Gene evolutionary trajectories in Mycobacterium tuberculosis reveal temporal signs of selection.

Genetic differences between different Mycobacterium tuberculosis complex (MTBC) strains determine their ability to transmit within different host populations, their latency times, and their drug resistance profiles. Said differences usually emerge through de novo mutations and are maintained or discarded by the balance of evolutionary forces. Using a dataset of ∼5,000 strains representing global MTBC diversity, we determined the past and present selective forces that have shaped the current variability observed in the pathogen population. We identified regions that have evolved under changing types of selection since the time of the MTBC common ancestor. Our approach highlighted striking differences in the genome regions relevant for host­pathogen interaction and, in particular, suggested an adaptive role for the sensor protein of two-component systems. In addition, we applied our approach to successfully identify potential determinants of resistance to drugs administered as second-line tuberculosis treatments.

Cryptic Resistance Mutations Associated With Misdiagnoses of Multidrug-Resistant Tuberculosis.

Understanding why some multidrug-resistant tuberculosis cases are not detected by rapid phenotypic and genotypic routine clinical tests is essential to improve diagnostic assays and advance toward personalized tuberculosis treatment. Here, we combine whole-genome sequencing with single-colony phenotyping to identify a multidrug-resistant strain that had infected a patient for 9 years. Our investigation revealed the failure of rapid testing and genome-based prediction tools to identify the multidrug-resistant strain. The false-negative findings were caused by uncommon rifampicin and isoniazid resistance mutations. Although whole-genome sequencing data helped to personalize treatment, the patient developed extensively drug-resistant tuberculosis, highlighting the importance of coupling new diagnostic methods with appropriate treatment regimens.

Deciphering the Tangible Spatio-Temporal Spread of a 25-Year Tuberculosis Outbreak Boosted by Social Determinants.

Outbreak strains of Mycobacterium tuberculosis are promising candidates as targets in the search for intrinsic determinants of transmissibility, as they are responsible for many cases with sustained transmission; however, the use of low-resolution typing methods and restricted geographical investigations represent flaws in assessing the success of long-lived outbreak strains. We can now address the nature of outbreak strains by combining large genomic data sets and phylodynamic approaches. We retrospectively sequenced the whole genome of representative samples assigned to an outbreak circulating in the Canary Islands (the GC strain) since 1993, which accounts for ~20% of local tuberculosis cases. We selected a panel of specific single nucleotide polymorphism (SNP) markers for an in-silico search for additional outbreak-related sequences within publicly available tuberculosis genomic data. Using this information, we inferred the origin, spread, and epidemiological parameters of the GC strain. Our approach allowed us to accurately trace the historical and more recent dispersion of the GC strain. We provide evidence of a highly successful nature within the Canarian archipelago but limited expansion abroad. Estimation of epidemiological parameters from genomic data disagree with a distinctive biology of the GC strain. With the increasing availability of genomic data allowing for the accurate inference of strain spread and critical epidemiological parameters, we can now revisit the link between Mycobacterium tuberculosis genotypes and transmission, as is routinely carried out for SARS-CoV-2 variants of concern. We demonstrate that social determinants rather than intrinsically higher bacterial transmissibility better explain the success of the GC strain. Importantly, our approach can be used to trace and characterize strains of interest worldwide. IMPORTANCE Infectious disease outbreaks represent a significant problem for public health. Tracing outbreak expansion and understanding the main factors behind emergence and persistence remain critical to effective disease control. Our study allows researchers and public health authorities to use Whole-Genome Sequencing-based methods to trace outbreaks, and shows how available epidemiological information helps to evaluate the factors underpinning outbreak persistence. Taking advantage of all the freely available information placed in public repositories, researchers can accurately establish the expansion of an outbreak beyond original boundaries, and determine the potential risk of a strain to inform health authorities which, in turn, can define target strategies to mitigate expansion and persistence. Finally, we show the need to evaluate strain transmissibility in different geographic contexts to unequivocally associate spread to local or pathogenic factors, an important lesson taken from genomic surveillance of SARS-CoV-2.

An evolutionary functional genomics approach identifies novel candidate regions involved in isoniazid resistance in Mycobacterium tuberculosis.

Efforts to eradicate tuberculosis are hampered by the rise and spread of antibiotic resistance. Several large-scale projects have aimed to specifically link clinical mutations to resistance phenotypes, but they were limited in both their explanatory and predictive powers. Here, we combine functional genomics and phylogenetic associations using clinical strain genomes to decipher the architecture of isoniazid resistance and search for new resistance determinants. This approach has allowed us to confirm the main target route of the antibiotic, determine the clinical relevance of redox metabolism as an isoniazid resistance mechanism and identify novel candidate genes harboring resistance mutations in strains with previously unexplained isoniazid resistance. This approach can be useful for characterizing how the tuberculosis bacilli acquire resistance to new antibiotics and how to forestall them.

Genomic analyses of Mycobacterium tuberculosis from human lung resections reveal a high frequency of polyclonal infections.

