Renal and cardiac effects of the PDE9 inhibitor BAY 73-6691 in 5/6 nephrectomized rats.

It has been suggested that the novel selective phosphodiesterase 9 (PDE9) inhibitor may improve cardiac and renal function by blocking 3',5'-cyclic guanosine monophosphate (cGMP) degradation. 5/6 nephrectomized (5/6Nx) rats were used to investigate the effects of the PDE9 inhibitor (BAY 73-6691) on the heart and kidney. Two doses of BAY 73-6691 (1 mg/kg/day and 5 mg/kg/day) were given for 95 days. The 5/6Nx rats developed albuminuria, a decrease in serum creatinine clearance (Ccr), and elevated serum troponin T levels. Echocardiographic data showed that 5/6 nephrectomy resulted in increased fractional shortening (FS), stroke volume (SV), and left ventricular ejection fraction (EF). However, 95 days of PDE9 inhibitor treatment did not improve any cardiac and renal functional parameter. Histopathologically, 5/6 nephrectomy resulted in severe kidney and heart damage, such as renal interstitial fibrosis, glomerulosclerosis, and enlarged cardiomyocytes. Telmisartan attenuated renal interstitial fibrosis and glomerulosclerosis as well as improved cardiomyocyte size. However, except for cardiomyocyte size and renal perivascular fibrosis, BAY 73-6691 had no effect on other cardiac and renal histologic parameters. Pathway enrichment analysis using RNA sequencing data of kidney and heart tissue identified chronic kidney disease pathways, such as phosphatidylinositol 3-kinase (PI3K)-protein kinase B (Akt) signaling pathway, complement and coagulation cascades, and nuclear factor kappa B (NF-κB) signaling pathway. PDE9i did not affect any of these disease-related pathways. Two dosages of the PDE9 inhibitor BAY 73-6691 known to be effective in other rat models have only limited cardio-renal protective effects in 5/6 nephrectomized rats.

Rewiring Metabolic Flux in Corynebacterium glutamicum Using a CRISPR/dCpf1-Based Bifunctional Regulation System.

Corynebacterium glutamicum, a microorganism classified as generally recognized as safe for use in the industrial production of food raw materials and additives, has encountered challenges in achieving widespread adoption and popularization as microbial cell factories. These obstacles arise from the intricate nature of manipulating metabolic flux through conventional methods, such as gene knockout and enzyme overexpression. To address this challenge, we developed a CRISPR/dCpf1-based bifunctional regulation system to bidirectionally regulate the expression of multiple genes in C. glutamicum. Specifically, through fusing various transcription factors to the C-terminus of dCpf1, the resulting dCpf1-SoxS exhibited both CRISPR interference (CRISPRi) and CRISPR activation (CRISPRa) capabilities in C. glutamicum by altering the binding sites of crRNAs. The bifunctional regulation system was used to fine-tune metabolic flux from shikimic acid (SA) and l-serine biosynthesis, resulting in 27-fold and 10-fold increases in SA and l-serine production, respectively, compared to the original strain. These findings highlight the potential of the CRISPR/dCpf1-based bifunctional regulation system in effectively enhancing the yield of target products in C. glutamicum.

Small RNA-big impact: exosomal miRNAs in mitochondrial dysfunction in various diseases.

