TMT 10-plex parameter file for high-low MS3 data

[Chris Barnes]

Hello all,

I'm working on a TMT 10-Plex experiment with a Lumos.  We have been acquiring MS3 data with a method that uses the linear ion trap for the MS2s.  Subsequently, I have a "high-low" parameters issue.  I am posting here to see if anyone has searched these kind of files and if anyone has a parameters file that they'd be willing to share.  I pasted my params file below, where I lifted the dynamic modification lines from another post by Jimmy.  I'm just trying to double check if I'm doing the searches right.  

Thanks for your help!

# comet_version 2015.02 rev. 5

# Comet MS/MS search engine parameters file.

# Everything following the '#' symbol is treated as a comment.

database_name = /some/path/db.fasta

decoy_search = 1                       # 0=no (default), 1=concatenated search, 2=separate search

num_threads = 0                        # 0=poll CPU to set num threads; else specify num threads directly (max 64)

#

# masses

#

peptide_mass_tolerance = 20.00

peptide_mass_units = 2                 # 0=amu, 1=mmu, 2=ppm

mass_type_parent = 1                   # 0=average masses, 1=monoisotopic masses

mass_type_fragment = 1                 # 0=average masses, 1=monoisotopic masses

precursor_tolerance_type = 1           # 0=MH+ (default), 1=precursor m/z; only valid for amu/mmu tolerances

isotope_error = 1                      # 0=off, 1=on -1/0/1/2/3 (standard C13 error), 2= -8/-4/0/4/8 (for +4/+8 labeling)

#

# search enzyme

#

search_enzyme_number = 1               # choose from list at end of this params file

num_enzyme_termini = 2                 # valid values are 1 (semi-digested), 2 (fully digested, default), 8 N-term, 9 C-term

allowed_missed_cleavage = 2            # maximum value is 5; for enzyme search

#

# Up to 9 variable modifications are supported

# format:  <mass> <residues> <0=variable/else binary> <max_mods_per_peptide> <term_distance> <n/c-term> <required>

#     e.g. 79.966331 STY 0 3 -1 0 0

#

variable_mod01 = 15.9949 M 0 3 -1 0 0

variable_mod02 = 229.162932 nK 1 4 -1 2 0  # variable modification with the TMT tag on n-termini or K.  If running this on an MS3 method file, also use the clear_mz_range option below

variable_mod03 = 0.0 X 0 3 -1 0 0

variable_mod04 = 0.0 X 0 3 -1 0 0

variable_mod05 = 0.0 X 0 3 -1 0 0

variable_mod06 = 0.0 X 0 3 -1 0 0

variable_mod07 = 0.0 X 0 3 -1 0 0

variable_mod08 = 0.0 X 0 3 -1 0 0

variable_mod09 = 0.0 X 0 3 -1 0 0

max_variable_mods_in_peptide = 5

require_variable_mod = 0

#

# fragment ions

#

# ion trap ms/ms:  1.0005 tolerance, 0.4 offset (mono masses), theoretical_fragment_ions = 1

# high res ms/ms:    0.02 tolerance, 0.0 offset (mono masses), theoretical_fragment_ions = 0

#

fragment_bin_tol = 1.0005                # binning to use on fragment ions

fragment_bin_offset = 0.4              # offset position to start the binning (0.0 to 1.0)

theoretical_fragment_ions = 1          # 0=use flanking peaks, 1=M peak only

use_A_ions = 0

use_B_ions = 1

use_C_ions = 0

use_X_ions = 0

use_Y_ions = 1

use_Z_ions = 0

use_NL_ions = 1                        # 0=no, 1=yes to consider NH3/H2O neutral loss peaks

#

# output

#

output_sqtstream = 0                   # 0=no, 1=yes  write sqt to standard output

output_sqtfile = 0                     # 0=no, 1=yes  write sqt file

output_txtfile = 0                     # 0=no, 1=yes  write tab-delimited txt file

output_pepxmlfile = 1                  # 0=no, 1=yes  write pep.xml file

output_percolatorfile = 0              # 0=no, 1=yes  write Percolator tab-delimited input file

output_outfiles = 0                    # 0=no, 1=yes  write .out files

print_expect_score = 1                 # 0=no, 1=yes to replace Sp with expect in out & sqt

num_output_lines = 5                   # num peptide results to show

show_fragment_ions = 0                 # 0=no, 1=yes for out files only

sample_enzyme_number = 1               # Sample enzyme which is possibly different than the one applied to the search.

