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

• carry out the majority of cellular functions • RNA levels are not always well-correlated with abundance

Hood et al. Mol. Cell. Proteomics 2004

Aebersold et al. Cell 2016 Proteomics ? Neuroscience Proteomics ? Neuroscience

Fractionation & 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 ) 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)

• 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 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 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

GPCR 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 et al. Nature 2020

Plants Bacteria Zhang et al. Nat Comm 2019 Branon et al. Nat Biotech 2018 Mair et al. eLife 2019 A recent example of proximity labeling in neuroscience

Liqun Luo Jiefu Li Shuo Han

“Cell-Surface Proteomic Profiling in the Fly Brain Uncovers Wiring Regulators” Jiefu Li*, Shuo Han* et al. Cell 2020 Cell surface proteomics in the developing fly brain

Goal: discover new regulators of synaptic wiring

Express peroxidase on the surface of olfactory projection neurons (PN) Cell surface proteomics in the developing fly brain

Screen hit rate Luo et al. PNAS 2019 Among our hits: chitinase, anion transporter, lipase, peptidase….

Molecular family-guided screen Li et al. Cell 2020 Some new directions in proximity labeling

Using proximity labeling to map protein translocation

Using proximity labeling to study RNA-protein interactions Some new directions in proximity labeling

Using proximity labeling to map protein translocation

Using proximity labeling to study RNA-protein interactions Using proximity labeling to map inter-organ communication

How do different parts of an organism signal to one another, at the molecular level? What proteins are secreted by one organ and received in another?

Norbert Perrimon et al. bioRxiv 2020 TurboID for for mapping inter-organ communication

Fat body Muscle

Biotinylated proteins Unlabeled proteins secreted from fat body

TurboID -KDEL Biotin from food

• Dissect • Enrich • 269 proteins detected biotinylated • ~80% have signal peptides proteins • Discovery of novel factor in fat body whose knockdown impairs • Identify by MS climbing ability • 70% of the 269 proteins have human orthologs

Norbert Perrimon et al. bioRxiv 2020

Some new directions in proximity labeling

Using proximity labeling to map protein translocation

Using proximity labeling to study RNA-protein interactions How to expand the scope of APEX proximity labeling? Bait

APEX Prey 0 0 Interacting Protein of interest proteins

Interacting DNA

Interacting RNA “APEX-seq” How to expand the scope of APEX proximity labeling? Bait

APEX Prey 0 0 Interacting Protein of interest proteins

APEX

Interacting DNA DNA locus of interest

APEX Interacting RNA “APEX-seq”

RNA of interest How to expand the scope of APEX proximity labeling? Bait

APEX Prey 0 0 Interacting Protein of interest proteins

APEX

Interacting DNA DNA locus of interest “CASPEX”

Discovery of proteins associated with a predefined Interacting genomic locus via dCas9-APEX-mediated RNA “APEX-seq” proximity labeling Steve Carr, Sam Myers et al. Nature Methods 2018 Erik Sontheimer et al. Nature Methods 2018 How to expand the scope of APEX proximity labeling? Bait

APEX Prey 0 0 Interacting Protein of interest proteins

APEX

Interacting DNA DNA locus of interest “CASPEX”

APEX Interacting RNA “APEX-seq”

RNA of interest Use dCas13 to target APEX to RNAs? dCas13 for targeting endogenous RNAs: first attempt

GFP dCas13a crRNA Not a robust method: • Actin is a super abundant transcript actin mRNA • Actin is concentrated in stress granules • Requires complex transcriptional GFP- marker Merge+ feedback system dCas13a (G3BP1) DAPI

actin guide1

actin guide2

Same problem with improved dCas13d non-target guide (dCasRx) –Konermann et al. Cell 2018

Abudayyeh…. Ting, Zhang et al. Nature 2017 Shuo Han Increase affinity of dCas13 for target RNA?

dsRNA binding domain (dsRBD) • From human protein kinase • Non-sequence specific • Binds to 12-16 base pairs of dsRNA • Affinity for dsRNA over ssRNA

ternary complex

dCas13 dsRBD to provide additional stabilization? gRNA target RNA

Shuo Han Increase affinity of dCas13 for target RNA?

HA FLAG dCas13 DAPI hTERT merge

hTR gRNA dCas13d NLS HA non-target gRNA

hTR gRNA dsRBD dCas13d BPNLS HA non-target gRNA

dsRBD

gRNA hTR Shuo Han et al. PNAS 2020 Increase affinity of dCas13 for target RNA?

dsRBD dCas13d dCas13d NLS HA BPNLS HA

HA FLAG HA FLAG dCas13 hTERT merge dCas13 hTERT merge

Shuo Han et al. PNAS 2020 Proteomics experiment to ID protein interaction partners of human telomerase RNA (hTR)

dCas13 77 proteins enriched dsRBD 44 high confidence crRNA hTR biotin APEX interacting H O 2 2 proteins biotin-phenol

1-minute live-cell streptavidin bead enrichment

intensity LC-MS/MS quantitative proteomics m/z

Shuo Han et al. PNAS 2020 Proteomics experiment to ID protein interaction partners of human telomerase RNA (hTR)

dCas13 77 proteins enriched dsRBD 44 high confidence crRNA hTR biotin APEX interacting H O 2 2 proteins biotin-phenol

