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Fell, C. W.

Publications and source records attributed to Fell, C. W..

2 recordsLinked to original sources

FIBCD1 is a Conserved Receptor for Chondroitin Sulphate Proteoglycans of the Brain Extracellular Matrix and a Candidate Gene for a Complex Neurodevelopmental Disorder

The brain extracellular matrix (ECM) is enriched in chondroitin sulphate proteoglycans (CSPGs) with variable sulphate modifications that intimately participate in brain maturation and function. Very little is known about how the changing biophysical properties of the CSPGs are signalled to neurons. Here, we report Fibrinogen C Domain Containing 1 (FIBCD1), a known chitin-binding receptor of the innate immune system, to be highly expressed in the hippocampus and to specifically bind CSPGs containing 4-O sulphate modification (CS-4S). Cultured Fibcd1 knockout (KO) neurons lack phenotypic and transcriptomic responses to CSPG stimulation. Further, Fibcd1 KO mice exhibit accumulation of CS-4S, likely resulting in deficits of hippocampal-dependent learning tasks and abrogated synaptic remodelling, a phenotype rescued by enzymatic digestion of CSPGs. Likewise, neuronal specific knockdown of a Fibcd1 orthologue in flies results in neuronal morphological changes at the neuromuscular junctions and behavioural defects. Finally, we report two undiagnosed patients with a complex neurodevelopmental disorder with deleterious variants in FIBCD1, strongly implicating FIBCD1 in the development of the disease. Taken together, our results demonstrate that FIBCD1 is a novel, evolutionarily conserved component of ECM sulphation recognition that is crucial for neuronal development and function.

neuroscience↗

BioProfiling.jl: Profiling biological perturbations with high-content imaging in single cells and heterogeneous populations

MotivationHigh-content imaging screens provide a cost-effective and scalable way to assess cell states across diverse experimental conditions. The analysis of the acquired microscopy images involves assembling and curating morphological measurements of individual cells into morphological profiles suitable for testing biological hypotheses. Despite being a critical step, there is currently no standard approach to morphological profiling and no solution is available for the high-performance Julia programming language. ResultsHere, we introduce BioProfiling.jl, an efficient end-to-end solution for compiling and filtering informative morphological profiles in Julia. The package contains all the necessary data structures to curate morphological measurements and helper functions to transform, normalize and visualize profiles. Robust statistical distances and permutation tests enable quantification of the significance of the observed changes despite the high fraction of outliers inherent to high-content screens. This package also simplifies visual artifact diagnostics, thus streamlining a bottleneck of morphological analyses. We showcase the features of the package by analyzing a chemical imaging screen, in which the morphological profiles prove to be informative about the compounds mechanisms of action and can be conveniently integrated with the network localization of molecular targets. AvailabilityThe Julia package is available on GitHub: https://github.com/menchelab/BioProfiling.jl We also provide Jupyter notebooks reproducing our analyses: https://github.com/menchelab/BioProfilingNotebooks Contactjoerg.menche@univie.ac.at

bioinformatics↗