Metagenomics-enabled microbial surveillance

Harmony in diversity: Reorganizing the families within the order Pseudomonadales

An accurate and coherent bacterial taxonomy is essential for studying the ecological aspects of microorganisms and for understanding microbial communities and their dynamics. The order Pseudomonadales is of particular importance in biological research due to its ability to interact with eukaryotic hosts, including taxa of clinical relevance (e.g.: Pseudomonas, Moraxella, Acinetobacter), or due to its functions in soil and water ecosystems. Despite their relevance, we have identified several inconsistencies in the organisation of genera within families in this order. Here, we perform comprehensive phylogenetic and phylogenomic analyses to reorganise these taxa. Average amino acid identity (AAI) values shared within and between families support our reclassifications. We propose seven new families, including new ecologically relevant families (e.g.: Oceanobacteraceae fam. nov.), as well as several taxonomic emendations. Our results also support the inclusion of Cellvibrionales and Oceanospirillales within Pseudomonadales. This revised organisation provides a robust delineation of these taxa into families, characterised by AAI values ranging from 60% to 77%. AAI distances between families are predominantly below 60%. This reclassification contributes to establishment of a more reliable taxonomic framework within Gammaproteobacteria, providing the basis for a more comprehensive understanding of their evolution.

Metaviromic and metagenomic study of the pathogens in unexplained pneumonia cases in goats

Goats are an economically important livestock species in China. However, the high mortality rate due to pneumonia represents a significant challenge to the development of intensive goat farms. 10 goat lung tissue samples were collected in this study, and all samples exhibited pneumonia of different severity as determined by lung lesion scoring and histopathological examination. Subsequently, this study employed qRT-PCR to measure the relative expression level of pro-inflammatory cytokines in lung tissue, and conducted metaviromic and metagenomic analyses to elucidate the structure and composition of the pulmonary microbiota, the correlation between the abundance of specific microbes and inflammatory factors, and between microbial abundance and the expression of virulence genes. Metaviromic results indicated that Ungulate tetraparvovirus 4 (83.3 %) had the highest relative abundance in the viral composition. Metagenomic data showed that Mycoplasma (28.2 %) and Streptococcus (24.8 %) are the primary dominant genus in goat pneumonia. Notably, a total of 8 pathogens associated with pneumonia in humans or animals were identified across all samples, including Mycoplasma ovipneumoniae, Streptococcus agalactiae, Streptococcus pneumoniae, Escherichia coli, Bordetella hinzii, Bibersteinia trehalosi, Bordetella pertussis, and Pasteurella multocida, with mixed infections with multiple pathogens are very common in this study. Correlation analysis indicates a significant association between the degree of pathogen co-infection and the severity of pulmonary lesions. Furthermore, Pasteurella multocida showed a significant positive correlation with the expression of IL-6 (P< 0.01). The pneumonia samples also revealed a multitude of virulence factors associated with bacterial pathogenicity including those related to biofilm formation, endotoxin production, bacterial invasion and evasion of host immunity. In conclusion, the present study can provide a reference for clinical pathogen diagnosis of unexplained pneumonia in goats.

The impact of anthropogenic activities on antimicrobial and heavy metal resistance in aquatic environments

This study investigated the prevalence and co-occurrence of antimicrobial (AMR) and metal resistance (MR) in aquatic environments with different human impacts. Metagenomes from pristine, rural and urban sites in Australia were analyzed with AMR ++ and customized binning pipelines. AMR was present in all environments, while MR was mainly in rural and urban samples. AMR gene diversity was higher in rural and urban sites, exhibiting resistance to more antibiotic classes (n = 10) than the pristine site (n = 4). Metal and multicompound resistance was more frequent in rural (14%) compared to urban samples (5%). Pristine samples lacked multidrug and multicompound resistance and had lower resistance to aminoglycosides and the MLS group. Multiresistance was evidenced by copper and aminocoumarin resistance in rural samples and aminoglycoside and mercury resistance in Pseudomonas in all environments. These findings highlight the impact of human activities on AMR and MR spread, emphasizing the need for environmental monitoring and management.

IMPORTANCE

Antimicrobial resistance (AMR) and metal resistance (MR) are critical global health concerns exacerbated by anthropogenic activities. The intricate mechanism underlying the interaction among anthropogenic activities, microbial communities, and resistance remains enigmatic. We developed novel bioinformatic pipelines to unveil this interaction in three aquatic environments. Our findings demonstrate the presence of specific bacterial communities that drive AMR and MR in rural and urban environments. This study underscores the significance of proper agricultural practices, comprehensive monitoring, and management strategies to reduce anthropogenic impacts on environmental resistance.

Harnessing methods, data analysis, and near-real-time wastewater monitoring for enhanced public health response using high throughput sequencing

Wastewater-based analysis has emerged as a pivotal method for monitoring SARS-CoV-2 (SC2). Leveraging high-throughput sequencing on wastewater samples facilitates a comprehensive, population-level assessment of circulating and emerging SC2 variants within a community. This study meticulously evaluates the detection performance, variant calling accuracy, and the time taken from sample collection to public data release for wastewater SC2 monitoring. Two different SC2 target enrichment panels were employed, Illumina MiSeq and Oxford Nanopore Technologies (ONT) GridION sequencing platforms for a robust analysis. Daily collection of routine raw grab and composite samples took place at a wastewater treatment plant (WWTP) site in Maryland, USA (MD) from mid-January 2022 to the end of June 2022. Total Nucleic Acid (TNA) was extracted from samples and target enrichment was executed using QIAseq DIRECT and NEBNext VarSkip Short amplicon kits, with subsequent sequencing on MiSeq or ONT GridION platforms, respectively. Obtained sequences was analyzed using custom CFSAN Wastewater Analysis Pipeline (C-WAP). Raw sequence data and detailed metadata were submitted to NCBI (BioProject PRJNA757291) as it became available. Wastewater data successfully detected the onset of new variants BA.2, BA.2.12, BA.4.6, and BA.5 to the observed population. Notably, Omicron sub-variants were identified approximately a week ahead of publicly available clinical data at the MD ZIP-code level. Variation in quality metrics paralleled the rise and fall of BA waves, underscoring the impact of viral load on sequencing quality. Regular updates of estimated variant proportions were made available on the FDA-CFSAN "Wastewater Surveillance for SARS-CoV-2 Variants" website. In contrast to the median 28-day turnaround, the lead time from sample collection to public release of raw sequence data via NCBI was remarkably swift, accomplished within a mere 57 h in this specific exercise. Processing, sequencing, and analysis methods empowered the swift and accurate detection of SC2 trends and circulating variants within a community, offering insights for public health decision-making.

Metagenomics studies in aquaculture systems: Big data analysis, bioinformatics, machine learning and quantum computing

The burgeoning field of aquaculture has become a pivotal contributor to global food security and economic growth, presently surpassing capture fisheries in aquatic animal production as evidenced by recent statistics. However, the dense fish populations inherent in aquaculture systems exacerbate abiotic stressors and promote pathogenic spread, posing a risk to sustainability and yield. This study delves into the transformative potential of metagenomics, a method that directly retrieves genetic material from environmental samples, in elucidating microbial dynamics within aquaculture ecosystems. Our findings affirm that metagenomics, bolstered by tools in big data analytics, bioinformatics, and machine learning, can significantly enhance the precision of microbial assessment and pathogen detection. Furthermore, we explore quantum computing's emergent role, which promises unparalleled efficiency in data processing and model construction, poised to address the limitations of conventional computational techniques. Distinct from metabarcoding, metagenomics offers an expansive, unbiased profile of microbial biodiversity, revolutionizing our capacity to monitor, predict, and manage aquaculture systems with high accuracy and adaptability. Despite the challenges of computational demands and variability in data standardization, this study advocates for continued technological integration, thereby fostering resilient and sustainable aquaculture practices in a climate of escalating global food requirements.

Exploring the Frontiers of Nanopore Sequencing in Food Safety and Food Microbiology

Foodborne illnesses are a significant global public health challenge, with an estimated 600 million cases annually. Conventional food microbiology methods tend to be laborious and time consuming, pose difficulties in real-time utilization, and can display subpar accuracy or typing capabilities. With the recent advancements in third-generation sequencing and microbial omics, nanopore sequencing technology and its long-read sequencing capabilities have emerged as a promising platform. In recent years, nanopore sequencing technology has been benchmarked for its amplicon sequencing, whole-genome and transcriptome analysis, meta-analysis, and other advanced omics approaches. This review comprehensively covers nanopore sequencing technology's current advances in food safety applications, including outbreak investigation, pathogen surveillance, and antimicrobial resistance profiling. Despite significant progress, ongoing research and development are crucial to overcoming challenges in sequencing chemistry, accuracy, bioinformatics, and real-time adaptive sampling to fully realize nanopore sequencing technology's potential in food safety and food microbiology.