                                       # Used to calculate NTT & NMC in pepXML output (default=1 for trypsin).

#

# mzXML parameters

#

scan_range = 0 0                       # start and scan scan range to search; 0 as 1st entry ignores parameter

precursor_charge = 0 0                 # precursor charge range to analyze; does not override any existing charge; 0 as 1st entry ignores parameter

override_charge = 0                    # 0=no, 1=override precursor charge states, 2=ignore precursor charges outside precursor_charge range, 3=see online

ms_level = 2                           # MS level to analyze, valid are levels 2 (default) or 3

activation_method = ALL                # activation method; used if activation method set; allowed ALL, CID, ECD, ETD, PQD, HCD, IRMPD

#

# misc parameters

#

digest_mass_range = 600.0 5000.0       # MH+ peptide mass range to analyze

num_results = 100                      # number of search hits to store internally

skip_researching = 1                   # for '.out' file output only, 0=search everything again (default), 1=don't search if .out exists

max_fragment_charge = 3                # set maximum fragment charge state to analyze (allowed max 5)

max_precursor_charge = 6               # set maximum precursor charge state to analyze (allowed max 9)

nucleotide_reading_frame = 0           # 0=proteinDB, 1-6, 7=forward three, 8=reverse three, 9=all six

clip_nterm_methionine = 0              # 0=leave sequences as-is; 1=also consider sequence w/o N-term methionine

spectrum_batch_size = 10000            # max. # of spectra to search at a time; 0 to search the entire scan range in one loop

decoy_prefix = DECOY_                  # decoy entries are denoted by this string which is pre-pended to each protein accession

output_suffix =                        # add a suffix to output base names i.e. suffix "-C" generates base-C.pep.xml from base.mzXML input

mass_offsets =                         # one or more mass offsets to search (values substracted from deconvoluted precursor mass)

#

# spectral processing

#

minimum_peaks = 10                     # required minimum number of peaks in spectrum to search (default 10)

minimum_intensity = 0                  # minimum intensity value to read in

remove_precursor_peak = 0              # 0=no, 1=yes, 2=all charge reduced precursor peaks (for ETD)

remove_precursor_tolerance = 1.5       # +- Da tolerance for precursor removal

clear_mz_range = 125.5 131.5           # for iTRAQ/TMT type data; will clear out all peaks in the specified m/z range

#

# additional modifications

#

add_Cterm_peptide = 0.0

add_Nterm_peptide = 0.0

add_Cterm_protein = 0.0

add_Nterm_protein = 0.0

add_G_glycine = 0.0000                 # added to G - avg.  57.0513, mono.  57.02146

add_A_alanine = 0.0000                 # added to A - avg.  71.0779, mono.  71.03711

add_S_serine = 0.0000                  # added to S - avg.  87.0773, mono.  87.03203

add_P_proline = 0.0000                 # added to P - avg.  97.1152, mono.  97.05276

add_V_valine = 0.0000                  # added to V - avg.  99.1311, mono.  99.06841

add_T_threonine = 0.0000               # added to T - avg. 101.1038, mono. 101.04768

add_C_cysteine = 57.021464             # added to C - avg. 103.1429, mono. 103.00918

add_L_leucine = 0.0000                 # added to L - avg. 113.1576, mono. 113.08406

add_I_isoleucine = 0.0000              # added to I - avg. 113.1576, mono. 113.08406

add_N_asparagine = 0.0000              # added to N - avg. 114.1026, mono. 114.04293

add_D_aspartic_acid = 0.0000           # added to D - avg. 115.0874, mono. 115.02694

add_Q_glutamine = 0.0000               # added to Q - avg. 128.1292, mono. 128.05858

add_K_lysine = 0.0000                  # added to K - avg. 128.1723, mono. 128.09496

