Unknown Circovirus in Immunosuppressed Patient with Hepatitis, France, 2022.

Hepatitis of undetermined origin can be caused by a wide variety of pathogens, sometimes emerging pathogens. We report the discovery, by means of routine shotgun metagenomics, of a new virus belonging to the family Circoviridae, genus Circovirus, in a patient in France who had acute hepatitis of unknown origin.

Dissecting the role of the human microbiome in COVID-19 via metagenome-assembled genomes.

Coronavirus disease 2019 (COVID-19), primarily a respiratory disease caused by infection with Severe Acute Respiratory Syndrome Coronavirus 2 (SARS-CoV-2), is often accompanied by gastrointestinal symptoms. However, little is known about the relation between the human microbiome and COVID-19, largely due to the fact that most previous studies fail to provide high taxonomic resolution to identify microbes that likely interact with SARS-CoV-2 infection. Here we used whole-metagenome shotgun sequencing data together with assembly and binning strategies to reconstruct metagenome-assembled genomes (MAGs) from 514 COVID-19 related nasopharyngeal and fecal samples in six independent cohorts. We reconstructed a total of 11,584 medium-and high-quality microbial MAGs and obtained 5403 non-redundant MAGs (nrMAGs) with strain-level resolution. We found that there is a significant reduction of strain richness for many species in the gut microbiome of COVID-19 patients. The gut microbiome signatures can accurately distinguish COVID-19 cases from healthy controls and predict the progression of COVID-19. Moreover, we identified a set of nrMAGs with a putative causal role in the clinical manifestations of COVID-19 and revealed their functional pathways that potentially interact with SARS-CoV-2 infection. Finally, we demonstrated that the main findings of our study can be largely validated in three independent cohorts. The presented results highlight the importance of incorporating the human gut microbiome in our understanding of SARS-CoV-2 infection and disease progression.

VirusTaxo: Taxonomic classification of viruses from the genome sequence using k-mer enrichment.

Classification of viruses into their taxonomic ranks (e.g., order, family, and genus) provides a framework to organize an abundant population of viruses. Next-generation metagenomic sequencing technologies lead to a rapid increase in generating sequencing data of viruses which require bioinformatics tools to analyze the taxonomy. Many metagenomic taxonomy classifiers have been developed to study microbiomes, but it is particularly challenging to assign the taxonomy of diverse virus sequences and there is a growing need for dedicated methods to be developed that are optimized to classify virus sequences into their taxa. For taxonomic classification of viruses from metagenomic sequences, we developed VirusTaxo using diverse (e.g., 402 DNA and 280 RNA) genera of viruses. VirusTaxo has an average accuracy of 93% at genus level prediction in DNA and RNA viruses. VirusTaxo outperformed existing taxonomic classifiers of viruses where it assigned taxonomy of a larger fraction of metagenomic contigs compared to other methods. Benchmarking of VirusTaxo on a collection of SARS-CoV-2 sequencing libraries and metavirome datasets suggests that VirusTaxo can characterize virus taxonomy from highly diverse contigs and provide a reliable decision on the taxonomy of viruses.

Metagenomic pipeline for identifying co-infections among distinct SARS-CoV-2 variants of concern: study cases from Alpha to Omicron.

Concomitant infection or co-infection with distinct SARS-CoV-2 genotypes has been reported as part of the epidemiological surveillance of the COVID-19 pandemic. In the context of the spread of more transmissible variants during 2021, co-infections are not only important due to the possible changes in the clinical outcome, but also the chance to generate new genotypes by recombination. However, a few approaches have developed bioinformatic pipelines to identify co-infections. Here we present a metagenomic pipeline based on the inference of multiple fragments similar to amplicon sequence variant (ASV-like) from sequencing data and a custom SARS-CoV-2 database to identify the concomitant presence of divergent SARS-CoV-2 genomes, i.e., variants of concern (VOCs). This approach was compared to another strategy based on whole-genome (metagenome) assembly. Using single or pairs of sequencing data of COVID-19 cases with distinct SARS-CoV-2 VOCs, each approach was used to predict the VOC classes (Alpha, Beta, Gamma, Delta, Omicron or non-VOC and their combinations). The performance of each pipeline was assessed using the ground-truth or expected VOC classes. Subsequently, the ASV-like pipeline was used to analyze 1021 cases of COVID-19 from Costa Rica to investigate the possible occurrence of co-infections. After the implementation of the two approaches, an accuracy of 96.2% was revealed for the ASV-like inference approach, which contrasts with the misclassification found (accuracy 46.2%) for the whole-genome assembly strategy. The custom SARS-CoV-2 database used for the ASV-like analysis can be updated according to the appearance of new VOCs to track co-infections with eventual new genotypes. In addition, the application of the ASV-like approach to all the 1021 sequenced samples from Costa Rica in the period October 12th-December 21th 2021 found that none corresponded to co-infections with VOCs. In conclusion, we developed a metagenomic pipeline based on ASV-like inference for the identification of co-infection with distinct SARS-CoV-2 VOCs, in which an outstanding accuracy was achieved. Due to the epidemiological, clinical, and molecular relevance of the concomitant infection with distinct genotypes, this work represents another piece in the process of the surveillance of the COVID-19 pandemic in Costa Rica and worldwide.

