DAH3.4 Protein interactions, sub –cellular locations and

arrays

Kathryn Lilley

Cambridge Centre for Proteomics

Department of Biochemistry

University of Cambridge

k.s.lilley@bioc.cam.ac.uk

www.bio.cam.ac.uk/proteomics/

Part III Systems Biology

Outline

• Protein-protein interactions

• Protein sub-cellular location

• Protein Arrays

• Limitations of proteomics and systems biology

Types of protein analysis

Proteins present PPI SCL Function

Mass Spectrometry

Western blotting

GFP tagging

Immuno- histochemistry

Enzyme assay

Arrays

Abundance

Quantitative Mass Spec

Western blotting

GFP tagging

Immuno- histochemistry

Enzyme assay

Arrays

Isoform status

Mass Spectrometry

Western blotting

Functional arrays

Y2H

Tagging + Mass Spectrometry

Western blotting

Structural studies

Protein Arrays

Biophysical assays (e.g.ITC,

AUC)

Mass Spectrometry

GFP tagging

Immuno- histochemistry

Enzyme assay

Functional arrays

Enzyme assay

Genetic approaches

Protein-Protein InteractionsPPI

Y2H

Tagging + Mass Spectrometry

Western blotting

Structural studies

Protein Arrays

Biophysical assays (e.g.ITC,

AUC)

Identification of protein binding partners

Methods to determine PPI

• Y2H (yeast two hybrid)

• Tagging + Mass Spectrometry

• Western blotting

• Structural studies

• Protein Arrays

• Biophysical assays (analytical ultracentrifugation)

Y2H

BD

ADGal4 transcription factor has two domains

Lac Z gene

BDAD

Lac z protein (can easily assayed using x-gal)

BD

AD

Bait Prey

If BD and AD are expressed separately, no transcription

If BD and AD are expressed as fusion proteins with proteins that interact that are brought close together structurally and can bring about transcription of LacZ

mRNA

UAS

Two-hybrid screen for protein partners

Bait and prey libraries expressed in yeast

Bait and prey can come from any organisms but must be fused to yeast AD and BD

Only any good for binary interactions

Very high false discovery rate

Protein Complex Purification

• Methods mostly based around fusion of bait protein and selective purification of complex by immunoprecipitation

• Methods can be ‘dirty’

Pull-down

Wash

Elute

Two potential problems:

All single step purifications – many extraneous protein co-purified.

Tagged proteins often over expressed.

Tag bait protein and pull it and its preys out of a mixture

Tag could be avidin (binds to Biotin) hexa histidine (binds to Ni-NTA) flag (small peptide epitope for which and antibody is available)

Tandem Affinity Purification Tagging

PROTEIN SPACER CBP TEV site PROTEIN A

IgG beadsPROTEIN SPACER CBP TEV site PROTEIN A

TEV protease

Calmodulin beadsPROTEIN SPACER CBP

Bind and wash

Bind and wash

Elute with Calcium

Run purified complex on 1D gel Identify components by MS

iPAC (parallel affinity chromatography)

S

F

FLAG M2 purification,

FLAG peptide elution

Strep purification,

Biotin elution

FLAG M2 purification,

FLAG peptide elution

Strep purification,

Biotin elution

Rees et al Mol.Cell Prot 2011

Bait with two tagsFlag and Strep

Negative control with no tags

Types of protein analysis

Proteins present PPI SCL Function

Mass Spectrometry

Western blotting

GFP tagging

Immuno- histochemistry

Enzyme assay

Arrays

Abundance

Quantitative Mass Spec

Western blotting

GFP tagging

Immuno- histochemistry

Enzyme assay

Arrays

Isoform status

Mass Spectrometry

Western blotting

Functional arrays

Y2H

Tagging + Mass Spectrometry

Western blotting

Structural studies

Protein Arrays

Biophysical assays (e.g.ITC,

AUC)

Mass Spectrometry

GFP tagging

Immuno- histochemistry

Enzyme assay

Functional arrays

Enzyme assay

Genetic approaches

Sub-cellular location

Mass Spectrometry

GFP tagging

Immuno- histochemistry

Enzyme assay

GFP tagging of yeast proteome

Huh et al, 2003

GFP tagged proteins

75% of the yeast proteome classified to 22 distinct location

Systems wide immuno-

histochemistry

Barbe et al, 2008

Antibodies to 488 proteins applied to 3 different human cell lines and images stored and publically accessible

Blue = DAPI staining of nucleus

Gentle cell lysis

Pure fraction

Protein correlation profiling

LOPIT

Subtractive proteomics

Invariant rich fraction

Proteomics approaches

Pure Fraction

Extract proteins

DigestLC-MS/MS

Parts list

Subtractive Proteomics

Boisvert et al (2010) Mol. Cell Prot 9:457

Invariant Rich Fraction

Rough microsomesSmooth microsomesGolgi Apparatus

‘enriched fractions’

