Deep mutational scanning of CYP2C19 in human cells reveals a substrate specificity-abundance tradeoff.

The Cytochrome P450s (CYPs) enzyme family metabolizes ∼80% of small molecule drugs. Variants in CYPs can substantially alter drug metabolism, leading to improper dosing and severe adverse drug reactions. Due to low sequence conservation, predicting variant effects across CYPs is challenging. Even closely related CYPs like CYP2C9 and CYP2C19, which share 92% amino acid sequence identity, display distinct phenotypic properties. Using Variant Abundance by Massively Parallel sequencing (VAMP-seq), we measured the steady-state protein abundance of 7,660 single amino acid variants in CYP2C19 expressed in cultured human cells. Our findings confirmed critical positions and structural features essential for CYP function and revealed how variants at conserved positions influence abundance. We jointly analyzed 4,670 variants whose abundance was measured in both CYP2C19 and CYP2C9, finding that the homologs have different variant abundances in substrate recognition sites within the hydrophobic core. We also measured the abundance of all single and some multiple WT amino acid exchanges between CYP2C19 and CYP2C9. While most exchanges had no effect, substitutions in substrate recognition site 4 (SRS4) reduced abundance in CYP2C19. Double and triple mutants showed distinct interactions, highlighting a region that points to differing thermodynamic properties between the two homologs. These positions are known contributors to substrate specificity, suggesting an evolutionary tradeoff between stability and enzymatic function. Finally, we analyzed 368 previously unannotated human variants, finding that 43% had decreased abundance. By comparing variant effects between these homologs, we uncovered regions underlying their functional differences, advancing our understanding of this versatile family of enzymes.

Calibration of variant effect predictors on genome-wide data masks heterogeneous performance across genes.

In silico variant effect predictions are available for nearly all missense variants but played a minimal role in clinical variant classification because they were deemed to provide only supporting evidence. Recently, the ClinGen Sequence Variant Interpretation (SVI) Working Group updated recommendations for variant effect prediction use. By analyzing control pathogenic and benign variants across all genes, they were able to compute evidence strength for predictor score intervals with some intervals generating moderate, strong, or even very strong evidence. However, this genome-wide approach could obscure heterogeneous predictor performance in different genes. We quantified the gene-by-gene performance of two top predictors, REVEL and BayesDel, by analyzing control variants in each predictor score interval in 3,668 disease-relevant genes. Approximately 10% of intervals had sufficient control variants for analysis, and ∼70% of these intervals exceeded the maximum number of incorrect predictions implied by the SVI recommendations. These trending discordant intervals arose owing to the divergence of the gene-specific distribution of predictions from the genome-wide distribution, suggesting that gene-specific calibration is needed in many cases. Approximately 22% of ClinVar missense variants of uncertain significance in genes we analyzed (REVEL = 100,629, BayesDel = 71,928) had predictions in trending discordant intervals. Thus, genome-wide calibrations could result in many variants receiving inappropriate evidence strength. To facilitate a review of the SVI's calibrations, we developed a web application enabling visualization of gene-specific predictions and trending concordant and discordant intervals.

Retinoic acid induces human gastruloids with posterior embryo-like structures.

Gastruloids are a powerful in vitro model of early human development. However, although elongated and composed of all three germ layers, human gastruloids do not morphologically resemble post-implantation human embryos. Here we show that an early pulse of retinoic acid (RA), together with later Matrigel, robustly induces human gastruloids with posterior embryo-like morphological structures, including a neural tube flanked by segmented somites and diverse cell types, including neural crest, neural progenitors, renal progenitors and myocytes. Through in silico staging based on single-cell RNA sequencing, we find that human RA-gastruloids progress further than other human or mouse embryo models, aligning to E9.5 mouse and CS11 cynomolgus monkey embryos. We leverage chemical and genetic perturbations of RA-gastruloids to confirm that WNT and BMP signalling regulate somite formation and neural tube length in the human context, while transcription factors TBX6 and PAX3 underpin presomitic mesoderm and neural crest, respectively. Looking forward, RA-gastruloids are a robust, scalable model for decoding early human embryogenesis.

