PepMANDIS is an automated pipeline that interrogates UniProt or user defined protein database and computes several protein/peptide properties and associated statistics to deduce a small list of the most representative, process-specific and MS-amenable peptides for a microbial enzymatic activity of interest. It is written in Python, and was tested on several Linux distributions (Fedora, Ubuntu and CentOS), macOS (High Sierra and Big Sur) and Windows (10).
PLEASE CITE our paper (citation is available at the end of this README file) and/or URL to this GitHub repo (https://github.com/matejmedvecky/pepmandis) when using PepMANDIS in your work.
Please do not hesitate to contact the authors if any troubleshooting is needed.
Following list of dependencies need to be installed prior to start using pepMANDIS:
- python 3 (versions used in tests: 3.7.6 High Sierra; 3.6.8 CentOS 7; 3.8.5 Windows 10)
- biopython (1.76 High Sierra, 1.78 CentOS 7, Windows 10)
- matplotlib (3.1.3 High Sierra; 3.3.4 CentOS 7; 3.3.3 Windows 10)
- multiprocess (0.70.9 High Sierra; 0.70.11 CentOS 7; Windows 10)
- numpy (1.18.1 High Sierra; 1.19.5 CentOS 7, Windows 10)
- pyopenms (2.4.0 High Sierra, CentOS 7; 2.6.0 Windows 10)
- selenium (3.141.0 High Sierra, CentOS 7, Windows 10)
They can be installed via pip (package installer for Python) in Terminal. E.g. pip install biopython.
If, after installation of pyopenms, ImportError message (Library not loaded) is risen,
openssl needs to be installed as well.
Example of installing openssl via homebrew in Terminal: brew install openssl.
Terminal can be opened by following ways:
Linux: press Ctrl+Alt+T
macOS: press Command+Space, type terminal and press Enter
Windows: press Windows+R, type cmd and press Enter
PepMANDIS pipeline uses either Safari or Chrome web browser for performing CONSeQuence analysis
(prediction of peptide LC-MS/MS detectability), therefore, one of them need to be installed
on user's computer. Chrome is the preferred one since Safari cannot be ran in the background.
Note for Safari users: To enable to control Safari via webdriver, 'Allow Remote Automation' option
in Safari's Develop menu must be enabled.
Note for Chrome users: User system's ChromeDriver must be compatible with the system's Chrome browser
version. ChromeDriver can be downloaded from
https://sites.google.com/a/chromium.org/chromedriver/downloads.
Please note that path to chromedriver executable needs to be specified in a configuration ('defaults.cfg') file.
macOS users can experience following exception: "chromedriver" cannot be opened because the developer cannot be verified.
This error can be fixed by making macOS trust chromedriver binary: xattr -d com.apple.quarantine /path/to/chromedriver.
Please note that pyOpenMS is published under 3-clause BSD licence (https://opensource.org/licenses/BSD-3-Clause).
- BLAST+ (2.10.0+ High Sierra) & BLAST non-redundant protein database (HIGHLY RECOMMENDED since large BLAST queries are moved to slower queue)
- PeptideSieve (0.51)
Non-redundant BLAST database can be downloaded via following FTP: https://ftp.ncbi.nlm.nih.gov/blast/db/ or by running 'update_blastdb.pl' script from https://www.ncbi.nlm.nih.gov/books/NBK537770/
Please note that path to BLAST NR protein DB need to be specified in a 'defaults.cfg' file.
To limit offline BLASTP search by taxonomy, user needs to provide a file with taxids (see https://www.ncbi.nlm.nih.gov/books/NBK546209/#cookbook.Limiting_a_BLAST_search_with_a). I prepared file 'bacterial.ids' containing all taxids available for Bacteria. It can be found in config/ directory of this repo. Please note that PATH to that file must be specified in 'defaults.cfg' file.
To obtain and install BLAST+ command line applications, please visit https://www.ncbi.nlm.nih.gov/books/NBK279690/.
Newer versions of macOS won't run PeptideSieve since LD_LIBRARY_PATH and DYLD_LIBRARY_PATH cannot be loaded due to 'System integrity protection'. User must turn it off in order to enable dyld library to be loaded.
