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Denitrifying bacterial assemblages respond to environmental conditions of a shallow estuary

ABSTRACT: Molecular analysis of dissimilatory nitrite reductase genes (nirS) was conducted using a customized microarray containing 165 nirS probes (archetypes) to identify members of sedimentary denitrifying communities. The goal of this study was to examine denitrifying community responses to changing environmental variables over spatial and temporal scales in the New River Estuary (NRE), NC, USA. Multivariate statistical analyses revealed three denitrifier assemblages and uncovered “generalist” and “specialist” archetypes based on the distribution of archetypes within these assemblages. Generalists, archetypes detected in all samples during at least one season, were commonly world-wide found in estuarine and marine ecosystems, comprised 11-29% of the abundant NRE archetypes. Archetypes found in a particular site, “specialists”, were found to co-vary based on site specific conditions. Archetypes specific to the lower estuary in winter were designated Cluster I and significantly correlated by sediment Chl a and porewater Fe2+. A combination of specialist and more widely distributed archetypes formed Clusters II and III, which separated based on salinity and porewater H2S, respectively. The co-occurrence of archetypes correlated with different environmental conditions highlights the importance of habitat type and niche differentiation among denitrifying communities and supports the essential role of individual community members in overall ecosystem function.

ORGANISM(S): uncultured bacterium synthetic construct

PROVIDER: GSE98190 | GEO | 2017/05/02

SECONDARY ACCESSION(S): PRJNA384981

REPOSITORIES: GEO

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Project description:The community composition (in terms of abundance, distribution and contribution of diverse clades) of bacteria involved in nitrogen transformations in the oxygen minimum zones may be related to the rates of fixed N loss in these systems. The abundance of both denirifying and anammox bacteria, and the assemblage composition of denitrifying bacteria were investigated in the Eastern Tropical South Pacific and the Arabian Sea using assays based on molecular markers for the two groups of bacteria. The abundance and distribution of bacteria associated with the fixed N removal processes denitrification and anammox were investigated using quantitative PCR for genes encoding nitrite reductase (nirK and nirS) in denitrifying bacteria and hydrazine oxidase(hzo) and 16S rRNA genesin anammox bacteria. All of these genes had depth distributions with maxima associated with the secondary nitrite maximum in low oxygen waters. NirS was mch more abundant than nirK, and much more abundant than the 16S rRNA gene from anammox bacteria. The ratio of hzo:16S rRNA for anammox was low and variable implying greater unexplored diversity in the the hzo gene. Assemblage composition of the abundant nirS-type denitrifiers was evaluated using a funcitonal gene microarray. Of the nirS archetypes represented on the microarray, very few occurred speficically in one region or depth interval, but the assemblages varied significantly. Community composition of denitrifiers based on microarray analysis of the nirS gene was most different between geographical regions. Within each region, the surface layer and OMZ assemblages clustered distinctly. Thus, in addition to spatial and temporal variation in denitrificaiton and anammox rates, both microbial abundance and community composition also vary between OMZ regions and depths. Two color array (Cy3 and Cy5): the universal standard 20-mer oligo is printed to the slide with a 70-mer oligo (an archetype). Environmental DNA sequences (fluoresced with Cy3) within 15% of the 70-mer conjugated to a 20-mer oligo (fluoresced with Cy5) complementary to the universal standard will bind to the oligo probes on the array. Signal is the ratio of Cy3 to Cy5. Three replicate probes were printed for each archetype. Two replicate arrays were run on duplicate targets.

Project description:Increasing atmospheric CO2 concentrations are causing decreased pH over vast expanses of the ocean. This decreasing pH may alter biogeochemical cycling of carbon and nitrogen via the microbial process of nitrification, a key process that couples these cycles in the ocean, but which is often sensitive to acidic conditions. Recent reports indicate a decrease in oceanic nitrification rates under experimentally lowered pH. How composition and abundance of ammonia oxidizing bacteria (AOB) and archaea (AOA) assemblages respond to decreasing oceanic pH, however, is unknown. We sampled microbes from two different acidification experiments and used a combination of qPCR and functional gene microarrays for the ammonia monooxygenase gene (amoA) to assess how acidification alters the structure of ammonia oxidizer assemblages. We show that despite widely different experimental conditions, acidification consistently altered the community composition of AOB by increasing the relative abundance of taxa related to the Nitrosomonas ureae clade. In one experiment this increase was sufficient to cause an increase in the overall abundance of AOB. There were no systematic shifts in the community structure or abundance of AOA in either experiment. These different responses to acidification underscore the important role of microbial community structure in the resiliency of marine ecosystems. amoA gene diversity from two ocean acidification experiments, Monterey Bay experiment (two time points, ambient and acidified) and Vineyard Sound experiment (ambient and acifidied, with and without nutrients) examined with 2 two-color arrays (Cy3 and Cy5): the universal standard 20-mer oligo is printed to the slide with a 70-mer oligo (an archetype). Environmental DNA sequences (fluoresced with Cy3) within 15% of the 70-mer conjugated to a 20-mer oligo (fluoresced with Cy5) complementary to the universal standard will bind to the oligo probes on the array. Signal is the ratio of Cy3 to Cy5.

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Denitrifying bacterial assemblages respond to environmental conditions of a shallow estuary

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