Abstract
Viruses modulate microbial communities and alter ecosystem functions. However, due to cultivation bottlenecks, specific virus-host interaction dynamics remain cryptic. In this study, we examined 127 single-cell amplified genomes (SAGs) from uncultivated SUP05 bacteria isolated from a model marine oxygen minimum zone (OMZ) to identify 69 viral contigs representing five new genera within dsDNA Caudovirales and ssDNA Microviridae. Infection frequencies suggest that ∼1/3 of SUP05 bacteria is viral-infected, with higher infection frequency where oxygen-deficiency was most severe. Observed Microviridae clonality suggests recovery of bloom-terminating viruses, while systematic co-infection between dsDNA and ssDNA viruses posits previously unrecognized cooperation modes. Analyses of 186 microbial and viral metagenomes revealed that SUP05 viruses persisted for years, but remained endemic to the OMZ. Finally, identification of virus-encoded dissimilatory sulfite reductase suggests SUP05 viruses reprogram their host's energy metabolism. Together, these results demonstrate closely coupled SUP05 virus-host co-evolutionary dynamics with the potential to modulate biogeochemical cycling in climate-critical and expanding OMZs.
Highlights
Microbial communities are critical drivers of nutrient and energy conversion process in natural and engineered ecosystems (Falkowski et al, 2008)
single-cell amplified genomes (SAGs) affiliated with SUP05 (n = 127) and Arctic96BD-19 (n = 9) populations were subsequently whole genome shotgun sequenced on the Illumina HiSeq platform
Most (113/127) SUP05 SAGs fell into two major operational taxonomic units (OTUs) or subclades, based on SSU rRNA gene sequence clustering at the 97% identity threshold—SUP05_01 (n = 65) and SUP05_03 (n = 48) (Figure 1—figure supplement 2)
Summary
Microbial communities are critical drivers of nutrient and energy conversion process in natural and engineered ecosystems (Falkowski et al, 2008). The vast majority of microbes and viruses remain uncultivated and their diversity is extensive, so that model system-based measurements rarely reflect the network properties of natural microbial communities. While cultureindependent methods, such as metagenomics and metatranscriptomics, can illuminate latent and expressed metabolic potential of microbial (Frias-Lopez et al, 2008; Venter et al, 2004; Stewart et al, 2012; DeLong et al, 2006) or viral communities (Angly et al, 2006; Hurwitz et al, 2013; Mizuno et al, 2013), interactions between community members remain difficult to resolve.
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