Metagenomics-enabled microbial surveillance

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.

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.

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.

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.

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 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.

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.

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.

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.

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.

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.

Metagenomics for Pathogen Detection During a Mass Mortality Event in Songbirds

Mass mortality events in wildlife can be indications of an emerging infectious disease. During the spring and summer of 2021, hundreds of dead passerines were reported across the eastern US. Birds exhibited a range of clinical signs including swollen conjunctiva, ocular discharge, ataxia, and nystagmus. As part of the diagnostic investigation, high-throughput metagenomic next-generation sequencing was performed across three molecular laboratories on samples from affected birds. Many potentially pathogenic microbes were detected, with bacteria forming the largest proportion; however, no singular agent was consistently identified, with many of the detected microbes also found in unaffected (control) birds and thus considered to be subclinical infections. Congruent results across laboratories have helped drive further investigation into alternative causes, including environmental contaminants and nutritional deficiencies. This work highlights the utility of metagenomic approaches in investigations of emerging diseases and provides a framework for future wildlife mortality events.

MetagenomicKG: a knowledge graph for metagenomic applications

Motivation

The sheer volume and variety of genomic content within microbial communities makes metagenomics a field rich in biomedical knowledge. To traverse these complex communities and their vast unknowns, metagenomic studies often depend on distinct reference databases, such as the Genome Taxonomy Database (GTDB), the Kyoto Encyclopedia of Genes and Genomes (KEGG), and the Bacterial and Viral Bioinformatics Resource Center (BV-BRC), for various analytical purposes. These databases are crucial for genetic and functional annotation of microbial communities. Nevertheless, the inconsistent nomenclature or identifiers of these databases present challenges for effective integration, representation, and utilization. Knowledge graphs (KGs) offer an appropriate solution by organizing biological entities and their interrelations into a cohesive network. The graph structure not only facilitates the unveiling of hidden patterns but also enriches our biological understanding with deeper insights. Despite KGs having shown potential in various biomedical fields, their application in metagenomics remains underexplored.

Results

We present MetagenomicKG, a novel knowledge graph specifically tailored for metagenomic analysis. MetagenomicKG integrates taxonomic, functional, and pathogenesis-related information from widely used databases, and further links these with established biomedical knowledge graphs to expand biological connections. Through several use cases, we demonstrate its utility in enabling hypothesis generation regarding the relationships between microbes and diseases, generating sample-specific graph embeddings, and providing robust pathogen prediction.

Availability and Implementation

The source code and technical details for constructing the MetagenomicKG and reproducing all analyses are available at Github: https://github.com/KoslickiLab/MetagenomicKG. We also host a Neo4j instance: http://mkg.cse.psu.edu:7474 for accessing and querying this graph.

Strain-level characterization of foodborne pathogens without culture enrichment for outbreak investigation using shotgun metagenomics facilitated with nanopore adaptive sampling

Introduction

Shotgun metagenomics has previously proven effective in the investigation of foodborne outbreaks by providing rapid and comprehensive insights into the microbial contaminant. However, culture enrichment of the sample has remained a prerequisite, despite the potential impact on pathogen detection resulting from the growth competition. To circumvent the need for culture enrichment, we explored the use of adaptive sampling using various databases for a targeted nanopore sequencing, compared to shotgun metagenomics alone.

Methods

The adaptive sampling method was first tested on DNA of mashed potatoes mixed with DNA of a Staphylococcus aureus strain previously associated with a foodborne outbreak. The selective sequencing was used to either deplete the potato sequencing reads or enrich for the pathogen sequencing reads, and compared to a shotgun sequencing. Then, living S. aureus were spiked at 105 CFU into 25 g of mashed potatoes. Three DNA extraction kits were tested, in combination with enrichment using adaptive sampling, following whole genome amplification. After data analysis, the possibility to characterize the contaminant with the different sequencing and extraction methods, without culture enrichment, was assessed.

Results

Overall, the adaptive sampling outperformed the shotgun sequencing. While the use of a host removal DNA extraction kit and targeted sequencing using a database of foodborne pathogens allowed rapid detection of the pathogen, the most complete characterization was achieved when using solely a database of S. aureus combined with a conventional DNA extraction kit, enabling accurate placement of the strain on a phylogenetic tree alongside outbreak cases.

Discussion

This method shows great potential for strain-level analysis of foodborne outbreaks without the need for culture enrichment, thereby enabling faster investigations and facilitating precise pathogen characterization. The integration of adaptive sampling with metagenomics presents a valuable strategy for more efficient and targeted analysis of microbial communities in foodborne outbreaks, contributing to improved food safety and public health.