Polyclonal infections occur when at least two unrelated strains of the same pathogen are detected in an individual. This has been linked to worse clinical outcomes in tuberculosis, as undetected strains with different antibiotic resistance profiles can lead to treatment failure. Here, we examine the amount of polyclonal infections in sputum and surgical resections from patients with tuberculosis in the country of Georgia. For this purpose, we sequence and analyse the genomes of Mycobacterium tuberculosis isolated from the samples, acquired through an observational clinical study (NCT02715271). Access to the lung enhanced the detection of multiple strains (40% of surgery cases) as opposed to just using a sputum sample (0-5% in the general population). We show that polyclonal infections often involve genetically distant strains and can be associated with reversion of the patient's drug susceptibility profile over time. In addition, we find different patterns of genetic diversity within lesions and across patients, including mutational signatures known to be associated with oxidative damage; this suggests that reactive oxygen species may be acting as a selective pressure in the granuloma environment. Our results support the idea that the magnitude of polyclonal infections in high-burden tuberculosis settings is underestimated when only testing sputum samples.

Tuberculosis in Liberia: high multidrug-resistance burden, transmission and diversity modelled by multiple importation events.

Tuberculosis (TB) surveillance is scarce in most African countries, even though it is the continent with the greatest disease incidence according to the World Health Organization. Liberia is within the 30 countries with the highest TB burden, probably as a consequence of the long civil war and the recent Ebola outbreak, both crippling the health system and depreciating the TB prevention and control programmes. Due to difficulties working in the country, there is a lack of resistance surveys and bacillus characterization. Here, we use genome sequencing of Mycobacteriumtuberculosis clinical isolates to fill this gap. Our results highlight that the bacillus population structure is dominated by lineage 4 strains that harbour an outstanding genetic diversity, higher than in the rest of Africa as a whole. Coalescent analyses demonstrate that strains currently circulating in Liberia were introduced several times beginning in the early year 600 CE until very recently coinciding with migratory movements associated with the civil war and Ebola epidemics. A higher multidrug-resistant (MDR)-TB frequency (23.5 %) than current estimates was obtained together with non-catalogued drug-resistance mutations. Additionally, 39 % of strains were in genomic clusters revealing that ongoing transmission is a major contribution to the TB burden in the country. Our report emphasizes the importance of TB surveillance and control in African countries where bacillus diversity, MDR-TB prevalence and transmission are coalescing to jeopardize TB control programmes.

The Future of TB Resistance Diagnosis: The Essentials on Whole Genome Sequencing and Rapid Testing Methods.

Tuberculosis resistance diagnostics have vastly improved in recent years thanks to the development of standardised phenotypic and molecular testing methods. However, these methods are either slow or limited in the number of resistant genotypes they can detect. With the advent of next-generation sequencing (NGS) we can sidestep all those problems, as we can sequence whole tuberculosis genomes at increasingly smaller costs and requiring less and less DNA. In this review, we explain how accumulated knowledge in the field has allowed us to go from phenotypic testing to molecular methods to Whole Genome Sequencing (WGS) for resistance diagnostics. We compare current diagnostic methods with WGS as to their efficacy in detecting resistant cases, and show how forthcoming advances in NGS technologies will be crucial in widespread implementation of WGS as a diagnostic tool.

The Future of TB Resistance Diagnosis: The Essentials on Whole Genome Sequencing and Rapid Testing Methods / El futuro del diagnóstico de la resistencia a la tuberculosis: lo imprescindible sobre la secuenciación completa del genoma y los métodos rápidos de diagnóstico

Tuberculosis resistance diagnostics have vastly improved in recent years thanks to the development of standardised phenotypic and molecular testing methods. However, these methods are either slow or limited in the number of resistant genotypes they can detect. With the advent of next-generation sequencing (NGS) we can sidestep all those problems, as we can sequence whole tuberculosis genomes at increasingly smaller costs and requiring less and less DNA. In this review, we explain how accumulated knowledge in the field has allowed us to go from phenotypic testing to molecular methods to Whole Genome Sequencing (WGS) for resistance diagnostics. We compare current diagnostic methods with WGS as to their efficacy in detecting resistant cases, and show how forthcoming advances in NGS technologies will be crucial in widespread implementation of WGS as a diagnostic tool

El diagnóstico de la tuberculosis resistente ha mejorado ampliamente en los últimos años gracias al desarrollo de pruebas estandarizadas de diagnóstico tanto fenotípicas como moleculares. Sin embargo, estas pruebas son o bien lentas o limitadas en el número de genotipos resistentes que son capaces de detectar. Con el auge de las nuevas tecnologías de secuenciación masiva podemos evitar esos problemas secuenciando el genoma completo cada vez a un coste más bajo y requiriendo cantidades menores de ADN. En esta revisión, explicamos cómo se ha podido progresar desde las pruebas fenotípicas a los métodos moleculares hasta la secuenciación del genoma completo para el diagnóstico de resistencias gracias a sucesivos descubrimientos en el campo. Comparamos la eficacia de la secuenciación del genoma completo para detectar casos resistentes con respecto a la de los métodos diagnósticos actuales, y mostramos cómo los avances futuros en esta tecnología serán cruciales para la implementación generalizada de esta herramienta diagnóstica