Cell-based glycoengineering of extracellular vesicles through precise genome editing.

Engineering of extracellular vesicles (EVs) towards more efficient targeting and uptake to specific cells has large potentials for their application as therapeutics. Carbohydrates play key roles in various biological interactions and are essential for EV biology. The extent to which glycan modification of EVs can be achieved through genetic glycoengineering of their parental cells has not been explored yet. Here we introduce targeted glycan modification of EVs through cell-based glycoengineering via modification of various enzymes in the glycosylation machinery. In a "simple cell" strategy, we modified major glycosylation pathways by knocking-out (KO) essential genes for N-glycosylation (MGAT1), O-GalNAc glycosylation (C1GALT1C1), glycosphingolipids (B4GALT5/6), glycosaminoglycans (B4GALT7) and sialylation (GNE) involved in the elongation or biosynthesis of the glycans in HEK293F cells. The gene editing led to corresponding glycan changes on the cells as demonstrated by differential lectin staining. Small EVs (sEVs) isolated from the cells showed overall corresponding glycan changes, but also some unexpected differences to their parental cell including enrichment preference for certain glycan structures and absence of other glycan types. The genetic glycoengineering did not significantly impact sEVs production, size distribution, or syntenin-1 biomarker expression, while a clonal influence on sEVs production yields was observed. Our findings demonstrate the successful implementation of sEVs glycoengineering via genetic modification of the parental cell and a stable source for generation of glycoengineered sEVs. The utilization of glycoengineered sEVs offers a promising opportunity to study the role of glycosylation in EV biology, as well as to facilitate the optimization of sEVs for therapeutic purposes.

IRF8 maintains mononuclear phagocyte and neutrophil function in acute kidney injury.

Immune cells are key players in acute tissue injury and inflammation, including acute kidney injury (AKI). Their development, differentiation, activation status, and functions are mediated by a variety of transcription factors, such as interferon regulatory factor 8 (IRF8) and IRF4. We speculated that IRF8 has a pathophysiologic impact on renal immune cells in AKI and found that IRF8 is highly expressed in blood type 1 conventional dendritic cells (cDC1s), monocytes, monocyte-derived dendritic cells (moDCs) and kidney biopsies from patients with AKI. In a mouse model of ischemia‒reperfusion injury (IRI)-induced AKI, Irf8 -/- mice displayed increased tubular cell necrosis and worsened kidney dysfunction associated with the recruitment of a substantial amount of monocytes and neutrophils but defective renal infiltration of cDC1s and moDCs. Mechanistically, global Irf8 deficiency impaired moDC and cDC1 maturation and activation, as well as cDC1 proliferation, antigen uptake, and trafficking to lymphoid organs for T-cell priming in ischemic AKI. Moreover, compared with Irf8 +/+ mice, Irf8 -/- mice exhibited increased neutrophil recruitment and neutrophil extracellular trap (NET) formation following AKI. IRF8 primarily regulates cDC1 and indirectly neutrophil functions, and thereby protects mice from kidney injury and inflammation following IRI. Our results demonstrate that IRF8 plays a predominant immunoregulatory role in cDC1 function and therefore represents a potential therapeutic target in AKI.

The role of ferroptosis in DM-induced liver injury.

The liver damage caused by Diabetes Mellitus (DM) has attracted increasing attention in recent years. Liver injury in DM can be caused by ferroptosis, a form of cell death caused by iron overload. However, the role of iron transporters in this context is still not clear. Herein, we attempted to shed light on the pathophysiological mechanism of ferroptosis. DM was induced in 8-week-old male rats by streptozotocin (STZ) before assessment of the degree of liver injury. Together with histopathological changes, variations in glutathione peroxidase 4 (GPX4), glutathione (GSH), superoxide dismutase (SOD), transferrin receptor 1 (TFR1), ferritin heavy chain (FTH), ferritin light chain (FTL), ferroportin and Prussian blue staining, were monitored in rat livers before and after treatment with Fer-1. In the liver of STZ-treated rats, GSH and SOD levels decreased, whereas those of malondialdehyde (MDA) increased. Expression of TFR1, FTH and FTL increased whereas that of glutathione peroxidase 4 (GPX4) and ferroportin did not change significantly. Prussian blue staining showed that iron levels increased. Histopathology showed liver fibrosis and decreased glycogen content. Fer-1 treatment reduced iron and MDA levels but GSH and SOD levels were unchanged. Expression of FTH and FTL was reduced whereas that of ferroportin showed a mild decrease. Fer-1 treatment alleviated liver fibrosis, increased glycogen content and mildly improved liver function. Our study demonstrates that ferroptosis is involved in DM-induced liver injury. Regulating the levels of iron transporters may become a new therapeutic strategy in ferroptosis-induced liver injury.

