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Mass Spectrometry makes it possible to measure protein/peptide masses (actually mass/charge ratio) with great accuracy Major uses Protein and peptide identification.

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Presentation on theme: "Mass Spectrometry makes it possible to measure protein/peptide masses (actually mass/charge ratio) with great accuracy Major uses Protein and peptide identification."— Presentation transcript:

1 Mass Spectrometry makes it possible to measure protein/peptide masses (actually mass/charge ratio) with great accuracy Major uses Protein and peptide identification Identification of post translational modifications (e.g. phosphorylation, methylation) Quantitation of relative protein abundance. Requires specialized approaches (e.g isotope labeling) Amide hydrogen exchange rates

2 Mass spectrometers contain
A method for generating ionized peptides (e.g. MALDI or electrospray ionization [ESI] ) A mass analyzer (e.g. TOF, quadrupole) A detector

3 MALDI: Matirx assisted laser desorption
Advantages: Ease of use Tolerant to a range of buffers/salt Simple analysis (predominantly singly charged species)-good for complex mixtures Well-suited for TOF. Allows larger molecules to analyzed

4 Electrospray ionization (ESI) Mass Spectrometry
Advantages: Highly sensitive Multiply charged sample leads to lower m/z ratio Can be coupled directly to HPLC output (LC-MS) No matrix background (better for samples <700D)

5 “Nanospray” reduces volume increases sensitivity

6 Need Solubility in Polar Solvent (MeOH, ACN, H2O, Acetone are best)
Properties of ESI Advantages Electrospray Ionization can be easily interfaced to LC. Absolute signals from Electrospray are more easily reproduced, therefore, better quantitation. Mass Accuracy is considered better. Multiple charging is more common then MALDI. Disadvantages No Fragmentation Need Polar Sample Need Solubility in Polar Solvent (MeOH, ACN, H2O, Acetone are best) Sensitive to Salts Suppression

7 Time of flight (TOF) mass analyzers

8 Converting a mass/charge spectra into a mass

9 Quadrupole analyzers act as a “mass filter”
DC positive pole plus RF signal form a “high pass” filter

10 DC negative pole plus RF signal form a “high pass” filter
Combined they act as a mass filter

11 Protein identification from mass spectra of tryptic peptide

12 Tandem Mass Spec allows Sequencing
Step1: Select a peptide of a well defined mass Step 2: Induce fragmentation of the peptide by collision with neutral atoms Step 3: Pass through a second mass analyzer to determine the mass of the fragments

13 Sequencing by Mass Spectrometry:
Critical to the analysis is the use of computers to analyze the full spectrum and turn this quickly into a peptide sequence.

14 Outline of a strategy for identifying proteins by mass spectrometry

15 Fourier transform ion cyclotron resonance (FTICR) Mass Spec

16 Fourier transform ion cyclotron resonance (FTICR) Mass Spec
Advantages: Very sensitive Extremely accurate Disadvantages: Machines are large expensive and difficult to run

17 Orbitrap mass analyzers
Leads to similar stable oscillating orbits with frequency determined by M/Z ratio as FTICR But confinement is based on electric field instead of magnetic: cheaper, smaller, no need for superconductor magnate, liquid helium etc.

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19 Turning mass spec data into complexes
Sample

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21 Bayes Theorem

22 Example: Drug testing Pr(D), or the probability that the employee is a drug user, regardless of any other information. This is 0.005, since 0.5% of the employees are drug users. Pr(N), or the probability that the employee is not a drug user. This is 1-Pr(D), or Pr(+|D), or the probability that the test is positive, given that the employee is a drug user. This is 0.99, since the test is 99% accurate. Pr(+|N), or the probability that the test is positive, given that the employee is not a drug user. This is 0.01, since the test will produce a false positive for 1% of non-users. Pr(+), or the probability of a positive test event, regardless of other information. This is or 1.5%, which found by adding the probability that the test will produce a true positive result in the event of drug use (= 99% x 0.5% = 0.495%) plus the probability that the test will produce a false positive in the event of non-drug use (= 1% x 99.5% = 0.995%). Given this information, we can compute the probability that an employee who tested positive is actually a drug user:

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24 Receiver Operator Correspondance (ROC) curves

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