenergic receptors and CYP2D6 and their possible effects in the metabolism of beta-blockers. They go in far more details than I want to here, so I'll limit myself to highlight the importance of their review: it turns out that patients with cardiovascular risk factors can suffer from potentially fatal complications after noncardiac surgery, and for that reason beta-blockers have been used as a preventive treatment of perioperative infarction. In this context, it is relevant to be able to predict the drug response based on the patient's genetic variation. Beta-blockers can indeed lower the risk of perioperative MI and cardiac death, but also carry a substantial risk for adverse cardiovascular side effects, such as hypotension and bradycardia. Given that genetic variation in CYP2D6-dependent metabolism and adrenergic signaling may affect the outcome, the authors conclude:

"Given the apparent inter-individual variation in efficacy and adverse effects of beta-blockers for prevention of perioperative MI, the biologic plausibility, and the low costs of genotyping by modern methods, it seems to us that a rigorous pharmacogenomic investigation is indicated. Ultimately, this could lead to a “genetic scorecard” that would recommend when a beta-blocker should be used and the dose, for prevention of perioperative MI."

As for me, I'm actually fine. I don't know what CYP2D6 alleles I carry, but the days full of adrenaline and jumping nerves are over. So, hooray for the beta-blockers!

[1] Nagele P, & Liggett SB (2011). Genetic Variation, β-blockers, and Perioperative Myocardial Infarction. Anesthesiology, 115 (6), 1316-27 PMID: 21918425

Photo: crystal sculpture, Santa Fe, NM. Canon 40D, focal length 85mm, shutter speed 1/30.

Guess what Santa got me for Xmas?

2011-12-27T08:51:00.000-08:00

No, not the bug... the lens! :)

It's a Canon 100mm macro lens and all I can say after two days of playing with it is... Macro photography is darn hard!! (More failed attempts on my G+ page, if you're curious.)

Sense and antisense in the human genome

2011-12-26T07:19:00.000-08:00

I hope you all had a wonderful holiday. Short post today, as I'm sure we're all still digesting all the yummy holiday food and sweets, and maybe some of you are still celebrating. One of my recurrent topics on the blog has been antisense genes. Until recently, I had no idea such things existed, let alone in humans. It turns out, they are quite abundant in humans.

Antisense genes are overlapping genes that are transcribed on opposite DNA strands. I've discussed how antisense genes regulate conjugation in bacteria, and how antisense RNA transcripts can be used in gene therapy. Today I'd like to discuss a paper that examined five different human cell types and found evidence for antisense transcripts in thousands of genes.

As you know, a gene is a piece of DNA, and a gene transcript is the RNA trasncribed from that gene. DNA is made of two strands coiled together, which are conventionally referred to as the plus strand and the minus strand. The general thought has been that sense transcripts produce functional proteins, whereas antisense transcripts have regulatory functions. For example, they can "silence" a gene since the antisense RNA will attach to the sense RNA and a double-stranded RNA can no longer produce a protein.

In [1], He et al. developed a technique that allows to change the RNA transcript in a way that, once turned back into DNA, it will only match either the plus or the minus DNA strand. This way one can establish from which strand it had been transcribed. The researchers analyzed five cell types: PBMC, peripheral blood mononuclear cells isolated from a healthy volunteer; Jurkat, a T cell leukemia line; HCT116, a colorectal cancer cell line; MiaPaCa2, a pancreatic cancer line; MRC5, a fibroblast cell line derived from normal lung. They called "S genes" the ones that contained only sense tags or had a sense/antisense tag ratio of 5 or more; "AS genes" contained only antisense tags or had a sense/antisense tag ratio of 0.2 or less; and finally, "SAS genes" contained both sense and antisense tags and had a sense/antisense ratio between 0.2 and 5.

I found this figure in particular to be quite interesting:

From the figure, it's clear that sense genes tend to accumulate in the exons (the coding bits of a gene), whereas the antisense genes accumulate more in the promoters, regions upstream of a gene that regulate and promote transcription, and, though to a less extent, in the terminator regions. The authors of the paper used these data to argue that, while

"promiscuous expression would lead to a uniform distribution of antisense tags across the genome, the observed distribution was nonrandom, localized to genes and within particular regions of genes, much like sense transcripts."

In other words, antisense genes are non-randomly distributed and may in fact contribute to antisense-mediated regulatory mechanism that, according to the data presented in [1] affects from 2900 to 6400 human genes. More on this in the next post! Happy Holidays, everyone!

[1] He, Y., Vogelstein, B., Velculescu, V., Papadopoulos, N., & Kinzler, K. (2008). The Antisense Transcriptomes of Human Cells Science, 322 (5909), 1855-1857 DOI: 10.1126/science.1163853

CHIMERAS is on wallpaper!

2011-12-23T04:53:00.000-08:00

I've been on Google+ for a couple of months, but I really got active only a couple of weeks ago. I discovered the Daily Photography Themes through a reader here and absolutely loved it. There are some truly, truly amazing photographers who share photos and tips, and in general, it's a great and very supportive community were you can't help but strive to take better pictures encouraged by the work of these superb photographers.

Well, one of those superb photographers, Jamie Furlong, organizes a weekly wallpaper contest, and I still can't believe that this week he picked my photo as the winner! You can download the image as a full resolution wallpaper (in various formats) here. All images there are fantastic, so don't leave the site without checking out Jamie's amazing portraits and street shots from India.

Happy Holidays everyone!

Guest post: How to camouflage a virus and why it's important

2011-12-22T05:22:00.000-08:00

Last week I covered a couple of recent gene therapy studies and discussed the different types of vectors used in order to make these therapies more efficient. One of the obstacles that hinders the efficiency of gene therapy is the immune system: if the patient has previously developed immunity against the viral vector, the virus will be quickly cleared out of the system without being able to deliver the genes. Therefore, the question is: how can we prevent the immune system from attacking the viral vector?

One of my regular readers here on the blog, antisocialbutterflie is an expert on "capsid recognition," and kindly offered to discuss the topic. The capsid is the outer shell of the virus and the idea is to disguise it so the antibodies won't recognize it. Without further ado, I'm going to let my guest take over the post.

The monumental advances in genetics over the last six decades have improved our understanding of diseases and where they originate. Now armed with this knowledge there are many disorders that we could fix if we had a way to deliver the right DNA. In many ways gene therapy is like the Cold War. We have nuclear warheads but it isn’t going to do any good if we don’t have an effective delivery system. A delivery system must first be able to hit the target but it must also allow the device to do its job and do it covertly enough that it doesn’t call up the defenses of its enemy too quickly. In the case of gene therapy you can’t just inject someone with naked DNA and expect something to happen. Thankfully nature helped us out by providing a fabulous rocket powered, laser guided missile system in the form of viruses.

You typically think of viruses in terms of disease but there are plenty of viruses that coexist without any the deleterious effects. The virus of choice for many gene therapy trials is the adeno-associated virus or AAV. AAV is a single stranded DNA virus indigenous to primates from the family parvoviridae, which may sound vaguely familiar if you’ve ever had a pet. This is the same family of viruses that give us canine parvo and B19 in humans, but in the case of AAV it doesn’t really do much of anything. In fact AAV can’t even replicate unless its host is also infected with a helper virus like adenovirus or herpes. They are also mildly immunogenic so they can travel (mostly) under the immune system’s radar without eliciting a strong response.

The virus only has two genes that can make seven proteins when you factor in alternate start sites and splice variants. Most gene therapy vectors utilize the cap gene and their resultant 3 VP proteins to create a viral shell for the therapeutic gene they want to deliver. Sixty of these proteins interlock together to make an icosahedron. Basically the pieces, when assembled, look like 20-sided dice with a therapeutic gene stuffed inside. As you might imagine the core fold of the protein has to be fairly specific to fit together but there are loopy bits on the exterior of the capsid called “variable regions” that give each variant its unique properties. These variable regions act like velcro to grab onto cell receptors. In multicellular organisms different tissues express different receptors so you can use these regions to target a specific cell type. Unfortunately it is also these variable regions that immune cells target for neutralizing antibody production. Since these viruses target humans, antibodies already exist to the naturally occurring variants, which is why many of the gene therapy vectors have to be tweaked to be effective.

There are several ways of engineering a good gene therapy vector that can escape the immune system while still targeting the tissues that you want. One strategy is to mix and match. This can be accomplished by mixing up whole capsid proteins from several serotypes or cutting out bits and pieces of different protein sequences and pasting them together to make a single new one. There is also directed evolution where you introduce errors in the gene to create a new protein sequence and then select for the mutations that confer the appropriate tissue specificity while still escaping the neutralizing antibodies. Another strategy involves adding a peptide to the capsid that you know binds a specific receptor as a way to target it. You can even create protective coats for your virus made from things like PEGs or lipids to allow it to evade the immune system in the same way enveloped viruses do. All of these alterations run the risk of blocking capsid assembly, changing tissue specificity, and/or reducing infectivity so it’s a bit of a crap shoot as to whether your efforts are all for naught. For every successfully engineered vector there are hundreds that didn’t work.

As mentioned in a previous post, there is also the issue of gene size. There is a finite amount of space inside that d20 and some of it has to be taken up by the inverted terminal repeat sequence that packages the DNA. If you have a bigger gene you need a bigger virus like adenovirus, HSV or HIV. These bigger viruses are made up of several capsid proteins that have to be accounted for and provoke a bigger immune response making the can of worms even larger.

I hope this enlightens you a bit to the field of gene therapy vector design and its challenges. Thanks to Elena for having me.

That was not only enlightening, but also exceptionally clear -- thank you! It was fascinating to learn that one of the ways this is accomplished is by introducing artificial mutations in order to trick the immune system... Another lesson learned from viruses themselves, as that is exactly how HIV escapes our immune defenses.

Antisocialbutterflie is an X-ray crystallographer with a PhD in biomedical science. She is currently a postdoc and dreaming of a day when she can step away from the bench, preferably before she sets fire to her FPLC. In addition to the random blog comment she occasionally writes fiction when time permits.

