There are several factors which may be confounding your analysis. 1. Not all integration sites are equivalent. Even if a population of cells all has a single integration site, the amount of readout of the gene is highly influenced by the specific location of the integration. You can see everything from no protein to high amounts depending on the activity of the region where the gene integrates. 2. GFP is a relatively long lived protein, at least in some cells. This means that depending on the timing of your experiment, you may be measuring something like cumulative production and not steady state levels. At high production levels, you may have a hard time keeping the positive cells on scale. 3. If your cell population is not clonal, there may be differences in the lifetime of the protein which will also affect levels of GFP independently of the number of integration sites. Combining all of these factors, a broad distribution of fluorescence intensity is not too much of a surprise. Best of luck with your project. -Jim Weaver ************************************************* * * * James L. Weaver Ph.D. * * Division of Applied Pharmacology Research * * Office of Testing & Research * * CDER MOD-1, FDA * * 8301 Muirkirk Rd, Laurel MD 20708 * * * * Phone: 301-827-8237 * * Fax: 301-594-3037 * * Email:WEAVER@CDER.FDA.GOV * * * * This email is my personal opinion and is * * NOT in any way official U.S. FDA Policy * ************************************************* * -----Original Message----- * From: Daniel Chipchase [mailto:D.Chipchase@oxfordbiomedica.co.uk] * Sent: Thursday, January 17, 2002 11:24 AM * To: Cytometry Mailing List * Subject: Statistical methods for Expression Analysis * * * * Dear Flowers, * I have been looking at promoter function in transduced cells * using a GFP * reporter for some time and am generally unhappy with the * rigour of the * 'answers' I am getting. What I really require is a * statistical method which * gives me a reproducible constant. * * The problem is that the 'true' level of expression should be the * fluorescence I would get off of 1 copy of integrated genome * (inc promoter * under investigation and GFP cassette) per cell. However, the * number of * copies per cell will vary (normally) I suppose, and also as * a result of my * transduction efficiency. As my transduction efficiency * improves I would * suppose hypothetically that the modal number of copies per cell would * increase. * * Anyway at present I am assuming that at a low transduction * percentage any * cells transduced will likely only include (and express) 1 * copy of GFP. * Therefore, after removing non-transduced cells, the * geometric mean of those * remaining should give me the expression level of GFP, which * when normalised * against a control vector gives me a benchmark. However, * having reviewed my * accumulated data it is often difficult to see any constant * expression at * lower levels of transduction. * * Also the means by which I remove the transduced from the * non-tranduced cells * is problematic. At low transduction levels where expression * may be fairly * low it is often the case that the transduced population is merely a * 'shoulder' on the the untransduced population when viewed on * a 1 parameter * histogram. I have found no 'satisfactory' way of determining * transduction * percentages in these cases. * * It has occurred to me that at at transduction levels * approaching 100% the * geometic mean might give you an answer that is constant and * comparable * between vectors. Might this not be a better approach? (it * would use up a lot * of raw materials though). * * Hoping someone out there understands what I talking about, * and can give me a * few hints * * Daniel Chipchase * Research Assistant *
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