Identification of a novel statovirus in a faecal sample from a calf with enteric disease

2021 ◽  
Vol 102 (9) ◽  
Author(s):  
Ben M. Hause ◽  
Eric Nelson ◽  
Jane Christopher-Hennings
Keyword(s):  
De Novo ◽  
Evolutionary Relationship ◽  
Plant Viruses ◽  
High Titre ◽  
Metagenomic Sequencing ◽  
Enteric Disease ◽  
Faecal Material ◽  
Taqman Pcr ◽  
Pcr Targeting ◽  
Generation Sequencing

A novel clade of RNA viruses was identified in the mammalian gastrointestinal tract by next-generation sequencing. Phylogenetically, these viruses are related to the genera Tombusviridae (plant viruses) and Flaviviridae, which includes mammalian, avian and insect hosts. Named in line with their characterization as stool-associated Tombus-like viruses, it is unclear if statoviruses infect mammals or are dietary in origin. Here, metagenomic sequencing of faecal material collected from a 10-week-old calf with enteric disease found that 20 % of the reads mapped to a de novo-assembled 4 kb contig with homology to statoviruses. Phylogenetic analysis of the statovirus genome found a clear evolutionary relationship with statovirus A, but, with only 47 % similarity, we propose that the statovirus sequence presents a novel species, statovirus F. A TaqMan PCR targeting statovirus F performed on faecal material found a cycle threshold of 11, suggesting a high titre of virus shed from the calf with enteric disease. A collection of 48 samples from bovine enteric disease diagnostic submissions were assayed by PCR to investigate statovirus F prevalence and 6 of 48 (12.5 %) were positive. An ELISA to detect antibodies to the coat protein found that antibodies to statovirus F were almost ubiquitous in bovine serum. Combined, the PCR and ELISA results suggest that statovirus F commonly infects cattle. Further research is needed to elucidate the aetiological significance of statovirus infection.

scholarly journals METAMVGL: a multi-view graph-based metagenomic contig binning algorithm by integrating assembly and paired-end graphs

2020 ◽  
Author(s):  
Zhenmiao Zhang ◽  
Lu Zhang
Keyword(s):  
De Novo ◽  
State Of The Art ◽  
Label Propagation ◽  
Next Generation Sequencing Data ◽  
Metagenomic Sequencing ◽  
Sequencing Data ◽  
Complete Genomes ◽  
Generation Sequencing ◽  
High Chance ◽  
Mock Communities

AbstractMotivationDue to the complexity of metagenomic community, de novo assembly on next generation sequencing data is commonly unable to produce microbial complete genomes. Metagenomic binning is a crucial task that could group the fragmented contigs into clusters based on their nucleotide compositions and read depths. These features work well on the long contigs, but are not stable for the short ones. Assembly and paired-end graphs can provide the connectedness between contigs, where the linked contigs have high chance to be derived from the same clusters.ResultsWe developed METAMVGL, a multi-view graph-based metagenomic contig binning algorithm by integrating both assembly and paired-end graphs. It could strikingly rescue the short contigs and correct the binning errors from dead ends subgraphs. METAMVGL could learn the graphs’ weights automatically and predict the contig labels in a uniform multi-view label propagation framework. In the experiments, we observed METAMVGL significantly increased the high-confident edges in the combined graph and linked dead ends to the main graph. It also outperformed with many state-of-the-art binning methods, MaxBin2, MetaBAT2, MyCC, CONCOCT, SolidBin and Graphbin on the metagenomic sequencing from simulation, two mock communities and real Sharon data.Availability and implementationThe software is available at https://github.com/ZhangZhenmiao/METAMVGL.

scholarly journals METAMVGL: a multi-view graph-based metagenomic contig binning algorithm by integrating assembly and paired-end graphs

2021 ◽  
Vol 22 (S10) ◽  
Author(s):  
Zhenmiao Zhang ◽  
Lu Zhang
Keyword(s):  
De Novo ◽  
Label Propagation ◽  
Next Generation Sequencing Data ◽  
Metagenomic Sequencing ◽  
Sequencing Data ◽  
Fecal Samples ◽  
Microbial Genomes ◽  
Metagenome Assembly ◽  
High Chance ◽  
Mock Communities

