Development and Aging
As cells develop, they inevitably evolve from a seemingly homogeneous population into a diverse array of types.
Studies that have blended different cell populations to examine population averages have the disadvantage of missing interesting heterogeneities that can only be known by studying single cells.
Like many scientists in the field, S. Steven Potter, Ph.D., professor of developmental biology at Cincinnati Children’s Hospital Medical Center, is using a mix of arrays and sequencing to profile gene expression in single cells.
“In one application we are performing microarray and RNA-seq gene expression profiling of single cells to better understand the earliest steps in making developmental decisions,” Dr. Potter says. “In another application we use single-cell analysis to create a high-resolution atlas of the gene expression patterns that drive organogenesis. For this, we disassemble developing organs to single cells, perform gene expression profiling, and reassemble the data to generate a fine structure picture of the gene expression programs that create the distinct differentiated cell type lineages of the adult organ.”
Meanwhile, the Buck Institute for Research on Aging’s James M. Flynn, Ph.D., research associate, is examining single cells as they age.
“We are examining the transcriptional profile of cells as they progress from presenescent to senescent stages, with significant implications in aging and cancer,” Dr. Flynn tells GEN. “We are currently looking into a number of bone disease models to help define cell types within the bone matrix.”
He and his colleagues have developed a method to extract single cortical osteoblasts from a small volume of compact bone and have identified rare cell populations responsible for generating new bone.
Using fluorescence-activated cell sorting (FACS) and single-cell transcriptomics, Dr. Flynn et al., have delved into the heterogeneity of osteoblast lineage cells derived in vivo from translational disease models. “We are now actively pursuing this approach to understand how gene expression in these cell populations shifts from a normal to disease state,” he says.
Once derived, storing rare cells can be a challenge. To address this, Dr. Flynn and his colleagues have developed sample storage methods that allow them to analyze cells down the line without significant loss of RNA integrity. Taking this approach, samples can be easily transported without loss of signal, or reliance on specialized equipment, he says.
“A second motivation when developing our approach is the ability to easily modify the target cell populations using FACS as our understanding of the cell biology changes,” Dr. Flynn explains. “I think this kind of iterative selection process will help pinpoint novel cell populations, which have previously been masked as we’ve only been studying the average from many thousands of cells in bulk studies of gene expression profiling.”