Inhibition of CRISPR-Cas12a trans-cleavage by lead (II)-induced G-quadruplex and its analytical application.

In this work, the inhibition of clustered regularly interspaced short palindromic repeats (CRISPR) - CRISPR associated protein (Cas) trans-cleavage by Pb2+-induced G-quadruplex has been firstly explored to detect Pb2+ in tea beverage and milk. In absence of Pb2+, the Na+-induced G-quadruplex can be cleaved by CRISPR-Cas12a. In contrast, Pb2+ can competitively combine with G-quadruplex, resulting in its conformational changes and resistance to trans-cleavage of CRISPR-Cas12a. Therefore, the fluorescence resonance energy transfer can happen. Pb2+ can be detected in a linear range from 100 nM to 5 µM with a lowest detection limit of 2.6 nM and a relative standard deviation of 4.32%. In summary, this work not only provides a new method for Pb2+ detection based on its induced G-quadruplex inhibition on CRISPR-Cas12a trans-cleavage, but also broadens the application of CRISPR-Cas system for heavy metal analysis in the field of food safety.

Bioactive substances and potentiality of marine microalgae.

Microalgae is one of the most important components in the aquatic ecosystem, and they are increasingly used in food and medicine production for human consumption due to their rapid growth cycle and survival ability in the harsh environment. Now, the exploration of microalgae has been gradually deepening, mainly focused on the field of nutrition, medicine, and cosmetics. A great deal of studies has shown that microalgae have a variety of functions in regulating the body health and preventing disease, such as nitrogen fixation, antitumor, antivirus, antioxidation, anti-inflammatory, and antithrombotic. Furthermore, microalgae can synthesize various high-valued bioactive substances, such as proteins, lipids, polysaccharides, and pigments. In this paper, we have briefly reviewed the research progress of main bioactive components in microalgae, proteins, lipids, polysaccharides, pigments, and other nutrients included, as well as their present application situation. This paper can provide the guidance for research and development of industrial production of microalgae.

Fabrication of Pickering emulsion based on particles combining pectin and zein: Effects of pectin methylation.

Although the stabilization of Pickering emulsions based on the interaction of pectin and zein is known to be effective, the effects of the degree of methylation (DM) of pectin on the stability of Pickering emulsions remains unclear. In the present study, pectin/zein particle dispersions (PZDs) were fabricated by anti-solvent precipitation based on different DM values of pectin (13.70 %-71.42 %). Differential Scanning Calorimetry (DSC) curves and Fourier transform infrared spectroscopy (FTIR) confirmed the methyl ester carbonyl and carbonyl groups significantly affected the formation of hydrogen bonds, which consequently resulting in the secondary conformation of PZDs as reflected by circular dichroism (CD). The PZDs fabricated by pectin with DM values higher than 35.50 % formation of the network between the barriers of the droplets, showed high stability against pH (3.0-9.0) and Ca2+ (60-300 mM) at an oil fraction (φ) of 0.60. Furthermore, the Pickering emulsions showed good lycopene protective effects.

Application of gas sensors for modelling the dynamic growth of Pseudomonas in pork stored at different temperatures.

Pseudomonas have a faster growth rate over other bacteria in chilled meat under aerobic conditions. A non-destructive method for modelling the dynamic growth of Pseudomonas in pork stored at different temperatures using gas sensors was presented in our work. Based on selected gas sensor data, the first-order kinetic equations (Gompertz and Logistic Functions) combined with the secondary model (Square-root Function) effectively simulated Pseudomonas growth in pork at different temperatures with R2 and RMSE values of 0.71-0.97 and 0.27-0.84, respectively. Additionally, these models showed high accuracy with correlation coefficients greater than 0.90, in addition to several individual accuracy values. Furthermore, HS-SPME/GC-MS results demonstrated the presence of identified key volatiles in samples inoculated with Pseudomonas, including three amine compounds (mercaptamine, 1-octanamine and 1-heptadecanamine), phenol and indole. Our work showed that gas sensors are a rapid, easy and non-destructive method with acceptable feasibility in modelling the dynamic growth of spoilage microorganisms in meat.

