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Future potential of metagenomics in clinical laboratories

INTRODUCTION

Rapid and sensitive diagnostic strategies are necessary for patient care and public health. Most of the current conventional microbiological assays detect only a restricted panel of pathogens at a time or require a microbe to be successfully cultured from a sample. Clinical metagenomics next-generation sequencing (mNGS) has the potential to unbiasedly detect all pathogens in a sample, increasing the sensitivity for detection and enabling the discovery of unknown infectious agents.

AREAS COVERED

High expectations have been built around mNGS; however, this technique is far from widely available. This review highlights the advances and currently available options in terms of costs, turnaround time, sensitivity, specificity, validation, and reproducibility of mNGS as a diagnostic tool in clinical microbiology laboratories.

EXPERT OPINION

The need for a novel diagnostic tool to increase the sensitivity of microbial diagnostics is clear. mNGS has the potential to revolutionise clinical microbiology. However, its role as a diagnostic tool has yet to be widely established, which is crucial for successfully implementing the technique. A clear definition of diagnostic algorithms that include mNGS is vital to show clinical utility. Similarly to real-time PCR, mNGS will one day become a vital tool in any testing algorithm.

fIDBAC: A Platform for Fast Bacterial Genome Identification and Typing

To study the contamination of microorganisms in the food industry, pharmaceutical industry, clinical diagnosis, or bacterial taxonomy, accurate identification of species is a key starting point of further investigation. The conventional method of identification by the 16S rDNA gene or other marker gene comparison is not accurate, because it uses a tiny part of the genomic information. The average nucleotide identity calculated between two whole bacterial genomes was proven to be consistent with DNA-DNA hybridization and adopted as the gold standard of bacterial species delineation. Furthermore, there are more bacterial genomes available in public databases recently. All of those contribute to a genome era of bacterial species identification. However, wrongly labeled and low-quality bacterial genome assemblies, especially from type strains, greatly affect accurate identification. In this study, we employed a multi-step strategy to create a type-strain genome database, by removing the wrongly labeled and low-quality genome assemblies. Based on the curated database, a fast bacterial genome identification platform (fIDBAC) was developed (http://fbac.dmicrobe.cn/). The fIDBAC is aimed to provide a single, coherent, and automated workflow for species identification, strain typing, and downstream analysis, such as CDS prediction, drug resistance genes, virulence gene annotation, and phylogenetic analysis.

Metagenomics next-generation sequencing tests take the stage in the diagnosis of lower respiratory tract infections

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The applications of mNGS for LRIs span a wide range of areas including LRI diagnosis, airway microbiome analyses, human host response analyses, and prediction of drug resistance.

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The workflow of mNGS used in clinical practice involves the wet-lab pipeline and dry-lab pipeline, the complex workflow poses challenges for its extensive use.

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mNGS will become an important tool in the field of infectious disease diagnosis in the next decade.

Metagenomic next-generation sequencing (mNGS) has changed the diagnosis landscape of lower respiratory tract infections (LRIs). With the development of newer sequencing assays, it is now possible to assess all microorganisms in a sample using a single mNGS analysis. The applications of mNGS for LRIs span a wide range of areas including LRI diagnosis, airway microbiome analyses, human host response analyses, and prediction of drug resistance. mNGS is currently in an exciting transitional period; however, before implementation in a clinical setting, there are several barriers to overcome, such as the depletion of human nucleic acid, discrimination between colonization and infection, high costs, and so on.

Aim of Review: In this review, we summarize the potential applications and challenges of mNGS in the diagnosis of LRIs to promote the integration of mNGS into the management of patients with respiratory tract infections in a clinical setting.

Key Scientific Concepts of Review: Once its analytical validation, clinical validation and clinical utility been demonstrated, mNGS will become an important tool in the field of infectious disease diagnosis.

