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Agoro R, Myslinski J, Marambio YG, Janosevic D, Jennings KN, Liu S, Hibbard LM, Fang F, Ni P, Noonan ML, Solis E, Chu X, Wang Y, Dagher PC, Liu Y, Wan J, Hato T, White KE. Dynamic Single Cell Transcriptomics Defines Kidney FGF23/KL Bioactivity and Novel Segment-Specific Inflammatory Targets. BIORXIV : THE PREPRINT SERVER FOR BIOLOGY 2024:2024.05.24.595014. [PMID: 38853876 PMCID: PMC11160572 DOI: 10.1101/2024.05.24.595014] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Grants] [Track Full Text] [Subscribe] [Scholar Register] [Indexed: 06/11/2024]
Abstract
FGF23 via its coreceptor αKlotho (KL) provides critical control of phosphate metabolism, which is altered in rare and very common syndromes, however the spatial-temporal mechanisms dictating renal FGF23 functions remain poorly understood. Thus, developing approaches to modify specific FGF23-dictated pathways has proven problematic. Herein, wild type mice were injected with rFGF23 for 1, 4 and 12h and renal FGF23 bioactivity was determined at single cell resolution. Computational analysis identified distinct epithelial, endothelial, stromal, and immune cell clusters, with differential expressional analysis uniquely tracking FGF23 bioactivity at each time point. FGF23 actions were sex independent but critically relied upon constitutive KL expression mapped within proximal tubule (S1-S3) and distal tubule (DCT/CNT) cell sub-populations. Temporal KL-dependent FGF23 responses drove unique and transient cellular identities, including genes in key MAPK- and vitamin D-metabolic pathways via early- (AP-1-related) and late-phase (EIF2 signaling) transcriptional regulons. Combining ATACseq/RNAseq data from a cell line stably expressing KL with the in vivo scRNAseq pinpointed genomic accessibility changes in MAPK-dependent genes, including the identification of FGF23-dependent EGR1 distal enhancers. Finally, we isolated unexpected crosstalk between FGF23-mediated MAPK signaling and pro-inflammatory TNF receptor activation via NF-κB, which blocked FGF23 bioactivity in vitro and in vivo . Collectively, our findings have uncovered novel pathways at the single cell level that likely influence FGF23-dependent disease mechanisms. Translational statement Inflammation and elevated FGF23 in chronic kidney disease (CKD) are both associated with poor patient outcomes and mortality. However, the links between these manifestations and the effects of inflammation on FGF23-mediated mineral metabolism within specific nephron segments remain unclear. Herein, we isolated an inflammatory pathway driven by TNF/NF-κB associated with regulating FGF23 bioactivity. The findings from this study could be important in designing future therapeutic approaches for chronic mineral diseases, including potential combination therapies or early intervention strategies. We also suggest that further studies could explore these pathways at the single cell level in CKD models, as well as test translation of our findings to interactions of chronic inflammation and elevated FGF23 in human CKD kidney datasets.
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Fu Y, Xiang Y, Zha J, Chen G, Dong Z. Enhanced STAT3/PIK3R1/mTOR signaling triggers tubular cell inflammation and apoptosis in septic-induced acute kidney injury: implications for therapeutic intervention. Clin Sci (Lond) 2024; 138:351-369. [PMID: 38411015 DOI: 10.1042/cs20240059] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 01/10/2024] [Revised: 02/20/2024] [Accepted: 02/26/2024] [Indexed: 02/28/2024]
Abstract
Septic acute kidney injury (AKI) is a severe form of renal dysfunction associated with high morbidity and mortality rates. However, the pathophysiological mechanisms underlying septic AKI remain incompletely understood. Herein, we investigated the signaling pathways involved in septic AKI using the mouse models of lipopolysaccharide (LPS) treatment and cecal ligation and puncture (CLP). In these models, renal inflammation and tubular cell apoptosis were accompanied by the aberrant activation of the mechanistic target of rapamycin (mTOR) and the signal transducer and activator of transcription 3 (STAT3) signaling pathways. Pharmacological inhibition of either mTOR or STAT3 significantly improved renal function and reduced apoptosis and inflammation. Interestingly, inhibition of STAT3 with pharmacological inhibitors or small interfering RNA blocked LPS-induced mTOR activation in renal tubular cells, indicating a role of STAT3 in mTOR activation. Moreover, knockdown of STAT3 reduced the expression of the phosphoinositide-3-kinase regulatory subunit 1 (PIK3R1/p85α), a key subunit of the phosphatidylinositol 3-kinase for AKT and mTOR activation. Chromatin immunoprecipitation assay also proved the binding of STAT3 to PIK3R1 gene promoter in LPS-treated kidney tubular cells. In addition, knockdown of PIK3R1 suppressed mTOR activation during LPS treatment. These findings highlight the dysregulation of mTOR and STAT3 pathways as critical mechanisms underlying the inflammatory and apoptotic phenotypes observed in renal tubular cells during septic AKI, suggesting the STAT3/ PIK3R1/mTOR pathway as a therapeutic target of septic AKI.
