ACADEMIA

Combining multimodal methods to identify disease-causing genes of interest and extract more information at a significantly reduced cost

Scientists at the New York Genome Center (NYGC) and the Icahn School of Medicine at Mount Sinai have been awarded a $1.5 million collaborative grant over three years from the Chan Zuckerberg Initiative (CZI) to support the development of a toolkit for integrated multimodal cell profiling. The project involves the development of new methods and tools that leverage the strengths of existing single-cell modalities and innovative computational methods to enable a more robust and efficient characterization of human immune cells. The team's new toolkit will be made freely available to the scientific community.

The award-winning project, "Multi-Modal Cell Profiling and Data Integration to Atlas the Immune System," is led by Peter Smibert, Ph.D., Manager, NYGC Technology Innovation Lab. Rahul Satija, Ph.D., Core Faculty Member at the New York Genome Center and Assistant Professor of Biology at New York University, and Adeeb Rahman, PhD, Director of Technology Development, Human Immune Monitoring Center and Associate Professor of Genetics and Genomic Sciences at Icahn School of Medicine at Mount Sinai, are co-principal investigators. The toolkit under development aims to leverage the particular strengths of individual technologies including scale, depth, and spatial resolution and use computational integration of the different data types for a more comprehensive view of single cells. {module In-article}

"We are deeply grateful to CZI for their support of our innovative and collaborative research to develop and deploy next-generation genomic tools that further enhance interrogation of individual cells," said Tom Maniatis, Ph.D., NYGC's Scientific Director and CEO. "Single-cell multimodal analysis is poised to play a key role in the detailed characterization of cells central to the Human Cell Atlas."

"Our aim is to both develop new methods for measuring important molecules in cells and exploit the advantages of existing methods," said Dr. Smibert. "By integrating the output of different technologies, we can cost-effectively interrogate cells in their appropriate tissue context." He noted his collaborators' expertise in single-cell modalities and computational methods is essential to the success of the project. The collaborative project will take advantage of the strengths of each of the core technologies: multimodal RNA and protein data from CITE-seq, developed in the NYGC Technology Innovation Lab, will inform the much higher throughput protein data from Mass cytometry (CyTOF), and together will inform the spatial data obtained by Multiplexed Ion Beam Imaging (MIBI) to identify cell interactions and neighborhoods. Dr. Rahman is an early adopter of CITE-seq and has deep experience deploying CyTOF and MIBI in his research. Dr. Satija is a leading developer of computational methods to effectively harness and integrate single-cell analysis methods.

The grant is part of CZI's Seed Networks for the Human Cell Atlas program, which aims to support foundational tools and resources for the Human Cell Atlas project, a scientific-led global initiative to create a reference map of all cell types in the human body and generate a fundamental reference for biomedical research. CZI's Seed Networks projects will generate new tools, open source analysis methods, and significant contributions of diverse data types to the Human Cell Atlas Data Coordination Platform, a resource that will enable broad data sharing across researchers and research institutes. Drs. Smibert and Satija were recipients of a 2017 CZI one-year pilot grant to develop a toolkit for the Human Cell Atlas research community on CITE-seq, and Dr. Satija has a separate pilot Human Cell Atlas grant for the integration of single-cell data from 2018.

The NYGC Technology Innovation Lab is a dedicated incubator within the NYGC comprised of a multidisciplinary team in which staff scientists and faculty, as well as many research collaborators, can explore and test breakthrough genomic tools and ideas.