Generalizable characteristics of false-positive bacterial variant calls

Minimizing false positives is a critical issue when variant calling as no method is without error. It is common practice to post-process a variant-call file (VCF) using hard filter criteria intended to discriminate true-positive (TP) from false-positive (FP) calls. These are applied on the simple principle that certain characteristics are disproportionately represented among the set of FP calls and that a user-chosen threshold can maximize the number detected. To provide guidance on this issue, this study empirically characterized all false SNP and indel calls made using real Illumina sequencing data from six disparate species and 166 variant-calling pipelines (the combination of 14 read aligners with up to 13 different variant callers, plus four ‘all-in-one’ pipelines). We did not seek to optimize filter thresholds but instead to draw attention to those filters of greatest efficacy and the pipelines to which they may most usefully be applied. In this respect, this study acts as a coda to our previous benchmarking evaluation of bacterial variant callers, and provides general recommendations for effective practice. The results suggest that, of the pipelines analysed in this study, the most straightforward way of minimizing false positives would simply be to use Snippy. We also find that a disproportionate number of false calls, irrespective of the variant-calling pipeline, are located in the vicinity of indels, and highlight this as an issue for future development.

SAUTE: sequence assembly using target enrichment

Background

Illumina is the dominant sequencing technology at this time. Short length, short insert size, some systematic biases, and low-level carryover contamination in Illumina reads continue to make assembly of repeated regions a challenging problem. Some applications also require finding multiple well supported variants for assembled regions.

Results

To facilitate assembly of repeat regions and to report multiple well supported variants when a user can provide target sequences to assist the assembly, we propose SAUTE and SAUTE_PROT assemblers. Both assemblers use de Bruijn graph on reads. Targets can be transcripts or proteins for RNA-seq reads and transcripts, proteins, or genomic regions for genomic reads. Target sequences are nucleotide and protein sequences for SAUTE and SAUTE_PROT, respectively.

Conclusions

For RNA-seq, comparisons with Trinity, rnaSPAdes, SPAligner, and SPAdes assembly of reads aligned to target proteins by DIAMOND show that SAUTE_PROT finds more coding sequences that translate to benchmark proteins. Using AMRFinderPlus calls, we find SAUTE has higher sensitivity and precision than SPAdes, plasmidSPAdes, SPAligner, and SPAdes assembly of reads aligned to target regions by HISAT2. It also has better sensitivity than SKESA but worse precision.

Supplementary Information

The online version contains supplementary material available at 10.1186/s12859-021-04174-9.

Antibiotic resistance: Time of synthesis in a post-genomic age

Antibiotic resistance has been highlighted by international organizations, including World Health Organization, World Bank and United Nations, as one of the most relevant global health problems. Classical approaches to study this problem have focused in infected humans, mainly at hospitals. Nevertheless, antibiotic resistance can expand through different ecosystems and geographical allocations, hence constituting a One-Health, Global-Health problem, requiring specific integrative analytic tools. Antibiotic resistance evolution and transmission are multilayer, hierarchically organized processes with several elements (from genes to the whole microbiome) involved. However, their study has been traditionally gene-centric, each element independently studied. The development of robust-economically affordable whole genome sequencing approaches, as well as other -omic techniques as transcriptomics and proteomics, is changing this panorama. These technologies allow the description of a system, either a cell or a microbiome as a whole, overcoming the problems associated with gene-centric approaches. We are currently at the time of combining the information derived from -omic studies to have a more holistic view of the evolution and spread of antibiotic resistance. This synthesis process requires the accurate integration of -omic information into computational models that serve to analyse the causes and the consequences of acquiring AR, fed by curated databases capable of identifying the elements involved in the acquisition of resistance. In this review, we analyse the capacities and drawbacks of the tools that are currently in use for the global analysis of AR, aiming to identify the more useful targets for effective corrective interventions.

Genomics and Virulence of Klebsiella pneumoniae Kpnu95 ST1412 Harboring a Novel Incf Plasmid Encoding Blactx-M-15 and Qnrs1 Causing Community Urinary Tract Infection

The emergence of extended-spectrum β-lactamase (ESBL)-producing multidrug resistant Klebsiella pneumoniae causing community urinary tract infections (CA-UTI) in healthy women undermines effective treatment and poses a public health concern. We performed a comprehensive genomic analysis (Illumina and MinION) and virulence studies using Caenorhabditis elegans nematodes to evaluate KpnU95, a bla_CTX-M-15-producing CA-UTI K. pneumoniae strain. Whole genome sequencing identified KpnU95 as sequence type 1412 and revealed the chromosomal and plasmid-encoding resistome, virulome and persistence features. KpnU95 possess a wide virulome and caused complete C. elegans killing. The strain harbored a single novel 180.3Kb IncFIB(K) plasmid (pKpnU95), which encodes ten antibiotic resistance genes, including bla_CTX-M-15 and qnrS1 alongside a wide persistome encoding heavy metal and UV resistance. Plasmid curing and reconstitution were used for loss and gain studies to evaluate its role on bacterial resistance, fitness and virulence. Plasmid curing abolished the ESBL phenotype, decreased ciprofloxacin MIC and improved bacterial fitness in artificial urine accompanied with enhanced copper tolerance, without affecting bacterial virulence. Meta-analysis supported the uniqueness of pKpnU95 and revealed plasmid-ST1412 lineage adaptation. Overall, our findings provide translational data on a CA-UTI K. pneumoniae ST1412 strain and demonstrates that ESBL-encoding plasmids play key roles in multidrug resistance and in bacterial fitness and persistence.

