Fixing mitochindrial mutations with targeted mitochondrial RNA import

If you've been reading the blog for a while now, you've heard this many times: not all mutations are deleterious, but the ones that are can increase the risk of certain cancers and diseases. Numerous genetic defects have been attributed to mutations, and mutation in the mtDNA, the mitochondrial DNA, are no exceptions:

"Specific mutations in mtDNA have been implicated in muscular and neuronal disease and in the decline of organ function with aging. Despite a significant need, there are currently no effective treatments for mtDNA alterations [1]".

I've often talked about gene therapy as a way to try and fix defects caused by genetic mutations. The idea behind gene therapy is to introduce the non-mutated gene into the cells so that the production of the healthy protein can be restored. So, a natural question to ask would be: can we use gene therapy to fix mtDNA mutations as well?

Unfortunately the answer is no: if a nuclear encoded protein is mutated, it may fail to assemble correctly in the cytosol and thus it may be prevented from entering the mitochondria correctly.  Fortunately, though, Wang et al. [1] had a different idea.

Back in February I discussed the migration of genes from the organelles to the nucleus and, in some cases, back to the nucleus, a phenomenon that took place throughout evolution. One of the consequences is that in the human genome the majority of mitochondrial proteins are encoded in nuclear genes. I recently discovered that this import/export activity is also true for RNA, tRNAs in particular.

Transfer RNA, or tRNA, is the type of RNA that pairs a complementary triplet (anti-codon) with each of the mRNA coding triplets (codon) as specified by the set of rules of the genetic code. This helps to place the corresponding amino acid into the right position of the protein sequence, as illustrated in the following figure from Wikipedia.

In their March PNAS paper, Wang et al. note:

"A subset of nucleus-encoded tRNAs is imported into the mitochondria of almost every organism. The number of imported tRNAs ranges from one in yeast to all in trypanosomes [protozoa] [. . .] The nucleus-encoded RNAs in the mitochondrion have potentially diverse import pathways, but the details of these pathways and import mechanisms are still being revealed."

Wang and colleagues asked the following question: could we use this naturally happening import activity to import healthy RNA into the mitochondria and "fix" mitochondrial mutations?

First, they made sure that the tRNAs they were going to use to "fix" the mutations were correctly imported into the mitochondria. In order to do so, the researchers appended a sequence, called RP sequence, to the 5' end of the RNAs. They observed, both in vitro and in vivo in mouse models, that

"Only mt-RNA precursors with the appended RP sequence were efficiently imported into isolated mitochondria."

In vivo, they generated expressions of the hCOX2 gene, with and without the RP import sequence, and introduced them in mouse cells.

"Cells expressing RP-hCOX2, but not hCOX2, nucleus-encoded mtRNA showed mitochondrial transcript import and hCOX2 protein translation within mitochondria, indicating that the RP import sequence also is required and functions with coding mtRNA in vivo."

Summarizing, the RP sequence functions as a "driver" that directs the RNA into the mitochondria and, once there, the RNA is indeed translated and the corresponding protein expressed.

Wang et al. applied all of the above to a cell line that harbors two mutations. Both mutations cause an inefficiency in tRNA translation, which results in defective cell respiration. Remember, tRNA is what defines the protein primary structure out of the "instructions" handed over by the mRNA. So, if there's not enough tRNA, not enough proteins are made, and that usually isn't a good thing. Though a complete recovery was not expected, as the mutant mt-tRNAs are still present, not substituted, the imported wild-type mt-tRNAs with three elements expressed (the extended stem, the RP sequence, and MRPS12 3' UTR -- see paper for details) were able to partly restore the respiratory defect caused by the mutations.

Compared to previous methods, this approach is innovative because it doesn't require the introduction of non-native TRNAs with foreign protein factors.

"Rationally engineered human mitochondrial tRNAs and mRNAs can both be efficiently targeted and functional. The fusion RNA presequences are encoded in the nuclear genome and can be imported into mitochondria where they are processed, restore translation, and are degraded via normal pathways in the mitochondrion."

