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. 2018 Apr 3;6(1):66.
doi: 10.1186/s40168-018-0441-4.

Gut-dependent microbial translocation induces inflammation and cardiovascular events after ST-elevation myocardial infarction

Xin Zhou  1 , Jing Li  2   3 , Junli Guo  4 , Bin Geng  5 , Wenjie Ji  1 , Qian Zhao  1 , Jinlong Li  1 , Xinlin Liu  1 , Junxiang Liu  1 , Zhaozeng Guo  1 , Wei Cai  1 , Yongqiang Ma  1 , Dong Ren  1 , Jun Miao  1 , Shaobo Chen  1 , Zhuoli Zhang  6 , Junru Chen  7 , Jiuchang Zhong  2   3 , Wenbin Liu  7 , Minghui Zou  8 , Yuming Li  9 , Jun Cai  10
Affiliations

Gut-dependent microbial translocation induces inflammation and cardiovascular events after ST-elevation myocardial infarction

Xin Zhou et al. Microbiome. .

Abstract

Background: Post-infarction cardiovascular remodeling and heart failure are the leading cause of myocardial infarction (MI)-driven death during the past decades. Experimental observations have involved intestinal microbiota in the susceptibility to MI in mice; however, in humans, identifying whether translocation of gut bacteria to systemic circulation contributes to cardiovascular events post-MI remains a major challenge.

Results: Here, we carried out a metagenomic analysis to characterize the systemic bacteria in a cohort of 49 healthy control individuals, 50 stable coronary heart disease (CHD) subjects, and 100 ST-segment elevation myocardial infarction (STEMI) patients. We report for the first time higher microbial richness and diversity in the systemic microbiome of STEMI patients. More than 12% of post-STEMI blood bacteria were dominated by intestinal microbiota (Lactobacillus, Bacteroides, and Streptococcus). The significantly increased product of gut bacterial translocation (LPS and D-lactate) was correlated with systemic inflammation and predicted adverse cardiovascular events. Following experimental MI, compromised left ventricle (LV) function and intestinal hypoperfusion drove gut permeability elevation through tight junction protein suppression and intestinal mucosal injury. Upon abrogation of gut bacterial translocation by antibiotic treatment, both systemic inflammation and cardiomyocyte injury in MI mice were alleviated.

Conclusions: Our results provide the first evidence that cardiovascular outcomes post-MI are driven by intestinal microbiota translocation into systemic circulation. New therapeutic strategies targeting to protect the gut barrier and eliminate gut bacteria translocation may reduce or even prevent cardiovascular events post-MI.

Keywords: Cardiovascular outcome; Gut permeability; Microbial translocation; Myocardial infarction.

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Conflict of interest statement

Authors’ information

Correspondence and requests for materials should be addressed to Jun Cai (caijun@fuwaihospital.org) and Yuming Li (cardiolab@gmail.com).

Ethics approval and consent to participate

The study was approved by local ethics committees (Pingjin Hospital Heart Center and Beijing Fuwai Hospital), and informed consent was obtained from all subjects. All animal care and experiments were performed in accordance with the guidelines of Institutional Animal Care and Use Committee of Pingjin Hospital Heart Center.

Consent for publication

Not applicable.

Competing interests

The authors declare that they have no competing interests.

Publisher’s Note

Springer Nature remains neutral with regard to jurisdictional claims in published maps and institutional affiliations.