Dynamic changes of proton populations in potato flours during fermentation and their relationship with digestibility and functional properties.

The effects of fermentation on the dynamic state of proton populations, digestibility, and functional properties of potato flours prepared from Atlantic and Kexin No. 1 were investigated. Depending on the changes in moisture content and digestibility of potato flours during fermentation, three proton populations were distinguished. Populations P21 and P22 of fermented potato flours gradually increased during fermentation, resistant starch content, swelling power, and pasting properties also increased, whereas moisture content, digestible starch content, and water solubility index gradually decreased. Correlation analyses showed that populations P21 and P22 had significantly positive correlations with resistant starch content, swelling power, peak viscosity, and breakdown viscosity of fermented potato flours (p < 0.05), while population P23 had significantly positive correlations with moisture content, digestible starch content, and water solubility index (p < 0.001). The results implied that the proton population was an important factor influencing the digestibility and functional properties of fermented potato flours.

Effects of Fermentation on Compositions, Color, and Functional Properties of Gelatinized Potato Flours.

This study investigated effects of fermentation on compositions, color, and functional properties of gelatinized potato flours from Atlantic and Kexin No.1 cultivars. Atlantic flour (AF) and Kexin No.1 flour (KF) were fermented using 1% yeast concentration, respectively. Fermentation further improved the nutritional and physicochemical features of gelatinized potato flours by means of increased protein and ash contents, and decreased the levels of moisture, lipid, soluble amylose, amylopectin, and total starch. The lightness and whiteness of potato flours were enhanced with the increase in fermentation time. There are gradual increases in water absorption index, emulsifying capacity and emulsifying stability of potato flours during fermentation. However, bulk density of them slightly reduced with the increase in fermentation time. In addition, fermentation has no significant effect on freeze-thaw stability of gelatinized potato flours. These results indicate that yeast fermentation could enhance certain processing characteristics of potato flours and improve the applicability of them in food formulations. PRACTICAL APPLICATION: Lately, China has started national project regarding the use of potato flour in foods. However, due to dark color and low protein content of potato flours, their application in food formulations was limited. This study analyzed the possible mechanisms by which yeast fermentation improved the nutritional and functional characteristics of Atlantic flour (AF) and Kexin No. 1 flour (KF). From applications standpoint, findings of this study could provide knowledge on the selection of potato flours for various food formulations.

Investigating lignin from Canna edulis ker residues induced activation of α-amylase: Kinetics, interaction, and molecular docking.

The lignin isolated from C. edulis ker residues showed a significant activating effect on α-amylase. Further studies revealed that the isolated lignin formed a 1:1 complex with α-amylase through hydrogen bonding and quenched fluorescence of α-amylase with a static quenching procedure. Binding with lignin led to conformational and granular size changes of α-amylase. Two-dimensional nuclear Overhauser spectroscopy (2D-NOESY) spectra suggested that OH in G units and ß-O-4 structure were the major binding sites of lignin on the α-amylase molecule. Molecular docking studies indicated that the binding residue on α-amylase for lignin was not the same as for chloride ions, and the major binding force was hydrogen bonding. Furthermore, the docking results also showed the structural change of lignin induced by α-amylase. Thus, this work provided a new insight into the interaction between lignin from Canna edulis ker residues and α-amylase, which may be beneficial to apply lignin in the food industry.

Evaluation of lipid oxidation of Chinese-style sausage during processing and storage based on electronic nose.

A portable electronic nose was used for extracting flavour fingerprint map of Chinese-style sausage during processing and storage, in parallel with detection of acid value (AV) and peroxide value (POV) for evaluating lipid oxidation. Sausage samples during processing and storage were divided into three and five quality phases, respectively. After comparison of sensors response to lipid oxidation, optimal sensor array was determined. Several classification and regression models were developed to classify samples into their respective quality phase and predict lipid oxidation using full and optimal sensor array. Results indicated classification accuracy for sausage samples were, respectively, above 95% and 82% during the processing and storage. For support vector machine (SVM) and artificial neural networks (ANN) regression models, good performance in predicting AV and POV were obtained, with the coefficients of determination (R2s) >0.914 and 0.814 during processing and storage, respectively. Thus, E-nose demonstrated acceptable feasibility in evaluating the degree of lipid oxidation of Chinese-style sausage during processing and storage.

