Evidence map›Paper›PMID 26677108›Full record

ArticleMicrobiologyOpen2016

Putative bacterial interactions from metagenomic knowledge with an integrative systems ecology approach.

Philippe Bordron, Mauricio Latorre, Maria-Paz Cortés, Mauricio González, Sven Thiele, Anne Siegel, Alejandro Maass, Damien Eveillard

Abstract read
In one paragraph

Article in MicrobiologyOpen, 2016. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 9 papers.

0numbers the graph read from it
0cells of the map it votes in
9citing 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

9 citing papers in PubMed.

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  6. Gene Expression Analysis ofFrontiers in microbiology · 2017
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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

8 authors.

Philippe BordronMathomics, Center for Mathematical Modeling, Universidad de Chile, Santiago, Chile.
Mauricio LatorreMathomics, Center for Mathematical Modeling, Universidad de Chile, Santiago, Chile.
Maria-Paz CortésMathomics, Center for Mathematical Modeling, Universidad de Chile, Santiago, Chile.
Mauricio GonzálezCenter for Genome Regulation (Fondap 15090007), Universidad de Chile, Santiago, Chile.
Sven ThieleMax Planck Institute for Dynamics of Complex Technical Systems, Magdeburg, Germany.
Anne SiegelIRISA, UMR 6074, CNRS, Rennes, France.
Alejandro MaassMathomics, Center for Mathematical Modeling, Universidad de Chile, Santiago, Chile.
Damien EveillardLINA, UMR CNRS 6241, EMN, Université de Nantes, Nantes, France.

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

Following the trend of studies that investigate microbial ecosystems using different metagenomic techniques, we propose a new integrative systems ecology approach that aims to decipher functional roles within a consortium through the integration of genomic and metabolic knowledge at genome scale. For the sake of application, using public genomes of five bacterial strains involved in copper bioleaching: Acidiphilium cryptum, Acidithiobacillus ferrooxidans, Acidithiobacillus thiooxidans, Leptospirillum ferriphilum, and Sulfobacillus thermosulfidooxidans, we first reconstructed a global metabolic network. Next, using a parsimony assumption, we deciphered sets of genes, called Sets from Genome Segments (SGS), that (1) are close on their respective genomes, (2) take an active part in metabolic pathways and (3) whose associated metabolic reactions are also closely connected within metabolic networks. Overall, this SGS paradigm depicts genomic functional units that emphasize respective roles of bacterial strains to catalyze metabolic pathways and environmental processes. Our analysis suggested that only few functional metabolic genes are horizontally transferred within the consortium and that no single bacterial strain can accomplish by itself the whole copper bioleaching. The use of SGS pinpoints a functional compartmentalization among the investigated species and exhibits putative bacterial interactions necessary for promoting these pathways.

Indexed as

AcidiphiliumAcidithiobacillusCopperDNA, BacterialEcosystemEubacterialesGenome, BacterialMetabolic Networks and PathwaysMetagenomicsCopperDNA, BacterialEnvironmental microbiologyin silico analysismetabolic pathwaysmolecular microbial ecology

Identifiers

PMID26677108
PMCPMC4767419

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Registered trials

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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.