Genomes of Gut Bacteria from Nasonia Wasps Shed Light on Phylosymbiosis and Microbe-Assisted Hybrid Breakdown

Phylosymbiosis is a cross-system trend whereby microbial community relationships recapitulate the host phylogeny. In Nasonia parasitoid wasps, phylosymbiosis occurs throughout development, is distinguishable between sexes, and benefits host development and survival. Moreover, the microbiome shifts in hybrids as a rare Proteus bacterium in the microbiome becomes dominant. The larval hybrids then catastrophically succumb to bacterium-assisted lethality and reproductive isolation between the species. Two important questions for understanding phylosymbiosis and bacterium-assisted lethality in hybrids are (i) do the Nasonia bacterial genomes differ from other animal isolates and (ii) are the hybrid bacterial genomes the same as those in the parental species? Here, we report the cultivation, whole-genome sequencing, and comparative analyses of the most abundant gut bacteria in Nasonia larvae, Providencia rettgeri and Proteus mirabilis. Characterization of new isolates shows Proteus mirabilis forms a more robust biofilm than Providencia rettgeri and that, when grown in coculture, Proteus mirabilis significantly outcompetes Providencia rettgeri. Providencia rettgeri genomes from Nasonia are similar to each other and more divergent from pathogenic, human associates. Proteus mirabilis from Nasonia vitripennis, Nasonia giraulti, and their hybrid offspring are nearly identical and relatively distinct from human isolates. These results indicate that members of the larval gut microbiome within Nasonia are most similar to each other, and the strain of the dominant Proteus mirabilis in hybrids is resident in parental species. Holobiont interactions between shared, resident members of the wasp microbiome and the host underpin phylosymbiosis and hybrid breakdown.

IMPORTANCE Animal and plant hosts often establish intimate relationships with their microbiomes. In varied environments, closely related host species share more similar microbiomes, a pattern termed phylosymbiosis. When phylosymbiosis is functionally significant and beneficial, microbial transplants between host species and host hybridization can have detrimental consequences on host biology. In the Nasonia parasitoid wasp genus, which contains a phylosymbiotic gut community, both effects occur and provide evidence for selective pressures on the holobiont. Here, we show that bacterial genomes in Nasonia differ from other environments and harbor genes with unique functions that may regulate phylosymbiotic relationships. Furthermore, the bacteria in hybrids are identical to those in parental species, thus supporting a hologenomic tenet that the same members of the microbiome and the host genome impact phylosymbiosis, hybrid breakdown, and speciation.

Recommendations for the introduction of metagenomic next-generation sequencing in clinical virology, part II: bioinformatic analysis and reporting

Metagenomic next-generation sequencing (mNGS) is an untargeted technique for determination of microbial DNA/RNA sequences in a variety of sample types from patients with infectious syndromes. mNGS is still in its early stages of broader translation into clinical applications. To further support the development, implementation, optimization and standardization of mNGS procedures for virus diagnostics, the European Society for Clinical Virology (ESCV) Network on Next-Generation Sequencing (ENNGS) has been established. The aim of ENNGS is to bring together professionals involved in mNGS for viral diagnostics to share methodologies and experiences, and to develop application guidelines. Following the ENNGS publication Recommendations for the introduction of mNGS in clinical virology, part I: wet lab procedure in this journal, the current manuscript aims to provide practical recommendations for the bioinformatic analysis of mNGS data and reporting of results to clinicians.

