Hamid Rabb

Motivation: Comparative analysis of spatial transcriptomics (ST) data is needed to identify genes that spatially change in their expression patterns between conditions, such as in diseased versus healthy tissues. Existing methods generally fail to distinguish changes in spatial patterning by focusing only on changes in gene expression magnitude for methods adapted from non-spatial data or on changes in significance of spatial variability for methods focusing on spatially-resolved data. Results: To address these limitations, we develop STcompare, a statistical framework for comparative analysis of ST data by testing for differences in spatial correlation and spatial fold-change across structurally matched locations. Using simulated data, we demonstrate how STcompare provides distinct insights from bulk differential gene expression analysis and spatially variable gene expression analysis as well as other spatial comparison methods. STcompare further robustly controls for false positives even in the presence of spatial autocorrelation common in ST data. We apply STcompare to real ST data of biological replicates of mouse brains to confirm high spatial correspondence of gene expression patterns across samples. We apply STcompare to identify genes that spatially change in mouse kidneys with acute kidney injury compared to a healthy control, revealing tissue compartment-specific molecular dysregulation. Overall, the application of this spatially-aware comparative analysis will enable the discovery of differential spatially patterned genes across various physiological and technological axes of interest. Availability: STcompare is implemented as an open-source R package at https://github.com/JEFworks-Lab/STcompare with additional documentation and tutorials available at https://jef.works/STcompare/.

Background: Kidney transplantation is the preferred treatment strategy for end-stage kidney disease. Deceased donor kidneys usually undergo cold storage until kidney transplantation, leading to cold ischemia injury that may contribute to poor graft outcomes. However, the molecular characterization of potential mechanisms of cold ischemia injury remains incomplete. Results: To bridge this knowledge gap, we leverage 10x Visium spatial transcriptomic technology to perform full transcriptome profiling of murine kidneys subject to varying durations of cold ischemia typical in a deceased donor kidney transplant setting. We develop a computational workflow to identify and compare spatiotemporal transcriptomic changes that accompany the injury pathophysiology in a tissue compartment-specific manner. We identify proportional enrichment of oxidative phosphorylation (OXPHOS) genes with increasing duration of cold ischemia injury within the oxygen-lean inner medulla region, suggestive of atypical metabolic presentation. This is distinct in cold ischemia injury tissue compared to warm ischemia–reperfusion kidney injury tissue. Spatiotemporal trends are validated by qPCR and immunofluorescence in a larger cohort of mice. Conclusions: Altogether, our spatiotemporal transcriptomic analysis identifies coordinated molecular changes within metabolic pathways such as OXPHOS deep within the cold ischemic kidney, highlighting the need for increased attention to the inner medulla and potential opportunities for new insights beyond those available from superficial biopsy-focused tissue examination.

This study presents the first exploration of the cellular and molecular mechanisms underlying GPR39 activation in a physiologically relevant in vitro model of the renal collecting duct, mpkCCD cells. Our findings implicate GPR39 in the regulation of aquaporin-2 expression and trafficking, cytoskeletal organization, and cellular metabolism. In addition, RNA sequencing of GPR39-activated cells revealed transcriptomic changes related to immune signaling, stress response, and differentiation.

Key Points: Chronic stress elevates neutrophil gelatinase-associated lipocalin and cystatin C. Chronic stress increases T helper 17 and regulatory T-cell populations in the kidney. Chronic stress could increase susceptibility to kidney diseases. Background: Chronic stress (CS) due to prolonged exposure to negative life events increases the risk of psychiatric illnesses and significantly affects physiologic processes. CS has also been linked to sustained systemic inflammation, resulting in dysregulated immune responses and organ function. We hypothesized that CS would lead to kidney inflammation and tested this in mice. Methods: Male C57BL/6J mice were subjected to CS by pair-housing them with CD-1 retired breeder mice. Kidney immune cells were isolated and evaluated by spectral flow cytometry. Cytokines were measured using a multiplex assay in kidney tissue and serum. Serum creatinine, cystatin C, and neutrophil gelatinase-associated lipocalin levels were measured. Results: Mice subjected to CS exhibited greater weight gain than the control group and had reduced fur quality. CS led to a decrease in the percentage of kidney CD4 ⁺ T cells (54.26%±0.89% versus 59.88%±1.25%, P < 0.001) and an increase in T helper 17 (2.3%±0.3% versus 0.83%±0.15%, P < 0.001) and regulatory T cells (3.42%±0.45% versus 1.53%±0.21%, P < 0.001). There was an increase in the kidney macrophage percentage in CS mice (88.33%±1.16% versus 84.26%±0.73%, P < 0.01). TNF- α levels were higher in the kidney of stressed mice (8.53±1.18 versus 3.15±1.29 pg/ml, P < 0.01). CS led to elevated levels of serum cystatin C (515.9±16.88 versus 456.6±14.79 ng/ml, P < 0.05) serum neutrophil gelatinase-associated lipocalin (833.1±282.4 versus 90.58±5.57 ng/ml, P < 0.0001). Conclusions: CS in mice led to kidney inflammation and immunologic changes. These could predispose to acute and CKDs in which inflammation plays a pathogenic role.

