Biology subjects

Hirst, R. A.

Publications and source records attributed to Hirst, R. A..

5 recordsLinked to original sources

bioRxiv2025

WS6 enables scalable ex vivo expansion and gene editing of epithelial basal stem cells

Modeling human epithelial diseases and developing cell-based therapies require robust methods to expand and manipulate epithelial stem and progenitor cells in vitro. Basal stem/progenitor cells from stratified epithelia can be expanded in 3T3-J2 fibroblast feeder cell co-culture systems, and the addition of the ROCK inhibitor Y-27632 enhances proliferation and culture longevity, a phenomenon described as conditional reprogramming. Here, we present a method incorporating the small molecule WS6 to further improve the proliferation and lifespan of cultured epithelial cells from multiple tissues, including airway, skin, and thymus. Cells maintained in this medium ( EpMED; FAD+Y+WS6) retain basal stem/progenitor cell identity and function, including the capacity to differentiate. We demonstrate their capacity to engraft in vivo in a tracheal transplantation model. In a second application, we generate clonal CRISPR-Cas9 genome edited nasal cultures, introducing targeted knockouts of DNAH5 or DNAI2 to create primary ciliary dyskinesia disease models. We anticipate that our method will have broad applications in epithelial cell biology, disease modeling, and regenerative medicine, while reducing reliance on immortalized or cancer cell lines and animal experimentation.

cell biology↗

bioRxiv2023

Single cell-guided prenatal derivation of primary epithelial organoids from the human amniotic and tracheal fluids.

Despite advances in prenatal diagnosis, it is still difficult to predict severity and outcomes of many congenital malformations. New patient-specific prenatal disease modelling may optimise personalised prediction. We and others have described the presence of mesenchymal stem cells in amniotic fluid (AFSC) that can generate induced pluripotent stem cells (iPSCs). The lengthy reprogramming processes, however, limits the ability to define individual phenotypes or plan prenatal treatment. Therefore, it would be advantageous if fetal stem cells could be obtained during pregnancy and expanded without reprogramming. Using single cell analysis, we characterised the cellular identities in amniotic fluid (AF) and identified viable epithelial stem/progenitor cells of fetal intestinal, renal and pulmonary origin. With relevance for prenatal disease modelling, these cells could be cultured to form clonal epithelial organoids manifesting small intestine, kidney and lung identity. To confirm this, we derived lung organoids from AF and tracheal fluid (TF) cells of Congenital Diaphragmatic Hernia (CDH) fetuses and found that they show differences to non-CDH controls and can recapitulate some pathological features of the disease. Amniotic Fluid Organoids (AFO) allow investigation of fetal epithelial tissues at clinically relevant developmental stages and may enable the development of therapeutic tools tailored to the fetus, as well as to predicting the effects of such therapies.

cell biology↗

bioRxiv2020

High-content screening for rare respiratory diseases: readthrough therapy in primary ciliary dyskinesia

Development of therapeutic approaches for rare respiratory diseases is hampered by the lack of systems that allow medium-to-high-throughput screening of fully differentiated respiratory epithelium from affected patients. This is a particular problem for primary ciliary dyskinesia (PCD), a rare genetic disease caused by mutations in genes that adversely affect ciliary movement and consequently mucociliary transport. Primary cell culture of basal epithelial cells from nasal brush biopsies, followed by ciliated differentiation at air-liquid interface (ALI) has proven to be a useful tool in PCD diagnostics but the techniques broader utility, including in pre-clinical PCD research, has been limited by the number of basal cells that it is possible to expand from such biopsies. Here, we describe a high-content, imaging-based screening method, enabled by extensive expansion of PCD patient basal cells and their culture into differentiated human respiratory epithelium in miniaturised 96-well transwell format ALI cultures. Analyses of ciliary beat pattern, beat frequency and ultrastructure indicate that a range of different PCD defects are retained in these cultures. We perform a proof-of-principle personalized investigation in reduced generation of motile cilia (RGMC), a rare and very severe form of PCD, in this case caused by a homozygous nonsense mutation (c.441C>A; p.Cys147*) in the MCIDAS gene. The screening system allowed multiple drugs inducing translational readthrough to be evaluated alone or in combination with inhibitors of nonsense-mediated decay. Restoration of basal body formation in the patients nasal epithelial cells was seen in vitro, suggesting a novel avenue for drug evaluation and development in PCD. SummaryWe describe primary cell culture of nasal epithelial cells from patients with primary ciliary dyskinesia including differentiatiation of these to a ciliary phenotype and high-content screening in miniaturised air-liquid interface cultures.

cell biology↗

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↗