Mystery Rays from Outer Space

I’ve talked about quasispecies several times, and emphasized that RNA viruses, with their high replication error rates, are most prone to forming quasispecies.

I’ve also pointed out, though, that actually measuring quasispecies is technically difficult, and measuring it for the larger DNA viruses would be even harder. You’d need to run sequences on many viral genomes, to see how much variation develops over time; and it’s only recently that sequencing tech has approached the point where it’s even thinkable, let alone affordable, to do that:

While large DNA viruses are thought to have low mutation rates, only a small fraction of their genomes have been analyzed at the single-nucleotide level.¹

So maybe DNA viruses might actually form quasispecies, and we don’t know it?

In fact, even for DNA viruses, mutants appear fairly quickly, given the appropriate selection pressure. In principle, these might not even be new mutations, but simply expansion of a particular part of a quasispecies that was already pre-existing. (It’s probably a fairly obvious point, but it’s important to remember that the introduction of new mutants, and their selection and expansion, are completely different processes. Some viruses throw out incredible numbers of mutants, but almost all of them are dead ends that are actively selected against, or at the least not selected for. Other viruses may make far fewer mutants, but given strong enough selection pressure some of these might rapidly take over the population. It’s very tricky to use observed mutations as a measure of mutation frequency, because observation often depends on selection to build up the numbers of the mutant before you can see it.)

At any rate, it’s a fair enough question,² but recently there has been some evidence that supports the concept of DNA virus genome stability. Wayne Yokoyama’s lab has actually sequenced multiple genomes of mouse cytomegalovirus (a large DNA virus — a member of the herpesvirus family) to look at quasispecies.¹

One of the things they did find was a significant number of variations in their stock, compared to the stock they had got it from years before:

… our laboratory’s Smith strain MCMV differed from the previously published Smith strain … There were 452 differences, including 50 insertion/deletions (indels) and 402 single-bp substitutions. … this high number of differences suggested that MCMV mutated in vivo, as we had previously maintained our MCMV stock by in vivo passages. ¹

In other words, the standard methods of maintaining a virus — repeatedly growing new stocks in cells, and using those new stocks to make yet more — allow the accumulation of variations in the genome — which is already well known, of course, but often neglected in lab experiments.  Again, as I point out above, the number of observed mutations we see here doesn’t tell us much about the actual mutation frequency.

How often do mutations arise? By running the virus through cells repeatedly (in vitro, that is) and then seeing how individual clones differed, they determined that there are very, very few mutations per replication. What’s more, and even more impressively, very few mutations appeared after passages through mice (in vivo):

… the remaining 9 mutations allowed us to estimate the mutation rate of MCMV as 1.0 x 10^–7 mutations per bp per day after in vivo passage, very similar to the mutation rate calculated for in vitro passage.¹

(My emphasis) For comparison, the MCMV genome is not quite 250,000 bp long, so we’re looking at around one mutation per 40-50 genomes per day (if I’m dividing right). That’s hundreds of times more stable than most RNA viruses (see the table here³ for some RNA virus error rates).  Still, there’s plenty of room for natural selection in there, because of course there are hundreds or thousands of new MCMV genomes being made per day even in the most conservative estimate (and maybe more like millions or hundreds of millions), so dozens to thousands of them are mutants.

So, not surprisingly, Yokoyama’s group was able to detect a cluster of mutations that were almost certainly selected in the mouse; without going into detail, these mutations were in a viral gene (m157) that’s known to be recognized by the (laboratory) mouse immune system, so it wasn’t surprising that mutants were selected. And such mutants did not appear in mice without the appropriate immune component, demonstrating the role of natural selection in this cluster.

They offer a number of cautions, including one that’s raised in almost all such studies:

One caveat to our mutation analysis is that lethal mutations were probably underrepresented in the final DNA pool since, by definition, they did not propagate. Nonetheless, this limitation is intrinsic to all mutation analysis.¹

Still, the results are solid and reassuring, supporting a basic concept in viral evolution.

1. Cheng, T., Valentine, M., Gao, J., Pingel, J., & Yokoyama, W. (2009). Stability of Murine Cytomegalovirus Genome after In Vitro and In Vivo Passage Journal of Virology, 84 (5), 2623-2628 DOI: 10.1128/JVI.02142-09[↩][↩][↩][↩][↩]
2. Well asked, invisible non-existent person![↩]
3. CASTRO, C., ARNOLD, J., & CAMERON, C. (2005). Incorporation fidelity of the viral RNA-dependent RNA polymerase: a kinetic, thermodynamic and structural perspective. Virus Research, 107 (2), 141-149 DOI:10.1016/j.virusres.2004.11.004[↩]

I’ve mentioned the APOBEC family before (for example, here and here). They’re a group of mammalian genes that (among other things) protect against retrovirus infection.

DIfferent strains of mice have different resistance to retrovirus infection. Some strains are highly resistant, others quite susceptible. At least some of this difference in susceptibility comes down to different expression levels of mouse APOBEC3: High expression of the gene gives good resistance to some retroviruses, low expression gives less resistance.