PepMANDIS repository with the souce code can be obtained via git:
git clone https://github.com/matejmedvecky/pepmandis.git
Files are located in bin directory:
They can by accessed by following command from current working directory where PepMANDIS repo was cloned into:
cd pepmandis/bin
Template of 'defaults.cfg' config file (with UNIX-like paths). It is included in config/ directory of this repo. Please change /path/to/ to actual path to desired files:
[ChromeDriver]
path=/Applications/chromedriver
[blastp]
executable=blastp
databasePath=/path/to/database/nr
[PeptideSieve]
executable=PeptideSieve.osx.i386
propertiesFilePath=/path/to/propertiesFile.txt
[taxidFile]
taxidFilePath=/path/to/taxid_file
Example of config file for Windows:
[ChromeDriver]
path=C:\\Users\\admin\\chromedriver\\chromedriver.exe
[blastp]
executable=blastp
databasePath=C:\\Users\\admin\\blastnrdatabase\\nr
[taxidFile]
taxidFilePath=C:\\Users\\admin\\pepmandis\\config\\bacterial.ids
pepMANDIS.py [options] -m "desired_molecule_name"
e.g. pepMANDIS.py -m "catechol-1,2-dioxygenase"
or python pepMANDIS.py -m "catechol-1,2-dioxygenase"
or py pepMANDIS.py -m "catechol-1,2-dioxygenase"
Help:
pepMANDIS -h
Open the terminal (press Ctrl+Alt+T in Linux or press Command+Space, type 'terminal' and press Enter in macOS).
If path to pepMANDIS.py is not in your environment PATH, execute it as follows:
/path/to/pepMANDIS.py [options] -m "desired_molecule_name"
If the script is in your current working directory, execute it by following way:
./pepMANDIS.py [options] -m "desired_molecule_name"
Open the terminal (press Windows+R, type 'cmd' and press Enter).
If path to pepMANDIS.py is not in your environment PATH, execute it as follows:
C:\path\to\pepMANDIS.py [options] -m "desired_molecule_name"
or python C:\path\to\pepMANDIS.py -m "desired_molecule_name"
or py C:\path\to\pepMANDIS.py -m "desired_molecule_name"
If the script is in your current working directory, execute it by following way:
pepMANDIS.py [options] -m "desired_molecule_name"
or python pepMANDIS.py -m "desired_molecule_name"
or py pepMANDIS.py -m "desired_molecule_name"
-
-m,--molecule: Specify protein name bounded by quotes (e.g. "catechol 1,2-dioxygenase")
that is used to programmatically query UniProt database and retrieve all relevant
entries, and to generate a list of potential protein synonyms reported in BLAST
non-redundant protein DB. REQUIRED. -
--no-usearch: Use this option if input sequences are provided in a FASTA AA
file (argument-i). Gathering of UniProt data will be avoided. -
--extra-input: Use this option if an additional dataset with protein sequences in FASTA AA
format is also provided (argument-e). Such proteins will be compared to
entries gathered from UniProt DB or sequences provided by '-i' argument
and exact matching peptides only will be used in the downstream analysis.
(See manual or manuscript for more detailed info). -
--custom-url: UniProt search URL is provided as an argument; program will
extract input sequences using provided URL.--utaxonomyarg is omitted
if this argument is specified. -
--no-bsearch: Do not perform BLASTP search. -
--offline-blastp: Perform offline blasting (RECOMMENDED). Provide path to nr database (databasePath) in a
config file 'defaults.cfg'. -
--run-peptidesieve: By default, CONSeQuence tool is only run in order to predict detectability
of peptides by MS. This option enables PeptideSieve to be executed as well. -
-C,--config: Specify path to the configuration file (e.g. /Users/me/Documents/defaults.cfg).
[default: ./defaults.cfg (current working directory)]. -
-l,--length: Coefficient of allowed length variation of entries. Allowed
lengths interval = (median length value) +- (coefficient of l variation)*(median length value). Entries with higher length
difference are removed. [default: 0.25] -
--no-putatives: Use this option if putative molecules from UniProt search should
be removed. -
-u,--utaxonomy: Restrict protein search in UniProt database for organisms
specified by taxonomy keywords bounded by quotes: for AND use
character '&', for OR use character '|', for NOT use character
'-'. (E.g. "Actinobacteria|Proteobacteria-Pseudomonadales" which
means Actinobacteria OR Proteobacteria without (NOT)
Pseudomonadales). [default: "Bacteria"] -
-c,--cleavages: Number of missed cleavages for the trypsin digestion of proteins.
