Signatures of transmission in within-hostM. tuberculosisvariation

Abstract

AbstractBackgroundBecauseM. tuberculosisevolves slowly, transmission clusters often contain multiple individuals with identical consensus genomes, making it difficult to reconstruct transmission chains. Finding additional sources of sharedM. tuberculosisvariation could help overcome this problem. Previous studies have reportedM. tuberculosisdiversity within infected individuals; however, whether within-host variation improves transmission inferences remains unclear.MethodsTo evaluate the transmission information present in within-hostM. tuberculosisvariation, we re-analyzed publicly available sequence data from three household transmission studies, using household membership as a proxy for transmission linkage between donor-recipient pairs.FindingsWe found moderate levels of minority variation present inM. tuberculosissequence data from cultured isolates that varied significantly across studies (mean: 6, 7, and 170 minority variants above a 1% minor allele frequency threshold, outside of PE/PPE genes). Isolates from household members shared more minority variants than did isolates from unlinked individuals in the three studies (mean 98 shared minority variants vs. 10; 0.8 vs. 0.2, and 0.7 vs. 0.2, respectively). Shared within-host variation was significantly associated with household membership (OR: 1.51 [1.30,1.71], for one standard deviation increase in shared minority variants). Models that included shared within-host variation improved the accuracy of predicting household membership in all three studies as compared to models without within-host variation (AUC: 0.95versus0.92, 0.99versus0.95, and 0.93versus0.91).InterpretationWithin-hostM. tuberculosisvariation persists through culture and could enhance the resolution of transmission inferences. The substantial differences in minority variation recovered across studies highlights the need to optimize approaches to recover and incorporate within-host variation into automated phylogenetic and transmission inference.FundingNIAID: 5K01AI173385