Biology subjects

Smith, R. J. H.

Publications and source records attributed to Smith, R. J. H..

6 recordsLinked to original sources

bioRxiv2026

Monoclonal nephritic factors reveal insights into C3 convertase dynamics and dysregulation

C3- and C5-nephritic factors are potent but poorly understood autoantibodies that dysregulate complement convertases. To date, their underlying mechanisms of action, epitopes, and sequences remain unknown. To address this knowledge gap, we immune profiled B cells from a nephritic factor-positive C3 glomerulopathy patient and identified the first monoclonal C3- and C5-nephritic factors. We present the structure of a C3-nephritic factor bound to a C3 convertase with the convertase protease domain unexpectedly rotated and inhibited. This rotation advances our understanding of complement convertase progression and decay, explains disease-associated convertase variants, and reveals the molecular mechanism by which nephritic factors can either activate or inhibit convertase activity. We also detail heterogeneity within and between C3- and C5-nephritic factors in terms of convertase binding, stabilizing capacity, regulator inhibition, fluid-phase activation, and disease contribution. These findings improve stratification of patients with C3 glomerulopathy, redefine basic C3 convertase dynamics, and provide insights into antibody-mediated modulation of the complement system.

immunology↗

bioRxiv2026

The prevalence of protein misfolding as a mechanism for hereditary deafness

Hearing loss is the most common sensory deficit impacting [~]5% of the worlds population. The Deafness Variation Database (DVD) is a public resource of deafness variants, containing over 380,000 missense variants across 224 genes, with 303,577 classified as a variant of uncertain significance (VUS). To address the challenge of evaluating each deafness associated VUS, we evaluate a family of probabilistic frameworks to quantify the strength of computational evidence based on ACMG/AMP recommendations. First, CADD and REVEL are compared using Bayesian models parameterized using either a ClinVar 2019 dataset or labeled DVD variants. The REVEL model built using the DVD dataset demonstrates the best accuracy, sensitivity, and specificity. Incorporation of (in)tolerance to missense variation based on sorting each gene into three bins (tolerant, average, intolerant) shows that intolerant DVD genes are consistent with a higher prior probability of being pathogenic (25.7%) than average (10.7%) or tolerant (8.7%) genes. Finally, the impact of protein folding stability was incorporated using a 2D likelihood, which surpassed the simpler models while also offering a biophysical rationale for the disease mechanism. The protein folding-informed Bayesian model results in 28,866 prioritized VUSs reaching a posterior probability of pathogenicity above 98% with a false positive rate of only 0.14%. Overall, 54,752 missense variants are predicted to cause protein folding destabilization of greater than 1.0 kcal/mol, while 18,706 of the 28,886 prioritized VUS (65%) surpass this threshold. From these VUSs, we identify twelve probands where the patients genetic diagnosis is upgraded to likely pathogenic/pathogenic. We highlight two variants that cause clear structural disruption, demonstrating the impact of biophysical characterization on variant evaluation. Author SummaryWe investigate the impacts of single amino acid changes on protein structure and folding in the context of hearing loss. Hearing loss is the most common impairment of the main senses affecting nearly 5% of the worlds population. About 45% of people with hearing loss receive a diagnosis after targeted genetic testing. Here, we integrate biophysical data that quantifies the effect of a change to protein sequence on protein folding in combination with genetic data to improve our ability to identify protein amino acid changes that are likely to impact hearing. Our work leads to 12 patients receiving an upgraded diagnosis with their variant disrupting protein stability. Although the method is applied to hearing loss, it can be used for interpreting protein sequence changes in other disease contexts.

genetics↗

bioRxiv2024

A predominately pulmonary activation of complement in a mouse model of severe COVID-19

Evidence from in vitro studies and observational human disease data suggest the complement system plays a significant role in SARS-CoV-2 pathogenesis, although how complement dysregulation develops in patients with severe COVID-19 is unknown. Here, using a mouse-adapted SARS-CoV-2 virus (SARS2-N501YMA30) and a mouse model of severe COVID-19, we identify significant serologic and pulmonary complement activation following infection. We observed C3 activation in airway and alveolar epithelia, and in pulmonary vascular endothelia. Our evidence suggests that while the alternative pathway is the primary route of complement activation, components of both the alternative and classical pathways are produced locally by respiratory epithelial cells following infection, and increased in primary cultures of human airway epithelia in response to cytokine exposure. This locally generated complement response appears to precede and subsequently drive lung injury and inflammation. Results from this mouse model recapitulate findings in humans, which suggest sex-specific variance in complement activation, with predilection for increased C3 activity in males, a finding that may correlate with more severe disease. Our findings indicate that complement activation is a defining feature of severe COVID-19 in mice and lay the foundation for further investigation into the role of complement in COVID-19.

