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In the Journal of Cell Science, University of Illinois Cancer Center member Alexandra Naba, PhD, presents MatriCom, a web application and a companion R package, devised to infer communications between extracellular matrix (ECM) components and between different cell populations and the ECM from single-cell RNA-sequencing (scRNA-Seq) datasets. Funding sources for this work include the National Institutes of Health (NIH) and the National Cancer Institute (NCI).

Naba is the co-corresponding author on the publication, “MatriCom, a Single-Cell RNA-Sequencing Data Mining Tool to Infer Cell-Extracellular Matrix Interactions,” along with Valerio Izzi, PhD, at the University of Oulu in Finland. Other coauthors are Asia M. Paguntalan, MS, a Visiting Research Specialist in the Naba Lab at the University of Illinois Chicago (UIC), and members of the Izzi Lab.

Pictured: Alexandra Naba, PhD

An Associate Professor in the Department of Physiology and Biophysics at the University of Illinois College of Medicine at UIC, Naba studies the role of the ECM in development, health and disease, mainly concentrating on cancer. The ECM is a complex meshwork of proteins forming the framework of all multicellular organisms. She seeks to understand how the ECM contributes to diseases and looks to develop new diagnostic and therapeutic strategies. Naba is also the founder of the Matrisome Project, a free online resource that helps scientists study the ECM by sharing protocols, tools and datasets. 

Her latest publication expands on her lab's efforts to devise intuitive tools to mine omic datasets with a focus on the ECM. MatriCom relies on a unique database, MatriComDB, of over 25,000 curated interactions involving matrisome components to impute interactions from expression data.

You can read the project abstract excerpted below and read the full article at this link. 

MatriCom offers the option to query user-generated or open-access datasets sourced from large sequencing efforts. MatriCom also accounts for specific rules governing ECM protein interactions. We illustrate how MatriCom can generate novel biological insights by building the first human kidney matrisome communication network. Last, applied to a panel of 46 scRNA-Seq datasets of healthy adult tissues, we demonstrate how MatriCom can shed light on the mechanisms of conservation and diversification of ECM assemblies and cell–ECM interactions.

This work was supported in part by the National Human Genome Research Institute (NHGRI), the NIH Common Fund through the Office of Strategic Coordination/NIH Office of the Director, the NCI, and a start-up fund from Naba’s department.