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Red blood cells capture and deliver bacterial DNA to drive host responses during polymicrobial sepsis
L.K. Metthew Lam, … , Robert P. Dickson, Nilam S. Mangalmurti
L.K. Metthew Lam, … , Robert P. Dickson, Nilam S. Mangalmurti
Published December 12, 2024
Citation Information: J Clin Invest. 2025;135(4):e182127. https://doi.org/10.1172/JCI182127.
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Research Article Inflammation Pulmonology

Red blood cells capture and deliver bacterial DNA to drive host responses during polymicrobial sepsis

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Abstract

Red blood cells (RBCs), traditionally recognized for their role in transporting oxygen, play a pivotal role in the body’s immune response by expressing TLR9 and scavenging excess host cell-free DNA. DNA capture by RBCs leads to accelerated RBC clearance and triggers inflammation. Whether RBCs can also acquire microbial DNA during infections is unknown. Murine RBCs acquire microbial DNA in vitro, and bacterial DNA–induced (bDNA-induced) macrophage activation was augmented by WT, but not Tlr9-deleted, RBCs. In a mouse model of polymicrobial sepsis, RBC-bound bDNA was elevated in WT mice but not in erythroid Tlr9–deleted mice. Plasma cytokine analysis in these mice revealed distinct sepsis clusters characterized by persistent hypothermia and hyperinflammation in the most severely affected mice. RBC Tlr9 deletion attenuated plasma and tissue IL-6 production in the most severely affected group. Parallel findings in humans confirmed that RBCs from patients with sepsis harbored more bDNA than did RBCs from healthy individuals. Further analysis through 16S sequencing of RBC-bound DNA illustrated distinct microbial communities, with RBC-bound DNA composition correlating with plasma IL-6 in patients with sepsis. Collectively, these findings unveil RBCs as overlooked reservoirs and couriers of microbial DNA, capable of influencing host inflammatory responses in sepsis.

Authors

L.K. Metthew Lam, Nathan J. Klingensmith, Layal Sayegh, Emily Oatman, Joshua S. Jose, Christopher V. Cosgriff, Kaitlyn A. Eckart, John McGinniss, Piyush Ranjan, Matthew Lanza, Nadir Yehya, Nuala J. Meyer, Robert P. Dickson, Nilam S. Mangalmurti

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Figure 2

Plasma cytokine levels and gene expression in WT and Erytlr9–/– mice following CS injection.

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Plasma cytokine levels and gene expression in WT and Erytlr9–/– mice fol...
(A) Plasma cytokine levels 24 hours after CS or D5W injection. n = 8–17 per group from 4 independent studies. (B) UMAP derived from the 9 measured plasma cytokine concentrations colored according to whether the mice developed persistent or transient hypothermia or were controls (D5W). (C) Weighted kernel density estimation illustrating relative concentrations (red higher, blue lower) of the cytokines in each cluster. (D) Heatmap of cytokines structured with agglomerative clustering similarly illustrating the correlation between cytokine concentration and hypothermia. (E) Plasma cytokine levels 24 hours after CS or D5W injection; plasma cytokines were stratified on the basis of hypothermic state. Trans, transient hypothermia; Pers, persistent hypothermia 24 hours after injection. (F) Splenic expression of immune genes stratified according to the hypothermic state. (G) Association between bacterial load and tissue cytokine levels in the spleen. Spearman’s correlation coefficient was determined, with an asterisk denoting a significant correlation between tissue cytokine levels and bacterial load. (H) Hepatic expression of immune genes stratified on the basis of hypothermic state. (I) Association between bacterial load and tissue cytokine levels in the liver. Spearman’s correlation coefficient was determined, with an asterisk denoting a significant correlation between tissue cytokine levels and bacterial load. n = 4–8 per temperature-stratified group from 4 independent studies (F–I). *P < 0.05, **P < 0.01, ***P < 0.001, and ****P < 0.0001, by 1-way Kruskal-Wallis test with Dunn’s post hoc test (A) and 1-way ANOVA with Holm-Šidák test (E, F, and H).

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ISSN: 0021-9738 (print), 1558-8238 (online)

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