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Begar, E.

Publications and source records attributed to Begar, E..

2 recordsLinked to original sources

Centriolar satellites are dynamic membrane-less organelles that assemble via a hierarchical pathway

Centriolar satellites (CS) are ubiquitous, membrane-less organelles recognized for organelle crosstalk, plasticity, diverse functions and links to developmental and neuronal diseases. However, the molecular principles governing their assembly and regulation remain poorly understood. To address this, we developed cellular and in vitro biogenesis assays that allow spatiotemporal quantification of CS granule properties during assembly, remodeling and maintenance. Using these tools, we show that CS assemble via a hierarchical pathway initiated by PCM1 scaffold formation followed by regulated client recruitment. PCM1 intrinsically assembles into granules through multimerization, a process modulated by cytoskeleton. High-resolution imaging revealed that PCM1 and its clients occupy distinct subdomains with different compositions and dynamics, adding an additional layer of regulation. Perturbing PCM1 multimerization impaired ciliary signaling, underscoring its functional importance. Collectively, these findings define the molecular basis of CS biogenesis, establish new tools to probe their context-dependent functions, and provide a framework for understanding how CS deregulation contributes to disease. More broadly, the principles uncovered here may extend to other membrane-less organelles, explaining their specificity and plasticity.

cell biology↗

CilioGenics: an integrated method and database for predicting novel ciliary genes

Discovering the entire list of human ciliary genes would help in the diagnosis of cilia-related human disorders known as ciliopathy, but at present the genetic diagnosis of many ciliopathies (over 30%) is far from complete (Bachmann-Gagescu et al., 2015; Knopp et al., 2015; Paff et al., 2018). In a theory, many independent approaches may uncover the whole list of ciliary genes, but 30% of the genes on the ciliary gene list are still ciliary candidate genes (van Dam et al., 2019; Vasquez et al., 2021). All of these cutting-edge techniques, however, have relied on a different single strategy to discover ciliary candidate genes. Because different methodologies demonstrated distinct capabilities with varying quality, categorizing the ciliary candidate genes in the ciliary gene list without further evidence has been difficult. Here, we present a method for predicting ciliary capacity of each human gene that incorporates diverse methodologies (single-cell RNA sequencing, protein-protein interactions (PPIs), comparative genomics, transcription factor (TF)-network analysis, and text mining). By integrating multiple approaches, we reveal previously undiscovered ciliary genes. Our method, CilioGenics, outperforms other approaches that are dependent on a single method. Our top 500 gene list contains 256 new candidate ciliary genes, with 31 experimentally validated. Our work suggests that combining several techniques can give useful evidence for predicting the ciliary capability of all human genes.

bioinformatics↗