How come some strains have higher expression than others? Turns out that it’s because a retrovirus inserted in the APOBEC3 region of the genome of certain mouse strains, and that insertion cranks up expression of the APOBEC3.

We discovered that the mA3 allele in virus resistant mice is disrupted by insertion of the regulatory sequences of a mouse leukemia virus, and this insertion is associated with enhanced mA3 expression.  ((Sanville, B., Dolan, M., Wollenberg, K., Yan, Y., Martin, C., Yeung, M., Strebel, K., Buckler-White, A., & Kozak, C. (2010). Adaptive Evolution of Mus Apobec3 Includes Retroviral Insertion and Positive Selection at Two Clusters of Residues Flanking the Substrate Groove PLoS Pathogens, 6 (7) DOI: 10.1371/journal.ppat.1000974))

So perhaps low APOBEC expression allowed retrovirus infection, which led to insertion of the retrovirus genome, which increased APOBEC3 expression and provided resistance to further retrovirus infection.

Quasispecies theory predicts that slower replicators will be favored if they give rise to progeny that are on average more fit; these populations occupy short, flat regions of the fitness landscape … Flat quasispecies accept mutation without a corresponding effect on fitness … A flat quasispecies with an expansive mutant repertoire can explore vast regions of sequence space without consequence and is poised to adapt to rapid environmental change.

–Lauring, A., & Andino, R. (2010). Quasispecies Theory and the Behavior of RNA Viruses PLoS Pathogens, 6 (7) DOI: 10.1371/journal.ppat.1001005

(My emphasis)  RNA viruses in general form quasispecies because they have such high mutation rates.  Many (though by no means all) emerging infections are the result of RNA viruses. I’ve pointed before to aspects of viruses that might help them jump from species to species (for example, here — though this is a DNA virus, not an RNA virus, and I don’t think it runs in quasispecies — and the string of posts I link to inside that one).

One example Lauring and Andino point to is influenza virus hemagglutinin (HA). Influenza mutates very rapidly, of course, but most of the changes are harmful to the virus. But changes in HA seem to be very well tolerated. Since HA is a major target of the immune system, this property allows influenza to avoid the immune system without getting hit by defects in fitness associated with the immune evasion.  This is a contrast to, say, HIV (generalizing here! This isn’t always true). HIV within a patient undergoes constant changes to avoid the immune response, but many of these changes reduce the overall viral fitness. If you take the mutated HIV into an environment without that particular immune response, the virus quickly mutates back to its original, more-fit, form.

I’m not sure how we would assess, in advance, which viruses are more “flat” than others and that are therefore more able to adapt to new species, but it’s something to think about as we look at new viruses and new viral variants. I would be interested in SARS, for example — what happened to mutation tolerance as the virus adapted to humans? Was the virus that originally jumped into humans different in this was from the ones that normally infect bats? Not easy to measure, though.

I’ve been going to some influenza-related conferences in the past week, including the International Conference on Emerging Infectious Diseases in Atlanta.  One of the topics that’s come up several times is the public awareness of the 2009 pandemic H1N1 — there’s a general sense that the general public has lost interest in, or even is actively contemptuous of, the influenza pandemic.  This is causing a lot of frustration, and some bafflement, among the fairly specialized audience here.

I don’t have any particular insights into this, but it’s striking to me that there may be some parallel to the vastly worse 1918 pandemic.  Like 2009, the 1918 flu did virtually all its damage in the USA in less than a month, around October of 1918. (The difference, of course, was that in 1918 the virus killed far more of the people it infected.) In spite of the huge number of deaths that virus caused, though, it seemed to quickly recede into people’s memory as well.  I refer you to Alfred Crosby’s history of the outbreak (Amazon link), which is actually called “America’s Forgotten Pandemic: The Influenza of 1918″, for  a much more detailed discussion.

Is there something about these sort of explosive, but short-lived, outbreaks that lets them be easily replaced in peoples’ anxiety closet?

Short comments about what I’ve been reading (besides several hundred influenza articles):

Hedskog, C., Mild, M., Jernberg, J., Sherwood, E., Bratt, G., Leitner, T., Lundeberg, J., Andersson, B., & Albert, J. (2010). Dynamics of HIV-1 Quasispecies during Antiviral Treatment Dissected Using Ultra-Deep Pyrosequencing PLoS ONE, 5 (7) DOI: 10.1371/journal.pone.0011345

The whole deep sequencing thing is going to profoundly change our knowledge of viral pathogenesis, as well as their ecology.

With highly mutation-prone viruses like HIV, hepatitis C virus, or influenza, our understanding of genome sequences has been based on the overall average genome — the average of a vast and diverse population. That average, that we’ve been calling the genome of these viruses, may not even exist as such, and certainly the minor variants that have been missed by traditional methods are also critically important, because they can explode out within a few days to take over the entire population, given the right set of circumstances. For example, if among those minor variants there are a few drug-resistant strains, then as soon as you treat the host, those variants may be able to take over.

