Characterization of Coastal Urban Watershed Bacterial Communities Leads to Alternative Community-Based Indicators

Background

Microbial communities in aquatic environments are spatially and temporally dynamic due to environmental fluctuations and varied external input sources. A large percentage of the urban watersheds in the United States are affected by fecal pollution, including human pathogens, thus warranting comprehensive monitoring.

Methodology/Principal Findings

Using a high-density microarray (PhyloChip), we examined water column bacterial community DNA extracted from two connecting urban watersheds, elucidating variable and stable bacterial subpopulations over a 3-day period and community composition profiles that were distinct to fecal and non-fecal sources. Two approaches were used for indication of fecal influence. The first approach utilized similarity of 503 operational taxonomic units (OTUs) common to all fecal samples analyzed in this study with the watershed samples as an index of fecal pollution. A majority of the 503 OTUs were found in the phyla Firmicutes, Proteobacteria, Bacteroidetes, and Actinobacteria. The second approach incorporated relative richness of 4 bacterial classes (Bacilli, Bacteroidetes, Clostridia and α-proteobacteria) found to have the highest variance in fecal and non-fecal samples. The ratio of these 4 classes (BBC∶A) from the watershed samples demonstrated a trend where bacterial communities from gut and sewage sources had higher ratios than from sources not impacted by fecal material. This trend was also observed in the 124 bacterial communities from previously published and unpublished sequencing or PhyloChip- analyzed studies.

Conclusions/Significance

This study provided a detailed characterization of bacterial community variability during dry weather across a 3-day period in two urban watersheds. The comparative analysis of watershed community composition resulted in alternative community-based indicators that could be useful for assessing ecosystem health.     

Biological consequences of improving the structural stability of hairpins that have antimicrobial activity

Designing new antimicrobial peptides (AMPs) focuses heavily on the activity of the peptide and less on the elements that stabilize the secondary structure of these peptides. Studies have shown that improving the structure of naturally occurring AMPs can affect activity and so here we explore the relationship between structure and activity of two non‐naturally occurring AMPs. We have used a backbone‐cyclized peptide as a template and designed an uncyclized analogue of this peptide that has antimicrobial activity. We focused on beta‐hairpin‐like structuring features. Improvements to the structure of this peptide reduced the activity of the peptide against gram‐negative, Escherichia coli but improved the activity against gram‐positive, Corynebacterium glutamicum. Distinctions in structuring effects on gram‐negative versus gram‐positive activity were also seen in a second peptide system. Structural improvements resulted in a peptide that was more active than the native against gram‐positive bacterium but less active against gram‐negative bacterium. Our results show that there is not always a correlation between improved hairpin‐structuring and activity. Other factors such as the type of bacteria being targeted as well as net positive charge can play a role in the potency of AMPs. Copyright © 2017 European Peptide Society and John Wiley & Sons, Ltd.     

Long‐term temporal and spatial trends in eutrophication status of the Baltic Sea

Much of the Baltic Sea is currently classified as ‘affected by eutrophication’. The causes for this are twofold. First, current levels of nutrient inputs (nitrogen and phosphorus) from human activities exceed the natural processing capacity with an accumulation of nutrients in the Baltic Sea over the last 50–100 years. Secondly, the Baltic Sea is naturally susceptible to nutrient enrichment due to a combination of long retention times and stratification restricting ventilation of deep waters. Here, based on a unique data set collated from research activities and long‐term monitoring programs, we report on the temporal and spatial trends of eutrophication status for the open Baltic Sea over a 112‐year period using the HELCOM Eutrophication Assessment Tool (HEAT 3.0). Further, we analyse variation in the confidence of the eutrophication status assessment based on a systematic quantitative approach using coefficients of variation in the observations. The classifications in our assessment indicate that the first signs of eutrophication emerged in the mid‐1950s and the central parts of the Baltic Sea changed from being unaffected by eutrophication to being affected. We document improvements in eutrophication status that are direct consequences of long‐term efforts to reduce the inputs of nutrients. The reductions in both nitrogen and phosphorus loads have led to large‐scale alleviation of eutrophication and to a healthier Baltic Sea. Reduced confidence in our assessment is seen more recently due to reductions in the scope of monitoring programs. Our study sets a baseline for implementation of the ecosystem‐based management strategies and policies currently in place including the EU Marine Strategy Framework Directives and the HELCOM Baltic Sea Action Plan.     

