Skip to main content

LisSero

In silico serogroup typing prediction for Listeria monocytogenes

PyPI PyPI - Python Version PyPI - Wheel

Authors

  • Jason Kwong (@kwongjc) - GitHub: kwongj
  • Josh Zhang (@abcdtree) - GitHub: abcdtree
  • Torsten Seemann (@torstenseemann) - GitHub: tseemann

Maintainers

  • MDU PHL - Josh Zhang, Kristy Horan, and Anders Gonçalves da Silva

Dependencies

Installation

pip3 install lissero

Installing BLAST 2.10.0

Brew:

brew install blast

Conda:

conda install -c bioconda blast 

In silico serogrouping for Listeria monocytogenes

LisSero is based on a method of predicting serogroup for Listeria monocytogenes using PCR, as described by Doumith et al (see References).

It detects the presence or absence of 5 genes (lmo1118, lmo0737, ORF2110, ORF2819 and Prs).

The patterns obtained reflect the four main serotypes (1/2a, 1/2b, 1/2c, and 4b) obtained from food and human sources.

The patterns are not based on genes involved in somatic (O) or flagellar (H) biosynthesis, and are not specific to just one serotype, but rather to a group of serotypes.

Serogroup lmo1118 lmo0737 ORF2110 ORF2819 Prs
1/2a, 3a - + - - +
1/2b, 3b, 7 - - - + +
1/2c, 3c + + - - +
4b, 4d, 4e - - + + +
4b, 4d, 4e* - + + + +
Listeria spp. +

If only Prs is detected, these isolates are often serotype 4a or 4c, though LisSero reports these as "Nontypable".

Usage

$ lissero --help

Usage: lissero [OPTIONS] FASTA...

  In silico serogroup prediction for L. monocytogenes. Alleles: lmo1118,
  lmo0737, ORF2819, ORF2110, Prs

  References:

  * Doumith et al. Differentiation of the major Listeria monocytogenes
  serovars by multiplex PCR. J Clin Microbiol, 2004; 42:8; 3819-22

Options:
  -s, --serotype_db TEXT
  --min_id FLOAT          Minimum percent identity to accept a match. [0-100]
                          [default: 95.0]

  --min_cov FLOAT         Minimum coverage of the gene to accept a match.
                          [0-100]  [default: 95.0]
  --logfile TEXT          Save log to a file instead of printing to stderr
  --debug
  --help    

Example usage

lissero my_fasta.fa

Example output

ID SEROTYPE PRS LMO0737 LMO1118 ORF2110 ORF2819 COMMENT
/path/to/my_fasta.fa 4b, 4d, 4e FULL NONE NONE FULL FULL

Output explained

The output consist of 8 columns:

  • ID: At the moment the full path to your file
  • SEROTYPE: A predicted serotype if possible, otherwise Nontypeable
  • Five columns for each of the genes with either:
    • FULL: for a complete match to the gene in the database (as defined by the --min_cov and --min_id flags which default to at least 95% coverage and percent id)
    • NONE: when there is no match to the database
    • PARTIAL: where there are matches that fall below the --min_cov and --min_id thresholds
  • COMMENTS: Which will try to explain a Nontypeable results. Current cases are:
    • No Prs found: when there is no FULL match to the Prs gene is not likely to be a Listeria monocytogenes
    • Presence of all 5 genes, not a known serotype: when all 5 genes are present
    • No combination of fully matched genes resulted in a known serotype: An unknown combination
    • In addition, it will say Unusual 4b with lmo0737 when reporting 4b, 4d, 4e* serotype

Change Log

Version 0.4.1

  • Implemented unit test for all possible 32 possible gene patterns
  • Implemented more verbose output with presence/absence info for each gene
  • Implemented test of FASTA file, and will exit with warning if a file does not appear to be a FASTA file
  • Implement test of whether an input file exists or not
  • Implemented logging using Loguru
  • Added option to log to a file (--logfile; stderr remains default)
  • Logging now includes the BLAST command used
  • Removed all references in the code to Binary Typing
  • Implemented --version flag
  • Added some better docs

Version 0.4.0

  • Removed support for Binary Typing
  • Consolidated repos in MDU-PHL
  • Changed executable from run_lissero to lissero

Bugs

Please submit via the GitHub issues page: https://github.com/MDU-PHL/LisSero/issues

Software Licence

GPLv2: https://github.com/MDU-PHL/LisSero/blob/master/LICENSE

References

  • Doumith et al. Differentiation of the major Listeria monocytogenes serovars by multiplex PCR. J Clin Microbiol, 2004; 42:8; 3819-22.

Metadata

Release files for lissero 0.4.9

For a detailed explanation of source distributions (sdists) and built distributions (wheels), please see the package formats documentation.

Source distribution (sdist)

Source distribution for lissero 0.4.9
File Size Uploaded Provenance
lissero-0.4.9.tar.gz 30.9 kB Without provenance Details

Built distribution (wheel)

Table of built distributions (wheels) for lissero 0.4.9
File Interpreter ABI Platform
lissero-0.4.9-py3-none-any.whl Python 3 none any Details

Total release size: 59.6 kB

Release files / lissero-0.4.9.tar.gz

Download URL lissero-0.4.9.tar.gz
Size 30.9 kB
Tags Source
SHA-256 checksum
How to use checksums
533f8863d8e5a063c5a11c4458342b44a33399366a53ef797f291485597cf94c
BLAKE2b-256 checksum
How to use checksums
841f37ef562c3c4e32562d75038391a95e69b59b3b43e36bff5df8b1dbdf653d
Upload date
Uploaded using Trusted Publishing?
What is trusted publishing?
No
Uploaded via twine/3.4.1 importlib_metadata/3.10.0 pkginfo/1.7.0 requests/2.25.1 requests-toolbelt/0.9.1 tqdm/4.59.0 CPython/3.9.2

Release files / lissero-0.4.9-py3-none-any.whl

Download URL lissero-0.4.9-py3-none-any.whl
Size 28.7 kB
Tags Python 3
SHA-256 checksum
How to use checksums
8047f5beef6462bd4c065d945060b4935eae84ad4db023ee4dc45c1fa80317ea
BLAKE2b-256 checksum
How to use checksums
91bce6c0d76af4b88163f6bf1444446827ddfe842c696919c61e46374c91980f
Upload date
Uploaded using Trusted Publishing?
What is trusted publishing?
No
Uploaded via twine/3.4.1 importlib_metadata/3.10.0 pkginfo/1.7.0 requests/2.25.1 requests-toolbelt/0.9.1 tqdm/4.59.0 CPython/3.9.2

Security for lissero 0.4.9

Provenance

Provenance describes where a file came from. On PyPI, provenance is shared via attestations, which provide a verifiable record of the build or publishing details. View details, limitations and caveats.

No provenance found

None of the files in this release were uploaded with provenance metadata.

A note on package security

PyPI is a repository for distributing packages, not a service for auditing them. While third-party security researchers and our staff do their best to detect and remove malicious packages, PyPI cannot guarantee the quality, security or suitability of any given package.

To learn more about protecting yourself from malicious actors, visit our package security documentation.

Anthropic, PBC Visionary sponsor Bloomberg Visionary sponsor Hudson River Trading Visionary sponsor Meta Visionary sponsor NVIDIA Visionary sponsor Microsoft Sustainability sponsor Depot Continuous Integration AWS Cloud computing and Security Sponsor Datadog Monitoring Fastly CDN Google Download Analytics Sentry Error logging StatusPage Status page