💎 metaGEM

Note An easy-to-use workflow for generating context specific genome-scale metabolic models and predicting metabolic interactions within microbial communities directly from metagenomic data.

metaGEM is a Snakemake workflow that integrates an array of existing bioinformatics and metabolic modeling tools, for the purpose of predicting metabolic interactions within bacterial communities of microbiomes. From whole metagenome shotgun datasets, metagenome assembled genomes (MAGs) are reconstructed, which are then converted into genome-scale metabolic models (GEMs) for in silico simulations. Additional outputs include abundance estimates, taxonomic assignment, growth rate estimation, pangenome analysis, and eukaryotic MAG identification.

⚙️ Installation

You can start using metaGEM on your cluster with just one line of code with the mamba package manager

mamba create -n metagem -c bioconda metagem

This will create an environment called metagem and start installing dependencies. Please consult the config/README.md page for more detailed setup instructions.

🔧 Usage

Clone this repo

git clone https://github.com/franciscozorrilla/metaGEM.git && cd metaGEM/workflow

Run metaGEM without any arguments to see usage instructions:

bash metaGEM.sh ``` Usage: bash metaGEM.sh [-t|--task TASK] [-j|--nJobs NUMBER OF JOBS] [-c|--cores NUMBER OF CORES] [-m|--mem GB RAM] [-h|--hours MAX RUNTIME] [-l|--local]

Options: -t, --task Specify task to complete:

                    SETUP
                        createFolders
                        downloadToy
                        organizeData
                        check

                    CORE WORKFLOW
                        fastp 
                        megahit 
                        crossMapSeries
                        kallistoIndex
                        crossMapParallel
                        kallisto2concoct 
                        concoct 
                        metabat
                        maxbin 
                        binRefine 
                        binReassemble 
                        extractProteinBins
                        carveme
                        memote
                        organizeGEMs
                        smetana
                        extractDnaBins
                        gtdbtk
                        abundance

                    BONUS
                        grid
                        prokka
                        roary
                        eukrep
                        eukcc

                    VISUALIZATION (in development)
                        stats
                        qfilterVis
                        assemblyVis
                        binningVis
                        taxonomyVis
                        modelVis
                        interactionVis
                        growthVis

-j, --nJobs Specify number of jobs to run in parallel -c, --nCores Specify number of cores per job -m, --mem Specify memory in GB required for job -h, --hours Specify number of hours to allocated to job runtime -l, --local Run jobs on local machine for non-cluster usage ```

🧉 Try it now

You can set up and use metaGEM on the cloud by following along the google colab notebook.

Please note that google colab does not provide the computational resources necessary to fully run metaGEM on a real dataset. This notebook demonstrates how to set up and use metaGEM by perfoming the first steps in the workflow on a toy dataset.

💩 Tutorials

metaGEM can be used to explore your own gut microbiome sequencing data from at-home-test-kit services such as unseen bio. The following tutorial showcases the metaGEM workflow on two unseenbio samples.

For an introductory metabolic modeling tutorial, refer to the resources compiled for the EMBOMicroCom: Metabolite and species dynamics in microbial communities workshop in 2022.

For a more advanced tutorial, check out the resources we put together for the SymbNET: from metagenomics to metabolic interactions course in 2022.

🏛️ Wiki

Refer to the wiki for additional usage tips, frequently asked questions, and implementation details.

📦 Datasets

• You can access the metaGEM-generated results for the publication here. 🧪 Small communities of gut microbes from lab cultures 💩 Real gut microbiome samples from Swedish diabetes paper 🪴 Plant-associated soil samples from Chinese rhizobiome study 🌏 Bulk-soil samples from Australian biodiversity analysis 🌊 Ocean water samples from global TARA Oceans expeditions
• Additionally, you can access metaGEM-generated results from a reanalysis of recently published ancient metagenomes here.

🐍 Workflow

Core

1. Quality filter reads with fastp
2. Assembly with megahit
3. Draft bin sets with CONCOCT, MaxBin2, and MetaBAT2
4. Refine & reassemble bins with metaWRAP
5. Taxonomic assignment with GTDB-tk
6. Relative abundances with bwa and samtools
7. Reconstruct & evaluate genome-scale metabolic models with CarveMe and memote
8. Species metabolic coupling analysis with SMETANA

Bonus

1. Growth rate estimation with GRiD, SMEG or CoPTR
2. Pangenome analysis with roary
3. Eukaryotic draft bins with EukRep and EukCC

🏗️ Active Development

If you want to see any new additional or alternative tools incorporated into the metaGEM workflow please raise an issue or create a pull request. Snakemake allows workflows to be very flexible, so adding new rules is as easy as filling out the following template and adding it to the Snakefile:

``` rule package-name: input: rules.rulename.output output: f'{config["path"]["root"]}/{config["folder"]["X"]}/{{IDs}}/output.file' message: """ Helpful and descriptive message detailing goal of this rule/package. """ shell: """ # Well documented command line instructions go here

    # Load conda environment 
    set +u;source activate {config[envs][package]};set -u;

    # Run tool
    package-name -i {input} -o {output}
    """

```

🖇️ Publications

The metaGEM workflow has been used in multiple studies, including the following non-exhaustive list:

Plastic-degrading potential across the global microbiome correlates with recent pollution trends J Zrimec, M Kokina, S Jonasson, F Zorrilla, A Zelezniak MBio, 2021

Competition-cooperation in the chemoautotrophic ecosystem of Movile Cave: first metagenomic approach on sediments Chiciudean, I., Russo, G., Bogdan, D.F. et al. Environmental Microbiome, 2022

The National Ecological Observatory Network’s soil metagenomes: assembly and basic analysis Werbin ZR, Hackos B, Lopez-Nava J et al. F1000Research, 2022

Microbial interactions shape cheese flavour formation Melkonian, C., Zorrilla, F., Kjærbølling, I. et al. Nature Communications, 2023

🍾 Please cite

metaGEM: reconstruction of genome scale metabolic models directly from metagenomes Francisco Zorrilla, Filip Buric, Kiran R Patil, Aleksej Zelezniak Nucleic Acids Research, 2021; gkab815, https://doi.org/10.1093/nar/gkab815

⭐ Star History

📲 Contact

Please reach out with any comments, concerns, or discussions regarding metaGEM.