Metagenomic Sequencing of Tomato Plants with Wilt Symptoms Allows for Strain-Level Pathogen Identification and Genome-Based Characterization

Diseases that affect the vascular system or the pith are of great economic impact because they can rapidly destroy the affected plants, leading to complete loss in production. Fast and precise identification is thus important to inform containment and management, but many identification methods are slow because they are culture-dependent and do not reach strain resolution. Here we used culture-independent long-read metagenomic sequencing of DNA extracted directly from the stems of two tomato samples that displayed wilt symptoms. We obtained enough sequencing reads to assemble high-quality metagenome-assembled genomes of Ralstonia solanacearum from one sample and of Pseudomonas corrugata from the other. The genome sequences allowed us to identify both pathogens to the strain level using the genomeRxiv platform, perform phylogenetic analyses, predict virulence genes, and infer antibiotic and copper resistance. In the case of R. solanacearum, it was straightforward to exclude the pathogen from being the Select Agent race 3 biovar 2. Using the Branchwater tool, it was also possible to determine the worldwide distribution of both pathogen strains based on public metagenomic sequences. The entire analysis could have been completed within 2 days, starting with sample acquisition. Steps necessary toward establishing metagenomic sequencing as a more routine approach in plant diseases clinics are discussed.

Anthropogenic activity and climate change exacerbate the spread of pathogenic bacteria in the environment

Climate change is profoundly affecting human health. Human pathogenic bacteria (HPB) infections mediated by the environment are considered a substantial cause of global health losses. However, the biogeography of HPB and their response to climate change remain largely unknown. Here, we constructed and analyzed a global atlas of potential HPB using 1,066,584 samples worldwide. HPB are widely present in the global environment, and their distribution follows a latitudinal diversity gradient. Climate and anthropogenic factors are identified as major drivers of the global distribution of HPB. Our predictions indicated that by the end of this century, the richness, abundance, and invasion risk of HPB will increase globally, with this upward trend becoming more pronounced as development sustainability declines. Therefore, the threat of environmentally mediated HPB infections to human health may be more severe in a world where anthropogenic activities are intensifying and the global climate is warming.

Hydrogel-Transformable Probiotic Powder for Targeted Eradication of Helicobacter pylori with Enhanced Gastric Mucosal Repair and Microbiota Preservation

Lactobacillus reuteri (L. reuteri) therapies represent a potentially effective approach to eradicating Helicobacter pylori (H. pylori). However, the difficulty in bacterial viability preservation and harsh gastric environment compromises the survival and on-target delivery of L. reuteri. This study presents a novel bacterium-mediated bacterial elimination strategy using an edible L. reuteri@HTP probiotic powder for targeted bacterial elimination. The probiotic powder is obtained by grinding a lyophilized hydrogel composed of L. reuteri, hyaluronic acid (HA), tannic acid (TA), and polyvinyl alcohol (PVA). Upon contact with water, the powder quickly transforms into a hydrogel, enhancing L. reuteri's survival in the harsh gastric environment and ensuring selective release at H. pylori-infected inflammatory sites. L. reuteri targets and reduces H. pylori colonization while secreting reuterin to eliminate the bacteria. Additionally, TA's antioxidant properties help alleviate inflammation, and HA supports gastric mucosal repair. L. reuteri@HTP powder preserves the integrity of the gut microbiota, facilitating the restoration of a healthy microbiome. In particular, the probiotic powder remains stable at room temperature for at least six months, providing a promising alternative to traditional antibiotics for H. pylori treatment. This strategy combines targeted eradication, mucosal healing, and microbiome restoration, offering a new approach to treating gastric infections.

Microplastic induces microbial nitrogen limitation further alters microbial nitrogentransformation: Insights from metagenomic analysis

Microplastic has a significant impact on soil microbial communities, which play crucial roles in soil nitrogen (N) cycles. However, there is a limited understanding of their influences on genes associated with the entire N cycling pathways. Through a 120-day soil incubation using conventional (PE and PET) and biodegradable microplastics (PLA and PBAT), coupled with 16S rRNA and metagenomic sequencing, we investigated the responses of N-cycling genes to microplastics in two contrasting soils (i.e. black soil and loess soil). We found that biodegradable microplastics strongly altered microbial N functional profiles, and enhanced the abundance of numerous key genes involved in N fixation, organic N mineralization, N reduction, and denitrification. Furthermore, biodegradable microplastics significantly decreased net N mineralization (Nm) compared to control and conventional microplastic treatments, suggesting microbial N immobilization outweighed N mineralization. Analysis of the function-taxon bipartite network showed that the Nm was well predicted for the abundances and diversity of bacteria within specific modules, with Nm decreasing, the abundances of specific taxa in a given network modules increasing. These results indicated that biodegradable microplastics act as a carbon source to select specific taxa involved in enhancing N bioavailability (e.g., N fixation and organic N mineralization) to meet microbial N demand, which in turn filtered the bacterial community (decreased diversity but increased abundances) and gradually formed specific function-taxon modules. Comparing the two soils, microbes in the less fertile alkaline loess soil were more sensitive to biodegradable microplastics than those in the nutrient-rich acid black soil. Our study indicated that increasing usage of biodegradable plastics in the future may lead to accelerated soil microbial N limitation and transformation.

Advanced genomic research in understanding fish-borne zoonotic parasitic infection

Fish-borne zoonotic parasites pose substantial risks to human health and global aquaculture, primarily through raw or undercooked fish consumption. The rapid expansion of aquaculture, increasing global fish trade, and rising human populations have amplified these concerns. Despite widespread awareness of meat-borne zoonoses, fish-borne parasitic infections remain underrecognized, especially in developed countries. Traditional morphological and molecular methods have provided critical foundations for studying these parasites, yet recent genomic advances have revolutionized our understanding of their genetic diversity, biology, and host-pathogen dynamics. This review underscores the significance of integrating genomic approaches with conventional methods to enhance disease surveillance, risk assessment, and control strategies. Harnessing genomic tools will enable the development of effective interventions to mitigate zoonotic parasite impacts, protect human health, and promote sustainable aquaculture. A comprehensive, genomics-driven approach is essential to overcoming the global challenges of fish-borne zoonotic infections.

Applying prospective tree-temporal scan statistics to genomic surveillance data to detect emerging SARS-CoV-2 variants and salmonellosis clusters in New York City

BACKGROUND

The detection of communicable disease clusters in genomic surveillance data typically involves the application of rule-based signaling criteria, which can be arbitrary. In contrast, scan statistics that are used for spatiotemporal cluster detection can flexibly scan in calendar time, and scan statistics that are used for pharmacovigilance can flexibly scan along hierarchical tree structures that are based on diagnosis codes.

METHODS

New York City (NYC) Health Department staff applied tree-temporal scan statistics prospectively to genomic surveillance data with a hierarchical nomenclature for COVID-19 and salmonellosis cases that were diagnosed among NYC residents. We searched weekly for recent case increases at any granularity, from large phylogenetic branches to small groups of indistinguishable isolates. Using free and open-source TreeScan software, we looked for emerging SARS-CoV-2 variants based on Pango lineages during August 2021-November 2023 and emerging clusters of Salmonella isolates based on allele codes during November 2022-November 2023.

RESULTS

The SARS-CoV-2 Omicron subvariant EG.5.1 first signaled as locally emerging on 22 June 2023, 7 weeks before the World Health Organization designated it as a variant of interest. During 1 year of salmonellosis analyses, TreeScan detected 15 credible clusters that were worth investigating for common exposures and two data-quality issues for correction.

CONCLUSION

A challenge was the maintenance of timely and specific lineage assignments, and a limitation was that genetic distances between tree nodes were not considered. By automatically sifting through genomic data and generating ranked shortlists of nodes with statistically unusual recent case increases, TreeScan assisted in detecting emerging variants and clusters of communicable diseases and in prioritizing them for investigation.

