Literature DB >> 10194392

Application of a fed-batch system to produce RNA by in vitro transcription.

J A Kern1, R H Davis.   

Abstract

A novel fed-batch method is presented for the production of RNA by in vitro transcription performed in a stirred-cell reactor with pH-controlled addition of reaction components. Solution equilibrium analysis is applied to determine the ratios of feed components (including nucleoside triphosphates (NTPs), magnesium salt, and base) which allow the desired NTP concentrations, free magnesium concentration, and pH to be maintained during the reaction. Results are presented for fed-batch and batch reactions performed with two DNA templates encoding a 12mer RNA and a 38mer RNA. For the dodecamer RNA, the fed-batch mode is only modestly better than batch reactions, with no significant increase in the efficiency of NTP incorporation but with 40% improvement in the amount of RNA produced per unit of polymerase or DNA. For the 38mer, fed-batch transcription provides a substantial increase in the efficiency of NTP incorporation and 100% improvement in the production of RNA per unit of polymerase or DNA. Cost analyses are presented which show how optimal NTP concentrations in batch and fed-batch reactions will be dependent on the relative costs of NTPs, T7 RNA polymerase, and DNA templates for the particular application. The use of a fed-batch mode appears to have the potential for substantial improvement in the economics of RNA production for at least some RNA sequences.

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Year:  1999        PMID: 10194392     DOI: 10.1021/bp990008g

Source DB:  PubMed          Journal:  Biotechnol Prog        ISSN: 1520-6033


  3 in total

1.  A multiphysics model of in vitro transcription coupling enzymatic reaction and precipitation formation.

Authors:  Satoru Akama; Masayuki Yamamura; Takanori Kigawa
Journal:  Biophys J       Date:  2012-01-18       Impact factor: 4.033

2.  An RNase P-Based Assay for Accurate Determination of the 5'-Deoxy-5'-azidoguanosine-Modified Fraction of in Vitro-Transcribed RNAs.

Authors:  Seth E Lyon; Tien-Hao Chen; Andrew J Wallace; Katie Adib; Venkat Gopalan
Journal:  Chembiochem       Date:  2018-10-24       Impact factor: 3.164

3.  Maximizing mRNA vaccine production with Bayesian optimization.

Authors:  Sara Sousa Rosa; Davide Nunes; Luis Antunes; Duarte M F Prazeres; Marco P C Marques; Ana M Azevedo
Journal:  Biotechnol Bioeng       Date:  2022-09-05       Impact factor: 4.395

  3 in total

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