Pulicherla, N., & Asokan, A. (2011). Peptide affinity reagents for AAV capsid recognition and purification Gene Therapy, 18 (10), 1020-1024 DOI: 10.1038/gt.2011.46

Fingerprint evidence: not exactly what CSI showed you

2011-12-20T05:21:00.000-08:00

Every scientific type of analysis has an error rate. I've mentioned it before: science is not about certainty, it's about accurately measuring the uncertainties. Unfortunately, when it comes to forensic sciences, this causes a logical problem: scientists like to talk about being 90% sure about something, but in trials there's only two outcomes: innocent or guilty. You can't do 90% guilty and 10% innocent.

It occurred to me that this was an issue when I heard somebody talk about how fingerprint analysis has no error rate. Being a statistician, all sorts of red flags rose in my head. Of course there's an error rate! Any procedure has an error rate because the error rate is a definition: you count the number of successful identifications and divide by the total number of comparisons made. Maybe the fingerprint matching has never failed? Unfortunately, that's not true.

As some of you know, I was in Los Angeles last month and I was lucky enough to speak to a fingerprint analyst with the LAPD. She explained the procedure to me, which is pretty cool, actually. Blood fingerprints are photographed. Everything else is dusted: black powder is used for clear surfaces, and white powder for dark surfaces. The powder sticks to the oily residue from hands and the rest is brushed away. The analyst then applies tape to the surface, which lifts the dust that has attached to the oily residues. This accurately reproduces the print onto the tape and the tape is then transferred to a card.

The typical procedure is to scan the card into the computer and send it to a number of databases, the largest of which is IAFIS, maintained by the FBI. An automated algorithm comes back with 2-3 possible matches with the prints lifted from the scene, and at that point a person compares the matches from the database with the in order to make a final identification. If the database comes back with no match, but the police has obtained the prints from a possible suspect, then again the comparison is done by hand.

Just like any other procedure that deems itself as "scientific," fingerprint analysis too needs an error rate, and I'm not alone in making this claim: in 2010 UCLA law professor Jennifer Mnookin obtained a federal grant in order to study error rates in fingerprint evidence. The difficulties are intrinsic: you have to fold in the variability from analyst to analyst and from case to case, as some fingerprints are lifted in ideal situations whereas others are only partial, blurred, etc.

To explain the importance of this type of research, in a 2010 paper [1] Mnookin asks the following question to two hypothetical law students:

"Is fingerprint identification one of the most secure forms of evidence we have, or is its scientific validity remarkably untested?"

Sadly, one of her hypothetical students

"would discover that the scientific validity of fingerprint evidence is surprisingly untested. He would ascertain, for example, that there were no generally shared and validated objective standards for declaring a ‘match’ either required by judges within the courtroom as a precondition to admissibility, or self-imposed by the fingerprint community—that in the end, deciding whether or not a match existed was left to the discretion of each examiner based on his judgement and experience. He would find, in sharp contrast to, say, DNA profiling, that there was no fully specified statistical model of fingerprinting, that would permit the likelihood that two prints came from the same person to be expressed in probabilistic terms."

Mnookin concludes:

"Assuming that errors were not randomly distributed across the array of test prints, proficiency tests designed genuinely to test both the method and its limits might provide useful information about the circumstances that tended to lead to errors, and perhaps could lead to practices that could reduce the likelihood of making such mistakes. Such proficiency tests are technically feasible, and whatever they found would teach us a good deal more about the frequency of errors than we know at present."

To get a more rounded perspective on the matter, I contacted my friend Mark Pryor, an assistant district attorney with the County of Travis, in Texas. Mark was very happy to hear from me, and he was even happier to tell me that he had just found a home for his novel The Bookseller, signing a three-book-deal with Seventh Street Books, a new mystery and thriller imprint from Prometheus Books. Way to go, Mark! He answered my questions while floating twelve inches above ground...

EEG: I understand that every time you have an expert witness take the stand they have to state what their expertise is, and their background and how many cases they've investigated, etc. Are they ever asked, over the course of the testimony, what the error rate for their kind of analysis is? Is it at all required for some kind of analyses?

MP: Yes, they always explain their qualifications, experience and training. This is for two reasons: one, to qualify them as an expert, so that they pass what's known as the Daubert test for scientific expert testimony. That's a call for the judge. But it's also so the jury can know them a little, understand who this person is giving the scientific opinion/testimony. I have never heard one asked what about error rates, actually.

EEG: Has a defense lawyer ever questioned fingerprint analyses during one of your cases, and if so, how did you reply to that? If not, how would you reply to that?

MP: I have not taken a fingerprint case to trial yet, so no. I'm sure if I did, defense counsel would thoroughly question the expert, maybe about error rates, certainly about the procedures they use and the practices in place to make sure there were no mistakes. I think what I would emphasize in my re-direct of such an expert is precisely those same things: making it clear neither I nor the fingerprint expert has any interest in making a mistake and blaming the wrong person for a crime. In other words, I want my print expert to come across precisely as he is: a disinterested expert on the science of fingerprint analysis.

EEG: More in general, do you ever "question" the scientific evidence that detectives bring to your desk before deciding whether or not to issue an arrest warrant?

MP: I personally don't have anything to do with arrest warrants, a detective will get that from the judge directly. Sometimes I'll review one if it's a big case, but I generally won't see any scientific evidence - usually because the arrest is based on non-scientific evidence because a lot of the science stuff takes a while to process (I'm thinking of DNA here). Now, for trial I always look very hard at ALL my evidence, scientific included. Again, for two reasons: I don't want to try an innocent person, and also because I don't want to find out any mistakes/weaknesses once I'm in trial, I want to know those in advance!

I confess I'm still a bit troubled by the process. TV shows like CSI make it look like scientific evidence is either black or white, while unfortunately there's a full range of grays in between. And like Mark said, the bottom line is not to try an innocent person. I'm glad the law is represented by scrupulous people like Mark, but I'm also grateful that Professor Mnookin got her grant. I couldn't find any update on her website, but I'll keep an eye on it because I'm eager to find out about their results.

As for Mark, his book The Bookseller will hit the shelves towards the end of 2012, but in the meantime you can follow his blog, DA Confidential, where he discusses being an assistant district attorney, a father, a husband, and a writer.

[1] Mnookin, J. (2007). The validity of latent fingerprint identification: confessions of a fingerprinting moderate Law, Probability and Risk, 7 (2), 127-141 DOI: 10.1093/lpr/mgm022

Enough with OXTR associations. Here's what I really want to know.

2011-12-18T07:07:00.000-08:00

EDIT: After reading the post, please check out the comments. Luke, from Genomes Unzipped, helped me understand the matter better, so don't miss his comment!

Another OXTR paper came out in PNAS, the third since September. OXTR is the gene coding the oxytocin receptor. Given the benefits of oxytocin (dubbed the "love hormone"), people have focused on studying this gene and, in particular, possible associations between a common OXTR polymorphism, rs53576, and various behaviors:

"One SNP in the third intron of OXTR has emerged as a particularly promising candidate in recent studies on human social behavior: rs53576 (G/A). In recent studies, the A allele of rs53576 has been associated with reduced maternal sensitivity to child behavior, lower empathy, reduced reward dependence, lower optimism and self-esteem, and, in men, negative affect. Moreover, the A allele has also been associated with a larger startle response and reduced amygdala activation during emotional face processing. Associations have also been reported between other variants of OXTR and amygdala volume, risk for autism, the quality of infants‚ attachment bonds with their caregivers, attachment anxiety in adult females, and autistic-like social difficulties in adult males [1]."

This study in particular [1] recruited 194 individuals and found an association between the SNP in question and the way the participants reacted to positive feedback during stressful situations. They did this by measuring cortisol responses to stress based on the fact that psychosocial stress increase the levels of salivary cortisol. In AA carriers they found that these levels remained unchanged whether they received the support or not. The researchers conclude:

"Physiologically, it can be speculated that oxytocin released in the context of social support influences stress processing systems via oxytocin receptors in hypothalamic‚ limbic circuits. One likely important site of action is the amygdala, critically involved in basic emotional processing and the regulation of complex social behavior."

I confess I've been eagerly following these OXTR studies and indeed they make a great story. There's a part, though, that puzzles me, and the reason why I'm discussing this paper today is to ask a general question. If you're an expert on these things I welcome your input.

I understand these are important studies because, despite some recent criticism, they are still getting published, and PNAS, as we all know, is one of the top science journals out there. However, the thing I don't understand is that rs53576 is a silent SNP. That's actually not surprising, because, as it turns out, most common polymorphisms are silent. What is surprising, though, is that most silent SNPs are non functional, and none of these studies I've read seems to raise the question. Let me explain.

Rs53576 sits in an intron, a part of the gene that is not transcribed into RNA and hence, in this case, does not affect the way the oxytocin receptor is made. In the analogous studies we do in my group, which are NOT on humans, we look for non-silent mutations because those are the ones that affect the crystal structure of the protein. We then look at what differences in structure these mutations yield to explain how more or less molecules bind to the protein, and this how we explain the observed effects. If rs53576 were a non-silent mutation, I'd know where to look to explain these associations: I'd look at how the SNP affects the crystal structure of the receptor, the hypothesis being that the oxytocin receptor in AA carriers binds less oxytocin than GG carriers (or something along those lines, I obviously don't know the details of this particular receptor). But rs53576 is silent. Hence, if the associations are real, there is something else going on. So, why hasn't anybody raised the question of what else is going on here?

The first thing that comes to mind is that this particular SNP could be in linkage disequilibrium with some other SNP or groups of SNPs which, instead, are non-silent. We tend to inherit polymorphisms in groups, and so if rs53576 comes in the same "package" (they're called haplotype blocks) as some other functional SNP, then rs53576 is NOT the causal SNP for all these effects and we should really be looking elsewhere. The way to find out, of course, is to repeat all these studies with whole genome data. But, it could also be an epigenetic change or a post-transcriptional modification occurring between the primary transcript RNA (which contains both introns and exons) and the mature messenger RNA (which then yields to the protein). The positions of introns can indeed affect the translational properties of the RNA, and that's what yields to the so-called "functional intronic SNPs." The fact that intronic polymorphisms can be functional is extremely interesting, and in fact, last year, this study showed that one particular SNP found in one intron of GH1, the growth hormone, could indeed be functional.

