Modular, robust and extendible multicellular circuit design in yeast

  1. Alberto Carignano
  2. Dai Hua Chen
  3. Cannon Mallory
  4. Clay R Wright
  5. Georg Seelig  Is a corresponding author
  6. Eric Klavins  Is a corresponding author
  1. University of Washington, United States
  2. Virginia Tech, United States

Abstract

Division of labor between cells is ubiquitous in biology but the use of multi-cellular consortia for engineering applications is only beginning to be explored. A significant advantage of multi-cellular circuits is their potential to be modular with respect to composition but this claim has not yet been extensively tested using experiments and quantitative modeling. Here, we construct a library of 24 yeast strains capable of sending, receiving or responding to three molecular signals, characterize them experimentally and build quantitative models of their input-output relationships. We then compose these strains into two- and three-strain cascades as well as a four-strain bistable switch and show that experimentally measured consortia dynamics can be predicted from the models of the constituent parts. To further explore the achievable range of behaviors, we perform a fully automated computational search over all two-, three- and four-strain consortia to identify combinations that realize target behaviors including logic gates, band-pass filters and time pulses. Strain combinations that are predicted to map onto a target behavior are further computationally optimized and then experimentally tested. Experiments closely track computational predictions. The high reliability of these model descriptions further strengthens the feasibility and highlights the potential for distributed computing in synthetic biology.

Data availability

Figure 1 - Source Data 1, Figure 2 - Source Data 1, Figure 3 - Source Data 1, Figure 4 - Source Data 1, Figure 5 - Source Data 1 contain the numerical data used to generate the figures

Article and author information

Author details

  1. Alberto Carignano

    Department of Electrical and Computer Engineering, University of Washington, Seattle, United States
    Competing interests
    The authors declare that no competing interests exist.
    ORCID icon "This ORCID iD identifies the author of this article:" 0000-0003-3306-9365
  2. Dai Hua Chen

    Department of Electrical and Computer Engineering, University of Washington, Seattle, United States
    Competing interests
    The authors declare that no competing interests exist.
  3. Cannon Mallory

    Department of Electrical and Computer Engineering, University of Washington, Seattle, United States
    Competing interests
    The authors declare that no competing interests exist.
  4. Clay R Wright

    Department of Biological Systems Engineering, Virginia Tech, Blacksburg, United States
    Competing interests
    The authors declare that no competing interests exist.
  5. Georg Seelig

    Department of Electrical and Computer Engineering, University of Washington, Seattle, United States
    For correspondence
    gseelig@uw.edu
    Competing interests
    The authors declare that no competing interests exist.
    ORCID icon "This ORCID iD identifies the author of this article:" 0000-0002-3163-8782
  6. Eric Klavins

    Department of Electrical and Computer Engineering, University of Washington, Seattle, United States
    For correspondence
    klavins@uw.edu
    Competing interests
    The authors declare that no competing interests exist.
    ORCID icon "This ORCID iD identifies the author of this article:" 0000-0002-3805-5117

Funding

Office of Naval Research (N00014-16-1-3189)

  • Alberto Carignano
  • Georg Seelig
  • Eric Klavins

National Science Foundation (1807132)

  • Alberto Carignano
  • Eric Klavins

The funders had no role in study design, data collection and interpretation, or the decision to submit the work for publication.

Reviewing Editor

  1. Xiaojun Tian

Version history

  1. Received: October 8, 2021
  2. Preprint posted: October 14, 2021 (view preprint)
  3. Accepted: March 20, 2022
  4. Accepted Manuscript published: March 21, 2022 (version 1)
  5. Accepted Manuscript updated: March 22, 2022 (version 2)
  6. Version of Record published: April 11, 2022 (version 3)

Copyright

© 2022, Carignano et al.

This article is distributed under the terms of the Creative Commons Attribution License permitting unrestricted use and redistribution provided that the original author and source are credited.

Metrics

  • 1,537
    Page views
  • 278
    Downloads
  • 3
    Citations

Article citation count generated by polling the highest count across the following sources: Crossref, PubMed Central, Scopus.

Download links

A two-part list of links to download the article, or parts of the article, in various formats.

Downloads (link to download the article as PDF)

Open citations (links to open the citations from this article in various online reference manager services)

Cite this article (links to download the citations from this article in formats compatible with various reference manager tools)

  1. Alberto Carignano
  2. Dai Hua Chen
  3. Cannon Mallory
  4. Clay R Wright
  5. Georg Seelig
  6. Eric Klavins
(2022)
Modular, robust and extendible multicellular circuit design in yeast
eLife 11:e74540.
https://doi.org/10.7554/eLife.74540

Share this article

https://doi.org/10.7554/eLife.74540

Further reading

    1. Computational and Systems Biology
    Ron Sender, Elad Noor ... Yuval Dor
    Research Article

    Cell-free DNA (cfDNA) tests use small amounts of DNA in the bloodstream as biomarkers. While it is thought that cfDNA is largely released by dying cells, the proportion of dying cells' DNA that reaches the bloodstream is unknown. Here, we integrate estimates of cellular turnover rates to calculate the expected amount of cfDNA. By comparing this to the actual amount of cell type-specific cfDNA, we estimate the proportion of DNA reaching plasma as cfDNA. We demonstrate that <10% of the DNA from dying cells is detectable in plasma, and the ratios of measured to expected cfDNA levels vary a thousand-fold among cell types, often reaching well below 0.1%. The analysis suggests that local clearance, presumably via phagocytosis, takes up most of the dying cells' DNA. Insights into the underlying mechanism may help to understand the physiological significance of cfDNA and improve the sensitivity of liquid biopsies.

    1. Computational and Systems Biology
    2. Evolutionary Biology
    Roee Ben Nissan, Eliya Milshtein ... Ron Milo
    Research Article

    Synthetic autotrophy is a promising avenue to sustainable bioproduction from CO2. Here, we use iterative laboratory evolution to generate several distinct autotrophic strains. Utilising this genetic diversity, we identify that just three mutations are sufficient for Escherichia coli to grow autotrophically, when introduced alongside non-native energy (formate dehydrogenase) and carbon-fixing (RuBisCO, phosphoribulokinase, carbonic anhydrase) modules. The mutated genes are involved in glycolysis (pgi), central-carbon regulation (crp), and RNA transcription (rpoB). The pgi mutation reduces the enzyme’s activity, thereby stabilising the carbon-fixing cycle by capping a major branching flux. For the other two mutations, we observe down-regulation of several metabolic pathways and increased expression of native genes associated with the carbon-fixing module (rpiB) and the energy module (fdoGH), as well as an increased ratio of NADH/NAD+ - the cycle’s electron-donor. This study demonstrates the malleability of metabolism and its capacity to switch trophic modes using only a small number of genetic changes and could facilitate transforming other heterotrophic organisms into autotrophs.