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. 2025 Aug 20:16:1622009.
doi: 10.3389/fmicb.2025.1622009. eCollection 2025.

Effect of Lactiplantibacillus plantarum LPJZ-658 on caecum microbiota and serum metabolomics of Luhua broiler

Mengjiao Li  1   2 , Zhongyuan Liu  2 , Chen Chen  2 , Ziqi Liu  2 , Liming Liu  2
Affiliations

Effect of Lactiplantibacillus plantarum LPJZ-658 on caecum microbiota and serum metabolomics of Luhua broiler

Mengjiao Li et al. Front Microbiol. .

Abstract

Introduction: The purpose of this study was to investigate the effects of dietary supplementation of Lactiplantibacillus plantarum LPJZ-658 on body weight and serum indexes of Luhua broiler, and to explore the relevant mechanism of probiotic function of LPJZ-658 based on intestinal microbiota and serum metabolomics.

Methods: One hundred one-day-old Luhua broiler were randomly divided into the control group (CON) and LPJZ-658 treatment group (LPJZ-658). The CON group was fed a basal diet, and the LPJZ-658 group was fed the basal diet supplemented with 2 × 109 cfu/kg of LPJZ-658. The study lasted for 28 days. At the end of the experiment, serum and caecum samples were collected for analysis.

Results: In the LPJZ-658 group, the serum IgA level, and activity of SOD were significantly higher, concentration of MDA was markedly lower than in the CON group. Caecum microbiota showed that LPJZ-658 could dramatically change the composition of cecum flora. It's mainly by increasing the level of Lactobacillus, Lachnoclostridium, and Parasutterella, and reducing the level of Clostridia_UCG-014, Faecalibacterium, Blautia, Eubacterium_coprostanoligenes_group, Anaerofilum and Shuttle. In addition, serum non-targeted metabolomics results showed that there were 49 serum differential metabolites between the two groups, and the main metabolic pathways affected by LPJZ-658 included phenylalanine, tyrosine and tryptophan biosynthesis, arachidonic acid metabolism, and tyrosine metabolism.

Discussion: In summary, LPJZ-658 can improve the serum immune performance and antioxidant capacity of Luhua broiler by regulating the composition of caecum microbiota and serum metabolome, thus improving the health status of Luhua broiler and culture efficiency.

Keywords: 16S rRNA; Lactiplantibacillus plantarum LPJZ-658; Luhua broiler; cecal microbiota; serum metabolomics.

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Conflict of interest statement

The authors declare that the research was conducted in the absence of any commercial or financial relationships that could be construed as a potential conflict of interest.

Figures

Figure 1
Figure 1
Effects of LPJZ-658 on weekly body weight of Luhua broiler.
Figure 2
Figure 2
The effect of dietary supplementation with LPJZ-658 on the composition of cecal microbiota. (A) The species accumulation boxplot. (B) Venn diagram. (C) PCoA of cecal flora based on Jaccard distance. (D) Alpha diversity of cecal flora. Statistical significance was denoted by *p < 0.05, **p < 0.01 and ***p < 0.001.
Figure 3
Figure 3
The effects of LPJZ-658 on composition of cecal flora of Luhua broiler. The relative abundance of microbial composition at phyla (A) and genus level (B). (C) Differential microbiota at the genus level. Statistical significance was denoted by *p < 0.05, **p < 0.01 and ***p < 0.001.
Figure 4
Figure 4
Linear discriminant analysis (LDA) effect size (LEfSe) analysis of cecal microbiota. (A) Distribution histogram of linear discriminant analysis (LDA) values (LDA score = 4). (B) Evolutionary branching diagram.
Figure 5
Figure 5
PICRUSt predicted analysis (A) and significantly changed metabolic pathways (B).
Figure 6
Figure 6
Changes in the metabolite profiles between the two groups. Representative base peak chromatograms of serum samples acquired from 50% methanol in water extracts [(A) ESI+ and (B) ESI−]. (C) PCA score plots of the CON and LPJZ-658 group, based on the data acquired from 50% methanol in water extracts (left, ESI+, and right, ESI−). (D) OPLS-DA score plots of CON and LPJZ-658 group based on the data acquired from 50% methanol in water extracts (left, ESI+, and right, ESI−). The volcano diagram [(E) ESI+ and (F) ESI−]. (G) Heatmap of changes in the intensity of biomarkers in two groups.
Figure 7
Figure 7
Sankey diagram of metabolic pathway analysis.
Figure 8
Figure 8
Correlation analysis among differential serum metabolites and caecum microbiota.
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