pubmed.ncbi.nlm.nih.gov

Chronic Trichuris muris Infection Decreases Diversity of the Intestinal Microbiota and Concomitantly Increases the Abundance of Lactobacilli - PubMed

  • ️Thu Jan 01 2015

Chronic Trichuris muris Infection Decreases Diversity of the Intestinal Microbiota and Concomitantly Increases the Abundance of Lactobacilli

Jacob Bak Holm et al. PLoS One. 2015.

Abstract

The intestinal microbiota is vital for shaping the local intestinal environment as well as host immunity and metabolism. At the same time, epidemiological and experimental evidence suggest an important role for parasitic worm infections in maintaining the inflammatory and regulatory balance of the immune system. In line with this, the prevalence of persistent worm infections is inversely correlated with the incidence of immune-associated diseases, prompting the use of controlled parasite infections for therapeutic purposes. Despite this, the impact of parasite infection on the intestinal microbiota, as well as potential downstream effects on the immune system, remain largely unknown. We have assessed the influence of chronic infection with the large-intestinal nematode Trichuris muris, a close relative of the human pathogen Trichuris trichiura, on the composition of the murine intestinal microbiota by 16S ribosomal-RNA gene-based sequencing. Our results demonstrate that persistent T. muris infection dramatically affects the large-intestinal microbiota, most notably with a drop in the diversity of bacterial communities, as well as a marked increase in the relative abundance of the Lactobacillus genus. In parallel, chronic T. muris infection resulted in a significant shift in the balance between regulatory and inflammatory T cells in the intestinal adaptive immune system, in favour of inflammatory cells. Together, these data demonstrate that chronic parasite infection strongly influences the intestinal microbiota and the adaptive immune system. Our results illustrate the complex interactions between these factors in the intestinal tract, and contribute to furthering the understanding of this interplay, which is of crucial importance considering that 500 million people globally are suffering from these infections and their potential use for therapeutic purposes.

PubMed Disclaimer

Conflict of interest statement

Competing Interests: The authors have declared that no competing interests exist.

Figures

Fig 1
Fig 1. Time-dependent changes of the microbiota diversity due to chronic T. muris infection.

Non-metric Multi-Dimensional Scaling (NMDS) plot using Bray-Curtis dissimilarity indices from (A) faecal microbiota from 10 infected mice sampled at various time points from day 0 to day 35, and (B) caecal microbiota from uninfected mice at day 0 and uninfected/infected mice at day 35. Ellipses are labelled according to the corresponding day of analysis. Relative abundance at family level was fitted as vectors based on 9999 permutations and scaled by their correlation coefficient.

Fig 2
Fig 2. Chronic T. muris infection results in decreased alpha but increased beta diversity of the microbiota.

(A) Median alpha diversity based on Shannon index of unfiltered microbiota data for faecal and caecal samples. The upper and lower whiskers correspond to the 25th and 75th percentiles. (B) Median beta diversity based on Sørensen index for faecal and caecal samples. The whiskers correspond to the 25th and 75th percentiles. Statistical analyses were performed with one-way ANOVA, followed by Tukey’s post-test for multiple comparisons using Prism (GraphPad software). The light blue colour for uninfected caecal samples indicates the ten mice sacrificed at day 0, and therefore not repeated sampling as for the faecal samples. The following definitions were used to denote statistical significance: * (p<0.05), ** (p<0.01), *** (p<0.001), while p>0.05 was considered not significant (NS).

Fig 3
Fig 3. Chronic T. muris infection affects the composition of the microbiota.

Taxa summary plots at family level showing (A) changes in microbiota composition of faecal samples from the infected mice from day 0 to day 35, and (B) the microbiota composition of uninfected and infected mice at day 35 for faecal and caecal samples. “Unknown” refers to OTUs that we were unable to classify. Data represent mean relative abundance.

Fig 4
Fig 4. Chronic T. muris infection alters the relative abundance of multiple genera.

