Multiplexed, multimodal profiling of the intracellular activity, interactions, and druggability of protein variants using LABEL-seq

Multiplexed assays of variant effect are powerful tools for assessing the impact of protein sequence variation, but are limited to measuring a single protein property and often rely on indirect readouts of intracellular protein function. Here, we developed LAbeling with Barcodes and Enrichment for biochemicaL analysis by sequencing (LABEL-seq), a platform for the multimodal profiling of thousands of protein variants in cultured human cells. Multimodal measurement of ~20,000 variant effects for ~1,600 BRaf variants using LABEL-seq revealed that variation at positions that are frequently mutated in cancer had minimal effects on folding and intracellular abundance but could dramatically alter activity, protein-protein interactions, and druggability. Integrative analysis of our multimodal measurements identified networks of positions with similar roles in regulating BRaf's signaling properties and enabled predictive modeling of variant effects on complex processes such as cell proliferation and small molecule-promoted degradation. LABEL-seq provides a scalable approach for the direct measurement of multiple biochemical effects of protein variants in their native cellular context, yielding insight into protein function, disease mechanisms, and druggability.

Defining and Reducing Variant Classification Disparities

Background

Multiplexed Assays of Variant Effects (MAVEs) can test all possible single variants in a gene of interest. The resulting saturation-style data may help resolve variant classification disparities between populations, especially for variants of uncertain significance (VUS).

Methods

We analyzed clinical significance classifications in 213,663 individuals of European-like genetic ancestry versus 206,975 individuals of non-European-like genetic ancestry from All of Us and the Genome Aggregation Database. Then, we incorporated clinically calibrated MAVE data into the Clinical Genome Resource's Variant Curation Expert Panel rules to automate VUS reclassification for BRCA1, TP53, and PTEN .

Results

Using two orthogonal statistical approaches, we show a higher prevalence ( p ≤5.95e-06) of VUS in individuals of non-European-like genetic ancestry across all medical specialties assessed in all three databases. Further, in the non-European-like genetic ancestry group, higher rates of Benign or Likely Benign and variants with no clinical designation ( p ≤2.5e-05) were found across many medical specialties, whereas Pathogenic or Likely Pathogenic assignments were higher in individuals of European-like genetic ancestry ( p ≤2.5e-05). Using MAVE data, we reclassified VUS in individuals of non-European-like genetic ancestry at a significantly higher rate in comparison to reclassified VUS from European-like genetic ancestry ( p =9.1e-03) effectively compensating for the VUS disparity. Further, essential code analysis showed equitable impact of MAVE evidence codes but inequitable impact of allele frequency ( p =7.47e-06) and computational predictor ( p =6.92e-05) evidence codes for individuals of non-European-like genetic ancestry.

Conclusions

Generation of saturation-style MAVE data should be a priority to reduce VUS disparities and produce equitable training data for future computational predictors.

Multiplexed Functional Assessments of MYH7 Variants in Human Cardiomyocytes

BACKGROUND

Pathogenic autosomal-dominant missense variants in MYH7 (myosin heavy chain 7), which encodes the sarcomeric protein (β-MHC [beta myosin heavy chain]) expressed in cardiac and skeletal myocytes, are a leading cause of hypertrophic cardiomyopathy and are clinically actionable. However, ≈75% of MYH7 missense variants are of unknown significance. While human-induced pluripotent stem cells (hiPSCs) can be differentiated into cardiomyocytes to enable the interrogation of MYH7 variant effect in a disease-relevant context, deep mutational scanning has not been executed using diploid hiPSC derivates due to low hiPSC gene-editing efficiency. Moreover, multiplexable phenotypes enabling deep mutational scanning of MYH7 variant hiPSC-derived cardiomyocytes are unknown.

METHODS

To overcome these obstacles, we used CRISPRa On-Target Editing Retrieval enrichment to generate an hiPSC library containing 113 MYH7 codon variants suitable for deep mutational scanning. We first established that β-MHC protein loss occurs in a hypertrophic cardiomyopathy human heart with a pathogenic MYH7 variant. We then differentiated the MYH7 missense variant hiPSC library to cardiomyocytes for multiplexed assessment of β-MHC variant abundance by massively parallel sequencing and hiPSC-derived cardiomyocyte survival.

RESULTS

Both the multiplexed assessment of β-MHC abundance and hiPSC-derived cardiomyocyte survival accurately segregated all known pathogenic variants from synonymous variants. Functional data were generated for 4 variants of unknown significance and 58 additional MYH7 missense variants not yet detected in patients.

CONCLUSIONS

This study leveraged hiPSC differentiation into disease-relevant cardiomyocytes to enable multiplexed assessments of MYH7 missense variants for the first time. Phenotyping strategies used here enable the application of deep mutational scanning to clinically actionable genes, which should reduce the burden of variants of unknown significance on patients and clinicians.

Pacybara: accurate long-read sequencing for barcoded mutagenized allelic libraries

MOTIVATION

Long-read sequencing technologies, an attractive solution for many applications, often suffer from higher error rates. Alignment of multiple reads can improve base-calling accuracy, but some applications, e.g. sequencing mutagenized libraries where multiple distinct clones differ by one or few variants, require the use of barcodes or unique molecular identifiers. Unfortunately, sequencing errors can interfere with correct barcode identification, and a given barcode sequence may be linked to multiple independent clones within a given library.

RESULTS

Here we focus on the target application of sequencing mutagenized libraries in the context of multiplexed assays of variant effects (MAVEs). MAVEs are increasingly used to create comprehensive genotype-phenotype maps that can aid clinical variant interpretation. Many MAVE methods use long-read sequencing of barcoded mutant libraries for accurate association of barcode with genotype. Existing long-read sequencing pipelines do not account for inaccurate sequencing or nonunique barcodes. Here, we describe Pacybara, which handles these issues by clustering long reads based on the similarities of (error-prone) barcodes while also detecting barcodes that have been associated with multiple genotypes. Pacybara also detects recombinant (chimeric) clones and reduces false positive indel calls. In three example applications, we show that Pacybara identifies and correctly resolves these issues.

AVAILABILITY AND IMPLEMENTATION

Pacybara, freely available at https://github.com/rothlab/pacybara, is implemented using R, Python, and bash for Linux. It runs on GNU/Linux HPC clusters via Slurm, PBS, or GridEngine schedulers. A single-machine simplex version is also available.

CAGI, the Critical Assessment of Genome Interpretation, establishes progress and prospects for computational genetic variant interpretation methods

BACKGROUND

The Critical Assessment of Genome Interpretation (CAGI) aims to advance the state-of-the-art for computational prediction of genetic variant impact, particularly where relevant to disease. The five complete editions of the CAGI community experiment comprised 50 challenges, in which participants made blind predictions of phenotypes from genetic data, and these were evaluated by independent assessors.