[1] Wang, G., Shimada, E., Zhang, J., Hong, J., Smith, G., Teitell, M., & Koehler, C. (2012). Correcting human mitochondrial mutations with targeted RNA import Proceedings of the National Academy of Sciences, 109 (13), 4840-4845 DOI: 10.1073/pnas.1116792109

How we see it -- a photobook to celebrate beauty

The wonderful artist and photographer Beth Akerman has put together a photobook featuring the work of 33 female photographers. Well, I should rephrase: 32 photographers and a wannabe! I am so honored to have my pictures bound together with the wonderful work of what I consider the most talented lady photographers on G+. The book is titled How we see it because it celebrates the world "as we see it." We all have a different take, a different style, a different philosophy and one goal: share the beauty around us through our images.

The book is available for purchase from Blurb and the proceedings will be donated to http://loveyourbody.nowfoundation.org/ an organization that deals with body image and eating disorders.

The above is one of the images I shared for the book. Below is the cover of the book and the link to buy or preview the book.

How We See It....

A Celebration of Di...

By Compiled by Beth ...

Book Preview

Towards a new era of synthetic genetics

NOTE: this is a short post since this particular study has already been extensively discussed all over the scientific blogosphere, see for example this post. Here I just want to give a very general overview for those who may have not yet heard about this. I think my writer friends in particular will be extremely intrigued by this news.

In life as we know it, the storage and propagation of genetic information relies on two molecules: RNA and DNA. Both are made of building blocks called nucleotides, which are in turn composed of a nitrogenous base, a five-carbon sugar, and one phosphate group. The sugar in the RNA nucleotide is called ribose, and the one in the DNA nucleotides deoxyribose.

Most likely, the very first forms of life had RNA only. Being a single stranded molecule, it is less complex than DNA, but also less stable. As life became more complex, it evolved towards a more complex molecule. But have RNA and DNA always been the only two existing molecules capable of heredity and evolution?

In order to address the question, Pinheiro et al. [1] studied six new molecules (XNAs, for xeno nucleic acids) with the capability to store and propagate genetic information. The molecules were obtained using alternative sugar-like components in lieu of the five-carbon sugar. Synthetic nucleic acids are only the starting point. The key point the researchers had to address was: can these be synthesized back and forth from DNA? Because you see, the way genetic information is stored and passed on is through back and forth transcription between DNA and RNA so that proteins can be made.

Indeed, Pinheiro et al. engineered special polymerase enzymes able to do exactly that: reverse transcribe XNA into DNA and, viceversa, forward transcribe DNA into XNA.

"All six XNAs studied by Pinheiro et al. bind to complementary RNA and DNA and are resistant to degradation by biological nucleases. Construction of genetic systems based on alternative chemical platforms may ultimately lead to the synthesis of novel forms of life [2]."

I can see the imagination of a few people out there running wild. Yes, it is indeed wild. Think of the possibilities. Pinheiro and colleagues call this field of synthetic genetics a "route to novel sequence space."

Of course, this is just a first step. Let's not forget that life as we know it took billions of years to evolve from those first molecules of RNA. In my previous post I quoted Waddington's metaphor who compared the evolution and diversification of cells to marbles rolling down a rugged landscape. Gravity is the driving force and the pits and inclines are the constraints. What is to happen, though, if we, humans, start changing this landscape?

[1] Pinheiro, V., Taylor, A., Cozens, C., Abramov, M., Renders, M., Zhang, S., Chaput, J., Wengel, J., Peak-Chew, S., McLaughlin, S., Herdewijn, P., & Holliger, P. (2012). Synthetic Genetic Polymers Capable of Heredity and Evolution Science, 336 (6079), 341-344 DOI: 10.1126/science.1217622

[2] Joyce, G. (2012). Toward an Alternative Biology Science, 336 (6079), 307-308 DOI: 10.1126/science.1221724

Canalization and epigenetic landscapes: if horses and rhinoceroses share the same ancestor, why don't we have rhinohorses?

A concept that has always puzzled me is: how do new species arise? Of course, you're thinking, mutations accumulate, until you produce a brand new organism. But if that's the case, why don't we see human-monkey hybrids, or rhinohorses, or . . . you get the picture. What puzzles me is where do the intermediate steps between two closely related species go? There are so many mutations that make one species diverge from another, yet you don't see one organism for each new mutations that arises. You see the endpoints. What happens in the middle? At the DNA level you see all shades of gray, but at the species level all you see is black and white (horse or non-horse). Why aren't those mutations expressed in new organisms as things progress from rhinoceros to horses, for example?

