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. 2023 Sep 7:14:1235906.
doi: 10.3389/fmicb.2023.1235906. eCollection 2023.

Natural and anthropogenic carbon input affect microbial activity in salt marsh sediment

Affiliations

Natural and anthropogenic carbon input affect microbial activity in salt marsh sediment

Erin S Frates et al. Front Microbiol. .

Abstract

Salt marshes are dynamic, highly productive ecosystems positioned at the interface between terrestrial and marine systems. They are exposed to large quantities of both natural and anthropogenic carbon input, and their diverse sediment-hosted microbial communities play key roles in carbon cycling and remineralization. To better understand the effects of natural and anthropogenic carbon on sediment microbial ecology, several sediment cores were collected from Little Sippewissett Salt Marsh (LSSM) on Cape Cod, MA, USA and incubated with either Spartina alterniflora cordgrass or diesel fuel. Resulting shifts in microbial diversity and activity were assessed via bioorthogonal non-canonical amino acid tagging (BONCAT) combined with fluorescence-activated cell sorting (FACS) and 16S rRNA gene amplicon sequencing. Both Spartina and diesel amendments resulted in initial decreases of microbial diversity as well as clear, community-wide shifts in metabolic activity. Multi-stage degradative frameworks shaped by fermentation were inferred based on anabolically active lineages. In particular, the metabolically versatile Marinifilaceae were prominent under both treatments, as were the sulfate-reducing Desulfovibrionaceae, which may be attributable to their ability to utilize diverse forms of carbon under nutrient limited conditions. By identifying lineages most directly involved in the early stages of carbon processing, we offer potential targets for indicator species to assess ecosystem health and highlight key players for selective promotion of bioremediation or carbon sequestration pathways.

Keywords: biogeochemistry; carbon cycle; metabolic activity; microbial diversity; salt marsh.

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Conflict of interest statement

The authors declare that the research was conducted in the absence of any commercial or financial relationships that could be construed as a potential conflict of interest.

Figures

FIGURE 1
FIGURE 1
Photograph of in situ core incubations in the Berry Pond at Little Sippewissett Salt Marsh.
FIGURE 2
FIGURE 2
Multiple dimensional scaling (MDS) plot revealing the similarity between microbial communities according to Aitchison distance metrics. Blue points represent control treatment B (21 day incubated HPG controls) communities, purple points represent control treatment F (4 day incubated HPG controls) communities, and gray points represent communities from remaining treatments. Point shape represents horizon depth (p = 0.118; value determined for active communities).
FIGURE 3
FIGURE 3
Barplots revealing the relative abundance of active phyla within each sediment horizon of the 21-day (control treatment B) and 4-day (control treatment F) cores. Communities with less than 5% relative abundance were pooled, as were ASVs of indeterminate phyla.
FIGURE 4
FIGURE 4
Multiple dimensional scaling (MDS) plot revealing the similarity between microbial communities according to Aitchison distance metrics. Blue points represent control treatment B (21 day incubated HPG controls) communities, green points represent treatment C (21 day Spartina and HPG incubations) communities, red points represent treatment D (21 day Spartina and 4 day HPG incubations) communities, and gray points represent communities from remaining treatments. Point shape represents horizon depth (pBD = 0.005, pBE = 0.008, pDE = 0.012; values determined for active communities).
FIGURE 5
FIGURE 5
Barplots revealing the relative abundance of active phyla within each sediment horizon of the control core (group B), early stage Spartina treatment (treatment C), and late stage Spartina treatment (treatment D). Communities with less than 5% relative abundance were pooled, as were ASVs of indeterminate phyla.
FIGURE 6
FIGURE 6
Enrichment figures depicting the relative abundance of select active families within each sediment horizon. Bars indicate the ratio between the control (control treatment B, blue) and treatment [treatment C (A) and treatment D (B), yellow] communities. Faded bars represent ratios wherein the control group has a relative abundance of zero.
FIGURE 7
FIGURE 7
Enrichment figures depicting the relative abundance of active SRB families within each sediment horizon. Bars indicate the ratio between the control groups (blue) and their respective treatment group (yellow) communities. Faded bars represent ratios wherein the control group has a relative abundance of zero.
FIGURE 8
FIGURE 8
Schematic diagram demonstrating our proposed model of microbially mediated Spartina breakdown in LSSM. We attribute the degradation of the cordgrass’s three primary components to a multi-stage process driven by a range of taxa poised to respond to a variety of downstream Spartina metabolites.
FIGURE 9
FIGURE 9
Multiple dimensional scaling (MDS) plot revealing the similarity between microbial communities according to Aitchison distance metrics. Blue points represent control treatment F (4 day incubated HPG controls) communities, yellow points represent treatment G (4 day diesel HPG incubations), and gray points represent communities from remaining treatments. Point shape represents horizon depth (p = 0.028; value determined for active communities).
FIGURE 10
FIGURE 10
Barplots revealing the relative abundance of active phyla within each sediment horizon of the control core (control treatment F) and diesel treatment (treatment G). Communities with less than 5% relative abundance were pooled, as were ASVs of indeterminate phyla.
FIGURE 11
FIGURE 11
Enrichment figures depicting the relative abundance of select, active families within each sediment horizon. Bars indicate the ratio between the control (group F, blue) and treatment (group G, yellow) communities. Faded bars represent ratios wherein the control group has a relative abundance of zero.
FIGURE 12
FIGURE 12
Flowchart demonstrating our proposed model of microbially mediated diesel breakdown in LSSM. Here, we focus on the degradation of small aromatic hydrocarbons, which is likely driving the community shift in our anthropogenic experiment.

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