This blog was originally posted on the Earth System Science @Exeter blog in November 2013.
Marine bacteria are a key component of oceanic ecosystems and are important drivers of primary productivity and nutrient cycling. Phages (viruses of bacteria) play a key role in their hosts ecology. In addition to aiding the transfer of genes between bacteria, they are also a major cause of mortality; responsible for infecting and reproducing inside bacterial cells which can eventually lead to them bursting open, killing the cell and releasing new phages into the environment. This process is important as it recycles nutrients and may also aid with transport of some material to the deep ocean. Both bacteria and phage evolve on rapid timescales to attempt to evade or exploit the other – however, the basic mode of coevolution between bacteria and phage is unclear. Understanding how these communities interact and respond to each other is therefore an important step towards unravelling the ecological and evolutionary processes in these systems and towards greater biological realism for ocean carbon modelling.
Cross infection data from the Moebus and Nattkemper 1981 North Atlantic dataset reanalysed by Flores et al. 2013. Each spot indicates the precense of infection between a bacterial host isolate (rows) and a phage isolate (columns). Squares highlight the large scale modular pattern, whilst many of the modules contain a nested pattern within them. White spots indicate an infection between two different module classes.
One type of data exploring the community structure between bacteria and phage comes in the form of a binary infection network – formed by checking which bacterial isolates each phage isolate can infect – where presence of infection is indicated by a 1 and absence of infection by a 0. The largest dataset of this kind was collected by Moebus and Nattkemper 1981 in the North Atlantic and reanalysis by Flores et al. 2013 showed that it displayed what we term a nested-modular structure. This means that there exists specific groupings of phage which can infect specific groupings of bacteria with few infections between different groupings (modular), but also that within each of these modules there is a pattern such that there is a gradient in susceptibility to infection from the within module bacteria and a gradient of ability to infect from the within module phage (nested). The size of this dataset makes it useful as a means to look for signals of the coevolutionary processes that led to its formation.
We recently published a paper in Interface Focus exploring interaction networks formed by models of coevolutionary dynamics between bacteria and phage motivated by the question: what mechanisms are required to promote a nested-modular community structure? In this paper we explore what we term the relaxed lock-and-key model that represents the fitting of phage tail fibres (keys) to bacterial cell receptors (locks) that sustains high diversity of bacteria and phage and compare the structural properties of the networks formed in our model with those in the Moebus and Nattkemper 1981 data.
We find that our model networks can create high diversity communities of phage and bacteria with nested-modular structures and that the relaxed lock-and-key mode of coevolution provides a plausible explanation for these features being found in ocean samples. We also highlight how it can be difficult to directly compare experimental and model data and suggest that productive avenues for future research will be to look at other large scale cross-infection datasets to see if the nested-modular structures observed in the North Atlantic are characteristic of a coevolutionary signal across phage-host systems. In addition the development of experimental techniques to gain quantitative information about the interaction strengths in these types of data and the analytical techniques with which to analyse them will be useful tools for understanding phage-bacteria coevolution.
Phage on toast 