Abundant and persistent sulfur‐oxidizing microbial populations are responsive to hypoxia in the Chesapeake Bay

Abstract

The number, size and severity of aquatic low-oxygen dead zones are increasing worldwide. Microbial processes in low-oxygen environments have important ecosystem-level consequences, such as denitrification, greenhouse gas production and acidification. To identify key microbial processes occurring in lowoxygen bottom waters of the Chesapeake Bay, we sequenced both 16S rRNA genes and shotgun metagenomic libraries to determine the identity, functional potential and spatiotemporal distribution of microbial populations in the water column. Unsupervised clustering algorithms grouped samples into three clusters using water chemistry or microbial communities, with extensive overlap of cluster composition between methods. Clusters were strongly differentiated by temperature, salinity and oxygen. Sulfuroxidizing microorganisms were found to be enriched in the low-oxygen bottom water and predictive of hypoxic conditions. Metagenome-assembled genomes demonstrate that some of these sulfuroxidizing populations are capable of partial denitrification and transcriptionally active in a prior study. These results suggest that microorganisms capable of oxidizing reduced sulfur compounds are a previously unidentified microbial indicator of low oxygen in the Chesapeake Bay and reveal ties between the sulfur, nitrogen and oxygen cycles that could be important to capture when predicting the ecosystem response to remediation efforts or climate change.

Major trends and environmental correlates of spatiotemporal shifts in the distribution of genes compared to a biogeochemical model simulation in the Chesapeake Bay

“…AmoABC genes are evolutionarily similar to methane monooxygenase genes (Holmes et al 1995), which are not differentiated in KEGG, but methane oxidizing taxonomic groups made up only 0.9-4.0% of the total amoABC gene signal. Additionally, we searched for bacterial amoABC genes at the oxycline in another metagenomic dataset taken from multiple depths within the water column at CB3.3C (Arora-Williams et al 2022), but did not find any amoA genes with a . CC-BY-NC 4.0 International license available under a (which was not certified by peer review) is the author/funder, who has granted bioRxiv a license to display the preprint in perpetuity.…”

“…Previous work in the Bay has identified major drivers of community changes and abundant and active taxa and functions that were under-appreciated within this ecosystem. Seasonal changes have been identified as the most significant driver of changes in community composition (Arora-Williams et al 2022;Kan et al 2006;Wang et al 2020), with shifts associated with spatial distribution using 16S rRNA gene sequencing (Arora-Williams et al 2022;Wang et al 2020) along the length of the Bay being of secondary importance. Community composition (Crump et al 2007) and gene expression (Hewson et al 2014) change in response to low oxygen conditions, with specific taxa and functions predictive of hypoxic conditions (Arora-Williams et (Crump et al 2007), with expression of genes associated with sulfate reduction increasing in deep anoxic water (Hewson et al 2014).…”

“…Community composition (Crump et al 2007) and gene expression (Hewson et al 2014) change in response to low oxygen conditions, with specific taxa and functions predictive of hypoxic conditions (Arora-Williams et (Crump et al 2007), with expression of genes associated with sulfate reduction increasing in deep anoxic water (Hewson et al 2014). Through analysis of taxa and genome composition from metagenome assembled genome analysis, sulfide oxidation coupled to at least partial denitrification was identified as a common microbial response to low oxygen in the water column that was previously under-appreciated within this ecosystem (Arora-Williams et al 2022). Metagenomic analysis could identify other currently under-appreciated microbially mediated processes or reveal delayed or accelerated on-set of specific processes that could have a substantial influence on nutrient cycles, oxygen concentrations, or greenhouse gas emissions.…”

“…Hall and colleagues (Hall et al 2018) argue that a robust conceptual framework is needed to link the resident microbes to the processes they mediate. Although a few studies have been conducted within aquatic ecosystems to link microbial populations, genes, transcripts and proteins to the observed changes in chemical concentrations in these systems (Arora-Williams et al 2022;Haas et al 2021;Louca et al 2016a;Preheim et al 2016;Reed et al 2014), much work remains to be done to understand how such linkages vary across ecosystems. As we continue to map genes to their ecosystems using a framework that provides a mechanistic understanding of the factors that influence these processes, our understanding of these relationships will continue to improve and lead to further discoveries The Chesapeake Bay (hereafter, "the Bay") is an important example of a critical coastal ecosystem that has experienced significant declines in ecosystem health and productivity associated with nutrient and sediment pollution.…”

“…We have previously demonstrated that differences in sample storage (i.e. freezing the filter on the boat or freezing water and filtering in the lab) does not significantly change the microbial community composition (Arora-Williams et al 2022). This separate dataset was only used to verify the distribution of genes in the water column, but was not used for other parts of the analysis because comparable environmental measurements (e.g.…”