Occurrence, transmission and risks assessment of pathogens in aquatic environments accessible to humans

Pathogens are ubiquitously detected in various natural and engineered water systems, posing potential threats to public health. However, it remains unclear which human-accessible waters are hotspots for pathogens, how pathogens transmit to these waters, and what level of health risk associated with pathogens in these environments. This review collaboratively focuses and summarizes the contamination levels of pathogens on the 5 water systems accessible to humans (natural water, drinking water, recreational water, wastewater, and reclaimed water). Then, we showcase the pathways, influencing factors and simulation models of pathogens transmission and survival. Further, we compare the health risk levels of various pathogens through Quantitative Microbial Risk Assessment (QMRA), and assess the limitations of water-associated QMRA application. Pathogen levels in wastewater are consistently higher than in other water systems, with no significant variation for Cryptosporidium spp. among five water systems. Hydraulic conditions primarily govern the transmission of pathogens into human-accessible waters, while environmental factors such as temperature impact pathogens survival. The median and mean values of computed public health risk levels posed by pathogens consistently surpass safety thresholds, particularly in the context of recreational waters. Despite the highest pathogens levels found in wastewater, the calculated health risk is significantly lower than in other water systems. Except pathogens concentration, variables like the exposure mode, extent, and frequency are also crucial factors influencing the public health risk in water systems. This review shares valuable insights to the more accurate assessment and comprehensive management of public health risk in human-accessible water environments.

"Smart markets": harnessing the potential of new technologies for endemic and emerging infectious disease surveillance in traditional food markets

Emerging and endemic zoonotic diseases continue to threaten human and animal health, our social fabric, and the global economy. Zoonoses frequently emerge from congregate interfaces where multiple animal species and humans coexist, including farms and markets. Traditional food markets are widespread across the globe and create an interface where domestic and wild animals interact among themselves and with humans, increasing the risk of pathogen spillover. Despite decades of evidence linking markets to disease outbreaks across the world, there remains a striking lack of pathogen surveillance programs that can relay timely, cost-effective, and actionable information to decision-makers to protect human and animal health. However, the strategic incorporation of environmental surveillance systems in markets coupled with novel pathogen detection strategies can create an early warning system capable of alerting us to the risk of outbreaks before they happen. Here, we explore the concept of "smart" markets that utilize continuous surveillance systems to monitor the emergence of zoonotic pathogens with spillover potential.IMPORTANCEFast detection and rapid intervention are crucial to mitigate risks of pathogen emergence, spillover and spread-every second counts. However, comprehensive, active, longitudinal surveillance systems at high-risk interfaces that provide real-time data for action remain lacking. This paper proposes "smart market" systems harnessing cutting-edge tools and a range of sampling techniques, including wastewater and air collection, multiplex assays, and metagenomic sequencing. Coupled with robust response pathways, these systems could better enable Early Warning and bolster prevention efforts.

Viral Communities Contribute More to the Lysis of Antibiotic-Resistant Bacteria than the Transduction of Antibiotic Resistance Genes in Anaerobic Digestion Revealed by Metagenomics

Ecological role of the viral community on the fate of antibiotic resistance genes (ARGs) (reduction vs proliferation) remains unclear in anaerobic digestion (AD). Metagenomics revealed a dominance of Siphoviridae and Podoviridae among 13,895 identified viral operational taxonomic units (vOTUs) within AD, and only 21 of the vOTUs carried ARGs, which only accounted for 0.57 ± 0.43% of AD antibiotic resistome. Conversely, ARGs locating on plasmids and integrative and conjugative elements accounted for above 61.0%, indicating a substantial potential for conjugation in driving horizontal gene transfer of ARGs within AD. Virus-host prediction based on CRISPR spacer, tRNA, and homology matches indicated that most viruses (80.2%) could not infect across genera. Among 480 high-quality metagenome assembly genomes, 95 carried ARGs and were considered as putative antibiotic-resistant bacteria (pARB). Furthermore, lytic phages of 66 pARBs were identified and devoid of ARGs, and virus/host abundance ratios with an average value of 71.7 indicated extensive viral activity and lysis. The infectivity of lytic phage was also elucidated through laboratory experiments concerning changes of the phage-to-host ratio, pH, and temperature. Although metagenomic evidence for dissemination of ARGs by phage transduction was found, the higher proportion of lytic phages infecting pARBs suggested that the viral community played a greater role in reducing ARB numbers than spreading ARGs in AD.

Finding Candida auris in public metagenomic repositories

Candida auris is a newly emerged multidrug-resistant fungus capable of causing invasive infections with high mortality. Despite intense efforts to understand how this pathogen rapidly emerged and spread worldwide, its environmental reservoirs are poorly understood. Here, we present a collaborative effort between the U.S. Centers for Disease Control and Prevention, the National Center for Biotechnology Information, and GridRepublic (a volunteer computing platform) to identify C. auris sequences in publicly available metagenomic datasets. We developed the MetaNISH pipeline that uses SRPRISM to align sequences to a set of reference genomes and computes a score for each reference genome. We used MetaNISH to scan ~300,000 SRA metagenomic runs from 2010 onwards and identified five datasets containing C. auris reads. Finally, GridRepublic has implemented a prospective C. auris molecular monitoring system using MetaNISH and volunteer computing.

