PHDtools : A platform for pathogen detection and multi-dimensional genetic signatures decoding to realize pathogen genomics data analyses online
Copyright © 2024 Elsevier B.V. All rights reserved..
OBJECTIVES: Facing the emerging diseases, rapid identification of the pathogen and multi-dimensional characterization of the genomic features at both isolate-level and population-level through high-throughput sequencing data can provide invaluable information to guide the development of antiviral agents and strategies. However, a user-friendly program is in urgent need for clinical laboratories without bioinformatics background to decode the complex big genomics data.
METHODS: In this study, we developed an interactive online platform named PHDtools with a total of 15 functions to analyze metagenomics data to identify the potential pathogen and decode multi-dimensional genetic signatures including intra-/inter-host variations and lineage-level variations. The platform was applied to analyze the meta-genomic data of the samples collected from the 172 imported COVID-19 cases.
RESULTS: According to the analytical results of mNGS, 27 patients were found to have the co-infections of SARS-CoV-2 with either influenza virus (n = 9) or human picobirnavirus (n = 19). Enough coverages of all the assembled SARS-CoV-2 genomes provided the sub-lineages of Omicron variant, and the number of mutations in the non-structural genes and M gene was increased, as well as the intra-host variations occurred in E and M gene were under positive selection (Ka/Ks > 1). These findings of increased or changed mutations in the SARS-CoV-2 genome characterized the current adaptive evolution patterns of Omicron sub-lineages, and revealed the evolution speed of these sub-lineages might increase.
CONCLUSIONS: Consequently, the application of PHDtools has proved that this platform is accurate, user-friendly and convenient for clinical users who are deficient in bioinformatics, and the clinical monitor of SARS-CoV-2 genomes by PHDtools also highlighted the potential evolution features of current SARS-CoV-2 and indicated that the development of anti-SARS-CoV-2 agents and new-designed vaccines should incorporate the gene variations other than S gene.
| Medienart: |
E-Artikel |
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| Erscheinungsjahr: |
2024 |
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| Erschienen: |
2024 |
| Enthalten in: |
Zur Gesamtaufnahme - volume:909 |
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| Enthalten in: |
Gene - 909(2024) vom: 30. März, Seite 148306 |
| Sprache: |
Englisch |
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| Beteiligte Personen: |
Xiong, Dongyan [VerfasserIn] |
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| Links: |
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| Themen: |
Antiviral Agents |
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| Anmerkungen: |
Date Completed 26.03.2024 Date Revised 26.03.2024 published: Print-Electronic Citation Status MEDLINE |
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| doi: |
10.1016/j.gene.2024.148306 |
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| funding: |
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| Förderinstitution / Projekttitel: |
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NLM368985792 |
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| 100 | 1 | |a Xiong, Dongyan |e verfasserin |4 aut | |
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| 500 | |a published: Print-Electronic | ||
| 500 | |a Citation Status MEDLINE | ||
| 520 | |a Copyright © 2024 Elsevier B.V. All rights reserved. | ||
| 520 | |a OBJECTIVES: Facing the emerging diseases, rapid identification of the pathogen and multi-dimensional characterization of the genomic features at both isolate-level and population-level through high-throughput sequencing data can provide invaluable information to guide the development of antiviral agents and strategies. However, a user-friendly program is in urgent need for clinical laboratories without bioinformatics background to decode the complex big genomics data | ||
| 520 | |a METHODS: In this study, we developed an interactive online platform named PHDtools with a total of 15 functions to analyze metagenomics data to identify the potential pathogen and decode multi-dimensional genetic signatures including intra-/inter-host variations and lineage-level variations. The platform was applied to analyze the meta-genomic data of the samples collected from the 172 imported COVID-19 cases | ||
| 520 | |a RESULTS: According to the analytical results of mNGS, 27 patients were found to have the co-infections of SARS-CoV-2 with either influenza virus (n = 9) or human picobirnavirus (n = 19). Enough coverages of all the assembled SARS-CoV-2 genomes provided the sub-lineages of Omicron variant, and the number of mutations in the non-structural genes and M gene was increased, as well as the intra-host variations occurred in E and M gene were under positive selection (Ka/Ks > 1). These findings of increased or changed mutations in the SARS-CoV-2 genome characterized the current adaptive evolution patterns of Omicron sub-lineages, and revealed the evolution speed of these sub-lineages might increase | ||
| 520 | |a CONCLUSIONS: Consequently, the application of PHDtools has proved that this platform is accurate, user-friendly and convenient for clinical users who are deficient in bioinformatics, and the clinical monitor of SARS-CoV-2 genomes by PHDtools also highlighted the potential evolution features of current SARS-CoV-2 and indicated that the development of anti-SARS-CoV-2 agents and new-designed vaccines should incorporate the gene variations other than S gene | ||
| 650 | 4 | |a Journal Article | |
| 650 | 4 | |a Genomics | |
| 650 | 4 | |a Multi-dimensional | |
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| 650 | 4 | |a Pathogen detection | |
| 650 | 4 | |a Variation identification | |
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| 700 | 1 | |a Zhang, Xiaoxu |e verfasserin |4 aut | |
| 700 | 1 | |a Xu, Bohan |e verfasserin |4 aut | |
| 700 | 1 | |a Shi, Mengjuan |e verfasserin |4 aut | |
| 700 | 1 | |a Chen, Min |e verfasserin |4 aut | |
| 700 | 1 | |a Dong, Zhuo |e verfasserin |4 aut | |
| 700 | 1 | |a Zhong, Jie |e verfasserin |4 aut | |
| 700 | 1 | |a Gong, Rui |e verfasserin |4 aut | |
| 700 | 1 | |a Wu, Chang |e verfasserin |4 aut | |
| 700 | 1 | |a Li, Ji |e verfasserin |4 aut | |
| 700 | 1 | |a Wei, Hongping |e verfasserin |4 aut | |
| 700 | 1 | |a Yu, Junping |e verfasserin |4 aut | |
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