Whatever it is, at this point, isn't it more interesting to investigate what's going on with this SNP at the molecular level rather than looking at all these association studies which may or may not be true?

[1] Chen, F., Kumsta, R., von Dawans, B., Monakhov, M., Ebstein, R., & Heinrichs, M. (2011). Common oxytocin receptor gene (OXTR) polymorphism and social support interact to reduce stress in humans Proceedings of the National Academy of Sciences, 108 (50), 19937-19942 DOI: 10.1073/pnas.1113079108

Photo: Fall colors along the Rio Grande. Shutter speed 1/40, F-stop 5.6, ISO speed 100, and focal length 85mm.

Epigenetic reprogramming: how cells start afresh

2011-12-17T06:49:00.000-08:00

Last week I talked about the chromatin, the complex of DNA and proteins that resides inside the nucleus. There were two key points to that post: (1) the topology inside of the chromatin, or, in other words, how the chromosomes are arranged inside the nucleus, is correlated to which genes are active and which aren't; (2) these changes in the chromatin that allow for gene expression and gene silencing can be inherited, though how it's still a mystery.

I admit I left that second point a bit vague last week. So, with the help of a fantastic review I found on PubMed [1], today I'd like to develop the topic further.

The rearrangements of the chromosomes within the chromatin determine what are known as epigenetic marks:

"Epigenetic marks are covalent modifications of the DNA (DNA methylation) or post-translational modifications of the histone proteins (histone modifications) that make up the chromatin into which our DNA is packaged. [1]"

Different cells in the body present different epigenetic marks depending on which genes are expressed and which are silent. Within a specific cell line, epigenetic marks are conserved as cells divide, thus maintaining the differentiated state of the cell. For example, skin cells will divide in skin cells and not change into brain cells, right?

This is true for all cells in the body except one very special set: the germline cells. If you think about it, it makes perfect sense: germ cells give rise to an embryo, and hence have to remain undifferentiated. Therefore, all epigenetic marks must be reset in order to enable a completely new undifferentiated state, a process called epigenetic reprogramming.

"It is almost twenty years since the discovery of the biological importance of germline DNA methylation in the context of imprinted genes, and ten years since the identification of the key enzymes responsible for de novo DNA methylation in mammals. Even so, what specifies why specific DNA sequences become epigenetically distinguished in germ cells is still only partially understood."

During developmental epigenetic reprogramming, primordial germ cells emerge with their own epigenetic marks and, as these cells migrate and proliferate, the marks are gradually lost (DNA methylation is globally erased):

It's interesting to see how the new marks are established in an asymmetric fashion for males and females. In the male embryo, de novo methylation takes place and the new marks are established and completed by birth. In the female embryo, the process is arrested in the oocytes and resumed at puberty. In the event of a fertilized oocyte, the marks are erased again, as illustrated by the blue and red line descending again in the above figure.

Smallwood and Kelsey explain the various phases of the above processes in great detail. Interestingly,

"DNA methylation is distributed throughout the genome, at repetitive elements and single-copy sequences. With the recent development of genome-wide methylation profiling techniques employing next-generation sequencing, the full pattern of DNA methylation in gametes, and how it is laid down during germ-cell development, is beginning to emerge. [...]Despite the advances in the identification of key factors in DNA methylation in the germline, many questions remain over mechanism – in particular, how a select number of imprinted gDMRs and CGIs are specified for DNA methylation. The development of deep-sequencing technologies has opened new horizons, and it is now possi- ble to profile DNA methylation on a genome-wide scale in very small amounts of genomic DNA, providing an unparalleled opportunity to shed new light on mechanisms of de novo DNA methylation in germ cells [13,81]. Because the interaction of DNMT3 proteins with nucleosomes is regulated by several histone modifications (at least in vitro) it is now imperative that such capabilities are matched by the development of chromatin immunoprecipitation sequencing (ChIP-Seq) protocols to profile histone modifications in vivo in limited amounts of starting material; this would undoubtedly represent an important advance in the field of epigenetic reprogramming."

I asked my dad, a developmental biologist from the University of Pisa, what his thoughts were on the matter, and this is what he had to say:

"The conclusion to be drawn from these latest findings is thus as follows. So far we have been looking at single epigenetic changes and asked the question what does each one of them mean in relation to the phenotypic effects envisioned on an organismic scale. Needless to say that we have not gone very far by pursuing this simple-minded approach. The newly emerging evidence is pointing to another direction. Taken together, the epigenetic markers of chromatin imprinting, histone acetylation and base methylation should perhaps be considered as systemic modifications rather than simple one-to-one cause-effects relationships. By this I mean to say that the nuclear context in which such modifications occur is as important as any other macromolecular co-factor sustaining their interaction with the phenotypic counterparts. Perhaps by knowing how epigenetic markers are changed on a genomic scale it would be possible in the future to understand how they relate to one another and how altogether have provided living creatures with an adequate responding repertoire to adapt to ever changing environments during evolution."

[1] Smallwood SA, & Kelsey G (2011). De novo DNA methylation: a germ cell perspective. Trends in genetics : TIG PMID: 22019337

Icicles!

2011-12-16T14:07:00.000-08:00

Do you know the origin of Christmas Trees? I don't, and I suppose I could look it up, but as I went out to shoot a few photos this morning (the light was gorgeous), I saw many many Christmas trees out there... all decorated in icicles. And so I thought, "Hmm. Maybe that's how the tradition was born..."

So mice can be vaccinated against HIV. What about humans, though?

2011-12-15T05:43:00.000-08:00

I hope I can get away with yet another paper on gene therapy this week. You may actually have already heard about this one: it came out at the end of November and it had quite some resonance because the researchers claimed to have established lasting immunogenicity to HIV in mice‚ using, again gene therapy.

I have already discussed the potential use of gene therapy to cure HIV. In fact, the only human to ever be "cured" of HIV was a leukemia patient who, after receiving a genetically modified vector, developed HIV-resistant T-cells. In that case gene therapy was the only way to save the patient's life as he was dying of leukemia. It was quite an interesting study and I loved learning about it. However, in general, gene therapy is NOT a feasible way to end the AIDS pandemic. It's too expensive, too risky, and 2/3 of the infected people live in South Africa where even drugs are too expensive, you can imagine gene therapy.

No, the most efficient means to wipe out the virus, from both an economical and a clinical perspective, is a vaccine.

Okay, I'm biased. I work on HIV vaccine design. And when this paper appeared in Nature many colleagues rolled their eyes. "Too risky." "Too impractical." "It'll never work in humans." Which meant I had to read the paper. So I did.

From the abstract:

"As an alternative to immunization, vector-mediated gene transfer could be used to engineer secretion of the existing broadly neutralizing antibodies into the circulation. Here we describe a practical implementation of this approach, which we call vectored immunoprophylaxis (VIP), which in mice induces lifelong expression of these monoclonal antibodies at high concentrations from a single intramuscular injection. This is achieved using a specialized adeno-associated virus vector optimized for the production of full-length antibody from muscle tissue. We show that humanized mice receiving VIP appear to be fully protected from HIV infection, even when challenged intravenously with very high doses of replication-competent virus. Our results suggest that successful translation of this approach to humans may produce effective prophylaxis against HIV."

So, it is some kind of vaccine. And at the same time it's not. In a standard vaccine you inject a deactivated form of the virus in order to elicit antibody production in the host. With this new method, instead, you inject a virus which carries the genes for the antibodies. Instead of letting the immune system find a way to produce the antibodies, the researchers provided the "instructions" on how to make them: they injected into the muscle a viral vector containing the genes for the antibodies.

The vector used in the study is a self-complementary adeno-associated virus, which I discussed here. The researchers produced AAV vectors that either expressed luciferase (for the controls) or the neutralizing antibody b12 and administered them to mice through a single intramuscular injection. The mice were then populated with human peripheral mononuclear cells and then challenged with HIV. After the challenge, most mice expressing luciferase showed dramatic loss of CD4 cells (the cells infected by HIV) whereas mice expressing b12 antibody showed no CD4 cell depletion. Basically, the therapy was working.

They also tested a cocktail of historically known broadly neutralizing antibodies: b12, 2G12, 4E10, and 2F5. Again, after being adoptively populated with huPBMCs, the mice were

"challenged by intravenous injection with HIV and sampled weekly to quantify CD4 cell depletion over time. Animals expressing b12 were completely protected from infection, whereas those expressing 2G12, 4E10 and 2F5 were partly protected."

Finally, they repeated the experiment with one of the newest and most potent broadly neutralizing antibodies, VRC01, and found similar results, with higher protection established at higher doses of the vector.

The fact that the mice were challenged intravenously is quite impressive because mucosa routes present a bottleneck for the virus, whereas intravenous challenges are much more efficient in initiating the infection.

A number of things remain to be seen, the safety and efficacy of the therapy in particular. In this hemophilia B study the administration of intravenous AAV showed lasting results, even though the new genes were expressed at a low level. However, other scAAV studies have failed and, as an additional word of caution, we should not forget all the therapies successfully tested in mice that later failed in humans: assuming this technique passes the required safety checks, it still remains to be seen whether results in humans would be comparable to the mouse model.

Still. Despite my original bias, I confess I find these results pretty cool. Don't tell my boss, though!

Balazs, A., Chen, J., Hong, C., Rao, D., Yang, L., & Baltimore, D. (2011). Antibody-based protection against HIV infection by vectored immunoprophylaxis Nature DOI: 10.1038/nature10660

Photo: Sunset on Croc Rock and the Rio Grande. Shutter speed 1/25, focal length 38mm, f-stop 5.0, ISO speed 100.

Not all vectors are created equal

2011-12-13T11:10:00.000-08:00

As I was reading the paper I discussed yesterday, I realized there was a part I didn't fully understand and I needed to research more. I received some great comments on that post that pointed me in the right direction.

A gene delivery vector is an engineered virus modified so that it contains the genes needed for therapy. Once inside the cell, the genetic material needs to reach the nucleus where it has to recruit a complementary DNA strand in order for the gene to be expressed.

Conceptually, it seems easy enough. In practice, every step of the way has its hurdles and of all the vectors you inject into the host, only a fraction turns into expressed genes. With adeno-associated virus (AAV) the major bottleneck is the de novo synthesis of the DNA: not all the single-stranded DNA delivered to the nucleus is successfully converted into double-stranded DNA, thus hindering the efficiency of the vector.