Mitochondria are multitasking organelles involved in maintaining the cell homoeostasis. Beyond its well-established role in cellular bioenergetics, mitochondria also function as signal organelles to propagate various cellular outcomes. However, mitochondria have a self-destructive arsenal of factors driving the development of diseases caused by mitochondrial dysfunction. Extracellular vesicles (EVs), a heterogeneous group of membranous nano-sized vesicles, are present in a variety of bodily fluids. EVs serve as mediators for intercellular interaction. Exosomes are a class of small EVs (30-100 nm) released by most cells. Exosomes carry various cargo including microRNAs (miRNAs), a class of short noncoding RNAs. Recent studies have closely associated exosomal miRNAs with various human diseases, including diseases caused by mitochondrial dysfunction, which are a group of complex multifactorial diseases and have not been comprehensively described. In this review, we first briefly introduce the characteristics of EVs. Then, we focus on possible mechanisms regarding exosome-mitochondria interaction through integrating signalling networks. Moreover, we summarize recent advances in the knowledge of the role of exosomal miRNAs in various diseases, describing how mitochondria are changed in disease status. Finally, we propose future research directions to provide a novel therapeutic strategy that could slow the disease progress mediated by mitochondrial dysfunction.

Qualitative Proteome-wide Lysine Crotonylation Profiling Reveals Protein Modification Alteration in the Leukocyte Extravasation Pathway in Systemic Lupus Erythematosus.

BACKGROUND: Systemic lupus erythematosus (SLE) is a severe systemic autoimmune disease with multiple manifestations. Lysine crotonylation (Kcr) is a newly discovered posttranslational modification epigenetic pattern that may affect gene expression and is linked to diseases causally. METHODS: We collected blood samples from 11 SLE individuals and 36 healthy subjects. Then, we used highly sensitive liquid chromatography-mass spectrometry technology to carry out proteomics and quantitative crotonylome analysis of SLE peripheral blood mononuclear cells in this investigation, which indicated the unique etiology of SLE. Finally, we verified the expression of critical protein in the leukocyte extravasation pathway by online database analysis and Western blot. RESULTS: There were 618 differentially expressed proteins (DEPs), and 612 crotonylated lysine sites for 272 differentially modified proteins (DMPs) found. These DEPs and DMPs are primarily enriched in the leukocyte extravasation signaling pathway, such as MMP8, MMP9, and ITGAM. CONCLUSIONS: This is the first study of crotonylated modification proteomics in SLE. The leukocyte extravasation signaling pathway had a considerable concentration of DEPs and DMPs, indicating that this pathway may be involved in the pathogenic development of SLE.

Dysregulated coagulation system links to inflammation in diabetic kidney disease.

Diabetic kidney disease (DKD) is a significant contributor to end-stage renal disease worldwide. Despite extensive research, the exact mechanisms responsible for its development remain incompletely understood. Notably, patients with diabetes and impaired kidney function exhibit a hypercoagulable state characterized by elevated levels of coagulation molecules in their plasma. Recent studies propose that coagulation molecules such as thrombin, fibrinogen, and platelets are interconnected with the complement system, giving rise to an inflammatory response that potentially accelerates the progression of DKD. Remarkably, investigations have shown that inhibiting the coagulation system may protect the kidneys in various animal models and clinical trials, suggesting that these systems could serve as promising therapeutic targets for DKD. This review aims to shed light on the underlying connections between coagulation and complement systems and their involvement in the advancement of DKD.

Uncovering the mechanism of Qidan Dihuang Granule in the treatment of diabetic kidney disease combined network pharmacology, UHPLC-MS/MS with experimental validation.

Background and aim: Diabetic Kidney Disease (DKD) is a common microvascular complication of diabetes mellitus. Multi-center, randomized controlled trials have shown that Qidan Dihuang Granule (QDDHG) reduces the levels of albuminuria of DKD. However, the specific mechanisms of QDDHG on DKD are not clarified. Thus, this study utilized network pharmacology, UHPLC-MS/MS (Ultra-High Performance Liquid Chromatography - Mass Spectrometry) and animal experiments to reveal the mechanisms of QDDHG on DKD. Experimental procedure: Screening and retrieving active ingredients and corresponding targets of QDDHG on DKD through the TCMSP, ETCM, Disgenet, GeneCards, Omim and DrugBank databases. The PPI were performed with BioGrid, STRING, OmniPath, InWeb-IM. AutoDock Vina molecular docking module to estimate the validation from the compounds and target proteins. Free energy to estimate the binding affinity for identified compounds and target proteins. The ingredients of QDDHG were analyzed utilizing UHPLC-MS/MS. In vivo experiment with db/db mice were used to verify the targets and pathway predicted by network pharmacology. Results and conclusion: The results demonstrated that QDDHG has 18 active compounds and 13 target proteins of QDDHG exerted a crucial role in treatment of DKD. QDDHG affect the multiple biological processes included cellular response to lipid, response to oxidative stress, and various pathways, such as AGE-RAGE, PI3K-Akt, MAPK, TNF, EGFR, STAT3. The results of UHPLC-MS/MS showed that six ingredients predicted by network pharmacology were also verified in experiment. In vivo experiment verified the effects of QDDHG on protecting the renal function mainly through inhibited the expression of EGFR, STAT3 and pERK in the db/db mice.