An integrated approach to determine the abundance, mutation rate and phylogeny of the SARS-CoV-2 genome

The analysis of the SARS-CoV-2 genome datasets has significantly advanced our understanding of the biology and genomic adaptability of the virus. However, the plurality of advanced sequencing datasets-such as short and long reads-presents a formidable computational challenge to uniformly perform quantitative, variant or phylogenetic analysis, thus limiting its application in public health laboratories engaged in studying epidemic outbreaks. We present a computational tool, Infectious Pathogen Detector (IPD), to perform integrated analysis of diverse genomic datasets, with a customized analytical module for the SARS-CoV-2 virus. The IPD pipeline quantitates individual occurrences of 1060 pathogens and performs mutation and phylogenetic analysis from heterogeneous sequencing datasets. Using IPD, we demonstrate a varying burden (5.055-999655.7 fragments per million) of SARS-CoV-2 transcripts across 1500 short- and long-read sequencing SARS-CoV-2 datasets and identify 4634 SARS-CoV-2 variants (~3.05 variants per sample), including 449 novel variants, across the genome with distinct hotspot mutations in the ORF1ab and S genes along with their phylogenetic relationships establishing the utility of IPD in tracing the genome isolates from the genomic data (as accessed on 11 June 2020). The IPD predicts the occurrence and dynamics of variability among infectious pathogens-with a potential for direct utility in the COVID-19 pandemic and beyond to help automate the sequencing-based pathogen analysis and in responding to public health threats, efficaciously. A graphical user interface (GUI)-enabled desktop application is freely available for download for the academic users at http://www.actrec.gov.in/pi-webpages/AmitDutt/IPD/IPD.html and for web-based processing at http://ipd.actrec.gov.in/ipdweb/ to generate an automated report without any prior computational know-how.

A computational toolset for rapid identification of SARS-CoV-2, other viruses and microorganisms from sequencing data

In this paper, we present a toolset and related resources for rapid identification of viruses and microorganisms from short-read or long-read sequencing data. We present fastv as an ultra-fast tool to detect microbial sequences present in sequencing data, identify target microorganisms and visualize coverage of microbial genomes. This tool is based on the k-mer mapping and extension method. K-mer sets are generated by UniqueKMER, another tool provided in this toolset. UniqueKMER can generate complete sets of unique k-mers for each genome within a large set of viral or microbial genomes. For convenience, unique k-mers for microorganisms and common viruses that afflict humans have been generated and are provided with the tools. As a lightweight tool, fastv accepts FASTQ data as input and directly outputs the results in both HTML and JSON formats. Prior to the k-mer analysis, fastv automatically performs adapter trimming, quality pruning, base correction and other preprocessing to ensure the accuracy of k-mer analysis. Specifically, fastv provides built-in support for rapid severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) identification and typing. Experimental results showed that fastv achieved 100% sensitivity and 100% specificity for detecting SARS-CoV-2 from sequencing data; and can distinguish SARS-CoV-2 from SARS, Middle East respiratory syndrome and other coronaviruses. This toolset is available at: https://github.com/OpenGene/fastv.

Genomics of an endemic cystic fibrosis Burkholderia multivorans strain reveals low within-patient evolution but high between-patient diversity

Burkholderia multivorans is a member of the Burkholderia cepacia complex (Bcc), notorious for its pathogenicity in persons with cystic fibrosis. Epidemiological surveillance suggests that patients predominantly acquire B. multivorans from environmental sources, with rare cases of patient-to-patient transmission. Here we report on the genomic analysis of thirteen isolates from an endemic B. multivorans strain infecting four cystic fibrosis patients treated in different pediatric cystic fibrosis centers in Belgium, with no evidence of cross-infection. All isolates share an identical sequence type (ST-742) but whole genome analysis shows that they exhibit peculiar patterns of genomic diversity between patients. By combining short and long reads sequencing technologies, we highlight key differences in terms of small nucleotide polymorphisms indicative of low rates of adaptive evolution within patient, and well-defined, hundred kbps-long segments of high enrichment in mutations between patients. In addition, we observed large structural genomic variations amongst the isolates which revealed different plasmid contents, active roles for transposase IS3 and IS5 in the deactivation of genes, and mobile prophage elements. Our study shows limited within-patient B. multivorans evolution and high between-patient strain diversity, indicating that an environmental microdiverse reservoir must be present for this endemic strain, in which active diversification is taking place. Furthermore, our analysis also reveals a set of 30 parallel adaptations across multiple patients, indicating that the specific genomic background of a given strain may dictate the route of adaptation within the cystic fibrosis lung.

