Modulation of epithelial sodium channel (ENaC) expression in mouse lung infected with Pseudomonas aeruginosa

BACKGROUND: The intratracheal instillation of Pseudomonas aeruginosa entrapped in agar beads in the mouse lung leads to chronic lung infection in susceptible mouse strains. As the infection generates a strong inflammatory response with some lung edema, we tested if it could modulate the expression of genes involved in lung liquid clearance, such as the α, β and γ subunits of the epithelial sodium channel (ENaC) and the catalytic subunit of Na(+)-K(+)-ATPase. METHODS: Pseudomonas aeruginosa entrapped in agar beads were instilled in the lung of resistant (BalB/c) and susceptible (DBA/2, C57BL/6 and A/J) mouse strains. The mRNA expression of ENaC and Na(+)-K(+)-ATPase subunits was tested in the lung by Northern blot following a 3 hours to 14 days infection. RESULTS: The infection of the different mouse strains evoked regulation of α and β ENaC mRNA. Following Pseudomonas instillation, the expression of αENaC mRNA decreased to a median of 43% on days 3 and 7 after infection and was still decreased to a median of 45% 14 days after infection (p < 0.05). The relative expression of βENaC mRNA was transiently increased to a median of 241%, 24 h post-infection before decreasing to a median of 43% and 54% of control on days 3 and 7 post-infection (p < 0.05). No significant modulation of γENaC mRNA was detected although the general pattern of expression of the subunit was similar to α and β subunits. No modulation of α(1)Na(+)-K(+)-ATPase mRNA, the catalytic subunit of the sodium pump, was recorded. The distinctive expression profiles of the three subunits were not different, between the susceptible and resistant mouse strains. CONCLUSIONS: These results show that Pseudomonas infection, by modulating ENaC subunit expression, could influence edema formation and clearance in infected lungs

Comparison of Muscle Transcriptome between Pigs with Divergent Meat Quality Phenotypes Identifies Genes Related to Muscle Metabolism and Structure

Background: Meat quality depends on physiological processes taking place in muscle tissue, which could involve a large pattern of genes associated with both muscle structural and metabolic features. Understanding the biological phenomena underlying muscle phenotype at slaughter is necessary to uncover meat quality development. Therefore, a muscle transcriptome analysis was undertaken to compare gene expression profiles between two highly contrasted pig breeds, Large White (LW) and Basque (B), reared in two different housing systems themselves influencing meat quality. LW is the most predominant breed used in pig industry, which exhibits standard meat quality attributes. B is an indigenous breed with low lean meat and high fat contents, high meat quality characteristics, and is genetically distant from other European pig breeds. Methodology/Principal Findings: Transcriptome analysis undertaken using a custom 15 K microarray, highlighted 1233 genes differentially expressed between breeds (multiple-test adjusted P-value,0.05), out of which 635 were highly expressed in the B and 598 highly expressed in the LW pigs. No difference in gene expression was found between housing systems. Besides, expression level of 12 differentially expressed genes quantified by real-time RT-PCR validated microarray data. Functional annotation clustering emphasized four main clusters associated to transcriptome breed differences: metabolic processes, skeletal muscle structure and organization, extracellular matrix, lysosome, and proteolysis, thereb

RNA-seq analysis in plant–fungus interactions

Many fungi are pathogens that infect important food and plantation crops, reducing both yield and quality of food products. Understanding plant–fungus interactions is crucial as knowledge in this area is required to formulate sustainable strategies to improve plant health and crop productivity. High-throughput RNA-sequencing (RNA-seq) enables researchers to gain insights of the mixed and multispecies transcriptomes in plant–fungus interactions. Interpretation of huge data generated by RNA-seq has led to new insights in this area, facilitating a system approach in unraveling interactions between plant hosts and fungal pathogens. In this review, the application and challenges of RNA-seq analysis in plant–fungus interactions will be discussed