pyngoST unifies molecular typing for Neisseria gonorrhoeae. By providing genome assemblies in fasta format, pyngoST can extract up to three typing schemes (NG-STAR, MLST and NG-MAST) and two modifications (NG-STAR Clonal Complexes and NG-MAST Genogroups). These schemes are detailed below:
- NG-STAR: N. gonorrhoeae Sequence Typing for Antimicrobial Resistance, hosted at Public Health Agency of Canada, National Microbiology Laboratory NG-STAR Canada. This is a typing scheme published by Demczuk et al. 2017 that targets 7 genes associated to cephalosporin, macrolides and fluoroquinolones resistance: penA, mtrR, porB, ponA, gyrA, parC and 23S rRNA.
- NG-STAR CCs (Clonal Complexes), published by Golparian et al, 2021. This scheme groups NG-STAR sequence types (STs) into Clonal Complexes (CCs) for a better fit of the typing scheme with the population structure of antimicrobial resistant (AMR) lineages.
- MLST (Multi-Locus Sequence Typing), hosted at PubMLST Neisseria. This scheme was published by Maiden et al, 1998 and targets 7 housekeeping genes of the Neisseria genus: abcZ, adk, aroE, fumC, gdh, pdhC and pgm.
- NG-MAST v2 (N. gonorrhoeae Multi-Antigen Sequence Typing), hosted at PubMLST Neisseria. This scheme was published by Martin et al. 2004 and targets 2 genes encoding rapidly-evolving surface antigens: porB and tbpbB.
- NG-MAST Genogroups, as described by Harris et al, 2018. As NG-MAST loci are highly-variable, they poorly match the population structure of N. gonorrhoeae. Genogroups were described to group NG-MAST types, however they are calculated on the specific dataset under study and thus, are not comparable among studies.
pyngoST is written in python3 and uses the pyahocorasick library for fast simultaneous multi-loci search in N. gonorrhoeae genomes.
First, a database is built that contains updated fasta files with all the known alleles for 7 NG-STAR, 7 MLST and 2 NG-MAST loci as well as the known NG-STAR, MLST and NG-MAST profiles up to the building of the database. Then, a simultaneous screening of all loci is performed on the input assembly files (in FASTA) format using the Aho-Corasick string-searching algorithm.
I recommend to create a python3 virtual environment and install pyngoST using pip.
## Create and activate a virtual environment (i.e. `venv` or any other name):
python3 -m venv venv
source venv/bin/activate
## Install pyngoST using pip install on the latest distribution
pip install pyngoST
Activate the virtual environment whenever you want to use pyngoST. Exit the virtual environment by running deactivate:
## Activate virtualenv
source venv/bin/activate
## Run pyngSTar
## Exit virtualenv
deactivate
NOTE: After installing with pip, the package can be run from /Users/username/venv/lib/python3.X/site-packages/pyngoST/pyngoST.py. You can add it to your PATH or create an alias to use it more easily, as in:
alias pyngoST.py="/Users/username/venv/bin/python3 /Users/username/venv/lib/python3.X/site-packages/pyngoST/pyngoST.py"
You can download updated allele and profiles files for the three schemes using -d. NG-STAR alleles and profiles will be downloaded and adapted from NG-STAR Canada). MLST and NG-MAST alleles and profiles will be downloaded from PubMLST Neisseria. By default, it will create the database under the allelesDB folder if it does not exist in the working directory. You can provide a database name with -n. If a CSV file containing NG-STAR CCs is included with -cc, CCs will be integrated into the database.
## Create the database as 'allelesDB'
pyngoST.py -d
## Create the database with another name
pyngoST.py -d -n othernameDB
## Create the database with another name and include NG-STAR CCs
pyngoST.py -d -n othernameDB -cc NGSTAR_CCs.csv
During the creation of the database, a dictionary containing all alleles of all loci is saved as a pickle file, which will be loaded every time pyngoST is run.
If you choose to manually modify any of the files in the database and/or you want to include NG-STAR CCs (not previously included when the database was downloaded), you need to update the existing pickle file in the database with -u. Use -p to specify the path to the existing database.
## Update the pickle file in the database
pyngoST.py -u -p /path/to/allelesDB
## Incorporate NG-STAR CCs and update the pickle file in the database
pyngoST.py -u -p /path/to/allelesDB -cc NGSTAR_CCs.csv
usage: pyngoST [options]
pyngoST: fast, simultaneous and accurate multiple sequence typing of Neisseria gonorrhoeae genome collections
Citation:
Sanchez-Buso L, Sanchez-Serrano A, Golparian D and Unemo M.
pyngoST: fast, simultaneous and accurate multiple sequence typing of Neisseria gonorrhoeae genome collections.
