Introduction to Quantitative and Targeted Proteomics

Maciej LalowskiHiLIFE, Meilahti Clinical Proteomics Core Facility

University of Helsinki, FinlandFinnish Proteomics Society, President

Aalto University25.03.2019

1

Schematic representation of proteomic approaches

Gregorich, Z. R.; Chang, Y. H.; Ge, Y. Pflugers Archiv-European Journal of Physiology 2014, 466, 1199-12092

Schematic representation of quantitative proteomic approaches

Journal of Clinical and Translational Hepatology 2014 ;2(1): 23-303

Top-down: Two-dimensional gelelectrophoresis (2-DE)

• 1st dimension: IEF;Proteins areseparated accordingto their isoelectricpoint (IP)

• 2nd dimension: SDS-PAGE, Proteins areseparated accordingto their molecularweight

• Efficient: More than2000 proteinsresolved in E. Coli celllysates and ~8000 inbrain lysates

pH 10

SDS-

PAG

E

pH 3

4

pI 6.94.1

Mr(kDa)

200

15

About 2000 proteins

Phosphorylations?Glycosylations?Other types of PTMs?

Protein fingerprint (2-DE)

5

Protein quantitation (2D-DIGE)

6

2D-DIGE laboratory workflow

Bebek et al. J Nutritional Biochemistry 2014

7

Quantitate: pros and cons

© 2012 SlideShare Inc. 8

Plasma proteome challenge

Identification of 1,442 proteins in plasma that span more than 6logs of protein abundance as determined by mass spectral countsand independent assays of a subset of proteins identified in astudy of plasma from a pancreatic cancer mouse mode.

9

Mass spectrometry principles

Data Dependent AcquisitionData Independent AcquisitionSingle Reaction Monitoring

Fragmentation

Fragmentation

Fragmentation

Most abundant precursor ions

All precursor ions

Predefined precursor ionQ1 Q2 Q3

10

© 2012 SlideShare Inc. 11

SILAC- Stable isotope labeling with amino acids in cell culture

One of the cell populations is fed with growth medium containing normal amino acids (State A). In contrast, the second(third) population is fed with growth medium containing amino acids labeled with stable (non-radioactive)heavy isotopes (B-C). The medium can contain f.ex. Arg labeled with six 13C instead of the normal 12C or 2H4-lysine(Lys4). From ratios we calculate the relative protein abundance.

Geiger T, et al., Nature protocols (2011) . https://www.biochem.mpg.de/221777/SILAC 12

Different variants of SILAC for the analysis of cellularproteome dynamics

SILAC can be used to quantify differences in steady-state protein levels, measuredifferences in protein synthesis and reveal protein turnover (courtesy of M. Selbach, MDC).

13

Metabolic labeling

Drawbacks: unpredictable mass shifts induced by total 15N labeling14

iTRAQ-isobaric tags relative abundance quantitation

iTRAQ uses stable isotope labeled molecules that can be covalently bonded to theN-terminus and side chain amines of proteins. 4-, 8, 10- plex quantitiation

15

ICAT- isotope-coded affinity tags quantitation

ICAT reagent pairs are Cysteine-binding tags that differ in molecular weightby use of hydrogen or carbon isotopes

16

Enzymatic 18O label workflow

Pros:Ø Can apply to virtually any sample

type including clinical samples,Ø Peptides labeled by 16O and 18O co-

elute from the RP chromatographiccolumns which allows for accuratequantification,

Ø Amendable to low sampleconcentration

Cons:Ø Only 2 samples can be compared

to each other at one time,Ø Difficulty accommodating complex

experimental design,

http://proteomics.case.edu/proteomics/17

Overview of the label-free quantitative MS experimental workflow

Label-free quantitative proteomics can be divided into two approaches; spectral counting (SC) and AUCmeasurement (AUC). Spectral TIC combines features of both SC and AUC approaches.

Neilson KA et al, Proteomics 2011 Feb;11(4):535-53 18

Schematic representation of the two different label-freeapproaches

In the spectral-counting approach peptide and protein abundances can be estimated based onthe number of acquired peptide spectrum matches. In the ion-intensity-based approach thechanges of peptide abundances are determined by measuring and comparing thechromatographic peak areas of the corresponding peptides.

Megger DA et al, BBA 2013 Aug;1834(8):1581-90 19

TMT- tandem mass tags

The recent extension of TMT multiplexing to 10 conditions has beenenabled by utilizing neutron encoded tags with reporter ion m/z differences

of 0.0063 Da

Wu et al., Nature.2013, 499(7456):

79–82

20

CMT approach generates multiples reporter ion series forincreased quantitative information

Braun CR et al, Anal. Chem. , 2015, 87 (19), 9855–9863. 21

Peak intensity is the intensityat the highest point of the MS1peak for a peptideMS product ion abundance(MS2 intensities)

22

Mass spectrometry principles

Data Dependent AcquisitionData Independent AcquisitionSingle Reaction Monitoring

Fragmentation

Fragmentation

Fragmentation

Most abundant precursor ions

All precursor ions

Predefined precursor ionQ1 Q2 Q3

23

Courtesy of Bruno Domon 24

MRM analysis of Aß17-28 peptides from the brain

Analytical 2µm Acclaim PepMap RSLC C18, 75µm x 250mm column (Thermo™). Linear gradient of 3 to 35% of 0.1% FA/ACNon a QTRAP 6500+ (SCIEX™).

Four different labelling statuses of Ab17-28 peptide, i.e.unlabeled, Lys U-13C6; U-15N2, uniformly labelled 15N and Lys-13

can be detected.

25

Complementarity of unbiased and biased approaches tophosphoproteomics for understanding cell signal pathways

Stuart J. Cordwell, and Melanie Y. White Circulation. 2012;126:1803-1807

Copyright © American Heart Association, Inc. All rights reserved.

Ø Novel (N)Ø Known (K)Ø Abs against known

sites (W) ofPhosphorylation

Ø SRM/MRM usesunique precursorand fragment ionpairs (transitions)to specificallytarget peptidescontaining sites ofinterest (S) tocomplete pathwaymapping.

26

MRM in clinical medicine (examples)

Ø The quantification of proteins in the cerebrospinal fluid toaid understanding of the later stages of multiple sclerosis(26 markers of progressive MS)

Ø The development of quantitative validation techniquesfor plasma biomarkers (LOQ in low ng/ml, appropriate forserum biomarkers)

• The demonstration of robust targeted assays for cancerassociated protein quantification in both plasma andurine samples from patients (over 1,000 cancer-associated proteins in both serum and urine, confirmedELISA results for ApoA1, transferrin, β2-microglobulinand TTR)

27

Courtesy Christina Ludwig et al., TU Munich 28

Courtesy Christina Ludwig et al., TU Munich 29

Ø The mission of FinnProt

ØMake proteomics research readily available for the largescientific community in Finland,ØPromote research and education in proteomics and protein

chemistry (scholarshisps/organizing the events)ØAct as the official Finnish collaborative body to international

proteomics organizations (EuPA),

FinnProt was founded in 2004

Finnish Proteomics Society FinnProt

More info on FinnProt from http://www.finnprot.fi/

30