Microbiota Implications in Endocrine-Related Diseases: From Development to Novel Therapeutic Approaches

This comprehensive review article delves into the critical role of the human microbiota in the development and management of endocrine-related diseases. We explore the complex interactions between the microbiota and the endocrine system, emphasizing the implications of microbiota dysbiosis for the onset and progression of various endocrine disorders. The review aims to synthesize current knowledge, highlighting recent advancements and the potential of novel therapeutic approaches targeting microbiota-endocrine interactions. Key topics include the impact of microbiota on hormone regulation, its role in endocrine pathologies, and the promising avenues of microbiota modulation through diet, probiotics, prebiotics, and fecal microbiota transplantation. We underscore the importance of this research in advancing personalized medicine, offering insights for more tailored and effective treatments for endocrine-related diseases.

Effect of wastewater collection and concentration methods on assessment of viral diversity

Monitoring of potentially pathogenic human viruses in wastewater is of crucial importance to understand disease trends in communities, predict potential outbreaks, and boost preparedness and response by public health departments. High throughput metagenomic sequencing opens an opportunity to expand the capabilities of wastewater surveillance. However, there are major bottlenecks in the metagenomic enabled wastewater surveillance, including the complexities in selecting appropriate sampling and concentration/virus enrichment methods as well as in bioinformatic analysis of complex samples with low human virus concentrations. To evaluate the abilities of two commonly used sampling and concentration methods in virus identification, virus communities concentrated with Virus Adsorption-Elution (VIRADEL) and PolyEthylene Glycol (PEG) precipitation were compared for three interceptor sites. Results indicated that more viral reads were obtained by the VIRADEL concentration method, with 2.84 ± 0.57 % viral reads in the sample. For samples concentrated with PEG, the average proportion of viral reads in the sample was 0.63 ± 0.19 %. In all wastewater samples, bacteriophage affiliated with the families Siphoviridae, Myoviridae and Podoviridae were found to be the abundant populations. Comparison against a custom Swiss-Prot human virus database indicated that the relatively abundant human viruses (average proportions in human virus community greater than 1.00 %) in samples concentrated with the VIRADEL method were Orthopoxvirus, Rhadinovirus, Parapoxvirus, Varicellovirus, Hepatovirus, Simplexvirus, Molluscipoxvirus, Parechovirus, Lymphocryptovirus, and Spumavirus. In samples concentrated with the PEG method, fewer human viruses were found to be relatively abundant. These were Orthopoxvirus, Rhadinovirus, Varicellovirus, Simplexvirus, Molluscipoxvirus, Lymphocryptovirus, and Betacoronavirus. Contigs of Betacoronavirus, which contains severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2), were identified in VIRADEL and PEG samples. Our study demonstrates the feasibility of using metagenomics in wastewater surveillance as a first screening tool and the need for selecting the appropriate virus concentration methods and optimizing bioinformatic approaches in analyzing metagenomic data of wastewater samples.

Virome of Australia's most endangered parrot in captivity evidenced of harboring hitherto unknown viruses

IMPORTANCE

The impact of circulating viruses on the critically endangered, orange-bellied parrot (OBP) population can be devastating. The OBP already faces numerous threats to its survival in the wild, including habitat loss, predation, and small population impacts. Conservation of the wild OBP population is heavily reliant on supplementation using OBPs from a managed captive breeding program. These birds may act as a source for introduction of a novel disease agent to the wild population that may affect survival and reproduction. It is, therefore, essential to monitor and assess the health of OBPs and take appropriate measures to prevent and control the spread of viral infections. This requires knowledge of the existing virome to identify novel and emerging viruses and support development of appropriate measures to manage associated risk. By monitoring and protecting these animals from emerging viral diseases, we can help ensure their ongoing survival and preserve the biodiversity of our planet.

Metagenomics-Based Microbial Ecological Community Threshold and Indicators of Anthropogenic Disturbances in Estuarine Sediments

Assessing the impacts of cumulative anthropogenic disturbances on estuarine ecosystem health is challenging. Using spatially distributed sediments from the Pearl River Estuary (PRE) in southern China, which are significantly influenced by anthropogenic activities, we demonstrated that metagenomics-based surveillance of benthic microbial communities is a robust approach to assess anthropogenic impacts on estuarine benthic ecosystems. Correlational and threshold analyses between microbial compositions and environmental conditions indicated that anthropogenic disturbances in the PRE sediments drove the taxonomic and functional variations in the benthic microbial communities. An ecological community threshold of anthropogenic disturbances was identified, which delineated the PRE sediments into two groups (H and L) with distinct taxa and functional traits. Group H, located nearshore and subjected to a higher level of anthropogenic disturbances, was enriched with pollutant degraders, putative human pathogens, fecal pollution indicators, and functional traits related to stress tolerance. In contrast, Group L, located offshore and subjected to a lower level of anthropogenic disturbances, was enriched with halotolerant and oligotrophic taxa and functional traits related to growth and resource acquisition. The machine learning random forest model identified a number of taxonomic and functional indicators that could differentiate PRE sediments between Groups H and L. The identified ecological community threshold and microbial indicators highlight the utility of metagenomics-based microbial surveillance in assessing the adverse impacts of anthropogenic disturbances in estuarine sediments, which can assist environmental management to better protect ecosystem health.

