12 research outputs found
Host Genetics and Environmental Factors Regulate Ecological Succession of the Mouse Colon Tissue-Associated Microbiota
Background: The integration of host genetics, environmental triggers and the microbiota is a recognised factor in the pathogenesis of barrier function diseases such as IBD. In order to determine how these factors interact to regulate the host immune response and ecological succession of the colon tissue-associated microbiota, we investigated the temporal interaction between the microbiota and the host following disruption of the colonic epithelial barrier. Methodology/Principal Findings: Oral administration of DSS was applied as a mechanistic model of environmental damage of the colon and the resulting inflammation characterized for various parameters over time in WT and Nod2 KO mice. Results: In WT mice, DSS damage exposed the host to the commensal flora and led to a migration of the tissue-associated bacteria from the epithelium to mucosal and submucosal layers correlating with changes in proinflammatory cytokine profiles and a progressive transition from acute to chronic inflammation of the colon. Tissue-associated bacteria levels peaked at day 21 post-DSS and declined thereafter, correlating with recruitment of innate immune cells and development of the adaptive immune response. Histological parameters, immune cell infiltration and cytokine biomarkers of inflammation were indistinguishable between Nod2 and WT littermates following DSS, however, Nod2 KO mice demonstrated significantly higher tissue-associated bacterial levels in the colon. DSS damage and Nod2 genotype independently regulated the community structure of the colon microbiota
Human lung mast cell and eosinophil adhesion to bronchial epithelium
Asthma is initiated at the mucosal surface upon aeroallergen exposure and mast cell activation. Release of eosinophil cationic proteins is thought to be responsible for epithelial damage. In this study, human peripheral blood eosinophil and human lung mast cell (HLMC) adhesion to bronchial epithelium were investigated. A high proportion of HLMC adhered to epithelial cell monolayers compared to eosinophils. In both cases, adhesion was cation-independent, and was not inhibited by function-blocking ICAM-1 mAb, despite increased basal epithelial ICAM-1 expression upon cytokine activation.;HLMC adhesion was not modulated by function blocking mAb to cell adhesion molecule families, preincubation with carbohydrates, HLMC activation (SCF or TGF-P), or epithelial activation (cytokines). A significant reduction in adhesion was observed upon pretreatment with anti-IgE, pronase, -galactosidase or endo--N-acetylgalactosaminidase (HLMC) or 4% paraformaldehyde (epithelium). No evidence for galectin involvement in adhesion was observed.;Eosinophil adhesion to alveolar epithelium was not modulated by eosinophil activation with PAF. Adhesion to bronchial epithelium was enhanced upon activation of both eosinophils (Mn2+) and epithelium (cytomix). A proportion of the enhanced adhesion was 2 (CD 18) integrin-mediated.;In conclusion, the adhesion mechanisms of mast cells and eosinophils to bronchial epithelium were different, possibly relating to their divergent in vivo functions. The differences in proportions of adherent mast cells and eosinophils to bronchial epithelium during asthma may result in the widely documented lack of mast cells compared to eosinophils in sputum and BAL in vivo.
Host genetics and environmental factors regulate ecological succession of the colon tissue-associated microbiota
Background: The integration of host genetics, environmental triggers and the microbiota is a recognised factor in the pathogenesis of barrier function diseases such as IBD. In order to determine how these factors interact to regulate the host immune response and ecological succession of the colon tissue-associated microbiota, we investigated the temporal interaction between the microbiota and the host following disruption of the colonic epithelial barrier. Methodology/Principal Findings: Oral administration of DSS was applied as a mechanistic model of environmental damage of the colon and the resulting inflammation characterized for various parameters over time in WT and Nod2 KO mice. Results: In WT mice, DSS damage exposed the host to the commensal flora and led to a migration of the tissue-associated bacteria from the epithelium to mucosal and submucosal layers correlating with changes in proinflammatory cytokine profiles and a progressive transition from acute to chronic inflammation of the colon. Tissue-associated bacteria levels peaked at day 21 post-DSS and declined thereafter, correlating with recruitment of innate immune cells and development of the adaptive immune response. Histological parameters, immune cell infiltration and cytokine biomarkers of inflammation were indistinguishable between Nod2 and WT littermates following DSS, however, Nod2 KO mice demonstrated significantly higher tissue-associated bacterial levels in the colon. DSS damage and Nod2 genotype independently regulated the community structure of the colon microbiota. Conclusions/Significance: The results of these experiments demonstrate the integration of environmental and genetic factors in the ecological succession of the commensal flora in mammalian tissue. The association of Nod2 genotype (and other host polymorphisms) and environmental factors likely combine to influence the ecological succession of the tissue-associated microflora accounting in part for their association with the pathogenesis of inflammatory bowel diseases
Community Structure Comparison: Libshuff and Parsimony Statistical Analysis of Colon-Associated Bacterial Populations.
