Publications

Genome editing in Kluyveromyces and Ogataea yeasts using a broad-host-range Cas9/gRNA co-expression plasmid

This paper is a collaboration between colleagues in Delft and UCC. They have constructed a plasmid that has shown to be efficient in deactivating the ADE2 gene in four different yeast species. This could open up new paths of research in non-conventional yeasts. Read the pre-publication here.

Under pressure: evolutionary engineering of yeast strains for improved performance in fuels and chemicals production

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CHASSY PIs from Delft worked on this mini review of recent technological advances in

evolutionary engineering of yeast strains for various industrial biotechnology applications. The review is available to read in Current Opinion in Biotechnology. You can read the abstract here: Show abstract... ABSTRACT: Evolutionary engineering, which uses laboratory evolution to select for industrially relevant traits, is a popular strategy in the development of high-performing yeast strains for industrial production of fuels and chemicals. By integrating whole-genome sequencing, bioinformatics, classical genetics and genome-editing techniques, evolutionary engineering has also become a powerful approach for identification and reverse engineering of molecular mechanisms that underlie industrially relevant traits. New techniques enable acceleration of in vivo mutation rates, both across yeast genomes and at specific loci. Recent studies indicate that phenotypic trade-offs, which are often observed after evolution under constant conditions, can be mitigated by using dynamic cultivation regimes. Advances in research on synthetic regulatory circuits offer exciting possibilities to extend the applicability of evolutionary engineering to products of yeasts whose synthesis requires a net input of cellular energy.

FnCpf1: a novel and efficient genome editing tool for Saccharomyces cerevisiae

CHASSY PI, Jean-Marc Daran of TU Delft and his colleagues have experimented with using a new type of CRISPR technology for genome editing in the industrial yeast, Saccharomyces cerevisiae. They found Cpf1 to be highly efficient at introducing point mutations with high fidelity, and multi-gene editing. The system was also efficient at promoting recombination of the repair fragment. The published research is available to read in Nucleic Acids Research. You can read the abstract here: Show abstract... ABSTRACT: Cpf1 is a new class II family of CRISPR-Cas RNA-programmable endonucleases with unique features that make it a very attractive alternative or complement to Cas9 for genome engineering. Using constitutively expressed Cpf1 from Francisella novicida, the present study demonstrates that FnCpf1 can mediate RNA-guided DNA cleavage at targeted genomic loci in the popular model and industrial yeast Saccharomyces cerevisiae. FnCpf1 very efficiently and precisely promoted repair DNA recombination with efficiencies up to 100%. Furthermore, FnCpf1 was shown to introduce point mutations with high fidelity. While editing multiple loci with Cas9 is hampered by the need for multiple or complex expression constructs, processing itself a customized CRISPR array FnCpf1 was able to edit four genes simultaneously in yeast with a 100% efficiency. A remarkable observation was the unexpected, strong preference of FnCpf1 to cleave DNA at target sites harbouring 5′-TTTV-3′ PAM sequences, a motif reported to be favoured by Cpf1 homologs of Acidaminococcus and Lachnospiraceae. The present study supplies several experimentally tested guidelines for crRNA design, as well as plasmids for FnCpf1 expression and easy construction of crRNA expression cassettes in S. cerevisiae. FnCpf1 proves to be a powerful addition to S. cerevisiae CRISPR toolbox.

Improving the phenotype predictions of a yeast genome-scale metabolic model by incorporating enzymatic constraints

Genome-scale metabolic models (GEMS) are a useful tool for calculating metabolic phenotypes. Research by CHASSY PI Jens Nielsen and his colleagues have improved the GEMs for Saccharomyces cerevisiae by applying GECKO, a method that also accounts for enzymes as part of reactions. This method is expected to increase the use of model-based design in metabolic engineering. The research is available to read in Molecular Systems Biology. You can read the abstract here: Show abstract... ABSTRACT: Genome-scale metabolic models (GEMs) are widely used to calculate metabolic phenotypes. They rely on defining a set of constraints, the most common of which is that the production of metabolites and/or growth are limited by the carbon source uptake rate. However, enzyme abundances and kinetics, which act as limitations on metabolic fluxes, are not taken into account. Here, we present GECKO, a method that enhances a GEM to account for enzymes as part of reactions, thereby ensuring that each metabolic flux does not exceed its maximum capacity, equal to the product of the enzyme’s abundance and turnover number. We applied GECKO to a Saccharomyces cerevisiae GEM and demonstrated that the new model could correctly describe phenotypes that the previous model could not, particularly under high enzymatic pressure conditions, such as yeast growing on different carbon sources in excess, coping with stress, or overexpressing a specific pathway. GECKO also allows to directly integrate quantitative proteomics data; by doing so, we significantly reduced flux variability of the model, in over 60% of metabolic reactions. Additionally, the model gives insight into the distribution of enzyme usage between and within metabolic pathways. The developed method and model are expected to increase the use of model-based design in metabolic engineering.

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