Cell-cell Frontiers

Title: Dynamics of bacterial communities driven by antagonistic quorum sensing pathways

Background: Cell-cell communication has the potential to transform a discrete group of cells into a thriving community.

Communication between unicellular bacteria can convert them into multicellular communities that can withstand several stressors effectively. This is particularly important for microorganisms competing for a specific niche, to establish their dominance over other microbes occupying the same habitat. A bacterial community in general is composed of isogenic but functionally diverse bacterial population subsets which stem from cellular heterogeneity. Such heterogeneous populations ensures that few subsets of bacteria adopt phenotypes that accommodate for fluctuating conditions in the environment during colonisation or infection of a host. This phenotypic plasticity in an isogenic bacterial population is key for the genesis of division of labour, however, the molecular basis of such functional diversification is largely uncharacterized and unexplored.

Quorum sensing is at the heart of bacterial…

Title: Novel strategies for studying proteostasis in the aging brain

Problem or question being addressed: Aging is the largest risk factor for a majority of neurodegenerative disorders, including Alzheimer’s disease (AD) and vascular dementia[1]. Despite growing incidence for such diseases, there are currently no therapeutics capable of reversing progression of aging-related cognitive decline. Through the use of heterochronic parabiosis however, or the surgical joining of circulatory systems between young and old mice, our group and others have demonstrated that blood-borne factors (generated by cells in the periphery) from young animals are capable of reversing many deleterious effects seen in the brain as a result of aging[2-6]. Understanding the molecular mechanisms underlying functional improvement in the brain post-parabiosis may help to identify novel therapeutic targets for neurodegeneration seen in disease or normal healthy aging. Complicating this, heterochronic parabiosis is an extraordinarily complex experimental paradigm, involving intricate cell-cell communication networks across…

MultiNicheNet: modeling cell-cell communication from multi-sample multi-condition single-cell transcriptomics data

Problem setting

Studying intercellular communication is essential for an improved understanding of tissue biology and disease pathophysiology. Advances in single-cell and spatial transcriptomics help address this need through their ability to generate molecular profiles of cells within a tissue1. Several computational approaches have been developed to investigate cell-cell communication from these profiles2. Most tools infer cell-cell communication by predicting interactions between ligands (membrane-bound or secreted extracellular proteins) expressed by sender cell types and receptors expressed by receiver cell types3. These tools provide a comprehensive list of potential expressed ligand-receptor pairs, but they don’t provide a functional understanding of cell-cell communication because they don’t infer the response of the receiver cell type in reaction to the ligand-receptor binding.

Other tools approach the cell-cell communication inference problem differently by incorporating downstream signaling of ligand-receptor interactions. We previously developed NicheNet (https://github.com/saeyslab/nichenetr) which predicts…

4D-NicheNet: modeling of spatiotemporal cell-cell communication dynamics by using prior knowledge on ligand-to-target signaling paths

Problem setting

Studying intercellular communication is essential for an improved understanding of tissue biology and disease pathophysiology. Advances in single-cell and spatial transcriptomics help address this need through their ability to generate molecular profiles of cells within a tissue1. Several computational approaches have been developed to investigate cell-cell communication from these profiles2,3. Most tools infer cell-cell communication by predicting interactions between ligands (membrane-bound or secreted extracellular proteins) expressed by sender cell types and receptors expressed by receiver cell types. Whereas these methods provide a comprehensive overview of potential expressed ligand-receptor pairs, they don’t provide a functional understanding of cell-cell communication because they don’t infer the response of the receiver cell type in reaction to the ligand-receptor binding.

To address this problem, we previously developed the computational method NicheNet (https://github.com/saeyslab/nichenetr)5. NicheNet starts from human or mouse…