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Insusceptibility of members of the class Mollicutes to rifampin: studies of the Spiroplasma citri RNA polymerase beta-subunit gene.

ABSTRACT: In order to study the mechanism of insusceptibility of Spiroplasma citri to rifampin, we have cloned and sequenced its rpoB gene, which encodes the beta subunit of RNA polymerase. By comparison of the deduced amino acid sequence with sequences of beta subunits from susceptible and resistant bacteria, it was possible to identify several differences in the so-called Rif region (encompassing rpoB codons 500 to 575 in the Escherichia coli sequence). We constructed a chimeric rpoB gene made of the E. coli rpoB gene in which the Rif region was replaced by the equivalent region from S. citri. E. coli cells harboring this chimeric gene were resistant to rifampin. Subsequent experiments involving site-directed mutagenesis demonstrated that a single amino acid substitution (asparagine at position 526) was able to provide high-level rifampin resistance in E. coli.

SUBMITTER: Gaurivaud P

PROVIDER: S-EPMC163219 | biostudies-other | 1996 Apr

REPOSITORIES: biostudies-other

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Insusceptibility of members of the class Mollicutes to rifampin: studies of the Spiroplasma citri RNA polymerase beta-subunit gene.

Gaurivaud P P Laigret F F Bove J M JM

Antimicrobial agents and chemotherapy 19960401 4

In order to study the mechanism of insusceptibility of Spiroplasma citri to rifampin, we have cloned and sequenced its rpoB gene, which encodes the beta subunit of RNA polymerase. By comparison of the deduced amino acid sequence with sequences of beta subunits from susceptible and resistant bacteria, it was possible to identify several differences in the so-called Rif region (encompassing rpoB codons 500 to 575 in the Escherichia coli sequence). We constructed a chimeric rpoB gene made of the E. ...[more]

PMID: 8849240

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Project description:Bacterial DNA-dependent RNA polymerase (RNAP) has subunit composition beta'betaalpha(I)alpha(II)omega. The role of omega has been unclear. We show that omega is homologous in sequence and structure to RPB6, an essential subunit shared in eukaryotic RNAP I, II, and III. In Escherichia coli, overproduction of omega suppresses the assembly defect caused by substitution of residue 1362 of the largest subunit of RNAP, beta'. In yeast, overproduction of RPB6 suppresses the assembly defect caused by the equivalent substitution in the largest subunit of RNAP II, RPB1. High-resolution structural analysis of the omega-beta' interface in bacterial RNAP, and comparison with the RPB6-RPB1 interface in yeast RNAP II, confirms the structural relationship and suggests a "latching" mechanism for the role of omega and RPB6 in promoting RNAP assembly.

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Predicting rifampicin resistance mutations in bacterial RNA polymerase subunit beta based on majority consensus.

Project description:BackgroundMutations in an enzyme target are one of the most common mechanisms whereby antibiotic resistance arises. Identification of the resistance mutations in bacteria is essential for understanding the structural basis of antibiotic resistance and design of new drugs. However, the traditionally used experimental approaches to identify resistance mutations were usually labor-intensive and costly.ResultsWe present a machine learning (ML)-based classifier for predicting rifampicin (Rif) resistance mutations in bacterial RNA Polymerase subunit β (RpoB). A total of 186 mutations were gathered from the literature for developing the classifier, using 80% of the data as the training set and the rest as the test set. The features of the mutated RpoB and their binding energies with Rif were calculated through computational methods, and used as the mutation attributes for modeling. Classifiers based on five ML algorithms, i.e. decision tree, k nearest neighbors, naïve Bayes, probabilistic neural network and support vector machine, were first built, and a majority consensus (MC) approach was then used to obtain a new classifier based on the classifications of the five individual ML algorithms. The MC classifier comprehensively improved the predictive performance, with accuracy, F-measure and AUC of 0.78, 0.83 and 0.81for training set whilst 0.84, 0.87 and 0.83 for test set, respectively.ConclusionThe MC classifier provides an alternative methodology for rapid identification of resistance mutations in bacteria, which may help with early detection of antibiotic resistance and new drug discovery.

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