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ABSTRACT Detection of mixed Mycobacterium tuberculosis (MTB) infections is essential, particularly when resistance mutations are present in minority bacterial populations that may affect patients’ disease evolution and treatment. Whole-genome sequencing (WGS) has extended the amount of key information available for the diagnosis of MTB infection, including the identification of mixed infections. Having genomic information at diagnosis for early intervention requires carrying out WGS directly on the clinical samples. However, few studies have been successful with this approach due to the low representation of MTB DNA in sputa. In this study, we evaluated the ability of a strategy based on specific MTB DNA enrichment by using a newly designed capture platform (MycoCap) to detect minority variants and mixed infections by WGS on controlled mixtures of MTB DNAs in a simulated sputum genetic background. A pilot study was carried out with 12 samples containing 98% of a DNA pool from sputa of patients without MTB infection and 2% of MTB DNA mixtures at different proportions. Our strategy allowed us to generate sequences with a quality equivalent to those obtained from culture: 62.5× depth coverage and 95% breadth coverage (for at least 20× reads). Assessment of minority variant detection was carried out by manual analysis and allowed us to identify heterozygous positions up to a 95:5 ratio. The strategy also automatically distinguished mixed infections up to a 90:10 proportion. Our strategy efficiently captures MTB DNA in a nonspecific genetic background, allows detection of minority variants and mixed infections, and is a promising tool for performing WGS directly on clinical samples. IMPORTANCE We present a new strategy to identify mixed infections and minority variants in Mycobacterium tuberculosis by whole-genome sequencing. The objective of the strategy is the direct detection in patient sputum; in this way, minority populations of resistant strains can be identified at the time of diagnosis, facilitating identification of the most appropriate treatment for the patient from the first moment. For this, a platform for capturing M. tuberculosis-specific DNA was designed to enrich the clinical sample and obtain quality sequences.

We present the first complete analysis of the epidemiological scenario around a reinfection by SARS-CoV-2, more severe than the first episode, including three cases preceding the reinfection, the reinfected case per se

We report a complex epidemiological scenario of a nosocomial COVID-19 outbreak in the second wave, based on WGS analysis. Initially, standard epidemiological findings led to the assumption of a homogeneous outbreak caused by a single SARS-CoV-2 strain.