Minimal Supplying Community Search (misosoup) is a command line tool
designed to search for minimal microbial communities, wherein every member is
essential for the community's persistence within a given medium. Its primary
functions include:
- Identifying minimal communities within a specified medium.
- Identifying minimal "supplying" communities within a medium, where each member is necessary for the growth of a focal strain or species of interest.
To utilize misosoup, users provide a set of genome-scale metabolic models,
each representing a potential member of the community. The program then employs
constraint-based optimizations to determine minimal communities. These
optimizations assume a metabolic steady-state, akin to Flux Balance Analysis.
Once computations are complete, misosoup outputs information about community
members, their respective growth rates, as well as their metabolic consumptions
and secretions, presented in a format both readable by humans and parseable by
software.
To find minimal microbial communities misosoup solves a repeated sequence of
optimization problems using MILP formulations:
- Minimize the number of community member (see Zelezniak, et al. PNAS doi:10.1073/pnas.1421834112).
- Fix the active community members and check the feasibility of the entire community.
- Optionally: Maximize community biomass (sum of individual growth rates).
- Optionally: Perform an optimization to reflect parsimonious enzyme usage (see Lewis, et al. Mol Syst Bio doi:10.1038/msb.2010.47).
misosoup requires a version of Python >=3.9 and <3.12.
The latest stable version of misosoup is available through pip and hence it can be installed executing:
pip install misosoupmisosoupuses theGurobyoptimizer that is free for academic use but does require a license.- Academic licenses can be obtained on the gurobi license page
- Precise instructions on how to obtain and setup the gurobi licenses can be found on the gurobi website.
After installation, detailed usage instructions can be found with:
misosoup -hTo use misosoup with its default settings, you can use the following command:
misosoup MODEL_PATH/*.xml --output OUTPUT_FILE --media MEDIA_FILE --strain STRAINMODEL_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. An example file with a correct format to
introduce a media composition can be found in
examples/.
- Load media from MEDIA_FILE. An example file with a correct format to
introduce a media composition can be found in
--strain- Indicates the focal STRAIN model id. If no strain is provided,
misosoupcomputes minimal communities.
- Indicates the focal STRAIN model id. If no strain is provided,
misosoup can be used with additional arguments.
misosoup MODEL_PATH/*.xml --output OUTPUT_FILE --media MEDIA_FILE --strain STRAIN --parsimony --community-size COMMUNITY_SIZE --minimal-growth MINIMAL_GROWTH--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 is 0.01 (1/h).
As output misosoup will generate a yaml file with the following general
structure:
medium:
strain|min:
- <Solution1>
- <Solution2>The solutions indicated above contain two entries, the first is a dictionary
with the community composition, and the second is a dictionary with the growth
rates and fluxes through exchange reactions of the respective optimized
solution. An example of an output file can be found in examples/.
This package includes an example directory containing models and media
specifications, enabling users to perform a straightforward analysis using
misosoup. The example demonstrates how to identify minimal microbial
communities that utilize acetate as the sole carbon source. The results of this
analysis are pre-generated and available in the directory for reference.
To execute the analysis, navigate to the example directory and use the
following command:
cd example/marine/
misosoup ./strains/*.xml --output ./output.yaml --media media.yaml --strain A1R12 --media-select acThis command instructs misosoup to analyze the specified microbial strains
for their ability to support the growth of strain
A1R12 in a Minimal Basal Medium
(MBM) with acetate (ac) as the exclusive carbon source.
The simulation results, detailed in output.yaml, reveal two potential
microbial communities capable of supporting A1R12 growth:
- Solution 1: Community comprising A1R12 and I2R16, indicating a symbiotic relationship sufficient for growth on acetate.
- Solution 2: Community comprising A1R12 and I3M07. Detailed analysis of
this community shows:
- Both strains produce carbon dioxide as a by-product, with strain-specific
CO2 fluxes of
R_EX_co2_e_A1R12_i: 0.564for A1R12 andR_EX_co2_e_I3M07_i: 0.1312for I3M07. - The total community-level carbon dioxide production is quantified by the
flux
R_EX_co2_e: 1.695, highlighting the combined metabolic activity.
- Both strains produce carbon dioxide as a by-product, with strain-specific
CO2 fluxes of
These solutions showcase misosoup's ability to predict minimal microbial
communities based on specific metabolic requirements, facilitating targeted
research and application in microbial ecology and synthetic biology.
If you use misosoup, please cite our paper.
snakemake is a useful tool to execute many experiments and gather results.
See misosoup Workflow Template
on how to use it.
Any contributions are welcome.