Integrate Knowledge: Exploring Single Cells
Understanding why some individual cells respond differently to stimuli such as drugs and disease proteins may provide insights into aging and disease. James Eberwine, PhD, Elmer Holmes Bobst Professor of Pharmacology in the Perelman School of Medicine, and Junhyong Kim, PhD, PhD, Edmund J. and Louise W. Kahn Professor of Biology in the School of Arts and Sciences, have received a five-year, $10 million grant from the National Institutes of Health (NIH) to study these variations, by looking at the role of messenger RNA (mRNA) molecules in this process. Kim and Eberwine are also co-directors of the Penn Genomic Frontiers Institute, a university-wide institute dedicated to the advancement of the interdisciplinary field of genomics research.
Eberwine and Kim are studying how to characterize the variability in identity and abundances of RNA molecules that are transcribed from the genome of human neurons and heart cells. These are the so-called excitable cells, those that use bioelectricity for communication and everyday functions. Many human nervous system diseases derive from changes in electrical responsiveness of neurons and heart arrhythmias account for many heart-related deaths.
There are considerable cell-to-cell differences in function associated with normal environmental stimuli and in dysfunction associated with disease in excitable cells. This is likely involved in why cells respond differently to such stimuli as drugs and disease proteins. Understanding this variation may provide insights into how cells respond individually and in coordinated groups to aging and disease challenges.
The Penn team proposes to look at the extent of single-cell variation for the entire transcriptome of different excitable cell types and also for a subset of mRNAs that encode therapeutically important molecules called G protein-couple receptors.
They will combine key technologies developed in the Eberwine and Kim labs to approach single-cell variation. The Eberwine lab developed the methods for single-cell mRNA analysis including a novel functional genomics technology called Transcriptome Induced Phenotype Remodeling, or TIPeR, to manipulate the mRNA of excitable cells. TIPeR uses RNA populations to direct the DNA in the host nucleus to change the cell’s RNA populations to that of a destination cell type, which in turn changes the phenotype of the cell by resulting in the expression of different genes.
The Eberwine lab was the first to develop such RNA reprogramming technologies. There are about 100,000 mRNA molecules in a neuron at any one time. TIPeR permits all or a fraction of these mRNAs to be moved between live cells where they will modify recipient cell function in ways that can analyzed.
The Kim lab developed novel computational analysis tools and systems-biology models for analyzing single cell variation. These include new algorithms and statistical methods for characterizing RNA sequencing data from single cells and a systems-biology model that frames RNA population of cells as dynamic systems with key functional constraints defining allowable variability of different cell types and how they change with a cell’s microenvironment. The two labs have been working together for the past six years, integrating state-of-art molecular biology, neuroscience, and computational biology.
This is an interdisciplinary effort requiring the expertise of clinical and basic scientists, including neurosurgeons and cardiologists. Co-investigators involved in this project include Sean Grady, MD, Charles Harrison Frazier Professor and Chairman of Neurosurgery at the Perelman School of Medicine, Jai-Yoon Sul, assistant professor of Pharmacology, Tamas Bartfai, PhD, the Scripps Research Institute and Bernhard Kuhn, MD, Assistant Professor of Pediatrics, Boston Children’s Hospital.
One Cell at a Time
Single cell analysis emerged as an important field of research after new technologies with improved sensitivity made it possible to measure cell-to-cell differences in living organisms and correlate the variation with changes in biological function and disease processes.
By profiling individual cells, researchers can identify rare cell types as well as alterations in the health or condition of specific cells that may relate to functional changes and to determine the influence of cellular organization and environment on such cells and states. The long-term goal of the SCAP is to accelerate the move towards personalizing health to the cellular level by understanding the link between cell variation, tissue and organ function, and emergence of disease.
Overall, the NIH to accelerate the development and application of single cell analysis across a variety of fields. The goal is to understand what makes individual cells unique and to pave the way for medical treatments that are based on disease mechanisms at the cellular level.
“The development of new technologies that can detect differences between individual cells within the same tissue is crucial to our understanding of a wide variety of diseases,” said NIH Director Francis S. Collins, M.D., Ph.D. “This Common Fund Program is an excellent example of how the NIH can accelerate the pace of biomedical discovery.”
The Single Cell Analysis Program will fund three research centers that will work together to identify patterns of gene expression in individual human cells within a variety of tissues including the brain, heart, placenta, and olfactory system. The goal is to reveal previously undetectable differences in the molecular composition of individual cells; this will offer a new way to categorize cells using a genetic signature. The funded groups will be managed as an integrated network to maximize collaboration. All data and protocols will be made available to the research community.
For a detailed description of the funded grants as well as information about the Single Cell Analysis Program, please visit http://commonfund.nih.gov/singlecell/.
The Single Cell Analysis Program is funded through the Common Fund, and managed by the NIH Office of the Director in partnership with the National Institute of Biomedical Imaging and Biotechnology (NIBIB) and National Institute of Mental Health (NIMH), both part of NIH.