Skip to main page content
U.S. flag

An official website of the United States government

Dot gov

The .gov means it’s official.
Federal government websites often end in .gov or .mil. Before sharing sensitive information, make sure you’re on a federal government site.

Https

The site is secure.
The https:// ensures that you are connecting to the official website and that any information you provide is encrypted and transmitted securely.

Access keys NCBI Homepage MyNCBI Homepage Main Content Main Navigation
. 2022 Mar 18:12:842007.
doi: 10.3389/fcimb.2022.842007. eCollection 2022.

Changes in Gut Microbiota by the Lactobacillus casei Anchoring the K88 Fimbrial Protein Prevented Newborn Piglets From Clinical Diarrhea

Affiliations

Changes in Gut Microbiota by the Lactobacillus casei Anchoring the K88 Fimbrial Protein Prevented Newborn Piglets From Clinical Diarrhea

Da Qin et al. Front Cell Infect Microbiol. .

Abstract

In the last 20 years, accumulating evidence indicates that the gut microbiota contribute to the development, maturation, and regulation of the host immune system and mediate host anti-pathogen defenses. Lactobacillus casei (L.casei) is a normal flora of the gastrointestinal tract in mammals and, as a great mucosal delivery vehicle, has wide use in bioengineering. However, the diarrhea prevention role of commensal intestinal microbiota interfered by the recombinant L.casei (rL.casei) in newborn piglets is not well understood. In our study, newborn piglets orally fed with the rL.casei surface displayed the fimbrial protein K88 of enterotoxigenic Escherichia coli (ETEC) and their feces were collected for a period of time after feeding. The next-generation sequencing of these fecal samples showed that the relative abundance of L.casei was significantly increased. The oral administration of rL.casei altered the intestinal microbial community as evidenced by altered microbial diversity and microbial taxonomic composition. Remarkably, the functional enhancing of the intestinal bacterial community by rL.casei was positively correlated with membrane transport, replication, and repair (p < 0.05). The specific antibody detection indicates that high levels of anti-K88 secretory immunoglobulin A (sIgA) were induced in fecal samples and systemic immunoglobulin G was produced in serum. The diarrhea rate in piglets caused by ETEC K88 was decreased by about 24%. Thus, the oral administration of rL.casei not only activated the mucosal and humoral immune responses in vivo but also contributed to shape the intestinal probiotics in newborn piglets and to significantly reduce the diarrhea rates of newborn piglets.

Keywords: 16S rRNA sequencing; ETEC K88; diarrhea; gut microbiota; newborn piglets; rLactobacillus casei.

