aSPIRE is a tool for the processing of peptide abundances using label-free quantification mass spectrometry
Please cite the following publication if you are using aSPIRE:
Soh, W.T., Roetschke, H.P., Cormican, J.A. et al. Protein degradation by human 20S proteasomes elucidates the interplay between peptide hydrolysis and splicing. Nat Commun 15, 1147 (2024). https://doi.org/10.1038/s41467-024-45339-3
List of contents:
aSPIRE processes peptide-spectrum matches (PSMs) that were assigned by inSPIRE, quantifies them using Skyline and constructs a generation kinetic for each identified peptide. It can be run on a Linux, Mac or Windows laptop or workstation. However (Note, that software testing was done only on macOS/Linux).
The main steps of aSPIRE are:
- parsing of inSPIRE assignments (PSMs), peptide mapping and creation of input files for Skyline
- quantification of peptides across all raw files provided using Skyline (can be run either automatically by using a Docker image or manually on a Windows machine, see below for more details)
- aggregation of peptide abundances to generation kinetics
- removal of potential synthesis errors and contaminants
- data normalisation and filtering of noisy data points
- results visualisation (peptide generation kinetics, total ion chromatograms, peptide coverage maps, residue maps etc.)
The following instructions need to be executed oncy once to set up aSPIRE. Once this is done, you can directly progress to the execution for any further runs.
aSPIRE relies on Conda and Snakemake.
In order to install Conda, click on this link and follow the installation guidelines for your respective operating system.
After installing Conda, you need to install Snakemake. The Snakemake installation procedure is described here.
Briefly, open the terminal on your computer and paste the following lines sequentially:
conda install -n base -c conda-forge conda
conda activate base
conda create -c conda-forge -c bioconda -n aspire snakemake
Additionally, you might need to run conda update conda. We repeatedly faced some issues around Conda installations, particularly with devices with Apple M1 cores. Please refer to this tutorial for troubleshooting your installation.
Download this repository as a .zip file (click on Code at the upper right corner of this repository --> Download ZIP), move the .zip file in the desired directory on your computer and unpack it. Open the terminal in this directory and enter:
conda activate aspire
For the extraction of peptide abundances, aSPIRE relies on Skyline. There are two ways to execute aSPIRE and Skyline.
- If you have limited experience with command line, a Windows machine available and only a few samples to process we recommend manual execution.
- For high-throughput data processing with aSPIRE we recommend executing Skyline via command line in automated fashion.
Choose one of these methods according to your requirements and follow the respective instructions below.
Install Skyline on your Windows machine following the vendor's instructions. In the config file, remember to change the flag
automatedSkyline: no
to no (see config file section for detailed instructions). Make sure to follow the instructions in Skyline_tutorial.pdf during execution.
The command line option requires the installation of Docker. Skyline is containerised in this Docker image. Pull the image and make sure that it works:
docker pull chambm/pwiz-skyline-i-agree-to-the-vendor-licenses
docker run -it --rm chambm/pwiz-skyline-i-agree-to-the-vendor-licenses wine SkylineCmd --help
You should see information for all possible flags printed. In the config file, remember to change the flag
automatedSkyline: yes
to yes (see config file section for detailed instructions).
All input information should be provided in the data/ folder. Please have a look at the files config.yaml and sample_list.csv in that folder.
Open data/config.yaml using a text editor such as VS code or Sublime. Fill in the information as in the example:
protein_name: CaM
spAngle: 0
qVal: 0.01
RT: 150000000
raw_file_loc: /absolute_path/to/folder_with_all_raw_files/
automatedSkyline: yes
skyline_report: MS1_HPR
| flag | explanation |
|---|---|
protein_name |
Name of the kinetic that should be analysed by aSPIRE. Must correspond to the protein_name column in the sample list (see below). |
spAngle |
Lower limit of spectral angles. Postfiltering of inSPIRE assignments is not recommended - do not change unless you have a reason to do so. |
qVal |
False discovery rate for which PSMs are filtered. Set to 1% per default. |
RT |
Upper limit of retention time error. Postfiltering of inSPIRE assignments is not recommended - do not change unless you have a reason to do so. |
raw_file_loc |
Absolute path pointing towards a folder that contains all raw files. This folder can also be located on a remote file server, however, the device from which you are running aSPIRE must have access to this folder. |
automatedSkyline |
Logical indicated whether Skyline should be executed manually or automatically via command line (see above). Enter yes or no. |
skyline_report |
Do not change. |
Special attention should be paid to protein_name, raw_file_loc and automatedSkyline flags. All other flags can be left to their default.