[default: 0] -
-x,--mins: Smallest size [in AA] of digested peptide to be kept in a
dataset. [default: 8] -
-y,--maxs: Largest size [in AA] of digested peptide to be kept in a dataset.
[default: 25] -
-b,--btaxonomy: Limit ONLINE BLASTP search against proteins belonging to organisms
specified by taxonomy keywords bounded by quotes: for AND use
character '&', for OR use character '|', for NOT use character
'-'. (E.g. "Actinobacteria|Proteobacteria-Pseudomonadales" which
means Actinobacteria OR Proteobacteria without (NOT)
Pseudomonadales). Please note that in order to limit OFFLINE BLASTP search
by taxomony, user needs to provide file with taxids (see manual). [default: "Bacteria"] -
-k,--ktaxonomy: Specified genera/species (genera is represented by just one
word; species is represented by just two words separated by space)
will be represented by 3 peptides (per genera/species) in a final
list of selected peptides. Bound specified taxonomy by quotes; for
AND use character '&' (E.g. "Pseudomonas&Pseudomonas putida" will
output 3 peptides representing genera Pseudomonas in file
'Selected_peptides.genera' as well as 3 peptides representing
species Pseudomonas putida in file 'Selected_peptides.species').
[default: None] -
-s,--specificity: Peptide specificity score threshold. [default: 90.0] -
-a,--avoid-spec-filt-list: Provide a list of peptides for that specificity scores are omitted.
I.e. specificity score-based filtering step will not apply for such peptides.
Bound specified peptides by quotes and separate individual entries by comma
(E.g. "ENPPVLPK,SGLFTSEELPR"). -
-cd,--cdetectability: Minimum number of CONSeQence ML algorithms (out of 4) considering a peptide
as detectable by MS to pass detectability filter. Please note that maximum
value is 4. [default: 1] -
-pd,--pdetectability: PeptideSieve detectability score threshold. [default: 0.6] -
-f,--chemmod-filter: Minimum number of possible chemical modifications of a peptide
to be omitted from final selection lists. [default: 4] -
-n,--peptide-calc-count: Number of peptides with the highest coverage in terms of microbial species
to calculate specificity and detectability scores for. [default: 400] -
-N,--peptide-out-count: Number of peptides to be output to 'Selected_peptides.*' files. [default: 50] -
-t,--threads: Number of threads (processes) to be used in parallel blasting.
Works for online as well as offline blasting. [default: 4] -
-T,--timeout: Maximum time (in seconds) to wait for online BLASTP results.
[default: 1500] -
-z,--min-synname-length: Minimum number of words blastp synonymous name consist of to be
accepted as synonymous name. [default: 1] -
-U,--in-url: Specify UniProt URL in quotes. Applicable only if--custom-url
argument is specified. -
-i,--in-aa-file: Specify path to dataset with protein sequences in FASTA AA format (e.g.
infile.faa). Applicable only if--no-usearchargument is specified. Following
header formats are allowed: '>PROTEIN_ID' or '>PROTEIN_ID~COV=<value>' if
coverage (expected copy number) of entries is also provided.
(E.g. >enzyme4552~COV=12.5). Value can be either integer or float larger than 1.0. -
-e,--in-extra-aa-file: Specify path to an extra input fasta AA file (e.g. infile_extra.faa).
Applicable only if--extra-inputargument is specified. Following
header formats are allowed: '>PROTEIN_ID' or '>PROTEIN_ID~COV=<value>' in
case of coverage (expected copy number) of entries is also provided.
(E.g. >enzyme4552~COV=12.5). Value can be either integer or float larger than 1.0. -
-I,--in-blastp-file: Specify path to 'blastp.xml' file generated in previous program
run to be used for functional specificity calculations instead of re-runing
long-lasting BLASTP search on the same dataset.' -
--stats-only: Print general info, protein statistics and figures, and exit.