Risk and protective factors for mental disorders beyond genetics: an evidence‐based atlas

Decades of research have revealed numerous risk factors for mental disorders beyond genetics, but their consistency and magnitude remain uncer­tain. We conducted a “meta‐umbrella” systematic synthesis of umbrella reviews, which are systematic reviews of meta‐analyses of individual studies, by searching international databases from inception to January 1, 2021. We included umbrella reviews on non‐purely genetic risk or protective factors for any ICD/DSM mental disorders, applying an established classification of the credibility of the evidence: class I (convincing), class II (highly suggestive), class III (suggestive), class IV (weak). Sensitivity analyses were conducted on prospective studies to test for temporality (reverse causation), TRANSD criteria were applied to test transdiagnosticity of factors, and A Measurement Tool to Assess Systematic Reviews (AMSTAR) was employed to address the quality of meta‐analyses. Fourteen eligible umbrella reviews were retrieved, summarizing 390 meta‐analyses and 1,180 associations between putative risk or protective factors and mental disorders. We included 176 class I to III evidence associations, relating to 142 risk/protective factors. The most robust risk factors (class I or II, from prospective designs) were 21. For dementia, they included type 2 diabetes mellitus (risk ratio, RR from 1.54 to 2.28), depression (RR from 1.65 to 1.99) and low frequency of social contacts (RR=1.57). For opioid use disorders, the most robust risk factor was tobacco smoking (odds ratio, OR=3.07). For non‐organic psychotic disorders, the most robust risk factors were clinical high risk state for psychosis (OR=9.32), cannabis use (OR=3.90), and childhood adversities (OR=2.80). For depressive disorders, they were widowhood (RR=5.59), sexual dysfunction (OR=2.71), three (OR=1.99) or four‐five (OR=2.06) metabolic factors, childhood physical (OR=1.98) and sexual (OR=2.42) abuse, job strain (OR=1.77), obesity (OR=1.35), and sleep disturbances (RR=1.92). For autism spectrum disorder, the most robust risk factor was maternal overweight pre/during pregnancy (RR=1.28). For attention‐deficit/hyperactivity disorder (ADHD), they were maternal pre‐pregnancy obesity (OR=1.63), maternal smoking during pregnancy (OR=1.60), and maternal overweight pre/during pregnancy (OR=1.28). Only one robust protective factor was detected: high physical activity (hazard ratio, HR=0.62) for Alzheimer’s disease. In all, 32.9% of the associations were of high quality, 48.9% of medium quality, and 18.2% of low quality. Transdiagnostic class I‐III risk/protective factors were mostly involved in the early neurodevelopmental period. The evidence‐based atlas of key risk and protective factors identified in this study represents a benchmark for advancing clinical characterization and research, and for expanding early intervention and preventive strategies for mental disorders.     

Quantitative modeling of membrane deformations by multihelical membrane proteins: application to G-protein coupled receptors

The interpretation of experimental observations of the dependence of membrane protein function on the properties of the lipid membrane environment calls for a consideration of the energy cost of protein-bilayer interactions, including the protein-bilayer hydrophobic mismatch. We present a novel (to our knowledge) multiscale computational approach for quantifying the hydrophobic mismatch-driven remodeling of membrane bilayers by multihelical membrane proteins. The method accounts for both the membrane remodeling energy and the energy contribution from any partial (incomplete) alleviation of the hydrophobic mismatch by membrane remodeling. Overcoming previous limitations, it allows for radially asymmetric bilayer deformations produced by multihelical proteins, and takes into account the irregular membrane-protein boundaries. The approach is illustrated by application to two G-protein coupled receptors: rhodopsin in bilayers of different thickness, and the serotonin 5-HT_2A receptor bound to pharmacologically different ligands. Analysis of the results identifies the residual exposure that is not alleviated by bilayer adaptation, and its quantification at specific transmembrane segments is shown to predict favorable contact interfaces in oligomeric arrays. In addition, our results suggest how distinct ligand-induced conformations of G-protein coupled receptors may elicit different functional responses through differential effects on the membrane environment.