Background/Question/Methods Sulfur cycling microbial communities in salt marsh sediment mediate an ecosystem-scale recycling and detoxification system central to coastal marsh productivity. Without the actions of sulfur oxidizing bacteria, grass and rush root respiration would be subject to toxic concentrations of sulfide, which is produced by sulfate reducing bacteria that thrive on the carbon compounds produced by living roots. Despite the prevalence and importance of sulfur cycling microbes in coastal environments, they are currently not well represented in metagenomic databases. The recent emergence of deep shotgun metagenomic datasets from multiple research groups has presented the opportunity to collaboratively coalesce datasets from ecologically diverse salt marsh environments, enabling investigation of commonalities and differences among microbial genes, organisms, and communities across contrasting latitudes and dominant vegetation. Here, we implemented a bioinformatic pipeline to assemble (MEGAHIT), bin (metaWRAP), functionally-annotate (DRAM), and compare (GTDB-Tk, Anvi’o, PATRIC) metagenomes using publicly available, deeply sequenced datasets from sediments under smooth cordgrass (Sporobolus alterniflorus), saltmeadow cordgrass (Sporobolus pumilus), and black needlerush (Juncus roemerianus), sampled in marshes in Alabama and Massachusetts. Results/Conclusions Assembly and binning with stringent criteria resulted in the reconstruction of 21 and 17 bacterial MAGs encoding complete pathways for sulfur oxidation and sulfate reduction, respectively, all of which were > 90 % complete with < 5% contamination. All sulfur oxidizing MAGs belonged to Proteobacteria while sulfate reducing MAGs were affiliated with Acidobacteria, Bacteroidota, Gemmatimonadota, and Desulfobacterota phyla. Most of these MAGs belonged to uncultured lineages defined by alphanumeric identifiers including the “UBA”, “SG8”, and “RBG” datasets. A read recruitment analysis showed patterns of distribution among these lineages based on location and plant-host. In sum, we provide an analytical approach designed to distill MAGs from deeply sequenced datasets and support comparisons with shallow datasets, revealing an underexplored reservoir of novel lineages and metabolic potential within the microbial communities inhabiting ecologically diverse salt marsh environments.
