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      A comparison of Agrobacterium-mediated transformation and protoplast-mediated transformation with CRISPR-Cas9 and bipartite gene targeting substrates, as effective gene targeting tools for Aspergillus carbonarius

      , , , , ,
      Journal of Microbiological Methods
      Elsevier BV

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          Abstract

          In recent years, versatile genetic tools have been developed and applied to a number of filamentous fungi of industrial importance. However, the existing techniques have limitations when it comes to achieve the desired genetic modifications, especially for efficient gene targeting. In this study, we used Aspergillus carbonarius as a host strain due to its potential as a cell factory, and compared three gene targeting techniques by disrupting the ayg1 gene involved in the biosynthesis of conidial pigment in A. carbonarius. The absence of the ayg1 gene leads to phenotypic change in conidia color, which facilitated the analysis on the gene targeting frequency. The examined transformation techniques included Agrobacterium-mediated transformation (AMT) and protoplast-mediated transformation (PMT). Furthermore, the PMT for the disruption of the ayg1 gene was carried out with bipartite gene targeting fragments and the recently adapted CRISPR-Cas9 system. All three techniques were successful in generating Δayg1 mutants, but showed different efficiencies. The most efficient method for gene targeting was AMT, but further it was shown to be dependent on the choice of Agrobacterium strain. However, there are different advantages and disadvantages of all three gene targeting methods which are discussed, in order to facilitate future approaches for fungal strain improvements.

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          Author and article information

          Journal
          Journal of Microbiological Methods
          Journal of Microbiological Methods
          Elsevier BV
          01677012
          April 2017
          April 2017
          : 135
          : 26-34
          Article
          10.1016/j.mimet.2017.01.015
          28159628
          01913bf3-2a63-4e15-9671-e9d9c61bafe4
          © 2017

          https://www.elsevier.com/tdm/userlicense/1.0/

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