Making the Most of Your Edman Sequencing Data: A Primer on Data Calling, Analysis, Interpretation, and Reporting

Transcription

1 Making the Most of Your Edman Sequencing Data: A Primer on Data Calling, Analysis, Interpretation, and Reporting ESRG Tutorial, ABRF 2003, Feb Denver, CO Ben Madden, Mayo Clinic, Rochester, MN

2 Topics Covered 1. Aspects of calling amino acids 2. Factors that interfere with making amino acid assignments 3. Database searching 4. Reporting results 5. Calling, searching, and interpreting sample examples.

3 Goals of Edman Sequencing Assign N-terminal sequence Identify the protein(s)/peptide(s) present in sample Locate position of mutation/modification Indirectly establish presence of amino terminal modification (acetylation( acetylation, pyroglutamic,, etc..)

4 Data generation Detecting changes in the heights/areas of peaks corresponding to PTH-amino acids in a series of consecutive HPLC chromatograms. - Increases in height, signal presence of amino acid at a particular cycle followed by decrease at a later cycle - some noise level changes are present throughout the run

5 Analysis of raw data Requires the means to compare peak heights or peak areas in one chromatogram with the peak heights and areas in succeeding chromatograms.

6 Methods of calling amino acids Strip chart recorder /light box Computer chromatography software - ABI Model HP/Agilent Chemstation - SequencePro - any chromatography software

7 Chromatography software: Overlay or stacking option Compares 2 or more chromatograms - manually visualize the differences in peak heights - more forgiving of inconsistencies in chromatography :2 :3 :Std

8 Chromatography software: Subtraction mode option Shows combined image of current chromatogram minus peaks of prior chromatogram - requires tight chromatography - hard to see consecutive amino acids A-singleexm Residue H D N S Q TG E A REF R P M 0.00 WDPU F I K L V

9 Chromatography software Histograms options - peak height/areas of a single amino acid in each cycle of the run - requires good integration/quantitation

10 Chromatography software Software calling options - requires tight chromatography and solid integration - may miss problematic amino acids - not always reliable

11 What constitutes a called amino acid? Potentially any signal that rises above background level variations and falls at a later cycle can be an assignment Calls may be defined as positive or tentative depending on how far above background levels the peaks rise Experience is a factor

12 Calling amino acids Although all amino acids are similar in the Edman degradation reactions and the resulting PTH-amino acids all have very similar extinction coefficients at 269nm, there are some modifications that can affect the height/areas of the HPLC peaks

13 Calling amino acids PTH-ser recoveries are lower due to loss of H 2 O - forms PTH-DTT-dehydroalanine derivative 4.00 A S 0.00 dha

14 Calling amino acids 4.00 PTH-thr recovery can be lower due to loss of H 2 O - forms numerous dehydro-aminoisobutyric acid-dtt derivatives B- Celgene/JM UbcH :Residue 5 dptu T xx x x D N S Q G E A R Y P V dpu W F I K L

15 Calling amino acids Methionine can oxidize, resulting in lower recovery of PTH-Met M MetO

16 Calling amino acids PTH-Glu is accompanied by PTH-Glu Glu- aniline amide which becomes more abundant in later cycles :13 : E E

17 Calling amino acids Tryptophan is often oxidized to several kynureninyl adducts,resulting in low or no recovery of PTH-Trp Trp :8 :9 :Std ox W Std pks in orange P V DPTU W DPU F

18 Calling amino acids No PTH-cysteine peaks are observed due to loss of H 2 S - might see some PTH-DTT-dehydroalanine - must be alkylated (iodoacetamide,, vinyl- pryidine, acrylamide,, etc ) PTC-proline is slow to cleave leaving greater than normal lag

19 Calling amino acids PVDF blot where cysteine reacted with acrylamide during electrophoresis Proline lag :6 :7 :Std P 2.00 PTH-S-proprionamide-Cys E H

20 Calling amino acids PTH-Asn and PTH-Gln will partially deamidate to give PTH-Asp and PTH- Glu PTH-His and PTH-Arg can be low due to poor extraction

21 Calling amino acids Blank cycles can occur due to: - unalkylated cys - completely oxidized trp - modified amino acid asn-cho, (N)-X-S/T motif

22 Calling amino acids Multiple amino acids per cycle - major and minor signals might be used to assign more than one sequence - more challenging to distinguish major and minor with comparable signals, taking into account low recovery a.a. s (C,W,S,T,R,H,M) - numerous low level signals in each cycle may just be noise

23 Calling amino acids Rising background throughout the run - dependent on protein stability - more prominent with larger protein runs - will limit length of calls

24 Factors preventing good assignments Presence of non sample amino acids - contaminated cartridge blocks cleaning procedures using MeOH, acn/h2o, nitric acid, pyrolysis - contaminated supports (PVDF blots, PVDFstrips,, GF,etc) - dirty Polybrene

25 Factors preventing good assignments Sequencer performance (chemical or mechanical problems) - excessive lag - poor repetitive yield - evaluate by running a standard protein frequently or use an internal peptide standard for each run

26 Factors preventing good assignments Sequencer chemical artifacts - bad solvents and reagents, additives excessive DTT in S2B - HPLC solvents, buffers, additives - co-gln Gln,, aniline, DPTU, DPU