Comprehensive Analysis of Fatty Acid Metabolism in Diabetic Nephropathy from the Perspective of Immune Landscapes, Diagnosis and Precise Therapy.

Objective: Diabetic nephropathy (DN) represents the principal cause of end-stage renal diseases worldwide, lacking effective therapies. Fatty acid (FA) serves as the primary energy source in the kidney and its dysregulation is frequently observed in DN. Nevertheless, the roles of FA metabolism in the occurrence and progression of DN have not been fully elucidated. Methods: Three DN datasets (GSE96804/GSE30528/GSE104948) were obtained and combined. Differentially expressed FA metabolism-related genes were identified and subjected to DN classification using "ConsensusClusterPlus". DN subtypes-associated modules were discovered by "WGCNA", and module genes underwent functional enrichment analysis. The immune landscapes and potential drugs were analyzed using "CIBERSORT" and "CMAP", respectively. Candidate diagnostic biomarkers of DN were screened using machine learning algorithms. A prediction model was constructed, and the performance was assessed using receiver operating characteristic (ROC) curves, calibration curves, and decision curve analysis (DCA). The online tool "Nephroseq v5" was conducted to reveal the clinical significance of the candidate diagnostic biomarkers in patients with DN. A DN mouse model was established to verify the biomarkers' expression. Results: According to 39 dysregulated FA metabolism-related genes, DN samples were divided into two molecular subtypes. Patients in Cluster B exhibited worse outcomes with a different immune landscape compared with those in Cluster A. Ten potential small-molecular drugs were predicted to treat DN in Cluster B. The diagnostic model based on PRKAR2B/ANXA1 was created with ideal predictive values in early and advanced stages of DN. The correlation analysis revealed significant association between PRKAR2B/ANXA1 and clinical characteristics. The DN mouse model validated the expression patterns of PRKAR2B/ANXA1. Conclusion: Our study provides new insights into the role of FA metabolism in the classification, immunological pathogenesis, early diagnosis, and precise therapy of DN.

Neutrophil Percentage-to-Albumin Ratio and Risk of Mortality in Patients on Peritoneal Dialysis.

Background: Neutrophil percentage-to-albumin ratio (NPAR), a new inflammatory marker, has been shown to be associated with poor prognosis in patients with cardiovascular disease. However, limited evidence is available for its role in peritoneal dialysis (PD) patients. Our study aimed at investigating the prognostic value of NPAR for mortality in PD patients. Patients and Methods: This was a single center retrospective cohort study. A total of 1966 PD patients were enrolled in our study from January 2006 to December 2016 and were followed up until December 2021. Patients were stratified into tertiles according to baseline NPAR levels. The associations between NPAR levels with all-cause and cardiovascular mortality were estimated using Cox proportional hazards models. Receiver operating characteristic (ROC) analysis was performed to compare the mortality predictive values of NPAR and other known biomarkers, such as NLR (neutrophil-to-lymphocyte ratio), PLR (platelet-to-lymphocyte ratio), LHR (low-density lipoprotein cholesterol-to-high-density lipoprotein cholesterol ratio) and MLR (monocyte-to-lymphocyte ratio). Results: During a median follow-up of 48.1 months, 503 (25.6%) patients died, in which cardiovascular disease (CVD) death dominated 50.3%. Multivariate Cox regression analysis revealed that the highest NPAR tertile was significantly associated with a higher risk of all-cause and cardiovascular mortality (HR 1.51, 95% CI 1.14-1.98; HR 1.57, 95% CI 1.07-2.31; respectively) compared with tertile 1. The AUC values of NPAR were 0.62 (95% CI 0.60-0.65, P < 0.001) for all-cause mortality and 0.61 (95% CI 0.57-0.65, P < 0.001) for cardiovascular mortality. Conclusion: Our study showed that higher NPAR levels were independently associated with increased risk of all-cause and cardiovascular mortality in PD patients. Notably, our results demonstrated that NPAR exhibited superior predictive value for mortality compared to NLR, PLR, MLR, and LHR.