PathoFact: a pipeline for the prediction of virulence factors and antimicrobial resistance genes in metagenomic data

Comparative genomic analysis of an emerging Pseudomonadaceae member, Thiopseudomonas alkaliphila

Thiopseudomonas alkaliphila, an organism recently classified within the Pseudomonadaceae family, has been detected in diverse sources such as human tissues, animal guts, industrial fermenters, and decomposition environments, suggesting a diverse ecological role. However, a large knowledge gap exists in how T. alkaliphila functions. In this comparative genomic analysis, adaptations indicative of habitat specificity among strains and genomic similarity to known opportunistic pathogens are revealed. Genomic investigation reveals a core metabolic utilization of multiple oxidative and non-oxidative catabolic pathways, suggesting adaptability to varied environments and carbon sources. The genomic repertoire of T. alkaliphila includes secondary metabolites, such as antimicrobials and siderophores, indicative of its involvement in microbial competition and resource acquisition. Additionally, the presence of transposases, prophages, plasmids, and Clustered Regularly Interspaced Short Palindromic Repeats-Cas systems in T. alkaliphila genomes suggests mechanisms for horizontal gene transfer and defense against viral predation. This comprehensive genomic analysis expands our understanding on the ecological functions, community interactions, and potential virulence of T. alkaliphila, while emphasizing its adaptability and diverse capabilities across environmental and host-associated ecosystems.IMPORTANCEAs the microbial world continues to be explored, new organisms will emerge with beneficial and/or pathogenetic impact. Thiopseudomonas alkaliphila is a species originally isolated from clinical human tissue and fluid samples but has not been attributed to disease. Since its classification, T. alkaliphila has been found in animal guts, animal waste, decomposing remains, and biogas fermentation reactors. This is the first study to provide an in-depth view of the metabolic potential of publicly available genomes belonging to this species through a comparative genomics and draft pangenome calculation approach. It was found that T. alkaliphila is metabolically versatile and likely adapts to diverse energy sources and environments, which may make it useful for bioremediation and in industrial settings. A range of virulence factors and antibiotic resistances were also detected, suggesting T. alkaliphila may operate as an undescribed opportunistic pathogen.

Sequencing-based analysis of microbiomes

Microbiomes occupy a range of niches and, in addition to having diverse compositions, they have varied functional roles that have an impact on agriculture, environmental sciences, and human health and disease. The study of microbiomes has been facilitated by recent technological and analytical advances, such as cheaper and higher-throughput DNA and RNA sequencing, improved long-read sequencing and innovative computational analysis methods. These advances are providing a deeper understanding of microbiomes at the genomic, transcriptional and translational level, generating insights into their function and composition at resolutions beyond the species level.

Metagenomic and transcriptomic analysis revealing the impact of oxytetracycline and ciprofloxacin on gut microbiota and gene expression in the Chinese giant salamander (Andrias davidianus)

Excessive antibiotic use has led to the spread of antibiotic resistance genes (ARGs), impacting gut microbiota and host health. However, the effects of antibiotics on amphibian populations remain unclear. We investigated the impact of oxytetracycline (OTC) and ciprofloxacin (CIP) on Chinese giant salamanders (Andrias davidianus), focusing on gut microbiota, ARGs, and gene expression by performing metagenome and transcriptome sequencing. A. davidianus were given OTC (20 or 40 mg/kg) or CIP (50 or 100 mg/kg) orally for 7 days. The results revealed that oral administration of OTC and CIP led to distinct changes in microbial composition and functional potential, with CIP treatment having a greater impact than OTC. Antibiotic treatment also influenced the abundance of ARGs, with an increase in fluoroquinolone and multi-drug resistance genes observed post-treatment. The construction of metagenome-assembled genomes (MAGs) accurately validated that CIP intervention enriched fish-associated potential pathogens Aeromonas hydrophila carrying an increased number of ARGs. Additionally, mobile genetic elements (MGEs), such as phages and plasmids, were implicated in the dissemination of ARGs. Transcriptomic analysis of the gut revealed significant alterations in gene expression, particularly in immune-related pathways, with differential effects observed between OTC and CIP treatments. Integration of metagenomic and transcriptomic data highlighted potential correlations between gut gene expression and microbial composition, suggesting complex interactions between the host gut and its gut microbiota in response to antibiotic exposure. These findings underscore the importance of understanding the impact of antibiotic intervention on the gut microbiome and host health in amphibians, particularly in the context of antibiotic resistance and immune function.

The footprint of gut microbiota in gallbladder cancer: a mechanistic review

Gallbladder cancer (GBC) is the most common malignant tumor of the biliary system with the worst prognosis. Even after radical surgery, the majority of patients with GBC have difficulty achieving a clinical cure. The risk of tumor recurrence remains more than 65%, and the overall 5-year survival rate is less than 5%. The gut microbiota refers to a variety of microorganisms living in the human intestine, including bacteria, viruses and fungi, which profoundly affect the host state of general health, disease and even cancer. Over the past few decades, substantial evidence has supported that gut microbiota plays a critical role in promoting the progression of GBC. In this review, we summarize the functions, molecular mechanisms and recent advances of the intestinal microbiota in GBC. We focus on the driving role of bacteria in pivotal pathways, such as virulence factors, metabolites derived from intestinal bacteria, chronic inflammatory responses and ecological niche remodeling. Additionally, we emphasize the high level of correlation between viruses and fungi, especially EBV and Candida spp., with GBC. In general, this review not only provides a solid theoretical basis for the close relationship between gut microbiota and GBC but also highlights more potential research directions for further research in the future.

An in-depth investigation of the microbiota and its virulence factors associated with severe udder cleft dermatitis lesions

Udder cleft dermatitis (UCD) is a skin condition affecting the anterior parts of the udder in dairy cattle. In the present study, we aimed to shed light on the microbiota in severe UCD lesions versus healthy udder skin by putting forward a taxonomic and functional profile based on a virulence factor analysis. Through shotgun metagenomic sequencing, we found a high proportion of bacteria in addition to a low abundance of archaea. A distinct clustering of healthy udder skin versus UCD lesion samples was shown by applying principal component analysis and (sparse) partial least squares analysis on the metagenomic data. Proteobacteria, Bacillota, and Actinomycetota were among the most abundant phyla in healthy udder skin samples. In UCD samples, Bacteroidota was the most abundant phylum. At genus level, Bifidobacterium spp. had the highest relative abundance in healthy skin samples, whereas Porphyromonas spp. and Corynebacterium spp. had the highest relative abundance in UCD samples. In the differential abundance analysis, Porphyromonas spp. and Bacteroides spp. were significantly differentially abundant in UCD samples, whereas Bifidobacterium spp., Staphylococcus sp. AntiMn-1, and Staphylococcus equorum were more commonly found in healthy samples. Moreover, the abundance of several treponeme phylotypes was significantly higher in lesion samples. The streptococcal cysteine protease speB was among the most abundant virulence factors present in severe UCD lesions, while a plethora of virulence factors such as the antitoxin relB were downregulated, possibly contributing to creating the ideal wound climate for the dysbiotic community. Network analysis showed healthy lesion samples had a large network ofpositive, correlations between the abundances of beneficial species such as Aerococcus urinaeequi and Bifidobacterium angulatum, indicating that the healthy skin microbiome forms an active protective bacterial network, which is disrupted in case of UCD. In UCD samples, a smaller microbial network mainly consisting of positive correlations between the abundances of Bacteroides fragilis and anaerobic Bacteroidota was exposed. Moreover, a high correlation between the taxonomic data and virulence factors was revealed, concurrently with 2 separate networks of microbes and virulence factors. One network, matching with the taxonomic findings in the healthy udder skin samples, showcased a community of harmless or beneficial bacteria, such as Bifidobacterium spp. and Butyrivibrio proteoclasticus, associated with hcnB, hcnC, relB, glyoxalase, and cupin 2. The other network, corresponding to UCD samples, consisted of pathogenic or facultative pathogenic and mainly anaerobic bacteria such as Treponema spp., Mycoplasmopsis spp., and bovine gammaherpesvirus 4, that correlated with virulence factors SpvB, fhaB, and haemagglutination activity domain-associated factor. Our results point toward a dysbiotic community with a notable decrease in diversity and evenness, with a loss of normal skin inhabitants and innocuous or useful species making way for predominantly anaerobic, facultative pathogens. The shift in the abundance of virulence factors such as fhaB and SpvB could play a role in the manifestation of a local micro-environment favorable to the microbiome associated with udder skin lesions. Lastly, the presence of specific networks between microbial species, and between microbes and virulence factors was shown.

