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Abstract Prosthetic joint infections (PJI) are economically and personally costly, and their incidence has been increasing in the United States. Herein, we compared 16S rRNA amplicon sequencing (16S), shotgun metagenomics (MG) and metatranscriptomics (MT) in identifying pathogens causing PJI. Samples were collected from 30 patients, including 10 patients undergoing revision arthroplasty for infection, 10 patients receiving revision for aseptic failure, and 10 patients undergoing primary total joint arthroplasty. Synovial fluid and peripheral blood samples from the patients were obtained at time of surgery. Analysis revealed distinct microbial communities between primary, aseptic, and infected samples using MG, MT, (PERMANOVA p = 0.001), and 16S sequencing (PERMANOVA p

Hospital-acquired infections (HAIs) pose a serious threat to patients, and hospitals spend billions of dollars each year to reduce and treat these infections. Many HAIs are due to contamination from workers’ hands and contact with high-touch surfaces. Therefore, we set out to test the efficacy of a new preventative technology, AIONX® Antimicrobial Technologies, Inc’s cleanSURFACES®, which is designed to complement daily chemical cleaning events by continuously preventing re-colonization of surfaces. To that end, we swabbed surfaces before (Baseline) and after (Post) application of the cleanSURFACES® at various time points (Day 1, Day 7, Day 14, and Day 28). To circumvent limitations associated with culture-based and 16S rRNA gene amplicon sequencing methodologies, these surface swabs were processed using metatranscriptomic (RNA) analysis to allow for comprehensive taxonomic resolution and the detection of active microorganisms. Overall, there was a significant (P < 0.05) global reduction of microbial diversity in Post-intervention samples. Additionally, Post sample microbial communities clustered together much more closely than Baseline samples based on pairwise distances calculated with the weighted Jaccard distance metric, suggesting a defined shift after product application. This shift was characterized by a general depletion of several microbes among Post samples, with multiple phyla also being reduced over the duration of the study. Notably, specific clinically relevant microbes, including Staphylococcus aureus, Clostridioides difficile and Streptococcus spp., were depleted Post-intervention. Taken together, these findings suggest that chemical cleaning events used jointly with cleanSURFACES® have the potential to reduce colonization of surfaces by a wide variety of microbes, including many clinically relevant pathogens.

Arsenic is ubiquitous in nature, highly toxic, and is particularly abundant in Southern Asia. While many studies have focused on areas like Bangladesh and West Bengal, India, disadvantaged regions within Nepal have also suffered from arsenic contamination levels, with wells and other water sources possessing arsenic contamination over the recommended WHO and EPA limit of 10 μg/L, some wells reporting levels as high as 500 μg/L. Despite the region's pronounced arsenic concentrations within community water sources, few investigations have been conducted to understand the impact of arsenic contamination on host gut microbiota health. This study aims to examine differential arsenic exposure on the gut microbiome structure within two disadvantaged communities in southern Nepal. Fecal samples (n = 42) were collected from members of the Mahuawa (n = 20) and Ghanashyampur (n = 22) communities in southern Nepal. The 16S rRNA gene was amplified from fecal samples using Illumina-tag PCR and subject to high-throughput sequencing to generate the bacterial community structure of each sample. Bioinformatics analysis and multivariate statistics were conducted to identify if specific fecal bacterial assemblages and predicted functions were correlated with urine arsenic concentration. Our results revealed unique assemblages of arsenic volatilizing and pathogenic bacteria positively correlated with increased arsenic concentration in individuals within the two respective communities. Additionally, we observed that commensal gut bacteria negatively correlated with increased arsenic concentration in the two respective communities. Our study has revealed that arsenic poses a broader human health risk than was previously known. It is influential in shaping the gut microbiome through its enrichment of arsenic volatilizing and pathogenic bacteria and subsequent depletion of gut commensals. This aspect of arsenic has the potential to debilitate healthy humans by contributing to disorders like heart and liver cancers and diabetes, and it has already been shown to contribute to serious diseases and disorders, including skin lesions, gangrene and several types of skin, renal, lung, and liver cancers in disadvantaged areas of the world like Nepal.

Abstract Diverticular disease is commonly associated with the older population in the United States. As individual’s age, diverticulae, or herniation of the mucosa through the colonic wall, develop. In 10–25% of individuals, the diverticulae become inflamed, resulting in diverticulitis. The gut ecosystem relies on the interaction of bacteria and fungi to maintain homeostasis. Although bacterial dysbiosis has been implicated in the pathogenesis of diverticulitis, associations between the microbial ecosystem and diverticulitis remain largely unstudied. This study investigated how the cooperative network of bacteria and fungi differ between a diseased area of the sigmoid colon chronically affected by diverticulitis and adjacent non-affected tissue. To identify mucosa-associated microbes, bacterial 16S rRNA and fungal ITS sequencing were performed on chronically diseased sigmoid colon tissue (DT) and adjacent tissue (AT) from the same colonic segment. We found that Pseudomonas and Basidiomycota OTUs were associated with AT while Microbacteriaceae and Ascomycota were enriched in DT. Bipartite co-occurrence networks were constructed for each tissue type. The DT and AT networks were distinct for each tissue type, with no microbial relationships maintained after intersection merge of the groups. Our findings indicate that the microbial ecosystem distinguishes chronically diseased tissue from adjacent tissue.