Air sampling accurately captures circulating zoonotic viral diversity emerging from poultry live-animal markets

Environmental surveillance has emerged as a pivotal strategy for early detection of pathogens that pose threats to humans (1) but has not been utilized for zoonotic agents. In Asia, live-bird markets (LBMs) are key human-animal interfaces for zoonotic virus transmission (2). Traditional sampling strategies are time-consuming, expensive, threaten animal welfare and have significant occupational biosafety risks. In this study, we assessed the performance of metagenomics on environmental samples (ES) compared to traditional poultry swabs for detecting avian viral pathogens in LBMs in Cambodia. ES, including air, cage swabs, and carcass wash water, were collected alongside throat and cloacal swabs from domestic chickens and ducks across twelve sampling visits in two LBMs over a 15-month period. Viral nucleic acids were extracted and sequenced using a capture probe-based metagenomics approach. Our results show that metagenomics on ES outperformed traditional poultry samples in detecting the highly pathogenic Influenza A/H5N1, including circulating clades 2.3.4.4b and 2.3.2.1c, which were found in the environment but missed by poultry swabs on multiple occasions. Environmental metagenomics was also highly sensitive in the detection of over 40 other viruses from key pathogen families such as Astroviridae, Coronaviridae, Picornaviridae, and Retroviridae. Viral contigs from ES showed high similarity to those from poultry swabs further highlighting the accuracy of this approach. Our findings highlight metagenomics on ES can precisely and effectively replicate metagenomic results from traditional surveillance samples, offering broader coverage and enhanced detection of avian pathogens. This robust approach could be pivotal for mitigating zoonotic spillover, controlling pathogen transmission at LBMs, and enhancing pandemic preparedness strategies.

Deciphering antibiotic resistance genes and plasmids in pathogenic bacteria from 166 hospital effluents in Shanghai, China

Although previous studies using phenotypic or metagenomic approaches have revealed the patterns of antibiotic resistance genes (ARGs) in hospital effluents in local regions, limited information is available regarding the antibiotic resistome and plasmidome in human pathogenic bacteria in hospital effluents of megacity in China. To address this knowledge gap, we analyzed effluent samples from 166 hospitals across 13 geographical districts in Shanghai, China, using both cultivation-based approaches and metagenomics. A total of 357 strains were isolated from these samples, with the predominant species being Escherichia coli (n = 61), Aeromonas hydrophila (n = 57), Klebsiella pneumoniae (n = 48), and Aeromonas caviae (n = 42). Those identified indicator bacteria were classified into biosafety level 1 (BSL-1, 60 %) and BSL-2 (40 %). We identified 1237 ARG subtypes across 22 types, predominantly including beta-lactam, tetracycline, multidrug, polymyxin, and aminoglycoside resistance genes, using culture-enriched phenotypic metagenomics. Mobile genetic elements such as plasmids, transposons (tnpA), integrons (intI1), and insertion sequences (IS91) were abundant. We recovered 135 plasmids classified into mobilizable (n = 94) and non-mobilizable (n = 41) types. Additionally, 80 metagenome-assembled genomes (MAGs) were reconstructed from the hospital effluents for the assessment of ARG transmission risks, including genes for last-line antibiotics such as blaNDM, blaKPC, blaimiH, and mcr. This study is the first to comprehensively characterize and assess the risk of antimicrobial resistance levels and plasmidome in the hospital effluents of China's megacity, providing city-wide surveillance data and evidence to inform public health interventions.

Antimicrobials from endophytes as novel therapeutics to counter drug-resistant pathogens

The rapid increase in antimicrobial resistance (AMR) projects a "global emergency" and necessitates a need to discover alternative resources for combating drug-resistant pathogens or "superbugs." One of the key themes in "One Health Concept" is based on the fact that the interconnected network of humans, the environment, and animal habitats majorly contribute to the rapid selection and spread of AMR. Moreover, the injudicious and overuse of antibiotics in healthcare, the environment, and associated disciplines, further aggravates the concern. The prevalence and persistence of AMR contribute to the global economic burden and are constantly witnessing an upsurge due to fewer therapeutic options, rising mortality statistics, and expensive healthcare. The present decade has witnessed the extensive exploration and utilization of bio-based resources in harnessing antibiotics of potential efficacies. The discovery and characterization of diverse chemical entities from endophytes as potent antimicrobials define an important yet less-explored area in natural product-mediated drug discovery. Endophytes-produced antimicrobials show potent efficacies in targeting microbial pathogens and synthetic biology (SB) mediated engineering of endophytes for yield enhancement, forms a prospective area of research. In keeping with the urgent requirements for new/novel antibiotics and growing concerns about pathogenic microbes and AMR, this paper comprehensively reviews emerging trends, prospects, and challenges of antimicrobials from endophytes and their effective production via SB. This literature review would serve as the platform for further exploration of novel bioactive entities from biological organisms as "novel therapeutics" to address AMR.

Clinical metagenomics: ethical issues

Metagenomics is increasingly used for diagnosis in hospital settings. It is useful particularly in cases of unknown aetiology, where novel or difficult-to-diagnose pathogens are suspected, and/or following unexplained disease outbreaks. In this paper, we present three use cases that draw on existing reports: one involving a patient in intensive care with encephalitis of unknown aetiology; a second case with likely infection with drug-resistant Klebsiella pneumoniae and an incidental finding of unknown relevance; and a third case situated in an unexplained outbreak of acute hepatitis in children, with severe outcomes due to co-infection. We examine each case in turn, highlighting ethical questions arising in relation to clinical issues including: disclosure to patients of untreatable disease, cost-effectiveness, the value of resistance testing, sensitivity and specificity, uncertain or unexpected findings, patient consent and data sharing. We conclude by proposing recommendations for further research and developing particular pieces of guidance to improve clinical uses of metagenomics for diagnosis.

Antibiotic Resistance Genes and Microbiota in Brassica oleracea var. acephala Cultivated in South Korea: Potential for Resistance Transmission

Antimicrobial resistance (AMR) poses a critical global public health challenge. This study investigates the microbiome of Brassica oleracea var. acephala (kale) to evaluate the role of food production systems, particularly plant-derived foods, in AMR dissemination. Using 16S rRNA gene sequencing and metagenomic shotgun sequencing, we analyzed microbial diversity and antimicrobial resistance genes (ARGs) in kale samples. Results showed significant regional differences in microbiota composition and ARG distribution, with traditional fertilizer use linked to higher ARG prevalence in coliform bacteria compared to farms using other fertilization methods. Additionally, we confirmed ARG transfer potential by Klebsiella pneumoniae within coliform populations. Storage conditions notably affected microbial dynamics, with higher temperatures promoting K. pneumoniae growth in washed samples. These findings revealed the importance of AMR research in plant-derived foods and highlight the need for improved agricultural practices to mitigate the risks associated with high ARG abundance in coliform bacteria.

Deciphering mixed infections by plant RNA virus and reconstructing complete genomes simultaneously present within-host

Local co-circulation of multiple phylogenetic lineages is particularly likely for rapidly evolving pathogens in the current context of globalisation. When different phylogenetic lineages co-occur in the same fields, they may be simultaneously present in the same host plant (i.e. mixed infection), with potentially important consequences for disease outcome. This is the case in Burkina Faso for the rice yellow mottle virus (RYMV), which is endemic to Africa and a major constraint on rice production. We aimed to decipher the distinct RYMV isolates that simultaneously infect a single rice plant and to sequence their genomes. To this end, we tested different sequencing strategies, and we finally combined direct cDNA ONT (Oxford Nanopore Technology) sequencing with the bioinformatics tool RVhaplo. This method was validated by the successful reconstruction of two viral genomes that were less than a hundred nucleotides apart (out of a genome of 4450nt length, i.e. 2-3%), and present in artificial mixes at a ratio of up to a 99/1. We then used this method to subsequently analyze mixed infections from field samples, revealing up to three RYMV isolates within one single rice plant sample from Burkina Faso. In most cases, the complete genome sequences were obtained, which is particularly important for a better estimation of viral diversity and the detection of recombination events. The method described thus allows to identify various haplotypes of RYMV simultaneously infecting a single rice plant, obtaining their full-length sequences, as well as a rough estimate of relative frequencies within the sample. It is efficient, cost-effective, as well as portable, so that it could further be implemented where RYMV is endemic. Prospects include unravelling mixed infections with other RNA viruses that threaten crop production worldwide.