Dispersion of antimicrobial resistant bacteria in pig farms and in the surrounding environment

BACKGROUND

Antimicrobial resistance has been identified as a major threat to global health. The pig food chain is considered an important source of antimicrobial resistance genes (ARGs). However, there is still a lack of knowledge on the dispersion of ARGs in pig production system, including the external environment.

RESULTS

In the present study, we longitudinally followed one swine farm located in Italy from the weaning phase to the slaughterhouse to comprehensively assess the diversity of ARGs, their diffusion, and the bacteria associated with them. We obtained shotgun metagenomic sequences from 294 samples, including pig feces, farm environment, soil around the farm, wastewater, and slaughterhouse environment. We identified a total of 530 species-level genome bins (SGBs), which allowed us to assess the dispersion of microorganisms and their associated ARGs in the farm system. We identified 309 SGBs being shared between the animals gut microbiome, the internal and external farm environments. Specifically, these SGBs were characterized by a diverse and complex resistome, with ARGs active against 18 different classes of antibiotic compounds, well matching antibiotic use in the pig food chain in Europe.

CONCLUSIONS

Collectively, our results highlight the urgency to implement more effective countermeasures to limit the dispersion of ARGs in the pig food systems and the relevance of metagenomics-based approaches to monitor the spread of ARGs for the safety of the farm working environment and the surrounding ecosystems.

A Metagenomic Investigation of Potential Health Risks and Element Cycling Functions of Bacteria and Viruses in Wastewater Treatment Plants

The concentration of viruses in sewage sludge is significantly higher (10-1000-fold) than that found in natural environments, posing a potential risk for human and animal health. However, the composition of these viruses and their role in the transfer of pathogenic factors, as well as their role in the carbon, nitrogen, and phosphorus cycles remain poorly understood. In this study, we employed a shotgun metagenomic approach to investigate the pathogenic bacteria and viral composition and function in two wastewater treatment plants located on a campus. Our analysis revealed the presence of 1334 amplicon sequence variants (ASVs) across six sludge samples, with 242 ASVs (41.22% of total reads) identified as pathogenic bacteria. Arcobacter was found to be the most dominant pathogen accounting for 6.79% of total reads. The virome analysis identified 613 viral genera with Aorunvirus being the most abundant genus at 41.85%. Approximately 0.66% of these viruses were associated with human and animal diseases. More than 60% of the virome consisted of lytic phages. Host prediction analysis revealed that the phages primarily infected Lactobacillus (37.11%), Streptococcus (21.11%), and Staphylococcus (7.11%). Furthermore, our investigation revealed an abundance of auxiliary metabolic genes (AMGs) involved in carbon, nitrogen, and phosphorus cycling within the virome. We also detected a total of 113 antibiotic resistance genes (ARGs), covering major classes of antibiotics across all samples analyzed. Additionally, our findings indicated the presence of virulence factors including the clpP gene accounting for approximately 4.78%, along with toxin genes such as the RecT gene representing approximately 73.48% of all detected virulence factors and toxin genes among all samples analyzed. This study expands our understanding regarding both pathogenic bacteria and viruses present within sewage sludge while providing valuable insights into their ecological functions.

Genomic analysis of lumpy skin disease virus asian variants and evaluation of its cellular tropism

Lumpy skin disease virus (LSDV) is a poxvirus that mainly affects cattle and can lead to symptoms such as severe reduction in milk production as well as infertility and mortality, which has resulted in dramatic economic loss in affected countries in Africa, Europe, and Asia. In this study, we successfully isolated two strains of LSDV from different geographical regions in China. Comparative genomic analyses were performed by incorporating additional LSDV whole genome sequences reported in other areas of Asia. Our analyses revealed that LSDV exhibited an 'open' pan-genome. Phylogenetic analysis unveiled distinct branches of LSDV evolution, signifying the prevalence of multiple lineages of LSDV across various regions in Asia. In addition, a reporter LSDV expressing eGFP directed by a synthetic poxvirus promoter was generated and used to evaluate the cell tropism of LSDV in various mammalian and avian cell lines. Our results demonstrated that LSDV replicated efficiently in several mammalian cell lines, including human A549 cells. In conclusion, our results underscore the necessity for strengthening LSD outbreak control measures and continuous epidemiological surveillance.

MetaCerberus: distributed highly parallelized HMM-based processing for robust functional annotation across the tree of life

MOTIVATION

MetaCerberus is a massively parallel, fast, low memory, scalable annotation tool for inference gene function across genomes to metacommunities. MetaCerberus provides an elusive HMM/HMMER-based tool at a rapid scale with low memory. It offers scalable gene elucidation to major public databases, including KEGG (KO), COGs, CAZy, FOAM, and specific databases for viruses, including VOGs and PHROGs, from single genomes to metacommunities.

RESULTS

MetaCerberus is 1.3× as fast on a single node than eggNOG-mapper v2 on 5× less memory using an exclusively HMM/HMMER mode. In a direct comparison, MetaCerberus provides better annotation of viruses, phages, and archaeal viruses than DRAM, Prokka, or InterProScan. MetaCerberus annotates more KOs across domains when compared to DRAM, with a 186× smaller database, and with 63× less memory. MetaCerberus is fully integrated for automatic analysis of statistics and pathways using differential statistic tools (i.e. DESeq2 and edgeR), pathway enrichment (GAGE R), and pathview R. MetaCerberus provides a novel tool for unlocking the biosphere across the tree of life at scale.

AVAILABILITY AND IMPLEMENTATION

MetaCerberus is written in Python and distributed under a BSD-3 license. The source code of MetaCerberus is freely available at https://github.com/raw-lab/metacerberus compatible with Python 3 and works on both Mac OS X and Linux. MetaCerberus can also be easily installed using bioconda: mamba create -n metacerberus -c bioconda -c conda-forge metacerberus.

Nanoformulated meloxicam and rifampin: inhibiting quorum sensing and biofilm formation in Pseudomonas aeruginosa

Background: We aimed to investigate the simultaneous effects of meloxicam and rifampin nanoformulations with solid lipid nanoparticle (SLN) and nanostructured lipid carrier (NLC) substrates on inhibiting the quorum-sensing system of Pseudomonas aeruginosa and preventing biofilm formation by this bacterium. Methods: Antimicrobial activity of rifampin and meloxicam encapsulated with SLNs and NLCs against P. aeruginosa PAO1 was assessed by disk diffusion, minimum inhibitory concentration (MIC) and minimum bactericidal concentration (MBC). Results: The SLN formulation was associated with lower doses for the MIC and minimum bactericidal concentration in comparison to NLC. Moreover, our results demonstrated that both nanoformulations were able to produce 100% inhibition of the biofilm formation of P. aeruginosa PAO1. Conclusion: All these findings suggest that meloxicam and rifampin encapsulated with SLNs could be the most effective formulation against P. aeruginosa.

Routes of dispersion of antibiotic resistance genes from the poultry farm system

Poultry farms are hotspots for the development and spread of antibiotic resistance genes (ARGs), due to high stocking densities and extensive use of antibiotics, posing a threat of spread and contagion to workers and the external environment. Here, we applied shotgun metagenome sequencing to characterize the gut microbiome and resistome of poultry, workers and their households - also including microbiomes from the internal and external farm environment - in three different farms in Italy during a complete rearing cycle. Our results highlighted a relevant overlap among the microbiomes of poultry, workers, and their families (gut and skin), with clinically relevant ARGs and associated mobile elements shared in both poultry and human samples. On a finer scale, the reconstruction of species-level genome bins (SGBs) allowed us to delineate the dynamics of microorganism and ARGs dispersion from farm systems. We found the associations with worker microbiomes representing the main route of ARGs dispersion from poultry to human populations. Collectively, our findings clearly demonstrate the urgent need to implement more effective procedures to counteract ARGs dispersion from poultry food systems and the relevance of metagenomics-based metacommunity approaches to monitor the ARGs dispersion process for the safety of the working environment on farms.

Role of vertical and horizontal microbial transmission of antimicrobial resistance genes in early life: insights from maternal-infant dyads

Early life represents a critical window for metabolic, cognitive and immune system development, which is influenced by the maternal microbiome as well as the infant gut microbiome. Antibiotic exposure, mode of delivery and breastfeeding practices modulate the gut microbiome and the reservoir of antibiotic resistance genes (ARGs). Vertical and horizontal microbial gene transfer during early life and the mechanisms behind these transfers are being uncovered. In this review, we aim to provide an overview of the current knowledge on the transfer of antibiotic resistance in the mother-infant dyad through vertical and horizontal transmission and to highlight the main gaps and challenges in this area.

