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Proteomics Informatics – Proteomics Informatics –

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Proteomics Informatics – - PPT Presentation

Protein characterization posttranslational modifications and proteinprotein interactions  Week 10 Top down bottom up Top down Bottom up masscharge intensity Top down Bottom up ID: 600978

localization protein modifications peptides protein localization peptides modifications mass cross gfp dna precursor vif specific peptide vhh cdr3 intensity

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Slide1

Proteomics Informatics –

Protein characterization: post-translational modifications and protein-protein interactions (Week 10)Slide2

Top down / bottom up

Top down

Bottom up

mass/charge

intensitySlide3

Top down Bottom up

Charge distribution

mass/charge

intensity

mass/charge

intensity

1+

2+

3+

4+

27+

31+Slide4

Top down Bottom up

Isotope distribution

mass/charge

intensity

mass/charge

intensitySlide5

Fragmentation

Top down

Bottom up

FragmentationSlide6

Correlations between modifications

Top down

Bottom upSlide7

Alternative Splicing

Top down

Bottom up

Exon

1

2

3Slide8

Top down

Kellie et al., Molecular BioSystems 2010

Protein

mass spectra

Fragment

mass spectraSlide9

Protein Complexes

A

B

A

C

D

Digestion

Mass spectrometrySlide10

Sowa et al., Cell 2009

Protein Complexes – specific/non-specific bindingSlide11

Protein Complexes – specific/non-specific binding

Choi et al., Nature Methods 2010Slide12

Tackett et al. JPR 2005

Protein Complexes – specific/non-specific bindingSlide13

Analysis of Non-Covalent Protein Complexes

Taverner et al., Acc Chem Res 2008Slide14

Non-Covalent Protein Complexes

Schreiber et al., Nature 2011Slide15

More / better quality interactions

Affinity Capture Optimization Screen

+

Cell extraction

Lysate

clearance/

Batch Binding

Binding/Washing/Eluting

SDS-PAGE

Filtration

LaCava

,

Hakhverdyan

,

Domanski

,

RoutSlide16

Over 20 different extraction and washing

conditions ~ 10 years or art.(41 pullouts are shown)

Molecular Architecture of the NPC

Actual model

Alber

F. et al. Nature (450) 683-694.

2007

Alber

F. et al. Nature (450) 695-700.

2007Slide17

Cloning nanobodies for GFP pullouts

Atypical heavy chain-only IgG antibody produced in

camelid

family – retain high affinity for antigen without light chain

Aimed to clone individual single-domain VHH antibodies against GFP – only ~15

kDa

, can be

recombinantly

expressed, used as bait for pullouts, etc.To identify full repertoire, will identify GFP binders through combination of high-throughput DNA sequencing and mass spectrometry

VHH clone for recombinant expressionSlide18

Cloning

llamabodies for GFP pullouts

Llama GFP immunization

Lymphocyte

total RNA

Crude serum

VHH

amplicon

454 DNA sequencing

RT / Nested

PCR

IgG

fractionation &

GFP affinity

purification

VHH DNA sequence library

GFP-specific

VHH fraction

LC-MS/MS

GFP-specific

VHH clones

Bone marrow aspiration

Serum bleed

500

400

300

1000

bp

No. of Reads

Read length (

bp

)

VH

VHH

Fridy

, Li

,

Keegan,

Chait

, RoutSlide19

CDR3: 100.0% (14/14); combined CDR: 100.0% (33/33); DNA count: 10

MAQVQLVESGGGLVQAGGSLR

LSCVASGRTFSGYAMGWFR

QTPGRER

EAVAAITWSAHSTYYSDSVK

DR

FTISIDNTRNTGYLQMNSLKPEDTAVYYCTVRHGTWFTTSRYWTDWGQGTQVTVS

CDR3: 100.0% (14/14); combined CDR: 72.7% (24/33;