Corrigendum to "The novel putative methyltransferase METTL7A as one prognostic biomarker potentially associated with immune infiltration in human renal cancer".

[This corrects the article DOI: 10.1016/j.heliyon.2023.e15371.].

CRISPR/Cas9-Mediated Gene Correction in Osteopetrosis Patient-Derived iPSCs.

BACKGROUND: Osteopetrosis represents a rare genetic disease with a wide range of clinical and genetic heterogeneity, which results from osteoclast failure. Although up to 10 genes have been identified to be related with osteopetrosis, the pathogenesis of osteopetrosis remains foggy. Disease-specific induced pluripotent stem cells (iPSCs) and gene-corrected disease specific iPSCs provide a platform to generate attractive in vitro disease cell models and isogenic control cellular models respectively. The purpose of this study is to rescue the disease causative mutation in osteopetrosis specific induced pluripotent stem cells and provide isogenic control cellular models. METHODS: Based on our previously established osteopetrosis-specific iPSCs (ADO2-iPSCs), we repaired the point mutation R286W of the CLCN7 gene in ADO2-iPSCs by the clustered regularly interspaced short palindromic repeats (CRISPR)/CRISPR-associated protein 9 (Cas9) mediated homologous recombination. RESULTS: The obtained gene corrected ADO2-iPSCs (GC-ADO2-iPSCs) were characterized in terms of hESC-like morphology, a normal karyotype, expression of pluripotency markers, homozygous repaired sequence of CLCN7 gene, and the ability to differentiate into cells of three germ layers. CONCLUSIONS: We successfully corrected the point mutation R286W of the CLCN7 gene in ADO2-iPSCs. This isogenic iPSC line is an ideal control cell model for deciphering the pathogenesis of osteopetrosis in future studies.

Urinary microbiota and serum metabolite analysis in patients with diabetic kidney disease.

Background: Diabetic kidney disease (DKD) is a common and potentially fatal consequence of diabetes. Chronic renal failure or end-stage renal disease may result over time. Numerous studies have demonstrated the function of the microbiota in health and disease. The use of advanced urine culture techniques revealed the presence of resident microbiota in the urinary tract, undermining the idea of urine sterility. Studies have demonstrated that the urine microbiota is related with urological illnesses; nevertheless, the fundamental mechanisms by which the urinary microbiota influences the incidence and progression of DKD remain unclear. The purpose of this research was to describe key characteristics of the patients with DKD urinary microbiota in order to facilitate the development of diagnostic and therapeutic for DKD. Methods: We evaluated the structure and composition of the microbiota extracted from urine samples taken from DKD patients (n = 19) and matched healthy controls (n = 15) using 16S rRNA gene sequencing. Meanwhile, serum metabolite profiles were compared using liquid chromatography-tandem mass spectrometry (LC-MS/MS). Associations between clinical characteristics, urine microbiota, and serum metabolites were also examined. Finally, the interaction between urine microbiota and serum metabolites was clarified based on differential metabolite abundance analysis. Results: The findings indicated that the DKD had a distinct urinary microbiota from the healthy controls (HC). Taxonomic investigations indicated that the DKD microbiome had less alpha diversity than a control group. Proteobacteria and Acidobacteria phyla increased in the DKD, while Firmicutes and Bacteroidetes decreased significantly (P < 0.05). Acidobacteria was the most prevalent microbiota in the DKD, as determined by the Linear discriminant analysis Effect Size (LEfSe) plot. Changes in the urinary microbiota of DKD also had an effect on the makeup of metabolites. Short-chain fatty acids (SCFAs) and protein-bound uremic toxins (PBUTs) were shown to be specific. Then we discovered that arginine and proline metabolism was the primary mechanism involved in the regulation of diabetic kidney disease. Conclusions: This study placed the urinary microbiota and serum metabolite of DKD patients into a functional framework and identified the most abundant microbiota in DKD (Proteobacteria and Acidobacteria). Arginine metabolites may have a major effect on DKD patients, which correlated with the progression of DKD.

