Effect of dissolved organic matter on bacterial regrowth and response after ultraviolet disinfection.

The effect of dissolved organic matter (DOM) on bacterial regrowth in water after disinfection using ultraviolet (UV) light emitting diodes (UVLEDs) is still unclear. Herein, the regrowth and responses of Vibrio parahaemolyticus and Bacillus cereus were investigated after being exposed to UVLEDs at combined wavelengths (265 and 280 nm) in a phosphate-buffered saline consisting of Suwannee River natural organic matter (SRNOM) and Suwannee River fulvic acid (SRFA). Low-molecular-weight (MW) organic compounds, which may form into intermediary photoproducts, and indicate bacterial repair metabolism, were characterized through non-target screening using orbitrap mass spectrometry. This study demonstrates the ability of the UVLEDs-inactivated cells to regrow. After UV exposure, a considerable upregulation of RecA was observed in two strains. With increasing the incubation time, the expression levels of RecA in V. parahaemolyticus increased, which may be attributed to the dark repair mechanism. Coexisting anionic DOM affects both the disinfection and bacterial regrowth processes. The time required for bacterial regrowth after UV exposure reflects the time needed for the individual cells to reactivate, and it differs in the presence or absence of DOM. In the presence of DOM, the cells were less damaged and required less time to grow. The UVLEDs exposure results in the occurrence of low-MW organic compounds, including carnitine or acryl-carnitine with N-acetylmuramic acid, which are associated with bacterial repair metabolism. Overall, the results of this study expand the understanding of the effects of water matrices on bacterial health risks. This can aid in the development of more effective strategies for water disinfection.

Metabolomic identification of biochemical changes induced by fluoxetine in an insulinoma cell line (MIN6).

Background and purpose: The use of fluoxetine raises the risk of pancreatic beta-cell dysfunction. However, the specific mechanism behind its mechanism of action in beta cells is unknown. This study investigated the cellular response of MIN6 cells to fluoxetine using untargeted cell-based metabolomics. Experimental approach: Metabolic profiling of MIN6 cells was performed using liquid chromatography-high resolution mass spectrometry (LC-HRMS) analysis on samples prepared under optimized conditions, followed by principal component analysis, partial least squares-discriminant analysis, and pair-wise orthogonal projections to latent structures discriminant analyses. Findings/Results: Sixty-six metabolites that had been differentially expressed between the control and fluoxetine-treated groups demonstrated that the citric acid cycle is mainly perturbed by fluoxetine treatment. Conclusion and implications: The current study provides insights into the molecular mechanisms of fluoxetine effects in MIN6 cells.

Exploring the mechanisms of clozapine-induced blood-brain barrier dysfunction using untargeted metabolomics and cellular metabolism analysis.

Brain microvascular endothelial cells (BMVECs) from the blood- brain barrier form a highly selective membrane that protects the brain from circulating blood and maintains a stable microenvironment for the central nervous system. BMVEC dysfunction has been implicated in a variety of neurological and psychiatric disorders. Clozapine, a widely used antipsychotics, has been demonstrated to alter the permeability of BMVECs, but the underlying mechanisms of this effect are not fully understood. In this study, we investigated the effects of clozapine in BMVECs using untargeted metabolomics analysis. Our results illustrated that treatment with clozapine led to significant changes in the metabolic profile of BMVECs, including alterations in amino acid and energy metabolism. These findings suggest that clozapine affects BMVEC permeability through its effects on cellular metabolism. Our study could inform the development of more targeted and effective treatments for understanding the relationships among clozapine, cellular metabolism, and BMVECs in more detail.

Quantification of antipsychotic biotransformation in brain microvascular endothelial cells by using untargeted metabolomics.

Most studies of antipsychotic-therapies have highlighted the discrepancy between plasma and brain pharmacokinetics of antipsychotics, but how the drug changes through the blood brain barrier (BBB) has not been investigated. Cell-based metabolomics using liquid chromatography-mass spectrometry (LC-MS) combined with multivariate data analysis were applied for screening of antipsychotic metabolites in the BBB. We applied this approach to analyze the antipsychotic biotransformation in brain microvascular endothelia cells (BMVECs), the main component of the BBB. From this study, five, four, three, and one metabolite of chlorpromazine, clozapine, haloperidol and risperidone, respectively, were locally metabolized on the BMVECs. These results confirm that there is a drug biotransformation process within the BBB and show that drug metabolite screening employed cell-based metabolomics using LC-MS, combined with multivariate analysis in the study of BMVECs exposed to antipsychotics can provide a way to screen drug metabolites in the BBB.

Application of gelatin-coated magnetic particles for isolation of genomic DNA from bacterial cells.

Gelatin-coated magnetic particles were implemented for bacterial genomic DNA isolation in this study. Based on structural differences in the cell wall, the standard strains Staphylococcus aureus and Escherichia coli were selected. The quantity, quality, and timing process for DNA extraction using gelatin-coated magnetite were compared to reference phenol-chloroform extraction and a commercially available kit. Approximately twice as much DNA was recovered with the use of coated magnetite, providing greater yields than other DNA extraction methods. In addition, the DNA quality was determined using 16S ribosomal DNA (rDNA) gene amplification by polymerase chain reaction (PCR). The described technique is rapid, simple, and a well-suited method to use with PCR for diagnosis of bacterial infections.