SAR202 Genomes from the Dark Ocean Predict Pathways for the Oxidation of Recalcitrant Dissolved Organic Matter


Citation
Landry et al. (2017). mBio 8 (2)
Names (3)
“Monstramariaceae” “Monstramariales” “Monstramaria”
Subjects
Microbiology Virology
Abstract
ABSTRACT Deep-ocean regions beyond the reach of sunlight contain an estimated 615 Pg of dissolved organic matter (DOM), much of which persists for thousands of years. It is thought that bacteria oxidize DOM until it is too dilute or refractory to support microbial activity. We analyzed five single-amplified genomes (SAGs) from the abundant SAR202 clade of dark-ocean bacterioplankton and found they encode multiple families of paralogous enzymes involved in carbon catabolism, including several families of oxidative enzymes that we hypothesize participate in the degradation of cyclic alkanes. The five partial genomes encoded 152 flavin mononucleotide/F420-dependent monooxygenases (FMNOs), many of which are predicted to be type II Baeyer-Villiger monooxygenases (BVMOs) that catalyze oxygen insertion into semilabile alicyclic alkanes. The large number of oxidative enzymes, as well as other families of enzymes that appear to play complementary roles in catabolic pathways, suggests that SAR202 might catalyze final steps in the biological oxidation of relatively recalcitrant organic compounds to refractory compounds that persist. IMPORTANCE Carbon in the ocean is massively sequestered in a complex mixture of biologically refractory molecules that accumulate as the chemical end member of biological oxidation and diagenetic change. However, few details are known about the biochemical machinery of carbon sequestration in the deep ocean. Reconstruction of the metabolism of a deep-ocean microbial clade, SAR202, led to postulation of new biochemical pathways that may be the penultimate stages of DOM oxidation to refractory forms that persist. These pathways are tied to a proliferation of oxidative enzymes. This research illuminates dark-ocean biochemistry that is broadly consequential for reconstructing the global carbon cycle.
Authors
Publication date
2017-05-03
DOI
10.1128/mbio.00413-17