NASA’s shameful analysis of the alleged bacteria in the Mars meteorite made me very suspicious of their microbiology, an attitude that’s only strengthened by my reading of this paper.
NASA’s shameful analysis of the alleged bacteria in the Mars meteorite made me very suspicious of their microbiology, an attitude that’s only strengthened by my reading of this paper.
|Worldwide HIV/AIDs Epidemic Statistics|
(We are in the process of selling one home and buying another, while at work I just finished organizing a course on biosecurity for an international group. In the upcoming week I’m traveling to a conference in Washington. To say nothing of the Thanksgiving holiday. All this means short and scarce updates for a little while.)
We know that the immune response to HIV forces the virus to evolve at great speeds, so that the viral targets of the immune response change and become at least temporarily invisible. We also know that the specific targets are different for almost every infected person. So although you have rapid evolution in each individual, what does this mean to overall evolution of the global population of HIV?
The several dozen CTL epitopes we survey from HIV-1 gag, RT and nef reveal a relatively sedate rate of evolution with average rates of escape measured in years and reversion in decades. For many epitopes in HIV, occasional rapid within-host evolution is not reflected in fast evolution at the population level.1
(My emphasis) This is a modeling study (though it did look at real-life data to some extent), but their conclusion is consistent with larger-scale population studies as well; see my previous post here and links therein.
|RINDERPEST. Lips and gums, showing apthous condition1|
1711 (via 1902):
Rinderpest is the most fatal disease affecting cattle. … The first great epizootic of which there seems to be records occurred about 1709 and spread over nearly all of the countries of Europe. It is reported that 1,500,000 cattle died from its effects during the years from 1711 to 1714. 2
1839 (via 1861):
Previously to the present century the only well recognized epizootics that are known to have prevailed extensively among horned cattle in Europe were the Eczema Epizootica, or “mouth and foot disease”, a complaint well known in England since the year 1839, and the terrible Rinderpest or Steppe murrain.
This last named disease, which is described as being of the nature of a highly infections typhus fever, terminating in dysentary, is said to be indigenous to the Steppes of Tartary and Siberia, from whence it has descended, from time to time, upon Russia, Germany, and other European countries.
It has been estimated that during the eighteenth century the Rinderpest destroyed, in Europe, as many as two hundred millions of cattle.3
1865 (via 1880) :
In 1865 the plague appeared in Holland, and was carried thence to England. In both countries the disease carried off one hundred thousand head of cattle in the course of a few months.4
1889 (via 1909):
About the year 1889, or shortly before, a virulent form of rinderpest started among the domestic cattle and wild buffalo almost at the northern border of the buffalo’s range, and within the next few years worked gradually southward to beyond the Zambesi. It wrought dreadful havoc among the cattle and in consequence decimated by starvation many of the cattle-owning tribes; it killed many of the large bovine antelopes, and it wellnigh exterminated the buffalo.5
14 October 2010, Rome – An ambitious global effort that has brought rinderpest, a deadly cattle plague, to the brink of extinction is ending all field activities, paving the way for official eradication of the disease.6
John Hawks1 has a long and very interesting post on the human mutation rate — not just the actual number (which turns out to be less well documented and much more slippery than I had realized), but the techniques used to calculate the rate, and difficulties therein.
So much of the literature in this area is ultimately circular, I’m pulling out my sparse hair reading through it. By the time we get back to the mid-1990′s, the sequence data are even sparser than my hair by today’s standards — only a few hundred base pairs, or a sampling of restriction sites. But the divergence time estimates have propagated forward from that time to today, recycled through the assumptions of papers in the intervening time. It’s like the genetic equivalent of money laundering!
Conceptually, it’s very reminiscent of the questions about viral mutation rates, although the technical barriers are quite different and (especially for RNA viruses!) the mutation rates are vastly different. For example, Hawks’ post talks about which edge of a two-fold range the human mutation rate falls on — between 2.5 x 10-8 and 1.1 x 10-8 mutations per site; in a table I’ve used before we see a ten-thousand-fold range for poliovirus error rate estimates.
|RNA virus mutation rates 2|
I have to get my kids ready for school now, so I don’t have time to talk about the techniques here — it’s notable that sequencing, though much easier on the tiny viral genomes than on the much vaster human scale, hasn’t completely resolved the issue, though the variation gets smaller as sequencing technology gets getter.