Abstract Background Due to the complexity of microbial communities, de novo assembly on next generation sequencing data is commonly unable to produce complete microbial genomes. Metagenome assembly binning becomes an essential step that could group the fragmented contigs into clusters to represent microbial genomes based on contigs’ nucleotide compositions and read depths. These features work well on the long contigs, but are not stable for the short ones. Contigs can be linked by sequence overlap (assembly graph) or by the paired-end reads aligned to them (PE graph), where the linked contigs have high chance to be derived from the same clusters. Results We developed METAMVGL, a multi-view graph-based metagenomic contig binning algorithm by integrating both assembly and PE graphs. It could strikingly rescue the short contigs and correct the binning errors from dead ends. METAMVGL learns the two graphs’ weights automatically and predicts the contig labels in a uniform multi-view label propagation framework. In experiments, we observed METAMVGL made use of significantly more high-confidence edges from the combined graph and linked dead ends to the main graph. It also outperformed many state-of-the-art contig binning algorithms, including MaxBin2, MetaBAT2, MyCC, CONCOCT, SolidBin and GraphBin on the metagenomic sequencing data from simulation, two mock communities and Sharon infant fecal samples. Conclusions Our findings demonstrate METAMVGL outstandingly improves the short contig binning and outperforms the other existing contig binning tools on the metagenomic sequencing data from simulation, mock communities and infant fecal samples.

scholarly journals Next‐generation sequencing in two cases of de novo acute basophilic leukaemia

2021 ◽  
Author(s):  
Takuya Shimizu ◽  
Tadakazu Kondo ◽  
Yasuhito Nannya ◽  
Mizuki Watanabe ◽  
Toshio Kitawaki ◽  
...  
Keyword(s):  
Next Generation Sequencing ◽  
De Novo ◽  
Next Generation ◽  
Generation Sequencing

scholarly journals Metagenomic Next-Generation Sequencing for Pathogen Detection and Transcriptomic Analysis in Pediatric Central Nervous System Infections

2021 ◽  
Author(s):  
Nanda Ramchandar ◽  
Nicole G Coufal ◽  
Anna S Warden ◽  
Benjamin Briggs ◽  
Toni Schwarz ◽  
...  
Keyword(s):  
Central Nervous System ◽  
Nervous System ◽  
Next Generation Sequencing ◽  
Usual Care ◽  
Transcriptomic Analysis ◽  
Cns Infection ◽  
Metagenomic Sequencing ◽  
Next Generation ◽  
Cns Infections ◽  
Generation Sequencing

Abstract Background Pediatric central nervous system (CNS) infections are potentially life-threatening and may incur significant morbidity. Identifying a pathogen is important, both in terms of guiding therapeutic management, but also in characterizing prognosis. Usual care testing by culture and PCR is often unable to identify a pathogen. We examined the systematic application of metagenomic next-generation sequencing (mNGS) for detecting organisms and transcriptomic analysis of cerebrospinal fluid (CSF) in children with CNS infections. Methods We conducted a prospective multi-site study that aimed to enroll all children with a CSF pleocytosis and suspected CNS infection admitted to one of three tertiary pediatric hospitals during the study timeframe. After usual care testing had been performed, the remaining CSF was sent for mNGS and transcriptomic analysis. Results We screened 221 and enrolled 70 subjects over a 12-month recruitment period. A putative organism was isolated from CSF in 25 (35.7%) subjects by any diagnostic modality. mNGS of the CSF samples identified a pathogen in 20 (28.6%) subjects, which were also all identified by usual care testing. The median time to result was 38 hours. Conclusion Metagenomic sequencing of CSF has the potential to rapidly identify pathogens in children with CNS infections.

Molecular marker information from de novo assembled transcriptomes of chilli pepper (Capsicum annuum L.) varieties based on next-generation sequencing technology

2014 ◽  
Vol 12 (S1) ◽  
pp. S83-S86 ◽  
Author(s):  
Yul-Kyun Ahn ◽  
Swati Tripathi ◽  
Young-Il Cho ◽  
Jeong-Ho Kim ◽  
Hye-Eun Lee ◽  
...  
Keyword(s):  
Molecular Markers ◽  
Next Generation Sequencing ◽  
De Novo ◽  
Transcriptome Assembly ◽  
Sequence Variant ◽  
Nucleotide Polymorphisms ◽  
Next Generation ◽  
Chilli Pepper ◽  
Next Generation Sequencing Technology ◽  
Generation Sequencing