Identification of potential microbial risk factors associated with fecal indicator exceedances at recreational beaches

BACKGROUND

Fecal bacterial densities are proxy indicators of beach water quality, and beach posting decisions are made based on Beach Action Value (BAV) exceedances for a beach. However, these traditional beach monitoring methods do not reflect the full extent of microbial water quality changes associated with BAV exceedances at recreational beaches (including harmful cyanobacteria). This proof of concept study evaluates the potential of metagenomics for comprehensively assessing bacterial community changes associated with BAV exceedances compared to non-exceedances for two urban beaches and their adjacent river water sources.

RESULTS

Compared to non-exceedance samples, BAV exceedance samples exhibited higher alpha diversity (diversity within the sample) that could be further differentiated into separate clusters (Beta-diversity). For Beach A, Cyanobacterial sequences (resolved as Microcystis and Pseudanabaena at genus level) were significantly more abundant in BAV non-exceedance samples. qPCR validation supported the Cyanobacterial abundance results from metagenomic analysis and also identified saxitoxin genes in 50% of the non-exceedance samples. Microcystis sp and saxitoxin gene sequences were more abundant on non-exceedance beach days (when fecal indicator data indicated the beach should be open for water recreational purposes). For BAV exceedance days, Fibrobacteres, Pseudomonas, Acinetobacter, and Clostridium sequences were significantly more abundant (and positively correlated with fecal indicator densities) for Beach A. For Beach B, Spirochaetes (resolved as Leptospira on genus level) Burkholderia and Vibrio sequences were significantly more abundant in BAV exceedance samples. Similar bacterial diversity and abundance trends were observed for river water sources compared to their associated beaches. Antibiotic Resistance Genes (ARGs) were also consistently detected at both beaches. However, we did not observe a significant difference or correlation in ARGs abundance between BAV exceedance and non-exceedance samples.

CONCLUSION

This study provides a more comprehensive analysis of bacterial community changes associated with BAV exceedances for recreational freshwater beaches. While there were increases in bacterial diversity and some taxa of potential human health concern associated with increased fecal indicator densities and BAV exceedances (e.g. Pseudomonas), metagenomics analyses also identified other taxa of potential human health concern (e.g. Microcystis) associated with lower fecal indicator densities and BAV non-exceedances days. This study can help develop more targeted beach monitoring strategies and beach-specific risk management approaches.

Metagenomic next-generation sequencing for the identification of infections caused by Gram-negative pathogens and the prediction of antimicrobial resistance

OBJECTIVE

The aim of this study was to evaluate the efficacy of metagenomic next-generation sequencing (mNGS) for the identification of Gram-negative bacteria (GNB) infections and the prediction of antimicrobial resistance.

METHODS

A retrospective analysis was conducted on 182 patients with diagnosis of GNB infections who underwent mNGS and conventional microbiological tests (CMTs).

RESULTS

The detection rate of mNGS was 96.15%, higher than CMTs (45.05%) with a significant difference (χ 2 = 114.46, P < .01). The pathogen spectrum identified by mNGS was significantly wider than CMTs. Interestingly, the detection rate of mNGS was substantially higher than that of CMTs (70.33% vs 23.08%, P < .01) in patients with but not without antibiotic exposure. There was a significant positive correlation between mapped reads and pro-inflammatory cytokines (interleukin-6 and interleukin-8). However, mNGS failed to predict antimicrobial resistance in 5 of 12 patients compared to phenotype antimicrobial susceptibility testing results.

CONCLUSIONS

Metagenomic next-generation sequencing has a higher detection rate, a wider pathogen spectrum, and is less affected by prior antibiotic exposure than CMTs in identifying Gram-negative pathogens. The mapped reads may reflect a pro-inflammatory state in GNB-infected patients. Inferring actual resistance phenotypes from metagenomic data remains a great challenge.

Metagenomic assembly is the main bottleneck in the identification of mobile genetic elements

Antimicrobial resistance genes (ARG) are commonly found on acquired mobile genetic elements (MGEs) such as plasmids or transposons. Understanding the spread of resistance genes associated with mobile elements (mARGs) across different hosts and environments requires linking ARGs to the existing mobile reservoir within bacterial communities. However, reconstructing mARGs in metagenomic data from diverse ecosystems poses computational challenges, including genome fragment reconstruction (assembly), high-throughput annotation of MGEs, and identification of their association with ARGs. Recently, several bioinformatics tools have been developed to identify assembled fragments of plasmids, phages, and insertion sequence (IS) elements in metagenomic data. These methods can help in understanding the dissemination of mARGs. To streamline the process of identifying mARGs in multiple samples, we combined these tools in an automated high-throughput open-source pipeline, MetaMobilePicker, that identifies ARGs associated with plasmids, IS elements and phages, starting from short metagenomic sequencing reads. This pipeline was used to identify these three elements on a simplified simulated metagenome dataset, comprising whole genome sequences from seven clinically relevant bacterial species containing 55 ARGs, nine plasmids and five phages. The results demonstrated moderate precision for the identification of plasmids (0.57) and phages (0.71), and moderate sensitivity of identification of IS elements (0.58) and ARGs (0.70). In this study, we aim to assess the main causes of this moderate performance of the MGE prediction tools in a comprehensive manner. We conducted a systematic benchmark, considering metagenomic read coverage, contig length cutoffs and investigating the performance of the classification algorithms. Our analysis revealed that the metagenomic assembly process is the primary bottleneck when linking ARGs to identified MGEs in short-read metagenomics sequencing experiments rather than ARGs and MGEs identification by the different tools.

Premise Plumbing Pipe Materials and In-Building Disinfectants Shape the Potential for Proliferation of Pathogens and Antibiotic Resistance Genes

In-building disinfectants are commonly applied to control the growth of pathogens in plumbing, particularly in facilities such as hospitals that house vulnerable populations. However, their application has not been well optimized, especially with respect to interactive effects with pipe materials and potential unintended effects, such as enrichment of antibiotic resistance genes (ARGs) across the microbial community. Here, we used triplicate convectively mixed pipe reactors consisting of three pipe materials (PVC, copper, and iron) for replicated simulation of the distal reaches of premise plumbing and evaluated the effects of incrementally increased doses of chlorine, chloramine, chlorine dioxide, and copper-silver disinfectants. We used shotgun metagenomic sequencing to characterize the resulting succession of the corresponding microbiomes over the course of 37 weeks. We found that both disinfectants and pipe material affected ARG and microbial community taxonomic composition both independently and interactively. Water quality and total bacterial numbers were not found to be predictive of pathogenic species markers. One result of particular concern was the tendency of disinfectants, especially monochloramine, to enrich ARGs. Metagenome assembly indicated that many ARGs were enriched specifically among the pathogenic species. Functional gene analysis was indicative of a response of the microbes to oxidative stress, which is known to co/cross-select for antibiotic resistance. These findings emphasize the need for a holistic evaluation of pathogen control strategies for plumbing.

Influence of genomic variations on glanders serodiagnostic antigens using integrative genomic and transcriptomic approaches

Glanders is a highly contagious and life-threatening zoonotic disease caused by Burkholderia mallei (B. mallei). Without an effective vaccine or treatment, early diagnosis has been regarded as the most effective method to prevent glanders transmission. Currently, the diagnosis of glanders is heavily reliant on serological tests. However, given that markedly different host immune responses can be elicited by genetically different strains of the same bacterial species, infection by B. mallei, whose genome is unstable and plastic, may result in various immune responses. This variability can make the serodiagnosis of glanders challenging. Therefore, there is a need for a comprehensive understanding and assessment of how B. mallei genomic variations impact the appropriateness of specific target antigens for glanders serodiagnosis. In this study, we investigated how genomic variations in the B. mallei genome affect gene content (gene presence/absence) and expression, with a special focus on antigens used or potentially used in serodiagnosis. In all the genome sequences of B. mallei isolates available in NCBI's RefSeq database (accessed in July 2023) and in-house sequenced samples, extensive small and large variations were observed when compared to the type strain ATCC 23344. Further pan-genome analysis of those assemblies revealed variations of gene content among all available genomes of B. mallei. Specifically, differences in gene content ranging from 31 to 715 genes with an average of 334 gene presence-absence variations were found in strains with complete or chromosome-level genome assemblies, using the ATCC 23344 strain as a reference. The affected genes included some encoded proteins used as serodiagnostic antigens, which were lost due mainly to structural variations. Additionally, a transcriptomic analysis was performed using the type strain ATCC 23344 and strain Zagreb which has been widely utilized to produce glanders antigens. In total, 388 significant differentially expressed genes were identified between these two strains, including genes related to bacterial pathogenesis and virulence, some of which were associated with genomic variations, particularly structural variations. To our knowledge, this is the first comprehensive study to uncover the impacts of genetic variations of B. mallei on its gene content and expression. These differences would have significant impacts on host innate and adaptive immunity, including antibody production, during infection. This study provides novel insights into B. mallei genetic variants, knowledge which will help to improve glanders serodiagnosis.

