MS Annika Spectral Library exporter

Generate a spectral library for Spectronaut from MS Annika results.

Usage

• Install python 3.7+: https://www.python.org/downloads/
• Install requirements: pip install -r requirements.txt
• Export MS Annika CSMs from Proteome Discoverer to Microsoft Excel format. Filter out decoys beforehand and filter for high-confidence CSMs (see below).
• Convert any RAW files to *.mgf format.
• Set your desired parameters in config.py (see below).
• Run python create_spectral_library.py.
• If the script successfully finishes, the target spectral library should be generated with the extension _spectralLibrary.csv.
• Additionally decoy libraries are generated with the extensions:
  • _spectralLibraryDECOY_DD.csv: library with decoy-decoy crosslinks.
  • _spectralLibraryDECOY_DT.csv: library with decoy-target crosslinks.
  • _spectralLibraryDECOY_TD.csv: library with target-decoy crosslinks.
  • Decoys are generated by the reverse strategy as described by Zhang et al. here: https://doi.org/10.1021/acs.jproteome.7b00614.
• The full spectral library including all target and decoy annotations is created with extension _spectralLibraryFULL.csv.
  • This spectral library should be used with Spectronaut!

GUI

Important: The GUI currently only is supported up to version 1.1.6!

Alternatively to the commandline-based python script, a GUI is also available via Docker:

• After installing Docker [Quick Guide here] run the following command:

  docker run -p 8501:8501 michabirklbauer/spectrallibraryexporter
  

• Navigate to localhost:8501 in your browser. You should see the MS Annika Spectral Library exporter GUI!

If you don't have/want to install Docker you can also run the GUI natively using the following commands:

• Open a terminal inside MSAnnika_Spectral_Library_exporter.
• Enter cp gui/streamlit_app.py ..
• Enter cp gui/streamlit_util.py ..
• Enter pip install streamlit.
• Enter streamlit run streamlit_app.py --server.maxUploadSize 5000.
• Navigate to localhost:8501 in your browser. You should see the MS Annika Spectral Library exporter GUI!

Exporting MS Annika results to Microsoft Excel

The script uses a Micrsoft Excel files as input, for that MS Annika results need to be exported from Proteome Discoverer. It is recommended to first filter results according to your needs, e.g. filter for high-confidence CSMs and filter out decoy CSMs as depicted below.

Results can then be exported by selecting File > Export > To Microsoft Excel… > Level 1: CSMs > Export in Proteome Discoverer.

Parameters

The following parameters need to be adjusted for your needs in the config.py file:

##### PARAMETERS #####

# name of the mgf file containing the MS2 spectra
SPECTRA_FILE = ["20220215_Eclipse_LC6_PepMap50cm-cartridge_mainlib_DSSO_3CV_stepHCD_OT_001.mgf"]
# name of the CSM file exported from Proteome Discoverer
CSMS_FILE = "20220215_Eclipse_LC6_PepMap50cm-cartridge_mainlib_DSSO_3CV_stepHCD_OT_001.xlsx"
# name of the experiment / run (any descriptive text is allowed)
RUN_NAME = "20220215_Eclipse_LC6_PepMap50cm-cartridge_mainlib_DSSO_3CV_stepHCD_OT_001-(1)"
# name of the sample organism that should be reported in the spectral library
ORGANISM = "Homo sapiens"
# name of the crosslink modification
CROSSLINKER = "DSSO"
# possible modifications and their monoisotopic masses
MODIFICATIONS = \
    {"Oxidation": [15.994915],
     "Carbamidomethyl": [57.021464],
     "DSSO": [54.01056, 85.98264, 103.99320]}
# expected ion types (any of a, b, c, x, y, z)
ION_TYPES = ("b", "y")
# maximum expected charge of fragment ions
MAX_CHARGE = 4
# tolerance for matching peaks
MATCH_TOLERANCE = 0.02
# parameters for calculating iRT
iRT_PARAMS = {"iRT_m": 1.3066, "iRT_t": 29.502}

In case you have more than one SPECTRA_FILE you can specify that like this:

##### PARAMETERS #####

# name of the mgf file containing the MS2 spectra
SPECTRA_FILE = ["20220215_Eclipse_LC6_PepMap50cm-cartridge_mainlib_DSSO_3CV_stepHCD_OT_001.mgf",
                "20220215_Eclipse_LC6_PepMap50cm-cartridge_mainlib_DSSO_3CV_stepHCD_OT_002.mgf"]
# name of the CSM file exported from Proteome Discoverer
CSMS_FILE = "20220215_Eclipse_LC6_PepMap50cm-cartridge_mainlib_DSSO_3CV_stepHCD_OT_001.xlsx"
# name of the experiment / run (any descriptive text is allowed)
RUN_NAME = "20220215_Eclipse_LC6_PepMap50cm-cartridge_mainlib_DSSO_3CV_stepHCD_OT_001-(1)"
# name of the sample organism that should be reported in the spectral library
ORGANISM = "Homo sapiens"
# name of the crosslink modification
CROSSLINKER = "DSSO"
# possible modifications and their monoisotopic masses
MODIFICATIONS = \
    {"Oxidation": [15.994915],
     "Carbamidomethyl": [57.021464],
     "DSSO": [54.01056, 85.98264, 103.99320]}
# expected ion types (any of a, b, c, x, y, z)
ION_TYPES = ("b", "y")
# maximum expected charge of fragment ions
MAX_CHARGE = 4
# tolerance for matching peaks
MATCH_TOLERANCE = 0.02
# parameters for calculating iRT
iRT_PARAMS = {"iRT_m": 1.3066, "iRT_t": 29.502}

Known Issues

List of known issues

Citing

If you are using the MS Annika Spectral Library exporter script please cite:

MS Annika 2.0 Identifies Cross-Linked Peptides in MS2–MS3-Based Workflows at High Sensitivity and Specificity
Micha J. Birklbauer, Manuel Matzinger, Fränze Müller, Karl Mechtler, and Viktoria Dorfer
Journal of Proteome Research 2023 22 (9), 3009-3021
DOI: 10.1021/acs.jproteome.3c00325

If you are using MS Annika please cite:

MS Annika 2.0 Identifies Cross-Linked Peptides in MS2–MS3-Based Workflows at High Sensitivity and Specificity
Micha J. Birklbauer, Manuel Matzinger, Fränze Müller, Karl Mechtler, and Viktoria Dorfer
Journal of Proteome Research 2023 22 (9), 3009-3021
DOI: 10.1021/acs.jproteome.3c00325

or

MS Annika: A New Cross-Linking Search Engine
Georg J. Pirklbauer, Christian E. Stieger, Manuel Matzinger, Stephan Winkler, Karl Mechtler, and Viktoria Dorfer
Journal of Proteome Research 2021 20 (5), 2560-2569
DOI: 10.1021/acs.jproteome.0c01000

License

• MIT

Contact

• [email protected]