Bacterial communities as indicators of environmental pollution by POPs in marine sediments.

Decades of intensive discharge from industrial activities into coastal systems has resulted in the accumulation of a variety of persistent organic pollutants (POPs) in marine waters and sediments, having detrimental impacts on aquatic ecosystems and the resident biota. POPs are among the most hazardous chemicals originating from industrial activities due to their biotoxicity and resistance to environmental degradation. Bacterial communities are known to break down many of these aromatic compounds, and different members of naturally occurring bacterial consortia have been described to work in syntrophic association to thrive in heavily contaminated waters and sediments, making them potential candidates as bioindicators of environmental pollution. In this study environmental, sampling was combined with chemical analysis of pollutants and high-resolution sequencing of bacterial communities using Next Generation Sequencing molecular biology tools. The aim of the present study was to describe the bacterial communities from marine sediments containing high loads of POPs and to identify relevant members of the resident microbial communities that may act as bioindicators of contamination. Marine sediments were collected from a coastal bay area of the Baltic Sea historically influenced by intense industrial activity, including metal smelting, oil processing, and pulp and paper production. Different types of POPs were detected at high concentrations. Fiberbank sediments, resulting from historic paper industry activity, were found to harbour a clearly distinct bacterial community including a number of bacterial taxa capable of cellulolytic and dechlorination activities. Our findings indicate that specific members of the bacterial communities thrive under increasing levels of POPs in marine sediments, and that the abundances of certain taxa correlate with specific POPs (or groups), which could potentially be employed in monitoring, status assessment and environmental management purposes.

Corrigendum: Effects of Organic Pollutants on Bacterial Communities Under Future Climate Change Scenarios.

[This corrects the article DOI: 10.3389/fmicb.2018.02926.].

Effects of Organic Pollutants on Bacterial Communities Under Future Climate Change Scenarios.

Coastal ecosystems are highly dynamic and can be strongly influenced by climate change, anthropogenic activities (e.g., pollution), and a combination of the two pressures. As a result of climate change, the northern hemisphere is predicted to undergo an increased precipitation regime, leading in turn to higher terrestrial runoff and increased river inflow. This increased runoff will transfer terrestrial dissolved organic matter (tDOM) and anthropogenic contaminants to coastal waters. Such changes can directly influence the resident biology, particularly at the base of the food web, and can influence the partitioning of contaminants and thus their potential impact on the food web. Bacteria have been shown to respond to high tDOM concentration and organic pollutants loads, and could represent the entry of some pollutants into coastal food webs. We carried out a mesocosm experiment to determine the effects of: (1) increased tDOM concentration, (2) organic pollutant exposure, and (3) the combined effect of these two factors, on pelagic bacterial communities. This study showed significant responses in bacterial community composition under the three environmental perturbations tested. The addition of tDOM increased bacterial activity and diversity, while the addition of organic pollutants led to an overall reduction of these parameters, particularly under concurrent elevated tDOM concentration. Furthermore, we identified 33 bacterial taxa contributing to the significant differences observed in community composition, as well as 35 bacterial taxa which responded differently to extended exposure to organic pollutants. These findings point to the potential impact of organic pollutants under future climate change conditions on the basal coastal ecosystem, as well as to the potential utility of natural bacterial communities as efficient indicators of environmental disturbance.

Multicriteria approach to select polyaromatic river mutagen candidates.

The identification of unknown compounds remains one of the most challenging tasks to link observed toxic effects in complex environmental mixtures to responsible toxicants in effect-directed analysis (EDA). Here, a workflow is presented based on nontarget liquid chromatography-high resolution mass spectrometry (LC-HRMS) starting with molecular formulas determined in a previous study. A compound database search (ChemSpider) was performed to retrieve candidates for each formula. Subsequently, the number of candidates was reduced by applying MS-, physical-chemical, and chromatography-based selection criteria including HRMS/MS fragmentation and plausibility, ionization efficiency with different ion sources and detection modes, acid/base behavior, octanol/water partitioning, retention time prediction and finally toxic effects (mutagenicity caused by aromatic amines). The workflow strongly decreased the number of possible candidates and resulted in the tentative identification of possible mutagens and the positive identification of the nonmutagen benzyl(diphenyl) phosphine oxide in a mutagenic fraction. The positive identification of mutagens was hampered by a lack of commercially available standards. The workflow is an innovative and promising approach and forms an excellent basis for possible further advancements.

Integrated biological-chemical approach for the isolation and selection of polyaromatic mutagens in surface waters.

Many environmental mutagens, including polyaromatic compounds are present in surface waters, often in complex mixtures and at low concentrations. The present study provides and applies a novel, integrated approach to isolate polyaromatic mutagens in river water using a sample from the River Elbe. The sample was taken downstream of industrial discharges using blue rayon (BR) as a passive sampler that selectively adsorbs polyaromatic compounds and was subjected to effect-directed fractionation in order to characterise the compounds causing the detected effect(s). The procedure relies on three complementary fractionation steps, the Ames fluctuation assay with strains TA98, YG1024 and YG1041 with and without S9 activation and analytical screening. Several mutagenic fractions were isolated by combining mutagenicity testing with fractionation. The enhanced mutagenicity in the nitroreductase and/or O-acetyltransferase overexpressing strains YG1024 and YG1041 strains suggested amino- and/or nitro-compounds causing mutagenicity in several fractions. Analytical screening of mutagenic fractions with LC-HRMS/MS provided a list of molecular formulas typically containing one to ten nitrogen and at least two oxygen atoms supporting the presence of amino and nitro-compounds in the mutagenic fractions.

Consensus structure elucidation combining GC/EI-MS, structure generation, and calculated properties.

This article explores consensus structure elucidation on the basis of GC/EI-MS, structure generation, and calculated properties for unknown compounds. Candidate structures were generated using the molecular formula and substructure information obtained from GC/EI-MS spectra. Calculated properties were then used to score candidates according to a consensus approach, rather than filtering or exclusion. Two mass spectral match calculations (MOLGEN-MS and MetFrag), retention behavior (Lee retention index/boiling point correlation, NIST Kovat's retention index), octanol-water partitioning behavior (log K(ow)), and finally steric energy calculations were used to select candidates. A simple consensus scoring function was developed and tested on two unknown spectra detected in a mutagenic subfraction of a water sample from the Elbe River using GC/EI-MS. The top candidates proposed using the consensus scoring technique were purchased and confirmed analytically using GC/EI-MS and LC/MS/MS. Although the compounds identified were not responsible for the sample mutagenicity, the structure-generation-based identification for GC/EI-MS using calculated properties and consensus scoring was demonstrated to be applicable to real-world unknowns and suggests that the development of a similar strategy for multidimensional high-resolution MS could improve the outcomes of environmental and metabolomics studies.