Using meta-omics of contaminated sediments to monitor changes in pathways relevant to climate regulation.

Microbially mediated biogeochemical processes are crucial for climate regulation and may be disrupted by anthropogenic contaminants. To better manage contaminants, we need tools that make real-time causal links between stressors and altered microbial functions, and the potential consequences for ecosystem services such as climate regulation. In a manipulative field experiment, we used metatranscriptomics to investigate the impact of excess organic enrichment and metal contamination on the gene expression of nitrogen and sulfur metabolisms in coastal sediments. Our gene expression data suggest that excess organic enrichment results in (i) higher transcript levels of genes involved in the production of toxic ammonia and hydrogen sulfide and (ii) lower transcript levels associated with the degradation of a greenhouse gas (nitrous oxide). However, metal contamination did not have any significant impact on gene expression. We reveal the genetic mechanisms that may lead to altered productivity and greenhouse gas production in coastal sediments due to anthropogenic contaminants. Our data highlight the applicability of metatranscriptomics as a management tool that provides an immense breadth of information and can identify potentially impacted process measurements that need further investigation.

Core sediment bacteria drive community response to anthropogenic contamination over multiple environmental gradients.

In this study, 454 pyrosequencing of the 16S rRNA gene was used to investigate sediment bacterial community response to contaminant disturbance across six estuaries with differing levels of 'modification'. We observed a significant influence of metal and polycyclic aromatic hydrocarbon contaminants in shaping bacterial community composition, structure and diversity, with metals being the more influential contaminant. An abundant and pervasive 'core' set of bacteria found in every sample were largely responsible for mediating community response to contamination. These 13 core operational taxonomic units were mostly comprised of Gamma-, Delta-, Alphaproteobacteria and Acidobacteria. Sediment silt and metals together explained the most variation in bacterial community composition (19.7%). Following this strong contaminant signature, salinity and temperature represented important environmental variables predicting 10.9% of community variation. While overall network connectivity measures supported the idea of an inherently diverse soil microbiome with some degree of functional redundancy, lower values observed in contaminated sediments indicate potential structural perturbations in the community from fracturing or loss of bacterial associations. The large number of unclassified sequences obtained in this study contribute to improving our understanding of environmentally relevant strains in relation to anthropogenic contamination, which have been overlooked in laboratory studies.

Bacterial communities are sensitive indicators of contaminant stress.

With many environments worldwide experiencing at least some degree of anthropogenic modification, there is great urgency to identify sensitive indicators of ecosystem stress. Estuarine organisms are particularly vulnerable to anthropogenic contaminants. This study presents bacterial communities as sensitive indicators of contaminant stress. Sediments were collected from multiple sites within inner and outer zones of three heavily modified and three relatively unmodified estuaries. Bacterial communities were censused using Automated Ribosomal Intergenic Spacer Analysis and analysed for a suite of metal and PAH contaminants. Shifts in both bacterial community composition and diversity showed strong associations with sediment contaminant concentrations, particularly with metals. Importantly, these changes are discernable from environmental variation inherent to highly complex estuarine environments. Moreover, variation in bacterial communities within sites was limited. This allowed for differences between sites, zones and estuaries to be explained by variables of interest such as contaminants that vary between, but not within individual sites.