A roadmap for the generation of benchmarking resources for antimicrobial resistance detection using next generation sequencing

Next Generation Sequencing technologies significantly impact the field of Antimicrobial Resistance (AMR) detection and monitoring, with immediate uses in diagnosis and risk assessment. For this application and in general, considerable challenges remain in demonstrating sufficient trust to act upon the meaningful information produced from raw data, partly because of the reliance on bioinformatics pipelines, which can produce different results and therefore lead to different interpretations. With the constant evolution of the field, it is difficult to identify, harmonise and recommend specific methods for large-scale implementations over time. In this article, we propose to address this challenge through establishing a transparent, performance-based, evaluation approach to provide flexibility in the bioinformatics tools of choice, while demonstrating proficiency in meeting common performance standards. The approach is two-fold: first, a community-driven effort to establish and maintain “live” (dynamic) benchmarking platforms to provide relevant performance metrics, based on different use-cases, that would evolve together with the AMR field; second, agreed and defined datasets to allow the pipelines’ implementation, validation, and quality-control over time. Following previous discussions on the main challenges linked to this approach, we provide concrete recommendations and future steps, related to different aspects of the design of benchmarks, such as the selection and the characteristics of the datasets (quality, choice of pathogens and resistances, etc.), the evaluation criteria of the pipelines, and the way these resources should be deployed in the community.

High-Throughput Metagenomics for Identification of Pathogens in the Clinical Settings

The application of sequencing technology is shifting from research to clinical laboratories owing to rapid technological developments and substantially reduced costs. However, although thousands of microorganisms are known to infect humans, identification of the etiological agents for many diseases remains challenging as only a small proportion of pathogens are identifiable by the current diagnostic methods. These challenges are compounded by the emergence of new pathogens. Hence, metagenomic next-generation sequencing (mNGS), an agnostic, unbiased, and comprehensive method for detection, and taxonomic characterization of microorganisms, has become an attractive strategy. Although many studies, and cases reports, have confirmed the success of mNGS in improving the diagnosis, treatment, and tracking of infectious diseases, several hurdles must still be overcome. It is, therefore, imperative that practitioners and clinicians understand both the benefits and limitations of mNGS when applying it to clinical practice. Interestingly, the emerging third-generation sequencing technologies may partially offset the disadvantages of mNGS. In this review, mainly: a) the history of sequencing technology; b) various NGS technologies, common platforms, and workflows for clinical applications; c) the application of NGS in pathogen identification; d) the global expert consensus on NGS-related methods in clinical applications; and e) challenges associated with diagnostic metagenomics are described.

Modern diagnostic technologies for HIV

Novel diagnostic technologies, including nanotechnology, microfluidics, -omics science, next-generation sequencing, genomics big data, and machine learning, could contribute to meeting the UNAIDS 95-95-95 targets to end the HIV epidemic by 2030. Novel technologies include multiplexed technologies (including biomarker-based point-of-care tests and molecular platform technologies), biomarker-based combination antibody and antigen technologies, dried-blood-spot testing, and self-testing. Although biomarker-based rapid tests, in particular antibody-based tests, have dominated HIV diagnostics since the development of the first HIV test in the mid-1980s, targets such as nucleic acids and genes are now used in nanomedicine, biosensors, microfluidics, and -omics to enable early diagnosis of HIV. These novel technologies show promise as they are associated with ease of use, high diagnostic accuracy, rapid detection, and the ability to detect HIV-specific markers. Additional clinical and implementation research is needed to generate evidence for use of novel technologies and a public health approach will be required to address clinical and operational challenges to optimise their global deployment.

Genetic Diversity Among Mycobacterium avium Subspecies Revealed by Analysis of Complete Genome Sequences