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Affiliation(s)
- Ying Fu
- Department of Nephrology, Hunan Key Laboratory of Kidney Disease and Blood Purification, The Second Xiangya Hospital of Central South University, Changsha 410011, China
| | - Yu Xiang
- Department of Nephrology, Hunan Key Laboratory of Kidney Disease and Blood Purification, The Second Xiangya Hospital of Central South University, Changsha 410011, China
| | - Jie Zha
- Department of Nephrology, Hunan Key Laboratory of Kidney Disease and Blood Purification, The Second Xiangya Hospital of Central South University, Changsha 410011, China
| | - Guochun Chen
- Department of Nephrology, Hunan Key Laboratory of Kidney Disease and Blood Purification, The Second Xiangya Hospital of Central South University, Changsha 410011, China
| | - Zheng Dong
- Department of Nephrology, Hunan Key Laboratory of Kidney Disease and Blood Purification, The Second Xiangya Hospital of Central South University, Changsha 410011, China
- Department of Cellular Biology and Anatomy, Medical College of Georgia at Augusta University and Charlie Norwood VA Medical Center, Augusta, GA, U.S.A
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Liu T, Li X, Pang M, Wang L, Li Y, Sun X. Machine learning-based endoplasmic reticulum-related diagnostic biomarker and immune microenvironment landscape for osteoarthritis. Aging (Albany NY) 2024; 16:4563-4578. [PMID: 38428406 PMCID: PMC10968715 DOI: 10.18632/aging.205611] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 10/13/2023] [Accepted: 01/23/2024] [Indexed: 03/03/2024]
Abstract
BACKGROUND Osteoarthritis (OA) is the most common degenerative joint disease worldwide. Further improving the current limited understanding of osteoarthritis has positive clinical value. METHODS OA samples were collected from GEO database and endoplasmic reticulum related genes (ERRGs) were identified. The WGCNA network was further built to identify the crucial gene module. Based on the expression profiles of characteristic ERRGs, LASSO algorithm was used to select key factors according to the minimum λ value. Random forest (RF) algorithm was used to calculate the importance of ERRGs. Subsequently, overlapping genes based on LASSO and RF algorithms were identified as ERRGs-related diagnostic biomarkers. In addition, OA specimens were also collected and performed qRT-PCR quantitative analysis of selected ERRGs. RESULTS We identified four ERRGs associated with OA risk assessment through machine learning methods, and verified the abnormal expressions of these screened markers in OA patients through in vitro experiments. The influence of selected markers on OA immune infiltration was also evaluated. CONCLUSIONS Our results provide new evidence for the role of ER stress in the OA progression, as well as new markers and potential intervention targets for OA.
