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Research Spending & Results

Award Detail

Awardee:TRUSTEES OF COLUMBIA UNIVERSITY IN THE CITY OF NEW YORK, THE
Doing Business As Name:Columbia University
PD/PI:
  • Dana Peer
  • (212) 854-4397
  • dpeer@biology.columbia.edu
Award Date:06/04/2012
Estimated Total Award Amount: $ 1,150,810
Funds Obligated to Date: $ 1,150,810
  • FY 2015=$431,731
  • FY 2012=$719,079
Start Date:06/01/2012
End Date:05/31/2017
Transaction Type:Grant
Agency:NSF
Awarding Agency Code:4900
Funding Agency Code:4900
CFDA Number:47.074
Primary Program Source:040100 NSF RESEARCH & RELATED ACTIVIT
Award Title or Description:CAREER: Characterizing a Landscape of Signal Processing in the Immune System
Federal Award ID Number:1149728
DUNS ID:049179401
Parent DUNS ID:049179401
Program:Systems and Synthetic Biology

Awardee Location

Street:2960 Broadway
City:NEW YORK
State:NY
ZIP:10027-6902
County:New York
Country:US
Awardee Cong. District:10

Primary Place of Performance

Organization Name:Columbia University
Street:1212 Amsterdam Ave
City:New York
State:NY
ZIP:10027-7003
County:New York
Country:US
Cong. District:10

Abstract at Time of Award

Intellectual Merit. Signaling networks are the information processing devices of cells and organisms. These drive complex processes such as the development of an entire human being from a single cell and protecting the body in a coordinated response to a pathogen. The immune system presents a unique opportunity for studying development in mammals. White blood cells undergo differentiation and proliferation, a never-ending process throughout the life of the organism. The goal of this research is to present a global, systems view of the immune system, its function and its development. The approach is based on a new revolutionary technology, Mass-Cytometry, which enables us to observe cellular signaling and development at unprecedented resolution and detail. This empowers the exploration of development in a brand new way, unraveling the mystery of how we are made from just a single cell. Broader Impacts. Biological research is paved with novel technologies that lead to new opportunities, new challenges, and most importantly new discoveries. Elucidating general principles for molecular signal processing and development have great utility across a host of fundamental challenges in modern biology. This is an exciting era, during which interdisciplinary research can really make an impact on biology. To make such impact requires scientists trained in both quantitative and biological sciences. A key part of this project is to develop ways to distill complex science to a broader community, including science expo for K-8 and specialized systems biology training at the undergraduate and graduate levels. The modeling and visualization tools developed in this project are ideal for presenting the complexity of biological systems in a more tangible and concrete manner for students and are ideal training and outreach resources. The synergistic combination of technology and computation will have a transformative influence on broad topics across all of biology.

Publications Produced as a Result of this Research

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Sean C. Bendall, Kara L. Davis, El-ad David Amir, Michelle D. Tadmor, Erin F. Simonds, Tiffany J. Chen, Daniel K. Shenfeld, Garry P. Nolan, and Dana Pe?er "Single-Cell Trajectory Detection Uncovers Progression and Regulatory Coordination in Human B Cell Development" Cell, v.157, 2014, p.714. doi:http://dx.doi.org/10.1016/j.cell.2014.04.005 

Sean C Bendall*, Kara L Davis*, El-ad David Amir*, Michelle D Tadmor, Erin F Simonds, Tiffany J Chen, Daniel K Shenfeld, Garry P Nolan&, Dana Pe?er& "Single-Cell Trajectory Detection Uncovers Progression and Regulatory Coordination in Human B cell Development" Cell, v.157, 2014, p..

Gabriele Gut , Michelle D Tadmor, Dana Pe?er Lucas Pelkmans Prisca Liberali "Trajectories of cell-cycle progression from fixed and local cell populations" Nature Methods, v.12, 2015, p.951. doi:DOI:10.1038/NMETH.3545 

Sayantan Bose, Zhenmao Wan, Ambrose Carr, Abbas H. Rizvi, Gregory Vieira, Dana Pe?er and Peter A. Sims "Scalable microfluidics for single-cell RNA printing and sequencing" Genome Biology, v.16, 2015, p.. doi:DOI 10.1186/s13059-015-0684-3 

Gabriele Gut*, Michelle D. Tadmor*, Dana Pe?er&, Lucas Pelkmans&, Prisca Liberali& (2 first authors, 3 last authors) "Cycler: inferring a trajectory of cell cycle progression from fixed cell populations" Nature Methods, v., 2015, p..

