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Summary concepts of protein technology

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Summary of the course concepts of protein technology given by Xaveer Van Ostade & Kurt Boonen (for all master students BMW)

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Summary concepts of protein technology & applications
Introduction
• EXAM: Article → read it + know every step from the article for the exam (but you can bring it
with you for the exam)
• Examination: Written
– ± 5 questions:
o 2 questions (Prof. Boonen), may include an exercise (15 points)
o 2 questions (Prof. Van Ostade), may include an exercise (15 points)
o 1 question: article (10 points)

Definition proteomics
→ Determination of the complete set of proteins that is present in a system, under specific
circumstances:
• System can be different:
– Protein complex
– Subcellular compartment
– Cell
– Tissue
– Organism → e.g. yeast, drosophila…
• But the circumstances can be different
– Treatment → Cells can be treated with kurkuma, this can be done for 30 minutes, but
also for 4 days
– The time after treatment can also be different
– The condition of the cell (age, normal, infected, tumor)
– …

Why proteomics
→ Different reasons

Compared to genomics, proteomics is “the real thing”
• Proteins are the workhorses of the cell
– Motorcycle contains many parts
o The list is the genome → but these words mean nothing → need to be
translated to these different words → these words need to work together =
proteins → then you can drive your motorcycle
• Genome sequencing
– Estimation: humans ± 20-40.000 genes, yeast 6000, Drosophila 13000, Caenorhabditis
18.000, plant 26.000
– Still difficult to predict genes: verification of gene product by proteomic analysis is still
neccessary.
o Human almost have the same number of genes as other species → and yet we
think we are more complex
→ “proteogenomics”

mRNA vs. protein profiling
• mRNA at a low abundance, high protein expression (and vice versa)
– A lot of cells have a high amount of mRNA but not a lot of proteins or visa versa
– The amount of mRNA not always correlate with the amount of proteins → microarrays
/ RNA seq are insufficient to measure protein expression

, • Left: mRNA is expressed a a high level, yet no proteins are produced
• Right: some proteins are expressed, but a low amount of mRNA is present for these proteins

More (6-8) proteins/gene
• Posttranslational modifications (PTMs)
– Many more proteins can come from one gene → after translation the protein is
chemically modified (this has a function)
– A RNA is translated into a protein but this protein can differ by heaving attach different
posttranslational tags
o Phosphorylation, glycosylation…
o Many ways to modify the protein
– To make to distinction we need to develop proteomic technics that make the difference
between the two and also to identify the post translational modifications
• Alternative splicing → isoforms
– Due to different splicing, different proteins can be made of the same mRNA molecule
– One gene can slice
o Normal splicing: after translation → protein
o Alternative splicing: some parts of the proteins could be missing or you have
additional parts

Protein interaction networks
→ Protein is almost never working on its own → they are working in complexes
→ proteins needs to interact with each otjer → important to know how cells work, live, how they react
on medicines, etc.
• Higher order of complexity without drastic increase of number of components. About 78% of
yeast proteins is involved in complex.
• Most cellular processes are regulated by protein complexes instead of individual proteins.
• Functional proteomics: definition of protein as an element in an interaction network
(‘contextual function’), rather than ascribing it to one function.

Cellular localization
• Depending on the biological state of the cell, a protein can be localised in one or different
cellular locations (nucleus, cytosol, plasma membrane mitochondria, ER…).
• Different binding partners in different locations → One protein can have several functions,
depending on the localisation in the cell.
– Protein coming from mRNA; it can occur in the nucleus or it can interfere at the
membrane → two different functions for one protein

,→ All these features cannot be predicted by genome sequencing ➔ proteomics !!

Proteomics as part of systems biology
• In order to understand the dynamic complexity of an organism, an integrated image of all
aspects of proteins needs to be developed (so far only the average of all possible states is
measured):
• If we have a cell under certain circumstances and we want to know which circumstances these
are then we want to know which events play in the cell (on the proteome level and a nucleic
acid level) → we bring all the knowledge to
– mRNA and protein profiles and how these change over time, e.g. during development
or changing conditions (e.g. pathological).
– Knowledge of the state and properties of all proteins:
o Posttranslational modifications
o Cellular localization
o Binding of ‘metabolomic’ ligands: e.g.. haem ring, metal ions, glucose, ATP,
ADP, GTP, GDP… .
o Alternative splicing
o Proteolytic degradation . Hence, synthesis, localization and activity status of a
protease are regulating factors.
o Oligomeric state and contribution in complexes.
o Structure, conformation and allosteric mechanisms
– All protein-protein interactions in space and time in one cell.
o If we want to follow a cell during a treatment with a compound then we need
to know the protein-protein interaction
• Together with genomic and metabolomic data (in space and time) → systems biology

The different faces of proteomics
(You can divide them into 3)
• Proteomics sensu strictu
– Large scale identification and characterization of proteins, inclusive their
posttranslational modifications (‘shotgun’ proteomics)
o Shotgun proteomics → we try to identify and characterize as many proteins as
possible
• Differential Proteomics
– Large scale comparison of protein expression levels.
– Used most of the time
– If you have a healthy tissue and a cancer tissue you want to know which proteins are
upregulated or downregulated in the cancer tissue as compared with the healthy tissue
(but you can also compare infected and non-infected cells)
– Leads us to biomarkers
• Cell-mapping proteomics
– Protein-protein interaction studies

, Identification of proteins: principles
1) Protein extraction from sample
2) Optional: protein separation → then your able to identify them
- Sometimes we cut them in peptides.
- Most of the mass spectrometers work better with peptides compared
to proteins. The peptides also have to be separated.
3) Protein digestion (with a protease = usually trypsin)
4) Peptide liquid chromatografie
- separate the peptides
5) Electrospray ionization → entering the mass spectrometry
- Peptides are ionized and are coming into the gas phase
6) Optional: ion mobility
- Separate the peptides on the basis of ion mobility
7) (tandem) mass spectrometry
8) Data analysis
- Bioinformatics
o Set of tools that gives you the identification of the peptide and
the protein to which the peptide belongs
o Depending of the outcome you can choose the program that
can tell you in which pathway they are involved




1) Sample preparation
• Break up tissues or cells, extract protein fraction.
– You can separate the different proteins (not necessary)
• Modification of proteins for further analysis (denaturation, reduction etc. ). Dependent on the
forthcoming methods for separation/purification and identification.
• Important variables that determine the success of separation/purification and identification:
– Method of cell lysis, type of detergent
o Study protein-protein interaction → you cannot use strong detergents
o You need to know which detergent you can use
– pH → separate proteins
o Low pH → majority of proteins will be protonated (+) → you don’t need a strong
anion exchange column, because that is positive charged and you will have
repulsion and not separation
– Temperature → important if you want to know something about folding
– Proteolytic degradation (addition of protease inhibitors).
o Many proteins are very fragile, and are very quicky degraded by proteases
o Lyse cells → lyse nucleus, mitochondria… → proteins come together in one pool
and they see proteins that they normally never see ➔ protease inhibitors
• In many cases: trial and error, so sometimes… it is really black magic

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