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Affiliation(s)
- Tingting Liu
- Research Center for Drug Safety Evaluation of Hainan, Hainan Medical University, Haikou, Hainan 571199, China
| | - Xiaomao Li
- Jiangsu Food and Pharmaceutical Science College, Huaian, Jiangsu 223023, China
| | - Mu Pang
- The Fourth Clinical Medical College of Guangzhou University of Chinese Medicine (Shenzhen Traditional Chinese Medicine Hospital), Shenzhen, Guangdong 518000, China
| | - Lifen Wang
- Research Center for Drug Safety Evaluation of Hainan, Hainan Medical University, Haikou, Hainan 571199, China
| | - Ye Li
- Chongqing Three Gorges Medical College, Chongqing 404120, China
| | - Xizhe Sun
- Research Center for Drug Safety Evaluation of Hainan, Hainan Medical University, Haikou, Hainan 571199, China
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Gisch DL, Brennan M, Lake BB, Basta J, Keller MS, Melo Ferreira R, Akilesh S, Ghag R, Lu C, Cheng YH, Collins KS, Parikh SV, Rovin BH, Robbins L, Stout L, Conklin KY, Diep D, Zhang B, Knoten A, Barwinska D, Asghari M, Sabo AR, Ferkowicz MJ, Sutton TA, Kelly KJ, De Boer IH, Rosas SE, Kiryluk K, Hodgin JB, Alakwaa F, Winfree S, Jefferson N, Türkmen A, Gaut JP, Gehlenborg N, Phillips CL, El-Achkar TM, Dagher PC, Hato T, Zhang K, Himmelfarb J, Kretzler M, Mollah S, Jain S, Rauchman M, Eadon MT. The chromatin landscape of healthy and injured cell types in the human kidney. Nat Commun 2024; 15:433. [PMID: 38199997 PMCID: PMC10781985 DOI: 10.1038/s41467-023-44467-6] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 06/15/2023] [Accepted: 12/14/2023] [Indexed: 01/12/2024] Open
Abstract
There is a need to define regions of gene activation or repression that control human kidney cells in states of health, injury, and repair to understand the molecular pathogenesis of kidney disease and design therapeutic strategies. Comprehensive integration of gene expression with epigenetic features that define regulatory elements remains a significant challenge. We measure dual single nucleus RNA expression and chromatin accessibility, DNA methylation, and H3K27ac, H3K4me1, H3K4me3, and H3K27me3 histone modifications to decipher the chromatin landscape and gene regulation of the kidney in reference and adaptive injury states. We establish a spatially-anchored epigenomic atlas to define the kidney's active, silent, and regulatory accessible chromatin regions across the genome. Using this atlas, we note distinct control of adaptive injury in different epithelial cell types. A proximal tubule cell transcription factor network of ELF3, KLF6, and KLF10 regulates the transition between health and injury, while in thick ascending limb cells this transition is regulated by NR2F1. Further, combined perturbation of ELF3, KLF6, and KLF10 distinguishes two adaptive proximal tubular cell subtypes, one of which manifested a repair trajectory after knockout. This atlas will serve as a foundation to facilitate targeted cell-specific therapeutics by reprogramming gene regulatory networks.
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Affiliation(s)
- Debora L Gisch
- Indiana University School of Medicine, Indianapolis, IN, 46202, USA
| | | | - Blue B Lake
- Department of Bioengineering, University of California, San Diego, La Jolla, CA, USA
- San Diego Institute of Science, Altos Labs, San Diego, CA, USA
| | - Jeannine Basta
- Washington University in Saint Louis, St. Louis, MO, 63103, USA
| | | | | | | | - Reetika Ghag
- Washington University in Saint Louis, St. Louis, MO, 63103, USA
| | - Charles Lu
- Washington University in Saint Louis, St. Louis, MO, 63103, USA
| | - Ying-Hua Cheng
- Indiana University School of Medicine, Indianapolis, IN, 46202, USA
| | | | - Samir V Parikh
- Ohio State University Wexner Medical Center, Columbus, OH, 43210, USA
| | - Brad H Rovin
- Ohio State University Wexner Medical Center, Columbus, OH, 43210, USA
| | - Lynn Robbins
- St. Louis Veteran Affairs Medical Center, St. Louis, MO, 63106, USA
| | - Lisa Stout
