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Summary Partim Van Ostade: Concepts of Protein technology and applications €8,99   In winkelwagen

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Summary Partim Van Ostade: Concepts of Protein technology and applications

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Full summary and notes on the part of the course Concepts of Protein technology and applications given by prof. Van Ostade. Separate document online for the part taught by prof. Boonen! The course Concepts of Protein technology and applications () is the updated version of the course proteomic...

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  • 20 december 2021
  • 52
  • 2021/2022
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Concepts of Protein Technology & Applications:
v. Ostade
- Theory 30 hrs. (15/20) & Practicum 25 hrs. (5/20)
- Demonstration of mass spectrometer in December
- Article about proteomics: read and understand -> bring it to the exam!
- ‘Refresh’ lesson?
- 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 1-2 questions: article (10 points)
- Not successful in part prof. Maudsley or Van Ostade (< 8/20) -> no credits!


Introduction
Definition Proteomics:
Determination of the complete set of proteins that is present in a system, under specific
circumstances
System: Circumstances:
- Protein complex - Treatment (e.g. chemo, hormones..)
- Subcellular compartment - Time after treatment
- Cell - Condition of the cell (age, normal, infected, tumor…)
- Tissue - …
- Organism
Why proteomics?
Various reasons:

1. Compared to genomics, proteomics is ‘the real thing’

Proteins are the work horses from the cell and perform the work. The genes contain the information
but the real work happens because of the proteins. And these can change a lot: they can be
modified, they can interact… They are diverse in their function which gives information on the state
of the cell. Suppose you have a motorcycle and you know all these parts = genomics. But these parts
assemble and interact with each other = proteomics.

Genome sequencing:
- Humans have +- 20.000-40.000 genes, yeast 6000, plant 26.000, Drosophila 13.000
- Its still difficult to predict genes: verification of gene product by proteomic analysis =
necessary
 Proteogenomics

2. mRNA vs. protein profiling

mRNA sequencing gives information on expression levels of mRNA. BUT there is not always a direct
correlation between the amount of expressed mRNA and the abundancy of that particular protein.
There are situations where a low level of mRNA gives a high abundancy of proteins or vice versa.

, There is no diagonal line so no direct
correlation between mRNA and protein
profiling.

3. More (6-8) proteins per gene

3.1 Posttranslational modifications (PTMs)

A protein can be chemically modified after it is synthesized. This can be done in several ways:
glycosylation, phosphorylation, methylation, acetylation, acylation, ubiquitination, …



3.2 Alternative splicing -> isoforms

A produced mRNA can be spliced or alternative spliced which
give other proteins resulting from the same gene. α-1-
antitrypsin can be spliced into 22 different isoforms.



4. Protein interaction networks

= Higher order of complexity without drastic increase of number of components.

Genes normally don’t interact with each other. Proteins interact with each other all the time. At least
78% of yeast proteins is involved in complex. Most cellular processes are regulated by protein
complexes instead of individual proteins. You can study a protein and determine the expression level
but as long as you study it individually, the results won’t be very valuable.

Functional proteomics: definition of protein as an element in an interaction network (‘contextual
function’), rather than ascribing it to one function.




5. 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.

, All these features cannot be predicted by genome sequencing  proteomics.

Proteomics as a part of systems biology
Proteins can change all the time. We must perform several studies to know the states of this protein,
and integrate the results of these studies to have a realistic idea of the behaviour of the proteome in
the cell. In order to understand the dynamic complexity of an organism, an integrated image of all
aspects of proteins needs to be developed:
1 First off, we can study mRNA profiles and protein profiles and investigate how these change over
time, e.g. during development or changing conditions (e.g. pathological). And see how the abundancy
of the mRNA or protein change over time.

Secondly, another possibility is to study the state and properties of the proteins over time:
- Posttranslational modifications
- Cellular localization
2 - Binding of ‘metabolomic’ ligands: e.g. haem ring, metal ions, glucose, ATP, ADP, GTP,GDP…
- Alternative splicing forms
- Proteolytic degradation: synthesis, localization and activity of proteases are regulating
factors
- Oligomeric state and contribution in complexes
- Structure, conformation and allosteric mechanisms
3 Third, we can study all protein-protein interactions in space and time in one cell.

 together with genomic and metabolomic data (in space and time) we can try to form system
biology

Together: ‘shotgun’ proteom
The different faces of proteomics You identify many proteins
1. Proteomics sensu strictu quantify them at the same ti
Large scale identification and characterization of proteins, inclusive You know which are present
their posttranslational modifications: list of which proteins are present you can compare e.g. a hea
and a cancer cell: which prot
2. Differential proteomics
are upregulated, compare PTM
Large scale comparison of protein expression levels: most used
3. Cell-mapping proteomics
Protein-protein interaction studies


Identification of proteins: principle

, 1. Sample preparation
You can have a good mass spectrometer but if your sample is not prepared carefully, your results
won’t be any good. It’s important to make a good design of what you’re going to do.

1. Break up tissues or cells, extract protein fraction
2. Modification of proteins for further analysis
a. Denaturation, reduction,…
b. Dependent on forthcoming methods for separation/purification and identification
3. Important variables that determine the success of separation/purification and identification:
a. Method of cell lysis, type of detergent, pH, temp, proteolytic degradation (protease
inhibitors)…
4. In many cases: trial and error

You must prepare the proteins for mass spectrometry analysis. Most MS can only deal with smaller
protein parts: peptides. You can cut the proteins into peptides by protease treatments. The most
used protease treatment is trypsin. It only cuts at the C-terminal end of a Lys and Arg residue.

Chymotrypsin cuts at the C-terminal of large hydrophobic residues (Tyr, Phe, Trp): smaller pieces.


2. Separation of proteins/peptides
If you want to separate proteins you need to detect them, which can be very difficult since the
amount of cellular material that gives you a certain amount of protein is very small. If you use 100
million cells you get 10 mg of material. If you want to detect a protein with 10 protein copies/cell you
can’t see it by gel electroforese, Coomassie or Silver staining. With 1000 protein copies/cell you will
only see it by silver staining, if there are 100.000 protein copies you can see it also by Coomassie. It is
thus very difficult to detect low abundant proteins. Proteomics goes into the fM and sometimes aM
range.




In plasma the protein concentrations vary by 11 orders of magnitude. You have very abundant
proteins like Hb, but you have proteins that are very low abundant, like interleukins.

To separate proteins, you can use several separation methods. Every separation method has a peak
capacity: the maximum amount of peaks you can have in a certain separation. By using two methods
that make use of different physical or chemical characteristics you use orthogonal methods. This
enables you to multiple the peak capacity of both methods. If you use three methods you can
multiple three peak capacity. This enables you to get a very high peak capacity for a chromatographic
system that uses N-techniques for separation. In most of the situation we use 2D separation multiple
times.

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