Explore the vast range of titles available.

Culturing and genomic sequencing of Mycobacterium tuberculosis (MTB) from tuberculosis (TB) cases is the basis for many research and clinical applications. The alternative, culture-free sequencing from diagnostic samples, is promising but poses challenges to obtain and analyse the MTB genome. Paradoxically, culture is assumed to impose a diversity bottleneck, which, if true, would entail unexplored consequences. To unravel this paradox we generate high-quality genomes of sputum-culture pairs from two different settings after developing a workflow for sequencing from sputum and a tailored bioinformatics analysis. Careful downstream comparisons reveal sources of sputum-culture incongruences due to false positive/negative variation associated with factors like low input MTB DNA or variable genomic depths. After accounting for these factors, contrary to the bottleneck dogma, we identify a 97% variant agreement within sputum-culture pairs, with a high correlation also in the variants’ frequency (0.98). The combined analysis from five different settings and more than 100 available samples shows that our results can be extrapolated to different TB epidemic scenarios, demonstrating that for the cases tested culture accurately mirrors clinical samples. Comparison of Mycobacterium tuberculosis genetic diversity between diagnostic sputum and paired cultures shows a high correlation in the presence and frequency of variants when analyzing samples from five different tuberculosis incidence settings.

The Mycobacterium tuberculosis complex (MTBC) comprises the species that causes tuberculosis (TB) which affects 10 million people every year. A robust classification of species, lineages, and sub-lineages is important to explore associations with drug resistance, epidemiological patterns or clinical outcomes. We present a rapid and easy-to-follow methodology to classify clinical TB samples into the main MTBC clades. Approaches are based on the identification of lineage and sub-lineage diagnostic SNP using a real-time PCR high resolution melting assay and classic Sanger sequencing from low-concentrated, low quality DNA. Thus, suitable for implementation in middle and low-income countries. Once we validated our molecular procedures, we characterized a total of 491 biological samples from human and cattle hosts, representing countries with different TB burden. Overall, we managed to genotype ~95% of all samples despite coming from unpurified and low-concentrated DNA. Our approach also allowed us to detect zoonotic cases in eight human samples from Nigeria. To conclude, the molecular techniques we have developed, are accurate, discriminative and reproducible. Furthermore, it costs less than other classic typing methods, resulting in an affordable alternative method in TB laboratories.

Tuberculosis remains one of the main causes of death worldwide. The long and cumbersome process of culturing Mycobacterium tuberculosis complex (MTBC) bacteria has encouraged the development of specific molecular tools for detecting the pathogen. Most of these tools aim to become novel tuberculosis diagnostics, and big efforts and resources are invested in their development, looking for the endorsement of the main public health agencies. Surprisingly, no study had been conducted where the vast amount of genomic data available is used to identify the best MTBC diagnostic markers. In this work, we use large-scale comparative genomics to provide a catalog of 30 characterized loci that are unique to the MTBC. Some of these genes could be targeted to assess the physiological status of the bacilli. Remarkably, none of the conventional MTBC markers is in our catalog. In addition, we develop a qPCR assay to accurately quantify MTBC DNA in clinical samples.

Culturing Mycobacterium tuberculosis (MTB) from tuberculosis cases is the basis for many research and clinical applications. Paradoxically, it is assumed to impose a diversity bottleneck, which, if true, would entail unexplored consequences. The alternative, culture-free sequencing from diagnostic samples, is a promising but challenging approach both to obtain and analyse the MTB genome from the complex sample. This study obtains high-quality genomes of sputum-culture pairs from two different settings after developing a workflow for sequencing from sputum and a tailored bioinformatics pipeline. Our approach reveals that 88% of variants called in culture-free sequencing analysis are false positives due to supplementary alignments, mostly in enriched-sputa samples. Overall, contrary to the bottleneck dogma, we identify a 97% variant agreement within sputum-culture pairs, with a high correlation also in the variants frequency (0.98). Our findings extrapolate to all publicly available data, thus demonstrating that in most cases culture accurately mirrors clinical samples.Competing Interest StatementThe authors have declared no competing interest.