SIEVE 2.1 Proteomics Example

Transcription

1 SIEVE 2.1 Proteomics Example

2 Software Overview What is SIEVE? SIEVE is Thermo Scientific s differential software solution. SIEVE will continue to enhance our current product for label-free differential analysis platforms for all of the omics markets. Differential analysis tool that aids in discovering molecular changes between states (including but not limited to disease states and therapeutic effects). SIEVE software was designed to provide the ability to automate confidently and reproducibly, the semiquantitative measurement of differentially expressed proteins, metabolites and other compounds correlating with a disease state, drug response or other perturbation. S tatistical I terative E xploratory V isualization E nvironment It s important to note that SIEVE software is not limited to proteomics or metabolomics discovery, but supports label-free differential analysis from any type of research application (e.g. Food Safety Analysis, Protein/Peptide-based Therapeutics, etc). 2

3 Who is using SIEVE and for what applications? SIEVE enables its customers to make the world healthier, cleaner and safer. Proteomics Biomarker discovery in plasma, tissue, cell culture, urine, saliva Disulfide bond validation in purified protein Population studies of Crohn s disease in camels Quantify samples that contain their own precursor label, similar to SILAC Global evaluation of the saliva proteome as it changes with age Scanning electron microsope image of a cancerous (left) and normal cell, showing differences in cell brush. Image courtesy Igor Sokolov. Small Molecule Biomarker discovery in plasma, tissue, cell culture, urine, spit Monitoring drug degradation due to environmental stresses. Metabolomic and Lipidomic profiling Ingredient screening in Food and Safety Water purification monitoring Improving agriculture (tomatoes, whiskey, wine, corn) Acquisition quality assessment Screening purified therapeutics for environmental and/or product modifications Direct infusion of olive oil using DART, looking for impurities. And the list keeps growing 4

4 How Does SIEVE Work?

5 Software Solution for Differential Analysis Mass Frontier Structural Elucidation Pinpoint Samples LC-MS/MS GC-MS DART ProteinCenter Biological interpretation Chromatographic Alignment Mascot Proteome Discoverer Identification Search or Import Detection Local Database ChemSpider Statistical Analysis 6

6 SIEVE Analysis Platform Statistically rigorous automated label-free LC/MS differential analysis platform State 1 Raw file Reports: State 2 Raw file State Raw file Workflow Align Detect Identify Components Relative Quantification Statistical Analysis Trend information Identification Applied to: Any experiment that compares one group to another. 7

7 SIEVE Workflow Alignment Unaligned basepeaks 8

8 SIEVE Workflow Alignment Aligned basepeaks 9

9 SIEVE Workflow Frame Step1: Define Parameters Frame: a well defined rectangular region in the M/Z versus Retention Time plane. 10

10 SIEVE Workflow Frame Step2: Define Depth At this step in SIEVE the user defines how deep into the data the software will go. This parameter is always the most difficult to determine/set because it depends heavily on the datasets, instrument, and experiments. 11

11 SIEVE Workflow Frame What does a frame look like? 12

12 SIEVE Workflow Identification Step3: Identification Import Mascot Frame MW Proteome Discoverer chemspider web service Local database List of candidates 13

13 Software Walkthrough

14 Proteomics Example Files: Control_A (n=4) Sample_B (n=4) Sample_C (n=4) NSI Positive Ion full scan LC-MS LTQ-Orbitrap 60K resolution Goals: Find the exact monoisotopic MW of components that are statistically significantly different between the Control and Sample_B and Control and Sample_C. Determine peptide and protein ID s by importing SEQUEST peptide identifications from Proteome Discoverer

15 Identical Sample A Sample B Sample C 100 µg E. coli lysate 12 Total Protein Spikes - 10 Non-E. coli proteins - 2 E. coli proteins 100 µg E. coli lysate 12 Total Protein Spikes - 10 Non-E. coli proteins - 2 E. coli proteins 100 µg E. coli lysate 12 Total Protein Spikes - 10 Non-E. coli proteins - 2 E. coli proteins Spikes at Different Levels and Ratios 16