Functional enrichment of integrons: Facilitators of antimicrobial resistance and niche adaptation

Integrons are genetic elements, found among diverse bacteria and archaea, that capture and rearrange gene cassettes to rapidly generate genetic diversity and drive adaptation. Despite their broad taxonomic and geographic prevalence, and their role in microbial adaptation, the functions of gene cassettes remain poorly characterized. Here, using a combination of bioinformatic and experimental analyses, we examined the functional diversity of gene cassettes from different environments. We find that cassettes encode diverse antimicrobial resistance (AMR) determinants, including those conferring resistance to antibiotics currently in the developmental pipeline. Further, we find a subset of cassette functions is universally enriched relative to their broader metagenomes. These are largely involved in (a)biotic interactions, including AMR, phage defense, virulence, biodegradation, and stress tolerance. The remainder of functions are sample-specific, suggesting that they confer localised functions relevant to their microenvironment. Together, they comprise functional profiles different from bulk metagenomes, representing niche-adaptive components of the prokaryotic pangenome.

Composition, antibiotic resistance, and virulence analysis of microbiota in dormitory drain pipes

Introduction

Dormitory washbasins can breed microorganisms that produce odorous gases, polluting the indoor environment.

Methods

We utilized metagenome sequencing to analyze the microbiota of 40 samples from the drain pipes of dormitory washbasins. Our study aimed to investigate the microbial community structure, antibiotic resistance genes, and virulence factors, and to identify potential influencing factors such as gender, hometown, frequency of hand sanitizer usage, and number of dormitory residents.

Results

The analysis revealed 12 phyla and 147 genera, with Proteobacteria and Actinobacteria being the dominant phyla, and Mycobacterium and Nakamurella being the dominant genera. We found that the factors influencing the microbial community structure of the dormitory washbasin drain pipe are complex. The investigated factors have a slight influence on the drain pipe microbial community, with gender exerting a discernible influence. The annotation results revealed the presence of various virulence factors, pathogenic toxins and antibiotic resistance genes, including 246 different toxin types and 30 different types of antibiotic resistance genes. In contrast to the observed differences in microbial composition among samples, the distribution of resistance genes shows relatively small changes among samples. Antibiotics should be a contributing factor in the overall increase of antibiotic resistance genes in drain pipes.

Discussion

Overall, our study provides important insights into the community structure and function of microorganisms in dormitory drainage systems, and can guide efforts to prevent and control microbial pollution.

Populational genomic insights of Paraclostridium bifermentans as an emerging human pathogen

Paraclostridium bifermentans (P.b) is an emerging human pathogen that is phylogenomically close to Paeniclostridium sordellii (P.s), while their populational genomic features and virulence capacity remain understudied. Here, we performed comparative genomic analyses of P.b and compared their pan-genomic features and virulence coding profiles to those of P.s. Our results revealed that P.b has a more plastic pangenome, a larger genome size, and a higher GC content than P.s. Interestingly, the P.b and P.s share similar core-genomic functions, but P.b encodes more functions in nutrient metabolism and energy conversion and fewer functions in host defense in their accessory-genomes. The P.b may initiate extracellular infection processes similar to those of P.s and Clostridium perfringens by encoding three toxin homologs (i.e., microbial collagenase, thiol-activated cytolysin, phospholipase C, which are involved in extracellular matrices degradation and membrane damaging) in their core-genomes. However, P.b is less toxic than the P.s by encoding fewer secretion toxins in the core-genome and fewer lethal toxins in the accessory-genome. Notably, P.b carries more toxins genes in their accessory-genomes, particularly those of plasmid origin. Moreover, three within-species and highly conserved plasmid groups, encoding virulence, gene acquisition, and adaptation, were carried by 25-33% of P.b strains and clustered by isolation source rather than geography. This study characterized the pan-genomic virulence features of P.b for the first time, and revealed that P. bifermentans is an emerging pathogen that can threaten human health in many aspects, emphasizing the importance of phenotypic and genomic characterizations of in situ clinical isolates.

Diversity and function of mountain and polar supraglacial DNA viruses

Mountain and polar glaciers cover 10% of the Earth's surface and are typically extreme environments that challenge life of all forms. Viruses are abundant and active in supraglacial ecosystems and play a crucial role in controlling the supraglacial microbial communities. However, our understanding of virus ecology on glacier surfaces and their potential impacts on downstream ecosystems remains limited. Here, we present the supraglacial virus genome (SgVG) catalog, a 15-fold expanded genomic inventory of 10,840 DNA-virus species from 38 mountain and polar glaciers, spanning habitats such as snow, ice, meltwater, and cryoconite. Supraglacial DNA-viruses were highly specific compared to viruses in other ecosystems yet exhibited low public health risks. Supraglacial viral communities were primarily constrained by habitat, with cryoconite displaying the highest viral activity levels. We observed a prevalence of lytic viruses in all habitats, especially in cryoconite, but a high level of lysogenic viruses in snow and ice. Additionally, we found that supraglacial viruses could be linked to ∼83% of obtained prokaryotic phyla/classes and possessed the genetic potential to promote metabolism and increase cold adaptation, cell mobility, and phenolic carbon use of hosts in hostile environmental conditions using diverse auxiliary metabolic genes. Our results provide the first systematic characterization of the diversity, function, and public health risks evaluation of mountain and polar supraglacial DNA viruses. This understanding of glacial viruses is crucial for function assessments and ecological modeling of glacier ecosystems, especially for the Tibetan Plateau's Mountain glaciers, which support ∼20% of the human populations on Earth.

Bacteremia due to Clostridium innocuum: Analysis of four cases and literature review

Clostridium innocuum is a Gram-positive anaerobic spore-forming bacillus that has been identified as part of the normal intestinal microbiota. This bacterium has been rarely associated with human infections, and only few severe infections have been reported until now. In this work, we report on four patients with bacteremia due to C. innocuum, which were well identified by MALDI-TOF MS. Moreover, a review of the previous published cases of bacteremia due to this anaerobic bacterium has been performed.

A Comprehensive Bioinformatics Resource Guide for Genome-Based Antimicrobial Resistance Studies

The use of high-throughput sequencing technologies and bioinformatic tools has greatly transformed microbial genome research. With the help of sophisticated computational tools, it has become easier to perform whole genome assembly, identify and compare different species based on their genomes, and predict the presence of genes responsible for proteins, antimicrobial resistance, and toxins. These bioinformatics resources are likely to continuously improve in quality, become more user-friendly to analyze the multiple genomic data, efficient in generating information and translating it into meaningful knowledge, and enhance our understanding of the genetic mechanism of AMR. In this manuscript, we provide an essential guide for selecting the popular resources for microbial research, such as genome assembly and annotation, antibiotic resistance gene profiling, identification of virulence factors, and drug interaction studies. In addition, we discuss the best practices in computer-oriented microbial genome research, emerging trends in microbial genomic data analysis, integration of multi-omics data, the appropriate use of machine-learning algorithms, and open-source bioinformatics resources for genome data analytics.

RVFScan predicts virulence factor genes and hypervirulence of the clinical metagenome

Bacterial infections often involve virulence factors that play a crucial role in the pathogenicity of bacteria. Accurate detection of virulence factor genes (VFGs) is essential for precise treatment and prognostic management of hypervirulent bacterial infections. However, there is a lack of rapid and accurate methods for VFG identification from the metagenomic data of clinical samples. Here, we developed a Reads-based Virulence Factors Scanner (RVFScan), an innovative user-friendly online tool that integrates a comprehensive VFG database with similarity matrix-based criteria for VFG prediction and annotation using metagenomic data without the need for assembly. RVFScan demonstrated superior performance compared to previous assembly-based and read-based VFG predictors, achieving a sensitivity of 97%, specificity of 98% and accuracy of 98%. We also conducted a large-scale analysis of 2425 clinical metagenomic datasets to investigate the utility of RVFScan, the species-specific VFG profiles and associations between VFGs and virulence phenotypes for 24 important pathogens were analyzed. By combining genomic comparisons and network analysis, we identified 53 VFGs with significantly higher abundances in hypervirulent Klebsiella pneumoniae (hvKp) than in classical K. pneumoniae. Furthermore, a cohort of 1256 samples suspected of K. pneumoniae infection demonstrated that RVFScan could identify hvKp with a sensitivity of 90%, specificity of 100% and accuracy of 98.73%, with 90% of hvKp samples consistent with clinical diagnosis (Cohen's kappa, 0.94). RVFScan has the potential to detect VFGs in low-biomass and high-complexity clinical samples using metagenomic reads without assembly. This capability facilitates the rapid identification and targeted treatment of hvKp infections and holds promise for application to other hypervirulent pathogens.

