Determinants of trafficking, conduction, and disease within a K+ channel revealed through multiparametric deep mutational scanning

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.

Rosace: a robust deep mutational scanning analysis framework employing position and mean-variance shrinkage

Deep mutational scanning (DMS) measures the effects of thousands of genetic variants in a protein simultaneously. The small sample size renders classical statistical methods ineffective. For example, p-values cannot be correctly calibrated when treating variants independently. We propose Rosace, a Bayesian framework for analyzing growth-based DMS data. Rosace leverages amino acid position information to increase power and control the false discovery rate by sharing information across parameters via shrinkage. We also developed Rosette for simulating the distributional properties of DMS. We show that Rosace is robust to the violation of model assumptions and is more powerful than existing tools.

The full spectrum of SLC22 OCT1 mutations illuminates the bridge between drug transporter biophysics and pharmacogenomics

Mutations in transporters can impact an individual's response to drugs and cause many diseases. Few variants in transporters have been evaluated for their functional impact. Here, we combine saturation mutagenesis and multi-phenotypic screening to dissect the impact of 11,213 missense single-amino-acid deletions, and synonymous variants across the 554 residues of OCT1, a key liver xenobiotic transporter. By quantifying in parallel expression and substrate uptake, we find that most variants exert their primary effect on protein abundance, a phenotype not commonly measured alongside function. Using our mutagenesis results combined with structure prediction and molecular dynamic simulations, we develop accurate structure-function models of the entire transport cycle, providing biophysical characterization of all known and possible human OCT1 polymorphisms. This work provides a complete functional map of OCT1 variants along with a framework for integrating functional genomics, biophysical modeling, and human genetics to predict variant effects on disease and drug efficacy.

Molecular basis of proton-sensing by G protein-coupled receptors

Three proton-sensing G protein-coupled receptors (GPCRs), GPR4, GPR65, and GPR68, respond to changes in extracellular pH to regulate diverse physiology and are implicated in a wide range of diseases. A central challenge in determining how protons activate these receptors is identifying the set of residues that bind protons. Here, we determine structures of each receptor to understand the spatial arrangement of putative proton sensing residues in the active state. With a newly developed deep mutational scanning approach, we determined the functional importance of every residue in proton activation for GPR68 by generating ~9,500 mutants and measuring effects on signaling and surface expression. This unbiased screen revealed that, unlike other proton-sensitive cell surface channels and receptors, no single site is critical for proton recognition in GPR68. Instead, a network of titratable residues extend from the extracellular surface to the transmembrane region and converge on canonical class A GPCR activation motifs to activate proton-sensing GPCRs. More broadly, our approach integrating structure and unbiased functional interrogation defines a new framework for understanding the rich complexity of GPCR signaling.

Multiplex Functional Characterization of Protein Variant Libraries in Mammalian Cells with Single-Copy Genomic Integration and High-Throughput DNA Sequencing

Sequencing-based, massively parallel genetic assays have enabled simultaneous characterization of the genotype-phenotype relationships for libraries encoding thousands of unique protein variants. Since plasmid transfection and lentiviral transduction have characteristics that limit multiplexing with pooled libraries, we developed a mammalian synthetic biology platform that harnesses the Bxb1 bacteriophage DNA recombinase to insert single promoterless plasmids encoding a transgene of interest into a pre-engineered "landing pad" site within the cell genome. The transgene is expressed behind a genomically integrated promoter, ensuring only one transgene is expressed per cell, preserving a strict genotype-phenotype link. Upon selecting cells based on a desired phenotype, the transgene can be sequenced to ascribe each variant a phenotypic score. We describe how to create and utilize landing pad cells for large-scale, library-based genetic experiments. Using the provided examples, the experimental template can be adapted to explore protein variants in diverse biological problems within mammalian cells.

