Based on enzymatic reactions-triggered changes of pH values and biocomputing, a novel and multistage interconnection biological network with multiple easy-detectable signal outputs has been developed. Compared with traditional chemical computing, the enzyme-based biological system could overcome the interference between reactions or the incompatibility of individual computing gates and offer a unique opportunity to assemble multicomponent/multifunctional logic circuitries. Our system included four enzyme inputs: β-galactosidase (β-gal), glucose oxidase (GOx), esterase (Est) and urease (Ur). With the assistance of two signal transducers (gold nanoparticles and acid–base indicators) or pH meter, the outputs of the biological network could be conveniently read by the naked eyes. In contrast to current methods, the approach present here could realize cost-effective, label-free and colorimetric logic operations without complicated instrument. By designing a series of Boolean logic operations, we could logically make judgment of the compositions of the samples on the basis of visual output signals. Our work offered a promising paradigm for future biological computing technology and might be highly useful in future intelligent diagnostics, prodrug activation, smart drug delivery, process control, and electronic applications.
In this study, we propose three methods of acidic pH shifting of egg yolk granules (EYGs) to investigate effects of EYGs structure on properties of EYGs-salted ovalbumin (SO) gels. Different pH parameters affect protein unfolding behavior, as well as assembly of high-density lipoprotein (HDL) and phosvitin during acidification. The main mechanism was a change in the microenvironment of hydrophobic amino acid residues and new hydrogen bonds, which induced the reassembly. Besides, low-content EYGs increased the mixed gel network structure density, cohesiveness (0.12–0.14) and chewiness (29.46–49.11). While mixed gels with high content EYGs had higher hardness and recovery rate, and were more tightly bound to water molecules. EYGs-4-6 exhibited greater hydrogen bonding forces, which could lead to a more rigid network and greater potential for use as an active filler. Our study tracked the trajectory of pH-shifting preparations of reassembled EYGs while providing new insight into nutritional value of SO gel.
In this study, soy protein isolate (SPI) was modified by a pulsed electric field (PEF) combined with pH shifting treatment (10 kV/cm, pH 11) to prepare SPI nanoparticles (PSPI11) for efficient loading of lutein. The results showed that when the mass ratio of SPI to lutein was 25:1, the encapsulation efficiency of lutein in PSPI11 increased from 54% to 77%, and the loading capacity increased by 41% compared to the original SPI. The formed SPI-lutein composite nanoparticles (PSPI11-LUTNPs) had smaller, more homogeneous sizes and larger negative charges than SPI7-LUTNPs. The combined treatment favored the unfolding of the SPI structure and could expose its interior hydrophobic groups to bind with lutein. Nanocomplexation with SPIs significantly improved the solubility and stability of lutein, with PSPI11 showing the greatest improvement. As a result, PEF combined with pH shifting pretreatment is an effective method for developing SPI nanoparticles loaded and protected with lutein.
危险品化学品经营许可证（带存储）