Perinatal liver inflammation is associated with persistent elevation of CXCL10 and its canonical receptor CXCR3 on common myeloid progenitors.

Biliary atresia (BA) is a leading cause of liver failure in infants. Despite effective surgical drainage, patients with BA exhibit attenuated immune responses to childhood vaccines, suggesting there are long-lasting alterations to immune function. The perinatal liver is home to hematopoietic stem and progenitor cells (HSPCs) and serves as the epicenter for rapidly progressive and significantly morbid inflammatory diseases like BA. We have previously established the role of neonatal myeloid progenitors in the pathogenesis of perinatal liver inflammation (PLI) and hypothesize that PLI leads to long-term changes to HSPCs in mice that recovered from PLI. To test this hypothesis, we compared the changes that occur to HSPCs and mature myeloid populations in the bone marrow of adult mice during homeostasis and during PLI. Our results demonstrate that HSPCs from animals that recover from PLI ("PLI-recovered") undergo long-term expansion with a reduced proliferative capacity. Notably, PLI leads to persistent activation of common myeloid progenitors through the involvement of CXCL10 and its canonical receptor, CXCR3. Our data suggests that the CXCR3-CXCL10 axis may mediate the changes in HSPCs that lead to altered immune function observed in BA, providing support for a targetable pathway to mitigate the detrimental long-term immune effects observed in patients with BA.

Concordance of MERFISH spatial transcriptomics with bulk and single-cell RNA sequencing.

Spatial transcriptomics extends single-cell RNA sequencing (scRNA-seq) by providing spatial context for cell type identification and analysis. Imaging-based spatial technologies such as multiplexed error-robust fluorescence in situ hybridization (MERFISH) can achieve single-cell resolution, directly mapping single-cell identities to spatial positions. MERFISH produces a different data type than scRNA-seq, and a technical comparison between the two modalities is necessary to ascertain how to best integrate them. We performed MERFISH on the mouse liver and kidney and compared the resulting bulk and single-cell RNA statistics with those from the Tabula Muris Senis cell atlas and from two Visium datasets. MERFISH quantitatively reproduced the bulk RNA-seq and scRNA-seq results with improvements in overall dropout rates and sensitivity. Finally, we found that MERFISH independently resolved distinct cell types and spatial structure in both the liver and kidney. Computational integration with the Tabula Muris Senis atlas did not enhance these results. We conclude that MERFISH provides a quantitatively comparable method for single-cell gene expression and can identify cell types without the need for computational integration with scRNA-seq atlases.