DNA count: 1

MADVQLVESGGGLVQSGGSRTLSCA

ASGRVLATYHLGWF

RQSPGRER

EAVAAITWSAHSTYYSDSVK

GR

FTISIDNARNTGYLQMNSLKPEDTAVYYCTVRHGTWFTVSRYWTDWGQGTQVTVS

CDR3: 100.0% (14/14); combined CDR: 72.7% (24/33); DNA count: 1

MAQVQLVESGGALVQAGASLSVS

CAASGGTISKYNMAWFRR

APGRER

EAVAAITWSAHSTYYSDSVK

DR

FTISIDNTRNTGYLQMNSLKPEDTAVYYCTVRHGTWFTTSRYWTDWGQGTQVTVS

CDR3: 100.0% (14/14); combined CDR: 42.4% (14/33); DNA count: 1

MAQVQLEESGGGLVQAGDSLT

LSCSASGRTFTNYAMAWSRQA

PGKE

RELLAAIDAAGGATYYSD

SVKGR

FTISIDNTRNTGYLQMNSLKPEDTAVYYCTVRHGTWFTTSRYWTDWGQGTQVTVS

CDR3: 100.0% (14/14); combined CDR: 42.4% (14/33); DNA count: 1

MAQVQLVESGGGRVQAGGSLTL

SCVGSEGIFWNHVMGWFR

QSPGKDREFVA

RISKIGGTTN

YADSVKGR

FTISIDNTRNTGYLQMNSLKPEDTAVYYCTVRHGTWFTTSRYWTDWGQGTQVTVS

CDR1

CDR2

CDR3

Underlined regions are covered by MS

Rank sequences according to:

CDR3 coverage; Overall coverage;

Combined CDR coverage; DNA counts;

Identifying full-length sequences from peptidesSlide20

Sequence diversity of 26 verified

anti-GFP nanobodies

Of ~200 positive sequence hits, 44 high confidence clones were synthesized and tested for expression and GFP binding: 26 were confirmed GFP binders.

Sequences have characteristic conserved VHH residues, but significant diversity in CDR regions.

FR1

CDR1

FR2

CDR2

CDR3

FR3

FR4Slide21

HIV-1

gp120

Lipid Bilayer

gp41

MA

CA

NC

PR

IN

RT

RNA

Particle

Genome

env

rev

vpu

tat

nef

3

LTR

5

LTR

vif

gag

pol

vpr

CA

MA

NC

p6

PR

RT

IN

gp41

gp120

9,200 nucleotidesSlide22

Genetic-Proteomic Approach

Tagged Viral Protein

Tag

Protein Complex

SDS-PAGE

*

Mass SpectrometrySlide23

I-Dirt

for Specific Interaction

3xFLAG Tagged HIV-1

WT HIV-1

Infection

Light

Heavy

(

13

C labeled Lys, Arg)

1:1 Mix

Immunoisolation

MS

I-DIRT

=

I

sotopic

D

ifferentiation of

I

nteractions as

R

andom or

T

argeted

Lys

Arg

(+6 daltons)

(+6 daltons)

Modified from Tackett AJ

et al

., J Proteome Res. (2005) 4, 1752-6. Slide24

IDIRT and Reverse IDIRT

Env-3xFLAG

Vif-3xFLAG

Luo

, Jacobs, Greco, Cristae,

Muesing

,

Chait

, RoutSlide25

Protein Exchange

Vif-3F

Heavy labeled Vif-3F lysate

IP in heavy labeled Vif-3F lysate

Vif-3F

Light labeled

wt

lysate

Incubation with light labeled

wt

lysate

Vif-3F

15min

Vif-3F

5min

Stable

Interactor

Vif-3F

Interactor

with fast exchange

60min Slide26

Env

Time Course SILACDifferentially labeled infection harvested at early or late stage of infection

Distinguish proteins that interact with

Env

at early or late stage during infection

Early during infection

Late during infectio

n

Light

Heavy

(

13

C labeled Lys,

Arg

)

