Evaluation of Metagenomics Next-Generation Sequencing as a Diagnostic Tool for Influenza Virus-Positive Respiratory Samples in Retired Fitness Players

The use of Metagenomics Next-Generation Sequencing (mNGS) as a diagnostic tool for respiratory infections, particularly in the context of retired fitness players, presents a novel avenue for optimizing healthcare and wellness in this unique population. Respiratory illnesses, including influenza, can have profound effects on the health and performance of retired athletes, making accurate and timely diagnosis paramount. In this study, we aimed to assess the applicability of mNGS in diagnosing influenza virus infections in retired fitness players. We collected and analyzed respiratory samples from this specific cohort, leveraging mNGS technology. Our research focused on evaluating mNGS's potential as a diagnostic tool compared to conventional methods. Our findings underscored the remarkable capabilities of mNGS. When compared to traditional diagnostic techniques, mNGS demonstrated superior sensitivity in detecting influenza virus-positive respiratory samples in retired fitness players. Additionally, mNGS facilitated the identification of not only known influenza strains but also previously undetected viral variants, offering a comprehensive view of the viral landscape. The utilization of mNGS as a diagnostic tool in the care of retired fitness players holds great promise in enhancing their health monitoring and overall well-being. This technology can aid in the early detection and precise characterization of respiratory infections, contributing to the timely implementation of targeted interventions and improving the quality of healthcare for this unique and health-conscious population. (AU)

Multicenter assessment of shotgun metagenomics for pathogen detection.

BACKGROUND: Shotgun metagenomics has been used clinically for diagnosing infectious diseases. However, most technical assessments have been limited to individual sets of reference standards, experimental workflows, and laboratories. METHODS: A reference panel and performance metrics were designed and used to examine the performance of shotgun metagenomics at 17 laboratories in a coordinated collaborative study. We comprehensively assessed the reliability, key performance determinants, reproducibility, and quantitative potential. FINDINGS: Assay performance varied significantly across sites and microbial classes, with a read depth of 20 millions as a generally cost-efficient assay setting. Results of mapped reads by shotgun metagenomics could indicate relative and intra-site (but not absolute or inter-site) microbial abundance. INTERPRETATION: Assay performance was significantly impacted by the microbial type, the host context, and read depth, which emphasizes the importance of these factors when designing reference reagents and benchmarking studies. Across sites, workflows and platforms, false positive reporting and considerable site/library effects were common challenges to the assay's accuracy and quantifiability. Our study also suggested that laboratory-developed shotgun metagenomics tests for pathogen detection should aim to detect microbes at 500 CFU/mL (or copies/mL) in a clinically relevant host context (10^5 human cells/mL) within a 24h turn-around time, and with an efficient read depth of 20M. FUNDING: This work was supported by National Science and Technology Major Project of China (2018ZX10102001).

MetaGeneBank: a standardized database to study deep sequenced metagenomic data from human fecal specimen.

BACKGROUND: Microbiome big data from population-scale cohorts holds the key to unleash the power of microbiomes to overcome critical challenges in disease control, treatment and precision medicine. However, variations introduced during data generation and processing limit the comparisons among independent studies in respect of interpretability. Although multiple databases have been constructed as platforms for data reuse, they are of limited value since only raw sequencing files are considered. DESCRIPTION: Here, we present MetaGeneBank, a standardized database that provides details on sample collection and sequencing, and abundances of genes, microbiota and molecular functions for 4470 raw sequencing files (over 12 TB) collected from 16 studies covering over 10 types of diseases and 14 countries using a unified data-processing pipeline. The incorporation of tools that enable browsing and searching with descriptive attributes, gene sequences, microbiota and functions makes the database user-friendly. We found that the source of specimen contributes more than sequencing centers or platforms to the variations of microbiota. Special attention should be paid when re-analyzing sequencing files from different countries. CONCLUSIONS: Collectively, MetaGeneBank provides a gateway to utilize the untapped potential of gut metagenomic data in helping fighting against human diseases. With the continuous updating of the database in terms of data volume, data types and sample types, MetaGeneBank would undoubtedly be the benchmarking database in the future in respect of data reuse, and would be valuable in translational science.

viromeBrowser: A Shiny App for Browsing Virome Sequencing Analysis Results.