Proteomics profiling and lysine malonylation analysis in primary Sjogren's syndrome.

Primary Sjogren's Syndrome (pSS) is a chronic autoimmune disease, with unclear pathogenies. Lysine-malonylation (Kmal) as a novel post-translational modification (PTMs) was found associated with metabolic, immune, and inflammatory processes. For purpose of investigating the proteomic profile and functions of kmal in pSS, liquid chromatography-tandem mass spectrometry (LC-MS/MS)-based analysis and bioinformatics analysis are performed based on twenty-eight pSS patients versus twenty-seven healthy controls (HCs). A total of 331 down-regulated proteins and 289 up-regulated proteins are observed in differentially expressed proteins (DEPs) of pSS. We discover the expression of transforming growth factor beta-1 (TGFB1) and CD40 ligand downregulate which enriches in the inflammatory associated pathway. Expression of signal transducer and activator of transcription 1-alpha/beta (STAT1) show upregulation and enrich in type I interferon signaling pathway and IL-27-mediated signaling pathway. In differentially malonylated proteins (DMPs) of pSS, we identify 3 proteins are down-regulated in 7 sites and 18 proteins are up-regulated in 19 sites. Expression of malonylated integrin-linked kinase (ILK) significantly enrich in the focal adhesion pathway. Together, our data provide evidence that downregulation of TGFB1 and CD40LG play a critical role in the inflammatory process of pSS, while upregulation of STAT1 may be associated with IL-27 immunity and pSS immune dysfunction. Moreover, kmal modification at the kinase domain of ILK may destabilize ILK that thus contributing to pSS pathogenies by regulating the focal adhesion pathway. SIGNIFICANCE: Our research offered the first characterization of Kmal, a newly identified form of lysine acylation in pSS, as well as proteomic data on individuals with pSS. In this study, we found that several key DMPs were associated with focal adhesion pathway, which contributes to the development of pSS. The present results provide an informative dataset for the future exploration of Kmal in pSS.

Machine learning-based intradialytic hypotension prediction of patients undergoing hemodialysis: A multicenter retrospective study.