Here are some of my previous posts that mention replication error and mutation rates …
|T cells (green) and herpesvirus-infected cells (red)
(from Akiko Iwasaki)
We know that lots of viruses, especially herpesviruses, block antigen presentation. The assumption has been that they are thereby preventing T cells from recognizing infected cells, though long-term readers of this blog1 will know that I’ve been puzzled about the details of this for quite a while.
Our data indicate that the human CD8+ T cell pool comprises a diverse reactivity to target cells with impairments in the intracellular processing pathway2
If so, you might wonder why the viruses would bother blocking antigen presentation. They might avoid recognition by T cells specific for the viral proteins, but at the cost of being recognized and eliminated by the T cells that recognize antigen-presentation-defective cells.
As always, I don’t have an answer. I do have the unhelpful observation that viruses are incredibly subtle and efficient, and given that herpesviruses have apparently maintained the ability to block antigen presentation for some 400 million years it’s presumably useful to them. I’ll also add the even more unhelpful observation that immune systems are also incredibly subtle and efficient and have also persisted for 450 million years.
However, there may be a clue in the techniques that Lampen et al used to turn up this subset of T cells: They used multiple rounds of stimulation, which is going to expand these cells massively. We don’t know how abundant they are inside a normal human – perhaps they are so rare that they don’t have a chance to impinge on herpesvirus infection early enough.
The catch with that, though, is that tumors also frequently get rid of antigen presentation via mutation; in fact, eliminating antigen presentation seems to be one of the most common forms of mutations in cancers, suggesting that it’s an important part of their ability to survive and expand in the face of immune attack. Tumors are immunologically present much longer than viruses ((Although herpesviruses set up a lifelong infection, most of that is generally in a non-immunogenic, latent form). So why doesn’t this long-term tumor presence lead to amplification of these antigen-presentation-deficient-specific T cells that would eliminate the tumor?
My guess here is that this is where TRegs come in. As I said in a recent post, TRegs are very commonly, if not universally, associated with tumors, and prevent immune attack on the tumor. I wonder if the tumors mutate to avoid T cell recognition early in their development, before they are able to trigger the TReg response; that allows them to grow large enough and long enough that by the time the presentation-defect-destroyers kick in, the tumors have their TReg defenders set up. (I admit that this doesn’t account for the correlation between a tumor’s loss of antigen presentation, and poor prognosis, but I leave this as an exercise for the reader.)
And, of course, where either of these defense systems for the proto-tumor fails, we normally would simply not see any tumor at all. Perhaps this is happening all the time inside us — proto-tumors are being eliminated by T cells, some are mutating their antigen presentation pathway and lasting a little longer and are then eliminated by a different subset of T cells, and we never know it.
|TRegs infiltrate into a tumor|
There’s increasing evidence supporting the notion that tumors are often not rejected by the immune system because regulatory T cells actively block the immune response to the tumor cells. 1
That means that within the tumor, two branches of the immune response are fighting it out. If the TRegs win, the tumor will not be rejected (and may eventually kill the host); if the rejection branch2 wins, the tumor may be rejected and the host may survive a little longer.
Both TRegs and rejection-branch T cells are driven by specific antigen. That is, as opposed to the general patterns that drive innate immune responses, the T cells are activated by peptides associated with major histocompatibility complexes (mainly class II MHC, for the TRegs).
So that raises an interesting question: What specific peptides activate the TRegs in the tumors, and are they different from the ones that activate rejection-type CD4s?
The question is even more interesting than it may seem at first glance, because3 there are different TReg subsets with different peptide preferences. One set of TRegs likes to see ordinary self-peptides: Peptides that are naturally present, and that should not be rejected because, well, they’re part of you. “Normal” rejection-type T cells don’t see those peptides, because those that do are killed during their development (or are converted into TRegs during development, probably). The other group of TRegs sees foreign peptides, that would be expected to be rejected. You need these TRegs as well, because there are times when a chronic immune response, even to a foreign invader, is more harmful than the invader itself; so under those circumstances, some rejection-type T cells get converted into TRegs, and those can shut down the response to the invader, hopefully to reach a happy accommodation.