I don't know if there's only one answer to this question, but what really helped me clarify the issue were the concepts of epigenetic landscape and canalization.

The expression "epigenetic landscape" was coined by British developmental biologist Conrad Hal Waddington (1905-1975). He compared gene regulation during development to marbles rolling downhill towards a wall. As cells differentiate, the different cell fates are represented by the lowest points in a landscape made of several pits, some lower than others. Waddington also coined the expression "canalization" to describe the ability of organisms to produce the same phenotype against genetic and environmental variations.

Let's understand this better. I often talk about mutations, genetic variation, and how mutations can cause diseases or increase the risk of disease. At the same time, there are mutations that have no effect whatsoever. The math geeks out there will appreciate this metaphor: genotypic variation is not in a 1-1 correspondence with phenotypic variation. In fact, there are phenotypic traits that do not change despite genetic and/or environmental changes.

"There seems to be a strong robustness of some phenotypes against genetic and non-genetic change or perturbation. More generally, the amount and quality of phenotypic variation can differ dramatically within and among populations. Some traits are highly invariant within species while simultaneously being highly variable among closely related species; other characters seem to be highly conserved among species or clades [1]."

On the one hand, canalization provides a buffer to phenotypes that are optimized in terms of fitness against genetic and environmental variation, making them more robust and stable. On the other hand, it allows for non-expressed genetic variation to accumulate: since it's not expressed, there's no selection, hence it persists in the population. So, even when a species "looks" homogeneous, it doesn't mean it's actually genetically homogeneous. There are underlying genetic differences that do not affect the phenotype. To me this represents a "hidden reservoir" of genetic variability. So long as the phenotype is fit, it is convenient to keep it that way. But once a selective sweep takes place, epigenetic changes take place and are likely to act differently on different genomes, thus providing a phenotypically homogeneous population with the potential for genetic change.

"The cryptic pool of genetic variation accumulated under canalization can be phenotypically expressed again if genetic or environmental change uncovers the silent genetic variation, thereby increasing phenotypic variation in the population. Decanalizing conditions can be due to environmental perturbations that change environment-dependent gene expression or allele substitutions that render canalizing mechanisms nonfunctional."

So, you see what's happening: when a certain phenotype is stable and fit, it doesn't mean it's not changing genetically. It is, but there's a buffering mechanism that prevents the genetic changes to be expressed. It's like a marble trying to get out of a pit: it rolls around the lowest point, and small perturbations will make it roll higher or lower along the walls of the pit. In order to make it out of the pit, it needs a big perturbation, one large enough to provide energy to make the jump. That's when the cryptic variation suddenly becomes expressed and forms a new species.

I'm sure biologists are raising their brows at me, as there are probably better and more technical ways to say this, but I wanted to express it in simple words.

Now to a more deeper look, for those of you who are interested in a bit more technicalities: what are the molecular mechanisms of canalization? In other words, what prevents genetic and environmental changes to affect the phenotype of an organisms?

"The proximate (molecular) mechanisms causing canalization, as well as the nature of the perturbations, can be manifold. For example, the canalizing mechanisms can potentially be located at any level of the biological hierarchy, from gene expression, RNA stability, protein structure and folding, intermediate metabolism and physiology to morphology, behavior, and life-history traits."

Furthermore, stability in one trait may depend on the variability of other traits, and the buffering may indeed involve complex epistatic pathways. In simpler words: a change in one locus may involve other genes whose expression needs to change in order to maintain the phenotype despite the change. This makes canalization particularly difficult to measure because not only it's not always obvious at what level the regulatory mechanisms are taking place, but also how many genes or loci it actually involves.

[1] Flatt T (2005). The evolutionary genetics of canalization. The Quarterly review of biology, 80 (3), 287-316 PMID: 16250465

 

Four decades of computational genomics.