- Washington University in Saint Louis, St. Louis, MO, 63103, USA
| | - Kimberly Y Conklin
- Department of Bioengineering, University of California, San Diego, La Jolla, CA, USA
| | - Dinh Diep
- Department of Bioengineering, University of California, San Diego, La Jolla, CA, USA
| | - Bo Zhang
- Washington University in Saint Louis, St. Louis, MO, 63103, USA
| | - Amanda Knoten
- Washington University in Saint Louis, St. Louis, MO, 63103, USA
| | - Daria Barwinska
- Indiana University School of Medicine, Indianapolis, IN, 46202, USA
| | - Mahla Asghari
- Indiana University School of Medicine, Indianapolis, IN, 46202, USA
| | - Angela R Sabo
- Indiana University School of Medicine, Indianapolis, IN, 46202, USA
| | | | - Timothy A Sutton
- Indiana University School of Medicine, Indianapolis, IN, 46202, USA
| | | | | | - Sylvia E Rosas
- Joslin Diabetes Center, Harvard Medical School, Boston, MA, 02215, USA
| | | | | | | | - Seth Winfree
- University of Nebraska Medical Center, Omaha, NE, 68198, USA
| | - Nichole Jefferson
- Kidney Precision Medicine Project Community Engagement Committee, Dallas, TX, USA
| | - Aydın Türkmen
- Istanbul School of Medicine, Division of Nephrology, Istanbul, Turkey
| | - Joseph P Gaut
- Department of Bioengineering, University of California, San Diego, La Jolla, CA, USA
| | | | | | | | - Pierre C Dagher
- Indiana University School of Medicine, Indianapolis, IN, 46202, USA
| | - Takashi Hato
- Indiana University School of Medicine, Indianapolis, IN, 46202, USA
| | - Kun Zhang
- Department of Bioengineering, University of California, San Diego, La Jolla, CA, USA
| | | | | | - Shamim Mollah
- Washington University in Saint Louis, St. Louis, MO, 63103, USA
| | - Sanjay Jain
- Washington University in Saint Louis, St. Louis, MO, 63103, USA.
| | - Michael Rauchman
- Washington University in Saint Louis, St. Louis, MO, 63103, USA.
| | - Michael T Eadon
- Indiana University School of Medicine, Indianapolis, IN, 46202, USA.
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Heruye S, Myslinski J, Zeng C, Zollman A, Makino S, Nanamatsu A, Mir Q, Janga SC, Doud EH, Eadon MT, Maier B, Hamada M, Tran TM, Dagher PC, Hato T. Inflammation primes the kidney for recovery by activating AZIN1 A-to-I editing. BIORXIV : THE PREPRINT SERVER FOR BIOLOGY 2023:2023.11.09.566426. [PMID: 37986799 PMCID: PMC10659426 DOI: 10.1101/2023.11.09.566426] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Grants] [Track Full Text] [Subscribe] [Scholar Register] [Indexed: 11/22/2023]
Abstract
The progression of kidney disease varies among individuals, but a general methodology to quantify disease timelines is lacking. Particularly challenging is the task of determining the potential for recovery from acute kidney injury following various insults. Here, we report that quantitation of post-transcriptional adenosine-to-inosine (A-to-I) RNA editing offers a distinct genome-wide signature, enabling the delineation of disease trajectories in the kidney. A well-defined murine model of endotoxemia permitted the identification of the origin and extent of A-to-I editing, along with temporally discrete signatures of double-stranded RNA stress and Adenosine Deaminase isoform switching. We found that A-to-I editing of Antizyme Inhibitor 1 (AZIN1), a positive regulator of polyamine biosynthesis, serves as a particularly useful temporal landmark during endotoxemia. Our data indicate that AZIN1 A-to-I editing, triggered by preceding inflammation, primes the kidney and activates endogenous recovery mechanisms. By comparing genetically modified human cell lines and mice locked in either A-to-I edited or uneditable states, we uncovered that AZIN1 A-to-I editing not only enhances polyamine biosynthesis but also engages glycolysis and nicotinamide biosynthesis to drive the recovery phenotype. Our findings implicate that quantifying AZIN1 A-to-I editing could potentially identify individuals who have transitioned to an endogenous recovery phase. This phase would reflect their past inflammation and indicate their potential for future recovery.
