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

Synthetic Mechanotransduction Using Engineered SynNotch Receptors

D. Christopher Sloas, View ORCID ProfileJohn T. Ngo
doi: https://doi.org/10.1101/2022.05.01.490205
D. Christopher Sloas
1Department of Biomedical Engineering and Biological Design Center, Boston University, Boston, MA 02215, USA
  • Find this author on Google Scholar
  • Find this author on PubMed
  • Search for this author on this site
John T. Ngo
1Department of Biomedical Engineering and Biological Design Center, Boston University, Boston, MA 02215, USA
  • Find this author on Google Scholar
  • Find this author on PubMed
  • Search for this author on this site
  • ORCID record for John T. Ngo
  • For correspondence: jtngo@bu.edu
  • Abstract
  • Full Text
  • Info/History
  • Metrics
  • Supplementary material
  • Preview PDF
Loading

Abstract

Cells can sense and interpret mechanical stimuli from their environment, but the ability to engineer customized mechanosensing capabilities has remained a synthetic biology challenge. Here, we introduce a set of synthetic Notch (SynNotch)-derived proteins that can be used to convert extracellular tensile forces into specifiable gene expression changes. By elevating the tension levels needed to induce SynNotch activation, in combination with structure-guided mutagenesis, we designed tunable mechanoreceptors with sensitivities in the physiologically relevant picoNewton (pN) range. Cells expressing these receptors could distinguish between varying levels of ligand-mediated tension and enact customizable transcriptional responses in turn. The utility of these tools was demonstrated by the design of a decision-making circuit, through which fibroblasts could be made to differentiate into myoblasts in response to mechanostimulation with tensile forces of distinct magnitudes. This work provides insight regarding how mechanically-induced structural alterations in proteins can be used to transduce physical forces into biochemical signals, and the system should facilitate further programming of force-related phenomena in biological systems.

Competing Interest Statement

The authors are co-inventors on a patent relating to mechanically-regulated gene expression control.

Copyright 
The copyright holder for this preprint is the author/funder, who has granted bioRxiv a license to display the preprint in perpetuity. All rights reserved. No reuse allowed without permission.
Back to top
PreviousNext
Posted May 01, 2022.
Download PDF

Supplementary Material

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.
Synthetic Mechanotransduction Using Engineered SynNotch Receptors
(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
Synthetic Mechanotransduction Using Engineered SynNotch Receptors
D. Christopher Sloas, John T. Ngo
bioRxiv 2022.05.01.490205; doi: https://doi.org/10.1101/2022.05.01.490205
Reddit logo Twitter logo Facebook logo LinkedIn logo Mendeley logo
Citation Tools
Synthetic Mechanotransduction Using Engineered SynNotch Receptors
D. Christopher Sloas, John T. Ngo
bioRxiv 2022.05.01.490205; doi: https://doi.org/10.1101/2022.05.01.490205

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 (4847)
  • Biochemistry (10781)
  • Bioengineering (8035)
  • Bioinformatics (27263)
  • Biophysics (13967)
  • Cancer Biology (11115)
  • Cell Biology (16035)
  • Clinical Trials (138)
  • Developmental Biology (8773)
  • Ecology (13270)
  • Epidemiology (2067)
  • Evolutionary Biology (17346)
  • Genetics (11681)
  • Genomics (15905)
  • Immunology (11015)
  • Microbiology (26054)
  • Molecular Biology (10628)
  • Neuroscience (56486)
  • Paleontology (417)
  • Pathology (1729)
  • Pharmacology and Toxicology (3000)
  • Physiology (4539)
  • Plant Biology (9618)
  • Scientific Communication and Education (1613)
  • Synthetic Biology (2685)
  • Systems Biology (6970)
  • Zoology (1508)