Automated detection of rare-event pathogens through time-gated luminescence scanning microscopy.

Many microorganisms have a very low threshold (<10 cells) to trigger infectious diseases, and, in these cases, it is important to determine the absolute cell count in a low-cost and speedy fashion. Fluorescent microscopy is a routine method; however, one fundamental problem has been associated with the existence in the sample of large numbers of nontarget particles, which are naturally autofluorescent, thereby obscuring the visibility of target organisms. This severely affects both direct visual inspection and the automated microscopy based on computer pattern recognition. We report a novel strategy of time-gated luminescent scanning for accurate counting of rare-event cells, which exploits the large difference in luminescence lifetimes between the lanthanide biolabels, >100 μs, and the autofluorescence backgrounds, <0.1 μs, to render background autofluorescence invisible to the detector. Rather than having to resort to sophisticated imaging analysis, the background-free feature allows a single-element photomultiplier to locate rare-event cells, so that requirements for data storage and analysis are minimized to the level of image confirmation only at the final step. We have evaluated this concept in a prototype instrument using a 2D scanning stage and applied it to rare-event Giardia detection labeled by a europium complex. For a slide area of 225 mm(2) , the time-gated scanning method easily reduced the original 40,000 adjacent elements (0.075 mm × 0.075 mm) down to a few "elements of interest" containing the Giardia cysts. We achieved an averaged signal-to-background ratio of 41.2 (minimum ratio of 12.1). Such high contrasts ensured the accurate mapping of all the potential Giardia cysts free of false positives or negatives. This was confirmed by the automatic retrieving and time-gated luminescence bioimaging of these Giardia cysts. Such automated microscopy based on time-gated scanning can provide novel solutions for quantitative diagnostics in advanced biological, environmental, and medical sciences.