ProteinGym: Large-Scale Benchmarks for Protein Design and Fitness Prediction

Predicting the effects of mutations in proteins is critical to many applications, from understanding genetic disease to designing novel proteins that can address our most pressing challenges in climate, agriculture and healthcare. Despite a surge in machine learning-based protein models to tackle these questions, an assessment of their respective benefits is challenging due to the use of distinct, often contrived, experimental datasets, and the variable performance of models across different protein families. Addressing these challenges requires scale. To that end we introduce ProteinGym, a large-scale and holistic set of benchmarks specifically designed for protein fitness prediction and design. It encompasses both a broad collection of over 250 standardized deep mutational scanning assays, spanning millions of mutated sequences, as well as curated clinical datasets providing high-quality expert annotations about mutation effects. We devise a robust evaluation framework that combines metrics for both fitness prediction and design, factors in known limitations of the underlying experimental methods, and covers both zero-shot and supervised settings. We report the performance of a diverse set of over 70 high-performing models from various subfields (eg., alignment-based, inverse folding) into a unified benchmark suite. We open source the corresponding codebase, datasets, MSAs, structures, model predictions and develop a user-friendly website that facilitates data access and analysis.

Two epilepsy-associated variants in KCNA2 (KV 1.2) at position H310 oppositely affect channel functional expression

Two KCNA2 variants (p.H310Y and p.H310R) were discovered in paediatric patients with epilepsy and developmental delay. KCNA2 encodes KV 1.2-channel subunits, which regulate neuronal excitability. Both gain and loss of KV 1.2 function cause epilepsy, precluding the prediction of variant effects; and while H310 is conserved throughout the KV -channel superfamily, it is largely understudied. We investigated both variants in heterologously expressed, human KV 1.2 channels by immunocytochemistry, electrophysiology and voltage-clamp fluorometry. Despite affecting the same channel, at the same position, and being associated with severe neurological disease, the two variants had diametrically opposite effects on KV 1.2 functional expression. The p.H310Y variant produced 'dual gain of function', increasing both cell-surface trafficking and activity, delaying channel closure. We found that the latter is due to the formation of a hydrogen bond that stabilizes the active state of the voltage-sensor domain. Additionally, H310Y abolished 'ball and chain' inactivation of KV 1.2 by KV β1 subunits, enhancing gain of function. In contrast, p.H310R caused 'dual loss of function', diminishing surface levels by multiple impediments to trafficking and inhibiting voltage-dependent channel opening. We discuss the implications for KV -channel biogenesis and function, an emergent hotspot for disease-associated variants, and mechanisms of epileptogenesis. KEY POINTS: KCNA2 encodes the subunits of KV 1.2 voltage-activated, K+ -selective ion channels, which regulate electrical signalling in neurons. We characterize two KCNA2 variants from patients with developmental delay and epilepsy. Both variants affect position H310, highly conserved in KV channels. The p.H310Y variant caused 'dual gain of function', increasing both KV 1.2-channel activity and the number of KV 1.2 subunits on the cell surface. H310Y abolished 'ball and chain' (N-type) inactivation of KV 1.2 by KV β1 subunits, enhancing the gain-of-function phenotype. The p.H310R variant caused 'dual loss of function', diminishing the presence of KV 1.2 subunits on the cell surface and inhibiting voltage-dependent channel opening. As H310Y stabilizes the voltage-sensor active conformation and abolishes N-type inactivation, it can serve as an investigative tool for functional and pharmacological studies.

Development of automated patch clamp assays to overcome the burden of variants of uncertain significance in inheritable arrhythmia syndromes

Advances in next-generation sequencing have been exceptionally valuable for identifying variants in medically actionable genes. However, for most missense variants there is insufficient evidence to permit definitive classification of variants as benign or pathogenic. To overcome the deluge of Variants of Uncertain Significance, there is an urgent need for high throughput functional assays to assist with the classification of variants. Advances in parallel planar patch clamp technologies has enabled the development of automated high throughput platforms capable of increasing throughput 10- to 100-fold compared to manual patch clamp methods. Automated patch clamp electrophysiology is poised to revolutionize the field of functional genomics for inheritable cardiac ion channelopathies. In this review, we outline i) the evolution of patch clamping, ii) the development of high-throughput automated patch clamp assays to assess cardiac ion channel variants, iii) clinical application of these assays and iv) where the field is heading.

