How to sequence 10,000 bacterial genomes and retain your sanity: an accessible, efficient and global approach
Non-typhoidal Salmonella(NTS)are typically associated with enterocolitis and linked to the industrialisation of food production. In recent years, NTS has been associated with invasive disease (iNTS disease) causing an estimated 77,000 deaths each year worldwide; 80% of mortality occurs in sub-Sahara...
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Published in | Access microbiology Vol. 4; no. 5 |
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Main Authors | , , , , , , , , , , , , , , , , , |
Format | Journal Article |
Language | English |
Published |
18.05.2022
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Online Access | Get full text |
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Summary: | Non-typhoidal Salmonella(NTS)are typically associated with enterocolitis and linked to the industrialisation of food production. In recent years, NTS has been associated with invasive disease (iNTS disease) causing an estimated 77,000 deaths each year worldwide; 80% of mortality occurs in sub-Saharan Africa. New clades of S. Typhimurium and S. Enteritidis have been identified, which are characterised by genomic degradation, altered prophage repertoires and novel multidrug resistant plasmids. To understand how these clades are contributing to the burden and severity of iNTS disease, it is crucial to expand genome-based surveillance to cover more countries, and incorporate historical isolates to generate an evolutionary timeline of the development of iNTS.
We developedand validateda robust and inexpensive method for large-scale collection and sequencing of bacterial genomes. The “10,000 Salmonella genomes” project established a worldwide research collaboration to generate information relevant to the epidemiology, drug resistance and virulence factors of Salmonellae using a whole-genome sequencing approach. By streamlining collection of isolates and developing an efficient logistics pipeline, we gathered 10,419 clinical and environmental isolates from collections in low and middle-income countries within six months. Genome sequences are now available for isolates from 51 countries/territories dating from 1949 to 2017, with ~80 % representing African and Latin-American datasets. Our method can be applied to other large sample collections that require maximisation of resources within a limited timeframe. Detailed genome analyses are in progress and it is hoped that the resulting data will contribute to public health control strategies in low and middle-income countries. |
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ISSN: | 2516-8290 2516-8290 |
DOI: | 10.1099/acmi.ac2021.po0349 |