RESULTS

Performance was particularly strong for clinical pathogenic variants, including some difficult-to-diagnose cases, and extends to interpretation of cancer-related variants. Missense variant interpretation methods were able to estimate biochemical effects with increasing accuracy. Assessment of methods for regulatory variants and complex trait disease risk was less definitive and indicates performance potentially suitable for auxiliary use in the clinic.

CONCLUSIONS

Results show that while current methods are imperfect, they have major utility for research and clinical applications. Emerging methods and increasingly large, robust datasets for training and assessment promise further progress ahead.

A mutational atlas for Parkin proteostasis

Proteostasis can be disturbed by mutations affecting folding and stability of the encoded protein. An example is the ubiquitin ligase Parkin, where gene variants result in autosomal recessive Parkinsonism. To uncover the pathological mechanism and provide comprehensive genotype-phenotype information, variant abundance by massively parallel sequencing (VAMP-seq) is leveraged to quantify the abundance of Parkin variants in cultured human cells. The resulting mutational map, covering 9219 out of the 9300 possible single-site amino acid substitutions and nonsense Parkin variants, shows that most low abundance variants are proteasome targets and are located within the structured domains of the protein. Half of the known disease-linked variants are found at low abundance. Systematic mapping of degradation signals (degrons) reveals an exposed degron region proximal to the so-called "activation element". This work provides examples of how missense variants may cause degradation either via destabilization of the native protein, or by introducing local signals for degradation.

Profiling of drug resistance in Src kinase at scale uncovers a regulatory network coupling autoinhibition and catalytic domain dynamics

Kinase inhibitors are effective cancer therapies, but resistance often limits clinical efficacy. Despite the cataloging of numerous resistance mutations, our understanding of kinase inhibitor resistance is still incomplete. Here, we comprehensively profiled the resistance of ∼3,500 Src tyrosine kinase mutants to four different ATP-competitive inhibitors. We found that ATP-competitive inhibitor resistance mutations are distributed throughout Src's catalytic domain. In addition to inhibitor contact residues, residues that participate in regulating Src's phosphotransferase activity were prone to the development of resistance. Unexpectedly, we found that a resistance-prone cluster of residues located on the top face of the N-terminal lobe of Src's catalytic domain contributes to autoinhibition by reducing catalytic domain dynamics, and mutations in this cluster led to resistance by lowering inhibitor affinity and promoting kinase hyperactivation. Together, our studies demonstrate how drug resistance profiling can be used to define potential resistance pathways and uncover new mechanisms of kinase regulation.

Will variants of uncertain significance still exist in 2030?

In 2020, the National Human Genome Research Institute (NHGRI) made ten "bold predictions," including that "the clinical relevance of all encountered genomic variants will be readily predictable, rendering the diagnostic designation 'variant of uncertain significance (VUS)' obsolete." We discuss the prospects for this prediction, arguing that many, if not most, VUS in coding regions will be resolved by 2030. We outline a confluence of recent changes making this possible, especially advances in the standards for variant classification that better leverage diverse types of evidence, improvements in computational variant effect predictor performance, scalable multiplexed assays of variant effect capable of saturating the genome, and data-sharing efforts that will maximize the information gained from each new individual sequenced and variant interpreted. We suggest that clinicians and researchers can realize a future where VUSs have largely been eliminated, in line with the NHGRI's bold prediction. The length of time taken to reach this future, and thus whether we are able to achieve the goal of largely eliminating VUSs by 2030, is largely a consequence of the choices made now and in the next few years. We believe that investing in eliminating VUSs is worthwhile, since their predominance remains one of the biggest challenges to precision genomic medicine.

Antigen perception in T cells by long-term Erk and NFAT signaling dynamics

Immune system threat detection hinges on T cells' ability to perceive varying peptide-major histocompatibility complex (pMHC) antigens. As the Erk and NFAT pathways link T cell receptor engagement to gene regulation, their signaling dynamics may convey information about pMHC inputs. To test this idea, we developed a dual reporter mouse strain and a quantitative imaging assay that, together, enable simultaneous monitoring of Erk and NFAT dynamics in live T cells over day-long timescales as they respond to varying pMHC inputs. Both pathways initially activate uniformly across various pMHC inputs but diverge only over longer (9+ h) timescales, enabling independent encoding of pMHC affinity and dose. These late signaling dynamics are decoded via multiple temporal and combinatorial mechanisms to generate pMHC-specific transcriptional responses. Our findings underscore the importance of long timescale signaling dynamics in antigen perception and establish a framework for understanding T cell responses under diverse contexts.

Pacybara: Accurate long-read sequencing for barcoded mutagenized allelic libraries

Long read sequencing technologies, an attractive solution for many applications, often suffer from higher error rates. Alignment of multiple reads can improve base-calling accuracy, but some applications, e.g. sequencing mutagenized libraries where multiple distinct clones differ by one or few variants, require the use of barcodes or unique molecular identifiers. Unfortunately, sequencing errors can interfere with correct barcode identification, and a given barcode sequence may be linked to multiple independent clones within a given library. Here we focus on the target application of sequencing mutagenized libraries in the context of multiplexed assays of variant effects (MAVEs). MAVEs are increasingly used to create comprehensive genotype-phenotype maps that can aid clinical variant interpretation. Many MAVE methods use long-read sequencing of barcoded mutant libraries for accurate association of barcode with genotype. Existing long-read sequencing pipelines do not account for inaccurate sequencing or non-unique barcodes. Here, we describe Pacybara, which handles these issues by clustering long reads based on the similarities of (error-prone) barcodes while also detecting barcodes that have been associated with multiple genotypes. Pacybara also detects recombinant (chimeric) clones and reduces false positive indel calls. In three example applications, we show that Pacybara identifies and correctly resolves these issues.

Optogenetic Microwell Array Screening System: A High-Throughput Engineering Platform for Genetically Encoded Fluorescent Indicators

Genetically encoded fluorescent indicators (GEFIs) are protein-based optogenetic tools that change their fluorescence intensity when binding specific ligands in cells and tissues. GEFI encoding DNA can be expressed in cell subtypes while monitoring cellular physiological responses. However, engineering GEFIs with physiological sensitivity and pharmacological specificity often requires iterative optimization through trial-and-error mutagenesis while assessing their biophysical function in vitro one by one. Here, the vast mutational landscape of proteins constitutes a significant obstacle that slows GEFI development, particularly for sensors that rely on mammalian host systems for testing. To overcome these obstacles, we developed a multiplexed high-throughput engineering platform called the optogenetic microwell array screening system (Opto-MASS) that functionally tests thousands of GEFI variants in parallel in mammalian cells. Opto-MASS represents the next step for engineering optogenetic tools as it can screen large variant libraries orders of magnitude faster than current methods. We showcase this system by testing over 13,000 dopamine and 21,000 opioid sensor variants. We generated a new dopamine sensor, dMASS1, with a >6-fold signal increase to 100 nM dopamine exposure compared to its parent construct. Our new opioid sensor, μMASS1, has a ∼4.6-fold signal increase over its parent scaffold's response to 500 nM DAMGO. Thus, Opto-MASS can rapidly engineer new sensors while significantly shortening the optimization time for new sensors with distinct biophysical properties.

