Biology subjects

Beales, P. L.

Publications and source records attributed to Beales, P. L..

5 recordsLinked to original sources

bioRxiv2023

De-suppression of mesenchymal cell identities and variable phenotypic outcomes associated with knockout of Bbs1.

Bardet-Biedl syndrome (BBS) is an archetypal ciliopathy caused by dysfunction of primary cilia. BBS affects multiple tissues, including the kidney, eye and hypothalamic satiety response. Understanding pan-tissue mechanisms of pathogenesis versus those which are tissue specific, and gauging their associated inter-individual variation owing to genetic background and stochastic processes, is of paramount importance in syndromology. The BBSome is a membrane trafficking and intraflagellar transport (IFT) adaptor protein complex formed by 8 BBS proteins, including BBS1, which is the most commonly mutated gene in BBS. To investigate disease pathogenesis we generated a series of clonal renal collecting duct IMCD3 cell lines carrying defined biallelic nonsense or frameshift mutations in Bbs1, as well as a panel of matching wild-type CRISPR control clones. Using a phenotypic screen and an unbiased multi-omics approach we note significant clonal variability for all assays, emphasising the importance of analysing panels of genetically-defined clones. Our results suggest that BBS1 is required for suppression of mesenchymal cell identities as IMCD3 cell passage number increases. This was associated with a failure to express epithelial cell markers and tight junction formation, which was variable amongst clones. Transcriptomic analysis of hypothalamic preparations from BBS mutant mice, and BBS patient fibroblasts, suggested that dysregulation of epithelial-to-mesenchymal transition (EMT) genes is a general predisposing feature of BBS across tissues. Collectively this work suggests that the dynamic stability of the BBSome is essential for suppression of mesenchymal cell identities as epithelial cells differentiate.

genetics↗

bioRxiv2021

MOPower: an R-shiny application for the simulation and power calculation of multi-omics studies.

BackgroundMulti-omics studies are increasingly used to help understand the underlying mechanisms of clinical phenotypes, integrating information from the genome, transcriptome, epigenome, metabolome, proteome and microbiome. This integration of data is of particular use in rare disease studies where the sample sizes are often relatively small. Methods development for multi-omics studies is in its early stages due to the complexity of the different individual data types. There is a need for software to perform data simulation and power calculation for multi-omics studies to test these different methodologies and help calculate sample size before the initiation of a study. This software, in turn, will optimise the success of a study. ResultsThe interactive R shiny application MOPower described below simulates data based on three different omics using statistical distributions. It calculates the power to detect an association with the phenotype through analysis of n number of replicates using a variety of the latest multi-omics analysis models and packages. The simulation study confirms the efficiency of the software when handling thousands of simulations over ten different sample sizes. The average time elapsed for a power calculation run between integration models was approximately 500 seconds. Additionally, for the given study design model, power varied with the increase in the number of features affecting each method differently. For example, using MOFA had an increase in power to detect an association when the study sample size equally matched the number of features. ConclusionsMOPower addresses the need for flexible and user-friendly software that undertakes power calculations for multi-omics studies. MOPower offers users a wide variety of integration methods to test and full customisation of omics features to cover a range of study designs.

bioinformatics↗

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↗

bioRxiv2020

Altered hematopoietic system and self-tolerance in Bardet-Biedl Syndrome

Bardet-Biedl Syndrome (BBS) is a pleiotropic genetic disease caused by dysfunction of primary cilia. The immune system of patients with BBS or another ciliopathy has not been investigated, most likely because hematopoietic cells do not form cilia. However, there are multiple indications that the impairment of the processes typically associated with cilia might influence the hematopoietic compartment and immunity. In this study, we analyzed clinical data of BBS patients as well as a corresponding mouse model of BBS4 deficiency. We uncovered that BBS patients have higher incidence of certain autoimmune diseases. BBS patients and animal models have elevated white blood cell levels and altered red blood cell and platelet compartments. Moreover, we observed that BBS4 deficiency alters the development and homeostasis of B cells in mice. Some of the hematopoietic system alterations were caused by the BBS-induced obesity. Overall, our study reveals a connection between a ciliopathy and the alterations of the immune system and the hematopoietic compartment.

genetics↗

bioRxiv2017

CiliaCarta: An Integrated And Validated Compendium Of Ciliary Genes

The cilium is an essential organelle at the surface of most mammalian cells whose dysfunction causes a wide range of genetic diseases collectively called ciliopathies. The current rate at which new ciliopathy genes are identified suggests that many ciliary components remain undiscovered. We generated and rigorously analyzed genomic, proteomic, transcriptomic and evolutionary data and systematically integrated these using Bayesian statistics into a predictive score for ciliary function. This resulted in 285 candidate ciliary genes. We found experimental evidence of ciliary associations for 24 out of 36 analyzed candidate proteins. In addition, we show that OSCP1, which has previously been implicated in two distinct non-ciliary functions, causes a cilium dysfunction phenotype when depleted in zebrafish. The candidate list forms the basis of CiliaCarta, a comprehensive ciliary compendium covering 836 genes. The resource can be used to objectively prioritize candidate genes in whole exome or genome sequencing of ciliopathy patients and can be accessed at http://bioinformatics.bio.uu.nl/john/syscilia/ciliacarta/.

bioinformatics↗