Stellate cells, hepatocytes, and endothelial cells imprint the Kupffer cell identity on monocytes colonizing the liver macrophage niche

Macrophages are strongly adapted to their tissue of residence. Yet, little is known about the cell-cell interactions that imprint the tissue-specific identities of macrophages in their respective niches. Using conditional depletion of liver Kupffer cells, we traced the developmental stages of monocytes differentiating into Kupffer cells and mapped the cellular interactions imprinting the Kupffer cell identity. Kupffer cell loss induced tumor necrosis factor (TNF)- and interleukin-1 (IL-1) receptor-dependent activation of stellate cells and endothelial cells, resulting in the transient production of chemokines and adhesion molecules orchestrating monocyte engraftment. Engrafted circulating monocytes transmigrated into the perisinusoidal space and acquired the liver-associated transcription factors inhibitor of DNA 3 (ID3) and liver X receptor-alpha (LXR-alpha). Coordinated interactions with hepatocytes induced ID3 expression, whereas endothelial cells and stellate cells induced LXR-alpha via a synergistic NOTCH-BMP pathway. This study shows that the Kupffer cell niche is composed of stellate cells, hepatocytes, and endothelial cells that together imprint the liver-specific macrophage identity

Modeling intercellular communication from transcriptomics data

Ontcijferen hoe cellen communiceren is nodig om betere inzichten te verwerven in fundamentele biologie en in ziektes waarin cel-cel-communicatieprocessen ontregeld zijn (bv. kanker en COVID-19). Het bestuderen van intercellulaire communicatie is echter zeer uitdagend. Dankzij transcriptomics technologieën is het nu mogelijk om de genexpressie van interagerende cellen te bepalen. Maar, het achterhalen van cel-cel communicatie uit deze transcriptomics data vereist geavanceerde algoritmes. Tijdens dit doctoraat werd een nieuw algoritme, NicheNet, ontwikkeld dat toelaat om te bestuderen hoe signalen geproduceerd door de ene cel de genexpressie kunnen beïnvloeden in een andere cel. Hierdoor kan NicheNet hypotheses genereren over welke communicatiepatronen cruciaal zijn in een bepaald biologische systeem. Dit werd geïllustreerd tijdens een studie over Kupffer cellen waarin verschillende hypotheses van NicheNet gevalideerd konden worden. Hoewel NicheNet een nuttige methode is gebleken, heeft het meerdere beperkingen. Daarom werd in het laatste deel van dit doctoraat een nieuw algoritme ontwikkeld, MultiNicheNet. MultiNicheNet bouwt verder op NicheNet om datasets van grote cohorten patiënten beter te kunnen analyzeren. Hierdoor kunnen betere hypotheses over de rol van cel-cel communicatie in verschillende ziektes gegenereerd worden. Samengevat beschrijft deze thesis dus de ontwikkeling en toepassing van nieuwe algoritmes om cel-cel communicatie te bestuderen o.b.v. transcriptomics data

NicheNet input networks

NicheNet input networks The directory should be unzipped and placed within the 'data/' folder </p

NicheNet : modeling intercellular communication by linking ligands to target genes

Computational methods that model how gene expression of a cell is influenced by interacting cells are lacking. We present NicheNet (https://github.com/saeyslab/nichenetr), a method that predicts ligand-target links between interacting cells by combining their expression data with prior knowledge on signaling and gene regulatory networks. We applied NicheNet to tumor and immune cell microenvironment data and demonstrate that NicheNet can infer active ligands and their gene regulatory effects on interacting cells

Data and code to reproduce all analyses described in the NicheNet paper

Here you can find a directory containing the data and code to reproduce all analyses described in the NicheNet paper. This will be open access after publication. The subdirectories contain following information: *networks: data and scripts to create the integrated ligand-receptor, signaling and gene regulatory networks *evaluation: data and scripts to validate the NicheNet model. Includes scripts for optimization and characterization of data sources as well. *application: data and scripts used to apply NicheNet to single-cell data from Puram et al. and Medaglia et al. *data_nichenet: final networks, models and expression dataset

A Complement Atlas identifies interleukin 6 dependent alternative pathway dysregulation as a key druggable feature of COVID-19

To improve COVID-19 therapy, it is essential to understand the mechanisms driving critical illness. The complement system is an essential part of innate host defense that can also contribute to injury. All complement pathways have been implicated in COVID-19 pathogenesis, however the upstream drivers and downstream consequences on tissue injury remain ill-defined. Here, we demonstrate that complement activation is mediated by the alternative pathway and we provide a comprehensive atlas of the alterations in complement around the time of respiratory deterioration. Proteome and single-cell sequencing mapping across cell types and tissues reveals a division of labor between lung epithelial, stromal and myeloid cells in the production of complement, in addition to liver-derived factors. Upstream, IL-6 drives complement responses, linking complement dysregulation to approved COVID-19 therapies. In an exploratory proteomic study, C5 inhibition improves epithelial damage and markers of disease severity. Collectively, these results identify complement dysregulation as a key druggable feature of COVID-19

A cellular hierarchy in melanoma uncouples growth and metastasis.

Although melanoma is notorious for its high degree of heterogeneity and plasticity1,2, the origin and magnitude of cell-state diversity remains poorly understood. Equally, it is unclear whether growth and metastatic dissemination are supported by overlapping or distinct melanoma subpopulations. Here, by combining mouse genetics, single-cell and spatial transcriptomics, lineage tracing and quantitative modelling, we provide evidence of a hierarchical model of tumour growth that mirrors the cellular and molecular logic underlying the cell-fate specification and differentiation of the embryonic neural crest. We show that tumorigenic competence is associated with a spatially localized perivascular niche, a phenotype acquired through an intercellular communication pathway established by endothelial cells. Consistent with a model in which only a fraction of cells are fated to fuel growth, temporal single-cell tracing of a population of melanoma cells with a mesenchymal-like state revealed that these cells do not contribute to primary tumour growth but, instead, constitute a pool of metastatic initiating cells that switch cell identity while disseminating to secondary organs. Our data provide a spatially and temporally resolved map of the diversity and trajectories of melanoma cell states and suggest that the ability to support growth and metastasis are limited to distinct pools of cells. The observation that these phenotypic competencies can be dynamically acquired after exposure to specific niche signals warrant the development of therapeutic strategies that interfere with the cancer cell reprogramming activity of such microenvironmental cues

Spatial proteogenomics reveals distinct and evolutionarily conserved hepatic macrophage niches

The liver is the largest solid organ in the body, yet it remains incompletely characterized. Here we present a spatial proteogenomic atlas of the healthy and obese human and murine liver combining single-cell CITE-seq, single-nuclei sequencing, spatial transcriptomics, and spatial proteomics. By integrating these multi-omic datasets, we provide validated strategies to reliably discriminate and localize all hepatic cells, including a population of lipid-associated macrophages (LAMs) at the bile ducts. We then align this atlas across seven species, revealing the conserved program of bona fide Kupffer cells and LAMs. We also uncover the respective spatially resolved cellular niches of these macrophages and the microenvironmental circuits driving their unique transcriptomic identities. We demonstrate that LAMs are induced by local lipid exposure, leading to their induction in steatotic regions of the murine and human liver, while Kupffer cell development crucially depends on their cross-talk with hepatic stellate cells via the evolutionarily conserved ALK1-BMP9/10 axis.SCOPUS: ar.jinfo:eu-repo/semantics/publishe