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

Alessio Mancini, Filmon Eyassu, Max Conway, Annalisa Occhipinti, Pietro Lió, Claudio Angione, Sandra Pucciarelli

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    Abstract

    The 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.
    After 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.
    The 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.
    Original languageEnglish
    Pages (from-to)442-442
    Number of pages1
    JournalBMC Bioinformatics
    Volume19
    Issue number(Suppl 15)
    DOIs
    Publication statusPublished - 30 Nov 2018

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