In vitro Digestion of Phaseolus vulgaris L. Cooked Beans Induces Autophagy in Colon Cancer Cells.
Clizia BernardiGiulia MacrìMarco BiagiElisabetta MiraldiFederica FinettiLorenza TrabalziniPublished in: Foods (Basel, Switzerland) (2023)
Phaseolus vulgaris L. (common bean) contains high levels of proteins, unsaturated fatty acids, minerals, fibers, and vitamins, and for this reason, it represents an essential component of the diet. More than 40,000 varieties of beans have been recognized and are staple foods in the traditional cuisine of many countries. In addition to its high nutritional value, P. vulgaris is also characterized by its nutraceutical properties and favors environmental sustainability. In this manuscript, we studied two different varieties of P. vulgaris , Cannellino and Piattellino. We investigated the effects of traditional processing (soaking and cooking) and in vitro gastrointestinal digestion of beans on their phytochemical composition and anticancer activity. Using HT29 and HCT116 colon cancer cell lines, we showed that the extract obtained after gastrointestinal digestion of cooked beans (the bioaccessible fraction, BF) induces cell death through the induction of the autophagic process. We demonstrated that the BF of Cannellino and Piattellino beans at the concentration of 100 μg/mL reduces cell vitality, measured by MMT assay, of both HT29 (88.41% ± 5.79 and 94.38% ± 0.47) and HCT116 (86.29% ± 4.3 and 91.23% ± 0.52) cell lines. Consistently, the treatment of HT29 cells with 100 μg/mL of Cannellino and Piattellino BFs reduced clonogenicity by 95% ± 2.14 and 96% ± 0.49, respectively. Moreover, the activity of extracts appeared to be selective for colon cancer cells. The data shown in this work further confirm P. vulgaris to be among foods with beneficial effects for human health.
Keyphrases
- cell death
- cell cycle arrest
- human health
- risk assessment
- induced apoptosis
- oxidative stress
- fatty acid
- signaling pathway
- pi k akt
- anaerobic digestion
- weight loss
- stem cells
- endoplasmic reticulum stress
- physical activity
- electronic health record
- single cell
- machine learning
- big data
- cell therapy
- mesenchymal stem cells
- combination therapy
- deep learning
- anti inflammatory
- single molecule