Tutorials: Mar 15, 2010 (Vol. 30, No. 6)

Integrating Cellular Imaging Data Effectively

Advances Allow Researchers to Compare Images Taken at Different Times and Settings

(Page 1 of 2)

    Fluorescence has emerged as a widely used signal in life science research. In particular, fluorescence microscopy techniques have enabled researchers to characterize molecular interactions in natural cell environments. These techniques have been enhanced by electron multiplying charge coupled device (EMCCD) cameras providing sub-electron read noise and enabling visualization of everything from single molecules and sub-cellular structures to whole animals in vivo.

    Fluorescence microscopy has advanced all stages of the drug discovery process, including target discovery, candidate screening with cell-based assays, toxicology evaluations, and mode-of-action studies. However, analyzing the wealth of knowledge from imaging experiments can be difficult. For years, life science researchers have struggled with the irreproducibility of images from CCD and EMCCD cameras. The analog-to-digital units (ADUs) in which those cameras report imaging data are known by many names, including gray-scale units and fluorescence units.

    The problem is that ADUs are merely electronic representations of the number of photons hitting the sensor. The way in which cameras make this representation varies, even between the same make and model of camera. So an ADU doesn’t directly correlate with real incident light.

    While technological advances have brought quantitative elements to imaging—such as cell counting and structural measurement—solutions for quantitation of fluorescence intensity, independent of users and equipment, is far from standard.

    This is a hurdle for scientific data sharing, especially for multisite collaborations. The variable nature of the raw ADUs that cameras produce limit the labs’ ability to control for experimental variability and directly compare imaging data. Thus, knowledge produced by imaging experiments can be difficult to interpret.

    Why ADUs Are Arbitrary

    When scientific images are acquired on a CCD or EMCCD camera, the observed pixel value is impacted by many factors, including variable gain settings, sensor aging (in the case of some EMCCD cameras), and camera-to-camera differences in sensitivity and bias (or offset) settings.

    Essential for visualizing dim signals from live cells is the high signal-to-noise ratio provided by EMCCD cameras. Those cameras multiply photoelectrons generated by incoming photons into many more electrons by moving the charge through a high-voltage extended register—the effect of which is called EM gain. However, actual applied gain can often diverge from the indicated multiplication selected by the user.

    Manufacturers most often do not report exact values, so a requested gain factor by a user may in reality be slightly different from what a camera provides. For some older camera designs, the applied multiplication also might not scale linearly, such that a gain setting of 800 does not actually produce twice the signal as that of 400. This all means that the gray levels assigned in the produced image can diverge from the actual incoming photons that they represent.

    Some EMCCD chips are known to “age”. Their actual applied EM gain reduces over time as the device is used. The camera that once had a true measured EM gain of 400 will not have the same gain when put at the same setting as weeks pass. Thus, an equivalent number of photons can produce a different observed response in ADUs as the camera is utilized and time passes. When not corrected for, these variables confine the meaning of an ADU to a single camera’s behavior at a single time point.

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