RM

RM + SM

SM

Golgi

Gilchrist et al (2006) Cell 127:1265

2

4

6

8

10

12

14

16

18

20

1

3

5

7

9

11

13

15

17

19

Gtl-6 Golgi

Cyt b5sER

Sec12ER

2 4 6 8 10 12 14 16 18 201 3 5 7 9 11 13 15 17 19

Carbonate wash

Tom Dunkley

Distribution Profiling

LOPIT Protocol

LC-MS/MS (SCX/RP)

Localisation of organelle proteins using isotope tagging (LOPIT)

Quantification Identification

Dunkley et al (2006) Proc. Natl. Acad. Sciences

103:6518

PCA Analysis of iTRAQ Dataset

GolgiGolgi

ERER

VacuoleVacuole

Plasma Plasma membranemembrane

Mito/PlastidMito/Plastid

GolgiGolgi

ERER

VacuoleVacuole

Plasma Plasma membranemembrane

Mito/PlastidMito/Plastid

MarkerPredicted markerLOPIT assignedno location assigned+

Types of protein analysis

Proteins present PPI SCL Function

Mass Spectrometry

Western blotting

GFP tagging

Immuno- histochemistry

Enzyme assay

Arrays

Abundance

Quantitative Mass Spec

Western blotting

GFP tagging

Immuno- histochemistry

Enzyme assay

Arrays

Isoform status

Mass Spectrometry

Western blotting

Functional arrays

Y2H

Tagging + Mass Spectrometry

Western blotting

Structural studies

Protein Arrays

Biophysical assays (e.g.ITC,

AUC)

Mass Spectrometry

GFP tagging

Immuno- histochemistry

Enzyme assay

Functional arrays

Enzyme assay

Genetic approaches

Function

Functional arrays

Enzyme assay

Genetic approaches

Functional genomics

• One-by one knock out and observe phenotype

Kamath et al, 2003, used RNAi to inhibit the function of, 86% of the 19,427 predicted genes of C. elegans and identified 1,722 mutant phenotypes

Karlas et al 2010, screened a genome-wide siRNA library consisting of approximately 62,000 siRNAs targeting ,17,000 annotated genes and ,6,000 predicted genes in conjunction with infection of a lung epithelial cell line with H1N1 virus. They found that 287 host cell genes influence infection.

• In silico predictions

Sequence alignment Structure alignment

• Functional Arrays• e.g. Kinase substrates.calmodulin binding, ……

Protein Arrays

Three types:

Functional Arrays

Analytical/Diagnostic Arrays

Tissue Arrays

How to make them

Slides derivatised with the following on to which proteins can be spotting using contact printing methods

Nitrocellulose

Amino silane

Gold coated

Bifunctional cross linkers

Biotin/avidin

hexa-histidine/ Nickel (Ni-NTA)

Synthesis of a yeast protein array

Mok et al, 2009

Proteins expressed with a tag which makes them easy to purify

Still a major task to express and purify every proteins from an organism

Protein in situ arrays (PISA)

Nucleic Acid Programmable Protein Array (NAPPA)

DNA Array to Protein Array (DAPA)

Protein DNA

New approach?

He et al (2009) New Biotechnology 26:227

Detection

Fluorescence

Radioactivity

Quantum dots

Surface plasmon resonance

Mass spectrometry

Functional arrays

Kinase Substrates

For more examples see Chen and Snyder (2010) J. Proteomics 74:2147-57

Analytical/Diagnostic Arrays

Protein Expression Profiling on Capture Arrays

Antibody Affinity Arrays

A2M2SAffinity Arrays and MALDI Mass Spectrometry

Darii et al, 2009

Tissue Arrays

• Tissues mounted to standard silanized slides.• Formalin-fixed paraffin-embedded human tissues• Used for immunohistochemistry, in situ hybridization,

fluorescent in situ hybridisation and in situ PCR• Available from different companies supplying cancerous

and normal tissues

Human Protein Atlas

Tissue arrays, 48 normal tissue types, 20 cancers. Cell line arrays – 47 different cell lines Immunohistochemitsry - Sections of tissuesImmunohistochemistry of 3 cell lines

Antibodies raised against expressed sequence tags , a specific epitope for each human protein PrESTs

www.proteinatlas.org

Strengths

Under represented proteins present

Functional information

High throughput

Weaknesses

Proteins need to be in correct orientation and in vivo relevant structure

Unknown splicing variants not detected

Mixed PTMs not detected

Co-interacting partners not detected

Off target interactions

High cost of manufacture

Problems with proteomics and systems biology

Tip of ice berg

Combinatorial PTMs

Keeping complexes together

Tissue specificity

Synchronisation of cells

Singel cell proteomics

Whole proteome is highly dynamic

Often not enough samples/resources to carry out sufficient replicate experiments

Single Cell Proteomics

Bendall et al (2011) Science

ICPMS

Inductively coupled plasma MS