Food Bioscience最新文献

Kidney stones, often resulting from a complex interplay of factors including oxalic acid, uric acid, and calcium. Current treatments lack comprehensive consideration of these factors and come with side effects. In this study, Lactobacillus paracasei GR-10 and Pediococcus acidilactici GR-11 were isolated from the fermented food “Jiangshui”. GR-10 demonstrated the ability to degrade 62.70% of oxalic acid (10 mM) within 24 h, while GR-11 degraded 28.60% of uric acid (4 mM). Combined treatment with GR-10 and GR-11 significantly reduced the number of stones in rats with ethylene glycol-induced kidney stones. This reduction was accompanied by a 57.19% decrease in urinary oxalate and a 52.80% decrease in serum uric acid levels. Simultaneously, urinary calcium level decreased by 27.18%. Inflammatory markers and indicators of oxidative stress associated with kidney stones were restored. Furthermore, the combined treatment effectively regulated the microbiota imbalance induced by kidney stones, resulting in reduced purine nucleoside accumulation in rat feces. This study offers promising insights into probiotics as an adjunct therapy for the prevention of kidney stones in the future.

Lactobacillus aggregation is a bacterial behavior, in which Lactobacillus cells adhere to each other or other strains to form aggregates. Substantial evidence indicates that Lactobacillus aggregation is closely related to biofilm formation, adhesion, colonization, and host physiological functions. Current reviews on Lactobacillus aggregation are often limited to a few aspects, or serve as a single step to address other related problems. In this paper, we review the current state and characteristics of self- and co-aggregations, including aggregation percentages, influencing factors, molecular mechanisms, and functions. Lactobacillus aggregation is a strain-specific behavior, rather than a species-specific one, and the characteristics of both aggregations are similar. The same species of Lactobacillus exhibits a relatively broad range of aggregation percentage, and involved in different influencing factors and mechanisms. Moreover, the same factors and mechanisms also participate in different Lactobacillus aggregations. This is mainly because of the complexity of aggregations. Meanwhile, we also summarize the functions of aggregation, including enhancing bacterial survival, promoting biofilm formation and involving in host physiological regulation.

Fermented broad beans (Vicia faba L.), commonly known as meju, serve as a crucial raw material for producing Pixian Doubanjiang (DBJ), a traditional condiment in Chinese cuisine. However, there is limited information on the dynamics of fungal populations and the activity shifts of key enzymes during DBJ meju fermentation. This study aimed to elucidate the microbial composition, active genera, expressed genes and pathways during the DBJ meju fermentation. The general chemical components, free amino acids, enzymes and volatile compounds were also investigated; the correlations between active genera and physicochemical factors were analyzed, at different fermentation stages. The results demonstrated that protease was the predominant enzyme during meju fermentation. A total of 32 major volatile compounds were identified, with most alcohols and aldehydes showing a sharp increase from the early to the middle stages, followed by stabilization until the end of fermentation. Significant shifts in metatranscriptomic composition at the genus level were observed, with Aspergillus, Staphylococcus, and Tulasnella emerging as the core active genera in the process. Notably, cellulase activity was positively correlated with the presence of Tulasnella. Additionally, Aspergillus and Tulasnella were found to play a crucial role in developing the unique aroma of DBJ meju. Our findings on the succession of active genera and their correlation with physicochemical factors are expected to provide substantial evidence for potential quality control and enhancement of this renowned Chinese condiment.

The controversy surrounding the impact of acesulfame potassium (Ace-K) on metabolic health has been growing. Here, male C57BL/6 mice were given Ace-K for 11 weeks (sterile water as the control group, 40 mg/kg body weight as the low dose group, 120 mg/kg as the high dose group), subsequently gut microbiome and targeted metabolomics were conducted to evaluate the effect of Ace-K on host health. Gut microbiota was perturbed by Ace-K, as evidenced by the down-regulation of beneficial bacteria and the increased abundance of Collinsella associated with inflammation. Fatty acids metabolism was altered by Ace-K, as evidenced by elevated long chain fatty acids (LCFAs) in liver and serum. Notably, the reduction of related genes and proteins correlated to carnitine metabolism and hepatic carnitine metabolites by Ace-K led to a reduction in the β-oxidation of LCFAs, ultimately causing the accumulation of LCFAs. These findings uncovered new perspectives on Ace-K-induced hepatic inflammation and fatty acids accumulation.

