Bayesian mixture analysis for metagenomic community profiling

Evaluating metagenomics and targeted approaches for diagnosis and surveillance of viruses

BACKGROUND

Metagenomics is a powerful approach for the detection of unknown and novel pathogens. Workflows based on Illumina short-read sequencing are becoming established in diagnostic laboratories. However, high sequencing depth requirements, long turnaround times, and limited sensitivity hinder broader adoption. We investigated whether we could overcome these limitations using protocols based on untargeted sequencing with Oxford Nanopore Technologies (ONT), which offers real-time data acquisition and analysis, or a targeted panel approach, which allows the selective sequencing of known pathogens and could improve sensitivity.

METHODS

We evaluated detection of viruses with readily available untargeted metagenomic workflows using Illumina and ONT, and an Illumina-based enrichment approach using the Twist Bioscience Comprehensive Viral Research Panel (CVRP), which targets 3153 viruses. We tested samples consisting of a dilution series of a six-virus mock community in a human DNA/RNA background, designed to resemble clinical specimens with low microbial abundance and high host content. Protocols were designed to retain the host transcriptome, since this could help confirm the absence of infectious agents. We further compared the performance of commonly used taxonomic classifiers.

RESULTS

Capture with the Twist CVRP increased sensitivity by at least 10-100-fold over untargeted sequencing, making it suitable for the detection of low viral loads (60 genome copies per ml (gc/ml)), but additional methods may be needed in a diagnostic setting to detect untargeted organisms. While untargeted ONT had good sensitivity at high viral loads (60,000 gc/ml), at lower viral loads (600-6000 gc/ml), longer and more costly sequencing runs would be required to achieve sensitivities comparable to the untargeted Illumina protocol. Untargeted ONT provided better specificity than untargeted Illumina sequencing. However, the application of robust thresholds standardized results between taxonomic classifiers. Host gene expression analysis is optimal with untargeted Illumina sequencing but possible with both the CVRP and ONT.

CONCLUSIONS

Metagenomics has the potential to become standard-of-care in diagnostics and is a powerful tool for the discovery of emerging pathogens. Untargeted Illumina and ONT metagenomics and capture with the Twist CVRP have different advantages with respect to sensitivity, specificity, turnaround time and cost, and the optimal method will depend on the clinical context.

Untargeted metagenomics protocol for the diagnosis of infection from CSF and tissue from sterile sites

Metagenomic next-generation sequencing (mNGS) is an untargeted technique capable of detecting all microbial nucleic acid within a sample. This protocol outlines our wet laboratory method for mNGS of cerebrospinal fluid (CSF) specimens and tissues from sterile sites. We use this method routinely in our clinical service, processing 178 specimens over the past 2.5 years in a laboratory that adheres to ISO:15189 standards. We have successfully used this protocol to diagnose multiple cases of encephalitis and hepatitis.

Metagenomic profiling pipelines improve taxonomic classification for 16S amplicon sequencing data

Most experiments studying bacterial microbiomes rely on the PCR amplification of all or part of the gene for the 16S rRNA subunit, which serves as a biomarker for identifying and quantifying the various taxa present in a microbiome sample. Several computational methods exist for analyzing 16S amplicon sequencing. However, the most-used bioinformatics tools cannot produce high quality genus-level or species-level taxonomic calls and may underestimate the potential accuracy of these calls. We used 16S sequencing data from mock bacterial communities to evaluate the sensitivity and specificity of several bioinformatics pipelines and genomic reference libraries used for microbiome analyses, concentrating on measuring the accuracy of species-level taxonomic assignments of 16S amplicon reads. We evaluated the tools DADA2, QIIME 2, Mothur, PathoScope 2, and Kraken 2 in conjunction with reference libraries from Greengenes, SILVA, Kraken 2, and RefSeq. Profiling tools were compared using publicly available mock community data from several sources, comprising 136 samples with varied species richness and evenness, several different amplified regions within the 16S rRNA gene, and both DNA spike-ins and cDNA from collections of plated cells. PathoScope 2 and Kraken 2, both tools designed for whole-genome metagenomics, outperformed DADA2, QIIME 2 using the DADA2 plugin, and Mothur, which are theoretically specialized for 16S analyses. Evaluations of reference libraries identified the SILVA and RefSeq/Kraken 2 Standard libraries as superior in accuracy compared to Greengenes. These findings support PathoScope and Kraken 2 as fully capable, competitive options for genus- and species-level 16S amplicon sequencing data analysis, whole genome sequencing, and metagenomics data tools.

