Protein expression profile of rat type two alveolar epithelial cells during hyperoxic stress and recovery

Abstract

In rodent model systems, the sequential changes in lung morphology resulting from hyperoxic injury are well characterized and are similar to changes in human acute respiratory distress syndrome. In the injured lung, alveolar type two (AT2) epithelial cells play a critical role in restoring the normal alveolar structure. Thus characterizing the changes in AT2 cells will provide insights into the mechanisms underpinning the recovery from lung injury. We applied an unbiased systems-level proteomics approach to elucidate molecular mechanisms contributing to lung repair in a rat hyperoxic lung injury model. AT2 cells were isolated from rat lungs at predetermined intervals during hyperoxic injury and recovery. Protein expression profiles were determined by using iTRAQ with tandem mass spectrometry. Of the 959 distinct proteins identified, 183 significantly changed in abundance during the injury-recovery cycle. Gene ontology enrichment analysis identified cell cycle, cell differentiation, cell metabolism, ion homeostasis, programmed cell death, ubiquitination, and cell migration to be significantly enriched by these proteins. Gene set enrichment analysis of data acquired during lung repair revealed differential expression of gene sets that control multicellular organismal development, systems development, organ development, and chemical homeostasis. More detailed analysis identified activity in two regulatory pathways, JNK and miR 374. A novel short time-series expression miner algorithm identified protein clusters with coherent changes during injury and repair. We concluded that coherent changes occur in the AT2 cell proteome in response to hyperoxic stress. These findings offer guidance regarding the specific molecular mechanisms governing repair of the injured lung.

Keywords: acute respiratory distress syndrome; alveolar epithelial cell proteome; bioinformatics; hyperoxia.

Fig. 1.

Mass spectrometric (MS) changes in representative alveolar type 2 cell proteins. Surfactant protein B (identified in all 3 iTRAQ MS/MS experiments) and peroxiredoxin-6, an antioxidant enzyme, and β₁ unit of Na,K-ATPase (identified in 2 of the 3 iTRAQ MS/MS experiments) changes in protein abundance at various time points of hyperoxia and recovery. Each line represents the temporal changes in protein abundance for 2 animals at each time point.

Fig. 2.

Biological processes enriched by proteins identified by the linear mixed-effects model to demonstrate a significant change during hyperoxic injury and recovery. A linear mixed-effects ANOVA model identified 183 proteins that demonstrated a significant change during injury and recovery time course controlling for a false discovery rate ≤10%. Gene ontology (GO) enrichment analysis using Database for Annotation, Visualization, and Integrated Discovery was performed on these 183 proteins, and a functional annotation-clustering tool was used to group related biological processes. In the functional annotation-clustering tool, an enrichment score of 1.3 that corresponds to a nonlog scale P value of 0.05 was used as the cutoff for significance. The pie chart shows the number of proteins that belong to each functional cluster.

Fig. 3.

A: protein clusters identified using the short time-series expression miner (STEM) algorithm that demonstrate coherent changes during hyperoxic injury and recovery. Data from the 3 separate iTRAQ experiments were analyzed using “repeat data” functionality in the STEM algorithm. Of the 50 distinct randomly generated model profiles tested, the 7 profiles that had a significantly higher number of proteins assigned to them are depicted in each small square. For each individual profile, the horizontal axis represents the 7 time points of our experimental design. The vertical axis represents the change in protein expression. The number on the top left-hand corner of a profile box is the STEM-generated profile ID number, and the bottom left-hand corner is the number of proteins assigned to that profile. B: individual protein expression patterns from 4 STEM profiles (a–d). 4 of the 7 model profiles shown in Fig. 3 had groups of proteins (clusters) that had interesting temporal changes in their expression pattern (protein abundance relative to controls) during injury and recoveries. Each colored line represents an individual protein expression. The horizontal axis represents experimental time points, and the vertical axis represents changes in the protein expression. Gene symbols of the individual proteins in each of the profile are provided in Supplemental Table S5. The GO enrichment analysis for the proteins represented in each profile is shown in Table 3.

Fig. 4.

A: moesin protein expression. a: Moesin relative expression by iTRAQ labeling and mass spectrometer. Each line represents the temporal changes in protein abundance for 2 animals at each time point. b: Western blot analysis of moesin at the various experimental time points obtained with equal protein loading. B: CD9 protein expression. a: CD9 relative expression by iTRAQ labeling and mass spectrometer. Each line represents the temporal changes in protein abundance for 2 animals at each time point. b: Western blot analysis of CD9 at the various experimental time points obtained with equal protein loading (55 μg).