e644bf4df923932a166ad38e3650d07d pmc_9965957.pdf 0f942ef882fd9fa7c183b45755b260ceeeeb7c78 pmc_9965957.pdf 46666a5b78b83cbbb3f0ed41ce38e170e60f04f31e141f455185f03bb4424601 pmc_9965957.pdf Title: Bioinformatic Tools for NGS-Based Metagenomics to Improve the Clinical Diagnosis of Emerging, Re-Emerging and New Viruses Subject: Epidemics and pandemics have occurred since the beginning of time, resulting in millions of deaths. Many such disease outbreaks are caused by viruses. Some viruses, particularly RNA viruses, are characterized by their high genetic variability, and this can affect certain phenotypic features: tropism, antigenicity, and susceptibility to antiviral drugs, vaccines, and the host immune response. The best strategy to face the emergence of new infectious genomes is prompt identification. However, currently available diagnostic tests are often limited for detecting new agents. High-throughput next-generation sequencing technologies based on metagenomics may be the solution to detect new infectious genomes and properly diagnose certain diseases. Metagenomic techniques enable the identification and characterization of disease-causing agents, but they require a large amount of genetic material and involve complex bioinformatic analyses. A wide variety of analytical tools can be used in the quality control and pre-processing of metagenomic data, filtering of untargeted sequences, assembly and quality control of reads, and taxonomic profiling of sequences to identify new viruses and ones that have been sequenced and uploaded to dedicated databases. Although there have been huge advances in the field of metagenomics, there is still a lack of consensus about which of the various approaches should be used for specific data analysis tasks. In this review, we provide some background on the study of viral infections, describe the contribution of metagenomics to this field, and place special emphasis on the bioinformatic tools (with their capabilities and limitations) available for use in metagenomic analyses of viral pathogens. Keywords: NGS; deep-sequencing; viruses; metagenomics; zoonosis; diagnostic tools Author: Marta Ibañez-Lligoña, Sergi Colomer-Castell, Alejandra González-Sánchez, Josep Gregori, Carolina Campos, Damir Garcia-Cehic, Cristina Andrés, Maria Piñana, Tomàs Pumarola, Francisco Rodríguez-Frias, Andrés Antón and Josep Quer Creator: LaTeX with hyperref Producer: pdfTeX-1.40.21 CreationDate: Wed Feb 22 04:47:46 2023 CET ModDate: Wed Feb 22 04:51:03 2023 CET Tagged: no UserProperties: no Suspects: no Form: none JavaScript: no Pages: 15 Encrypted: no Page size: 595.276 x 841.89 pts (A4) Page rot: 0 File size: 357103 bytes Optimized: no PDF version: 1.7 name type encoding emb sub uni object ID ------------------------------------ ----------------- ---------------- --- --- --- --------- XQKSOB+VnURWPalladioL Type 1 Custom yes yes no 10 0 CQTXPQ+URWPalladioL-Bold Type 1 Custom yes yes no 15 0 LYVHBA+URWPalladioL-Roma Type 1 Custom yes yes no 20 0 FBIMTW+URWPalladioL-Ital Type 1 Custom yes yes no 24 0 JUXSQN+VnURWPalladioL-Bold Type 1 Custom yes yes no 28 0 HOWKDX+TimesNewRomanPS-BoldItalicMT Type 1C WinAnsi yes yes no 46 0 Jhove (Rel. 1.28.0, 2023-05-18) Date: 2023-12-16 02:30:15 CET RepresentationInformation: pmc_9965957.pdf ReportingModule: PDF-hul, Rel. 1.12.4 (2023-03-16) LastModified: 2023-03-09 02:13:28 CET Size: 357103 Format: PDF Version: 1.7 Status: Well-Formed and valid SignatureMatches: PDF-hul MIMEtype: application/pdf PDFMetadata: Objects: 499 FreeObjects: 1 IncrementalUpdates: 0 DocumentCatalog: PageLayout: SinglePage PageMode: UseNone Outlines: Item: Title: Introduction Destination: section.1 Item: Title: What Is Metagenomics? Destination: section.2 Children: Item: Title: What Does Metagenomics Involve? Destination: subsection.2.1 Item: Title: Alternatives to Metagenomics Destination: subsection.2.2 Item: Title: Enrichment of Viruses in Metagenomic Samples Destination: subsection.2.3 Item: Title: Available Bioinformatic Tools Destination: section.3 Children: Item: Title: Bioinformatic Tools for Data QC Destination: subsection.3.1 Item: Title: Bioinformatic Tools for Data Pre-Processing Destination: subsection.3.2 Children: Item: Title: Tools for Quality Trimming Destination: subsubsection.3.2.1 Item: Title: Tools for Filtering Untargeted Reads Destination: subsubsection.3.2.2 Item: Title: Bioinformatic Tools for Assembly Destination: subsection.3.3 Children: Item: Title: Tools for Short-Read Assembly Destination: subsubsection.3.3.1 Item: Title: Tools for Long-Read Assembly Destination: subsubsection.3.3.2 Item: Title: Tools for Hybrid Assembly Destination: subsubsection.3.3.3 Item: Title: Bioinformatic Tools for Quality Control of Metagenome Assembly Destination: subsection.3.4 Item: Title: Tools for Identification of Known Viruses Destination: subsection.3.5 Item: Title: Bioinformatic Tools for Contig Binning Destination: subsection.3.6 Item: Title: Conclusions Destination: section.4 Item: Title: References Destination: section.4 Info: Title: Bioinformatic Tools for NGS-Based Metagenomics to Improve the Clinical Diagnosis of Emerging, Re-Emerging and New Viruses Author: Marta Ibañez-Lligoña, Sergi Colomer-Castell, Alejandra González-Sánchez, Josep Gregori, Carolina Campos, Damir Garcia-Cehic, Cristina Andrés, Maria Piñana, Tomàs Pumarola, Francisco Rodríguez-Frias, Andrés Antón and Josep Quer Subject: Epidemics and pandemics have occurred since the beginning of time, resulting in millions of deaths. Many such disease outbreaks are caused by viruses. Some viruses, particularly RNA viruses, are characterized by their high genetic variability, and this can affect certain phenotypic features: tropism, antigenicity, and susceptibility to antiviral drugs, vaccines, and the host immune response. The best strategy to face the emergence of new infectious genomes is prompt identification. However, currently available diagnostic tests are often limited for detecting new agents. High-throughput next-generation sequencing technologies based on metagenomics may be the solution to detect new infectious genomes and properly diagnose certain diseases. Metagenomic techniques enable the identification and characterization of disease-causing agents, but they require a large amount of genetic material and involve complex bioinformatic analyses. A wide variety of analytical tools can be used in the quality control and pre-processing of metagenomic data, filtering of untargeted sequences, assembly and quality control of reads, and taxonomic profiling of sequences to identify new viruses and ones that have been sequenced and uploaded to dedicated databases. Although there have been huge advances in the field of metagenomics, there is still a lack of consensus about which of the various approaches should be used for specific data analysis tasks. In this review, we provide some background on the study of viral infections, describe the contribution of metagenomics to this field, and place special emphasis on the bioinformatic tools (with their capabilities and limitations) available for use in metagenomic analyses of viral pathogens. Keywords: NGS; deep-sequencing; viruses; metagenomics; zoonosis; diagnostic tools Creator: LaTeX with hyperref Producer: pdfTeX-1.40.21 CreationDate: Wed Feb 22 04:47:46 CET 2023 ModDate: Wed Feb 22 04:51:03 CET 2023 ID: 0x3d409ac9a14517aaa80a898c743a49c4, 0x3d409ac9a14517aaa80a898c743a49c4 Filters: FilterPipeline: FlateDecode Fonts: Type1: Font: BaseFont: LYVHBA+URWPalladioL-Roma FontSubset: true FirstChar: 2 LastChar: 252 FontDescriptor: FontName: LYVHBA+URWPalladioL-Roma Flags: Symbolic FontBBox: -166, -283, 1021, 943 FontFile: true EncodingDictionary: Differences: true Font: BaseFont: FBIMTW+URWPalladioL-Ital FontSubset: true FirstChar: 2 LastChar: 121 FontDescriptor: FontName: FBIMTW+URWPalladioL-Ital Flags: Symbolic FontBBox: -170, -305, 1010, 941 FontFile: true EncodingDictionary: Differences: true Font: BaseFont: XQKSOB+VnURWPalladioL FontSubset: true FirstChar: 146 LastChar: 226 FontDescriptor: FontName: XQKSOB+VnURWPalladioL Flags: Symbolic FontBBox: -166, -283, 1021, 943 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