Preprint: https://doi.org/10.1099/mgen.0.001189
GitHub: https://github.com/leosanbu/pyngoST
optional arguments:
-h, --help show this help message and exit
-i INPUT [INPUT ...], --input INPUT [INPUT ...]
Input files (fasta or tab/csv)
-r READ_FILE, --read_file READ_FILE
File containing the paths to the input files
-s SCHEMES, --schemes SCHEMES
Typing schemes to query separated by commas (options: NG-STAR, MLST, NG-MAST) (default=NG-STAR)
-g, --genogroups Calculate NG-MAST genogroups from NG-MAST types (default=False)
-c, --ngstarccs Include NG-STAR CCs in output table (default=False)
-m, --mosaic_pena Report if the penA allele sequence is a mosaic or semimosaic (default=False)
-b, --blast_new_alleles
Use blastn to find the closest alleles to new ones (default=False)
-a, --alleles_out Print fasta files with new alleles (optional, default=False)
-q OUT_PATH, --out_path OUT_PATH
Path used to save output files (default: current directory)
-o OUT_FILENAME, --out_filename OUT_FILENAME
Name of file to print the results table to (optional, default=screen output)
-y ONLY_ASSIGNCCS, --only_assignccs ONLY_ASSIGNCCS
Only assign CCs from a table with NG-STAR STs. Indicate as value the number of the column that contains the STs (optional, default=None)
-z, --only_assignsts Only assign STs from a table with NG-STAR, MLST and/or NG-MAST profiles (optional, default=None)
-t NUM_THREADS, --num_threads NUM_THREADS
Number of processes to use for computation (optional, default=1)
-p PATH, --path PATH Path to database containing MLST/NG-STAR alleles and profiles. If not available, use -d to create an updated database
-d, --download_db Download updated allele and profile files and create database
-n DB_NAME, --db_name DB_NAME
Name of the folder that will contain the database in case a download is requested with -d (default=allelesDB in working directory)
-u, --update Only recreate the database pickle file
-cc NGSTARCCSFILE, --ngstarccsfile NGSTARCCSFILE
File with the NG-STAR clonal complexes (NG-STAR CCs) database (csv) to integrate to NG-STAR profiles
| Option | Description |
|---|---|
| -i | list of assembly files (* can be used to input multiple files in a directory). |
| -r | text file containing a list of paths to assembly files. |
| -s | schemes to query and report: NG-STAR,MLST,NG-STAR or any combination/order separated by commas. |
| -g | calculate NG-MAST genogroups from NG-MAST typing using the rules described in Harris et al, 2018. |
| -c | report NG-STAR Clonal Complexes from NG-STAR STs in the final results table. |
| -m | report the type of penA mosaicism (mosaic, semi-mosaic or non-mosaic). |
| -b | blast new alleles to identify the closest among the known ones. |
| -a | save new alleles to output fasta files. |
| -o | name of output file where to save the results table. By default, results will print to the screen. |
| -q | path where to save results if different from the working directory. |
| -y | only call NG-STAR Clonal Complexes from a table of NG-STAR STs. Specify the number of column containing the STs. |
| -z | only assign STs from a table containing allelic profiles of any of NG-STAR, MLST and NG-STAR (specify with -s). |
| -t | number of threads for multithreading the main processing function from fasta files. |
| -p | path to the database file to be used by pyngoST. |
| -d | download allele and ST profile files and create the database. |
| -n | name of the database folder if different from allelesDB. |
| -u | update the database by recreating the pickle file. |
| -cc | input CSV file containing the NG-STAR Clonal Complexes database. |
The main feature of pyngoST is to extract molecular typing information from N. gonorrhoeae assembly files. Input files can be indicated with -i directly or inside a text file, which can be read by pyngoSTusing -r. The path to the database is specified with -p and the typing schemes requested with -s (any of NG-STAR, NG-MAST and/or MLST in any order). Examples are shown below, including other options.