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.

Augmented surveillance of antimicrobial resistance with high-throughput robotics detects transnational flow of fluoroquinolone-resistant Escherichia coli strain into poultry

BACKGROUND

Food animal AMR surveillance programs assess only small numbers of Escherichia coli (from 100 to 600 per animal class) nationally each year, severely limiting the evaluation of public health risk(s). Here we demonstrate an affordable approach for early detection of emerging resistance on a broad scale that can also accurately characterize spatial and temporal changes in resistance.

METHODS

Caecal samples (n = 295) obtained from 10 meat poultry were screened using high-throughput robotics. Initial screening via agar dilution (5310 plates) quantified AMR carriage (cfu/g) for each sample. Ciprofloxacin-resistant isolates (n = 91) proceeded to downstream broth microdilution susceptibility testing. A subset of 28 ciprofloxacin-resistant isolates underwent WGS and phylogenetic analysis.

RESULTS

Intra- and inter-flock carriage of resistance varied with drug class. Ampicillin and tetracycline resistance was ubiquitous to most birds in all flocks with an average carriage rate of 5.8 log10 cfu/g. Gentamicin and ciprofloxacin-resistant E. coli colonized fewer birds, and had an average carriage rate of 1.2 log10 cfu/g and 1.0 log10 cfu/g of faeces, respectively. Resistance to extended-spectrum cephalosporins was absent. ST354 was the dominant ST among the WGS isolates, but they demonstrated markedly lower resistance gene carriage than their international counterparts.

CONCLUSIONS

These data amply demonstrate the ineffectiveness of commonly relied-on approaches to AMR surveillance for achieving early detection of emergence, or for measuring spatial and temporal resistance trends. Genetic analysis suggested there has been transnational flow of a ciprofloxacin-resistant strain into Australian poultry flocks, explaining their detection in a nation that prohibits fluoroquinolone use in poultry.

Gut microbiota research nexus: One Health relationship between human, animal, and environmental resistomes

The emergence and rapid spread of antimicrobial resistance is of global public health concern. The gut microbiota harboring diverse commensal and opportunistic bacteria that can acquire resistance via horizontal and vertical gene transfers is considered an important reservoir and sink of antibiotic resistance genes (ARGs). In this review, we describe the reservoirs of gut ARGs and their dynamics in both animals and humans, use the One Health perspective to track the transmission of ARG-containing bacteria between humans, animals, and the environment, and assess the impact of antimicrobial resistance on human health and socioeconomic development. The gut resistome can evolve in an environment subject to various selective pressures, including antibiotic administration and environmental and lifestyle factors (e.g., diet, age, gender, and living conditions), and interventions through probiotics. Strategies to reduce the abundance of clinically relevant antibiotic-resistant bacteria and their resistance determinants in various environmental niches are needed to ensure the mitigation of acquired antibiotic resistance. With the help of effective measures taken at the national, local, personal, and intestinal management, it will also result in preventing or minimizing the spread of infectious diseases. This review aims to improve our understanding of the correlations between intestinal microbiota and antimicrobial resistance and provide a basis for the development of management strategies to mitigate the antimicrobial resistance crisis.

Lessons identified for a future pandemic

Pandemics are complex events requiring a coordinated, global response. The response to the pandemic exposed vulnerabilities in system preparedness. Lessons arising from the COVID-19 pandemic are characterized by four broad themes: (i) investment in public health and health infrastructure, (ii) countermeasures (medical and non-medical), (iii) risk communication and public health measures and (iv) investment in people and partnerships. Learning from the COVID-19 pandemic identifies an approach that focusses on capacities and capabilities that are pathogen agnostic, ensuring that we can respond to diverse emerging infectious disease threats will be essential. The lessons learned from previous and ongoing infectious disease outbreaks should be kept under constant review, in line with technological and scientific advances, to improve our ability to detect, mitigate and respond to new and emerging threats.

A comprehensive review of microbial contamination in the indoor environment: sources, sampling, health risks, and mitigation strategies

The quality of the indoor environment significantly impacts human health and productivity, especially given the amount of time individuals spend indoors globally. While chemical pollutants have been a focus of indoor air quality research, microbial contaminants also have a significant bearing on indoor air quality. This review provides a comprehensive overview of microbial contamination in built environments, covering sources, sampling strategies, and analysis methods. Microbial contamination has various origins, including human occupants, pets, and the outdoor environment. Sampling strategies for indoor microbial contamination include air, surface, and dust sampling, and various analysis methods are used to assess microbial diversity and complexity in indoor environments. The review also discusses the health risks associated with microbial contaminants, including bacteria, fungi, and viruses, and their products in indoor air, highlighting the need for evidence-based studies that can relate to specific health conditions. The importance of indoor air quality is emphasized from the perspective of the COVID-19 pandemic. A section of the review highlights the knowledge gap related to microbiological burden in indoor environments in developing countries, using India as a representative example. Finally, potential mitigation strategies to improve microbiological indoor air quality are briefly reviewed.

