Daily Sepsis Research Analysis
Three studies advance sepsis science across mechanism and diagnostics: dimethyl fumarate (DMF) mitigates sepsis-induced lung injury by blocking STING-driven ferroptosis and preserving GPX4; a gut microbiota-derived Proline–Leucine dipeptide exacerbates lung inflammation via C/EBP-β/NOD2/NF-κB; and plasma extracellular vesicle 5-hydroxymethylcytosine signatures show high accuracy for diagnosing septic cardiomyopathy.
Summary
Three studies advance sepsis science across mechanism and diagnostics: dimethyl fumarate (DMF) mitigates sepsis-induced lung injury by blocking STING-driven ferroptosis and preserving GPX4; a gut microbiota-derived Proline–Leucine dipeptide exacerbates lung inflammation via C/EBP-β/NOD2/NF-κB; and plasma extracellular vesicle 5-hydroxymethylcytosine signatures show high accuracy for diagnosing septic cardiomyopathy.
Research Themes
- Ferroptosis and innate immune signaling in sepsis
- Gut–lung axis and microbiome-derived metabolites
- Epigenetic extracellular vesicle biomarkers for organ dysfunction
Selected Articles
1. Dimethyl fumarate improves sepsis-induced acute lung injury by inhibiting STING-mediated ferroptosis.
In CLP-induced sepsis models, DMF reduced ferroptosis, inflammation, and oxidative injury in lungs, and improved histology. Mechanistically, DMF blocked STING activation and prevented STING-mediated autophagic degradation of GPX4, thereby limiting ROS and ferroptotic death.
Impact: This study links STING signaling to ferroptosis via GPX4 autophagic degradation and identifies DMF as a dual-function inhibitor, highlighting a tractable therapeutic axis for sepsis-induced lung injury.
Clinical Implications: While preclinical, the data support repurposing DMF—already approved for multiple sclerosis—as a candidate to mitigate sepsis-related ALI/ARDS by targeting the STING–ferroptosis axis.
Key Findings
- CLP increased pulmonary ferroptosis, inflammation, and oxidative stress; DMF markedly attenuated these and improved histological injury.
- DMF suppressed LPS-induced ferroptosis in MLE-12 alveolar epithelial cells.
- DMF inhibited STING activation and prevented STING-mediated autophagic degradation of GPX4, reducing ROS and ferroptotic death.
Methodological Strengths
- Integrated in vivo CLP sepsis model with complementary in vitro validation.
- Mechanistic dissection linking STING signaling to GPX4 autophagic degradation and ferroptosis.
Limitations
- Preclinical animal and cell models without human clinical validation.
- Optimal dosing, timing, and safety of DMF in sepsis remain untested.
Future Directions: Validate the STING–ferroptosis–GPX4 axis and DMF efficacy in large-animal models and early-phase clinical trials; develop biomarkers to identify ferroptosis-high sepsis patients.
The precise pathogenic mechanisms underlying sepsis-induced acute respiratory distress syndrome (ARDS) remain incompletely characterized. Emerging evidence implicates ferroptosis of alveolar epithelial cells in ARDS pathogenesis, though the regulatory networks governing this association require further elucidation. Stimulator of interferon genes (STING), conventionally recognized as a pivotal mediator of innate immunity through DNA-sensing pathways, has recently been linked to ferroptosis. This investigation elucidates the pulmonary protective mechanisms of DMF in sepsis-induced ALI models. Experimental data revealed elevated ferroptotic activity, inflammatory markers, and oxidative stress in lungs following cecal ligation and puncture (CLP) procedures. DMF administration significantly attenuated pulmonary ferroptosis while concurrently mitigating inflammation and oxidative damage, ultimately ameliorating histological lung injury. Complementary in vitro studies demonstrated DMF's capacity to suppress lipopolysaccharide (LPS)-induced ferroptosis in MLE-12 cells. Mechanistic analyses identified dual protective pathways. DMF not only inhibited LPS-triggered STING activation and subsequent proinflammatory cytokine production but also prevented STING-mediated autophagic degradation of glutathione peroxidase 4 (GPX4). This dual action effectively reduced reactive oxygen species (ROS) accumulation and ferroptotic cell death. These findings position DMF as a promising therapeutic candidate with dual pharmacological actions - functioning as both a STING pathway inhibitor and ferroptosis suppressor.
2. Gut microbiota-derived Proline-Leucine dipeptide aggravated sepsis-induced acute lung injury via activating Nod2/NF-κB signaling pathway.
Multi-omics profiling in sepsis revealed elevated Pro–Leu, alongside dysbiosis, which correlated with worsened lung injury. Pro–Leu and LPS synergistically amplified TNF-α, IL-6, and IL-1β via C/EBP-β/NOD2/NF-κB in lung tissues and MH-S cells.
Impact: Identifies a specific microbiota-derived dipeptide as a modifiable mediator of the gut–lung axis in sepsis, providing a concrete pathway (NOD2/NF-κB) for therapeutic targeting.
Clinical Implications: Although preclinical, measuring Pro–Leu or modulating its production/signaling (e.g., via microbiome interventions or NOD2/NF-κB blockade) could mitigate sepsis-associated lung injury.
Key Findings
- Sepsis reduced gut microbiota diversity and increased Bacteroidetes and Escherichia–Shigella, with concomitant elevation of the Pro–Leu dipeptide.
- Pro–Leu levels correlated with microbial community shifts and exacerbated sepsis-induced lung injury in mice.