immunology↗

bioRxiv2021

Protein Structure Prediction Using a Maximum Likelihood Formulation of a Recurrent Geometric Network

Only [~]40% of the human proteome has structural coordinates available from experiment (i.e., X-ray crystallography, NMR spectroscopy, or cryo-EM) or homology modeling with quality templates (i.e., 30% sequence identity or greater), leaving most of the proteome structurally unsolved. Deep learning (DL) methods for predicting protein structure can help close knowledge gaps where experimental and homology models are difficult to obtain. Recent advances in these DL methods have shown promising results in expanding structural coverage to the scale of the entire human proteome, providing researchers with more complete protein structural information. Here, we improve upon an existing DL algorithm for protein structure prediction, the Recurrent Geometric Network (RGN). We first expand the training dataset to include experimental uncertainty data in the form of atomic displacement parameters, then derive a maximum likelihood loss function that incorporates this uncertainty data into model training. Compared to the original RGN, our novel maximum likelihood model improves the rate of convergence of initial model training and ultimately results in more accurate structure prediction according to the root mean square deviation (RMSD) of backbone atoms, the Global Distance Test (GDT), the Global Distance Test High Accuracy (GDT-HA), and the Template-Modeling Score (TM-Score). Our model also predicts structures with more favorable backbone torsions, which provide more accurate starting coordinates for downstream physics-based simulations. Based on these results, our maximum likelihood reformulation provides a framework for improving existing or future machine learning algorithms for protein structure prediction. The augmented dataset, data collection scripts, reformulated RGN source code, and a series of trained models are publicly available at https://github.com/SchniedersLab/likelihood-rgn.

biophysics↗

bioRxiv2020

Biallelic mutation of CLRN2 causes non-syndromic hearing loss in humans

Deafness, the most frequent sensory deficit in humans, is extremely heterogenous with hundreds of genes probably involved. Clinical and genetic analyses of an extended consanguineous family with pre-lingual, moderate-to-profound autosomal recessive sensorineural hearing loss, allowed us to identify CLRN2, encoding a tetraspan protein as a new deafness gene. Homozygosity mapping followed by exome sequencing identified a 15.2 Mb locus on chromosome 4p15.32p15.1 containing a missense pathogenic variant in CLRN2 (c.494C>A, NM_001079827.2) segregating with the disease. Using in vitro RNA splicing analysis, we show that the CLRN2 c.494C>A mutation leads to two events: 1) the substitution of a highly conserved threonine (uncharged amino acid) to lysine (charged amino acid) at position 165, p.(Thr165Lys), and 2) aberrant splicing, with the retention of intron 2 resulting in a stop codon after 26 additional amino acids, p.(Gly146Lysfs*26). Expression studies and phenotyping of newly produced zebrafish and mouse models deficient for clarin 2 further confirm that clarin 2, expressed in the inner ear hair cells, is essential for normal organization and maintenance of the auditory hair bundles, and for hearing function. Together, our findings identify CLRN2 as a new deafness gene, which will impact future diagnosis and treatment for deaf patients.

genetics↗

bioRxiv2020

Novel Loss-of-Function Mutations in COCH Cause Autosomal Recessive Nonsyndromic Deafness

COCH is the most abundantly expressed gene in the cochlea. Unsurprisingly, mutations in COCH underly deafness in mice and humans. Two forms of deafness are linked to mutations in COCH, the well-established autosomal dominant nonsyndromic hearing loss, with or without vestibular dysfunction (DFNA9) via a gain-of-function/dominant-negative mechanism, and more recently autosomal recessive nonsyndromic hearing loss (DFNB110) via nonsense variants. Using a combination of targeted gene panels, exome sequencing and functional studies, we identified four novel pathogenic variants (two nonsense variants, one missense and one inframe deletion) in COCH as the cause of autosomal recessive hearing loss in a multi-ethnic cohort. To investigate whether the non-truncating variants exert their effect via a loss-of-function mechanism, we used mini-gene splicing assays. Our data showed both the missense and inframe deletion variants altered RNA-splicing by creating an exon splicing silencer and abolishing an exon splicing enhancer, respectively. Both variants create frameshifts and are predicted to result in a null allele. This study confirms the involvement of loss-of-function mutations in COCH in autosomal recessive nonsyndromic hearing loss, expands the mutational landscape of DFNB110 to include coding variants that alter RNA-splicing, and highlights the need to investigate the effect of coding variants on RNA-splicing.

genetics↗