A chemically controlled Cas9 switch enables temporal modulation of diverse effectors

CRISPR-Cas9 has yielded a plethora of effectors, including targeted transcriptional activators, base editors and prime editors. Current approaches for inducibly modulating Cas9 activity lack temporal precision and require extensive screening and optimization. We describe a versatile, chemically controlled and rapidly activated single-component DNA-binding Cas9 switch, ciCas9, which we use to confer temporal control over seven Cas9 effectors, including two cytidine base editors, two adenine base editors, a dual base editor, a prime editor and a transcriptional activator. Using these temporally controlled effectors, we analyze base editing kinetics, showing that editing occurs within hours and that rapid early editing of nucleotides predicts eventual editing magnitude. We also reveal that editing at preferred nucleotides within target sites increases the frequency of bystander edits. Thus, the ciCas9 switch offers a simple, versatile approach to generating chemically controlled Cas9 effectors, informing future effector engineering and enabling precise temporal effector control for kinetic studies.

An Atlas of Variant Effects to understand the genome at nucleotide resolution

Sequencing has revealed hundreds of millions of human genetic variants, and continued efforts will only add to this variant avalanche. Insufficient information exists to interpret the effects of most variants, limiting opportunities for precision medicine and comprehension of genome function. A solution lies in experimental assessment of the functional effect of variants, which can reveal their biological and clinical impact. However, variant effect assays have generally been undertaken reactively for individual variants only after and, in most cases long after, their first observation. Now, multiplexed assays of variant effect can characterise massive numbers of variants simultaneously, yielding variant effect maps that reveal the function of every possible single nucleotide change in a gene or regulatory element. Generating maps for every protein encoding gene and regulatory element in the human genome would create an 'Atlas' of variant effect maps and transform our understanding of genetics and usher in a new era of nucleotide-resolution functional knowledge of the genome. An Atlas would reveal the fundamental biology of the human genome, inform human evolution, empower the development and use of therapeutics and maximize the utility of genomics for diagnosing and treating disease. The Atlas of Variant Effects Alliance is an international collaborative group comprising hundreds of researchers, technologists and clinicians dedicated to realising an Atlas of Variant Effects to help deliver on the promise of genomics.

CRaTER enrichment for on-target gene editing enables generation of variant libraries in hiPSCs

Standard transgenic cell line generation requires screening 100-1000s of colonies to isolate correctly edited cells. We describe CRISPRa On-Target Editing Retrieval (CRaTER) which enriches for cells with on-target knock-in of a cDNA-fluorescent reporter transgene by transient activation of the targeted locus followed by flow sorting to recover edited cells. We show CRaTER recovers rare cells with heterozygous, biallelic-editing of the transcriptionally-inactive MYH7 locus in human induced pluripotent stem cells (hiPSCs), enriching on average 25-fold compared to standard antibiotic selection. We leveraged CRaTER to enrich for heterozygous knock-in of a library of variants in MYH7, a gene in which missense mutations cause cardiomyopathies, and recovered hiPSCs with 113 different variants. We differentiated these hiPSCs to cardiomyocytes and show MHC-β fusion proteins can localize as expected. Additionally, single-cell contractility analyses revealed cardiomyocytes with a pathogenic, hypertrophic cardiomyopathy-associated MYH7 variant exhibit salient HCM physiology relative to isogenic controls. Thus, CRaTER substantially reduces screening required for isolation of gene-edited cells, enabling generation of functional transgenic cell lines at unprecedented scale.

Molecular determinants of Hsp90 dependence of Src kinase revealed by deep mutational scanning

Hsp90 is a molecular chaperone involved in the refolding and activation of numerous protein substrates referred to as clients. While the molecular determinants of Hsp90 client specificity are poorly understood and limited to a handful of client proteins, strong clients are thought to be destabilized and conformationally extended. Here, we measured the phosphotransferase activity of 3,929 variants of the tyrosine kinase Src in both the presence and absence of an Hsp90 inhibitor. We identified 84 previously unknown functionally dependent client variants. Unexpectedly, many destabilized or extended variants were not functionally dependent on Hsp90. Instead, functionally dependent client variants were clustered in the αF pocket and β1-β2 strand regions of Src, which have yet to be described in driving Hsp90 dependence. Hsp90 dependence was also strongly correlated with kinase activity. We found that a combination of activation, global extension, and general conformational flexibility, primarily induced by variants at the αF pocket and β1-β2 strands, was necessary to render Src functionally dependent on Hsp90. Moreover, the degree of activation and flexibility required to transform Src into a functionally dependent client varied with variant location, suggesting that a combination of regulatory domain disengagement and catalytic domain flexibility are required for chaperone dependence. Thus, by studying the chaperone dependence of a massive number of variants, we highlight factors driving Hsp90 client specificity and propose a model of chaperone-kinase interactions. This article is protected by copyright. All rights reserved.

Machine vision reveals micronucleus rupture as a potential driver of the transcriptomic response to aneuploidy

Micronuclei are aberrant nuclear compartments that trap a portion of a cell's chromatin in a distinct organelle separate from the nucleus and are drivers of inflammation, DNA damage, chromosome instability, and chromothripsis. Many of the consequences of micronucleus formation stem from micronucleus rupture: the sudden loss of micronucleus compartmentalization, resulting in mislocalization of nuclear factors and the exposure of chromatin to the cytosol for the remainder of interphase. Micronuclei form primarily from segregation errors during mitosis, errors that also give rise to other, non-exclusive phenotypes, including aneuploidy and chromatin bridges. The stochastic formation of micronuclei and phenotypic overlap confounds the use of population-level assays or hypothesis discovery, requiring labor-intensive techniques to visually identify and follow micronucleated cells individually. In this study, we present a novel technique for automatically identifying and isolating micronucleated cells generally and cells with ruptured micronuclei specifically using a de novo neural net combined with Visual Cell Sorting. As a proof of concept, we compare the early transcriptomic responses to micronucleation and micronucleus rupture with previously published responses to aneuploidy, revealing micronucleus rupture to be a potential driver of the aneuploidy response.

