(searched for: doi:10.1038/s41591-021-01344-3)
International Journal of Molecular Sciences, Volume 22; doi:10.3390/ijms22147249
The liver is an essential immunological organ due to its gatekeeper position to bypassing antigens from the intestinal blood flow and microbial products from the intestinal commensals. The tissue-resident liver macrophages, termed Kupffer cells, represent key phagocytes that closely interact with local parenchymal, interstitial and other immunological cells in the liver to maintain homeostasis and tolerance against harmless antigens. Upon liver injury, the pool of hepatic macrophages expands dramatically by infiltrating bone marrow-/monocyte-derived macrophages. The interplay of the injured microenvironment and altered macrophage pool skews the subsequent course of liver injuries. It may range from complete recovery to chronic inflammation, fibrosis, cirrhosis and eventually hepatocellular cancer. This review summarizes current knowledge on the classification and role of hepatic macrophages in the healthy and injured liver.
Frontiers in Immunology, Volume 12; doi:10.3389/fimmu.2021.705465
Liver allograft recipients are more likely to develop transplantation tolerance than those that receive other types of organ graft. Experimental studies suggest that immune cells and other non-parenchymal cells in the unique liver microenvironment play critical roles in promoting liver tolerogenicity. Of these, liver interstitial dendritic cells (DCs) are heterogeneous, innate immune cells that appear to play pivotal roles in the instigation, integration and regulation of inflammatory responses after liver transplantation. Interstitial liver DCs (recruited in situ or derived from circulating precursors) have been implicated in regulation of both ischemia/reperfusion injury (IRI) and anti-donor immunity. Thus, livers transplanted from mice constitutively lacking DCs into syngeneic, wild-type recipients, display increased tissue injury, indicating a protective role of liver-resident donor DCs against transplant IRI. Also, donor DC depletion before transplant prevents mouse spontaneous liver allograft tolerance across major histocompatibility complex (MHC) barriers. On the other hand, mouse liver graft-infiltrating host DCs that acquire donor MHC antigen via “cross-dressing”, regulate anti-donor T cell reactivity in association with exhaustion of graft-infiltrating T cells and promote allograft tolerance. In an early phase clinical trial, infusion of donor-derived regulatory DCs (DCreg) before living donor liver transplantation can induce alterations in host T cell populations that may be conducive to attenuation of anti-donor immune reactivity. We discuss the role of DCs in regulation of warm and liver transplant IRI and the induction of liver allograft tolerance. We also address design of cell therapies using DCreg to reduce the immunosuppressive drug burden and promote clinical liver allograft tolerance.
Published: 23 May 2021
The growing availability of single-cell data has sparked an increased interest in the inference of cell-cell communication from this data. Many tools have been developed for this purpose. Each of them consists of a resource of intercellular interactions prior knowledge and a method to predict potential cell-cell communication events. Yet the impact of the choice of resource and method on the resulting predictions is largely unknown. To shed light on this, we created a framework, available at https://github.com/saezlab/ligrec_decoupler, to facilitate a comparative assessment of methods for inferring cell-cell communication from single cell transcriptomics data and then compared 15 resources and 6 methods. We found few unique interactions and a varying degree of overlap among the resources, and observed uneven coverage in terms of pathways and biological categories. We analysed a colorectal cancer single cell RNA-Seq dataset using all possible combinations of methods and resources. We found major differences among the highest ranked intercellular interactions inferred by each method even when using the same resources. The varying predictions lead to fundamentally different biological interpretations, highlighting the need to benchmark resources and methods. Findings Built a framework to systematically combine 15 resources and 6 methods to estimate cell-cell communication from single-cell RNA data Cell-cell communication resources are often built from the same original databases and very few interactions are unique to a single resource. Yet overlap varies among resources and certain biological terms are unevenly represented Different methods and resources provided notably different results The observed disagreement among the methods could have a considerable impact on the interpretation of results