Lacticaseibacillus rhamnosus is a generalist that can adapt to different ecological niches, serving as a valuable source of probiotics. The genome of L. rhamnosus X253 contains one chromosome and no plasmids, with a size of 2.99 Mb. Both single-copy orthologous gene-based phylogenetic analysis and average nucleotide identity indicated that dairy-derived L. rhamnosus X253 was most closely related to the human-intestine-derived strain L. rhamnosus LOCK908, rather than other dairy strains. The adaptation of L. rhamnosus X253 and the human-intestine-derived strain L. rhamnosus GG to different ecological niches was explained by structural variation analysis and COG annotation. Hemolytic assays, API ZYM assays, and antimicrobial susceptibility tests were performed to validate risk-related sequences such as virulence factors, toxin-encoding genes, and antibiotic-resistance genes in the genomes of L. rhamnosus X253 and GG. The results showed that L. rhamnosus GG was able to use L-fucose, had a higher tolerance to bile salt, and adhered better to CaCo-2 cells. In contrast, L. rhamnosus X253 was capable of utilizing D-lactose, withstood larger quantities of hydrogen peroxide, and possessed excellent antioxidant properties. This study confirmed the safety and probiotic properties of L. rhamnosus X253 via complete genome and phenotype analysis, suggesting its potential as a probiotic.

Gray sufu, a traditional fermented food derived from soybeans, undergoes a complex fermentation process. This study aimed to investigate the dynamics of the microbial community during sufu fermentation and its relationship with key quality characteristics. Through systematic sampling of sufu at different phases of fermentation, 143 bacterial genera and 84 fungal genera involved in the process were identified. Among these, Chishuiella, Enterococcus, Lactococcus, and Weissella emerged as the predominant bacterial communities. After seven days of ripening fermentation, Trichosporon supplanted Diutina as the predominant fungus, accounting for more than 84% of all fungi. Using redundancy analysis, significant correlations between microbiota and physicochemical properties were uncovered. Chishuiella and Empedobacter displayed positive relationships with pH, soluble protein, and amino nitrogen content. In addition, five biogenic amines were detected, and it was determined that tyramine accounted for more than 75% of the total biogenic amines in the final gray sufu products. Spearman correlation analysis revealed significant positive relationships between Lactococcus, Enterococcus, Tetragenococcus, Halanaerobium, and Trichosporon and the five biogenic amines examined. These findings shed light on the complex interactions between microorganisms and biogenic amines during the fermentation of gray sufu, thereby facilitating the development of microbial regulation strategies for better quality control.

Due to the intricate complexity of the original microbiota, residual heat-resistant enzymes, and chemical components, identifying the essential factors that affect dairy quality using traditional methods is challenging. In this study, raw milk, pasteurized milk, and ultra-heat-treated (UHT) milk samples were collectively analyzed using metagenomic next-generation sequencing (mNGS), high-throughput liquid chromatography-mass spectrometry (LC-MS), and gas chromatography–mass spectrometry (GC-MS). The results revealed that raw milk and its corresponding heated dairy products exhibited different trends in terms of microbiota shifts and metabolite changes during storage. Via the analysis of differences in microbiota and correlation analysis of the microorganisms present in differential metabolites in refrigerated pasteurized milk, the top three differential microorganisms with increased abundance, Microbacterium (p < 0.01), unclassified Actinomycetia class (p < 0.05), and Micrococcus (p < 0.01), were detected; these were highly correlated with certain metabolites in pasteurized milk (r > 0.8). This indicated that these genera were the main proliferating microorganisms and were the primary genera involved in the metabolism of pasteurized milk during refrigeration-based storage. Microorganisms with decreased abundance were classified into two categories based on correlation analysis with certain metabolites. It was speculated that the heat-resistant enzyme system of a group of microorganisms with high correlation (r > 0.8), such as Pseudomonas and Acinetobacter, was the main factor causing milk spoilage and that the group with lower correlation (r < 0.3) had a lower impact on the storage process of pasteurized dairy products. By comparing the metabolic pathway results based on metagenomic and metabolite annotation, it was proposed that protein degradation may be associated with microbial growth, whereas lipid degradation may be linked to raw milk’s initial heat-resistant enzymes. By leveraging the synergy of metagenomics and metabolomics, the interacting factors determining the quality evolution of dairy products were systematically investigated, providing a novel perspective for controlling dairy processing and storage effectively.

Currently, the inspection and supervision of animal ingredients relies primarily upon specific amplification-dependent methods, whose efficiency and accuracy are being seriously challenged by the increasing diversity and complexity of meat products. High-throughput sequencing (HTS) technology was employed to develop an alternative method to detect animal-derived ingredients in meat products. A custom-built database containing 2,354 complete mitochondrial genomic sequences from animals, an identification analysis pipeline based on short-sequence alignment, and a web-based server were built to facilitate this detection. The entire process, including DNA extraction, gene amplification, and sequencing, was established and optimized for both marker gene (part of the CYTB gene)-based detection and total DNA-based detection. Using simulated samples containing various levels of pig, cattle, sheep, chicken, rabbit, and mice ingredients, the detection capability and accuracy of this method were investigated. The results of this study indicated that the method is capable of detecting animal components in meats that are present at levels as low as 1%. Our method was then tested using 28 batches of real meat products such as raw meat slices, raw meat mince, cooked dried meat, cooked meat sausage, and other supermarket samples, with a traditional qPCR method as the control. The results demonstrated an accuracy of 97.65% for the qualitative detection method, which indicate that the developed method is reliable for the detection of animal components. The method is also effective for the identification of unknown food samples containing mixed animal components, which suggests a good future in application.

Probiotics are universally recognized for their health benefits, despite the fact that their effects depend on the strain. Identification and enumeration of probiotic strains are required prior to evaluating their effectiveness. Lacticaseibacillus rhamnosus X253 is a potential probiotic strain with antioxidant capacity. Comparative genomics and single nucleotide polymorphisms (SNPs) were used to identify a strain-specific locus within the holA gene for strain X253 that was distinct in 30 different L. rhamnosus strains. Using quantitative PCR, the primers and probe designed for the locus were able to distinguish L. rhamnosus X253 from the other 20 probiotic strains. The chosen locus remained stable over 19 generations. The sensitivity of the assay was 0.2 pg genomic DNA of L. rhamnosus X253, or 10³ cfu/mL bacteria of this strain. In terms of repeatability and reproducibility, relative standard deviations (RSD) were less than 1% and 3%, respectively. Additionally, this assay achieved accurate enumerations of L. rhamnosus X253 in spiked milk and complex powder samples. The strain-specific assay could be used for quality control and compliance assessment of dairy products.