Comprehensive and spatially mapped molecular atlases of organs at a cellular level are a critical resource to gain insights into pathogenic mechanisms and personalized therapies for diseases. The Kidney Precision Medicine Project (KPMP) is an endeavor to generate 3-dimensional (3D) molecular atlases of healthy and diseased kidney biopsies using multiple state-of-the-art OMICS and imaging technologies across several institutions. Obtaining rigorous and reproducible results from disparate methods and at different sites to interrogate biomolecules at a single cell level or in 3D space is a significant challenge that can be a futile exercise if not well controlled. We describe a "follow the tissue" pipeline for generating a reliable and authentic single cell/region 3D molecular atlas of human adult kidney. Our approach emphasizes quality assurance, quality control, validation and harmonization across different OMICS and imaging technologies from sample procurement, processing, storage, shipping to data generation, analysis and sharing. We established benchmarks for quality control, rigor, reproducibility and feasibility across multiple technologies through a pilot experiment using common source tissue that was processed and analyzed at different institutions and different technologies. A peer review system was established to critically review quality control measures and the reproducibility of data generated by each technology before being approved to interrogate clinical biopsy specimens. The process established economizes the use of valuable biopsy tissue for multi-OMICS and imaging analysis with stringent quality control to ensure rigor and reproducibility of results and serves as a model for precision medicine projects across laboratories, institutions and consortia.
From March through December 2020, 100 autopsies were performed (Semmelweis University, Budapest, Hungary), with chart review, of patients with severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) infection demonstrated by real-time reverse-transcription polymerase chain reaction testing (mean age, 74.73 years, range 40–102 years; 50 males, mean age 71.96 years, and 50 females, mean age 77.5 years). Classified by the date of death, 21 cases were from the pandemic’s “first wave” (March through July) and 79 from the “second wave” (August through December). Three mortality categories were defined by relevance of SARS-CoV-2 infection: (1) “strong” association (n=57), in which COVID-19 was primary responsible for death; (2) “contributive” association (n=27), in which a pre-existing condition independent of COVID-19 was primary responsible for death, albeit with substantial COVID-19 co-morbidity; (3) “weak” association (n=16), in which COVID-19 was minimally or not at all responsible for death. Distributions among categories differed between the first wave, in which the “contributive” association cases dominated (strong: 24%, contributive: 48%, weak: 28%), and the second wave, in which the “strong” association cases dominated (strong: 66%, contributive: 21%, weak: 13%). Charted co-morbidities included hypertension (85 %), cardiovascular diseases (71 %), diabetes (40 %), cerebrovascular diseases (31 %), chronic respiratory diseases (30 %), malignant tumors (20 %), renal diseases (19 %), diseases of the central nervous system (15 %), and liver diseases (6 %). Autopsy evaluation analyzed alterations on macroscopy as well as findings on microscopy of scanned and scored sections of formalin-fixed, paraffin-embedded tissue samples (50–80 blocks/case). Severity of histological abnormalities in the lung differed significantly between “strong” and “contributive” (p<0.0001) and between “strong” and “weak” categories (p<0.0001). Abnormalities included diffuse alveolar damage, macrophage infiltration, and vascular and alveolar fibrin aggregates (lung), with macro- and microvascular thrombi and thromboemboli (lung, kidney, liver). In conclusion, autopsies clarified in what extent COVID-19 was responsible for death, demonstrated the pathological background of clinical signs and symptoms, and identified organ alterations that led to the death. Clinicopathologic correlation, with conference discussions of severity of co-morbidities and of direct pathological signs of disease, permitted accurate categorization of cause of death and COVID-19 association as “strong,” “contributive,” or “weak.” Lung involvement, with reduced ventilatory capacity, was the primary cause of death in the “strong” and “contributive” categories. Shifts in distribution among categories, with “strong” association between COVID-19 and death dominating in the second wave, may reflect improved clinical management of COVID-19 as expertise grew.
Kidney Precision Medicine Project (KPMP) is building a spatially specified human kidney tissue atlas in health and disease with single-cell resolution. Here, we describe the construction of an integrated reference map of cells, pathways, and genes using unaffected regions of nephrectomy tissues and undiseased human biopsies from 56 adult subjects. We use single-cell/nucleus transcriptomics, subsegmental laser microdissection transcriptomics and proteomics, near-single-cell proteomics, 3D and CODEX imaging, and spatial metabolomics to hierarchically identify genes, pathways, and cells. Integrated data from these different technologies coherently identify cell types/subtypes within different nephron segments and the interstitium. These profiles describe cell-level functional organization of the kidney following its physiological functions and link cell subtypes to genes, proteins, metabolites, and pathways. They further show that messenger RNA levels along the nephron are congruent with the subsegmental physiological activity. This reference atlas provides a framework for the classification of kidney disease when multiple molecular mechanisms underlie convergent clinical phenotypes.
Persistent tissue reservoirs of HIV present a major barrier to cure. Defining subsets of infected cells in tissues is a major focus of HIV cure research. Herein, we describe a novel multiplexed in situ hybridization (ISH) (RNAscope) protocol to detect HIV-DNA (vDNA) and HIV-RNA (vRNA) in formalin-fixed paraffin-embedded (FFPE) human tissues in combination with immunofluorescence (IF) phenotyping of the infected cells. We show that multiplexed IF and ISH (mIFISH) is suitable for quantitative assessment of HIV vRNA and vDNA and that multiparameter IF phenotyping allows precise identification of the cellular source of the ISH signal. We also provide semi-quantitative data on the impact of various tissue fixatives on the detectability of vDNA and vRNA with RNAscope technology. Finally, we describe methods to quantitate the ISH signal on whole-slide digital images and validation of the quantitative ISH data with quantitative real-time PCR for vRNA. It is our hope that this approach will provide insight into the biology of HIV tissue reservoirs and to inform strategies aimed at curing HIV.
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