Enhanced guide-RNA design and targeting analysis for precise CRISPR genome editing of single and consortia of industrially relevant and non-model organisms.

Motivation: Genetic diversity of non-model organisms offers a repertoire of unique phenotypic features for exploration and cultivation for synthetic biology and metabolic engineering applications. To realize this enormous potential, it is critical to have an efficient genome editing tool for rapid strain engineering of these organisms to perform novel programmed functions. Results: To accommodate the use of CRISPR/Cas systems for genome editing across organisms, we have developed a novel method, named CRISPR Associated Software for Pathway Engineering and Research (CASPER), for identifying on- and off-targets with enhanced predictability coupled with an analysis of non-unique (repeated) targets to assist in editing any organism with various endonucleases. Utilizing CASPER, we demonstrated a modest 2.4% and significant 30.2% improvement (F-test, P < 0.05) over the conventional methods for predicting on- and off-target activities, respectively. Further we used CASPER to develop novel applications in genome editing: multitargeting analysis (i.e. simultaneous multiple-site modification on a target genome with a sole guide-RNA requirement) and multispecies population analysis (i.e. guide-RNA design for genome editing across a consortium of organisms). Our analysis on a selection of industrially relevant organisms revealed a number of non-unique target sites associated with genes and transposable elements that can be used as potential sites for multitargeting. The analysis also identified shared and unshared targets that enable genome editing of single or multiple genomes in a consortium of interest. We envision CASPER as a useful platform to enhance the precise CRISPR genome editing for metabolic engineering and synthetic biology applications. Availability and implementation: https://github.com/TrinhLab/CASPER. Contact: ctrinh@utk.edu. Supplementary information: Supplementary data are available at Bioinformatics online.

CRISPR/Cas9-mediated targeted mutagenesis for functional genomics research of crassulacean acid metabolism plants.

Crassulacean acid metabolism (CAM) is an important photosynthetic pathway in diverse lineages of plants featuring high water-use efficiency and drought tolerance. A big challenge facing the CAM research community is to understand the function of the annotated genes in CAM plant genomes. Recently, a new genome editing technology using CRISPR/Cas9 has become a more precise and powerful tool than traditional approaches for functional genomics research in C3 and C4 plants. In this study, we explore the potential of CRISPR/Cas9 to characterize the function of CAM-related genes in the model CAM species Kalanchoë fedtschenkoi. We demonstrate that CRISPR/Cas9 is effective in creating biallelic indel mutagenesis to reveal previously unknown roles of blue light receptor phototropin 2 (KfePHOT2) in the CAM pathway. Knocking out KfePHOT2 reduced stomatal conductance and CO2 fixation in late afternoon and increased stomatal conductance and CO2 fixation during the night, indicating that blue light signaling plays an important role in the CAM pathway. Lastly, we provide a genome-wide guide RNA database targeting 45 183 protein-coding transcripts annotated in the K. fedtschenkoi genome.

Potency of CRISPR-Cas Antifungals Is Enhanced by Cotargeting DNA Repair and Growth Regulatory Machinery at the Genetic Level.

The emergence of virulent, resistant, and rapidly evolving fungal pathogens poses a significant threat to public health, agriculture, and the environment. Targeting cellular processes with standard small-molecule intervention may be effective but requires long development times and is prone to antibiotic resistance. To overcome the current limitations of antibiotic development and treatment, this study harnesses CRISPR-Cas systems as antifungals by capitalizing on their adaptability, specificity, and efficiency in target design. The conventional design of CRISPR-Cas antimicrobials, based on induction of DNA double-strand breaks (DSBs), is potentially less effective in fungi due to robust eukaryotic DNA repair machinery. Here, we report a novel design principle to formulate more effective CRISPR-Cas antifungals by cotargeting essential genes with DNA repair defensive genes that remove the fungi's ability to repair the DSB sites of essential genes. By evaluating this design on the model fungus Saccharomyces cerevisiae, we demonstrated that essential and defensive gene cotargeting is more effective than either essential or defensive gene targeting alone. The top-performing CRISPR-Cas antifungals performed as effectively as the antibiotic Geneticin. A gene cotargeting interaction analysis revealed that cotargeting essential genes with RAD52 involved in homologous recombination (HR) was the most synergistic combination. Fast growth kinetics of S. cerevisiae induced resistance to CRISPR-Cas antifungals, where genetic mutations mostly occurred in defensive genes and guide RNA sequences.

CASPER: An Integrated Software Platform for Rapid Development of CRISPR Tools.

Both academic and enterprise software solutions exist for designing CRISPR targets. They offer advantages when designing guide RNAs (gRNAs) but often focus on a select number of model organisms. Those that offer a wide variety of organisms can be limited in support of alternative endonucleases and downstream analyses such as multitargeting and population analyses to interrogate a microbiome. To accommodate broad CRISPR utilization, we developed a flexible platform software CRISPR Associated Software for Pathway Engineering and Research (CASPER) for gRNA generation and analysis in any organism and with any CRISPR-Cas system. CASPER combines traditional gRNA design tools with unique functions such as multiple Cas-type gRNA generation and evaluation of spacer redundancy in a single species or microbiome. The analyses have implications for strain-, species-, or genus-specific CRISPR diagnostic probe design and microbiome manipulation. The novel features of CASPER are packaged in a user-friendly interface to create a computational environment for researchers to streamline the utility of CRISPR-Cas systems.

