Proteomics and its applications Proteomics involves the analysis of the entire complement of proteins in a cell, tissue or organism. It assesses protein activities, modifications, localization and interactions. Proteomics uses techniques like gel electrophoresis, mass spectrometry and liquid chromatography to separate and identify proteins. These techniques can be applied to discover disease biomarkers, develop diagnostic tools, and gain insights into disease pathogenesis and treatment. Proteomics has applications in studying various diseases including cancer, diabetes and infections. It provides insights into cellular processes and systems biology.

1. Proteomics and its applications
Ravi Kumar, PhD

2. Proteomics
• The analysis of the entire protein complement
in a given cell, tissue, body fluid and organism
• Proteomics assesses activities, modifications,
localization, and interactions of proteins in
complexes.

3. Genomics Transcriptome Proteomics
Introduction

4. • Proteome indicates the total proteins expressed by a genome in a cell or tissue
• Proteomics is increasingly being used to discover potential biomarkers
noninvasively.
• Biomarkers detection might allow identification of patients who would benefit
from further evaluation.
• With the development of proteomic techniques, proteome analysis provides a
fast, non-invasive diagnostic tool for patients with various diseases.
• The advent of highly sensitive proteomic technologies can identify proteins
associated with development of diseases well before any clinically identifiable
alteration.
• MS has a high resolving power and identifies proteins with more accuracy
• Proteomic technologies can be applied for an un-biased examination to detect
novel biomarkers that could play a critical role in disease diagnostics, treatment
monitoring and prognosis.

5. History of proteomics
• SDS-PAGE discovered by Laemmli in 1970.
• O’Farrell (1975) applied IEF to protein samples
prior to SDS-PAGE to pioneer the concept of 2-
DE.
• JJ Thomson (1913) identified M/Z ratio
• Hillenkamp (1988) developed MALDI-MS.
• Fenn (1988) developed ESI-MS
• In 1993, Henzel et al. reported the first work
related to the identification of protein from the
2DE.
• Marc Wilkins coined the word ‘proteome’ in
1995 PROTEins complement of the genOMICS

6. 2002 Nobel Prizes in
Chemistry
Mass spectrometry for macromolecules
"for their development of soft desorption
ionisation methods for
MS analyses of biological macromolecules"
Koichi Tanaka John B. Fenn

7. Proteomics objectives
Protein/peptide separation
Identification and characterization of resolved
proteins by MS
Data analysis and applications.

8. Experimental Work flow
Protein identification
(Sequest & Mascot)
Proper sample collection and storage
Sample pre-processing
Protein identification LC-MS/MS
Immuno depletion/protein concentration etc
In gel Tryptic digestion/ in-solution digestion
Bioinformatic Analysis
Protein separation by
1D SDS-PAGE/ 2DE
Or
Fractionation by LC

9. Proteomic techniques
• Gel based
– SDS-PAGE
– 2-DE
• Off gel base
– LC (SCX, RP-LC, Immuno affinity)
• Quantitative proteomics
– iTRAQ, ICAT, SILAC
• MS
– MALDI, LC-MS, SLDI, CE-MS

10. Data bases
• Data analysis search engines
• Sequest
• MASCOT
• X tandam
• Peaks
• Protein data bases
• NCBS
• Swiss port

11. protein separation by SDS-PAGE
• SDS

12. • What is SDS-PAGE?
– SDS-PAGE a type of gel electrophoresis.
• What is the purpose of doing gel
electrophoresis?
– It has been seen that by running a gel we are able
to identify more proteins from the sample.

13. • An electric current is applied across the gel, causing proteins
will differentially migrate based on their molecular mass.
• Staining will be done by using Coomassie Blue dye R-250,
colloidal CBB G-250, Sypro ruby and silver stain
• periodic acid-Schiff (PAS), will be used to detect
glycoproteins.

14. 2-DE• Proteins separates based on
• PI
• MW
“You’ve got one protein missing …”
“No, you’ve one extra protein !”

