Related Experiment Video
Updated: Jul 8, 2026
Isolation of Region-specific Microglia from One Adult Mouse Brain Hemisphere for Deep Single-cell RNA Sequencing
Published on: December 3, 2019
Integration of bulk RNA-seq and scRNA-seq reveals cell subsets and gene signatures associated with Glaesserella
Ke Xu1, Zixin Wang1, Ying Zhu1
1Laboratory of Genetic Breeding, Reproduction and Precision Livestock Farming & Hubei Provincial Center of Technology Innovation for Domestic Animal Breeding, School of Animal Science and Nutritional Engineering, Wuhan Polytechnic University, Wuhan, 430023, China.
Background:
Glaesserella parasuis (GPS) is a major bacterial pathogen threatening the pig industry worldwide. It is widely prevalent in pig farms across China; however, to date, no effective strategies for its prevention and control are available. It causes divergent outcomes ranging from asymptomatic carriage to lethal disease; however, the underlying mechanisms remain unclear. In this study, we integrated bulk- and single-cell RNA-seq of over 98,000 porcine alveolar macrophages from a well-defined piglet infection model (including control, mild, and severe groups).
Results:
This is the first multi-omics dissection of macrophage heterogeneity in GPS infection at single-cell resolution. We identified four transcriptionally distinct macrophage subpopulations, with two inflammation-associated subsets (Im-Mac and Inf- Mac) that expanded dramatically with increasing disease severity. Pseudotime analysis revealed that severe infection skews macrophage differentiation almost exclusively toward pro-inflammatory fates. Integrated analysis revealed two opposing cellular programs dictating clinical outcomes: a protective program (active in mild infections, marked by CXCL10, CD69, SERPING1, and KMO) balancing immune recruitment with regulation, and a pathogenic program (dominating severe infections, characterized by a 16-gene signature including AMCF-II, CCL2, SERPINB2, CD14, ECE1, and IL7R). Notably, 9 of these 16 genes overlapped with a core set of 58 genes that were positively correlated with disease progression.
Conclusions:
We propose a balanced model in which the equilibrium between protective and pathogenic macrophage programs dictates the outcome of GPS infection. These findings provide novel cell-state-specific biomarkers and a molecular framework for understanding the divergent clinical outcomes of GPS infection.