In this paper, deep sequencing of people with HIV shows that drug-resistant variants do exist even before treatment, but they are normally very rare. They can take over during treatment with the particular drug, but when treatment is stopped they rapidly regress to rarity. This is presumably because the drug resistance makes the virus globally less fit (in the natural selection meaning of the term). When their more-fit brethren are destroyed by a drug these crippled, but drug-resistant, variants can grow out, but remove that selective pressure and the more wild-type versions take over once again.

As well as implications for treatment, this tells us something about viral reserves:

In most patients, drug resistant variants were replaced by wild-type variants identical to those present before treatment, suggesting rebound from latent reservoirs. ¹

1. Hedskog, C., Mild, M., Jernberg, J., Sherwood, E., Bratt, G., Leitner, T., Lundeberg, J., Andersson, B., & Albert, J. (2010). Dynamics of HIV-1 Quasispecies during Antiviral Treatment Dissected Using Ultra-Deep Pyrosequencing PLoS ONE, 5 (7) DOI: 10.1371/journal.pone.0011345[↩]

I was getting a little concerned and distressed by the lack of evidence for any function of viral MHC class I immune evasion. It’s kind of a relief to see articles demonstrating function coming out.

MHC class I is the target for cytotoxic T lymphocytes (CTL), which are generally believed to be pretty important in controlling viral infection. So when some viruses were shown to block MHC class I in cultured cells, it seemed pretty obvious that this would be a big benefit for the virus. You’d expect these viruses to be exceptionally resistant to CTL, for example.

But when people actually looked in animals (as opposed to in tissue culture), the ability to block MHC class I didn’t seem to do all that much. I’ve summarized some of those experiments here and here. For example, the MHC class I immune evasion genes in adenoviruses and in mouse cytomegalovirus (MCMV) didn’t show much effect on the actual infection at all.¹ Mouse herpesvirus 68 (MHV68) had shown an effect, but not at the time point that you might expect — not early after infection, when CTL are kicking in and clearing virus, but rather later on, during the latent phase.²

We all believed there must be a function, because viruses don’t hang on to genes for millions of years unless those genes are important,³ but I was starting to wonder if perhaps we were looking in the wrong places — whether any immune effects might be spillover from some other function, say. But, as I say, we’re starting to get confirmation that these things really are doing more or less what we’d expected all along.

A little while ago, Klaus Fruh and Louise Pickert showed a significant effect of MHC class I immune evasion in rhesus cytomegalovirus: without that ability new viruses couldn’t superinfect hosts that already carry the virus. ⁴ (I talked about it here.) It’s quite possible — though of course not certain until it’s actually tested — that this is also true for human cytomegaloviruses (which are very closely related to the rhesus version) and for mouse CMV (which are less closely related but in the same family). So now we have functional data for MHC class I immune evasion for representatives of two broad groups of viruses, the betaherpesviruses (the cytomegaloviruses) and the gammaherpesviruses (the MHV68 story).

Now there’s another paper⁵ showing a function for the MHC class I immune evasion ability of HIV (actually for SIV, but again it’s probably true for the closely-related HIV).

HIV has a gene, nef, that can block MHC class I expression. This has been shown in cultured cells, but understanding its relevance in actual infections has been difficult:

Although these data suggest that Nef-mediated immune evasion could play an important role in AIDS pathogenesis, there has been little direct evidence linking disease progression with MHC-I downregulation in vivo. ⁵

Obviously you can’t make a nef-less HIV and just throw it into people to see what happens. Even doing the experiment in monkeys with SIV is complicated by the fact that nef is very polyfunctional — as well as downregulating MHC class I, it also targets a number of other molecules.

But you can take advantage of natural variation, both in the virus and the host.  Nef isn’t equally effective on all MHC class I types, for one thing. As well, nef can develop mutations within the host.  It turns out that rapid disease progression correlates with the extent of MHC class I downregulation, whereas effects on other genes affected by nef (CD3 and CD4) didn’t correlate:

The extent of MHC-I downregulation on SIV-infected cells varied among animals …  the level of MHC-I downregulation on SIV-infected cells was significantly greater in the rapid progressor animals than in normal progressors.  … high levels of MHC-I downregulation on SIV-infected cells are associated with uncontrolled virus replication and a lack of strong SIV-specific immune responses.⁵

This is strictly a correlation study, so we can’t confidently say that MHC downregulation causes disease progression. Still, it’s an interesting finding, and perhaps one that can be followed up in human studies.

