Biology subjects

Moffat, J.

Publications and source records attributed to Moffat, J..

24 records · Page 2Linked to original sources

bioRxiv2019

Cell cycle regulation of mitochondrial protein import revealed by genome-scale pooled bimolecular fluorescence complementation screening

A central focus of systems biology is the functional mapping of protein-protein interactions under physiological conditions. Here we describe MaGiCaL-BiFC, a lentivirus-based bimolecular fluorescence protein-fragment complementation approach for the high-throughput, genome-scale identification of protein-protein interactions in mammalian cells. After developing and validating this methodology using known protein-protein interaction pairs, we constructed genome-scale pooled BiFC libraries using the human ORFeome cDNA collection. These pooled libraries, containing [~] 12,000 unique human cDNAs, were used to screen for candidate interaction partners of the mitochondrial transmembrane protein TOMM22. Following infection of cells with the TOMM22 bait and the pooled cDNA libraries, cells harboring candidate TOMM22 interacting proteins were isolated from the cell pool via fluorescence activated cell sorting, and identified via microarray analysis. This approach identified several known interaction partners of TOMM22, as well as novel physical and functional partners that link the mitochondrial network to proteins involved in diverse cellular processes. Notably, protein kinase CK2 was identified as a novel physical interaction partner of human TOMM22. We found that this association occurs preferentially during mitosis and involves direct phosphorylation of TOMM22, an event that may lead to attenuation of mitochondrial protein import. Together, this data contributes to the growing body of evidence suggesting eloquent coordination between cell cycle progression and mitochondrial physiology. Importantly, through high-throughput screening and focused validation, our study demonstrates the power of the MaGiCaL-BiFC approach to uncover novel functional protein-protein interactions, including those involving proteins with membrane-spanning domains, or of a transient nature, all within their native cellular environment.

systems biology↗

bioRxiv2019

Scalable, FACS-Free Genome-Wide Phenotypic Screening

Genome-scale functional genetic screens can identify key regulators of a phenotype of interest, such as determinants of protein expression or modification. Here, we present a rapid, high-throughput approach to phenotypic CRISPR-Cas9 screening. To study factors that modulate the display of CD47 on the cell surface, we processed an entire genome-wide screen containing more than 108 cells in under one hour and maintained high levels of cell viability using a highly scalable cell sorting technology. We robustly identified modulators of CD47 function including QPCTL, an enzyme required for formation of the pyroglutamyl modification at the N-terminus of this protein.

genomics↗

bioRxiv2019

mTORC1 IN THE ORBITOFRONTAL CORTEX PROMOTES HABITUAL ALCOHOL SEEKING

The mammalian target of rapamycin complex 1 (mTORCl) plays an important role in dendritic translation, synaptic plasticity, and learning and memory. We previously showed that heavy alcohol use activates mTORC1 in the orbitofrontal cortex (OFC) of rodents. Here, we set out to determine the consequences of alcohol-dependent mTORC1 activation in the OFC. We found that although inhibition of mTORC1 in the OFC does not alter rat alcohol intake per se, it attenuates alcohol seeking. We then tested whether mTORC1 in the OFC is required for goal-directed or habitual alcohol seeking. To do so, rats were trained self-administer alcohol under a random ratio (RR) or a random interval (RI) schedule of reinforcement, which biases toward goal-directed or habitual responding, respectively, and tested whether mTORC1 inhibition alters lever presses following alcohol devaluation. We found that pharmacological inhibition of mTORC1 or knockdown of the adaptor protein, Raptor, did not affect goal-directed alcohol responding but restored sensitivity to devaluation in RI-trained rats. In contrast, habitual responding for sucrose was unaltered by mTORC1 inhibition. These data suggest that mTORC1 in the OFC drives alcohol habit. We then elucidate the mechanism by which mTORC1 is activated by alcohol, and found that the recruitment of GluN2B during alcohol withdrawal stimulates mTORC1 in OFC cFos-positive neurons. Finally, we show that inhibition of GluN2B in the OFC attenuates both alcohol seeking and habitual responding for alcohol. Together, our data suggest that alcohol withdrawal promotes an NMDAR-dependent activation of mTORC1 which in turn drives habitual alcohol seeking.

neuroscience↗

bioRxiv2017

Identifying drug-gene interactions from CRISPR knockout screens with drugZ

Chemogenetic profiling enables the identification of gene mutations that enhance or suppress the activity of small molecules. This knowledge provides insights into drug mechanism-of-action, genetic vulnerabilities, and resistance mechanisms, all of which may help stratify patient populations. We present drugZ, an algorithm for identifying both synergistic and suppressor chemogenetic interactions from highly sensitive CRISPR screens, available at github.com/hart-lab/drugz. In screens for interactions with a poly(ADP-ribose) polymerase (PARP) inhibitor, DrugZ identifies a greater fraction of the homologous recombination repair pathway than contemporary methods, and confirms KEAP1 loss as a resistance factor for ERK inhibitors.

bioinformatics↗

bioRxiv2017

Coessentiality And Cofunctionality: A Network Approach To Learning Genetic Vulnerabilities From Cancer Cell Line Fitness Screens

Genetic interaction networks are a powerful approach for functional genomics, and the synthetic lethal interactions that comprise these networks offer a compelling strategy for identifying candidate cancer targets. As the number of published shRNA and CRISPR perturbation screens in cancer cell lines expands, there is an opportunity for integrative analysis that goes further than pairwise synthetic lethality and discovers genetic vulnerabilities of related sets of cell lines. We re-analyze over 100 high-quality, genome-scale shRNA screens in human cancer cell lines and derive a quantitative fitness score for each gene that accurately reflects genotype-specific gene essentiality. We identify pairs of genes with correlated essentiality profiles and merge them into a cancer coessentiality network, where shared patterns of genetic vulnerability in cell lines give rise to clusters of functionally related genes in the network. Network clustering discriminates among all three defined subtypes of breast cancer cell lines (basal, luminal, and Her2-amplified), and further identifies novel subsets of Her2+ and ovarian cancer cells. We demonstrate the utility of the network as a platform for both hypothesis-driven and data-driven discovery of context-specific essential genes and their associated biomarkers.

genomics↗

bioRxiv2017

Evaluation and Design of Genome-wide CRISPR/Cas9 Knockout Screens

The adaptation of CRISPR/Cas9 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 re-analyze 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 (BAGEL) algorithm to identify essential genes, to 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 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.

systems biology↗