(A) Heat-map illustrating changes over time in mean relative abundance at genus level for faecal samples from infected mice. Data are log10 transformed and colour-scaled in the horizontal direction. Blue indicates low values and red indicates high values. Dendrograms are based on hierarchical cluster analysis with Bray-Curtis dissimilarity indices. (B) Log10 fold change between infected and uninfected faecal samples from day 35. (*) Indicates that the genus was undetected in either infected or uninfected samples. Detected only in uninfected: Robinsoniella (0.003%), Sporobacter (0.06%). Detected only in infected: Escherichia/Shigella (0.06%), Enterococcus (0.04%).

Fig 5
Fig 5. Chronic T. muris infection alters the regulatory/inflammatory T cell balance in the large intestine.

(A) Haematopoietic cell numbers (cellularity) in the LI LP of T. muris-infected and uninfected mice. (B-C) Proportion of (B) CD4+ TCRβ+ cells, and (C) IFN-γ+ T-bet+ CD4+ T cells in the LI LP of T. muris-infected and uninfected mice. (D) Representative flow cytometry plots of FoxP3, IFN-γ and IL-10-expressing CD4+ T cells in the LI LP. Numbers indicate frequencies of CD4+ T cells. Blue = uninfected, red = T. muris-infected (day 20). (E) T. muris-derived E/S antigen-specific secretion of IFN-γ by cells isolated from the LI LP of T. muris-infected and uninfected mice after ex vivo stimulation for 48 h. (F) Proportion of FoxP3+ CD4+ T cells in the LI LP of T. muris-infected and uninfected mice. (G) Ratio between FoxP3+ and IFN-γ+ T-bet+ CD4+ T cells in the LI LP of T. muris-infected and uninfected mice. (H) Proportion of IL-10+ FoxP3+ CD4+ T cells in the LI LP of T. muris-infected and uninfected mice. Bar graphs are displayed as mean (n = 6) with standard deviation. Statistical analyses were performed with one-way ANOVA, followed by Tukey’s post-test for multiple comparisons using Prism (GraphPad software). The following definitions were used to denote statistical significance: * (p<0.05), ** (p<0.01), *** (p<0.001), while p>0.05 was considered not significant (NS).

Similar articles

Cited by

References

    1. Sommer F, Backhed F. The gut microbiota—masters of host development and physiology. Nature reviews Microbiology. 2013;11(4):227–38. 10.1038/nrmicro2974 - DOI - PubMed
    1. Tremaroli V, Backhed F. Functional interactions between the gut microbiota and host metabolism. Nature. 2012;489(7415):242–9 10.1038/nature11552 - DOI - PubMed
    1. Backhed F, Ding H, Wang T, Hooper LV, Koh GY, Nagy A, et al. The gut microbiota as an environmental factor that regulates fat storage. Proceedings of the National Academy of Sciences of the United States of America. 2004;101(44):15718–23. - PMC - PubMed
    1. Russell WR, Hoyles L, Flint HJ, Dumas ME. Colonic bacterial metabolites and human health. Current opinion in microbiology. 2013;16(3):246–54. 10.1016/j.mib.2013.07.002 - DOI - PubMed
    1. Mazmanian SK, Liu CH, Tzianabos AO, Kasper DL. An immunomodulatory molecule of symbiotic bacteria directs maturation of the host immune system. Cell. 2005;122(1):107–18. - PubMed

Publication types

MeSH terms

Grants and funding

This work was supported by grants from the Novo Nordisk Foundation (www.novonordiskfonden.dk), The Carlsberg Foundation (www.carlsbergfondet.dk), and the Swedish Medical Research Council (www.vr.se). Yuliaxis Ramayo-Caldas was funded by the European Union, in the framework of the Marie-Curie FP7 COFUND People Programme, through the award of an AgreenSkills' fellowship (under grant agreement n° 267196; www.agreenskills.eu). The funding sources had no role in study design, data collection and analysis, decision to publish, or preparation of the manuscript.