Profile Of Lung Tissue Research Articles

Identification of multiple dysregulated metabolic pathways by GC-MS-based profiling of lung tissue in mice with PM2.5-induced asthma

The risk of development of asthma, a multi-faceted chronic disease, increases as a result of exposure to PM2.5. However, the mechanism underlying asthma-related metabolic changes caused by PM2.5 exposure is unclear. Here, we investigated the major metabolic changes, metabolic pathways involved, and underlying molecular mechanisms in mice with PM2.5 exposure-induced asthma. Forty-eight adult female mice were randomly assigned to control (C), low concentration-PM2.5 exposure: 0.50 mg kg−1 (L), medium concentration-PM2.5 exposure: 1.58 mg kg−1 (M), and high concentration-PM2.5 exposure: 4.98 mg kg−1 (H) groups. M and H groups presented significantly higher IL-4, IL-8, IL-1β, IL-5, IL-13, and OVA-specific IgE levels, and significantly lower IFN-γ levels, than the C group, as well as significantly increased eosinophil count and MUC5AC expression in the lung tissue. These findings indicate that exposure to medium and high concentrations of PM2.5 induced asthma in mice. Statistical analyses identified 13 asthma-related major metabolites, which were analyzed by gas chromatography-mass spectrometry (GC-MS). Meta Mapp Software revealed 4 major metabolic pathways. PM2.5-induced ATP requirement and oxidative stress may perturb metabolic processes in asthma. The present findings increase our understanding of the toxic effect of PM2.5 in the development of asthma and identify potentially useful biomarkers.

Identification and validation of differentially expressed transcripts by RNA-sequencing of formalin-fixed, paraffin-embedded (FFPE) lung tissue from patients with Idiopathic Pulmonary Fibrosis

BackgroundIdiopathic Pulmonary Fibrosis (IPF) is a lethal lung disease of unknown etiology. A major limitation in transcriptomic profiling of lung tissue in IPF has been a dependence on snap-frozen fresh tissues (FF). In this project we sought to determine whether genome scale transcript profiling using RNA Sequencing (RNA-Seq) could be applied to archived Formalin-Fixed Paraffin-Embedded (FFPE) IPF tissues.ResultsWe isolated total RNA from 7 IPF and 5 control FFPE lung tissues and performed 50 base pair paired-end sequencing on Illumina 2000 HiSeq. TopHat2 was used to map sequencing reads to the human genome. On average ~62 million reads (53.4% of ~116 million reads) were mapped per sample. 4,131 genes were differentially expressed between IPF and controls (1,920 increased and 2,211 decreased (FDR < 0.05). We compared our results to differentially expressed genes calculated from a previously published dataset generated from FF tissues analyzed on Agilent microarrays (GSE47460). The overlap of differentially expressed genes was very high (760 increased and 1,413 decreased, FDR < 0.05). Only 92 differentially expressed genes changed in opposite directions. Pathway enrichment analysis performed using MetaCore confirmed numerous IPF relevant genes and pathways including extracellular remodeling, TGF-beta, and WNT. Gene network analysis of MMP7, a highly differentially expressed gene in both datasets, revealed the same canonical pathways and gene network candidates in RNA-Seq and microarray data. For validation by NanoString nCounter® we selected 35 genes that had a fold change of 2 in at least one dataset (10 discordant, 10 significantly differentially expressed in one dataset only and 15 concordant genes). High concordance of fold change and FDR was observed for each type of the samples (FF vs FFPE) with both microarrays (r = 0.92) and RNA-Seq (r = 0.90) and the number of discordant genes was reduced to four.ConclusionsOur results demonstrate that RNA sequencing of RNA obtained from archived FFPE lung tissues is feasible. The results obtained from FFPE tissue are highly comparable to FF tissues. The ability to perform RNA-Seq on archived FFPE IPF tissues should greatly enhance the availability of tissue biopsies for research in IPF.

Network Clusters Analysis Based on Protein–Protein Interaction Network Constructed in Phosgene-Induced Acute Lung Injury

Acute lung injury (ALI) is characterized by impairment in gas exchange and/or lung mechanics that leads to hypoxemia with the presence of diffuse pulmonary infiltrate. Assessments of lung injury play important roles in the development of rational medical countermeasures. The purpose of this study is to investigate the molecular mechanisms of phosgene-induced lung injury. We downloaded the gene expression profile of lung tissue from mice exposed to air or phosgene from gene expression omnibus database and identified differentially expressed genes (DEGs) in ALI. Furthermore, we constructed a protein-protein interaction (PPI) network and identified network clusters. In total, 582 DEGs were found and 4 network clusters were identified in the constructed PPI network. Gene set enrichment analysis found that DEGs were mainly involved in mitochondrion organization and biogenesis, mRNA metabolic process, negative regulation of transferase activity or catalytic activity, and coenzyme metabolic process. Pathways of spliceosome, glutathione metabolism, and cell cycle were dysregulated in phosgene-induced ALI. Besides, we identified four genes, including F3, Meis1, Pvf, and Cdc6 in network clusters, which may be used as biomarkers of phosgene-induced ALI. Our results revealed biological processes and pathways involved in phosgene-induced ALI and may expand understandings of phosgene-induced ALI. However, further experiments are needed to confirm our findings.

Radon-Induced Proteomic Profile of Lung Tissue in Rats

The aim of this study was to investigate the differential expression of proteins in lung of rats following long-term exposure to radon. The total proteins of lung tissue from Wistar rats exposed to radon for cumulative doses up to 100, 200, or 400 WLM (working level months) were isolated by two-dimensional electrophoresis (2-DE) and analyzed with ImageMaster 2D Platinum software. Comparison of the 2-DE images between the control and radon-exposed groups resulted in 14 upregulated and 9 downregulated protein spots, of which 15 were identified by matrix-assisted laser desorption/ionization time-of-flight (MALDI-TOF) or matrix-assisted laser desorption/ionization time-of-flight/time-of-flight mass spectrometry (MALDI-TOF/TOF-MS). The simultaneous up-expressions of RAGE and S100A6 indicated that both proteins might be applied as biomarkers for lung injury induced by long-term radon exposure.