Systematic identification of structure-specific protein-protein interactions.

The physical interactome of a protein can be altered upon perturbation, modulating cell physiology and contributing to disease. Identifying interactome differences of normal and disease states of proteins could help understand disease mechanisms, but current methods do not pinpoint structure-specific PPIs and interaction interfaces proteome-wide. We used limited proteolysis-mass spectrometry (LiP-MS) to screen for structure-specific PPIs by probing for protease susceptibility changes of proteins in cellular extracts upon treatment with specific structural states of a protein. We first demonstrated that LiP-MS detects well-characterized PPIs, including antibody-target protein interactions and interactions with membrane proteins, and that it pinpoints interfaces, including epitopes. We then applied the approach to study conformation-specific interactors of the Parkinson's disease hallmark protein alpha-synuclein (aSyn). We identified known interactors of aSyn monomer and amyloid fibrils and provide a resource of novel putative conformation-specific aSyn interactors for validation in further studies. We also used our approach on GDP- and GTP-bound forms of two Rab GTPases, showing detection of differential candidate interactors of conformationally similar proteins. This approach is applicable to screen for structure-specific interactomes of any protein, including posttranslationally modified and unmodified, or metabolite-bound and unbound protein states.

Parallel Proteomic Workflow for Mass Spectrometric Analysis of Tissue Samples Preserved by Different Methods.

Formalin-fixed and paraffin-embedded (FFPE) and optimal cutting temperature (OCT)-embedded and frozen tissue specimens in biobanks are highly valuable in clinical studies but proteomic and post-translational modification (PTM) studies using mass spectrometry (MS) have been limited due to structural arrangement of proteins and contaminations from embedding material. This study aims to develop a parallel proteomic workflow for FFPE and OCT/frozen samples that allows for large-scale, quick, reproducible, qualitative, and quantitative high-resolution MS analysis. The optimized protocol gives details on removal of embedding material, protein extraction, and multienzyme digestion using filter-aided sample preparation method. The method was evaluated by investigating the protein expression levels in nonmuscle-invasive and muscle-invasive bladder cancer samples in two cohorts and MS spectra were carefully reviewed for contaminations. More than 2000 and 3000 proteins in FFPE and OCT/frozen samples, respectively, were identified, and samples could be clustered in different tumor stages based on their protein expression. Furthermore, more than 250 and 400 phosphopeptides could be identified from specific patient samples of FFPE and OCT/frozen, respectively, using titanium dioxide enrichment. The paper presents unique data describing the similarities and differences observed in FFPE and OCT/frozen samples and shows the feasibility to detect proteins and site-specific phosphorylation even after long-term storage of clinical samples.

Limited Proteolysis-Mass Spectrometry to Identify Metabolite-Protein Interactions.

Metabolite-protein interactions regulate diverse cellular processes, prompting the development of methods to investigate the metabolite-protein interactome at a global scale. One such method is our previously developed structural proteomics approach, limited proteolysis-mass spectrometry (LiP-MS), which detects proteome-wide metabolite-protein and drug-protein interactions in native bacterial, yeast, and mammalian systems, and allows identification of binding sites without chemical modification. Here we describe a detailed experimental and analytical workflow for conducting a LiP-MS experiment to detect small molecule-protein interactions, either in a single-dose (LiP-SMap) or a multiple-dose (LiP-Quant) format. LiP-Quant analysis combines the peptide-level resolution of LiP-MS with a machine learning-based framework to prioritize true protein targets of a small molecule of interest. We provide an updated R script for LiP-Quant analysis via a GitHub repository accessible at https://github.com/RolandBruderer/MiMB-LiP-Quant .

Environmental Signals Act as a Driving Force for Metabolic and Defense Responses in the Antarctic Plant Colobanthus quitensis.

During evolution, plants have faced countless stresses of both biotic and abiotic nature developing very effective mechanisms able to perceive and counteract adverse signals. The biggest challenge is the ability to fine-tune the trade-off between plant growth and stress resistance. The Antarctic plant Colobanthus quitensis has managed to survive the adverse environmental conditions of the white continent and can be considered a wonderful example of adaptation to prohibitive conditions for millions of other plant species. Due to the progressive environmental change that the Antarctic Peninsula has undergone over time, a more comprehensive overview of the metabolic features of C. quitensis becomes particularly interesting to assess its ability to respond to environmental stresses. To this end, a differential proteomic approach was used to study the response of C. quitensis to different environmental cues. Many differentially expressed proteins were identified highlighting the rewiring of metabolic pathways as well as defense responses. Finally, a different modulation of oxidative stress response between different environmental sites was observed. The data collected in this paper add knowledge on the impact of environmental stimuli on plant metabolism and stress response by providing useful information on the trade-off between plant growth and defense mechanisms.