Members of the Mycobacterium tuberculosis complex (MTBC) show distinct host adaptations, preferences and phenotypes despite being >99% identical at the nucleic acid level. Previous studies have explored gene expression changes between the members, however few studies have probed differences in gene essentiality. To better understand the functional impacts of the nucleic acid differences between Mycobacterium bovis and Mycobacterium tuberculosis, we used the Mycomar T7 phagemid delivery system to generate whole genome transposon libraries in laboratory strains of both species and compared the essentiality status of genes during growth under identical in vitro conditions. Libraries contained insertions in 54% of possible TA sites in M. bovis and 40% of those present in M. tuberculosis, achieving similar saturation levels to those previously reported for the MTBC. The distributions of essentiality across the functional categories were similar in both species. 527 genes were found to be essential in M. bovis whereas 477 genes were essential in M. tuberculosis and 370 essential genes were common in both species. CRISPRi was successfully utilised in both species to determine the impacts of silencing genes including wag31, a gene involved in peptidoglycan synthesis and Rv2182c/Mb2204c, a gene involved in glycerophospholipid metabolism. We observed species specific differences in the response to gene silencing, with the inhibition of expression of Mb2204c in M. bovis showing significantly less growth impact than silencing its orthologue (Rv2182c) in M. tuberculosis. Given that glycerophospholipid metabolism is a validated pathway for antimicrobials, our observations suggest that target vulnerability in the animal adapted lineages cannot be assumed to be the same as the human counterpart. This is of relevance for zoonotic tuberculosis as it implies that the development of antimicrobials targeting the human adapted lineage might not necessarily be effective against the animal adapted lineage. The generation of a transposon library and the first reported utilisation of CRISPRi in M. bovis will enable the use of these tools to further probe the genetic basis of survival under disease relevant conditions.

A definitive transcriptome atlas for the non‐coding expressed elements of the members of the Mycobacterium tuberculosis complex (MTBC) does not exist. Incomplete lists of non‐coding transcripts can be obtained for some of the reference genomes (e.g., M. tuberculosis H37Rv) but to what extent these transcripts have homologues in closely related species or even strains is not clear. This has implications for the analysis of transcriptomic data; non‐coding parts of the transcriptome are often ignored in the absence of formal, reliable annotation. Here, we review the state of our knowledge of non‐coding RNAs in pathogenic mycobacteria, emphasizing the disparities in the information included in commonly used databases. We then proceed to review ways of combining computational solutions for predicting the non‐coding transcriptome with experiments that can help refine and confirm these predictions.

This is the first report of the genetic requirements of an animal-adapted member of the Mycobacterium tuberculosis complex (MTBC) in a natural host. M. bovis has devastating impacts on cattle, and bovine tuberculosis is a considerable economic, animal welfare, and public health concern. The data highlight the importance of mycobacterial cholesterol catabolism and identify several new virulence factors.

A whole genome co-expression network was created using Mycobacterium tuberculosis transcriptomic data from publicly available RNA-sequencing experiments covering a wide variety of experimental conditions. The network includes expressed regions with no formal annotation, including putative short RNAs and untranslated regions of expressed transcripts, along with the protein-coding genes. These unannotated expressed transcripts were among the best-connected members of the module sub-networks, making up more than half of the "hub" elements in modules that include protein-coding genes known to be part of regulatory systems involved in stress response and host adaptation. This dataset provides a valuable resource for investigating the role of non-coding RNA, and conserved hypothetical proteins, in transcriptomic remodelling. Based on their connections to genes with known functional groupings and correlations with replicated host conditions, predicted expressed transcripts can be screened as suitable candidates for further experimental validation.

A definitive transcriptome atlas for the non-coding expressed elements of pathogenic mycobacteria does not exist. Incomplete lists of non-coding transcripts can be obtained for some of the reference genomes (e.g. Mycobacterium tuberculosis H37Rv) but to what extent these transcripts have homologues in closely related species or even strains is not clear. This has implications for the analysis of transcriptomic data; non-coding parts of the transcriptome are often ignored in the absence of formal, reliable annotation. Here, we review the state of our knowledge of non-coding RNAs in pathogenic mycobacteria, emphasising the disparities in the information included in commonly used databases. We then proceed to review ways of combining computational solutions for predicting the non- coding transcriptome with experiments that can help refine and confirm these predictions.

