Comparative Evaluation of 5-n-Alkylresorcinol Extraction Conditions from Wheat Bran via Metabolite Profiling: Implications for Antiproliferative Activity
Year: 2025
Type: article
Abstract: Alkylresorcinols (ARs) are bioactive phenolic lipids with potential health-promoting properties; they are particularly abundant in wheat bran. This study aimed to compare the efficiency of eight extraction methods—including Soxhlet, ultrasound-assisted extraction (UAE), and overnight solvent-assisted maceration (OSAM) protocols—used in the removal of ARs from wheat bran, and to evaluate the association between AR composition and antiproliferative activity. A metabolite profiling approach using HPLC-DAD-MS identified 12 AR homologs differing in side-chain length and functional groups. Among the extraction strategies, the UA extraction, OSAM and Soxhlet-assisted with only acetone yielded the highest concentrations of bioactive ARs, particularly the C17–C25 homologs characteristic of cereals. Sparse partial least squares discriminant analysis (sPLS-DA) determined the discrimination of the different extraction methods, while variable importance scores revealed that AR homologs such as C25, C19:1, and C23:Oxo were key to the distinguishment of the extraction methods. Antiproliferative assays against PC-3 prostate cancer cells (IC50 = 13.3–55.6 µg/mL) demonstrated that extracts rich in oxygenated ARs exhibited significantly higher antiproliferative effects than those dominated by saturated compounds. This finding suggests that both side-chain length and functionalization (e.g., keto groups) influence AR bioactivity. These findings suggest that extraction conditions can be optimized not only to enhance AR yield but also to enrich homologs with higher antiproliferative potential, providing foundations for exploring AR-enriched products derived from wheat bran.
Source: Foods
Institution: Military University Nueva Granada
Language: English
Subfield: Biochemistry
Field: Medicine
Domain: Health Sciences
Open Access status: gold
Estimated APC paid: $3,499
Award: G5754317433
OpenAlex ID: W4411350451
