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Population-based sequencing of Mycobacterium tuberculosis reveals how current population dynamics are shaped by past epidemics.

ABSTRACT: Transmission is a driver of tuberculosis (TB) epidemics in high-burden regions, with assumed negligible impact in low-burden areas. However, we still lack a full characterization of transmission dynamics in settings with similar and different burdens. Genomic epidemiology can greatly help to quantify transmission, but the lack of whole genome sequencing population-based studies has hampered its application. Here, we generate a population-based dataset from Valencia region and compare it with available datasets from different TB-burden settings to reveal transmission dynamics heterogeneity and its public health implications. We sequenced the whole genome of 785 Mycobacterium tuberculosis strains and linked genomes to patient epidemiological data. We use a pairwise distance clustering approach and phylodynamic methods to characterize transmission events over the last 150 years, in different TB-burden regions. Our results underscore significant differences in transmission between low-burden TB settings, i.e., clustering in Valencia region is higher (47.4%) than in Oxfordshire (27%), and similar to a high-burden area as Malawi (49.8%). By modeling times of the transmission links, we observed that settings with high transmission rate are associated with decades of uninterrupted transmission, irrespective of burden. Together, our results reveal that burden and transmission are not necessarily linked due to the role of past epidemics in the ongoing TB incidence, and highlight the need for in-depth characterization of transmission dynamics and specifically tailored TB control strategies.

SUBMITTER: Cancino-Munoz I

PROVIDER: S-EPMC9323001 | biostudies-literature |

REPOSITORIES: biostudies-literature

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Project description:Whole genome sequencing has revolutionised the interrogation of mycobacterial genomes. Recent studies have reported conflicting findings on the genomic stability of Mycobacterium tuberculosis during the evolution of drug resistance. In an age where whole genome sequencing is increasingly relied upon for defining the structure of bacterial genomes, it is important to investigate the reliability of next generation sequencing to identify clonal variants present in a minor percentage of the population. This study aimed to define a reliable cut-off for identification of low frequency sequence variants and to subsequently investigate genetic heterogeneity and the evolution of drug resistance in M. tuberculosis.Genomic DNA was isolated from single colonies from 14 rifampicin mono-resistant M. tuberculosis isolates, as well as the primary cultures and follow up MDR cultures from two of these patients. The whole genomes of the M. tuberculosis isolates were sequenced using either the Illumina MiSeq or Illumina HiSeq platforms. Sequences were analysed with an in-house pipeline.Using next-generation sequencing in combination with Sanger sequencing and statistical analysis we defined a read frequency cut-off of 30% to identify low frequency M. tuberculosis variants with high confidence. Using this cut-off we demonstrated a high rate of genetic diversity between single colonies isolated from one population, showing that by using the current sequencing technology, single colonies are not a true reflection of the genetic diversity within a whole population and vice versa. We further showed that numerous heterogeneous variants emerge and then disappear during the evolution of isoniazid resistance within individual patients. Our findings allowed us to formulate a model for the selective bottleneck which occurs during the course of infection, acting as a genomic purification event.Our study demonstrated true levels of genetic diversity within an M. tuberculosis population and showed that genetic diversity may be re-defined when a selective pressure, such as drug exposure, is imposed on M. tuberculosis populations during the course of infection. This suggests that the genome of M. tuberculosis is more dynamic than previously thought, suggesting preparedness to respond to a changing environment.

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Population-based sequencing of Mycobacterium tuberculosis reveals how current population dynamics are shaped by past epidemics.

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