Pooled profiling of natural Mycobacterium tuberculosis diversity: linking genes, bacterial behaviours, and clinical outcomes

Sequencing technologies have revolutionised bacterial research. Despite the remarkable progress in bacterial genome characterisation, knowledge of their gene functions and functional networks is lagging, which is not unexpected, considering that gene functions are often complex, context dependent, and redundant. Nonetheless, the primary bottleneck is technical: strategies for functional characterisation struggle to keep pace with exponentially increasing sequencing data. For example, the costs of bacterial genomic sequencing and analyses are now similar to those of phenotypic antibiotic susceptibility testing. Consequently, an enormous gap exists between genetic characterisation and a mechanistic understanding of gene function, especially when one looks beyond the few intensively investigated bacterial species. The classic approach to bacterial gene function characterisation involves assessing the effects of gene disruption (loss of function) or overexpression (gain of function) on specific phenotypes. Mutant libraries allow this approach to be applied to thousands of genes, providing a genome-wide perspective on gene function. In arrayed libraries, each mutant, having a single modified gene per genome, is stored and tested individually.1Zaslaver A Bren A Ronen M et al.A comprehensive library of fluorescent transcriptional reporters for Escherichia coli.Nat Methods. 2006; 3: 623-628Crossref PubMed Scopus (556) Google Scholar,2Baym M Shaket L Anzai IA Adesina O Barstow B Rapid construction of a whole-genome transposon insertion collection for Shewanella oneidensis by Knockout Sudoku.Nat Commun. 2016; 713270Crossref PubMed Scopus (40) Google Scholar Conversely, pooled libraries combine all mutants into a single sample. In the pooling approach, genome-wide mutagenesis (mainly done through transposon mutagenesis or CRISPR-based gene silencing) is coupled with mutant-specific barcode sequencing, allowing simultaneous evaluation of thousands of mutants during experimental challenges such as growth or antibiotic exposure.3Bosch B DeJesus MA Poulton NC et al.Genome-wide gene expression tuning reveals diverse vulnerabilities of M tuberculosis.Cell. 2021; 184: 4579-4592.e24Summary Full Text Full Text PDF PubMed Google Scholar,4Price MN Wetmore KM Waters RJ et al.Mutant phenotypes for thousands of bacterial genes of unknown function.Nature. 2018; 557: 503-509Crossref PubMed Scopus (290) Google Scholar However, genome-wide mutagenesis has limitations: it primarily focuses on single loss-of-function mutations and mostly ignores gene–gene interactions that might be required for conferring a distinct phenotype. Moreover, mutants artificially generated in laboratory strains might not occur naturally and are typically tested on a single genetic background. Notably, the effect of isogenic gene deletions on human disease cannot be inferred. An alternative approach is to study existing natural bacterial diversity shaped by short-term and long-term evolution. Whole-genome sequencing and phenotypic characterisation of a large number of bacterial isolates can help to identify mechanisms such as drug resistance, which could be overlooked when using other methods.5The CRyPTIC ConsortiumGenome-wide association studies of global Mycobacterium tuberculosis resistance to 13 antimicrobials in 10,228 genomes identify new resistance mechanisms.PLoS Biol. 2022; 20e3001755Google Scholar However, analysing these isolates could be challenging, as the isolates often have many thousand genetic variants, unlike isogenic mutant libraries. In traditional genome-wide association studies, genotypes are iteratively associated with the phenotype of interest, with the strongest associations considered probably causal. More recent approaches, summarised by the term phenogenomic analyses,6Boeck L Burbaud S Skwark M et al.Mycobacterium abscessus pathogenesis identified by phenogenomic analyses.Nat Microbiol. 2022; 7: 1431-1441Crossref PubMed Scopus (15) Google Scholar aim to integrate the complexity of the genetic effects, such as variant effects on protein function or epistatic interactions. Nonetheless, limitations persist, including those related to bacterial clonal progeny, small allele frequency, and effect size of genetic variants. Many of these limitations can be mitigated by increasing the sample size, albeit through increased experimental efforts. In an Article published in The Lancet Microbe, Sydney Stanley and colleagues presented a comprehensive approach elucidating the relationship among genetic variants, phenotypes, and clinical outcomes for Mycobacterium tuberculosis.7Stanley S Spaulding CN Liu Q et al.Identification of bacterial determinants of tuberculosis infection and treatment outcomes: a phenogenomic analysis of clinical strains.Lancet Microbe. 2024; https://doi.org/10.1016/S2666-5247(24)00022-3Summary Full Text Full Text PDF Google Scholar The authors integrated a unique barcode into 158 drug-susceptible M tuberculosis isolates obtained from individuals with pulmonary tuberculosis in Ho Chi Minh City, Viet Nam, pooled the isolates, and challenged this M tuberculosis pool with different experimental conditions. Deep sequencing of the barcodes revealed the clinical isolate composition of the pool before and after challenge, allowing the authors to quantify the relative fitness of each isolate in each condition. Fitness phenotypes correlated with cavitary lung disease and treatment failure, suggesting that these traits are valuable surrogate markers for clinical outcomes (herein named intermediate phenotypes). Remarkably, the authors identified reduced in-vitro fitness to be associated with poor clinical outcome. Notably, a causality of this association, for example delayed antibiotic killing of metabolically less active bacteria, remains to be established.8Lopatkin AJ Stokes JM Zheng EJ et al.Bacterial metabolic state more accurately predicts antibiotic lethality than growth rate.Nat Microbiol. 2019; 4: 2109-2117Crossref PubMed Scopus (134) Google Scholar To investigate the molecular determinants underlying these intermediate phenotypes, the authors coupled the phenotypic profiles with whole-genome sequencing and phenogenomic analyses. With this approach, the authors identified variants in Rv1339, a phosphodiesterase-encoding gene, and a subclade of lineage 1 strains (L1.1.1.1) associated with reduced fitness and clinical outcomes, underscoring the potential relevance to human disease. These bacterial traits and their associated genetic variations provide valuable insights into bacterial adaptation in tuberculosis, offering potential avenues for drug discovery and molecular diagnostics. Linking pooled phenotypic assessments with genome-wide associations might become a powerful tool in functional genomics. The scalability of pooled profiling, extending potentially to thousands of clinical isolates, would allow creation of expansive libraries that could be shared among scientists with different research aims and strategies. Comprehensive experimental approaches could be applied to many bacterial species and address bacterial phenotypes that go far beyond bacterial fitness.9Cain AK Barquist L Goodman AL et al.A decade of advances in transposon-insertion sequencing.Nat Rev Genet. 2020; 21: 526-540Crossref PubMed Scopus (0) Google Scholar Combined with advanced computational methods, such phenotyping strategies might be crucial in deconvoluting the intricate genetic networks that drive natural bacterial behaviours, thereby revealing the factors responsible for bacterial success and clinical failure. I declare no competing interests and acknowledge Andres Floto for his input in this Comment. I was supported by Swiss National Science Foundation (#185792, #215557), Cloëtta Foundation, and Goldschmidt-Jacobson Foundation. Identification of bacterial determinants of tuberculosis infection and treatment outcomes: a phenogenomic analysis of clinical strainsSlow 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.