add_E_glutamic_acid = 0.0000           # added to E - avg. 129.1140, mono. 129.04259

add_M_methionine = 0.0000              # added to M - avg. 131.1961, mono. 131.04048

add_O_ornithine = 0.0000               # added to O - avg. 132.1610, mono  132.08988

add_H_histidine = 0.0000               # added to H - avg. 137.1393, mono. 137.05891

add_F_phenylalanine = 0.0000           # added to F - avg. 147.1739, mono. 147.06841

add_R_arginine = 0.0000                # added to R - avg. 156.1857, mono. 156.10111

add_Y_tyrosine = 0.0000                # added to Y - avg. 163.0633, mono. 163.06333

add_W_tryptophan = 0.0000              # added to W - avg. 186.0793, mono. 186.07931

add_B_user_amino_acid = 0.0000         # added to B - avg.   0.0000, mono.   0.00000

add_J_user_amino_acid = 0.0000         # added to J - avg.   0.0000, mono.   0.00000

add_U_user_amino_acid = 0.0000         # added to U - avg.   0.0000, mono.   0.00000

add_X_user_amino_acid = 0.0000         # added to X - avg.   0.0000, mono.   0.00000

add_Z_user_amino_acid = 0.0000         # added to Z - avg.   0.0000, mono.   0.00000

#

# COMET_ENZYME_INFO _must_ be at the end of this parameters file

#

[COMET_ENZYME_INFO]

0.  No_enzyme              0      -           -

1.  Trypsin                1      KR          P

2.  Trypsin/P              1      KR          -

3.  Lys_C                  1      K           P

4.  Lys_N                  0      K           -

5.  Arg_C                  1      R           P

6.  Asp_N                  0      D           -

7.  CNBr                   1      M           -

8.  Glu_C                  1      DE          P

9.  PepsinA                1      FL          P

10. Chymotrypsin           1      FWYL        P

  

[Jimmy Eng]

The parameters seem fine for searching low-res MS2 scans.  I'm confused because you mention MS3 data ... if you want to search MS3 scans then set "ms_level = 3".  Also if you're really using all 10 channels of the 10-Plex TMT, you need high-res fragment ion spectra to differentiate between 8 of the reporter ions.

Also, you're highly encourage to update to the latest 2016.02 rev. 2 release of Comet.  Here are the release notes to the 2016.02 release describing the changes and and more importantly bug fixes since the 2015.02 rev. 5 version you appear to be using.

[Paulo C Carvalho]

i guess his ms3 is the multinotch i.e. , where the reporter ion signal will be found .   patternlab for proteomics can handle multinotch data and is  fully compatible with comet. use the isobaric analyzer. should you need any help please do not hesitate in contacting ne.  you can also checkout patternlabs nature protocok, there is a section on isobaric data as well.

cheers

paulo

--

Paulo Costa Carvalho

http://pcarvalho.com

[Chris Barnes]

Hi all,

First, thanks for your input so far.  We had the Thermo engineer come on-site and walk us through some methods and this is a method that he implemented.  Basically, his statement was that we didn't need the high resolution necessarily for the MS2 data and that we could still match peptides to the linear ion-trap MS2 data, which would save us time.  The MS3 data is collected as a Top 10 method from the MS2s in the iontrap where the Top 10 MS2 fragments for that precursor are sent back to the Orbitrap for the MS3 spectra acquisition with a higher collision energy.  Basically, you have a "Top 10" in the ion trap of the MS2 peaks that are collected for that given original precursor.  This does have the "Multi-notch Isolation = True" in the MS3 scan as it is the collection of 10 MS2 fragments that are used to derive the MS3 TMT tags in the Orbi.  Since this is a separate scan event in the raw file, I guess that I naively thought that Libra would work to extract this data since there is a TMT 10-plex functionality integrated into Libra in TPP 5.0, but honestly I haven't gotten that far yet and when I've tried, it failed already.  We do have a working copy of PD that can get us through all of the TMT scans and we are trying to implement MaxQuant for this as well, but MaxQuant is currently also crashing.  I like TPP tools better, generally, and wanted to give this workflow a try to see if I could get the MS3 quant data out.  This post was originally there to make sure that I have all of the mass settings and variable modifications correct in the original search.  Nothing beyond would matter if that is not correct.