PubMed Disclaimer

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
Piglets’ weight detail and fimbrial K88-specific antibody responses in serum and fecal samples. Piglets’ weight detail in days 0 (A) and piglets’ weight detail in days 28 (B) are shown by boxplots. Specific IgG antibody in serum samples (C), specific IgA antibody in serum samples (D), and specific sIgA antibody in fecal samples (E) based on optical density by ELISA. All diagrams were shown by R software (version 3.6.1) with the ggplot2 package. The boxplots represent the diversity measures for the 5 analysis groups (center line, median; box limits, first and third quartiles; whiskers, 1.5 × interquartile range). All outliers are plotted as individual points. The number up to the two groups means p value which is calculated by the Student’s t-test.
Figure 2
Figure 2
The diarrhea occurring rate in piglets (A). PCR identification of diarrhea samples (B). The diarrhea rate in the control group was 25%, but that in the treatment group did not occur (A). Lanes 1–6, PCR templates from diarrhea piglet feces; Lane 7, rL.casei plasmid template as positive control; Lane 8, ETEC K88 as positive control; Lane 9, negative control. The ETEC K88 gene was amplified by PCR, suggesting that the symptoms of piglets’ diarrhea were caused by ETEC K88 (B).
Figure 3
Figure 3
The α-diversity index of the intestinal flora in piglets. The Chao1 diversity (A), ACE diversity (B), Shannon diversity (C), and Simpson diversity (D) based on OTU relative abundances were shown by R software (version 3.6.1) with the ggplot2 package. The boxplots represent the diversity measures for the 5 analysis groups (center line, median; box limits, first and third quartiles; whiskers, 1.5 × interquartile range). All outliers are plotted as individual points. The number up to the two groups means p value which is calculated by the Student’s t-test.
Figure 4
Figure 4
The β-diversity in piglet intestinal flora. PCA plot (A) was based on OTU relative abundances, and samples are colored according to each sample group. PCoA plot (B) and NMDS plot (C) based on weighted UniFrac distances between samples calculated using OTU relative abundances. The variance explained by each axis is stated as a percentage in parentheses.
Figure 5
Figure 5
UPGMA phylogenetic tree constructed based on weighted UniFrac distances.
Figure 6
Figure 6
The intestinal flora detail of piglets after L.casei treatment, microbiota at the Phylum level (A), Class level (B), Family level(C) and Genus level (D) were shown by bar plot. The top 20 taxons of Family and Genus abundance were taken to analyse the effect of probiotic L.casei on intestinal flora composition in piglets.
Figure 7
Figure 7
Based on the OTU relative abundance of each sample, the differences of bacterial abundances among the Ctrl15 group, Ctrl28 group, and the first feeding groups OA15 and OA28 were analyzed by using STAMP software with two-sided Student’s t-test. Ctrl15 group vs. OA15 group (A), Ctrl28 group vs. OA28 group (B), OA15 group vs. OA28 group (C). GraPhlAn tools were used for visualization of the hierarchical tree (D). The hierarchical tree shows the hierarchical relationship of all taxons (represented by nodes) from phylum to genus (arranged from inner circle to outer circle in turn), and the node size corresponds to the average relative abundance of the taxon. The top 20 taxons of relative abundance will also be identified by letters in the figure (arranged from phylum to genus in order from outer layer to inner layer). The top 30 taxons of genus abundance were taken to analyze the differences between each sample (E) and each group (F) by heat maps which were drawn by R software (version 3.6.1) with the ggplot2 package.
Figure 8
Figure 8
Based on the relative abundances of bacterial taxa, random forest regression analysis was taken and the top 20 taxons of genus in mean decrease in accuracy were visualized by R software.
Figure 9
Figure 9
Comparisons of the predominant gene pathways of the bacterial microbiota in different groups as predicted by PICRUSt. The box diagram describes the relative abundance in each group (A). The differences of metabolism among the Ctrl15 group, Ctrl28 group, and the first feeding L.casei groups OA15 and OA28 were analyzed by using STAMP software with two-sided Student’s t-test. Ctrl15 group vs. OA15 group (B), Ctrl28 group vs. OA28 group (C), and OA15 group vs. OA28 group (D).
Figure 10
Figure 10
Correlation analysis between intestinal microflora composition changes and body function indexes. The Spearman rank correlation analysis was used and drawn by R software (version 3.6.1) with pheatmap package. The color legend is on the top right of the figure. Red indicates positive correlation; blue indicates negative correlation. *p < 0.05 and **p < 0.01 using Student’s t-test to evaluate differences between every two targets.

Similar articles

Cited by

References

    1. Azad M. A. K., Sarker M., Wan D. (2018). Immunomodulatory Effects of Probiotics on Cytokine Profiles. BioMed. Res. Int. 2018, 8063647. doi: 10.1155/2018/8063647 - DOI - PMC - PubMed
    1. Bai Y., Wang G., Qi H., Wang Y., Xu C., Yue L., et al. . (2020). Immunogenicity of 987P Fimbriae of Enterotoxigenic Escherichia Coli Surface-Displayed on Lactobacillus Casei. Res. Vet. Sci. 128, 308–314. doi: 10.1016/j.rvsc.2019.12.016 - DOI - PubMed
    1. Bokulich N. A., Subramanian S., Faith J. J., Gevers D., Gordon J. I., Knight R., et al. . (2013). Quality-Filtering Vastly Improves Diversity Estimates From Illumina Amplicon Sequencing. Nat. Methods 10, 57–59. doi: 10.1038/nmeth.2276 - DOI - PMC - PubMed
    1. Breiman L. (2001). Random Forests. Mach. Learn 45, 5–32. doi: 10.1023/A:1010933404324 - DOI
    1. Caporaso J. G., Kuczynski J., Stombaugh J., Bittinger K., Bushman F. D., Costello E. K., et al. . (2010). QIIME Allows Analysis of High-Throughput Community Sequencing Data. Nat. Methods 7, 335–336. doi: 10.1038/nmeth.f.303 - DOI - PMC - PubMed

Publication types