Clinical Metagenomics Is Increasingly Accurate and Affordable to Detect Enteric Bacterial Pathogens in Stool

Can Wastewater Surveillance Enhance Genomic Tracking of Climate-Driven Pathogens?

Climate change heightens the threat of infectious diseases in Europe, necessitating innovative surveillance methods. Based on 390 scientific papers, for the first time, this review associates climate-related pathogens, data related to their presence in wastewater, and associated available genomic detection methods. This deep analysis reveals a wide range of pathogens that can be tracked through methods such as quantitative and digital PCR, as well as genomic pathogen enrichment in combination with sequencing and metagenomics. Nevertheless, significant gaps remain in the development of methods, particularly for vector-borne pathogens, and in their general harmonization relating to performance criteria. By offering an overview of recent advancements while identifying critical gaps, we advocate for collaborative research and validation to integrate detection techniques into surveillance frameworks. This will enhance public health resilience against emerging infectious diseases driven by climate change.

A Metagenomics Pipeline to Characterize Self-Collected Vaginal Microbiome Samples

Vaginitis is a widespread issue for women worldwide, yet current diagnostic tools are lacking. Bacterial vaginosis (BV) is the most prevalent type of vaginitis, found in 10-50% of reproductive-aged women. Current diagnostic methods for BV rely on clinical criteria, microscopy, or the detection of a few microbes by qPCR. However, many vaginal infections lack a single etiological agent and are characterized by changes in the vaginal microbiome community structure (e.g., BV is defined as a loss of protective lactobacilli resulting in an overgrowth of anaerobic bacteria). Shotgun metagenomic sequencing provides a comprehensive view of all the organisms present in the vaginal microbiome (VMB), allowing for a better understanding of all potential etiologies. Here, we describe a robust VMB metagenomics sequencing test with a sensitivity of 93.1%, a specificity of 90%, a negative predictive value of 93.4%, and a positive predictive value of 89.6% certified by Clinical Laboratory Improvement Amendments (CLIA), the College of American Pathologist (CAP), and the Clinical Laboratory Evaluation Program (CLEP). We sequenced over 7000 human vaginal samples with this pipeline and described general findings and comparisons to US census data.

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.

Tick-Borne Diseases in Sub-Saharan Africa: A Systematic Review of Pathogens, Research Focus, and Implications for Public Health

Sub-Saharan Africa, with its hot and humid climate, is a conducive zone for tick proliferation. These vectors pose a major challenge to both animal and human health in the region. However, despite the relevance of emerging diseases and evidence of tick-borne disease emergence, very few studies have been dedicated to investigating zoonotic pathogens transmitted by ticks in this area. To raise awareness of the risks of tick-borne zoonotic diseases in sub-Saharan Africa, and to define a direction for future research, this systematic review considers the trends of research on tick-borne bacteria, parasites, and viruses from 2012 to 2023, aiming to highlight the circulation of these pathogens in ticks, cattle, sheep, goats, and humans. For this purpose, three international databases were screened to select 159 papers fitting designed inclusion criteria and used for qualitative analyses. Analysis of these studies revealed a high diversity of tick-borne pathogens in sub-Saharan Africa, with a total of 37 bacterial species, 27 parasite species, and 14 viruses identified. Among these, 27% were zoonotic pathogens, yet only 11 studies investigated their presence in humans. Furthermore, there is growing interest in the investigation of bacteria and parasites in both ticks and ruminants. However, research into viruses is limited and has only received notable interest from 2021 onwards. While studies on the detection of bacteria, including those of medical interest, have focused on ticks, little consideration has been given to these vectors in studies of parasites circulation. Regarding the limited focus on zoonotic pathogens transmitted by ticks, particularly in humans, despite documented cases of emerging zoonoses and the notable 27% proportion reported, further efforts should be made to fill these gaps. Future studies should prioritize the investigation of zoonotic pathogens, especially viruses, which represent the primary emerging threats, by adopting a One Health approach. This will enhance the understanding of their circulation and impact on both human and animal health. In addition, more attention should be given to the risk factors/drivers associated to their emergence as well as the perception of the population at risk of infection from these zoonotic pathogens.