Report of the third conference on next-generation sequencing for adventitious virus detection in biologics for humans and animals

Next-generation sequencing (NGS) has been proven to address some of the limitations of the current testing methods for adventitious virus detection in biologics. The International Alliance for Biological Standardization (IABS), the U.S. Food and Drug Administration (FDA), and the European Directorate for the Quality of Medicines and Healthcare (EDQM) co-organized the "3rd Conference on Next-generation Sequencing for Adventitious Virus Detection in Biologics for Humans and Animals", which was held on September 27-28, 2022, in Rockville, Maryland, U.S.A. The meeting gathered international representatives from regulatory and public health authorities and other government agencies, industry, contract research organizations, and academia to present the current status of NGS applications and the progress on NGS standardization and validation for detection of viral adventitious agents in biologics, including human and animal vaccines, gene therapies, and biotherapeutics. Current regulatory expectations were discussed for developing a scientific consensus regarding using NGS for detection of adventitious viruses. Although there are ongoing improvements in the NGS workflow, the development of reference materials for facilitating method qualification and validation support the current use of NGS for adventitious virus detection.

Genomic investigations of unexplained acute hepatitis in children

Since its first identification in Scotland, over 1,000 cases of unexplained paediatric hepatitis in children have been reported worldwide, including 278 cases in the UK1. Here we report an investigation of 38 cases, 66 age-matched immunocompetent controls and 21 immunocompromised comparator participants, using a combination of genomic, transcriptomic, proteomic and immunohistochemical methods. We detected high levels of adeno-associated virus 2 (AAV2) DNA in the liver, blood, plasma or stool from 27 of 28 cases. We found low levels of adenovirus (HAdV) and human herpesvirus 6B (HHV-6B) in 23 of 31 and 16 of 23, respectively, of the cases tested. By contrast, AAV2 was infrequently detected and at low titre in the blood or the liver from control children with HAdV, even when profoundly immunosuppressed. AAV2, HAdV and HHV-6 phylogeny excluded the emergence of novel strains in cases. Histological analyses of explanted livers showed enrichment for T cells and B lineage cells. Proteomic comparison of liver tissue from cases and healthy controls identified increased expression of HLA class 2, immunoglobulin variable regions and complement proteins. HAdV and AAV2 proteins were not detected in the livers. Instead, we identified AAV2 DNA complexes reflecting both HAdV-mediated and HHV-6B-mediated replication. We hypothesize that high levels of abnormal AAV2 replication products aided by HAdV and, in severe cases, HHV-6B may have triggered immune-mediated hepatic disease in genetically and immunologically predisposed children.

An Adagio for Viruses, Played Out on Ancient DNA

Studies of ancient DNA have transformed our understanding of human evolution. Paleogenomics can also reveal historic and prehistoric agents of disease, including endemic, epidemic, and pandemic pathogens. Viruses-and in particular those with single- or double-stranded DNA genomes-are an important part of the paleogenomic revolution, preserving within some remains or environmental samples for tens of thousands of years. The results of these studies capture the public imagination, as well as giving scientists a unique perspective on some of the more slowly evolving viruses which cause disease. In this review, we revisit the first studies of historical virus genetic material in the 1990s, through to the genomic revolution of recent years. We look at how paleogenomics works for viral pathogens, such as the need for careful precautions against modern contamination and robust computational pipelines to identify and analyze authenticated viral sequences. We discuss the insights into virus evolution which have been gained through paleogenomics, concentrating on three DNA viruses in particular: parvovirus B19, herpes simplex virus 1, and smallpox. As we consider recent worldwide transmission of monkeypox and synthetic biology tools that allow the potential reconstruction of extinct viruses, we show that studying historical and ancient virus evolution has never been more topical.

Viral metagenomic sequencing in the diagnosis of meningoencephalitis: a review of technical advances and diagnostic yield

INTRODUCTION

Meningoencephalitis patients are often severely impaired and benefit from early etiological diagnosis, though many cases remain without identified cause. Metagenomics as pathogen agnostic approach can result in additional etiological findings; however, the exact diagnostic yield when used as a secondary test remains unknown.

AREAS COVERED

This review aims to highlight recent advances with regard to wet and dry lab methodologies of metagenomic testing and technical milestones that have been achieved. A selection of procedures currently applied in accredited diagnostic laboratories is described in more detail to illustrate best practices. Furthermore, a meta-analysis was performed to assess the additional diagnostic yield utilizing metagenomic sequencing in meningoencephalitis patients. Finally, the remaining challenges for successful widespread implementation of metagenomic sequencing for the diagnosis of meningoencephalitis are addressed in a future perspective.

