The functional impact of 1,570 individual amino acid substitutions in human OTC

Biochemical Characterization of Disease-Associated Variants of Human Ornithine Transcarbamylase

Human ornithine transcarbamylase deficiency (OTCD) is the most common ureagenesis disorder in the world. OTCD is an X-linked genetic deficiency in which patients experience hyperammonemia to varying degrees depending on the severity of the genetic mutation. More than two-thirds of the known mutations are caused by single nucleotide substitutions. In this paper, partial order optimum likelihood (POOL), a machine learning method, is used to analyze single nucleotide substitutions in OTC with varying disease phenotypes and predicted catalytic efficiencies. Specifically, we used a computed metric, μ4, a measure of the degree of coupling between an ionizable residue and its neighbors, calculated for the catalytic residues, to identify which protein variants were most likely to have impacted catalytic activities. From this analysis, 17 disease-associated variants were selected plus one additional variant, representing a range of μ4 values and POOL ranks. Then μ4 predictions were compared with established bioinformatics tools, SIFT, PolyPhen-2, Provean, FATHMM, MutPred2, and MutationTaster2. The bioinformatics tools predicted that most of these mutations are deleterious. The variants were biochemically characterized using kinetics assays, size exclusion chromatography, and differential scanning fluorimetry. POOL combined with μ4 analysis was able to predict correctly which variants were catalytically hindered in vitro for 17 out of 18 variants. Then by expressing a subset of these proteins in cell culture, mechanisms for disease were proposed. Analysis using μ4 is a complementary method to the sequence-based bioinformatics tools for predicting the effects of mutation on catalytic function.

Rare biochemical & genetic conditions: clues for broader mechanistic insights

Rare disorders often represent a molecular deviation from hi-fidelity genomic integrity networks and are often perceived as too difficult or unimportant for further mechanistic studies. Here, we synthesize evidence demonstrating how valuable knowledge of biochemical pathways related to rare disorders can be for biomedicine. To this end, we describe several rare congenital lipid, protein, organic acid, and glycan metabolism disorders and discuss how rare phenotypes (such as "extreme responders") and case reports (such as the lenalidomide cases) have provided clues for drug discovery or repurposing. We also discuss how rare disorders such as Gaucher disease and ultra-rare genetic syndromes can provide insights into cancer and mTOR-driven metabolism, respectively. Our discussion highlights the continued value of biochemical pathways and studies in understanding human pathophysiology and drug discovery even in the genomics era.

Kingdom-specific lipid unsaturation calibrates sequence evolution in membrane arm subunits of eukaryotic respiratory complexes

Sequence evolution of protein complexes (PCs) is constrained by protein-protein interactions (PPIs). PPI-interfaces are predominantly conserved and hotspots for disease-related mutations. How do lipid-protein interactions (LPIs) constrain sequence evolution of membrane-PCs? We explore Respiratory Complexes (RCs) as a case study as these allow to compare sequence evolution in subunits exposed to both lipids in inner-mitochondrial membrane (IMM) and lipid-free aqueous matrix. We find that lipid-exposed surfaces of the IMM-subunits but not of the matrix subunits are populated with non-PPI disease-causing mutations signifying LPIs in stabilizing RCs. Further, IMM-subunits including their exposed surfaces show high intra-kingdom sequence conservation but remarkably diverge beyond. Molecular Dynamics simulation suggests contrasting LPIs of structurally superimposable but sequence-wise diverged IMM-exposed helices of Complex I (CI) subunit Ndufa1 from human and Arabidopsis depending on kingdom-specific unsaturation of cardiolipin fatty acyl chains. in cellulo assays consolidate inter-kingdom incompatibility of Ndufa1-helices due to the lipid-exposed amino acids. Plant-specific unsaturated fatty acids in human cells also trigger CI-instability. Taken together, we posit that altered LPIs calibrate sequence evolution at the IMM-arms of eukaryotic RCs.

