Multi-omic analysis of human kidney tissue identified medulla-specific gene expression patterns

Imaging and spatially resolved mass spectrometry applications in nephrology

The application of spatially resolved mass spectrometry (MS) and MS imaging approaches for studying biomolecular processes in the kidney is rapidly growing. These powerful methods, which enable label-free and multiplexed detection of many molecular classes across omics domains (including metabolites, drugs, proteins and protein post-translational modifications), are beginning to reveal new molecular insights related to kidney health and disease. The complexity of the kidney often necessitates multiple scales of analysis for interrogating biofluids, whole organs, functional tissue units, single cells and subcellular compartments. Various MS methods can generate omics data across these spatial domains and facilitate both basic science and pathological assessment of the kidney. Optimal processes related to sample preparation and handling for different MS applications are rapidly evolving. Emerging technology and methods, improvement of spatial resolution, broader molecular characterization, multimodal and multiomics approaches and the use of machine learning and artificial intelligence approaches promise to make these applications even more valuable in the field of nephology. Overall, spatially resolved MS and MS imaging methods have the potential to fill much of the omics gap in systems biology analysis of the kidney and provide functional outputs that cannot be obtained using genomics and transcriptomic methods.

The boundaries of normal kidney tissue for biomedical research

PURPOSE OF REVIEW

In this review, we highlight the importance of understanding the inherent biological variability in normal kidney, or healthy reference tissue, to establish an accurate reference point for biomedical research. We explore this and the advantages and limitations of various sources of healthy reference tissue suitable for structural and omics-level studies.

RECENT FINDINGS

Several large consortia are employing omic technologies for diseased and normal kidney tissue, underscoring the importance of utilizing healthy reference tissue in these studies. Emerging approaches, such as artificial intelligence and multiomic analyses, are expanding our understanding of structural and molecular heterogeneity in healthy reference kidney tissue and uncovering new insights.

SUMMARY

Biological variability in healthy reference tissue at the functional, structural, and molecular level is complex and remains an active area of study. Thoughtful selection of healthy reference tissue sources is critical, providing the greatest potential for producing high-quality research outcomes.

Understanding developing kidneys and Wilms tumors one cell at a time

Single-cell sequencing-based techniques are revolutionizing all fields of biomedical sciences, including normal kidney development and how this is disturbed in the development of Wilms tumor. The many different techniques and the differences between them can obscure which technique is best used to answer which question. In this review we summarize the techniques currently available, discuss which have been used in kidney development or Wilms tumor context, and which techniques can or should be combined to maximize the increase in biological understanding we can get from them.

A guide to studying 3D genome structure and dynamics in the kidney

The human genome is tightly packed into the 3D environment of the cell nucleus. Rapidly evolving and sophisticated methods of mapping 3D genome architecture have shed light on fundamental principles of genome organization and gene regulation. The genome is physically organized on different scales, from individual genes to entire chromosomes. Nuclear landmarks such as the nuclear envelope and nucleoli have important roles in compartmentalizing the genome within the nucleus. Genome activity (for example, gene transcription) is also functionally partitioned within this 3D organization. Rather than being static, the 3D organization of the genome is tightly regulated over various time scales. These dynamic changes in genome structure over time represent the fourth dimension of the genome. Innovative methods have been used to map the dynamic regulation of genome structure during important cellular processes including organism development, responses to stimuli, cell division and senescence. Furthermore, disruptions to the 4D genome have been linked to various diseases, including of the kidney. As tools and approaches to studying the 4D genome become more readily available, future studies that apply these methods to study kidney biology will provide insights into kidney function in health and disease.

Epigenetics of Hypertensive Nephropathy

Hypertensive nephropathy (HN) is a leading cause of chronic kidney disease (CKD) and end-stage renal disease (ESRD), contributing to significant morbidity, mortality, and rising healthcare costs. In this review article, we explore the role of epigenetic mechanisms in HN progression and their potential therapeutic implications. We begin by examining key epigenetic modifications-DNA methylation, histone modifications, and non-coding RNAs-observed in kidney disease. Next, we discuss the underlying pathophysiology of HN and highlight current in vitro and in vivo models used to study the condition. Finally, we compare various types of HN-induced renal injury and their associated epigenetic mechanisms with those observed in other kidney injury models, drawing inferences on potential epigenetic therapies for HN. The information gathered in this work indicate that epigenetic mechanisms can drive the progression of HN by regulating key molecular signaling pathways involved in renal damage and fibrosis. The limitations of Renin-Angiotensin-Aldosterone System (RAAS) inhibitors underscore the need for alternative treatments targeting epigenetic pathways. This review emphasizes the importance of further research into the epigenetic regulation of HN to develop more effective therapies and preventive strategies. Identifying novel epigenetic markers could provide new therapeutic opportunities for managing CKD and reducing the burden of ESRD.

Multi-Omics Integration in Nephrology: Advances, Challenges, and Future Directions

Omics technologies have transformed nephrology, providing deep insights into molecular mechanisms of kidney disease and enabling more precise diagnostic tools, therapeutic strategies, and prognostic markers. Multi-omics data integration, spanning bulk, single-cell, and spatial omics, offers a comprehensive view of kidney biology in health and disease. In this review, we explore methods and challenges for integrating transcriptomic, epigenomic, and spatial data. By combining omics layers, researchers can uncover novel molecular interactions and spatial tissue organization, advancing our understanding of diseases like diabetic kidney disease and autosomal polycystic kidney disease. This integrated approach is reshaping diagnostic and therapeutic strategies in nephrology and is critical for optimizing insights available from spatial and multi-omics analysis.

Transcriptomic, epigenomic, and spatial metabolomic cell profiling redefines regional human kidney anatomy

A large-scale multimodal atlas that includes major kidney regions is lacking. Here, we employed simultaneous high-throughput single-cell ATAC/RNA sequencing (SHARE-seq) and spatially resolved metabolomics to profile 54 human samples from distinct kidney anatomical regions. We generated transcriptomes of 446,267 cells and chromatin accessibility profiles of 401,875 cells and developed a package to analyze 408,218 spatially resolved metabolomes. We find that the same cell type, including thin limb, thick ascending limb loop of Henle and principal cells, display distinct transcriptomic, chromatin accessibility, and metabolomic signatures, depending on anatomic location. Surveying metabolism-associated gene profiles revealed non-overlapping metabolic signatures between nephron segments and dysregulated lipid metabolism in diseased proximal tubule (PT) cells. Integrating multimodal omics with clinical data identified PLEKHA1 as a disease marker, and its in vitro knockdown increased gene expression in PT differentiation, suggesting possible pathogenic roles. This study highlights previously underrepresented cellular heterogeneity underlying the human kidney anatomy.

Multi-omics data integration shines a light on the renal medulla

The renal medulla maintains salt and water balance and is prone to dysregulation because of high oxygen demand. Challenges in obtaining high-quality tissue have limited characterization of molecular programs regulating the medulla. Haug et al. leveraged gene expression, chromatin accessibility, long-range chromosomal interactions, and spatial transcriptomics to build a reference set of medullary tissue marker genes to define the medullary role in kidney function, exemplifying the strength and utility of multi-omic data integration.