Whole-genome sequencing and metagenomics reveal diversity and prevalence of Listeria spp. from soil in the Nantahala National Forest

Listeria spp. are widely distributed environmental bacteria associated with human foodborne illness. The ability to detect and characterize Listeria strains in the natural environment will contribute to improved understanding of transmission routes of contamination. The current standard for surveillance and outbreak source attribution is whole-genome sequencing (WGS) of Listeria monocytogenes clinical isolates. Recently, metagenomic sequencing has also been explored as a tool for the detection of Listeria spp. in environmental samples. This study evaluated soil samples from four locations across altitudes ranging from 1,500 to 4,500 ft in the Nantahala National Forest in North Carolina, USA. Forty-two Listeria isolates were cultured and sequenced, and 12 metagenomes of soil bacterial communities were generated. These isolates comprised 14 distinct strains from five species, including Listeria cossartiae subsp. cayugensis (n = 8; n represents the number of distinct strains), L. monocytogenes (n = 3), "Listeria swaminathanii" (Lsw) (n = 1), Listeria marthii (n = 1), and Listeria booriae (n = 1). Most strains (n = 13) were isolated from lower altitudes (1,500 or 2,500 ft), while the L. swaminathanii strain was isolated from both higher (4,500 ft) and lower (1,500 ft) altitudes. Metagenomic analysis of soil described a reduction in both bacterial community diversity and relative abundance of Listeria spp. as the altitude increased. Soil pH and cation exchange capacity were positively correlated (P < 0.05) with the abundance of Listeria spp. as detected by metagenomics. By integrating culture-independent metagenomics with culture-based WGS, this study advances current knowledge regarding distribution of Listeria spp. in the natural environment and suggests the potential for future use of culture-independent methods in tracking the transmission of foodborne pathogens.

IMPORTANCE

As a foodborne pathogen, Listeria continues to cause numerous illnesses in humans and animals. Studying the diversity and distribution of Listeria in soil is crucial for understanding potential sources of contamination and developing effective strategies to prevent foodborne outbreaks of listeriosis. Additionally, examining the ecological niches and survival mechanisms of Listeria in natural habitats provides insights into its persistence and adaptability, informing risk assessments and public health interventions. This research contributes to a broader understanding of microbial ecology and the factors influencing foodborne pathogen emergence, ultimately enhancing food safety and protecting public health. Moreover, using a metagenomic approach provides a detailed understanding of the soil microbial ecosystems, leading to more effective monitoring and control of foodborne pathogens. This study also highlights the potential for integrating metagenomics into routine surveillance systems for food safety in the near future.

High-throughput single-cell sequencing of activated sludge microbiome

Wastewater treatment plants (WWTPs) represent one of biotechnology's largest and most critical applications, playing a pivotal role in environmental protection and public health. In WWTPs, activated sludge (AS) plays a major role in removing contaminants and pathogens from wastewater. While metagenomics has advanced our understanding of microbial communities, it still faces challenges in revealing the genomic heterogeneity of cells, uncovering the microbial dark matter, and establishing precise links between genetic elements and their host cells as a bulk method. These issues could be largely resolved by single-cell sequencing, which can offer unprecedented resolution to show the unique genetic information. Here we show the high-throughput single-cell sequencing to the AS microbiome. The single-amplified genomes (SAGs) of 15,110 individual cells were clustered into 2,454 SAG bins. We find that 27.5% of the genomes in the AS microbial community represent potential novel species, highlighting the presence of microbial dark matter. Furthermore, we identified 1,137 antibiotic resistance genes (ARGs), 10,450 plasmid fragments, and 1,343 phage contigs, with shared plasmid and phage groups broadly distributed among hosts, indicating a high frequency of horizontal gene transfer (HGT) within the AS microbiome. Complementary analysis using 1,529 metagenome-assembled genomes from the AS samples allowed for the taxonomic classification of 98 SAG bins, which were previously unclassified. Our study establishes the feasibility of single-cell sequencing in characterizing the AS microbiome, providing novel insights into its ecological dynamics, and deepening our understanding of HGT processes, particularly those involving ARGs. Additionally, this valuable tool could monitor the distribution, spread, and pathogenic hosts of ARGs both within AS environments and between AS and other environments, which will ultimately contribute to developing a health risk evaluation system for diverse environments within a One Health framework.

The need for adaptability in detection, characterization, and attribution of biosecurity threats

Modern biotechnology necessitates robust biosecurity protocols to address the risk of engineered biological threats. Current efforts focus on screening DNA and rejecting the synthesis of dangerous elements but face technical and logistical barriers. Screening should integrate into a broader strategy that addresses threats at multiple stages of development and deployment. The success of this approach hinges upon reliable detection, characterization, and attribution of engineered DNA. Recent advances notably aid the potential to both develop threats and analyze them. However, further work is needed to translate developments into biosecurity applications. This work reviews cutting-edge methods for DNA analysis and recommends avenues to improve biosecurity in an adaptable manner.

Spatial and Temporal Dynamics of Chemical and Microbial Contamination in Nonurban Floodwaters

During major flood events, waterborne contaminants are relatively poorly characterized. This is due to logistical difficulties associated with obtaining water samples in potentially dangerous flood conditions. Herein, we report analyses of water samples from a large, flooded landscape in Victoria, Australia, during a major flood event. We collected 83 samples from seven rivers and 18 river locations as far apart as 520 km. The sampling campaign covered a 26-day window, with 3 samples taken weekly from each site. Floodwater samples were analyzed for 778 contaminants and 544 microbial species were identified using eDNA. Our study shows that 85 contaminants were detected in floodwaters. Fungicides, phthalates, plant macronutrients, metal(loid)s and PPCPs were better explained by land uses, whereas herbicides and insecticides were explained by a mixture of land use and water flow data. Potentially pathogenic orders with the highest detection rates were Enterobacterales (82.4%), Mycobacteriales (70.6%) and Legionellales (58.8%). Contaminants and microbial signatures responded to rainfall, water flow and water level, demonstrating increased and varied human and environmental risks of exposure during the sampling window. Our work underlines the importance of rigorous and timely monitoring and provides an evidence-base for decision making during increasingly frequent and intense climate driven flood events.

The application status of sequencing technology in global respiratory infectious disease diagnosis

Next-generation sequencing (NGS) has revolutionized clinical microbiology, particularly in diagnosing respiratory infectious diseases and conducting epidemiological investigations. This narrative review summarizes conventional methods for routine respiratory infection diagnosis, including culture, smear microscopy, immunological assays, image techniques as well as polymerase chain reaction(PCR). In contrast to conventional methods, there is a new detection technology, sequencing technology, and here we mainly focus on the next-generation sequencing NGS, especially metagenomic NGS(mNGS). NGS offers significant advantages over traditional methods. Firstly, mNGS eliminates assumptions about pathogens, leading to faster and more accurate results, thus reducing diagnostic time. Secondly, it allows unbiased identification of known and novel pathogens, offering broad-spectrum coverage. Thirdly, mNGS not only identifies pathogens but also characterizes microbiomes, analyzes human host responses, and detects resistance genes and virulence factors. It can complement targeted sequencing for bacterial and fungal classification. Unlike traditional methods affected by antibiotics, mNGS is less influenced due to the extended survival of pathogen DNA in plasma, broadening its applicability. However, barriers to full integration into clinical practice persist, primarily due to cost constraints and limitations in sensitivity and turnaround time. Despite these challenges, ongoing advancements aim to improve cost-effectiveness and efficiency, making NGS a cornerstone technology for global respiratory infection diagnosis.

Factors impacting target-enriched long-read sequencing of resistomes and mobilomes

We investigated the efficiency of target-enriched long-read sequencing (TELSeq) for detecting antimicrobial resistance genes (ARGs) and mobile genetic elements (MGEs) within complex matrices. We aimed to overcome limitations associated with traditional antimicrobial resistance (AMR) detection methods, including short-read shotgun metagenomics, which can lack sensitivity, specificity, and the ability to provide detailed genomic context. By combining biotinylated probe-based enrichment with long-read sequencing, we facilitated the amplification and sequencing of ARGs, eliminating the need for bioinformatic reconstruction. Our experimental design included replicates of human fecal microbiota transplant material, bovine feces, pristine prairie soil, and a mock human gut microbial community, allowing us to examine variables including genomic DNA input and probe set composition. Our findings demonstrated that TELSeq markedly improves the detection rates of ARGs and MGEs compared to traditional sequencing methods, underlining its potential for accurate AMR monitoring. A key insight from our research is the importance of incorporating mobilome profiles to better predict the transferability of ARGs within microbial communities, prompting a recommendation for the use of combined ARG-MGE probe sets for future studies. We also reveal limitations for ARG detection from low-input workflows, and describe the next steps for ongoing protocol refinement to minimize technical variability and expand utility in clinical and public health settings. This effort is part of our broader commitment to advancing methodologies that address the global challenge of AMR.

