Browsing by Author "Dagher, Pierre C."
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Item A multimodal and integrated approach to interrogate human kidney biopsies with rigor and reproducibility: guidelines from the Kidney Precision Medicine Project(American Physiological Society, 2021) El-Achkar, Tarek M.; Eadon, Michael T.; Menon, Rajasree; Lake, Blue B.; Sigdel, Tara K.; Alexandrov, Theodore; Parikh, Samir; Zhang, Guanshi; Dobi, Dejan; Dunn, Kenneth W.; Otto, Edgar A.; Anderton, Christopher R.; Carson, Jonas M.; Luo, Jinghui; Park, Chris; Hamidi, Habib; Zhou, Jian; Hoover, Paul; Schroeder, Andrew; Joanes, Marianinha; Azeloglu, Evren U.; Sealfon, Rachel; Winfree, Seth; Steck, Becky; He, Yongqun; D’Agati, Vivette; Iyengar, Ravi; Troyanskaya, Olga G.; Barisoni, Laura; Gaut, Joseph; Zhang, Kun; Laszik, Zoltan; Rovin, Brad H.; Dagher, Pierre C.; Sharma, Kumar; Sarwal, Minnie M.; Hodgin, Jeffrey B.; Alpers, Charles E.; Kretzler, Matthias; Jain, Sanjay; Medicine, School of MedicineComprehensive and spatially mapped molecular atlases of organs at a cellular level are a critical resource to gain insights into pathogenic mechanisms and personalized therapies for diseases. The Kidney Precision Medicine Project (KPMP) is an endeavor to generate three-dimensional (3-D) molecular atlases of healthy and diseased kidney biopsies by using multiple state-of-the-art omics and imaging technologies across several institutions. Obtaining rigorous and reproducible results from disparate methods and at different sites to interrogate biomolecules at a single-cell level or in 3-D space is a significant challenge that can be a futile exercise if not well controlled. We describe a “follow the tissue” pipeline for generating a reliable and authentic single-cell/region 3-D molecular atlas of human adult kidney. Our approach emphasizes quality assurance, quality control, validation, and harmonization across different omics and imaging technologies from sample procurement, processing, storage, shipping to data generation, analysis, and sharing. We established benchmarks for quality control, rigor, reproducibility, and feasibility across multiple technologies through a pilot experiment using common source tissue that was processed and analyzed at different institutions and different technologies. A peer review system was established to critically review quality control measures and the reproducibility of data generated by each technology before their being approved to interrogate clinical biopsy specimens. The process established economizes the use of valuable biopsy tissue for multiomics and imaging analysis with stringent quality control to ensure rigor and reproducibility of results and serves as a model for precision medicine projects across laboratories, institutions and consortia.Item Alterations in Protein Translation and Carboxylic Acid Catabolic Processes in Diabetic Kidney Disease(MDPI, 2022-03-30) Collins, Kimberly S.; Eadon, Michael T.; Cheng, Ying-Hua; Barwinska, Daria; Ferreira, Ricardo Melo; McCarthy, Thomas W.; Janosevic, Danielle; Syed, Farooq; Maier, Bernhard; El-Achkar, Tarek M.; Kelly, Katherine J.; Phillips, Carrie L.; Hato, Takashi; Sutton, Timothy A.; Dagher, Pierre C.; Medicine, School of MedicineDiabetic kidney disease (DKD) remains the leading cause of end-stage kidney disease despite decades of study. Alterations in the glomerulus and kidney tubules both contribute to the pathogenesis of DKD although the majority of investigative efforts have focused on the glomerulus. We sought to examine the differential expression signature of human DKD in the glomerulus and proximal tubule and corroborate our findings in the db/db mouse model of diabetes. A transcriptogram network analysis of RNAseq data from laser microdissected (LMD) human glomerulus and proximal tubule of DKD and reference nephrectomy samples revealed enriched pathways including rhodopsin-like receptors, olfactory signaling, and ribosome (protein translation) in the proximal tubule of human DKD biopsy samples. The translation pathway was also enriched in the glomerulus. Increased translation in diabetic kidneys was validated using polyribosomal profiling in the db/db mouse model of diabetes. Using single nuclear RNA sequencing (snRNAseq) of kidneys from db/db mice, we prioritized additional pathways identified in human DKD. The top overlapping pathway identified in the murine snRNAseq proximal tubule clusters and the human LMD proximal tubule compartment was carboxylic acid catabolism. Using ultra-performance liquid chromatography-mass spectrometry, the fatty acid catabolism pathway was also found to be dysregulated in the db/db mouse model. The Acetyl-CoA metabolite was down-regulated in db/db mice, aligning with the human differential expression of the genes ACOX1 and ACACB. In summary, our findings demonstrate that proximal tubular alterations in