Genome analyses of 174 strains of Mycobacterium tuberculosis provide insight into the evolution of drug resistance and reveal potential drug targets

Description of Bacterial RNA Transcripts Detected in Mycobacterium tuberculosis - Infected Cells from Peripheral Human Granulomas using Single Cell RNA Sequencing

Mycobacterium tuberculosis (Mtb) remains a global human health threat and a significant cause of human morbidity and mortality. We document here the capture of Mtb transcripts in libraries designed to amplify eukaryotic mRNA. These reads are often considered spurious or nuisance and are rarely investigated. Because of early literature suggesting the possible presence of polyadenylated transcripts in Mtb RNA, we included the H37Rv Mtb reference genome when assembling scRNA seq libraries from fine needle aspirate samples from patients presenting at the TB clinic, Port Moresby General Hospital, Papua New Guinea. We used 10X Genomics single-cell RNA sequencing transcriptomics pipeline, which initiates mRNA amplification with poly-T primers on ~30-micron beads designed to capture, in this case, human mRNA associated with individual cells in the clinical samples. Utilizing the 10X Genomics Cell Ranger tool to align sequencing reads, we consistently detected bacterial small and large ribosomal subunit RNA sequences (rrs and rrl, respectively) and other bacterial gene transcripts in the cell culture and patient samples. We interpret Mtb reads associated with the host cell's unique molecular identifier (UMI) and transcriptome to indicate infection of that individual host cell. The Mtb transcripts detected showed frequent sequence variation from the reference genome, with greater than 90% of the rrs or rrl reads from many clinical samples having at least 1 sequence difference compared to the H37Rv reference genome. The data presented includes only bacterial sequences from patients with TB infections that were confirmed by the hospital pathology lab using acid-fast microscopy and/or GeneXpert analysis. The repeated, non-random nature of the sequence variations detected in Mtb rrs and rrl transcripts from multiple patients, suggests that, even though this appears to be a stochastic process, there is possibly some selective pressure that limits the types and locations of sequence variation allowed. The variation does not appear to be entirely artefactual, and it is hypothesized that it could represent an additional mechanism of adaptation to enhance bacterial fitness against host defenses or chemotherapy.

Discordance in Phenotypic and Genotypic Susceptibility Testing for Streptomycin Due to Nonsynonymous/Nonsense/Deletion Frame-Shift Mutations in Gidb Among Clinical Mycobacterium tuberculosis Isolates in Kuwait

OBJECTIVE

Increasing reports of resistance to newer anti-tuberculosis drugs have prompted the search for other alternative drugs. Streptomycin could be used for the treatment of drug-resistant tuberculosis if susceptibility of Mycobacterium tuberculosis isolate to streptomycin could be accurately detected. We performed phenotypic and genotypic drug susceptibility testing (DST) of 118 M. tuberculosis isolates for streptomycin.

MATERIALS AND METHODS

Fifty pansusceptible and 68 multidrug-resistant M. tuberculosis (MDR-TB) isolates were used. Phenotypic DST for streptomycin, rifampicin, isoniazid and ethambutol was performed by mycobacteria growth indicator tube (MGIT) 960 System. Genotypic DST was done by GenoTypeMTBDRplus assay for rifampicin and isoniazid and by PCR-sequencing of rpsL, rrs and gidB genes for streptomycin. MDR-TB isolates were genotyped by spoligotyping.

RESULTS

Phenotypic DST identified 50 isolates susceptible to all four drugs (pansusceptible). Sixty-one of 68 MDR-TB isolates were resistant to streptomycin. Genotypic testing for rifampicin and isoniazid yielded expected results. Fifty pansusceptible and 7 streptomycin-susceptible MDR-TB isolates contained no mutation in rpsL or rrs, while 47, 2 and 1 STR-resistant isolate contained rpsL, rrs and rpsL + rrs mutations, respectively. Of the remaining 11 STR-resistant MDR-TB, 9 isolates contained deletion frame-shift/nonsynonymous mutations in gidB. Surprisingly, 13 pansusceptible isolates also contained deletion frame-shift/nonsense/nonsynonymous mutations in gidB. Also, 30 of 68 MDR-TB but only 2 of 50 pansusceptible isolates belonged to the Beijing genotype.

CONCLUSIONS

Our data show that, like ifampicin, ethambutol and pyrazinamide, streptomycin also exhibits discordant phenotypic and genotypic DST results for some M. tuberculosis isolates. Hence, streptomycin should be included in therapy regimens only if both phenotypic and genotypic resistance testing indicate susceptibility to avoid amplification of resistance and drug toxicity.

