Controlling the Formation of Polyelectrolyte Complex Nanoparticles Using Programmable pH Reactions

Enabling complexation of weak polyelectrolytes, in the presence of a programmable pH-modulation, offers a means to achieve temporal control over polyelectrolyte coassembly. Here, by mixing oppositely charged poly(allylamine hydrochloride) and poly(sodium methacrylate) in a (bi)sulfite buffer, nanoscopic complex coacervates are formed. Addition of formaldehyde initiates the formaldehyde-sulfite clock reaction, affecting the polyelectrolyte assembly in two ways. First, the abrupt pH increase from the reaction changes the charge density of the polyelectrolytes and thus the ratio of cationic and anionic species. Simultaneously, reactions between the polyamine and formaldehyde lead to chemical modifications on the polymer. Interestingly, core–shell polymeric nanoparticles are produced, which remain colloidally stable for months. Contrastingly, in the same system, in the absence of the clock reaction, aggregation and phase separation occur within minutes to days after mixing. Introducing an acid-producing reaction enables further temporal control over the coassembly, generating transient nanoparticles with nanoscopic dimensions and an adjustable lifetime of tens of minutes

Spatial distribution of αs1-caseins and β-caseins in milk gels acidified with glucono-δ-lactone

Acid-induced destabilization of casein micelles leads to coagulation of milk which plays an important role in the formation of yogurt. The resulting protein network is formed by aggregation and reconfiguration of casein micelles, including the release of a portion of caseins from these micelles. It is so far unknown how individual αs1-and β-caseins are organized within this complex network, and how their distribution depends on yogurt composition and processing. Here, we imaged the spatial distribution of caseins using stimulated emission depletion (STED) microscopy and single-molecule localization microscopy (SMLM). We used fluorescently tagged antibodies against αs1-and β-caseins to localize them inside glucono-δ-lactone (GDL)-acidified milk gels. We conducted quantitative skeleton analysis of STED images and showed that αs1-and β-caseins contribute with different levels of connectivity to the acid induced milk network

Super resolution microscopy imaging of pH induced changes in the microstructure of casein micelles

Acidification of milk destabilizes casein micelles (CMs) and results in network formation. This process is fundamental during the manufacturing of dairy gels such as cheese and yoghurts. Understanding the structural alterations of CMs during this process aids to predict the physicochemical and sensory properties of dairy gels. Herein we utilize direct Stochastic Optical Reconstruction Microscopy (dSTORM) to visualize individual hydrated CMs and characterize pH-dependent changes in CM size distributions. CMs were immobilized, fixed, labelled with caseins-specific primary antibodies, and imaged by dSTORM using Alexa Fluor 647 conjugated secondary antibodies. While antibodies specific to κ- and β-casein were used to stain CMs, only β-casein antibodies enabled reproducible imaging of micelles across the entire chosen pH window. Furthermore, CM's structural evolution was studied at acidic pH values representing the conditions during acid milk gel formation and at three elevated pH values. dSTORM imaging of casein aggregates at pH 4.5, below the isoelectric point of caseins, showed that β-casein distribution throughout the protein network and resolved nano-sized pores within the structure. Moreover, automated and quantitative image analysis revealed that the average size of CMs increased upon alkalization to pH 7.5 and 8.3, whilst narrow size distributions were found upon acidification to pH 5.5

Quantitative image analysis of influence of polysaccharides on protein network formation in GDL-acidified milk gels

Exopolysaccharides (EPS) are commonly used to improve the texture of yogurt. These polysaccharides interact with casein micelles, the major protein in milk, via electrostatic and depletion mechanisms during fermentation by lactic acid bacteria (LAB). However, the relationship between the physicochemical properties and monosaccharide composition of EPS and their impact on yogurt texture is not yet fully understood. To address this knowledge gap, we studied the effects of polysaccharides commonly used as food additives on acid-induced milk protein networks. Confocal laser scanning microscopy (CLSM) was used to image the network microstructures. Image analysis, including Fourier transform, autocorrelation, and binarization-based techniques, was applied to quantify key structural features of the mixed milk protein/polysaccharide gels. These parameters were then related to the macroscopic properties of the model food matrices, such as elastic and viscous moduli and yield point. We found that the addition of neutral polysaccharides resulted in a concentration-dependent increase in structure factor, protein domain size, and pore fraction. In contrast, the presence of charged polysaccharides led to an increase in protein domain size, a decrease in pore fraction, and a decrease in elastic and viscous moduli. These results demonstrate the use of a quantitative image analysis method for selecting LAB with favorable EPS properties to improve yogurt texture