Reference no: EM133178628

Targeted Proteomics - workflow

Within this coursework, you will be required to use a number of web-based databases and search tools to both identify and then quantify an unknown peptide.

Part 1: Peptide mass fingerprinting
You have been given a peak list generated from an MALDI MS experiment following extraction of a protein band resulting from SDS-PAGE. Trypsin was used to digest the target protein. The protein was isolated from a strain of Escherichia coliand is presented below. Outline the methodology of how peptide mass fingerprinting and database searching is utilized to help identify a protein from proteomic data sets?

• Outline the methodology of how peptide mass fingerprinting and database searching is utilized to help identify a protein from proteomic data sets?
(100 words)

By use of the MASCOT protein identification tool determine the potential ID of the target protein. Support in the use of this database will be given via the blackboard site located in the "Support Resources section".
From the data generated and a follow-up BLAST search construct a short response with details on;
• Protein putative identification with details on function?
• Probability score?
• What is the protein coverage?
• What masses went unidentified?
• What is the average mass accuracy of this mass spectrometer?
• Why do you think we missed finding some of the peptides?

(data analysis with explanation ~200 words equivalent)

Part 2: Protein identification from MS/MS data
In order to validate the putative ID from part 1, the most intence peak from the peptide fingerprinting experiment was investigated by MS/MS. You will find a text readable .mgf file containing relevant data on the blackboard site called M0001.mgf.
• Outline the minimumconsti tuents of this MASCO readable .mgf file?
By use of the MASCO protein ID tool perform a more detailed search on your target peptide. From the data generated construct a short response with details on
• Protein putative identifications?
• Probability scores?
• What was the sequences of the identified peptide?

(data analysis with explanation ~100 words equivalent)

Part 3: Relative Quantification
iTRAQ allows the relative quantification of peptides resulting from MS/MS data by recording the peak areas of reporter ions. You have each been given a data set to statistically analysis. levels of the protein of interest that have been proposed to be a modulated by treatment with a new drug. Peak areas for the relevant reporter ions have been determined to study this effect with samples taken fromculturestreated with increasing amounts of the drug. Considering the data shown in Table 1 and taking the no treatment sampleas the control, calculate the relative expression of the protein of interest in the test samples. Determine the significance the results and hence at which concentration at which the drug has a significant effect.
(data analysis with explanation ~100 words equivalent)

Part 4: Critical analysis of quantification methods
iTRAQ has been used in the example above to determine the relative abundance of the target peptide. In the following section critically compare alternative strategies for the quantification of peptide abundance in targeted and untargeted proteomics.
(500 words)