Make sure to save the config file after modifying it!
Open data/sample_list.csv with MS Excel/Numbers etc or a text editor. Fill in the information as in the example:
| protein_name | substrateID | substrateSeq | digestTime | biological_replicate | final_assignments | raw_file |
|---|---|---|---|---|---|---|
| CaM | CaM | CaM.fasta | 0 | b1 | CaM_psms.csv | HRoetschke_291222_040123_Fu_CaM_b1R1_0h.raw |
| CaM | CaM | CaM.fasta | 1 | b1 | CaM_psms.csv | HRoetschke_291222_040123_Fu_CaM_b1R1_1h.raw |
| CaM | CaM | CaM.fasta | 2 | b1 | CaM_psms.csv | HRoetschke_291222_040123_Fu_CaM_b1R1_2h.raw |
| CaM | CaM | CaM.fasta | 4 | b1 | CaM_psms.csv | HRoetschke_291222_040123_Fu_CaM_b1R1_4h.raw |
| CaM | CaM | CaM.fasta | 4 | b2 | CaM_psms.csv | HRoetschke_291222_040123_Fu_CaM_b2R1_4h.raw |
A few general remarks:
- Please always provide a full kinetic including control measurements.
- You can put any number of proteins / experiments in the sample list. However, only a single protein can be processed at once. Specify the
protein_nameyou would like to analyse in the config file (see above). - Do not put any white spaces, umlauts or empty rows in the sample list. Also, every column has to be filled, even if there are duplicated entries (e.g., substrateID).
Explanation of sample list columns:
| column | explanation |
|---|---|
protein_name |
The name of the protein/polypeptide to which the respective list entry corresponds. Choose a short and comprehensive name and avoid white spaces or special characters. |
substrateID |
ID under which the given protein will appear in the final output. Can be identical to protein_name (recommended), but this does not have to be the case. |
substrateSeq |
Save the substrate sequence in a single-entry .fasta file and deploy it in data/sequences/. Specify the name of the .fasta file in the substrateSeq column of the sample list. |
digestTime |
Time point. Please provide the time in hours! For instance, if the digestion time is 15 min, enter 0.25. Do not put any units in this column! Zero-hours time points are treated as control measurements. Please enter 0 as time point for all control measurements. |
biological_replicate |
Name of the biological replicate. In the final kinetics, the mean over all technical replicates is calculated, whereas biological replicates are displayed separately. Please have a look at the full sample list (data/sample_list.csv) for clarification. |
final_assignments |
PSM list from inSPIRE (NOT peptide list!). It has to be copied into data/inSPIRE and re-named according to the example in the sample list. Specify the name of the inSPIRE output files in this column. |
raw_file |
Provide the full name (including .raw suffix) of the raw file for the respective sample. You do NOT have to copy the raw files to your device. However, the device from which you are running aSPIRE must have access to this folder. |
After filling in all information, save the sample list in .csv format. Important! In case you are creating/editing the sample_list.csv file in Microsoft Excel, make sure to save it as actual comma-separated file. I.e., Save as --> Comma-separated Values (.csv) To check that the sample list is in the correct format, you can open it using a text editor and verify that the columns are separated by commas (and NOT semicolons).
Make sure you changed all input files and provided all necessary information. Open a terminal in the aSPIRE directory of your terminal. After entering pwd into the terminal, it should display ./aSPIRE or ./aSPIRE-v.1. Activate the conda environment (if not done so already) via:
conda activate aspire
Execute aSPIRE via:
snakemake --use-conda --cores all
The progress of the execution should appear in your terminal window. Additionally, all statements are saved in a log file (results/protein_name/log.txt).
In case you have installed an older version of Conda/Snakemake and encounter an error when executing the tool, try executing
snakemake --use-conda --cores all --conda-frontend conda
After your jobs finished, enter
conda deactivate
in order to terminate your Conda environment.