27 Factors preventing good assignments Sequencer chemical artifacts cont. - R2B (red) vsr2c (blue) (+/- PMTC) :10 :

28 20.00 DPTU PMTC :9 : R2C red vs R2B blue :9 : ox Trp

29 Factors preventing good HPLC problems assignments - retention time reproducibility replace worn pump seals eliminating leaky fittings gradients / column equilibration - baseline flatness acetone, KH 2 PO 4 - column life lower, broader peaks with older column

30 4.00 normal Pump seal failure :3 :4 :

31 Factors preventing good assignments clc guard column failure

32 Factors affecting good assignments Samples - sample amount / purity the lower the amount, the higher the purity required for confident calls - sample prep (see last years tutorial online at

33 Reasons for database searching Identification of protein sample - Is assigned sequence in the database? - Does the hit clearly identify the protein? Is the match real or by chance? Longer sequences for definitive hits Determine if the sequence is unique. - Is assigned sequence not in the database? - Does no exact hit mean you have a new sequence?

34 Reason for database searching Determine homology to other sequences in the database - need enough sequence to establish a relation Sort multiple Edman assignments - multiple amino acids per cycle

35 Statistical based search BLAST algorithms - Altschul,S.F., Gish,W., Miller,W., Myers.E.W., and Lipman,D.J. (1990) J.Mol Mol. Biol.. 215, FASTA - Lipman,, D.J. and Pearson, W.R. (1985) Science 227, SSEARCH (Smith-Waterman Waterman) - Smith, T.F. and Waterman,, M.S. (1981) J. Mol. Biol.. 147,

36 Text based search algorithms FINDPATTERN (GCG) MSPATTERN / MSEDMAN Peptidesearch

37 Protein Databases NCBI nr SWALL Swissprot TrEMBL Ludwig nr Owl PIR PRF

38 Factors that influence database searching Search algorithm (FASTA,BLAST,SSEARCH) Length of query sequence (>5) Scoring matrix (PAM#,BLOSUM#) Gap cost / Penalty

39 Factors that influence database searching Wordsize(1-3) Filtering Expect (E) Database

40 Web-Based Searching National Center for Biotechnology Information (NCBI) - ncbi.nlm.nih.gov/blast/ - online BLAST tutorial - BLAST searches - nr database

41 Web-Based Searching European Molecular Biology Laboratory-European Bioinformatics Institute (EMBL-EBI) - ebi.ac..ac.uk/tools - FASTA - BLAST - SSEARCH - SWALL database

42 Database Searching: First Attempt BLAST default parameters - filter - BLOSUM62 - expect 10 - wordsize 3 - database nr FASTA default parameters - BLOSUM50 - expect 1 - wordsize (k-tup tup) ) 2 - database swall

43 Search returns no hits Search parameters too strict - remove filters - increase Expect - use lower PAM or higher BLOSUM matrix - decrease word size - At NCBI BLAST can use nearly identical short sequences option E PAM30

44 Search returns many hits Are the hits occurring by random chance? - parameters not strict enough decrease E higher PAM or lower BLOSUM use filter Are the hits to a highly conserved sequence? Need more sequence data

45 Searching still returns no exact hit Sequence not in protein database - search nucleotide database TBLASTN, TFASTA - EST s

46 Database searching with multiple amino acids Amino acids are similar in amount Cannot assign a major sequence Use search algorithms that allow multiple entries Use search results to sort amino acid assignments into protein sequences

47 Web based searching: multiple amino acids Text based searching - Protein Prospector ( MSPATTERN numerous databases M.W. / species filtering - PepSearch ( mann.embl- heidelberg.de/.de/grouppages/pagelink/pepti desearchpage.html)

48 Web based searching: multiple amino acids Statistical based searching - FASTF / FASTF3 fasta.bioch.virginia.edu ebi.ac..ac.uk/fasta33 numerous databases

49 Reporting Results: Contents Whatever the user wants Raw data (PTH chromatograms, list of all amino acid yields) Called amino acids in each cycle - major and minor - positive or tentative Pmoles (raw or background subtracted) Initial yield / repetitive yield

50 Reporting Results: Contents Individual cycle comments Comments on the sequencing run Assigned sequence/s Database search parameters and results Reconcile the sequencer data and database results

51 Reporting Results: contents Sequencer and run conditions Sample workup

52 Reporting Results: styles Lab designed report forms Sequence analysis software printouts Spreadsheets Wordprocessor Database programs (Filemaker Pro) Handwritten report /

53 ESRG 2003 Sample User Reports 36 reports received - 25 lab designed report form - 6 sequence analysis software printout - 3 spreadsheet copy of handwritten lab notebook page

54 Information included in ABRF ESRG 2003 user reports Information included in ABRF ESRG 2003 user reports % Sample information 58% Sample preparation 17% Sequencer run conditions 14% Raw data 8% Manuallly called amino acids 89% Positive / tentative call distinction 69% Place for minor calls 33% Computer called amino acids 14% Pmole raw 44% Pmole background subtracted 22% Individual cycle discussion 39% Assigned sequence 69% IY / RY information 31% Sequencing run discussion 33% Edman degradation discussion 17% Perform database search 44% Database search parameters 25% Copy of database search results 88% Copy of database protein entry 38% Database search discussion 50%

55 ESRG 2003 Report Examples

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