ARGem: a new metagenomics pipeline for antibiotic resistance genes: metadata, analysis, and visualization

Antibiotic resistance is of crucial interest to both human and animal medicine. It has been recognized that increased environmental monitoring of antibiotic resistance is needed. Metagenomic DNA sequencing is becoming an attractive method to profile antibiotic resistance genes (ARGs), including a special focus on pathogens. A number of computational pipelines are available and under development to support environmental ARG monitoring; the pipeline we present here is promising for general adoption for the purpose of harmonized global monitoring. Specifically, ARGem is a user-friendly pipeline that provides full-service analysis, from the initial DNA short reads to the final visualization of results. The capture of extensive metadata is also facilitated to support comparability across projects and broader monitoring goals. The ARGem pipeline offers efficient analysis of a modest number of samples along with affordable computational components, though the throughput could be increased through cloud resources, based on the user's configuration. The pipeline components were carefully assessed and selected to satisfy tradeoffs, balancing efficiency and flexibility. It was essential to provide a step to perform short read assembly in a reasonable time frame to ensure accurate annotation of identified ARGs. Comprehensive ARG and mobile genetic element databases are included in ARGem for annotation support. ARGem further includes an expandable set of analysis tools that include statistical and network analysis and supports various useful visualization techniques, including Cytoscape visualization of co-occurrence and correlation networks. The performance and flexibility of the ARGem pipeline is demonstrated with analysis of aquatic metagenomes. The pipeline is freely available at https://github.com/xlxlxlx/ARGem.

Predicting variable gene content in Escherichia coli using conserved genes

Having the ability to predict the protein-encoding gene content of an incomplete genome or metagenome-assembled genome is important for a variety of bioinformatic tasks. In this study, as a proof of concept, we built machine learning classifiers for predicting variable gene content in Escherichia coli genomes using only the nucleotide k-mers from a set of 100 conserved genes as features. Protein families were used to define orthologs, and a single classifier was built for predicting the presence or absence of each protein family occurring in 10%-90% of all E. coli genomes. The resulting set of 3,259 extreme gradient boosting classifiers had a per-genome average macro F1 score of 0.944 [0.943-0.945, 95% CI]. We show that the F1 scores are stable across multi-locus sequence types and that the trend can be recapitulated by sampling a smaller number of core genes or diverse input genomes. Surprisingly, the presence or absence of poorly annotated proteins, including "hypothetical proteins" was accurately predicted (F1 = 0.902 [0.898-0.906, 95% CI]). Models for proteins with horizontal gene transfer-related functions had slightly lower F1 scores but were still accurate (F1s = 0.895, 0.872, 0.824, and 0.841 for transposon, phage, plasmid, and antimicrobial resistance-related functions, respectively). Finally, using a holdout set of 419 diverse E. coli genomes that were isolated from freshwater environmental sources, we observed an average per-genome F1 score of 0.880 [0.876-0.883, 95% CI], demonstrating the extensibility of the models. Overall, this study provides a framework for predicting variable gene content using a limited amount of input sequence data. IMPORTANCE Having the ability to predict the protein-encoding gene content of a genome is important for assessing genome quality, binning genomes from shotgun metagenomic assemblies, and assessing risk due to the presence of antimicrobial resistance and other virulence genes. In this study, we built a set of binary classifiers for predicting the presence or absence of variable genes occurring in 10%-90% of all publicly available E. coli genomes. Overall, the results show that a large portion of the E. coli variable gene content can be predicted with high accuracy, including genes with functions relating to horizontal gene transfer. This study offers a strategy for predicting gene content using limited input sequence data.

Determining the Contribution of Micro/Nanoplastics to Antimicrobial Resistance: Challenges and Perspectives

Microorganisms colonizing the surfaces of microplastics form a plastisphere in the environment, which captures miscellaneous substances. The plastisphere, owning to its inherently complex nature, may serve as a "Petri dish" for the development and dissemination of antibiotic resistance genes (ARGs), adding a layer of complexity in tackling the global challenge of both microplastics and ARGs. Increasing studies have drawn insights into the extent to which the proliferation of ARGs occurred in the presence of micro/nanoplastics, thereby increasing antimicrobial resistance (AMR). However, a comprehensive review is still lacking in consideration of the current increasingly scattered research focus and results. This review focuses on the spread of ARGs mediated by microplastics, especially on the challenges and perspectives on determining the contribution of microplastics to AMR. The plastisphere accumulates biotic and abiotic materials on the persistent surfaces, which, in turn, offers a preferred environment for gene exchange within and across the boundary of the plastisphere. Microplastics breaking down to smaller sizes, such as nanoscale, can possibly promote the horizontal gene transfer of ARGs as environmental stressors by inducing the overgeneration of reactive oxygen species. Additionally, we also discussed methods, especially quantitatively comparing ARG profiles among different environmental samples in this emerging field and the challenges that multidimensional parameters are in great necessity to systematically determine the antimicrobial dissemination risk in the plastisphere. Finally, based on the biological sequencing data, we offered a framework to assess the AMR risks of micro/nanoplastics and biocolonizable microparticles that leverage multidimensional AMR-associated messages, including the ARGs' abundance, mobility, and potential acquisition by pathogens.

Microdiversity of the vaginal microbiome is associated with preterm birth

Preterm birth (PTB) is the leading cause of neonatal morbidity and mortality. The vaginal microbiome has been associated with PTB, yet the mechanisms underlying this association are not fully understood. Understanding microbial genetic adaptations to selective pressures, especially those related to the host, may yield insights into these associations. Here, we analyze metagenomic data from 705 vaginal samples collected during pregnancy from 40 women who delivered preterm spontaneously and 135 term controls from the Multi-Omic Microbiome Study-Pregnancy Initiative. We find that the vaginal microbiome of pregnancies that ended preterm exhibited unique genetic profiles. It was more genetically diverse at the species level, a result which we validate in an additional cohort, and harbored a higher richness and diversity of antimicrobial resistance genes, likely promoted by transduction. Interestingly, we find that Gardnerella species drove this higher genetic diversity, particularly during the first half of the pregnancy. We further present evidence that Gardnerella spp. underwent more frequent recombination and stronger purifying selection in genes involved in lipid metabolism. Overall, our population genetics analyses reveal associations between the vaginal microbiome and PTB and suggest that evolutionary processes acting on vaginal microbes may play a role in adverse pregnancy outcomes such as PTB.

Microdiversity of the Vaginal Microbiome is Associated with Preterm Birth

Preterm birth (PTB) is the leading cause of neonatal morbidity and mortality. The vaginal microbiome has been associated with PTB, yet the mechanisms underlying this association are not fully understood. Understanding microbial genetic adaptations to selective pressures, especially those related to the host, may yield new insights into these associations. To this end, we analyzed metagenomic data from 705 vaginal samples collected longitudinally during pregnancy from 40 women who delivered preterm spontaneously and 135 term controls from the Multi-Omic Microbiome Study-Pregnancy Initiative (MOMS-PI). We find that the vaginal microbiome of pregnancies that ended preterm exhibits unique genetic profiles. It is more genetically diverse at the species level, a result which we validate in an additional cohort, and harbors a higher richness and diversity of antimicrobial resistance genes, likely promoted by transduction. Interestingly, we find that Gardnerella species, a group of central vaginal pathobionts, are driving this higher genetic diversity, particularly during the first half of the pregnancy. We further present evidence that Gardnerella spp. undergoes more frequent recombination and stronger purifying selection in genes involved in lipid metabolism. Overall, our results reveal novel associations between the vaginal microbiome and PTB using population genetics analyses, and suggest that evolutionary processes acting on the vaginal microbiome may play a vital role in adverse pregnancy outcomes such as preterm birth.