Deep mutational scanning of proteins in mammalian cells

Protein mutagenesis is essential for unveiling the molecular mechanisms underlying protein function in health, disease, and evolution. In the past decade, deep mutational scanning methods have evolved to support the functional analysis of nearly all possible single-amino acid changes in a protein of interest. While historically these methods were developed in lower organisms such as E. coli and yeast, recent technological advancements have resulted in the increased use of mammalian cells, particularly for studying proteins involved in human disease. These advancements will aid significantly in the classification and interpretation of variants of unknown significance, which are being discovered at large scale due to the current surge in the use of whole-genome sequencing in clinical contexts. Here, we explore the experimental aspects of deep mutational scanning studies in mammalian cells and report the different methods used in each step of the workflow, ultimately providing a useful guide toward the design of such studies.

Accurate proteome-wide missense variant effect prediction with AlphaMissense

The vast majority of missense variants observed in the human genome are of unknown clinical significance. We present AlphaMissense, an adaptation of AlphaFold fine-tuned on human and primate variant population frequency databases to predict missense variant pathogenicity. By combining structural context and evolutionary conservation, our model achieves state-of-the-art results across a wide range of genetic and experimental benchmarks, all without explicitly training on such data. The average pathogenicity score of genes is also predictive for their cell essentiality, capable of identifying short essential genes that existing statistical approaches are underpowered to detect. As a resource to the community, we provide a database of predictions for all possible human single amino acid substitutions and classify 89% of missense variants as either likely benign or likely pathogenic.

Rapid Characterization of the Functional and Pharmacological Consequences of Cantú Syndrome KATP Channel Mutations in Intact Cells

Gain-of-function of KATP channels, resulting from mutations in either KCNJ8 (encoding inward rectifier sub-family 6 [Kir6.1]) or ABCC9 (encoding sulphonylurea receptor [SUR2]), cause Cantú syndrome (CS), a channelopathy characterized by excess hair growth, coarse facial appearance, cardiomegaly, and lymphedema. Here, we established a pipeline for rapid analysis of CS mutation consequences in Landing pad HEK 293 cell lines stably expressing wild type (WT) and mutant human Kir6.1 and SUR2B. Thallium-influx and cell membrane potential, reported by fluorescent Tl-sensitive Fluozin-2 and voltage-sensitive bis-(1,3-dibutylbarbituric acid)trimethine oxonol (DiBAC4(3)) dyes, respectively, were used to assess channel activity. In the Tl-influx assay, CS-associated Kir6.1 mutations increased sensitivity to the ATP-sensitive potassium (KATP) channel activator, pinacidil, but there was strikingly little effect of pinacidil for any SUR2B mutations, reflecting unexpected differences in the molecular mechanisms of Kir6.1 versus SUR2B mutations. Compared with the Tl-influx assay, the DiBAC4(3) assay presents more significant signal changes in response to subtle KATP channel activity changes, and all CS mutants (both Kir6.1 and SUR2B), but not WT channels, caused marked hyperpolarization, demonstrating that all mutants were activated under ambient conditions in intact cells. Most SUR2 CS mutations were markedly inhibited by <100 nM glibenclamide, but sensitivity to inhibition by glibenclamide, repaglinide, and PNU37883A was markedly reduced for Kir6.1 CS mutations. Understanding functional consequences of mutations can help with disease diagnosis and treatment. The analysis pipeline we have developed has the potential to rapidly identify mutational consequences, aiding future CS diagnosis, drug discovery, and individualization of treatment. SIGNIFICANCE STATEMENT: We have developed new fluorescence-based assays of channel activities and drug sensitivities of Cantú syndrome (CS) mutations in human Kir6.1/SUR2B-dependent KATP channels, showing that Kir6.1 mutations increase sensitivity to potassium channel openers, while SUR2B mutations markedly reduce K channel opener (KCO) sensitivity. However, both Kir6.1 and SUR2B CS mutations are both more hyperpolarized than WT cells under basal conditions, confirming pathophysiologically relevant gain-of-function, validating DiBAC4(3) fluorescence to characterize hyperpolarization induced by KATP channel activity under basal, non KCO-activated conditions.

