Polymorphisms in Rv3806c (ubiA) and the upstream region of embA in relation to ethambutol resistance in clinical isolates of Mycobacterium tuberculosis from North India

A dose-response model for statistical analysis of chemical genetic interactions in CRISPRi screens

An important application of CRISPR interference (CRISPRi) technology is for identifying chemical-genetic interactions (CGIs). Discovery of genes that interact with exposure to antibiotics can yield insights to drug targets and mechanisms of action or resistance. The objective is to identify CRISPRi mutants whose relative abundance is suppressed (or enriched) in the presence of a drug when the target protein is depleted, reflecting synergistic behavior. Different sgRNAs for a given target can induce a wide range of protein depletion and differential effects on growth rate. The effect of sgRNA strength can be partially predicted based on sequence features. However, the actual growth phenotype depends on the sensitivity of cells to depletion of the target protein. For essential genes, sgRNA efficiency can be empirically measured by quantifying effects on growth rate. We observe that the most efficient sgRNAs are not always optimal for detecting synergies with drugs. sgRNA efficiency interacts in a non-linear way with drug sensitivity, producing an effect where the concentration-dependence is maximized for sgRNAs of intermediate strength (and less so for sgRNAs that induce too much or too little target depletion). To capture this interaction, we propose a novel statistical method called CRISPRi-DR (for Dose-Response model) that incorporates both sgRNA efficiencies and drug concentrations in a modified dose-response equation. We use CRISPRi-DR to re-analyze data from a recent CGI experiment in Mycobacterium tuberculosis to identify genes that interact with antibiotics. This approach can be generalized to non-CGI datasets, which we show via an CRISPRi dataset for E. coli growth on different carbon sources. The performance is competitive with the best of several related analytical methods. However, for noisier datasets, some of these methods generate far more significant interactions, likely including many false positives, whereas CRISPRi-DR maintains higher precision, which we observed in both empirical and simulated data.

Genetic diversification of persistent Mycobacterium abscessus within cystic fibrosis patients

Mycobacterium (M.) abscessus infections in Cystic Fibrosis (CF) patients cause a deterioration of lung function. Treatment of these multidrug-resistant pathogens is associated with severe side-effects, while frequently unsuccessful. Insight on M. abscessus genomic evolvement during chronic lung infection would be beneficial for improving treatment strategies. A longitudinal study enrolling 42 CF patients was performed at a CF center in Berlin, Germany, to elaborate phylogeny and genomic diversification of in-patient M. abscessus. Eleven of the 42 CF patients were infected with M. abscessus. Five of these 11 patients were infected with global human-transmissible M. abscessus cluster strains. Phylogenetic analysis of 88 genomes from isolates of the 11 patients excluded occurrence of M. abscessus transmission among members of the study group. Genome sequencing and variant analysis of 30 isolates from 11 serial respiratory samples collected over 4.5 years from a chronically infected patient demonstrated accumulation of gene mutations. In total, 53 genes exhibiting non-synonymous variations were identified. Enrichment analysis emphasized genes involved in synthesis of glycopeptidolipids, genes from the embABC (arabinosyltransferase) operon, betA (glucose-methanol-choline oxidoreductase) and choD (cholesterol oxidase). Genetic diversity evolved in a variety of virulence- and resistance-associated genes. The strategy of M. abscessus populations in chronic lung infection is not clonal expansion of dominant variants, but to sustain simultaneously a wide range of genetic variants facilitating adaptation of the population to changing living conditions in the lung. Genomic diversification during chronic infection requires increased attention when new control strategies against M. abscessus infections are explored.

Using genomics to understand the origin and dispersion of multidrug and extensively drug resistant tuberculosis in Portugal

Portugal is a low incidence country for tuberculosis (TB) disease. Now figuring among TB low incidence countries, it has since the 1990s reported multidrug resistant and extensively drug resistant (XDR) TB cases, driven predominantly by two strain-types: Lisboa3 and Q1. This study describes the largest characterization of the evolutionary trajectory of M/XDR-TB strains in Portugal, spanning a time-period of two decades. By combining whole-genome sequencing and phenotypic susceptibility data for 207 isolates, we report the geospatial patterns of drug resistant TB, particularly the dispersion of Lisboa3 and Q1 clades, which underly 64.2% and 94.0% of all MDR-TB and XDR-TB isolates, respectively. Genomic-based similarity and a phylogenetic analysis revealed multiple clusters (n = 16) reflecting ongoing and uncontrolled recent transmission of M/XDR-TB, predominantly associated with the Lisboa3 and Q1 clades. These clades are now thought to be evolving in a polycentric mode across multiple geographical districts. The inferred evolutionary history is compatible with MDR- and XDR-TB originating in Portugal in the 70's and 80's, respectively, but with subsequent multiple emergence events of MDR and XDR-TB particularly involving the Lisboa3 clade. A SNP barcode was defined for Lisboa3 and Q1 and comparison with a phylogeny of global strain-types (n = 28 385) revealed the presence of Lisboa3 and Q1 strains in Europe, South America and Africa. In summary, Portugal displays an unusual and unique epidemiological setting shaped by >40 years of uncontrolled circulation of two main phylogenetic clades, leading to a sympatric evolutionary trajectory towards XDR-TB with the potential for global reach.