ABSTRACT There has been no prior application of matched metagenomics and metatranscriptomics in Clostridioides difficile infection (CDI) evaluating the role of fungi in CDI or identifying community functions that contribute to the development of this disease. We collected diarrheal stools from 49 inpatients (18 of whom tested positive for CDI) under stringent inclusion criteria. We utilized a tiered sequencing approach to identify enriched bacterial and fungal taxa, using 16S and internal transcribed spacer (ITS) rRNA gene amplicon sequencing, with matched metagenomics and metatranscriptomics performed on a subset of the population. Distinct bacterial and fungal compositions distinguished CDI-positive and -negative patients, with the greatest differentiation between the cohorts observed based on bacterial metatranscriptomics. Bipartite network analyses demonstrated that Aspergillus and Penicillium taxa shared a strong positive relationship in CDI patients and together formed negative cooccurring relationships with several bacterial taxa, including the Oscillospira, Comamonadaceae, Microbacteriaceae, and Cytophagaceae. Metatranscriptomics revealed enriched pathways in CDI patients associated with biofilm production primarily driven by Escherichia coli and Pseudomonas, quorum-sensing proteins, and two-component systems related to functions such as osmotic regulation, linoleic acid metabolism, and flagellar assembly. Differential expression of functional pathways unveiled a mechanism by which the causal dysbiosis of CDI may self-perpetuate, potentially contributing to treatment failures. We propose that CDI has a distinct fungus-associated bacteriome, and this first description of metatranscriptomics in human subjects with CDI demonstrates that inflammation, osmotic changes, and biofilm production are key elements of CDI pathophysiology. IMPORTANCE Our data suggest a potential role for fungi in the most common nosocomial bacterial infection in the United States, introducing the concept of a transkingdom interaction between bacteria and fungi in this disease. We also provide the first direct measure of microbial community function in Clostridioides difficile infection using patient-derived tissue samples, revealing antibiotic-independent mechanisms by which C. difficile infection may resist a return to a healthy gut microbiome.

Acid mine drainage (AMD) is an environmental issue that can be characterized by either acidic or circumneutral pH and high dissolved metal content in contaminated waters. It is estimated to affect roughly 3000 miles of waterways within the state of Pennsylvania, with half being acidic and half being circumneutral. To negate the harmful effects of AMD, ∼300 passive remediation systems have been constructed within the state of Pennsylvania. In this study, we evaluated the microbial community structure and functional capability associated with Middle Branch passive remediation system in central PA. Sediment and water samples were collected from each area within the passive remediation system and its receiving stream. Environmental parameters associated with the remediation system were found to explain a significant amount of variation in microbial community structure. This study revealed shifts in microbial community structure from acidophilic bacteria in raw AMD discharge to a more metabolically diverse set of taxa (i.e., Acidimicrobiales, Rhizobiales, Chthoniobacteraceae) toward the end of the system. Vertical flow ponds and the aerobic wetland showed strong metabolic capability for sulfur redox environments. These findings are integral to the understanding of designing effective passive remediation systems because it provides insight as to how certain bacteria [sulfate reducing bacteria (SRBs) and sulfur oxidizing bacteria (SOBs)] are potentially contributing to a microbially mediated AMD remediation process. This study further supports previous investigations that demonstrated the effectiveness of SRBs in the process of removing sulfate and heavy metals from contaminated water.

Unconventional oil and gas (UOG) extraction, also known as hydraulic fracturing, is becoming more prevalent with the increasing use and demand for natural gas; however, the full extent of its environmental impacts is still unknown. Here we measured physicochemical properties and bacterial community composition of sediment samples taken from twenty-eight streams within the Marcellus shale formation in northeastern Pennsylvania differentially impacted by hydraulic fracturing activities. Fourteen of the streams were classified as UOG+, and thirteen were classified as UOG- based on the presence of UOG extraction in their respective watersheds. One stream was located in a watershed that previously had UOG extraction activities but was recently abandoned. We utilized high-throughput sequencing of the 16S rRNA gene to infer differences in sediment aquatic bacterial community structure between UOG+ and UOG- streams, as well as correlate bacterial community structure to physicochemical water parameters. Although overall alpha and beta diversity differences were not observed, there were a plethora of significantly enriched operational taxonomic units (OTUs) within UOG+ and UOG- samples. Our biomarker analysis revealed many of the bacterial taxa enriched in UOG+ streams can live in saline conditions, such as Rubrobacteraceae. In addition, several bacterial taxa capable of hydrocarbon degradation were also enriched in UOG+ samples, including Oceanospirillaceae. Methanotrophic taxa, such as Methylococcales, were significantly enriched as well. Several taxa that were identified as enriched in these samples were enriched in samples taken from different streams in 2014; moreover, partial least squares discriminant analysis (PLS-DA) revealed clustering between streams from the different studies based on the presence of hydraulic fracturing along the second axis. This study revealed significant differences between bacterial assemblages within stream sediments of UOG+ and UOG- streams and identified several potential biomarkers for evaluating and monitoring the response of autochthonous bacterial communities to potential hydraulic fracturing impacts.