High-throughput functional mapping of variants in an arrhythmia gene, KCNE1, reveals novel biology

Background

KCNE1 encodes a 129-residue cardiac potassium channel (IKs) subunit. KCNE1 variants are associated with long QT syndrome and atrial fibrillation. However, most variants have insufficient evidence of clinical consequences and thus limited clinical utility.

Results

Here, we demonstrate the power of variant effect mapping, which couples saturation mutagenesis with high-throughput sequencing, to ascertain the function of thousands of protein coding KCNE1 variants. We comprehensively assayed KCNE1 variant cell surface expression (2,554/2,709 possible single amino acid variants) and function (2,539 variants). We identified 470 loss-of-surface expression and 588 loss-of-function variants. Out of the 588 loss-of-function variants, only 155 had low cell surface expression. The latter half of the protein is dispensable for protein trafficking but essential for channel function. 22 of the 30 KCNE1 residues (73%) highly intolerant of variation were in predicted close contact with binding partners KCNQ1 or calmodulin. Our data were highly concordant with gold standard electrophysiological data (ρ = -0.65), population and patient cohorts (32/38 concordant variants), and computational metrics (ρ = -0.55). Our data provide moderate-strength evidence for the ACMG/AMP functional criteria for benign and pathogenic variants.

Conclusions

Comprehensive variant effect maps of KCNE1 can both provide insight into IKs channel biology and help reclassify variants of uncertain significance.

CRaTER enrichment for on-target gene-editing enables generation of variant libraries in hiPSCs

Standard transgenic cell line generation requires screening 100-1000s of colonies to isolate correctly edited cells. We describe CR ISPR a On- T arget E diting R etrieval (CRaTER) which enriches for cells with on-target knock-in of a cDNA-fluorescent reporter transgene by transient activation of the targeted locus followed by flow sorting to recover edited cells. We show CRaTER recovers rare cells with heterozygous, biallelic-editing of the transcriptionally-inactive MYH7 locus in human induced pluripotent stem cells (hiPSCs), enriching on average 25-fold compared to standard antibiotic selection. We leveraged CRaTER to enrich for heterozygous knock-in of a library of single nucleotide variants (SNVs) in MYH7 , a gene in which missense mutations cause cardiomyopathies, and recovered hiPSCs with 113 different MYH7 SNVs. We differentiated these hiPSCs to cardiomyocytes and show MYH7 fusion proteins can localize as expected. Thus, CRaTER substantially reduces screening required for isolation of gene-edited cells, enabling generation of transgenic cell lines at unprecedented scale.

Probing ion channel functional architecture and domain recombination compatibility by massively parallel domain insertion profiling

Protein domains are the basic units of protein structure and function. Comparative analysis of genomes and proteomes showed that domain recombination is a main driver of multidomain protein functional diversification and some of the constraining genomic mechanisms are known. Much less is known about biophysical mechanisms that determine whether protein domains can be combined into viable protein folds. Here, we use massively parallel insertional mutagenesis to determine compatibility of over 300,000 domain recombination variants of the Inward Rectifier K⁺ channel Kir2.1 with channel surface expression. Our data suggest that genomic and biophysical mechanisms acted in concert to favor gain of large, structured domain at protein termini during ion channel evolution. We use machine learning to build a quantitative biophysical model of domain compatibility in Kir2.1 that allows us to derive rudimentary rules for designing domain insertion variants that fold and traffic to the cell surface. Positional Kir2.1 responses to motif insertion clusters into distinct groups that correspond to contiguous structural regions of the channel with distinct biophysical properties tuned towards providing either folding stability or gating transitions. This suggests that insertional profiling is a high-throughput method to annotate function of ion channel structural regions.

Closing the gap: Systematic integration of multiplexed functional data resolves variants of uncertain significance in BRCA1, TP53, and PTEN

Clinical interpretation of missense variants is challenging because the majority identified by genetic testing are rare and their functional effects are unknown. Consequently, most variants are of uncertain significance and cannot be used for clinical diagnosis or management. Although not much can be done to ameliorate variant rarity, multiplexed assays of variant effect (MAVEs), where thousands of single-nucleotide variant effects are simultaneously measured experimentally, provide functional evidence that can help resolve variants of unknown significance (VUSs). However, a rigorous assessment of the clinical value of multiplexed functional data for variant interpretation is lacking. Thus, we systematically combined previously published BRCA1, TP53, and PTEN multiplexed functional data with phenotype and family history data for 324 VUSs identified by a single diagnostic testing laboratory. We curated 49,281 variant functional scores from MAVEs for these three genes and integrated four different TP53 multiplexed functional datasets into a single functional prediction for each variant by using machine learning. We then determined the strength of evidence provided by each multiplexed functional dataset and reevaluated 324 VUSs. Multiplexed functional data were effective in driving variant reclassification when combined with clinical data, eliminating 49% of VUSs for BRCA1, 69% for TP53, and 15% for PTEN. Thus, multiplexed functional data, which are being generated for numerous genes, are poised to have a major impact on clinical variant interpretation.

Integrating thousands of PTEN variant activity and abundance measurements reveals variant subgroups and new dominant negatives in cancers

Background

PTEN is a multi-functional tumor suppressor protein regulating cell growth, immune signaling, neuronal function, and genome stability. Experimental characterization can help guide the clinical interpretation of the thousands of germline or somatic PTEN variants observed in patients. Two large-scale mutational datasets, one for PTEN variant intracellular abundance encompassing 4112 missense variants and one for lipid phosphatase activity encompassing 7244 variants, were recently published. The combined information from these datasets can reveal variant-specific phenotypes that may underlie various clinical presentations, but this has not been comprehensively examined, particularly for somatic PTEN variants observed in cancers.

Methods

Here, we add to these efforts by measuring the intracellular abundance of 764 new PTEN variants and refining abundance measurements for 3351 previously studied variants. We use this expanded and refined PTEN abundance dataset to explore the mutational patterns governing PTEN intracellular abundance, and then incorporate the phosphatase activity data to subdivide PTEN variants into four functionally distinct groups.

Results

This analysis revealed a set of highly abundant but lipid phosphatase defective variants that could act in a dominant-negative fashion to suppress PTEN activity. Two of these variants were, indeed, capable of dysregulating Akt signaling in cells harboring a WT PTEN allele. Both variants were observed in multiple breast or uterine tumors, demonstrating the disease relevance of these high abundance, inactive variants.

Conclusions

We show that multidimensional, large-scale variant functional data, when paired with public cancer genomics datasets and follow-up assays, can improve understanding of uncharacterized cancer-associated variants, and provide better insights into how they contribute to oncogenesis.

Supplementary Information

The online version contains supplementary material available at 10.1186/s13073-021-00984-x.