protein translation and carboxylic acid catabolism are key features in both human and murine DKD.Item An atlas of healthy and injured cell states and niches in the human kidney(Springer Nature, 2023) Lake, Blue B.; Menon, Rajasree; Winfree, Seth; Hu, Qiwen; Ferreira, Ricardo Melo; Kalhor, Kian; Barwinska, Daria; Otto, Edgar A.; Ferkowicz, Michael; Diep, Dinh; Plongthongkum, Nongluk; Knoten, Amanda; Urata, Sarah; Mariani, Laura H.; Naik, Abhijit S.; Eddy, Sean; Zhang, Bo; Wu, Yan; Salamon, Diane; Williams, James C.; Wang, Xin; Balderrama, Karol S.; Hoover, Paul J.; Murray, Evan; Marshall, Jamie L.; Noel, Teia; Vijayan, Anitha; Hartman, Austin; Chen, Fei; Waikar, Sushrut S.; Rosas, Sylvia E.; Wilson, Francis P.; Palevsky, Paul M.; Kiryluk, Krzysztof; Sedor, John R.; Toto, Robert D.; Parikh, Chirag R.; Kim, Eric H.; Satija, Rahul; Greka, Anna; Macosko, Evan Z.; Kharchenko, Peter V.; Gaut, Joseph P.; Hodgin, Jeffrey B.; KPMP Consortium; Eadon, Michael T.; Dagher, Pierre C.; El-Achkar, Tarek M.; Zhang, Kun; Kretzler, Matthias; Jain, Sanjay; Medicine, School of MedicineUnderstanding kidney disease relies on defining the complexity of cell types and states, their associated molecular profiles and interactions within tissue neighbourhoods1. Here we applied multiple single-cell and single-nucleus assays (>400,000 nuclei or cells) and spatial imaging technologies to a broad spectrum of healthy reference kidneys (45 donors) and diseased kidneys (48 patients). This has provided a high-resolution cellular atlas of 51 main cell types, which include rare and previously undescribed cell populations. The multi-omic approach provides detailed transcriptomic profiles, regulatory factors and spatial localizations spanning the entire kidney. We also define 28 cellular states across nephron segments and interstitium that were altered in kidney injury, encompassing cycling, adaptive (successful or maladaptive repair), transitioning and degenerative states. Molecular signatures permitted the localization of these states within injury neighbourhoods using spatial transcriptomics, while large-scale 3D imaging analysis (around 1.2 million neighbourhoods) provided corresponding linkages to active immune responses. These analyses defined biological pathways that are relevant to injury time-course and niches, including signatures underlying epithelial repair that predicted maladaptive states associated with a decline in kidney function. This integrated multimodal spatial cell atlas of healthy and diseased human kidneys represents a comprehensive benchmark of cellular states, neighbourhoods, outcome-associated signatures and publicly available interactive visualizations.Item Application of Laser Microdissection to Uncover Regional Transcriptomics in Human Kidney Tissue(MyJove Corporation, 2020-06-09) Barwinska, Daria; Ferkowicz, Michael J.; Cheng, Ying-Hua; Winfree, Seth; Dunn, Kenneth W.; Kelly, Katherine J.; Sutton, Timothy A.; Rovin, Brad H.; Parikh, Samir V.; Phillips, Carrie L.; Dagher, Pierre C.; El-Achkar, Tarek M.; Eadon, Michael T.; Medicine, School of MedicineGene expression analysis of human kidney tissue is an important tool to understand homeostasis and disease pathophysiology. Increasing the resolution and depth of this technology and extending it to the level of cells within the tissue is needed. Although the use of single nuclear and single cell RNA sequencing has become widespread, the expression signatures of cells obtained from tissue dissociation do not maintain spatial context. Laser microdissection (LMD) based on specific fluorescent markers would allow the isolation of specific structures and cell groups of interest with known localization, thereby enabling the acquisition of spatially-anchored transcriptomic signatures in kidney tissue. We have optimized an LMD methodology, guided by a rapid fluorescence-based stain, to isolate five distinct compartments within the human kidney and conduct subsequent RNA sequencing from valuable human kidney tissue specimens. We also present quality control parameters to enable the assessment of adequacy of the collected specimens. The workflow outlined in this manuscript shows the feasibility of this approach to isolate sub-segmental transcriptomic signatures with high confidence. The methodological approach presented here may also be applied to other tissue types with substitution of relevant antibody markers.Item Automatic segmentation of intravital fluorescence microscopy images by K-means clustering of FLIM phasors(OSA, 2019-08) Zhang, Yide; Hato, Takashi; Dagher, Pierre C.; Nichols, Evan L.; Smith, Cody J.; Dunn, Kenneth W.; Howard, Scott S.; Medicine, School of MedicineFluorescence lifetime imaging microscopy (FLIM) provides additional contrast for fluorophores with overlapping emission spectra. The phasor approach to FLIM greatly reduces the complexity of FLIM analysis and enables