title: Application of high content biology to yield quantitative spatial proteomic information on protein acetylations.
abstract: High content analysis (HCA; also referred to as high content biology) is a quantitative, automated, medium-throughput microscopy approach whereby cell images are segmented into relevant compartments (nuclei, cytoplasm) and the staining in each compartment quantified by computer algorithms. The extraction of quantitative information from the cell image generates a wealth of data which contributes significantly to the acceleration of drug discovery and biological research. Here we have adapted HCA to analyze protein acetylations in the cytoskeleton. This approach yields associative information on the link between acetylation and cytoskeletal organization. The protocol also describes optimization steps for cytoskeletal analysis and its application across different cell types, and HCA platforms. The methods described herein are readily adaptable to non-cytoskeletal acetylations and have been applied to the analysis of transcription factors.
authors: Molecular Gastroenterology Research Group, Department of Oncology, University of Sheffield, Sheffield, UK.
authors: Bernard M
authors: BM
authors: Corfe
authors: Josephine
authors: J
authors: Kilner
authors: Joanna
authors: J
authors: Chowdry
authors: Roderick S P
authors: RS
authors: Benson
authors: Gareth J
authors: GJ
authors: Griffiths
authors: Caroline A
authors: CA
authors: Evans
mesh_terms: D000107:Acetylation; D000465:Algorithms; D018938:Caco-2 Cells; D045744:Cell Line, Tumor; D019295:Computational Biology / Q000379:methods*; D003599:Cytoskeleton / Q000378:metabolism* / Q000648:ultrastructure; D004797:Enzyme-Linked Immunosorbent Assay / Q000379:methods; D005434:Flow Cytometry; D045325:HCT116 Cells; D019073:HT29 Cells; D006801:Humans; D007091:Image Processing, Computer-Assisted / Q000379:methods*; D061986:MCF-7 Cells; D008853:Microscopy; D011506:Proteins / Q000032:analysis* / Q000378:metabolism
chemical_list: D011506:Proteins