Exploring Microbial Dark Matter for the Discovery of Novel Natural Products: Characteristics, Abundance Challenges and Methods

The objective of this review is to investigate microbial dark matter (MDM) with a focus on its potential for discovering novel natural products (NPs). This first part will examine the characteristics and abundance of these previously unexplored microbial communities, as well as the challenges faced in identifying and harnessing their unique biochemical properties and novel methods in this field. MDMs are thought to hold great potential for the discovery of novel NPs, which could have significant applications in medicine, agriculture, and industry. In recent years, there has been a growing interest in exploring MDM to unlock its potential. In fact, developments in genome-sequencing technologies and sophisticated phylogenetic procedures and metagenomic techniques have contributed to drastically make important changes in our sights on the diversity of microbial life, including the very outline of the tree of life. This has led to the development of novel technologies and methodologies for studying these elusive microorganisms, such as single-cell genomics, metagenomics, and culturomics. These approaches enable researchers to isolate and analyze individual microbial cells, as well as entire communities, providing insights into their genetic and metabolic potential. By delving into the MDM, scientists hope to uncover new compounds and biotechnological advancements that could have far-reaching impacts on various fields.

Effects of storage period and season on the microecological characteristics of Jiangxiangxing high-temperature Daqu

Metagenomics, non-targeted metabolomics, and metaproteomics were employed to analyze the microecological succession of high-temperature Daqu during storage, elucidate the adaptation mechanism of the microbial community of Daqu to storage environments, and clarify the microecological characteristics of Daqu during different seasons. During storage, the relative abundances of Bacillus, Oceanobacillus, Staphylococcus, and Aspergillus in Daqu had significantly increased, while those of Kroppenstedtia, Saccharopolyspora, Thermoascus, and Thermomyces had significantly decreased. During the first 3 months of storage, compound metabolism of Daqu was primarily dominated by generation of small molecular substances and then shifted to metabolism of amino sugars. During the storage process, homogeneous selection (15.57 %) and homogeneous diffusion (14.86 %) of the microbial communities of Daqu were much larger than during the fermentation process, while the variable selection assembly (29.43 %) was smaller than during the fermentation process. Among the 2509 proteins identified in the four-season Daqu, bacterial protein expression was 1.46-fold greater than that of fungi. Seasonal factors influenced the function of Daqu by alterations to Bacillus subtilis, Oceanobacillus iheyensis, and Aspergillus nidulans and other microbial functions. Carbon and benzoic acid metabolism of Daqu was relatively increased during the spring, while metabolism of alkaloids and tyrosine was upregulated during the summer, amino acid synthesis and starch metabolism were enriched during the autumn, and peptidoglycan synthesis was relatively greater during the winter. Adjusting the moisture content of Daqu during the storage period was shown to reduce microecological differentiation caused by seasonal temperature variations.

Evidence of a highly divergent novel parvovirus in Australia's critically endangered western ground parrot/kyloring (Pezoporus flaviventris)

Detecting pathogens in endangered animal populations is vital for understanding and mitigating threats to their survival. The critically endangered western ground parrot (Pezoporus flaviventris, WGP), with a population as low as 150 individuals in Australia, faces an imminent risk of extinction. Despite this urgency, research on viral pathogens in this species remains limited. This study aimed to identify and characterise viruses present in faecal samples from seven individual WGP using a viral metagenomic approach. Analysis of the sequenced datasets revealed the presence of a novel virus belonging to the Parvoviridae family, named psittaciform chaphamaparvovirus 7 (PsChPV-7). The genome of PsChPV-7 contains typical structural and functional gene sequences found in Parvoviridae but is highly divergent, indicating its classification as a distinct species. Phylogenetic analysis placed PsChPV-7 within a unique sub-clade of the Chaphamaparvovirus genus, suggesting its evolutionary significance as an ancient lineage within this group. These findings may contribute to the development of strategic management and biosecurity plans aimed at conserving this endangered WGP.

New insights into the roles of fungi and bacteria in the development of medicinal plant

BACKGROUND

The interaction between microorganisms and medicinal plants is a popular topic. Previous studies consistently reported that microorganisms were mainly considered pathogens or contaminants. However, with the development of microbial detection technology, it has been demonstrated that fungi and bacteria affect beneficially the medicinal plant production chain.

AIM OF REVIEW

Microorganisms greatly affect medicinal plants, with microbial biosynthesis a high regarded topic in medicinal plant-microbial interactions. However, it lacks a systematic review discussing this relationship. Current microbial detection technologies also have certain advantages and disadvantages, it is essential to compare the characteristics of various technologies.

KEY SCIENTIFIC CONCEPTS OF REVIEW

This review first illustrates the role of fungi and bacteria in various medicinal plant production procedures, discusses the development of microbial detection and identification technologies in recent years, and concludes with microbial biosynthesis of natural products. The relationship between fungi, bacteria, and medicinal plants is discussed comprehensively. We also propose a future research model and direction for further studies.

Exploring the dichotomy: Shotgun metagenomics reveals diversity of beneficial and pathogenic protist community in arid wetlands of northeastern South Africa

Arid regions harbor seasonal and permanent wetlands, as biodiversity hotspots crucial for ecosystem services despite harsh conditions. These wetlands, typically dependent on episodic intense rainfall, are understudied compared to their humid counterparts. While the diversity of plants and animals in these wetlands is well-known, the microbial communities remain largely unexplored. To address this knowledge gap, we employed metagenome sequencing technologies to profile protist communities, including pathogenic protozoa, and their associated functional pathways, in sediment of permanent and seasonal arid freshwater wetlands across northern South Africa. Results revealed a core community of protists dominated by phylum Apicomplexa (66.73 %), Euglenazoa (19.03 %), Bacillariophyta (5.44 %), Metamonada (4.65 %), Cryptophyta (1.90 %), and Amoebazoa (1.21 %). Seasonal wetlands showed significantly higher protist diversity compared to permanent wetlands (Shannon index, p = 0.019; Chao1, p = 0.0095). A high abundance and diversity of human and zoonotic pathogenic protists (87.67 %) was observed, with lower levels of photoautotrophs (6.69 %) and limited diversity of phagotrophs (5.64 %). Key photoautotrophs identified included diatoms (Thalassiosiraceae and Phaeodactylaceae) and cryptophytes (genus Hemiselmis and Cryptophyta), with consumers/phagotrophs exhibited a correlation with the bacterial community abundance (r2 = 0.218, p < 0.001). Pathogenic protozoans identified, include malaria-causing Plasmodium, kinetoplastids (genus Besnoita, Theilleria, Neospora, Toxoplasma, Encephalitozoon, and Babesia) and waterborne protozoans of public health importance (such as Cryptosporidium parvum and Giardia lamblia). Furthermore, the enrichment of pathogenesis-associated pathways (amino acid biosynthesis, peptidoglycan maturation, heme biosynthesis and degradation, and the Calvin-Benson-Bassham cycle), along with virulence gene families identified, highlighted these wetlands as potential reservoirs for infectious diseases. Our results unveil a baseline protist taxonomic and functional composition within arid wetlands, including beneficial and pathogenic protozoa. The close proximity of these wetlands to human activity raises concern for local and transboundary spread of these pathogens. Thus, continued monitoring is vital for disease control and preserving these unique ecosystems.

VirID: Beyond Virus Discovery-An Integrated Platform for Comprehensive RNA Virus Characterization

RNA viruses exhibit vast phylogenetic diversity and can significantly impact public health and agriculture. However, current bioinformatics tools for viral discovery from metagenomic data frequently generate false positive virus results, overestimate viral diversity, and misclassify virus sequences. Additionally, current tools often fail to determine virus-host associations, which hampers investigation of the potential threat posed by a newly detected virus. To address these issues we developed VirID, a software tool specifically designed for the discovery and characterization of RNA viruses from metagenomic data. The basis of VirID is a comprehensive RNA-dependent RNA polymerase database to enhance a workflow that includes RNA virus discovery, phylogenetic analysis, and phylogeny-based virus characterization. Benchmark tests on a simulated data set demonstrated that VirID had high accuracy in profiling viruses and estimating viral richness. In evaluations with real-world samples, VirID was able to identify RNA viruses of all types, but also provided accurate estimations of viral genetic diversity and virus classification, as well as comprehensive insights into virus associations with humans, animals, and plants. VirID therefore offers a robust tool for virus discovery and serves as a valuable resource in basic virological studies, pathogen surveillance, and early warning systems for infectious disease outbreaks.