a useful image segmentation technique by selecting adjacent phasor points and labeling their corresponding pixels with different colors. This phasor labeling process, however, is empirical and could lead to biased results. In this Letter, we present a novel and unbiased approach to automate the phasor labeling process using an unsupervised machine learning technique, i.e., K-means clustering. In addition, we provide an open-source, user-friendly program that enables users to easily employ the proposed approach. We demonstrate successful image segmentation on 2D and 3D FLIM images of fixed cells and living animals acquired with two different FLIM systems. Finally, we evaluate how different parameters affect the segmentation result and provide a guideline for users to achieve optimal performance.Item Bacterial sepsis triggers an antiviral response that causes translation shutdown(American Society for Clinical Investigation, 2019-01-02) Hato, Takashi; Maier, Bernhard; Syed, Farooq; Myslinski, Jered; Zollman, Amy; Plotkin, Zoya; Eadon, Michael T.; Dagher, Pierre C.; Medicine, School of MedicineIn response to viral pathogens, the host upregulates antiviral genes that suppress translation of viral mRNAs. However, induction of such antiviral responses may not be exclusive to viruses, as the pathways lie at the intersection of broad inflammatory networks that can also be induced by bacterial pathogens. Using a model of Gram-negative sepsis, we show that propagation of kidney damage initiated by a bacterial origin ultimately involves antiviral responses that result in host translation shutdown. We determined that activation of the eukaryotic translation initiation factor 2-α kinase 2/eukaryotic translation initiation factor 2α (Eif2ak2/Eif2α) axis is the key mediator of translation initiation block in late-phase sepsis. Reversal of this axis mitigated kidney injury. Furthermore, temporal profiling of the kidney translatome revealed that multiple genes involved in formation of the initiation complex were translationally altered during bacterial sepsis. Collectively, our findings imply that translation shutdown is indifferent to the specific initiating pathogen and is an important determinant of tissue injury in sepsis.Item Cellular and Molecular Interrogation of Kidney Biopsy Specimens(Wolters Kluwer, 2022) Eadon, Michael T.; Dagher, Pierre C.; El-Achkar, Tarek M.; Medicine, School of MedicinePurpose of review: Traditional histopathology of the kidney biopsy specimen has been an essential and successful tool for the diagnosis and staging of kidney diseases. However, it is likely that the full potential of the kidney biopsy has not been tapped so far. Indeed, there is now a concerted worldwide effort to interrogate kidney biopsy samples at the cellular and molecular levels with unprecedented rigor and depth. This review examines these novel approaches to study kidney biopsy specimens and highlights their potential to refine our understanding of the pathophysiology of kidney disease and lead to precision-based diagnosis and therapy. Recent findings: Several consortia are now active at studying kidney biopsy samples from various patient cohorts with state-of-the art cellular and molecular techniques. These include advanced imaging approaches as well as deep molecular interrogation with tools such as epigenetics, transcriptomics, proteomics and metabolomics. The emphasis throughout is on rigor, reproducibility and quality control. Summary: Although these techniques to study kidney biopsies are complementary, each on its own can yield novel ways to define and classify kidney disease. Therefore, great efforts are needed in order to generate an integrated output that can propel the diagnosis and treatment of kidney disease into the realm of precision medicine.Item Clinical, histopathologic and molecular features of idiopathic and diabetic nodular mesangial sclerosis in humans(Oxford University Press, 2021) Eadon, Michael T.; Lampe, Sam; Baig, Mirza M.; Collins, Kimberly S.; Ferreira, Ricardo Melo; Mang, Henry; Cheng, Ying-Hua; Barwinska, Daria; El-Achkar, Tarek M.; Schwantes-An, Tae-Hwi; Winfree, Seth; Temm, Constance J.; Ferkowicz, Michael J.; Dunn, Kenneth W.; Kelly, Katherine J.; Sutton, Timothy A.; Moe, Sharon M.; Moorthi, Ranjani N.; Phillips, Carrie L.; Dagher, Pierre C.; Medicine, School of MedicineBackground: Idiopathic nodular mesangial sclerosis, also called idiopathic nodular glomerulosclerosis (ING), is a rare clinical entity with an unclear pathogenesis. The hallmark of this disease is the presence of nodular mesangial sclerosis on histology without clinical evidence of diabetes mellitus or other predisposing diagnoses. To achieve insights into its pathogenesis, we queried the clinical, histopathologic and transcriptomic features of ING and nodular diabetic nephropathy (DN). Methods: All renal biopsy reports accessioned