Paraoxonase (PON) comprises a trio of mammalian enzymes that have been reported to have a number of roles including the inhibition of bacterial virulence and biofilm formation by microorganisms that quorum sense with acylated homoserine lactones (AHLs). PON have previously been reported to inhibit P. aeruginosa biofilm formation in mammalian airways and skin. An innate immune role for PON in urinary tract infection has not previously been reported. We performed western blots for PON1 in urine from patients with urinary tract infection (UTI), and also tested UTI urine for the presence of AHLs using a cellular reporter system. Urine sample microbiota was assessed through sequencing of the 16S rRNA marker gene. We report here that PON1 was not found in the urine of control subjects, however, in patients with UTI, PON1 was associated with the presence of E. coli in urine. AHLs, but not PON, were found in the bulk urine of those with P. aeruginosa UTI. Microbial consortia of PON positive UTI urine was found to be distinct from PON negative UTI urine; differentially over-represented bacteria in PON positive samples included a number of environmental opportunists. We hypothesize that PON may inhibit the quorum sensing activity of AHLs in UTI, as has previously described in skin and airways.

Objective: To test the feasibility of targeted gown and glove use by healthcare personnel caring for high-risk nursing-home residents to prevent Staphylococcus aureus acquisition in short-stay residents. Design: Uncontrolled clinical trial. Setting: This study was conducted in 2 community-based nursing homes in Maryland. Participants: The study included 322 residents on mixed short- and long-stay units. Methods: During a 2-month baseline period, all residents had nose and inguinal fold swabs taken to estimate S. aureus acquisition. The intervention was iteratively developed using a participatory human factors engineering approach. During a 2-month intervention period, healthcare personnel wore gowns and gloves for high-risk care activities while caring for residents with wounds or medical devices, and S. aureus acquisition was measured again. Whole-genome sequencing was used to assess whether the acquisition represented resident-to-resident transmission. Results: Among short-stay residents, the methicillin-resistant S. aureus acquisition rate decreased from 11.9% during the baseline period to 3.6% during the intervention period (odds ratio [OR], 0.28; 95% CI, 0.08-0.92; P = .026). The methicillin-susceptible S. aureus acquisition rate went from 9.1% during the baseline period to 4.0% during the intervention period (OR, 0.41; 95% CI, 0.12-1.42; P = .15). The S. aureus resident-to-resident transmission rate decreased from 5.9% during the baseline period to 0.8% during the intervention period. Conclusions: Targeted gown and glove use by healthcare personnel for high-risk care activities while caring for residents with wounds or medical devices, regardless of their S. aureus colonization status, is feasible and potentially decreases S. aureus acquisition and transmission in short-stay community-based nursing-home residents.

Additional file 2 Supplemental Table 1: DNA Sequences in This Study.

BACKGROUND:Cholera has been present and recurring in Zambia since 1977. However, there is a paucity of data on genetic relatedness and diversity of the Vibrio cholerae isolates responsible for these outbreaks. Understanding whether the outbreaks are seeded from existing local isolates or if the outbreaks represent separate transmission events can inform public health decisions.RESULTS:Seventy-two V. cholerae isolates from outbreaks in 2009/2010, 2016, and 2017/2018 in Zambia were characterized using multilocus variable number tandem repeat analysis (MLVA) and whole genome sequencing (WGS). The isolates had eight distinct MLVA genotypes that clustered into three MLVA clonal complexes (CCs). Each CC contained isolates from only one outbreak. The results from WGS revealed both clustered and dispersed single nucleotide variants. The genetic relatedness of isolates based on WGS was consistent with the MLVA, each CC was a distinct genetic lineage and had nearest neighbors from other East African countries. In Lusaka, isolates from the same outbreak were more closely related to themselves and isolates from other countries than to isolates from other outbreaks in other years.CONCLUSIONS:Our observations are consistent with i) the presence of random mutation and alternative mechanisms of nucleotide variation, and ii) three separate transmission events of V. cholerae into Lusaka, Zambia. We suggest that locally, case-area targeted invention strategies and regionally, well-coordinated plans be in place to effectively control future cholera outbreaks.