Modelling the effectiveness of surveillance based on metagenomics in detecting, monitoring, and forecasting antimicrobial resistance in livestock production under economic constraints

Current surveillance of antimicrobial resistance (AMR) is mostly based on testing indicator bacteria using minimum inhibitory concentration (MIC) panels. Metagenomics has the potential to identify all known antimicrobial resistant genes (ARGs) in complex samples and thereby detect changes in the occurrence earlier. Here, we simulate the results of an AMR surveillance program based on metagenomics in the Danish pig population. We modelled both an increase in the occurrence of ARGs and an introduction of a new ARG in a few farms and the subsequent spread to the entire population. To make the simulation realistic, the total cost of the surveillance was constrained, and the sampling schedule was set at one pool per month with 5, 20, 50, or 100 samples. Our simulations demonstrate that a pool of 20-50 samples and a sequencing depth of 250 million fragments resulted in the shortest time to detection in both scenarios, with a time delay to detection of change of [Formula: see text]15 months in all scenarios. Compared with culture-based surveillance, our simulation indicates that there are neither significant reductions nor increases in time to detect a change using metagenomics. The benefit of metagenomics is that it is possible to monitor all known resistance in one sampling and laboratory procedure in contrast to the current monitoring that is based on the phenotypic characterisation of selected indicator bacterial species. Therefore, overall changes in AMR in a population will be detected earlier using metagenomics due to the fact that the resistance gene does not have to be transferred to and expressed by an indicator bacteria before it is possible to detect.

Application of high-throughput sequencing technologies and analytical tools for pathogen detection in urban water systems: Progress and future perspectives

The ubiquitous presence of pathogenic microorganisms, such as viruses, bacteria, fungi, and protozoa, in urban water systems poses a significant risk to public health. The emergence of infectious waterborne diseases mediated by urban water systems has become one of the leading global causes of mortality. However, the detection and monitoring of these pathogenic microorganisms have been limited by the complexity and diversity in the environmental samples. Conventional methods were restricted by long assay time, high benchmarks of identification, and narrow application sceneries. Novel technologies, such as high-throughput sequencing technologies, enable potentially full-spectrum detection of trace pathogenic microorganisms in complex environmental matrices. This review discusses the current state of high-throughput sequencing technologies for identifying pathogenic microorganisms in urban water systems with a concise summary. Furthermore, future perspectives in pathogen research emphasize the need for detection methods with high accuracy and sensitivity, the establishment of precise detection standards and procedures, and the significance of bioinformatics software and platforms. We have compiled a list of pathogens analysis software/platforms/databases that boast robust engines and high accuracy for preference. We highlight the significance of analyses by combining targeted and non-targeted sequencing technologies, short and long reads technologies, sequencing technologies, and bioinformatic tools in pursuing upgraded biosafety in urban water systems.

Exploring clonality and virulence gene associations in bloodstream infections using whole-genome sequencing and clinical data

Background

Bloodstream infections (BSIs) remain a significant cause of mortality worldwide. Causative pathogens are routinely identified and susceptibility tested but only very rarely investigated for their resistance genes, virulence factors, and clonality. Our aim was to gain insight into the clonality patterns of different species causing BSI and the clinical relevance of distinct virulence genes.

Methods

For this study, we whole-genome-sequenced over 400 randomly selected important pathogens isolated from blood cultures in our diagnostic department between 2016 and 2021. Genomic data on virulence factors, resistance genes, and clonality were cross-linked with in-vitro data and demographic and clinical information.

Results

The investigation yielded extensive and informative data on the distribution of genes implicated in BSI as well as on the clonality of isolates across various species.

Conclusion

Associations between survival outcomes and the presence of specific genes must be interpreted with caution, and conducting replication studies with larger sample sizes for each species appears mandatory. Likewise, a deeper knowledge of virulence and host factors will aid in the interpretation of results and might lead to more targeted therapeutic and preventive measures. Monitoring transmission dynamics more efficiently holds promise to serve as a valuable tool in preventing in particular BSI caused by nosocomial pathogens.

Development of a portable on-site applicable metagenomic data generation workflow for enhanced pathogen and antimicrobial resistance surveillance

Rapid, accurate and comprehensive diagnostics are essential for outbreak prevention and pathogen surveillance. Real-time, on-site metagenomics on miniaturized devices, such as Oxford Nanopore Technologies MinION sequencing, could provide a promising approach. However, current sample preparation protocols often require substantial equipment and dedicated laboratories, limiting their use. In this study, we developed a rapid on-site applicable DNA extraction and library preparation approach for nanopore sequencing, using portable devices. The optimized method consists of a portable mechanical lysis approach followed by magnetic bead-based DNA purification and automated sequencing library preparation, and resulted in a throughput comparable to a current optimal, laboratory-based protocol using enzymatic digestion to lyse cells. By using spike-in reference communities, we compared the on-site method with other workflows, and demonstrated reliable taxonomic profiling, despite method-specific biases. We also demonstrated the added value of long-read sequencing by recovering reads containing full-length antimicrobial resistance genes, and attributing them to a host species based on the additional genomic information they contain. Our method may provide a rapid, widely-applicable approach for microbial detection and surveillance in a variety of on-site settings.

