Evidence map›Paper›PMID 30497359›Full record

ArticleBMC bioinformatics2018

CiliateGEM: an open-project and a tool for predictions of ciliate metabolic variations and experimental condition design.

Alessio Mancini, Filmon Eyassu, Maxwell Conway, Annalisa Occhipinti, Pietro Liò, Claudio Angione, Sandra Pucciarelli

Open access · goldAbstract read
In one paragraph

Article in BMC bioinformatics, 2018. 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
0.1field-weighted citation impact, top 50% 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, 3 citations in OpenAlex.

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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

7 authors at 3 institutions in 2 countries.

Alessio ManciniSchool of Biosciences and Veterinary Medicine, University of Camerino, Camerino, Italy.
Filmon EyassuDepartment of Computer Science and Information Systems, Teesside University, Middlesbrough, UK.
Maxwell ConwayComputer Laboratory, University of Cambridge, Cambridge, UK.
Annalisa OcchipintiComputer Laboratory, University of Cambridge, Cambridge, UK.
Pietro LiòComputer Laboratory, University of Cambridge, Cambridge, UK.
Claudio AngioneDepartment of Computer Science and Information Systems, Teesside University, Middlesbrough, UK.
Sandra PucciarelliSchool of Biosciences and Veterinary Medicine, University of Camerino, Camerino, Italy. sandra.pucciarelli@unicam.it.
University of Cambridge · GBTeesside University · GBUniversità di Camerino · IT

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

backgroundThe study of cell metabolism is becoming central in several fields such as biotechnology, evolution/adaptation and human disease investigations. Here we present CiliateGEM, the first metabolic network reconstruction draft of the freshwater ciliate Tetrahymena thermophila. We also provide the tools and resources to simulate different growth conditions and to predict metabolic variations. CiliateGEM can be extended to other ciliates in order to set up a meta-model, i.e. a metabolic network reconstruction valid for all ciliates. Ciliates are complex unicellular eukaryotes of presumably monophyletic origin, with a phylogenetic position that is equal from plants and animals. These cells represent a new concept of unicellular system with a high degree of species, population biodiversity and cell complexity. Ciliates perform in a single cell all the functions of a pluricellular organism, including locomotion, feeding, digestion, and sexual processes.

resultsAfter generating the model, we performed an in-silico simulation with the presence and absence of glucose. The lack of this nutrient caused a 32.1% reduction rate in biomass synthesis. Despite the glucose starvation, the growth did not stop due to the use of alternative carbon sources such as amino acids.

conclusionsThe future models obtained from CiliateGEM may represent a new approach to describe the metabolism of ciliates. This tool will be a useful resource for the ciliate research community in order to extend these species as model organisms in different research fields. An improved understanding of ciliate metabolism could be relevant to elucidate the basis of biological phenomena like genotype-phenotype relationships, population genetics, and cilia-related disease mechanisms.

Indexed as

Research DesignSoftwareAnimalsBiomassPhylogenyTetrahymena thermophilaCiliatesFlux balance analysisGenome scale reconstructionMetabolic pathwaysTetrahymena thermophila

Identifiers

PMID30497359
PMCPMC6266953
OpenAlexW2902880011

What OpenQuestion holds

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LicenceCC BY
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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.