A new method for detecting mixed Mycobacterium tuberculosis infection and reconstructing constituent strains provides insights into transmission
MixInfect2 accurately detects samples with evidence of mixed infection from short-read WGS data and provides an excellent estimate of the mixture proportions. While there are limitations in reconstructing the constituent strain sequences of mixed samples, we present recommendations for the best approach to include these isolates in further analyses.
Authors
- Benjamin Sobkowiak (ORCID: https://orcid.org/0000-0002-1382-1137)
- Melanie H. Chitwood (ORCID: https://orcid.org/0000-0002-9289-5694)
- Louis Grandjean (ORCID: https://orcid.org/0000-0002-1457-8327)
- Taane Gregory Clark (ORCID: https://orcid.org/0000-0001-8985-9265)
- Valeriu Crudu (ORCID: https://orcid.org/0000-0001-5059-8002)
- Ted Cohen (ORCID: https://orcid.org/0000-0002-8091-7198)
- Patrick Cudahy (ORCID: https://orcid.org/0000-0003-4462-9567)
- Katharine S. Walter (ORCID: https://orcid.org/0000-0003-0065-2204)
- Caroline Colijn (ORCID: https://orcid.org/0000-0001-6097-6708)
Institutions
- Simon Fraser University (CA)
- University of Utah (US)
- Yale University (US)
- London School of Hygiene & Tropical Medicine (GB)
- Phthisiopneumology Institute "Chiril Draganiuc" (MD)
- Université Bourgogne Franche-Comté (FR)
- Institute of Infection and Immunity (CA)
- University College London (GB)
Publication Details
- Journal
- Genome Medicine
- Published
- 2025-01-27
- DOI
- https://doi.org/10.1186/s13073-025-01430-y
- Citations
- 3
- Primary Topic
- Mycobacterium research and diagnosis
- Type
- article
- Field-Weighted Citation Impact
- 4.06
Funders
- National Institute of Allergy and Infectious Diseases