Gather catechol-1,2-dioxygenase protein entries from UniProt DB, compute basic statistics and exit program:
pepMANDIS.py -m "catechol-1,2-dioxygenase" --stats-only
Perform offline blasting using 12 threads, with path to the configuration file specified:
pepMANDIS.py -m "catechol-1,2-dioxygenase" --offline-blastp -t 12 -C /Users/me/Software/pepmandis/config/defaults.cfg
Limit UniProt retrieval to protein entries belonging to either Actinobacteria or Proteobacteria phyla, perform offline blasting with 12 threads, avoid specificity score-based filtering for peptides 'SQSDFNLR,HGQRPAHIHFFISAPGHR,LIAAAGWHAWRPAHLHVK', peptides must be considered as detectable by at least 2 CONSeQuence algorithms:\
pepMANDIS.py -m "catechol-1,2-dioxygenase" -u "Actinobacteria|Proteobacteria" --offline-blastp -t 12 -a "SQSDFNLR,HGQRPAHIHFFISAPGHR,LIAAAGWHAWRPAHLHVK" -cd 2
Proteins from file 'extraProteins.faa' will be compared against entries gathered from UniProt DB, set length variation coefficient to 1 (i.e. do not
filter proteins according to their lengths), set minimum peptide size to 6 amino acids:
pepMANDIS.py -m "catechol-1,2-dioxygenase" --extra-input -e extraProteins.faa -l 1.0 -x 6
Avoid gathering of input proteins from UniProt DB and use proteins from file 'myProteins.faa' instead, use 1200 peptides with the highest species coverage for properties calculations, and re-use 'blastp_results_refined.xml' from previous run:\
pepMANDIS.py -m "catechol-1,2-dioxygenase" --no-usearch -i myProteins.faa -n 1200 --no-bsearch -I results_catechol12dioxygenase_04_Feb_2021_13.33.21/blastp_results_refined.xml
genera_pie_chart_1.uniprot_entries.png: chart illustrating frequencies of occurrence of input proteins (retrieved from UniProt DB) within the genera belonging to the most abundant phylum.
genera_pie_chart_2.uniprot_entries.png: chart illustrating frequencies of occurrence of input proteins (retrieved from UniProt DB) within the genera belonging to the second most abundant phylum.
phyla_pie_chart.uniprot_entries.png: chart illustrating frequencies of occurrence of input proteins (retrieved from UniProt DB) within the phylum level.
length_distribution.uniprot_entries.png: histogram showing the length distribution of input proteins.
UniProt_proteins.faa: FASTA AA file with protein sequences retrieved from UniProt DB that were used for the downstream analysis.
initial_info.txt: file providing information about input parameters as well as summary statistics such as median, mean and standard deviation of protein lengths before and after refinement, and taxonomy statistics (i.e. counts of proteins belonging to different phyla, genera and species).
peptide_candidates_for_calculations\*.faa: FASTA AA files with peptides selected for calculations of specific properties.
peptide_candidates_for_calculations.txt: tab-delimited file with peptides selected for calculations of specific properties.
possible_chemical_modifications.txt: tab-delimited file containing peptide sequences along with information about the number and type of possible chemical modifications of ther AA sequences.
blastp_results.xml: XML file with results of BLASTP search.
blastp_results_refined.xml: XML file with refined results of BLASTP search.
peptide_blastp_specificity.txt: file containing information about the synonyms of the target protein generated from BLASTP search as well as information regarding the specificity score calculations.
Peptides_complete_info.txt: tab-delimited file containing all the peptides within the specified length thresholds derived from initial proteins (when primary protein/peptide sequences are compared against a secondary dataset, only the peptides having an exact match are included) together with information, such as AA sequence, frequency of occurrence among proteins, number of different species encoding each peptide, PeptideSieve and CONSeQuence scores, functional specificity score, number of possible chemical modifications and related taxonomy.
Selected_peptides.genera: list of predicted best target peptides amenable to LC-MS/MS analysis covering as many genera as possible.
Selected_peptides.species: list of predicted best target peptides amenable to LC-MS/MS analysis covering as many species as possible.
Matej Medvecky
Manolis Mandalakis
Medvecky M, Mandalakis M. (2021). PepMANDIS: A peptide selection tool for designing function-based targeted proteomic assays in mixed microbial communities. Front Chem. 9:722087. doi: 10.3389/fchem.2021.722087