Background: The gut microbiome plays an important role in human health and disease. Kidney Precision Medicine Project (KPMP) is a well‐phenotyped, kidney biopsy‐proven cohort of AKI and CKD patients. Comprehensive profiling of gut microbiota can uncover novel mechanistic, diagnostic, and therapeutic strategies for CKD and AKI patients. Methods: We performed metagenomic whole genome sequencing (mWGS; > 25 million reads) on KPMP stool samples. mWGS data of healthy controls from 4 published studies was used. Kraken2 and MetaPhlAn3 were used for taxonomic assignment, and HUMAnN3 for functional annotation. Results: Kraken2 analysis showed significantly higher abundance of Ruminococcus bicirculans in CKD (6.47) compared to AKI (1.82) and healthy individuals (2.42; p = 0.01). Furthermore, the abundance of Gordonibacter pamelaeae increased in CKD (0.30) compared to AKI (0.07; p = 0.05) and healthy individuals (0.03). The percent mean abundance of genus Chryseobacterium was slightly higher in CKD (0.07) compared to AKI (0.05; p = 0.05) but reduced compared to healthy individuals (0.20; p < 0.001). MetaPhlAn3 identified alterations in Gordonibacter, Bacteroides , and Faecalibacterium with a significant increase in Clostridium asparagiforme in AKI (11.68) compared to CKD (0.03; p = 0.06) and healthy (0.01; p = 0.001) individuals. Roseburia hominis , Roseburia intestinalis , Dorea longicatena , and Gemmiger formicilis were significantly reduced in AKI compared to CKD and healthy individuals. LDA/HUMAnN3 analysis showed a significant correlation between several metabolites and bacterial species in this KPMP population. Conclusion: Kidney biopsy‐proven CKD and AKI patients show a distinct gut microbiota profile compared to healthy individuals. This high‐quality dataset is a valuable resource for developing microbiome‐based diagnostics and therapies for CKD and AKI.

We show that prophylactic MTAP inhibition protects against experimental AKI in mice. Transcriptomic data indicate that MTAP inhibition suppresses epithelial stress and maladaptive repair-related gene programs. Single-cell analysis of human AKI biopsies supports a role for MTAP in injured proximal tubule subpopulations, identifying it as a potential therapeutic target in AKI.

More than 850 million individuals worldwide, accounting for 10–15% of the adult population, are estimated to have chronic kidney disease. Each of these individuals is host to tens of trillions of microorganisms that are collectively referred to as microbiota — a dynamic ecosystem that both influences host health and is itself influenced by changes in the host. Available evidence supports the existence of functional connections between resident microorganisms and kidney health that are altered in the context of specific kidney diseases, including acute kidney injury, chronic kidney disease and renal stone disease. Moreover, promising data from preclinical studies suggest that targeting of gut microbial pathways may provide new therapeutic opportunities for the treatment of kidney disease. This Roadmap describes current understanding of the mechanisms by which microorganisms regulate host organ function, the effects of kidney disease on the gut microbiome, and how these insights may contribute to the development of microbe-targeted therapeutics. We highlight key knowledge gaps that remain to be addressed and strategies for addressing these, outlining both the promise and the potential pitfalls of leveraging our understanding of the gut microbiota to better understand and treat kidney disease.

Background: Kidney transplantation is the preferred treatment strategy for end-stage kidney disease. Deceased donor kidneys usually undergo cold storage until kidney transplantation, leading to cold ischemia injury that may contribute to poor graft outcomes. However, the molecular characterization of potential mechanisms of cold ischemia injury remains incomplete. Results: To bridge this knowledge gap, we leveraged the 10x Visium spatial transcriptomic technology to perform full transcriptome profiling of murine kidneys subject to varying durations of cold ischemia typical in a deceased donor kidney transplant setting. We developed a computational workflow to identify and compare spatiotemporal transcriptomic changes that accompany the injury pathophysiology in a tissue compartment-specific manner. We identified proportional enrichment of oxidative phosphorylation (OXPHOS) genes with increasing duration of cold ischemia injury within the oxygen-lean inner medulla region, suggestive of atypical metabolic presentation. This was distinct in cold ischemia injury tissue compared to warm ischemia-reperfusion kidney injury tissue. Spatiotemporal trends were validated by qPCR and immunofluorescence in a larger cohort of mice. We provide an interactive online browser at https://jef.works/CellCarto-ColdIschemia/ to facilitate exploration of our results by the broader scientific and clinical community. Conclusions: Altogether, our spatiotemporal transcriptomic analysis identified coordinated molecular changes within metabolic pathways such as OXPHOS deep within the cold ischemic kidney, highlighting the need for increased attention to the inner medulla and potential opportunities for new insights beyond those available from superficial biopsy-focused tissue examinations.