15. LC
• RP-LC

16. • SCX

17. • Immuno affinity

18. Mass Spec Principles
Ionizer
Sample
+
_
Mass Analyzer Detector
ESI
MALDI
Quadrupole (Q)
Iontrap (LT, Orbitrap)
TOF
FT -ICR
Micro channel plate
detector

19. Importance of Proteins
• they serve as catalysts that maintain metabolic processes in the cell.
• they serve as structural elements both within and outside the cell.
• they are signals secreted by one cell or deposited in the extracellular
matrix that are recognized by other cells.
• they are receptors that convey information about the extracellular
matrix to the cell.
• they serve as intracellular signaling components that mediate the effects
of receptors.
• they are key components of the machinery that determines which genes
are expressed and whether mRNAs are translated into proteins.
• they are involved in manipulation of DNA and RNA through processes
such as: DNA replication, DNA recombination, RNA splicing or editing.

20. applications
• What is Omics good for?
• WHAT? Biomarker / Drug target
• Establishing and mining proteome from
different species

21. • At least 200 different PTMs have been
identified.

22. • Expression proteomics
• Functional proteomics
• Mining: identification of proteins (catalog
the proteome)
• Protein-expression profile: identification of
protein interest in a particular state of the
tissue/organism
• Protein-network mapping: protein
interactions in living systems
• Mapping of protein modifications: how and
where proteins are modified.

23. Sample
collection
Proteins
extraction
Proteomic
analysis
Bioinformatics
analysis
Proteomic discovery
Less number of
sample size
Discovery
Detect multiple biomarker candidates
Biomarker discovery
Validation phase
Discovery phase
More number of
sample size
validation
Functional study
Diagnostics and
therapeutics use
Confirmation of biomarker panels in
test patient populations
Identification
The Biomarker Discovery Process

25. • Proteomic applications in Diabetes
• Helps in protein changes duo to glycation
• molecular mechanisms underpinning disease
processes and the effects of treatment
• To understand the impact of: stress,
environmental stimuli, food, genetic and obesity,
etc.
• Tissue proteomics to understand pathophysiology
and drug target.
• Helps in early diagnosis of diabetic
complications.
• identifying new targets for therapeutic
development.

26. • Identification of surrogate markers looking at the
plasma/urine/tissue proteome at different stages
of development of diabetes, its complications.
• To study the signal transduction network of the
insulin receptor and/or other cell surface
receptors.
• Characterization of the proteome or a subset of
the proteome of animal and cell models
• Identification of novel signaling molecules and
pathways involved in cell development,
differentiation, communication, function and
destruction, etc.
• for studying the regulation, synthesis, secretion,
and action of hormones and cytokines

27. • Proteomic applications in Cancer
• Proteins serve as hallmark for the
physiological status of cell
• The ability of physicians to effectively treat
cancer is directly dependent on their ability
to detect cancers at their earliest stages.
• Proteomic technologies hold recently great
promise in the search of new biomarkers for
the early detection and the discovery of new
therapeutic targets.

28. • Proteomics technologies to identify unique
biosignatures and biomarkers responsible for the
diagnosis, prognosis and therapeutic prediction
of such disease.
• Biomarkers found in blood, other body fluids, or
tissues that are a sign of a normal or abnormal
process, or disease. They may also be used to see
how well the body responds to a treatment for a
disease or condition.

29. • Other diseases
• Pancreatitis
• Tress induced poteomics
• Eye disease
• Cardiac diseases
• Smoking
• GI diseases
• Eclampsias
• Prostaties ,
• Infections,
• Autoimmune diseases, etc….

30. System biology
• Body fluids
• Blood cells
• Erythrocytes
• Leukococytes
• Monocyttes/macrophages
• Lymphocytes
• Platelet
• Plasma and serum
• Urine
• Amniotic fluid
• Cerebrospinal fluid
• Synovial fluid
• Saliva
• Sweat
• Tears
• Semen
• Etc…
• Solid tissues
• Heart
• Brain
• Thyroid
• Muscle
• Malignant
• Tissue culture
• Malignant cells
• Bacterial proteins

31. Proteins classes for Analysis and
characterization
• Membrane
• Soluble proteins
• Nuclear
• Chromosome-associated
• Phosphorylated
• Glycosylated
• Complexes

33. • genome alone is not sufficient for a complete
understanding of complex biological
processes.