El-ad David Amir, Kara L Davis, Michelle D Tadmor, Erin F Simonds, Jacob H Levine, Sean C Bendall, Daniel K Shenfeld, Smita Krishnaswamy, Garry P Nolan Dana Pe?er "viSNE enables visualization of high dimensional single-cell data and reveals phenotypic heterogeneity of leukemia" Nature Biotechnology, v.31, 2013, p.545. doi:doi:10.1038/nbt.2594 

Jacob H. Levine, Erin F. Simonds, Sean C. Bendall, Kara L. Davis, El-ad D. Amir, Michelle Tadmor, Oren Litvin, Harris Fienberg, Astraea Jager, Eli Zunder, Rachel Finck, Amanda L. Gedman, Ina Radtke, James R. Downing, Dana Pe?er*, Garry P. Nolan* (* Co-sen "Data-driven phenotypic dissection of AML reveals progenitor-like cells that correlate with prognosis" Cell, v., 2015, p..

El-ad David Amir, Erin Simonds, Michelle Tadmor, Kara Davis, Jacob Levine, Sean Bendall, Daniel Shenfeld , Smita Krishnaswamy, Garry Nolan and Dana Pe?er "viSNE enables visualization of high dimensional single-cell data and reveals phenotypic heterogeneity of leukemia" Nature Biotechnology, v.31, 2013, p..

Conditional density-based analysis of T cell signaling in single-cell data "Smita Krishnaswamy, Matthew H. Spitzer, Michael Mingueneau, Sean C. Bendall, Oren Litvin, Erica Stone, Dana Pe?er, Garry P. Nolan" Science, v.346, 2014, p.1079. doi:DOI: 10.1126/science/1250689 

Jacob H. Levine, Erin F. Simonds, Sean C. Bendall, Kara L. Davis, El-ad D. Amir, Michelle D. Tadmor, Oren Litvin, Harris G. Fienberg, Astraea Jager, Eli R. Zunder, Rachel Finck, Amanda L. Gedman, Ina Radtke, James R. Downing, Dana Pe?er, and Garry P. Nola "Data-Driven Phenotypic Dissection of AML Reveals Progenitor-like Cells that Correlate with Prognosis" Cell, v.162, 2015, p.184. doi:http://dx.doi.org/10.1016/j.cell.2015.05.047 

M. Mingueneau, S. Krishnaswamy, M. Spitzer, S.C. Bendall, E. L. Stone, S. M. Hedrick, D. Pe?er, D. Mathis, G. P. Nolan, C. Benoist "Single-cell mass cytometry of TCR signaling: amplification of small initial differences result in low ERK activation in NOD mice" PNAS, v.111, 2014, p.. doi:DOI:10.1073/pnas.1419337111 

Sean C Bendall, Kara L Davis, El-ad David Amir, Michelle D Tadmor, Erin F Simonds, Tiffany J Chen, Daniel K Shenfeld, Garry P Nolan, Dana Pe?er "Single-Cell Trajectory Detection Uncovers Progression and Regulatory Coordination Points in Human B cell Development" Cell, v.157, 2014, p.. doi:doi:10.1016/j.cell.2014.04.005 

Yaron E. Antebi , Shlomit Reich-Zeliger, Yuval Hart, Avi Mayo, Inbal Eizenberg, Jacob Rimer, Prabhakar Putheti, Dana Pe?er, Nir Friedman "Mapping Differentiation under Mixed Culture Conditions Reveals a Tunable Continuum of T Cell Fates" PLoS Biology, v.11, 2013, p.e1001616. doi:doi:10.1371/journal.pbio.1001616 

Manu Setty, Michelle Tadmor, Shlomit Reich-Zeliger, Omer Angel, Tomer Meir Salame, Sean Bendall, Nir Friedman, Dana Pe?er "Wishbone identifies bifurcating developmental trajectories from single cell data" Nature Biotechnology, v., 2016, p..

El-ad David Amir, Kara L Davis, Michelle D Tadmor, Erin F Simonds, Jacob H Levine, Sean C Bendall, Daniel K Shenfeld, Smita Krishnaswamy, Garry P Nolan, Dana Pe?er "viSNE enables visualization of high dimensional single-cell data and reveals phenotypic heterogeneity of leukemia" Nature Biotechnology, in press, v.?, 2013, p.?.

Sayantan Bose; Zhenmao Wan; Ambrose Carr; Abbas H. Rizvi; Gregory Vieira; Dana Pe'er; Peter A. Sims "Scalable Microfluidics for Single Cell RNA Printing and Sequencing" Genome Biology, v., 2015, p..

Sandhya Prahabakan*, Elham Azizi*, Ambrose Carr, Dana Pe?er "Dirichlet Process Mixture Model for Correcting Technical Variation in Single-Cell Gene Expression Data" International Conference for Machine Learning, v., 2016, p..