Luckily, there's a few alternatives. Suppose you have two viruses, and each carries complementary DNA. Assuming they both reach the nucleus, the two DNA strands will find each other (no need to recruit a complementary strand from the existing chromatin), and voila' -- you have a double-stranded DNA. Now, this in general wouldn't be possible with just any virus, because they tend to have a preference for which strand they carry. But with AAV we're in luck because it packages either strand with equal efficiency.

This approach is also prone to issues. For example, it's hard to predict whether or not the two complementary strands, once inside the nucleus, will find one another. The likelihood increases with the dose, but that also increases the chances of recombination.

What about packaging both strands inside the same vector? Turns out it's possible, even though you lose in capacity (you can't package as much DNA inside the virus, approximately half of what you could achieve with the previous AAV). As McCarty explains in [1]:

"This can be achieved by taking advantage of the tendency to produce dimeric inverted repeat genomes during the AAV replication cycle. If these dimers are small enough, they can be packaged in the same manner as conventional AAV genomes, and the two halves of the ssDNA molecule can fold and base pair to form a dsDNA molecule of half the length. Although this further restricts the transgene carrying capacity of an already small viral vector, it offers a substantial premium in the efficiency, and speed of onset, of transgene expression because dsDNA conversion is independent of host-cell DNA synthesis and vector concentration."

The above figure shows the steps through which this is achieved. Technical details aside, this new mechanism exploits the virus's ability to naturally form short complementary strands. The "shortness" diminishes the capacity, but if you can get away with delivering short genes, then you can efficiently bypass the de novo synthesis bottleneck and greatly increase the efficiency of the vector. These are called self-complementary vectors, scAAV in the case of adeno-associated virus.

There are still hurdles to circumvent. You still face the potential barrier posed by humoral immunity, the fact that the immune system might recognize the virus and destroy it before it can reach its destination. In [1] McCarty reviews several applications of scAAV, including cell lines where studies have been successful, and others that haven't. But the paper I discussed yesterday was certainly a great step forward and a success story in the use of scAAV vectors.

[1] McCarty, D. (2008). Self-complementary AAV Vectors; Advances and Applications Molecular Therapy, 16 (10), 1648-1656 DOI: 10.1038/mt.2008.171

Another gene therapy success story

2011-12-12T16:16:00.000-08:00

Last October I reported an incredible story in which researchers used an HIV chimeric virus to cure leukemia. Here's another success story.

Hemophilia B is a blood clotting disorder caused by spontaneous mutations in the Factor IX gene, leading to a deficiency of Factor IX, an enzyme essential in blood coagulation. The gene is expressed mostly in the liver, where the enzyme is produced and then sent into circulation in the blood. Less than 1% of normal levels of Factor IX lead to severe hemophilia and require a lifetime treatment of intravenous injections of FIX protein concentrate 2-3 times a week.

"Somatic gene therapy for hemophilia B offers the potential for a cure through continuous endogenous production of FIX after a single administration of vector, especially since a small rise in circulating FIX to at least 1% of normal levels can substantially ameliorate the bleeding phenotype [1]."

Unfortunately, previous gene therapy experiments have been unsuccessful, showing only transient expression of Factor IX (effects weaned off after a while). It is possible that the patients' immune system produces a T-cell response against the infused cells. In its essence, gene therapy is the transfer of a healthy gene in the cell line affected by the defective genes. This transfer is usually obtained through a modified virus (the "vector") because viruses have the innate ability to attack a cell and inject it with their own genetic material. When choosing a viral vector, therefore, it is essential to establish that the patient's immune system does not "recognize" the viral vector. That's often the problem with gene therapy: basically, you are trying to "fool" the immune system by injecting extraneous genetic material and hoping that it successfully replaces the defective one. However, the immune system is not so easy to fool.

Nathwani et al. [1] tried a new gene therapy approach. The vector typically used is a modified adenovirus, but the researchers used a self-complementary vector so it would yield higher efficiency in transgene expression. They also used a subtype of virus that has a lower prevalence in humans, and thus lower chances of patients having developed humoral immunity against it. Lastly, whether previous approaches would infuse the virus directly to the liver, in this study patients were administered the vector in the peripheral vein, which is a less invasive and safer approach.

The results were quite promising: "AAV-mediated expression of FIX at 2 to 11% of normal levels was observed in all participants. Four of the six discontinued FIX prophylaxis and remained free of spontaneous hemorrhage; in the other two, the interval between prophylactic injections was increased."

The difference in responses to the therapy was partly due to the fact that patients were given different doses of the genetically modified virus (low, moderate, and high), which in fact were dose dependent. However, it also suggests that individual immune responses and different exposures to the virus greatly affect the outcome. These factors need to be better understood and it will require a larger number of participants in future studies. Furthermore, as with any other gene therapy treatment, there are risks associated: the six participants are currently monitored for hepatic dysfunction, but the researchers are optimistic that, even with such potential risks, this kind of therapy

"has the potential to convert the severe bleeding phenotype into a mild form of the disease or to reverse it entirely."

Edited to add a cool comment from antisocialbutterflie:

Intriguingly enough my grad lab worked on AAV capsid proteins (not my project but I could give the first 15 minutes of a seminar from memory). It's a great gene therapy vector assuming (a) there isn't the preexisting immunity that you mentioned and (b) the gene you are therapifying (word?) is small enough.

The engineering of non-natural variants that exhibit the appropriate tissue specificity while escaping the existing immune response is pretty cool. It all boils down to a series of surface loops (variable regions) that mediate both the receptor-binding but also present the antigens that antibodies are developed against. Swapping out the antigenic residues are likely to disrupt the receptor binding and mess up the tissue specificity making it useless as a therapy vector.

There is also a finite amount of DNA it can package. If I remember correctly the max is around 8 kb. If it's bigger you have to turn to things like adenoviruses or the previously mentioned HIV.

[1] Nathwani, A., Tuddenham, E., Rangarajan, S., Rosales, C., McIntosh, J., Linch, D., Chowdary, P., Riddell, A., Pie, A., Harrington, C., O'Beirne, J., Smith, K., Pasi, J., Glader, B., Rustagi, P., Ng, C., Kay, M., Zhou, J., Spence, Y., Morton, C., Allay, J., Coleman, J., Sleep, S., Cunningham, J., Srivastava, D., Basner-Tschakarjan, E., Mingozzi, F., High, K., Gray, J., Reiss, U., Nienhuis, A., & Davidoff, A. (2011). Adenovirus-Associated Virus Vector–Mediated Gene Transfer in Hemophilia B New England Journal of Medicine DOI: 10.1056/NEJMoa1108046

Photo: sculpture by Joshua Tobey, Santa Fe, NM. Shutter speed 1/40, F-stop 7.1, focal length 75mm, ISO speed 100.

Remember back when...

2011-12-12T05:52:00.000-08:00

I generate most of my figures in R. What do you guys use? I suppose it changes from field to field. However, no matter what your field is, there comes a time when you have to use Adobe Illustrator to beautify your figures and get them paper-ready.

I have a love/hate relationship with AI.

I love it because it lets me do so many things.
I hate it because it won't let me do so many things.

So, the other day I was having one of my AI fits when everything around me got blurry, a heavy fog lifted in my office, and I was propelled back to ~~many~~, ahem, some years back when I was in elementary school and my dad was preparing his paper figures...

Okay, the blurring and the fog I added for special effects, but going back to my dad: he is a developmental biologist, and back in the days when Apples only came in black screens with fixed menus in a green font, my dad would start by developing his pictures in the camera obscura. He would then trim the pictures and mount them on paper board -- one board for each figure, and each figure had different panels.

Now, for the labeling, this is what he'd use:

Remember those? I loved them when I was a kid! We'd get comic books where you could add your characters to a scene -- it was fun! But those tiny letters my dad would use to label his photos -- man, they were a pain in the ***! And the letters were a piece of cake compared to the thin lines and geometrical shapes he'd use for the graphs. You'd have to press very delicately. If you pressed too hard you'd ruin the photo, or the lines would break, and you'd have to start over. If you'd press too lightly they'd come off and you'd find them all over your hand, the lines especially, sticking out like misplaced hairs.

Argh.

So, on second thoughts... I love AI. I really, really love AI.

Understanding the cell nucleus in order to unravel the mystery of epigenetic heritability

2011-12-09T07:04:00.000-08:00

The above image is the striking view of the surface of a cell nucleus (in pink). The dark crater represents a hole in the nucleus and offers a peek inside: the granular consistency that you see there are the chromosomes, bundled together in what may appear a random distribution but, in reality, is nothing but random:

"In all eukaryotic species analyzed so far, spatial genome arrangements are nonrandom: chromosomes or genomic loci occupy preferential positions with respect to each other and/or to nuclear landmarks [1]."

The nucleus contains a combination of DNA and proteins (mostly histones) called chromatin. Histones can be thought of spools around which the DNA wraps, forming a structure called nucleosome. Proteins in the chromatin can be silenced or activated, thus allowing differentiated cells to express only the genes necessary to their specific function. The budding yeast Saccharomyces cerevisiae was the first eukaryote cell to have its entire genome sequenced and, due to its relatively compact size (16 small chromosomes), it has been studied extensively to understand the structure of the cellular nucleus. For example, one of the largest protein complexes on the nuclear envelope is the nuclear pore complex, or NPC, which modulates the exchange of components between the nucleus and the cytoplasm. Several genes are relocated to the NPC when activated, and, as Zimmer and Fabre note [1],

"The region close to the nuclear envelope thus emerges as a mosaic, with the vicinity of NPCs representing zones favorable to transcription, whereas the zones between NPCs are more repressive."

These spatial arrangements are not static but they undergo re-arrangements (through complicated chemical alterations like cytosine methylation and/or post-translational modification of the histone amino acids). The extent of packaging of the nucleosome affects gene expression, however, to this day, little is known on what determines this delicate spatial arrangement.

