Year: 2026
Type: article
Abstract: Yarrowia lipolytica is a versatile cell factory widely used in bioprocesses for producing lipids, organic acids, and other high-value compounds. Historically, its genetic engineering was constrained by low homologous recombination (HR) efficiency and the predominance of non-homologous end joining (NHEJ), limiting strain development and metabolic pathway optimization. The advent of CRISPR-Cas technologies has revolutionized genome editing in Y. lipolytica, enabling precise, efficient, and multiplexed modifications. Innovations such as pCAS1yl and pCRISPRyl plasmids, along with genomic Cas9 integration, have enhanced targeted editing efficiency. CRISPR applications now extend to metabolic engineering for lipids, itaconic acid, erythritol, and other compounds. Beyond canonical Cas9, alternative systems, including CRISPRa, Cas12a, base editors, and sgRNA libraries, provide increased flexibility and functional diversity. Central to these approaches is the rational design of guide RNAs (gRNAs), supported by bioinformatics platforms such as CHOPCHOP v3, CRISPOR, CCTop, and Cas-OFFinder, which assist in target site selection, off-target prediction, and editing optimization. This review summarizes the main CRISPR/Cas9 applications in Y. lipolytica, highlighting key engineered strains and emphasizing the critical role of bioinformatics in improving editing strategies. We also propose a pipeline for systematic gRNA design based on published evidence and discuss future perspectives, including the integration of machine learning, artificial intelligence, and emerging CRISPR variants to further advance yeast metabolic engineering.
Authors: Rodrigo Gonçalves Dias, Fernanda Pinheiro Moreira Freitas, Samuel Lessa Barbosa, João Victor Marques Gonçalves Assis, Thaynara Lorenzoni Entringer, Juliana Silva Carneiro Fonseca, Miguel Edmundo Romanizio, Bruno Brayan Zanotti Pimentel, Maria Emilene Martino Campos-Galvão, Nívea Moreira Vieira, Luciano Gomes Fietto, Agustin Zsögön, Wendel Batista da Silveira
Institution: Universidade Federal de Viçosa
Language: English
Subfield: Molecular Biology
Domain: Life Sciences
Open Access status: hybrid
Estimated APC paid: $4,090
OpenAlex ID: W7162213717