Measuring Pharmacogene Variant Function at Scale Using Multiplexed Assays

As costs of next-generation sequencing decrease, identification of genetic variants has far outpaced our ability to understand their functional consequences. This lack of understanding is a central challenge to a key promise of pharmacogenomics: using genetic information to guide drug selection and dosing. Recently developed multiplexed assays of variant effect enable experimental measurement of the function of thousands of variants simultaneously. Here, we describe multiplexed assays that have been performed on nearly 25,000 variants in eight key pharmacogenes (ADRB2, CYP2C9, CYP2C19, NUDT15, SLCO1B1, TMPT, VKORC1, and the LDLR promoter), discuss advances in experimental design, and explore key challenges that must be overcome to maximize the utility of multiplexed functional data. Expected final online publication date for the Annual Review of Pharmacology and Toxicology, Volume 62 is January 2022. Please see http://www.annualreviews.org/page/journal/pubdates for revised estimates.

Understanding the Origins of Loss of Protein Function by Analyzing the Effects of Thousands of Variants on Activity and Abundance

Understanding and predicting how amino acid substitutions affect proteins are keys to our basic understanding of protein function and evolution. Amino acid changes may affect protein function in a number of ways including direct perturbations of activity or indirect effects on protein folding and stability. We have analyzed 6,749 experimentally determined variant effects from multiplexed assays on abundance and activity in two proteins (NUDT15 and PTEN) to quantify these effects and find that a third of the variants cause loss of function, and about half of loss-of-function variants also have low cellular abundance. We analyze the structural and mechanistic origins of loss of function and use the experimental data to find residues important for enzymatic activity. We performed computational analyses of protein stability and evolutionary conservation and show how we may predict positions where variants cause loss of activity or abundance. In this way, our results link thermodynamic stability and evolutionary conservation to experimental studies of different properties of protein fitness landscapes.

MaveRegistry: a collaboration platform for multiplexed assays of variant effect

Summary

Multiplexed assays of variant effect (MAVEs) are capable of experimentally testing all possible single nucleotide or amino acid variants in selected genomic regions, generating ‘variant effect maps’, which provide biochemical insight and functional evidence to enable more rapid and accurate clinical interpretation of human variation. Because the international community applying MAVE approaches is growing rapidly, we developed the online MaveRegistry platform to catalyze collaboration, reduce redundant efforts, allow stakeholders to nominate targets and enable tracking and sharing of progress on ongoing MAVE projects.

Availability and implementation

MaveRegistry service: https://registry.varianteffect.org. MaveRegistry source code: https://github.com/kvnkuang/maveregistry-front-end.

Multiplexed measurement of variant abundance and activity reveals VKOR topology, active site and human variant impact

Vitamin K epoxide reductase (VKOR) drives the vitamin K cycle, activating vitamin K-dependent blood clotting factors. VKOR is also the target of the widely used anticoagulant drug, warfarin. Despite VKOR's pivotal role in coagulation, its structure and active site remain poorly understood. In addition, VKOR variants can cause vitamin K-dependent clotting factor deficiency or alter warfarin response. Here, we used multiplexed, sequencing-based assays to measure the effects of 2,695 VKOR missense variants on abundance and 697 variants on activity in cultured human cells. The large-scale functional data, along with an evolutionary coupling analysis, supports a four transmembrane domain topology, with variants in transmembrane domains exhibiting strongly deleterious effects on abundance and activity. Functionally constrained regions of the protein define the active site, and we find that, of four conserved cysteines putatively critical for function, only three are absolutely required. Finally, 25% of human VKOR missense variants show reduced abundance or activity, possibly conferring warfarin sensitivity or causing disease.

Parallel Chemoselective Profiling for Mapping Protein Structure

Solution-based structural techniques complement high-resolution structural data by providing insight into the oft-missed links between protein structure and dynamics. Here, we present Parallel Chemoselective Profiling, a solution-based structural method for characterizing protein structure and dynamics. Our method utilizes deep mutational scanning saturation mutagenesis data to install amino acid residues with specific chemistries at defined positions on the solvent-exposed surface of a protein. Differences in the extent of labeling of installed mutant residues are quantified using targeted mass spectrometry, reporting on each residue's local environment and structural dynamics. Using our method, we studied how conformation-selective, ATP-competitive inhibitors affect the local and global structure and dynamics of full-length Src kinase. Our results highlight how parallel chemoselective profiling can be used to study a dynamic multi-domain protein, and suggest that our method will be a useful addition to the relatively small toolkit of existing protein footprinting techniques.

Comprehensive exploration of the translocation, stability and substrate recognition requirements in VIM-2 lactamase

Metallo-β-lactamases (MBLs) degrade a broad spectrum of β-lactam antibiotics, and are a major disseminating source for multidrug resistant bacteria. Despite many biochemical studies in diverse MBLs, molecular understanding of the roles of residues in the enzyme’s stability and function, and especially substrate specificity, is lacking. Here, we employ deep mutational scanning (DMS) to generate comprehensive single amino acid variant data on a major clinical MBL, VIM-2, by measuring the effect of thousands of VIM-2 mutants on the degradation of three representative classes of β-lactams (ampicillin, cefotaxime, and meropenem) and at two different temperatures (25°C and 37°C). We revealed residues responsible for expression and translocation, and mutations that increase resistance and/or alter substrate specificity. The distribution of specificity-altering mutations unveiled distinct molecular recognition of the three substrates. Moreover, these function-altering mutations are frequently observed among naturally occurring variants, suggesting that the enzymes have continuously evolved to become more potent resistance genes.

High-throughput discovery of trafficking-deficient variants in the cardiac potassium channel KV11.1

BACKGROUND

KCHN2 encodes the K_V11.1 potassium channel responsible for I_Kr, a major repolarization current during the cardiomyocyte action potential. Variants in KCNH2 that lead to decreased I_Kr have been associated with long QT syndrome type 2 (LQT2). The mechanism of LQT2 is most often induced loss of K_V11.1 trafficking to the cell surface. Accurately discriminating between variants with normal and abnormal trafficking would aid in understanding the deleterious nature of these variants; however, the volume of reported nonsynonymous KCNH2 variants precludes the use of conventional methods for functional study.

OBJECTIVE

The purpose of this study was to report a high-throughput, multiplexed screening method for KCNH2 genetic variants capable of measuring the cell surface abundance of hundreds of missense variants in the resulting K_V11.1 channel.

METHODS

We developed a method to quantitate K_V11.1 variant trafficking on a pilot region of 11 residues in the S5 helix.

RESULTS

We generated trafficking scores for 220 of 231 missense variants in the pilot region. For 5 of 5 variants, high-throughput trafficking scores validated when tested in single variant flow cytometry and confocal microscopy experiments. We further explored these results with planar patch electrophysiology and found that loss-of-trafficking variants do not produce I_Kr. Conversely, but expectedly, some variants that traffic normally were still functionally compromised.

