Expansion of the Yeast Modular Cloning Toolkit for CRISPR-Based Applications, Genomic Integrations and Combinatorial Libraries
Artikel i vetenskaplig tidskrift, 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.
genomic integration
library construction
modular cloning
Saccharomyces cerevisiae
gRNA array
toolkit
Författare
Maximilian Otto
Novo Nordisk Foundation Center for Biosustainability
Chalmers, Biologi och bioteknik, Systembiologi
Christos Skrekas
Chalmers, Biologi och bioteknik, Systembiologi
Novo Nordisk Foundation Center for Biosustainability
Michael Gossing
AstraZeneca AB
Johan Gustafsson
Wallenberg Center for Protein Research (WCPR)
Chalmers, Biologi och bioteknik, Systembiologi
Verena Siewers
Novo Nordisk Foundation Center for Biosustainability
Chalmers, Biologi och bioteknik, Systembiologi
Florian David
Novo Nordisk Foundation Center for Biosustainability
Chalmers, Biologi och bioteknik, Systembiologi
ACS Synthetic Biology
2161-5063 (eISSN)
Vol. 10 12 3461-3474Ämneskategorier
Inbäddad systemteknik
Bioinformatik och systembiologi
Datavetenskap (datalogi)
DOI
10.1021/acssynbio.1c00408
PubMed
34860007