Plastic leachate exposure drives antibiotic resistance and virulence in marine bacterial communities

Plastic pollution is a serious global problem, with more than 12 million tonnes of plastic waste entering the oceans every year. Plastic debris can have considerable impacts on microbial community structure and functions in marine environments, and has been associated with an enrichment in pathogenic bacteria and antimicrobial resistance (AMR) genes. However, our understanding of these impacts is largely restricted to microbial assemblages on plastic surfaces. It is therefore unclear whether these effects are driven by the surface properties of plastics, providing an additional niche for certain microbes residing in biofilms, and/or chemicals leached from plastics, the effects of which could extend to surrounding planktonic bacteria. Here, we examine the effects of polyvinyl chloride (PVC) plastic leachate exposure on the relative abundance of genes associated with bacterial pathogenicity and AMR within a seawater microcosm community. We show that PVC leachate, in the absence of plastic surfaces, drives an enrichment in AMR and virulence genes. In particular, leachate exposure significantly enriches AMR genes that confer multidrug, aminoglycoside and peptide antibiotic resistance. Additionally, enrichment of genes involved in the extracellular secretion of virulence proteins was observed among pathogens of marine organisms. This study provides the first evidence that chemicals leached from plastic particles alone can enrich genes related to microbial pathogenesis within a bacterial community, expanding our knowledge of the environmental impacts of plastic pollution with potential consequences for human and ecosystem health.

Cascade capture, oxidization and inactivation for removing multi-species pollutants, antimicrobial resistance and pathogenicity from hospital wastewater

As reservoirs of pathogens, antimicrobial resistant microorganisms and a wide variety of pollutants, hospital wastewaters (HWWs) need to be effectively treated before discharge. This study employed the functionalized colloidal microbubble technology as one-step fast HWW treatment. Inorganic coagulant (monomeric Fe(III)-coagulant or polymeric Al(III)-coagulant) and ozone were used as surface-decorator and gaseous core modifier, respectively. The Fe(III)- or Al(III)-modified colloidal gas (or, ozone) microbubbles (Fe(III)-CCGMBs, Fe(III)-CCOMBs, Al(III)-CCGMBs and Al(III)-CCOMBs) were constructed. Within 3 min, CCOMBs decreased COD_Cr and fecal coliform concentration to the levels meeting the national discharge standard for medical organization. Regrowth of bacteria was inhibited and biodegradability of organics was increased after the simultaneous oxidation and cell-inactivation process. The metagenomics analysis further reveals that Al(III)-CCOMBs performed best in capturing the virulence genes, antibiotic resistance genes and their potential hosts. The horizontal transfer of those harmful genes could be effectively hampered thanks to the removal of mobile genetic elements. Interestingly, the virulence factors of adherence, micronutrient uptake/acquisition and phase invasion could facilitate the interface-dominated capture. Featured as cascade processes of capture, oxidation and inactivation in the one-step operation, the robust Al(III)-CCOMB treatment is recommended for the HWW treatment and the protection of downstream aquatic environment.

Metagenomic insights into dietary remodeling of gut microbiota and antibiotic resistome in meat rabbits

The gut microbiota is a repository of antibiotic resistance genes (ARGs), which may affect the health of humans and animals. The intestinal flora is affected by many factors but it is unclear how the intestinal microflora and antibiotic resistome in rabbits might change under dietary intervention. Feeding with lettuce led to the amplification and transfer of exogenous ARGs in the intestinal flora, but there were no significant differences when fed lettuces grown with different manure types. For example, the lsaC of lettuce fed with bovine, chicken and pig manure without adding organic fertilizer increased by 0.143, 0.151, 0.179 and 0.169 logs respectively after 4 weeks, and the efrB also increased by 0.074, 0.068, 0.079 and 0.106 logs respectively. Network analysis showed that Clostridium_ sensu_ stricto_ 18 was a potential host of type 6 virulence factor genes (VFGs). Mantel analysis showed that ARGs were directly influenced by mobile genetic elements (MGEs) and VFGs. Thus, feeding rabbits lettuce grown with different manure types contribute to the transmission of ARGs by remodeling the intestinal microenvironment. In addition, diet may affect exogenous ARGs to change the intestinal antibiotic resistome and possibly threaten health.

Potential reservoirs of antimicrobial resistance in livestock waste and treated wastewater that can be disseminated to agricultural land

Livestock manure, dairy lagoon effluent, and treated wastewater are known reservoirs of antibiotic resistance genes (ARGs), antibiotic-resistant bacteria (ARB), and virulence factor genes (VFGs), and their application to agricultural farmland could be a serious public health threat. However, their dissemination to agricultural lands and impact on important geochemical pathways such as the nitrogen (N) cycle have not been jointly explored. In this study, shotgun metagenomic sequencing and analyses were performed to examine the diversity and composition of microbial communities, ARGs, VFGs, and N cycling genes in different livestock manure/lagoon and treated wastewater collected from concentrated animal feeding operations (CAFOs) and a municipal wastewater treatment plant along the west coast of the United States. Multivariate analysis showed that diversity indices of bacterial taxa from the different microbiomes were not significantly different based on InvSimpson (P = 0.05), but differences in ARG mechanisms were observed between swine manure and other microbiome sources. Comparative resistome profiling showed that ARGs in microbiome samples belonged to four core resistance classes: aminoglycosides (40-55 %), tetracyclines (30-45 %), beta-lactam-resistance (20-35 %), macrolides (18-30 %), and >50 % of the VFGs that the 24 microbiomes harbored were phyletically affiliated with two bacteria, Bacteroidetes fragilis and Enterobacter aerogenes. Network analysis based on Spearman correlation showed co-occurrence patterns between several genes such as transporter-gene and regulator, efflux pump and involved-in-polymyxin- resistance, aminoglycoside, beta-lactam, and macrolide with VFGs and bacterial taxa such as Firmicutes, Candidatus Themoplasmatota, Actinobacteria, and Bacteroidetes. Metabolic reconstruction of metagenome-assembled genome (MAGs) analysis showed that the most prevalent drug resistance mechanisms were associated with carbapenem resistance, multidrug resistance (MDR), and efflux pump. Bacteroidales was the main taxa involved in dissimilatory nitrate reduction (DNRA) in dairy lagoon effluent. This study demonstrates that the dissemination of waste from these sources can increase the spread of ARGs, ARB, and VFGs into agricultural lands, negatively impacting both soil and human health.

Reservoirs of antimicrobial resistance in the context of One Health

The emergence and spread of antimicrobial resistance (AMR) and resistant bacteria, are a global public health challenge. Through horizontal gene transfer, potential pathogens can acquire antimicrobial resistance genes (ARGs) that can subsequently be spread between human, animal, and environmental reservoirs. To understand the dissemination of ARGs and linked microbial taxa, it is necessary to map the resistome within different microbial reservoirs. By integrating knowledge on ARGs in the different reservoirs, the One Health approach is crucial to our understanding of the complex mechanisms and epidemiology of AMR. Here, we highlight the latest insights into the emergence and spread of AMR from the One Health perspective, providing a baseline of understanding for future scientific investigations into this constantly growing global health threat.

Efflux pumps activation caused by mercury contamination prompts antibiotic resistance and pathogen's virulence under ambient and elevated CO2 concentration

The occurrence and development of antibiotic resistance genes (ARGs) in pathogens poses serious threatens to global health. Agricultural soils provide reservoirs for pathogens and ARGs, closely related to public health and food safety. Especially, metals stress provides more long-standing selection pressure for ARGs, and climate change is a "threat multiplier" for the spread of ARGs. However, little is known about the impact of metals contamination on pathogens and ARGs in agricultural soils and their sensitivity to ongoing climate changes. To fill this gap, a pot experiment was conducted in open-top chambers (OTCs) to investigate the influence of mercury (Hg) contamination on the distribution of soil pathogens and ARGs under ambient and elevated CO₂ concentration. Results showed that the relative abundance of common plant and human pathogens increased significantly in Hg-contaminated soil under two CO₂ concentrations. Hg contamination was a positive effector of the activation of efflux pumps and offensive virulence factors (adhere and secretion system) under two CO₂ levels. Activation of efflux pumps caused by Hg contamination might contribute to changes of virulence or fitness of certain pathogens. Overall, our study emphasizes the critical role of efflux pumps as an intersection of antibiotic resistance and pathogen's virulence under Hg stress.

Altered infective competence of the human gut microbiome in COVID-19

BACKGROUND

Infections with SARS-CoV-2 have a pronounced impact on the gastrointestinal tract and its resident microbiome. Clear differences between severe cases of infection and healthy individuals have been reported, including the loss of commensal taxa. We aimed to understand if microbiome alterations including functional shifts are unique to severe cases or a common effect of COVID-19. We used high-resolution systematic multi-omic analyses to profile the gut microbiome in asymptomatic-to-moderate COVID-19 individuals compared to a control group.

