Connor Scott is a neuroscientist with over 9 years working in the biomedical field. He has extensive experience with human tissue, histology, molecular biology, and cellular biology. He specialises in bringing traditional histology into the modern era by developing workflows to bridge neuropathology with multiple ‘omic’ technologies using clinical, surgical, and post-mortem CNS material.
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D.Phil/PhD in Clinical Neurosciences, 2021
University of Oxford
BSc (Hons) in Biomedical Sciences, 2012
University of Greenwich
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Degeneration of the primary motor cortex is a defining feature of amyotrophic lateral sclerosis (ALS), which is associated with the accumulation of microscopic protein aggregates in neurons and glia. However, little is known about the quantitative burden and pattern of motor cortex proteinopathies across ALS genotypes. We combined quantitative digital image analysis with multi-level generalized linear modelling in an independent cohort of 82 ALS cases to explore the relationship between genotype, total proteinopathy load and cellular vulnerability to aggregate formation.
While nearly comprehensive proteome coverage can be achieved from bulk tissue or cultured cells, the data usually lacks spatial resolution. As a result, tissue based proteomics averages protein abundance across multiple cell types and/or localizations. With proteomics platforms lacking sensitivity and throughput to undertake deep single-cell proteome studies in order to resolve spatial or cell type dependent protein expression gradients within tissue, proteome analysis has been combined with sorting techniques to enrich for certain cell populations. However, the spatial resolution and context is lost after cell sorting. Here, we report an optimized method for the proteomic analysis of neurons isolated from post-mortem human brain by laser capture microdissection (LCM).