Prequalification of genome-based newborn screening for severe childhood genetic diseases through federated training based on purifying hyperselection

Genome-sequence-based newborn screening (gNBS) has substantial potential to improve outcomes in hundreds of severe childhood genetic disorders (SCGDs). However, a major impediment to gNBS is imprecision due to variants classified as pathogenic (P) or likely pathogenic (LP) that are not SCGD causal. gNBS with 53,855 P/LP variants, 342 genes, 412 SCGDs, and 1,603 therapies was positive in 74% of UK Biobank (UKB470K) adults, suggesting 97% false positives. We used the phenomenon of purifying hyperselection, which acts to decrease the frequency of SCGD causal diplotypes, to reduce false positives. Training of gene-disease-inheritance mode-diplotype tetrads in 618,290 control and affected subjects identified 293 variants or haplotypes and seven genes with variable inheritance contributing higher positive diplotype counts than consistent with purifying hyperselection and with little or no evidence of SCGD causality. With these changes, 2.0% of UKB470K adults were positive. In contrast, gNBS was positive in 7.2% of 3,118 critically ill children with suspected SCGDs and 7.9% of 705 infant deaths. When compared with rapid diagnostic genome sequencing (RDGS), gNBS had 99.1% recall. In eight true-positive children, gNBS was projected to decrease time to diagnosis by a median of 121 days and avoid life-threatening disease presentations in four children, organ damage in six children, ∼$1.25 million in healthcare cost, and ten (1.4%) infant deaths. Federated training predicated on purifying hyperselection provides a general framework to attain high precision in population screening. Federated training across many biobanks and clinical trials can provide a privacy-preserving mechanism for qualification of gNBS in diverse genetic ancestries.

Use of pure recombinant human enzymes to assess the disease-causing potential of missense mutations in urea cycle disorders, applied to N-acetylglutamate synthase deficiency

N-acetylglutamate synthase (NAGS) makes acetylglutamate, the essential activator of the first, regulatory enzyme of the urea cycle, carbamoyl phosphate synthetase 1 (CPS1). NAGS deficiency (NAGSD) and CPS1 deficiency (CPS1D) present identical phenotypes. However, they must be distinguished, because NAGSD is cured by substitutive therapy with the N-acetyl-L-glutamate analogue N-carbamyl-L-glutamate, while curative therapy of CPS1D requires liver transplantation. Since their differentiation is done genetically, it is important to ascertain the disease-causing potential of CPS1 and NAGS genetic variants. With this goal, we previously carried out site-directed mutagenesis studies with pure recombinant human CPS1. We could not do the same with human NAGS (HuNAGS) because of enzyme instability, leading to our prior utilization of a bacterial NAGS as an imperfect surrogate of HuNAGS. We now use genuine HuNAGS, stabilized as a chimera of its conserved domain (cHuNAGS) with the maltose binding protein (MBP), and produced in Escherichia coli. MBP-cHuNAGS linker cleavage allowed assessment of the enzymatic properties and thermal stability of cHuNAGS, either wild-type or hosting each one of 23 nonsynonymous single-base changes found in NAGSD patients. For all but one change, disease causation was accounted by the enzymatic alterations identified, including, depending on the variant, loss of arginine activation, increased Km Glutamate, active site inactivation, decreased thermal stability, and protein misfolding. Our present approach outperforms experimental in vitro use of bacterial NAGS or in silico utilization of prediction servers (including AlphaMissense), illustrating with HuNAGS the value for UCDs of using recombinant enzymes for assessing disease-causation and molecular pathogenesis, and for therapeutic guidance.