1:1 Mix

Immunoisolation

MS

Early

interactor

Late

interactorSlide27

M/Z

Peptides

Fragments

Fragmentation

Proteolytic

Peptides

Enzymatic Digestion

Protein

Complex

Chemical Cross-Linking

MS

MS/MS

Isolation

Cross-Linked

Protein Complex

Interaction Partners by

Chemical Cross-LinkingSlide28

M/Z

Peptides

Fragments

Fragmentation

Proteolytic

Peptides

Enzymatic Digestion

Protein

Complex

Chemical Cross-Linking

MS

MS/MS

Isolation

Cross-Linked

Protein Complex

Interaction Sites by

Chemical Cross-LinkingSlide29

Cross-linking

protein

n peptides with reactive groups

(n-1)n/2 potential

ways to cross-link peptides pairwise

+ many additional uninformative forms

Protein A +

IgG

heavy chain 990 possible

peptide pairs

Yeast NPC

˜

10

6

possible

peptide pairsSlide30

Protein

Crosslinking

by Formaldehyde

~1%

w/v

Fal

20 – 60 min

~0.3%

w/v

Fal

5 – 20 min

1/100 the volume

LaCavaSlide31

Protein

Crosslinking

by Formaldehyde

RED:

triplicate experiments,

FAl

treated

grindate

BLACK:

duplicated experiments, FAl treated cells (then ground)SCORE: Log Ion Current / Log protein abundance

Akgöl

, LaCava,

RoutSlide32

Cross-linking

Mass spectrometers have a limited dynamic range and it therefore important to limit the number of possible reactions not to dilute the cross-linked peptides.

For identification of a cross-linked

peptide pair,

both peptides have to be sufficiently long and required to give informative fragmentation.

High mass accuracy MS/MS is recommended because the spectrum will be a mixture of fragment ions from two peptides.

Because the cross-linked

peptides

are often large,

CAD is not ideal, but instead ETD is recommended.Slide33

Phosphopeptide identification

mprecursor = 2000 Da

D

m

precursor

= 1 Da

D

mfragment = 0.5 DaPhosphorylation

Localization of modificationsSlide34

Localization (d

min=3)

m

precursor

= 2000 Da

D

m

precursor

= 1 Da

D

m

fragment

= 0.5 Da

Phosphorylation

d

min

>=3 for 47% of human tryptic peptides

Localization of modificationsSlide35

Localization (d

min=2)

m

precursor

= 2000 Da

D

m

precursor

= 1 Da

D

m

fragment

= 0.5 Da

Phosphorylation

d

min

=2 for 33% of human tryptic peptides

Localization of modificationsSlide36

Localization (d

min=1)

m

precursor

= 2000 Da

D

m

precursor

= 1 Da

D

m

fragment

= 0.5 Da

Phosphorylation

d

min

=1 for 20% of human tryptic peptides

Localization of modificationsSlide37

Localization

(d=1*)

m

precursor

= 2000 Da

D

m

precursor

= 1 Da

D

m

fragment

= 0.5 Da

Phosphorylation

Localization of modificationsSlide38

Peptide with two possible modification sites

Localization of modificationsSlide39

Peptide with two possible modification sites

MS/MS spectrum

m/z

Intensity

Localization of modificationsSlide40

Peptide with two possible modification sites

MS/MS spectrum

m/z

Intensity

Matching

Localization of modificationsSlide41

Peptide with two possible modification sites

MS/MS spectrum

m/z

Intensity

Matching

Which

assignment

does

the data support?

1

,

1

or

2

, or

1

and

2

?

Localization of modificationsSlide42

AAYYQK

Visualization of evidence for localization

AAYYQKSlide43

Visualization of evidence for localizationSlide44

Visualization of evidence for localization

3

2

1

3

2

1Slide45

Estimation of global false

localization rate using decoy sites

By counting how many times the

phosphorylation

is localized to amino acids that can not be

phosphorylated

we can estimate the false localization rate as a function of amino acid frequency.

Amino acid frequency

False localization frequency

YSlide46

How much can we trust a

single localization assignment?

If we can generate the distribution of scores for assignment 1 when 2 is the correct assignment, it is possible to estimate the probability of obtaining a certain score by chance for a given peptide sequence and MS/MS spectrum assignment.

Slide47

Is it a mixture or not?

If we can generate the distribution of scores for assignment 2 when 1 is the correct assignment, it is possible to estimate the probability of obtaining a certain score by chance for a given peptide sequence and MS/MS spectrum assignment.

Slide48

1

and

2

1

1

or

2

Ø

Localization of modificationsSlide49

Proteomics Informatics –

Protein characterization: post-translational modifications and protein-protein interactions 

(Week 10)