Unknown

Dataset Information

0

Transcriptional profiling and targeted proteomics reveals common molecular changes associated with cigarette smoke-induced lung emphysema development in five susceptible mouse strains.


ABSTRACT: Mouse models are useful for studying cigarette smoke (CS)-induced chronic pulmonary pathologies such as lung emphysema. To enhance translation of large-scale omics data from mechanistic studies into pathophysiological changes, we have developed computational tools based on reverse causal reasoning (RCR).In the present study we applied a systems biology approach leveraging RCR to identify molecular mechanistic explanations of pathophysiological changes associated with CS-induced lung emphysema in susceptible mice.The lung transcriptomes of five mouse models (C57BL/6, ApoE (-/-) , A/J, CD1, and Nrf2 (-/-) ) were analyzed following 5-7 months of CS exposure.We predicted 39 molecular changes mostly related to inflammatory processes including known key emphysema drivers such as NF-?B and TLR4 signaling, and increased levels of TNF-?, CSF2, and several interleukins. More importantly, RCR predicted potential molecular mechanisms that are less well-established, including increased transcriptional activity of PU.1, STAT1, C/EBP, FOXM1, YY1, and N-COR, and reduced protein abundance of ITGB6 and CFTR. We corroborated several predictions using targeted proteomic approaches, demonstrating increased abundance of CSF2, C/EBP?, C/EBP?, PU.1, BRCA1, and STAT1.These systems biology-derived candidate mechanisms common to susceptible mouse models may enhance understanding of CS-induced molecular processes underlying emphysema development in mice and their relevancy for human chronic obstructive pulmonary disease.

SUBMITTER: Cabanski M 

PROVIDER: S-EPMC4464601 | biostudies-literature | 2015 Jul

REPOSITORIES: biostudies-literature

altmetric image

Publications

Transcriptional profiling and targeted proteomics reveals common molecular changes associated with cigarette smoke-induced lung emphysema development in five susceptible mouse strains.

Cabanski Maciej M   Fields Brett B   Boue Stephanie S   Boukharov Natalia N   DeLeon Hector H   Dror Natalie N   Geertz Marcel M   Guedj Emmanuel E   Iskandar Anita A   Kogel Ulrike U   Merg Celine C   Peck Michael J MJ   Poussin Carine C   Schlage Walter K WK   Talikka Marja M   Ivanov Nikolai V NV   Hoeng Julia J   Peitsch Manuel C MC  

Inflammation research : official journal of the European Histamine Research Society ... [et al.] 20150512 7


<h4>Background</h4>Mouse models are useful for studying cigarette smoke (CS)-induced chronic pulmonary pathologies such as lung emphysema. To enhance translation of large-scale omics data from mechanistic studies into pathophysiological changes, we have developed computational tools based on reverse causal reasoning (RCR).<h4>Objective</h4>In the present study we applied a systems biology approach leveraging RCR to identify molecular mechanistic explanations of pathophysiological changes associa  ...[more]

Similar Datasets

| S-EPMC5625220 | biostudies-literature
| S-EPMC6629245 | biostudies-literature
| S-EPMC3934169 | biostudies-literature
| S-EPMC3086754 | biostudies-literature
| S-EPMC4454642 | biostudies-literature
| S-EPMC10118454 | biostudies-literature
2014-11-28 | E-MTAB-2756 | biostudies-arrayexpress
| S-EPMC3982860 | biostudies-literature
| S-EPMC2742758 | biostudies-literature
| S-EPMC1280966 | biostudies-literature