Identification and Characterization of Mycobacterial Species Using Whole-Genome Sequences

Riojas, Marco A.; Frank, Andrew M.; Greenfield, Samuel R; King, Serina; Meehan, Conor J.; Strong, Michael; Wattam, Alice R.; Hazbón, Manzour Hernando

doi:10.1007/978-1-0716-1460-0_19

Cited by 2 publications

(1 citation statement)

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“…Whole-genome sequencing (WGS) can identify species and lineage, predict drug susceptibility with high accuracy through identifying speci c relevant mutations and has been heralded as a potential solution for the implementation of continuous surveillance and personalized therapy [7,8]. In principle, WGS provides the ultimate resolution for strain classi cation to trace infection sources and transmission networks and also allows for the simultaneous prediction of the complete antimicrobial susceptibility pro le of a given isolate.…”

Section: Introductionmentioning

confidence: 99%

Whole genome sequencing for tuberculosis disease species identification, lineage determination, and drug resistance detection in Kashgar prefecture, China

Liu,

Badeerhan,

Emam

et al. 2024

Preprint

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Background We aimed to use whole genome sequencing (WGS) to determine species and lineage composition and drug resistant profile in a high tuberculosis (TB)-burden region of China. Methods We conducted WGS to 1791 acid-fast staining positive isolates and culture-positive isolates collected from Kashgar prefecture in 2020. Bioinformatic analysis was applied to confirm species, lineage and drug resistant mutations. The drug susceptibility testing were performed on confirmed Mycobacterium tuberculosis complex(MTBC) isolates. We determined the accuracy of WGS by comparing with phenotypes. Results 95.03% (1702/1791) were identified MTBC, 3.18% (57/1791) were nontuberculous mycobacteria (NTM), 0.61% (11/1791) and 0.89%(16/1791) were Nocardia and Gordonia respectively, 4 were identified as mixed infection. MTBC were composed of lineage 2 (45.83%, 780/1702), lineage 3 (462/1702, 27.14%), lineage 4 (455/1702, 26.73%), lineage 1(1/1702, 0.06%) and M.bovis (La1, 4/1702, 0.24%). Resistance to rifampicin, ethambutol, fluoroquinolones, aminoglycosides and ethionamide were accurately predicted with sensitivity of 96.43%, 83.33%,100%, 100% and 94.74% by WGS, and resistance to isoniazid with the sensitivity of 81.62% . Conclusions WGS can be an important approach in assessing TB control strategy and for determining therapeutic schemes in high TB-burden regions. The drug resistant TB of Kashgar prefecture is at low level and the application of WGS may prevent the increase of resistance rate.

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Section: Introductionmentioning

confidence: 99%