1-minute live-cell biotinylation streptavidin bead enrichment

intensity LC-MS/MS quantitative proteomics nuclear annotation m/z

Shuo Han et al. PNAS 2020 Proteomics experiment to ID protein interaction partners of human telomerase RNA (hTR)

dCas13 77 proteins enriched dsRBD 44 high confidence crRNA hTR biotin APEX interacting H O 2 2 proteins biotin-phenol

1-minute live-cell biotinylation streptavidin bead enrichment

intensity LC-MS/MS quantitative proteomics nuclear annotation m/z RNA binding annotation

Shuo Han et al. PNAS 2020 Proteomics experiment to ID protein interaction partners of human telomerase RNA (hTR)

dCas13 77 proteins enriched dsRBD 44 high confidence crRNA hTR biotin APEX ALKBH5 interacting H O 2 2 proteins biotin-phenol

1-minute live-cell biotinylation streptavidin bead enrichment

intensity LC-MS/MS quantitative proteomics nuclear annotation m/z RNA binding annotation

Shuo Han et al. PNAS 2020 ALKBH5: an m6A demethylase

Affects mRNA translation, decay, splicing, transport

cell cycle, differentiation, stress response, innate immunity, cancer

Is hTR (a noncoding RNA) regulated by m6A and ALKBH5?

Chuan He ALKBH5 follow-up experiments

ALKBH5-Flag immunoprecipitates ALKBH5 overexpression endogenous hTR decreases m6A levels on hTR

wild-type

ALKBH5 OE

ALKBH5 overexpression ALKBH5 overexpression disrupts telomerase complex decreases telomerase activity

Boxuan Zhao, Shuo Han with Chuan He Working model: hTR may be dynamically regulated by m6A/ALKBH5

m6A writer (METTL) hTR m6A eraser (ALKBH5) Telomerase Telomerase inactive? active?

possible m6A modification sites on hTR

with Chuan He Boxuan Zhao, Shuo Han Eventual hope: fully expand the scope of proximity labeling

Bait

APEX Prey 0 0 Interacting Protein of interest proteins

APEX

Interacting DNA DNA locus of interest

APEX Interacting RNA

RNA of interest Summary of proximity labeling

• Compared to pull-downs & fractionation, proximity labeling: (1) can recover transient/ weak binders; (2) can be much more specific; (3) works on un-purifiable organelles • APEX is fast and versatile − can also tag RNA and be used for EM • TurboID and miniTurbo are simple and non-toxic − better in vivo

Future Directions • PL to study protein movement • Functional PL to map protein subclasses by location and function • New enzymes and labeling chemistries: non-biotin, non-toxic, broader reactivity & scope • Conditional labeling: Ca+2, light, or cell-cell contact regulated

https://www.researchsquare.com/article/rs-103196/v1 Limitations of proximity labeling

• Not single cell • Need to transfect/transduce sample • No tissue coordinates • One compartment at a time

Imaging & cytometry-based proteomic methods Proximity labeling-based proteomics CyTOF, MIBI, CODEX, Imaging mass cytometry

• Single cell and/or spatial coordinate • Detect endogenous proteins (no Pros data antibodies needed) • Detect 1000s of proteins at once • Subcellular information

• Limited by antibody quality • Averages across populations • Limited number of protein species Cons can be studied in a single experiment (~50?) • Useful for studying tissue • Useful for discovery heterogeneity • Useful for mapping subcellular • Useful for evaluating cellular structures & complexes responses to drugs, etc. Acknowledgements

Ting lab members: Wei Qin, Christina Kim, Mateo Funding: Isidro Sanchez Lopez, Robert Coukos, Kelvin Cho, NIH, Stanford, Chan Zuckerberg Biohub Elbeg Erdenee, Sifei Yin, Matt Ravalin, Peter Wu Tsai Neurosciences Institute Cavanagh, Boxuan Zhao, Rongbing Huang, Nick Kalogriopoulos, Song-Yi Lee, Eric Strand, Sabrina Collaborators: Kuta, Heegwang Roh, Joleen Cheah, Sean Waterton Steve Carr (mass spec proteomics) Liqun Luo (fly brain) Past Ting lab members: Tess Branon, Shuo Han, Jeff Norbert Perrimon (TurboID in flies) Martell, Hyun-Woo Rhee, Peng Zou, Victoria Hung, … and many others Stephanie Lam, Ken Loh, Chai Kaewsapsak

Stanford University

Clark Center & Bio-X ChEM-H Chemical Biology Institute Wu Tsai Neurosciences Institute Stanford Cancer Institute Stanford Center for CEH Genomics Department of Genetics Department of Biology Department of Chemistry What’s coming in the next two days

Wednesday, 9 am PT Tess Branon Design and execution of proximity labeling Former Ting lab grad student, experiments now a postdoc with Greg Barton at UC Berkeley

Thursday, 9 am PT Shuo Han Analysis of proximity labeling data Former Ting lab grad student, now a postdoc with Phil Beachy at Stanford

Panelists

Kelvin Cho Wei Qin Jiefu Li Grad Student with Postdoc with Postdoc with Alice Ting Alice Ting Mark Davis at Stanford