The West team is able to record the signal transduction dynamics with unprecedented temporal resolution involving millisecond switch times each with microsecond precision.
“We use the insulin-like growth factor receptor (IGFR) as a model for this analysis because the receptor is already dimerized in its active state on the cell membrane. This ensures the molecular states we capture are synchronized and not hidden within the variable diffusion timescales required for dimerization upon ligand stimulus,” commented Dr. West.
“Dr. Chiang has perfected the microfluidic timing and built an envirostat system that controls the normal cell culture conditions (37°C and 5% CO2) to maintain the integrity of the cells from syringe to microfluidic stimulation and reaction arrest. We can interrogate the status of the kinase center and determine the nature of the switching on process by comparing data from lengthy ligand treatments and from various IGFR mutants. Mechanistically, does the center work like a light switch or is it more like a domino effect from one phosphorylation site to another?”
Now that the team has optimized the system and demonstrated proof of concept, some of the interesting biological questions are just now being addressed. Is there cell-to-cell variation in stimulus patterns? Are there reaction intermediates that haven’t been seen before?
Beyond the study of early signaling, the system is amenable to the investigation of a huge variety of fast cell-surface interactions. Dr. West hopes the microfluidic technology will prompt biochemists and cell biologists to ask new questions.
Can you extrapolate the analytical results from the study of a cell population to what is going on in a single cell? As technology and analytical methods improve, scientists are starting to ask those questions and coming up with some surprising results.
At Fluidigm, Kenneth Livak, Ph.D., senior scientific fellow, has focused on meeting the challenges of analyzing single-cell gene-expression data. Practical steps for analyzing single-cell qPCR data had to be developed because the stochastic nature of eukaryotic transcription at the single-cell level meant that conventional methods for analyzing qPCR data often do not apply.
The company has developed protocols and developed an instrument, the BioMark™ HD, that enables qPCR analysis of transcripts from single cells. In population studies the data yields an average value rather than a real measure of individual cells.
The data can be misleading because this average is dominated by a small number of cells that have a high number of transcripts. Consequently, average measures of gene expression don’t give the real picture of what’s going on in the single cell as most cells in a population, even a homogeneous population, have a substantially lower number of transcripts that the average value.
“Single-cell gene expression is intrinsically noisy,” noted Dr. Livak. “This is based on the observation that eukaryotic transcription occurs in pulses with bursts of transcription interspersed with inactivity when transcripts decay. Consequently, there is significant variation from cell-to-cell that can range as much as 10- to 1,000-fold for every gene we look at.
“Normalization to housekeeping genes doesn’t help, as these housekeeping genes can vary as much as the genes we’re studying. We find that it is best to use ‘unnormalized’ data that actually is normalized on a per cell basis.”
More specifically, Dr. Livak reported that the solution is to look at enough genes in enough cells to apply a multivariant analysis to get a robust signature as to what is going on at the level of single-cell gene expression. A multivariant analysis, either hierarchal clustering or principal component analysis, allows you to look at the pattern of all genes in the study to get an understanding of what is happening at the individual cell level.
At Fluidigm, the approach is to take FACs-sorted tissue culture cells and plate them individually directly into lysis buffer in wells in a standard 96-well PCR plate. Reagents are added and the plate is put in a thermal cycler for the multiplexed reverse-transcriptase step. Ideally, in this multiplex preamplification step, sufficient cycles are run so that single cDNA molecules will generate at least five molecules per qPCR reaction chamber in the next step.
The cDNA pools are transferred by eight-channel pipetter to one side of the microfluidic chip. On the other side, singleplex PCR primers for the 96 genes to be analyzed are added. The chip is then put within the Biomark HD instrument where all pairwise combinations are mixed. The PCR reactions are run and analyzed in real time within the instrument, yielding 9,216 data points. The data output is presented as a histogram that shows the number of cells with each expression level bin for all the genes in the study.
Genomics Research Center
Convinced that this approach to gene expression in single cells will give new insight to biological phenomena, Fluidigm, in collaboration with the Broad Institute, recently announced the formation of a new single-cell genomics research center to be housed at the Broad Institute, where Dr. Livak will serve as the alliance manager. In this role he will oversee research projects at the center to make sure that while they deliver scientifically, they also help to develop protocols and identify opportunities that can be used and shared with the wider scientific community.
Fluidigm said the Broad Institute is the first of what could be many institutes around the world that will join the firm in its quest to push the envelope on what is known about biological phenomena at the single-cell level. The center will focus on the acceleration of the development of research methods and discoveries in mammalian single-cell genomics, as well as serve as a hub for collaboration among single-cell genomics researchers in pioneering fields including stem cells and cancer biology.
In the end, these learnings may help us, by analogy, to understand the forest for the trees.