EXPERT OPINION

The last decade has shown major advances in technical possibilities for using mNGS in diagnostic settings including cloud-based analysis. An additional advance may be the current established infrastructure of platforms for bioinformatic analysis of SARS-CoV-2, which may assist to pave the way for global use of clinical metagenomics.

Metagenomic evidence for a polymicrobial signature of sepsis

Our understanding of the host component of sepsis has made significant progress. However, detailed study of the microorganisms causing sepsis, either as single pathogens or microbial assemblages, has received far less attention. Metagenomic data offer opportunities to characterize the microbial communities found in septic and healthy individuals. In this study we apply gradient-boosted tree classifiers and a novel computational decontamination technique built upon SHapley Additive exPlanations (SHAP) to identify microbial hallmarks which discriminate blood metagenomic samples of septic patients from that of healthy individuals. Classifiers had high performance when using the read assignments to microbial genera [area under the receiver operating characteristic (AUROC=0.995)], including after removal of species ‘culture-confirmed’ as the cause of sepsis through clinical testing (AUROC=0.915). Models trained on single genera were inferior to those employing a polymicrobial model and we identified multiple co-occurring bacterial genera absent from healthy controls. While prevailing diagnostic paradigms seek to identify single pathogens, our results point to the involvement of a polymicrobial community in sepsis. We demonstrate the importance of the microbial component in characterising sepsis, which may offer new biological insights into the aetiology of sepsis, and ultimately support the development of clinical diagnostic or even prognostic tools.

Benchmark of thirteen bioinformatic pipelines for metagenomic virus diagnostics using datasets from clinical samples

INTRODUCTION

Metagenomic sequencing is increasingly being used in clinical settings for difficult to diagnose cases. The performance of viral metagenomic protocols relies to a large extent on the bioinformatic analysis. In this study, the European Society for Clinical Virology (ESCV) Network on NGS (ENNGS) initiated a benchmark of metagenomic pipelines currently used in clinical virological laboratories.

METHODS

Metagenomic datasets from 13 clinical samples from patients with encephalitis or viral respiratory infections characterized by PCR were selected. The datasets were analyzed with 13 different pipelines currently used in virological diagnostic laboratories of participating ENNGS members. The pipelines and classification tools were: Centrifuge, DAMIAN, DIAMOND, DNASTAR, FEVIR, Genome Detective, Jovian, MetaMIC, MetaMix, One Codex, RIEMS, VirMet, and Taxonomer. Performance, characteristics, clinical use, and user-friendliness of these pipelines were analyzed.

RESULTS

Overall, viral pathogens with high loads were detected by all the evaluated metagenomic pipelines. In contrast, lower abundance pathogens and mixed infections were only detected by 3/13 pipelines, namely DNASTAR, FEVIR, and MetaMix. Overall sensitivity ranged from 80% (10/13) to 100% (13/13 datasets). Overall positive predictive value ranged from 71-100%. The majority of the pipelines classified sequences based on nucleotide similarity (8/13), only a minority used amino acid similarity, and 6 of the 13 pipelines assembled sequences de novo. No clear differences in performance were detected that correlated with these classification approaches. Read counts of target viruses varied between the pipelines over a range of 2-3 log, indicating differences in limit of detection.

CONCLUSION

A wide variety of viral metagenomic pipelines is currently used in the participating clinical diagnostic laboratories. Detection of low abundant viral pathogens and mixed infections remains a challenge, implicating the need for standardization and validation of metagenomic analysis for clinical diagnostic use. Future studies should address the selective effects due to the choice of different reference viral databases.

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.

Evaluation of computational methods for human microbiome analysis using simulated data

BACKGROUND

Our understanding of the composition, function, and health implications of human microbiota has been advanced by high-throughput sequencing and the development of new genomic analyses. However, trade-offs among alternative strategies for the acquisition and analysis of sequence data remain understudied.

