scholarly journals Viral dark matter and virus–host interactions resolved from publicly available microbial genomes

eLife ◽  
2015 ◽  
Vol 4 ◽  
Author(s):  
Simon Roux ◽  
Steven J Hallam ◽  
Tanja Woyke ◽  
Matthew B Sullivan
Keyword(s):  
Sequence Space ◽  
Data Sets ◽  
Microbial Genomes ◽  
Bacterial Phyla ◽  
Viral Genomes ◽  
Host Interactions ◽  
Public Data ◽  
Ecological Importance ◽  
Genomic Recombination ◽  
Viral Sequences

The ecological importance of viruses is now widely recognized, yet our limited knowledge of viral sequence space and virus–host interactions precludes accurate prediction of their roles and impacts. In this study, we mined publicly available bacterial and archaeal genomic data sets to identify 12,498 high-confidence viral genomes linked to their microbial hosts. These data augment public data sets 10-fold, provide first viral sequences for 13 new bacterial phyla including ecologically abundant phyla, and help taxonomically identify 7–38% of ‘unknown’ sequence space in viromes. Genome- and network-based classification was largely consistent with accepted viral taxonomy and suggested that (i) 264 new viral genera were identified (doubling known genera) and (ii) cross-taxon genomic recombination is limited. Further analyses provided empirical data on extrachromosomal prophages and coinfection prevalences, as well as evaluation of in silico virus–host linkage predictions. Together these findings illustrate the value of mining viral signal from microbial genomes.

scholarly journals virMine: automated detection of viral sequences from complex metagenomic samples

PeerJ ◽  
2019 ◽  
Vol 7 ◽  
pp. e6695 ◽  
Author(s):  
Andrea Garretto ◽  
Thomas Hatzopoulos ◽  
Catherine Putonti
Keyword(s):  
Software Tool ◽  
Metagenomic Data ◽  
Data Sets ◽  
Data Repositories ◽  
Viral Genomes ◽  
Manual Curation ◽  
Public Data ◽  
Control Assembly ◽  
Signature Sequences ◽  
Viral Sequences

Metagenomics has enabled sequencing of viral communities from a myriad of different environments. Viral metagenomic studies routinely uncover sequences with no recognizable homology to known coding regions or genomes. Nevertheless, complete viral genomes have been constructed directly from complex community metagenomes, often through tedious manual curation. To address this, we developed the software tool virMine to identify viral genomes from raw reads representative of viral or mixed (viral and bacterial) communities. virMine automates sequence read quality control, assembly, and annotation. Researchers can easily refine their search for a specific study system and/or feature(s) of interest. In contrast to other viral genome detection tools that often rely on the recognition of viral signature sequences, virMine is not restricted by the insufficient representation of viral diversity in public data repositories. Rather, viral genomes are identified through an iterative approach, first omitting non-viral sequences. Thus, both relatives of previously characterized viruses and novel species can be detected, including both eukaryotic viruses and bacteriophages. Here we present virMine and its analysis of synthetic communities as well as metagenomic data sets from three distinctly different environments: the gut microbiota, the urinary microbiota, and freshwater viromes. Several new viral genomes were identified and annotated, thus contributing to our understanding of viral genetic diversity in these three environments.

scholarly journals SARS-CoV-2 Origins and Evolution: Insights from Coronaviruses Recombination and Phylogenetic Analysis

2020 ◽  
Author(s):  
Alltalents Tutsirayi Murahwa ◽  
Harris Onywera ◽  
Fredrick Nindo
Keyword(s):  
Phylogenetic Analysis ◽  
Infectious Agent ◽  
Functional Health ◽  
Global Epidemic ◽  
Viral Genomes ◽  
Virulent Strains ◽  
Spatio Temporal ◽  
Political Turmoil ◽  
Genomic Recombination ◽  
Viral Sequences

