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Mass Spectrophotometry and Protein Interaction Networks

Page history last edited by PBworks 13 years, 10 months ago


 

Section 1: Introduction to Mass Spectrophotometry

 

Over the past decade, mass spectrometry has undergone tremendous technological improvements allowing for its application to proteins, peptides, carbohydrates, DNA, drugs, and many other biologically relevant molecules. A mass spectrometer determines the mass of a molecule by measuring the mass-to-charge ratio (m/z) of its ion. Ions are generated by inducing either the loss or gain of a charge from a neutral species. Once formed, ions are electrostatically directed into a mass analyzer where they are separated according to m/z and finally detected. The result of molecular ionization, ion separation, and ion detection is a spectrum that can provide molecular mass and even structural information.

 

Theoretical Basis for Analyzing Mass

 

According to the Lorentz force and Newton's second law in electromagnetic field, we have the following equation.

So for different mass/charge ratio, the ions in the electromagnetic field can have different trajectories.

Solving the above two equations, we get the mass to charge ratio should satisfy:

Therefore, as different molecules have different mass to charge ratio, they follow different trajectories in the electromagnetic field. Their trajectories should also depend on their initial speed and the directions of the fields, but these can be calculated as well.

There are many types of mass analyzers, using either static or dynamic fields, and magnetic or electric fields, but all operate according to this same law. Each analyzer type has its strengths and weaknesses. Many mass spectrometers use two or more mass analyzers for tandem mass spectrometry (MS/MS). In addition to the more common mass analyzers listed below, there are other less common ones designed for special situations.

 

For the Time-of-flight (TOF) analyzer, it's just an electric field accelerating the ions through the same potential.By measuring the time they take to reach the detector, when the charge is known, the mass can be determined. If the particles all have the same charge, then their kinetic energies will be identical, and their velocities will depend only on their masses. Lighter ions will reach the detector first.

 

 

 

 

 

 

Mass spectrometry of proteins

 

Mass spectrometry is highly sensitive and versatile for studying proteins. Availability of genome sequence have also established it as a powerful tool for rapidly identify proteins from very complex biological samples. Advances in sample preparation methods and bioinformatics will continue to increase the scope of this technique for proteomics applications. It is useful for quantitative analysis of proteins as well as the characterisation of protein modifications. Comprehensive data about a system would provide mechanisms and regulatory events for cellular processes.

 

The two primary methods for ionization of whole proteins are electrospray ionization (ESI) and matrix-assisted laser desorption/ionization (MALDI). In keeping with the performance and mass range of available mass spectrometers, two approaches are used for characterizing proteins. In the first, intact proteins are ionized by either of the two techniques described above, and then introduced to a mass analyser. In the second, proteins are enzymatically digested into smaller peptides using an agent such as trypsin or pepsin. Other proteolytic digest agents are also used. The collection of peptide products are then introduced to the mass analyser. This is often referred to as the "bottom-up" approach of protein analysis.

 

Whole protein mass analysis is primarily conducted using either time-of-flight (TOF) MS, or Fourier transform ion cyclotron resonance (FT-ICR). These two types of instrument are preferable here because of their wide mass range, and in the case of FT-ICR, its high mass accuracy. Mass analysis of proteolytic peptides is a much more popular method of protein characterization, as cheaper instrument designs can be used for characterization. Additionally, sample preparation is easier once whole proteins have been digested into smaller peptide fragments. The most widely used instrument for peptide mass analysis is the quadrupole ion trap. Multiple stage quadrupole-time-of-flight and MALDI time-of-flight instruments also find use in this application.

 

 

Section 2: Protein Protein Interaction(PPI)

 

Introduction and motivation of studying PPI

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Protein-protein interactions affect all processes in a cell. Proteins rarely function in isolation. It has been proposed that all proteins in a given cell are connected through an extensive network, where non-covalent interactions are continuously forming and dissociating. The forces that are responsible for such interactions include electrostatic forces, hydrogen bonds , van der waals forces and hydrophobic effects . It is believed that hydrophobic effects drive protein-protein interactions, whilst hydrogen bonds and electrostatic interactions govern the specificity of the interface. Water is usually excluded from the contact region.

 

During the protein-protein interaction, the conserved domains physically interact with each other. Thus, understanding protein interactions at domain level gives detailed functional insights upon proteins that are either characterized or new discovered. However, unlike protein-protein interactions that can be discovered by some high throughput technologies such as two-hybrid systems, domain-domain interactions largely remain unknown.

 

 

Signals from the exterior of a cell are mediated to the inside of that cell by protein-protein interactions of the signalling molecules. This process, called signal transduction, plays a fundamental role in many biological processes and in many diseases (e.g. cancer). Proteins might interact for a long time to form part of a protein complex, a protein may be carrying another protein (for example, from cytoplasm to nucleus or vice versa in the case of the nuclear pore importins), or a protein may interact briefly with another protein just to modify it (for example, a protein kinase will add a phosphate to a target protein). This modification of proteins can itself change protein-protein interactions. For example, some proteins with SH2 domains only bind to other proteins when they are phosphorylated on the amino acid tyrosine. In conclusion, protein-protein interactions are of central importance for virtually every process in a living cell. Information about these interactions improves our understanding of diseases and can provide the basis for new therapeutic approaches.