<p>Community Structure Comparison: Libshuff and Parsimony Statistical Analysis of Colon-Associated Bacterial Populations.</p
Richness, diversity and taxonomic analysis of the WT and Nod2 KO colon tissue-associated bacterial communities.
<p>Top panel: Incidence of phyla from treatment groups of WT and Nod2 KO littermates. Mean +/− SEM (n = 4–6) for each group is shown. * p≤0.05, ** p<0.01 by 2 way ANOVA with Bonferroni's multiple comparison test. Bottom panels: the Chao and Shannon estimates for richness and diversity were calculated from individual mice from each group as indicated (n = 4–6). The mean +/− SEM are shown. No differences were statistically significant by ANOVA.</p
Comparison of physical and histological parameters and bacterial load of WT and Nod2 KO littermates following DSS damage.
<p><b>A.</b> Timelines and histology assessment for individual mice. No significant difference was observed between the two genotypes for physical parameters (body weight loss, colon length: not shown) nor histological scores between the two groups (see <a href="http://www.plosone.org/article/info:doi/10.1371/journal.pone.0030273#pone.0030273.s004" target="_blank">Figure S4</a> for data from 2 additional independent experiments). <b>B.</b> Colon, mesenteric lymph node and spleen tissue-associated bacterial loads assessed by FACS 42 days following DSS damage. ** = p≤0.01 by Anova with Bonferroni's multiple comparison test. <b>C.</b> Residence of commensal bacteria in the muscle layer in Nod2 KO mice. Examples of bacterial staining by EUB338 FISH probes are indicated by closed arrows in these representative images.</p
Phylogenetic tree visualisation of full length 16S rRNA sequences from WT and Nod2 KO mouse colon tissue 42 days post DSS or control as indicated.
<p>See <a href="http://www.plosone.org/article/info:doi/10.1371/journal.pone.0030273#s4" target="_blank">Materials and Methods</a> for parameters.</p
Temporal physical, histological and biomarker analysis of DSS damage.
<p>Mice were administered DSS in their drinking water from day 0 to day 5 and individual parameters outlined in each panel assessed by criteria described previously <a href="http://www.plosone.org/article/info:doi/10.1371/journal.pone.0030273#pone.0030273-Smith1" target="_blank">[41]</a>. * = p≤0.05, ** = p≤0.01, *** = p≤0.001 by 1-way Anova with Bonferroni's multiple comparison test. <b>A.</b> Body weight (physiological parameter for progression of inflammation) expressed as mean +/− SEM, n = 7. <b>B.</b> Fecal Score (combined weighted score of intestinal damage based on the presence of blood in the stool and subjective assessment of diarrhea) as a physiological indicator of colon tissue damage expressed as mean +/− SEM, n = 7. <b>C.</b> Colon length (physiological parameter for progression of inflammation) expressed as mean +/− SEM, n = 7. Statistical comparisons are versus Naive (no DSS-treatment) mice. <b>D.</b> Histology Score (quantitative assessment of microscopic tissue damage identical to that described previously <a href="http://www.plosone.org/article/info:doi/10.1371/journal.pone.0030273#pone.0030273-Smith1" target="_blank">[41]</a>) expressed as mean +/− SEM, n = 7. Statistical comparisons are versus Naive (no DSS-treatment) mice. <b>E.</b> Temporal cytokine (as indicated) profiles in colon homogenates from treated mice expressed as mean +/− SEM, n = 7. Statistical comparisons by Anova/Bonferroni. @ = p≤0.05 vs day 5, # = p≤0.05 vs day 8.</p
Proximity and progression of host/commensal interactions following DSS damage.
<p><b>A.</b> Localisation of commensal bacteria by EUB338 FISH probe analysis of FFPE sections from DSS-treated mice. Open arrows highlight examples of luminal or mucosal bacteria, closed arrows indicate bacteria associated with the muscle layers. E, epithelium. M, muscle. Bar = 50 µm. <b>B.</b> Quantification of colon tissue bacteria load in individual mice by FACS following DSS damage. * = p≤0.05, ** = p≤0.01, *** = p≤0.001 vs day 0 (no DSS treatment) by 1-way Anova with Bonferroni's correction.</p