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11/29/2011 (started on): Notes on the literature on phage-host dynamics

Winter et al. (2010)

“substantial investments into stress defense or avoidance strategies may result in a reduction in growth and reproduction and vice versa”

“viruses with a high multiplication rate degrade quickly, because under resource-limited conditions these viruses cannot invest higher levels of resources into the stability of their capsids but rather invest them into numbers of offspring.” See De Paepe and Taddei (2006) for this.

“Given the many examples of a trade-off between strategies maximizing growth and minimizing losses, from the very small and simple to the very large and complex, one cannot avoid concluding that such a trade-off appears to be a fundamental property of evolving biological entities existing in environments with limited resources.”

“The concept of negative frequency-dependent selection states that the fitness of an organism (e.g., success in reproduction) decreases as its frequency (relative abundance) increases. If correct, this mechanism selects for rare types and thus maintains high diversity. Soon after the discovery of high viral abundance in the ocean, it was argued that viruses might be instrumental in maintaining high prokaryotic richness (29, 93), because the viral infection rate depends on, among other parameters, the abundance of host cells. Thus, as suggested by negative frequency-dependent selection, abundant prokaryotic types will be exposed to strong viral pressure. Eventually, this and other ideas were incorporated into what is now known as the “killing the winner” hypothesis (KtW), where “winner” refers not necessarily to the most abundant but to the most active prokaryotic population. KtW was mathematically formalized in the context of an idealized food web comprised of prokaryotes, viruses, and protozoans grazing nonselectively on prokaryotes and is based on Lotka-Volterra-type equations.”

“In an oligotrophic environment (low total available resource level) the competition specialist would be expected to dominate, whereas in a eutrophic environment (high total available resource level) the system would be dominated by the defense specialist. It is important to realize that the âwinnerâ in KtW refers to the competition specialist, which may or may not correspond to the most abundant population.”

This comment does not seem to be consistent with Suttle (2007)’s picture that says that in oligotrophic oceans, the most abundant bacteria is the one that is highly resistant and has a slow growth rate (the defense specialist). See, for instance, this quote from Suttle (2007):

“active Roseobacter spp. populations are probably kept in check by viral lysis. By contrast, although SAR11 might be less active, it could be more abundant in oligotrophic waters because it is resistant to losses, including those from viral lysis”

Is this another comment that is not consistent with Suttle (2007)’s review:

“The biomasses of viruses with high adsorption constants are small because the size of the prokaryotic host population declines correspondingly”.

In Suttle (2007), the highly active viruses are abundant and feed on a reduced population of highly active hosts.

Issues concerning the “kill-the-winner” (KtW) hypothesis

  1. Mutation of the host toward phage resistance and the virus-host relationship

“the development of resistance to viral infection is rapid and [...] can influence or completely change the clonal composition of the host population from vulnerable to resistant. However, in most cases the development of resistance was associated with a fitness penalty for the resistant population.” Which is in agreement with the KtW hypothesis.

In the study of Middelboe et al. (2009), a strain was confronted to a pair of viruses from 24 different types. The strain is initially sensitive to all types of viruses but, with time, the strain mutates and the population is dominated by a strain that is resistant to either one or both of the viruses present. Small populations of non-resistant strains, however, were still present, keeping virus populations at relatively high level. Furthermore, the “[l]oss of sensitivity to virus infection was associated with a reduction in the ability to use various carbon sources”. This is consistent with Suttle’s picture: the dominant prokaryote has a slow growth rate but is phage-resistant while rare, fast growing, prokaryote still exists, but are highly phage sensitive.

But it gets more complicated:

“Nevertheless, the degree of resistance was not correlated to the loss of metabolic potential. Thus, both studies (52, 61) found that the cost of resistance is not proportional to the degree of resistance. A fitness penalty depending on the specific virus type rather than on the total number of different viruses to which resistance developed implies the existence of different mechanisms of resistance.”

The capacity of a host in taking nutrient may be related to its capacity of being infected:

“Many viruses infecting prokaryotes use as a docking site surface proteins that are also involved in the uptake of nutrients by the host cell (24, 66). A structural change in these surface proteins or in their abundance per host cell may result in resistance to viral infection and at the same time cause a reduction in the capabilities for uptake of nutrients (53).”

A host infected by a lysogenic virus may become resistant to further infection:

“Lysogenic viruses may also confer resistance by initiating the production of repressor proteins that ensure the host’s immunity to additional viral infection (21).”

Furthermore, different strain of host are infected by different types of virus and a specific strain can be infected itself by different types of viruses, thus “questioning the validity of the generally assumed specificity of the virus-host relationship and thus also making incorporation into a simple KtW structure difficult.”

See the discussion on the hierarchy of phage resistance in Wei et al. (2011).

  1. Influence of environmental conditions:

“KtW predicts that under highly productive conditions, predation is the major regulatory mechanism for community composition, whereas in environments with low productivity, competition drives community composition. This prediction has been confirmed in a model system consisting of two strains of Escherichia coli with different vulnerabilities to the virus T2 (11).” Read (11)?

  1. Feedback loop generated by release of lysis product

“Viral lysis of host cells releases not only progeny virus particles but also a cocktail of sugars, proteins and peptides, amino acids, nucleic acids, etc., that could serve as a source of nutrients for the surviving community.”

