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Alice Ting Proximity Labeling Slides 11-17-2020 Stanford Neuro-omics 2020 Virtual Workshop “Proteomics and proximity labeling in neuroscience” Alice Ting, Departments of Genetics, Biology, and Chemistry (by courtesy) "Mapping the Dynamic Architecture of Immune Cells in Normality & Disease” Garry Nolan, Department of Microbiology and Immunology, Stanford Wednesday, 9 am PT: “Design and execution of proximity labeling experiments” Tess Branon (with panelists Kelvin Cho, Wei Qin, Shuo Han, Jiefu Li) Thursday, 9 am PT: “Analysis of proximity labeling data” Shuo Han (with panelists Kelvin Cho, Wei Qin, Tess Branon, Jiefu Li) Organizers: Boxuan Zhao, Kelvin Cho Previous week: Transcriptomics This week: Proteomics • Proteins carry out the majority of cellular functions • RNA levels are not always well-correlated with protein abundance Hood et al. Mol. Cell. Proteomics 2004 Aebersold et al. Cell 2016 Proteomics ? Neuroscience Proteomics ? Neuroscience Fractionation & immunoprecipitation Imaging & cytometry purify cells of interest tissue purify ID organelle proteins of interest by mass cell spec purify protein complex of interest cell Creative applications of proteomics methods to Proteomics Neuroscience neuroscience Synaptosome and PSD (post- Cell type-specific proteomes by Large scale imaging of synaptic density) proteomics BONCAT endogenous synaptic via subcellular fractionation proteins with antibodies Schuman Nat Biotech 2017 Rizzoli Science 2014 Smith Neuron 2010 Yet many proteomics questions in neuroscience are still out of reach of current methods Proteomic composition of unpurifiable subcellular compartments, e.g., active • Single cell proteomes (analogous to scRNA-seq)? zone, AIS, neuron-glial synapse? • In situ/in tissue single cell proteomics? • Cell-type specific proteomes in vivo with no toxicity Identity of proteins & peptides that & minute-resolution? signal between cell types, and across • Proteomic signatures of functional cellular brain regions? ensembles? Proteoform diversity? Emerging innovations in proteomics that could potentially benefit neuroscience Activity-based protein profiling CyTOF Flow Cytometry, 2019 Blair Cravatt, Ann. Rev. Biochem 2008 Thermal proteome Top-down proteomics TODAY profiling Proximity labeling CODEX & MIBI Proximity labeling – Why? Two broad classes of proteomics methods Fractionation & immunoprecipitation Imaging & cytometry purify cells of interest tissue purify ID organelle proteins of interest by mass cell spec purify protein complex of interest cell Proximity labeling – Why? purify cells of interest tissue purify ID organelle run on cut out proteins of interest gel bands by mass cell spec purify protein complex of interest cell Proximity labeling – Why? Traditional mass spec proteomics work flow purify cells of interest tissue Problems: • Cell lysis disrupts compartments and complexes purify • Key components are lost organelle • Contaminants are picked up of interest • Purification takes hours to days cell • Many compartments & complexes purify protein cannot be purified complex of interest cell Many subcellular compartments are impossible to purify mitochondrial neuronal synaptic cleft intermembrane space • stress granules • pre-synaptic active zone • P-bodies • inhibitory post-synaptic density • RNA granules • axon initial segment • nuclear lamina • transport vesicles • nuclear envelope • autophagosomes • nucleolus • centrosome • outer mito membrane • cilia • mito-ER junctions • specific genomic loci • mito cristae junctions • many more.... Even organelles that can be purified, are not necessarily purified well Seglen et al. Biochem J. 1998 “MitoCarta” 1098 mouse proteins Cell 2008 Specificity 64% 90% “MitoCarta” Traditional mass spec proteomics work flow has limitations Traditional mass spec proteomics work flow purify cells of interest tissue Problems: • Cell lysis disrupts compartments and complexes purify • Key components are lost organelle • Contaminants are picked up of interest • Purification takes hours to days cell • Many compartments & complexes purify protein cannot be purified complex of interest cell New method that bypasses purification altogether, but still delivers subcellular/spatial information? Proximity labeling Tag (with biotin) proteomes of interest in living cells. Subsequently, isolate biotinylated proteins and identify them by mass-spec. Key: promiscuous labeling enzyme B XH X B B X not B = biotin labeled protein labeled Proximity labeling Tag (with biotin) proteomes of interest in living cells. Subsequently, isolate biotinylated proteins and identify them by mass-spec. Biotinylation in live cells biotin substrate • Lyse • Streptavidin beads 1 min • Mass spectrometry Genetically target promiscuous labeling enzyme to one specific region of cell = biotinylated site on