Spatially Resolved Transcriptomic Analysis of Acute Kidney Injury in a Female Murine Model
Single-cell sequencing technologies have advanced our understanding of kidney biology and disease, but the loss of spatial information in these datasets hinders our interpretation of intercellular communication networks and regional gene expression patterns. New spatial transcriptomic sequencing pla...
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| Vydáno v: | Journal of the American Society of Nephrology Ročník 33; číslo 2; s. 279 |
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| Hlavní autoři: | , , , , |
| Médium: | Journal Article |
| Jazyk: | angličtina |
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United States
01.02.2022
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| ISSN: | 1533-3450, 1533-3450 |
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| Abstract | Single-cell sequencing technologies have advanced our understanding of kidney biology and disease, but the loss of spatial information in these datasets hinders our interpretation of intercellular communication networks and regional gene expression patterns. New spatial transcriptomic sequencing platforms make it possible to measure the topography of gene expression at genome depth.
We optimized and validated a female bilateral ischemia-reperfusion injury model. Using the 10× Genomics Visium Spatial Gene Expression solution, we generated spatial maps of gene expression across the injury and repair time course, and applied two open-source computational tools, Giotto and SPOTlight, to increase resolution and measure cell-cell interaction dynamics.
An ischemia time of 34 minutes in a female murine model resulted in comparable injury to 22 minutes for males. We report a total of 16,856 unique genes mapped across our injury and repair time course. Giotto, a computational toolbox for spatial data analysis, enabled increased resolution mapping of genes and cell types. Using a seeded nonnegative matrix regression (SPOTlight) to deconvolute the dynamic landscape of cell-cell interactions, we found that injured proximal tubule cells were characterized by increasing macrophage and lymphocyte interactions even 6 weeks after injury, potentially reflecting the AKI to CKD transition.
In this transcriptomic atlas, we defined region-specific and injury-induced loss of differentiation markers and their re-expression during repair, as well as region-specific injury and repair transcriptional responses. Lastly, we created an interactive data visualization application for the scientific community to explore these results (http://humphreyslab.com/SingleCell/). |
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| AbstractList | Single-cell sequencing technologies have advanced our understanding of kidney biology and disease, but the loss of spatial information in these datasets hinders our interpretation of intercellular communication networks and regional gene expression patterns. New spatial transcriptomic sequencing platforms make it possible to measure the topography of gene expression at genome depth.
We optimized and validated a female bilateral ischemia-reperfusion injury model. Using the 10× Genomics Visium Spatial Gene Expression solution, we generated spatial maps of gene expression across the injury and repair time course, and applied two open-source computational tools, Giotto and SPOTlight, to increase resolution and measure cell-cell interaction dynamics.
An ischemia time of 34 minutes in a female murine model resulted in comparable injury to 22 minutes for males. We report a total of 16,856 unique genes mapped across our injury and repair time course. Giotto, a computational toolbox for spatial data analysis, enabled increased resolution mapping of genes and cell types. Using a seeded nonnegative matrix regression (SPOTlight) to deconvolute the dynamic landscape of cell-cell interactions, we found that injured proximal tubule cells were characterized by increasing macrophage and lymphocyte interactions even 6 weeks after injury, potentially reflecting the AKI to CKD transition.
