Proteomic mapping of intercellular synaptic environments via flavin-dependent photoredox catalysis

GlycoID Proximity Labeling to Identify O-GlcNAcylated Protein Interactomes in Live Cells

Cells continuously remodel their intracellular proteins with the monosaccharide O-linked N-acetylglucosamine (O-GlcNAc) to regulate metabolism, signaling, and stress. This protocol describes the use of GlycoID tools to capture O-GlcNAc dynamics in live cells. GlycoID constructs contain an O-GlcNAc binding domain linked to a proximity labeling domain and a subcellular localization sequence. When expressed in mammalian cells, GlycoID tracks changes in O-GlcNAc-modified proteins and their interactomes in response to chemical induction with biotin over time. Pairing the subcellular localization of GlycoID with the chemical induction of activity enables spatiotemporal studies of O-GlcNAc biology during cellular events such as insulin signaling. However, optimizing intracellular labeling experiments requires attention to several variables. Here, we describe two protocols to adapt GlycoID methods to a cell line and biological process of interest. Next, we describe how to conduct a semiquantitative proteomic analysis of O-GlcNAcylated proteins and their interactomes using insulin versus glucagon signaling as a sample application. This articles aims to establish baseline GlycoID protocols for new users and set the stage for widespread use over diverse cellular applications for the functional study of O-GlcNAc glycobiology. © 2024 Wiley Periodicals LLC. Basic Protocol 1: Expression of targeted GlycoID constructs to verify subcellular location and labeling activity in mammalian cells Basic Protocol 2: GlycoID labeling in live HeLa cells for O-GlcNAc proteomic comparisons.

Magnetic Bead-Based Workflow for Sensitive and Streamlined Cell Surface Proteomics

Cell surface proteins represent an important class of molecules for therapeutic targeting and cellular phenotyping. However, their enrichment and detection via mass spectrometry-based proteomics remains challenging due to low abundance, post-translational modifications, hydrophobic regions, and processing requirements. To improve their identification, we optimized a Cell-Surface Capture (CSC) workflow that incorporates magnetic bead-based processing. Using this approach, we evaluated labeling conditions (biotin tags and catalysts), enrichment specificity (streptavidin beads), missed cleavages (lysis buffers), nonenzymatic deamidation (digestion and deglycosylation buffers), and data acquisition methods (DDA, DIA, and TMT). Our findings support the use of alkoxyamine-PEG4-biotin plus 5-methoxy-anthranilic acid, SDS/urea-based lysis buffers, single-pot solid-phased-enhanced sample-preparation (SP3), and streptavidin magnetic beads for maximal surfaceome coverage. Notably, with semiautomated processing, sample handling was simplified and between ∼600 and 900 cell surface N-glycoproteins were identified from only 25-200 μg of HeLa protein. CSC also revealed significant differences between in vitro monolayer cultures and in vivo tumor xenografts of murine CT26 colon adenocarcinoma samples that may aid in target identification for drug development. Overall, the improved efficiency of the magnetic-based CSC workflow identified both previously reported and novel N-glycosites with less material and high reproducibility that should help advance the field of surfaceomics by providing insight in cellular phenotypes not previously documented.