Scanning mutagenesis of the voltage-gated sodium channel NaV1.2 using base editing

It is challenging to apply traditional mutational scanning to voltage-gated sodium channels (NaVs) and functionally annotate the large number of coding variants in these genes. Using a cytosine base editor and a pooled viability assay, we screen a library of 368 guide RNAs (gRNAs) tiling NaV1.2 to identify more than 100 gRNAs that change NaV1.2 function. We sequence base edits made by a subset of these gRNAs to confirm specific variants that drive changes in channel function. Electrophysiological characterization of these channel variants validates the screen results and provides functional mechanisms of channel perturbation. Most of the changes caused by these gRNAs are classifiable as loss of function along with two missense mutations that lead to gain of function in NaV1.2 channels. This two-tiered strategy to functionally characterize ion channel protein variants at scale identifies a large set of loss-of-function mutations in NaV1.2.

The full spectrum of OCT1 (SLC22A1) mutations bridges transporter biophysics to drug pharmacogenomics

Membrane transporters play a fundamental role in the tissue distribution of endogenous compounds and xenobiotics and are major determinants of efficacy and side effects profiles. Polymorphisms within these drug transporters result in inter-individual variation in drug response, with some patients not responding to the recommended dosage of drug whereas others experience catastrophic side effects. For example, variants within the major hepatic Human organic cation transporter OCT1 (SLC22A1) can change endogenous organic cations and many prescription drug levels. To understand how variants mechanistically impact drug uptake, we systematically study how all known and possible single missense and single amino acid deletion variants impact expression and substrate uptake of OCT1. We find that human variants primarily disrupt function via folding rather than substrate uptake. Our study revealed that the major determinants of folding reside in the first 300 amino acids, including the first 6 transmembrane domains and the extracellular domain (ECD) with a stabilizing and highly conserved stabilizing helical motif making key interactions between the ECD and transmembrane domains. Using the functional data combined with computational approaches, we determine and validate a structure-function model of OCT1s conformational ensemble without experimental structures. Using this model and molecular dynamic simulations of key mutants, we determine biophysical mechanisms for how specific human variants alter transport phenotypes. We identify differences in frequencies of reduced function alleles across populations with East Asians vs European populations having the lowest and highest frequency of reduced function variants, respectively. Mining human population databases reveals that reduced function alleles of OCT1 identified in this study associate significantly with high LDL cholesterol levels. Our general approach broadly applied could transform the landscape of precision medicine by producing a mechanistic basis for understanding the effects of human mutations on disease and drug response.

Emerging maps of allosteric regulation in cellular networks

Allosteric regulation is classically defined as action at a distance, where a perturbation outside of a protein active site affects function. While this definition has motivated many studies of allosteric mechanisms at the level of protein structure, translating these insights to the allosteric regulation of entire cellular processes - and their crosstalk - has received less attention, despite the broad importance of allostery for cellular regulation foreseen by Jacob and Monod. Here, we revisit an evolutionary model for the widespread emergence of allosteric regulation in colocalized proteins, describe supporting evidence, and discuss emerging advances in mapping allostery in cellular networks that link precise and often allosteric perturbations at the molecular level to functional changes at the pathway and systems levels.

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.

Molecular Mechanisms and Clinical Phenotypes of GJB2 Missense Variants

The GJB2 gene is the most common gene responsible for hearing loss (HL) worldwide, and missense variants are the most abundant type. GJB2 pathogenic missense variants cause nonsyndromic HL (autosomal recessive and dominant) and syndromic HL combined with skin diseases. However, the mechanism by which these different missense variants cause the different phenotypes is unknown. Over 2/3 of the GJB2 missense variants have yet to be functionally studied and are currently classified as variants of uncertain significance (VUS). Based on these functionally determined missense variants, we reviewed the clinical phenotypes and investigated the molecular mechanisms that affected hemichannel and gap junction functions, including connexin biosynthesis, trafficking, oligomerization into connexons, permeability, and interactions between other coexpressed connexins. We predict that all possible GJB2 missense variants will be described in the future by deep mutational scanning technology and optimizing computational models. Therefore, the mechanisms by which different missense variants cause different phenotypes will be fully elucidated.