And here's the intriguing bit: the re-arrangements the chromatin undergoes are generally reversible. And yet there's a level of these modifications that not only remains unmodified, it becomes inherited [2]:

"Chromatin modifications are often termed epigenetic marks; however, an unresolved issue in the field is the relationship between these modifications, including those established during transcription, and epigenetic inheritance (that is, the stability of these alterations during cell divisions and development). It seems that most, if not all, histone modifications are reversible, so it remains to be determined how epigenetic persistence of chromatin states is achieved, and which modifications are heritable."

These are the transgenerational epigenetic modifications I have discussed here and here. It's a real puzzle because heritability happens through the germ line cells, but in this cell line transcription only happens de-novo after fertilization. So at what level and how are epigenetic changes inherited? In [2], Berger reviews the various types of chromatin modifications and concludes with a nice analogy:

"Language is defined by the Webster dictionary as systematic means of communicating ideas using conventionalized signs or marks having understood meanings. This definition can be used to describe the complexity of the relationship between epigenetic marks and the biological processes they influence. As scientists, it falls to us to learn and understand this language a task that we have only begun to undertake."

EDIT: as I was preparing this post, I found this article on Scientific American, which talks about untangling the 3D human genome, and how the topology inside the nucleus determines which genes are on and off. There's a neat video, if you scroll to the bottom of the article.

[1] [1] Zimmer, C., & Fabre, E. (2011). Principles of chromosomal organization: lessons from yeast The Journal of Cell Biology, 192 (5), 723-733 DOI: 10.1083/jcb.201010058

[2] Berger, S. (2007). The complex language of chromatin regulation during transcription Nature, 447 (7143), 407-412 DOI: 10.1038/nature05915

Timing the AIDS pandemic and why it made history (Part II)

2011-12-08T05:14:00.000-08:00

In Part I of this post I discussed the Science paper that proved HIV was the result of a cross-transmission from chimpanzees to humans. In that paper, Hahn et al. conclude with an open question:

"The timing of SIVcpz transmission to humans, leading ultimately to the HIV-1 pandemic, has been a challenging question. We know from analyses of stored samples that humans in west central Africa had been infected with HIV-1 group M viruses by 1959 and with group O viruses by 1963. But how much earlier were these viruses introduced into the human population? [...] It should be possible to estimate the timing of the onset of the pandemic by calculating the date of the last common ancestor of HIV-1 group M."

In a phylogenetic tree (see the definition I gave last time), the last common ancestor is the root of the tree: that's the "patriarch" of the sample if you will, the one sequence from which, one divergent event at the time, the whole sample originated. Phylogenetic analyses allow us not only to reconstruct the evolutionary history of the sequences, but also, if you have a rough idea of what the mutation rate is (i.e. how often new mutations arise) to time them. It's a technique often referred to as "molecular clock," which originated from the observation that the number of molecular differences between different lineages increases linearly with time and that substitutions accumulated according to a Poisson distribution.

Korber et al. used parallel computers to apply maximum-likelihood tree-building methods to the envelope sequences (the envelope is one of the HIV genes) from 159 individuals. They note:

"Although it is unrealistic to expect that HIV-1 evolution will always rigidly adhere to a molecular clock, it is, however, the average behavior of many sequences that we consider here, and our control estimates of known times were accurate."

To this they combined another data point: the year of sampling of the sequences used to reconstruct the tree.

(A) The phylogenetic tree used for the calculation. (B) The branch lengths from the tree plotted versus the year of sampling an dprojected backwards in time.

Once they reconstructed the phylogenetic tree, with the root sitting more or less in the middle, and thus at the same distance from the various HIV subgroups (the clusters marked with capital letters in panel A above), they plotted the branch lengths of the tree against time (panel B) and did a linear fit to extrapolate the time since the last common ancestor: 1931, with a 95% confidence interval of 1915 to 1941. Furthermore, testing a known HIV-1 group M isolate from 1959 gave an accurate estimate for the date of its origin, indicating that the assumptions of the method are reasonable.

Notice that 1931 marks the year the first HIV-1 lineage, the M-group, started to spread and diversify in humans. It does not tell us whether or not the virus was transmitted at the same time as it started to diversify. It could be possible that the virus cross-transmitted to humans earlier and remained isolated within a small population. Around the '30s socioeconomic changes would've allowed the spread of the virus:

"Strictly speaking, our estimate is neither an upper nor a lower bound on the date of the actual zoonosis. Rather, it is the approximate time of the bottleneck event that was the genesis of the M group and captures the moment of the beginning of the expansion of the M group. If the M group originated in humans, then this would date the founder virus of the pandemic."

Another important question is addressed in the following commentary by David Hillis:

"If HIV has been present in human populations since at least the 1930s (and probably much earlier), why did AIDS not become prevalent until the 1970s? The phylogenetic trees of HIV-1 indicate that the spread of the virus was initially quite slow‚ by 1950 there existed 10 or fewer HIV-1 M-group lineages that left descendants that have survived to the present. The epidemic exploded in the 1950s and 1960s, coincident with the end of colonial rule in Africa, several civil wars, the introduction of widespread vaccination programs (with the deliberate or inadvertent reuse of needles), the growth of large African cities, the sexual revolution, and increased travel by humans to and from Africa. Given the roughly 10-year period from infection to progression to AIDS, it was not until the 1970s that the symptoms of AIDS became prevalent in infected individuals in the United States and Europe."

B. Korber, M. Muldoon, J. Theiler, F. Gao, R. Gupta, A. Lapedes, B. H. Hahn, S. Wolinsky, and T. Bhattacharya. (2000). Timing the Ancestor of the HIV-1 Pandemic Strains Science, 288 (5472), 1789-1796 DOI: 10.1126/science.288.5472.1789

Ethnobotany, shamanism and extremophiles: Alison Sinclair talks about world-building in science fiction

2011-12-06T05:25:00.000-08:00

My guest today writes science fiction "to indulge a passion for knowledge of all kinds and science and medicine in particular," and to "have an excuse to read about everything from oceanography to nanotechnology, from color theory to the history of microscopy." Alison Sinclair is the author of the Darkborn Trilogy as well as the novels Legacies, Blueheart, Cavalcade, and Throne Prince (co-authored with Lynda Williams). Her writing is beautiful and flawless, and her world-building is even more amazing, delving into "ethnobotany, shamanism and extremophiles (bacteria which live in hostile environments)"[1]. As she states in her bio, "I like to be able to ditch all assumptions and conventional wisdom and start entirely from scratch, running my fictional 'thought experiments' (Ursula Le Guin’s words) according to any parameters I please. Science fiction gives my imagination elbow room."

When she's not writing, Alison works at a hospital-based technology assessment unit, doing literature reviews and contributing to meta-analyses and cost-effectiveness analyses. I tried to keep track of all her degrees, but got lost after physics, biochemistry, and medicine...

I'm truly excited to welcome Alison to my blog today!

EEG: I'll start off with a geek question: I was browsing your blog and noticed that you had just posted some code in R, which of course I use all the time, so my jaw dropped in admiration...

AS: I've just (last year) finished a MSc in Epidemiology, and a number of our lecturers used R, so I did a lot of assignments using R (and some SAS, and some STATA). Since then, I've mainly used R for its graphics capabilities, but I have a couple of side projects that are on my list of things to get back to.

EEG: Do you think of yourself as primarily a scientist, a writer, or both?

AS: Still primarily a scientist, though I think the two have converged. "Scientist" was my ambition from childhood, although I was writing almost from the time I could hold a pen.

EEG: How much of your writing is influenced by your work as a scientist?

AS: I'm not sure what came first, the reading and TV viewing (Star Trek and other TV fiction, the Apollo and other space projects) influencing the career choice, or the career choice influencing the writing. Since I was intensely interested in science, when I discovered SF properly, I immediately started writing it. Pastiches of John Wyndham and Ray Bradbury, mainly, with forays into Clarke and Asimov. I had a long spell of trying to write mainstream (because I didn't connect with SF fandom until later), but it felt like a huge chunk of my reality was being left out.

As to how science influenced the writing: all of it. Characterization, problems, narratives, ethical framework. My first six novels were SF (3 published, 3 still unpublished). Legacies was the least influenced by my work as a scientist, because it was a world I'd been living with since childhood, though I started worldbuilding because I was keen on geology, physical geography and natural history. While I was writing Blueheart, I was working as a lab scientist, so along with my perennial interest in natural history and the sea, Blueheart got the molecular biology and bioengineering. While I was writing Cavalcade, I was at medical school, so the interest in medicine - and nanotechnology, and social dislocation - are all through it. Three of my main characters are scientists, and one of them does an autopsy under very strange circumstances. The next novel (unpublished) came out of a lecture in culture and ethics at medical school, talking about the culture clash between patients who came out of a different healing tradition - and I took to wondering what a physician from a different tradition would look like. As a novel, it wasn't a terribly successful experiment, and one of these days, I'll go back to it and see if distance has given me insight into its problems. Then, while working as a journal editor, I took my first course in epidemiology (if my lecturers only knew what I do with the knowledge they impart), which fed into two novels of what I describe as my "medical starship" series. And then I had an idea for a fantasy novel.

EEG: Tell us about the Darkborn Trilogy: how were the characters of Bal, Telmaine, and Ishmael born? (BTW, I love the names!)

AS: In irritation: I was reading a fantasy novel in which the whole light/dark trope was blatantly foregrounded in the characterization and the imagery, so much so that it annoyed me. So the first thing I thought about was the literal division into day and night, and then starting sympathetically with the "dark" characters. Balthasar and Floria and their paper wall came first. I'd been doing a lot of reading around the decades leading up to World War I for another project, and between having cut my teeth on fantasy written either before or between the wars, and feeling more comfortable with a more urban and developed setting, I came up with the Darkborn society. Balthasar seemed the kind of man who'd be married and settled, out of which came Telmaine, who is a contrast to him, temperamentally and socially. Then there was the question as to why she would be so determined to marry beneath her, which led to the nature of her magic. Ishmael was a bit of a surprise, when Telmaine tripped down the stairs and encountered him. He was originally supposed to be a kind of John Buchanesque hero, and never quite lost that, though he developed in his own direction. As part of the society I was building, I wanted names that were fairly elaborate. Balthasar and Ishmael came out of the Oxford Dictionary of First Names, as best I can recall. Telmaine's name was made up. I had a bit of an argument with myself over Ishmael's name, knowing it would have particular associations for US readers, but none of the alternatives would stick. Ishmael was Ishmael.