Abstract Background: It is imperative in the midst of a global epidemic to investigate the origins of the infectious agent especially when it has reached parts of the world with either ailing economies or pre-existing political turmoil consistent with non-functional health systems. Methods: To explore the possibility of cross species infection, genomic recombination and the emergence of novel coronaviruses in the near future we carried out recombination and phylogenetic analysis to determine the spatio-temporal evolution and origins of the current SARS-CoV-2 virus. Results: Our findings prove using two robust recombination tools, RDPv4.100 and SimPlot3.5.1 analysis that SARS-CoV-2 is a recombinant of pangolin and bat RaTG13 sequences as been previously shown elsewhere. We also report one novel recombinantion event between two SARS-CoV-2 sequences ( SARS-CoV-2 sequence, MT188341 , SARS-CoV-2 sequence, MT293183). Bearing in mind that the prerequisite for recombination is the occurrence two viral sequences in the same reservoir, biological niche or host at the same time we postulate either co-infection with the two viral sequences, or superinfection, both scenarios have not been reported elsewhere. Conclusion: The possibility of recombination between the SARS-CoV-2 sequences poses the likelihood of the emergence of new and maybe more or less virulent “strains” of the virus. We believe that the future of science lies in our ability to be able to use computational based methods to predict the genetic sequences of infectious agents of the next epidemics. The addition of more SARS-CoV-2 sequences has a bearing on the understanding of the origin, evolution and clinical outcome prediction of given viral genomes. More SARS-CoV-2 sequences are needed to elucidate our understanding of this family of viruses.

scholarly journals WgLink: reconstructing whole-genome viral haplotypes using L0 + L1-regularization

2020 ◽  
Author(s):  
Chen Cao ◽  
Matthew Greenberg ◽  
Quan Long
Keyword(s):  
Real Data ◽  
Data Sets ◽  
Whole Genome ◽  
Regularized Regression ◽  
Viral Genomes ◽  
Physical Linkage ◽  
Multiple Regions ◽  
Viral Sequences ◽  
Multiple Variants ◽  
Generation Sequencing

AbstractMany tools can reconstruct viral sequences based on next generation sequencing reads. Although existing tools effectively recover local regions, their accuracy suffers when reconstructing the whole viral genomes (strains). Moreover, they consume significant memory when the sequencing coverage is high or when the genome size is large. We present WgLink to meet this challenge. WgLink takes local reconstructions produced by other tools as input and patches the resulting segments together into coherent whole-genome strains. We accomplish this using an L0 + L1-regularized regression synthesizing variant allele frequency data with physical linkage between multiple variants spanning multiple regions simultaneously. WgLink achieves higher accuracy than existing tools both on simulated and real data sets while using significantly less memory (RAM) and fewer CPU hours. Source code and binaries are freely available at https://github.com/theLongLab/wglink.

scholarly journals SARS-CoV-2 Origins and Evolution: Insights from Coronaviruses Recombination and Phylogenetic Analysis

2020 ◽  
Author(s):  
Alltalents Tutsirayi Murahwa ◽  
Harris Onywera ◽  
Fredrick Nindo
Keyword(s):  
Phylogenetic Analysis ◽  
Infectious Agent ◽  
Functional Health ◽  
Global Epidemic ◽  
Viral Genomes ◽  
Virulent Strains ◽  
Spatio Temporal ◽  
Political Turmoil ◽  
Genomic Recombination ◽  
Viral Sequences