1. Gold MC, Munks MW, Wagner M, McMahon CW, Kelly A, Kavanagh DG, Slifka MK, Koszinowski UH, Raulet DH, & Hill AB (2004). Murine cytomegalovirus interference with antigen presentation has little effect on the size or the effector memory phenotype of the CD8 T cell response. Journal of immunology (Baltimore, Md. : 1950), 172 (11), 6944-53 PMID: 15153514
   Only slightly qualified by
   Lu, X., Pinto, A., Kelly, A., Cho, K., & Hill, A. (2006). Murine Cytomegalovirus Interference with Antigen Presentation Contributes to the Inability of CD8 T Cells To Control Virus in the Salivary Gland Journal of Virology, 80 (8), 4200-4202 DOI: 10.1128/JVI.80.8.4200-4202.2006[↩]
2. Stevenson, P., May, J., Smith, X., Marques, S., Adler, H., Koszinowski, U., Simas, J., & Efstathiou, S. (2002). K3-mediated evasion of CD8+ T cells aids amplification of a latent ?-herpesvirus Nature Immunology DOI: 10.1038/ni818[↩]
3. I will admit there’s a certain circular quality to this argument.  ”The gene must be important, because viruses don’t carry unimportant genes.  We know that, because this gene that they’ve hung on to must be important.”[↩]
4. Hansen, S., Powers, C., Richards, R., Ventura, A., Ford, J., Siess, D., Axthelm, M., Nelson, J., Jarvis, M., Picker, L., & Fruh, K. (2010). Evasion of CD8+ T Cells Is Critical for Superinfection by Cytomegalovirus Science, 328 (5974), 102-106 DOI: 10.1126/science.1185350[↩]
5. Friedrich, T., Piaskowski, S., Leon, E., Furlott, J., Maness, N., Weisgrau, K., Mac Nair, C., Weiler, A., Loffredo, J., Reynolds, M., Williams, K., Klimentidis, Y., Wilson, N., Allison, D., & Rakasz, E. (2010). High Viremia Is Associated with High Levels of In Vivo Major Histocompatibility Complex Class I Downregulation in Rhesus Macaques Infected with Simian Immunodeficiency Virus SIVmac239 Journal of Virology, 84 (10), 5443-5447 DOI: 10.1128/JVI.02452-09[↩][↩][↩]

About 15 minutes after I wrote my last article on influenza variation, I was reading the Journal of Virology  and ran across another paper¹ on the same thing, that at least partly addresses some of the missing points in the earlier ones.

To brutally truncate my earlier comments: influenza should generate a huge number of mutants as it replicates; but in the few studies that have been done, not all that many variants have actually been detected.

One of the points I raised was that the influenza variation was sampled at the end-point of the infection — after the patient had died, in the paper I talked about the other day.² Even though the virus had been through the maximum number of replication cycles, it had also experienced the maximal selection pressure, potentially reducing the number of surviving mutants. Is it possible that more variants arose earlier in the infection, but died off before they were detected?

This new paper¹  actually looked at exactly that. They used canine influenza as their model, so they could deliberately infect their patients and track through the infections from the beginning through the end. Even though they used a technique that is much less sensitive to mutations (and is probably more error-prone as well) they found tons of variation, and the pattern they found is fascinating:

Mutations arose readily in the infected animals and reached high frequencies in some vaccinated dogs, but they were mostly transient and often were not detected on subsequent days. Hence, CIV populations are highly dynamic and characterized by a rapid turnover of likely deleterious mutations. ((Hoelzer, K., Murcia, P., Baillie, G., Wood, J., Metzger, S., Osterrieder, N., Dubovi, E., Holmes, E., & Parrish, C. (2010). Intrahost Evolutionary Dynamics of Canine Influenza Virus in Naive and Partially Immune Dogs Journal of Virology, 84 (10), 5329-5335 DOI: 10.1128/JVI.02469-09))

(My emphasis) This (assuming it holds true in other studies) beautifully resolves much of the difference between the expected level of variation, and the level that’s observed at any one time point of infection. The explanation is that the variation does indeed appear, but it doesn’t persist.  There is variation is over time as well as at any one time point.

Figure 1. Variation between challenge influenza virus (yellow) and virus isolated from two naïve dogs 2 to 4 days after infection 1

There are a lot of very cool things about this study that I’m not going to talk about (differences between vaccinated and unvaccinated animals, evidence for antigenic escape) but there are two things that I thought were particularly exciting.

First is the question of why the mutations seem to be so transient. Part of that could just be chance, part of it is probably selection against deleterious mutants.

But it’s also worth keeping in mind that the viruses are replicating in a dynamic, rapidly-changing environment. The virus enters a host whose immune system is at rest but that immediately recognizes viral infection and ramps up interferons,  then other cytokines, then innate antiviral systems that build up and spill over into an adaptive immune response  …  a whole range of inflammation whose mediators and effectors change from hour to hour. Is this changing environment selecting for mutations that are briefly beneficial, and that then become deleterious as the situation changes a few hours later?

Second – when we think about viruses that are able to jump from one species to another, we think usually of mutants, virus that may be less fit in their “proper” hosts but adequately fit in some other species. (In fact canine influenza itself is a great example of this, a virus that jumped from horses into dogs six or seven years ago.  It is essentially equine influenza, but compared to the equine version it has a half-dozen variants that make it more suitable for replication in dogs.)