EEG: Interesting. I confess I had a similar experience, and my very first story (which sat in my head for decades!) finally came on paper after reading a book that triggered that kind of irritation. It made me realize that yes, it's good to read literary masterpieces, but the occasional crappy book can have a positive side, too!

Thanks so much for being here today, Alison. To find out more about Alison's books (and scientific work, too) visit her at www.alisonsinclair.ca.

Timing the AIDS pandemic and why it made history (Part I)

2011-12-05T05:36:00.000-08:00

This week I would like to discuss two Science papers that have marked a milestone in HIV research. In order to place them in the right context, I need to start with a brief historical digression. If you're interested in the history of the discovery of the AIDS disease, I highly recommend watching the movie And the Band Played On. It's very well done and realistically portrays how the medical investigation was conducted. For the purpose of my discussion here, though, I will start from the movement known as AIDS denialism.

From Wikipedia:

"AIDS denialism is the view held by a loosely connected group of people and organizations who deny that the human immunodeficiency virus (HIV) is the cause of acquired immune deficiency syndrome (AIDS). Some denialists reject the existence of HIV, while others accept that HIV exists but say that it is a harmless passenger virus and not the cause of AIDS."

Famous "denialists" include Nobel laureate Kary Mullis, UC Berkley professor Peter Duesberg (the first to isolate a cancer gene), and biologist Lynn Margulis (who discovered the origin of mitochondria through symbiosis). Oh, and I almost forgot Serge Lang, whose math books I revered back in grad school. (In case you didn't know, being a good scientist doesn't mean you get everything right.) There's some really sad stories associated to AIDS denialism, including a woman whose firm beliefs didn't falter not even after her three-year-old daughter died of AIDS complications. In fact, she even founded an organization to discourage HIV-positive pregnant women to take anti-HIV medications. Even sadder is what happened in South Africa: despite the fact that HAART therapy (a potent cocktail of anti-retroviral drugs) became available around the mid-nineties, the advent of the therapy was delayed because the then South Africa president Thabo Mbeki, along with the rest of the African National Congress party, convinced by the denialist movement, believed that AIDS was the result of poverty and malnutrition.

Part of the puzzle was that people didn't really know how the HIV virus had originated. There were various theories, often inconsistent or almost resembling sci-fi movies: these included several variations over the theory that HIV was a bio-warfare virus engineered by the US Government; another theory was that it had spread through the smallpox vaccination; and, finally, the most realistic was that it had spread through the polio vaccine, which had been developed on chimpanzee tissue, and there was a real possibility that the tissue could've been contaminated. Of course, the fact that nobody knew for sure, deepened the roots of AIDS denialism.

Now fast forward to January 2000, when Hahn et al. published a paper in Science [1] proving that HIV had been transmitted to humans from monkeys and had originated from the SIV virus. This is the paper I would like to discuss today. 2000 was the year South Africa's President Thabo Mbeki invited several HIV/AIDS denialists to join his Presidential AIDS Advisory Panel. That same year over 5,000 scientists and physicians signed the Durban Declaration in which they affirmed that AIDS was caused by HIV. Unfortunately, it didn't stop the estimated 300,000 AIDS deaths in South Africa that could have been prevented by introducing HAART therapy.

Hahn et al. analyzed the full-length genomic sequences of distinct primate lentiviruses from monkeys. These fell into five major, approximately equidistant, phylogenetic lineages:

"Evolutionary relationships of primate lentiviruses based on maximum-likelihood phylogenetic analysis of full-length Pol protein sequences. The five major lineages are color-coded. The scale bar indicates 0.1 amino acid replacement per site after correction for multiple hits."

The above figure is a phylogenetic tree, that is, a graphical representation of the genetic distances across the sample. Each leaf in the tree represents a genetic sequence, and sequences that are most similar are clustered together. As you move from the right to the left, you can reconstruct the evolutionary history of each sequence: for example, the two sequences HIV-1/LAI and HIV-1/ELI are roughly a few mutations away, which means they share a common ancestor. That common ancestor at some point originated the sequence HIV-1/U455. Each node represents a "coalescent" event, an event in which one sequence duplicated and a few new mutations were inserted. (What I just gave you is a schematic explanation, things can get more complicated than that, but let's keep things simple for the sake of the argument.) Phylogenetic trees are constructed using maximum-likelihood methods: basically you compute all possible trees and then choose the one that maximizes the probability function associated with it (the most likely tree). Obviously, this is not done by hand but by a computer program that goes through many iterations and hence takes a very long time. Today, supercomputing machines are utilized to speed up the process.

What can we learn from the above tree? First of all, notice that the lineages are color-coded. Each color represents one lineage found in one particular primate species, and the fact that colors tend to aggregate together in host-specific clusters tells us two things: (1) each lineage has been infecting their respective host for a relatively long time; (2) a "jump" from one host to another one represents a divergence in the evolution of the virus.

"HIV infections have also resulted from cross-species transmission events. Five lines of evidence have been used to substantiate the zoonotic origins of these viruses: (i) similarities in viral genome organization, (ii) phylogenetic relatedness, (iii) prevalence in the natural host, (iv) geographic coincidence, and (v) plausible routes of transmission."

Following the above logic, evidence collected from chimpanzees from Cameron led to conclude that the HIV-1 epidemic arose as a consequence of SIVcpz transmission from a particular chimpanzee subspecies, P. t. troglodytes, to humans.

"The seeds of the HIV-1 epidemic appear to have been planted in west equatorial Africa in the region encompassing Gabon, Equatorial Guinea, Cameroon, and the Republic of Congo (Congo-Brazzaville). It is only here that HIV-1 groups M, N, and O cocirculate in human populations and where chimpanzees (P. t. troglodytes) have been found to be infected with genetically closely related viruses."

The most likely transmission route from primates to humans would have been through blood exposure from butchering and consuming raw meat from infected animals. Such cross-species transmission are not unusual (several flu strains are often acquired that way), but they often represent an evolutionary dead-end for the virus as it may not be well-adapted to the new host. That was obviously not the case with HIV-1, whose high variability allowed it to readily adapt and dodge the human immune system.

In next post, I'll discuss the second Science paper that made history in this field.

Hahn, B., Shaw, G. M., De Cock, K. M, Sharp, P. M. (2000). AIDS as a Zoonosis: Scientific and Public Health Implications Science, 287 (5453), 607-614 DOI: 10.1126/science.287.5453.607

Another genetic puzzle: why is mitochondrial DNA only inherited from the mother's side?

2011-12-02T06:40:00.000-08:00

Remember when I told you that bacteria have circular DNA? Well, we have it too, only not in the nucleus where the rest of our DNA sits. It's a rather interesting story, one that biologist Lynn Margulis proved in 1967 [1]: our cells contain organelles called mitochondria, which originally were separate organisms (prokaryotes), and at some point entered a symbiotic relationship with eukaryotic cells through endosymbiosis. As a result, they contain their own, circular DNA called mitochondrial DNA or, in short, mtDNA.

Circularity is not the only fascinating thing about mtDNA. It contains 37 genes, and, because it's not found in the nucleus, non-nucleated cells like precortical cells (found in hair shafts) can't be used for DNA analysis, but can indeed be used to extract mtDNA. However, whereas nuclear DNA is unique to each individual, mtDNA is not. That's because it's inherited exclusively through the maternal lineage. As you know, paternal and maternal chromosomes undergo recombination and then fuse together to make the unique DNA of a new individual. However, mtDNA does not undergo recombination and the only variation happening is due to random mutations when the cell splits. These are quite rare and in fact, it's not unusual to share identical mtDNA with our siblings, and/or to inherit it unchanged from our mothers.

Maternal mtDNA inheritance occurs in most eukaryotic species, indicating that, from an evolutionary point of view, it's an old and conserved mechanism. One might argue that paternal gametes (sperm) are much smaller than maternal gametes (eggs) and therefore contribute a limited amount of mitochondria, which then get lost. In fact, the general belief was that, at least in some species, paternal mitochondria was excluded due to the fact that only the head of the spermatozoon enters the oocyte's cytoplasm. Well, that doesn't quite explain the whole story, and the mechanism that allows the clearance of paternal mitochondria during early embryonegesis was not understood until recently.

Two studies published in the November 25 issue of Science [2, 3] used a Caenorhabditis elegans model to show that the degradation of paternal mitochondria is achieved through involvement of autophagosomes, double membrane vesicles that recruit the organelles, engulf them, and then destroy them. Rawi et al. also proved that autophagy is triggered in the mouse too, within minutes after fertilization, whereas, in the absence of autophagosomes (which they induced artificially in some animals), the paternal mitochondria persist in the embryos.

This is a great step forward, but many questions remain unanswered, as Levine and Elazar note in the accompanying perspective:

"The findings of Sato and Sato and Al Rawi et al. help to explain how paternal mitochondria and mtDNA are destroyed, but why they are destroyed remains a mystery. Is heteroplasmy, the occurrence of more than one mtDNA genotype, dangerous for the developing embryo? Or is the degradation of paternal mitochondria merely a primitive defense in which the fertilized oocyte views the paternal mitochondria as a potentially dangerous intruder that must be destroyed?"

[1] Sagan, L. (Margulis, L.) (1967). On the origin of mitosing cells Journal of Theoretical Biology, 14 (3) DOI: 10.1016/0022-5193(67)90079-3

[2] Sato, M., & Sato, K. (2011). Degradation of Paternal Mitochondria by Fertilization-Triggered Autophagy in C. elegans Embryos Science, 334 (6059), 1141-1144 DOI: 10.1126/science.1210333

[3] Al Rawi, S., Louvet-Vallee, S., Djeddi, A., Sachse, M., Culetto, E., Hajjar, C., Boyd, L., Legouis, R., & Galy, V. (2011). Postfertilization Autophagy of Sperm Organelles Prevents Paternal Mitochondrial DNA Transmission Science, 334 (6059), 1144-1147 DOI: 10.1126/science.1211878

Tonemapping

2011-12-02T05:45:00.000-08:00

In a previous HDR post I hinted at the added feature of tonemapping, so I thought I'd post an example of a photo for which tonemapping quite improved the image. I took this photo last June in Massachusetts:

This is right across the street from where I lived as a graduate student, so no wonder I like the photo. But as you can see, the sky is really dull. It's flat. So I tonemapped and this is what I got:

Maybe you find the second image artificial. But I think it really brings out the texture of the sky, which, mind you, was there, and my eyes could see it because they would refocus when I'd look at the sky, but lenses can't do that. I find tonemapping to make a huge difference also when shooting in shady settings:

Bottom line: I'm not dogmatic when it comes to these things. Of course, most of the work is always done behind the viewfinder. But there's an art in editing images too, and that's what I'm trying to learn as well.

