Many of the projects described below rely on a method developed in our lab called Deep Mutational Scanning (DMS). For a summary of the assay, please click here.
Published paper on Deep Mutational Scanning:
Fowler DM, Fields S. Deep mutational scanning: a new style of protein science. Nature Methods. 2014 Aug;11(8):801-7.
Towards Testing all 35,397 Possible Missense Variants of BRCA1 for Function
BRCA1 is a breast and ovarian cancer-specific tumor suppressor gene and has been subject to much diagnostic sequencing. Multiple cancer-predisposing mutations have been identified along with >500 missense variants classified as Variants of Uncertain Significance or VUS. BRCA1 is an 1863 amino acid protein with two recognizable domains. The N-terminus contains a RING domain and is part of an active ubiquitin ligase and the C-terminus has tandem BRCT (BRCA1 C-Terminus) repeats that bind to phosphorylated peptides and activate transcription. BRCA1 is required for double-strand DNA break repair via homologous recombination, and mutations throughout the protein have deleterious effects on this function. We have devised several assays to score all of the 35,397 possible missense variants of BRCA1 for effects on the protein’s biochemical and cellular functions using a method of deep mutational scanning
We scored 2413 of the possible 5757 missense variants (40%) of the N-terminal 304 amino acids of BRCA1 for ubiquitin ligase function using a phage display system that selects for active variants in an in vitro autoubiquitination reaction. Within these variants 57 have been identified in patients as VUS. The range of ubiquitin ligase function of the VUS variants varied from nearly completely inactive to fully functional, suggesting that some of the variants of BRCA1 that are classified as VUS are nonfunctional ubiquitin ligases.
To assess the effect of mutation on ubiquitin ligase function a library of coding variants of the RING domains of BRCA1-BARD1 is fused to the T7 bacteriophage coat protein. The E3-phage are subjected to in vitro ubiquitination reactions followed by selection for phage coding for active E3 ligase (as outlined in the flow diagram below). Phages harboring active E3 ligases increase in abundance throughout selection whiles phages harboring E3 ligases with deleterious mutations decrease in abundance. These changes are measured by sequencing the input and selected populations. Enrichment ratios (E) are calculated by dividing the frequency at which each variant occurs in the selected population by its frequency in the input population.
We then compared the Enrichment ratio (E) scores for each variant from the deep mutational scan of the RING domain of BRCA1 to the BRCA1 informational database classification. 2356 variants were never found in the human population and, as expected, the E scores for these variants ranged from completely inactive to highly active. 57 of the variants were classified as VUS and many of these are nonfunctional ubiquitin ligases in our assay.
Finally, we are using a cell-based assay to score the effect of missense mutations in full-length BRCA1 on the ability of these variant BRCA1 proteins to rescue homologous recombination when the endogenous protein is repressed. To this end we are optimizing the molecular manipulations to build the libraries of variants with single amino acid changes into lentiviral vectors to transduce into a homologous recombination-reporter cell line.
•Lea Starita & Justin Gullingsrud
Starita LM, Young DL, Islam M, Kitzman JO, Gullingsrud J, Hause RJ, Fowler DM, Parvin JD, Shendure J, Fields S. Massively Parallel Functional Analysis of BRCA1 RING Domain Variants. Genetics. 2015 Mar 30. pii: genetics.115.175802.
Uncovering the Structural Basis of GPCR Functional Selectivity through Deep Mutational Scanning
G Protein Coupled Receptors (GPCRs) are a diverse family of plasma membrane bound proteins that all share 7 transmembrane helices, 3 intracellular loops, and 3 extracellular loops. There are close to 800 human GPCR genes which are responsible for a large proportion of the cellular communication in our species. Approximately 369 of these are non-sensory, making them current or potential drug targets. An estimated 40-60% of current therapeutic drugs target at least one GPCR, so advances in our understanding of signal transduction through GPCRs have potentially widespread clinical ramifications.
It has recently become clear that for any given G Protein Coupled Receptor (GPCR), multiple signaling pathways might be activated and multiple mechanisms might lead to receptor internalization at different rates depending on the specific ligand being used. This phenomenon is called “functional selectivity” or “biased agonism,” and its molecular and structural basis is only just starting to be elucidated. Though recent advances in crystallographic techniques have lead to an increasing number of structures for both active and inactive GPCRs, much remains unclear about the mechanisms of functional selectivity.
We are currently developing a set of high throughput assays for interrogating the effects of all single mutations in a GPCR on receptor expression, internalization, and signaling in a system that has already been shown to display functional selectivity: the Mu Opioid Receptor (MOR). This receptor is clinically important, as it’s the major target of opioid analgesics. Functionally distinct opioid agonists result in different amounts of tolerance development. Also, it is thought that several of the negative side effects of opioids, such as constipation and respiratory depression, might be mediated by a different pathway than their analgesic effects, which would make functional selectivity in this receptor particularly interesting clinically.
We have created a normalizable mammalian expression system for the MOR and cloned several mutants with known defects in cell surface expression into a lentiviral vector. We have demonstrated the feasibility of separating mutants based on their surface expression using a fluorescent antibody and flow cytometry. By binning cells by the amount of fluorescence, we can separate poorly expressed mutants from highly expressed mutants, and we can determine the contents of each bin by sequencing. We are currently generating a library of all single mutants of the MOR. Additional assays for receptor internalization and inhibition of calcium release will be developed after the library is created and functional selectivity will be examined by comparing results between assays using different agonists. Data generated in this project will complement structural data based on NMR and X ray crystallography by providing a functional map to overlay on the spatial one.
Using the Yeast Mating Pathway as a Model for Complex Trait Genetics
Uncovering the genetic underpinnings of complex traits has proven difficult. From crop yield to autism, variants identified in genome-wide association studies (GWAS) explain only a small fraction of the heritable phenotypic variation, leaving a significant gap in our understanding. Using the mating pathway of Saccharomyces cerevisiae (Fig. A), we seek to develop a model for testing hypotheses about complex trait genetics. For example: Does most variation underlying complex traits act additively or epistatically? What proportion of mutational effects are subject to environment? Do known genetic modifiers like the chaperone Hsp90 act on this variation? We make controlled modifications to the genetic architecture of mating and examine phenotypic output to develop expectations for the translation of genotype to phenotype. To do so, we utilize deep mutational scanning, a method that links a phenotypic output to a library of genetic variants via high-throughput sequencing. This method allows us to identify small-effect mutations in individual genes, as well as combinatorial effects of many small-effect mutations across multiple genes.
Effects of mutations in individual mating pathway components (Fig. B) are systematically determined by introducing tens of thousands of protein variants into large populations of yeast which are then subjected to selection for mating efficiency (Fig. C). Furthermore, variants are tested in the absence of strong genetic modifiers like the protein chaperone Hsp90 as well as under varying stress conditions to uncover variants with genetic and environmental dependencies, respectively. After determining individual effects of very large pools of variants, we test mutant libraries for each mating gene in combination (Fig. D) in order to empirically determine the role of epistasis between mating genes. This design allows us to comprehensively show how additive genetic variation, epistatic interactions, and environmental factors contribute to a complex trait.
Further, our model expands beyond a single complex trait. Components of the mating pathway have known crosstalk with high osmolar and invasive growth in yeast. We have investigated the role of a single set of biochemical changes in the transcription factor Ste12 in two different phenotypic assays: mating and invasion. A tradeoff between these two traits is evident (Fig. E), and a unified set of small biochemical changes allows a mechanistic interpretation of Ste12’s role in promoting either mating or invasion.