Cargando…
Pathway crosstalk perturbation network modeling for identification of connectivity changes induced by diabetic neuropathy and pioglitazone
BACKGROUND: Aggregation of high-throughput biological data using pathway-based approaches is useful to associate molecular results to functional features related to the studied phenomenon. Biological pathways communicate with one another through the crosstalk phenomenon, forming large networks of in...
Autores principales: | , , , , |
---|---|
Formato: | Online Artículo Texto |
Lenguaje: | English |
Publicado: |
BioMed Central
2019
|
Materias: | |
Acceso en línea: | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC6322225/ https://www.ncbi.nlm.nih.gov/pubmed/30616626 http://dx.doi.org/10.1186/s12918-018-0674-7 |
_version_ | 1783385576031911936 |
---|---|
author | de Anda-Jáuregui, Guillermo Guo, Kai McGregor, Brett A. Feldman, Eva L. Hur, Junguk |
author_facet | de Anda-Jáuregui, Guillermo Guo, Kai McGregor, Brett A. Feldman, Eva L. Hur, Junguk |
author_sort | de Anda-Jáuregui, Guillermo |
collection | PubMed |
description | BACKGROUND: Aggregation of high-throughput biological data using pathway-based approaches is useful to associate molecular results to functional features related to the studied phenomenon. Biological pathways communicate with one another through the crosstalk phenomenon, forming large networks of interacting processes. RESULTS: In this work, we present the pathway crosstalk perturbation network (PXPN) model, a novel model used to analyze and integrate pathway perturbation data based on graph theory. With this model, the changes in activity and communication between pathways observed in transitions between physiological states are represented as networks. The model presented here is agnostic to the type of biological data and pathway definition used and can be implemented to analyze any type of high-throughput perturbation experiments. We present a case study in which we use our proposed model to analyze a gene expression dataset derived from experiments in a BKS-db/db mouse model of type 2 diabetes mellitus–associated neuropathy (DN) and the effects of the drug pioglitazone in this condition. The networks generated describe the profile of pathway perturbation involved in the transitions between the healthy and the pathological state and the pharmacologically treated pathology. We identify changes in the connectivity of perturbed pathways associated to each biological transition, such as rewiring between extracellular matrix, neuronal system, and G-protein coupled receptor signaling pathways. CONCLUSION: The PXPN model is a novel, flexible method used to integrate high-throughput data derived from perturbation experiments; it is agnostic to the type of data and enrichment function used, and it is applicable to a wide range of biological phenomena of interest. ELECTRONIC SUPPLEMENTARY MATERIAL: The online version of this article (10.1186/s12918-018-0674-7) contains supplementary material, which is available to authorized users. |
format | Online Article Text |
id | pubmed-6322225 |
institution | National Center for Biotechnology Information |
language | English |
publishDate | 2019 |
publisher | BioMed Central |
record_format | MEDLINE/PubMed |
spelling | pubmed-63222252019-01-09 Pathway crosstalk perturbation network modeling for identification of connectivity changes induced by diabetic neuropathy and pioglitazone de Anda-Jáuregui, Guillermo Guo, Kai McGregor, Brett A. Feldman, Eva L. Hur, Junguk BMC Syst Biol Methodology Article BACKGROUND: Aggregation of high-throughput biological data using pathway-based approaches is useful to associate molecular results to functional features related to the studied phenomenon. Biological pathways communicate with one another through the crosstalk phenomenon, forming large networks of interacting processes. RESULTS: In this work, we present the pathway crosstalk perturbation network (PXPN) model, a novel model used to analyze and integrate pathway perturbation data based on graph theory. With this model, the changes in activity and communication between pathways observed in transitions between physiological states are represented as networks. The model presented here is agnostic to the type of biological data and pathway definition used and can be implemented to analyze any type of high-throughput perturbation experiments. We present a case study in which we use our proposed model to analyze a gene expression dataset derived from experiments in a BKS-db/db mouse model of type 2 diabetes mellitus–associated neuropathy (DN) and the effects of the drug pioglitazone in this condition. The networks generated describe the profile of pathway perturbation involved in the transitions between the healthy and the pathological state and the pharmacologically treated pathology. We identify changes in the connectivity of perturbed pathways associated to each biological transition, such as rewiring between extracellular matrix, neuronal system, and G-protein coupled receptor signaling pathways. CONCLUSION: The PXPN model is a novel, flexible method used to integrate high-throughput data derived from perturbation experiments; it is agnostic to the type of data and enrichment function used, and it is applicable to a wide range of biological phenomena of interest. ELECTRONIC SUPPLEMENTARY MATERIAL: The online version of this article (10.1186/s12918-018-0674-7) contains supplementary material, which is available to authorized users. BioMed Central 2019-01-07 /pmc/articles/PMC6322225/ /pubmed/30616626 http://dx.doi.org/10.1186/s12918-018-0674-7 Text en © The Author(s). 2019 Open AccessThis article is distributed under the terms of the Creative Commons Attribution 4.0 International License (http://creativecommons.org/licenses/by/4.0/), which permits unrestricted use, distribution, and reproduction in any medium, provided you give appropriate credit to the original author(s) and the source, provide a link to the Creative Commons license, and indicate if changes were made. The Creative Commons Public Domain Dedication waiver (http://creativecommons.org/publicdomain/zero/1.0/) applies to the data made available in this article, unless otherwise stated. |
spellingShingle | Methodology Article de Anda-Jáuregui, Guillermo Guo, Kai McGregor, Brett A. Feldman, Eva L. Hur, Junguk Pathway crosstalk perturbation network modeling for identification of connectivity changes induced by diabetic neuropathy and pioglitazone |
title | Pathway crosstalk perturbation network modeling for identification of connectivity changes induced by diabetic neuropathy and pioglitazone |
title_full | Pathway crosstalk perturbation network modeling for identification of connectivity changes induced by diabetic neuropathy and pioglitazone |
title_fullStr | Pathway crosstalk perturbation network modeling for identification of connectivity changes induced by diabetic neuropathy and pioglitazone |
title_full_unstemmed | Pathway crosstalk perturbation network modeling for identification of connectivity changes induced by diabetic neuropathy and pioglitazone |
title_short | Pathway crosstalk perturbation network modeling for identification of connectivity changes induced by diabetic neuropathy and pioglitazone |
title_sort | pathway crosstalk perturbation network modeling for identification of connectivity changes induced by diabetic neuropathy and pioglitazone |
topic | Methodology Article |
url | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC6322225/ https://www.ncbi.nlm.nih.gov/pubmed/30616626 http://dx.doi.org/10.1186/s12918-018-0674-7 |
work_keys_str_mv | AT deandajaureguiguillermo pathwaycrosstalkperturbationnetworkmodelingforidentificationofconnectivitychangesinducedbydiabeticneuropathyandpioglitazone AT guokai pathwaycrosstalkperturbationnetworkmodelingforidentificationofconnectivitychangesinducedbydiabeticneuropathyandpioglitazone AT mcgregorbretta pathwaycrosstalkperturbationnetworkmodelingforidentificationofconnectivitychangesinducedbydiabeticneuropathyandpioglitazone AT feldmaneval pathwaycrosstalkperturbationnetworkmodelingforidentificationofconnectivitychangesinducedbydiabeticneuropathyandpioglitazone AT hurjunguk pathwaycrosstalkperturbationnetworkmodelingforidentificationofconnectivitychangesinducedbydiabeticneuropathyandpioglitazone |