Biosensor-guided genome-wide CRISPR screens enable cis,cis-muconic acid overproduction in yeast
- 1Concordia University
Abstract
Classical pathway metabolic engineering relies on enhancing strain productivity through the introduction of rationally identified genetic perturbations, which while useful, are time-consuming and miss unintuitive targets. Genome-wide CRISPR screens offer an alternative by efficiently sampling genomes, enabling the engineering of novel phenotypes, and are further enhanced when combined with high-throughput strain interrogation methods. Here, using Saccharomyces cerevisiae, we engineered small molecule biosensors into population enrichment tools using zeocin resistance and fluorescence as signal outputs. We then introduced the multi-functional genome-wide CRISPR (MAGIC) library that targets every gene for activation, interference, or deletion, thus creating biosensor-aided MAGIC, or senMAGIC. As a case study, we utilized senMAGIC to identify single genetic determinants that improve productivity of the nylon precursors protocatechuic and cis,cis-muconic acids (PCA and ccM). These were then randomly assembled as triple gRNA-tRNA arrays for multiplexed gene perturbations to identify combinatorial effects. Top gRNA hits were then confirmed using direct genomic integrations in senMAGIC-free production strains, resulting in identifying known as well as novel targets that increase PCA and ccM titres. Our results demonstrate senMAGIC as a robust automation-friendly whole-genome evolution tool and highlight limitations of the method, providing a roadmap for future multifunctional CRISPR screens to optimize host metabolism for efficient bioprocesses.
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BibTeX
@misc{nasr2026biosensorguided,
title = {{Biosensor-guided genome-wide CRISPR screens enable cis,cis-muconic acid overproduction in yeast}},
author = {M. A. Nasr and A. Knoops and M. Thornbury and M. Davies and D. H. Kwan and V. J. J. Martin},
howpublished = {bioRxiv},
year = {2026},
month = oct,
doi = {10.64898/2026.10.31.762157},
url = {https://www.biorxiv.org/content/10.64898/2026.10.31.762157v1},
note = {CC BY-NC-ND},
}
RIS
TY - UNPB
TI - Biosensor-guided genome-wide CRISPR screens enable cis,cis-muconic acid overproduction in yeast
AU - M. A. Nasr
AU - A. Knoops
AU - M. Thornbury
AU - M. Davies
AU - D. H. Kwan
AU - V. J. J. Martin
PY - 2026
DA - 2026/10/31
PB - bioRxiv
DO - 10.64898/2026.10.31.762157
UR - https://www.biorxiv.org/content/10.64898/2026.10.31.762157v1
AB - Classical pathway metabolic engineering relies on enhancing strain productivity through the introduction of rationally identified genetic perturbations, which while useful, are time-consuming and miss unintuitive targets. Genome-wide CRISPR screens offer an alternative by efficiently sampling genomes, enabling the engineering of novel phenotypes, and are further enhanced when combined with high-throughput strain interrogation methods. Here, using Saccharomyces cerevisiae, we engineered small molecule biosensors into population enrichment tools using zeocin resistance and fluorescence as signal outputs. We then introduced the multi-functional genome-wide CRISPR (MAGIC) library that targets every gene for activation, interference, or deletion, thus creating biosensor-aided MAGIC, or senMAGIC. As a case study, we utilized senMAGIC to identify single genetic determinants that improve productivity of the nylon precursors protocatechuic and cis,cis-muconic acids (PCA and ccM). These were then randomly assembled as triple gRNA-tRNA arrays for multiplexed gene perturbations to identify combinatorial effects. Top gRNA hits were then confirmed using direct genomic integrations in senMAGIC-free production strains, resulting in identifying known as well as novel targets that increase PCA and ccM titres. Our results demonstrate senMAGIC as a robust automation-friendly whole-genome evolution tool and highlight limitations of the method, providing a roadmap for future multifunctional CRISPR screens to optimize host metabolism for efficient bioprocesses.
ER -