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. METHODS: In this study, we leveraged 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. RESULTS: We comprehensively assayed KCNE1 variant cell surface expression (2554/2709 possible single-amino-acid variants) and function (2534 variants). Our study identified 470 loss- or partial loss-of-surface expression and 574 loss- or partial loss-of-function variants. Of the 574 loss- or partial loss-of-function variants, 152 (26.5%) had reduced cell surface expression, indicating that most functionally deleterious variants affect channel gating. Nonsense variants at residues 56-104 generally had WT-like trafficking scores but decreased functional scores, indicating that 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 (with > 70% loss-of-function variants) were in predicted close contact with binding partners KCNQ1 or calmodulin. Our functional assay data were consistent with gold standard electrophysiological data (ρ = - 0.64), population and patient cohorts (32/38 presumed benign or pathogenic variants with consistent scores), and computational predictors (ρ = - 0.62). Our data provide moderate-strength evidence for the American College of Medical Genetics/Association of Molecular Pathology functional criteria for benign and pathogenic variants. CONCLUSIONS: Comprehensive variant effect maps of KCNE1 can both provide insight into I Ks channel biology and help reclassify variants of uncertain significance.

Deep mutational scanning reveals a correlation between degradation and toxicity of thousands of aspartoacylase variants.

Unstable proteins are prone to form non-native interactions with other proteins and thereby may become toxic. To mitigate this, destabilized proteins are targeted by the protein quality control network. Here we present systematic studies of the cytosolic aspartoacylase, ASPA, where variants are linked to Canavan disease, a lethal neurological disorder. We determine the abundance of 6152 of the 6260 ( ~ 98%) possible single amino acid substitutions and nonsense ASPA variants in human cells. Most low abundance variants are degraded through the ubiquitin-proteasome pathway and become toxic upon prolonged expression. The data correlates with predicted changes in thermodynamic stability, evolutionary conservation, and separate disease-linked variants from benign variants. Mapping of degradation signals (degrons) shows that these are often buried and the C-terminal region functions as a degron. The data can be used to interpret Canavan disease variants and provide insight into the relationship between protein stability, degradation and cell fitness.

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.

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.

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.

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.

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 (ß-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 ß-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 ß-MHC variant abundance by massively parallel sequencing and hiPSC-derived cardiomyocyte survival. RESULTS: Both the multiplexed assessment of ß-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.

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.

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.

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.

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.

Reactivity of Dissolved Organic Matter with the Hydrated Electron: Implications for Treatment of Chemical Contaminants in Water with Advanced Reduction Processes.

Advanced reduction processes (ARP) have garnered increasing attention for the treatment of recalcitrant chemical contaminants, most notably per- and polyfluoroalkyl substances (PFAS). However, the impact of dissolved organic matter (DOM) on the availability of the hydrated electron (eaq-), the key reactive species formed in ARP, is not completely understood. Using electron pulse radiolysis and transient absorption spectroscopy, we measured bimolecular reaction rates constant for eaq- reaction with eight aquatic and terrestrial humic substance and natural organic matter isolates ( kDOM,eaq-), with the resulting values ranging from (0.51 ± 0.01) to (2.11 ± 0.04) × 108 MC-1 s-1. kDOM,eaq- measurements at varying temperature, pH, and ionic strength indicate that activation energies for diverse DOM isolates are ≈18 kJ mol-1 and that kDOM,eaq- could be expected to vary by less than a factor of 1.5 between pH 5 and 9 or from an ionic strength of 0.02 to 0.12 M. kDOM,eaq- exhibited a significant, positive correlation to % carbonyl carbon for the isolates studied, but relationships to other DOM physicochemical properties were surprisingly more scattered. A 24 h UV/sulfite experiment employing chloroacetate as an eaq- probe revealed that continued eaq- exposure abates DOM chromophores and eaq- scavenging capacity over a several hour time scale. Overall, these results indicate that DOM is an important eaq- scavenger that will reduce the rate of target contaminant degradation in ARP. These impacts are likely greater in waste streams like membrane concentrates, spent ion exchange resins, or regeneration brines that have elevated DOM concentrations.

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 3929 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 ß1-ß2 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 ß1-ß2 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.