Whole-transcriptome analysis reveals mechanisms underlying antibacterial activity and biofilm inhibition by a malic acid combination (MAC) in Pseudomonas aeruginosa.

Background: Pseudomonas aeruginosa is a highly prevalent bacterial species known for its ability to cause various infections and its remarkable adaptability and biofilm-forming capabilities. In earlier work, we conducted research involving the screening of 33 metabolites obtained from a commercial source against two prevalent bacterial strains, Escherichia coli and Staphylococcus aureus. Through screening assays, we discovered a novel malic acid combination (MAC) consisting of malic acid, citric acid, glycine, and hippuric acid, which displayed significant inhibitory effects. However, the precise underlying mechanism and the potential impact of the MAC on bacterial biofilm formation remain unknown and warrant further investigation. Methods: To determine the antibacterial effectiveness of the MAC against Pseudomonas aeruginosa, we conducted minimum inhibitory concentration (MIC) and minimum bactericidal concentration (MBC) assays. Transmission electron microscopy (TEM) and scanning electron microscopy (SEM) techniques were employed to observe bacterial morphology and biofilm formation. We further performed a biofilm inhibition assay to assess the effect of the MAC on biofilm formation. Whole-transcriptome sequencing and bioinformatics analysis were employed to elucidate the antibacterial mechanism of the MAC. Additionally, the expression levels of differentially expressed genes were validated using the real-time PCR approach. Results: Our findings demonstrated the antibacterial activity of the MAC against P. aeruginosa. SEM analysis revealed that the MAC can induce morphological changes in bacterial cells. The biofilm assay showed that the MAC could reduce biofilm formation. Whole-transcriptome analysis revealed 1093 differentially expressed genes consisting of 659 upregulated genes and 434 downregulated genes, in response to the MAC treatment. Mechanistically, the MAC inhibited P. aeruginosa growth by targeting metabolic processes, secretion system, signal transduction, and cell membrane functions, thereby potentially compromising the survival of this human pathogen. This study provides valuable insights into the antibacterial and antibiofilm activities of the MAC, a synergistic and cost-effective malic acid combination, which holds promise as a potential therapeutic drug cocktail for treating human infectious diseases in the future.

iTRAQ-Based Quantitative Proteomics Approach Identifies Novel Diagnostic Biomarkers That Were Essential for Glutamine Metabolism and Redox Homeostasis for Gastric Cancer.

PURPOSE: To screen the novel biomarkers for gastric cancer and to determine the values of glutaminase 1 (GLS1) and gamma-glutamylcyclotransferase (GGCT) for detecting gastric cancer. EXPERIMENTAL DESIGN: A discovery group of four paired gastric cancer tissue samples are labeled with Isobaric tag for relative and absolute quantitation agents and identified with LC-ESI-MS/MS. A validation group of 168 gastric cancer samples and 30 healthy controls are used to validate the expression of GLS1 and GGCT. RESULTS: Four hundred and thirty-one proteins are found differentially expressed in gastric cancer tissues. Of these proteins, GLS1 and GGCT are found overexpressed in gastric cancer patients, with sensitivity of 75.6% (95% CI: 69-82.2%) and specificity of 81% (95% CI: 75-87%) for GLS1, and with sensitivity of 63.1% (95% CI: 55.7-71.5%) and specificity of 60.7% (95% CI: 53.3-68.2%) for GGCT. The co-expression of GLS1 and GGCT in gastric cancer tissues has sensitivity of 78.1% (95% CI: 70.1-86.1%) and specificity of 86.5% (95% CI: 79.5-93.4%). Moreover, both GLS1 and GGCT present higher expression of 82.6% (95% CI: 68.5-99.4%) and 73.9% (95% CI: 54.5-93.3%) in lymph node metastasis specimen than those in non-lymph node metastasis specimen. The areas under ROC curves are up to 0.734 for the co-expression of GLS1 and GGCT in gastric cancer. The co-expression of GLS1 and GGCT is strongly associated with histological grade, lymph node metastasis, and TNM stage Ⅲ/Ⅳ. CONCLUSIONS AND CLINICAL RELEVANCE: The present study provides the quantitative proteomic analysis of gastric cancer tissues to identify prognostic biomarkers of gastric cancer. The co-expression level of GLS1 and GGCT is of great clinical value to serve as diagnostic and therapeutic biomarkers for early gastric cancer.