BACKGROUND AND OBJECTIVE: Intradialytic hypotension (IDH) is closely associated with adverse clinical outcomes in HD-patients. An IDH predictor model is important for IDH risk screening and clinical decision-making. In this study, we used Machine learning (ML) to develop IDH model for risk prediction in HD patients. METHODS: 62,227 dialysis sessions were randomly partitioned into training data (70%), test data (20%), and validation data (10%). IDH-A model based on twenty-seven variables was constructed for risk prediction for the next HD treatment. IDH-B model based on ten variables from 64,870 dialysis sessions was developed for risk assessment before each HD treatment. Light Gradient Boosting Machine (LightGBM), Linear Discriminant Analysis, support vector machines, XGBoost, TabNet, and multilayer perceptron were used to develop the predictor model. RESULTS: In IDH-A model, we identified the LightGBM method as the best-performing and interpretable model with C- statistics of 0.82 in Fall30Nadir90 definitions, which was higher than those obtained using the other models (P<0.01). In other IDH standards of Nadir90, Nadir100, Fall20, Fall30, and Fall20Nadir90, the LightGBM method had a performance with C- statistics ranged 0.77 to 0.89. As a complementary application, the LightGBM model in IDH-B model achieved C- statistics of 0.68 in Fall30Nadir90 definitions and 0.69 to 0.78 in the other five IDH standards, which were also higher than the other methods, respectively. CONCLUSION: Use ML, we identified the LightGBM method as the good-performing and interpretable model. We identified the top variables as the high-risk factors for IDH incident in HD-patient. IDH-A and IDH-B model can usefully complement each other for risk prediction and further facilitate timely intervention through applied into different clinical setting.

The novel putative methyltransferase METTL7A as one prognostic biomarker potentially associated with immune infiltration in human renal cancer.

Among urological cancers, renal cancer has the highest fatality rate. In a previous pan-cancer study of the METTL family, we observed a stronger association between the METTL family members and the risk of renal cancer compared to other cancers. Among these members, METTL7A, a potential methyltransferase, was identified as a protective factor, although its role and mechanism in renal cancer remain unclear. In this study, we utilized public databases to examine the expression of METTL7A in renal cancer tissues and normal tissues and found that METTL7A expression was much lower in renal cancer tissues. We also noticed a link between low METTL7A expression and poor prognosis for patients. According to the results of our functional enrichment analysis, METTL7A may have a role in immunological functions in renal cancer. METTL7A expression was strongly linked with the degrees of immune cell infiltration and expression of numerous immunological components. METTL7A had significantly different effects on the survival times of renal cancer patients with high or low immune infiltration. Our findings suggest that METTL7A may be used as both a prognostic biomarker and an immunological target for kidney cancer. In conclusion, our study sheds light on the importance of METTL7A in renal cancer and emphasizes the potential of targeting METTL7A as a novel therapeutic strategy for kidney cancer.

Global-feature of autoimmune glomerulonephritis using proteomic analysis of laser capture microdissected glomeruli.

Background: IgA nephropathy (IgAN), (LN), membranous nephropathy (MN), and minimal change nephropathy (MCN) are all belonged to autoimmune glomerulonephritis. This study aimed to identify the specific proteomic characteristics of the four GNs diseases in order to provide frameworks for developing the appropriate drug for patients diagnosed with GNs disease. Methods: Liquid chromatography-tandem mass spectrometry (LC-MS/MS) was utilized to investigate proteomic features of glomerular tissues obtained by laser capture microdissection (LCM). 8 normal control cases, 11 IgAN cases, 19 LN cases, 5 MN cases, and 3 MCN cases in this study were selected for bioinformatics analyses. Results: The shared overlapping proteins among the top 100 DEPs of each GNs type were mostly downregulated, in which only FLII was significantly downregulated in the four GNs diseases. A2M was significantly upregulated in MN, IgAN, and LN subgroups. The pathway of complement and coagulation cascades was notably activated with NES value ranging 2.77 to 3.39 among MCN, MN, IgAN, and LN diseases, but the pattern of protein expression level were significantly different. In LN patients, the increased activity of complement and coagulation cascades was contributed by the high expression of multiple complements (C1QB, C3, C4A, C4B, C6, C8B, C8G, C9). Meanwhile, both C1QC and C4B were remarkably upregulated in MN patients. On the contrary, complement-regulating proteins (CD59) was substantially decreased in MCN and IgAN subgroup. Conclusions: The integrative proteomics analysis of the four GNs diseases provide insights into unique characteristics of GNs diseases and further serve as frameworks for precision medicine diagnosis and provide novel targets for drug development.