METHODS

We assessed eight popular taxonomic profiling pipelines; MetaPhlAn2, metaMix, PathoScope 2.0, Sigma, Kraken, ConStrains, Centrifuge and Taxator-tk, against a battery of metagenomic datasets simulated from real data. The metagenomic datasets were modeled on 426 complete or permanent draft genomes stored in the Human Oral Microbiome Database and were designed to simulate various experimental conditions, both in the design of a putative experiment; read length (75-1,000 bp reads), sequence depth (100K-10M), and in metagenomic composition; number of species present (10, 100, 426), species distribution. The sensitivity and specificity of each of the pipelines under various scenarios were measured. We also estimated the relative root mean square error and average relative error to assess the abundance estimates produced by different methods. Additional datasets were generated for five of the pipelines to simulate the presence within a metagenome of an unreferenced species, closely related to other referenced species. Additional datasets were also generated in order to measure computational time on datasets of ever-increasing sequencing depth (up to 6 × 107).

RESULTS

Testing of eight pipelines against 144 simulated metagenomic datasets initially produced 1,104 discrete results. Pipelines using a marker gene strategy; MetaPhlAn2 and ConStrains, were overall less sensitive, than other pipelines; with the notable exception of Taxator-tk. This difference in sensitivity was largely made up in terms of runtime, significantly lower than more sensitive pipelines that rely on whole-genome alignments such as PathoScope2.0. However, pipelines that used strategies to speed-up alignment between genomic references and metagenomic reads, such as kmerization, were able to combine both high sensitivity and low run time, as is the case with Kraken and Centrifuge. Absent species genomes in the database mostly led to assignment of reads to the most closely related species available in all pipelines. Our results therefore suggest that taxonomic profilers that use kmerization have largely superseded those that use gene markers, coupling low run times with high sensitivity and specificity. Taxonomic profilers using more time-consuming read reassignment, such as PathoScope 2.0, provided the most sensitive profiles under common metagenomic sequencing scenarios. All the results described and discussed in this paper can be visualized using the dedicated R Shiny application (https://github.com/microgenomics/HumanMicrobiomeAnalysis). All of our datasets, pipelines and results are made available through the GitHub repository for future benchmarking.

Advances in molecular diagnostic testing for central nervous system infections

PURPOSE OF REVIEW

Central nervous system (CNS) infections present an ongoing diagnostic challenge for clinicians, with an aetiological agent remaining unidentified in the majority of cases even in high-income settings. This review summarizes developments in a range of diagnostic methods published in the past 18 months.

RECENT FINDINGS

Several commercial assays exist for the detection of viral, bacterial and fungal pathogens using single multiplex PCR. Multicentre validation of the Biofire FilmArray panel illustrated high sensitivity for bacterial and fungal pathogens, but poor results for Cryptococcus species detection. The development of microarray cards for bacterial CNS pathogens shows promise but requires further validation. Few developments have been made in proteomics and transcriptomics, contrasted with significant increase in the use of metagenomic (or unbiased) sequencing. Novel viruses causing CNS infection have been described using this technique but contamination, cost, expertise and turnaround time requirements remain restrictive. Finally, the development of Gene Xpert and Ultra has revolutionized tuberculosis meningitis diagnostics with newly released recommendations for their use from the WHO.

SUMMARY

Progress has been made in the clinical validation and international recommendation of PCR-based tests for CNS infections. Sequencing techniques present the most dynamic field, although significant ongoing challenges persist.

Metagenomic analysis of a blood stain from the French revolutionary Jean-Paul Marat (1743-1793)

The French revolutionary Jean-Paul Marat (1743-1793) was assassinated in 1793 in his bathtub, where he was trying to find relief from the debilitating skin disease he was suffering from. At the time of his death, Marat was annotating newspapers, which got stained with his blood and were subsequently preserved by his sister. We extracted and sequenced DNA from the blood stain and also from another section of the newspaper, which we used for comparison. Results from the human DNA sequence analyses were compatible with a heterogeneous ancestry of Marat, with his mother being of French origin and his father born in Sardinia. Metagenomic analyses of the non-human reads uncovered the presence of fungal, bacterial and low levels of viral DNA. Relying on the presence/absence of microbial species in the samples, we could cast doubt on several putative infectious agents that have been previously hypothesised as the cause of his condition but for which we detect not a single sequencing read. Conversely, some of the species we detect are uncommon as environmental contaminants and may represent plausible infective agents. Based on all the available evidence, we hypothesize that Marat may have suffered from a fungal infection (seborrheic dermatitis), possibly superinfected with bacterial opportunistic pathogens.

