Osama Alian was the lead author in June 2016 at the International Association of Great Lakes Research meeting in Guelph, Ontario, presenting recent advances in the sensitivity and breadth of organisms detected with AFIDD, an Automated Fluorescence Intensity Detection Device, currently being developed in the laboratory of Dr. Jeffrey L. Ram, professor at Wayne State University. The abstract, entitled Automated Measurement of Enzymatic Activity for Monitoring Live Organisms in Ballast Water is coauthored by Hager Alkhafaji, Hannah Fine, Adrian Vasquez, Banani Sen, and Jeffrey Ram.

The background for the presentation is that US, Canadian, state, and international regulations will soon require ships entering the Great Lakes to treat ballast water so that virtually no live organisms will be released in discharged ballast water, thereby preventing the introduction of non-native or pathogenic species. The laboratory recently published a paper describing the Automated Fluorescence Intensity Detection Device (AFIDD), which was developed to differentiate live from dead organisms in ballast water by measuring enzymatic activity that metabolizes fluorescein diacetate (FDA, non-fluorescent) to fluorescein (fluorescent) in live organisms (Akram et al., 2015, Water Research 70:404-413).

The presentation described new modifications of AFIDD that increase detection sensitivity. Microorganisms (e.g. Ankistrodesmus algae) are captured on 0.2 um filters and backwashed into a reaction chamber with FDA for measurement. The type and mesh size of filters determines the size range of organisms detected and how many measurements can be made with the same filter. The protozoan Tetrahymena (typically >10 um in diameter) could be effectively captured and efficiently backwashed into the reaction chamber from a 5 um polycarbonate track-etched (PCTE) filter and measured with FDA at various cell densities.

This recent work can assist regulatory decisions on treating and discharging ballast and is supported by the Great Lakes Protection Fund, Project #964.