CONCLUSION

We describe a new method for detecting K_V11.1 trafficking-deficient variants in a multiplexed assay. This new method accurately generated trafficking data for variants in K_V11.1 and is extendable both to all residues in K_V11.1 and to other cell surface proteins.

Suppression of unwanted CRISPR-Cas9 editing by co-administration of catalytically inactivating truncated guide RNAs

CRISPR-Cas9 nucleases are powerful genome engineering tools, but unwanted cleavage at off-target and previously edited sites remains a major concern. Numerous strategies to reduce unwanted cleavage have been devised, but all are imperfect. Here, we report that off-target sites can be shielded from the active Cas9•single guide RNA (sgRNA) complex through the co-administration of dead-RNAs (dRNAs), truncated guide RNAs that direct Cas9 binding but not cleavage. dRNAs can effectively suppress a wide-range of off-targets with minimal optimization while preserving on-target editing, and they can be multiplexed to suppress several off-targets simultaneously. dRNAs can be combined with high-specificity Cas9 variants, which often do not eliminate all unwanted editing. Moreover, dRNAs can prevent cleavage of homology-directed repair (HDR)-corrected sites, facilitating scarless editing by eliminating the need for blocking mutations. Thus, we enable precise genome editing by establishing a flexible approach for suppressing unwanted editing of both off-targets and HDR-corrected sites.

High-throughput, microscope-based sorting to dissect cellular heterogeneity

Microscopy is a powerful tool for characterizing complex cellular phenotypes, but linking these phenotypes to genotype or RNA expression at scale remains challenging. Here, we present Visual Cell Sorting, a method that physically separates hundreds of thousands of live cells based on their visual phenotype. Automated imaging and phenotypic analysis directs selective illumination of Dendra2, a photoconvertible fluorescent protein expressed in live cells; these photoactivated cells are then isolated using fluorescence-activated cell sorting. First, we use Visual Cell Sorting to assess hundreds of nuclear localization sequence variants in a pooled format, identifying variants that improve nuclear localization and enabling annotation of nuclear localization sequences in thousands of human proteins. Second, we recover cells that retain normal nuclear morphologies after paclitaxel treatment, and then derive their single-cell transcriptomes to identify pathways associated with paclitaxel resistance in cancers. Unlike alternative methods, Visual Cell Sorting depends on inexpensive reagents and commercially available hardware. As such, it can be readily deployed to uncover the relationships between visual cellular phenotypes and internal states, including genotypes and gene expression programs.

A Premalignant Cell-Based Model for Functionalization and Classification of PTEN Variants

As sequencing becomes more economical, we are identifying sequence variations in the population faster than ever. For disease-associated genes, it is imperative that we differentiate a sequence variant as either benign or pathogenic, such that the appropriate therapeutic interventions or surveillance can be implemented. PTEN is a frequently mutated tumor suppressor that has been linked to the PTEN hamartoma tumor syndrome. Although the domain structure of PTEN and the functional impact of a number of its most common tumor-linked mutations have been characterized, there is a lack of information about many recently identified clinical variants. To address this challenge, we developed a cell-based assay that utilizes a premalignant phenotype of normal mammary epithelial cells lacking PTEN. We measured the ability of PTEN variants to rescue the spheroid formation phenotype of PTEN^-/- MCF10A cells maintained in suspension. As proof of concept, we functionalized 47 missense variants using this assay, only 19 of which have clear classifications in ClinVar. We utilized a machine learning model trained with annotated genotypic data to classify variants as benign or pathogenic based on our functional scores. Our model predicted with high accuracy that loss of PTEN function was indicative of pathogenicity. We also determined that the pathogenicity of certain variants may have arisen from reduced stability of the protein product. Overall, this assay outperformed computational predictions, was scalable, and had a short run time, serving as an ideal alternative for annotating the clinical significance of cancer-associated PTEN variants. SIGNIFICANCE: Combined three-dimensional tumor spheroid modeling and machine learning classifies PTEN missense variants, over 70% of which are currently listed as variants of uncertain significance. GRAPHICAL ABSTRACT: http://cancerres.aacrjournals.org/content/canres/80/13/2775/F1.large.jpg.

Deep Mutational Scan of an SCN5A Voltage Sensor

BACKGROUND

Variants in ion channel genes have classically been studied in low throughput by patch clamping. Deep mutational scanning is a complementary approach that can simultaneously assess function of thousands of variants.

METHODS

We have developed and validated a method to perform a deep mutational scan of variants in SCN5A, which encodes the major voltage-gated sodium channel in the heart. We created a library of nearly all possible variants in a 36 base region of SCN5A in the S4 voltage sensor of domain IV and stably integrated the library into HEK293T cells.

RESULTS

In preliminary experiments, challenge with 3 drugs (veratridine, brevetoxin, and ouabain) could discriminate wild-type channels from gain- and loss-of-function pathogenic variants. High-throughput sequencing of the pre- and postdrug challenge pools was used to count the prevalence of each variant and identify variants with abnormal function. The deep mutational scan scores identified 40 putative gain-of-function and 33 putative loss-of-function variants. For 8 of 9 variants, patch clamping data were consistent with the scores.

CONCLUSIONS

These experiments demonstrate the accuracy of a high-throughput in vitro scan of SCN5A variant function, which can be used to identify deleterious variants in SCN5A and other ion channel genes.

An improved platform for functional assessment of large protein libraries in mammalian cells

Multiplex genetic assays can simultaneously test thousands of genetic variants for a property of interest. However, limitations of existing multiplex assay methods in cultured mammalian cells hinder the breadth, speed and scale of these experiments. Here, we describe a series of improvements that greatly enhance the capabilities of a Bxb1 recombinase-based landing pad system for conducting different types of multiplex genetic assays in various mammalian cell lines. We incorporate the landing pad into a lentiviral vector, easing the process of generating new landing pad cell lines. We also develop several new landing pad versions, including one where the Bxb1 recombinase is expressed from the landing pad itself, improving recombination efficiency more than 2-fold and permitting rapid prototyping of transgenic constructs. Other versions incorporate positive and negative selection markers that enable drug-based enrichment of recombinant cells, enabling the use of larger libraries and reducing costs. A version with dual convergent promoters allows enrichment of recombinant cells independent of transgene expression, permitting the assessment of libraries of transgenes that perturb cell growth and survival. Lastly, we demonstrate these improvements by assessing the effects of a combinatorial library of oncogenes and tumor suppressors on cell growth. Collectively, these advancements make multiplex genetic assays in diverse cultured cell lines easier, cheaper and more effective, facilitating future studies probing how proteins impact cell function, using transgenic variant libraries tested individually or in combination.