Abstract Background: It is imperative in the midst of a global epidemic to investigate the origins of the infectious agent especially when it has reached parts of the world with either ailing economies or pre-existing political turmoil consistent with non-functional health systems. Methods: To explore the possibility of cross species infection, genomic recombination and the emergence of novel coronaviruses in the near future we carried out recombination and phylogenetic analysis to determine the spatio-temporal evolution and origins of the current SARS-CoV-2 virus. Results: Our findings prove using two robust recombination tools, RDPv4.100 and SimPlot3.5.1 analysis that SARS-CoV-2 is a recombinant of pangolin and bat RaTG13 sequences as been previously shown elsewhere. We also report one novel recombination event between two SARS-CoV-2 sequences (SARS-CoV-2 sequence, MT188341, SARS-CoV-2 sequence, MT293183). Bearing in mind that the prerequisite for recombination is the occurrence two viral sequences in the same reservoir, biological niche or host at the same time we postulate either co-infection with the two viral sequences, or superinfection, both scenarios have not been reported elsewhere. Conclusion: The possibility of recombination between the SARS-CoV-2 sequences poses the likelihood of the emergence of new and maybe more or less virulent “strains” of the virus. We believe that the future of science lies in our ability to be able to use computational based methods to predict the genetic sequences of infectious agents of the next epidemics. The addition of more SARS-CoV-2 sequences has a bearing on the understanding of the origin, evolution and clinical outcome prediction of given viral genomes. More SARS-CoV-2 sequences are needed to elucidate our understanding of this family of viruses.

scholarly journals SARS-CoV-2 Sequence Characteristics of COVID-19 Persistence and Reinfection

2021 ◽  
Author(s):  
Manish C Choudhary ◽  
Charles R Crain ◽  
Xueting Qiu ◽  
William Hanage ◽  
Jonathan Z Li
Keyword(s):  
Persistent Infection ◽  
Viral Evolution ◽  
Phylogenetic Reconstruction ◽  
Geographic Region ◽  
Antibody Treatment ◽  
Viral Genomes ◽  
Monoclonal Antibody Treatment ◽  
Viral Sequences ◽  
Sequence Characteristics ◽  
Baseline Health

Abstract Background Both SARS-CoV-2 reinfection and persistent infection have been reported, but sequence characteristics in these scenarios have not been described. We assessed published cases of SARS-CoV-2 reinfection and persistence, characterizing the hallmarks of reinfecting sequences and the rate of viral evolution in persistent infection. Methods A systematic review of PubMed was conducted to identify cases of SARS-CoV-2 reinfection and persistence with available sequences. Nucleotide and amino acid changes in the reinfecting sequence were compared to both the initial and contemporaneous community variants. Time-measured phylogenetic reconstruction was performed to compare intra-host viral evolution in persistent SARS-CoV-2 to community-driven evolution. Results Twenty reinfection and nine persistent infection cases were identified. Reports of reinfection cases spanned a broad distribution of ages, baseline health status, reinfection severity, and occurred as early as 1.5 months or >8 months after the initial infection. The reinfecting viral sequences had a median of 17.5 nucleotide changes with enrichment in the ORF8 and N genes. The number of changes did not differ by the severity of reinfection and reinfecting variants were similar to the contemporaneous sequences circulating in the community. Patients with persistent COVID-19 demonstrated more rapid accumulation of sequence changes than seen with community-driven evolution with continued evolution during convalescent plasma or monoclonal antibody treatment. Conclusions Reinfecting SARS-CoV-2 viral genomes largely mirror contemporaneous circulating sequences in that geographic region, while persistent COVID-19 has been largely described in immunosuppressed individuals and is associated with accelerated viral evolution.

MULFE: Multi-Label Learning via Label-Specific Feature Space Ensemble

2021 ◽  
Vol 16 (1) ◽  
pp. 1-24
Author(s):  
Yaojin Lin ◽  
Qinghua Hu ◽  
Jinghua Liu ◽  
Xingquan Zhu ◽  
Xindong Wu
Keyword(s):  
Empirical Studies ◽  
Feature Space ◽  
Training Data ◽  
Data Sets ◽  
Learning Framework ◽  
Feature Spaces ◽  
Public Data ◽  
Margin Distribution ◽  
Label Correlations ◽  
Label Correlation

