The Single Cell Analysis Program (SCAP) is funded by the National Institutes of Health (NIH) Common Fund. The Common Fund began a decade ago to support collaborative programs with participation by all NIH Institutes and Centers. These programs must also be transformative, catalytic, synergistic, and unique. The overall goal of SCAP is to accelerate the discovery, development, and translation of cross-cutting, innovative approaches to analyzing the heterogeneity of biologically relevant populations of cells in situ. The SCAP recently announced the launch of an exciting new “Follow that Cell” Challenge. The Challenge is a 2-phase call for submissions describing novel and robust methods for analysis of individual cells that can detect and assess dynamic changes in cell behavior and function over time. We recently spoke with Dr. Yong Yao, Challenge Lead for the NIH SCAP and Program Director at the National Institute of Mental Health (NIMH), part of NIH, to find out a bit more about the Challenge and the interesting subject area it focuses around.
Hello Dr. Yao – thank you for joining us today. Could you start by giving us a bit of background information on the Single Cell Analysis Program, its aims and mission, and how the Follow that Cell Challenge complements it?
Glad to be here, thank you! The Single Cell Analysis Program (SCAP) that we know today evolved out of several public workshops and discussions with various stakeholders in the scientific community beginning in 2010.
In conventional research, scientists often assume that most cells of a particular “type” are the same – however, data suggest that individual cells in a population could have different qualities and behaviors from one another, and this could impact the overall function and health of a cellular population. Surprisingly, we know very little about how individual cells change over time and we know even less about how to measure the functional changes in complex mixtures of cells, which is really what a tissue or organ is composed of.
It became clear that this is a cross-cutting, innovative research area that NIH should explore further. With this in mind, the overall goal of the SCAP is to accelerate the discovery, development and translation of approaches to analyzing the heterogeneity of biologically relevant populations of cells in situ. Specifically, the program aims to:
- Address key roadblocks in analyzing single cells by supporting cross-cutting, transformative research (See currently funded research here: http://commonfund.nih.gov/singlecell/fundedresearch)
- Catalyze the emerging field of single cell research by building a synergistic program of unique initiatives
- Coordinate NIH efforts in advancing the next-generation of technologies for single cell analysis in order to improve our ability to characterize cells and understand the biological significance of heterogeneity
The NIH has lots of grants supporting studies on populations of cells, watching cells in a dish using microscopes etc., however there are relatively few studies that tackle the issue of cellular heterogeneity by examining single cells and their microenvironment in living organisms. We hope that the SCAP and this Challenge will stimulate the field in addressing this.
The Follow that Cell Challenge is looking to source proposals for a method for analysis at the single cell level – can you explain what you mean by the term ‘single cell analysis’ and what is the potential impact of such novel methods in healthcare?
“Single cell analysis” refers to the study of individual cells and cellular heterogeneity in a population, which encompasses a wide range of novel molecular and cellular techniques. Some techniques and tools include advanced optical, electrochemical, mass spectrometry instrumentation, and sensor technology, while others involve micromanipulation of cells and gene sequencing techniques. Many approaches currently in use can offer snapshots of single cells, but are often not amenable to longitudinal studies that monitor changes in individual cells in situ. Cells are the fundamental units of life. Single cell analysis is not just one more step towards more sensitive detection, but is a critical step towards fundamental understanding of biology and human diseases. We know that most cells are healthy but this can change; they can change in significant ways becoming cancerous, infected by viruses, or can die prematurely. While many of the research projects NIH has supported in the past 3 years in this program are sometimes deemed “high risk”, we strive to support science that is of high impact and has the potential to transform patient care and therapeutics. Understanding how cells behave in healthy conditions, how they unfortunately transition to disease states, and how they may recover back to normal in response to clinical treatment will have great impact in healthcare.
How is the Challenge structured and why do you feel crowdsourcing has the potential to source advances in this area where more traditional innovation strategies have not?
What we are trying to do here is really different. Instead of just funding a few more grants, the NIH decided to offer a prize to the individual or team that comes up with the most creative way to measure changes in individual cells over time. We want new things, maybe even ideas that are a little off the wall. We hope this challenge stimulates fresh ideas from scientists with different backgrounds; we are looking for engineers, materials scientists, chemists etc. to partner with cell biologists and disease specialists to help solve this challenge.
Inventing new technologies and approaches that will help us track and measure changes in cells could have a profound effect on how we view cell health and emerging disease states at the cellular level. We hope this takes precision medicine to an all-new level.
Phase 1 of the challenge is theoretical, the idea phase. Finalists will be selected to move on to Phase 2 which will allow solvers to put their idea into practice. Phase 2 will be judged on how well the individual or team executed their plan and the quality of the data produced. Part of what’s different here for the NIH is that no money is awarded until and unless a solution is deemed to be a “winner”.
Thanks for your time Dr. Yao. Do you have any specific advice or guidance for people looking to enter the Challenge?
There is still time to register and submit a solution—the deadline is December 15, 2014. Because NIH is following the America COMPETES legislation, it’s important that potential solvers read the announcement in the Federal Register (https://www.federalregister.gov/articles/2014/08/11/2014-18870/announcement-of-requirements-and-registration-for-follow-that-cell-challenge) closely to understand the details of the challenge including eligibility criteria, what’s expected from potential solvers, how solutions will be judged etc. There is a lot of fine print.
We look forward to seeing your innovative ideas and new approaches that open new doors for basic biology and disease related research!