High-throughput sequencing has revolutionized the field of microbiology, however, reconstructing complete genomes of organisms from whole metagenomic shotgun sequencing data remains a challenge. Recovered genomes are often highly fragmented, due to uneven abundances of organisms, repeats within and across genomes, sequencing errors, and strain-level variation. To address the fragmented nature of metagenomic assemblies, scientists rely on a process called binning, which clusters together contigs inferred to originate from the same organism. Existing binning algorithms use oligonucleotide frequencies and contig abundance (coverage) within and across samples to group together contigs from the same organism. However, these algorithms often miss short contigs and contigs from regions with unusual coverage or DNA composition characteristics, such as mobile elements. Here, we propose that information from assembly graphs can assist current strategies for metagenomic binning. We use MetaCarvel, a metagenomic scaffolding tool, to construct assembly graphs where contigs are nodes and edges are inferred based on paired-end reads. We developed a tool, Binnacle, that extracts information from the assembly graphs and clusters scaffolds into comprehensive bins. Binnacle also provides wrapper scripts to integrate with existing binning methods. The Binnacle pipeline can be found on GitHub ( https://github.com/marbl/binnacle ). We show that binning graph-based scaffolds, rather than contigs, improves the contiguity and quality of the resulting bins, and captures a broader set of the genes of the organisms being reconstructed.

The advent of high throughput sequencing has enabled in-depth characterization of human and environmental microbiomes. Determining the taxonomic origin of microbial sequences is one of the first, and frequently only, analysis performed on microbiome samples. Substantial research has focused on the development of methods for taxonomic annotation, often making trade-offs in computational efficiency and classification accuracy. A side-effect of these efforts has been a reexamination of the bacterial taxonomy itself. Taxonomies developed prior to the genomic revolution captured complex relationships between organisms that went beyond uniform taxonomic levels such as species, genus, and family. Driven in part by the need to simplify computational workflows, the bacterial taxonomies used most commonly today have been regularized to fit within a standard seven taxonomic levels. Consequently, modern analyses of microbial communities are relatively coarse-grained. Few methods make classifications below the genus level, impacting our ability to capture biologically relevant signals. Here, we present ATLAS, a novel strategy for taxonomic annotation that uses significant outliers within database search results to group sequences in the database into partitions. These partitions capture the extent of taxonomic ambiguity within the classification of a sample. The ATLAS pipeline can be found on GitHub [https://github.com/shahnidhi/outlier_in_BLAST_hits]. We demonstrate that ATLAS provides similar annotations to phylogenetic placement methods, but with higher computational efficiency. When applied to human microbiome data, ATLAS is able to identify previously characterized taxonomic groupings, such as those in the class Clostridia and the genus Bacillus. Furthermore, the majority of partitions identified by ATLAS are at the subgenus level, replacing higher-level annotations with specific groups of species. These more precise partitions improve our detection power in determining differential abundance in microbiome association studies.

Diabetic foot ulcers (DFUs) are a major clinical problem exacerbated by prolonged bacterial infection. Macrophages, the primary innate immune cells, are multifunctional cells that regulate diverse processes throughout multiple phases of wound healing. To better understand the influence of microbial species on macrophage behavior, we cultured primary human monocyte-derived macrophages from four donors for 24 hours in media conditioned by bacteria and fungi (Pseudomonas aeruginosa, Corynebacterium amycolatum, Corynebacterium striatum, Staphylococcus aureus, Staphylococcus simulans, and Candida albicans) isolated from the DFUs of six patients. The effects of these microbe-derived signals on macrophage behavior were assessed by measuring the gene expression of a panel of 25 genes related to macrophage phenotype, angiogenesis, bacterial recognition, and cell survival, as well as secretion of two inflammatory cytokines using NanoString multiplex analysis. Principal component analysis showed that macrophage gene expression and protein secretion were affected by both microbial species as well as human donor. S. simulans and C. albicans caused up-regulation of genes associated with a proinflammatory (M1) phenotype, and P. aeruginosa caused an increase in the secretion of the proinflammatory cytokine and M1 marker tumor necrosis factor-alpha (TNFα). Together, these results suggest that macrophages respond to secreted factors from microbes by up-regulating inflammatory markers, and that the effects are strongly dependent on the monocyte donor. Ultimately, increased understanding of macrophage-microbe interactions will lead to the development of more targeted therapies for DFU healing.