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Affiliation(s)
- Segewkal Heruye
- Department of Medicine, Indiana University School of Medicine
| | - Jered Myslinski
- Department of Medicine, Indiana University School of Medicine
| | - Chao Zeng
- Faculty of Science and Engineering, Waseda University, Tokyo
| | - Amy Zollman
- Department of Medicine, Indiana University School of Medicine
| | - Shinichi Makino
- Department of Medicine, Indiana University School of Medicine
| | - Azuma Nanamatsu
- Department of Medicine, Indiana University School of Medicine
| | - Quoseena Mir
- Luddy School of Informatics, Computing, and Engineering, Indiana University
| | | | - Emma H Doud
- Department of Biochemistry and Molecular Biology, Indiana University School of Medicine
| | - Michael T Eadon
- Department of Medicine, Indiana University School of Medicine
| | - Bernhard Maier
- Department of Medicine, Indiana University School of Medicine
| | - Michiaki Hamada
- Faculty of Science and Engineering, Waseda University, Tokyo
- AIST-Waseda University Computational Bio Big-Data Open Innovation Laboratory, National Institute of Advanced Industrial Science and Technology, Tokyo
- Graduate School of Medicine, Nippon Medical School, Tokyo
| | - Tuan M Tran
- Department of Medicine, Indiana University School of Medicine
- Richard L. Roudebush Veterans Affairs Medical Center, Indianapolis
| | - Pierre C Dagher
- Department of Medicine, Indiana University School of Medicine
| | - Takashi Hato
- Department of Medicine, Indiana University School of Medicine
- Richard L. Roudebush Veterans Affairs Medical Center, Indianapolis
- Department of Medical and Molecular Genetics, Indiana University School of Medicine
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6
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Gisch DL, Brennan M, Lake BB, Basta J, Keller M, Ferreira RM, Akilesh S, Ghag R, Lu C, Cheng YH, Collins KS, Parikh SV, Rovin BH, Robbins L, Conklin KY, Diep D, Zhang B, Knoten A, Barwinska D, Asghari M, Sabo AR, Ferkowicz MJ, Sutton TA, Kelly KJ, Boer IHD, Rosas SE, Kiryluk K, Hodgin JB, Alakwaa F, Jefferson N, Gaut JP, Gehlenborg N, Phillips CL, El-Achkar TM, Dagher PC, Hato T, Zhang K, Himmelfarb J, Kretzler M, Mollah S, Jain S, Rauchman M, Eadon MT. The chromatin landscape of healthy and injured cell types in the human kidney. BIORXIV : THE PREPRINT SERVER FOR BIOLOGY 2023:2023.06.07.543965. [PMID: 37333123 PMCID: PMC10274789 DOI: 10.1101/2023.06.07.543965] [Citation(s) in RCA: 3] [Impact Index Per Article: 3.0] [Reference Citation Analysis] [Abstract] [Track Full Text] [Subscribe] [Scholar Register] [Indexed: 06/20/2023]
Abstract
There is a need to define regions of gene activation or repression that control human kidney cells in states of health, injury, and repair to understand the molecular pathogenesis of kidney disease and design therapeutic strategies. However, comprehensive integration of gene expression with epigenetic features that define regulatory elements remains a significant challenge. We measured dual single nucleus RNA expression and chromatin accessibility, DNA methylation, and H3K27ac, H3K4me1, H3K4me3, and H3K27me3 histone modifications to decipher the chromatin landscape and gene regulation of the kidney in reference and adaptive injury states. We established a comprehensive and spatially-anchored epigenomic atlas to define the kidney's active, silent, and regulatory accessible chromatin regions across the genome. Using this atlas, we noted distinct control of adaptive injury in different epithelial cell types. A proximal tubule cell transcription factor network of ELF3 , KLF6 , and KLF10 regulated the transition between health and injury, while in thick ascending limb cells this transition was regulated by NR2F1 . Further, combined perturbation of ELF3 , KLF6 , and KLF10 distinguished two adaptive proximal tubular cell subtypes, one of which manifested a repair trajectory after knockout. This atlas will serve as a foundation to facilitate targeted cell-specific therapeutics by reprogramming gene regulatory networks.
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