Towards integrated cross-sectoral surveillance of pathogens and antimicrobial resistance: Needs, approaches, and considerations for linking surveillance to action

Pathogenic and antimicrobial-resistant (AMR) microorganisms are continually transmitted between human, animal, and environmental reservoirs, contributing to the high burden of infectious disease and driving the growing global AMR crisis. The sheer diversity of pathogens, AMR mechanisms, and transmission pathways connecting these reservoirs create the need for comprehensive cross-sectoral surveillance to effectively monitor risks. Current approaches are often siloed by discipline and sector, focusing independently on parts of the whole. Here we advocate that integrated surveillance approaches, developed through transdisciplinary cross-sector collaboration, are key to addressing the dual crises of infectious diseases and AMR. We first review the areas of need, challenges, and benefits of cross-sectoral surveillance, then summarise and evaluate the major detection methods already available to achieve this (culture, quantitative PCR, and metagenomic sequencing). Finally, we outline how cross-sectoral surveillance initiatives can be fostered at multiple scales of action, and present key considerations for implementation and the development of effective systems to manage and integrate this information for the benefit of multiple sectors. While methods and technologies are increasingly available and affordable for comprehensive pathogen and AMR surveillance across different reservoirs, it is imperative that systems are strengthened to effectively manage and integrate this information.

Use of whole genome sequencing for surveillance and control of foodborne diseases: status quo and quo vadis

Improvements in sequencing quality, availability, speed and costs results in an increased presence of genomics in infectious disease applications. Nevertheless, there are still hurdles in regard to the optimal use of WGS for public health purposes. Here, we discuss the current state ("status quo") and future directions ("quo vadis") based on literature regarding the use of genomics in surveillance, hazard characterization and source attribution of foodborne pathogens. The future directions include the application of new techniques, such as machine learning and network approaches that may overcome the current shortcomings. These include the use of fixed genomic distances in cluster delineation, disentangling similarity or lack thereof in source attribution, and difficulties ascertaining function in hazard characterization. Although, the aforementioned methods can relatively easily be applied technically, an overarching challenge is the inference and biological/epidemiological interpretation of these large amounts of high-resolution data. Understanding the context in terms of bacterial isolate and host diversity allows to assess the level of representativeness in regard to sources and isolates in the dataset, which in turn defines the level of certainty associated with defining clusters, sources and risks. This also marks the importance of metadata (clinical, epidemiological, and biological) when using genomics for public health purposes.

A multicenter study on accuracy and reproducibility of nanopore sequencing-based genotyping of bacterial pathogens

Nanopore sequencing has shown the potential to democratize genomic pathogen surveillance due to its ease of use and low entry cost. However, recent genotyping studies showed discrepant results compared to gold-standard short-read sequencing. Furthermore, although essential for widespread application, the reproducibility of nanopore-only genotyping remains largely unresolved. In our multicenter performance study involving five laboratories, four public health-relevant bacterial species were sequenced with the latest R10.4.1 flow cells and V14 chemistry. Core genome MLST analysis of over 500 data sets revealed highly strain-specific typing errors in all species in each laboratory. Investigation of the methylation-related errors revealed consistent DNA motifs at error-prone sites across participants at read level. Depending on the frequency of incorrect target reads, this either leads to correct or incorrect typing, whereby only minimal frequency deviations can randomly determine the final result. PCR preamplification, recent basecalling model updates and an optimized polishing strategy notably diminished the non-reproducible typing. Our study highlights the potential for new errors to appear with each newly sequenced strain and lays the foundation for computational approaches to reduce such typing errors. In conclusion, our multicenter study shows the necessity for a new validation concept for nanopore sequencing-based, standardized bacterial typing, where single nucleotide accuracy is critical.

Detection and characterisation of a sixth Candida auris clade in Singapore: a genomic and phenotypic study

BACKGROUND

The emerging fungal pathogen Candida auris poses a serious threat to global public health due to its worldwide distribution, multidrug resistance, high transmissibility, propensity to cause outbreaks, and high mortality. We aimed to characterise three unusual C auris isolates detected in Singapore, and to determine whether they constitute a novel clade distinct from all previously known C auris clades (I-V).

METHODS

In this genotypic and phenotypic study, we characterised three C auris clinical isolates, which were cultured from epidemiologically unlinked inpatients at a large tertiary hospital in Singapore. The index isolate was detected in April, 2023. We performed whole-genome sequencing (WGS) and obtained hybrid assemblies of these C auris isolates. The complete genomes were compared with representative genomes of all known C auris clades. To provide a global context, 3651 international WGS data from the National Center for Biotechnology Information (NCBI) database were included in a high-resolution single nucleotide polymorphism (SNP) analysis. Antifungal susceptibility testing was done and antifungal resistance genes, mating-type locus, and chromosomal rearrangements were characterised from the WGS data of the three investigated isolates. We further implemented Bayesian logistic regression models to classify isolates into known clades and simulate the automatic detection of isolates belonging to novel clades as their WGS data became available.

FINDINGS

The three investigated isolates were separated by at least 37 000 SNPs (range 37 000-236 900) from all existing C auris clades. These isolates had opposite mating-type allele and different chromosomal rearrangements when compared with their closest clade IV relatives. The isolates were susceptible to all tested antifungals. Therefore, we propose that these isolates represent a new clade of C auris, clade VI. Furthermore, an independent WGS dataset from Bangladesh, accessed via the NCBI Sequence Read Archive, was found to belong to this new clade. As a proof-of-concept, our Bayesian logistic regression model was able to flag these outlier genomes as a potential new clade.

INTERPRETATION

The discovery of a new C auris clade in Singapore and Bangladesh in the Indomalayan zone, showing a close relationship to clade IV members most commonly found in South America, highlights the unknown genetic diversity and origin of C auris, particularly in under-resourced regions. Active surveillance in clinical settings, along with effective sequencing strategies and downstream analysis, will be essential in the identification of novel strains, tracking of transmission, and containment of adverse clinical effects of C auris infections.

FUNDING

Duke-NUS Academic Medical Center Nurturing Clinician Researcher Scheme, and the Genedant-GIS Innovation Program.

Massive expansion of the pig gut virome based on global metagenomic mining

The pig gut virome plays a vital role in the gut microbial ecosystem of pigs. However, a comprehensive understanding of their diversity and a reference database for the virome are currently lacking. To address this gap, we established a Pig Virome Database (PVD) that comprised of 5,566,804 viral contig sequences from 4650 publicly available gut metagenomic samples using a pipeline designated "metav". By clustering sequences, we identified 48,299 viral operational taxonomic units (vOTUs) genomes of at least medium quality, of which 92.83% of which were not found in existing major databases. The majority of vOTUs were identified as Caudoviricetes (72.21%). The PVD database contained a total of 2,362,631 protein-coding genes across the above medium-quality vOTUs genomes that can be used to explore the functional potential of the pig gut virome. These findings highlight the extensive diversity of viruses in the pig gut and provide a pivotal reference dataset for forthcoming research concerning the pig gut virome.

Nanopore R10.4 metagenomic detection of blaCTX-M/blaDHA antimicrobial resistance genes and their genetic environments in stool

The increasing prevalence of gut colonization with CTX-M extended-spectrum β-lactamase- and/or DHA plasmid-mediated AmpC-producing Escherichia coli is a concern. Here, we evaluate Nanopore-shotgun metagenomic sequencing (Nanopore-SMS) latest V14 chemistry to detect blaCTX-M and blaDHA genes from healthy stools. We test 25 paired samples characterized with culture-based methods (native and pre-enriched). Antimicrobial resistant genes (ARGs) are detected from reads and meta-assembled genomes (MAGs) to determine their associated genetic environments (AGEs). Sensitivity and specificity of native Nanopore-SMS are 61.1% and 100%, compared to 81.5% and 75% for pre-enriched Nanopore-SMS, respectively. Native Nanopore-SMS identifies only one sample with an AGE, whereas pre-enriched Nanopore-SMS recognizes 9/18 plasmids and 5/9 E. coli chromosomes. Pre-enriched Nanopore-SMS identifies more ARGs than native Nanopore-SMS (p < 0.001). Notably, blaCTX-Ms and blaDHAs AGEs (plasmid and chromosomes) are identified within 1 hour of sequencing. Furthermore, microbiota analyses show that pre-enriched Nanopore-SMS results in more E. coli classified reads (47% vs. 3.1%), higher differential abundance (5.69 log2 fold) and lower Shannon diversity index (p < 0.0001). Nanopore-SMS has the potential to be used for intestinal colonization screening. However, sample pre-enrichment is necessary to increase sensitivity. Further computational improvements are needed to reduce the turnaround time for clinical applications.

