Functional genomic screening in Komagataella phaffii enabled by high-activity CRISPR-Cas9 library.


Journal

Metabolic engineering
ISSN: 1096-7184
Titre abrégé: Metab Eng
Pays: Belgium
ID NLM: 9815657

Informations de publication

Date de publication:
15 Jul 2024
Historique:
received: 08 02 2024
revised: 06 06 2024
accepted: 14 07 2024
medline: 18 7 2024
pubmed: 18 7 2024
entrez: 17 7 2024
Statut: aheadofprint

Résumé

CRISPR-based high-throughput genome-wide loss-of-function screens are a valuable approach to functional genetics and strain engineering. The yeast Komagataella phaffii is a host of particular interest in the biopharmaceutical industry and as a metabolic engineering host for proteins and metabolites. Here, we design and validate a highly active 6-fold coverage genome-wide sgRNA library for this biotechnologically important yeast containing 30,848 active sgRNAs targeting over 99% of its coding sequences. Conducting fitness screens in the absence of functional non-homologous end joining (NHEJ), the dominant DNA repair mechanism in K. phaffii, provides a quantitative means to assess the activity of each sgRNA in the library. This approach allows for the experimental validation of each guide's targeting activity, leading to more precise screening outcomes. We used this approach to conduct growth screens with glucose as the sole carbon source and identify essential genes. Comparative analysis of the called gene sets identified a core set of K. phaffii essential genes, many of which relate to metabolic engineering targets, including protein production, secretion, and glycosylation. The high activity, genome-wide CRISPR library developed here enables functional genomic screening in K. phaffii, applied here to gene essentiality classification, and promises to enable other genetic screens.

Identifiants

pubmed: 39019250
pii: S1096-7176(24)00096-X
doi: 10.1016/j.ymben.2024.07.006
pii:
doi:

Types de publication

Journal Article

Langues

eng

Sous-ensembles de citation

IM

Informations de copyright

Copyright © 2024. Published by Elsevier Inc.

Auteurs

Aida Tafrishi (A)

Chemical and Environmental Engineering, University of California-Riverside, Riverside, CA, 92521, USA.

Varun Trivedi (V)

Chemical and Environmental Engineering, University of California-Riverside, Riverside, CA, 92521, USA.

Zenan Xing (Z)

Botany and Plant Sciences, University of California-Riverside, Riverside, CA 92521, USA.

Mengwan Li (M)

Chemical and Environmental Engineering, University of California-Riverside, Riverside, CA, 92521, USA.

Ritesh Mewalal (R)

DOE Joint Genome Institute, Lawrence Berkeley National Laboratory, Berkeley, CA 94720, USA.

Sean R Culter (SR)

Botany and Plant Sciences, University of California-Riverside, Riverside, CA 92521, USA.

Ian Blaby (I)

DOE Joint Genome Institute, Lawrence Berkeley National Laboratory, Berkeley, CA 94720, USA.

Ian Wheeldon (I)

Chemical and Environmental Engineering, University of California-Riverside, Riverside, CA, 92521, USA; Center for Industrial Biotechnology, University of California-Riverside, Riverside, CA 92521, USA. Electronic address: wheeldon@ucr.edu.

Classifications MeSH