No abstract

Exploring the composition and structure of the faecal microbial community improves the understanding of the role of the gut microbiota in the gastrointestinal function and the egg-laying performance of hens. Therefore, detection of hen–microbial interactions can explore a new breeding marker for the selection of egg production due to the important role of the gut microbiome in the host’s metabolism and health. Recently, the gut microbiota has been recognised as a regulator of host performance, which has led to investigations of the productive effects of changes in the faecal microbiome in various animals. In the present study, a metagenomics analysis was applied to characterise the composition and structural diversity of faecal microbial communities under two selections of egg-laying performance, high (H, n = 30) and low (L, n = 30), using 16S rRNA-based metagenomic association analysis. The most abundant bacterial compositions were estimated based on the operational classification units among samples and between the groups from metagenomic data sets. The results indicated that Firmicutes phylum has higher significant (P < 0.01) in the H group than in the L group. In addition, higher relative abundance phyla of Bacteroides and Fusobacteria were estimated in the H group than the L group, contrasting the phyla of Actinobacteria, Cyanobacteria and Proteobacteria were more relative abundance in the L group. The families (Lactobacillus, Bifidobacterium, Acinetobacter, Flavobacteriaceae, Lachnoclostridum and Rhodococcus) were more abundant in the H group based on the comparison between the H and L groups. Meanwhile, three types of phyla (Proteobacteria, Actinobacteria and Cyanobacteria) and six families (Acinetobacter, Avibacterium, Clostridium, Corynebacterium, Helicobacter and Peptoclostridium) were more abundant in the L group (P < 0.01). Overall, the selection of genotypes has enriched a relationship between the gut microbiota and the egg-laying performance. These findings suggest that the faecal microbiomes of chickens with high egg-laying performance have more diverse activities than those of chickens with low egg-laying performance, which may be related to the metabolism and health of the host and egg production variation.

Diabetes has become the third most serious threat to human health, after cancer and cardiovascular disease. Notably, Lactobacillus brevis is the most common species of LAB that produces γ-aminobutyric acid (GABA). The aim of this study is to clarify the effect of time, strain types, antibiotic concentrations, different levels of pH, and intestinal juices in aerobic or anaerobic conditions and the effect of interactions between these factors on the potential properties of KLDS 1.0727 and KLDS 1.0373, furthermore, antagonistic activity against foodborne pathogens. Moreover, another aim is to study the capability of KLDS 1.0727 and KLDS 1.0373 strains as gad gene carriers to express GABA that reduce the risk of type 1 diabetes in C57BL/6 mice as diabetic models. The obtained results exhibited the surprising tolerance of Lactobacillus brevis strains in vitro digestion models mimicking the conditions of the gastrointestinal tract, further, large antagonistic activity against foodborne pathogeneses. In vivo results displayed the significant effect on glucose level reduction, blood plasma, and histological assays of mice organs. As recommended, the use of Lactobacillus brevis strains should be widely shared in the market as a natural source of GABA in pharmaceutical and food applications.

Growth performance is a complex economic trait for avian production. The swan goose (Anser cygnoides) has never been exploited genetically like chickens or other waterfowl species such as ducks. Traditional phenotypic selection is still the main method for genetic improvement of geese body weight. In this study, specific locus amplified fragment sequencing (SLAF-seq) with bulked segregant analysis (BSA) was conducted for discovering and genotyping single nucleotide polymorphisms (SNPs) associated with marketing weight trait in male geese. A total of 149,045 SNPs were obtained from 427,093 SLAF tags with an average sequencing depth of 44.97-fold and a Q30 value of 93.26%. After SNPs’ filtering, a total of 12,917 SNPs were included in the study. The 31 highest significant SNPs—which had different allelic frequencies—were further validated by individual-based AS-PCR genotyping in two populations. The association between 10 novel SNPs and the marketing weight of male geese was confirmed. The 10 significant SNPs were involved in linear regression model analysis, which confirmed single-SNP associations and revealed three types of SNP networks for marketing weight. The 10 significant SNPs were located within or close to 10 novel genes, which were identified. The qPCR analysis showed significant difference between genotypes of each SNP in seven genes. Developed SLAF-seq and identified genes will enrich growth performance studies, promoting molecular breeding applications to boost the marketing weight of Chinese geese.