Potential routes of plastics biotransformation involving novel plastizymes revealed by global multi-omic analysis of plastic associated microbes.

Despite increasing efforts across various disciplines, the fate, transport, and impact of synthetic plastics on the environment and public health remain poorly understood. To better elucidate the microbial ecology of plastic waste and its potential for biotransformation, we conducted a large-scale analysis of all publicly available meta-omic studies investigating plastics (n = 27) in the environment. Notably, we observed low prevalence of known plastic degraders throughout most environments, except for substantial enrichment in riverine systems. This indicates rivers may be a highly promising environment for discovery of novel plastic bioremediation products. Ocean samples associated with degrading plastics showed clear differentiation from non-degrading polymers, showing enrichment of novel putative biodegrading taxa in the degraded samples. Regarding plastisphere pathogenicity, we observed significant enrichment of antimicrobial resistance genes on plastics but not of virulence factors. Additionally, we report a co-occurrence network analysis of 10 + million proteins associated with the plastisphere. This analysis revealed a localized sub-region enriched with known and putative plastizymes-these may be useful for deeper investigation of nature's ability to biodegrade man-made plastics. Finally, the combined data from our meta-analysis was used to construct a publicly available database, the Plastics Meta-omic Database (PMDB)-accessible at plasticmdb.org. These data should aid in the integrated exploration of the microbial plastisphere and facilitate research efforts investigating the fate and bioremediation potential of environmental plastic waste.

Metagenomic insights into the impact of litter from poultry Concentrated Animal Feeding Operations (CAFOs) to adjacent soil and water microbial communities.

In recent decades, human food consumption has led to an increased demand for animal-based foods, particularly chicken meat production. The state of Georgia, USA is one of the top broiler chicken producers in the United States, where animals are raised in Concentrated Animal Feeding Operations (CAFOs). Without proper management, CAFOs could negatively impact the environment and become a public health risk as a source of water and air pollution and/or by spreading antimicrobial resistance genes. In this study, we used metagenome sequencing to investigate the impact of the application of the CAFO's litter on adjacent soils and downstream creek waters in terms of microbial diversity and antimicrobial resistance profile changes. Our data indicate that while a few microbial groups increased in abundance within a short period of time after litter application, these populations subsequently decreased to levels similar to those found prior to the litter application or to below the detection limit of our metagenome sequencing effort. Microbial taxonomic composition analyses, relative abundance of Metagenome-Assembled Genomes (MAGs) and detection of Antimicrobial Resistance Genes (ARGs) allow us to conclude that this practice of litter application had a negligible effect on the microbiome or resistome profile of these soils and nearby waterways, likely due to its dilution in the field and/or outcompetition by indigenous microbes, revealing a minimal impact of these poultry facilities on the natural microbial communities.

A user's guide to the bioinformatic analysis of shotgun metagenomic sequence data for bacterial pathogen detection.

Metagenomics, i.e., shotgun sequencing of the total microbial community DNA from a sample, has become a mature technique but its application to pathogen detection in clinical, environmental, and food samples is far from common or standardized. In this review, we summarize ongoing developments in metagenomic sequence analysis that facilitate its wider application to pathogen detection. We examine theoretical frameworks for estimating the limit of detection for a particular level of sequencing effort, current approaches for achieving species and strain analytical resolution, and discuss some relevant modern tools for these tasks. While these recent advances are significant and establish metagenomics as a powerful tool to provide insights not easily attained by culture-based approaches, metagenomics is unlikely to emerge as a widespread, routine monitoring tool in the near future due to its inherently high detection limits, cost, and inability to easily distinguish between viable and non-viable cells. Instead, metagenomics seems best poised for applications involving special circumstances otherwise challenging for culture-based and molecular (e.g., PCR-based) approaches such as the de novo detection of novel pathogens, cases of co-infection by more than one pathogen, and situations where it is important to assess the genomic composition of the pathogenic population(s) and/or its impact on the indigenous microbiome.

An ANI gap within bacterial species that advances the definitions of intra-species units.

IMPORTANCE: Bacterial strains and clonal complexes are two cornerstone concepts for microbiology that remain loosely defined, which confuses communication and research. Here we identify a natural gap in genome sequence comparisons among isolate genomes of all well-sequenced species that has gone unnoticed so far and could be used to more accurately and precisely define these and related concepts compared to current methods. These findings advance the molecular toolbox for accurately delineating and following the important units of diversity within prokaryotic species and thus should greatly facilitate future epidemiological and micro-diversity studies across clinical and environmental settings.