Accurate predictions across multiple fields of microbiome research have far-reaching benefits to society, but there are few widely accepted quantitative tools to make accurate predictions about microbial communities and their functions. More discussion is needed about the current state of microbiome analysis and the tools required to overcome the hurdles preventing development and implementation of predictive analyses. We summarize the ideas generated by participants of the Mid-Atlantic Microbiome Meet-up in January 2019. While it was clear from the presentations that most fields have advanced beyond simple associative and descriptive analyses, most fields lack essential elements needed for the development and application of accurate microbiome predictions. Participants stressed the need for standardization, reproducibility, and accessibility of quantitative tools as key to advancing predictions in microbiome analysis. We highlight hurdles that participants identified and propose directions for future efforts that will advance the use of prediction in microbiome research.

Chronic wounds are a major complication of diabetes associated with high morbidity and health care expenditures. To investigate the role of colonizing microbiota in diabetic wound healing, clinical outcomes, and response to interventions, we conducted a longitudinal, prospective study of patients with neuropathic diabetic foot ulcers (DFU). Metagenomic shotgun sequencing revealed that strain-level variation of Staphylococcus aureus and genetic signatures of biofilm formation were associated with poor outcomes. Cultured wound isolates of S. aureus elicited differential phenotypes in mouse models that corresponded with patient outcomes, while wound "bystanders'' such as Corynebacterium striatum and Alcaligenes faecalis, typically considered commensals or contaminants, also significantly impacted wound severity and healing. Antibiotic resistance genes were widespread, and debridement, rather than antibiotic treatment, significantly shifted the DFU microbiota in patients with more favorable outcomes. These findings suggest that the DFU microbiota may be a marker for clinical outcomes and response to therapeutic interventions.

Dataset S1. Results from differential expression analysis. Rows contain the 15,448 features analyzed. Columns contain Ensembl feature id, mean expression of GF samples, mean expression of SPF samples, the NOISeq differential expression statistic theta, the probability of differential expression (equal to 1-FDR-corrected p value when using NOISeqBio, DEGs defined as those with prob. > 0.9), the log2 fold change in expression (upregulated in GF > 0, downregulated in GF

Chronic, non-healing wounds are a major complication of diabetes associated with high morbidity and health care expenditures estimated at $9-13 billion annually in the US. Though microbial infection and critical colonization is hypothesized to impair healing and contribute to severe outcomes such as amputation, antimicrobial therapy is inefficacious and the role of microbes in tissue repair, regeneration, and healing remains unclear. Here, in a longitudinal prospective cohort study of 100 subjects with non-infected neuropathic diabetic foot ulcer (DFU), we performed metagenomic shotgun sequencing to elucidate microbial temporal dynamics at strain-level resolution, to investigate pathogenicity and virulence of the DFU microbiome with respect to outcomes, and to determine the influence of therapeutic intervention on the DFU microbiota. Slow healing DFUs were associated with signatures of biofilm formation, host invasion, and virulence. Though antibiotic resistance was widespread at the genetic level, debridement, rather than antibiotic treatment, significantly shifted the DFU microbiome in patients with more favorable outcomes. Primary clinical isolates of S. aureus, C. striatum , and A. faecalis induced differential biological responses in keratinocytes and in a murine model of diabetic wound healing, with the S. aureus strain associated with non-healing wounds eliciting the most severe phenotype. Together these findings implicate strain-level diversification of the wound pathogen S. aureus in chronic wound outcomes, while revealing potential contributions from skin commensals and other previously underappreciated constituents of the wound microbiota.

