Aug 2026· Journal of Fungi· Vol 12· 0 citations· 57 references
Medicine
TL;DR
Compared with conventional homologous recombination, the CRISPR-Cas9 system substantially improved gene disruption efficiency, thereby overcoming a major limitation in the genetic manipulation of lichen-forming fungi.
Abstract
Lichen-forming fungi establish intimate symbiotic associations with photosynthetic partners and play important roles in diverse ecosystems, but functional genetic studies in these organisms remain limited by the lack of efficient genome-editing tools. In this study, we established an efficient CRISPR-Cas9-mediated gene disruption system in Umbilicaria muhlenbergii. Using this system, we achieved the targeted disruption of six candidate transcription factors with a high replacement efficiency of up to 65.0%. No off-target mutations were detected in any of the three independent mutants examined for each target gene. Preliminary phenotypic characterization of the resulting mutants revealed that disruption of UmSOM1 markedly impaired fungal growth, induced pseudohyphal development, and altered colony morphology and pigmentation. Compared with conventional homologous recombination, the CRISPR-Cas9 system substantially improved gene disruption efficiency, thereby overcoming a major limitation in the genetic manipulation of lichen-forming fungi. This system provides a robust platform for functional genomic studies and will accelerate investigations into the molecular mechanisms underlying fungal–algal symbiosis and morphological transitions in lichen-forming fungi.
A substantial decrease in menthofuran content in the essential oil of the edited line #10 compared to the wild-type control is revealed, thereby demonstrating a viable strategy for improving mint essential oil quality through genome-editing.
Fusarium oxysporum, as one of the most common filamentous fungi, possesses great biosynthetic potential for natural products. However, the lack of efficient genetic tools has hindered functional genome mining and metabolic engineering in this fungus. In this study, a novel highly efficient CRISPR/Cas9-based dual-sgRNA expression editing system for F. oxysporum was successfully developed through construction of a robust plasmid platform pFRCas9-G418 using incorporation of an endogenous histone H2B nuclear localization signal and a 5S rRNA promoter-driven polycistronic tRNA−sgRNA cassette. This system is suitable not only for single-gene editing but also for large-fragment deletion and multiplex gene editing, although the editing efficiency is somewhat lower. First, this new CRISPR/Cas9 system exhibited a high efficiency of 93.75% ± 6.25% for deletion of the Fusarium cyclin C1 (fcc1) gene (∼1 kb), which was usually selected as the target gene responsible for yellow pigment accumulation. Then, knockout of the core NRPS gene sanB (∼19 kb) and knock-in of the strong promoter gpdA in the N-methylsansalvamide (SA) biosynthetic gene cluster (BGC) in strain F. oxysporum R1 using this system, respectively, led to no SA yield and an increase of 26.4% SA titer, confirming its capacity for large gene deletion and gene knock-in. Furthermore, one-step dual-gene knockout of hat1 (histone acetyltransferase gene, ∼1.5 kb) and pacC (pH-responsive transcription factor, ∼2 kb) was first achieved in Fusarium species. This versatile platform provides a powerful tool for editing gene(s) of various sizes in F. oxysporum.
Wangjie Zhu, Jiao Liao, Yuanyuan Liu et al.· ACS Synthetic Biology· 0 citations
The potential of these CRISPR-Cas9 systems to serve as a robust foundation for the functional genomics and metabolic engineering of A. limacinum is demonstrated.
Kai Tomita, Yuji Nishida, D. Matsumoto et al.· Scientific Reports· 0 citations
It is demonstrated that Avr4 does not explain the resistance of Calcutta 4, suggesting that resistance is instead triggered by the recognition of other hitherto unknown effectors.
Maikel B. F. Steentjes, Gregory Ashe, Patricia Schöppl et al.· bioRxiv· 0 citations
A new method for surgically removing training examples from a model reveals that as datasets grow, the link between what a model learns and what it produces dissolves.