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A metagenomic analysis of the phase 2 Anopheles gambiae 1000 genomes dataset reveals a wide diversity of cobionts associated with field collected mosquitoes.

Authors :
Pastusiak, Andrzej
Reddy, Michael R.
Chen, Xiaoji
Hoyer, Isaiah
Dorman, Jack
Gebhardt, Mary E.
Carpi, Giovanna
Norris, Douglas E.
Pipas, James M.
Jackson, Ethan K.
Source :
Communications Biology. 5/30/2024, Vol. 7 Issue 1, p1-11. 11p.
Publication Year :
2024

Abstract

The Anopheles gambiae 1000 Genomes (Ag1000G) Consortium previously utilized deep sequencing methods to catalogue genetic diversity across African An. gambiae populations. We analyzed the complete datasets of 1142 individually sequenced mosquitoes through Microsoft Premonition's Bayesian mixture model based (BMM) metagenomics pipeline. All specimens were confirmed as either An. gambiae sensu stricto (s.s.) or An. coluzzii with a high degree of confidence (> 98% identity to reference). Homo sapiens DNA was identified in all specimens indicating contamination may have occurred either at the time of specimen collection, preparation and/or sequencing. We found evidence of vertebrate hosts in 162 specimens. 59 specimens contained validated Plasmodium falciparum reads. Human hepatitis B and primate erythroparvovirus-1 viral sequences were identified in fifteen and three mosquito specimens, respectively. 478 of the 1,142 specimens were found to contain bacterial reads and bacteriophage-related contigs were detected in 27 specimens. This analysis demonstrates the capacity of metagenomic approaches to elucidate important vector-host-pathogen interactions of epidemiological significance. A metagenomic analysis of 1,142 field-collected Anopheles gambiae mosquito specimens by the Microsoft Premonition Bayesian mixture model pipeline revealed a diverse set of vertebrate hosts, as well as the presence of Plasmodium parasites and other microbes. [ABSTRACT FROM AUTHOR]

Details

Language :
English
ISSN :
23993642
Volume :
7
Issue :
1
Database :
Academic Search Index
Journal :
Communications Biology
Publication Type :
Academic Journal
Accession number :
177597923
Full Text :
https://doi.org/10.1038/s42003-024-06337-9