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Predicting nitroimidazole antibiotic resistance mutations in Mycobacterium tuberculosis with protein engineering.

ABSTRACT: Our inability to predict which mutations could result in antibiotic resistance has made it difficult to rapidly identify the emergence of resistance, identify pre-existing resistant populations, and manage our use of antibiotics to effectively treat patients and prevent or slow the spread of resistance. Here we investigated the potential for resistance against the new antitubercular nitroimidazole prodrugs pretomanid and delamanid to emerge in Mycobacterium tuberculosis, the causative agent of tuberculosis (TB). Deazaflavin-dependent nitroreductase (Ddn) is the only identified enzyme within M. tuberculosis that activates these prodrugs, via an F420H2-dependent reaction. We show that the native menaquinone-reductase activity of Ddn is essential for emergence from hypoxia, which suggests that for resistance to spread and pose a threat to human health, the native activity of Ddn must be at least partially retained. We tested 75 unique mutations, including all known sequence polymorphisms identified among ~15,000 sequenced M. tuberculosis genomes. Several mutations abolished pretomanid and delamanid activation in vitro, without causing complete loss of the native activity. We confirmed that a transmissible M. tuberculosis isolate from the hypervirulent Beijing family already possesses one such mutation and is resistant to pretomanid, before being exposed to the drug. Notably, delamanid was still effective against this strain, which is consistent with structural analysis that indicates delamanid and pretomanid bind to Ddn differently. We suggest that the mutations identified in this work be monitored for informed use of delamanid and pretomanid treatment and to slow the emergence of resistance.

SUBMITTER: Lee BM

PROVIDER: S-EPMC7032734 | biostudies-literature | 2020 Feb

REPOSITORIES: biostudies-literature

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Predicting nitroimidazole antibiotic resistance mutations in Mycobacterium tuberculosis with protein engineering.

Lee Brendon M BM Harold Liam K LK Almeida Deepak V DV Afriat-Jurnou Livnat L Aung Htin Lin HL Forde Brian M BM Hards Kiel K Pidot Sacha J SJ Ahmed F Hafna FH Mohamed A Elaaf AE Taylor Matthew C MC West Nicholas P NP Stinear Timothy P TP Greening Chris C Beatson Scott A SA Nuermberger Eric L EL Cook Gregory M GM Jackson Colin J CJ

PLoS pathogens 20200207 2

Our inability to predict which mutations could result in antibiotic resistance has made it difficult to rapidly identify the emergence of resistance, identify pre-existing resistant populations, and manage our use of antibiotics to effectively treat patients and prevent or slow the spread of resistance. Here we investigated the potential for resistance against the new antitubercular nitroimidazole prodrugs pretomanid and delamanid to emerge in Mycobacterium tuberculosis, the causative agent of t ...[more]

PMID: 32032366

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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: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).

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Predicting nitroimidazole antibiotic resistance mutations in Mycobacterium tuberculosis with protein engineering.

Publications

Predicting nitroimidazole antibiotic resistance mutations in Mycobacterium tuberculosis with protein engineering.

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