DAMIAN: an open source bioinformatics tool for fast, systematic and cohort based analysis of microorganisms in diagnostic samples

We describe DAMIAN, an open source bioinformatics tool designed for the identification of pathogenic microorganisms in diagnostic samples. By using authentic clinical samples and comparing our results to those from established analysis pipelines as well as conventional diagnostics, we demonstrate that DAMIAN rapidly identifies pathogens in different diagnostic entities, and accurately classifies viral agents down to the strain level. We furthermore show that DAMIAN is able to assemble full-length viral genomes even in samples co-infected with multiple virus strains, an ability which is of considerable advantage for the investigation of outbreak scenarios. While DAMIAN, similar to other pipelines, analyzes single samples to perform classification of sequences according to their likely taxonomic origin, it also includes a tool for cohort-based analysis. This tool uses cross-sample comparisons to identify sequence signatures that are frequently present in a sample group of interest (e.g., a disease-associated cohort), but occur less frequently in control cohorts. As this approach does not require homology searches in databases, it principally allows the identification of not only known, but also completely novel pathogens. Using samples from a meningitis outbreak, we demonstrate the feasibility of this approach in identifying enterovirus as the causative agent.

CoreProbe: A Novel Algorithm for Estimating Relative Abundance Based on Metagenomic Reads

With the rapid development of high-throughput sequencing technology, the analysis of metagenomic sequencing data and the accurate and efficient estimation of relative microbial abundance have become important ways to explore the microbial composition and function of microbes. In addition, the accuracy and efficiency of the relative microbial abundance estimation are closely related to the algorithm and the selection of the reference sequence for sequence alignment. We introduced the microbial core genome as the reference sequence for potential microbes in a metagenomic sample, and we constructed a finite mixture and latent Dirichlet models and used the Gibbs sampling algorithm to estimate the relative abundance of microorganisms. The simulation results showed that our approach can improve the efficiency while maintaining high accuracy and is more suitable for high-throughput metagenomic data. The new approach was implemented in our CoreProbe package which provides a pipeline for an accurate and efficient estimation of the relative abundance of microbes in a community. This tool is available free of charge from the CoreProbe's website: Access the Docker image with the following instruction: sudo docker pull panhongfei/coreprobe:1.0.

Encephalitis diagnosis using metagenomics: application of next generation sequencing for undiagnosed cases

BACKGROUND

Current estimates suggest that even in the most resourced settings, the aetiology of encephalitis is identified in less than half of clinical cases. It is acknowledged that filling this gap needs a combination of rigorous sampling and improved diagnostic technologies. Next generation sequencing (NGS) methods are powerful tools with the potential for comprehensive and unbiased detection of pathogens in clinical samples. We reviewed the use of this new technology for the diagnosis of suspected infectious encephalitis, and discuss the feasibility for introduction of NGS methods as a frontline diagnostic test.

METHODS

A systematic literature review was performed, using MESH and text word searches for variants of "sequencing" and "encephalitis" in Medline and EMbase, and searching bibliographies and citations using the Web of Science database. Two authors independently reviewed, extracted and summarised data.

FINDINGS

The review identified 25 articles reporting 44 case reports of patients with suspected encephalitis for whom NGS was used as a diagnostic tool. We present the data and highlight themes arising from these cases. There are no randomly controlled trials to assess the utility of NGS as a diagnostic tool.

INTERPRETATION

There is increasing evidence of a role for NGS in the work-up of undiagnosed encephalitis. Lower costs and increasing accessibility of these technologies will facilitate larger studies of these patients. We recommend NGS should be considered as a front-line diagnostic test in chronic and recurring presentations and, given current sample-to-result turn-around times, as second-line in acute cases of encephalitis.

Deep sequencing reveals persistence of cell-associated mumps vaccine virus in chronic encephalitis

Routine childhood vaccination against measles, mumps and rubella has virtually abolished virus-related morbidity and mortality. Notwithstanding this, we describe here devastating neurological complications associated with the detection of live-attenuated mumps virus Jeryl Lynn (MuV^JL5) in the brain of a child who had undergone successful allogeneic transplantation for severe combined immunodeficiency (SCID). This is the first confirmed report of MuV^JL5 associated with chronic encephalitis and highlights the need to exclude immunodeficient individuals from immunisation with live-attenuated vaccines. The diagnosis was only possible by deep sequencing of the brain biopsy. Sequence comparison of the vaccine batch to the MuV^JL5 isolated from brain identified biased hypermutation, particularly in the matrix gene, similar to those found in measles from cases of SSPE. The findings provide unique insights into the pathogenesis of paramyxovirus brain infections.