Experiments in which complex virome sequencing data is generated remain difficult to explore and unpack for scientists without a background in data science. The processing of raw sequencing data by high throughput sequencing workflows usually results in contigs in FASTA format coupled to an annotation file linking the contigs to a reference sequence or taxonomic identifier. The next step is to compare the virome of different samples based on the metadata of the experimental setup and extract sequences of interest that can be used in subsequent analyses. The viromeBrowser is an application written in the opensource R shiny framework that was developed in collaboration with end-users and is focused on three common data analysis steps. First, the application allows interactive filtering of annotations by default or custom quality thresholds. Next, multiple samples can be visualized to facilitate comparison of contig annotations based on sample specific metadata values. Last, the application makes it easy for users to extract sequences of interest in FASTA format. With the interactive features in the viromeBrowser we aim to enable scientists without a data science background to compare and extract annotation data and sequences from virome sequencing analysis results.

MinION technology for microbiome sequencing applications for the conservation of cultural heritage.

The MinION single-molecule sequencing system has been attracting the attention of the community of microbiologists involved in the conservation of cultural heritage. The use of MinION for the conservation of cultural heritage is extremely recent, but surprisingly the only few applications available have been exploring many different substrates: stone, textiles, paintings and wax. The use of MinION sequencing is mainly used to address the metataxonomy (with special emphasis on non-cultivable microorganisms) with the effort to identify species involved in the degradation of the substrates. In this review, we show the current applications available on different artworks, showing how this technology can be a useful tool for microbiologists and conservators also in light of its low cost and the easy chemistry.

Single-virus genomics and beyond.

Viruses are extremely diverse and modulate important biological and ecological processes globally. However, much of viral diversity remains uncultured and yet to be discovered. Several powerful culture-independent tools, in particular metagenomics, have substantially advanced virus discovery. Among those tools is single-virus genomics, which yields sequenced reference genomes from individual sorted virus particles without the need for cultivation. This new method complements virus culturing and metagenomic approaches and its advantages include targeted investigation of specific virus groups and investigation of genomic microdiversity within viral populations. In this Review, we provide a brief history of single-virus genomics, outline how this emergent method has facilitated advances in virus ecology and discuss its current limitations and future potential. Finally, we address how this method may synergistically intersect with other single-virus and single-cell approaches.

MetaEuk-sensitive, high-throughput gene discovery, and annotation for large-scale eukaryotic metagenomics.

BACKGROUND: Metagenomics is revolutionizing the study of microorganisms and their involvement in biological, biomedical, and geochemical processes, allowing us to investigate by direct sequencing a tremendous diversity of organisms without the need for prior cultivation. Unicellular eukaryotes play essential roles in most microbial communities as chief predators, decomposers, phototrophs, bacterial hosts, symbionts, and parasites to plants and animals. Investigating their roles is therefore of great interest to ecology, biotechnology, human health, and evolution. However, the generally lower sequencing coverage, their more complex gene and genome architectures, and a lack of eukaryote-specific experimental and computational procedures have kept them on the sidelines of metagenomics. RESULTS: MetaEuk is a toolkit for high-throughput, reference-based discovery, and annotation of protein-coding genes in eukaryotic metagenomic contigs. It performs fast searches with 6-frame-translated fragments covering all possible exons and optimally combines matches into multi-exon proteins. We used a benchmark of seven diverse, annotated genomes to show that MetaEuk is highly sensitive even under conditions of low sequence similarity to the reference database. To demonstrate MetaEuk's power to discover novel eukaryotic proteins in large-scale metagenomic data, we assembled contigs from 912 samples of the Tara Oceans project. MetaEuk predicted >12,000,000 protein-coding genes in 8 days on ten 16-core servers. Most of the discovered proteins are highly diverged from known proteins and originate from very sparsely sampled eukaryotic supergroups. CONCLUSION: The open-source (GPLv3) MetaEuk software (https://github.com/soedinglab/metaeuk) enables large-scale eukaryotic metagenomics through reference-based, sensitive taxonomic and functional annotation. Video abstract.

Improving the usability and comprehensiveness of microbial databases.

Metagenomics studies leverage genomic reference databases to generate discoveries in basic science and translational research. However, current microbial studies use disparate reference databases that lack consistent standards of specimen inclusion, data preparation, taxon labelling and accessibility, hindering their quality and comprehensiveness, and calling for the establishment of recommendations for reference genome database assembly. Here, we analyze existing fungal and bacterial databases and discuss guidelines for the development of a master reference database that promises to improve the quality and quantity of omics research.

Benchmarking the MinION: Evaluating long reads for microbial profiling.

