Influence of Human Activities on Broad-Scale Estuarine-Marine Habitats Using Omics-Based Approaches Applied to Marine Sediments

Abstract

Rapid urban expansion and increased human activities have led to the progressive deterioration of many marine ecosystems. The diverse microbial communities that inhabit these ecosystems are believed to influence large-scale geochemical processes and, as such, analyzing their composition and functional metabolism can be a means to assessing an ecosystem’s resilience to physical and chemical perturbations, or at the very least provide baseline information and insight into future research needs. Here we show the utilization of organic and inorganic contaminant screening coupled with metabolomics and bacterial 16S rRNA gene sequencing to assess the microbial community structure of marine sediments and their functional metabolic output. The sediments collected from Moreton Bay (Queensland, Australia) contained low levels of organic and inorganic contaminants, typically below guideline levels. The sequencing dataset suggest that sulfur and nitrite reduction, dehalogenation, ammonia oxidation, and xylan degradation were the major metabolic functions. The community metabolites suggest a level of functional homogeneity down the 40-cm core depth sampled, with sediment habitat identified as a significant driver for metabolic differences. The communities present in river and sandy channel samples were found to be the most active, with the river habitats likely to be dominated by photoheterotrophs that utilized carbohydrates, fatty acids and alcohols as well as reduce nitrates to release atmospheric nitrogen and oxidize sulfur. Bioturbated mud habitats showed overlapping faunal activity between riverine and sandy ecosystems. Nitrogen-fixing bacteria and lignin-degrading bacteria were most abundant in the sandy channel and bioturbated mud, respectively. The use of omics-based approaches provide greater insight into the functional metabolism of these impacted habitats, extending beyond discrete monitoring to encompassing whole community profiling that represents true phenotypical outputs. Ongoing omics-based monitoring that focuses on more targeted pathway analyses is recommended in order to quantify the flux changes within these systems and establish variations from these baseline measurements.

Using Community Science to Reveal the Global Chemogeography of River Metabolomes

“…Over the past several years, this definition has been extended to encompass all metabolites present in complex environmental systems for which it is difficult to attribute specific metabolites to specific organisms [ 20 , 21 , 22 , 23 , 24 ]. Different metabolomic techniques have been implemented across fields to enhance our understanding of microbial communities [ 25 , 26 ], anthropogenic activities and pollution sources [ 27 , 28 , 29 ], and potential bioremediation strategies [ 30 ]. Recently, environmental metabolomics, enabled by ultrahigh-resolution mass spectrometry, has allowed us to reveal connections between OM character, reactivity, and biochemical transformations within and across river ecosystems [ 15 , 17 , 18 , 31 , 32 , 33 , 34 , 35 ].…”

Microbial Community Diversity of Coral Reef Sediments on Liuqiu Island, Southwestern Taiwan

“…Many bacteria genera were reported as indicators of pathogenicity and pollution [111][112][113][114][115][116][117]. For example, in a study of the South China Sea, the genera Vibrio, Pseudoalteromonas, Escherichia-Shigella, Psychrobacter, and Pseudomonas were used as environmental indicators to evaluate the impact of human activity [34].…”

Omics-based ecosurveillance for the assessment of ecosystem function, health, and resilience

“…To some degree, the importance of this gap between the measurement of a substance and the impact will vary with specific circumstances (e.g. season), but if the goal is a healthy and sustainable environment then lack of such information may hinder meaningful policy development and effective mitigation/harm reduction [ 9 ].…”

“…Of particular interest is our current understanding of microbial function within environmental microbiomes, which stems from conventional ecology-based surveys and the utility of more recent environmental genomics approaches (eDNA). Attempts to harmonise these data with physicochemical parameters of biotic/abiotic ecosystem (dys)function arising from environmental metabolomics data have been limited and show varying levels of success [ 9 , 21 , 52 ]. This is potentially biased towards a limited group of microbes (e.g.…”