Biology subjects

Webb, K.

Publications and source records attributed to Webb, K..

4 recordsLinked to original sources

bioRxiv2024

Structural Mapping of Polyclonal IgG Responses to HA After Influenza Virus Vaccination or Infection

Cellular and molecular characterization of immune responses elicited by influenza virus infection and seasonal vaccination have informed efforts to improve vaccine efficacy, breadth, and longevity. Here, we use negative stain electron microscopy polyclonal epitope mapping (nsEMPEM) to structurally characterize the humoral IgG antibody responses to hemagglutinin (HA) from human patients vaccinated with a seasonal quadrivalent flu vaccine or infected with influenza A viruses. Our data show that both vaccinated and infected patients had humoral IgGs targeting highly conserved regions on both H1 and H3 subtype HAs, including the stem and anchor, which are targets for universal influenza vaccine design. Responses against H1 predominantly targeted the central stem epitope in infected patients and vaccinated donors, whereas head epitopes were more prominently targeted on H3. Responses against H3 were less abundant, but a greater diversity of H3 epitopes were targeted relative to H1. While our analysis is limited by sample size, on average, vaccinated donors responded to a greater diversity of epitopes on both H1 and H3 than infected patients. These data establish a baseline for assessing polyclonal antibody responses in vaccination and infection, providing context for future vaccine trials and emphasizing the importance of carefully designing vaccines to boost protective responses towards conserved epitopes.

immunology↗

bioRxiv2019

Functional and in-silico interrogation of rare genomic variants impacting RNA splicing for the diagnosis of genomic disorders

PurposeTo develop a comprehensive analysis framework to identify pre-messenger RNA splicing mutations in the context of rare disease.\n\nMethodsWe assessed variants of uncertain significance through six in-silico prioritization strategies. Firstly, through comparison to functional analyses, we determined the precise effect on splicing of variants identified through clinical multi-disciplinary meetings. Next, we calculated the sensitivity of in-silico prioritization strategies to distinguish known splicing mutations from common variation (>2% in allele frequency in gnomAD) within relevant disease genes. These approaches defined an accurate in-silico strategy for variant prioritization, which we retrospectively applied to a large cohort of 2783 individuals who had previously received genomic testing for rare genomic disorders. We assessed the clinical impact of such prioritization strategies alongside routine diagnostic testing strategies.\n\nResultsWe identified 21 variants that potentially impacted splicing, and used cell based splicing assays to identify those variants which disrupted normal splicing. These findings underpinned new molecular diagnoses for 14 individuals. This process established that the use of pre-defined thresholds from a machine learning splice prediction algorithm, SpliceAI, was the most efficient method for variant prioritization, with a positive predictive value of 86%. We analysed 1,346,744 variants identified through diagnostic testing for 2783 individuals and observed that splicing variant prioritization strategies would improve clarity in clinical analysis for 15% of the individuals surveyed. Prioritized variants could provide new molecular diagnoses or provide additional support for molecular diagnosis for up to 81 individuals within our cohort.\n\nConclusionWe present an in-silico and functional analysis framework for the assessment of variants impacting pre-messenger RNA splicing which is applicable across monogenic disorders. Incorporation of these strategies improves clarity in diagnostic reporting, increases diagnostic yield and, with the advent of targeted treatment strategies, can directly alter patient clinical management.\n\nKey HighlightsO_LIWe establish an in-silico and functional analysis framework for the incorporation of splice variant assessment into diagnostic testing that is applicable across monogenic disorders.\nC_LIO_LIAfter assessment of six distinct variant prioritization strategies, we concluded that SpliceAI was the best method to accurately identify genomic variation disrupting normal pre-mRNA splicing. We determined this through (i) functional assessment of novel variants of uncertain significance described in this study, and (ii) calculation of sensitivity and specificity for prioritization strategies to distinguish known splicing mutations from common variants in the general population.\nC_LIO_LIWe describe novel disease-causing variants with support from cell based functional assays which underpin autosomal recessive, autosomal dominant and X-linked Mendelian disorders. This includes variants which are deeply intronic, within the nearby splice region of canonical splice sites and variants which activate cryptic splice sites within the protein-coding regions of genes.\nC_LIO_LIWe integrated the best performing variant prioritization strategy alongside clinical diagnostic testing for 2783 individuals referred to a well-established targeted gene panel test available through the UK National Health Service. We show that integration of such strategies will increase accuracy and clarity of diagnostic reporting, including the identification of variants which could provide new diagnoses and new carrier findings for referred individuals.\nC_LIO_LIFunctional assessment is essential for accurate clinical assessment of variants disrupting pre-mRNA splicing. We show through cell based functional assessments that variants impacting splicing may have complex impacts on pre-mRNA splicing, which may cause multiple interpretable consequences according to ACMG guidelines.\nC_LI

genomics↗

bioRxiv2018

Whole genome sequencing enables definitive diagnosis of Cystic Fibrosis and Primary Ciliary Dyskinesia

Understanding the genomic basis of inherited respiratory disorders can assist in the clinical management of individuals with these rare disorders. We apply whole genome sequencing for the discovery of disease-causing variants in the non-coding regions of known disease genes for two individuals with inherited respiratory disorders. We describe analysis strategies to pinpoint candidate non-coding variants within the non-coding genome and demonstrate aberrant RNA splicing as a result of deep intronic variants in DNAH11 and CFTR. These findings confirm clinical diagnoses of primary ciliary dyskinesia and cystic fibrosis, respectively.

genomics↗

bioRxiv2017

Decoys reveal the genetic and biochemical roles of redundant plant E3 ubiquitin ligases

The ubiquitin proteasome system (UPS) is the main cellular route for protein degradation in plants and is important for a wide range of biological processes including daily and seasonal timing. The UPS relies on the action of E3 ubiquitin ligases to specifically recognize substrate proteins and facilitate their ubiquitylation. In plants, there are three major challenges that inhibit studies of E3 ligase function: 1) rampant genetic redundancy, 2) labile interactions between an E3 ligase and its cognate substrates, and 3) a lack of tools for rapid validation of bona fide substrates. To overcome these 3 challenges, we have developed a decoy method that allows for rapid genetic analysis of E3 ligases, in vivo identification of substrates using immunoprecipitation followed by mass spectrometry, and reconstitution of the ubiquitylation reaction in mammalian cells to rapidly validate potential substrates. We employ the strategy to study the plant F-box proteins, ZTL, LKP2, and FKF1 revealing differential genetic impacts on circadian clock period and seasonal flowering. We identify a group of circadian clock transcriptional regulators that interact with ZTL, LKP2, and FKF1 in vivo providing a host of potential substrates that have not been seen previously. We then validate one substrate of ZTL, the plant circadian clock transcription factor CHE, and show that ZTL mediates CHE ubiquitylation and that the levels of the CHE protein cycle in daily timecourses. This work further untangles the complicated genetic roles of this family of E3 ligases and suggests that ZTL is a master regulator of a diverse set of critical clock transcription factors. Furthermore, the method that is validated here can be tool employed widely to overcome traditional challenges in studying redundant plant E3 ubiquitin ligases.

plant biology↗