Early intestinal microbiota changes in aged and adult mice with sepsis

Abstract

Background: The mortality rate associated with sepsis in elderly individuals is higher than that in younger individuals. The intestinal microbiota has been demonstrated to play an important role in the occurrence and development of sepsis. The purpose of this study was to investigate the differences in the intestinal microbiota between aged and adult mice with sepsis.

Methods: Thirty male C57BL mice were randomly divided into two groups: 15 in the adult group (AD group) and 15 in the age group (Age group). All the mice underwent caecal ligation and puncture to induce sepsis. Mice faeces were collected, and analysed using 16S rRNA sequencing. The liver and colon tissues were collected.

Results: There were significant differences in intestinal microbiota composition between the two groups. Compared with adult sepsis mice, the diversity of intestinal microbiota in the aged group was significantly reduced and the structure of dominant intestinal microbiota was changed. In the Age group, the microbiota associated with inflammatory factors increased, and the microbiota associated with the production of SCFAs (Ruminiclostridium, Prevotellaceae_UCG-001, Rikenella, Parabacteroides, Oscillibacter, Odoribacter, Muribaculum, Lachnoclostridium, Intestinimonas, Faecalibaculum, Anaerotruncus, Alloprevotella and Absiella) decreased. The metabolic pathways related to the microbiota also changed. Moreover, the proportion of inflammatory factors in Age group was higher than that in AD group.

Conclusion: Our results showed that there were significant differences in the abundance and structure of microbiota between aged and adult sepsis mice, Aged sepsis mice have more severe intestinal microbiota destruction and liver tissue inflammation than adult sepsis mice.

Keywords: 16S; adult mice; aged mice; intestinal microbiota; sepsis.

Figure 1

Inflammatory factors. RT–PCR showed that in colon tissue, the Age group exhibited increased levels of inflammatory factors (TNF-α, IL-6, ccl3, ccl5, ccl8, cxcl10 and ccl4) when compared with the AD group *P< 0.05, **P< 0.01, ***P< 0.001.

Figure 2

Microbial diversity. (A–D) The main purpose of alpha diversity is to reflect species richness, evenness, and sequencing depth. To reflect richness and uniformity, we used the Chao1, observed species, Shannon, and Simpson indexes. (E, F) β diversity reflects the microbial richness within and between groups. We used NMDS to observe the differences between samples. As shown in the figure, the two samples are far apart. The two groups of microbiota differ significantly, and the difference is statistically significant. *P< 0.05, **P< 0.01, ***P< 0.001.

Figure 3

Relative abundance. Relative microbiota distribution between the two groups. (A, B) phylum level. (C, D) genus level.

Figure 4

(A) Correlation network diagram: Different nodes in the network diagram represent different dominant genera. The connection between nodes indicates that there is a correlation between the two genera. By default, we show the relationship pair of correlation coefficientsRho> 0.4. (B) Bubble plot: The species annotation information and relative abundance (circle size) at the genus level in various sample groups as well as the species annotation information (circle colour) of the species-corresponding gate.

Figure 5

Linear discriminant analysis (LDA) integrated with effect size (LEfSe). (A) The circle radiating from inside to outside represents the taxonomic level from phylum to genus, and the species with no significant difference are yellow. (B) LDA value distribution histogram.

Figure 6

PICRUSt analysis. Functional prediction pathways in microbial differences among the groups.