Identification of bacterial determinants of tuberculosis infection and treatment outcomes: a phenogenomic analysis of clinical strains

Sydney Stanley; Caitlin N Spaulding; Qingyun Liu; Michael R Chase; Dang Thi Minh Ha; Phan Vuong Khac Thai; Nguyen Huu Lan; Do Dang Anh Thu; Nguyen Le Quang; Jessica Brown; Nathan D Hicks; Xin Wang; Maximillian Marin; Nicole C Howard; Andrew J Vickers; Wiktor M Karpinski; Michael C Chao; Maha R Farhat; Maxine Caws; Sarah J Dunstan; Nguyen Thuy Thuong Thuong; Sarah M Fortune

doi:10.1016/S2666-5247(24)00022-3

Identification of bacterial determinants of tuberculosis infection and treatment outcomes: a phenogenomic analysis of clinical strains

Lancet Microbe. 2024 May 6:S2666-5247(24)00022-3. doi: 10.1016/S2666-5247(24)00022-3. Online ahead of print.

Authors

Sydney Stanley¹, Caitlin N Spaulding¹, Qingyun Liu¹, Michael R Chase¹, Dang Thi Minh Ha², Phan Vuong Khac Thai², Nguyen Huu Lan², Do Dang Anh Thu³, Nguyen Le Quang³, Jessica Brown¹, Nathan D Hicks¹, Xin Wang¹, Maximillian Marin⁴, Nicole C Howard¹, Andrew J Vickers¹, Wiktor M Karpinski¹, Michael C Chao¹, Maha R Farhat⁵, Maxine Caws⁶, Sarah J Dunstan⁷, Nguyen Thuy Thuong Thuong⁸, Sarah M Fortune⁹

Affiliations

¹ Department of Immunology and Infectious Diseases, Harvard T H Chan School of Public Health, Boston, MA, USA.
² Pham Ngoc Thach Hospital, Ho Chi Minh City, Viet Nam.
³ Oxford University Clinical Research Unit, Hospital for Tropical Diseases, Ho Chi Minh City, Viet Nam.
⁴ Department of Biomedical Informatics, Harvard Medical School, Boston, MA, USA; Department of Systems Biology, Harvard Medical School, Boston, MA, USA.
⁵ Department of Biomedical Informatics, Harvard Medical School, Boston, MA, USA; Pulmonary and Critical Care Medicine, Massachusetts General Hospital, Boston, MA, USA.
⁶ Liverpool School of Tropical Medicine, Liverpool, UK; Birat Nepal Medical Trust, Kathmandu, Nepal.
⁷ Department of Infectious Diseases, University of Melbourne at the Peter Doherty Institute for Infection and Immunity, Parkville, VIC, Australia.
⁸ Oxford University Clinical Research Unit, Hospital for Tropical Diseases, Ho Chi Minh City, Viet Nam; Nuffield Department of Medicine, Centre for Tropical Medicine and Global Health, University of Oxford, Oxford, UK.
⁹ Department of Immunology and Infectious Diseases, Harvard T H Chan School of Public Health, Boston, MA, USA; Ragon Institute of MGH, MIT, and Harvard, Cambridge, MA, USA; Broad Institute of MIT and Harvard, Cambridge, MA, USA. Electronic address: sfortune@hsph.harvard.edu.

PMID: 38734030
DOI: 10.1016/S2666-5247(24)00022-3

Abstract

Background: Bacterial diversity could contribute to the diversity of tuberculosis infection and treatment outcomes observed clinically, but the biological basis of this association is poorly understood. The aim of this study was to identify associations between phenogenomic variation in Mycobacterium tuberculosis and tuberculosis clinical features.

Methods: We developed a high-throughput platform to define phenotype-genotype relationships in M tuberculosis clinical isolates, which we tested on a set of 158 drug-sensitive M tuberculosis strains sampled from a large tuberculosis clinical study in Ho Chi Minh City, Viet Nam. We tagged the strains with unique genetic barcodes in multiplicate, allowing us to pool the strains for in-vitro competitive fitness assays across 16 host-relevant antibiotic and metabolic conditions. Relative fitness was quantified by deep sequencing, enumerating output barcode read counts relative to input normalised values. We performed a genome-wide association study to identify phylogenetically linked and monogenic mutations associated with the in-vitro fitness phenotypes. These genetic determinants were further associated with relevant clinical outcomes (cavitary disease and treatment failure) by calculating odds ratios (ORs) with binomial logistic regressions. We also assessed the population-level transmission of strains associated with cavitary disease and treatment failure using terminal branch length analysis of the phylogenetic data.

Findings: M tuberculosis clinical strains had diverse growth characteristics in host-like metabolic and drug conditions. These fitness phenotypes were highly heritable, and we identified monogenic and phylogenetically linked variants associated with the fitness phenotypes. These data enabled us to define two genetic features that were associated with clinical outcomes. First, mutations in Rv1339, a phosphodiesterase, which were associated with slow growth in glycerol, were further associated with treatment failure (OR 5·34, 95% CI 1·21-23·58, p=0·027). Second, we identified a phenotypically distinct slow-growing subclade of lineage 1 strains (L1.1.1.1) that was associated with cavitary disease (OR 2·49, 1·11-5·59, p=0·027) and treatment failure (OR 4·76, 1·53-14·78, p=0·0069), and which had shorter terminal branch lengths on the phylogenetic tree, suggesting increased transmission.

Interpretation: Slow growth under various antibiotic and metabolic conditions served as in-vitro intermediate phenotypes underlying the association between M tuberculosis monogenic and phylogenetically linked mutations and outcomes such as cavitary disease, treatment failure, and transmission potential. These data suggest that M tuberculosis growth regulation is an adaptive advantage for bacterial success in human populations, at least in some circumstances. These data further suggest markers for the underlying bacterial processes that contribute to these clinical outcomes.

Funding: National Health and Medical Research Council/A∗STAR, National Institutes of Allergy and Infectious Diseases, National Institute of Child Health and Human Development, and the Wellcome Trust Fellowship in Public Health and Tropical Medicine.