Metagenomic analysis of the bacterial microbiome, resistome and virulome distinguishes Portuguese Serra da Estrela PDO cheeses from similar non-PDO cheeses: An exploratory approach

This study aimed to evaluate the microbiome, resistome and virulome of two types of Portuguese cheese using high throughput sequencing (HTS). Culture-dependent chromogenic methods were also used for certain groups/microorganisms. Eight samples of raw ewe's milk cheese were obtained from four producers: two producers with cheeses with a PDO (Protected Designation of Origin) label and the other two producers with cheeses without a PDO label. Agar-based culture methods were used to quantify total mesophiles, Enterobacteriaceae, Escherichia coli, Staphylococcus, Enterococcus and lactic acid bacteria. The presence of Listeria monocytogenes and Salmonella was also investigated. The selected isolates were identified by 16S rRNA gene sequencing and evaluated to determine antibiotic resistance and the presence of virulence genes. The eight cheese samples analyzed broadly complied with EC regulations in terms of the microbiological safety criteria. The HTS results demonstrated that Leuconostoc mesenteroides, Lactococcus lactis, Lactobacillus plantarum, Lacticaseibacillus rhamnosus, Enterococcus durans and Lactobacillus coryniformis were the most prevalent bacterial species in cheeses. The composition of the bacterial community varied, not only between PDO and non-PDO cheeses, but also between producers, particularly between the two non-PDO cheeses. Alpha-diversity analyses showed that PDO cheeses had greater bacterial diversity than non-PDO cheeses, demonstrating that the diversity of spontaneously fermented foods is significantly higher in cheeses produced without the addition of food preservatives and dairy ferments. Despite complying with microbiological regulations, both PDO and non-PDO cheeses harbored potential virulence genes as well as antibiotic resistance genes. However, PDO cheeses exhibited fewer of these virulence and antibiotic resistance genes compared to non-PDO cheeses. Therefore, the combination of conventional microbiological methods and the metagenomic approach could contribute to improving the attribution of the PDO label to this type of cheese.

Exploring viral diversity and metagenomics in livestock: insights into disease emergence and spillover risks in cattle

Cattle have a significant impact on human societies in terms of both economics and health. Viral infections pose a relevant problem as they directly or indirectly disrupt the balance within cattle populations. This has negative consequences at the economic level for producers and territories, and also jeopardizes human health through the transmission of zoonotic diseases that can escalate into outbreaks or pandemics. To establish prevention strategies and control measures at various levels (animal, farm, region, or global), it is crucial to identify the viral agents present in animals. Various techniques, including virus isolation, serological tests, and molecular techniques like PCR, are typically employed for this purpose. However, these techniques have two major drawbacks: they are ineffective for non-culturable viruses, and they only detect a small fraction of the viruses present. In contrast, metagenomics offers a promising approach by providing a comprehensive and unbiased analysis for detecting all viruses in a given sample. It has the potential to identify rare or novel infectious agents promptly and establish a baseline of healthy animals. Nevertheless, the routine application of viral metagenomics for epidemiological surveillance and diagnostics faces challenges related to socioeconomic variables, such as resource availability and space dedicated to metagenomics, as well as the lack of standardized protocols and resulting heterogeneity in presenting results. This review aims to provide an overview of the current knowledge and prospects for using viral metagenomics to detect and identify viruses in cattle raised for livestock, while discussing the epidemiological and clinical implications.

Zoonotic infections by avian influenza virus: changing global epidemiology, investigation, and control

Avian influenza virus continues to pose zoonotic, epizootic, and pandemic threats worldwide, as exemplified by the 2020-23 epizootics of re-emerging H5 genotype avian influenza viruses among birds and mammals and the fatal jump to humans of emerging A(H3N8) in early 2023. Future influenza pandemic threats are driven by extensive mutations and reassortments of avian influenza viruses rooted in frequent interspecies transmission and genetic mixing and underscore the urgent need for more effective actions. We examine the changing global epidemiology of human infections caused by avian influenza viruses over the past decade, including dramatic increases in both the number of reported infections in humans and the spectrum of avian influenza virus subtypes that have jumped to humans. We also discuss the use of advanced surveillance, diagnostic technologies, and state-of-the-art analysis methods for tracking emerging avian influenza viruses. We outline an avian influenza virus-specific application of the One Health approach, integrating enhanced surveillance, tightened biosecurity, targeted vaccination, timely precautions, and timely clinical management, and fostering global collaboration to control the threats of avian influenza viruses.

Exploring the secrets of marine microorganisms: Unveiling secondary metabolites through metagenomics

Marine microorganisms are increasingly recognized as primary producers of marine secondary metabolites, drawing growing research interest. Many of these organisms are unculturable, posing challenges for study. Metagenomic techniques enable research on these unculturable microorganisms, identifying various biosynthetic gene clusters (BGCs) related to marine microbial secondary metabolites, thereby unveiling their secrets. This review comprehensively analyses metagenomic methods used in discovering marine microbial secondary metabolites, highlighting tools commonly employed in BGC identification, and discussing the potential and challenges in this field. It emphasizes the key role of metagenomics in unveiling secondary metabolites, particularly in marine sponges and tunicates. The review also explores current limitations in studying these metabolites through metagenomics, noting how long-read sequencing technologies and the evolution of computational biology tools offer more possibilities for BGC discovery. Furthermore, the development of synthetic biology allows experimental validation of computationally identified BGCs, showcasing the vast potential of metagenomics in mining marine microbial secondary metabolites.

Metagenomic next-generation sequencing of cerebrospinal fluid reveals etiological and microbiological features in patients with various central nervous system infections

The application of metagenomic next-generation sequencing (mNGS) in pathogens detection of cerebrospinal fluid (CSF) is limited because clinical, microbiological, and biological information are not well connected. We analyzed the 428 enrolled patients' clinical features, pathogens diagnostic efficiency of mNGS in CSF, microbial community structure and composition in CSF, and correlation of microbial and clinical biomarkers in CSF. General characteristics were unspecific but helpful in formulating a differential diagnosis. CSF mNGS has a higher detection rate (34.6%) compared to traditional methods (5.4%). mNGS detection rate was higher when the time from onset to CSF collection was ≤20 days, the CSF leukocytes count was >200 × 106/L, the CSF protein concentration was >1.3 g/L, or CSF glucose concentration was ≤2.5 mmol/L in non-postoperative bacterial CNS infections (CNSi). CSF was not strictly a sterile environment, and the potential pathogens may contribute to the dysbiosis of CSF microbiome. Furthermore, clinical biomarkers were significantly relevant to CNS pathogens. Clinical data are helpful in choosing a proper opportunity to obtain an accurate result of mNGS, and can speculate whether the mNGS results are correct or not. Our study is a pioneering study exploring the CSF microbiome in different CNSIs.

Precision arbovirus serology with a pan-arbovirus peptidome

Arthropod-borne viruses represent a crucial public health threat. Current arboviral serology assays are either labor intensive or incapable of distinguishing closely related viruses, and many zoonotic arboviruses that may transition to humans lack any serologic assays. In this study, we present a programmable phage display platform, ArboScan, that evaluates antibody binding to overlapping peptides that represent the proteomes of 691 human and zoonotic arboviruses. We confirm that ArboScan provides detailed antibody binding information from animal sera, human sera, and an arthropod blood meal. ArboScan identifies distinguishing features of antibody responses based on exposure history in a Colombian cohort of Zika patients. Finally, ArboScan details epitope level information that rapidly identifies candidate epitopes with potential protective significance. ArboScan thus represents a resource for characterizing human and animal arbovirus antibody responses at cohort scale.

Mibianto: ultra-efficient online microbiome analysis through k-mer based metagenomics

Quantifying microbiome species and composition from metagenomic assays is often challenging due to its time-consuming nature and computational complexity. In Bioinformatics, k-mer-based approaches were long established to expedite the analysis of large sequencing data and are now widely used to annotate metagenomic data. We make use of k-mer counting techniques for efficient and accurate compositional analysis of microbiota from whole metagenome sequencing. Mibianto solves this problem by operating directly on read files, without manual preprocessing or complete data exchange. It handles diverse sequencing platforms, including short single-end, paired-end, and long read technologies. Our sketch-based workflow significantly reduces the data volume transferred from the user to the server (up to 99.59% size reduction) to subsequently perform taxonomic profiling with enhanced efficiency and privacy. Mibianto offers functionality beyond k-mer quantification; it supports advanced community composition estimation, including diversity, ordination, and differential abundance analysis. Our tool aids in the standardization of computational workflows, thus supporting reproducibility of scientific sequencing studies. It is adaptable to small- and large-scale experimental designs and offers a user-friendly interface, thus making it an invaluable tool for both clinical and research-oriented metagenomic studies. Mibianto is freely available without the need for a login at: https://www.ccb.uni-saarland.de/mibianto.

Realising a global One Health disease surveillance approach: insights from wastewater and beyond

One Health is a recognition of the shared environment inhabited by humans, animals and plants, and the impact of their interactions on the health of all organisms. The COVID-19 pandemic highlighted the need for a framework of pathogen surveillance in a tractable One Health paradigm to allow timely detection and response to threats to human and animal health. We present case studies centered around the recent global approach to tackle antimicrobial resistance and the current interest in wastewater testing, with the concept of "one sample many analyses" to be further explored as the most appropriate means of initiating this endeavor.