Smita Krishnaswamy, Matthew H. Spitzer, Michael Mingueneau, Sean C Bendall, Oren Litvin, Erica Stone, Dana Pe?er*#, Garry P Nolan* (* these authors contributed equally, # corresponding author) "Conditional Density-based Analysis of Variability in T Cell Signaling in Single-cell Data" Science, v., 2014, p..

Smita Krishnaswamy, Matthew H. Spitzer, Michael Mingueneau, Sean C. Bendall, Oren Litvin, Erica Stone, Dana Pe?er, Garry P. Nolan "Conditional density-based analysis of T cell signaling in single-cell data" Science, v.346, 2014, p.. doi:DOI: 10.1126/science.1250689 

Antebi YE, Reich-Zeliger S, Hart Y, Mayo A, Putheti P, Pe?er D, and Friedman N "Mapping differentiation under mixed conditions reveals a tunable continuum of T cell fates" PLOS Biolog, v.11, 2013, p..

Manu Setty, Michelle D Tadmor, Shlomit Reich-Zeliger, Omer Angel, Tomer Meir Salame, Pooja Kathail, Kristy Choi, Sean Bendall, Nir Friedman Dana Pe?er "Wishbone identifies bifurcating developmental trajectories from single-cell data" Nature Biotechnology, v.34, 2016, p.637. doi:doi:10.1038/nbt.3569 

Sandhya Prabhakaran, Elham Azizi, Ambrose Carr, Dana Pe'er "Dirichlet Process Mixture Model for Correcting Technical Variation in Single-Cell Gene Expression Data" Proceedings of the 33rd International Conference on Machine Learning,, v.48, 2016, p.1070. doi:http://dl.acm.org/citation.cfm?id=3045504 

Michael Mingueneau, Smita Krishnaswamy, Matthew H. Spitzer, Sean C. Bendall, Erica L. Stone, Stephen M. Hedrick, Dana Pe'er, Diane Mathis, Garry P. Nolan and Christophe Benoist "Single-cell mass cytometry of TCR signaling: amplification of small initial differences result in low ERK activation in NOD mice" PNAS, v., 2014, p..


Project Outcomes Report

Disclaimer

This Project Outcomes Report for the General Public is displayed verbatim as submitted by the Principal Investigator (PI) for this award. Any opinions, findings, and conclusions or recommendations expressed in this Report are those of the PI and do not necessarily reflect the views of the National Science Foundation; NSF has not approved or endorsed its content.

Rapidly evolving single cell technologies are transforming biology allowing researchers to query biological questions at unprecedented resolution. The NSF funding has enabled us to advance and utilize these technologies to gain fundamental insights into signaling as a means of cellular response, deepen our understanding of cell fate decisions and comprehensive characterization of heterogeneity in AML, a cancer of the blood cells. During the lifetime of the award, we have published 10 peer-reviewed high impact manuscripts in world leading journals such as Cell, Science and Nature Biotechnology.

Intellectual merit of the award

Single cell data is inherently noisy and very complex in nature. As part of our research, we have developed computational tools and methods such as viSNE, Biscuit and Phenograph which form a key part of the visualization and data analysis tool set widely used by researchers for single cell data analysis with viSNE being virtually synonymous with single cell data visualization. Our tools have produced results that are highly accurate, robust and reproducible in a wide array of applications.

Understanding how organisms develop from single cells and more generally cellular differentiation and how cells assimilate information from their environments to mount effective response are some of the most fundamental questions in biology. We have used single cell data to shed light on these key processes through our research funded by NSF. Our methods DREMI and DREVI to functionally and quantitatively to characterize intracellular signaling networks demonstrate how immune cells fine tune their responses and mount effective response. Our trajectory detection algorithms, Wanderlust, Cycler and Wishbone transformed the way cellular differentiation is computationally studied by establishing a novel framework for modeling differentiation. This cutting-edge research has significantly advanced our understanding of cell fate decisions and regulatory processes driving immune cell differentiation.

Broader impact of the award

The research carried out was highly inter-disciplinary and collaborative in nature bringing together scientists with expertise in computer science, mathematics, molecular biology and biochemistry. NSF funding has enabled us to cross-train graduate students and post docs across multiple disciplines, equipping a new breed of computational biologists to tackle key problems in biology. We have also provided research opportunities for undergraduate students who have benefited from their experiences in the lab to enter graduate programs in some of the best universities.

 The insights gained from our research along with the development of computational methods for understanding and analyzing single cell data was one of the drivers for establishment of the Human Cell Atlas project. Human Cell Atlas project is a global, multi-institute, transformative project that aims to build comprehensive reference maps for all cell types in the human body providing a basis for understanding human health and treating disease.

 

 


Last Modified: 09/13/2017
Modified by: Dana Peer

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