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Assessment of engineered cells using CellNet and RNA-seq.

Arthur H Radley¹, Remy M Schwab^1,2, Yuqi Tan^1,2

¹Department of Biomedical Engineering, Johns Hopkins University School of Medicine, Baltimore, Maryland, USA.

Nature Protocols

|April 28, 2017

Summary

CellNet assesses engineered cells by analyzing gene expression data against known networks. This computational platform helps improve cell fate engineering protocols for various cell types and species.

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Targeted RNA Sequencing Assay to Characterize Gene Expression and Genomic Alterations

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Published on: August 4, 2016

Area of Science:

Computational biology
Stem cell research
Genomics

Background:

Directed differentiation and direct conversion are key methods for engineering cell populations.
Assessing the fidelity of engineered cells to their intended cell type is crucial.
Gene regulatory networks (GRNs) are fundamental to cell identity and function.

Purpose of the Study:

To describe the application of the CellNet computational platform to RNA-sequencing data.
To provide a method for building new CellNet platforms for diverse species and cell types.
To enhance cell fate engineering protocols through data-driven hypotheses.

Main Methods:

CellNet analyzes gene expression data (microarray or RNA-seq) by comparing it to established expression profiles.
It assesses the degree to which cell- and tissue-specific GRNs are established in engineered cells.
New CellNet platforms can be constructed using public gene expression data for custom applications.

Main Results:

CellNet can be effectively applied to RNA-sequencing data, expanding its utility beyond microarrays.
The platform can be adapted to create new CellNet databases for different species or cell/tissue types.
Running CellNet analysis on preprocessed data is rapid (minutes), while building a new platform takes hours.

Conclusions:

CellNet is a versatile computational tool for evaluating engineered cells and guiding protocol optimization.
The adaptability of CellNet to RNA-seq and custom databases significantly broadens its research applications.
This work facilitates advancements in stem cell engineering and regenerative medicine.