Afro-TB dataset as a large scale genomic data of Mycobacterium tuberuclosis in Africa
Abstract Mycobacterium tuberculosis (MTB) is a pathogenic bacterium accountable for 10.6 million new infections with tuberculosis (TB) in 2021. The fact that the genetic sequences of M. tuberculosis vary widely provides a basis for understanding how this bacterium causes disease, how the immune syst...
| Main Authors: | , , , , |
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| Format: | Article |
| Language: | English |
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Nature Portfolio
2023-04-01
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| Series: | Scientific Data |
| Online Access: | https://doi.org/10.1038/s41597-023-02112-3 |
| _version_ | 1797846057127772160 |
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| author | Meriem Laamarti Yasmine El Fathi Lalaoui Rachid Elfermi Rachid Daoud Achraf El Allali |
| author_facet | Meriem Laamarti Yasmine El Fathi Lalaoui Rachid Elfermi Rachid Daoud Achraf El Allali |
| author_sort | Meriem Laamarti |
| collection | DOAJ |
| description | Abstract Mycobacterium tuberculosis (MTB) is a pathogenic bacterium accountable for 10.6 million new infections with tuberculosis (TB) in 2021. The fact that the genetic sequences of M. tuberculosis vary widely provides a basis for understanding how this bacterium causes disease, how the immune system responds to it, how it has evolved over time, and how it is distributed geographically. However, despite extensive research efforts, the evolution and transmission of MTB in Africa remain poorly understood. In this study, we used 17,641 strains from 26 countries to create the first curated African Mycobacterium tuberculosis (MTB) classification and resistance dataset, containing 13,753 strains. We identified 157 mutations in 12 genes associated with resistance and additional new mutations potentially associated with resistance. The resistance profile was used to classify strains. We also performed a phylogenetic classification of each isolate and prepared the data in a format that can be used for phylogenetic and comparative analysis of tuberculosis worldwide. These genomic data will extend current information for comparative genomic studies to understand the mechanisms and evolution of MTB drug resistance. |
| first_indexed | 2024-04-09T17:48:51Z |
| format | Article |
| id | doaj.art-006239dd542541d9aa19f6f1f52ddb27 |
| institution | Directory Open Access Journal |
| issn | 2052-4463 |
| language | English |
| last_indexed | 2024-04-09T17:48:51Z |
| publishDate | 2023-04-01 |
| publisher | Nature Portfolio |
| record_format | Article |
| series | Scientific Data |
| spelling | doaj.art-006239dd542541d9aa19f6f1f52ddb272023-04-16T11:06:40ZengNature PortfolioScientific Data2052-44632023-04-011011710.1038/s41597-023-02112-3Afro-TB dataset as a large scale genomic data of Mycobacterium tuberuclosis in AfricaMeriem Laamarti0Yasmine El Fathi Lalaoui1Rachid Elfermi2Rachid Daoud3Achraf El Allali4African Genome Center, Mohammed VI Polytechnic UniversityAfrican Genome Center, Mohammed VI Polytechnic UniversityAfrican Genome Center, Mohammed VI Polytechnic UniversityAfrican Genome Center, Mohammed VI Polytechnic UniversityAfrican Genome Center, Mohammed VI Polytechnic UniversityAbstract Mycobacterium tuberculosis (MTB) is a pathogenic bacterium accountable for 10.6 million new infections with tuberculosis (TB) in 2021. The fact that the genetic sequences of M. tuberculosis vary widely provides a basis for understanding how this bacterium causes disease, how the immune system responds to it, how it has evolved over time, and how it is distributed geographically. However, despite extensive research efforts, the evolution and transmission of MTB in Africa remain poorly understood. In this study, we used 17,641 strains from 26 countries to create the first curated African Mycobacterium tuberculosis (MTB) classification and resistance dataset, containing 13,753 strains. We identified 157 mutations in 12 genes associated with resistance and additional new mutations potentially associated with resistance. The resistance profile was used to classify strains. We also performed a phylogenetic classification of each isolate and prepared the data in a format that can be used for phylogenetic and comparative analysis of tuberculosis worldwide. These genomic data will extend current information for comparative genomic studies to understand the mechanisms and evolution of MTB drug resistance.https://doi.org/10.1038/s41597-023-02112-3 |
| spellingShingle | Meriem Laamarti Yasmine El Fathi Lalaoui Rachid Elfermi Rachid Daoud Achraf El Allali Afro-TB dataset as a large scale genomic data of Mycobacterium tuberuclosis in Africa Scientific Data |
| title | Afro-TB dataset as a large scale genomic data of Mycobacterium tuberuclosis in Africa |
| title_full | Afro-TB dataset as a large scale genomic data of Mycobacterium tuberuclosis in Africa |
| title_fullStr | Afro-TB dataset as a large scale genomic data of Mycobacterium tuberuclosis in Africa |
| title_full_unstemmed | Afro-TB dataset as a large scale genomic data of Mycobacterium tuberuclosis in Africa |
| title_short | Afro-TB dataset as a large scale genomic data of Mycobacterium tuberuclosis in Africa |
| title_sort | afro tb dataset as a large scale genomic data of mycobacterium tuberuclosis in africa |
| url | https://doi.org/10.1038/s41597-023-02112-3 |
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