If we look at any particular time point we may not find any of these potential emergent mutants. But if we look at all the time points, as in this study, perhaps these potential species-jumping mutants are popping up all the time, but only for a few hours at a time:

This observation suggests that mutations that facilitate adaptation to a new host species might occur transiently in the donor host despite any associated fitness costs and provide a transient reservoir of preadapted mutations. ¹

(My emphasis) There’s also theoretical and experimental work that probably addresses how this sort of pressure could drive population-level robustness.  For example, while heterogeneity is linked to fitness in HIV,³ Claus Wilke says:

Virus strains with a history of repeated genetic bottlenecks frequently show a diminished ability to adapt compared to strains that do not have such a history.⁴

I don’t know that work as well as I’d like to, but I think it’s probably relevant when considering local and global evolutionary pressures on the virus.

1. Hoelzer, K., Murcia, P., Baillie, G., Wood, J., Metzger, S., Osterrieder, N., Dubovi, E., Holmes, E., & Parrish, C. (2010). Intrahost Evolutionary Dynamics of Canine Influenza Virus in Naive and Partially Immune Dogs Journal of Virology, 84 (10), 5329-5335 DOI: 10.1128/JVI.02469-09[↩][↩][↩][↩]
2. Kuroda, M., Katano, H., Nakajima, N., Tobiume, M., Ainai, A., Sekizuka, T., Hasegawa, H., Tashiro, M., Sasaki, Y., Arakawa, Y., Hata, S., Watanabe, M., & Sata, T. (2010). Characterization of Quasispecies of Pandemic 2009 Influenza A Virus (A/H1N1/2009) by De Novo Sequencing Using a Next-Generation DNA Sequencer PLoS ONE, 5 (4) DOI: 10.1371/journal.pone.0010256[↩]
3. Bordería AV, Lorenzo-Redondo R, Pernas M, Casado C, Alvaro T, et al. (2010) Initial Fitness Recovery of HIV-1 Is Associated with Quasispecies Heterogeneity and Can Occur without Modifications in the Consensus Sequence. PLoS ONE 5(4): e10319. doi:10.1371/journal.pone.0010319[↩]
4. Novella, I., Presloid, J., Zhou, T., Smith-Tsurkan, S., Ebendick-Corpus, B., Dutta, R., Lust, K., & Wilke, C. (2010). Genomic Evolution of Vesicular Stomatitis Virus Strains with Differences in Adaptability Journal of Virology, 84 (10), 4960-4968 DOI: 10.1128/JVI.00710-09[↩]

Indeed, the amount of HIV diversity within a single infected individual can exceed the variability generated over the course of a global influenza epidemic, the latter of which results in the need for a new vaccine each year. ¹

That was said as part of a discussion on HIV vaccines, but let’s think about it from the influenza side.  Why is it true? Why doesn’t influenza have as many variants as HIV?

(Update: Another paper also looks at this question and points to some interesting explanations; I talk about that paper here.)

We know that influenza, like other RNA viruses, is prone to mutation (that is, it has an error-prone polymerase). Depending how you measure it, it’s likely that almost every new influenza genome has at least one mutation in it, meaning that every new infected animal or person should be be generating thousands upon thousands of new influenza variants.

Globally, of course we do see thousands of new flu variants each year.² But, based on replication fidelity, you’d expect to see a lot more — maybe not quite as many as HIV, but not far from it.

This is also true on a much smaller scale, looking within infected individuals (animals or people).  Even using modern deep-sequencing techniques (like those used in some of the HIV analyses) that should in theory be able to detect large numbers of mutations, there are fewer than you might expect based on the known replication fidelity — far fewer variants than in HIV:

Inasmuch as the mutation rate for type A influenza viruses is estimated at one nucleotide change per 10,000 nucleotide during replication and most infections are caused by as many as 10 to 1000 virions which likely possess varying numbers of nucleotide differences in their genomes, one can expect that each influenza A virion is possibly a quasispecies. However, we identified relatively few quasispecies – probably because the currently available sequence analysis software do not allow robust quasispecies analysis and extensive manual curation is necessary. We believe that with the help of improved bioinformatic tools we would detect more quasispecies populations in our sample sets.  ³

H1N1 (swine-origin influenza virus)

I don’t know enough about the computational side to comment on their bioinformatics point.  Another recent paper⁴ uses a similar approach and (at least at first) seems to reach an more conservative conclusion.  They talk about “quasispecies”, but they seem to be using the term rather loosely, to describe just a handful of distinct genomic sequences. These sequences differ by, for example, a single base (and a single amino acid) in the HA, where one of the sequences was present at about 75% of the sequences, and the other at about 25%. To me that’s not really a “quasispecies” — a quasispecies is something that needs to be defined by an average sequence even though the vast majority of the genomes are different from that average. (Here and here are Vincent Racaniello’s explanations at The Virology Blog.)  Two sequences is just two sequences.

