Bacterial Thunderdome: Decoding virulence, spiteful interactions, and diversity

What happens when two parasites infect the same host individual? Is the outcome similar to the Thunderdome: two parasites enter, one parasite leaves? Host-parasite interactions are rarely so simple. While a reductionist approach to understanding the interaction of a parasite or pathogen with its host may decompose the system to a single infection, nature is full of much more complex puzzles. Within the host, the battle itself raging between parasites (within-host competition) may have cascading effects on the host.

A recent paper on virulence caught my eye (Bashey et al., 2012) which provides an update to a very interesting result from the group a few years ago. The system includes bacterial parasites, along with parasitic nematodes, that infect insect larvae and eat/digest them from the inside out. Vigneux et al. (2008) found that when multiple parasite isolates are mixed in a host, the host mortality decreased. However, this only occurred when the isolates were not related. In the experiment, the researchers created low relatedness by mixing populations with migration. I reviewed the 2008 paper previously. The hypothesis was that chemical warfare among the parasites decreased the parasite load and reduced the negative effects on the host, virulence.

The bacteria produce chemical weapons, bateriocins, which can broadly harm other isolates, but relatives are left unharmed. These chemical weapons can be classified as spiteful: in the process of harming others they also harm the focal individual. This self-harm comes from the cost of making the chemical weapon. Others have labeled this antagonistic trait a greenbeard gene.

Greenbeards are genes that can identify the presence of copies of themselves in other individuals, and cause their bearer to behave nepotistically toward those individuals (Gardner and West, 2010).

Gardner and West explain that the origin of this term comes from Richard Dawkins illustrative example where individuals bearing this trait had green beards.

Experimental results: Recently, natural system specific isolates of the parasite have been cultured in the lab allowing more specific tests of the within-host competition (Hawlena et al., 2010a; Hawlena et al., 2010b). In the most recent paper, Bashey et al. (2012) found that the bacterial isolates that produce the toxin have a higher growth rate in coinfections (where within-host competition might be important). However, in the absence of coninfections, there was no relative growth rate advantage of the toxin producing, inhibitory, isolates. In coninfections, even though the toxin producing isolate was winning the internal host battle, lower host mortality rate emerged as an outcome.

A beautiful world: As an evolutionary biologist, I’m interested not only in the diversity of the natural world, but also the mechanisms that keep that diversity around. We often think of natural selection as favoring the fittest. If a single type is better than the rest, then over time, diversity will decrease. Often the analogy of hill climbing is used. On the other hand, if the fittest depends on the context of the other players involved, than diversity might be maintained. That is, what if the shape of the mountain range is constantly changing. In relation to this research,

bacteriocins might promote local diversity when producer, sensitive, and resistant strains are engaged in a version of the rock‐paper‐scissors game (i.e., the producer can kill the sensitive strain, the resistant strain outcompetes the producer, and the sensitive strain outcompetes the resistant strain) in a spatially structured environment (Hawlena et al., 2010b).

If bacteriocins are costly to produce, than they must provide some benefit in some contexts. Bashey et al (2012) suggest that this mechanism, where the fitness of a particular parasite isolate is context dependent, may explain the high frequency of bacteriocin production found in the natural populations surveyed in their earlier work (Hawlena et al., 2010a).

Stay tuned for future research by Dr. Farrar Bashey as she assures me more pieces to this puzzle will be revealed.

References

• Bashey F, Young SK, Hawlena H, Lively CM (2012) Spiteful Interactions between Sympatric Natural Isolates of Xenorhabdus Bovienii Benefit Kin and Reduce Virulence. Journal of Evolutionary Biology 25: 431-437. DOI: 10.1111/j.1420-9101.2011.02441.x
• Gardner A, West SA (2010) Greenbeards. Evolution 64: 25-38. DOI: 10.1111/j.1558-5646.2009.00842.x
• Hawlena H, Bashey F, Lively CM (2010a) The Evolution of Spite: Population Structure and Bacteriocin-Mediate Antagonism in Two Natural Populations of Xenorhabdus Bacteria. Evolution 64: 3198-3204. DOI: 10.1111/j.1558-5646.2010.01070.x
• Hawlena H, Bashey F, Mendes Soares H, Lively CM (2010b) Spiteful Interactions in a Natural Population of the Bacterium Xenorhabdus Bovienii. The American Naturalist 175: 374-381. DOI: 10.1086/650375
• Vigneux F, Bashey F, Sicard M, Lively CM (2008) Low Migration Decreases Interference Competition among Parasites and Increases Virulence. Journal of Evolutionary Biology 21: 1245-1251. DOI: 10.1111/j.1420-9101.2008.01576.x

Main Paper
BASHEY, F., YOUNG, S., HAWLENA, H., & LIVELY, C. (2012). Spiteful interactions between sympatric natural isolates of Xenorhabdus bovienii benefit kin and reduce virulence Journal of Evolutionary Biology, 25 (3), 431-437 DOI: 10.1111/j.1420-9101.2011.02441.x

