Evidence map›Paper›PMID 25462333›Full record

ArticleComputational biology and chemistry2014

Metabolic network motifs can provide novel insights into evolution: The evolutionary origin of Eukaryotic organelles as a case study.

Erin R Shellman, Yu Chen, Xiaoxia Lin, Charles F Burant, Santiago Schnell

Abstract read
In one paragraph

Article in Computational biology and chemistry, 2014. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 2 papers.

0numbers the graph read from it
0cells of the map it votes in
2citing 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

2 citing papers in PubMed.

  1. Article
  2. 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

5 authors.

Erin R ShellmanDepartment of Computational Medicine & Bioinformatics, University of Michigan Medical School, Ann Arbor, MI, USA.
Yu ChenDepartment of Chemical Engineering, University of Michigan School of Engineering, Ann Arbor, MI, USA.
Xiaoxia LinDepartment of Chemical Engineering, University of Michigan School of Engineering, Ann Arbor, MI, USA.
Charles F BurantDepartment of Internal Medicine, University of Michigan Medical School, Ann Arbor, MI, USA; Department of Molecular & Integrative Physiology, University of Michigan Medical School, Ann Arbor, MI, USA. Electronic address: burantc@med.umich.edu.
Santiago SchnellDepartment of Computational Medicine & Bioinformatics, University of Michigan Medical School, Ann Arbor, MI, USA; Department of Molecular & Integrative Physiology, University of Michigan Medical School, Ann Arbor, MI, USA. Electronic address: schnells@umich.edu.

Funding

Regional Pilot And Feasibility Study Grants ProgramP30DK020572 · NIDDK · UNIVERSITY OF MICHIGAN AT ANN ARBOR · PI Mehboob A Hussain · 2013 to 2026
$24.3M
Pilot and Feasibility (P and F) ProgramP30DK089503 · NIDDK · UNIVERSITY OF MICHIGAN AT ANN ARBOR · PI Joyce Lee · 2010 to 2026
$20.3M
Statistics and Bioinformatics Core - WangU24DK097153 · NIDDK · UNIVERSITY OF MICHIGAN AT ANN ARBOR · PI BURANT, CHARLES F · 2012 to 2017
$10.1M
SYTEMS AND INTEGRATIVE BIOLOGYT32GM008322 · NIGMS · UNIVERSITY OF MICHIGAN AT ANN ARBOR · PI LOW, MALCOLM JAMES · 1990 to 2020
$5.7M
Using Systems Biology to Understand Islet Adaptation and Failure DiabetesR01DK079084 · NIDDK · UNIVERSITY OF MICHIGAN AT ANN ARBOR · PI BURANT, CHARLES F · 2007 to 2010
$2.1M
NIDDK NIH HHS P30 DK020572NIDDK NIH HHS P30 DK089503NIDDK NIH HHS R01 DK079084NIDDK NIH HHS U24 DK097153NIGMS NIH HHS T32 GM008322
6 · The paper itself

Abstract

Phylogenetic trees are typically constructed using genetic and genomic data, and provide robust evolutionary relationships of species from the genomic point of view. We present an application of network motif mining and analysis of metabolic pathways that when used in combination with phylogenetic trees can provide a more complete picture of evolution. By using distributions of three-node motifs as a proxy for metabolic similarity, we analyze the ancestral origin of Eukaryotic organelles from the metabolic point of view to illustrate the application of our motif mining and analysis network approach. Our analysis suggests that the hypothesis of an early proto-Eukaryote could be valid. It also suggests that a δ- or ϵ-Proteobacteria may have been the endosymbiotic partner that gave rise to modern mitochondria. Our evolutionary analysis needs to be extended by building metabolic network reconstructions of species from the phylum Crenarchaeota, which is considered to be a possible archaeal ancestor of the eukaryotic cell. In this paper, we also propose a methodology for constructing phylogenetic trees that incorporates metabolic network signatures to identify regions of genomically-estimated phylogenies that may be spurious. We find that results generated from our approach are consistent with a parallel phylogenetic analysis using the method of feature frequency profiles.

Indexed as

Enzyme classificationEukaryotic cellEvolutionMetabolismNetwork motifsPhylogenies

Identifiers

PMID25462333
PMCPMC4254655

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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.