Recommendations for the collection and use of multiplexed functional data for clinical variant interpretation

Variants of uncertain significance represent a massive challenge to medical genetics. Multiplexed functional assays, in which the functional effects of thousands of genomic variants are assessed simultaneously, are increasingly generating data that can be used as additional evidence for or against variant pathogenicity. Such assays have the potential to resolve variants of uncertain significance, thereby increasing the clinical utility of genomic testing. Existing standards from the American College of Medical Genetics and Genomics (ACMG)/Association for Molecular Pathology (AMP) and new guidelines from the Clinical Genome Resource (ClinGen) establish the role of functional data in variant interpretation, but do not address the specific challenges or advantages of using functional data derived from multiplexed assays. Here, we build on these existing guidelines to provide recommendations to experimentalists for the production and reporting of multiplexed functional data and to clinicians for the evaluation and use of such data. By following these recommendations, experimentalists can produce transparent, complete, and well-validated datasets that are primed for clinical uptake. Our recommendations to clinicians and diagnostic labs on how to evaluate the quality of multiplexed functional datasets, and how different datasets could be incorporated into the ACMG/AMP variant-interpretation framework, will hopefully clarify whether and how such data should be used. The recommendations that we provide are designed to enhance the quality and utility of multiplexed functional data, and to promote their judicious use.

MaveDB: an open-source platform to distribute and interpret data from multiplexed assays of variant effect

Multiplex assays of variant effect (MAVEs), such as deep mutational scans and massively parallel reporter assays, test thousands of sequence variants in a single experiment. Despite the importance of MAVE data for basic and clinical research, there is no standard resource for their discovery and distribution. Here, we present MaveDB ( https://www.mavedb.org ), a public repository for large-scale measurements of sequence variant impact, designed for interoperability with applications to interpret these datasets. We also describe the first such application, MaveVis, which retrieves, visualizes, and contextualizes variant effect maps. Together, the database and applications will empower the community to mine these powerful datasets.

The Impact of Genetic Variants on PTEN Molecular Functions and Cellular Phenotypes

Phosphatase and tensin homolog (PTEN) is a tumor suppressor that directly regulates a diverse array of cellular phenotypes, including growth, migration, morphology, and genome stability. How a single protein impacts so many important cellular processes remains a fascinating question. This question has been partially resolved by the characterization of a slew of missense variants that alter or eliminate PTEN's various molecular functions, including its enzymatic activity, subcellular localization, and posttranslational modifications. Here, we review what is known about how PTEN variants impact molecular function and, consequently, cellular phenotype. In particular, we highlight eight informative "sentinel variants" that abrogate distinct molecular functions of PTEN. We consider two published massively parallel assays of variant effect that measured the effect of thousands of PTEN variants on protein abundance and enzymatic activity. Finally, we discuss how characterization of clinically ascertained variants, establishment of clinical sequencing databases, and massively parallel assays of variant effect yield complementary datasets for dissecting PTEN's role in disease.

Interrogation of CYP2D6 Structural Variant Alleles Improves the Correlation Between CYP2D6 Genotype and CYP2D6-Mediated Metabolic Activity

The cytochrome P450 2D6 (CYP2D6) gene locus is challenging to accurately genotype due to numerous single nucleotide variants and complex structural variation. Our goal was to determine whether the CYP2D6 genotype‐phenotype correlation is improved when diplotype assignments incorporate structural variation, identified by the bioinformatics tool Stargazer, with next‐generation sequencing data. Using CYP2D6 activity measured with substrates dextromethorphan and metoprolol, activity score explained 40% and 34% of variability in metabolite formation rates, respectively, when diplotype calls incorporated structural variation, increasing from 36% and 31%, respectively, when diplotypes did not incorporate structural variation. We also investigated whether the revised Clinical Pharmacogenetics Implementation Consortium (CPIC) recommendations for translating genotype to phenotype improve CYP2D6 activity predictions over the current system. Although the revised recommendations do not improve the correlation between activity score and CYP2D6 activity, perhaps because of low frequency of the CYP2D6*10 allele, the correlation with metabolizer phenotype group was significantly improved for both substrates. We also measured the function of seven rare coding variants: one (A449D) exhibited decreased (44%) and another (R474Q) increased (127%) activity compared with reference CYP2D6.1 protein. Allele‐specific analysis found that A449D is part of a novel CYP2D6*4 suballele, CYP2D6*4.028. The novel haplotype containing R474Q was designated CYP2D6*138 by PharmVar; another novel haplotype containing R365H was designated CYP2D6*139. Accuracy of CYP2D6 phenotype prediction is improved when the CYP2D6 gene locus is interrogated using next‐generation sequencing coupled with structural variation analysis. Additionally, revised CPIC genotype to phenotype translation recommendations provides an improvement in assigning CYP2D6 activity.

Biophysical and Mechanistic Models for Disease-Causing Protein Variants

The rapid decrease in DNA sequencing cost is revolutionizing medicine and science. In medicine, genome sequencing has revealed millions of missense variants that change protein sequences, yet we only understand the molecular and phenotypic consequences of a small fraction. Within protein science, high-throughput deep mutational scanning experiments enable us to probe thousands of variants in a single, multiplexed experiment. We review efforts that bring together these topics via experimental and computational approaches to determine the consequences of missense variants in proteins. We focus on the role of changes in protein stability as a driver for disease, and how experiments, biophysical models, and computation are providing a framework for understanding and predicting how changes in protein sequence affect cellular protein stability.

Multiplex assessment of protein variant abundance by massively parallel sequencing

Determining the pathogenicity of genetic variants is a critical challenge, and functional assessment is often the only option. Experimentally characterizing millions of possible missense variants in thousands of clinically important genes requires generalizable, scalable assays. We describe variant abundance by massively parallel sequencing (VAMP-seq), which measures the effects of thousands of missense variants of a protein on intracellular abundance simultaneously. We apply VAMP-seq to quantify the abundance of 7,801 single-amino-acid variants of PTEN and TPMT, proteins in which functional variants are clinically actionable. We identify 1,138 PTEN and 777 TPMT variants that result in low protein abundance, and may be pathogenic or alter drug metabolism, respectively. We observe selection for low-abundance PTEN variants in cancer, and show that p.Pro38Ser, which accounts for ~10% of PTEN missense variants in melanoma, functions via a dominant-negative mechanism. Finally, we demonstrate that VAMP-seq is applicable to other genes, highlighting its generalizability.