BugSplit enables genome-resolved metagenomics through highly accurate taxonomic binning of metagenomic assemblies.

A large gap remains between sequencing a microbial community and characterizing all of the organisms inside of it. Here we develop a novel method to taxonomically bin metagenomic assemblies through alignment of contigs against a reference database. We show that this workflow, BugSplit, bins metagenome-assembled contigs to species with a 33% absolute improvement in F1-score when compared to alternative tools. We perform nanopore mNGS on patients with COVID-19, and using a reference database predating COVID-19, demonstrate that BugSplit's taxonomic binning enables sensitive and specific detection of a novel coronavirus not possible with other approaches. When applied to nanopore mNGS data from cases of Klebsiella pneumoniae and Neisseria gonorrhoeae infection, BugSplit's taxonomic binning accurately separates pathogen sequences from those of the host and microbiota, and unlocks the possibility of sequence typing, in silico serotyping, and antimicrobial resistance prediction of each organism within a sample. BugSplit is available at https://bugseq.com/academic .

Viral diversity and potential environmental risk in microplastic at watershed scale: Evidence from metagenomic analysis of plastisphere.

Microplastics (MPs) have been considered as a new vector for the long-distance transport of pathogens in aquatic ecosystems. However, the composition of viral communities attached on MPs and their environmental risk are largely unknown. Here, we profiled the viral diversity and potential risk in five different MPs collected from the Beilun River based on metagenomic analysis. Nearly 2863 million raw reads were produced and assembled, and annotation resulted in the identification of 1719 different species of viruses in MPs. Viruses in polypropylene (PP) displayed the highest diversity, with about 250 specific viruses detected. Source tracking of viruses in MPs by the fast expectation-maximization microbial source tracking method (FEAST) demonstrated that viruses in upstream and downstream MPs are two major sources of viruses in estuary. Furthermore, the MP-type-dependent potential environmental risk of viruses was significant based on both antibiotic resistance genes (ARGs) and virulence factors (VFs) detected in viral metagenomes, and PP was confirmed with the highest potential environmental risk. This study reveals the high diversity and potential environmental risk of viruses in different MPs, and provides an important guidance for future environmental monitoring and understanding the potential risks associated with both viral transmission and MPs pollution.

The Human Virome: Viral Metagenomics, Relations with Human Diseases, and Therapeutic Applications.

The human body is colonized by a wide range of microorganisms. The field of viromics has expanded since the first reports on the detection of viruses via metagenomic sequencing in 2002. With the continued development of reference materials and databases, viral metagenomic approaches have been used to explore known components of the virome and discover new viruses from various types of samples. The virome has attracted substantial interest since the outbreak of the coronavirus disease 2019 (COVID-19) pandemic. Increasing numbers of studies and review articles have documented the diverse virome in various sites in the human body, as well as interactions between the human host and the virome with regard to health and disease. However, there have been few studies of direct causal relationships. Viral metagenomic analyses often lack standard references and are potentially subject to bias. Moreover, most virome-related review articles have focused on the gut virome and did not investigate the roles of the virome in other sites of the body in human disease. This review presents an overview of viral metagenomics, with updates regarding the relations between alterations in the human virome and the pathogenesis of human diseases, recent findings related to COVID-19, and therapeutic applications related to the human virome.

Distinct Metagenomic Signatures in the SARS-CoV-2 Infection.

Severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) infection can cause gastrointestinal symptoms in the patients, but the role of gut microbiota in SARS-CoV-2 infection remains unclear. Thus, in this study, we aim to investigate whether SARS-CoV-2 infection affects the composition and function of gut microbiota. In this study, we demonstrated for the first time that significant shifts in microbiome composition and function were appeared in both SARS-CoV-2-infected asymptomatic and symptomatic cases. The relative abundance of Candidatus_Saccharibacteria was significantly increased, whereas the levels of Fibrobacteres was remarkably reduced in SARS-CoV-2-infected cases. There was one bacterial species, Spirochaetes displayed the difference between patients and asymptomatic cases. On the genus level, Tyzzerella was the key species that remarkably increased in both symptomatic and asymptomatic cases. Analyses of genome annotations further revealed SARS-CoV-2 infection resulted in the significant 'functional dysbiosis' of gut microbiota, including metabolic pathway, regulatory pathway and biosynthesis of secondary metabolites etc. We also identified potential metagenomic markers to discriminate SARS-CoV-2-infected symptomatic and asymptomatic cases from healthy controls. These findings together suggest gut microbiota is of possible etiological and diagnostic importance for SARS-CoV-2 infection.