All results are stored in the results/protein_name/ folder.
aSPIRE produces a variety of tabular and graphic output, e.g., a table with full the annotation of each detected and quantified peptide, graphics of generation kinetics for each peptide, total ion chromatograms, coverage and residue maps, among others. For each specified protein name, the following files can be found in results/:
.
├── ASSIGNMENTS.RData
├── ASSIGNMENTS.csv
├── protein_name.fasta
├── protein_name.ssl
├── protein_name_YYMMDD.sky
├── protein_name_TICs.tsv
├── protein_name_finalKinetics.csv
├── MS1_HPR.csv
├── QUANTITIES_filtered.RData
├── QUANTITIES_raw.RData
├── log.txt
├── notQuant.csv
├── plots
│ ├── protein_name_TICs.done
│ ├── protein_name_TICs.pdf
│ ├── protein_name_coverage.pdf
│ ├── protein_name_coveragevalues.RData
│ ├── protein_name_finalKinetics.pdf
│ ├── protein_name_rawIntensities.pdf
│ ├── protein_name_residuemap.gif
│ └── protein_name_residuemap.pdf
└── skyline_log.txt
The relevant output files for the user are explained below.
| file name | explanation |
|---|---|
protein_name_finalKinetics.csv |
Table with full annotation of each identified and quantified peptide. Contaminants are labelled with NA in substrateID column. See below for detailed explanation of all columns. |
protein_name_finalKinetics.pdf |
Graphics of the generation kinetic for each peptide. Biological replicates are plotted as separate lines. Bars indicate SD between technical replicates. Substrate sequence origin coordinates as well as peptide sequence and product type are indicated. |
protein_name_YYMMDD.sky |
Skyline document. Can be opened in the Skyline GUI for direct access to chromatograms. |
protein_name_TICs.tsv |
Total ion chromatograms (TICs) for each raw file. |
protein_name_TICs.pdf |
Plots of TICs across 1) conditions or 2) replicates for QC. |
protein_name_coverage.pdf |
Coverage profiles with the abundance of canonical and spliced peptides over time. |
protein_name_residuemap.gif |
Visualisation of peptide origins and abundances. For each substrate residues, all peptides that contain this residue as potential origin are indicated. Bar height reflects relative abundance of a peptide. The height of each peptide stack is normalised to the coverage at this position. |
Example of residue maps:
protein_name_finalKinetics.csv is the main output file of aSPIRE. Please find an explanation of the file below:
| column | explanation |
|---|---|
substrateID |
substrate ID specified by the user in sample_list.csv. |
pepSeq |
Peptide sequence. Each peptide sequence is reported n-times, where n is the number of biological replicates. |
existsIlRedundantEquivalent |
Indicates whether an I/L-redundant equivalent of the sequence was identified as well. |
biological_replicate |
Biological replicate to which the intensities correspond. |
digestTimes |
Time points, separated by ;. |
intensities |
MS1 intensities that correspond to the respective time points, separated by ;. |
substrateSeq |
Amino acid sequence of the substrate. |
productType |
Peptide product type. PCP: non-spliced (canonical), PSP: spliced. |
spliceType |
Peptide splice type. cis: forward cis-spliced, revCis: reverse cis-spliced, trans: trans-spliced. Multiple possible product types are separated by ; (PCP denotes non-spliced peptides). |
positions |
Coordinates of the substrate origin of each peptide. Multiple possible origins are separated by ;. |
pepSeqAssigned |
I/L variant of the peptide sequence that was originally assigned during sequence identification. |
noScans |
Number of PSMs in which the peptide was identified. |
assignedScans |
PSMs in which the peptide was identified. Format: raw-file-name_scan-number. Multiple PSMs are separated by ;. |
spectralAngles |
Spectral angles corresponding to the PSMs (separated by ;). |
qValues |
q-values (FDRs) corresponding to the PSMs (separated by ;). |
ionScores |
Search engine scores corresponding to the PSMs (separated by ;). |
deltaRTs |
iRT errors corresponding to the PSMs (separated by ;). |
charges |
Charges corresponding to the PSMs (separated by ;). |
modifications |
Post-translational modifications (PTMs) corresponding to the PSMs (separated by ;). |