Skip to main content

No project description provided

Project description

MiSoS(oup)

Code style: black PyPI version

Minimal Supplying Community Search (misosoup) is a command line tool that searches for minimal microbial communities --- where every member is required for the community to persist in a medium. misosoup can be used for two major objectives: (1) Find minimal communities in a given medium or (2) Find minimal supplying communities in a medium; where every member is required for growth of a strain / species of interest (focal strain).

As input misosoup takes a set of genome-scale metabolic models; one for each strain / species that will be considered as potential community member. The tool will then execute a series of constraint-based optimizations to find minimal communities. For the computation of the solutions it is assumed a metabolic steady-state (as in Flux Balance Analysis) but no optimization criteria are required (although can be optionally applied). Once computed, community members, their respective growth rates and there metabolic consumption and secretion will be reported in a human-readable and parseable format.

Details

To find minimal microbial communities misosoup solves a repeated sequence of optimization problems using MILP formulations:

  1. Minimize the number of community member (see Zelezniak, et al. PNAS doi:10.1073/pnas.1421834112)
  2. Fix the active community members and check the feasibility of the entire community.
  3. Optionally: Optimize growth of the total community biomass.
  4. Optionally: Perform an optimization to reflect parsimonious enzyme usage (see Lewis, et al. Mol Syst Bio doi:10.1038/msb.2010.47)

Install MiSoS(soup)

misosoup requires a version of Python >3.7 and <3.10 (it will be compatible with 3.10 soon).

The latest stable version of misosoup is available through pip and hence it can easily installed executing:

pip install misosoup

Dependencies

  • misosoup uses the Guroby optimizer that is free for academic use but it requires a license.
  • Academic licenses can be obtained on the gurobi license page
  • To retrieve a license, the grbgetkey command is needed. The command is not provided with gurobipy when installed through pip. Please download the full gurobi version on their website and install gurobi with their installer.

Notes

  • If you are unable to install gurobipy, it may need to be installed manually e.g. on a hpc cluster, to make use of the local gurobi installation. In such a case please refer to the instructions on the cluster support page.

  • If misosoup requirements are not those of your local installation, you may consider installing it within a conda environment. Once you have anaconda installed in your computer you create an environment:

conda create --name misosoup --channel gurobi python=3.9 gurobi

then you activate it:

conda activate misosoup

and finally you can install misosoup within that environment.

pip install misosoup

By default, pip installation comes with a free-trial license. Once you obtain your academic license, you want to substitute the free license with the academic one. Search in the anaconda environment the license file:

find $path_misosoup_environment -iname '*gurobi.lic'

Which will return the $path_free_license. Now simply overwrite the free license by the academic one:

cp $path_academic_license $path_free_license

Usage

After installation, you can easily use misosoup with:

misosoup MODEL_PATH/*.xml --output OUTPUT_FILE --media MEDIA_FILE --strain STRAIN

Arguments

  • MODEL_PATH: indicates the path to the directory where the metabolic models are described. Strains with metabolic models included in this directory will be considered as potential members in the minimal communities. The models should be in sbml format and follow the same naming conventions (e.g. if glucose's id in one model is 'glc__D', the same id should be used in the other models).
  • --output
    • Use OUTPUT_FILE for output in yaml format. If it is not given, the results will be printed to stdout.
  • --media
    • Load media from MEDIA_FILE. The file should contain the description of the growth media that shall be tested. The file should contain a dictionary with all media that the community should be evaluated on. Each of the media needs to contain a dictionary of exchange reactions and there lower bound, (i.e. R_EX_ac_e: -10 provides acetate to the communities). The medium with id base_medium will be added to all media.
  • --strain
    • Indicates the focal STRAIN model id. If no strain is provided, misosoup computes minimal communities.