Middelboe (2000) “found that cell lysis and virus production were, in agreement with KtW, positively correlated with the host growth rate”. “The results also demonstrated that the burst size increased while the latent period decreased with increasing host growth rate and that the release of viral lysates stimulated growth of noninfected resistant cells.”

“Thus, although resistance to viral infection may have an associated fitness penalty (52), resource enrichment due to the lysis of vulnerable cells may have a mitigating effect.”

“Based on the available evidence, the question of whether or not a feedback loop that routes resources from vulnerable (competition specialist) to resistant (defense specialist) populations exists can be answered in the affirmative, yet it is currently not included in KtW.”

  1. Availability of resources

Several studies have analyzed the evolution of bacteria and virus populations in mesocosm with varying input of nutrients. In most cases, changes in bacteria coincide with changes in viruses, in accord with KtW.

  1. Experiments where viral abundance is manipulated

Effect of turbulence:

“Malits and Weinbauer (56) found that turbulence stimulated prokaryotic production, likely by enhancing the formation of microaggregates and nutrient availability. However, the presence of viruses appeared to reduce the number of microaggregates. Furthermore, turbulence together with viruses increased prokaryotic cell length. Those authors also report that specific phylotypes appeared to be inhibited or stimulated by turbulence and/or viruses.”

“Thus, host susceptibility is not necessarily proportional to host density, as is often assumed, and rare marine bacterioplankton groups may be more susceptible to virus-induced mortality because these groups may actually be the winners in the competition for nutrients”

  1. Effect of grazing

“Thus, grazing appears to increase the amount of resources available to the surviving populations in a feedback loop similar to viral lysis. Such a feedback loop is currently not included in KtW.”

  1. Observations

“viral infection and lysis are dynamic processes changing on time scales of hours to days” See reference 69.

Shortcoming of KtW

“Among its shortcomings is that the model relies on the assumption of steady-state conditions. Only very few environments actually remain in such a deadlocked situation for long. However, the problem is really one of temporal resolution. A good example is the study by Parada et al. (69), which found that although the ambient viral community is relatively stable over time, only a small number of viral types are actually produced at any given time. Thus, small and rapid changes in the activity of specific viral populations give rise to an overall stable viral community.”

“Another obvious problem in the assumptions underlying KtW is that in most environments prokaryotic hosts are vulnerable to more than one co-occurring virus population.”

The issue that grazing and viral lysis increase the availability of resources for prokaryotes that are phage-resistant and/or survive predation.

Wei et al. (2011)

Comment that there is a time scale here (about 30 days). This time scale is similar to time scale of nutrient input suggesting that it would be interesting to include this physical time scale in a simple model of virus-host interactions.

Follows et al. (2006)

In their model, they have classes of nutrient, phytoplankton and zooplankton. Only the classes of phytoplankton are chosen randomly. Only two classes of zooplankton are used.

Clokie et al. (2011)

“Several approaches have been used to determine the impact phages have on their host’s populations. Experimental evidence from chemostats and observations of phages/hosts in open systems have shown that for some bacterial species, populations of phages and hosts oscillate with time (44,45). The relationship between phages and their hosts has been modeled, and in a simple environment if there is no cost to host resistance the same oscillation in populations occurs (46=Rodriguez-Valera *et al*. 2009). However, if there is a cost to phage resistance, then bacteriophages have been theoretically and experimentally shown to drive host diversification (47=Middelboe et al. 2009, 48=Weitz et al. 2005, 49=Winter et al. 2010). Diversification of bacteria may occur in the phage receptor region, which may be related to nutrient uptake, or it may occur possibly on a faster timescale on CRISPR elements that can quickly evolve to provide a host defense system.”

Middelboe et al. (2009)

Cited by Winter et al. (2010) and Clokie et al. (2011).

“Based on the current knowledge about viral effects on bacterial communities, it seems likely that phageâhost interactions operate on many phylogenetic levels as well as on different time scales in the aquatic environment. Given this frame of phageâhost interactions, viral activity does not necessarily result in large fluctuations in population dynamics, but probably rather controls fast growing types, selects for resistance and a large strain diversity, and thereby dampens population fluctuations. In fact, a large strain diversity may be a key property of a bacterial population in terms of adaptation to changing phage communities.”

“We have here provided evidence that phage infections are driving a succession within a bacterial species towards phage-resistant strains with potential general implications for the diversity and functional properties of strains within phage-exposed populations of marine bacteria. We propose, therefore, that phage-mediated selection for resistant strains contributes to the large strain diversity observed for a number of specific bacterial and cyanobacterial species”

“This study has shown that phages drive the strain diversification of a bacterial population. Responses to the bacterial diversification by counter mutations in the phage population providing broad host range phages or new phages are known to occur (e.g. Mizoguchi et al., 2003), but have yet to be studied for marine bacteria. Thus, we are still only scratching the surface of the complex network of phageâhost interactions that contributes to the evolution of phages and bacteria in natural environments.”

Weitz et al. (2005)

Cited by Clokie et al. (2011) as a support for the argument that if there is a cost for a host to be resistant to a phage, the diversity of host will increase.