Estimation of GFP-tagged RNA numbers from temporal fluorescence intensity data

Motivation: MS2-GFP-tagging of RNA is currently the only method to measure intervals between consecutive transcription events in live cells. For this, new transcripts must be accurately detected from in-tensity time traces. Results: We present a novel method for automatically estimating RNA numbers and production intervals from temporal data of cell fluores-cence intensities that reduces uncertainty by exploiting temporal in-formation. We also derive a robust variant, more resistant to outliers caused e.g. by RNAs moving out of focus. Using Monte Carlo simu-lations, we show that the quantification of RNA numbers and produc-tion intervals is generally improved compared with previous methods. Finally, we analyze data from live Escherichia coli and show statistic-ally significant differences to previous methods. The new methods can be used to quantify numbers and production intervals of any fluores-cent probes, which are present in low copy numbers, are brighter than the cell background and degrade slowly