Plant extracts have recently received increased attention as alternative sources of antimicrobial agents in the fight against multidrug-resistant bacteria. Non-targeted metabolomics liquid chromatography-quadrupole time-of-flight tandem mass spectrometry, molecular networking, and chemometrics were used to evaluate the metabolic profiles of red and green leaves of two Brassica juncea (L.) varieties, var. integrifolia (IR and IG) and var. rugosa (RR and RG), as well as to establish a relationship between the elucidated chemical profiles and antivirulence activity. In total, 171 metabolites from different classes were annotated and principal component analysis revealed higher levels of phenolics and glucosinolates in var. integrifolia leaves and color discrimination, whereas fatty acids were enriched in var. rugosa, particularly trihydroxy octadecadienoic acid. All extracts demonstrated significant antibacterial activity against Staphylococcus aureus and Enterococcus faecalis, presenting the IR leaves the highest antihemolytic activity against S. aureus (99 % inhibition), followed by RR (84 %), IG (82 %), and RG (37 %) leaves. Antivirulence of IR leaves was further validated by reduction in alpha-hemolysin gene transcription (∼4-fold). Using various multivariate data analyses, compounds positively correlated to bioactivity, primarily phenolic compounds, glucosinolates, and isothiocyanates, were also identified.

In this work, an untargeted metabolomic approach based on sensitive analysis by on‐line solid‐phase extraction capillary electrophoresis mass spectrometry (SPE‐CE‐MS) in combination with multivariate data analysis is proposed as an efficient method for the identification of biomarkers of Huntington's disease (HD) progression in plasma. For this purpose, plasma samples from wild‐type (wt) and HD (R6/1) mice of different ages (8, 12, and 30 weeks), were analyzed by C₁₈‐SPE‐CE‐MS in order to obtain the characteristic electrophoretic profiles of low molecular mass compounds. Then, multivariate curve resolution alternating least squares (MCR‐ALS) was applied to the multiple full scan MS datasets. This strategy permitted the resolution of a large number of metabolites being characterized by their electrophoretic peaks and their corresponding mass spectra. A total number of 29 compounds were relevant to discriminate between wt and HD plasma samples, as well as to follow‐up the HD progression. The intracellular signaling was found to be the most affected metabolic pathway in HD mice after 12 weeks of birth, when mice already showed motor coordination deficiencies and cognitive decline. This fact agreed with the atrophy and dysfunction of specific neurons, loss of several types of receptors, and changed expression of neurotransmitters.