6 research outputs found

    Full humanization of the glycolytic pathway in Saccharomyces cerevisiae

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    Although transplantation of single genes in yeast plays a key role in elucidating gene functionality in metazoans, technical challenges hamper humanization of full pathways and processes. Empowered by advances in synthetic biology, this study demonstrates the feasibility and implementation of full humanization of glycolysis in yeast. Single gene and full pathway transplantation revealed the remarkable conservation of glycolytic and moonlighting functions and, combined with evolutionary strategies, brought to light context-dependent responses. Human hexokinase 1 and 2, but not 4, required mutations in their catalytic or allosteric sites for functionality in yeast, whereas hexokinase 3 was unable to complement its yeast ortholog. Comparison with human tissues cultures showed preservation of turnover numbers of human glycolytic enzymes in yeast and human cell cultures. This demonstration of transplantation of an entire essential pathway paves the way for establishment of species-, tissue-, and disease-specific metazoan models

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

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    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

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

    No full text
    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

    Extracting and characterizing protein-free megabase-pair DNA for in vitro experiments

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    Chromosome structure and function is studied using various cell-based methods as well as with a range of in vitro single-molecule techniques on short DNA substrates. Here, we present a method to obtain megabase-pair-length deproteinated DNA for in vitro studies. We isolated chromosomes from bacterial cells and enzymatically digested the native proteins. Mass spectrometry indicated that 97%–100% of DNA-binding proteins are removed from the sample. Fluorescence microscopy analysis showed an increase in the radius of gyration of the DNA polymers, while the DNA length remained megabase-pair sized. In proof-of-concept experiments using these deproteinated long DNA molecules, we observed DNA compaction upon adding the DNA-binding protein Fis or PEG crowding agents and showed that it is possible to track the motion of a fluorescently labeled DNA locus. These results indicate the practical feasibility of a “genome-in-a-box” approach to study chromosome organization from the bottom up.BN/Cees Dekker LabDynamics of Micro and Nano SystemsBT/Environmental Biotechnolog

    A deep learning system accurately classifies primary and metastatic cancers using passenger mutation patterns

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    In cancer, the primary tumour's organ of origin and histopathology are the strongest determinants of its clinical behaviour, but in 3% of cases a patient presents with a metastatic tumour and no obvious primary. Here,as part of the ICGC/TCGA Pan-Cancer Analysis of Whole Genomes (PCAWG) Consortium, we train a deep learning classifier to predict cancer type based on patterns of somatic passenger mutations detected in whole genome sequencing (WGS) of 2606 tumours representing 24 common cancer types produced by the PCAWG Consortium. Our classifier achieves an accuracy of 91% on held-out tumor samples and 88% and 83% respectively on independent primary and metastatic samples, roughly double the accuracy of trained pathologists when presented with a metastatic tumour without knowledge of the primary. Surprisingly, adding information on driver mutations reduced accuracy. Our results have clinical applicability, underscore how patterns of somatic passenger mutations encode the state of the cell of origin, and can inform future strategies to detect the source of circulating tumour DNA
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