The cellular pathways that maintain the quality control and transport of diverse potassium channels

Potassium channels are multi-subunit transmembrane proteins that permit the selective passage of potassium and play fundamental roles in physiological processes, such as action potentials in the nervous system and organismal salt and water homeostasis, which is mediated by the kidney. Like all ion channels, newly translated potassium channels enter the endoplasmic reticulum (ER) and undergo the error-prone process of acquiring post-translational modifications, folding into their native conformations, assembling with other subunits, and trafficking through the secretory pathway to reach their final destinations, most commonly the plasma membrane. Disruptions in these processes can result in detrimental consequences, including various human diseases. Thus, multiple quality control checkpoints evolved to guide potassium channels through the secretory pathway and clear potentially toxic, aggregation-prone misfolded species. We will summarize current knowledge on the mechanisms underlying potassium channel quality control in the secretory pathway, highlight diseases associated with channel misfolding, and suggest potential therapeutic routes.

Hacking hematopoiesis - emerging tools for examining variant effects

Hematopoiesis is a continuous process of blood and immune cell production. It is orchestrated by thousands of gene products that respond to extracellular signals by guiding cell fate decisions to meet the needs of the organism. Although much of our knowledge of this process comes from work in model systems, we have learned a great deal from studies on human genetic variation. Considerable insight has emerged from studies on presumed monogenic blood disorders, which continue to provide key insights into the mechanisms critical for hematopoiesis. Furthermore, the emergence of large-scale biobanks and cohorts has uncovered thousands of genomic loci associated with blood cell traits and diseases. Some of these blood cell trait-associated loci act as modifiers of what were once thought to be monogenic blood diseases. However, most of these loci await functional validation. Here, we discuss the validation bottleneck and emerging methods to more effectively connect variant to function. In particular, we highlight recent innovations in genome editing, which have paved the path forward for high-throughput functional assessment of loci. Finally, we discuss existing barriers to progress, including challenges in manipulating the genomes of primary hematopoietic cells.

The unique structural characteristics of the Kir 7.1 inward rectifier potassium channel: a novel player in energy homeostasis control

The inward rectifier potassium channel Kir7.1, encoded by the KCNJ13 gene, is a tetramer composed of two-transmembrane domain-spanning monomers, closer in homology to Kir channels associated with potassium transport such as Kir1.1, 1.2, and 1.3. Compared with other channels, Kir7.1 exhibits small unitary conductance and low dependence on external potassium. Kir7.1 channels also show a phosphatidylinositol 4,5-bisphosphate (PIP2) dependence for opening. Accordingly, retinopathy-associated Kir7.1 mutations mapped at the binding site for PIP2 resulted in channel gating defects leading to channelopathies such as snowflake vitreoretinal degeneration and Leber congenital amaurosis in blind patients. Lately, this channel's role in energy homeostasis was reported due to the direct interaction with the melanocortin type 4 receptor (MC4R) in the hypothalamus. As this channel seems to play a multipronged role in potassium homeostasis and neuronal excitability, we will discuss what is predicted from a structural viewpoint and its possible implications for hunger control.

DIMPLE: deep insertion, deletion, and missense mutation libraries for exploring protein variation in evolution, disease, and biology

Insertions and deletions (indels) enable evolution and cause disease. Due to technical challenges, indels are left out of most mutational scans, limiting our understanding of them in disease, biology, and evolution. We develop a low cost and bias method, DIMPLE, for systematically generating deletions, insertions, and missense mutations in genes, which we test on a range of targets, including Kir2.1. We use DIMPLE to study how indels impact potassium channel structure, disease, and evolution. We find deletions are most disruptive overall, beta sheets are most sensitive to indels, and flexible loops are sensitive to deletions yet tolerate insertions.

