Evidence map›Paper›PMID 34580179›Full record

ArticleLife science alliance2021

OrtSuite: from genomes to prediction of microbial interactions within targeted ecosystem processes.

João Pedro Saraiva, Alexandre Bartholomäus, René Kallies, Marta Gomes, Marcos Bicalho, Jonas Coelho Kasmanas, Carsten Vogt, Antonis Chatzinotas, Peter Stadler, Oscar Dias and 1 more

Abstract read
In one paragraph

Article in Life science alliance, 2021. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 1 paper.

0numbers the graph read from it
0cells of the map it votes in
1citing papers in PubMed
–field-weighted citation impact
1 · What the graph read from it

What it found

Each row is one number read from the abstract, on the scale the paper reported it, with its interval. Left of the dashed line favours the treatment, right favours the comparator. Under each row is the sentence it came from. New to these charts? A ten-minute tutorial.

The abstract states no effect estimate the extractor could read, or names no intervention and outcome on the map, so this paper lights no cell and moves no belief. It is still indexed, cited and linked below.

2 · The registry

The trial behind it

Trials whose registry record cites this paper, or whose number appears in the abstract. A trial that started after this paper was published is citing it as background, not reporting it.

Neither the registry nor the abstract names a trial number. If this is a trial report, that itself is worth knowing.

3 · Its place in the literature

Who cites it

1 citing paper in PubMed.

  1. Article
4 · The record

Corrections and comments

PubMed lists nothing against this paper. Absence here is not a guarantee, only a check that was made.

5 · Who and what money

Authors and funding

11 authors.

João Pedro SaraivaDepartment of Environmental Microbiology, Helmholtz Centre for Environmental Research-UFZ, Leipzig, Germany.ORCID 0000-0001-8251-1960
Alexandre BartholomäusGFZ German Research Centre for Geosciences, Section Geomicrobiology, Potsdam, Germany.ORCID 0000-0003-0970-7304
René KalliesDepartment of Environmental Microbiology, Helmholtz Centre for Environmental Research-UFZ, Leipzig, Germany.ORCID 0000-0002-9195-0276
Marta GomesCentre of Biological Engineering, University of Minho, Braga, Portugal.
Marcos BicalhoDepartment of Environmental Microbiology, Helmholtz Centre for Environmental Research-UFZ, Leipzig, Germany.
Jonas Coelho KasmanasDepartment of Environmental Microbiology, Helmholtz Centre for Environmental Research-UFZ, Leipzig, Germany.
Carsten VogtDepartment of Environmental Microbiology, Helmholtz Centre for Environmental Research-UFZ, Leipzig, Germany.ORCID 0000-0002-7605-6356
Antonis ChatzinotasDepartment of Environmental Microbiology, Helmholtz Centre for Environmental Research-UFZ, Leipzig, Germany.
Peter StadlerDepartment of Computer Science, Bioinformatics Group, Interdisciplinary Center for Bioinformatics, and Competence Center for Scalable Data Services and Solutions Dresden/Leipzig, University of Leipzig, Leipzig, Germany.ORCID 0000-0002-5016-5191
Oscar DiasCentre of Biological Engineering, University of Minho, Braga, Portugal.
Ulisses Nunes da RochaDepartment of Environmental Microbiology, Helmholtz Centre for Environmental Research-UFZ, Leipzig, Germany ulisses.rocha@ufz.de.ORCID 0000-0001-6972-6692

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

The high complexity found in microbial communities makes the identification of microbial interactions challenging. To address this challenge, we present OrtSuite, a flexible workflow to predict putative microbial interactions based on genomic content of microbial communities and targeted to specific ecosystem processes. The pipeline is composed of three user-friendly bash commands. OrtSuite combines ortholog clustering with genome annotation strategies limited to user-defined sets of functions allowing for hypothesis-driven data analysis such as assessing microbial interactions in specific ecosystems. OrtSuite matched, on average, 96% of experimentally verified KEGG orthologs involved in benzoate degradation in a known group of benzoate degraders. We evaluated the identification of putative synergistic species interactions using the sequenced genomes of an independent study that had previously proposed potential species interactions in benzoate degradation. OrtSuite is an easy-to-use workflow that allows for rapid functional annotation based on a user-curated database and can easily be extended to ecosystem processes where connections between genes and reactions are known. OrtSuite is an open-source software available at https://github.com/mdsufz/OrtSuite.

Indexed as

EcosystemGenome, BacterialSoftwareWorkflowAcetyl Coenzyme ABacteriaBase SequenceBenzoatesDatabases, GeneticGenomicsMicrobial InteractionsMolecular Sequence AnnotationSignal TransductionAcetyl Coenzyme ABenzoates

Identifiers

PMID34580179
PMCPMC8500227

What OpenQuestion holds

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LicenceCC BY
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Registered trials

None linked

Read under generation 80e0d062 · epoch 390. Bibliography from PubMed, PubMed Central and OpenAlex; grants from NIH RePORTER; trial links from ClinicalTrials.gov; estimates, votes and beliefs from the OpenQuestion graph.