By default, if -s is not specified, only NG-STAR STs will be reported. Use -r filelist.txt with a text containing the paths to multiple fasta files instead of -i *.fasta.
pyngoST.py -i *.fasta -p /path/to/allelesDB
Any of the NG-STAR, MLST and NG-MAST schemes can be requested with -s in any order. This order will be also used for the output table. NG-STAR CCs can be included into the reported table with -c and NG-MAST genogroups can be calculated with -g. Please note that genogroups calculation is computationally expensive for large datasets.
pyngoST.py -i *.fasta -p /path/to/allelesDB -s MLST,NG-MAST,NG-STAR -c -g
The output table for -s MLST,NG-MAST,NG-STAR -c -g looks like the following, including the columns Genogroup after the NG-MAST profile and NG-STAR_CC after the NG-STAR profile:
strain MLST abcZ adk aroE fumC gdh pdhC pgm NG-MAST POR TBPB Genogroup NG-STAR penA mtrR porB ponA gyrA parC 23S NG-STAR_CC
31919_4_101.fasta 8135 59 39 67 156 188 153 133 387 266 118 G387 3658 15.001 424 100 100 100 2 100 CC893
31919_4_12.fasta 11975 59 39 762 111 188 71 223 13571 7834 16 G2 84 22.001 15 100 100 100 7 100 CC352
31919_4_16.fasta 9363 126 39 67 238 148 153 133 12302 908 267 G12302 168 2.001 39 11 100 7 4 100 CC168
31919_4_17.fasta 11975 59 39 762 111 188 71 223 2 2 16 G2 84 22.001 15 100 100 100 7 100 CC352
Use -o <outfilename> to save output to file.
Blasting of new alleles to find the closest among the known ones can be requested with -b. These new alleles can be saved to fasta files with -a. Please, note that you need to have a blast installation in your PATH.
pyngoST.py -i *.fasta -p /path/to/allelesDB -s MLST,NG-MAST,NG-STAR -b -a
New alleles will be saved to individual .fasta files ending in <input_file>.<locus_name>.fasta. As an example, a new abcZ allele of the MLST scheme will be saved as 32386_1_293.fasta.abcZ.fasta and contains the following sequence:
>abcZ_NODE_4_length_153129_cov_24.801849_9917:10349
TTTGATACTGTTGCCGAAGGTTTGGGCTAAATTCGCGATTTATTGCGCCGTTATCATCATGTCAGCCATGAGTTGGAAAATGGTTCGAGTGAGCTCTTATTGAAAGAGCTTAACGAATTGCAACTTGAAATCGAAGCGAAGGACGGTTGGAAACTGGATGCGGCAGTCAAGCAGACTTTGGGGGAACTCGGTTTGCCGGAAAACAAAAAAATCGGCAACCTTTCCGGCGGTCAGAAAAAACGCGTCGCCTTAGCGCAGGCTTGGGTACAGAAGCCCGATGTATTGTTACTGGACGAACCGACCAACCATTTGGATATCGACGCGATTATTTGGTTGGAAAACCTGCTCAAAGCGTTTGAAGGCAGCTTGGTCGTGATTACCCACGACCGCCGTTTTTTGGACAATATCGCCACGCGCATTGTCGAACTCGATC
The structure of the sequence name is as follows:
<locus_name>_<contig_name>_<start_coordinate>:<end_coordinate>
where the coordinates indicate the exact position in the contig where this sequence was extracted.
New allelic sequences and STs should be submitted to curators at PubMLST Neisseria or NG-STAR Canada for assignment.
NOTE: From v1.1.3, pyngoST tries to find a specific trimming end for novel TBPB alleles (...AAAA####). It tries its best, however, sometimes it is confused by another similar region nearby. In this case, longer sequences are given as output and will need to be manually curated by users. A warning message will specify which output files are affected, e.g.:
# Warning: ECDC_PL18_047.fasta.TBPB.fasta is longer than 450 bp, please revise end trimming before submitting to PubMLST.
pyngoST has two extra functionalities that result from common procedures used in molecular epidemiology of N. gonorrhoeae:
- ST assignment from a table of allelic profiles of any of the NG-STAR, MLST and/or NG-MAST schemes.
- NG-STAR CCs assignment from a table containing a column with NG-STAR STs.