Mycobacterium avium comprises four subspecies that contain both human and veterinary pathogens. At the inception of this study, twenty-eight M. avium genomes had been annotated as RefSeq genomes, facilitating direct comparisons. These genomes represent strains from around the world and provided a unique opportunity to examine genome dynamics in this species. Each genome was confirmed to be classified correctly based on SNP genotyping, nucleotide identity and presence/absence of repetitive elements or other typing methods. The Mycobacterium avium subspecies paratuberculosis (Map) genome size and organization was remarkably consistent, averaging 4.8 Mb with a variance of only 29.6 kb among the 13 strains. Comparing recombination events along with the larger genome size and variance observed among Mycobacterium avium subspecies avium (Maa) and Mycobacterium avium subspecies hominissuis (Mah) strains (collectively termed non-Map) suggests horizontal gene transfer occurs in non-Map, but not in Map strains. Overall, M. avium subspecies could be divided into two major sub-divisions, with the Map type II (bovine strains) clustering tightly on one end of a phylogenetic spectrum and Mah strains clustering more loosely together on the other end. The most evolutionarily distinct Map strain was an ovine strain, designated Telford, which had >1,000 SNPs and showed large rearrangements compared to the bovine type II strains. The Telford strain clustered with Maa strains as an intermediate between Map type II and Mah. SNP analysis and genome organization analyses repeatedly demonstrated the conserved nature of Map versus the mosaic nature of non-Map M. avium strains. Finally, core and pangenomes were developed for Map and non-Map strains. A total of 80% Map genes belonged to the Map core genome, while only 40% of non-Map genes belonged to the non-Map core genome. These genomes provide a more complete and detailed comparison of these subspecies strains as well as a blueprint for how genetic diversity originated.

Bactopia: a Flexible Pipeline for Complete Analysis of Bacterial Genomes

Sequencing of bacterial genomes using Illumina technology has become such a standard procedure that often data are generated faster than can be conveniently analyzed. We created a new series of pipelines called Bactopia, built using Nextflow workflow software, to provide efficient comparative genomic analyses for bacterial species or genera. Bactopia consists of a data set setup step (Bactopia Data Sets [BaDs]), which creates a series of customizable data sets for the species of interest, the Bactopia Analysis Pipeline (BaAP), which performs quality control, genome assembly, and several other functions based on the available data sets and outputs the processed data to a structured directory format, and a series of Bactopia Tools (BaTs) that perform specific postprocessing on some or all of the processed data. BaTs include pan-genome analysis, computing average nucleotide identity between samples, extracting and profiling the 16S genes, and taxonomic classification using highly conserved genes. It is expected that the number of BaTs will increase to fill specific applications in the future. As a demonstration, we performed an analysis of 1,664 public Lactobacillus genomes, focusing on Lactobacillus crispatus, a species that is a common part of the human vaginal microbiome. Bactopia is an open source system that can scale from projects as small as one bacterial genome to ones including thousands of genomes and that allows for great flexibility in choosing comparison data sets and options for downstream analysis. Bactopia code can be accessed at https://www.github.com/bactopia/bactopiaIMPORTANCE It is now relatively easy to obtain a high-quality draft genome sequence of a bacterium, but bioinformatic analysis requires organization and optimization of multiple open source software tools. We present Bactopia, a pipeline for bacterial genome analysis, as an option for processing bacterial genome data. Bactopia also automates downloading of data from multiple public sources and species-specific customization. Because the pipeline is written in the Nextflow language, analyses can be scaled from individual genomes on a local computer to thousands of genomes using cloud resources. As a usage example, we processed 1,664 Lactobacillus genomes from public sources and used comparative analysis workflows (Bactopia Tools) to identify and analyze members of the L. crispatus species.

Metagenomics for neurological infections - expanding our imagination

Over the past two decades, the diagnosis rate for patients with encephalitis has remained poor despite advances in pathogen-specific testing such as PCR and antigen assays. Metagenomic next-generation sequencing (mNGS) of RNA and DNA extracted from cerebrospinal fluid and brain tissue now offers another strategy for diagnosing neurological infections. Given that mNGS simultaneously assays for a wide range of infectious agents in an unbiased manner, it can identify pathogens that were not part of a neurologist’s initial differential diagnosis either because of the rarity of the infection, because the microorganism has not been previously associated with a clinical phenotype or because it is a newly discovered organism. This Review discusses the technical advantages and pitfalls of cerebrospinal fluid mNGS in the context of patients with neuroinflammatory syndromes, including encephalitis, meningitis and myelitis. We also speculate on how mNGS testing potentially fits into current diagnostic testing algorithms given data on mNGS test performance, cost and turnaround time. Finally, the Review highlights future directions for mNGS technology and other hypothesis-free testing methodologies that are in development.

This Review discusses the advantages and pitfalls of metagenomic next-generation sequencing (mNGS) in patients with encephalitis, meningitis and myelitis. The authors outline data on mNGS test performance, cost and turnaround time and highlight future directions for mNGS technology.

