Here we apply a sensitive, spatially resolved workflow for the proteomic analysis of a tumour to identify proteins that display spatial expression patterns within the tissue in an unsupervised manner. Abstract and Poster - ASMS Conference on Mass Spectrometry and Allied Topics, May 31st - June 4th 2020.
Linking tissue microstructure with diffusion MRI signals throughout the brain Abstract and Poster - Whistler Scientific Workshop on Brain Functional Organization, Connectivity, and Behavior, March 1st - March 4th 2020.
Presented at 121st Meeting of the British Neuropathological Society, Developmental Neuropathology Symposium, 4th – 6th March 2020. Published Poster - Journal of Neuropathology and Applied Neurobiology.
The detection of specific TDP-43 peptides able to quantify the pathological fragments of TDP-43 in post mortem ALS brain tissue, offers the opportunity to develop an in vivo assay to measure pathological TDP-43. This would have major diagnostic, stratification and pharmacodynamic biomarker potential. The finding of CTF in cases labelled as AD may reflect the recent identification of a sub-group labelled Limbic-predominant Agerelated TDP-43 Encephalopathy. Published Abstract (Journal of Amyotrophic Lateral Sclerosis and Frontotemporal Degeneration, volume 20, S1, November 2019) and Poster - 30th International Symposium on ALS/MND, December 4th - 6th, 2019.
Diffusion MRI (dMRI) has great potential for studying the complexity of white matter fibre architecture non-invasively. However, because dMRI is an indirect measure of this microstructure, we require validation datasets for two main purposes. (i) to relate dMRI to microscopy data that directly measures the microstructure of interest; and (ii) to relate high-quality dMRI data to more conventional data quality. We present the NAMETBC dataset which addresses both of these goals. Article and Poster - International Society for Magnetic Resonance in Medicine (ISMRM) 27th Annual Meeting & Exhibition, May 11th - 16th, 2019.
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).
Here we describe a method to increase proteomic throughput by 10-times. The 10x increase in throughput increases possibilities for investigation into the spatial distribution of proteins throughout a tissue. We will next apply this methodology in order to determine spatial proteomic profiles of distinct histological features within a brain tumour. Abstract and Poster - 18th Human Proteome Organisation World Congress (HUPO2019), Australia, September 15th - 19th 2019.