Capturing clinically relevant Campylobacter attributes through direct whole genome sequencing of stool

Campylobacter is the leading bacterial cause of infectious intestinal disease, but the pathogen typically accounts for a very small proportion of the overall stool microbiome in each patient. Diagnosis is even more difficult due to the fastidious nature of Campylobacter in the laboratory setting. This has, in part, driven a change in recent years, from culture-based to rapid PCR-based diagnostic assays which have improved diagnostic detection, whilst creating a knowledge gap in our clinical and epidemiological understanding of Campylobacter genotypes - no isolates to sequence. In this study, direct metagenomic sequencing approaches were used to assess the possibility of replacing genome sequences with metagenome sequences; metagenomic sequencing outputs were used to describe clinically relevant attributes of Campylobacter genotypes. A total of 37 diarrhoeal stool samples with Campylobacter and five samples with an unknown pathogen result were collected and processed with and without filtration, DNA was extracted, and metagenomes were sequenced by short-read sequencing. Culture-based methods were used to validate Campylobacter metagenome-derived genome (MDG) results. Sequence output metrics were assessed for Campylobacter genome quality and accuracy of characterization. Of the 42 samples passing quality checks for analysis, identification of Campylobacter to the genus and species level was dependent on Campylobacter genome read count, coverage and genome completeness. A total of 65% (24/37) of samples were reliably identified to the genus level through Campylobacter MDG, 73% (27/37) by culture and 97% (36/37) by qPCR. The Campylobacter genomes with a genome completeness of over 60% (n=21) were all accurately identified at the species level (100%). Of those, 72% (15/21) were identified to sequence types (STs), and 95% (20/21) accurately identified antimicrobial resistance (AMR) gene determinants. Filtration of stool samples enhanced Campylobacter MDG recovery and genome quality metrics compared to the corresponding unfiltered samples, which improved the identification of STs and AMR profiles. The phylogenetic analysis in this study demonstrated the clustering of the metagenome-derived with culture-derived genomes and revealed the reliability of genomes from direct stool sequencing. Furthermore, Campylobacter genome spiking percentages ranging from 0 to 2% total metagenome abundance in the ONT MinION sequencer, configured to adaptive sequencing, exhibited better assembly quality and accurate identification of STs, particularly in the analysis of metagenomes containing 2 and 1% of Campylobacter jejuni genomes. Direct sequencing of Campylobacter from stool samples provides clinically relevant and epidemiologically important genomic information without the reliance on cultured genomes.

Non-Targeted RNA Sequencing: Towards the Development of Universal Clinical Diagnosis Methods for Human and Veterinary Infectious Diseases

Metagenomics offers the potential to replace and simplify classical methods used in the clinical diagnosis of human and veterinary infectious diseases. Metagenomics boasts a high pathogen discovery rate and high specificity, advantages absent in most classical approaches. However, its widespread adoption in clinical settings is still pending, with a slow transition from research to routine use. While longer turnaround times and higher costs were once concerns, these issues are currently being addressed by automation, better chemistries, improved sequencing platforms, better databases, and automated bioinformatics analysis. However, many technical options and steps, each producing highly variable outcomes, have reduced the technology's operational value, discouraging its implementation in diagnostic labs. We present a case for utilizing non-targeted RNA sequencing (NT-RNA-seq) as an ideal metagenomics method for the detection of infectious disease-causing agents in humans and animals. Additionally, to create operational value, we propose to identify best practices for the "core" of steps that are invariably shared among many human and veterinary protocols. Reference materials, sequencing procedures, and bioinformatics standards should accelerate the validation processes necessary for the widespread adoption of this technology. Best practices could be determined through "implementation research" by a consortium of interested institutions working on common samples.

Next-Generation Sequencing for the Detection of Microbial Agents in Avian Clinical Samples

