Purification of Precision-Fermented β-Lactoglobulin by Alginate Precipitation and Its Effect on Gelation

• An alginate-to-protein molar ratio of 0.05:1 at pH 3 precipitates 95 % protein. • Alginate precipitation increases the protein purity from 32 % to 75–87 %. • Mannan impurity remains soluble in the supernatant, enabling protein separation. • The method is selective and differentiates between target protein and mannoprotein. • The presence of alginate leads to a particulate-like protein gel formation. Precision fermentation using Komagataella phaffii enables the production of yeast-derived recombinant β-lactoglobulin (rBLG), without the ethical concerns associated with cow’s milk production. However, more cost-effective downstream processing strategies are needed than the conventional chromatographic purification. Alginate has been shown to facilitate the separation of rBLG from impurities through complex coacervation, exploiting electrostatic interactions between alginate and protein at low pH to enable rBLG isolation. As alginate is widely used in foods as a stabilising and gelling agent, its complete removal from the target protein may not be necessary. Optimal protein precipitation was achieved at pH 3 with an alginate-to-protein molar ratio of 0.05:1, resulting in a protein recovery of 95.3 %. Complete removal of alginate proved challenging; following the alginate removal step, a final protein purity of 87 % was achieved, with 13 % residual alginate. In contrast, when alginate was retained, the protein fraction had a purity of 74.5 %, with 25.5 % alginate. Gelation tests confirmed that unpurified rBLG at 28 % protein cannot gel, whereas rBLG purified with alginate resulted in an earlier onset of gelation (23–29 min) and a higher final strength (1–3 kPa) compared to the reference, although the gel remained relatively brittle (with a critical strain of 1–1.5 %). This study highlights alginate coacervation as a viable approach for rBLG purification and suggests that retaining residual alginate may be advantageous for tailoring functionality to specific end-use applications.