Rheostatic Control of Cas9-Mediated DNA Double Strand Break (DSB) Generation and Genome Editing

We recently reported two novel tools for precisely controlling and quantifying Cas9 activity: a chemically inducible Cas9 variant (ciCas9) that can be rapidly activated by small molecules and a ddPCR assay for time-resolved measurement of DNA double strand breaks (DSB-ddPCR). Here, we further demonstrate the potential of ciCas9 to function as a tunable rheostat for Cas9 function. We show that a new highly potent and selective small molecule activator paired with a more tightly regulated ciCas9 variant expands the range of accessible Cas9 activity levels. We subsequently demonstrate that ciCas9 activity levels can be dose-dependently tuned with a small molecule activator, facilitating rheostatic time-course experiments. These studies provide the first insight into how Cas9-mediated DSB levels correlate with overall editing efficiency. Thus, we demonstrate that ciCas9 and our DSB-ddPCR assay permit the time-resolved study of Cas9 DSB generation and genome editing kinetics at a wide range of Cas9 activity levels.

Correction to: A statistical framework for analyzing deep mutational scanning data

CORRECTION

After publication of our article [1] it was brought to our attention that a line of code was missing from our program to combine the within-replicate variance and between-replicate variance. This led to an overestimation of the standard errors calculated using the Enrich2 random-effects model.

Pharmacogenomics of CYP2C9: Functional and Clinical Considerations

CYP2C9 is the most abundant CYP2C subfamily enzyme in human liver and the most important contributor from this subfamily to drug metabolism. Polymorphisms resulting in decreased enzyme activity are common in the CYP2C9 gene and this, combined with narrow therapeutic indices for several key drug substrates, results in some important issues relating to drug safety and efficacy. CYP2C9 substrate selectivity is detailed and, based on crystal structures for the enzyme, we describe how CYP2C9 catalyzes these reactions. Factors relevant to clinical response to CYP2C9 substrates including inhibition, induction and genetic polymorphism are discussed in detail. In particular, we consider the issue of ethnic variation in pattern and frequency of genetic polymorphisms and clinical implications. Warfarin is the most well studied CYP2C9 substrate; recent work on use of dosing algorithms that include CYP2C9 genotype to improve patient safety during initiation of warfarin dosing are reviewed and prospects for their clinical implementation considered. Finally, we discuss a novel approach to cataloging the functional capabilities of rare 'variants of uncertain significance', which are increasingly detected as more exome and genome sequencing of diverse populations is conducted.

A framework for exhaustively mapping functional missense variants

Although we now routinely sequence human genomes, we can confidently identify only a fraction of the sequence variants that have a functional impact. Here, we developed a deep mutational scanning framework that produces exhaustive maps for human missense variants by combining random codon mutagenesis and multiplexed functional variation assays with computational imputation and refinement. We applied this framework to four proteins corresponding to six human genes: UBE2I (encoding SUMO E2 conjugase), SUMO1 (small ubiquitin‐like modifier), TPK1 (thiamin pyrophosphokinase), and CALM1/2/3 (three genes encoding the protein calmodulin). The resulting maps recapitulate known protein features and confidently identify pathogenic variation. Assays potentially amenable to deep mutational scanning are already available for 57% of human disease genes, suggesting that DMS could ultimately map functional variation for all human disease genes.

Quantitative Missense Variant Effect Prediction Using Large-Scale Mutagenesis Data

Large datasets describing the quantitative effects of mutations on protein function are becoming increasingly available. Here, we leverage these datasets to develop Envision, which predicts the magnitude of a missense variant's molecular effect. Envision combines 21,026 variant effect measurements from nine large-scale experimental mutagenesis datasets, a hitherto untapped training resource, with a supervised, stochastic gradient boosting learning algorithm. Envision outperforms other missense variant effect predictors both on large-scale mutagenesis data and on an independent test dataset comprising 2,312 TP53 variants whose effects were measured using a low-throughput approach. This dataset was never used for hyperparameter tuning or model training and thus serves as an independent validation set. Envision prediction accuracy is also more consistent across amino acids than other predictors. Finally, we demonstrate that Envision's performance improves as more large-scale mutagenesis data are incorporated. We precompute Envision predictions for every possible single amino acid variant in human, mouse, frog, zebrafish, fruit fly, worm, and yeast proteomes (https://envision.gs.washington.edu/).

Expression and Functional Characterization of Breast Cancer-Associated Cytochrome P450 4Z1 in Saccharomyces cerevisiae

CYP4Z1 is an "orphan" cytochrome P450 (P450) enzyme that has provoked interest because of its hypothesized role in breast cancer through formation of the signaling molecule 20-hydroxyeicosatetraenoic acid (20-HETE). We expressed human CYP4Z1 in Saccharomyces cerevisiae and evaluated its catalytic capabilities toward arachidonic and lauric acids (AA and LA). Specific and sensitive mass spectrometry assays enabled discrimination of the regioselectivity of hydroxylation of these two fatty acids. CYP4Z1 generated 7-, 8-, 9-, 10-, and 11-hydroxy LA, whereas the 12-hydroxy metabolite was not detected. HET0016, the prototypic CYP4 inhibitor, only weakly inhibited laurate metabolite formation (IC50 ∼15 μM). CYP4Z1 preferentially oxidized AA to the 14(S),15(R)-epoxide with high regioselectivity and stereoselectivity, a reaction that was also insensitive to HET0016, but neither 20-HETE nor 20-carboxy-AA were detectable metabolites. Docking of LA and AA into a CYP4Z1 homology model was consistent with this preference for internal fatty acid oxidation. Thus, human CYP4Z1 has an inhibitor profile and product regioselectivity distinct from most other CYP4 enzymes, consistent with CYP4Z1's lack of a covalently linked heme. These data suggest that, if CYP4Z1 modulates breast cancer progression, it does so by a mechanism other than direct production of 20-HETE.

A platform for functional assessment of large variant libraries in mammalian cells

Sequencing-based, massively parallel genetic assays have revolutionized our ability to quantify the relationship between many genotypes and a phenotype of interest. Unfortunately, variant library expression platforms in mammalian cells are far from ideal, hindering the study of human gene variants in their physiologically relevant cellular contexts. Here, we describe a platform for phenotyping variant libraries in transfectable mammalian cell lines in two steps. First, a landing pad cell line with a genomically integrated, Tet-inducible cassette containing a Bxb1 recombination site is created. Second, a single variant from a library of transfected, promoter-less plasmids is recombined into the landing pad in each cell. Thus, every cell in the recombined pool expresses a single variant, allowing for parallel, sequencing-based assessment of variant effect. We describe a method for incorporating a single landing pad into a defined site of a cell line of interest, and show that our approach can be used generate more than 20 000 recombinant cells in a single experiment. Finally, we use our platform in combination with a sequencing-based assay to explore the N-end rule by simultaneously measuring the effects of all possible N-terminal amino acids on protein expression.