The neglected continuously emerging Marburg virus disease in Africa: A global public health threat

Background and Aim

Severe viral hemorrhagic fever (VHF) is caused by Marburg virus which is a member of the Filoviridae (filovirus) family. Many Marburg virus disease (MVD) outbreaks are reported in five decades. A major notable outbreak with substantial reported cases of infections and deaths was in 2022 in Uganda. The World Health Organisation (WHO) reported MVD outbreak in Ghana in July 2022 following the detection of two probable VHF patients there. Further, the virus was reported from two other African countries, the Equatorial Guinea (February 2023) and Tanzania (March 2023). There have been 35 deaths out of 40 reported cases in Equatorial Guinea, and six of the nine confirmed cases in Tanzania so far.

Methods

Data particularly on the several MVD outbreaks as reported from the African countries were searched on various databases including the Pubmed, Scopus, and Web-of-science. Also, the primary data and reports from health agencies like the WHO and the Centers for Disease Control and Prevention CDC) were evaluated and the efficacy reviewed.

Results

Chiroptera in general and bat species like Rousettus aegyptiacus and Hipposideros caffer in particular are natural reservoirs of the Marburg virus. MVD-infected nonhuman primate African fruit-bat and the MVD-infected humans pose significant risk in human infections. Cross-border viral transmission and its potential further international ramification concerns raise the risk of its rapid spread and a potential outbreak. Occurrence of MVD is becoming more frequent in Africa with higher case fatality rates. Effective prophylactic and therapeutic interventions to counter this deadly virus are suggested.

Conclusion

In the face of the lack of effective therapeutics and preventives against MVD, supportive care is the only available option which contributes to the growing concern and disease severity. In view of the preventive approaches involving effective surveillance and monitoring system following the "One Health" model is extremely beneficial to ensure a healthy world for all, this article aims at emphasizing several MVD outbreaks, epidemiology, zoonosis of the virus, current treatment strategies, risk assessments, and the mitigation strategies against MVD.

Zoonotic mosquito-borne arboviruses: Spillover, spillback, and realistic mitigation strategies

Emerging zoonotic mosquito-borne viruses pose increasing health threats because of growing mosquito population, geographic expansions, and control challenges. We emphasize the need for global preparedness to effectively mitigate the health, societal, and economic impacts of spillover by these viruses through proactive measures of prediction, surveillance, prevention, and treatment.

CPGminer: An Interactive Dashboard to Explore the Genomic Features and Taxonomy of Complete Prokaryotic Genomes

Prokaryotes, the earliest forms of life on Earth, play crucial roles in global biogeochemical processes in virtually all ecosystems. The ever-increasing amount of prokaryotic genome sequencing data provides a wealth of information to examine fundamental and applied questions through systematic genome comparison. Genomic features, such as genome size and GC content, and taxonomy-centric genomic features of complete prokaryotic genomes (CPGs) are crucial for various fields of microbial research and education, yet they are often overlooked. Additionally, creating systematically curated datasets that align with research concerns is an essential yet challenging task for wet-lab researchers. In this study, we introduce CPGminer, a user-friendly tool that allows researchers to quickly and easily examine the genomic features and taxonomy of CPGs and curate genome datasets. We also provide several examples to demonstrate its practical utility in addressing descriptive questions.

Application of metagenomics for diagnosis of broilers displaying neurological symptoms

BACKGROUND

Thirty-two-day-old broiler chickens at a farm located in northwestern South Korea displayed adverse neurological symptoms including limping, lying down, and head shaking. Approximately 2.1% of chickens died or were culled due to severe symptoms. Five carcasses were submitted to the Avian Disease Division of the Animal and Plant Quarantine Agency (APQA) for disease diagnosis.

RESULTS

Broilers displayed severe pericarditis and perihepatitis associated with gross lesions. Broilers also displayed microscopic lesions in the cerebrum and in the granular layer of the cerebellum, which were associated with multifocal perivascular cuffing and purulent necrosis in the cerebrum, and severe meningitis with heterophil and lymphocyte infiltration. Staphylococcus spp. were identified in the liver and heart using bacteriological culture. PCR/RT-PCR assays revealed that broilers were negative for avian Clostridium botulinum, Newcastle disease virus, and avian encephalomyelitis virus. Bacterial and viral metagenomic analysis of brain sample further revealed the presence of Pseudomonas spp. and Marek's disease virus, which are known etiological agents of chicken meningoencephalitis.

