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Rapid acquisition and model-based analysis of cell-free transcription-translation reactions from non-model bacteria

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Title: Rapid acquisition and model-based analysis of cell-free transcription-translation reactions from non-model bacteria
Authors: Freemont, PS
Moore, S
MacDonald, J
Wienecke, S
Ishwarbhai, A
Tsipa, A
Aw, R
Kylilis, N
Bell, D
McCymont, D
Jensen, K
Polizzi, K
Biedendieck, R
Item Type: Journal Article
Abstract: Native cell-free transcription–translation systems offer a rapid route to characterize the regulatory elements (promoters, transcription factors) for gene expression from nonmodel microbial hosts, which can be difficult to assess through traditional in vivo approaches. One such host, Bacillus megaterium, is a giant Gram-positive bacterium with potential biotechnology applications, although many of its regulatory elements remain uncharacterized. Here, we have developed a rapid automated platform for measuring and modeling in vitro cell-free reactions and have applied this to B. megaterium to quantify a range of ribosome binding site variants and previously uncharacterized endogenous constitutive and inducible promoters. To provide quantitative models for cell-free systems, we have also applied a Bayesian approach to infer ordinary differential equation model parameters by simultaneously using time-course data from multiple experimental conditions. Using this modeling framework, we were able to infer previously unknown transcription factor binding affinities and quantify the sharing of cell-free transcription–translation resources (energy, ribosomes, RNA polymerases, nucleotides, and amino acids) using a promoter competition experiment. This allows insights into resource limiting-factors in batch cell-free synthesis mode. Our combined automated and modeling platform allows for the rapid acquisition and model-based analysis of cell-free transcription–translation data from uncharacterized microbial cell hosts, as well as resource competition within cell-free systems, which potentially can be applied to a range of cell-free synthetic biology and biotechnology applications.
Issue Date: 8-May-2018
Date of Acceptance: 26-Mar-2018
URI: http://hdl.handle.net/10044/1/59106
DOI: https://dx.doi.org/10.1073/pnas.1715806115
ISSN: 0027-8424
Publisher: National Academy of Sciences
Start Page: E4340
End Page: E4349
Journal / Book Title: Proceedings of the National Academy of Sciences
Volume: 115
Issue: 19
Copyright Statement: Copyright © 2018 the Author(s). Published by PNAS. This open access article is distributed under Creative Commons Attribution-NonCommercial- NoDerivatives License 4.0 (CC BY-NC-ND)
Sponsor/Funder: Engineering & Physical Science Research Council (EPSRC)
Engineering & Physical Science Research Council (EPSRC)
Funder's Grant Number: EP/K038648/1
EP/K503381/1
Keywords: Bacillus
automation
cell-free synthetic biology
in vitro transcription–translation
modeling
MD Multidisciplinary
Publication Status: Published
Online Publication Date: 2018-04-17
Appears in Collections:Bioengineering
Department of Medicine
Faculty of Medicine
Faculty of Natural Sciences



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