In this transcriptomic atlas, we defined region-specific and injury-induced loss of differentiation markers and their re-expression during repair, as well as region-specific injury and repair transcriptional responses. Lastly, we created an interactive data visualization application for the scientific community to explore these results (http://humphreyslab.com/SingleCell/). Single-cell sequencing technologies have advanced our understanding of kidney biology and disease, but the loss of spatial information in these datasets hinders our interpretation of intercellular communication networks and regional gene expression patterns. New spatial transcriptomic sequencing platforms make it possible to measure the topography of gene expression at genome depth.BACKGROUNDSingle-cell sequencing technologies have advanced our understanding of kidney biology and disease, but the loss of spatial information in these datasets hinders our interpretation of intercellular communication networks and regional gene expression patterns. New spatial transcriptomic sequencing platforms make it possible to measure the topography of gene expression at genome depth.We optimized and validated a female bilateral ischemia-reperfusion injury model. Using the 10× Genomics Visium Spatial Gene Expression solution, we generated spatial maps of gene expression across the injury and repair time course, and applied two open-source computational tools, Giotto and SPOTlight, to increase resolution and measure cell-cell interaction dynamics.METHODSWe optimized and validated a female bilateral ischemia-reperfusion injury model. Using the 10× Genomics Visium Spatial Gene Expression solution, we generated spatial maps of gene expression across the injury and repair time course, and applied two open-source computational tools, Giotto and SPOTlight, to increase resolution and measure cell-cell interaction dynamics.An ischemia time of 34 minutes in a female murine model resulted in comparable injury to 22 minutes for males. We report a total of 16,856 unique genes mapped across our injury and repair time course. Giotto, a computational toolbox for spatial data analysis, enabled increased resolution mapping of genes and cell types. Using a seeded nonnegative matrix regression (SPOTlight) to deconvolute the dynamic landscape of cell-cell interactions, we found that injured proximal tubule cells were characterized by increasing macrophage and lymphocyte interactions even 6 weeks after injury, potentially reflecting the AKI to CKD transition.RESULTSAn ischemia time of 34 minutes in a female murine model resulted in comparable injury to 22 minutes for males. We report a total of 16,856 unique genes mapped across our injury and repair time course. Giotto, a computational toolbox for spatial data analysis, enabled increased resolution mapping of genes and cell types. Using a seeded nonnegative matrix regression (SPOTlight) to deconvolute the dynamic landscape of cell-cell interactions, we found that injured proximal tubule cells were characterized by increasing macrophage and lymphocyte interactions even 6 weeks after injury, potentially reflecting the AKI to CKD transition.In this transcriptomic atlas, we defined region-specific and injury-induced loss of differentiation markers and their re-expression during repair, as well as region-specific injury and repair transcriptional responses. Lastly, we created an interactive data visualization application for the scientific community to explore these results (http://humphreyslab.com/SingleCell/).CONCLUSIONSIn this transcriptomic atlas, we defined region-specific and injury-induced loss of differentiation markers and their re-expression during repair, as well as region-specific injury and repair transcriptional responses. Lastly, we created an interactive data visualization application for the scientific community to explore these results (http://humphreyslab.com/SingleCell/). |
| Author | Humphreys, Benjamin D Wu, Haojia Dixon, Eryn E Muto, Yoshiharu Wilson, Parker C |
| Author_xml | – sequence: 1 givenname: Eryn E orcidid: 0000-0003-4604-7907 surname: Dixon fullname: Dixon, Eryn E organization: Division of Nephrology, Department of Medicine, Washington University in St. Louis, St. Louis, Missouri – sequence: 2 givenname: Haojia orcidid: 0000-0002-7866-2544 surname: Wu fullname: Wu, Haojia organization: Division of Nephrology, Department of Medicine, Washington University in St. Louis, St. Louis, Missouri – sequence: 3 givenname: Yoshiharu surname: Muto fullname: Muto, Yoshiharu organization: Division of Nephrology, Department of Medicine, Washington University in St. Louis, St. Louis, Missouri – sequence: 4 givenname: Parker C orcidid: 0000-0001-8647-9662 surname: Wilson fullname: Wilson, Parker C organization: Department of Pathology and Immunology, Washington University in St. Louis, St. Louis, Missouri – sequence: 5 givenname: Benjamin D orcidid: 0000-0002-6420-8703 surname: Humphreys fullname: Humphreys, Benjamin D organization: Department of Developmental Biology, Washington University in St. Louis, St. Louis, Missouri |
| BackLink | https://www.ncbi.nlm.nih.gov/pubmed/34853151$$D View this record in MEDLINE/PubMed |
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| SubjectTerms | Acute Kidney Injury - genetics Acute Kidney Injury - pathology Acute Kidney Injury - physiopathology Animals Cell Communication - genetics Disease Models, Animal Female Gene Expression Profiling - methods Gene Expression Profiling - statistics & numerical data Mice Mice, Inbred C57BL Reperfusion Injury - genetics Reperfusion Injury - pathology Reperfusion Injury - physiopathology RNA-Seq Single-Cell Analysis - methods Single-Cell Analysis - statistics & numerical data Software |
| Title | Spatially Resolved Transcriptomic Analysis of Acute Kidney Injury in a Female Murine Model |
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