Nanopore based DNA-sequencing delivers long reads, thereby simplifying the decipherment of bacterial communities. Since its commercial appearance, this technology has been assigned several attributes, such as its error proneness, comparatively low cost, ease-of-use, and, most notably, aforementioned long reads. The technology as a whole is under continued development. As such, benchmarks are required to conceive, test and improve analysis protocols, including those related to the understanding of the composition of microbial communities. Here we present a dataset composed of twelve different prokaryotic species split into four samples differing by nucleic acid quantification technique to assess the specificity and sensitivity of the MinION nanopore sequencer in a blind study design. Taxonomic classification was performed by standard taxonomic sequence classification tools, namely Kraken, Kraken2 and Centrifuge directly on reads. This allowed taxonomic assignments of up to 99.27% on genus level and 92.78% on species level, enabling true-positive classification of strains down to 25,000 genomes per sample. Full genomic coverage is achieved for strains abundant as low as 250,000 genomes per sample under our experimental settings. In summary, we present an evaluation of nanopore sequence processing analysis with respect to microbial community composition. It provides an open protocol and the data may serve as basis for the development and benchmarking of future data processing pipelines.

DNA extraction of microbial DNA directly from infected tissue: an optimized protocol for use in nanopore sequencing.

Identification of bacteria causing tissue infections can be comprehensive and, in the cases of non- or slow-growing bacteria, near impossible with conventional methods. Performing shotgun metagenomic sequencing on bacterial DNA extracted directly from the infected tissue may improve time to diagnosis and targeted treatment considerably. However, infected tissue consists mainly of human DNA (hDNA) which hampers bacterial identification. In this proof of concept study, we present a modified version of the Ultra-Deep Microbiome Prep kit for DNA extraction procedure, removing additional human DNA. Tissue biopsies from 3 patients with orthopedic implant-related infections containing varying degrees of Staphylococcus aureus were included. Subsequent DNA shotgun metagenomic sequencing using Oxford Nanopore Technologies' (ONT) MinION platform and ONTs EPI2ME WIMP and ARMA bioinformatic workflows for microbe and antibiotic resistance genes identification, respectively. The modified DNA extraction protocol led to an additional ~10-fold reduction of human DNA while preserving S. aureus DNA. Including the DNA sequencing and bioinformatics analyses, the presented protocol has the potential of identifying the infection-causing pathogen in infected tissue within 7 hours after biopsy. However, due to low number of S. aureus reads, positive identification of antibiotic resistance genes was not possible.

SPIKEPIPE: A metagenomic pipeline for the accurate quantification of eukaryotic species occurrences and intraspecific abundance change using DNA barcodes or mitogenomes.

The accurate quantification of eukaryotic species abundances from bulk samples remains a key challenge for community ecology and environmental biomonitoring. We resolve this challenge by combining shotgun sequencing, mapping to reference DNA barcodes or to mitogenomes, and three correction factors: (a) a percent-coverage threshold to filter out false positives, (b) an internal-standard DNA spike-in to correct for stochasticity during sequencing, and (c) technical replicates to correct for stochasticity across sequencing runs. The SPIKEPIPE pipeline achieves a strikingly high accuracy of intraspecific abundance estimates (in terms of DNA mass) from samples of known composition (mapping to barcodes R2  = .93, mitogenomes R2  = .95) and a high repeatability across environmental-sample replicates (barcodes R2  = .94, mitogenomes R2  = .93). As proof of concept, we sequence arthropod samples from the High Arctic, systematically collected over 17 years, detecting changes in species richness, species-specific abundances, and phenology. SPIKEPIPE provides cost-efficient and reliable quantification of eukaryotic communities.

Entirely Off-Grid and Solar-Powered DNA Sequencing of Microbial Communities during an Ice Cap Traverse Expedition.

Microbial communities in remote locations remain under-studied. This is particularly true on glaciers and icecaps, which cover approximately 11% of the Earth's surface. The principal reason for this is the inaccessibility of most of these areas due to their extreme isolation and challenging environmental conditions. While remote research stations have significantly lowered the barrier to studying the microbial communities on icecaps, their use has led to a bias for data collection in the near vicinity of these institutions. Here, miniaturisation of a DNA sequencing lab suitable for off-grid metagenomic studies is demonstrated. Using human power alone, this lab was transported across Europe's largest ice cap (Vatnajökull, Iceland) by ski and sledge. After 11 days of unsupported polar-style travel, a metagenomic study of a geothermal hot spring gorge was conducted on the remote northern edge of the ice cap. This tent-based metagenomic study resulted in over 24 h of Nanopore sequencing, powered by solar power alone. This study demonstrates the ability to conduct DNA sequencing in remote locations, far from civilised resources (mechanised transport, external power supply, internet connection, etc.), whilst greatly reducing the time from sample collection to data acquisition.

Sponges as natural environmental DNA samplers.