However! The authors do make their data available. I don’t have time to do a detailed look, but from what I think is a very conservative analysis, in one stretch of just 25-40 bases some 5-10% of the genomes have at least one mutation.⁵ If that’s roughly true across the whole genome, then each genome would have, what, maybe a half-dozen mutations on average. That, to me, really is a quasispecies.

(Do note that this is not the mutation frequency for any individual residue. No single point [with the two or three exceptions that the authors focused on] is mutated at much more than one in a thousand, and most probably more like one in many thousand, which is about what you’d expect. )

There are a myriad of complicating factors separating the error frequency in these genomes from the raw error rate of the viral polymerase. A couple of huge ones: These viruses had undergone a bunch of replications in the host – this isn’t the error rate per replication cycle, it’s the cumulative error rate after many cycles. The virus was from a patient who had died with (and probably of) the virus, and though we don’t know how many time the original infecting virus had replicated it was at least a half dozen cycles, perhaps two or three times that.

Influenza virion

On the other hand, during those replication cycles, many mutations (quite likely even the great majority of them) would have been deleterious or outright defective, so most of the mutations would have never propagated but would have just silently disappeared and not been counted at the end.

The most interesting point is that these mutations aren’t arising in a vacuum. Thinking now about which mutations survive and get detected, not the baseline rate of mutation formation: The variants are forming are in an environment that’s designed to be very hostile to viruses. Mutations are going to undergo selection by the immune system.

This is one place where influenza is going to experience a very a different set of pressures than HIV. HIV persists in the presence of the adaptive (T cell and antibody-based) immune response, whereas as the adaptive response kicks in for flu the virus gets evicted. HIV therefore not only have a much longer period (years instead of days) to throw out mutations, it also is shaped by the immune response. By comparison flu would probably only have a couple of replication cycles in the presence of an adaptive response.

Changes in the virus that accumulate over the handful of replication cycles would reflect a strong selection pressure. The vast majority of mutations, even those that aren’t completely defective, are going to be less fit than the original virus and won’t accumulate. Knowing which mutations do accumulate should be very interesting because it may tell us what the virus is going through in the host.  That’s what the authors of this paper focused on — the one particular site that had a much, much higher variant  frequency, more like 25% of the genomes.  The assumption is that this arose during the infection and was positively selected for. ⁶

The variants that replicate best in a host may be quite different from those that are effectively transmitted. That is, there may be multiple sources of selective pressure, of which we have previously mainly only seen transmission pressure (because that’s the main one that will accumulate in a population, because transmission represents a bottleneck in the virus’s evolution [link to The Virology Blog]).  The particular HA variant that was picked up here (that apparently accumulated during the infection) is rare globally. Is that a version of the HA that’s more efficient within a host, but that doesn’t transmit as well?

I think a major reason for the difference between HIV and influenza variant accumulation is the difference between within-host and between-host (transmission) selection.  HIV spends long, long periods within a single host, thousands of replication cycles, accumulating mutations.  The transmission bottlenecks come at much longer intervals and have a much larger accumulated population to work with.  Influenza has a comparatively brief period within the host, only a handful of replications before a new transmission bottleneck hits. ⁷

This sort of deep sequencing experiment on influenza will probably be improved over the next few years, and I’ll be very interested to see just how much variation there really is within on flu-infected host.

1. Walker, B., & Burton, D. (2008). Toward an AIDS Vaccine Science, 320 (5877), 760-764 DOI: 10.1126/science.1152622[↩]
2. More correctly, I suppose, we infer the presence of thousands of new variants based on the hundreds of them that we see, and knowing that we are only examining a tiny fraction of all the flu cases that are out there.[↩]
3. Ramakrishnan, M., Tu, Z., Singh, S., Chockalingam, A., Gramer, M., Wang, P., Goyal, S., Yang, M., Halvorson, D., & Sreevatsan, S. (2009). The Feasibility of Using High Resolution Genome Sequencing of Influenza A Viruses to Detect Mixed Infections and Quasispecies PLoS ONE, 4 (9) DOI: 10.1371/journal.pone.0007105[↩]
4. Kuroda, M., Katano, H., Nakajima, N., Tobiume, M., Ainai, A., Sekizuka, T., Hasegawa, H., Tashiro, M., Sasaki, Y., Arakawa, Y., Hata, S., Watanabe, M., & Sata, T. (2010). Characterization of Quasispecies of Pandemic 2009 Influenza A Virus (A/H1N1/2009) by De Novo Sequencing Using a Next-Generation DNA Sequencer PLoS ONE, 5 (4) DOI: 10.1371/journal.pone.0010256[↩]
5. I extracted the FASTQ data containing the short sequence reads matching influenza sequences from the supplemental PDF, converted it to FASTA, and used xdformat to move it into a BLAST database. Then I grabbed 40 bases from the genbank sequence CY045951.1, the PB2 segment of the closest-match influenza strain, choosing a region (positions 2151-2190) with very high coverage, and BLASTed this sequence against the short sequence data, using parameters such that I retrieved sequences that match at least 25 of 40 positions.  Of the  ~2050 hits I retrieved, about 120 had at least one internal mismatch. I can’t distinguish these from sequencing errors, but I think it’s much higher than you’d expect from sequencing error.  And I hope that my conservative approach (for example, I would have discarded mismatches at the ends of the hits) would balance out that source of confusion. [↩]
6. One point, by the way, that the authors didn’t cover was the possibility that this patient had actually been initially infected with more than one viral sequence.  We do know that a significant number of flu cases are doubly infected. The fact that the minor variant is a very unusual strain makes this less likely, but not impossible.[↩]
7. And I think it’s fair to say that the global population-based HIV variation — the transmission-selected amount of variation, as opposed to the vast within-individual variation — is rather more comparable to that of influenza.[↩]

