Literature DB >> 3098280

An RNA polymerase mutant with reduced accuracy of chain elongation.

A Blank, J A Gallant, R R Burgess, L A Loeb.   

Abstract

A new Escherichia coli RNA polymerase mutant was isolated which exhibited reduced accuracy of chain elongation in vivo and in vitro. The novel isolation procedure consisted of simultaneous selection for rifampicin resistance and screening for increased leakiness of an early, strongly polar nonsense mutation of lacZ, one of a special class of mutations whose leakiness reflects mainly transcriptional rather than translational errors. The spontaneous mutant thus isolated displayed a 3-4-fold increase in the leakiness of two different lacZ mutations of this class. Transduction analysis indicated that a single mutation, mapping in or very near the rpoB gene for the beta subunit of RNA polymerase, conferred both rifampicin resistance and increased nonsense leakiness. In an in vitro fidelity assay, homogeneous RNA polymerases from the mutant and parent strains exhibited error rates of 1/0.90 X 10(5) and 1/2.0 X 10(5), respectively, for the poly[d(A-T)] X poly[d(A-T)]-directed misincorporation of noncomplementary GMP. These error rates were verified by product analyses which further revealed that GMP was misincorporated in place of AMP in the synthesis of poly[r(A-U)]. The error rate of wild-type K12 RNA polymerase from a different source was 1/2.0 X 10(5), while that of a hybrid RNA polymerase, containing mutant core enzyme and wild-type sigma subunit, was 1/0.64 X 10(5). These error rates confirmed the selection of a transcriptional accuracy mutant. The error frequencies observed are much lower than those reported in other in vitro assays. The safeguards used to avoid artifactually enhanced misincorporation, and to thereby quantitate lower error rates, are discussed.

Entities:  

Mesh:

Substances:

Year:  1986        PMID: 3098280     DOI: 10.1021/bi00368a013

Source DB:  PubMed          Journal:  Biochemistry        ISSN: 0006-2960            Impact factor:   3.162


  58 in total

1.  The Influence of Look-Ahead on the Error Rate of Transcription.

Authors:  Y R Yamada; C S Peskin
Journal:  Math Model Nat Phenom       Date:  2010-01-27       Impact factor: 4.157

2.  T7 RNA polymerases backed up by covalently trapped proteins catalyze highly error prone transcription.

Authors:  Toshiaki Nakano; Ryo Ouchi; Junya Kawazoe; Seung Pil Pack; Keisuke Makino; Hiroshi Ide
Journal:  J Biol Chem       Date:  2012-01-10       Impact factor: 5.157

Review 3.  Cellular mechanisms that control mistranslation.

Authors:  Noah M Reynolds; Beth A Lazazzera; Michael Ibba
Journal:  Nat Rev Microbiol       Date:  2010-12       Impact factor: 60.633

4.  Selectivity and proofreading both contribute significantly to the fidelity of RNA polymerase III transcription.

Authors:  Nazif Alic; Nayla Ayoub; Emilie Landrieux; Emmanuel Favry; Peggy Baudouin-Cornu; Michel Riva; Christophe Carles
Journal:  Proc Natl Acad Sci U S A       Date:  2007-06-06       Impact factor: 11.205

5.  Transient mutators: a semiquantitative analysis of the influence of translation and transcription errors on mutation rates.

Authors:  J Ninio
Journal:  Genetics       Date:  1991-11       Impact factor: 4.562

6.  Fluctuations, pauses, and backtracking in DNA transcription.

Authors:  Margaritis Voliotis; Netta Cohen; Carmen Molina-París; Tanniemola B Liverpool
Journal:  Biophys J       Date:  2007-08-24       Impact factor: 4.033

7.  Transient reversal of RNA polymerase II active site closing controls fidelity of transcription elongation.

Authors:  Maria L Kireeva; Yuri A Nedialkov; Gina H Cremona; Yuri A Purtov; Lucyna Lubkowska; Francisco Malagon; Zachary F Burton; Jeffrey N Strathern; Mikhail Kashlev
Journal:  Mol Cell       Date:  2008-06-06       Impact factor: 17.970

8.  Potential role of phenotypic mutations in the evolution of protein expression and stability.

Authors:  Moshe Goldsmith; Dan S Tawfik
Journal:  Proc Natl Acad Sci U S A       Date:  2009-04-01       Impact factor: 11.205

9.  Large-scale detection of in vivo transcription errors.

Authors:  Jean-François Gout; W Kelley Thomas; Zachary Smith; Kazufusa Okamoto; Michael Lynch
Journal:  Proc Natl Acad Sci U S A       Date:  2013-10-28       Impact factor: 11.205

10.  Universally high transcript error rates in bacteria.

Authors:  Weiyi Li; Michael Lynch
Journal:  Elife       Date:  2020-05-29       Impact factor: 8.140

View more

北京卡尤迪生物科技股份有限公司 © 2022-2023.