Various factors, including drugs as well as non-molecular influences, induce alterations in the stability of proteins in cell lysates, living cells and organisms. These alterations can be probed by applying a stability-modifying agent, such as elevated temperature, to a varying degree. As a second dimension of variation, drug concentration or factor intensity can be used. However, the corresponding analysis scheme has a low throughput and high cost. Additionally, since traditional data analysis employs curve fitting, proteins with unusual behavior are frequently ignored. The novel Proteome Integral Stability Alteration (PISA) assay avoids these issues altogether, increasing the analysis throughput by one to two orders of magnitude for unlimited number of parameter variation points. The consumption of the compound and biological material decreases by the same factor. We envision widespread use of the PISA approach in chemical biology and drug development..
Deconvolution of targets and action mechanisms of anticancer compounds is fundamental in drug development. Here, we report on ProTargetMiner as a publicly available expandable proteome signature library of anticancer molecules in cancer cell lines. Based on 287 A549 adenocarcinoma proteomes affected by 56 compounds, the main dataset contains 7,328 proteins and 1,307,859 refined protein-drug pairs. These proteomic signatures cluster by compound targets and action mechanisms. The targets and mechanistic proteins are deconvoluted by partial least square modeling, provided through the website http://protargetminer.genexplain.com. For 9 molecules representing the most diverse mechanisms and the common cancer cell lines MCF-7, RKO and A549, deep proteome datasets are obtained. Combining data from the three cell lines highlights common drug targets and cell-specific differences. The database can be easily extended and merged with new compound signatures. ProTargetMiner serves as a chemical proteomics resource for the cancer research community, and can become a valuable tool in drug discovery.
Despite the immense importance of enzyme–substrate reactions, there is a lack of general and unbiased tools for identifying and prioritizing substrate proteins that are modified by the enzyme on the structural level. Here we describe a high-throughput unbiased proteomics method called System-wide Identification and prioritization of Enzyme Substrates by Thermal Analysis (SIESTA). The approach assumes that the enzymatic post-translational modification of substrate proteins is likely to change their thermal stability. In our proof-of-concept studies, SIESTA successfully identifies several known and novel substrate candidates for selenoprotein thioredoxin reductase 1, protein kinase B (AKT1) and poly-(ADP-ribose) polymerase-10 systems. Wider application of SIESTA can enhance our understanding of the role of enzymes in homeostasis and disease, opening opportunities to investigate the effect of post-translational modifications on signal transduction and facilitate drug discovery.
Despite the immense importance of enzyme-substrate reactions, there is a lack of generic and unbiased tools for identifying and prioritizing substrate proteins which are modulated in the structural and functional levels through modification. Here we describe a high-throughput unbiased proteomic method called System-wide Identification and prioritization of Enzyme Substrates by Thermal Analysis (SIESTA). The approach assumes that enzymatic posttranslational modification of substrate proteins might change their thermal stability. SIESTA successfully identifies several known and novel substrate candidates for selenoprotein thioredoxin reductase 1, protein kinase B (AKT1) and poly-(ADP-ribose) polymerase-10 systems in up to a depth of 7179 proteins. Wider application of SIESTA can enhance our understanding of the role of enzymes in homeostasis and disease, open new opportunities in investigating the effect of PTMs on signal transduction, and facilitate drug discovery.
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Chemotherapeutics cause the detachment and death of adherent cancer cells. When studying the proteome changes to determine the protein target and mechanism of action of anticancer drugs, the still-attached cells are normally used, whereas the detached cells are usually ignored. To test the hypothesis that proteomes of detached cells contain valuable information, we separately analyzed the proteomes of detached and attached HCT-116, A375, and RKO cells treated for 48 h with 5-fluorouracil, methotrexate and paclitaxel. Individually, the proteomic data on attached and detached cells had comparable performance in target and drug mechanism deconvolution, whereas the combined data significantly improved the target ranking for paclitaxel. Comparative analysis of attached versus detached proteomes provided further insight into cell life and death decision making. Six proteins consistently up- or downregulated in the detached versus attached cells regardless of the drug and cell type were discovered; their role in cell death/survival was tested by silencing them with siRNA. Knocking down USP11, CTTN, ACAA2, and EIF4H had anti-proliferative effects, affecting UHRF1 additionally sensitized the cells to the anticancer drugs, while knocking down RNF-40 increased cell survival against the treatments. Therefore, adding detached cells to the expression proteomics analysis of drug-treated cells can significantly increase the analytical value of the approach. The data have been deposited to the ProteomeXchange with identifier PXD007686.
Detailed characterization of cell type transitions is essential for cell biology in general and particularly for the development of stem cell-based therapies in regenerative medicine. To systematically study such transitions, we introduce a method that simultaneously measures protein expression and thermal stability changes in cells and provide the web-based visualization tool ProteoTracker. We apply our method to study differences between human pluripotent stem cells and several cell types including their parental cell line and differentiated progeny. We detect alterations of protein properties in numerous cellular pathways and components including ribosome biogenesis and demonstrate that modulation of ribosome maturation through SBDS protein can be helpful for manipulating cell stemness in vitro. Using our integrative proteomics approach and the web-based tool, we uncover a molecular basis for the uncoupling of robust transcription from parsimonious translation in stem cells and propose a method for maintaining pluripotency in vitro.
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