CONCLUSIONS

This study reports a diagnostic analysis of gross and histopathological lesions from 32-day-old broilers displaying unique neurological symptoms that revealed the presence of the several neurological diseases including meningoencephalitis. The causative agents associated with meningoencephalitis of broilers that had not been identified by routine diagnostic methods could be diagnosed by metagenomics, which proves the usefulness of metagenomics as a diagnostic tool for unknown neurological diseases in broilers.

Surface-modified bacteria: synthesis, functionalization and biomedical applications

The past decade has witnessed a great leap forward in bacteria-based living agents, including imageable probes, diagnostic reagents, and therapeutics, by virtue of their unique characteristics, such as genetic manipulation, rapid proliferation, colonization capability, and disease site targeting specificity. However, successful translation of bacterial bioagents to clinical applications remains challenging, due largely to their inherent susceptibility to environmental insults, unavoidable toxic side effects, and limited accumulation at the sites of interest. Cell surface components, which play critical roles in shaping bacterial behaviors, provide an opportunity to chemically modify bacteria and introduce different exogenous functions that are naturally unachievable. With the help of surface modification, a wide range of functionalized bacteria have been prepared over the past years and exhibit great potential in various biomedical applications. In this article, we mainly review the synthesis, functionalization, and biomedical applications of surface-modified bacteria. We first introduce the approaches of chemical modification based on the bacterial surface structure and then highlight several advanced functions achieved by modifying specific components on the surface. We also summarize the advantages as well as limitations of surface chemically modified bacteria in the applications of bioimaging, diagnosis, and therapy and further discuss the current challenges and possible solutions in the future. This work will inspire innovative design thinking for the development of chemical strategies for preparing next-generation biomedical bacterial agents.

Perspective on the development of synthetic microbial community (SynCom) biosensors

Synthetic microbial community (SynCom) biosensors are a promising technology for detecting and responding to environmental cues and target molecules. SynCom biosensors use engineered microorganisms to create a more complex and diverse sensing system, enabling them to respond to stimuli with enhanced sensitivity and accuracy. Here, we give a definition of SynCom biosensors, outline their construction workflow, and discuss current biosensing technology. We also highlight the challenges and future for developing and optimizing SynCom biosensors and the potential applications in agriculture and food management, biotherapeutic development, home sensing, urban and environmental monitoring, and the One Health foundation. We believe SynCom biosensors could be used in a real-time and remote-controlled manner to sense the chaos of constantly dynamic environments.

The Clinical Characteristics, Diagnostic Methods, Treatment, and Outcomes of Listeria monocytogenes Meningoencephalitis: A Case Series Study from China

Background

Listeria monocytogenes meningoencephalitis (LMM) is a rare but dangerous infection of the nervous system. This study intends to summarize and discuss the clinical features, diagnostic methods, treatment, and outcomes.

Methods

LMM patients treated in the First Affiliated Hospital of Zhengzhou University from June 2013 to December 2022 were retrospectively studied. The clinical data, magnetic resonance imaging (MRI), biochemical and hematological parameters, pathogen tests, treatments, and outcomes information were collected and summarized.

Results

Ten LMM patients were enrolled in this study. Three were female and seven were male, with a mean age of 54.5 years old. Seven (70%) of the patients had chronic conditions that either affected the liver (1 case), heart (1 case), or immune system (5 cases). The main clinical manifestations were fever (100%), headache, (60%), and disturbance of consciousness (60%). Out of the nine patients taken MRI, enhanced magnetic resonance imaging was observed with cerebral parenchyma and meningeal enhancement in 3 patients, whereas six patients showed non-specific abnormal signals and brain edema. Seven (70%) patients were positive for L. monocytogenes by bacterial culture and five patients were positive by further next-generation sequencing (NGS) test in CSF. All patients were treated with antibiotics based on antibiotic sensitivity tests or experience, with seven (70%) improved but three (30%) died within one month.

Conclusion

LMM patients have a high mortality rate. Considering the time and reliability of NGS reports, it would be better to identify L. monocytogenes infection in the CSF than bacterial culture. While, after diagnosis, giving timely and appropriate antibiotics would still be a challenge to achieve good outcomes.

COWID: an efficient cloud-based genomics workflow for scalable identification of SARS-COV-2

Implementing a specific cloud resource to analyze extensive genomic data on severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) poses a challenge when resources are limited. To overcome this, we repurposed a cloud platform initially designed for use in research on cancer genomics (https://cgc.sbgenomics.com) to enable its use in research on SARS-CoV-2 to build Cloud Workflow for Viral and Variant Identification (COWID). COWID is a workflow based on the Common Workflow Language that realizes the full potential of sequencing technology for use in reliable SARS-CoV-2 identification and leverages cloud computing to achieve efficient parallelization. COWID outperformed other contemporary methods for identification by offering scalable identification and reliable variant findings with no false-positive results. COWID typically processed each sample of raw sequencing data within 5 min at a cost of only US$0.01. The COWID source code is publicly available (https://github.com/hendrick0403/COWID) and can be accessed on any computer with Internet access. COWID is designed to be user-friendly; it can be implemented without prior programming knowledge. Therefore, COWID is a time-efficient tool that can be used during a pandemic.