Large-scale Pan Genomic Analysis of Mycobacterium tuberculosis Reveals Key Insights Into Molecular Evolutionary Rate of Specific Processes and Functions

Mycobacterium tuberculosis (Mtb) is the causative agent of tuberculosis (TB), an infectious disease that is a major killer worldwide. Due to selection pressure caused by the use of antibacterial drugs, Mtb is characterised by mutational events that have given rise to multi drug resistant (MDR) and extensively drug resistant (XDR) phenotypes. The rate at which mutations occur is an important factor in the study of molecular evolution, and it helps understand gene evolution. Within the same species, different protein-coding genes evolve at different rates. To estimate the rates of molecular evolution of protein-coding genes, a commonly used parameter is the ratio dN/dS, where dN is the rate of non-synonymous substitutions and dS is the rate of synonymous substitutions. Here, we determined the estimated rates of molecular evolution of select biological processes and molecular functions across 264 strains of Mtb. We also investigated the molecular evolutionary rates of core genes of Mtb by computing the dN/dS values, and estimated the pan genome of the 264 strains of Mtb. Our results show that the cellular amino acid metabolic process and the kinase activity function evolve at a significantly higher rate, while the carbohydrate metabolic process evolves at a significantly lower rate for M. tuberculosis. These high rates of evolution correlate well with Mtb physiology and pathogenicity. We further propose that the core genome of M. tuberculosis likely experiences varying rates of molecular evolution which may drive an interplay between core genome and accessory genome during M. tuberculosis evolution.

The Evolution of Diagnostic Techniques in the Paleopathology of Tuberculosis: A Scoping Review

Tuberculosis (TB) is an ancient chronic infectious disease that remains a global health concern. In human remains, the most common and characteristic clinical signs are the skeletal modifications involving the spine, such as in Pott's disease. Diagnosing TB in ancient human remains is challenging. Therefore, in this systematic review, the authors investigated the studies assessing molecular diagnosis of Pott's disease in ancient human remains with the intention to survey the literature, map the evidence, and identify gaps and future perspectives on TB in paleopathology. Our systematic review offers a full contextualization of the history of Pott's disease in ancient times. Our search strategy was performed between August 2022 and March 2023. The authors initially identified 340 records, and 74 studies were finally included and assessed for qualitative analysis. Due to non-specific clinical signs associated with TB, how best to diagnose tuberculosis in human remains still represents a central point. Nevertheless, ancient DNA (aDNA) analysis, lipid biomarkers, and spoligotyping might be extremely useful tools in the study of TB in human remains. Moreover, we propose the extraction and study of immune response genes involved in innate and adaptive immunity versus Mycobacterium spp. as an innovative and vastly overlooked approach in TB paleopathology. Complementary methodologies should be integrated to provide the best approach to the study of TB in human remains.

Structural and Dynamic Insights into the W68L, L85P, and T87A Mutations of Mycobacterium tuberculosis Inducing Resistance to Pyrazinamide

Tuberculosis (TB), the most frequent bacterium-mediated infectious disease caused by Mycobacterium tuberculosis, has been known to infect humans since ancient times. Although TB is common worldwide, the most recent report by the WHO (World Health Organization) listed the three countries of India, China, and Russia with 27%, 14%, and 8% of the global burden of TB, respectively. It has been reported that resistance to TB drugs, particularly by the pncA gene to the pyrazinamide drug due to mutations, significantly affects the effective treatment of TB. Understanding the mechanism of drug resistance using computational methods is of great interest to design effective TB treatment, exploring the structural features with these tools. Thus, keeping in view the importance of these methods, we employed state-of-the-art computational methods to study the mechanism of resistance caused by the W68L, L85P, and T87A mutations recently reported in 2021. We employed a molecular docking approach to predict the binding conformation and studied the dynamic properties of each complex using molecular dynamics simulation approaches. Our analysis revealed that compared to the wildtype, these three mutations altered the binding pattern and reduced the binding affinity. Moreover, the structural dynamic features also showed that these mutations significantly reduced the structural stability and packing, particularly by the W68L and L85P mutations. Moreover, principal component analysis, free energy landscape, and the binding free energy results revealed variation in the protein's motion and the binding energy. The total binding free energy was for the wildtype -9.61 kcal/mol, W68L -7.57 kcal/mol, L85P -6.99 kcal/mol, and T87A -7.77 kcal/mol. Our findings can help to design a structure-based drug against the MDR (multiple drug-resistant) TB.

Protein Integrated Network Analysis to Reveal Potential Drug Targets Against Extended Drug-Resistant Mycobacterium tuberculosis XDR1219

The reconstruction and analysis of the protein-protein interaction (PPI) network is a powerful approach to understand the complex biological and molecular functions in normal and disease states of the cell. The interactome of most organisms is largely unidentified except some model organisms. The current study focused on the construction of PPI network for the human pathogen Mycobacterium tuberculosis (MTB)-resistant strain XDR1219 using computational methods. In this work, a bioinformatics approach was employed to reveal potential drug targets. The pipeline adopted the combination of an extensive integrated network analysis that led to identify 22 key proteins involved in drug resistance, resistant metabolic pathways, virulence, pathogenesis and persistency of the infection. The MTB XDR1219 interactome consists of 11,383 non-redundant PPIs among 1499 proteins covering 38% of the entire MTB XDR1219 proteome. The overall quality of the network was assessed and topological parameters of the PPI were calculated. The predicted interactions were functionally annotated and their relevance was assessed with the functional similarity. The study attempts to present the interactome of previously unidentified MTB XDR1219 and revealed potential drug targets that can be further explored by scientific community.