Nanopore metagenomic sequencing of influenza virus directly from respiratory samples: diagnosis, drug resistance and nosocomial transmission, United Kingdom, 2018/19 influenza season.

BackgroundInfluenza virus presents a considerable challenge to public health by causing seasonal epidemics and occasional pandemics. Nanopore metagenomic sequencing has the potential to be deployed for near-patient testing, providing rapid infection diagnosis, rationalising antimicrobial therapy, and supporting infection-control interventions.AimTo evaluate the applicability of this sequencing approach as a routine laboratory test for influenza in clinical settings.MethodsWe conducted Oxford Nanopore Technologies (Oxford, United Kingdom (UK)) metagenomic sequencing for 180 respiratory samples from a UK hospital during the 2018/19 influenza season, and compared results to routine molecular diagnostic standards (Xpert Xpress Flu/RSV assay; BioFire FilmArray Respiratory Panel 2 assay). We investigated drug resistance, genetic diversity, and nosocomial transmission using influenza sequence data.ResultsCompared to standard testing, Nanopore metagenomic sequencing was 83% (75/90) sensitive and 93% (84/90) specific for detecting influenza A viruses. Of 59 samples with haemagglutinin subtype determined, 40 were H1 and 19 H3. We identified an influenza A(H3N2) genome encoding the oseltamivir resistance S331R mutation in neuraminidase, potentially associated with an emerging distinct intra-subtype reassortant. Whole genome phylogeny refuted suspicions of a transmission cluster in a ward, but identified two other clusters that likely reflected nosocomial transmission, associated with a predominant community-circulating strain. We also detected other potentially pathogenic viruses and bacteria from the metagenome.ConclusionNanopore metagenomic sequencing can detect the emergence of novel variants and drug resistance, providing timely insights into antimicrobial stewardship and vaccine design. Full genome generation can help investigate and manage nosocomial outbreaks.

Assessing saliva microbiome collection and processing methods.

The oral microbiome has been connected with lung health and may be of significance in the progression of SARS-CoV-2 infection. Saliva-based SARS-CoV-2 tests provide the opportunity to leverage stored samples for assessing the oral microbiome. However, these collection kits have not been tested for their accuracy in measuring the oral microbiome. Saliva is highly enriched with human DNA and reducing it prior to shotgun sequencing may increase the depth of bacterial reads. We examined both the effect of saliva collection method and sequence processing on measurement of microbiome depth and diversity by 16S rRNA gene amplicon and shotgun metagenomics. We collected 56 samples from 22 subjects. Each subject provided saliva samples with and without preservative, and a subset provided a second set of samples the following day. 16S rRNA gene (V4) sequencing was performed on all samples, and shotgun metagenomics was performed on a subset of samples collected with preservative with and without human DNA depletion before sequencing. We observed that the beta diversity distances within subjects over time was smaller than between unrelated subjects, and distances within subjects were smaller in samples collected with preservative. Samples collected with preservative had higher alpha diversity measuring both richness and evenness. Human DNA depletion before extraction and shotgun sequencing yielded higher total and relative reads mapping to bacterial sequences. We conclude that collecting saliva with preservative may provide more consistent measures of the oral microbiome and depleting human DNA increases yield of bacterial sequences.

Nanopore metagenomic sequencing for detection and characterization of SARS-CoV-2 in clinical samples.

OBJECTIVES: The COVID-19 pandemic has underscored the need for rapid novel diagnostic strategies. Metagenomic Next-Generation Sequencing (mNGS) may allow for the detection of pathogens that can be missed in targeted assays. The goal of this study was to assess the performance of nanopore-based Sequence-Independent Single Primer Amplification (SISPA) for the detection and characterization of SARS-CoV-2. METHODS: We performed mNGS on clinical samples and designed a diagnostic classifier that corrects for barcode crosstalk between specimens. Phylogenetic analysis was performed on genome assemblies. RESULTS: Our assay yielded 100% specificity overall and 95.2% sensitivity for specimens with a RT-PCR cycle threshold value less than 30. We assembled 10 complete, and one near-complete genomes from 20 specimens that were classified as positive by mNGS. Phylogenetic analysis revealed that 10/11 specimens from British Columbia had a closest relative to another British Columbian specimen. We found 100% concordance between phylogenetic lineage assignment and Variant of Concern (VOC) PCR results. Our assay was able to distinguish between the Alpha and Gamma variants, which was not possible with the current standard VOC PCR being used in British Columbia. CONCLUSIONS: This study supports future work examining the broader feasibility of nanopore mNGS as a diagnostic strategy for the detection and characterization of viral pathogens.

