We generated a comprehensive picture of protease substrates in anti-Fas-treated apoptotic human Jurkat T lymphocytes. We used combined fractional diagonal chromatography (COFRADIC) sorting of protein amino-terminal peptides coupled to oxygen-16 or oxygen-18 differential labeling. We identified protease substrates and located the exact cleavage sites within processed proteins. Our analysis yielded 1,834 protein identifications and located 93 cleavage sites in 71 proteins. Indirect evidence of apoptosis-specific cleavage within 21 additional proteins increased the total number of processed proteins to 92. Most cleavages were at caspase consensus sites; however, other cleavage specificities suggest activation of other proteases. We validated several new processing events by immunodetection and by an in vitro assay using recombinant caspases and synthetic peptides containing presumed cleavage sites. The spliceosome complex appeared a preferred target, as 14 of its members were processed. Differential isotopic labeling further revealed specific release of nucleosomal components from apoptotic nuclei.

Proximity labeling is a powerful approach for detecting protein-protein interactions. Most proximity labeling techniques use a promiscuous biotin ligase (PBL) or a peroxidase fused to a protein of interest, enabling the covalent biotin labelling of proteins and subsequent capture and identification of interacting and neighbouring proteins without the need for the protein complex to remain intact. To date, only few papers report on the use of proximity labeling in plants. Here, we present the results of a systematic study applying a variety of biotin-based proximity labeling approaches in several plant systems using various conditions and bait proteins. We show that TurboID is the most promiscuous variant in several plant model systems and establish protocols which combine Mass Spectrometry-based analysis with harsh extraction and washing conditions. We demonstrate the applicability of TurboID in capturing membrane-associated protein interactomes using Lotus japonicus symbiotically active receptor kinases as test-case. We further benchmark the efficiency of various PBLs in comparison with one-step affinity purification approaches. We identified both known as well as novel interactors of the endocytic TPLATE complex. We furthermore present a straightforward strategy to identify both nonbiotinylated as well as biotinylated peptides in a single experimental setup. Finally, we provide initial evidence that our approach has the potential to infer structural information of protein complexes.

Several studies have been published in which holistic approaches were used to characterise the proteome and transcriptome of human platelets. The key intent being that a deeper understanding of the normal and aberrant physiological functions of platelets can only be achieved if most biomolecular building blocks are mapped. Here we present the application of recently developed novel technologies that overcome some of the shortcomings of gel-based proteomics. Central in our approach is the so-called combined fractional diagonal chromatography (COFRADIC)-technology in which sets of representative peptides are sorted in a diagonal RP chromatographic system through a specific modification of their side chain. In this study we combined three different COFRADIC sorting techniques to analyse the proteome of human platelets. Methionyl, cysteinyl and amino terminal peptides were isolated and analysed by MS/MS. Merging the peptide identifications obtained after database searching resulted in a core set of 641 platelet proteins, which comprises the largest set identified today. In comparison to previously published platelet proteomes, we identified 404 novel platelet proteins containing a high number of hydrophobic membrane proteins and hypothetical proteins. Furthermore we discuss the observed characteristics and potential benefits of each of the different COFRADIC technologies for proteome analysis and highlight important issues that need to be considered when searching sequence databases using data obtained in peptide-centric, non-gel proteomics studies.