Are the TRegs in tumors the first kind, that are activated by the normal self-antigens that are present in the tumor cells (which are, remember, originally you to start with)? Or are they the second type, responding to the foreign antigen present in the tumor (mutated proteins, say, or over-expressed growth factors) but converted into a TReg type from a rejection-type when the tumor foreign antigens proved to be a chronic stuimulus?
A recent paper4 suggests it’s the latter:
This allows us to ask whether tumor-associated Treg cells arise from the repertoire of TCRs used by natural Treg cells or from the repertoire used by effector cells. We show that Treg population in tumors is dominated by T cells expressing the same TCRs as effector T cells. These data suggest that Treg in tumors are generated by expansion of a minor subset of Treg cells that shares TCRs with effector T cells or by conversion of effector CD4+ T cells and thus could represent adaptive Treg cells. 4
If this is generally true (and the authors do offer a helpful series of caveats) it has a very important implication. There’s a huge amount of interest in tumor vaccines — identify an antigen specific for the tumor, and induce a potent immune response to it, in the hope that T cells will then reject the tumor. But you see the problem: If the TRegs are stimulated by the same antigen, then your vaccine is going to increase both sides — the rejection branch and the TReg branch — and you’re no further ahead than when you started! This may be one of the reasons that tumor vaccines have been only intermittently effective. But it does make even more attractive another approach toward cancer immunization, where TRegs are specifically blocked, hopefully allowing the already-present rejection-type5 T cells to kick in and, maybe, eliminate the tumor:
This further suggests that improved cancer immunotherapy may depend on the ability to block tumor-antigen induced expansion of a minor Treg subset or generation of adaptive Treg cells, rather than solely on increasing the immunogenicity of vaccines. 4
|Malaria parasite in mosquito midgut|
We often think of mosquitoes as willing co-conspirators in spreading human1 pathogens. But of course, in most cases the mosquito would be just as happy to get rid of the pathogen themselves; even if it doesn’t cause as severe as disease in the mosquito as in humans, it’s not doing them any good.2
So why don’t the mosquitos get rid of these pathogens, rather than carrying them around to infect yet more vertebrates? We know that insects have a fairly elaborate immune system, albeit one that’s quite different from ours.
The answer seems to be (at least partially) that — just as with pathogens of vertebrates — the mosquito pathogens have evolved ways of evading the immune response, so that the mosquitos can’t eliminate them.
Our findings provide support for the hypothesis that mosquito-borne pathogens have evolved to evade innate immune responses in three vector mosquito species of major medical importance.
–Bartholomay, L., Waterhouse, R., Mayhew, G., Campbell, C., Michel, K., Zou, Z., Ramirez, J., Das, S., Alvarez, K., Arensburger, P., Bryant, B., Chapman, S., Dong, Y., Erickson, S., Karunaratne, S., Kokoza, V., Kodira, C., Pignatelli, P., Shin, S., Vanlandingham, D., Atkinson, P., Birren, B., Christophides, G., Clem, R., Hemingway, J., Higgs, S., Megy, K., Ranson, H., Zdobnov, E., Raikhel, A., Christensen, B., Dimopoulos, G., & Muskavitch, M. (2010). Pathogenomics of Culex quinquefasciatus and Meta-Analysis of Infection Responses to Diverse Pathogens Science, 330 (6000), 88-90 DOI: 10.1126/science.1193162
Our results suggest that, for typical connection strengths between communities, spatial heterogeneity has only a weak effect on outbreak size distributions, and on the risk of emergence per introduction. For example, if R0=1.4 or larger, any village connected to a large city by just ten commuters a day is, effectively, just a part of the city when considering the chances of emergence and the outbreak size distribution.
–Kubiak, R., Arinaminpathy, N., & McLean, A. (2010). Insights into the Evolution and Emergence of a Novel Infectious Disease PLoS Computational Biology, 6 (9) DOI: 10.1371/journal.pcbi.1000947
(See also “Measles Week, Part II: Emerging Disease“)
That light at the end of the sequencing tunnel is a freight train, heading toward us with a mile-long load of data.
I’m not finding time to give these papers a full post each, so let me pool together several in the same theme: MHC alleles and protection against pathogens.
It’s generally accepted that the reason there are so many MHC alleles is related to their ability to protect against pathogens.1 The version is probably the frequency-dependent selection model. According to this, pathogens are selected to be resistant to common MHC alleles, so individuals with rare alleles have a selective advantage and those alleles become more common, until pathogens are selected for resistance to them in turn. (Described in more detail here.).