- Pro–Leu and LPS upregulated C/EBP-β, NOD2, and p-NF-κB, enhancing TNF-α, IL-6, and IL-1β production in lung tissues and MH-S cells.
Methodological Strengths
- Combined 16S rDNA sequencing with untargeted metabolomics to link dysbiosis to specific metabolites.
- Validated mechanistic pathway across animal models and macrophage-like lung cells with signaling readouts.
Limitations
- Findings are limited to animal and cell models; human validation of Pro–Leu levels and effects is lacking.
- Complexity of microbiome–host interactions may limit generalizability and causality inference in humans.
Future Directions: Quantify Pro–Leu in human sepsis cohorts and test it as a biomarker and interventional target; evaluate microbiome or NOD2/NF-κB–directed therapies in translational studies.
OBJECTIVE: Gut microbiota-derived metabolites can modulate lung tissue damage via the gut-lung axis. This study aimed to delineate the alterations in gut microbiota and metabolites associated with sepsis and elucidate their role in potentiating lung tissue damage. METHODS: We employed 16S rDNA sequencing and non-targeted metabolomics to assess the changes in gut microbiota and metabolites, utilizing a rat model of sepsis. Furthermore, we investigated the contributions of the gut microbiota-derived Proline-Leucine (Pro-Leu) dipeptide and lipopolysaccharide (LPS) in driving lung inflammation, utilizing both mouse models and MH-S cells. RESULTS: Our findings indicate that sepsis significantly diminished gut microbiota diversity and markedly increased the relative abundance of Bacteroidetes and Escherichia-Shigella, as well as the metabolite Pro-Leu. Notably, Pro-Leu levels correlated with changes in bacterial communities. Additionally, Pro-Leu effectively exacerbated sepsis-induced lung damage. Both Pro-Leu and LPS notably enhanced pro-inflammatory cytokine production (TNF-α, IL-6, and IL-1β) by up-regulating C/EBP-β, p-NF-κB, and NOD2 in lung tissues and MH-S cells. CONCLUSIONS: Our findings suggest that Pro-Leu and LPS can synergistically intensify lung inflammation by activating the C/EBP-β/NOD2/NF-κB signaling pathways. IMPORTANCE: Our findings indicate that sepsis can lead to a disruption of the gut microbiota, an increase in pathogenic bacteria such as Escherichia-Shigella and Bacteroides, and that metabolites derived from the gut microbiota can modulate the lung inflammatory response through the gut-lung axis. Notably, Pro-Leu, a metabolite produced by the gut microbiota, was found to aggravate sepsis-induced ALI by activating the C/EBP-β/NOD2/NF-κB signaling pathways.
3. 5-Hydroxymethylcytosine signatures as diagnostic biomarkers for septic cardiomyopathy.
Plasma extracellular vesicle 5hmC-Seal profiling distinguished septic cardiomyopathy from sepsis without cardiomyopathy and non-sepsis controls with high accuracy, supported by external dataset validation.
Impact: Introduces an epigenetic liquid biopsy approach for septic cardiomyopathy with strong diagnostic performance, addressing a critical gap in early identification.
Clinical Implications: If validated prospectively, EV 5hmC signatures could complement echocardiography and cardiac biomarkers to enable earlier diagnosis and risk stratification of septic cardiomyopathy.
Key Findings
- 5hmC-Seal profiling of plasma EV DNA in 13 SCM, 18 sepsis without cardiomyopathy, and 8 non-sepsis controls enabled machine learning model development.
- The diagnostic model achieved accuracy 0.962 with 92.3% sensitivity and 88.89% specificity.
- External validation using GEO datasets reported accuracy up to 1.000 and differential diagnostic AUCs of 0.959 and 0.944.
Methodological Strengths
- Application of 5hmC-Seal to extracellular vesicle DNA enabling high-resolution epigenetic profiling.
- Use of machine learning with external dataset validation to assess diagnostic performance.
Limitations
- Small sample size increases risk of overfitting and limits generalizability.
- Validation relied on public datasets that may differ in sample type or context from EV 5hmC profiles; prospective multicenter validation is needed.
Future Directions: Prospective, multicenter studies to validate EV 5hmC classifiers, assay standardization, and head-to-head comparisons with echocardiography and cardiac biomarkers.
At present, there are currently no molecular biomarkers for the early diagnosis of sepsis cardiomyopathy (SCM) in clinical practice. This study focuses on an in-depth examination of the DNA hydroxymethylation profiles within plasma extracellular vesicles and explores potential molecular biomarkers during the process of SCM. The 5hmC-Seal sequencing technology was utilized to examine the hydroxymethylation modifications of extracellular vesicles DNAs in 13 patients with septic cardiomyopathy, 18 patients with sepsis without cardiomyopathy, and 8 patients without sepsis. Additionally, a diagnostic model was constructed using machine learning methods based on the differential hydroxymethylation modifications to screen for candidate biomarkers. The accuracy of the diagnostic model was 0.962, with a sensitivity and specificity of 92.3% and 88.89%, respectively. Furthermore, the diagnostic accuracy was validated using the GEO dataset, with an accuracy rate reaching 1 (GSE79962 and GSE66890), and the differential diagnostic accuracy rates also reached 0.959 and 0.944 (GSE79962). Together, the results suggest that extracellular vesicles DNAs hydroxymethylation markers can be used for diagnosis of septic cardiomyopathy.