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Kill the Winner hypothesis

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The "Kill the Winner" hypothesis (KTW) is a model of population growth involving prokaryotes, viruses and protozoans that links trophic interactions to biogeochemistry. It is based on the concept of prokaryotes taking one of two reactions to limited resources: "competition", that is, that priority directed to growth of the population, or a "winner"; and "defense", where the resources are directed to survival against attacks. It is then assumed that the better strategy for a phage, or virus which attacks prokaryotes, is to concentrate on the "winner", the most active population (possibly the most abundant). This tends to moderate the relative populations of the prokaryotes, rather than the "winner take all". The model is related to the Lotka–Volterra equations. Current understanding on KTW stems from our knowledge of lytic viruses and their host populations.

The competition specialist, or “winner”, often corresponds to the most abundant population in the community.[1] Their abundance and activity increase when the population competes for a shared limiting resource (e.g. phosphate) and win. The resource can exist as a free form or something that needs to be sequestered from biomass. Competition specialists (predators, grazers, parasites) are expected to dominate in oligotrophic environments, whereas they would be the losers in a eutrophic environment.[1] The increased abundance and activity of the “winner” also increases viral predation.

Defense specialists, tend to invest resources in avoidance strategies that may result in reduced growth and reproduction of the population; hence, the “loser” does not increase viral predation.[1] Defense specialists are expected to dominate in eutrophic environments.[1]

KTW represents an idealized microbial food web with mathematical parameters that only account for viral predation we have studied in vitro.[2][1] It is related to Lotka-Volterra type equations. The KTW model is based on the assumption of stable environmental conditions and is widely applicable to different trophic levels and complex microbial systems; however, it may not always be correct.[3][1] Because of its reliance of stable environmental conditions, it can only predict a small time point through a microbial community’s history. It also disregards the fact that a prokaryotic species can be attacked by more than one virus population at a time. KTW will become more accurate ,or even replaced, as more methodological limitations are explored for microbial communities. Piggyback-the-Winner (PTW) is a similar dynamic model of bacteria-virus interactions but incorporates the viral life cycle into the model.[4] PTW model states that the nonlinear relationship between viruses and prokaryotes is observed due to viral dynamics being suppressed at high host densities and super-infection exclusion, rather than developed “resistance” as suggested by the KTW model.[5]

See also

References

  1. ^ a b c d e f Winter C, Bouvier T, Weinbauer MG, Thingstad TF (March 2010). "Trade-offs between competition and defense specialists among unicellular planktonic organisms: the "killing the winner" hypothesis revisited". Microbiology and Molecular Biology Reviews. 74 (1): 42–57. doi:10.1128/MMBR.00034-09. PMC 2832346. PMID 20197498.
  2. ^ Koskella B, Brockhurst MA (September 2014). "Bacteria-phage coevolution as a driver of ecological and evolutionary processes in microbial communities". FEMS Microbiology Reviews. 38 (5): 916–31. doi:10.1111/1574-6976.12072. PMC 4257071. PMID 24617569.
  3. ^ Korytowski DA, Smith H (May 2017). "Permanence and Stability of a Kill the Winner Model in Marine Ecology". Bulletin of Mathematical Biology. 79 (5): 995–1004. arXiv:1605.01017. doi:10.1007/s11538-017-0265-6. PMID 28349407. S2CID 3959038.
  4. ^ Silveira CB, Rohwer FL (2016-07-06). "Piggyback-the-Winner in host-associated microbial communities". NPJ Biofilms and Microbiomes. 2 (1): 16010. doi:10.1038/npjbiofilms.2016.10. PMC 5515262. PMID 28721247.
  5. ^ Weitz JS, Beckett SJ, Brum JR, Cael BB, Dushoff J (September 2017). "Lysis, lysogeny and virus-microbe ratios". Nature. 549 (7672): E1–E3. Bibcode:2017Natur.549E...1W. doi:10.1038/nature23295. PMID 28933438. S2CID 4463234.

Further reading