Revisiting the Roles of Catalytic Residues in Human Ornithine Transcarbamylase

Human ornithine transcarbamylase (hOTC) is a mitochondrial transferase protein involved in the urea cycle and is crucial for the conversion of toxic ammonia to urea. Structural analysis coupled with kinetic studies of Escherichia coli, rat, bovine, and other transferase proteins has identified residues that play key roles in substrate recognition and conformational changes but has not provided direct evidence for all of the active residues involved in OTC function. Here, computational methods were used to predict the likely active residues of hOTC; the function of these residues was then probed with site-directed mutagenesis and biochemical characterization. This process identified previously reported active residues, as well as distal residues that contribute to activity. Mutation of active site residue D263 resulted in a substantial loss of activity without a decrease in protein stability, suggesting a key catalytic role for this residue. Mutation of predicted second-layer residues H302, K307, and E310 resulted in significant decreases in enzymatic activity relative to that of wild-type (WT) hOTC with respect to l-ornithine. The mutation of fourth-layer residue H107 to produce the hOTC H107N variant resulted in a 66-fold decrease in catalytic efficiency relative to that of WT hOTC with respect to carbamoyl phosphate and a substantial loss of thermal stability. Further investigation identified H107 and to a lesser extent E98Q as key residues involved in maintaining the hOTC quaternary structure. This work biochemically demonstrates the importance of D263 in hOTC catalytic activity and shows that residues remote from the active site also play key roles in activity.

Genetic aetiologies of acute liver failure

Acute liver failure (ALF) is a rare, rapidly evolving, clinical syndrome with devastating consequences where definitive treatment is by emergency liver transplantation. Establishing a diagnosis can be challenging and, historically, the cause of ALF was unidentified in up to half of children. However, recent technological and clinical advances in genomic medicine have led to an increasing proportion being diagnosed with monogenic aetiologies of ALF. The conditions encountered include a diverse group of inherited metabolic disorders each with prognostic and treatment implications. Often these disorders are clinically indistinguishable and may even mimic disorders of immune regulation or red cell disorders. Rapid genomic sequencing for children with ALF is, therefore, a key component in the diagnostic work up today. This review focuses on the monogenic aetiologies of ALF.

High-throughput assays to assess variant effects on disease

Interpreting the wealth of rare genetic variants discovered in population-scale sequencing efforts and deciphering their associations with human health and disease present a critical challenge due to the lack of sufficient clinical case reports. One promising avenue to overcome this problem is deep mutational scanning (DMS), a method of introducing and evaluating large-scale genetic variants in model cell lines. DMS allows unbiased investigation of variants, including those that are not found in clinical reports, thus improving rare disease diagnostics. Currently, the main obstacle limiting the full potential of DMS is the availability of functional assays that are specific to disease mechanisms. Thus, we explore high-throughput functional methodologies suitable to examine broad disease mechanisms. We specifically focus on methods that do not require robotics or automation but instead use well-designed molecular tools to transform biological mechanisms into easily detectable signals, such as cell survival rate, fluorescence or drug resistance. Here, we aim to bridge the gap between disease-relevant assays and their integration into the DMS framework.

Are asymptomatic carriers of OTC deficiency always asymptomatic? A multicentric retrospective study of risk using the UCDC longitudinal study database

BACKGROUND

Ornithine transcarbamylase deficiency (OTCD) due to an X-linked OTC mutation, is responsible for moderate to severe hyperammonemia (HA) with substantial morbidity and mortality. About 80% of females with OTCD remain apparently "asymptomatic" with limited studies of their clinical characteristics and long-term health vulnerabilities. Multimodal neuroimaging studies and executive function testing have shown that asymptomatic females exhibit limitations when stressed to perform at higher cognitive load and had reduced activation of the prefrontal cortex. This retrospective study aims to improve understanding of factors that might predict development of defined complications and serious illness in apparent asymptomatic females. A proband and her daughter are presented to highlight the utility of multimodal neuroimaging studies and to underscore that asymptomatic females with OTCD are not always asymptomatic.

METHODS

We review data from 302 heterozygote females with OTCD enrolled in the Urea Cycle Disorders Consortium (UCDC) longitudinal natural history database. We apply multiple neuroimaging modalities in the workup of a proband and her daughter.