Members of the Mycobacterium tuberculosis complex (MTBC) show distinct host adaptations, preferences and phenotypes despite being >99% identical at the nucleic acid level. Previous studies have explored gene expression changes between the members, however few studies have probed differences in gene essentiality. To better understand the functional impacts of the nucleic acid differences between Mycobacterium bovis and Mycobacterium tuberculosis we used the Mycomar T7 phagemid delivery system to generate whole genome transposon libraries in laboratory strains of both species and compared the essentiality status of genes during growth under identical in vitro conditions. Libraries contained insertions in 54% of possible TA sites in M. bovis and 40% of those present in M. tuberculosis, achieving similar saturation levels to those previously reported for the MTBC. The distributions of essentiality across the functional categories were similar in both species. 527 genes were found to be essential in M. bovis whereas 477 genes were essential in M. tuberculosis and 370 essential genes were common in both species. CRISPRi was successfully utilised in both species to determine the impacts of silencing genes including wag31, a gene involved in peptidoglycan synthesis and Rv2182c/Mb2204c, a gene involved in glycerophospholipid metabolism. We observed species specific differences in the response to gene silencing, with the inhibition of expression of Mb2204c in M. bovis showing significantly less growth impact than silencing its ortholog (Rv2182c) in M. tuberculosis. Given that glycerophospholipid metabolism is a validated pathway for antimicrobials, our observations suggest that target vulnerability in the animal adapted lineages cannot be assumed to be the same as the human counterpart. This is of relevance for zoonotic tuberculosis as it implies that the development of antimicrobials targeting the human adapted lineage might not necessarily be effective against the animal adapted lineage. The generation of a transposon library and the first reported utilisation of CRISPRi in M. bovis will enable the use of these tools to further probe the genetic basis of survival under disease relevant conditions.

Tuberculosis has severe impacts in both humans and animals. Understanding the genetic basis of survival of both Mycobacterium tuberculosis, the human adapted species, and Mycobacterium bovis, the animal adapted species is crucial to deciphering the biology of both pathogens. There are several studies that identify the genes required for survival of M. tuberculosis in vivo using mouse models, however, there are currently no studies probing the genetic basis of survival of M. bovis in vivo. In this study we utilise transposon insertion sequencing in M. bovis to determine the genes required for survival in cattle. We identify genes encoding established mycobacterial virulence functions such as the ESX-1 secretion system, PDIM synthesis, mycobactin synthesis and cholesterol catabolism that are required in vivo. We show that, as in M. tuberculosis, phoPR is required by M. bovis in vivo despite the known defect in signalling through this system. Comparison to studies performed in glycerol adapted species such as M. bovis BCG and M. tuberculosis suggests that there are differences in the requirement genes involved in cholesterol import (mce4 operon), oxidation (hsd) and detoxification (cyp125). We report good correlation with existing mycobacterial virulence functions, but also find several novel virulence factors, including genes involved in protein mannosylation, aspartate metabolism and glycerol-phosphate metabolism. These findings further extend our knowledge of the genetic basis of survival in vivo in bacteria that cause tuberculosis and provide insight for the development of novel diagnostics and therapeutics.

A whole genome co-expression network was created using Mycobacterium tuberculosis transcriptomic data from publicly available RNA-sequencing experiments covering a wide variety of experimental conditions. The network includes expressed regions with no formal annotation, including putative short RNAs and untranslated regions of expressed transcripts, along with the protein-coding genes. These unannotated expressed transcripts were among the best-connected members of the module sub-networks, making up more than half of the 'hub' elements in modules that include protein-coding genes known to be part of regulatory systems involved in stress response and host adaptation.This dataset provides a valuable resource for investigating the role of non-coding RNA, and conserved hypothetical proteins, in transcriptomic remodelling. Based on their connections to genes with known functional groupings and correlations with replicated host conditions, predicted expressed transcripts can be screened as suitable candidates for further experimental validation. Non-coding RNA prediction and quantificationEach dataset was run through the R-package, baerhunter (Ozuna et al., 2019), using the 'feature_file_editor' function optimised to the most appropriate parameters for the sequencing depth (https://doi.org/10.5281/zenodo.7709329). 'Count_features' and 'tpm_norm_flagging' functions were used for transcript quantification and to identify low