Dataset Information

A proteomics investigation of cigarette smoke exposed Wistar rats revealed improved anti-inflammatory effects of the cysteamine nanoemulsions delivered via inhalation

ABSTRACT: Cigarette smoking is the major cause of chronic inflammatory diseases such as Chronic Obstructive Pulmonary Disease (COPD). It is paramount to develop pharmacological interventions and delivery strategies against the cigarette smoke (CS) associated oxidative stress in COPD. This study in Wistar rats examined cysteamine in nanoemulsions to counteract the cigarette smoke distressed microenvironment. In vivo, 28 days of cigarette smoke and 15 days of cysteamine nanoemulsions treatment starting on 29th day consisting of oral and inhalation routes were established in Wistar rats. Additionally, we conducted inflammatory and epithelial-to-mesenchymal transition (EMT) studies in vitro in human bronchial epithelial cell lines (BEAS2B) using 5% cigarette smoke extract. Inflammatory and anti-inflammatory markers such as TNF-α, IL-6, IL-1ß, IL-8, IL-10, IL-13, have been quantified in bronchoalveolar lavage fluid (BALF) to evaluate the effects of the cysteamine nanoemulsions in normalizing the diseased condition. Histopathological analysis of the alveoli and the trachea showed the distorted, lung parenchyma and ciliated epithelial barrier, respectively. To obtain mechanistic insights into the cigarette smoke COPD rat model, “shotgun” proteomics of the lung tissues have been carried out using high-resolution mass spectrometry wherein genes such as ABI1, PPP3CA, PSMA2, FBLN5, ACTG1, CSNK2A1, and ECM1 exhibited significant differences across all the groups. Pathway analysis showed autophagy, signaling by receptor tyrosine kinase, cytokine signaling in immune system, extracellular matrix organization, and hemostasis, as the major contributing pathways across all the studied groups. This work offers new preclinical findings on how cysteamine taken orally or inhaled can combat cigarette smoke-induced oxidative stress.

INSTRUMENT(S): Orbitrap Fusion

ORGANISM(S): Rattus Norvegicus (rat)

TISSUE(S): Lung

SUBMITTER: Gautam Sharma

LAB HEAD: Sanjeeva Srivasatva

PROVIDER: PXD033529 | Pride | 2023-08-21

REPOSITORIES: Pride

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			Action	DRS
	01102021_Fusion_Gautum_CFO1_LFQ.raw	Raw
	01102021_Fusion_Gautum_CFO2_LFQ.raw	Raw
	01102021_Fusion_Gautum_CFO3_LFQ.raw	Raw
	01102021_Fusion_Gautum_CFO4_LFQ.raw	Raw
	01102021_Fusion_Gautum_CFO5_LFQ.raw	Raw

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A Proteomics Investigation of Cigarette Smoke Exposed Wistar Rats Revealed Improved Anti-Inflammatory Effects of the Cysteamine Nanoemulsions Delivered <i>via</i> Inhalation.

Sharma Gautam G Pund Swati S Govindan Rajkumar R Nissa Mehar Un MU Biswas Deeptarup D Middha Sanniya S Ganguly Koustav K Anand Mahesh Padukudru MP Banerjee Rinti R Srivastava Sanjeeva S

Omics : a journal of integrative biology 20230811 8

Cigarette smoking is the major cause of chronic inflammatory diseases such as chronic obstructive pulmonary disease (COPD). It is paramount to develop pharmacological interventions and delivery strategies against the cigarette smoke (CS) associated oxidative stress in COPD. This study in Wistar rats examined cysteamine in nanoemulsions to counteract the CS distressed microenvironment. <i>In vivo</i>, 28 days of CS and 15 days of cysteamine nanoemulsions treatment starting on 29th day consisting ...[more]

PMID: 37581495

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Project description:One of the most common smoking-related diseases, chronic obstructive pulmonary disease (COPD), results from a dysregulated, multi-tissue inflammatory response to cigarette smoke. We hypothesized that systemic inflammatory signals in genome-wide blood gene expression can identify clinically important COPD-related disease subtypes, and we leveraged pre-existing gene interaction networks to guide unsupervised clustering of blood microarray expression data. Using network-informed non-negative matrix factorization, we analyzed genome-wide blood gene expression from 229 former smokers in the ECLIPSE Study, and we identified novel, clinically relevant molecular subtypes of COPD. These network-informed clusters were more stable and more strongly associated with measures of lung structure and function than clusters derived from a network-naÃ¯ve approach, and they were associated with subtype-specific enrichment for inflammatory and protein catabolic pathways. These clusters were successfully reproduced in an independent sample of 135 smokers from the COPDGene Study. Briefly, gene expression was derived from whole blood samples in ECLIPSE subjects and peripheral blood mononuclear cells (PBMCs) for the COPDGene subjects. Gene expression profiling was performed using the Affymetrix Human U133 Plus2 array. Gene expression data were log-transformed, and background correction and normalization were performed for the merged ECLIPSE and COPDGene samples using robust multi-array averaging and quantile normalization as implemented in the affy Bioconductor package[27]. Of the 136 COPDGene subjects reported in a previous publication[13], one self-reported African-American subject was removed from analysis, which was conducted on the remaining 135 non-Hispanic white subjects. To identify a set of genes associated with COPD, we performed differential expression analysis for 38,519 probesets in ECLIPSE that passed quality control measures. Normalized probeset intensities were related to measures indicative of two primary dimensions of pulmonary impairment in COPD airway obstruction as indicated by two measures of spirometric lung function (FEV1 (% of predicted) and FEV1/FVC) and lung parenchymal destruction, i.e., emphysema (as quantified by the percentage of low attenuation area less than -950 Hounsfield units on lung computed tomography, %LAA-950). The analysis was conducted using the limma Bioconductor package, and the false discovery rate was controlled at 5%. The following covariates were included in the differential expression analysis age, pack-years of cigarette smoke exposure, and gender. After standardizing gene expression data from 229 ECLIPSE subjects by the variance of each probe set, we applied NMF[29] and NBS[6] to identify meta-patients (i.e. subtypes or subject clusters) and meta-genes (i.e. representative subtype expression profiles). Cross-sectional study of smokers. 229 subjects from the ECLIPSE study were analyzed in the model discovery phase. 135 subjects from the COPDGene Study (GSE42057) were used for replication. Please note that the entire data set for total 364 samples including the re-analyzed samples is provided in the *364samples.txt files.