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Ancestral antibiotic resistance in Mycobacterium tuberculosis.

ABSTRACT: Chemotherapeutic options to treat tuberculosis are severely restricted by the intrinsic resistance of Mycobacterium tuberculosis to the majority of clinically applied antibiotics. Such resistance is partially provided by the low permeability of their unique cell envelope. Here we describe a complementary system that coordinates resistance to drugs that have penetrated the envelope, allowing mycobacteria to tolerate diverse classes of antibiotics that inhibit cytoplasmic targets. This system depends on whiB7, a gene that pathogenic Mycobacterium shares with Streptomyces, a phylogenetically related genus known as the source of diverse antibiotics. In M. tuberculosis, whiB7 is induced by subinhibitory concentrations of antibiotics (erythromycin, tetracycline, and streptomycin) and whiB7 null mutants (Streptomyces and Mycobacterium) are hypersusceptible to antibiotics in vitro. M. tuberculosis is also antibiotic sensitive within a monocyte model system. In addition to antibiotics, whiB7 is induced by exposure to fatty acids that pathogenic Mycobacterium species may accumulate internally or encounter within eukaryotic hosts during infection. Gene expression profiling analyses demonstrate that whiB7 transcription determines drug resistance by activating expression of a regulon including genes involved in ribosomal protection and antibiotic efflux. Components of the whiB7 system may serve as attractive targets for the identification of inhibitors that render M. tuberculosis or multidrug-resistant derivatives more antibiotic-sensitive.

SUBMITTER: Morris RP

PROVIDER: S-EPMC1186028 | biostudies-literature |

REPOSITORIES: biostudies-literature

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Project description:A novel method for the detection of any alteration within a defined sequence has recently been demonstrated (A. Lishanski, N. Kurn, and E. F. Ullman, Nucleic Acids Res. 28:E42, 2000; A. Lishanski, Clin. Chem. 46:9, 2000). Essential to this method are the generation of partial duplexes that are capable of forming four-stranded structures and the ability to detect inhibition of branch migration in these structures (I. G. Panyutin and P. Hsieh, J. Mol. Biol. 230:413-424, 1993). Inhibition of branch migration indicates the presence of sequence alteration. This mutation detection method, termed branch migration inhibition (BMI), is suitable for the detection of drug resistance in M. tuberculosis, which is frequently associated with multiple mutations within known genes. We describe the genotypic determination of the rifampin (RMP) and pyrazinamide (PZA) susceptibilities of M. tuberculosis isolates, using BMI coupled with the luminescence oxygen channeling immunoassay (LOCI) (E. F. Ullman et al., Proc. Natl. Acad. Sci. USA 91:5426-5430, 1994). RMP and PZA resistances are associated with multiple mutations within the rpoB and pncA genes, respectively. M. tuberculosis genomic DNA samples prepared from 46 clinical isolates were used for genotypic determination of RMP resistance in a "blind study." Similarly, PZA resistance was determined using genomic DNA samples prepared from 37 clinical isolates. Full agreement of the genotypic and phenotypic determinations of drug susceptibility was demonstrated. RMP susceptibility determination directly from cells of 10 clinical isolates grown in culture was also demonstrated. The genotypic result of only 1 out of 10 isolates did not agree with the phenotypic susceptibility testing result. Sequence analysis of the rpoB gene of this clinical isolate revealed a single base substitution, most likely a silent point mutation. The new BMI-LOCI mutation detection method is a rapid and accurate procedure for the genotypic determination of the RMP and PZA susceptibilities of M. tuberculosis clinical isolates. BMI can also be detected by using commercially available automated enzyme-linked immunosorbent assay plate formats (Lishanski et al., Nucleic Acids Res. 28:E42, 2000).

Project description:BACKGROUND:Tuberculosis is an infectious bacterial disease caused by Mycobacterium tuberculosis. It remains a major health threat, killing over one million people every year worldwide. An early antibiotic therapy is the basis of the treatment, and the emergence and spread of multidrug and extensively drug-resistant mutant strains raise significant challenges. As these bacteria grow very slowly, drug resistance mutations are currently detected using molecular biology techniques. Resistance mutations are identified by sequencing the resistance-linked genes followed by a comparison with the literature data. The only online database is the TB Drug Resistance Mutation database (TBDReaM database); however, it requires mutation detection before use, and its interrogation is complex due to its loose syntax and grammar. DESCRIPTION:The MUBII-TB-DB database is a simple, highly structured text-based database that contains a set of Mycobacterium tuberculosis mutations (DNA and proteins) occurring at seven loci: rpoB, pncA, katG; mabA(fabG1)-inhA, gyrA, gyrB, and rrs. Resistance mutation data were extracted after the systematic review of MEDLINE referenced publications before March 2013. MUBII analyzes the query sequence obtained by PCR-sequencing using two parallel strategies: i) a BLAST search against a set of previously reconstructed mutated sequences and ii) the alignment of the query sequences (DNA and its protein translation) with the wild-type sequences. The post-treatment includes the extraction of the aligned sequences together with their descriptors (position and nature of mutations). The whole procedure is performed using the internet. The results are graphs (alignments) and text (description of the mutation, therapeutic significance). The system is quick and easy to use, even for technicians without bioinformatics training. CONCLUSION:MUBII-TB-DB is a structured database of the mutations occurring at seven loci of major therapeutic value in tuberculosis management. Moreover, the system provides interpretation of the mutations in biological and therapeutic terms and can evolve by the addition of newly described mutations. Its goal is to provide easy and comprehensive access through a client-server model over the Web to an up-to-date database of mutations that lead to the resistance of M. tuberculosis to antibiotics.

Project description:Two billion people are infected with Mycobacterium tuberculosis, leading to 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, Mykrobe predictor, which provided offline species identification and drug resistance predictions for M. tuberculosis from whole genome sequencing (WGS) data. Performance was insufficient to support the use of WGS as an alternative to conventional phenotype-based DST, due to mutation catalogue limitations. Here we present a new tool, Mykrobe, which provides the same functionality based on a new software implementation. Improvements include i) an updated mutation catalogue giving greater sensitivity to detect pyrazinamide resistance, ii) support for user-defined resistance catalogues, iii) improved identification of non-tuberculous mycobacterial species, and iv) an updated statistical model for Oxford Nanopore Technologies sequencing data. Mykrobe is released under MIT license at https://github.com/mykrobe-tools/mykrobe. We incorporate mutation catalogues from the CRyPTIC consortium et al. (2018) and from Walker et al. (2015), and make improvements based on performance on an initial set of 3206 and an independent set of 5845 M. tuberculosis Illumina sequences. To give estimates of error rates, we use a prospectively collected dataset of 4362 M. tuberculosis isolates. Using culture based DST as the reference, we estimate Mykrobe to be 100%, 95%, 82%, 99% sensitive and 99%, 100%, 99%, 99% specific for rifampicin, isoniazid, pyrazinamide and ethambutol resistance prediction respectively. We benchmark against four other tools on 10207 (=5845+4362) samples, and also show that Mykrobe gives concordant results with nanopore data. We measure the ability of Mykrobe-based DST to guide personalized therapeutic regimen design in the context of complex drug susceptibility profiles, showing 94% concordance of implied regimen with that driven by phenotypic DST, higher than all other benchmarked tools.

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Ancestral antibiotic resistance in Mycobacterium tuberculosis.

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