To effectively utilize apple pomace resources, we extracted apple pomace polyphenols using natural deep eutectic solvent (NADES) as the medium, with a solvent-to-solid ratio of 50 mL/g, for a duration of 120 min. Compared to conventional extraction solvents (ethanol and methanol), four NADES significantly enhanced the extraction efficiency of polyphenols from apple pomace. Notably, NADES 1 (betaine: urea = 1:1, 30% water) and NADES 2 (betaine: malic acid = 1:1, 30% water) exhibited superior extraction capabilities, with maximum values reaching 5.245 ± 0.124 mg GAE/g pomace and 5.157 ± 0.164 mg GAE/g pomace, respectively, in Qinguan apple pomace. Both solvents reached their maximum extraction efficiency within 120 min, with NADES 1 achieving a maximum extraction amount of 4.8325 mg GAE/g and NADES 2 achieving 5.3039 mg GAE/g from Fuji apple pomace. NADES 1 and NADES 2 were more efficient in extracting monophenols such as quercetin, rutin, gallic acid, and procyanidin, whereas organic solvents (methanol and ethanol) were more effective for monophenols like methyl gallate and phlorizin. Furthermore, polyphenol extracts obtained using NADES from Fuji apple pomace displayed varying levels of antibacterial effectiveness, with NADES 4 (glucose: lactic acid = 1:5, 60% water) and NADES 2 showing superior efficacy against Escherichia coli and Staphylococcus aureus. This comprehensive study not only demonstrated the potential of NADES in extracting polyphenols from apple pomace but also highlighted their applicability as natural preservatives in the food industry.

Gelatinous polysaccharide-based fresh products are influenced by environmental and temperature changes, and maintaining their quality and freshness has always been a challenge. Intelligent management and control of cold chain logistics systems have been extensively used in transporting and storing these goods to overcome the problem. This review introduces common quality deterioration issues, including those encountered during the transportation and storage of these products, such as softening, water loss, and color changes. The application of intelligent detection technologies, including gas detection, intelligent label, and spectral detection is reviewed to achieve real-time monitoring and evaluation of product status. This article also introduces the Internet of Things, wireless sensor networks, and radio frequency identification for product data transmission. It utilizes artificial neural networks and digital twins to build quality models, achieving better management of gelatinous polysaccharide-based fresh products in the cold chain. Moreover, some preservation techniques are used to increase the longevity of these products in storage and reduce losses in the cold chain. These techniques include irradiation, chemical treatment, and coating preservation. This review will, hopefully, encourage additional work that may help reach the goal of having better intelligent quality control of gelatinous polysaccharide-based fresh products during cold chain logistics.

With the global population increasing and lifestyle improving, the demand for high-quality nutritional aquatic foods has been rising. Muscle fat is a crucial nutritional index for evaluating the quality of fish flesh. However, the comprehensive and systematic understanding of the molecular mechanism underlying differences in muscle fat deposition remains insufficient. In this study, we integrated transcriptomics and metabolomics of selected samples with extremely high and low muscle fat in common carp (Cyprinus carpio), the major freshwater aquaculture fish in Asia, to identify critical genes, metabolites and metabolic pathways. We totally identified 204 differentially expressed genes (DEGs) and 1528 differentially accumulated metabolites (DAMs). Glycerolipid, glycerophospholipid and glyoxylate and dicarboxylate metabolisms were enriched through both transcriptomics and metabolomics. These lipid metabolism pathways may be regulated by some critical signal transduction pathways, including Extracellular matrix [ECM]-receptor interaction, mTOR signaling pathway and FoxO signaling pathway. Combined with the validation of gene expression and biochemical indices, a supposed regulatory network was established. To our knowledge, it is the first study to apply a multi-omics approach in fish with naturally different muscle fat to comprehensively elucidate the mechanism. This study could deepen our understanding of the molecular mechanism of muscle fat deposition and be helpful for improving the quality of fish.