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How to Predict Molecular Interactions between Species?

Organisms constantly interact with other species through physical contact which leads to changes on the molecular level, for example the transcriptome. These changes can be monitored for all genes, with the help of high-throughput experiments such as RNA-seq or microarrays. The adaptation of the gen...

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Autores principales: Schulze, Sylvie, Schleicher, Jana, Guthke, Reinhard, Linde, Jörg
Formato: Online Artículo Texto
Lenguaje:English
Publicado: Frontiers Media S.A. 2016
Materias:
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC4814556/
https://www.ncbi.nlm.nih.gov/pubmed/27065992
http://dx.doi.org/10.3389/fmicb.2016.00442
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author Schulze, Sylvie
Schleicher, Jana
Guthke, Reinhard
Linde, Jörg
author_facet Schulze, Sylvie
Schleicher, Jana
Guthke, Reinhard
Linde, Jörg
author_sort Schulze, Sylvie
collection PubMed
description Organisms constantly interact with other species through physical contact which leads to changes on the molecular level, for example the transcriptome. These changes can be monitored for all genes, with the help of high-throughput experiments such as RNA-seq or microarrays. The adaptation of the gene expression to environmental changes within cells is mediated through complex gene regulatory networks. Often, our knowledge of these networks is incomplete. Network inference predicts gene regulatory interactions based on transcriptome data. An emerging application of high-throughput transcriptome studies are dual transcriptomics experiments. Here, the transcriptome of two or more interacting species is measured simultaneously. Based on a dual RNA-seq data set of murine dendritic cells infected with the fungal pathogen Candida albicans, the software tool NetGenerator was applied to predict an inter-species gene regulatory network. To promote further investigations of molecular inter-species interactions, we recently discussed dual RNA-seq experiments for host-pathogen interactions and extended the applied tool NetGenerator (Schulze et al., 2015). The updated version of NetGenerator makes use of measurement variances in the algorithmic procedure and accepts gene expression time series data with missing values. Additionally, we tested multiple modeling scenarios regarding the stimuli functions of the gene regulatory network. Here, we summarize the work by Schulze et al. (2015) and put it into a broader context. We review various studies making use of the dual transcriptomics approach to investigate the molecular basis of interacting species. Besides the application to host-pathogen interactions, dual transcriptomics data are also utilized to study mutualistic and commensalistic interactions. Furthermore, we give a short introduction into additional approaches for the prediction of gene regulatory networks and discuss their application to dual transcriptomics data. We conclude that the application of network inference on dual-transcriptomics data is a promising approach to predict molecular inter-species interactions.
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spelling pubmed-48145562016-04-08 How to Predict Molecular Interactions between Species? Schulze, Sylvie Schleicher, Jana Guthke, Reinhard Linde, Jörg Front Microbiol Microbiology Organisms constantly interact with other species through physical contact which leads to changes on the molecular level, for example the transcriptome. These changes can be monitored for all genes, with the help of high-throughput experiments such as RNA-seq or microarrays. The adaptation of the gene expression to environmental changes within cells is mediated through complex gene regulatory networks. Often, our knowledge of these networks is incomplete. Network inference predicts gene regulatory interactions based on transcriptome data. An emerging application of high-throughput transcriptome studies are dual transcriptomics experiments. Here, the transcriptome of two or more interacting species is measured simultaneously. Based on a dual RNA-seq data set of murine dendritic cells infected with the fungal pathogen Candida albicans, the software tool NetGenerator was applied to predict an inter-species gene regulatory network. To promote further investigations of molecular inter-species interactions, we recently discussed dual RNA-seq experiments for host-pathogen interactions and extended the applied tool NetGenerator (Schulze et al., 2015). The updated version of NetGenerator makes use of measurement variances in the algorithmic procedure and accepts gene expression time series data with missing values. Additionally, we tested multiple modeling scenarios regarding the stimuli functions of the gene regulatory network. Here, we summarize the work by Schulze et al. (2015) and put it into a broader context. We review various studies making use of the dual transcriptomics approach to investigate the molecular basis of interacting species. Besides the application to host-pathogen interactions, dual transcriptomics data are also utilized to study mutualistic and commensalistic interactions. Furthermore, we give a short introduction into additional approaches for the prediction of gene regulatory networks and discuss their application to dual transcriptomics data. We conclude that the application of network inference on dual-transcriptomics data is a promising approach to predict molecular inter-species interactions. Frontiers Media S.A. 2016-03-31 /pmc/articles/PMC4814556/ /pubmed/27065992 http://dx.doi.org/10.3389/fmicb.2016.00442 Text en Copyright © 2016 Schulze, Schleicher, Guthke and Linde. http://creativecommons.org/licenses/by/4.0/ This is an open-access article distributed under the terms of the Creative Commons Attribution License (CC BY). The use, distribution or reproduction in other forums is permitted, provided the original author(s) or licensor are credited and that the original publication in this journal is cited, in accordance with accepted academic practice. No use, distribution or reproduction is permitted which does not comply with these terms.
spellingShingle Microbiology
Schulze, Sylvie
Schleicher, Jana
Guthke, Reinhard
Linde, Jörg
How to Predict Molecular Interactions between Species?
title How to Predict Molecular Interactions between Species?
title_full How to Predict Molecular Interactions between Species?
title_fullStr How to Predict Molecular Interactions between Species?
title_full_unstemmed How to Predict Molecular Interactions between Species?
title_short How to Predict Molecular Interactions between Species?
title_sort how to predict molecular interactions between species?
topic Microbiology
url https://www.ncbi.nlm.nih.gov/pmc/articles/PMC4814556/
https://www.ncbi.nlm.nih.gov/pubmed/27065992
http://dx.doi.org/10.3389/fmicb.2016.00442
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