Go to The Journal of Clinical Investigation
  • About
  • Editors
  • Consulting Editors
  • For authors
  • Publication ethics
  • Publication alerts by email
  • Transfers
  • Advertising
  • Job board
  • Contact
  • Physician-Scientist Development
  • Current issue
  • Past issues
  • By specialty
    • COVID-19
    • Cardiology
    • Immunology
    • Metabolism
    • Nephrology
    • Oncology
    • Pulmonology
    • All ...
  • Videos
  • Collections
    • In-Press Preview
    • Resource and Technical Advances
    • Clinical Research and Public Health
    • Research Letters
    • Editorials
    • Perspectives
    • Physician-Scientist Development
    • Reviews
    • Top read articles

  • Current issue
  • Past issues
  • Specialties
  • In-Press Preview
  • Resource and Technical Advances
  • Clinical Research and Public Health
  • Research Letters
  • Editorials
  • Perspectives
  • Physician-Scientist Development
  • Reviews
  • Top read articles
  • About
  • Editors
  • Consulting Editors
  • For authors
  • Publication ethics
  • Publication alerts by email
  • Transfers
  • Advertising
  • Job board
  • Contact

Usage Information

Resident macrophage subpopulations occupy distinct microenvironments in the kidney
Matthew D. Cheung, Elise N. Erman, Kyle H. Moore, Jeremie M.P. Lever, Zhang Li, Jennifer R. LaFontaine, Gelare Ghajar-Rahimi, Shanrun Liu, Zhengqin Yang, Rafay Karim, Bradley K. Yoder, Anupam Agarwal, James F. George
Matthew D. Cheung, Elise N. Erman, Kyle H. Moore, Jeremie M.P. Lever, Zhang Li, Jennifer R. LaFontaine, Gelare Ghajar-Rahimi, Shanrun Liu, Zhengqin Yang, Rafay Karim, Bradley K. Yoder, Anupam Agarwal, James F. George
View: Text | PDF
Resource and Technical Advance Immunology Nephrology

Resident macrophage subpopulations occupy distinct microenvironments in the kidney

  • Text
  • PDF
Abstract

The kidney contains a population of resident macrophages from birth that expands as it grows and forms a contiguous network throughout the tissue. Kidney-resident macrophages (KRMs) are important in homeostasis and the response to acute kidney injury. While the kidney contains many microenvironments, it is unknown whether KRMs are a heterogeneous population differentiated by function and location. We combined single-cell RNA-Seq (scRNA-Seq), spatial transcriptomics, flow cytometry, and immunofluorescence imaging to localize, characterize, and validate KRM populations during quiescence and following 19 minutes of bilateral ischemic kidney injury. scRNA-Seq and spatial transcriptomics revealed 7 distinct KRM subpopulations, which are organized into zones corresponding to regions of the nephron. Each subpopulation was identifiable by a unique transcriptomic signature, suggesting distinct functions. Specific protein markers were identified for 2 clusters, allowing analysis by flow cytometry or immunofluorescence imaging. Following injury, the original localization of each subpopulation was lost, either from changing locations or transcriptomic signatures. The original spatial distribution of KRMs was not fully restored for at least 28 days after injury. The change in KRM localization confirmed a long-hypothesized dysregulation of the local immune system following acute injury and may explain the increased risk for chronic kidney disease.

Authors

Matthew D. Cheung, Elise N. Erman, Kyle H. Moore, Jeremie M.P. Lever, Zhang Li, Jennifer R. LaFontaine, Gelare Ghajar-Rahimi, Shanrun Liu, Zhengqin Yang, Rafay Karim, Bradley K. Yoder, Anupam Agarwal, James F. George

×

Usage data is cumulative from December 2024 through December 2025.

Usage JCI PMC
Text version 2,161 1,183
PDF 333 0
Figure 568 7
Table 70 0
Supplemental data 215 75
Citation downloads 85 0
Totals 3,432 1,265
Total Views 4,697

Usage information is collected from two different sources: this site (JCI) and Pubmed Central (PMC). JCI information (compiled daily) shows human readership based on methods we employ to screen out robotic usage. PMC information (aggregated monthly) is also similarly screened of robotic usage.

Various methods are used to distinguish robotic usage. For example, Google automatically scans articles to add to its search index and identifies itself as robotic; other services might not clearly identify themselves as robotic, or they are new or unknown as robotic. Because this activity can be misinterpreted as human readership, data may be re-processed periodically to reflect an improved understanding of robotic activity. Because of these factors, readers should consider usage information illustrative but subject to change.

Advertisement

Copyright © 2025 American Society for Clinical Investigation
ISSN 2379-3708

Sign up for email alerts