Macedo, RitaIsidro, JoanaFerreira, RitaPinto, MiguelBorges, VítorDuarte, SílviaVieira, LuísGomes, João Paulo2024-01-242024-01-242023-02-02Int J Mol Sci. 2023 Feb 2;24(3):2912. doi: 10.3390/ijms240329121661-6596http://hdl.handle.net/10400.18/8973(This article belongs to the Special Issue CRISPR-Cas in Genomic Manipulation and Antimicrobial Resistance)The application of whole genome sequencing of Mycobacterium tuberculosis directly on clinical samples has been investigated as a means to avoid the time-consuming need for culture isolation that can lead to a potential prolonged suboptimal antibiotic treatment. We aimed to provide a proof-of-concept regarding the application of the molecular capture of M. tuberculosis genomes directly from positive sputum samples as an approach for epidemiological and drug susceptibility predictions. Smear-positive sputum samples (n = 100) were subjected to the SureSelectXT HS Target Enrichment protocol (Agilent Technologies, Santa Clara, CA, USA) and whole-genome sequencing analysis. A higher number of reads on target were obtained for higher smear grades samples (i.e., 3+ followed by 2+). Moreover, 37 out of 100 samples showed ≥90% of the reference genome covered with at least 10-fold depth of coverage (27, 9, and 1 samples were 3+, 2+, and 1+, respectively). Regarding drug-resistance/susceptibility prediction, for 42 samples, ≥90% of the >9000 hits that are surveyed by TB-profiler were detected. Our results demonstrated that M. tuberculosis genome capture and sequencing directly from clinical samples constitute a potential valid backup approach for phylogenetic inferences and resistance prediction, essentially in settings when culture is not routinely performed or for samples that fail to grow.engMycobacterium tuberculosisRNA-baitsMolecular CaptureResistanceSurveillanceTarget EnrichmentDrug TherapyEpidemiologyMicrobiologyGeneticsWhole Genome SequencingTuberculosisnfecções RespiratóriasResistência aos AntimicrobianosMolecular Capture of Mycobacterium tuberculosis Genomes Directly from Clinical Samples: A Potential Backup Approach for Epidemiological and Drug Susceptibility Inferencesjournal article10.3390/ijms24032912