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Frontiers in Veterinary Science· 2026Q1

Spatial transcriptomic profiling of porcine tissue microarray detecting subclinical circovirus infection

Woo Seok Kim, Sunmin Song, Hyeonjeon Cho, Jong-Eun Park et al.

Short summary

Spatial transcriptomics successfully detected porcine circovirus type 2 (PCV2) transcripts within proximal tubular cells in archival kidney tissue microarrays, enabling subclinical infection diagnosis.

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Key points

  • Spatial transcriptomics (Stereo-seq) identified four distinct kidney microstructures (glomerulus, proximal tubule, distal convoluted tubule, collecting duct) using marker genes.
  • PCV2 transcripts were detected specifically within proximal tubular cells.
  • The method successfully analyzed archival tissue microarrays, demonstrating high sensitivity for host and microbe transcriptomes.
  • This technique integrates gene expression profiling with bioinformatics for tissue microstructure reconstruction and pathogen diagnosis.

AI-generated from the title and abstract; the full text is not read.

Abstract

Porcine Circovirus type 2 (PCV2) is a key pathogen in pigs that induces host immunosuppression, leading to severe secondary infections such as porcine circovirus-associated disease (PCVAD), resulting in significant economic losses for the swine industry. More recently, it has emerged as a pathogen that needs to be ruled out in porcine xenotransplantation research due to issues related to latent infection. In this study, we established a methodology for distinguishing cell types and detecting the viral transcripts within porcine tissue microarrays using spatial transcriptomics techniques. Random primer capture-based Stereo-seq, followed by unsupervised cell clustering, distinguished four major microstructures within kidney tissue cores, each defined by a distinct marker gene: glomerulus (MAGI2), proximal tubule (CUBN), distal convoluted tubule (SLC8A1), and collecting duct (ERBB4). We further detected PCV2 transcripts in well-segmented proximal tubular cells. The spatial transcriptomics technique used in this study was able to detect both host and microbe transcriptomes with high sensitivity in tissue microarrays re-embedded from archival samples for diagnostic purposes. This suggests that spatial transcriptomics is an advanced pathology technology that integrates spatially resolved gene expression profiling with downstream bioinformatics and computational analysis, enabling the reconstruction of tissue microstructure and the diagnosis of emerging and re-emerging pathogens at the molecular level.

The authors' abstract, as published at the source. Frontiers in Veterinary Science, 2026 · DOI ↗

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Field: Animal Science and Zoology

Animal Science and ZoologyAgricultural and Biological Sciences