Profiling Immune Cells in the Kidney Using Tissue Cytometry and Machine Learning

Abstract

The immune system governs key functions that maintain renal homeostasis through various effector cells that reside in or infiltrate the kidney. These immune cells play an important role in shaping adaptive or maladaptive responses to local or systemic stress and injury. We increasingly recognize that microenvironments within the kidney are characterized by a unique distribution of immune cells, the function of which depends on this unique spatial localization. Therefore, quantitative profiling of immune cells in intact kidney tissue becomes essential, particularly at a scale and resolution that allow the detection of differences between the various “nephro-ecosystems” in health and disease. In this review, we discuss advancements in tissue cytometry of the kidney, performed through multiplexed confocal imaging and analysis using the Volumetric Tissue Exploration and Analysis (VTEA) software. We highlight how this tool has improved our understanding of the role of the immune system in the kidney and its relevance in the pathobiology of renal disease. We also discuss how the field is increasingly incorporating machine learning to enhance the analytic potential of imaging data and provide unbiased methods to explore and visualize multidimensional data. Such novel analytic methods could be particularly relevant when applied to profiling immune cells. Furthermore, machine-learning approaches applied to cytometry could present venues for nonexhaustive exploration and classification of cells from existing data and improving tissue economy. Therefore, tissue cytometry is transforming what used to be a qualitative assessment of the kidney into a highly quantitative, imaging-based “omics” assessment that complements other advanced molecular interrogation technologies.