<i>TranSyT</i>, an innovative framework for identifying transport systems

Lagoa, Davide Rafael Santos; Jl, Faria; F, Liu; Cunha, Emanuel; Henry, Chris; Dias, Óscar

doi:10.1101/2021.04.29.441738

Cited by 5 publications

(3 citation statements)

References 31 publications

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“…Transport reactions were automatically generated using the TranSyT (Lagoa et al ., 2021) tool. Nevertheless, additional transport reactions were added if reported in the literature, or if necessary for the model functionality.…”

Section: Methodsmentioning

confidence: 99%

The first multi-tissue diel genome-scale metabolic model of a woody plant highlights suberin biosynthesis pathways in Quercus suber

Cunha

Silva

Chaves

et al. 2021

Preprint

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In the last decade, genome-scale metabolic models have been increasingly used to study plant metabolic behaviour at the tissue and multi-tissue level in different environmental conditions. Quercus suber (Q. suber), also known as the cork oak tree, is one of the most important forest communities of the Mediterranean/Iberian region. In this work, we present the genome-scale metabolic model of the Q. suber (iEC7871), the first of a woody plant. The metabolic model comprises 7871 genes, 6230 reactions, and 6481 metabolites across eight compartments. Transcriptomics data was integrated into the model to obtain tissue-specific models for the leaf, inner bark, and phellogen. Each tissue's biomass composition was determined to improve model accuracy and merged into a diel multi-tissue metabolic model to predict interactions among the three tissues at the light and dark phases. The metabolic models were also used to analyze the pathways associated with the synthesis of suberin monomers. Nevertheless, the models developed in this work can provide insights about other aspects of the metabolism of Q. suber, such as its secondary metabolism and cork formation.

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Section: Methodsmentioning

confidence: 99%

The first multi-tissue diel genome-scale metabolic model of a woody plant highlights suberin biosynthesis pathways in Quercus suber

Cunha

Silva

Chaves

et al. 2021

Preprint

Self Cite

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show abstract

“…There are also specific transporter and transporter substrate specificity tools available as web services and/or downloadable software to run locally. Some are components or plugins for packages for metabolic modelling, specifically aimed at providing transporter reactions (such as merlin, which uses TransSyT [ 58 ], and Pathway Tools, which uses rast/tip ), a task for which TransAAP has also been extensively utilized. Some examples of other transporter tools or databases that exist include TrSSP utilized in the Starmerella bombicola analysis example mentioned above [ 59 ], an annotation pipeline optimized for eukaryotic organisms that uses homology modelling approaches followed by machine-learning methods to refine predictions, and provides general substrate class, but not specific substrate, and has restrictions on processivity (maximum 2000 fasta sequences).…”

Section: Methods and Resultsmentioning

confidence: 99%

TransAAP: an automated annotation pipeline for membrane transporter prediction in bacterial genomes

et al. 2023

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Membrane transporters are a large group of proteins that span cell membranes and contribute to critical cell processes, including delivery of essential nutrients, ejection of waste products, and assisting the cell in sensing environmental conditions. Obtaining an accurate and specific annotation of the transporter proteins encoded by a micro-organism can provide details of its likely nutritional preferences and environmental niche(s), and identify novel transporters that could be utilized in small molecule production in industrial biotechnology. The Transporter Automated Annotation Pipeline (TransAAP) (http://www.membranetransport.org/transportDB2/TransAAP_login.html) is a fully automated web service for the prediction and annotation of membrane transport proteins in an organism from its genome sequence, by using comparisons with both curated databases such as the TCDB (Transporter Classification Database) and TDB, as well as selected Pfams and TIGRFAMs of transporter families and other methodologies. TransAAP was used to annotate transporter genes in the prokaryotic genomes in the National Center for Biotechnology Information (NCBI) RefSeq; these are presented in the transporter database TransportDB (http://www.membranetransport.org) website, which has a suite of data visualization and analysis tools. Creation and maintenance of a bioinformatic database specific for transporters in all genomic datasets is essential for microbiology research groups and the general research/biotechnology community to obtain a detailed picture of membrane transporter systems in various environments, as well as comprehensive information on specific membrane transport proteins.

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“…Transport reactions were automatically generated using the TranSyT [ 87 ] tool directly in merlin using default parameters. This tool annotates transport genes using the Transporter Classification system based on homology searches against TCDB.…”

Section: Methodsmentioning

confidence: 99%

The first multi-tissue genome-scale metabolic model of a woody plant highlights suberin biosynthesis pathways in Quercus suber

Cunha,

Silva,

Chaves

et al. 2023

PLoS Comput Biol

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Over the last decade, genome-scale metabolic models have been increasingly used to study plant metabolic behaviour at the tissue and multi-tissue level under different environmental conditions. Quercus suber, also known as the cork oak tree, is one of the most important forest communities of the Mediterranean/Iberian region. In this work, we present the genome-scale metabolic model of the Q. suber (iEC7871). The metabolic model comprises 7871 genes, 6231 reactions, and 6481 metabolites across eight compartments. Transcriptomics data was integrated into the model to obtain tissue-specific models for the leaf, inner bark, and phellogen, with specific biomass compositions. The tissue-specific models were merged into a diel multi-tissue metabolic model to predict interactions among the three tissues at the light and dark phases. The metabolic models were also used to analyse the pathways associated with the synthesis of suberin monomers, namely the acyl-lipids, phenylpropanoids, isoprenoids, and flavonoids production. The models developed in this work provide a systematic overview of the metabolism of Q. suber, including its secondary metabolism pathways and cork formation.

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TranSyT, an innovative framework for identifying transport systems

Cited by 5 publications

References 31 publications

The first multi-tissue diel genome-scale metabolic model of a woody plant highlights suberin biosynthesis pathways in Quercus suber

The first multi-tissue diel genome-scale metabolic model of a woody plant highlights suberin biosynthesis pathways in Quercus suber

TransAAP: an automated annotation pipeline for membrane transporter prediction in bacterial genomes

The first multi-tissue genome-scale metabolic model of a woody plant highlights suberin biosynthesis pathways in Quercus suber

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