Host-hijacking and planktonic piracy: how phages command the microbial high seas

Microbial communities living in the oceans are major drivers of global biogeochemical cycles. With nutrients limited across vast swathes of the ocean, marine microbes eke out a living under constant assault from predatory viruses. Viral concentrations exceed those of their bacterial prey by an order of magnitude in surface water, making these obligate parasites the most abundant biological entities in the ocean. Like the pirates of the 17th and 18th centuries that hounded ships plying major trade and exploration routes, viruses have evolved mechanisms to hijack microbial cells and repurpose their cargo and indeed the vessels themselves to maximise viral propagation. Phenotypic reconfiguration of the host is often achieved through Auxiliary Metabolic Genes - genes originally derived from host genomes but maintained and adapted in viral genomes to redirect energy and substrates towards viral synthesis. In this review, we critically evaluate the literature describing the mechanisms used by bacteriophages to reconfigure host metabolism and to plunder intracellular resources to optimise viral production. We also highlight the mechanisms used when, in challenging environments, a 'batten down the hatches' strategy supersedes that of 'plunder and pillage'. Here, the infecting virus increases host fitness through phenotypic augmentation in order to ride out the metaphorical storm, with a concomitant impact on host substrate uptake and metabolism, and ultimately, their interactions with their wider microbial community. Thus, the traditional view of the virus-host relationship as predator and prey does not fully characterise the variety or significance of the interactions observed. Recent advances in viral metagenomics have provided a tantalising glimpse of novel mechanisms of viral metabolic reprogramming in global oceans. Incorporation of these new findings into global biogeochemical models requires experimental evidence from model systems and major improvements in our ability to accurately predict protein function from sequence data.