Expansion of the Yeast Modular Cloning Toolkit for CRISPR-Based Applications, Genomic Integrations and Combinatorial Libraries
Journal article, 2021
Standardisation of genetic parts has become a topic of increasing interest over the last decades. The promise of simplifying molecular cloning procedures, while at the same time making them more predictable and reproducible has led to the design of several biological standards, one of which is modular cloning (MoClo). The Yeast MoClo toolkit provides a large library of characterised genetic parts combined with a comprehensive and flexible assembly strategy. Here we aimed to (1) simplify the adoption of the standard by providing a simple design tool for including new parts in the MoClo library, (2) characterise the toolkit further by demonstrating the impact of a BglII site in promoter parts on protein expression, and (3) expand the toolkit to enable efficient construction of gRNA arrays, marker-less integration cassettes and combinatorial libraries. These additions make the toolkit more applicable for common engineering tasks and will further promote its adoption in the yeast biological engineering community.
Saccharomyces cerevisiae
gRNA array
toolkit
library construction
modular cloning
genomic integration
Author
Maximilian Otto
Novo Nordisk Foundation
Chalmers, Biology and Biological Engineering, Systems and Synthetic Biology
Christos Skrekas
Chalmers, Biology and Biological Engineering, Systems and Synthetic Biology
Novo Nordisk Foundation
Michael Gossing
AstraZeneca AB
Johan Gustafsson
Wallenberg Center for Protein Research (WCPR)
Chalmers, Biology and Biological Engineering, Systems and Synthetic Biology
Verena Siewers
Chalmers, Biology and Biological Engineering, Systems and Synthetic Biology
Novo Nordisk Foundation
Florian David
Chalmers, Biology and Biological Engineering, Systems and Synthetic Biology
Novo Nordisk Foundation
ACS Synthetic Biology
2161-5063 (eISSN)
Vol. 10 12 3461-3474Subject Categories
Embedded Systems
Bioinformatics and Systems Biology
Computer Science
DOI
10.1021/acssynbio.1c00408
PubMed
34860007