endogenous protein Labeling radius 1-5 nm Information is recorded while cells are alive, membranes and complexes are intact, & spatial relationships are preserved. What is the promiscuous enzyme? Two broad families of enzymes for proximity labeling Peroxidase family Biotin ligase family + ATP B OH B B B B O B−AMP • APEX2 • BioID • BASU • HRP • TurboID • AirID • Split-APEX2 • miniTurbo • Split-BioID • Split-HRP • BioID2 • Split-TurboID Wednesday, 9 am PT: “Design and execution of proximity labeling experiments” Tess Branon (with panelists Kelvin Cho, Wei Qin, Shuo Han, Jiefu Li) • How to select the best proximity labeling (PL) enzyme for your application • How to design and validate PL enzyme fusion constructs Two of our favorite proximity labeling enyzmes APEX2 (peroxidase family) • Directed evolution from soybean ascorbate peroxidase B OH B • Covalently labels Tyrosine • Labeling time: 10 sec – 1 minute B O • Labeling radius: 1 – 5 nm • Add biotin-phenol (BP) + H O to initiate labeling Rhee et al. Science 2013 2 2 Lam et al. Nature Methods 2016 • Best option for cell culture: fast, small labeling radius TurboID (biotin ligase family) • Directed evolution from E. coli biotin ligase (BirA) B + ATP • Covalently labels Lysine B • Labeling time: 1 – 10 min B−AMP • Labeling radius: 1 – 5 nm • Add biotin to initiate labeling; cell provides ATP Branon et al. • Best option in vivo: simple & non-toxic (no H2O2) but slower Nature Biotech 2018 than APEX Engineering of APEX2 ascorbate peroxidase 1-5 nm APEX B OH B B O not labeled B = biotin labeled protein Wild-type soybean APEX APEX2 ascorbate peroxidase Structure- guided Yeast display mutagenesis directed & screening evolution Martell et al. Lam et al. Nature Biotech 2012 Nature Methods 2015 +H2O2 +H O 2 2 Biotin-phenol Phenoxyl radical APEX2 is also useful for electron microscopy Mitochondria Chromatin Cytoskeleton post-synaptic density MTS-APEX APEX-H2B Vimentin-APEX2 PSD95-APEX2 H2N NH2 APEX2 DAB H2N NH2 APEX as a genetically-encoded DAB polymer reporter for electron microscopy Martell et al. Nature Biotech 2012 OsO4 dark stain by electron microscopy APEX2 also biotinylates endogenous RNA (“APEX-seq”) APEX2 + + biotin-phenol BP radical RNA BP-RNA adduct Transcriptome atlas contains data for 3,250 genes & >1000 transcript isoforms HEK293T human cells Fazal, Han, … Chang, Ting, Cell 2019 Applications of APEX2 and TurboID proximity labeling APEX can be used to map organelle proteomes ER lumen • 338 proteins Mitochondrial matrix • >98% specificity • 495 proteins • 63% coverage • >95% specificity • 85% coverage Rhee et al. Science 2013 Mitochondrial intermembrane space Mitochondrial ER membrane • 127 proteins nucleoid (mtDNA) Mitochondrial • 634 proteins • >94% specificity • 37 proteins outer membrane • >89% specificity • 65% coverage • >81% specificity • 44% coverage • 137 proteins • 62% coverage Hung et al. Hung et al. eLife 2017 Molecular Cell • >84% specificity Han et al. Cell Chemical 2014 • 53% coverage Biology 2017 Hung et al. eLife 2017 Paste Cell header here Excitatory glutamatergic Inhibitory GABAergic synaptic cleft synaptic cleft • 199 proteins enriched • 42 proteins enriched • >89% specificity • >90% specificity • 69% coverage • 46% coverage Ken Loh et al. Cell 2016 APEX mapping of unpurifiable subcellular compartments Stress granules Primary cilia Lipid droplet Mito-ER contacts Yeo et al. Cell 2018 Nachury et al. Dev Cell 2015 Bersuker et al. Dev Cell 2018 Cho et al. JBC 2017 Hung et al. eLife 2017 Early endosome Ciliary membrane Plasma membrane-ER contacts Olmo et al. EMBO Reports 2019 Kohli et al. EMBO Reports 2017 Zhou et al. Nature Cell Biol 2015 APEX mapping of protein interactomes GPCR interactome GPCR interactome Microprotein Fibroblast growth factor Gygi et al. Cell 2017 Krogan et al. Cell 2017 MIEF1 interactome interactome Saghatelian et al. Wesche et al. Biochemistry Biochemistry 2018 2018 Genomic locus interactome Voltage-gated calcium channel Bacterial secretion protein Carr et al. Nat Methods 2018 interactome TssA interactome Marx et al. Nature 2020 Cascales et al. Nat Microbiology 2018 TurboID mapping of organelles, macromolecular complexes, and protein interactomes ER membrane A-kinase anchoring mutants Plant immune signaling receptor Rare plant transcription factors Branon et al. Smith et al. Zhang et al. Mair et al. eLife 2019 Nat Biotech 2018 PNAS 2018 Nat Comm 2019 Cytoskeletal regulators Non-centrosomal MTOCs Inter-organ trafficking Bozal-Basterra et al. Sanchez et al. Droujinine et al. eLife 2020 BioRxiv 2020 BioRxiv 2020 TurboID can be used in many different model organisms C. elegans Drosophila Branon et al. Nat Biotech 2018 Branon et al. Nat Biotech 2018 Sanchez et al. BioRxiv 2020 Droujinine et al. BioRxiv 2020 Yeast Branon et al. Nat Biotech 2018 Mice Takano
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