Genetics of congenital arrhythmia syndromes: the challenge of variant interpretation

Congenital arrhythmia syndromes are rare genetic disorders that can cause a high risk of sudden cardiac death. Expert panels have affirmed 15 genes that are linked to congenital arrhythmias. These genes mostly encode cardiac ion channel proteins or associated regulatory proteins that generate the cardiac action potential. Common genetic variation modulates the risk of rare variants and partially explains the incomplete penetrance of these disorders. As genetic testing becomes more prevalent, a major challenge is that most detected variants are annotated as variants of uncertain significance. This review will highlight emerging methods that are refining our understanding of arrhythmia genetics, including phenotype risk scores, large cohorts, in vitro functional assays, structural models, and computational predictions.

Functional genomics of OCTN2 variants informs protein-specific variant effect predictor for Carnitine Transporter Deficiency

Genetic variants in SLC22A5, encoding the membrane carnitine transporter OCTN2, cause the rare metabolic disorder Carnitine Transporter Deficiency (CTD). CTD is potentially lethal but actionable if detected early, with confirmatory diagnosis involving sequencing of SLC22A5. Interpretation of missense variants of uncertain significance (VUSs) is a major challenge. In this study, we sought to characterize the largest set to date (n = 150) of OCTN2 variants identified in diverse ancestral populations, with the goals of furthering our understanding of the mechanisms leading to OCTN2 loss-of-function (LOF) and creating a protein-specific variant effect prediction model for OCTN2 function. Uptake assays with 14C-carnitine revealed that 105 variants (70%) significantly reduced transport of carnitine compared to wild-type OCTN2, and 37 variants (25%) severely reduced function to less than 20%. All ancestral populations harbored LOF variants; 62% of green fluorescent protein (GFP)-tagged variants impaired OCTN2 localization to the plasma membrane of human embryonic kidney (HEK293T) cells, and subcellular localization significantly associated with function, revealing a major LOF mechanism of interest for CTD. With these data, we trained a model to classify variants as functional (>20% function) or LOF (<20% function). Our model outperformed existing state-of-the-art methods as evaluated by multiple performance metrics, with mean area under the receiver operating characteristic curve (AUROC) of 0.895 ± 0.025. In summary, in this study we generated a rich dataset of OCTN2 variant function and localization, revealed important disease-causing mechanisms, and improved upon machine learning-based prediction of OCTN2 variant function to aid in variant interpretation in the diagnosis and treatment of CTD.

Ion-ing out the genetic variants of Kir2.1

Deep mutational scanning provides new insights into how mutations alter the expression and activity of the potassium ion channel Kir2.1, which is associated with many diseases.

Towards generalizable predictions for G protein-coupled receptor variant expression

Missense mutations that compromise the plasma membrane expression (PME) of integral membrane proteins are the root cause of numerous genetic diseases. Differentiation of this class of mutations from those that specifically modify the activity of the folded protein has proven useful for the development and targeting of precision therapeutics. Nevertheless, it remains challenging to predict the effects of mutations on the stability and/ or expression of membrane proteins. In this work, we utilize deep mutational scanning data to train a series of artificial neural networks to predict the PME of transmembrane domain variants of G protein-coupled receptors from structural and/ or evolutionary features. We show that our best-performing network, which we term the PME predictor, can recapitulate mutagenic trends within rhodopsin and can differentiate pathogenic transmembrane domain variants that cause it to misfold from those that compromise its signaling. This network also generates statistically significant predictions for the relative PME of transmembrane domain variants for another class A G protein-coupled receptor (β₂ adrenergic receptor) but not for an unrelated voltage-gated potassium channel (KCNQ1). Notably, our analyses of these networks suggest structural features alone are generally sufficient to recapitulate the observed mutagenic trends. Moreover, our findings imply that networks trained in this manner may be generalizable to proteins that share a common fold. Implications of our findings for the design of mechanistically specific genetic predictors are discussed.