Genetic epistasis

2011-12-01T07:06:00.000-08:00

A while ago, in a post titled the Missing Heritability, I discussed the fact that some risk alleles (gene copies that have been found to increase the risk for a certain disease) may turn out to be counter-effected by other genes and thus explain why some people with these alleles never develop the particular disease. At the time I did a quick search on PubMed but couldn't come up with anything in the literature. Well, I was missing the keyword: epistasis. The word comes from the Greek "epi", which means "upon," and "stasis," which means to stop (I see my mom gloating out there in the audience!): compositional epistasis is the mechanism by which the effect of one allele is modified, and in some cases even blocked, by other gene alleles. This of course is hard to detect, but intuition tells us that it is a rather diffuse phenomenon. Genes are far from being "push-buttons," rather, they work in concert, initiating complex pathways, and therefore more often than not, a single gene is unlikely to give us a complete picture.

Back to my quest. I searched "genetic epistasis" on PubMed and this time I found a lot of interesting stuff. As a disclaimer I should say that for some of these studies there are contrasting outcomes in the literature (some results weren't reproduced in different populations). Nonetheless, I think that we are just starting to scrape the tip of the iceberg: gene-to-gene interaction are complex and poorly understood, but they certainly hold the key to the mysterious ways in which our genome works. Despite the skepticism expressed by some in the field, I do believe that single-gene studies are limited and should eventually give way to whole-genome studies.

[1] Evidence of biologic epistasis between BDNF and SLC6A4 and implications for depressionEpistasis of BDNF and SLC6A4 in depression.

SERT is a protein whose function is to terminate and recycle the neurotransmitter serotonin. Historically, serotonin has been associated to happiness and well-being, which explains why SERT is the target of numerous drugs addressing psychiatric disorders. SLC6A4, the gene encoding SERT, has been extensively studied and one polymorphism in particular, 5-HTTLPR (which is not a SNP, a single-base mutation, rather some individuals present a long allele with a 44 base-pair insertion, compared to the short allele) has been associated to the efficacy of some antidepressants and also to other psychiatric disorders. On the other hand, the brain-derived neurotrophic factor (BDNF) protein is involved in the growth, proliferation, and differentiation of certain neurons. The gene encoding BDNF has been associated to bipolar disorder and improved general cognitive ability. Two genes, two (apparently) distinct pathways and signaling systems. Using anatomical neuroimaging techniques in a sample of healthy subjects (n=111), Pezawas et al. showed

"that the BDNF MET allele, which is predicted to have reduced responsivity to 5-HT signaling, protects against 5-HTTLPR S allele-induced effects on a brain circuitry encompassing the amygdala and the subgenual portion of the anterior cingulate (rAC). Our analyses revealed no effect of the 5-HTTLPR S allele on rAC volume in the presence of BDNF MET alleles, whereas a significant volume reduction (P<0.001) was seen on BDNF VAL/VAL background. [...] These data provide in vivo evidence of biologic epistasis between SLC6A4 and BDNF in the human brain by identifying a neural mechanism linking serotonergic and neurotrophic signaling on the neural systems level, and have implications for personalized treatment planning in depression."

[2] Renin-angiotensin system gene polymorphisms and coronary artery disease in a large angiographic cohort: detection of high order gene-gene interaction.

Tsai et al. [2] recruited 1254 patients who underwent cardiac catheterization (735 with documented coronary artery disease and 519 without) and individually matched them with controls based on corresponding risk factors for coronary artery disease. The researchers genotyped several polymorphisms: one in the angiotensin-converting enzyme gene, six in the angiotensinogen gene, and one in the angiotensin II type I receptor gene. In single-locus analyses, no locus was associated with coronary artery disease or acute myocardial infarction. However:

"Significant three-locus (G-217A, M235T and I/D) gene-gene interactions were detected by multifactor-dimensionality reduction method (highest cross-validation consistency 10.0, lowest prediction error 40.56%, P=0.017) and many even higher order gene-gene interactions by multilocus genotype disequilibrium tests (16 genotype disequilibria exclusively found in the controls, all of which included at least two genes among AGT, ACE and AT1R genes). Our study is the first to demonstrate epistatic, high-order, gene-gene interactions between RAS gene polymorphisms and CAD. These results are compatible with the concept of multilocus and multi-gene effects in complex diseases that would be missed with conventional approaches."

I've added below a few more references on epistasis for those interested in researching the topic further.

Photo: Walt Disney Concert Hall, Los Angeles, CA. Shutter speed 1/15, focal length 24mm, F-stop 22, ISO speed 100.

[1] Pezawas, L., Meyer-Lindenberg, A., Goldman, A., Verchinski, B., Chen, G., Kolachana, B., Egan, M., Mattay, V., Hariri, A., & Weinberger, D. (2008). Evidence of biologic epistasis between BDNF and SLC6A4 and implications for depression Molecular Psychiatry, 13 (7), 709-716 DOI: 10.1038/mp.2008.32

[2] Tsai CT, Hwang JJ, Ritchie MD, Moore JH, Chiang FT, Lai LP, Hsu KL, Tseng CD, Lin JL, & Tseng YZ (2007). Renin-angiotensin system gene polymorphisms and coronary artery disease in a large angiographic cohort: detection of high order gene-gene interaction. Atherosclerosis, 195 (1), 172-80 PMID: 17118372

[3] Wiltshire S, Bell JT, Groves CJ, Dina C, Hattersley AT, Frayling TM, Walker M, Hitman GA, Vaxillaire M, Farrall M, Froguel P, & McCarthy MI (2006). Epistasis between type 2 diabetes susceptibility Loci on chromosomes 1q21-25 and 10q23-26 in northern Europeans. Annals of human genetics, 70 (Pt 6), 726-37 PMID: 17044847

[4] Abou Jamra R, Fuerst R, Kaneva R, Orozco Diaz G, Rivas F, Mayoral F, Gay E, Sans S, Gonzalez MJ, Gil S, Cabaleiro F, Del Rio F, Perez F, Haro J, Auburger G, Milanova V, Kostov C, Chorbov V, Stoyanova V, Nikolova-Hill A, Onchev G, Kremensky I, Jablensky A, Schulze TG, Propping P, Rietschel M, Nothen MM, Cichon S, Wienker TF, & Schumacher J (2007). The first genomewide interaction and locus-heterogeneity linkage scan in bipolar affective disorder: strong evidence of epistatic effects between loci on chromosomes 2q and 6q. American journal of human genetics, 81 (5), 974-86 PMID: 17924339

[5] Coutinho AM, Sousa I, Martins M, Correia C, Morgadinho T, Bento C, Marques C, Ataíde A, Miguel TS, Moore JH, Oliveira G, & Vicente AM (2007). Evidence for epistasis between SLC6A4 and ITGB3 in autism etiology and in the determination of platelet serotonin levels. Human genetics, 121 (2), 243-56 PMID: 17203304

Sample size, P-values, and publication bias: the positive aspects of negative thinking

2011-11-29T05:41:00.000-08:00

If you follow the science blogging community, you may have noticed a lot of talking about sample size in the past couple of weeks. So I did my share of mulling things over and this is what I came up with.

1- The study in question had a small sample size but reported a significant p-value (<0.05). Such study is NOT underpowered. An underpowered study is a study that does not have a sufficiently large sample size to allow detection of a significant result. A significant result is by definition a p-value less than 5%, which the study in question had. So, even though in general small sample size studies are indeed underpowered, that wasn't the issue in this particular case. In general, you are not likely to see many underpowered studies published (see point 5 below).

2- The issue with ANY small sample size study is the fact that you are not capturing the whole fluctuation in the population. And if you are not capturing the whole fluctuation, chances are, your error model is wrong, and a wrong error model leads to a wrong p-value. In other words, even if you do get a significant p-value, there's a question of whether or not that particular p-value is at all meaningful.

3- Why publish a study with a small sample size, then? Welcome to the life of a scientist. You set off with a grand plan, write a grant to sequence say 100 individuals, get the money to sequence 50, then you clean the data and end up with 30. Okay, those are made-up numbers, but you get the idea. So now you got your 30 sequences and you try to make the best out of them. You state all the caveats in the discussion section of your paper and advocate for further analyses and discuss future directions. If your paper gets published you have some leverage in your next grant, as in: "Look! I saw something with 30 sequences, which is clearly not enough, so now I'm applying to get money to sequence 100." Many scientific advances have ben made following exactly this route.

4- I've been talking a lot about p-values, but... What the heck is a p-value? A p-value of, say, 0.05 boils down to the following: if your results were completely random, and you were to repeat your experiment 100 times, you would observe your original result 5% of the time just out of pure chance. Suppose for example you want to see if a particular gene allele is associated with cancer. You do your experiment and come up with a p-value of 0.03. This means that if there really was no association whatsoever between the trait you measured and cancer, you would see your particular population distribution 3% of the time out of pure chance. Now, you see why anything above 5% is not significant: to observe something 10% of the time out of pure chance means that whatever you are trying to measure is a random effect. But to see it 3% of the time makes it rare enough that we are allowed to believe that there may be something in there after all. Notice that this is pretty much how science works. Many science outsiders think that "scientific" means "certain." Not true. Scientific means we can measure the uncertainty and when it's small enough we believe the result.