RESULTS

Among the females in the database, 143 were noted as symptomatic at baseline (Sym). We focused on females who were asymptomatic (Asx, n = 111) and those who were asymptomatic initially upon enrollment in study but who later became symptomatic sometime during follow-up (Asx/Sym, n = 22). The majority of Asx (86%) and Asx/Sym (75%) subjects did not restrict protein at baseline, and ~38% of Asx and 33% of Asx/Sym subjects suffered from mild to severe neuropsychiatric conditions such as mood disorder and sleep problems. The risk of mild to severe HA sometime later in life for the Asx and Asx/Sym subjects as a combined group was ~4% (5/133), with ammonia ranging from 77 to 470 μM and at least half (2/4) of subjects requiring hospital admission and nitrogen scavenger therapy. For this combined group, the median age of first HA crisis was 50 years, whereas the median age of first symptom which included neuropsychiatric and/or behavioral symptoms was 17 years. The multimodal neuroimaging studies in female heterozygotes with OTCD also underscore that asymptomatic female heterozygotes with OTCD (e.g., proband) are not always asymptomatic.

CONCLUSIONS

Analysis of Asx and Asx/Sym females with OTCD in this study suggests that future evidence-based management guidelines and/or a clinical risk score calculator for this cohort could be useful management tools to reduce morbidity and improve long-term quality of life.

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.

Constructing and interpreting a large-scale variant effect map for an ultrarare disease gene: Comprehensive prediction of the functional impact of PSAT1 genotypes

Reduced activity of the enzymes encoded by PHGDH, PSAT1, and PSPH causes a set of ultrarare, autosomal recessive diseases known as serine biosynthesis defects. These diseases present in a broad phenotypic spectrum: at the severe end is Neu-Laxova syndrome, in the intermediate range are infantile serine biosynthesis defects with severe neurological manifestations and growth deficiency, and at the mild end is childhood disease with intellectual disability. However, L-serine supplementation, especially if started early, can ameliorate and in some cases even prevent symptoms. Therefore, knowledge of pathogenic variants can improve clinical outcomes. Here, we use a yeast-based assay to individually measure the functional impact of 1,914 SNV-accessible amino acid substitutions in PSAT. Results of our assay agree well with clinical interpretations and protein structure-function relationships, supporting the inclusion of our data as functional evidence as part of the ACMG variant interpretation guidelines. We use existing ClinVar variants, disease alleles reported in the literature and variants present as homozygotes in the primAD database to define assay ranges that could aid clinical variant interpretation for up to 98% of the tested variants. In addition to measuring the functional impact of individual variants in yeast haploid cells, we also assay pairwise combinations of PSAT1 alleles that recapitulate human genotypes, including compound heterozygotes, in yeast diploids. Results from our diploid assay successfully distinguish the genotypes of affected individuals from those of healthy carriers and agree well with disease severity. Finally, we present a linear model that uses individual allele measurements to predict the biallelic function of ~1.8 million allele combinations corresponding to potential human genotypes. Taken together, our work provides an example of how large-scale functional assays in model systems can be powerfully applied to the study of ultrarare diseases.

Diagnostic and Management Issues in Patients with Late-Onset Ornithine Transcarbamylase Deficiency

Ornithine transcarbamylase deficiency (OTCD) is the most common inherited disorder of the urea cycle and, in general, is transmitted as an X-linked recessive trait. Defects in the OTC gene cause an impairment in ureagenesis, resulting in hyperammonemia, which is a direct cause of brain damage and death. Patients with late-onset OTCD can develop symptoms from infancy to later childhood, adolescence or adulthood. Clinical manifestations of adults with OTCD vary in acuity. Clinical symptoms can be aggravated by metabolic stressors or the presence of a catabolic state, or due to increased demands upon the urea. A prompt diagnosis and relevant biochemical and genetic investigations allow the rapid introduction of the right treatment and prevent long-term complications and mortality. This narrative review outlines challenges in diagnosing and managing patients with late-onset OTCD.