Identifying Pseudomonas syringae Type III Secreted Effector Function via a Yeast Genomic Screen.

Gram-negative bacterial pathogens inject type III secreted effectors (T3SEs) directly into host cells to promote pathogen fitness by manipulating host cellular processes. Despite their crucial role in promoting virulence, relatively few T3SEs have well-characterized enzymatic activities or host targets. This is in part due to functional redundancy within pathogen T3SE repertoires as well as the promiscuity of individual T3SEs that can have multiple host targets. To overcome these challenges, we generated and characterized a collection of yeast strains stably expressing 75 T3SE constructs from the plant pathogen Pseudomonas syringae This collection is devised to facilitate heterologous genetic screens in yeast, a non-host organism, to identify T3SEs that target conserved eukaryotic processes. Among 75 T3SEs tested, we identified 16 that inhibited yeast growth on rich media and eight that inhibited growth on stress-inducing media. We utilized Pathogenic Genetic Array (PGA) screens to identify potential host targets of P. syringae T3SEs. We focused on the acetyltransferase, HopZ1a, which interacts with plant tubulin and alters microtubule networks. To uncover putative HopZ1a host targets, we identified yeast genes with genetic interaction profiles most similar (i.e., congruent) to the PGA profile of HopZ1a and performed a functional enrichment analysis of these HopZ1a-congruent genes. We compared the congruence analyses above to previously described HopZ physical interaction datasets and identified kinesins as potential HopZ1a targets. Finally, we demonstrated that HopZ1a can target kinesins by acetylating the plant kinesins HINKEL and MKRP1, illustrating the utility of our T3SE-expressing yeast library to characterize T3SE functions.

Evaluation and Design of Genome-Wide CRISPR/SpCas9 Knockout Screens.

The adaptation of CRISPR/SpCas9 technology to mammalian cell lines is transforming the study of human functional genomics. Pooled libraries of CRISPR guide RNAs (gRNAs) targeting human protein-coding genes and encoded in viral vectors have been used to systematically create gene knockouts in a variety of human cancer and immortalized cell lines, in an effort to identify whether these knockouts cause cellular fitness defects. Previous work has shown that CRISPR screens are more sensitive and specific than pooled-library shRNA screens in similar assays, but currently there exists significant variability across CRISPR library designs and experimental protocols. In this study, we reanalyze 17 genome-scale knockout screens in human cell lines from three research groups, using three different genome-scale gRNA libraries. Using the Bayesian Analysis of Gene Essentiality algorithm to identify essential genes, we refine and expand our previously defined set of human core essential genes from 360 to 684 genes. We use this expanded set of reference core essential genes, CEG2, plus empirical data from six CRISPR knockout screens to guide the design of a sequence-optimized gRNA library, the Toronto KnockOut version 3.0 (TKOv3) library. We then demonstrate the high effectiveness of the library relative to reference sets of essential and nonessential genes, as well as other screens using similar approaches. The optimized TKOv3 library, combined with the CEG2 reference set, provide an efficient, highly optimized platform for performing and assessing gene knockout screens in human cell lines.