Biology subjects

Gaetani, M.

Publications and source records attributed to Gaetani, M..

21 records · Page 2Linked to original sources

bioRxiv2022

Mapping the GALNT1 substrate landscape with versatile proteomics tools

O-GalNAc type glycosylation is a common post-translational modification (PTM) of proteins catalyzed by polypeptide GalNAc transferases, but the substrate specificity of these transferases is poorly understood. Here we develop a strategy based on integral thermal proteome solubility profiling to identify and prioritize the protein substrates of polypeptide N-acetylgalactosaminyltransferase 1 (GALNT1). Combined with glycoprotein enrichment followed by HCD and soft EThcD gas-phase fragmentation technique, we uncover hundreds of novel GALNT1 substrates in two model human cell lines. GALNT1-mediated O-glycosylation is more common on Thr than Ser residues, with a strong preference for Pro at positions +3 and +4 in respect to O-glycosylation. These results implicate GALNT1 in potentially regulating proteins in several diverse pathways, including some unexpected processes, such as TCA cycle and DNA transcription. This study depicts a roadmap for identification of functional substrates for glycosyltransferases, facilitating fundamental insight into the role of glycosylation in homeostasis and disease.

biochemistry↗

bioRxiv2018

Proteome Integral Stability Alteration assay dramatically increases throughput and sensitivity in profiling factor-induced proteome changes

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.

cancer biology↗

bioRxiv2018

ProTargetMiner: A proteome signature library of anticancer molecules for functional discovery

We present a publicly available, expandable proteome signature library of anticancer molecules in A549 adenocarcinoma cells. Based on 287 proteomes affected by 56 drugs, the main dataset contains 7,328 proteins and 1,307,859 refined protein-drug pairs. By employing the specificity concept in partial least square modeling, deconvolution of drug targets and mechanistic proteins is achieved for most compounds, including some kinase inhibitors. We built the first protein co-regulation database that takes into account both protein expression and degradation. A surprising number of strong anti-correlations is found, underscoring the importance of protein repression in cell regulation. Our analysis uncovered a group of proteins with extremely steady expression which are likely essential for core cellular functions. These findings bring about deeper understanding of cell mechanics. Extension of the dataset to novel compounds will facilitate drug design. The introduced specificity concept and modeling scheme are beneficial in other analysis types as well.\n\nStatement of SignificanceProTargetMiner is the first of its kind library of proteome responses of human cancer cells to anticancer molecules. This expandable resource facilitates the deconvolution of drug targets, action mechanisms, and cellular effects. It reveals death modalities, uncovers protein co-regulation and anti-correlation networks and defines the \"untouchable\" proteome essential for core cellular functionalities.

cell biology↗