RESULTS

We found a striking increase in the overall abundance and expression of both virulence factors and antimicrobial resistance genes in COVID-19. Importantly, these genes are encoded and expressed by commensal taxa from families such as Acidaminococcaceae and Erysipelatoclostridiaceae, which we found to be enriched in COVID-19-positive individuals. We also found an enrichment in the expression of a betaherpesvirus and rotavirus C genes in COVID-19-positive individuals compared to healthy controls.

CONCLUSIONS

Our analyses identified an altered and increased infective competence of the gut microbiome in COVID-19 patients. Video Abstract.

Diversity and Prevalence of Clostridium innocuum in the Human Gut Microbiota

Clostridia are a polyphyletic group of Gram-positive, spore-forming anaerobes in the Firmicutes phylum that significantly impact metabolism and functioning of the human gastrointestinal tract. Recently, Clostridia were divided into two separate classes, Clostridia and Erysipelotrichia, based on phenotypic and 16S rRNA gene-based differences. While Clostridia include many well-known pathogenic bacteria, Erysipelotrichia remain relatively uncharacterized, particularly regarding their role as a pathogen versus commensal. Despite wide recognition as a commensal, the erysipelotrichial species Clostridium innocuum has recently been associated with various disease states. To further understand the ecological and potential virulent role of C. innocuum, we conducted a genomic comparison across 38 C. innocuum isolates and 194 publicly available genomes. Based on colony morphology, we isolated multiple C. innocuum cultivars from the feces of healthy human volunteers (n = 5). Comparison of the 16S rRNA gene of our isolates against publicly available microbiota data sets in healthy individuals suggests a high prevalence of C. innocuum across the human population (>80%). Analysis of single nucleotide polymorphisms (SNPs) across core genes and average nucleotide identify (ANI) revealed the presence of four clades among all available genomes (n = 232 total). Investigation of carbohydrate and protein utilization pathways, including comparison against the carbohydrate-activating enzyme (CAZyme) database, demonstrated inter- and intraclade differences that were further substantiated in vitro. Collectively, these data indicate genetic variance within the C. innocuum species that may help clarify its role in human disease and health. IMPORTANCE Clostridia are a group of medically important anaerobes as both commensals and pathogens. Recently, a new class of Erysipelotrichia containing a number of reassigned clostridial species has emerged, including Clostridium innocuum. Recent studies have implicated C. innocuum as a potential causative agent of diarrhea in patients from whom Clostridioides difficile could not be isolated. Using genomic and in vitro comparison, this study sought to characterize C. innocuum in the healthy human gut. Our analyses suggest that C. innocuum is a highly prevalent and diverse species, demonstrating clade-specific differences in metabolism and potential virulence. Collectively, this study is the first investigation into a broader description of C. innocuum as a human gut inhabitant.

Glacier-Fed Stream Biofilms Harbor Diverse Resistomes and Biosynthetic Gene Clusters

Antimicrobial resistance (AMR) is a universal phenomenon the origins of which lay in natural ecological interactions such as competition within niches, within and between micro- to higher-order organisms. To study these phenomena, it is crucial to examine the origins of AMR in pristine environments, i.e., limited anthropogenic influences. In this context, epilithic biofilms residing in glacier-fed streams (GFSs) are an excellent model system to study diverse, intra- and inter-domain, ecological crosstalk. We assessed the resistomes of epilithic biofilms from GFSs across the Southern Alps (New Zealand) and the Caucasus (Russia) and observed that both bacteria and eukaryotes encoded twenty-nine distinct AMR categories. Of these, beta-lactam, aminoglycoside, and multidrug resistance were both abundant and taxonomically distributed in most of the bacterial and eukaryotic phyla. AMR-encoding phyla included Bacteroidota and Proteobacteria among the bacteria, alongside Ochrophyta (algae) among the eukaryotes. Additionally, biosynthetic gene clusters (BGCs) involved in the production of antibacterial compounds were identified across all phyla in the epilithic biofilms. Furthermore, we found that several bacterial genera (Flavobacterium, Polaromonas, Superphylum Patescibacteria) encode both atimicrobial resistance genes (ARGs) and BGCs within close proximity of each other, demonstrating their capacity to simultaneously influence and compete within the microbial community. Our findings help unravel how naturally occurring BGCs and AMR contribute to the epilithic biofilms mode of life in GFSs. Additionally, we report that eukaryotes may serve as AMR reservoirs owing to their potential for encoding ARGs. Importantly, these observations may be generalizable and potentially extended to other environments that may be more or less impacted by human activity. IMPORTANCE Antimicrobial resistance is an omnipresent phenomenon in the anthropogenically influenced ecosystems. However, its role in shaping microbial community dynamics in pristine environments is relatively unknown. Using metagenomics, we report the presence of antimicrobial resistance genes and their associated pathways in epilithic biofilms within glacier-fed streams. Importantly, we observe biosynthetic gene clusters associated with antimicrobial resistance in both pro- and eukaryotes in these biofilms. Understanding the role of resistance in the context of this pristine environment and complex biodiversity may shed light on previously uncharacterized mechanisms of cross-domain interactions.

HyperVR: a hybrid deep ensemble learning approach for simultaneously predicting virulence factors and antibiotic resistance genes

Infectious diseases emerge unprecedentedly, posing serious challenges to public health and the global economy. Virulence factors (VFs) enable pathogens to adhere, reproduce and cause damage to host cells, and antibiotic resistance genes (ARGs) allow pathogens to evade otherwise curable treatments. Simultaneous identification of VFs and ARGs can save pathogen surveillance time, especially in situ epidemic pathogen detection. However, most tools can only predict either VFs or ARGs. Few tools that predict VFs and ARGs simultaneously usually have high false-negative rates, are sensitive to the cutoff thresholds and can only identify conserved genes. For better simultaneous prediction of VFs and ARGs, we propose a hybrid deep ensemble learning approach called HyperVR. By considering both best hit scores and statistical gene sequence patterns, HyperVR combines classical machine learning and deep learning to simultaneously and accurately predict VFs, ARGs and negative genes (neither VFs nor ARGs). For the prediction of individual VFs and ARGs, in silico spike-in experiment (the VFs and ARGs in real metagenomic data), and pseudo-VFs and -ARGs (gene fragments), HyperVR outperforms the current state-of-the-art prediction tools. HyperVR uses only gene sequence information without strict cutoff thresholds, hence making prediction straightforward and reliable.

Phytostabilization mitigates antibiotic resistance gene enrichment in a copper mine tailings pond

Mining-impacted environments are distributed globally and have become increasingly recognized as hotspots of antibiotic resistance genes (ARGs). However, there are currently no reports on treatment technologies to deal with such an important environmental problem. To narrow this knowledge gap, we implemented a phytostabilization project in an acidic copper mine tailings pond and employed metagenomics to explore ARG characteristics in the soil samples. Our results showed that phytostabilization decreased the total ARG abundance in 0-10 cm soil layer by 75 %, which was companied by a significant decrease in ARG mobility, and a significant increase in ARG diversity and microbial diversity. Phytostabilization was also found to drastically alter the ARG host composition and to significantly reduce the total abundance of virulence factor genes of ARG hosts. Soil nutrient status, heavy metal toxicity and SO₄^2- concentration were important physicochemical factors to affect the total ARG abundance, while causal mediation analysis showed that their effects were largely mediated by the changes in ARG mobility and microbial diversity. The increase in ARG diversity associated with phytostabilization was mainly mediated by a small subgroup of ARG hosts, most of which could not be classified at the genus level and deserve further research in the future.

OmicStudio: A composable bioinformatics cloud platform with real-time feedback that can generate high-quality graphs for publication

OmicStudio focuses on speed, quality together with flexibility. Generally, OmicStudio can not only meet the users' demand of ordinary bioinformatics data analysis, statistics, and visualization, but also provides them freedom of data mining beyond developer's framework. Additionally, unlimited to developer's aesthetics, users can get more elegant graphs through customizing. Available online https://www.omicstudio.cn.