Rotaviruses are one of the most common causes of gastroenteritis in children.  A new rotavirus vaccine was introduced a few years ago; what impact has it had on disease?

This study confirms on a national scale that the 2008 rotavirus season among children aged <5 years was dramatically reduced compared to pre-RV5 seasons.  …  Based on the observed decrease during the 2008 season, we estimated that ~55,000 acute gastroenteritis hospitalizations were prevented during the 2008 rotavirus season in the United States. A decrease of this magnitude would translate into the elimination of 1 in every 20 hospitalizations among US children aged <5 years.¹

(My emphasis)

Here’s what that looks like:

Interestingly, the reduction in gastroenteritis wasn’t only in vaccinated children:

In 2008, acute gastroenteritis hospitalization rates decreased for all children aged <5 years, including those who were either too young or too old to be eligible for RV5 vaccination. …These findings … raise the possibility that vaccination of a proportion of the population could be conferring indirect benefits (ie, herd immunity) to nonvaccinated individuals through reduced viral transmission in the community¹

(My emphasis, again)

Assuming this continues to hold up (and similar studies² have found similar large reductions) it’s a striking example of herd immunity.

(Added later: The vaccine this paper looked at was RotaTeq.  This is not the vaccine that was recently found to be contaminated with porcine circovirus genomic fragments; that was the other rotavirus vaccine, Rotarix.)³

(Second update: RotaTeq apparently also is contaminated with porcine circovirus genomic fragments.)

1. Curns, A., Steiner, C., Barrett, M., Hunter, K., Wilson, E., & Parashar, U. (2010). Reduction in Acute Gastroenteritis Hospitalizations among US Children After Introduction of Rotavirus Vaccine: Analysis of Hospital Discharge Data from 18 US States The Journal of Infectious Diseases DOI: 10.1086/652403[↩][↩][↩]
2. For references see
   Weinberg, G., & Szilagyi, P. (2010). Vaccine Epidemiology: Efficacy, Effectiveness, and the Translational Research Roadmap The Journal of Infectious Diseases DOI: 10.1086/652404[↩]
3. I haven’t talked about the Rotarix withdrawal because I think it’s been widely and very well covered on other blogs.  (I have 536 papers in my list of things I want to talk about here some time, so I usually don’t bother blogging about findings other places cover in detail.)  Vincent Racaniello at the Virology Blog has his usual high-quality commentary on it here.  He also made an important point on his podcast, This Week In Virology (either number 75 or number 77, I don’t remember which), which I don’t see explicitly on the post: The circovirus-containing vaccine went through all the safety trials, and no problems were seen.

   Obviously circovirus genomes aren’t supposed to be in the vaccine and they’ve got to go.  But (1) we don’t know if the genomes are infectious, or just fragments; (2) there’s no evidence, in spite of centuries of exposure to porcine circovirus, that it has any effects in humans; (3) the vaccines were shown to be safe, at least in the short term.

   On a larger scale, we’re entering a new era of analysis.  I suspect more of this sort of contamination will turn up as the sensitivity of our screening techniques improve, much like chemical detection: As we improve chemical detection to the parts-per-billion and parts-per-trillion level there needs to be better understanding of safety levels. Is this true for biologics? There are good arguments that there may be no safe level for some biologics, and any detection should lead to withdrawal, but on the other hand there clearly is a safe level for other biologics.  Human poop is loaded with vast amounts of viruses of peppers, for example; now that we know that should we regulate pepper mottle virus?

   I don’t have answers, which is why I relegate this to a footnote, albeit a long a rambling footnote.[↩]

Human cytomegalovirus-infected cell

A number of viruses, especially herpesviruses, block the MHC class I antigen presentation system. It’s been widely assumed that this is for the obvious reason and that it allows the virus to avoid T cell recognition and elimination. But there’s been an awkward lack of experimental support for that assumption, to the point that I’ve begun to question it (and, more productively, to develop experimental systems with which to test it).   (See the list of posts below for some of my earlier comment on the subject.)

Now, at last, Klaus Fruh offers actual evidence that this assumption may be correct. ¹

This deserves a long post, which it’s not going to get today.² Briefly, Klaus’s group used a herpesvirus of monkeys (rhesus cytomegalovirus; rhCMV) to test this. This is closely related to the human herpesvirus human cytomegalovirus, which is a ubiquitous virus; the vast majority of humans have it, are infected with it as toddlers, remain infected with it throughout their lives, and don’t suffer any problems with it. It’s a rare cause of a mono-like disease, and it’s a concern in immune-suppressed people (especially transplant recipients), but mainly it seems to be a pretty innocuous hitchhiker.