Lack of association of novel mutation Asp397Gly in aftB gene with ethambutol resistance in clinical isolates of Mycobacterium tuberculosis

To discover additional genotypic indicators for ethambutol (EMB) resistant M. tuberculosis, we studied polymorphisms in arabinofuranosyl transferase encoding genes aftA (Rv3792), aftB (Rv3805) and aftC (Rv2673) in 38 EMB resistant and 34 EMB susceptible isolates from India and a repository established by the World Health Organization (WHO) Special Programme for Research and Training in Tropical Disease (TDR) by DNA sequencing. The results were correlated with the minimum inhibitory concentration (MIC) of EMB and mutations in embB (Rv3795). The most common non-synonymous polymorphism identified in aftB was Asp397Gly in 12/38 (31.6%) EMB resistant and 3/34 (8.8%) EMB susceptible isolates. Interestingly, 10/12 (83.3%) EMB resistant isolates with aftB Asp397Gly mutation also carried embB306, embB402 or embB497 mutations. Association of Asp397Gly polymorphism with EMB resistance was statistically significant (p 0.0216). However, overexpression of the mutant aftB in M. tuberculosis H37Rv did not exhibit any change in the MIC. Whole genome sequencing of a panel of Indian isolates and SNP cluster grouping (SCG) of TDR strains revealed an association between aftB mutation Asp397Gly and Beijing genotype or SCG2, a cluster group representing the Beijing genotype. To conclude, though aftBAsp397Gly mutation is not associated with EMB resistance, this mutation may be a phylogenetic marker for the Beijing clade.

Association of ubiA mutations and high-level of ethambutol resistance among Mycobacterium tuberculosis Thai clinical isolates

Ethambutol (EMB) is the first-line antituberculosis drug and a potential supplementary agent for a treatment regimen of multidrug-resistant (MDR) and extensively drug-resistant (XDR) tuberculosis (TB). It has long been known that mutations in embCAB operon, encoding EMB target, arabinosyltransferase, confer resistance to EMB. Recently, ubiA was additionally reported to be specifically associated with high-level EMB resistance in Mycobacterium tuberculosis. However, such information on ubiA is very limited. This study aimed to investigate correlations between mutations in ubiA and phenotypic EMB resistance among EMB-resistant (EMB^R) M. tuberculosis Thai clinical isolates. Minimum inhibitory concentration (MIC) level of EMB and ubiA sequences were determined and analyzed. Of 68 EMB^R-MDR isolates, 8.9% harbored mutations in ubiA. However, 10.0% and 46.6% of EMB-sensitive (EMB^S)-MDR and pan-susceptible isolates also had ubiA mutations detected, respectively. Most nonsynonymous mutations, L31P, A35S, and V55M were only found in the EMB^R-MDR isolates except E149D which was also found in EMB^S-MDR and pan-susceptible isolates. A further phylogenetic analysis based on spoligotyping and IS6110-RFLP illustrated that E149D was in fact associated to EAI-families rather than EMB resistance. By excluding synonymous mutations and the E149D, we found a high correlation between ubiA mutations and high-level of EMB resistance with 100.0% specificity. In conclusion, despite its rare occurrence, mutations in ubiA can potentially be a marker for a detection of high level of EMB resistance at least in the MDR M. tuberculosis background.

Drug targeted virtual screening and molecular dynamics of LipU protein of Mycobacterium tuberculosis and Mycobacterium leprae

The lipolytic protein LipU was conserved in mycobacterium sp. including M. tuberculosis (MTB LipU) and M. leprae (MLP LipU). The MTB LipU was identified in extracellular fraction and was reported to be essential for the survival of mycobacterium. Therefore to address the problem of drug resistance in pathogen, LipU was selected as a drug target and the viability of finding out some FDA approved drugs as LipU inhibitors in both the cases was explored. Three-dimensional (3D) model structures of MTB LipU and MLP LipU were generated and stabilized through molecular dynamics (MD). FDA approved drugs were screened against these proteins. The result showed that the top-scoring compounds for MTB LipU were Diosmin, Acarbose and Ouabain with the Glide XP score of -12.8, -11.9 and -11.7 kcal/mol, respectively, whereas for MLP LipU protein, Digoxin (-9.2 kcal/mol), Indinavir (-8.2 kcal/mol) and Travoprost (-8.2 kcal/mol) showed highest affinity. These drugs remained bound in the active site pocket of MTB LipU and MLP LipU structure and interaction grew stronger after dynamics. RMSD, RMSF and Rg were found to be persistent throughout the simulation period. Hydrogen bonds along with large number of hydrophobic interactions stabilized the complex structures. Binding free energies obtained through Prime/MM-GBSA were found in the significant range from -63.85 kcal/mol to -34.57 kcal/mol for MTB LipU and -71.33 kcal/mol to -23.91 kcal/mol for MLP LipU. The report suggested high probability of these drugs to demolish the LipU activity and could be probable drug candidates to combat TB and leprosy disease.