Monsoon affects the distribution of antibiotic resistome in Tibetan glaciers

Antibiotic-resistance gene (ARG) is a biological pollutant and is globally distributed due to increased anthropogenic activities. ARGs in the cryosphere have received increased attention due to global warming, and ARGs in glaciers are predicted to be released into downstream ecosystems during glacier melting. In this study, ARG distribution and influential factors were investigated in 85 samples from 21 Tibetan glaciers, covering snow, ice, and cryoconite habitats. The results revealed ARGs against 29 antibiotics in Tibetan glaciers, dominated by tetracycline, bacitracin, macrolide, and fluoroquinolone resistance. ARGs in snow exhibited biogeographic patterns influenced by atmospheric circulation. Specifically, monsoon-dominated glaciers exhibited a significantly higher abundance of ARGs than the westerly-dominated glaciers, which could be associated with higher antibiotic usage in the Indian subcontinent. Of the 3241 metagenome-assembled genomes obtained, 36.8% of which were identified as ARG hosts and 33.8% were multidrug-resistant. In addition, 90 ARGs were linked to mobile genetic elements (MGEs). 90.9% and 9.1% of MGEs were identified as plasmid and phage in 45 MAGs carrying both ARGs and MGEs. Our study suggests a greater risk of ARGs being released from the monsoon-dominated glaciers, which were the glaciers that melt at high rates and thus need to be carefully monitored.

Pathogen-associated gene discovery workflows for novel antivirulence therapeutic development

Novel therapeutics to manage bacterial infections are urgently needed as the impact and prevalence of antimicrobial resistance (AMR) grows. Antivirulence therapeutics are an alternative approach to antibiotics that aim to attenuate virulence rather than target bacterial essential functions, while minimizing microbiota perturbation and the risk of AMR development. Beyond known virulence factors, pathogen-associated genes (PAGs; genes found only in pathogens to date) may play an important role in virulence or host association. Many identified PAGs encode uncharacterized hypothetical proteins and represent an untapped wealth of novel drug targets. Here, we review current advances in antivirulence drug research and development, including PAG identification, and provide a comprehensive workflow from the discovery of antivirulence drug targets to drug discovery. We highlight the importance of integrating bioinformatic/genomic-based methods for novel virulence factor discovery, coupled with experimental characterization, into existing drug screening platforms to develop novel and effective antivirulence drugs.

Gut microbiome function and composition in infants from rural Kenya and association with human milk oligosaccharides

The gut microbiota evolves rapidly after birth, responding dynamically to environmental factors and playing a key role in short- and long-term health. Lifestyle and rurality have been shown to contribute to differences in the gut microbiome, including Bifidobacterium levels, between infants. We studied the composition, function and variability of the gut microbiomes of 6- to 11-month-old Kenyan infants (n = 105). Shotgun metagenomics showed Bifidobacterium longum to be the dominant species. A pangenomic analysis of B. longum in gut metagenomes revealed a high prevalence of B. longum subsp. infantis (B. infantis) in Kenyan infants (80%), and possible co-existence of this subspecies with B. longum subsp. longum. Stratification of the gut microbiome into community (GMC) types revealed differences in composition and functional features. GMC types with a higher prevalence of B. infantis and abundance of B. breve also had a lower pH and a lower abundance of genes encoding pathogenic features. An analysis of human milk oligosaccharides (HMOs) classified the human milk (HM) samples into four groups defined on the basis of secretor and Lewis polymorphisms revealed a higher prevalence of HM group III (Se+, Le-) (22%) than in most previously studied populations, with an enrichment in 2'-fucosyllactose. Our results show that the gut microbiome of partially breastfed Kenyan infants over the age of six months is enriched in bacteria from the Bifidobacterium community, including B. infantis, and that the high prevalence of a specific HM group may indicate a specific HMO-gut microbiome association. This study sheds light on gut microbiome variation in an understudied population with limited exposure to modern microbiome-altering factors.

Comparative genomic analyses of the clinically-derived Winkia strain NY0527: the reassignment of W. neuii subsp. neuii and W. neuii subsp. antitratus into two separate species and insights into their virulence characteristics

Background

Winkia neuii, previously known as Actinomyces neuii, is increasingly recognized as a causative agent of various human infections, while its taxonomy and genomic insights are still understudied.

Methods

A Winkia strain NY0527 was isolated from the hip abscess of a patient, and its antibiotic susceptibility was assessed. The genome was hybrid assembled from long-reads and short-reads sequencing. Whole-genome-based analyses on taxa assignment, strain diversity, and pathogenesis were conducted.

Results

The strain was found to be highly susceptible to beta-lactam antibiotics, but resistant to erythromycin, clindamycin, and amikacin. The complete genome sequences of this strain were assembled and found to consist of a circular chromosome and a circular plasmid. Sequence alignment to the NCBI-nt database revealed that the plasmid had high sequence identity (>90%) to four Corynebacterium plasmids, with 40-50% query sequence coverage. Furthermore, the plasmid was discovered to possibly originate from the sequence recombination events of two Corynebacterium plasmid families. Phylogenomic tree and genomic average nucleotide identity analyses indicated that many Winkia sp. strains were still erroneously assigned as Actinomyces sp. strains, and the documented subspecies within W. neuii should be reclassified as two separate species (i.e., W. neuii and W. anitratus). The core genome of each species carried a chromosome-coded beta-lactamase expression repressor gene, which may account for their broadly observed susceptibility to beta-lactam antibiotics in clinical settings. Additionally, an ermX gene that expresses fluoroquinolone resistance was shared by some W. neuii and W. anitratus strains, possibly acquired by IS6 transposase-directed gene transfer events. In contrast, tetracycline resistance genes were exclusively carried by W. neuii strains. In particular, W. neuii was found to be more pathogenic than W. anitratus by encoding more virulence factors (i.e., 35-38 in W. neuii vs 27-31 in W. anitratus). Moreover, both species encoded two core pathogenic virulence factors, namely hemolysin and sialidase, which may facilitate their infections by expressing poreformation, adhesion, and immunoglobulin deglycosylation activities.

Conclusion

This study highlights the underappreciated taxonomic diversity of Winkia spp. and provides populational genomic insights into their antibiotic susceptibility and pathogenesis for the first time, which could be helpful in the clinical diagnosis and treatment of Winkia spp. infections.

MP4: a machine learning based classification tool for prediction and functional annotation of pathogenic proteins from metagenomic and genomic datasets

Bacteria can exceptionally evolve and develop pathogenic features making it crucial to determine novel pathogenic proteins for specific therapeutic interventions. Therefore, we have developed a machine-learning tool that predicts and functionally classifies pathogenic proteins into their respective pathogenic classes. Through construction of pathogenic proteins database and optimization of ML algorithms, Support Vector Machine was selected for the model construction. The developed SVM classifier yielded an accuracy of 81.72% on the blind-dataset and classified the proteins into three classes: Non-pathogenic proteins (Class-1), Antibiotic Resistance Proteins and Toxins (Class-2), and Secretory System Associated and capsular proteins (Class-3). The classifier provided an accuracy of 79% on real dataset-1, and 72% on real dataset-2. Based on the probability of prediction, users can estimate the pathogenicity and annotation of proteins under scrutiny. Tool will provide accurate prediction of pathogenic proteins in genomic and metagenomic datasets providing leads for experimental validations. Tool is available at: http://metagenomics.iiserb.ac.in/mp4 .

Mobilome-driven segregation of the resistome in biological wastewater treatment

Biological wastewater treatment plants (BWWTP) are considered to be hotspots for the evolution and subsequent spread of antimicrobial resistance (AMR). Mobile genetic elements (MGEs) promote the mobilization and dissemination of antimicrobial resistance genes (ARGs) and are thereby critical mediators of AMR within the BWWTP microbial community. At present, it is unclear whether specific AMR categories are differentially disseminated via bacteriophages (phages) or plasmids. To understand the segregation of AMR in relation to MGEs, we analyzed meta-omic (metagenomic, metatranscriptomic and metaproteomic) data systematically collected over 1.5 years from a BWWTP. Our results showed a core group of 15 AMR categories which were found across all timepoints. Some of these AMR categories were disseminated exclusively (bacitracin) or primarily (aminoglycoside, MLS and sulfonamide) via plasmids or phages (fosfomycin and peptide), whereas others were disseminated equally by both. Combined and timepoint-specific analyses of gene, transcript and protein abundances further demonstrated that aminoglycoside, bacitracin and sulfonamide resistance genes were expressed more by plasmids, in contrast to fosfomycin and peptide AMR expression by phages, thereby validating our genomic findings. In the analyzed communities, the dominant taxon Candidatus Microthrix parvicella was a major contributor to several AMR categories whereby its plasmids primarily mediated aminoglycoside resistance. Importantly, we also found AMR associated with ESKAPEE pathogens within the BWWTP, and here MGEs also contributed differentially to the dissemination of the corresponding ARGs. Collectively our findings pave the way toward understanding the segmentation of AMR within MGEs, thereby shedding new light on resistome populations and their mediators, essential elements that are of immediate relevance to human health.