Correlation of Serum FGF23 and Chronic Kidney Disease-Mineral and Bone Abnormality Markers With Cardiac Structure Changes in Maintenance Hemodialysis Patients.

Background: CKD-MBD is a mineral and bone metabolism syndrome caused by chronic kidney disease. FGF23 is an important factor regulating phosphorus and is the main influencer in the CKD-MBD process. In this study, we observed the correlation among serum FGF23 and calcium, phosphorus and parathyroid hormone, and the correlation between FGF23 levels and cardiac structural changes in MHD patients. Methods: We examined serum FGF23 concentrations in 107 cases of MHD patients using the ELISA method, recorded demographic information and biochemical data, and analyzed the correlation between serum FGF23 levels and blood calcium and blood phosphorus and PTH levels. All patients were evaluated by cardiac color ultrasound, and we finally analyzed the association between the FGF23 level and cardiac structural changes. Results: In 107 cases of MHD patients, serum FGF23 levels were linearly associated with serum calcium (r = 0.27 P < 0.01) and parathyroid hormone levels (r = 0.25, P < 0.05). FGF 23 was negatively correlated with age (r = -0.44, P < 0.01).Serum FGF23 levels were correlated with right atrial hypertrophy in HD patients (P < 0.05). No correlation was found among FGF23, left ventricular hypertrophy/enlargement, and valve calcification stenosis (P > 0.05). Conclusion: Serum FGF23 showed a positive correlation among blood calcium levels and PTH levels in hemodialysis patients, and FGF23 levels can affect the incidence of right atrial hypertrophy in MHD patients.

Serum proteome and metabolome uncover novel biomarkers for the assessment of disease activity and diagnosing of systemic lupus erythematosus.

Systemic lupus erythematosus (SLE) is an autoimmune disease affecting thousands of people. There are still no effective biomarkers for SLE diagnosis and disease activity assessment. We performed proteomics and metabolomics analyses of serum from 121 SLE patients and 106 healthy individuals, and identified 90 proteins and 76 metabolites significantly changed. Several apolipoproteins and the metabolite arachidonic acid were significantly associated with disease activity. Apolipoprotein A-IV (APOA4), LysoPC(16:0), punicic acid and stearidonic acid were correlated with renal function. Random forest model using the significantly changed molecules identified 3 proteins including ATRN, THBS1 and SERPINC1, and 5 metabolites including cholesterol, palmitoleoylethanolamide, octadecanamide, palmitamide and linoleoylethanolamide, as potential biomarkers for SLE diagnosis. Those biomarkers were further validated in an independent cohort with high accuracy (AUC = 0.862 and 0.898 for protein and metabolite biomarkers respectively). This unbiased screening has led to the discovery of novel molecules for SLE disease activity assessment and SLE classification.

Serum metabolomics analysis reveals metabolite profile and key biomarkers of idiopathic membranous nephropathy.

Background: Idiopathic membranous nephropathy (IMN) is an organ-specific autoimmune disease with multiple and complex pathogenic mechanisms. Currently, renal biopsy is considered the gold standard for diagnosing membranous nephropathy. However, there were limitations to the renal puncture biopsy, such as the relatively high cost, longer time consuming, and the risk of invasive procedures. We investigated the profile of serum metabolites in IMN patients based on the UHPLC-QE-MS metabolomics technique for exploring the potential disease biomarkers and clinical implementation. Methods: In our research, we collected serum samples from healthy control (n = 15) and IMN patients (n = 25) to perform metabolomics analysis based on the UHPLC-QE-MS technique. Result: We identified 215 differentially expressed metabolites (DEMs) between the IMN and healthy control (HC) groups. Furthermore, these DEMs were significantly identified in histidine metabolism, arginine and proline metabolism, pyrimidine metabolism, purine metabolism, and steroid hormone biosynthesis. Several key DEMs were significantly correlated with the level of clinical parameters, such as serum albumin, IgG, UTP, and cholesterol. Among them, dehydroepiandrosterone sulfate (DHEAS) was considered the reliable diagnostic biomarker in the IMN group. There was an increased abundance of actinobacteria, phylum proteobacteria, and class gammaproteobacterial in IMN patients for host-microbiome origin analysis. Conclusion: Our study revealed the profiles of DEMs from the IMN and HC groups. The result demonstrated that there were disorders of amino acids, nucleotides, and steroids hormones metabolism in IMN patients. The down-regulation of DHEAS may be associated with the imbalance of the immune environment in IMN patients. In host-microbiome origin analysis, the gut microbiota and metabolite disturbances were present in IMN patients.

