Engineering topics

Schwartz, Cory

Publications and source records attributed to Schwartz, Cory.

4 records

DOE OSTI2023

acCRISPR: an activity-correction method for improving the accuracy of CRISPR screens

Abstract High throughput CRISPR screens are revolutionizing the way scientists unravel the genetic underpinnings of engineered and evolved phenotypes. One of the critical challenges in accurately assessing screening outcomes is accounting for the variability in sgRNA cutting efficiency. Poorly active guides targeting genes essential to screening conditions obscure the growth defects that are expected from disrupting them. Here, we develop acCRISPR, an end-to-end pipeline that identifies essential genes in pooled CRISPR screens using sgRNA read counts obtained from next-generation sequencing. acCRISPR uses experimentally determined cutting efficiencies for each guide in the library to provide an activity correction to the screening outcomes via calculation of an optimization metric, thus determining the fitness effect of disrupted genes. CRISPR-Cas9 and -Cas12a screens were carried out in the non-conventional oleaginous yeast Yarrowia lipolytica and acCRISPR was used to determine a high-confidence set of essential genes for growth under glucose, a common carbon source used for the industrial production of oleochemicals. acCRISPR was also used in screens quantifying relative cellular fitness under high salt conditions to identify genes that were related to salt tolerance. Collectively, this work presents an experimental-computational framework for CRISPR-based functional genomics studies that may be expanded to other non-conventional organisms of interest.

59 BASIC BIOLOGICAL SCIENCES↗

DOE OSTI2022

Genome‐wide CRISPR‐Cas9 screen reveals a persistent null‐hyphal phenotype that maintains high carotenoid production in Yarrowia lipolytica

Abstract Yarrowia lipolytica is a metabolic engineering host of growing industrial interest due to its ability to metabolize hydrocarbons, fatty acids, glycerol, and other renewable carbon sources. This dimorphic yeast undergoes a stress‐induced transition to a multicellular hyphal state, which can negatively impact biosynthetic activity, reduce oxygen and nutrient mass transfer in cell cultures, and increase culture viscosity. Identifying mutations that prevent the formation of hyphae would help alleviate the bioprocess challenges that they create. To this end, we conducted a genome‐wide CRISPR screen to identify genetic knockouts that prevent the transition to hyphal morphology. The screen identified five mutants with a null‐hyphal phenotype— ΔRAS2 , ΔRHO5 , ΔSFL1 , ΔSNF2 , and ΔPAXIP1 . Of these hits, only ΔRAS2 suppressed hyphal formation in an engineered lycopene production strain over a multiday culture. The RAS2 knockout was also the only genetic disruption characterized that did not affect lycopene production, producing more than 5 mg L −1 OD −1 from a heterologous pathway with enhanced carbon flux through the mevalonate pathway. These data suggest that a ΔRAS2 mutant of Y. lipolytica could prove useful in engineering a metabolic engineering host of the production of carotenoids and other biochemicals.

59 BASIC BIOLOGICAL SCIENCES↗

DOE OSTI2022

Genome-wide functional screens enable the prediction of high activity CRISPR-Cas9 and -Cas12a guides in Yarrowia lipolytica

Abstract Genome-wide functional genetic screens have been successful in discovering genotype-phenotype relationships and in engineering new phenotypes. While broadly applied in mammalian cell lines and in E. coli , use in non-conventional microorganisms has been limited, in part, due to the inability to accurately design high activity CRISPR guides in such species. Here, we develop an experimental-computational approach to sgRNA design that is specific to an organism of choice, in this case the oleaginous yeast Yarrowia lipolytica . A negative selection screen in the absence of non-homologous end-joining, the dominant DNA repair mechanism, was used to generate single guide RNA (sgRNA) activity profiles for both SpCas9 and LbCas12a. This genome-wide data served as input to a deep learning algorithm, DeepGuide, that is able to accurately predict guide activity. DeepGuide uses unsupervised learning to obtain a compressed representation of the genome, followed by supervised learning to map sgRNA sequence, genomic context, and epigenetic features with guide activity. Experimental validation, both genome-wide and with a subset of selected genes, confirms DeepGuide’s ability to accurately predict high activity sgRNAs. DeepGuide provides an organism specific predictor of CRISPR guide activity that with retraining could be applied to other fungal species, prokaryotes, and other non-conventional organisms.

59 BASIC BIOLOGICAL SCIENCES↗

DOE OSTI2020

Stress-tolerant non-conventional microbes enable next-generation chemical biosynthesis

Microbial chemical production is a rapidly growing industry, with much of the growth fueled by advances in synthetic biology. New approaches have enabled rapid strain engineering for the production of various compounds; however, translation to industry is often problematic because native phenotypes of model hosts prevent the design of new low-cost bioprocesses. Here, in this work, we argue for a new approach that leverages the native stress-tolerant phenotypes of non-conventional microbes that directly address design challenges from the outset. Growth at high temperature, high salt and solvent concentrations, and low pH can enable cost savings by reducing the energy required for product separation, bioreactor cooling, and maintaining sterile conditions. These phenotypes have the added benefit of allowing for the use of low-cost sugar and water resources. Non-conventional hosts are needed because these phenotypes are polygenic and thus far have proven difficult to recapitulate in the common hosts Escherichia coli and Saccharomyces cerevisiae.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