The role of fungi in the diagnosis of colorectal cancer

Colorectal cancer (CRC) is a prevalent tumour with high morbidity rates worldwide, and its incidence among younger populations is rising. Early diagnosis of CRC can help control the associated mortality. Fungi are common microorganisms in nature. Recent studies have shown that fungi may have a similar association with tumours as bacteria do. As an increasing number of tumour-associated fungi are discovered, this provides new ideas for the diagnosis and prognosis of tumours. The relationship between fungi and colorectal tumours has also been recently identified by scientists. Therefore, this paper describes the limitations and prospects of the application of fungi in diagnosing CRC and predicting CRC prognosis.

Tackling Soil ARG-Carrying Pathogens with Global-Scale Metagenomics

Antibiotic overuse and the subsequent environmental contamination of residual antibiotics poses a public health crisis via an acceleration in the spread of antibiotic resistance genes (ARGs) through horizontal gene transfer. Although the occurrence, distribution, and driving factors of ARGs in soils have been widely investigated, little is known about the antibiotic resistance of soilborne pathogens at a global scale. To explore this gap, contigs from 1643 globally sourced metagnomes are assembled, yielding 407 ARG-carrying pathogens (APs) with at least one ARG; APs are detected in 1443 samples (sample detection rate of 87.8%). The richness of APs is greater in agricultural soils (with a median of 20) than in non-agricultural ecosystems. Agricultural soils possess a high prevalence of clinical APs affiliated with Escherichia, Enterobacter, Streptococcus, and Enterococcus. The APs detected in agricultural soils tend to coexist with multidrug resistance genes and bacA. A global map of soil AP richness is generated, where anthropogenic and climatic factors explained AP hot spots in East Asia, South Asia, and the eastern United States. The results herein advance this understanding of the global distribution of soil APs and determine regions prioritized to control soilborne APs worldwide.

A Comprehensive Review for the Surveillance of Human Pathogenic Microorganisms in Shellfish

Bivalve molluscan shellfish have been consumed for centuries. Being filter feeders, they may bioaccumulate some microorganisms present in coastal water, either naturally or through the discharge of human or animal sewage. Despite regulations set up to avoid microbiological contamination in shellfish, human outbreaks still occur. After providing an overview showing their implication in disease, this review aims to highlight the diversity of the bacteria or enteric viruses detected in shellfish species, including emerging pathogens. After a critical discussion of the available methods and their limitations, we address the interest of technological developments using genomics to anticipate the emergence of pathogens. In the coming years, further research needs to be performed and methods need to be developed in order to design the future of surveillance and to help risk assessment studies, with the ultimate objective of protecting consumers and enhancing the microbial safety of bivalve molluscan shellfish as a healthy food.

Detection of blaCTX-M and blaDHA genes in stool samples of healthy people: comparison of culture- and shotgun metagenomic-based approaches

We implemented culture- and shotgun metagenomic sequencing (SMS)-based methods to assess the gut colonization with extended-spectrum cephalosporin-resistant Enterobacterales (ESC-R-Ent) in 42 volunteers. Both methods were performed using native and pre-enriched (broth supplemented with cefuroxime) stools. Native culture screening on CHROMID® ESBL plates resulted in 17 positive samples, whereas the pre-enriched culture (gold-standard) identified 23 carriers. Overall, 26 ESC-R-Ent strains (24 Escherichia coli) were identified: 25 CTX-M and 3 DHA-1 producers (2 co-producing CTX-Ms). Using the SMS on native stool ("native SMS") with thresholds ≥60% for both identity and coverage, only 7 of the 23 pre-enriched culture-positive samples resulted positive for blaCTX-M/blaDHA genes (native SMS reads mapping to blaCTX-M/blaDHAs identified in gold-standard: sensitivity, 59.0%; specificity 100%). Moreover, an average of 31.5 and 24.6 antimicrobial resistance genes (ARGs) were detected in the 23 pre-enriched culture-positive and the 19 negative samples, respectively. When the pre-enriched SMS was implemented, more blaCTX-M/blaDHA genes were detected than in the native assay, including in stools that were pre-enriched culture-negative (pre-enriched SMS reads mapping to blaCTX-M/blaDHAs identified in gold-standard: sensitivity, 78.3%; specificity 75.0%). In addition, the pre-enriched SMS identified on average 38.6 ARGs/sample, whereas for the corresponding native SMS it was 29.4 ARGs/sample. Notably, stools resulting false-negative by using the native SMS had lower concentrations of ESC-R-Ent (average: ~105 vs. ~107 CFU/g) and E. coli classified reads (average: 193,959 vs. 1.45 million) than those of native SMS positive samples. Finally, the detection of blaCTX-M/blaDHA genes was compared with two well-established bioinformatic tools. In conclusion, only the pre-enriched SMS assured detection of most carriers of ESC-R-Ent. However, its performance was not comparable to the pre-enriched culture-based approach.