Figures

Fig. 1
Fig. 1
Elevated richness of microbiota in the blood of in human adults with STEMI. a–bThe microbial richness and α-diversity (as accessed by Shannon index) based on the genera profile in control (n = 49), CHD (n = 50), and STEMI patients (n = 100). The distribution and density of samples are displayed in violin plots. Boxes represent the interquartile ranges, the inside black plots represent the median, and circles are outliers. P values are from Wilcoxon rank sum test. c Principal coordinate analysis (PCoA) based on the OTU table separate STEMI group from the controls and CHDs. Significant P values of Anosim and multi-response permutation procedure (MRPP) between groups emphasize the differences in microbial community structure. d Heatmap tree shows genera significantly different in STEMIs as compared to those in controls and CHDs, and their phylogenic relationships. The abundance profiles are expressed by z-scores, and genera were clustered based on Bray Curtis distance in the clustering tree. e Relative abundance of the top 40 most different genera across groups at adjusting P value ≤ 0.05 by Wilcoxon rank sum test and Benjamin and Hochberg method. The abundance profiles are transformed into z-scores by subtracting the average abundance and dividing the standard deviation of all samples. z-score is negative when the row abundance is lower than the mean. f The percentage of bacteria in control, CHD, and STEMI samples originated from oral and gut. More than 7.8% controls, 7.2% CHD, and 12% STEMI are derived from gut-specific microbiome. Boxes represent the interquartile ranges, the inside line represents the median. ***P < 0.001; Wilcoxon rank-sum test
Fig. 2
Fig. 2
Increased plasma levels of LPS and d-lactate after STEMI are associated with CD14++CD16+ monocyte. a–b The dynamic changes of LPS and d-lactate in STEMI patients after admission as compared to CHD controls and healthy controls. The data are presented by box and whisker plots: the boxes extend from the 25th to the 75th percentile, with a line at the median. The whiskers extend above and below the box to show the 5th–95th percentiles of values. The number below each box and whisker plot shows the median value. *P < 0.05, **P < 0.01, ***P < 0.001, Kruskal-Wallis test followed by a Dunn’s test. c The temporal profiles of LPS and d-lactate levels in STEMI patients as fold changes to stable CHD controls. Data are presented as mean ± s.e.m. d–e The association of plasma Δ LPS and Δ d-lactate (all Δ are calculated after logarithmic transformations) with CD14++CD16+ monocytes. The left panels show the result from all STEMI patients, and right panels show the subgroups of anterior MI patients. Correlation coefficients are reported as Pearson linear correlations
Fig. 3
Fig. 3
Higher LPS and d-lactate post-STEMI predict a poorer cardiovascular outcome, and TCM score was established. a–c ROC curve analysis of Δ LPS, Δ d-lactate, and translocation z-score for 3-year MACEs. d–f The univariate Kaplan-Meier survival analysis of Δ LPS (days 2–1), Δ d-lactate (days 2–1) and translocation z-score for 3-year MACEs. The patients are stratified according to the optimal cut-off values derived from ROC curve analyses. g The multivariate-adjusted Cox regression survival plot (with adjustment of age, LVEF (day 2) and SYNTAX score as categorical variables). The number adjacent to each line indicates the TCM score value. h The ROC curve analysis of TCM score
Fig. 4
Fig. 4
Schematic diagrams showing the coefficients relating inflammation markers, compromised LVEF with adverse cardiovascular events and the mediation effect of translocation z-score. a Association between CD14++CD16+ monocytes and MACE mediated by translocation z-score. b Association between compromised LVEF (derived from Youden index for MACE) and MACE mediated by translocation z-score. c Association between hs-CRP and MACE mediated by translocation z-score. β indicates coefficients in regression analysis; TE, total effect; ADE, average direct effect; ACME, average causal mediation effect; CI, confidence interval; MACE, major adverse cardiovascular events; LVEF, left ventricular ejection fraction; hs-CRP, high-sensitivity C-reactive protein. *P < 0.05, **P < 0.01
Fig. 5
Fig. 5
Increased gut permeability and microbial products are associated with monocyte in mice model of MI. a Gut permeability is elevated in the colon of MI mice. n = 4–6 for each group. b The augments of permeability in the distal small intestine, cecum, and colon at the third day of MI. n = 6 for each group. c–d The serum levels of LPS and d-lactate are enhanced after MI. n = 5 for each group. e–f The Ly6Chi monocyte proportion in MI mice is significantly increased as compared to the sham group. n = 5 for each group. g–h LPS and d-lactate are positively correlated with Ly6Chi monocyte proportion. n = 5 for each group. Correlation coefficients are reported as Pearson linear correlations. Data are presented as mean ± s.e.m. **P < 0.01; ***P < 0.001, vs respective shams, t test
Fig. 6
Fig. 6
The loss expression of tight junction protein occludin post-MI leads to intestinal mucosal injury. a The mRNA levels of occludin in colon tissues are decreased post-infarction. n = 5 for each group. b Western blot analysis of occludin protein expression in relative to GAPDH in the colon from MI mice. n = 5 for each group. c Representative immunofluorescence images of occludin (green) in the intestinal epithelium of MI mice. Nuclei are stained with DAPI (blue), and scale bars are 50 μm. d Transmission electron microscope image of sections from the intestinal epithelium of MI mice. Scale bars are 1 μm. Data are presented as mean ± s.e.m. *P < 0.05, vs respective shams, t test
Fig. 7
Fig. 7
Treatment of PMB eliminate serum LPS, alleviated monocytosis, and cardiomyocyte injury post-infarction. a The serum levels of LPS post-MI are suppressed by administration of PMB. n = 3–5 for each group. b The Ly6Chi monocyte proportions in MI mice are decreased in the presence of PMB. n = 5 for each group. c The infarct areas post-MI are reduced by PMB. n = 5 for each group. d–f Cardiomyocyte inflammation, macrophage infiltration, and collagen areas induced by MI are alleviated after PMB treatment. n = 5 for each group. NS, normal saline. All the data were from the third day of MI. Data are presented as mean ± s.e.m. **P < 0.01; ***P < 0.001, one-way ANOVA with Tukey’s post hoc test
Fig. 8
Fig. 8
Schematic illustration of the proposed interaction between STEMI, microbial translocation, and future ischemic events. Increased gut permeability and bacterial translocation from the gut lumen due to intestinal hypoperfusion post-STEMI are involved in the pathogenesis of monocytosis and inflammation and have the potential of contributing to further ischemic events and heart failure
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