The CMV family of herpesviruses carry a particularly impressive arsenal of anti-MHC class I immune evasion genes. (MHC class I is the target that antiviral T cells, also known as cytotoxic T lymphocytes or CTL, recognize. There’s an outline of the process that permits that recognition here.) Whereas herpesviruses like herpes simplex, or chicken-pox virus, and so on, seem to use only one gene to block MHC class I, CMVs seem to use three or four. This would suggest that this sort of immune evasion is really important for these viruses, but when Ann Hill actually tested that notion in mice³ removing these immune evasion genes had only a very small impact.

Fruh’s group has now done something similar using his rhesus model, and looked at an unusual characteristic of CMVs: They are able to repeatedly superinfect the same host. That is, someone⁴ can be infected with CMV, can have an apparently effective immune response to CMV, and yet can be infected by a new CMV virus. This is pretty unusual, of course. You’d expect that there would be a vaccine-type effect, in which the natural infection would drive a protective immune response. As far as I know, you don’t often see this sort of superinfection even with other herpesviruses, which is why, for example, the chicken-pox vaccine works.

“Human cytomegalovirus infected human endothelial cells” by Joerg Schroeer

They made a pretty drastic mutant of the RhCMV to eliminate all four of the MHC class I immune evasion genes (taking out another half-dozen genes as collateral damage, but they checked that these weren’t confounding the story). This mutant virus, in spite of having completely lost its ability to block MHC class I, was perfectly able to infect monkeys and to set up a long-term infection — just like Ann Hill’s findings with mouse CMV. What the mutant virus was not able to do was superinfection.

Together, our results suggested that RhCMV was unable to superinfect in the absence of the homologs of US2, US3, US6, and US11 because the virus was no longer able to avoid elimination by CTL. ⁵

But when the pre-infected monkeys had their CTL temporarily eliminated, then the mutant viruses were able to superinfect. What’s more, after the virus got in and set up its new infection, CTL couldn’t clear them, even though the viruses still had no ability to evade MHC class I:

Our data imply that T cell evasion is not required for establishment of primary CMV infection or once the sites of persistence (e.g., kidney and salivary gland epithelial cells) have been occupied, but rather it is essential to enable CMV to reach these sites of persistence from the peripheral site of inoculation in the CMV-immune host. ⁵

This is really cool stuff. It offers an explanation for why Hill’s group didn’t see an effect for MHC class I immune evasion in their mouse CMV model — they didn’t specifically look at superinfection, though they looked at many other aspects of infection. (Does mouse CMV superinfect as robustly as human?)  It also offers an explanation for why experimental CMV vaccines have been ineffective — the immune evasion functions allow the virus to temporarily evade the immune response.

As I say, I don’t think superinfection is so common in other families of herpesviruses, so this may not be a universal explanation for MHC class I immune evasion by herpesviruses; but then, it’s been the CMV system that’s been most puzzling, anyway, so we may not need to go so far to look for answers after all.

1. Hansen, S., Powers, C., Richards, R., Ventura, A., Ford, J., Siess, D., Axthelm, M., Nelson, J., Jarvis, M., Picker, L., & Fruh, K. (2010). Evasion of CD8+ T Cells Is Critical for Superinfection by Cytomegalovirus Science, 328 (5974), 102-106 DOI: 10.1126/science.1185350[↩]
2. I’m still chilling with my kids on their spring break, not to mention a dozen other distractions[↩]
3. Gold, M. C., Munks, M. W., Wagner, M., McMahon, C. W., Kelly, A., Kavanagh, D. G., Slifka, M. K., Koszinowski, U. H., Raulet, D. H., and Hill, A. B. (2004). Murine cytomegalovirus interference with antigen presentation has little effect on the size or the effector memory phenotype of the CD8 T cell response. J Immunol 172, 6944-6953.

   Pinto, A. K., and Hill, A. B. (2005). Viral interference with antigen presentation to CD8+ T cells: lessons from cytomegalovirus. Viral Immunol 18, 434-444.

   Lu, X., Pinto, A. K., Kelly, A. M., Cho, K. S., and Hill, A. B. (2006). Murine cytomegalovirus interference with antigen presentation contributes to the inability of CD8 T cells to control virus in the salivary gland. J Virol 80, 4200-4202.[↩]

4. Or some monkey[↩]
5. Hansen, S., Powers, C., Richards, R., Ventura, A., Ford, J., Siess, D., Axthelm, M., Nelson, J., Jarvis, M., Picker, L., & Fruh, K. (2010). Evasion of CD8+ T Cells Is Critical for Superinfection by Cytomegalovirus Science, 328 (5974), 102-106 DOI: 10.1126/science.1185350[↩][↩]