At a time of unprecedented impacts on marine biodiversity, scientists are rapidly becoming persuaded by the potential of screening large swathes of the oceans through the retrieval, amplification and sequencing of trace DNA fragments left behind by marine organisms; an approach known as 'environmental DNA' (eDNA) [1]. In trying to circumvent the many challenges associated with water filtration and DNA isolation from environmental samples, significant investment is being made in high-tech solutions, such as automated underwater vehicles and robots [2]. Here, instead, we explored a simpler, alternative option, based on the recovery of eDNA from sponges (phylum Porifera), the planet's most effective water-filterers. We obtained sponge samples from Mediterranean and Antarctic surveys, extracted total DNA from their tissues, and obtained tens of thousands of fish DNA reads via metabarcoding, which were able to clearly distinguish samples from the two regions. One Antarctic sample yielded hundreds of reads from chinstrap penguin (Pygoscelis antarcticus) and Weddell seal (Leptonychotes weddellii). We argue that this 'natural sampler DNA' (nsDNA) approach is poised to become a powerful, affordable, universal tool for aquatic biodiversity monitoring globally.

Extraction of Plant DNA by Microneedle Patch for Rapid Detection of Plant Diseases.

In-field molecular diagnosis of plant diseases via nucleic acid amplification is currently limited by cumbersome protocols for extracting and isolating pathogenic DNA from plant tissues. To address this challenge, a rapid plant DNA extraction method was developed using a disposable polymeric microneedle (MN) patch. By applying MN patches on plant leaves, amplification-assay-ready DNA can be extracted within a minute from different plant species. MN-extracted DNA was used for direct polymerase chain reaction amplification of plant plastid DNA without purification. Furthermore, using this patch device, extraction of plant pathogen DNA ( Phytophthora infestans) from both laboratory-inoculated and field-infected leaf samples was performed for detection of late blight disease in tomato. MN extraction achieved 100% detection rate of late blight infections for samples after 3 days of inoculation when compared to the conventional gold standard cetyltrimethylammonium bromide (CTAB)-based DNA extraction method and 100% detection rate for all blind field samples tested. This simple, cell-lysis-free, and purification-free DNA extraction method could be a transformative approach to facilitate rapid sample preparation for molecular diagnosis of various plant diseases directly in the field.

Clinical metagenomics.

Clinical metagenomic next-generation sequencing (mNGS), the comprehensive analysis of microbial and host genetic material (DNA and RNA) in samples from patients, is rapidly moving from research to clinical laboratories. This emerging approach is changing how physicians diagnose and treat infectious disease, with applications spanning a wide range of areas, including antimicrobial resistance, the microbiome, human host gene expression (transcriptomics) and oncology. Here, we focus on the challenges of implementing mNGS in the clinical laboratory and address potential solutions for maximizing its impact on patient care and public health.

Mobile antibiotic resistome in wastewater treatment plants revealed by Nanopore metagenomic sequencing.

BACKGROUND: Wastewater treatment plants (WWTPs) are recognized as hotspots for horizontal gene transfer (HGT) of antibiotic resistance genes (ARGs). Despite our understanding of the composition and distribution of ARGs in WWTPs, the genetic location, host, and fate of ARGs remain largely unknown. RESULTS: In this study, we combined Oxford Nanopore and Illumina metagenomics sequencing to comprehensively uncover the resistome context of influent, activated sludge, and effluent of three WWTPs and simultaneously track the hosts of the ARGs. The results showed that most of the ARGs detected in all compartments of the WWTPs were carried by plasmids. Transposons and integrons also showed higher prevalence on plasmids than on the ARG-carrying chromosome. Notably, integrative and conjugative elements (ICEs) carrying five types of ARGs were detected, and they may play an important role in facilitating the transfer of ARGs, particularly for tetracycline and macrolide-lincosamide-streptogramin (MLS). A broad spectrum of ARGs carried by plasmids (29 subtypes) and ICEs (4 subtypes) was persistent across the WWTPs. Host tracking showed a variety of antibiotic-resistant bacteria in the effluent, suggesting the high potential for their dissemination into receiving environments. Importantly, phenotype-genotype analysis confirmed the significant role of conjugative plasmids in facilitating the survival and persistence of multidrug-resistant bacteria in the WWTPs. At last, the consistency in the quantitative results for major ARGs types revealed by Nanopore and Illumina sequencing platforms demonstrated the feasibility of Nanopore sequencing for resistome quantification. CONCLUSION: Overall, these findings substantially expand our current knowledge of resistome in WWTPs, and help establish a baseline analysis framework to study ARGs in the environment.

