To Develop the Method for UHPLC-HRMS to Determine the Antibacterial Potential of a Central American Medicinal Plant

Flow Injection-High Resolution-Electrospray Ionization-Mass Spectrometry (FI-HR-ESI-MS) Method for the Screening of Antimicrobial Pharmaceutical Drugs and Compounds against Klebsiella pneumoniae

The development of drug resistant microorganism is a global threat. Therefore, screening of more compounds for antimicrobial potentials is needed. Hence, a rapid method was developed for the screening of antimicrobial drugs and compounds against Klebsiella pneumoniae using Flow Injection Analysis-High Resolution-Mass Spectrometry. The method was optimized for bacterial culture time and concentration of drugs. IC₅₀ values for the drugs were calculated from the percent intensity of 704.5207 m/z of K. pneumoniae at 5 hrs incubation. This mass was proposed as diacylglycerophosphoethanolamine and observed as a potential biomarker of K. pneumoniae for the evaluation of inhibition potential of antimicrobial drugs and compounds. The calculated values for half maximal inhibitory concentration of cefixime, gentamicin and enrofloxacin were 0.052, 0.028 and 0.042 µg/mL, respectively. Ten compounds were also screened against the developed method, among them one compound (RSE-6) was found to be active with IC₅₀ value of 45.08 µg/mL. The obtained results were further compared with MIC values, obtained from micro dilution and Alamar blue assay after 24 hrs incubation. In comparison to these methods, developed method is sensitive, reproducible, rapid and robust for the determination of IC₅₀ value or inhibition potential of the drugs and compounds even at early incubation period of 5 hours.

Chromatographic Profiling with Machine Learning Discriminates the Maturity Grades of Nicotiana tabacum L. Leaves

Nicotiana tabacum L. (NTL) is an important agricultural and economical crop. Its maturity is one of the key factors affecting its quality. Traditionally, maturity is discriminated visually by humans, which is subjective and empirical. In this study, we concentrated on detecting as many compounds as possible in NTL leaves from different maturity grades using ultra-performance liquid chromatography ion trap time-of-flight mass spectrometry (UPLC-IT-TOF/MS). Then, the low-dimensional embedding of LC-MS dataset by t-distributed stochastic neighbor embedding (t-SNE) clearly showed the separation of the leaves from different maturity grades. The discriminant models between different maturity grades were established using orthogonal partial least squares discriminant analysis (OPLS-DA). The quality metrics of the models are R2Y = 0.939 and Q2 = 0.742 (unripe and ripe), R2Y = 0.900 and Q2 = 0.847 (overripe and ripe), and R2Y = 0.972 and Q2 = 0.930 (overripe and unripe). The differential metabolites were screened by their variable importance in projection (VIP) and p-Values. The existing tandem mass spectrometry library of plant metabolites, the user-defined library of structures, and MS-FINDER were combined to identify these metabolites. A total of 49 compounds were identified, including 12 amines, 14 lipids, 10 phenols, and 13 others. The results can be used to discriminate the maturity grades of the leaves and ensure their quality.