Piggybacking Instead of Killing: New Insights Into Virus Community Dynamics

The human microbiome is an important component of human health and disease. It is an ecosystem of microbes that exists in and on humans, and can affect disease states through disturbances in composition, diversity, metabolism, etc. Understanding the human microbiome will not only allow us to better understand human health, but it will also allow us to treat medical conditions in new and effective ways (e.g. Fecal Microbiota Transplants).

Most studies to date have focused on understanding the bacterial component of the human microbiome. While this route has proven beneficial, it fails to consider the more complex system at large. Bacteria are interacting with communities of microbes including viruses (including bacteriophages which are viruses that infect only bacteria), and understanding these phage-bacteria dynamics is crucial for understanding the true human microbiome system. Our paper this week provides such insights into the dynamics of virus communities and their interactions with their bacterial hosts.

This paper by Knowles et al builds off of two observations. The first is that many phage-bacteria communities have been modeled to follow the "kill-the-winner" model of predation. This model states that lytic phages target and kill the most successful bacteria (the "winners"), thus preventing dominance of a single successful bacterium and maintaining relatively even bacterial distributions. The second observation is that many community phages are in fact temperate (they can exist while silently integrated in their bacterial host genome) and are poorly incorporated into the existing kill-the-winner model. To reconcile this disagreement, Knowles et al developed an extended model called "piggyback-the-winner".

Examples of cyclical predator/prey relationships which
are observed in phage-bacteria systems. SOURCE

The proposed "piggyback-the-winner" model states that instead of "killing the winner" when bacterial density increases, lytic activity is instead suppressed and an increased proportion of phages enter their dormant, integrated infectious state. This model is based largely on the observation that virus density often decreases as "microbe" density increases. The group provides a variety of sources of evidence to support their model in viral communities at large (please read the paper for details).

One point of concern with this paper is that the group relies heavily on linear relationships between bacteria and phages, when we know that these predator-prey dynamics often follow cyclical patterns. This is not to say that the study is flawed or less valuable, but it would have been nice to hear more about the implications of the more accurate cyclical models over the linear models that were used. This is especially relevant because some of the scatter plots seem to be approaching more of a cyclical pattern than linear.

tl;dr

So what can we take away from this paper? Knowles et al is proposing a new predator-prey model called the "piggyback-the-winner" model which essentially states that more microbes equals fewer viruses. The group primarily supports their model with linear abundance modeling from a variety of microbiomes, spanning from oceans to humans. This is a valuable step toward our understanding of the entire microbiome (bacteria, viruses, etc) and will inform future studies, both environmental and medical. We are also likely to see this model develop as more sophisticated techniques are used.

If you enjoyed our discussion, go ahead and check out the full paper in Nature. There you can find all of the details that we skimmed over here in our brief discussion. It is actually a relatively short read so it is worth checking out. And of course if you have any comments to add or questions to ask, speak out in the comments below, reach out on Twitter, or send an email!

Works Cited

Knowles B, Silveira CB, Bailey BA, Barott K, Cantu VA, Cobián-Güemes AG, Coutinho FH, Dinsdale EA, Felts B, Furby KA, George EE, Green KT, Gregoracci GB, Haas AF, Haggerty JM, Hester ER, Hisakawa N, Kelly LW, Lim YW, Little M, Luque A, McDole-Somera T, McNair K, de Oliveira LS, Quistad SD, Robinett NL, Sala E, Salamon P, Sanchez SE, Sandin S, Silva GG, Smith J, Sullivan C, Thompson C, Vermeij MJ, Youle M, Young C, Zgliczynski B, Brainard R, Edwards RA, Nulton J, Thompson F, & Rohwer F (2016). Lytic to temperate switching of viral communities. Nature, 531 (7595), 466-70 PMID: 26982729