Best,

chris

[Jimmy Eng]

Chris,

Libra will work with this data.  I always forget about it but I actually extend Libra to look for the reporter ions in the MS3 scans a few years back.  Simply add "<reporterFromMS3 value="1" />" into your Libra condition.xml file.  If you need assistance to figure out where the TPP is failing, I can follow-up with you offline.  Also if you're up for it, give Paulo's PatternLab for Proteomics a look; it's a nice suite of integrated tools that Comet compatible as Paulo mentions.

- Jimmy

[Eric Chan]

Hello all,

I'm learning to process MultiNotch-MS3 TMT Lumos data in comet, but have run into a problem at the post analysis step.

I can complete the comet search without issues if I use the default high-low ms2 settings:

fragment_bin_tol = 1.0005              # binning to use on fragment ions

fragment_bin_offset = 0.4              # offset position to start the binning (0.0 to 1.0)

Since my MS2 is collected in "Turbo" scans, I thought I should allow for larger fragment_bin_tol  (+/- 0.9Da).  However, I'd run into an "Error - XCORR DECOY" if I raise the fragment_bin_tol

fragment_bin_tol = 1.8000              # binning to use on fragment ions  (I've also tried 1.5000 and got the same error)

fragment_bin_offset = 0.4              # offset position to start the binning (0.0 to 1.0)

 - Input file: 20180611_AM01.mzXML

   - Load spectra: 31294

     - Search progress:  99%

     - Post analysis: Error - XCORR DECOY: dFragMass 629.286400, iFragMass 350, ArraySize 350, InputMass 629.354113, scan 74252, z 1 Error - XCORR DECOY: dFragMass 607.290800, iFragMass 338, ArraySize 338, InputMass 607.367601, scan 18274, z 1 Error - XCORR DECOY: dFragMass 710.329000, iFragMass 395, ArraySize 395, InputMass 710.344896, scan 62870, z 1 Error - XCORR DECOY: dFragMass 699.262000, iFragMass 389, ArraySize 389, InputMass 699.425219, scan 26624, z 1

Please pardon my lack of understanding of the "post analysis" step.

Could you give me some pointers on how to set "fragment_bin_tol " properly, if the low-res MS2 is expected to give larger errors (e.g. +/- 0.9Da)?

Thanks in advance for your advice.

-Eric

[Phillip Wilmarth]

Hi Eric,

I do not think there is any reason to use the Turbo scan rate mode for the SPS MS3 method. The cycle time should be limited by the high resolution MS3 scans in the Orbitrap. My past experience with SEQUEST was that any fragment ion tolerances greater than 1.0 made SEQUEST really unhappy. Jimmy will probably have some insight into if Comet likes tolerances greater than 1.0005.

Cheers,

Phil W.

[Eric Chan]

Hi Phil,

My mistake for blindly following the default settings in XCalibur.  I'll switch back to using Rapid or Normal MS2 scans.

Thanks for point that out.

-Eric

[Jimmy Eng]

Comet should work fine with "fragment_bin_tolerance" settings greater than 1.0005.  In fact, the error messages that are reported in the "Post analysis" portion of the search can be safely ignored.  Those error messages should really be warnings and in fact do not terminate the search.  They are part of the E-value calculations, generating a decoy/null xcorr distribution when the search does not match enough peptides and conditions that generate the "errors" should have minimal impact on the calculated E-values themselves.

I will revisit this in the code and possibly just suppress the warnings in a future release.  So Eric, feel free to use a "fragment_bin_tol = 1.8000" if you believe that's the proper setting for your data.  Note that the optimal "fragment_bin_offset" is likely not "0.4" in that case though.

Jimmy

[Phillip Wilmarth]

Hi Eric,

We have a plain Fusion. I double checked the methods parameters we use for SPS MS3 acquisition. The IT scan rate is rapid (not turbo). I do not know if our method is the default from Thermo or one we modified. It seems to work fine.

Cheers,

Phil