Dataset for: Chemical knockdown of Dnmt1 by 5-Azacitidine induced degradation

Dataset supports the thesis &#39;Proteomic analysis of Wntand epigenetic regulatory protein networks in colorectal cancer&#39; chapter &#39;Chemical knockdown of Dnmt1 by 5-Azacitidine induced degradation&#39;.</span

Dataset for: A novel inducible knockdown approach to investigate Dnmt1

Dataset supports the thesis &#39;Proteomic analysis of Wntand epigenetic regulatory protein networks in colorectal cancer&#39; chapter &#39;A novel inducible knockdown approach to investigate Dnmt1&#39;.</span

Dataset for: Proteomic analysis of Dnmt1 hypomorphic colorectal cancer cells reveals activation of markers of epithelial-mesenchymal transition and re-localization of Beta-Catenin

Dataset supports the thesis &#39;Proteomic analysis of Wntand epigenetic regulatory protein networks in colorectal cancer&#39; chapter &#39;Proteomic analysis of Dnmt1 hypomorphiccolorectal cancer cells reveals activation of markers of epithelial-mesenchymal transition and re-localization of Beta-Catenin&#39;.</span

Profiling the Human Phosphoproteome to Estimate the True Extent of Protein Phosphorylation

[Image: see text] Public phosphorylation databases such as PhosphoSitePlus (PSP) and PeptideAtlas (PA) compile results from published papers or openly available mass spectrometry (MS) data. However, there is no database-level control for false discovery of sites, likely leading to the overestimation of true phosphosites. By profiling the human phosphoproteome, we estimate the false discovery rate (FDR) of phosphosites and predict a more realistic count of true identifications. We rank sites into phosphorylation likelihood sets and analyze them in terms of conservation across 100 species, sequence properties, and functional annotations. We demonstrate significant differences between the sets and develop a method for independent phosphosite FDR estimation. Remarkably, we report estimated FDRs of 84, 98, and 82% within sets of phosphoserine (pSer), phosphothreonine (pThr), and phosphotyrosine (pTyr) sites, respectively, that are supported by only a single piece of identification evidence—the majority of sites in PSP. We estimate that around 62 000 Ser, 8000 Thr, and 12 000 Tyr phosphosites in the human proteome are likely to be true, which is lower than most published estimates. Furthermore, our analysis estimates that 86 000 Ser, 50 000 Thr, and 26 000 Tyr phosphosites are likely false-positive identifications, highlighting the significant potential of false-positive data to be present in phosphorylation databases

Proteomic characterization of GSK3β knockout shows altered cell adhesion and metabolic pathway utilisation in colorectal cancer cells

Glycogen-specific kinase (GSK3β) is an integral regulator of the Wnt signalling pathway as well as many other diverse signalling pathways and processes. Dys-regulation of GSK3β is implicated in many different pathologies, including neurodegenerative disorders as well as many different tumour types. In the context of tumour development, GSK3β has been shown to play both oncogenic and tumour suppressor roles, depending upon tissue, signalling environment or disease progression. Although multiple substrates of the GSK3β kinase have been identified, the wider protein networks within which GSK3β participates are not well known, and the consequences of these interactions not well understood. In this study, LC-MS/MS expression analysis was performed using knockout GSK3β colorectal cancer cells and isogenic controls in colorectal cancer cell lines carrying dominant stabilizing mutations of β-catenin. Consistent with the role of GSK3β, we found that β-catenin levels and canonical Wnt activity are unaffected by knockout of GSK3β and therefore used this knockout cell model to identify other processes in which GSK3β is implicated. Quantitative proteomic analysis revealed perturbation of proteins involved in cell-cell adhesion, and we characterized the phenotype and altered proteomic profiles associated with this. We also characterized the perturbation of metabolic pathways resulting from GSK3β knockout and identified defects in glycogen metabolism. In summary, using a precision colorectal cancer cell-line knockout model with constitutively activated β-catenin we identified several of the diverse pathways and processes associated with GSK3β function.</p

The Gene Ontology Knowledgebase in 2023

: The Gene Ontology (GO) knowledgebase (http://geneontology.org) is a comprehensive resource concerning the functions of genes and gene products (proteins and non-coding RNAs). GO annotations cover genes from organisms across the tree of life as well as viruses, though most gene function knowledge currently derives from experiments carried out in a relatively small number of model organisms. Here, we provide an updated overview of the GO knowledgebase, as well as the efforts of the broad, international consortium of scientists that develops, maintains and updates the GO knowledgebase. The GO knowledgebase consists of three components: 1) the Gene Ontology - a computational knowledge structure describing functional characteristics of genes; 2) GO annotations - evidence-supported statements asserting that a specific gene product has a particular functional characteristic; and 3) GO Causal Activity Models (GO-CAMs) - mechanistic models of molecular "pathways" (GO biological processes) created by linking multiple GO annotations using defined relations. Each of these components is continually expanded, revised and updated in response to newly published discoveries, and receives extensive QA checks, reviews and user feedback. For each of these components, we provide a description of the current contents, recent developments to keep the knowledgebase up to date with new discoveries, as well as guidance on how users can best make use of the data we provide. We conclude with future directions for the project