README.md

---
language: en
license: cc-by-4.0
tags:
- chemistry
- biology
pretty_name: "Microbiome Immunity Project: Protein Universe"
dataset_summary: >-
  ~200,000 predicted structures for diverse protein sequences from 1,003
  representative genomes across the microbial tree of life and annotate
  them functionally on a per-residue basis.
dataset_description: >-
  Large-scale structure prediction on representative protein domains from
  the Genomic Encyclopedia of Bacteria and Archaea (GEBA1003) reference
  genome database across the microbial tree of life. From a non-redundant
  GEBA1003 gene catalog protein sequences without matches to any structural databases
  and which produced multiple-sequence alignments of N_eff > 16 and all
  putative novel domains between 40 and 200 residues were extracted.
  For each sequence 20,000 Rosetta de novo models and up to 5 DMPfold models
  were generated. The initial output dataset (MIP_raw) of about 240,000
  models were curated to high-quality models comprising about 75% of the
  original dataset (MIP_curated). Functional annotations of the entire
  dataset were created using structure-based Graph Convolutional Network
  embeddings from DeepFRI.
acknowledgements: >-
  We kindly acknowledge the support of the IBM World Community Grid team
  (Caitlin Larkin, Juan A Hindo, Al Seippel, Erika Tuttle, Jonathan D Armstrong,
  Kevin Reed, Ray Johnson, and Viktors Berstis), and the community of 790,000
  volunteers who donated 140,661 computational years since Aug 2017 of their
  computer time over the course of the project. This research was also
  supported in part by PLGrid Infrastructure (to PS). The authors thank Hera
  Vlamakis and Damian Plichta from the Broad Institute for helpful discussions.
  The work was supported by the Flatiron Institute as part of the Simons Foundation
  to J.K.L., P.D.R., V.G., D.B., C.C., A.P., N.C., I.F., and R.B. This research
  was also supported by grants NAWA PPN/PPO/2018/1/00014 to P.S. and T.K.,
  PLGrid to P.S., and NIH - DK043351 to T.V. and R.J.X.
repo: https://github.com/microbiome-immunity-project/protein_universe
citation_bibtex: >-
  @article{KoehlerLeman2023,
    title = {Sequence-structure-function relationships in the microbial protein universe},
    volume = {14},
    ISSN = {2041-1723},
    url = {http://dx.doi.org/10.1038/s41467-023-37896-w},
    DOI = {10.1038/s41467-023-37896-w},
    number = {1},
    journal = {Nature Communications},
    publisher = {Springer Science and Business Media LLC},
    author = {Koehler Leman,  Julia and Szczerbiak,  Pawel and Renfrew,  P. Douglas and Gligorijevic,  Vladimir and Berenberg,  Daniel and Vatanen,  Tommi and Taylor,  Bryn C. and Chandler,  Chris and Janssen,  Stefan and Pataki,  Andras and Carriero,  Nick and Fisk,  Ian and Xavier,  Ramnik J. and Knight,  Rob and Bonneau,  Richard and Kosciolek,  Tomasz},
    year = {2023},
    month = apr
  }
citation_apa: >-
  Koehler Leman, J., Szczerbiak, P., Renfrew, P. D., Gligorijevic, V., Berenberg,
  D., Vatanen, T., … Kosciolek, T. (2023). Sequence-structure-function relationships
  in the microbial protein universe. Nature Communications, 14(1), 2351.
  doi:10.1038/s41467-023-37896-w
size_categories:
- 100k<n<1M
---
# Microbiome Immunity Project: Protein Universe
~200,000 predicted structures for diverse protein sequences from 1,003
representative genomes across the microbial tree of life and annotate
them functionally on a per-residue basis.

## Dataset Details

### Dataset Description
Large-scale structure prediction on representative protein domains from
the Genomic Encyclopedia of Bacteria and Archaea (GEBA1003) reference
genome database across the microbial tree of life. From a non-redundant
GEBA1003 gene catalog protein sequences without matches to any structural databases
and which produced multiple-sequence alignments of N_eff > 16 and all
putative novel domains between 40 and 200 residues were extracted.
For each sequence 20,000 Rosetta de novo models and up to 5 DMPfold models
were generated. The initial output dataset (MIP_raw) of about 240,000
models were curated to high-quality models comprising about 75% of the
original dataset (MIP_curated): Models were filtered out if (1) Rosetta
models had >60% coil content or DMPFold models with >80% coil content,
(2) the averaging the pairwise TM-scores of the 10 lowest-scoring models
was less than 0.4, and (3) if the Rosetta and DMPfold models had TM-score
less than 0.5. Functional annotations of the entire dataset were
created using structure-based Graph Convolutional Network
embeddings from DeepFRI.