Next-generation sequencing technique has been known as a useful tool for de novo transcriptome assembly, functional annotation of genes and identification of molecular markers. This study was carried out to mine molecular markers from de novo assembled transcriptomes of four chilli pepper varieties, the highly pungent ‘Saengryeg 211’ and non-pungent ‘Saengryeg 213’ and variably pigmented ‘Mandarin’ and ‘Blackcluster’. Pyrosequencing of the complementary DNA library resulted in 361,671, 274,269, 279,221, and 316,357 raw reads, which were assembled in 23,607, 19,894, 18,340 and 20,357 contigs, for the four varieties, respectively. Detailed sequence variant analysis identified numerous potential single-nucleotide polymorphisms (SNPs) and simple sequence repeats (SSRs) for all the varieties for which the primers were designed. The transcriptome information and SNP/SSR markers generated in this study provide valuable resources for high-density molecular genetic mapping in chilli pepper and Quantitative trait loci analysis related to fruit qualities. These markers for pepper will be highly valuable for marker-assisted breeding and other genetic studies.

scholarly journals Metagenomic Next-Generation Sequencing Reveals Individual Composition and Dynamics of Anelloviruses during Autologous Stem Cell Transplant Recipient Management

Viruses ◽  
2018 ◽  
Vol 10 (11) ◽  
pp. 633 ◽  
Author(s):  
Antonin Bal ◽  
Clémentine Sarkozy ◽  
Laurence Josset ◽  
Valérie Cheynet ◽  
Guy Oriol ◽  
...  
Keyword(s):  
Stem Cell ◽  
Next Generation Sequencing ◽  
Stem Cell Transplant ◽  
Autologous Stem Cell Transplant ◽  
Individual Variability ◽  
Cell Transplant ◽  
Next Generation ◽  
Post Transplantation ◽  
Pcr Targeting ◽  
Generation Sequencing

Over recent years, there has been increasing interest in the use of the anelloviruses, the major component of the human virome, for the prediction of post-transplant complications such as severe infections. Due to an important diversity, the comprehensive characterization of this viral family over time has been poorly studied. To overcome this challenge, we used a metagenomic next-generation sequencing (mNGS) approach with the aim of determining the individual anellovirus profile of autologous stem cell transplant (ASCT) patients. We conducted a prospective pilot study on a homogeneous patient cohort regarding the chemotherapy regimens that included 10 ASCT recipients. A validated viral mNGS workflow was used on 108 plasma samples collected at 11 time points from diagnosis to 90 days post-transplantation. A complex interindividual variability in terms of abundance and composition was noticed. In particular, a strong sex effect was found and confirmed using quantitative PCR targeting torque teno virus, the most abundant anellovirus. Interestingly, an important turnover in the anellovirus composition was observed during the course of the disease revealing a strong intra-individual variability. Although more studies are needed to better understand anellovirus dynamics, these findings are of prime importance for their future use as biomarkers of immune competence.

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

2021 ◽  
Author(s):  
Jutte J.C. de Vries ◽  
Julianne R. Brown ◽  
Nicole Fischer ◽  
Igor A. Sidorov ◽  
Sofia Morfopoulou ◽  
...  
Keyword(s):  
De Novo ◽  
Respiratory Infections ◽  
Limit Of Detection ◽  
Bioinformatic Analysis ◽  
Clinical Samples ◽  
Mixed Infections ◽  
Metagenomic Sequencing ◽  
User Friendliness ◽  
Viral Pathogens ◽  
Clinical Diagnostic

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 analysed 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 analysed. 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.

scholarly journals TrawlerWeb: an online de novo motif discovery tool for next-generation sequencing datasets

BMC Genomics ◽  
2018 ◽  
Vol 19 (1) ◽  
Author(s):  
Louis T. Dang ◽  
Markus Tondl ◽  
Man Ho H. Chiu ◽  
Jerico Revote ◽  
Benedict Paten ◽  
...  
Keyword(s):  
Next Generation Sequencing ◽  
Motif Discovery ◽  
De Novo ◽  
Next Generation ◽  
De Novo Motif Discovery ◽  
Generation Sequencing
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