"Every genome is the result of a mostly shared, but partly unique, 3.8-billion-year evolutionary journey from the origin of life. Diversity is created mostly by copy errors during replication."

The above is taken from a review in the latest issue of Science [1] that summarizes the progress made in the field of computational genomics since the first sequences obtained back in the mid-seventies. I highly recommend reading the review. Here, I'd like to highlight a few relevant points.

Zerbino, Paten, and Haussler summarize nicely the different types of DNA edits that over those 3.8 billion years have brought us the genetic diversity we observe today. Replication copy errors give rise to single-base changes that can get fixed in the entire population (substitution) or can be present in only part of the population (single-nucleotide polymorphisms). Multiple sequential bases can be duplicated or erased, in which case we talk about indels. Rearrangements can occur, leading to changes in gene copies or even chromosome numbers.

There's so much more to a DNA sequence than just a string of four letters. Genes are not fully understood until you look at their history throughout evolution and throughout the single individual's life, their regulatory mechanisms, their interactions with other genes (epistasis), their epigenetic pathways, their function, etc. With this in mind, computational genomics has the arduous task of not only efficiently store and retrieve the enormous amounts of data, but also build models that encompass epigenetic mechanisms, metabolic pathways, and gene regulatory networks.

"Combining evolutionary, mechanistic, and functional models, computational genomics interprets genomic data along three dimensions. A gene is simultaneously a DNA sequence evolving in time (history), a piece of chromatin that interacts with other molecules (mechanism), and, as a gene product, an actor in pathways of activity within the cell that affect the organism (function). [. . .] Beyond the basics of storing, indexing, and searching the world's genomes, the three fundamental, interrelated challenges of computational genomics are to explain genome evolution, model molecular phenotypes as a consequence of genotype, and predict organismal phenotype."

Genomic evolution is studied using phylogenetic analyses. This presents its challenges, starting from finding optimal ways to align the sequences: in order to compare different sequences, one has to make sure that there is a one-to-one correspondence between each base in each sequence, as shown in the figure below.

Once aligned, one builds phylogenetic trees in order to represent the evolutionary history of the sequences: from the leaves of the tree all the way back to the root, each node in the tree represents a "coalescent" event in the evolutionary history, in other words the event when two distinct lineages shared a common ancestor.

"When applied to more than two species or to multiple gene copies within a species, phylogenetic methods provide an explicit order of gene descent through shared ancestry. [. . .] Finding the optimal phylogeny under probabilistic or parsimony models of substitutions (and also of indels) is NP-hard, and considerable effort has been devoted to obtaining efficient and accurate heuristic solutions."

Right now algorithms that compute phylogenetic trees are computationally intensive and take a long time to run. As the sequencing technology advances and it's possible to sequence more data, larger regions, and in a more efficient way, the challenge is in making also the phylogenetic analyses more computationally efficient.

The next big challenge computational genomics embraces is predicting causal variants. Whole genome studies have to take to account population stratification due to the fact that we are a relatively young species and, as such, all related. New databases are emerging in order to provide epigenetic context and data, RNA expression, and protein levels. All this needs to be folded in in order to make causal predictions from genotype to phenotype.

The coming together of all this information will benefit medical research on multiple levels. Since nearly all cancers are caused by genetic modifications, computational genomics will help us understand cancer therapeutics and tumorigenesis. Stem cell research will also benefit from progress made in computational genomics as it involves the full understanding of variants and their effects not just on the genome, but also on the epigenome and gene expression.

"To face the challenges of obtaining the maximum information from every sequencing experiment, we must borrow advances from a spectrum of different research fields and tie them together into foundational mathematical models implemented with numerical methods. There is a tension between the comprehensiveness of models and their computational efficiency. [. . .] As a common language develops, shaped by our increasing knowledge of biology, we anticipate that computational genomics will provide enhanced ability to explore and exploit the genome structures and processes that lie at the heart of life."

[1] Zerbino, D., Paten, B., & Haussler, D. (2012). Integrating Genomes Science, 336 (6078), 179-182 DOI: 10.1126/science.1216830

The molecular evolution of the senses

Last week we learned that vertebrates react to smells and tastes using G-protein-coupled receptors (GPCRs), a family of proteins that "sense" molecules outside the cell surface and, depending on the molecule, activate a series of cascade events inside the cell which triggers the appropriate cellular response. This is how we distinguish good flavors from bad flavors and similarly with smells.