Despite critical functions in cutaneous health and disease, it is unclear how resident skin microbial communities are altered by topical antimicrobial interventions commonly used in personal and clinical settings. Here we show that acute exposure to antiseptic treatments elicits rapid but short-term depletion of microbial community diversity and membership. Thirteen subjects were enrolled in a longitudinal treatment study to analyze the effects of topical treatments (i.e., ethanol, povidone-iodine, chlorhexidine, and water) on the skin microbiome at two skin sites of disparate microenvironment: forearm and back. Treatment effects were highly dependent on personalized and body site-specific colonization signatures, which concealed community dynamics at the population level when not accounted for in this analysis. The magnitude of disruption was influenced by the identity and abundance of particular bacterial inhabitants. Lowly abundant members of the skin microbiota were more likely to be displaced, and subsequently replaced, by the most abundant taxa prior to treatment. Members of the skin commensal family Propionibactericeae were particularly resilient to treatment, suggesting a distinct competitive advantage in the face of disturbance. These results provide insight into the stability and resilience of the skin microbiome, while establishing the impact of topical antiseptic treatment on skin bacterial dynamics and community ecology.

The Mid-Atlantic Microbiome Meet-up (M3) organization brings together academic, government, and industry groups to share ideas and develop best practices for microbiome research. In January of 2018, M3 held its fourth meeting, which focused on recent advances in biodefense, specifically those relating to infectious disease, and the use of metagenomic methods for pathogen detection. Presentations highlighted the utility of next-generation sequencing technologies for identifying and tracking microbial community members across space and time. However, they also stressed the current limitations of genomic approaches for biodefense, including insufficient sensitivity to detect low-abundance pathogens and the inability to quantify viable organisms. Participants discussed ways in which the community can improve software usability and shared new computational tools for metagenomic processing, assembly, annotation, and visualization. Looking to the future, they identified the need for better bioinformatics toolkits for longitudinal analyses, improved sample processing approaches for characterizing viruses and fungi, and more consistent maintenance of database resources. Finally, they addressed the necessity of improving data standards to incentivize data sharing. Here, we summarize the presentations and discussions from the meeting, identifying the areas where microbiome analyses have improved our ability to detect and manage biological threats and infectious disease, as well as gaps of knowledge in the field that require future funding and focus.

Culture-independent analysis of microbial communities frequently relies on amplification and sequencing of the prokaryotic 16S ribosomal RNA gene. Typical analysis pipelines group sequences into operational taxonomic units (OTUs) to infer taxonomic and phylogenetic relationships. Here, we present HmmUFOtu, a novel tool for processing microbiome amplicon sequencing data, which performs rapid per-read phylogenetic placement, followed by phylogenetically informed clustering into OTUs and taxonomy assignment. Compared to standard pipelines, HmmUFOtu more accurately and reliably recapitulates microbial community diversity and composition in simulated and real datasets without relying on heuristics or sacrificing speed or accuracy.

Background: The skin harbors complex communities of resident microorganisms, yet little is known of their physiological roles and the molecular mechanisms that mediate cutaneous host-microbe interactions. Here, we profiled skin transcriptomes of mice reared in the presence and absence of microbiota to elucidate the range of pathways and functions modulated in the skin by the microbiota. Results: A total of 2820 genes were differentially regulated in response to microbial colonization and were enriched in gene ontology (GO) terms related to the host-immune response and epidermal differentiation. Innate immune response genes and genes involved in cytokine activity were generally upregulated in response to microbiota and included genes encoding toll-like receptors, antimicrobial peptides, the complement cascade, and genes involved in IL-1 family cytokine signaling and homing of T cells. Our results also reveal a role for the microbiota in modulating epidermal differentiation and development, with differential expression of genes in the epidermal differentiation complex (EDC). Genes with correlated co-expression patterns were enriched in binding sites for the transcription factors Klf4, AP-1, and SP-1, all implicated as regulators of epidermal differentiation. Finally, we identified transcriptional signatures of microbial regulation common to both the skin and the gastrointestinal tract. Conclusions: With this foundational approach, we establish a critical resource for understanding the genome-wide implications of microbially mediated gene expression in the skin and emphasize prospective ways in which the microbiome contributes to skin health and disease.

