4D-diaXLMS

Introduction

4D-diaXLMS is a workflow which could allow the diaPASEF analysis on proteome-wide cross-linking study.

Please report any problems directly to the github issue tracker. Also, you can send feedback to [email protected].

Publications

Y. Hao,# M. Chen,# X. Huang, H. Xu, P. Wu, S. Chen,* 4D-diaXLMS: Proteome-wide Four-Dimensional Data-Independent Acquisition Workflow for Cross-linking Mass Spectrometry. Anal. Chem. 2023, 95(37), 14077-14085. https://pubs.acs.org/doi/full/10.1021/acs.analchem.3c02824

Guide to use 4D-diaXLMS

1. Analysis ddaPASEF data by pLink2 software

The DIA analysis in 4D-diaXLMS is library-based search, so you need to establish a experimental spectrum library on ddaPASEF mode.

a. Convert ddaPASEF data to mgf file

The .d file of ddaPASEF data should be convert to mgf file using Bruker Compass DataAnalysis software (version 5.3.236.352) with 'Shotgun PASEF ProteinAnalysis.m' method.

b. Process the mgf file with 'process_mgf_file.py'

Example:

python process_mgf_file.py --filedir './data/example.mgf'  --filename 'example'

It will generate a 'example_plink.mgf' which could be processed by pLink2 software.

c. Analyze the mgf file with pLink2.

The 'example_plink.mgf' files were imported to pLink2(2.3.11) for database search.

d. Process the cross-linked results of pLink2 with 'process_plink_results.py'

Example:

python process_plink_results.py --inputdir './data/example.csv' --outputdir './data/example'

It will generate a 'example_crosslink_filter.csv' file.

2. Generate 4D crosslinking library

Here you could generate a 4D crosslinking library based on the 'example_plink.mgf' and 'example_crosslink_filter.csv' by running 'generate_4D_library.py' Example:

python generate_4D_library.py --resultsdir './data/example_crosslink_filter.csv' --mgfdir './data/example_plink.mgf' --crosslinker 'DSS'

It will generate two library files 'example_crosslink_filter_DIANN_lib.csv' and 'example_crosslink_filter_normal_lib.csv', the 'example_crosslink_filter_DIANN_lib.csv' file could be directly used by DIA-NN software.

3. Merge multiple libraries

If you have several fractions, there may be some overlap identification between multiple fractions, so it is necessary to remove the overlap. You can merge these 'normal_lib.csv' into one csv file, and then run the 'filter_library.py' Example:

python filter_library.py --filedir './data/merge.csv' 

It will generate two library files 'merge_filter_DIANN_lib.csv' and 'merge_filter_normal_lib.csv', the 'merge_filter_DIANN_lib.csv' file could be directly used by DIA-NN software.

4. Analysis diaPASEF data by DIA-NN software with 4D cross-linking library

DIA-NN (version 1.8.1) was used to process raw (.d) file using the 4D cross-linking spectral library. FASTA file was not selected. Other parameters was set as follows: ms1 accuracy, 15 ppm; ms2 accuracy, 15 ppm; precursor FDR, 1%; neural network class, single-pass model; quantification strategy, robust LC; cross-run normalisation, RT-dependent.

License

4D-diaXLMS is distributed under an Apache License. See the LICENSE file for details.