We also learned that tastes are not always shared across species. In fact, the genes that encode GPCRs have been turned on and off throughout evolution multiple times, allowing for example some species to be sensitive to certain tastes or smells or colors, while others aren't. How do we know?

The molecular evolution of sensory systems can be retraced by looking at two things in particular: (1) the multigene families that encode the smell, taste, and pheromone receptors; (2) pseudogenes, the remnants of once functional genes that have been silenced and/or replaced by new genes. I've talked about pseudogenes in older posts (look here and here). The DNA is often redundant and gene duplication events occur relatively frequently throughout evolution. Sometimes a copy carries a mutation that, if advantageous, may be picked up by a selective sweep. When that happens, the older, now redundant copy gets silenced and becomes a pseudogene -- a no longer coding portion of DNA. Through phylogenetic analyses, researchers can determine when these genes lost their functionality and understand how senses have evolved across species.

In [1] Emily Liman gives a beautiful example with vision: the photoreceptors in our eyes contain photopigments consisting of a GPC receptor called opsin. Humans, apes, and some primates have three distinct types of opsin, each able to maximally absorb either blue, red, or green light. This makes our vision trichromatic. Other animals like rodents, instead, are dichromatic: they only have two kinds of opsins, which maximally absorb either blue or red/green. Now, it turns out, the green opsin gene is nearly identical to the red opsin gene, making it likely that one derived from the other through a duplication event. On the other hand, humans have completely lost the capacity to detect pheromones, which is the function of the vomeronasal organ. The GPCRs in the vomeronasal organ are encoded by two gene families called V1R and V2R. Mice have 165 functional genes in the V1R family and 61 in the V24, whereas humans have 4 possibly functional genes in the former and none in the latter. However, we have roughly 200 pseudogenes in the V1R family, indicating that at some point in our evolutionary history these genes underwent a loss of function. Computational methods show that the loss of vomeronasal functionality in human evolution happened 25-40 million years ago, which happens to be the same timeline as to when trichromacy appeared.

"Interestingly, this is the same time when trichromacy appeared, suggesting that visual signaling may have replaced pheromone signaling. Indeed, catarrhine primates show prominent female sexual swelling and other sexual dimorphisms, which provide a visual signal of reproductive and social status. Thus, it is likely that as primates began to rely on these signals over chemical signals, the vomeronasal organ became redundant, and selective pressure was relaxed on molecules it uniquely expresses."

Similar observations can be made about the olfactory receptor genes: humans have 802 genes, of which ~50% are pseudogenes, versus the 25% of the 1,391 genes in the mouse, indicating that at some point in our evolutionary history selection on these genes was relaxed.

There have been evolutionary changes in taste sensation as well, and typically these changes reflect adaptive changes in diet.

"Taste allows animals to determine the nutritive content of food before ingestion: of the five identified taste modalities, three (sweet, umami, and salty) signal the presence of essential nutrients and lead to ingestive behavior. The other two modalities, bitter and sour, signal the presence of toxins or the spoilage of food, respectively, and, to most animals, are aversive."

Genes encoding the sweet receptors are well conserved across all land vertebrates with the exception of cats, whose sweet receptor T1R2 is a pseudogene (and therefore non-functional). three of the bitter receptors have become pseudogenes in humans and, furthermore, a polymorphism has been reported in the population which affects the way some of us perceive a molecule called phenythiocarbimide. This variation was also found in chimpanzee, which makes the polymorphism predate the divergence of the two species.

In conclusion,

"Expansion of the number of genes encoding sensory GPCRs has, in some cases, expanded the repertoire of signals that animals detect, allowing them to occupy new niches, while, in other cases, evolution has favored a reduction in the repertoire of receptors and their cognate signal transduction components when these signals no longer provide a selective advantage."