 

Methods and Techniques to study PPI

 

As protein-protein interactions are so important there is a multitude of methods to detect them. Each of the approaches has its own strengths and weaknesses, especially with regard to the sensitivity and specificity of the method. A high sensitivity means that many of the interactions that occur in reality are detected by the screen. A high specificity indicates that most of the interactions detected by the screen are also occurring in reality.

 

 

  • Co-immunoprecipitation is considered to be the gold standard assay for protein-protein interactions, especially when it is performed with endogenous (not overexpressed and not tagged) proteins. The protein of interest is fished out of the cells with a specific antibody. Interaction partners which stick to this protein are subsequently identified by western blotting. Interactions detected by this approach are considered to be real. However, this method can only verify interactions between suspected interaction partners. Thus, it is not a screening approach.

 

  • The yeast two-hybrid screen investigates the interaction between artificial fusion proteins inside the nucleus of yeast. This approach can fish out binding partners of a protein in an unbiased manner. However, the method has a notorious high false-positive rate which makes it necessary to verify the identified interactions by co-immunoprecipitation.

 

  • Tandem affinity purification (TAP) detects interactions within the correct cellular environment (e.g. in the cytosol of a mammalian cell) (Rigaut et al., 1999). This is a big advantage compared to the yeast two-hybrid approach. However, the TAP tag method requires two successive steps of protein purification. Thus, it can not readily detect transient protein-protein interactions.

 

  • Quantitative immunoprecipitation combined with knock-down (QUICK) relies on co-immunoprecipitation, quantitative mass spectrometry (SILAC) and RNA interference (RNAi). This method detects interactions among endogenous non-tagged proteins (Selbach and Mann, 2006). Thus, it has the same high confidence as co-immunoprecipitation. However, this method also depends on the availability of suitable antibodies.

 

 

(a figure showing the principles of Y2H method)

 

 

Section 3: Properties of Protein-Protein Interaction Networks

 

Am example of yeast protein interaction network.

 

Shown above is a yeast protein protein interaction network, the PPIs are determined by the yeast two hybrid method. The proteins that can interact with each other are linked with a line, whereas the proteins that cannot interact with each other don't have an edge between them. From the graph, we can see that there are some highly connected nodes which can connect to a large number of other proteins. But the number of proteins with only a few edges are much larger.

 

This graph only tells us approximately how many proteins interact with each other, it does not provide any information on function or structure about any particular proteins in the graph.

 

Claims of properties of PPI network

According to some popular theory, the PPI network has a "power law" behavior. That is to say, as similar with the yeast PPI graph, the probability of appearance of highly connected nodes are infrequent, while the probability of appearance of less connected nodes are highly frequent. The frequency decays exponentialy with the increase of number of edges for the protein. Some theory argues that the formation of this power law property of PPI network comes from gene duplication. During gene duplication, when a new node is duplicated, it copies all the same edges that it's mother node has, therefore making the long-lived healthy proteins eventually evolve into highly connected node in the PPI graph. Although this theory so far to a large extend is only a conjecture, it has been viewed as one of the most widely accepted explainations of PPI network.

 

 

 

Some arguments and Ambiguities

Some claim that the current data for PPI is not enough for proving that this network has a power law property. The reason is most PPI graphs cover only several hundreds of proteins, therefore in the log scale, it's only two orders of magnitude or slightly more. And usually in the end of the log-log scale plot, the tail gets noisy and fluctuate was large, so it could well be just some other kind of distribution, like poission or gaussian, because of the noise and limited scale of the PPI data so far.

 

References:

References for Mass Spectrometry:

 

 

 

References for PPI:

  • Dandekar T., Snel B.,Huynen M. and Bork P. (1998) "Conservation of gene order: a fingerprint of proteins that physically interact." Trends Biochem. Sci. (23),324-328
  • Enright A.J.,Iliopoulos I.,Kyripides N.C. and Ouzounis C.A. (1999) "Protein interaction maps for complete genomes based on gene fusion events." Nature (402), 86-90
  • Marcotte E.M., Pellegrini M., Ng H.L., Rice D.W., Yeates T.O., Eisenberg D. (1999) "Detecting protein function and protein-protein interactions from genome sequences." Science (285), 751-753
  • Albert R. and Barabási A.-L., "Statistical mechanics of complex networks", Rev. Mod. Phys. 74, 47–97 (2002).
  • Amaral, LAN, Scala, A., Barthelemy, M., Stanley, HE., "Classes of behavior of small-world networks". Proceedings of the National Academy of Sciences (USA) 97:11149-11152 (2000).
  • Barabási, Albert-László Linked: How Everything is Connected to Everything Else, 2004 ISBN 0-452-28439-2
  • Barabási, Albert-László and Reka, Albert. "Emergence of scaling in random networks". Science, 286:509-512, October 15, 1999.
  • Pazos F., Valencia A. (2001). "Similarity of phylogenetic trees as indicator of protein-protein interaction." Protein Engineering, 9 (14), 609-614

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