- **Acknowledgements:**
  We kindly acknowledge the support of the IBM World Community Grid team
  (Caitlin Larkin, Juan A Hindo, Al Seippel, Erika Tuttle, Jonathan D Armstrong,
  Kevin Reed, Ray Johnson, and Viktors Berstis), and the community of 790,000
  volunteers who donated 140,661 computational years since Aug 2017 of their
  computer time over the course of the project. This research was also
  supported in part by PLGrid Infrastructure (to PS). The authors thank Hera
  Vlamakis and Damian Plichta from the Broad Institute for helpful discussions.
  The work was supported by the Flatiron Institute as part of the Simons Foundation
  to J.K.L., P.D.R., V.G., D.B., C.C., A.P., N.C., I.F., and R.B. This research
  was also supported by grants NAWA PPN/PPO/2018/1/00014 to P.S. and T.K.,
  PLGrid to P.S., and NIH - DK043351 to T.V. and R.J.X.

- **License:** cc-by-4.0

### Dataset Sources [optional]

<!-- Provide the basic links for the dataset. -->

- **Repository:** https://github.com/microbiome-immunity-project/protein_universe
- **Paper:**
  Koehler Leman, J., Szczerbiak, P., Renfrew, P. D., Gligorijevic, V., Berenberg,
  D., Vatanen, T., … Kosciolek, T. (2023). Sequence-structure-function relationships
  in the microbial protein universe. Nature Communications, 14(1), 2351.
  doi:10.1038/s41467-023-37896-w
- **Zenodo Repository:** https://doi.org/10.5281/zenodo.6611431


## Uses
Exploration of sequence-structure-function relationship in naturally ocurring proteins.
The MIP database is complementary to and distinct from the other large-scale predicted
protein structure databases such as the EBI AlphaFold database because it consists of
proteins from Archaea and Bacteria, whose protein sequences are generally shorter
than Eukaryotic.

### Direct Use
This dataset could be used to

-


### Out-of-Scope Use

While this dataset has been curated for quality, in some cases the predicted structures
may not represent physically realistic conformations. Thus caution much be used when using
it as training data for protein structure prediction and design.

## Dataset Structure

    microbiome_immunity_project_dataset
      dataset
        dmpfold_high_quality_function_predictions
          DeepFRI_MIP_<chunk-index>_<gene-ontology-prefix>_pred_scores.json.gz
        dmpfold_high_quality_models
          MIP_<MIP-ID>.pdb.gz.pdb.gz


### Source Data

Sequences were obtained from the Genomic Encyclopedia of Bacteria and Archaea
([GEBA1003](https://genome.jgi.doe.gov/portal/geba1003/geba1003.info.html)) reference
genome database across the microbial tree of life:

> **1,003 reference genomes of bacterial and archaeal isolates expand coverage of the tree of life**
> We present 1,003 reference genomes that were sequenced as part of the Genomic Encyclopedia of Bacteria
> and Archaea (GEBA) initiative, selected to maximize sequence coverage of phylogenetic space.
> These genomes double the number of existing type strains and expand their overall phylogenetic
> diversity by 25%. Comparative analyses with previously available finished and draft genomes reveal
> a 10.5% increase in novel protein families as a function of phylogenetic diversity. The GEBA genomes
> recruit 25 million previously unassigned metagenomic proteins from 4,650 samples, improving their
> phylogenetic and functional interpretation. We identify numerous biosynthetic clusters and experimentally
> validate a divergent phenazine cluster with potential new chemical structure and antimicrobial activity.
> This Resource is the largest single release of reference genomes to date. Bacterial and archaeal isolate
> sequence space is still far from saturated, and future endeavors in this direction will continue to be a
> valuable resource for scientific discovery.

#### Data Collection and Processing

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#### Who are the source data producers?

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## Bias, Risks, and Limitations

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### Recommendations

<!-- This section is meant to convey recommendations with respect to the bias, risk, and technical limitations. -->

{{ bias_recommendations | default("Users should be made aware of the risks, biases and limitations of the dataset. More information needed for further recommendations.", true)}}

## Citation

    @article{KoehlerLeman2023,
      title = {Sequence-structure-function relationships in the microbial protein universe},
      volume = {14},
      ISSN = {2041-1723},
      url = {http://dx.doi.org/10.1038/s41467-023-37896-w},
      DOI = {10.1038/s41467-023-37896-w},
      number = {1},
      journal = {Nature Communications},
      publisher = {Springer Science and Business Media LLC},
      author = {Koehler Leman,  Julia and Szczerbiak,  Pawel and Renfrew,  P. Douglas and Gligorijevic,  Vladimir and Berenberg,  Daniel and Vatanen,  Tommi and Taylor,  Bryn C. and Chandler,  Chris and Janssen,  Stefan and Pataki,  Andras and Carriero,  Nick and Fisk,  Ian and Xavier,  Ramnik J. and Knight,  Rob and Bonneau,  Richard and Kosciolek,  Tomasz},
      year = {2023},
      month = apr
    }



## Dataset Card Authors
Matthew O'Meara ([email protected])