[1] Liman, Emily R (2006). Use it or lose it: molecular evolution of sensory signaling in primates Pflugers Arch. , 2 (453), 125-31 DOI: 10.1007/s00424-006-0120-3

Cats (and other carnivores) don't have a sweet tooth, they have a sweet pseudogene

Cats are insensitive to sweetness. Like all vertebrates, they react to smells and tastes using G-protein-coupled receptors (GPCRs), a family of proteins that "sense" molecules outside the cell surface. Depending on the molecule, GPCRs activate a series of cascade events inside the cell that triggers the appropriate cellular response.

There are five distinct flavors: sweet, salty, bitter, sour, and umami. We have different GPCRs for each different taste, and each group is encoded by a family of genes. Differences in taste perceptions reflect differences in these genes. For example, the genes encoding for the bitter taste receptors vary in sequence and number across species, most likely reflecting the ability of a certain species to detect foods that are toxic or harmful to them. Another family of genes, Tas1r, mediates the sweet taste, and one gene in particular, Tas1r2 is a psedugene in cats, which explains why they have lost the sweet taste receptor.

I've talked about pseudogenes in older posts (look here and here): the DNA is often redundant and gene duplication events occur relatively frequently throughout evolution. Sometimes a copy carries a mutation that, if advantageous, may be picked up by a selective sweep. When that happens, the older, now redundant gene copy gets silenced and becomes a pseudogene -- a no longer coding portion of DNA.

Back to cats: the fact that they possess Tas1r2, one of the genes encoding the sweet taste receptor, indicates that some "cat ancestor" had the fully functional gene and hence could detect sweet tastes. However, at some point down the line, the gene turned into a pseudogene and lost its functionality, making cats insensitive to sweet foods. Is this unique to cats? Many carnivores that have atrophied taste systems swallow their food whole and seem to be also likely to have pseudogenized taste GPCR genes (causing them to be insensitive to certain tastes). That's one of the hypothesis posed by Jiang and colleagues in a recent PNAS paper titled "Major loss in carnivorous mammals" [1].

"We found that seven of the 12 species examined from the order Carnivora -- only those that feed exclusively on meat -- had pseudogenized Tas1r2 genes as predicted. Furthermore, we confirmed our hypothesis that, in addition to the loss of Tas1r2, both the sea lion and bottlenose dolphin lack Tas1r1 and Tas1r3 receptor genes, suggesting an absence of both sweet and umami taste-quality perception. Additionally, we failed to detect intact bitter receptor genes Tas2rs from the dolphin genome, suggesting that this modality may be lost, or its function greatly reduced, in dolphins. Thus, taste loss is much more widespread than previously thought, and such losses are consistent with altered feeding strategies."

Jiang et al. sequenced Tas1r2 from 12 species within the Carnivora order and found that 5 had an intact gene, whereas 2 (the sea lion and the fur seal) had a mutation in the start codon (the first bit of the gene) that prevents it from being translated, making the gene no longer functional. Additional deletions in Tas1r2 lead into thinking that it has turned into a pseudogene in these two species. The Pacific harbor seal Tas1r2 revealed a frameshift mutation (a disruption in the "coding" into amino acids) and several early stop codons that would cause the relative mRNA to be incomplete and hence the gene defective. Similar off-reading-frame disruptive mutations were found in the remaining species (Asian small-clawed otter, spotted hyena, fossa, bottlenose dolphin, and banded linsang). With the exception of the sea lion and fur seal, none of the mutations disrupting the reading frame were shared between species. This is interesting, as it seems to indicate that the loss of functionality in Tas1r2 happened independently many times during the evolution of these Carnivora species.

They also did a phylogenetic analysis using Tas1r2 sequence data from 18 Carnivora species, of which 8 had a pseudogenized Tas1r2, and 10 had an intact one, and finally compared taste preferences between small-clawed otters (which have a defective Tas1r2) and spectacled bears (which, instead, have an intact Tas1r2). The statistician in me couldn't help but notice that they had only 2 otters and only 4 bears -- the small sample size red light went off in my head. That said, they saw that the otters saw no preference for sugar, whereas the bears showed a strong preference for both natural sugars and noncaloric sweeteners (hey, you never know, even bears may want to save a few calories here and there so they can indulge in others!). With the exception of cats, this was the first study to test taste preferences in animals with a defective Tas1r2.