Additional arguments

misosoup can be used with the additional arguments:

misosoup MODEL_PATH/*.xml --output OUTPUT_FILE --media MEDIA_FILE --strain STRAIN --parsimony --community-size COMMUNITY_SIZE --minimal-growth MINIMAL_GROWTH --exchange-format EXCHANGE_FORMAT --validate --log LOG
  • --parsimony
    • If this flag is used the algorithm will return the solution that minimizes the total flux. This does not affect the community members but can alter what each member consumes and secretes.
  • --community-size
    • Instead of looking for all communities, find all communities up to size COMMUNITY_SIZE
  • --minimal-growth
    • Set the MINIMAL_GROWTH rate of strains. Every strain that makes up a community needs to satisfy this minimal growth constraint. The default growth rate used is 0.01 (1/h).

For further description:

misosoup --help

Output file

The .yaml output file will give:

  • The community members: y_<STRAIN_NAME>: 1.0.
  • The growth of each community member Growth_<STRAIN_NAME>.
  • The total community growth community_growth.
  • The flux at which metabolites are taken up or secreted to the medium. Negative and positive fluxes indicate consumption and secretion, respectively. This consumption/secretion pattern is given for:
    • The community as a whole: (R_EX_<ID>_e)
    • Each community member separately (R_EX_<ID>_<STRAIN_NAME>_i).

Example

cd example

The following code will run misosoup to find minimal supplying communities for A1R12 in a medium that contains acetate as carbon source:

misosoup ./strains/*.xml --output ./output_example.yaml --media media_mbm_no_co2_hco3.yaml --strain A1R12 --parsimony

In the example, we run misosoup to find minimal supplying communities that would allow growth of the strain A1R12 in MBM with acetate (ac) as the sole source of carbon. Looking at the output of the simulation example_output.yaml) you'll see that misosoup found two alternative supplying communities:

  • Solution 1: A1R12 can grow when in the presence of I3M07. If we inspect this solution in more detail we can see (for example):
    • Each strain produces carbon dioxide. We note this by looking at the strain-specific carbon dioxide fluxes: R_EX_co2_e_A1R12_i: 0.742 and R_EX_co2_e_I3M07_i: 0.957.
    • The community as a whole also produces carbon dioxide, which can be seen looking at the community-level carbon dioxide flux R_EX_co2_e: 1.699.
  • Solution 2: A1R12 can grow when in the presence of I2R16. A similar analysis to the one conducted for solution 1 could be followed.

Citation

If you use misosoup, please cite X.

Workflows

snakemake is a useful tool to execute many experiments and gather results. See misosoup Workflow Template on how to use it.

Development

Any contributions are welcome.

MIT License

Copyright (c) 2021 Nicolas Ochsner

Permission is hereby granted, free of charge, to any person obtaining a copy of this software and associated documentation files (the "Software"), to deal in the Software without restriction, including without limitation the rights to use, copy, modify, merge, publish, distribute, sublicense, and/or sell copies of the Software, and to permit persons to whom the Software is furnished to do so, subject to the following conditions:

The above copyright notice and this permission notice shall be included in all copies or substantial portions of the Software.

THE SOFTWARE IS PROVIDED "AS IS", WITHOUT WARRANTY OF ANY KIND, EXPRESS OR IMPLIED, INCLUDING BUT NOT LIMITED TO THE WARRANTIES OF MERCHANTABILITY, FITNESS FOR A PARTICULAR PURPOSE AND NONINFRINGEMENT. IN NO EVENT SHALL THE AUTHORS OR COPYRIGHT HOLDERS BE LIABLE FOR ANY CLAIM, DAMAGES OR OTHER LIABILITY, WHETHER IN AN ACTION OF CONTRACT, TORT OR OTHERWISE, ARISING FROM, OUT OF OR IN CONNECTION WITH THE SOFTWARE OR THE USE OR OTHER DEALINGS IN THE SOFTWARE.

Project details


Download files

Download the file for your platform. If you're not sure which to choose, learn more about installing packages.

Source Distribution

misosoup-2.1.1.tar.gz (24.4 kB view hashes)

Uploaded Source

Built Distribution

misosoup-2.1.1-py3-none-any.whl (25.2 kB view hashes)

Uploaded Python 3

Supported by

AWS AWS Cloud computing and Security Sponsor Datadog Datadog Monitoring Fastly Fastly CDN Google Google Download Analytics Microsoft Microsoft PSF Sponsor Pingdom Pingdom Monitoring Sentry Sentry Error logging StatusPage StatusPage Status page