Is the Red Queen showing her face? Evidence of negative frequency dependent selection by parasites

Recently Wolinska and Spaak (2009) provide a survey of Daphnia infections by genotype across a number of lakes in Italy and Switzerland. They present their results as empirical evidence of Red Queen dynamics in which coevolution with virulent parasites generates continued evolution. Although Van Valen (1973) originally presented a macroevolutionary argument where by reciprocal selection of hosts and their parasites generates conditions for continuous change, Bell (1982) narrowed the focus as a mechanistic explanation for the evolution or maintenance of sexual reproduction through cyclical changes in genotype frequencies. Wolinska and Spaak (2009) are not addressing the evolution of sex, but looking for evidence that parasites in Daphnia populations are generating negative frequency dependent selection such that a rare genotype has an advantage. Evidence consistent with the Red Queen has been found in other systems using spatially distributed samples (e.g. Dybdahl and Lively 1995) to look non-random infection rates as well as more directly looking at changes in frequencies of common genotypes (e.g. Dybdahl and Lively 1998).

Wolinska and Spaak (2009) propose three hypotheses to test with their data. The first is that common genotypes should be either over or under infected compared to a random sample. This prediction is based on stereotyped cyclical dynamics of genotypes of hosts and parasites (image two out of sync sine waves). At some points, the common clones will be targeted by the parasites and become overly infected. As a genotype becomes common, parasites haven't started attacking this genotype yet (i.e. time lagged), so it is under infected. In their survey, the found that indeed, some of the populations showed over infection (n = 1) and other showed under infection (n = 11), although the majority of cases did show no significant difference from random infection probabilities which is predicted as being a rare event. Their second hypothesis was that common genotypes should over the course of time decline if they are being tracked by parasites. The previous sample included only different lakes; where as the data needed to test this hypothesis are temporal samples from the same location. Their additional data is consistent with common genotypes declining over time (9 out of 10 cases). However, it is unclear to me how the general trend in this data of common genotypes decreasing over time, leads to the evidence supporting the first hypothesis. Shouldn't they find many more over infected common clones? A third hypothesis that they tested regarded host-parasite interactions maintaining diversity and an evenness of genotype frequencies which their data supported.

When discussing this paper, we were interested in what happens to predictions based on Red Queen dynamics when more than one parasite is involved. Previous empirical papers and theory seems to be generally focused on a host and a common parasite, but we know hosts are attacked by all kinds of parasites and pathogens. The system described by Wolinska and Spaak (2009) involves a host hybrid complex as well as four different parasites and questions about host specialization and hybrid maintenance were addressed in a previous paper (Wolinska et al. 2007). Where is the companion theoretical work to provide testable hypotheses?

References

Bell, G. 1982. The Masterpiece of Nature: The Evolution and Genetics of Sexuality. University of California Press, Berkeley.

Dybdahl, M. F., and C. M. Lively. 1995. Host-Parasite Interactions: Infection of Common Clones in Natural Populations of a Freshwater Snail (Potamopyrgus antipodarum). Proceedings of the Royal Society of London. Series B: Biological Sciences 260:99-103.

Dybdahl, M. F., and C. M. Lively. 1998. Host-parasite coevolution: Evidence for rare advantage and time-lagged selection in a natural population. Evolution 52:1057-1066.

Van Valen, L. 1973. A new evolutionary law. Evolutionary Theory 1:1-30.

Wolinska, J., B. Keller, M. Manca, and P. Spaak. 2007. Parasite survey of a Daphnia hybrid complex: host-specificity and environment determine infection. Journal of Animal Ecology 76:191-200.

Wolinska, J., and P. Spaak. 2009. The cost of being common: evidence from natural Daphnia populations. Evolution 63:1893-1901.

Wolinska, J., & Spaak, P. (2009). The cost of being common: evidence from natural Daphnia populations Evolution, 63 (7), 1893-1901 DOI: 10.1111/j.1558-5646.2009.00663.x

Selection Mosaics or environmental interactions

Vale and Little (2009) published recent work on parasite infection variation across a temperature gradient. Specific parasite infections are often the result of genetic interactions of both the host and parasite, sometimes referred to as genotype by genotype interactions (GxG). The authors of this paper used an ideal interaction between Daphnia magna and a bacterial parasite, Pasteuria ramose. The experiment was such that they could test multiple levels on interactions. They isolated multiple host clonal lines (n = 4) as well as parasite lines (n = 4) and compared infection rates as well as parasite growth rates across three different temperatures. The paper details the experiment very well, so I'll spare details here, but a good model for future studies.

