Evidence map›Paper›PMID 34707596›Full record

ReviewFrontiers in microbiology2021

Uncovering the Role of Metabolism in Oomycete-Host Interactions Using Genome-Scale Metabolic Models.

Sander Y A Rodenburg, Michael F Seidl, Dick de Ridder, Francine Govers

Open access · goldAbstract readReview
In one paragraph

Review in Frontiers in microbiology, 2021. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 3 papers.

0numbers the graph read from it
0cells of the map it votes in
3citing papers in PubMed
0.5field-weighted citation impact, top 37% of its field
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

3 citing papers in PubMed, 6 citations in OpenAlex.

  1. Article
  2. Article
  3. 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

4 authors at 1 institution in 1 country.

Sander Y A RodenburgLaboratory of Phytopathology, Wageningen University & Research, Wageningen, Netherlands.
Michael F SeidlLaboratory of Phytopathology, Wageningen University & Research, Wageningen, Netherlands.
Dick de RidderBioinformatics Group, Wageningen University & Research, Wageningen, Netherlands.
Francine GoversLaboratory of Phytopathology, Wageningen University & Research, Wageningen, Netherlands.
Wageningen University & Research · NL

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

Metabolism is the set of biochemical reactions of an organism that enables it to assimilate nutrients from its environment and to generate building blocks for growth and proliferation. It forms a complex network that is intertwined with the many molecular and cellular processes that take place within cells. Systems biology aims to capture the complexity of cells, organisms, or communities by reconstructing models based on information gathered by high-throughput analyses (omics data) and prior knowledge. One type of model is a genome-scale metabolic model (GEM) that allows studying the distributions of metabolic fluxes, i.e., the "mass-flow" through the network of biochemical reactions. GEMs are nowadays widely applied and have been reconstructed for various microbial pathogens, either in a free-living state or in interaction with their hosts, with the aim to gain insight into mechanisms of pathogenicity. In this review, we first introduce the principles of systems biology and GEMs. We then describe how metabolic modeling can contribute to unraveling microbial pathogenesis and host-pathogen interactions, with a specific focus on oomycete plant pathogens and in particular

Indexed as

genome-scale metabolic modelmetabolic networksPhytophthora infestansplant pathogenic oomycetesplant–pathogen interactionssystems biology

Identifiers

PMID34707596
PMCPMC8543037
OpenAlexW3206427103

What OpenQuestion holds

Textmetadata
LicenceCC BY
Read underepoch 390

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.