Sample summary statistics. Rows contain the 16 samples analyzed; with columns containing associated sequencing statistics and metadata. (XLSX 56Â kb)

Skin microbiota can impact allergic and autoimmune responses, wound healing, and anti-microbial defense. We investigated the role of skin microbiota in cutaneous leishmaniasis and found that human patients infected with Leishmania braziliensis develop dysbiotic skin microbiota, characterized by increases in the abundance of Staphylococcus and/or Streptococcus. Mice infected with L. major exhibit similar changes depending upon disease severity. Importantly, this dysbiosis is not limited to the lesion site, but is transmissible to normal skin distant from the infection site and to skin from co-housed naive mice. This observation allowed us to test whether a pre-existing dysbiotic skin microbiota influences disease, and we found that challenging dysbiotic naive mice with L. major or testing for contact hypersensitivity results in exacerbated skin inflammatory responses. These findings demonstrate that a dysbiotic skin microbiota is not only a consequence of tissue stress, but also enhances inflammation, which has implications for many inflammatory cutaneous diseases.

The skin microbiome is a complex ecosystem with important implications for cutaneous health and disease. Topical antibiotics and antiseptics are often employed to preserve the balance of this population and inhibit colonization by more pathogenic bacteria. However, despite their widespread use, the impact of these interventions on broader microbial communities remains poorly understood. Here, we report the longitudinal effects of topical antibiotics and antiseptics on skin bacterial communities and their role in Staphylococcus aureus colonization resistance. In response to antibiotics, cutaneous populations exhibited an immediate shift in bacterial residents, an effect that persisted for multiple days posttreatment. By contrast, antiseptics elicited only minor changes to skin bacterial populations, with few changes to the underlying microbiota. While variable in scope, both antibiotics and antiseptics were found to decrease colonization by commensal Staphylococcus spp. by sequencing- and culture-based methods, an effect which was highly dependent on baseline levels of Staphylococcus Because Staphylococcus residents have been shown to compete with the skin pathogen S. aureus, we also tested whether treatment could influence S. aureus levels at the skin surface. We found that treated mice were more susceptible to exogenous association with S. aureus and that precolonization with the same Staphylococcus residents that were previously disrupted by treatment reduced S. aureus levels by over 100-fold. In all, the results of this study indicate that antimicrobial drugs can alter skin bacterial residents and that these alterations can have critical implications for cutaneous host defense.

Localized genomic variability is crucial for the ongoing conflicts between infectious microbes and their hosts. An understanding of evolutionary and adaptive patterns associated with genomic variability will help guide development of vaccines and antimicrobial agents. While most analyses of the human microbiome have focused on taxonomic classification and gene annotation, we investigated genomic variation of skin- associated viral communities. We evaluated patterns of viral genomic variation across 16 healthy human volunteers. Human papillomavirus (HPV) and Staphylococcus phages contained 106 and 465 regions of diversification, or hypervariable loci, respectively. Propionibacterium phage genomes were minimally divergent and contained no hypervariable loci. Genes containing hypervariable loci were involved in functions including host tropism and immune evasion. HPV and Staphylococcus phage hypervariable loci were associated with purifying selection. Amino acid substitution patterns were virus dependent, as were predictions of their phenotypic effects. We identified diversity generating retroelements as one likely mechanism driving hypervariability. We validated these findings in an independently collected skin metagenomic sequence dataset, suggesting that these features of skin virome genomic variability are widespread. Our results highlight the genomic variation landscape of the skin virome and provide a foundation for better understanding community viral evolution and the functional implications of genomic diversification of skin viruses.