5- Now that we understand what p-values are we get to another issue: publication bias. Follow the logic: I just said that we start believing a result whenever the p-value is less than 5%. Basically, you can forget publishing anything that has a p-value above 5%. But, you won't know your p-value unless you do the experiment, and you won't publish unless you get a low p-value. Which means, you will never see all the similar studies that were carried out and yielded a high p-value. Suppose an experiment were repeated across different labs 100 times. Then, just by chance alone, 5% of these experiments yield a p-value of 5% or less. However, what you end up seeing in print are the experiments that yielded the "good" p-value, not the ones that yielded the negative results. As Dirnagl and Lauritzen put it [1],

"Only data that are available via publications‚ and, to a certain extent, via presentations at conferences‚ can contribute to progress in the life sciences. However, it has long been known that a strong publication bias exists, in particular against the publication of data that do not reproduce previously published material or that refute the investigators‚ initial hypothesis."

People address the issue with meta-analyses, in which several studies are examined and both positive and negative results are pooled together in order to estimate the "true" effects.

"In many cases effect sizes shrink dramatically, hinting at the fact that very often the literature represents the positive tip of an iceberg, whereas unpublished data loom below the surface. Such missing data would have the potential to have a significant impact on our pathophysiological understanding or treatment concepts."

A new movement is rising, which advocates the publication of negative results (i.e. results that did not substantiate the alternative hypothesis), and more journals are integrating this into either a "Negative Result" section or, as BioMed Central has done, even dedicating a journal to it, the Journal of Negative Results in Biomedicine.

I welcome and embrace the change in thinking. It's the same logic I advocate for mathematical models. My new motto: "Negative results? Bring them on!" Maybe I'll have a T-shirt made -- anyone want one too?

[1] Dirnagl, U., & Lauritzen, M. (2010). Fighting publication bias: introducing the Negative Results section Journal of Cerebral Blood Flow & Metabolism, 30 (7), 1263-1264 DOI: 10.1038/jcbfm.2010.51

Courtney Schafer, author of the Shattered Sigil trilogy, on writing, mountaineering, and solving complex algorithms

2011-11-28T05:59:00.000-08:00

Sky, mountains, and sea: Courtney Schafer, my amazing guest today, masters it all. She's an electrical engineer working for an aerospace company, a mountaineer and a scuba diver. Oh, and of course, the author of The Whitefire Crossing, the first book in the Shatter Sigil trilogy, a fantasy novel that beautifully blends all of Courtney's passions. I'm so excited to be talking with Courtney today!

EEG: You are an electrical engineer, your husband is a scientist, and you both love speculative fiction. How do the two -- science and speculative fiction -- mingle in your everyday life?

CS: Interestingly enough, though my husband’s background is in atmospheric science and mine is in electrical engineering, these days we both do the same sort of thing at work: signal and image processing algorithm development. Thankfully we are saved from discussing algorithms over the dinner table by the fact we work for different companies and so can’t discuss proprietary information with each other! But since we both love SF and science, we have plenty of conversations about subjects like the future of the space program, whether FTL or wormhole travel is more plausible from a scientific standpoint, that kind of thing. My husband is a slow reader and spends most of his reading time on technical articles, so we don’t discuss SF books much, but we both love watching SF movies and TV series (and mocking the science when they get it wrong). Farscape, Firefly, Fringe, Supernatural, Carnivale, Invisible Man, Nowhere Man, and many others grace our DVD shelves and have been watched many times over.

EEG: Your debut novel, The Whitefire Crossing, features amazing mountaineering, powerful magic, adventure, and complex characters that completely engage you into the story. Your love for mountaineering (you are a rock climber yourself, not to mention skier, scuba diver, etc.!) clearly transpires in your fantastic descriptions. But what about science? Do you find that your scientific background helped you develop the Shattered Sigil world, and if so, how?

CS: I find that working out the plot of a novel feels extremely similar to solving a complex algorithm problem. There’s the same mix of logical reasoning flavored with sudden sparks of inspiration. So in that sense, the analysis skills I’ve developed in years of working as an engineer have been quite helpful in writing the Shattered Sigil series! Heh, and as for direct influence… one day I was describing to a co-worker how my blood mages cast spells. He said, “So… they basically lay out giant circuit diagrams on the floor and channel power through them.” Me: “…OMG you are so right!” I guess I love electrical engineering too much to leave it out of my fantasy world entirely.

EEG: Ohhhh... High Five! I feel exactly the same about plotting. It's like solving a mathematical system with a lot of variables. You start with the equations (the premise and the characters), then you sit down and solve it. Okay, sorry, let's get back to the interview.

The Tainted City, the sequel to The Whitefire Crossing, is due in late 2012. Can you give us a little sneak peek on what's coming up next for Dev and the city of Ninavel? Are you working on some other projects? (Given how you make mountains come alive, I'm wondering what would happen if you'd turn to the ocean and use your scuba-diving experience for a completely new world...)

CS: I just turned over a bunch of scenes and a synopsis for The Tainted City to the cover artist (the amazingly talented David Palumbo, who also did the art for The Whitefire Crossing). It’s very exciting to see the book start the publication process (even though I haven’t yet finished writing it!). Tentative publication date is October 2012. As for a sneak peek…Dev gets out of the predicament he’s in at the end of The Whitefire Crossing, though not in the way he wanted. He and Kiran return to Ninavel – not entirely of their own choice – and find the city a far more dangerous place than they’d feared. Someone’s murdering mages in ways that mimic the most spine-chilling tales of demons, Tainted children like Dev’s young friend Melly are vanishing without a trace, and Kiran’s former master Ruslan intends to seize the opportunity to reclaim his wayward apprentice and revenge himself on Dev. Even though much of the action takes place in Ninavel, Dev’s climbing and wilderness skills still come into play, as do the Whitefire Mountains.

Right now I’m spending every spare second on finishing The Tainted City (it’s tough to find time to write between my day job and parenting my 2 year old!), but I have a few ideas for other projects. Ha, funny you should mention the scuba-diving – I confess I absolutely love stories set in ocean worlds. (Seriously, I even liked Waterworld. Well, the first part of it, at least, before Dennis Hopper started chewing scenery.) So who knows, perhaps I’ll write an ocean-based fantasy one day.

EEG: And when you do, I'll be the first one to buy it!

Courtney, thanks so much for sharing your love for the mountains, the sea, science and writing with us. To find out more about Courtney and her books, please visit her website. She also blogs at the Night Bazaar, a group blog where authors published by Night Shade Books share tips on writing and getting published.

More HDRs

2011-11-27T09:19:00.000-08:00

All attempts to balance the backlight, which can be pretty strong around here. They all have some degree of ghosting problems, either because I didn't have a tripod (first two) or because the clouds were moving too fast (last one). First and second pictures are looking down to Pueblo Canyon, and the third is the Rio Grande. Fourth is the cougar in town! (Jemez Mountains in the background.)

I know that face! Sort of...

2011-11-26T06:50:00.000-08:00

In graduate school I had a Chinese friend who one day asked me the name of the fellow student who'd just stopped by to borrow a book. I told her, she thanked me, and added, "It's so hard for me to remember faces. You guys look all alike to me."

Now, you have to understand that I'm petite, brunette with dark eyes (very Italian), and the girl she'd just asked about was the typical Northern European type, tall, blond, and blue eyes. The concept was truly intriguing. I tend to mix up Eastern Asians, but that day I learned that Asians tend to mix up Caucasians.

You may have noticed this in other contexts, for example when people tell you who you or your child looks like and they come up with the funniest things. However, the "other-race" effect (less accurate recognition of people of a different race than self) is real and has been documented in the literature [1,2]. In these studies, participants were presented faces from different ethnic groups, including their own. In a second phase, a mix of already observed and never-seen before faces was presented, and participants had to recognize which they had already seen. In [1], researchers measured different brain potentials (through EEG) and inferred a pattern between the potential intensities with the act of remembering a face:

"Individuation may tend to be uniformly high for same-race faces but lower and less reliable for other-race faces. Individuation may also be more readily applied for other-race faces that appear less stereotypical. These electrophysiological measures thus provide novel evidence that poorer memory for other-race faces stems from encoding that is inadequate because it fails to emphasize individuating information."

An event-related potential (or ERP) is a brain response to a stimulus (the faces, in this particular case). They are measured through EEG and they have several components as shown in the figure below (P1, N1, P2, N2, and P2):

In [1] researchers found interesting patterns between two components in particular, P2 and N200, and the ability to recognize a face:

"Among all the potentials examined, frontocentral N200 potentials and occipitotemporal P2 potentials were particularly informative because they yielded other-race-specific memory findings. We thus propose that these potentials indexed face individuation that tended to be uniformly high for same-race faces but lower and more variable for other-race faces."

Even though I don't have the expertise to understand all the technicalities presented in the paper (but I do welcome comments, if anybody out there wants to provide more insight), I find these results quite intriguing. For example, participants were also asked to rate the "racial typicality" of each face, and other-race faces that were "less typical" seemed to be easier to recognize. Also, the amount of exposure of an individual to the other-race group affects the results, as the brain can indeed train itself to recognition.

A curious trivia is that both studies state at the beginning that all participants were right-handed. Is there a reason for this? Does being left-handed introduce a bias in this kind of studies?

[1] Lucas, H., Chiao, J., & Paller, K. (2011). Why Some Faces won't be Remembered: Brain Potentials Illuminate Successful Versus Unsuccessful Encoding for Same-Race and Other-Race Faces Frontiers in Human Neuroscience, 5 DOI: 10.3389/fnhum.2011.00020

[2] Herzmann, G., Willenbockel, V., Tanaka, J., & Curran, T. (2011). The neural correlates of memory encoding and recognition for own-race and other-race faces Neuropsychologia, 49 (11), 3103-3115 DOI: 10.1016/j.neuropsychologia.2011.07.019

Happy Thanksgiving!!

2011-11-24T00:14:00.000-08:00

Amazing pumpkin carving by artist Ray Villafane.

I know many of you don't live in the US and therefore don't celebrate Thanksgiving (or celebrate it at a different time). Still, I'd like to take the chance to thank all of my featured authors for taking the time to come over and chat with me about their books and science writing. And, most importantly, I'd like to thank each and every one of you for reading, following, tweeting, commenting, liking on Facebook, sending feedback, and actively participating to this blog. In four months I've had 9,500 pageviews, and about 500 unique weekly visits from over 50 different countries!

THANK YOU all and HAPPY THANKSGIVING!

(Even if you don't celebrate Thanksgiving.)