The particular steps in this concept are each fairly straightforward and reasonably well supported. We know that different MHC alleles can be more or less effective against pathogens; we see some instances of pathogens developing resistance to particular MHC alleles, and so on. But it’s been quite difficult to put all the pieces together. The best examples of pathogens evolving resistance to MHC alleles, for instance, are within a single host, in the case of HIV. When we look at even this virus over a population instead, it’s much harder to detect any particular adaptation to MHC (though there may be some).
The problem is (probably) that we’re looking at a single frame of a movie. This is a dynamic process, as the pathogens and the individuals within a population co-evolve. It’s hard to see fossil MHC alleles and just as hard to see fossil viral epitopes. The snapshot we see today may be at any point along the process – the pathogen may have the upper hand, the hosts may, or they may be perfectly balanced. (Also, of course, the host need to deal with thousands of pathogens, while each pathogen may focus on one or a handful of hosts. It would take a fairly assertive pathogen to single-handedly push a host population toward differential allele usage. The host’s version of the movie frame would actually be a blur of a thousand frames from a thousand movies, each of which is shown at different speeds and with a different starting point, all overlapping and interacting with each other.)
So observations supporting the frequency-dependent model have been rather scarce; in fact, instances where MHC alleles differentially affect pathogens are themselves relatively scarce, and those are the starting points from which frequency-dependent selection arises. So I’m always intrigued when we learn of cases where there are specific resistance and susceptibility alleles of MHC for particular pathogens, in the wild, and in a population rather than an individual.
Here are some I’ve noticed in the past few weeks.
Koehler, R., Walsh, A., Saathoff, E., Tovanabutra, S., Arroyo, M., Currier, J., Maboko, L., Hoelsher, M., Robb, M., Michael, N., McCutchan, F., Kim, J., & Kijak, G. (2010). Class I HLA-A*7401 Is Associated with Protection from HIV-1 Acquisition and Disease Progression in Mbeya, Tanzania The Journal of Infectious Diseases DOI: 10.1086/656913
Other MHC class I alleles have been shown to be protective against HIV, so this is mainly adding to the list; but it;s a shortish list, so any additions are interesting.
MacNamara, A., Rowan, A., Hilburn, S., Kadolsky, U., Fujiwara, H., Suemori, K., Yasukawa, M., Taylor, G., Bangham, C., & Asquith, B. (2010). HLA Class I Binding of HBZ Determines Outcome in HTLV-1 Infection PLoS Pathogens, 6 (9) DOI: 10.1371/journal.ppat.1001117
An attempt to link observed protective MHC alleles, with the mechanism of protection, concluding that being able to induce T cell recognition of a specific HTLV-1 protein is associated with protection. This is conceptually similar to the proposed mechanism by which [some] MHC alleles protect against HIV,2 where a specific peptide target can’t mutate away from T cell recognition.
Appanna, R., Ponnampalavanar, S., Lum Chai See, L., & Sekaran, S. (2010). Susceptible and Protective HLA Class 1 Alleles against Dengue Fever and Dengue Hemorrhagic Fever Patients in a Malaysian Population PLoS ONE, 5 (9) DOI: 10.1371/journal.pone.0013029
They identify MHC alleles that may be associated with protection against disease, and protection against severe disease. I’m a little uncomfortable with the relatively small number of patients involved here (less than 100), and would like to see it confirmed in a larger study.
Guivier, E., Galan, M., Male, P., Kallio, E., Voutilainen, L., Henttonen, H., Olsson, G., Lundkvist, A., Tersago, K., Augot, D., Cosson, J., & Charbonnel, N. (2010). Associations between MHC genes and Puumala virus infection in Myodes glareolus are detected in wild populations, but not from experimental infection data Journal of General Virology, 91 (10), 2507-2512 DOI: 10.1099/vir.0.021600-0
We revealed significant genetic differentiation between PUUV-seronegative and -seropositive bank voles sampled in wild populations … Also, we found no significant associations between infection success and MHC alleles among laboratory-colonized bank voles, which is explained by a loss of genetic variability that occurred during the captivity of these voles.
The difference between wild and captive voles is reminiscent of the difficulty and confusion involved in MHC function in lab mice. In at least one set of experiments, it was necessary to have semi-feral mice before mechanisms could be teased apart.