Jiang, P., Josue, J., Li, X., Glaser, D., Li, W., Brand, J., Margolskee, R., Reed, D., & Beauchamp, G. (2012). From the Cover: Major taste loss in carnivorous mammals Proceedings of the National Academy of Sciences, 109 (13), 4956-4961 DOI: 10.1073/pnas.1118360109

Avian flu papers will be published!

Apologies if you've heard about this already, I was away last week and I'm slowly catching up.

The members of the National Science Advisory Board for Biosecurity (NSABB) finally gave the green light for the two papers on the avian flu virus to be published in full in Science and Nature respectively. I originally discussed the issue in this post, and you can read about the update here. Basically, the two papers independently showed that an artificially mutated strain of H5N1 (the so-called avian flu, a highly pathogenic flu strain, under normal conditions transmissible only through contaminated fluids) could be transmitted through aerosol (not just fluids) in ferrets. Back in December, the NSABB had recommended not to publish the papers in full, and in particular to redact the data on the mutations that conferred the new transmission route to the virus.

Security issues aside, which I have already discussed, the part that struck me about the Science news story [1] is this:

"The original papers were typical Science and Nature papers: very brief, short on detailed discussion, little to no information on biosafety/biosecurity/mitigation, and perhaps even a little sensational," says NSABB member Lynn Enquist, a molecular biologist at Princeton University. Fouchier's original paper, in particular, was somewhat misleading, several NSABB members told Science. [. . .] Fouchier agrees that his original 2500- word Science manuscript was "not as clear and as explicit as it could have been if we had been given another couple of hundred words."

It's an issue I am very sensitive to because even though I understand high-profile journals like Science need to keep a word limit, we (authors) often struggle to meet this limit and have to sacrifice clarity in order to keep the report concise. Invariably, the reviewers come back with confused comments. I don't have a solution to this, but it is a problem. In this particular case, the solution was to allow Fouchier and colleagues extra words to present the data.

The other statement I'd like to highlight is one NSABB member Michael Imperiale of the University of Michigan Medical School in Ann Arbor made, also reported in [1]:

"What it came down to for me ... [is that there] might be a risk to not publishing."

Something I completely agree with. Sharing the data will motivate more funding into this type of research and more surveillance.

[1] Cohen, J., & Malakoff, D. (2012). On Second Thought, Flu Papers Get Go-Ahead Science, 336 (6077), 19-20 DOI: 10.1126/science.336.6077.19

The emergence of new bacterial lineages

Bacterial speciation is somehow a mystery given that bacteria reproduce asexually, in other words, they don't have the benefit of genetic cross-overs to ensure enough genetic diversity in the new generations. So how do they achieve enough genetic diversification to ensure new speciation? Horizontal gene transfer is one way, and since it is not restricted to exchanges within species, it does achieve highly divergent traits.

Bacteria can exchange genes (often in the form of plasmids, circular bits of DNA), through bacterial conjugation, and this mechanism is thought to play a fundamental role in developing drug-resistant strains. Though gene-specific selective sweeps have been observed in bacterial populations (a gene allele that increases the fitness and hence prevails over the other alleles until it becomes the only allele in the population), this does not reconcile well with the current mathematical models of bacterial diversification, which seem to favor whole-genome sweeps rather than single-gene ones. A new Science study [1] shows that ecological differentiation between two recently diverged populations of bacteria is more similar to sexual differentiation than previously predicted by mathematical models. As Shapiro et al. conclude in their abstract:

"These findings reconcile previous, seemingly contradictory empirical observations of the genetic structure of bacterial populations and point to a more unified process of differentiation in bacteria and sexual eukaryotes than previously thought."

Shapiro et al. sequenced whole genomes from two populations of ocean bacteria called Vibrio cyclitrophicus. They obtained 20 isolates, 13 from one lineage (called "L") and 7 from the second lineage (called "S"). The two lineages show evidence of recent ecological differentiation, but they also present over 99% average amino acid identity, making it an ideal framework for identifying recombination events.