In multi-label learning, label correlations commonly exist in the data. Such correlation not only provides useful information, but also imposes significant challenges for multi-label learning. Recently, label-specific feature embedding has been proposed to explore label-specific features from the training data, and uses feature highly customized to the multi-label set for learning. While such feature embedding methods have demonstrated good performance, the creation of the feature embedding space is only based on a single label, without considering label correlations in the data. In this article, we propose to combine multiple label-specific feature spaces, using label correlation, for multi-label learning. The proposed algorithm, mu lti- l abel-specific f eature space e nsemble (MULFE), takes consideration label-specific features, label correlation, and weighted ensemble principle to form a learning framework. By conducting clustering analysis on each label’s negative and positive instances, MULFE first creates features customized to each label. After that, MULFE utilizes the label correlation to optimize the margin distribution of the base classifiers which are induced by the related label-specific feature spaces. By combining multiple label-specific features, label correlation based weighting, and ensemble learning, MULFE achieves maximum margin multi-label classification goal through the underlying optimization framework. Empirical studies on 10 public data sets manifest the effectiveness of MULFE.

scholarly journals Illuminating the Plant Rhabdovirus Landscape through Metatranscriptomics Data

Viruses ◽  
2021 ◽  
Vol 13 (7) ◽  
pp. 1304
Author(s):  
Nicolás Bejerman ◽  
Ralf G. Dietzgen ◽  
Humberto Debat
Keyword(s):  
Plant Species ◽  
High Throughput Sequencing ◽  
Plant Viruses ◽  
The Novel ◽  
Coding Regions ◽  
Public Data ◽  
Invaluable Tool ◽  
Sequencing Platforms ◽  
Viral Sequences ◽  
Plant Rhabdovirus

Rhabdoviruses infect a large number of plant species and cause significant crop diseases. They have a negative-sense, single-stranded unsegmented or bisegmented RNA genome. The number of plant-associated rhabdovirid sequences has grown in the last few years in concert with the extensive use of high-throughput sequencing platforms. Here, we report the discovery of 27 novel rhabdovirus genomes associated with 25 different host plant species and one insect, which were hidden in public databases. These viral sequences were identified through homology searches in more than 3000 plant and insect transcriptomes from the National Center for Biotechnology Information (NCBI) Sequence Read Archive (SRA) using known plant rhabdovirus sequences as the query. The identification, assembly and curation of raw SRA reads resulted in sixteen viral genome sequences with full-length coding regions and ten partial genomes. Highlights of the obtained sequences include viruses with unique and novel genome organizations among known plant rhabdoviruses. Phylogenetic analysis showed that thirteen of the novel viruses were related to cytorhabdoviruses, one to alphanucleorhabdoviruses, five to betanucleorhabdoviruses, one to dichorhaviruses and seven to varicosaviruses. These findings resulted in the most complete phylogeny of plant rhabdoviruses to date and shed new light on the phylogenetic relationships and evolutionary landscape of this group of plant viruses. Furthermore, this study provided additional evidence for the complexity and diversity of plant rhabdovirus genomes and demonstrated that analyzing SRA public data provides an invaluable tool to accelerate virus discovery, gain evolutionary insights and refine virus taxonomy.

Improvements for research data repositories: The case of text spam

2021 ◽  
pp. 016555152199863
Author(s):  
Ismael Vázquez ◽  
María Novo-Lourés ◽  
Reyes Pavón ◽  
Rosalía Laza ◽  
José Ramón Méndez ◽  
...  
Keyword(s):  
Web Application ◽  
Research Data ◽  
Data Sets ◽  
Data Repositories ◽  
Software Applications ◽  
Public Data ◽  
Protection Mechanisms ◽  
Experimental Protocols ◽  
Learning Research ◽  
Processing Steps

Current research has evolved in such a way scientists must not only adequately describe the algorithms they introduce and the results of their application, but also ensure the possibility of reproducing the results and comparing them with those obtained through other approximations. In this context, public data sets (sometimes shared through repositories) are one of the most important elements for the development of experimental protocols and test benches. This study has analysed a significant number of CS/ML ( Computer Science/ Machine Learning) research data repositories and data sets and detected some limitations that hamper their utility. Particularly, we identify and discuss the following demanding functionalities for repositories: (1) building customised data sets for specific research tasks, (2) facilitating the comparison of different techniques using dissimilar pre-processing methods, (3) ensuring the availability of software applications to reproduce the pre-processing steps without using the repository functionalities and (4) providing protection mechanisms for licencing issues and user rights. To show the introduced functionality, we created STRep (Spam Text Repository) web application which implements our recommendations adapted to the field of spam text repositories. In addition, we launched an instance of STRep in the URL https://rdata.4spam.group to facilitate understanding of this study.

