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Becton Dickinson Acquires Single-Cell Genomics Startup Cellular Research

NEW YORK (GenomeWeb) – Becton Dickinson said after the close of the market Tuesday that it has acquired San Francisco Bay Area single-cell genomics startup Cellular Research for an undisclosed amount.

Founded in 2011 by Stanford University and Silicon Valley entrepreneurs including Stephen Fodor, Glenn Fu, and Stephen Quake, Cellular Research has developed tools for massively parallel single-cell genetic analysis based on its proprietary molecular indexing technology.

Similar to DNA barcoding techniques, molecular indexing encodes individual mRNA molecules within single cells at the time of reverse transcription, enabling the generation of highly multiplexed gene expression profiles.

BD said that by combining this technology with its cell sorting and flow cytometry expertise and product portfolio, it will be able to provide researchers with an integrated sample prep workflow to quantify and study gene expression in large numbers of individual cells. The comprehensive workflow is intended to enable researchers to better understand the genomic diversity of single cells and help identify new approaches for targeted clinical diagnostics and therapies in fields such as immunology, immune-oncology, and personalized medicine, BD said.

BD and Cellular Research already had a co-marketing agreement in place for single-cell sequencing that combined the molecular barcoding technology with BD's FACS single-cell sorting instruments.

In a statement, Linda Tharby, president of BD Life Sciences, noted that the addition of Cellular Research builds on BD's October 2014 acquisition of Irish sample prep automation firm GenCell "and underscores BD's commitment to a genomics strategy focused on next-generation sequencing sample preparation."

Cellular Research currently offers the Pixel System, which provides absolute digital mRNA quantitation from single cells for gene expression studies. It also told GenomeWeb in February that its plans to launch a massively parallel single-cell RNA-seq application in 2016.

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