Multiomics and Health: A Holistic Approach to Better Understand the Role of the Microbiome.

The present Special Issue focuses on the latest approaches to health and public health microbiology using multiomics [...].

Utilizing the VirIdAl Pipeline to Search for Viruses in the Metagenomic Data of Bat Samples.

According to various estimates, only a small percentage of existing viruses have been discovered, naturally much less being represented in the genomic databases. High-throughput sequencing technologies develop rapidly, empowering large-scale screening of various biological samples for the presence of pathogen-associated nucleotide sequences, but many organisms are yet to be attributed specific loci for identification. This problem particularly impedes viral screening, due to vast heterogeneity in viral genomes. In this paper, we present a new bioinformatic pipeline, VirIdAl, for detecting and identifying viral pathogens in sequencing data. We also demonstrate the utility of the new software by applying it to viral screening of the feces of bats collected in the Moscow region, which revealed a significant variety of viruses associated with bats, insects, plants, and protozoa. The presence of alpha and beta coronavirus reads, including the MERS-like bat virus, deserves a special mention, as it once again indicates that bats are indeed reservoirs for many viral pathogens. In addition, it was shown that alignment-based methods were unable to identify the taxon for a large proportion of reads, and we additionally applied other approaches, showing that they can further reveal the presence of viral agents in sequencing data. However, the incompleteness of viral databases remains a significant problem in the studies of viral diversity, and therefore necessitates the use of combined approaches, including those based on machine learning methods.

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 next-generation sequencing in the family outbreak of psittacosis: the first reported family outbreak of psittacosis in China under COVID-19.

Chlamydia psittaci infection in humans, also known as psittacosis, is usually believed to be an uncommon disease which mainly presents as community-acquired pneumonia (CAP). It is usually sporadic, but outbreaks of infection may occasionally occur. In outbreaks, diagnosis and investigations were usually hampered by the non-specificity of laboratory testing methods to identify C. psittaci. In this study, we use metagenomic next-generation sequencing (mNGS) in the diagnosis of a family outbreak of psittacosis under COVID-19. Three members of an extended family of 6 persons developed psittacosis with pneumonia and hepatic involvement with common symptoms of fever and weakness. Two newly purchased pet parrots, which had died successively, were probably the primary source of infection. Imagings show lung consolidations and infiltrates, which are difficult to be differentiated from CAP caused by other common pathogens. mNGS rapidly identified the infecting agent as C. psittaci within 48 h. The results of this work suggest that there are not characteristic clinical manifestations and imagings of psittacosis pneumonia which can differentiate from CAP caused by other pathogens. The use of mNGS can improve accuracy and reduce the delay in the diagnosis of psittacosis especially during the outbreak, which can shorten the course of the disease control. Family outbreak under COVID-19 may be related to the familial aggregation due to the epidemic. To our knowledge, this is the first reported family outbreak of psittacosis in China, and the first reported psittacosis outbreak identified by the method of mNGS in the world.

Explorative assessment of coronavirus-like short sequences from host-associated and environmental metagenomes.

The ongoing COVID-19 pandemic has not only globally caused a high number of causalities, but is also an unprecedented challenge for scientists. False-positive virus detection tests not only aggravate the situation in the healthcare sector, but also provide ground for speculations. Previous studies have highlighted the importance of software choice and data interpretation in virome studies. We aimed to further expand theoretical and practical knowledge in bioinformatics-driven virome studies by focusing on short, virus-like DNA sequences in metagenomic data. Analyses of datasets obtained from different sample types (terrestrial, animal and human related samples) and origins showed that coronavirus-like sequences have existed in host-associated and environmental samples before the current COVID-19 pandemic. In the analyzed datasets, various Betacoronavirus-like sequences were detected that also included SARS-CoV-2 matches. Deepening analyses indicated that the detected sequences are not of viral origin and thus should not be considered in virome profiling approaches. Our study confirms the importance of parameter selection, especially in terms of read length, for reliable virome profiling. Natural environments are an important source of coronavirus-like nucleotide sequences that should be taken into account when virome datasets are analyzed and interpreted. We therefore suggest that processing parameters are carefully selected for SARS-CoV-2 profiling in host related as well as environmental samples in order to avoid incorrect identifications.