Gene Coexpression Connectivity Predicts Gene Targets Underlying High Ionic-Liquid Tolerance in Yarrowia lipolytica.

Microbial tolerance to organic solvents such as ionic liquids (ILs) is a robust phenotype beneficial for novel biotransformation. While most microbes become inhibited in 1% to 5% (vol/vol) IL (e.g., 1-ethyl-3-methylimidazolium acetate), we engineered a robust Yarrowia lipolytica strain (YlCW001) that tolerates a record high of 18% (vol/vol) IL via adaptive laboratory evolution. Yet, genotypes conferring high IL tolerance in YlCW001 remain to be discovered. In this study, we shed light on the underlying cellular processes that enable robust Y. lipolytica to thrive in inhibitory ILs. By using dynamic transcriptome sequencing (RNA-Seq) data, we introduced Gene Coexpression Connectivity (GeCCo) as a metric to discover genotypes conferring desirable phenotypes that might not be found by the conventional differential expression (DE) approaches. GeCCo selects genes based on their number of coexpressed genes in a subnetwork of upregulated genes by the target phenotype. We experimentally validated GeCCo by reverse engineering a high-IL-tolerance phenotype in wild-type Y. lipolytica. We found that gene targets selected by both DE and GeCCo exhibited the best statistical chance at increasing IL tolerance when individually overexpressed. Remarkably, the best combination of dual-overexpression genes was genes selected by GeCCo alone. This nonintuitive combination of genes, BRN1 and OYE2, is involved in guiding/regulating mitotic cell division, chromatin segregation/condensation, microtubule and cytoskeletal organization, and Golgi vesicle transport. IMPORTANCE Cellular robustness to cope with stressors is an important phenotype. Y. lipolytica is an industrial robust oleaginous yeast that has recently been discovered to tolerate record high concentrations of ILs, beneficial for novel biotransformation in organic solvents. However, genotypes that link to IL tolerance in Y. lipolytica are largely unknown. Due to the complex IL-tolerant phenotype, conventional gene discovery and validation based on differential gene expression approaches are time-consuming due to a large search space and might encounter a high false-discovery rate. Here, using the developed Gene Coexpression Connectivity (GeCCo) method, we identified and validated a subset of most promising gene targets conferring the IL-tolerant phenotypes and shed light on their potential mechanisms. We anticipate GeCCo being a useful method to discover the genotype-to-phenotype link.

In Silico Processing of the Complete CRISPR-Cas Spacer Space for Identification of PAM Sequences.

Despite extensive exploration of the diversity of CRISPR-Cas (Clustered Regularly Interspaced Short Palindromic Repeats, CRISPR associated) systems, biological applications have been mostly confined to Class 2 systems, specifically the Cas9 and Cas12 (formerly Cpf1) single effector proteins. A key limitation of exploring and utilizing other CRISPR-Cas systems with unique functionalities, particularly Class I types and their multi-protein effector complex, is the knowledge of the system's protospacer adjacent motif (PAM) sequence identity. In this work, the authors developed a systematic pipeline, named CASPERpam, that enables a comprehensive assessment of the PAM sequences of all the available CRISPR-Cas systems in the NCBI database of bacterial genomes. The CASPERpam analysis reveals that within the 30 389 assemblies previously screened for CRISPR arrays, there exists 26 364 spacers that match somewhere in the viral, bacterial, and plasmid databases of NCBI, using the constraints of 95% sequence identity and 95% sequence coverage for blast hits. When grouping these results by species, the authors identified putative PAM sequences for 1049 among 1493 unique species. The remaining species either have insufficient data or an undetermined result from the analysis. Finally, the authors assigned a confidence score to each species' PAM prediction and generate categories that largely cover the revealed diversity of PAM motifs, providing a baseline for further experimental studies including PAM assays. The authors envision CASPERpam is a useful bioinformatic tool for understanding and harnessing the diversity of CRISPR-Cas systems.

Effect of protected research time on ABSITE scores during general surgery residency.

BACKGROUND: Objective - To determine whether residents with one or more years of dedicated research time (Research Residents, RR) improved their ABSITE scores compared to those without (Non-Research Residents, N-RR). METHODS: A retrospective review of general surgery residents' ABSITE scores from 1995 to 2016 was performed. RR were compared to N-RR. Additional analysis of At Risk (AR) v Not At Risk residents (NAR) (35th percentile as PGY1-2) was also performed. RESULTS: Cohort - 147 residents (34 RR and 113 N-RR). There were no differences in initial ABSITE scores (p = 0.47). By definition, the AR group had lower scores than NAR. Overall, post-research RR v PGY-4 N-RR scores did not differ (p = 0.84). Only the AR residents improved their scores (p = 0.0009 v NAR p = 0.42), regardless of research group (p = 0.70). CONCLUSION: Protected research time did not improve residents' ABSITE scores, regardless of initial scores. At Risk residents improved regardless of research group status.