In these two cases, the input file is a CSV or tabular table containing the mentioned information and is specified with
-i. Other necessary parameter is-pto specify the path to an updated database. The specific options to use these features are exemplified below:
To run pyngoST from a table of allelic profiles use -z. Specify the typing schemes to look at with -s and include -c if NG-STAR CCs are also requested.
pyngoST.py -i testassignSTs.tsv -p /path/to/allelesDB -z -s MLST,NG-MAST,NG-STAR -c
The example testassignSTs.tsv file looks like:
strain penA mtrR porB ponA gyrA parC 23S abcZ adk aroE fumC gdh pdhC pgm POR TBPB
31919_4_101.fasta 15.001 424 100 100 100 2 100 59 39 67 156 188 153 133 266 118
31919_4_12.fasta 22.001 15 100 100 100 7 100 59 39 762 111 188 71 223 7834 16
31919_4_16.fasta 2.001 39 11 100 7 4 100 126 39 67 238 148 153 133 908 267
31919_4_17.fasta 22.001 15 100 100 100 7 100 59 39 762 111 188 71 223 2 16
And the output file will contain a MLST, NG-MAST, NG-STAR and NG-STAR_CCs columns as requested:
strain MLST abcZ adk aroE fumC gdh pdhC pgm NG-MAST POR TBPB NG-STAR penA mtrR porB ponA gyrA parC 23S NG-STAR_CC
31919_4_101.fasta 8135 59 39 67 156 188 153 133 387 266 118 3658 15.001 424 100 100 100 2 100 CC893
31919_4_12.fasta 11975 59 39 762 111 188 71 223 13571 7834 16 84 22.001 15 100 100 100 7 100 CC352
31919_4_16.fasta 9363 126 39 67 238 148 153 133 12302 908 267 168 2.001 39 11 100 7 4 100 CC168
31919_4_17.fasta 11975 59 39 762 111 188 71 223 2 2 16 84 22.001 15 100 100 100 7 100 CC352
To only call NG-STAR CCs from a table containing a column with NG-STAR STs use -y <column_number>, where <column_number> is the number of the column (starting from 1) in the table that contains the NG-STAR STs. The -c option is also requested to activate the search of NG-STAR CCs.
pyngoST.py -i testNGSTAR.tsv -p /path/to/allelesDB -c -y 2
The example testNGSTAR.tsv file looks like:
strain NG-STAR penA mtrR porB ponA gyrA
31919_4_101.fasta 3658 15.001 424 100 100 100
31919_4_12.fasta 84 22.001 15 100 100 100
31919_4_16.fasta 168 2.001 39 11 100 7
31919_4_17.fasta 84 22.001 15 100 100 100
And the output table will have an appended column containing the NG-STAR CCs:
strain NG-STAR penA mtrR porB ponA gyrA NG-STAR_CC
31919_4_101.fasta 3658 15.001 424 100 100 100 CC893
31919_4_12.fasta 84 22.001 15 100 100 100 CC352
31919_4_16.fasta 168 2.001 39 11 100 7 CC168
31919_4_17.fasta 84 22.001 15 100 100 100 CC352
In both -y and -z modes, the input file can also be comma-separated (CSV). The output results will show using the same separator than the input files.
Use -o <outfilename> to save output to file.
pyngoST was conceived to be a fast command line tool for molecular typing of N. gonorrhoeae genome collections. When using it on a large number of fasta files, some tasks can be computationally expensive, such as blasting new alleles to existing ones or, especially, calculating NG-MAST genogroups, which compromise speed. To overcome this, pyngoST includes multithreading using the concurrent.futures module.
Multithreading is applied to the process_files() function, which, for each input fasta file, finds exact matches of existing alleles for all loci of the three schemes using pyahocorasick, blasts new alleles if requested, and assigns STs from allele profiles.
Please note that only computationally intensive tasks are worth multithreading, such as combining the blasting of new alleles with the calculation of NG-MAST genogroups. You can multithread using -t <number of threads, i.e:
## Run pyngoST on 400 FASTA files requesting the blasting of new alleles with -b and genogroups calculation with -g on 8 threads
pyngoST.py -i /path/to/400genomes/*.fasta -p /path/to/allelesDB -s MLST,NG-MAST,NG-STAR -c -g -b -t 8
The request of NG-STAR CCs with -c is not a calculation but only a query of the existing database and it does not add significantly more computation time compared to not requesting CCs.
If you use pyngoST or integrate it into your pipelines and use it in a scientific publication, we would appreciate if you could cite our work:
Sánchez-Busó L, Sánchez-Serrano A, Golparian D, Unemo M. pyngoST: fast, simultaneous and accurate multiple sequence typing of Neisseria gonorrhoeae genome collections. Microb Genom. 2024 Jan;10(1):001189. doi: 10.1099/mgen.0.001189. PMID: 38288762; PMCID: PMC10868605.