Meningoencephalitis remains a challenging diagnosis owing to the multitude of possible infectious and autoimmune causes.

Meningoencephalitis is associated with a high rate of morbidity and mortality and requires prompt diagnosis and treatment.

Metagenomic next-generation sequencing (mNGS) is now a clinically validated test for neuroinfectious diseases that can aid clinicians with a timely diagnosis.

mNGS can improve the detection of pathogens that were missed by clinicians or on standard direct testing.

mNGS does not perform well when indirect tests are required to make the diagnosis (for example, serology), when infections are compartmentalized and for certain low abundance pathogens.

The clinical context of the case is required when interpreting the results of mNGS.

Complete genome sequence of a methicillin-resistant Staphylococcus lugdunensis strain and characteristics of its staphylococcal cassette chromosome mec

Symptoms of Staphylococcus lugdunensis infection are often similar to those of Staphylococcus aureus infection, including skin and soft-tissue lesions, bacteremia and infective endocarditis. Despite the severity of these infections, S. lugdunensis is regarded as a less important pathogen than drug-resistant S. aureus. To investigate its ability to cause infectious diseases, a methicillin-resistant S. lugdunensis (MRSL) strain JICS135 was isolated from a patient with bacteremia and subjected to whole genome sequencing. Similar to most strains of methicillin-resistant S. aureus (MRSA), this MRSL strain possessed the staphylococcal cassette chromosome mec (SCCmec) located close to the origin of replication. However, the SCCmec in this MRSL strain, with three ccr complexes, was structurally unique and currently untypable. Moreover, the SCCmec of this MRSL strain was found to carry two genes encoding microbial surface components recognizing adhesive matrix molecules (MSCRAMM)-like proteins accompanied by glycosyl transferases, one of which may have been derived from S. aureus and the other from S. epidermidis, indicating that this MRSL evolved to carry virulence factors from other staphylococci. The emergence of this strain, the first MRSL strain whose genome has been sequenced completely, may be of public concern.

Insights on early mutational events in SARS-CoV-2 virus reveal founder effects across geographical regions

Here we aim to describe early mutational events across samples from publicly available SARS-CoV-2 sequences from the sequence read archive and GenBank repositories. Up until 27 March 2020, we downloaded 50 illumina datasets, mostly from China, USA (WA State) and Australia (VIC). A total of 30 datasets (60%) contain at least a single founder mutation and most of the variants are missense (over 63%). Five-point mutations with clonal (founder) effect were found in USA next-generation sequencing samples. Sequencing samples from North America in GenBank (22 April 2020) present this signature with up to 39% allele frequencies among samples (n = 1,359). Australian variant signatures were more diverse than USA samples, but still, clonal events were found in these samples. Mutations in the helicase, encoded by the ORF1ab gene in SARS-CoV-2 were predominant, among others, suggesting that these regions are actively evolving. Finally, we firmly urge that primer sets for diagnosis be carefully designed, since rapidly occurring variants would affect the performance of the reverse transcribed quantitative PCR (RT-qPCR) based viral testing.

Terminating contamination: large-scale search identifies more than 2,000,000 contaminated entries in GenBank

Genomic analyses are sensitive to contamination in public databases caused by incorrectly labeled reference sequences. Here, we describe Conterminator, an efficient method to detect and remove incorrectly labeled sequences by an exhaustive all-against-all sequence comparison. Our analysis reports contamination of 2,161,746, 114,035, and 14,148 sequences in the RefSeq, GenBank, and NR databases, respectively, spanning the whole range from draft to “complete” model organism genomes. Our method scales linearly with input size and can process 3.3 TB in 12 days on a 32-core computer. Conterminator can help ensure the quality of reference databases. Source code (GPLv3): https://github.com/martin-steinegger/conterminator

prewas: data pre-processing for more informative bacterial GWAS

While variant identification pipelines are becoming increasingly standardized, less attention has been paid to the pre-processing of variants prior to their use in bacterial genome-wide association studies (bGWAS). Three nuances of variant pre-processing that impact downstream identification of genetic associations include the separation of variants at multiallelic sites, separation of variants in overlapping genes, and referencing of variants relative to ancestral alleles. Here we demonstrate the importance of these variant pre-processing steps on diverse bacterial genomic datasets and present prewas, an R package, that standardizes the pre-processing of multiallelic sites, overlapping genes, and reference alleles before bGWAS. This package facilitates improved reproducibility and interpretability of bGWAS results. prewas enables users to extract maximal information from bGWAS by implementing multi-line representation for multiallelic sites and variants in overlapping genes. prewas outputs a binary SNP matrix that can be used for SNP-based bGWAS and will prevent the masking of minor alleles during bGWAS analysis. The optional binary gene matrix output can be used for gene-based bGWAS, which will enable users to maximize the power and evolutionary interpretability of their bGWAS studies. prewas is available for download from GitHub.