An emerging opportunistic infection: fatal astrovirus (VA1/HMO-C) encephalitis in a pediatric stem cell transplant recipient

Neuroinvasive astrovirus (VA1-HMO-C) is an emerging life-threatening infection in immunocompromised hosts. We describe an 8-month-old child who died of VA1/HMO-C encephalitis following bone marrow transplantation. The diagnosis was only made post-mortem using RNA deep sequencing of the brain. Repeat analysis of the post-mortem brain tissue using polymerase chain reaction specific primers for VA1/HMO-C was positive. Astrovirus VA1/HMO-C should be included in the evaluation of patients with similar encephalitis.

A Bayesian Framework for the Classification of Microbial Gene Activity States

Numerous methods for classifying gene activity states based on gene expression data have been proposed for use in downstream applications, such as incorporating transcriptomics data into metabolic models in order to improve resulting flux predictions. These methods often attempt to classify gene activity for each gene in each experimental condition as belonging to one of two states: active (the gene product is part of an active cellular mechanism) or inactive (the cellular mechanism is not active). These existing methods of classifying gene activity states suffer from multiple limitations, including enforcing unrealistic constraints on the overall proportions of active and inactive genes, failing to leverage a priori knowledge of gene co-regulation, failing to account for differences between genes, and failing to provide statistically meaningful confidence estimates. We propose a flexible Bayesian approach to classifying gene activity states based on a Gaussian mixture model. The model integrates genome-wide transcriptomics data from multiple conditions and information about gene co-regulation to provide activity state confidence estimates for each gene in each condition. We compare the performance of our novel method to existing methods on both simulated data and real data from 907 E. coli gene expression arrays, as well as a comparison with experimentally measured flux values in 29 conditions, demonstrating that our method provides more consistent and accurate results than existing methods across a variety of metrics.

Metataxonomic and Metagenomic Approaches vs. Culture-Based Techniques for Clinical Pathology

Diagnoses that are both timely and accurate are critically important for patients with life-threatening or drug resistant infections. Technological improvements in High-Throughput Sequencing (HTS) have led to its use in pathogen detection and its application in clinical diagnoses of infectious diseases. The present study compares two HTS methods, 16S rRNA marker gene sequencing (metataxonomics) and whole metagenomic shotgun sequencing (metagenomics), in their respective abilities to match the same diagnosis as traditional culture methods (culture inference) for patients with ventilator associated pneumonia (VAP). The metagenomic analysis was able to produce the same diagnosis as culture methods at the species-level for five of the six samples, while the metataxonomic analysis was only able to produce results with the same species-level identification as culture for two of the six samples. These results indicate that metagenomic analyses have the accuracy needed for a clinical diagnostic tool, but full integration in diagnostic protocols is contingent on technological improvements to decrease turnaround time and lower costs.

Astrovirus VA1/HMO-C: an increasingly recognized neurotropic pathogen in immunocompromised patients

Brain biopsy from a child with unknown cause of encephalopathy was deep-sequenced. Astrovirus VA1/HMO-C was identified, highly divergent from human astroviruses and 95% identical to astrovirus previously associated with encephalitis. Findings suggest astrovirus VA1/HMO-C is an under-recognized cause of viral encephalitis.

Background. An 18-month-old boy developed encephalopathy, for which extensive investigation failed to identify an etiology, 6 weeks after stem cell transplant. To exclude a potential infectious cause, we performed high-throughput RNA sequencing on brain biopsy.

Methods. RNA-Seq was performed on an Illumina Miseq, generating 20 million paired-end reads. Nonhost data were checked for similarity to known organisms using BLASTx. The full viral genome was sequenced by primer walking.

Results. We identified an astrovirus, HAstV-VA1/HMO-C-UK1(a), which was highly divergent from human astrovirus (HAstV 1–8) genotypes, but closely related to VA1/HMO-C astroviruses, including one recovered from a case of fatal encephalitis in an immunosuppressed child. The virus was detected in stool and serum, with highest levels in brain and cerebrospinal fluid (CSF). Immunohistochemistry of the brain biopsy showed positive neuronal staining. A survey of 680 stool and 349 CSF samples identified a related virus in the stool of another immunosuppressed child.

Conclusions. The discovery of HAstV-VA1/HMO-C-UK1(a) as the cause of encephalitis in this case provides further evidence that VA1/HMO-C viruses, unlike HAstV 1–8, are neuropathic, particularly in immunocompromised patients, and should be considered in the differential diagnosis of encephalopathy. With a turnaround from sample receipt to result of <1 week, we confirm that RNA-Seq presents a valuable diagnostic tool in unexplained encephalitis.