The characteristics of extrachromosomal circular DNA in patients with end-stage renal disease.

BACKGROUND: End-stage renal disease (ESRD) is the final stage of chronic kidney disease (CKD). In addition to the structurally intact chromosome genomic DNA, there is a double-stranded circular DNA called extrachromosomal circular DNA (eccDNA), which is thought to be involved in the epigenetic regulation of human disease. However, the features of eccDNA in ESRD patients are barely known. In this study, we identified eccDNA from ESRD patients and healthy people, as well as revealed the characteristics of eccDNA in patients with ESRD. METHODS: Using the high-throughput Circle-Sequencing technique, we examined the eccDNA in peripheral blood mononuclear cells (PBMCs) from healthy people (NC) (n = 12) and ESRD patients (n = 16). We analyzed the length distribution, genome elements, and motifs feature of eccDNA in ESRD patients. Then, after identifying the specific eccDNA in ESRD patients, we explored the potential functions of the target genes of the specific eccDNA. Finally, we investigated the probable hub eccDNA using algorithms. RESULTS: In total, 14,431 and 11,324 eccDNAs were found in the ESRD and NC groups, respectively, with sizes ranging from 0.01 kb to 60 kb at most. Additionally, the ESRD group had a greater distribution of eccDNA on chromosomes 4, 11, 13, and 20. In two groups, we also discovered several motifs of specific eccDNAs. Furthermore, we identified 13,715 specific eccDNAs in the ESRD group and 10,585 specific eccDNAs in the NC group, both of which were largely annotated as mRNA catalog. Pathway studies using Gene Ontology (GO) and the Kyoto Encyclopedia of Genes and Genomes (KEGG) showed that the specific eccDNA in ESRD was markedly enriched in cell junction and communication pathways. Furthermore, we identified potentially 20 hub eccDNA-targeting genes from all ESRD-specific eccDNA-targeting genes. Also, we found that 39 eccDNA-targeting genes were associated with ESRD, and some of these eccDNAs may be related to the pathogenesis of ESRD. CONCLUSIONS: Our findings revealed the characteristics of eccDNA in ESRD patients and discovered potentially hub and ESRD-relevant eccDNA-targeting genes, suggesting a novel probable mechanism of ESRD.

Renoprotective effects of empagliflozin are linked to activation of the tubuloglomerular feedback mechanism and blunting of the complement system.

