Spotless, a reproducible pipeline for benchmarking cell type deconvolution in spatial transcriptomics.

Spatial transcriptomics (ST) technologies allow the profiling of the transcriptome of cells while keeping their spatial context. Since most commercial untargeted ST technologies do not yet operate at single-cell resolution, computational methods such as deconvolution are often used to infer the cell type composition of each sequenced spot. We benchmarked 11 deconvolution methods using 63 silver standards, 3 gold standards, and 2 case studies on liver and melanoma tissues. We developed a simulation engine called synthspot to generate silver standards from single-cell RNA-sequencing data, while gold standards are generated by pooling single cells from targeted ST data. We evaluated methods based on their performance, stability across different reference datasets, and scalability. We found that cell2location and RCTD are the top-performing methods, but surprisingly, a simple regression model outperforms almost half of the dedicated spatial deconvolution methods. Furthermore, we observe that the performance of all methods significantly decreased in datasets with highly abundant or rare cell types. Our results are reproducible in a Nextflow pipeline, which also allows users to generate synthetic data, run deconvolution methods and optionally benchmark them on their dataset (https://github.com/saeyslab/spotless-benchmark).

A complement atlas identifies interleukin-6-dependent alternative pathway dysregulation as a key druggable feature of COVID-19.

Improvements in COVID-19 treatments, especially for the critically ill, require deeper understanding of the mechanisms driving disease pathology. The complement system is not only a crucial component of innate host defense but can also contribute to tissue injury. Although all complement pathways have been implicated in COVID-19 pathogenesis, the upstream drivers and downstream effects on tissue injury remain poorly defined. We demonstrate that complement activation is primarily mediated by the alternative pathway, and we provide a comprehensive atlas of the complement alterations around the time of respiratory deterioration. Proteomic and single-cell sequencing mapping across cell types and tissues reveals a division of labor between lung epithelial, stromal, and myeloid cells in complement production, in addition to liver-derived factors. We identify IL-6 and STAT1/3 signaling as an upstream driver of complement responses, linking complement dysregulation to approved COVID-19 therapies. Furthermore, an exploratory proteomic study indicates that inhibition of complement C5 decreases epithelial damage and markers of disease severity. Collectively, these results support 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.

TIM3+ TRBV11-2 T cells and IFNγ signature in patrolling monocytes and CD16+ NK cells delineate MIS-C.

In rare instances, pediatric SARS-CoV-2 infection results in a novel immunodysregulation syndrome termed multisystem inflammatory syndrome in children (MIS-C). We compared MIS-C immunopathology with severe COVID-19 in adults. MIS-C does not result in pneumocyte damage but is associated with vascular endotheliitis and gastrointestinal epithelial injury. In MIS-C, the cytokine release syndrome is characterized by IFNγ and not type I interferon. Persistence of patrolling monocytes differentiates MIS-C from severe COVID-19, which is dominated by HLA-DRlo classical monocytes. IFNγ levels correlate with granzyme B production in CD16+ NK cells and TIM3 expression on CD38+/HLA-DR+ T cells. Single-cell TCR profiling reveals a skewed TCRß repertoire enriched for TRBV11-2 and a superantigenic signature in TIM3+/CD38+/HLA-DR+ T cells. Using NicheNet, we confirm IFNγ as a central cytokine in the communication between TIM3+/CD38+/HLA-DR+ T cells, CD16+ NK cells, and patrolling monocytes. Normalization of IFNγ, loss of TIM3, quiescence of CD16+ NK cells, and contraction of patrolling monocytes upon clinical resolution highlight their potential role in MIS-C immunopathogenesis.

ILC3s control splenic cDC homeostasis via lymphotoxin signaling.

The spleen contains a myriad of conventional dendritic cell (cDC) subsets that protect against systemic pathogen dissemination by bridging antigen detection to the induction of adaptive immunity. How cDC subsets differentiate in the splenic environment is poorly understood. Here, we report that LTα1ß2-expressing Rorgt+ ILC3s, together with B cells, control the splenic cDC niche size and the terminal differentiation of Sirpα+CD4+Esam+ cDC2s, independently of the microbiota and of bone marrow pre-cDC output. Whereas the size of the splenic cDC niche depended on lymphotoxin signaling only during a restricted time frame, the homeostasis of Sirpα+CD4+Esam+ cDC2s required continuous lymphotoxin input. This latter property made Sirpα+CD4+Esam+ cDC2s uniquely susceptible to pharmacological interventions with LTßR agonists and antagonists and to ILC reconstitution strategies. Together, our findings demonstrate that LTα1ß2-expressing Rorgt+ ILC3s drive splenic cDC differentiation and highlight the critical role of ILC3s as perpetual regulators of lymphoid tissue homeostasis.

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.

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-α (LXR-α). Coordinated interactions with hepatocytes induced ID3 expression, whereas endothelial cells and stellate cells induced LXR-α 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.