Series |

Tools and technologies

Important advances in our understanding of kidney development and renal function and disease have been aided by the use of new technologies and by studies in model organisms. In this article series, Nature Reviews Nephrology presents articles that explore the tools and techniques that are improving our understanding of renal development, physiology and disease mechanisms as well as contributing to advances in the screening, diagnosis and management of kidney diseases.

Reviews and Perspectives

Technological advances continue to expand the use of proteomics in medicine. In this Review, the authors discuss proteomics research findings in nephrology and the potential, as well as the limitations, of using proteomics techniques to uncover disease mechanisms and develop new therapeutic strategies.

Review Article | | Nature Reviews Nephrology

This Review provides an overview of fluorescence-based microscopy techniques that have been used to study molecular processes within the kidney. The authors describe how the development of cutting-edge technologies has enabled high spatiotemporal resolution of molecular interactions and processes, and how these approaches have aided our understanding of kidney dynamics.

Review Article | | Nature Reviews Nephrology

Ontologies are powerful tools that facilitate the integration of large and disparate data sets. Here, researchers from the Kidney Precision Medicine Project provide an introduction to ontologies, including those developed by the consortium, describing how these will be used to improve the annotation of kidney-relevant data, eventually leading to new definitions of kidney disease in support of precision medicine.

Review Article | | Nature Reviews Nephrology

Developments in digital pathology and computational image analysis have the potential to identify new disease mechanisms, improve disease classification and prognostication, and ultimately aid the identification of targeted therapies. In this Review, the authors provide an outline of the digital ecosystem in nephropathology and describe potential applications and challenges associated with the emerging armamentarium of technologies for image analysis.

Review Article | | Nature Reviews Nephrology

Classification of kidney diseases according to their molecular mechanisms has potential to improve patient outcomes through the identification of targeted therapeutic approaches. This Review provides an overview of the ways in which omics and other data types can be integrated to enhance our understanding of the mechanisms underlying kidney function and failure.

Review Article | | Nature Reviews Nephrology

Sullivan and Susztak examine the process of translating data on genetic variants associated with common kidney diseases into information about the underlying disease mechanisms. The authors propose that identification of causal variants, genetic regulatory mechanisms, target-gene products and disease-associated phenotypes is crucial to this process.

Review Article | | Nature Reviews Nephrology

Applying single-cell RNA sequencing (scRNA-seq) to human tissues can reveal the phenotypic diversity of resident and infiltrating cells at high resolution. In this Review, the authors examine important design considerations for applying this technology to kidney cells and discuss current findings from scRNA-seq studies of lupus nephritis.

Review Article | | Nature Reviews Nephrology

In this Review, Stewart and colleagues describe how single-cell technologies, in particular single-cell RNA sequencing, can be used to map the complex immune landscape within organs, and how such technologies might provide insights into the role of the immune system in kidney health and disease pathogenesis.

Review Article | | Nature Reviews Nephrology

Current in vitro nephrotoxicity screens are poorly predictive of toxicity in humans. Here, the authors describe mechanisms of nephrotoxic injury, the functional features of tubular cell models that are essential for predicting the toxicity of pharmaceutical compounds, and novel in vitro cell models under development.

Review Article | | Nature Reviews Nephrology

News and comment

The drug development pipeline for kidney diseases is plagued with challenges ranging from an insufficient understanding of disease mechanisms to a lack of robust preclinical models. Bioengineering approaches have the potential to streamline preclinical drug discovery efforts and improve the success of clinical trials for kidney disease.

Comment | | Nature Reviews Nephrology

Artificial intelligence is increasingly being used to improve diagnosis and prognostication for acute and chronic kidney diseases. Studies with this objective published in 2019 relied on a variety of available data sources, including electronic health records, intraoperative physiological signals, kidney ultrasound imaging, and digitized biopsy specimens.

Year in Review | | Nature Reviews Nephrology

Single-cell genomics provide a powerful approach to investigate the intrinsic complexity of the kidney and understand the diverse cell types and states that exist during kidney development, homeostasis and disease. Several advances were made in 2019 that enhance our understanding of kidney immune cell states in health and disease and the quality of current kidney organoid model systems for studying human diseases.

Year in Review | | Nature Reviews Nephrology

2019 saw advances in the generation of induced pluripotent stem cell (iPSC)-derived nephron progenitors and in our understanding of how nephrons form in a kidney organoid. Fundamental studies of regeneration in zebrafish continue to provide vital clues as to how we might use iPSC-derived cells to regenerate a human nephron in vivo.

Year in Review | | Nature Reviews Nephrology

Once confined to the world of science fiction, advances in information technology, particularly in computational and storage resources, have enabled use of artificial intelligence in medicine to become a reality. Two new studies report the use of deep learning — currently the most promising algorithmic artificial intelligence approach — in kidney pathology.

News & Views | | Nature Reviews Nephrology

To advance kidney discovery, our community is driven to maximize the utility of genomic data that we all generate. We can best accomplish this through excellence in appropriately incorporating publicly available genomic data into our research efforts and by enthusiastically embracing widespread data sharing in a manner that facilitates its broad use.

Comment | | Nature Reviews Nephrology

A new study discovered thousands of expression quantitative trait loci (eQTLs) in the renal glomerular and tubulointerstitial compartments and integrated these data with other omics data sets to identify genes with roles in the pathogenesis of chronic kidney disease. This report reinforces the necessity of using compartment-derived eQTLs to advance kidney genomic discovery.

News & Views | | Nature Reviews Nephrology

Technologies such as proteomics provide a snapshot of a specific cellular state but are unable to directly record successive signalling events. Two new CRISPR-mediated analogue multi-event recording apparatus (CAMERA) systems enable sequential recording of endogenous and exogenous signalling events by targeted DNA modifications, thereby allowing systematic interrogation of different cellular states.

News & Views | | Nature Reviews Nephrology