Hyperspectral imaging detection of decayed honey peaches based on their chlorophyll content.

Honey peach is a very common but highly perishable market fruit. When pathogens infect fruit, chlorophyll as one of the important components related to fruit quality, decreased significantly. Here, the feasibility of hyperspectral imaging to determine the chlorophyll content thus distinguishing diseased peaches was investigated. Three optimal wavelengths (617nm, 675nm, and 818nm) were selected according to chlorophyll content via successive projections algorithm. Partial least square regression models were established to determine chlorophyll content. Three band ratios were obtained using these optimal wavelengths, which improved spatial details, but also integrates the information of chemical composition from spectral characteristics. The band ratio values were suitable to classify the diseased peaches with 98.75% accuracy and clearly show the spatial distribution of diseased parts. This study provides a new perspective for the selection of optimal wavelengths of hyperspectral imaging via chlorophyll content, thus enabling the detection of fungal diseases in peaches.

Predicting the growth situation of Pseudomonas aeruginosa on agar plates and meat stuffs using gas sensors.

A rapid method of predicting the growing situation of Pseudomonas aeruginosa is presented. Gas sensors were used to acquire volatile compounds generated by P. aeruginosa on agar plates and meat stuffs. Then, optimal sensors were selected to simulate P. aeruginosa growth using modified Logistic and Gompertz equations by odor changes. The results showed that the responses of S8 or S10 yielded high coefficients of determination (R2) of 0.89-0.99 and low root mean square errors (RMSE) of 0.06-0.17 for P. aeruginosa growth, fitting the models on the agar plate. The responses of S9, S4 and the first principal component of 10 sensors fit well with the growth of P. aeruginosa inoculated in meat stored at 4 °C and 20 °C, with R2 of 0.73-0.96 and RMSE of 0.25-1.38. The correlation coefficients between the fitting models, as measured by electronic nose responses, and the colony counts of P. aeruginosa were high, ranging from 0.882 to 0.996 for both plate and meat samples. Also, gas chromatography-mass spectrometry results indicated the presence of specific volatiles of P. aeruginosa on agar plates. This work demonstrated an acceptable feasibility of using gas sensors-a rapid, easy and nondestructive method for predicting P. aeruginosa growth.

Growth Simulation and Discrimination of Botrytis cinerea, Rhizopus stolonifer and Colletotrichum acutatum Using Hyperspectral Reflectance Imaging.

This research aimed to develop a rapid and nondestructive method to model the growth and discrimination of spoilage fungi, like Botrytis cinerea, Rhizopus stolonifer and Colletotrichum acutatum, based on hyperspectral imaging system (HIS). A hyperspectral imaging system was used to measure the spectral response of fungi inoculated on potato dextrose agar plates and stored at 28°C and 85% RH. The fungi were analyzed every 12 h over two days during growth, and optimal simulation models were built based on HIS parameters. The results showed that the coefficients of determination (R2) of simulation models for testing datasets were 0.7223 to 0.9914, and the sum square error (SSE) and root mean square error (RMSE) were in a range of 2.03-53.40×10(-4) and 0.011-0.756, respectively. The correlation coefficients between the HIS parameters and colony forming units of fungi were high from 0.887 to 0.957. In addition, fungi species was discriminated by partial least squares discrimination analysis (PLSDA), with the classification accuracy of 97.5% for the test dataset at 36 h. The application of this method in real food has been addressed through the analysis of Botrytis cinerea, Rhizopus stolonifer and Colletotrichum acutatum inoculated in peaches, demonstrating that the HIS technique was effective for simulation of fungal infection in real food. This paper supplied a new technique and useful information for further study into modeling the growth of fungi and detecting fruit spoilage caused by fungi based on HIS.