The authors found significant GxG interactions for most of the traits measured in the infection process, including both early (probability of infection) and later (parasite growth rate). However differences in genotype by environment (GxE) interactions showed up for different places in the infection timeline. The probability of infection showed a host genotype by temperature interaction, but this was a weak affect and the authors make the important point that the relative rank order wasn't changed. The reason this is key is that it is often emphasized that GxE interactions are a mechanism of the maintenance of different genotypes. If each genotype has high fitness in only some environments, and the environment varies, then there can be some period of time where polymorphism is maintained. In terms of interactions of the parasite genotype and the environment, there were initially some interactions with transmission potential and growth rate, however rank differences were again absent. The paper makes one further step and examines the combined transmission potential (spore production and infectivity). This isn't quite a measure of R₀ because of complications with the effect of dose on infection rate and the interaction between parasite genotype and temperature disappears.

The study failed to find evidence of a GxGxE interaction, but the authors were correct to point out, that this is only the case for the environmental variable measured (temperature). Given that temperature is an important component of the environment for this interaction, I was surprised by this result. Perhaps, it would have been different if the difference were not just in constant temperature, but in some sort of variable environment. In the very last paragraph, Vale and Little (2009) emphasize that the lack of GxGxE interactions mean that the specificity of the interactions are robust to environmental noise. However, it is just such noise that others have proposed as important in maintaining variation. These interactions are the selection mosaics in the Geographic Mosaic Theory of Coevolution (Thompson 1999, 2005).

References

Thompson, J. N. 1999. Specific hypotheses on the geographic mosaic of coevolution. American Naturalist 153:S1-S14.

Thompson, J. N. 2005.
The Geographic Mosaic of Coevolution. University of Chicago Press, Chicago.

Vale, P. F., and T. J. Little. 2009. Measuring parasite fitness under genetic and thermal variation. Heredity online early.

Paper read

Vale, P., & Little, T. (2009). Measuring parasite fitness under genetic and thermal variation Heredity DOI: 10.1038/hdy.2009.54

Why do I have so many parasites?

This week's paper (Bordes et al 2009) looked for forces that influence the parasite diversity or parasite species richness (PSR) among mammals. While it may seem almost impossible to think that there might be a single factor, there have been many different proposed influences (e.g. body size, geographic range, population density). The host home range, "area used in daily and seasonal movements" (Bordes et al 2009), could be related to the parasite diversity in two distinct ways. Their first prediction is that as home range increases so will PSR because it will result in an increased contact with diverse habitats (and therefore parasites). Their "spatial dispersion model of parasite acquisition" uses parasite transmission and host density to get this relationship to predict the opposite relationship. The results of their analyses supported the second prediction.

The group found the methods and results of this paper relatively straight forward. The use of independent contrasts to control for the effect of phylogeny was very appropriate in this paper. We did find one area of the analysis confusing with respect to the host sampling number. It is well known that sampling intensity may bias the number of parasites found on a host . The more hosts one searches the more parasites will be found up to some saturation point. The authors controlled for the bias by using the residuals of parasite richness and host number. However, we were then confused by the inclusion of "Host sample size" in the regression analyses. While other variables in the regression analyses were significant, it was hard to determine the impact of this highly significant variable on the total fit of the model. We were left wondering how much of the variation in PSR did the home range explain?

The main conclusion of this paper is to confirm a roll for epidemiological factors (density and transmission) on the relationship between home range and PSR. The results show a negative relationship between home range and PSR which is consistent with their second prediction. The strong negative relationship between home range and host density relates their effect to how this can influence the number of parasites. It seems that home range not only describes a complicated trait of a host species, but is perhaps influenced by a complicated set of other factors.

Today's group speculated on broader potential relationships of host traits and parasite diversity. Could there be a more universal law that predicts the parasite species load? This study and many of the citations contained within focus on animals and their macroparasites. Maybe there is a rule that works across such taxonomic divisions? The paper cited previous work on the role of body mass (Arneberg 2002, Lindenfors et al 2007) and parasite diversity with larger hosts being home to a larger number of parasites. Can this relationship be scaled up to incorporate host density? What about the total mass of a host species?

References

Bordes, F., S. Morand, D. A. Kelt, and D. Van Vuren. 2009. Home Range and Parasite Diversity in Mammals. The American Naturalist 173:467-474.

Arneberg, P. 2002. Host population density and body mass as determinants of species richness in parasite communities: comparative analyses of directly transmitted nematodes of mammals. Ecography 25:88–94.

Lindenfors, P., C. L. Nunn, K. E. Jones, A. A. Cunningham, W. Sechrest, and J. L. Gittleman. 2007. Parasite species richness in carnivores: effects of host body mass, latitude, geographical range and population density. Global Ecology and Biogeography 1:1–14.

Bordes, F., Morand, S., Kelt, D., & Van Vuren, D. (2009). Home Range and Parasite Diversity in Mammals The American Naturalist, 173 (4), 467-474 DOI: 10.1086/597227