at Indiana University Health from 2001 to 2016 were reviewed to identify 48 ING cases. Clinical and histopathologic features were compared between individuals with ING and DN (n = 751). Glomeruli of ING (n = 5), DN (n = 18) and reference (REF) nephrectomy (n = 9) samples were isolated by laser microdissection and RNA was sequenced. Immunohistochemistry of proline-rich 36 (PRR36) protein was performed. Results: ING subjects were frequently hypertensive (95.8%) with a smoking history (66.7%). ING subjects were older, had lower proteinuria and had less hyaline arteriolosclerosis than DN subjects. Butanoate metabolism was an enriched pathway in ING samples compared with either REF or DN samples. The top differentially expressed gene, PRR36, had increased expression in glomeruli 248-fold [false discovery rate (FDR) P = 5.93 × 10-6] compared with the REF and increased 109-fold (FDR P = 1.85 × 10-6) compared with DN samples. Immunohistochemistry revealed a reduced proportion of cells with perinuclear reaction in ING samples as compared to DN. Conclusions: Despite similar clinical and histopathologic characteristics in ING and DN, the uncovered transcriptomic signature suggests that ING has distinct molecular features from nodular DN. Further study is warranted to understand these relationships.Item Convolutional neural network denoising in fluorescence lifetime imaging microscopy (FLIM)(SPIE, 2021) Mannam, Varun; Zhang, Yide; Yuan, Xiaotong; Hato, Takashi; Dagher, Pierre C.; Nichols, Evan L.; Smith, Cody J.; Dunn, Kenneth W.; Howard, Scott; Medicine, School of MedicineFluorescence lifetime imaging microscopy (FLIM) systems are limited by their slow processing speed, low signal- to-noise ratio (SNR), and expensive and challenging hardware setups. In this work, we demonstrate applying a denoising convolutional network to improve FLIM SNR. The network will integrated with an instant FLIM system with fast data acquisition based on analog signal processing, high SNR using high-efficiency pulse-modulation, and cost-effective implementation utilizing off-the-shelf radio-frequency components. Our instant FLIM system simultaneously provides the intensity, lifetime, and phasor plots in vivo and ex vivo. By integrating image de- noising using the trained deep learning model on the FLIM data, provide accurate FLIM phasor measurements are obtained. The enhanced phasor is then passed through the K-means clustering segmentation method, an unbiased and unsupervised machine learning technique to separate different fluorophores accurately. Our experimental in vivo mouse kidney results indicate that introducing the deep learning image denoising model before the segmentation effectively removes the noise in the phasor compared to existing methods and provides clearer segments. Hence, the proposed deep learning-based workflow provides fast and accurate automatic segmentation of fluorescence images using instant FLIM. The denoising operation is effective for the segmentation if the FLIM measurements are noisy. The clustering can effectively enhance the detection of biological structures of interest in biomedical imaging applications.Item Endothelial STAT3 Modulates Protective Mechanisms in a Mouse Ischemia-Reperfusion Model of Acute Kidney Injury(hindawi publishing corporation, 2017) Dube, Shataakshi; Matam, Tejasvi; Yen, Jessica; Mang, Henry E.; Dagher, Pierre C.; Hato, Takashi; Sutton, Timothy A.; Medicine, School of MedicineSTAT3 is a transcriptional regulator that plays an important role in coordinating inflammation and immunity. In addition, there is a growing appreciation of the role STAT3 signaling plays in response to organ injury following diverse insults. Acute kidney injury (AKI) from ischemia-reperfusion injury is a common clinical entity with devastating consequences, and the recognition that endothelial alterations contribute to kidney dysfunction in this setting is of growing interest. Consequently, we used a mouse with a genetic deletion of Stat3 restricted to the endothelium to examine the role of STAT3 signaling in the pathophysiology of ischemic AKI. In a mouse model of ischemic AKI, the loss of endothelial STAT3 signaling significantly exacerbated kidney dysfunction, morphologic injury, and proximal tubular oxidative stress. The increased severity of ischemic AKI was associated with more robust endothelial-leukocyte adhesion and increased tissue accumulation of F4/80+ macrophages. Moreover, important proximal tubular adaptive mechanisms to injury were diminished in association with decreased tissue mRNA levels of the epithelial cell survival cytokine IL-22. In aggregate, these findings suggest that the endothelial STAT3 signaling plays an important role in limiting kidney dysfunction in ischemic AKI and that selective pharmacologic activation of endothelial STAT3 signaling could serve as a potential therapeutic target.