Scientists from Albert Einstein College of Medicine have used automated fluorescence microscopy to visualize transcriptional "pulsing" of single genes in live eukaryotic cells one of the first kinetic interrogations into cellular transcriptional activity and a step toward eventually understanding how a cell's surroundings affect gene expression.
The study is also an example of how scientists can use rudimentary high-content imaging technology in basic cell biology a trend that high-content imaging vendors have recently begun to notice [see box, below].
As detailed in a paper published in the May 23 issue of Current Biology, a group led by Albert Einstein researchers Jonathan Chubb (currently at the University of Dundee, UK) and Robert Singer used an in vivo RNA detection technique to visualize transcription of an endogenous developmental gene in amoeba.
Specifically, the technique exploited the "high-affinity interaction between a genomic stem loop and the coat protein of the MS2 RNA bacteriophage," the researchers wrote. They integrated cassettes for MS2 stem loops into single endogenous genes of the amoeba Dictyostelium. The loops were transcribed into RNA, and the researchers detected the resulting transcripts using GFP fused to the phage MS2 coat protein.
"The advantage to the cell of pulsatile rather than continuous transcription may be sensitivity in the control of gene expression."
Although the researchers did not use a commercial high-content imaging platform per se, their imaging setup was driven by IP Lab and certain scientific image acquisition and analysis software developed by Scanalytics that was acquired with the company last year by BD Biosciences. Since then, BD has incorporated the technology into its high-content analysis and screening platforms (see CBA News, 7/18/2005).
Otherwise, the Albert Einstein scientists used an inverted Olympus microscope, appropriate excitation and emission filters, a motorized microscope stage, and a highly sensitive CCD camera essentially the "guts" of a lower end kinetic high-content imaging system.
Their studies revealed that gene expression occurs in discrete and irregular pulses of activity with typical "gene-on" and "gene-off" times of five to six minutes. The researchers also found that the basic properties of transcriptional pulses, such as length and intensity, were consistent throughout development of the cell, and that changes in frequency were "modest."
The above results were "surprising in light of the strong changes in transcriptional stimuli occurring throughout differentiation, and [imply] rigidity in signaling circuits regulating a gene," the researchers wrote. "Variation occurs not in these properties of the pulses, but in the number of cells recruited into the expressing population.
"The advantage to the cell of pulsatile rather than continuous transcription may be sensitivity in the control of gene expression," they wrote. "Pulsing permits greater flexibility in transcriptional decisions the cell is less committed to a particular program if it does not make all the required RNA in one burst."
In addition, the researchers used an algorithm that can detect non-random clustering of cells based on gene expression similar to the type of algorithm that might be applied in a commercial high-content imaging system to reveal that aggregated cells tend to express genes in concert with one another.
Ben Butkus ([email protected])
Academic Trendspotting: Can Vendors Exploit an Emerging HCI Marketplace?
The Albert Einstein study underscores the two types of markets that are emerging for high-content imaging in the academic sector. To be sure, academics are increasingly engaging in the type of high-throughput, cell-based, small-molecule screening campaigns traditionally undertaken by pharmaceutical companies.
Such efforts often require a commercial high-content imaging system capable of scanning well plates with relatively high throughput, but stripped down enough to make them more financially feasible for academic labs.
Most HCS vendors now offer a platform that fits the above profile Cellomics' KinetiScan, Molecular Devices' ImageXpress Micro, BD Biosciences' Pathway 435 and 415, and Applied Precision's CellWorx are all examples.
But live-cell imaging has also been around for years in basic academic research, and many scientists have more recently begun adopting high-content imaging components sensitive CCD cameras, automated hardware, and sophisticated image-analysis software to fashion "homemade" automated microscopes in their labs.
Vendors have also begun to address this emerging market segment, particularly the image analysis aspect. Molecular Devices' MetaMorph software is perhaps the most well-known and established example even though this software drives the company's commercial HCS platforms, it is also one of the more popular image-analysis packages employed by academic researchers conducting sophisticated cellular imaging.
Other options in this space include the IP Lab from BD Biosciences used by the Albert Einstein researchers; Definiens' Cellenger; software from Vala Sciences; BioImagene's CellMine; SVision's SVCell; and open-source packages such as the Whitehead Institute's CellProfiler.