Vernonia amygdalina Leaf Extract Induces Apoptosis in HeLa Cells: A Metabolomics and Proteomics Study.

Medicinal plants produce various bioactive molecules with potential anti-cancer properties with favorable safety profiles. We aimed to investigate the comprehensive composition of Vernonia amygdalina leaf extract and its cytotoxic effects via apoptosis in HeLa cells. The metabolomics approach using LC-MS/MS was conducted to gather the metabolite profile of the extract. Proteomics was performed to understand the comprehensive mechanistic pathways of action. The apoptosis was visualized by cellular staining and the apoptotic proteins were evaluated. V. amygdalina leaf extract exhibited dose-dependent cytotoxic effects on both HeLa and Vero cells after 24 h of exposure in the MTT assay with the IC50 values of 0.767 ± 0.0334 and 4.043 ± 0.469 µg mL-1, respectively, which demonstrated a higher concentration required for Vero cell cytotoxicity. The metabolomic profile of 112 known metabolites specified that the majority of them were alkaloids, phenolic compounds, and steroids. Among these metabolites, deacetylvindoline and licochalcone B were suggested to implicate cytotoxicity. The cytotoxic pathways involved the response to stress and cell death which was similar to doxorubicin. The upstream regulatory proteins, phosphatase and tensin homolog deleted on chromosome ten (PTEN) and X-box binding protein 1 (XBP1), were significantly altered, supporting the regulation of apoptosis and cell death. The levels of apoptotic proteins, c-Jun N-terminal kinases (JNK), p53, and caspase-9 were significantly increased. The novel insights gained from the metabolomic profiling and proteomic pathway analysis of V. amygdalina leaf extract have identified crucial components related to apoptosis induction, highlighting its potential to develop future chemotherapy.

High-Resolution Bacterial Cytological Profiling Reveals Intrapopulation Morphological Variations upon Antibiotic Exposure.

Phenotypic heterogeneity is crucial to bacterial survival and could provide insights into the mechanism of action (MOA) of antibiotics, especially those with polypharmacological actions. Although phenotypic changes among individual cells could be detected by existing profiling methods, due to the data complexity, only population average data were commonly used, thereby overlooking the heterogeneity. In this study, we developed a high-resolution bacterial cytological profiling method that can capture morphological variations of bacteria upon antibiotic treatment. With an unprecedented single-cell resolution, this method classifies morphological changes of individual cells into known MOAs with an overall accuracy above 90%. We next showed that combinations of two antibiotics induce altered cell morphologies that are either unique or similar to that of an antibiotic in the combinations. With these combinatorial profiles, this method successfully revealed multiple cytological changes caused by a natural product-derived compound that, by itself, is inactive against Acinetobacter baumannii but synergistically exerts its multiple antibacterial activities in the presence of colistin. The findings have paved the way for future single-cell profiling in bacteria and have highlighted previously underappreciated intrapopulation variations caused by antibiotic perturbation.