dkNET Webinar: Mapping the Human Landscape of Metabolite-Mediated Communication Signals Between Single Cells

Join dkNET Webinar on Friday, November 8, 2024, 11 am - 12 pm PT

Presenter: Kaifu Chen, PhD, Associate Professor, Department of Pediatrics, Harvard Medical School

Abstract

Cell-cell communication (CCC) is crucial for cellular function and tissue homeostasis. Due to fundamental differences in the underlying biological mechanisms, existing methods for protein-oriented CCC detection often miss metabolite-mediated CCC (mCCC). To fill this gap, we first developed MEBOCOST, an algorithm designed on top of scRNA-seq and metabolic flux balance analysis to detect mCCC among single cells. Comprehensive benchmarking analyses based on simulation, spatial, CRISPR screen, and clinical patient data demonstrated the robustness of MEBOCOST in detecting biologically significant mCCC events. We next applied MEBOCOST to landscape analysis and identified 210,215 significant mCCC events from 2 million single cells across 228 cell types of 13 tissues, 56 disease states, and 70 biological conditions. Notably, analysis in white adipose tissues unraveled macrophages as the predominant source of mCCC reprogramming in obese patients. Moreover, analysis in mice brown adipocyte tissue successfully recapitulated known and further uncovered new mCCC events, including a glutamine-mediated endothelial-to-adipocyte communication experimentally verified to regulate adipocyte differentiation. The MEBOCOST algorithm and our web portal, MCCP (http://cbp-kfc.org/mccp/), which allows researchers to explore the mCCC atlas easily, will be a valuable resource for metabolism research in diverse biological contexts and disease samples.

The top 3 key questions that MEBOCOST can answer:

1. Is there a curated knowledge base for individual metabolites reported as might mediate signaling events between cells in a tissue?

2. Is there a web portal for biological researchers to easily check individual metabolite-mediated communication signals between cells in any published single cell RNA-sequencing (scRNA-seq) datasets?

3. Is there a computational tool to detect metabolite-mediated communication signals between cells in a new single cell RNA sequencing (scRNA-seq) dataset?

Dial-in Information: https://uchealth.zoom.us/meeting/register/tZArde6orz8iGdKoCg5ysS4C_wm6ONaEouCt

Date/Time: Friday, November 8, 2024, 11 am - 12 pm PT

Upcoming webinars schedule: https://dknet.org/about/webinar