A metagenomics-based workflow for the detection and genomic characterization of GBS in raw freshwater fish

The unexpected foodborne outbreak in Singapore in 2015 has accentuated Group B Streptococcus (GBS, Streptococcus agalactiae) sequence type 283 as an emerging foodborne pathogen transmitted via the consumption of contaminated raw freshwater fish. Isolation-based workflows utilizing conventional microbiological and whole-genome sequencing methods are commonly used to support biosurveillance efforts critical for the control management of this emerging foodborne pathogen. However, these isolation-based workflows tend to have relatively long turnaround times that hamper a timely response for implementing risk mitigation. To address this gap, we have developed a metagenomics-based workflow for the simultaneous detection and genomic characterization of GBS in raw freshwater fish. Notably, our validation results showed that this metagenomics-based workflow could achieve comparable accuracy and potentially better detection limits while halving the turnaround time (from 2 weeks to 5 days) relative to an isolation-based workflow. The metagenomics-based workflow was also successfully adapted for use on a portable long-read nanopore sequencer, demonstrating its potential applicability for real-time point-of-need testing. Using GBS in freshwater fish as an example, this work represents a proof-of-concept study that supports the feasibility and validity of metagenomics as a rapid and accurate test methodology for the detection and genomic characterization of foodborne pathogens in complex food matrices.

IMPORTANCE

The need for a rapid and accurate food microbiological testing method is apparent for a timely and effective foodborne outbreak response. This is particularly relevant for emerging foodborne pathogens such as Group B Streptococcus (GBS) whose associated food safety risk might be undercharacterized. By using GBS in raw freshwater fish as a case example, this study describes the development of a metagenomics-based workflow for rapid food microbiological safety testing and surveillance. This study can inform as a working model for various foodborne pathogens in other complex food matrices, paving the way for future methodological development of metagenomics for food microbiological safety testing.

Metagenomic comparison of gut communities between wild and captive Himalayan griffons

Introduction

Himalayan griffons (Gyps himalayensis), known as the scavenger of nature, are large scavenging raptors widely distributed on the Qinghai-Tibetan Plateau and play an important role in maintaining the balance of the plateau ecosystem. The gut microbiome is essential for host health, helping to maintain homeostasis, improving digestive efficiency, and promoting the development of the immune system. Changes in environment and diet can affect the composition and function of gut microbiota, ultimately impacting the host health and adaptation. Captive rearing is considered to be a way to protect Himalayan griffons and increase their population size. However, the effects of captivity on the structure and function of the gut microbial communities of Himalayan griffons are poorly understood. Still, availability of sequenced metagenomes and functional information for most griffons gut microbes remains limited.

Methods

In this study, metagenome sequencing was used to analyze the composition and functional structures of the gut microbiota of Himalayan griffons under wild and captive conditions.

Results

Our results showed no significant differences in the alpha diversity between the two groups, but significant differences in beta diversity. Taxonomic classification revealed that the most abundant phyla in the gut of Himalayan griffons were Fusobacteriota, Proteobacteria, Firmicutes_A, Bacteroidota, Firmicutes, Actinobacteriota, and Campylobacterota. At the functional level, a series of Kyoto Encyclopedia of Genes and Genome (KEGG) functional pathways, carbohydrate-active enzymes (CAZymes) categories, virulence factor genes (VFGs), and pathogen-host interactions (PHI) were annotated and compared between the two groups. In addition, we recovered nearly 130 metagenome-assembled genomes (MAGs).

Discussion

In summary, the present study provided a first inventory of the microbial genes and metagenome-assembled genomes related to the Himalayan griffons, marking a crucial first step toward a wider investigation of the scavengers microbiomes with the ultimate goal to contribute to the conservation and management strategies for this near threatened bird.

Magnetic Nanoagent Coated with an Activated Macrophage Membrane for Colorimetric Detection of Bacteria

The construction of cell mimics replicating the surface landscape and biological functions of the cell membrane offers promising prospects for biomedical research and applications. Inspired by the inherent recognition capability of immune cells toward pathogens, we have fabricated activated macrophage membrane-coated magnetic silicon nanoparticles (aM-MSNPs) in this work as an isolation and recognition tool for enhanced bacterial analysis. Specifically, the natural protein receptors on the activated macrophage membrane endow the MSNPs with a broad-spectrum binding capacity to different pathogen species. By further incorporation of a tyramide amplification strategy, direct naked-eye analysis of specific bacteria with a detection limit of 10 CFU/mL can be achieved. Moreover, application to the diagnosis of urinary tract infections has also been validated, and positive samples spiked with bacteria can be clearly distinguished with an accuracy of 100%. This work may enrich cell membrane-based architectures and provide an experimental paradigm for point-of-care testing (POCT) detection of bacteria.

Next-generation sequencing survey of acute febrile illness in Senegal (2020-2022)

Introduction

Acute febrile illnesses (AFI) in developing tropical and sub-tropical nations are challenging to diagnose due to the numerous causes and non-specific symptoms. The proliferation of rapid diagnostic testing and successful control campaigns against malaria have revealed that non-Plasmodium pathogens still contribute significantly to AFI burden. Thus, a more complete understanding of local trends and potential causes is important for selecting the correct treatment course, which in turn will reduce morbidity and mortality. Next-generation sequencing (NGS) in a laboratory setting can be used to identify known and novel pathogens in individuals with AFI.

Methods

In this study, plasma was collected from 228 febrile patients tested negative for malaria at clinics across Senegal from 2020-2022. Total nucleic acids were extracted and converted to metagenomic NGS libraries. To identify viral pathogens, especially those present at low concentration, an aliquot of each library was processed with a viral enrichment panel and sequenced. Corresponding metagenomic libraries were also sequenced to identify non-viral pathogens.

Results and Discussion

Sequencing reads for pathogens with a possible link to febrile illness were identified in 51/228 specimens, including (but not limited to): Borrelia crocidurae (N = 7), West Nile virus (N = 3), Rickettsia felis (N = 2), Bartonella quintana (N = 1), human herpesvirus 8 (N = 1), and Saffold virus (N = 1). Reads corresponding to Plasmodium falciparum were detected in 19 specimens, though their presence in the cohort was likely due to user error of rapid diagnostic testing or incorrect specimen segregation at the clinics. Mosquito-borne pathogens were typically detected just after the conclusion of the rainy season, while tick-borne pathogens were mostly detected before the rainy season. The three West Nile virus strains were phylogenetically characterized and shown to be related to both European and North American clades. Surveys such as this will increase the understanding of the potential causes of non-malarial AFI, which may help inform diagnostic and treatment options for clinicians who provide care to patients in Senegal.

A novel multifunctional SERS microfluidic sensor based on ZnO/Ag nanoflower arrays for label-free ultrasensitive detection of bacteria

This study proposes a microfluidic platform for rapid enrichment and ultrasensitive SERS detection of bacteria. The platform comprises ZnO nanoflower arrays decorated with silver nanoparticles to enhance the SERS sensitivity. The ZnO nanoflower array substrate with a 3D reticular columnar structure is prepared using the hydrothermal method. SEM analysis depicts the 3.05 μm gap distribution of the substrate array to intercept the most bacteria in the particle sizes range of 0.5 to 3 μm. Then, silver nanoparticles are deposited on the ZnO nano-array surface by liquid evaporation self-assembly. TEM and SEM analysis indicate nanosize of Ag particles, evenly distributed on the substrate, enhancing the SERS efficiency and improving sensing reproducibility. The probe molecules (R6G) are tested to demonstrate the high SERS activity of the proposed microfluidic sensor. Then, Escherichia coli, Staphylococcus aureus, Enterococcus faecalis, and Bacillus subtilis are selected, demonstrating the sensor's excellent bacterial capture and sensitive recognition capabilities, with a detection limit as low as 102 CFU mL-1. Additionally, the antibacterial properties of ZnO/Ag heterojunction nanostructures are studied, suggesting their ability to inactivate bacteria. Compared with the traditional Au-enhanced chip, the sensor preparation is easy, safe, reliable, and low-cost. Moreover, the ZnO nano-array exhibits a large specific surface area, high interception ability, stronger and uniform SERS performance, and effective and reliable detection of trace pathogens. This work provides potential future ZnO/Ag microfluidic SERS sensor applications for rapid, unlabeled, and trace pathogens detection in clinical and environmental applications, potentially achieving breakthroughs in early detection, prevention, and treatment.