Fecal microbiota transplantation promotes reduction of antimicrobial resistance by strain replacement.

Multidrug-resistant organism (MDRO) colonization is a fundamental challenge in antimicrobial resistance. Limited studies have shown that fecal microbiota transplantation (FMT) can reduce MDRO colonization, but its mechanisms are poorly understood. We conducted a randomized, controlled trial of FMT for MDRO decolonization in renal transplant recipients called PREMIX (NCT02922816). Eleven participants were enrolled and randomized 1:1 to FMT or an observation period followed by delayed FMT if stool cultures were MDRO positive at day 36. Participants who were MDRO positive after one FMT were treated with a second FMT. At last visit, eight of nine patients who completed all treatments were MDRO culture negative. FMT-treated participants had longer time to recurrent MDRO infection versus PREMIX-eligible controls who were not treated with FMT. Key taxa (Akkermansia muciniphila, Alistipes putredinis, Phocaeicola dorei, Phascolarctobacterium faecium, Alistipes species, Mesosutterella massiliensis, Barnesiella intestinihominis, and Faecalibacterium prausnitzii) from the single feces donor used in the study that engrafted in recipients and metabolites such as short-chain fatty acids and bile acids in FMT-responding participants uncovered leads for rational microbiome therapeutic and diagnostic development. Metagenomic analyses revealed a previously unobserved mechanism of MDRO eradication by conspecific strain competition in an FMT-treated subset. Susceptible Enterobacterales strains that replaced baseline extended-spectrum ß-lactamase-producing strains were not detectable in donor microbiota manufactured as FMT doses but in one case were detectable in the recipient before FMT. These data suggest that FMT may provide a path to exploit strain competition to reduce MDRO colonization.

Parallel deployment of passive and composite samplers for surveillance and variant profiling of SARS-CoV-2 in sewage.

Wastewater-based epidemiology during the COVID-19 pandemic has proven useful for public health decision-making but is often hampered by sampling methodology constraints, particularly at the building- or neighborhood-level. Time-weighted composite samples are commonly used; however, autosamplers are expensive and can be affected by intermittent flows in sub-sewershed contexts. In this study, we compared time-weighted composite, grab, and passive sampling via Moore swabs, at four locations across a college campus to understand the utility of passive sampling. After optimizing the methods for sample handling and processing for viral RNA extraction, we quantified SARS-CoV-2 N1 and N2, as well as a fecal strength indicator, PMMoV, by ddRT-PCR and applied tiled amplicon sequencing of the SARS-CoV-2 genome. Passive samples compared favorably with composite samples in our study area: for samples collected concurrently, 42 % of the samples agreed between Moore swab and composite samples and 58 % of the samples were positive for SARS-CoV-2 using Moore swabs while composite samples were below the limit of detection. Variant profiles from Moore swabs showed a shift from variant BA.1 to BA.2, consistent with in-person saliva samples. These data have implications for the broader implementation of sewage surveillance without advanced sampling technologies and for the utilization of passive sampling approaches for other emerging pathogens.

Toward shotgun metagenomic approaches for microbial source tracking sewage spills based on laboratory mesocosms.

Little is known about the genomic diversity of the microbial communities associated with raw municipal wastewater (sewage), including whether microbial populations specific to sewage exist and how such populations could be used to improve source attribution and apportioning in contaminated waters. Herein, we used the influent of three wastewater treatment plants in Atlanta, Georgia (USA) to perturb laboratory freshwater mesocosms, simulating sewage contamination events, and followed these mesocosms with shotgun metagenomics over a 7-day observational period. We describe 15 abundant non-redundant bacterial metagenome-assembled genomes (MAGs) ubiquitous within all sewage inocula yet absent from the unperturbed freshwater control at our analytical limit of detection. Tracking the dynamics of the populations represented by these MAGs revealed varied decay kinetics, depending on (inferred) phenotypes, e.g., anaerobes decayed faster than aerobes under the well-aerated incubation conditions. Notably, a portion of these populations showed decay patterns similar to those of common markers, Enterococcus and HF183. Despite the apparent decay of these populations, the abundance of ß-lactamase encoding genes remained high throughout incubation relative to the control. Lastly, we constructed genomic libraries representing several different fecal sources and outline a bioinformatic approach which leverages these libraries for identifying and apportioning contamination signal among multiple probable sources using shotgun metagenomic data.