Matrix matters: the importance of the food matrix in bioaccessibility and basolateral recovery of microalgal-sourced DHA.

Abstract

Omega-3 long-chain polyunsaturated fatty acids (LC-PUFAs), such as docosahexaenoic acid (DHA), are known for their positive health effects. To meet recommended intake levels, people commonly consume fish and microalgal oils as supplements, typically in the form of encapsulated triacylglycerols (TAGs). However, ingesting omega-3 LC-PUFAs dispersed in a food matrix may be beneficial, as this has been shown to improve digestion for other oil types. This study investigated the in vitro bioaccessibility and basolateral recovery of DHA in DHA-rich microalgae oil in various forms: bulk oil, encapsulated oil, powdered oil, and oil incorporated into a protein matrix. After adapting the INFOGEST protocol for lipid digestion, we assessed bioaccessibility after in vitro digestion using back titration and gas chromatography coupled to a flame ionization detector (GC-FID). We used a Caco-2 cell model, adapted to take into account the lipid adhesion to the plastic plate, to assess basolateral DHA recovery. Results showed that the digestion of encapsulated oil and bulk oil was similar (n = 3). Powdered oil showed higher bioaccessibility than bulk oil (47.0 ± 2.5% for powder and 9.5 ± 0.7% for bulk, n = 3). In the Caco-2 model, powdered oil showed higher basolateral recovery (4.8 ± 0.9%) than bulk oil (1.2 ± 0.2%), although the experimental model limits interpretation (n = 3). To evaluate matrix effects, we designed a vegan cheese-like matrix (VCM) using different proteins. DHA in the VCM was 38% more bioaccessible than in bulk oil (n = 3), and we observed no differences in basolateral recovery. Our findings highlight that food matrices play a critical role in DHA bioaccessibility and basolateral recovery, potentially indicating increased intestinal uptake. Rather than a one-size-fits-all approach, methodological choices, including digestion protocols, transport models, and quantification strategies, should be selected based on the specific research question.