Miniaturization and optimization of 384-well compatible RNA sequencing library preparation.

Preparation of high-quality sequencing libraries is a costly and time-consuming component of metagenomic next generation sequencing (mNGS). While the overall cost of sequencing has dropped significantly over recent years, the reagents needed to prepare sequencing samples are likely to become the dominant expense in the process. Furthermore, libraries prepared by hand are subject to human variability and needless waste due to limitations of manual pipetting volumes. Reduction of reaction volumes, combined with sub-microliter automated dispensing of reagents without consumable pipette tips, has the potential to provide significant advantages. Here, we describe the integration of several instruments, including the Labcyte Echo 525 acoustic liquid handler and the iSeq and NovaSeq Illumina sequencing platforms, to miniaturize and automate mNGS library preparation, significantly reducing the cost and the time required to prepare samples. Through the use of External RNA Controls Consortium (ERCC) spike-in RNAs, we demonstrated the fidelity of the miniaturized preparation to be equivalent to full volume reactions. Furthermore, detection of viral and microbial species from cell culture and patient samples was also maintained in the miniaturized libraries. For 384-well mNGS library preparations, we achieved cost savings of over 80% in materials and reagents alone, and reduced preparation time by 90% compared to manual approaches, without compromising quality or representation within the library.

Overview of Trends in the Application of Metagenomic Techniques in the Analysis of Human Enteric Viral Diversity in Africa's Environmental Regimes.

There has been an increase in the quest for metagenomics as an approach for the identification and study of the diversity of human viruses found in aquatic systems, both for their role as waterborne pathogens and as water quality indicators. In the last few years, environmental viral metagenomics has grown significantly and has enabled the identification, diversity and entire genome sequencing of viruses in environmental and clinical samples extensively. Prior to the arrival of metagenomics, traditional molecular procedures such as the polymerase chain reaction (PCR) and sequencing, were mostly used to identify and classify enteric viral species in different environmental milieu. After the advent of metagenomics, more detailed reports have emerged about the important waterborne viruses identified in wastewater treatment plant effluents and surface water. This paper provides a review of methods that have been used for the concentration, detection and identification of viral species from different environmental matrices. The review also takes into consideration where metagenomics has been explored in different African countries, as well as the limitations and challenges facing the approach. Procedures including sample processing, experimental design, sequencing technology, and bioinformatics analysis are discussed. The review concludes by summarising the current thinking and practices in the field and lays bare key issues that those venturing into this field need to consider and address.

Three invariant Hi-C interaction patterns: Applications to genome assembly.

Assembly of reference-quality genomes from next-generation sequencing data is a key challenge in genomics. Recently, we and others have shown that Hi-C data can be used to address several outstanding challenges in the field of genome assembly. This principle has since been developed in academia and industry, and has been used in the assembly of several major genomes. In this paper, we explore the central principles underlying Hi-C-based assembly approaches, by quantitatively defining and characterizing three invariant Hi-C interaction patterns on which these approaches can build: Intrachromosomal interaction enrichment, distance-dependent interaction decay and local interaction smoothness. Specifically, we evaluate to what degree each invariant pattern holds on a single locus level in different species, cell types and Hi-C map resolutions. We find that these patterns are generally consistent across species and cell types but are affected by sequencing depth, and that matrix balancing improves consistency of loci with all three invariant patterns. Finally, we overview current Hi-C-based assembly approaches in light of these invariant patterns and demonstrate how local interaction smoothness can be used to easily detect scaffolding errors in extremely sparse Hi-C maps. We suggest that simultaneously considering all three invariant patterns may lead to better Hi-C-based genome assembly methods.

dRep: a tool for fast and accurate genomic comparisons that enables improved genome recovery from metagenomes through de-replication.

The number of microbial genomes sequenced each year is expanding rapidly, in part due to genome-resolved metagenomic studies that routinely recover hundreds of draft-quality genomes. Rapid algorithms have been developed to comprehensively compare large genome sets, but they are not accurate with draft-quality genomes. Here we present dRep, a program that reduces the computational time for pairwise genome comparisons by sequentially applying a fast, inaccurate estimation of genome distance, and a slow, accurate measure of average nucleotide identity. dRep achieves a 28 × increase in speed with perfect recall and precision when benchmarked against previously developed algorithms. We demonstrate the use of dRep for genome recovery from time-series datasets. Each metagenome was assembled separately, and dRep was used to identify groups of essentially identical genomes and select the best genome from each replicate set. This resulted in recovery of significantly more and higher-quality genomes compared to the set recovered using co-assembly.