Metabolic regulation by p53 family members

The function of p53 is best understood in response to genotoxic stress, but increasing evidence suggests that p53 also plays a key role in the regulation of metabolic homeostasis. p53 and its family members directly influence various metabolic pathways, enabling cells to respond to metabolic stress. These functions are likely to be important for restraining the development of cancer but could also have a profound effect on the development of metabolic diseases, including diabetes. A better understanding of the metabolic functions of p53 family members may aid in the identification of therapeutic targets and reveal novel uses for p53-modulating drugs

CCL24 regulates biliary inflammation and fibrosis in primary sclerosing cholangitis

ˆCCL24 is a pro-fibrotic, pro-inflammatory chemokine expressed in several chronic fibrotic diseases. In the liver, CCL24 plays a role in fibrosis and inflammation, and blocking CCL24 led to reduced liver injury in experimental models. We studied the role of CCL24 in primary sclerosing cholangitis (PSC) and evaluated the potential therapeutic effect of blocking CCL24 in this disease. Multidrug resistance gene 2-knockout (Mdr2-/-) mice demonstrated CCL24 expression in liver macrophages and were used as a relevant experimental PSC model. CCL24-neutralizing monoclonal antibody, CM-101, significantly improved inflammation, fibrosis, and cholestasis-related markers in the biliary area. Moreover, using spatial transcriptomics, we observed reduced proliferation and senescence of cholangiocytes following CCL24 neutralization. Next, we demonstrated that CCL24 expression was elevated under pro-fibrotic conditions in primary human cholangiocytes and macrophages, and it induced proliferation of primary human hepatic stellate cells and cholangiocytes, which was attenuated following CCL24 inhibition. Correspondingly, CCL24 was found to be highly expressed in liver biopsies of patients with PSC. CCL24 serum levels correlated with Enhanced Liver Fibrosis score, most notably in patients with high alkaline phosphatase levels. These results suggest that blocking CCL24 may have a therapeutic effect in patients with PSC by reducing liver inflammation, fibrosis, and cholestasis

Metabolic adaptation of acute lymphoblastic leukemia to the central nervous system microenvironment depends on Stearoyl CoA desaturase

Metabolic reprogramming is a key hallmark of cancer, but less is known about metabolic plasticity of the same tumor at different sites. Here, we investigated the metabolic adaptation of leukemia in two different microenvironments, the bone marrow and the central nervous system (CNS). We identified a metabolic signature of fatty acid synthesis in CNS leukemia, highlighting stearoyl-CoA desaturase (SCD) as a key player. In vivo SCD overexpression increases CNS disease, whereas genetic or pharmacological inhibition of SCD decreases CNS load. Overall, we demonstrated that leukemic cells dynamically rewire metabolic pathways to suit local conditions and that targeting these adaptations can be exploited therapeutically

Emergence of division of labor in tissues through cell interactions and spatial cues

Summary: Most cell types in multicellular organisms can perform multiple functions. However, not all functions can be optimally performed simultaneously by the same cells. Functions incompatible at the level of individual cells can be performed at the cell population level, where cells divide labor and specialize in different functions. Division of labor can arise due to instruction by tissue environment or through self-organization. Here, we develop a computational framework to investigate the contribution of these mechanisms to division of labor within a cell-type population. By optimizing collective cellular task performance under trade-offs, we find that distinguishable expression patterns can emerge from cell-cell interactions versus instructive signals. We propose a method to construct ligand-receptor networks between specialist cells and use it to infer division-of-labor mechanisms from single-cell RNA sequencing (RNA-seq) and spatial transcriptomics data of stromal, epithelial, and immune cells. Our framework can be used to characterize the complexity of cell interactions within tissues

Deep learning and alignment of spatially resolved single-cell transcriptomes with Tangram

AbstractCharting an organs’ biological atlas requires us to spatially resolve the entire single-cell transcriptome, and to relate such cellular features to the anatomical scale. Single-cell and single-nucleus RNA-seq (sc/snRNA-seq) can profile cells comprehensively, but lose spatial information. Spatial transcriptomics allows for spatial measurements, but at lower resolution and with limited sensitivity. Targeted in situ technologies solve both issues, but are limited in gene throughput. To overcome these limitations we present Tangram, a method that aligns sc/snRNA-seq data to various forms of spatial data collected from the same region, including MERFISH, STARmap, smFISH, Spatial Transcriptomics (Visium) and histological images. Tangram can map any type of sc/snRNA-seq data, including multimodal data such as those from SHARE-seq, which we used to reveal spatial patterns of chromatin accessibility. We demonstrate Tangram on healthy mouse brain tissue, by reconstructing a genome-wide anatomically integrated spatial map at single-cell resolution of the visual and somatomotor areas.</jats:p