"Our proposed evolutionary scenario is based on three lines of evidence: (i) Most of the genetic divergence between ecological populations is restricted to a few genomic loci with low diversity within one or both of the populations, suggesting recent sweeps of confined regions of the genome. (ii) We show that only one of the two chromosomes constituting the genome has swept through part of one population. (iii) The most recent recombination events tend to be population specific but older events are not, reinforcing the notion that these populations are on independent evolutionary trajectories, which may ultimately lead to the formation of genotypic clusters with different ecology."

Based on the above observations, Shapiro et al. conclude that the two lineages under study came from a common and ecologically homogeneous population. They observed recently acquired, habitat-specific genes and a decrease in recombination events between populations, leading the two lineages to a recent divergence in protein-coding genes due to the different environments. By extrapolating this emerging trend, the researchers predict that the two lineages will eventually form genetically distinct clusters.

"Thus, a mechanism of gene-centered sweeps may eventually lead to a pattern characteristic of genomewide sweeps. In this way, our study of the very early stages of ecological specialization has provided a simple resolution to seemingly conflicting empirical observations."

[1] B. Jesse Shapiro, Jonathan Friedman, Otto X. Cordero, Sarah P. Preheim, Sonia C. Timberlake, Gitta Szabó, Martin F. Polz, & Eric J. Alm1 (2012). Population Genomics of Early Events in the Ecological Differentiation of Bacteria Science , 336 (6077) DOI: 10.1126/science.1218198

Renato Dulbecco, February 22, 1914 – February 19, 2012

Last February 19 Nobel laureate Renato Dulbecco died at age 97. Dulbecco
discovered how viruses integrate their genomes into host cells, something I've often talked about when describing the HIV life cycle. Dulbecco was mostly interested in oncoviruses, (viruses that have the potential to trigger tumors) and, in particular, the molecular mechanisms through which this could happen. He studied a virus called SV40, or simian virus 40, a polyomavirus that infects both monkeys and humans. He was also among the scientists that launched the Human Genome Project.

Over about a decade between the late '50s and the late '60s, Dulbecco and his group showed that SV40 contains DNA in a circular form and that the virus is able to permanently integrate its DNA in the cellular DNA, forming what is called a provirus. Interestingly, they found that the virus could grow in certain cell cultures, but did not grow in others, where instead it induced a cancer-like state. Dulbecco was fascinated by how the virus could achieve this as he believed the key to this mechanism could shed light on tumorigenesis in general.

In cells where the virus does not replicate, the integrated viral DNA expresses one protein in particular, the "T antigen," which the virus uses for replication. The T antigen alters the cell's replication cycle (for example by inactivating the p53 tumor suppressant proteins) favoring cell replication. Since the viral DNA is integrated in the cell's DNA, by promoting DNA replication, the virus ensures its own replication. As this happens, though, mutations start accumulating increasing the likelihood of the cell line becoming carcinogenic. In other words, it's the accumulation of mutations that eventually leads to cancer.

What about HIV? HIV is an RNA virus, not a DNA virus like SV40, and yet it uses the same mechanism that SV40 uses to replicate: integration into the host's DNA. HIV achieves this by first transforming its RNA into DNA through an enzyme called reverse transcriptase. It was Howard Temin, a graduate student in Dulbecco's laboratory, who did his Ph.D. thesis on another oncovirus, the Rous sarcoma virus, that realized that this RNA virus was able to alter the host cell DNA (edited after Dr. Racaniello's comment below). This finding led to the discovery, a few years later, of the reverse transcriptase enzyme, for which Howard Temin, David Baltimore, and Renato Dulbecco shared the 1975 Nobel Prize in Medicine (David Baltimore made the same discovery independently).

Dulbecco R (1973). Cell transformation by viruses and the role of viruses in cancer. The eleventh Marjory Stephenson Memorial Lecture. Journal of general microbiology, 79 (1), 7-17 PMID: 4359401

Canyonlands, Utah

Last pic... tomorrow I'll go back to science, promise! :)

Monument Valley

The "Mittens."

Dead Horse Point

It's April already and I've managed to come down with one of my epic colds, so I'm taking a break from regular posting. To make it up to you guys, I leave you with this photo of the Colorado River in Utah. This was taken in Dead Horse State Park, Utah. Hope you like it!