16 Carbonic anhydrase I Catalase Cytochrome c Glucose oxidase Glycerokinase Hexokinase Horseradish peroxidase Lactoperoxidase Myoglobin Serum albumin Tryptophanase Ubiquitin Quantity (pmol) E.Coli Spiked Study SIEVE 2.1 Analysis SampleA SampleB

17 Launch SIEVE 2.0 and create a new experiment 18

18 Select Chromatographic Alignment and Framing algorithm and Control Compare Trend Experiment Type then name your experiment file Click Next 19

19 Drag & drop the raw files from the ABRF folder here. Click on File Name to sort the files so they are grouped together. 20

20 Scan the raw files for details by clicking here 21

21 Files are OK Click Next 22

22 Type in group names, separate them with a space. Select one group as the ratio group or control. Select alignment reference file Click Next 23

23 Select default RT, m/z width, and mass range. M/Z width is +/- 5 ppm when the width is set to 10ppm, so don t set this too small. Click Next 24

24 Use default settings for first analysis then lower threshold and increase number of frames. Click Next 25

25 SIEVE automatically selects the full MS scan type Click Next 26

26 Defer Identification if Proteome Discoverer or Mascot results are to be imported into the software. This is done after the framing analysis is complete. If a database is to be searched using the DB LookUp select that that here. Click Next 27

27 Click Finish 28

28 Save your file Save as a.sdb file 29

29 From the processing tab, review the SIEVE processing parameters 30

30 Save your parameter changes by clicking on Update 31

31 Run entire workflow by clicking here. The import is done manually after framing is complete. 32

32 Unaligned 33

33 Aligned 34

34 Found 1633 frames which is 895 isotope clusters Now import PD search results, click Tools above then select Import Protein ID s. 35

35 Proteome Discoverer results from version 1.4 can be imported into SIEVE 2.1 Browse for PD files 36

36 Drag and drop the files. The raw file name must match in order to import the results using Match by Scan 37

37 If importing Mascot results either from PD or Mascot itself use this filter based on ion score. If importing SEQUEST results without Percolator select this import filter. Standard xcorr vs charge state. If importing SEQUEST results with Percolator select this import filter. This will import all ID with q-values less than 5%. Click import into SIEVE 38

38 Right click to add or remove columns 39

39 Right click here to add specific columns using Field Chooser 40

40 PRElement- is the cluster element, i.e. the isotopic assignment. PRElement=0, (A0), =1 (A1), 2= (A3) PRRoot- Is the Frame ID A0 for the cluster. Charge- Is determined from the cluster. PRSize- Is the number of frames that make up the cluster. See example below. 41

41 All variables can be used as frame filters to reduce the results. For example the filter string: Prelement=0 and prsize>2 and charge>1 Press enter on keyboard to apply filters. Would mean show only A0 or C12 frames for isotope clusters that had more than 3 isotopes and who s charge is greater than 1. Results show 162 frames out of 1633 total passed the filter. 42

42 Large triangles are indicators for the MS2 scans. Click on p-value_sample_b to sort and find significant changes between Control and Sample_B. GoodID column provides a reference for if a frame has been matched to a peptide ID. If GoodID = -1, no MS2 GoodID = 0, MS2 were searched but no match passed ID criteria. GoodID=1, match was found 43

43 Click here to view trend intensities Frame #1 m/z Click here to view Principal Component Analysis 44

44 Frame #1 m/z Sample C Sample B Control 45

45 Click here to add more column options 46

46 Protein Ratios 47

47 Expand the + to see peptide, then frame information 48

48 Click here to select protein to view ratio plot for peptides. Then click Ratio tab to see that protein. 49

49 Change protein by clicking on different accession number here. Protein name being displayed and its ratio. Change the ratio group by selecting a different group here. The plot displays the peptides from a specific protein. Ratio on the x-axis. 50

50 New protein ratio calculation options. No weighting is default. 51