Skip to main content
bioRxiv
  • Home
  • About
  • Submit
  • ALERTS / RSS
Advanced Search
New Results

A MATLAB Toolbox for Modeling Genetic Circuits in Cell-Free Systems

View ORCID ProfileVipul Singhal, View ORCID ProfileZoltan A. Tuza, View ORCID ProfileZachary Z. Sun, View ORCID ProfileRichard M. Murray
doi: https://doi.org/10.1101/2020.08.05.237990
Vipul Singhal
1Genome Institute of Singapore, Singapore
  • Find this author on Google Scholar
  • Find this author on PubMed
  • Search for this author on this site
  • ORCID record for Vipul Singhal
  • For correspondence: vipuls@gis.a-star.edu.sg
Zoltan A. Tuza
2Department of Bioengineering, Imperial College London, London, UK
  • Find this author on Google Scholar
  • Find this author on PubMed
  • Search for this author on this site
  • ORCID record for Zoltan A. Tuza
Zachary Z. Sun
3Tierra Bioscienes, Berkeley, CA, USA
  • Find this author on Google Scholar
  • Find this author on PubMed
  • Search for this author on this site
  • ORCID record for Zachary Z. Sun
Richard M. Murray
4Departments of Control and Dynamical Systems and Biology and Biological Engineering, California Institute of Technology, Pasadena, CA, USA
  • Find this author on Google Scholar
  • Find this author on PubMed
  • Search for this author on this site
  • ORCID record for Richard M. Murray
  • Abstract
  • Full Text
  • Info/History
  • Metrics
  • Supplementary material
  • Data/Code
  • Preview PDF
Loading

Abstract

We introduce a MATLAB based simulation toolbox, called txtlsim, for an E. coli based Transcription-Translation (TX-TL) system. This toolbox accounts for several cell-free related phenomena, such as resource loading, consumption, and degradation, and in doing so, models the dynamics of TX-TL reactions for the entire duration of batch-mode experiments. We use a Bayesian parameter inference approach to characterize the reaction rate parameters associated with the core transcription, translation and mRNA degradation mechanics of the toolbox, allowing it to reproduce constitutive mRNA and protien expression trajectories. We demonstrate the use of this characterized toolbox in a circuit behavior prediction case study for an incoherent feed-forward loop.

Competing Interest Statement

RMM and ZZS declare a conflict of interest: RMM, ZZS hold ownership in Tierra Biosciences (formerly Synvitrobio). The work presented here was funded off of a DARPA SBIR to Synvitrobio, Inc. (ZZS), contract No: W911NF-16-P-0003, and a Caltech Grubstake Grant (RMM, ZZS).

Footnotes

  • This work was performed while all authors were at Caltech. VS was with the Computation and Neural Systems option, ZAT was a visiting graduate student with the Department of Control and Dynamical Systems, and ZZS was with the Biology option.

  • https://github.com/vipulsinghal02/txtlsim_buildacell

Copyright 
The copyright holder for this preprint is the author/funder, who has granted bioRxiv a license to display the preprint in perpetuity. It is made available under a CC-BY 4.0 International license.
Back to top
PreviousNext
Posted August 05, 2020.
Download PDF

Supplementary Material

Data/Code
Email

Thank you for your interest in spreading the word about bioRxiv.

NOTE: Your email address is requested solely to identify you as the sender of this article.

Enter multiple addresses on separate lines or separate them with commas.
A MATLAB Toolbox for Modeling Genetic Circuits in Cell-Free Systems
(Your Name) has forwarded a page to you from bioRxiv
(Your Name) thought you would like to see this page from the bioRxiv website.
CAPTCHA
This question is for testing whether or not you are a human visitor and to prevent automated spam submissions.
Share
A MATLAB Toolbox for Modeling Genetic Circuits in Cell-Free Systems
Vipul Singhal, Zoltan A. Tuza, Zachary Z. Sun, Richard M. Murray
bioRxiv 2020.08.05.237990; doi: https://doi.org/10.1101/2020.08.05.237990
Reddit logo Twitter logo Facebook logo LinkedIn logo Mendeley logo
Citation Tools
A MATLAB Toolbox for Modeling Genetic Circuits in Cell-Free Systems
Vipul Singhal, Zoltan A. Tuza, Zachary Z. Sun, Richard M. Murray
bioRxiv 2020.08.05.237990; doi: https://doi.org/10.1101/2020.08.05.237990

Citation Manager Formats

  • BibTeX
  • Bookends
  • EasyBib
  • EndNote (tagged)
  • EndNote 8 (xml)
  • Medlars
  • Mendeley
  • Papers
  • RefWorks Tagged
  • Ref Manager
  • RIS
  • Zotero
  • Tweet Widget
  • Facebook Like
  • Google Plus One

Subject Area

  • Synthetic Biology
Subject Areas
All Articles
  • Animal Behavior and Cognition (4382)
  • Biochemistry (9591)
  • Bioengineering (7090)
  • Bioinformatics (24857)
  • Biophysics (12600)
  • Cancer Biology (9956)
  • Cell Biology (14349)
  • Clinical Trials (138)
  • Developmental Biology (7948)
  • Ecology (12105)
  • Epidemiology (2067)
  • Evolutionary Biology (15988)
  • Genetics (10925)
  • Genomics (14738)
  • Immunology (9869)
  • Microbiology (23660)
  • Molecular Biology (9484)
  • Neuroscience (50860)
  • Paleontology (369)
  • Pathology (1539)
  • Pharmacology and Toxicology (2682)
  • Physiology (4013)
  • Plant Biology (8657)
  • Scientific Communication and Education (1508)
  • Synthetic Biology (2394)
  • Systems Biology (6433)
  • Zoology (1346)