Two billion people are infected with , leading to Mycobacterium tuberculosis 10 million new cases of active tuberculosis and 1.5 million deaths annually. Universal access to drug susceptibility testing (DST) has become a World Health Organization priority. We previously developed a software tool, , which provided offline species identification and drug Mykrobe predictor resistance predictions for from whole genome sequencing M. tuberculosis (WGS) data. Performance was insufficient to support the use of WGS as an alternative to conventional phenotype-based DST, due to mutation catalogue limitations.

The open sharing of genomic data provides an incredibly rich resource for the study of bacterial evolution and function and even anthropogenic activities such as the widespread use of antimicrobials. However, these data consist of genomes assembled with different tools and levels of quality checking, and of large volumes of completely unprocessed raw sequence data. In both cases, considerable computational effort is required before biological questions can be addressed. Here, we assembled and characterised 661,405 bacterial genomes retrieved from the European Nucleotide Archive (ENA) in November of 2018 using a uniform standardised approach. Of these, 311,006 did not previously have an assembly. We produced a searchable COmpact Bit-sliced Signature (COBS) index, facilitating the easy interrogation of the entire dataset for a specific sequence (e.g., gene, mutation, or plasmid). Additional MinHash and pp-sketch indices support genome-wide comparisons and estimations of genomic distance. Combined, this resource will allow data to be easily subset and searched, phylogenetic relationships between genomes to be quickly elucidated, and hypotheses rapidly generated and tested. We believe that this combination of uniform processing and variety of search/filter functionalities will make this a resource of very wide utility. In terms of diversity within the data, a breakdown of the 639,981 high-quality genomes emphasised the uneven species composition of the ENA/public databases, with just 20 of the total 2,336 species making up 90% of the genomes. The overrepresented species tend to be acute/common human pathogens, aligning with research priorities at different levels from individual interests to funding bodies and national and global public health agencies.

The Mycobacterium tuberculosis complex (MTBC) is composed of several highly genetically related species that can be broadly classified into those that are human-host adapted and those that possess the ability to propagate and transmit in a variety of wild and domesticated animals. Since the initial description of the bovine tubercle bacillus, now known as Mycobacterium bovis, by Theobald Smith in the late 1800's, isolates originating from a wide range of animal hosts have been identified and characterized as M. microti, M. pinnipedii, the Dassie bacillus, M. mungi, M. caprae, M. orygis and M. suricattae. This chapter outlines the events resulting in the identification of each of these animal-adapted species, their close genetic relationships, and how genome-based phylogenetic analyses of species-specific variation amongst MTBC members is beginning to unravel the events that resulted in the evolution of the MTBC and the observed host tropism between the human- and animal-adapted member species.

The Mycobacterium tuberculosis complex (MTBC) is the collective term given to the group of bacteria that cause tuberculosis (TB) in mammals. It has been reported that M. tuberculosis H37Rv, a standard reference MTBC strain, is attenuated in cattle compared to Mycobacterium bovis. However, as M. tuberculosis H37Rv was isolated in the early 1930s, and genetic variants are known to exist, we sought to revisit this question of attenuation of M. tuberculosis for cattle by performing a bovine experimental infection with a recent M. tuberculosis isolate. Here we report infection of cattle using M. bovis AF2122/97, M. tuberculosis H37Rv, and M. tuberculosis BTB1558, the latter isolated in 2008 during a TB surveillance project in Ethiopian cattle. We show that both M. tuberculosis strains caused reduced gross pathology and histopathology in cattle compared to M. bovis. Using M. tuberculosis H37Rv and M. bovis AF2122/97 as the extremes in terms of infection outcome, we used RNA-Seq analysis to explore differences in the peripheral response to infection as a route to identify biomarkers of progressive disease in contrast to a more quiescent, latent infection. Our work shows the attenuation of M. tuberculosis strains for cattle, and emphasizes the potential of the bovine model as a ‘One Health’ approach to inform human TB biomarker development and post-exposure vaccine development.

We present pandora, a novel pan-genome graph structure and algorithms for identifying variants across the full bacterial pan-genome. As much bacterial adaptability hinges on the accessory genome, methods which analyze SNPs in just the core genome have unsatisfactory limitations. Pandora approximates a sequenced genome as a recombinant of references, detects novel variation and pan-genotypes multiple samples. Using a reference graph of 578 Escherichia coli genomes, we compare 20 diverse isolates. Pandora recovers more rare SNPs than single-reference-based tools, is significantly better than picking the closest RefSeq reference, and provides a stable framework for analyzing diverse samples without reference bias.