Direct-targeted next-generation sequencing (tNGS), with its undoubtedly superior diagnostic capacity over real-time PCR (RT-PCR), and direct-non-targeted NGS (ntNGS), with its higher capacity to identify and characterize multiple agents, are both likely to become diagnostic methods of choice in the future. tNGS is a rapid and sensitive method for precise characterization of suspected agents. ntNGS, also known as agnostic diagnosis, does not require a hypothesis and has been used to identify unsuspected infections in clinical samples. Implemented in the form of multiplexed total DNA metagenomics or as total RNA sequencing, the approach produces comprehensive and actionable reports that allow semi-quantitative identification of most of the agents present in respiratory, cloacal, and tissue samples. The diagnostic benefits of the use of direct tNGS and ntNGS are high specificity, compatibility with different types of clinical samples (fresh, frozen, FTA cards, and paraffin-embedded), production of nearly complete infection profiles (viruses, bacteria, fungus, and parasites), production of "semi-quantitative" information, direct agent genotyping, and infectious agent mutational information. The achievements of NGS in terms of diagnosing poultry problems are described here, along with future applications. Multiplexing, development of standard operating procedures, robotics, sequencing kits, automated bioinformatics, cloud computing, and artificial intelligence (AI) are disciplines converging toward the use of this technology for active surveillance in poultry farms. Other advances in human and veterinary NGS sequencing are likely to be adaptable to avian species in the future.

Use of a taxon-specific reference database for accurate metagenomics-based pathogen detection of Listeria monocytogenes in turkey deli meat and spinach

BACKGROUND

The reliability of culture-independent pathogen detection in foods using metagenomics is contingent on the quality and composition of the reference database. The inclusion of microbial sequences from a diverse representation of taxonomies in universal reference databases is recommended to maximize classification precision for pathogen detection. However, these sizable databases have high memory requirements that may be out of reach for some users. In this study, we aimed to assess the performance of a foodborne pathogen (FBP)-specific reference database (taxon-specific) relative to a universal reference database (taxon-agnostic). We tested our FBP-specific reference database's performance for detecting Listeria monocytogenes in two complex food matrices-ready-to-eat (RTE) turkey deli meat and prepackaged spinach-using three popular read-based DNA-to-DNA metagenomic classifiers: Centrifuge, Kraken 2 and KrakenUniq.

RESULTS

In silico host sequence removal led to substantially fewer false positive (FP) classifications and higher classification precision in RTE turkey deli meat datasets using the FBP-specific reference database. No considerable improvement in classification precision was observed following host filtering for prepackaged spinach datasets and was likely a consequence of a higher microbe-to-host sequence ratio. All datasets classified with Centrifuge using the FBP-specific reference database had the lowest classification precision compared to Kraken 2 or KrakenUniq. When a confidence-scoring threshold was applied, a nearly equivalent precision to the universal reference database was achieved for Kraken 2 and KrakenUniq. Recall was high for both reference databases across all datasets and classifiers. Substantially fewer computational resources were required for metagenomics-based detection of L. monocytogenes using the FBP-specific reference database, especially when combined with Kraken 2.

CONCLUSIONS

A universal (taxon-agnostic) reference database is not essential for accurate and reliable metagenomics-based pathogen detection of L. monocytogenes in complex food matrices. Equivalent classification performance can be achieved using a taxon-specific reference database when the appropriate quality control measures, classification software, and analysis parameters are applied. This approach is less computationally demanding and more attainable for the broader scientific and food safety communities.

Shotgun metagenomics of fecal samples from children in Peru reveals frequent complex co-infections with multiple Campylobacter species

Campylobacter spp. are a major cause of bacterial diarrhea worldwide and are associated with high rates of mortality and linear growth faltering in children living in low- to middle-income countries (LMICs). Campylobacter jejuni and Campylobacter coli are most often the causative agents of enteric disease among children in LMICs. However, previous work on a collection of stool samples from children under 2 years of age, living in a low resource community in Peru with either acute diarrheal disease or asymptomatic, were found to be qPCR positive for Campylobacter species but qPCR negative for C. jejuni and C. coli. The goal of this study was to determine if whole-genome shotgun metagenomic sequencing (WSMS) could identify the Campylobacter species within these samples. The Campylobacter species identified in these stool samples included C. jejuni, C. coli, C. upsaliensis, C. concisus, and the potential new species of Campylobacter, "Candidatus Campylobacter infans". Moreover, WSMS results demonstrate that over 65% of the samples represented co-infections with multiple Campylobacter species present in a single stool sample, a novel finding in human populations.

Analysis of shotgun metagenomic data obtained from fecal samples of children living in a low resource tropical community of Peru revealed multiple Campylobacter species. Co-infections with more than one Campylobacter species within the same sample was a common finding. A potential new species of Campylobacter was also detected within these samples.