Spatial single cell metabolomics: Current challenges and future developments

New tools to study renal fibrogenesis

PURPOSE OF REVIEW

Kidney fibrosis is a key pathological aspect and outcome of chronic kidney disease (CKD). The advent of multiomic analyses using human kidney tissue, enabled by technological advances, marks a new chapter of discovery in fibrosis research of the kidney. This review highlights the rapid advancements of single-cell and spatial multiomic techniques that offer new avenues for exploring research questions related to human kidney fibrosis development.

RECENT FINDINGS

We recently focused on understanding the origin and transition of myofibroblasts in kidney fibrosis using single-cell RNA sequencing (scRNA-seq) [1] . We analysed cells from healthy human kidneys and compared them to patient samples with CKD. We identified PDGFRα+/PDGFRβ+ mesenchymal cells as the primary cellular source of extracellular matrix (ECM) in human kidney fibrosis. We found several commonly shared cell states of fibroblasts and myofibroblasts and provided insights into molecular regulators. Novel single-cell and spatial multiomics tools are now available to shed light on cell lineages, the plasticity of kidney cells and cell-cell communication in fibrosis.

SUMMARY

As further single-cell and spatial multiomic approaches are being developed, opportunities to apply these methods to human kidney tissues expand similarly. Careful design and optimisation of the multiomic experiments are needed to answer questions related to cell lineages, plasticity and cell-cell communication in kidney fibrosis.

Protocol for analyzing energy metabolic pathway dependency in human liver cancer cell lines

Cellular energy metabolism analysis is complex, expensive, and indirect. We present a protocol to analyze relative contribution of metabolic pathways to ATP production by directly measuring ATP levels. We describe steps for cell counting and seeding in 96-well plate, treating with metformin, and systematic inhibition with metabolic inhibitors. We then detail procedures for a viability and ATP assay and calculating energy metabolism dependency. This high-throughput and accessible protocol works with any cell line and allows for flexible perturbation studies.

Insights into targeting cellular senescence with senolytic therapy: The journey from preclinical trials to clinical practice

Interconnected, fundamental aging processes are central to many illnesses and diseases. Cellular senescence is a mechanism that halts the cell cycle in response to harmful stimuli. Senescent cells (SnCs) can emerge at any point in life, and their persistence, along with the numerous proteins they secrete, can negatively affect tissue function. Interventions aimed at combating persistent SnCs, which can destroy tissues, have been used in preclinical models to delay, halt, or even reverse various diseases. Consequently, the development of small-molecule senolytic medicines designed to specifically eliminate SnCs has opened potential avenues for the prevention or treatment of multiple diseases and age-related issues in humans. In this review, we explore the most promising approaches for translating small-molecule senolytics and other interventions targeting senescence in clinical practice. This discussion highlights the rationale for considering SnCs as therapeutic targets for diseases affecting individuals of all ages.

Emerging Functional Connections Between Metabolism and Epigenetic Remodeling in Neural Differentiation

Stem cells possess extraordinary capacities for self-renewal and differentiation, making them highly valuable in regenerative medicine. Among these, neural stem cells (NSCs) play a fundamental role in neural development and repair processes. NSC characteristics and fate are intricately regulated by the microenvironment and intracellular signaling. Interestingly, metabolism plays a pivotal role in orchestrating the epigenome dynamics during neural differentiation, facilitating the transition from undifferentiated NSC to specialized neuronal and glial cell types. This intricate interplay between metabolism and the epigenome is essential for precisely regulating gene expression patterns and ensuring proper neural development. This review highlights the mechanisms behind metabolic regulation of NSC fate and their connections with epigenetic regulation to shape transcriptional programs of stemness and neural differentiation. A comprehensive understanding of these molecular gears appears fundamental for translational applications in regenerative medicine and personalized therapies for neurological conditions.

Epigenetics in obesity: Mechanisms and advances in therapies based on natural products

Obesity is a major risk factor for morbidity and mortality because it has a close relationship to metabolic illnesses, such as diabetes, cardiovascular diseases, and some types of cancer. With no drugs available, the mainstay of obesity management remains lifestyle changes with exercise and dietary modifications. In light of the tremendous disease burden and unmet therapeutics, fresh perspectives on pathophysiology and drug discovery are needed. The development of epigenetics provides a compelling justification for how environmental, lifestyle, and other risk factors contribute to the pathogenesis of obesity. Furthermore, epigenetic dysregulations can be restored, and it has been reported that certain natural products obtained from plants, such as tea polyphenols, ellagic acid, urolithins, curcumin, genistein, isothiocyanates, and citrus isoflavonoids, were shown to inhibit weight gain. These substances have great antioxidant potential and are of great interest because they can also modify epigenetic mechanisms. Therefore, understanding epigenetic modifications to target the primary cause of obesity and the epigenetic mechanisms of anti-obesity effects with certain phytochemicals can prove rational strategies to prevent the disease and develop novel therapeutic interventions. Thus, the current review aimed to summarize the epigenetic mechanisms and advances in therapies for obesity based on natural products to provide evidence for the development of several potential anti-obesity drug targets.

Spatial multi-omics: novel tools to study the complexity of cardiovascular diseases

Spatial multi-omic studies have emerged as a promising approach to comprehensively analyze cells in tissues, enabling the joint analysis of multiple data modalities like transcriptome, epigenome, proteome, and metabolome in parallel or even the same tissue section. This review focuses on the recent advancements in spatial multi-omics technologies, including novel data modalities and computational approaches. We discuss the advancements in low-resolution and high-resolution spatial multi-omics methods which can resolve up to 10,000 of individual molecules at subcellular level. By applying and integrating these techniques, researchers have recently gained valuable insights into the molecular circuits and mechanisms which govern cell biology along the cardiovascular disease spectrum. We provide an overview of current data analysis approaches, with a focus on data integration of multi-omic datasets, highlighting strengths and weaknesses of various computational pipelines. These tools play a crucial role in analyzing and interpreting spatial multi-omics datasets, facilitating the discovery of new findings, and enhancing translational cardiovascular research. Despite nontrivial challenges, such as the need for standardization of experimental setups, data analysis, and improved computational tools, the application of spatial multi-omics holds tremendous potential in revolutionizing our understanding of human disease processes and the identification of novel biomarkers and therapeutic targets. Exciting opportunities lie ahead for the spatial multi-omics field and will likely contribute to the advancement of personalized medicine for cardiovascular diseases.