The mechanisms of nephroprotection in nondiabetic chronic kidney disease (CKD) models by sodium-glucose cotransporter 2 (SGLT2) inhibitors are not well defined. Five groups were established: sham-operated rats, placebo-treated rats with 5/6 nephrectomy (5/6Nx), 5/6Nx + telmisartan (5 mg/kg/day), 5/6Nx + empagliflozin (3 mg/kg/day), and 5/6Nx + empagliflozin (15 mg/kg/day). Treatment duration was 95 days. Empagliflozin showed a dose-dependent beneficial effect on the change from baseline of creatinine clearance (Ccr). The urinary albumin-to-creatinine ratio likewise improved in a dose-dependent manner. Both dosages of empagliflozin improved morphological kidney damage parameters such as renal interstitial fibrosis and glomerulosclerosis. 5/6 nephrectomy led to a substantial reduction of urinary adenosine excretion, a surrogate parameter of the tubuloglomerular feedback (TGF) mechanism. Empagliflozin caused a dose-dependent increase in urinary adenosine excretion. The urinary adenosine excretion was negatively correlated with renal interstitial fibrosis and positively correlated with Ccr. Immunofluorescence analysis revealed that empagliflozin had no effect on CD8+ and CD4+ T cells as well as on CD68+ cells (macrophages). To further explore potential mechanisms, a nonhypothesis-driven approach was used. RNA sequencing followed by quantitative real-time polymerase chain reaction revealed that complement component 1Q subcomponent A chain (C1QA) as well as complement component 1Q subcomponent C chain (C1QC) gene expression were upregulated in the placebo-treated 5/6Nx rats and this upregulation was blunted by treatment with empagliflozin. In conclusion, empagliflozin-mediated nephroprotection in nondiabetic CKD is due to a dose-dependent activation of the TGF as well as empagliflozin-mediated effects on the complement system.

Metabolic Engineering of Microorganisms to Produce Pyruvate and Derived Compounds.

Pyruvate is a hub of various endogenous metabolic pathways, including glycolysis, TCA cycle, amino acid, and fatty acid biosynthesis. It has also been used as a precursor for pyruvate-derived compounds such as acetoin, 2,3-butanediol (2,3-BD), butanol, butyrate, and L-alanine biosynthesis. Pyruvate and derivatives are widely utilized in food, pharmaceuticals, pesticides, feed additives, and bioenergy industries. However, compounds such as pyruvate, acetoin, and butanol are often chemically synthesized from fossil feedstocks, resulting in declining fossil fuels and increasing environmental pollution. Metabolic engineering is a powerful tool for producing eco-friendly chemicals from renewable biomass resources through microbial fermentation. Here, we review and systematically summarize recent advances in the biosynthesis pathways, regulatory mechanisms, and metabolic engineering strategies for pyruvate and derivatives. Furthermore, the establishment of sustainable industrial synthesis platforms based on alternative substrates and new tools to produce these compounds is elaborated. Finally, we discuss the potential difficulties in the current metabolic engineering of pyruvate and derivatives and promising strategies for constructing efficient producers.

Urine metabolomics reveals biomarkers and the underlying pathogenesis of diabetic kidney disease.

PURPOSE: Diabetic kidney disease (DKD) is the most common complication of type 2 diabetes mellitus (T2DM), and its pathogenesis is not yet fully understood and lacks noninvasive and effective diagnostic biomarkers. In this study, we performed urine metabolomics to identify biomarkers for DKD and to clarify the potential mechanisms associated with disease progression. METHODS: We applied a liquid chromatography-mass spectrometry-based metabolomics method combined with bioinformatics analysis to investigate the urine metabolism characteristics of 79 participants, including healthy subjects (n = 20), T2DM patients (n = 20), 39 DKD patients that included 19 DKD with microalbuminuria (DKD + micro) and 20 DKD with macroalbuminuria (DKD + macro). RESULTS: Seventeen metabolites were identified between T2DM and DKD that were involved in amino acid, purine, nucleotide and primarily bile acid metabolism. Ultimately, a combined model consisting of 2 metabolites (tyramine and phenylalanylproline) was established, which had optimal diagnostic performance (area under the curve (AUC) = 0.94). We also identified 19 metabolites that were co-expressed within the DKD groups and 41 metabolites specifically expressed in the DKD + macro group. Ingenuity pathway analysis revealed three interaction networks of these 60 metabolites, involving the sirtuin signaling pathway and ferroptosis signaling pathway, as well as the downregulation of organic anion transporter 1, which may be important mechanisms that mediate the progression of DKD. CONCLUSIONS: This work reveals the metabolic alterations in T2DM and DKD, constructs a combined model to distinguish them and delivers a novel strategy for studying the underlying mechanism and treatment of DKD.