Liquid biopsy for infectious diseases: a focus on microbial cell-free DNA sequencing

Metagenomic next-generation sequencing (mNGS) of microbial cell-free DNA (mcfDNA sequencing) is becoming an attractive diagnostic modality for infectious diseases, allowing broad-range pathogen detection, noninvasive sampling, and rapid diagnosis. At this key juncture in the translation of metagenomics into clinical practice, an integrative perspective is needed to understand the significance of emerging mcfDNA sequencing technology. In this review, we summarized the actual performance of the mcfDNA sequencing tests recently used in health care settings for the diagnosis of a variety of infectious diseases and further focused on the practice considerations (challenges and solutions) for improving the accuracy and clinical relevance of the results produced by this evolving technique. Such knowledge will be helpful for physicians, microbiologists and researchers to understand what is going on in this quickly progressing field of non-invasive pathogen diagnosis by mcfDNA sequencing and promote the routine implementation of this technique in the diagnosis of infectious disease.

Point-Counterpoint: Should We Be Performing Metagenomic Next-Generation Sequencing for Infectious Disease Diagnosis in the Clinical Laboratory?

INTRODUCTIONWith established applications of next-generation sequencing in inherited diseases and oncology, clinical laboratories are evaluating the use of metagenomics for identification of infectious agents directly from patient samples, to aid in the diagnosis of infections. Metagenomic next-generation sequencing for infectious diseases promises an unbiased approach to detection of microbes that does not depend on growth in culture or the targeting of specific pathogens. However, the issues of contamination, interpretation of results, selection of databases used for analysis, and prediction of antimicrobial susceptibilities from sequencing data remain challenges. In this Point-Counterpoint, Steve Miller and Charles Chiu discuss the pros of using direct metagenomic sequencing, while Kyle Rodino and Melissa Miller argue for the use of caution.

Clinical metagenomics for infectious corneal ulcers: Rags to riches?

The emergence of clinical metagenomics as an unbiased, hypothesis-free approach to diagnostic testing is set to fundamentally alter the way infectious diseases are detected. Long envisioned as the solution to the limitations of culture-based conventional microbiology, next generation sequencing methods will soon mature, and our attention will inevitably turn to how they can be applied to areas of medicine which need it most urgently. In ophthalmology, the demand for this technology is particularly pressing for the care of infectious corneal ulcers, where current diagnostic tests may fail to identify a causative organism in over half of cases. However, the optimism found in the budding discourse surrounding clinical metagenomics belies the reality that clinicians and scientists will soon be inundated by oppressive volumes of sequencing data, much of which will be foreign and unfamiliar. Therefore, our success in translating clinical metagenomics is likely to hinge on how we make sense of these data, and understanding its implications for the interpretation and implementation of sequencing into routine clinical care. In this consortium-led review, we provide an outline of these data-related issues and how they may be used to inform technical workflows, with the hope that we may edge closer to realizing the potential of clinical metagenomics for this important unmet need.

Third-Generation Sequencing in the Clinical Laboratory: Exploring the Advantages and Challenges of Nanopore Sequencing

Metagenomic sequencing for infectious disease diagnostics is an important tool that holds promise for use in the clinical laboratory. Challenges for implementation so far include high cost, the length of time to results, and the need for technical and bioinformatics expertise. However, the recent technological innovation of nanopore sequencing from Oxford Nanopore Technologies (ONT) has the potential to address these challenges. ONT sequencing is an attractive platform for clinical laboratories to adopt due to its low cost, rapid turnaround time, and user-friendly bioinformatics pipelines. However, this method still faces the problem of base-calling accuracy compared to other platforms. This review highlights the general challenges of pathogen detection in clinical specimens by metagenomic sequencing, the advantages and disadvantages of the ONT platform, and how research to date supports the potential future use of nanopore sequencing in infectious disease diagnostics.