Integration of viral DNA sequences in cells transformed by adenovirus 2 or SV40

1980 ◽  
Vol 210 (1180) ◽  
pp. 423-435 ◽  
Keyword(s):  
Cell Lines ◽  
Dna Sequences ◽  
Viral Genome ◽  
Viral Dna ◽  
Viral Genomes ◽  
Viral Dnas ◽  
Cellular Dna ◽  
Viral Insertion ◽  
Viral Sequences ◽  
Heteroduplex Formation

We have cloned and propagated in prokaryotic vectors the viral DNA sequences that are integrated in a variety of cells transformed by adenovirus 2 or SV40. Analysis of the clones reveals that the viral DNA sequences sometimes are arranged in a simple fashion, collinear with the viral genome; in other cell lines there are complex arrangements of viral sequences in which tracts of the viral genome are inverted with respect to each other. In several cases the nucleotide sequences at the joints between cell and viral sequences have been determined: usually there is a sharp transition between cellular and viral DNAs. The viral sequences are integrated at different locations within the genomes of different cell lines; likewise there is no specific site on the viral genomes at which integration occurs. Sometimes the viral sequences are integrated within repetitive cellular DNA, and sometimes within unique sequences. In some cases there is evidence that the viral sequences along with the flanking cell DNA have been amplified after integration. The sequences that flank the viral insertion in the line of SV40-transformed rat cells known as 14B have been used as probes to isolate, from untransformed rat cells, clones that carry the region of the chromosome in which integration occurred. Analysis of the structure of these clones by restriction endonuclease digestion and heteroduplex formation shows that a rearrangement of cellular sequences has occurred, presumably as a consequence of integration.

Fast and accurate detection of surface defect based on improved YOLOv4

2021 ◽  
Vol ahead-of-print (ahead-of-print) ◽  
Author(s):  
Jiawei Lian ◽  
Junhong He ◽  
Yun Niu ◽  
Tianze Wang
Keyword(s):  
Feature Extraction ◽  
Real Time ◽  
Surface Defect ◽  
Steel Ingot ◽  
Industrial Applications ◽  
Data Sets ◽  
Data Set ◽  
Processing Technologies ◽  
Content Type ◽  
Public Data

Purpose The current popular image processing technologies based on convolutional neural network have the characteristics of large computation, high storage cost and low accuracy for tiny defect detection, which is contrary to the high real-time and accuracy, limited computing resources and storage required by industrial applications. Therefore, an improved YOLOv4 named as YOLOv4-Defect is proposed aim to solve the above problems. Design/methodology/approach On the one hand, this study performs multi-dimensional compression processing on the feature extraction network of YOLOv4 to simplify the model and improve the feature extraction ability of the model through knowledge distillation. On the other hand, a prediction scale with more detailed receptive field is added to optimize the model structure, which can improve the detection performance for tiny defects. Findings The effectiveness of the method is verified by public data sets NEU-CLS and DAGM 2007, and the steel ingot data set collected in the actual industrial field. The experimental results demonstrated that the proposed YOLOv4-Defect method can greatly improve the recognition efficiency and accuracy and reduce the size and computation consumption of the model. Originality/value This paper proposed an improved YOLOv4 named as YOLOv4-Defect for the detection of surface defect, which is conducive to application in various industrial scenarios with limited storage and computing resources, and meets the requirements of high real-time and precision.

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