Iodine speciation and bioavailability in edible seaweeds harvested in Galicia

Zusammenfassung

This work has been developed in the context of a region with a recent industry of seaweeds for human consumption. It is well known that algae are one of the organisms containing the highest concentrations of iodine (I), an essential trace element for humans. Nevertheless there is still a lack or information about the nature of the iodinated compounds present in algae and on their bioavailability. The main objectives of this PhD thesis were to study in depth the I content from edible seaweeds harvested in Galicia (north-western Spain), the chemical nature of the iodinated species and its bioavailability in human beings. A sample pre-treatment process based on an alkaline solubilisation with further detection by inductively coupled plasma mass spectrometry (ICP-MS) was optimized and applied to the assessment of the iodine (I) and bromine (Br) determination in several seaweed samples. After measuring other trace and major elements, pattern recognition techniques were used to classify seaweeds according to their type and variety. The study of iodinated species in edible seaweeds is also covered with: i) The development of an I vapour generation technique for the first order speciation of some iodinated species, ii) The enzymatic extraction of monoiodotyrosine (MIT) and diiodotyrosine (DIT). iii) The characterization of the water soluble fraction in terms of I content and molecular weight of iodinated species. iv) The extraction of iodinated proteins. High performance liquid chromatography (HPLC) coupled to ICP-MS, and gel electrophoresis with detection by laser ablation coupled to ICP-MS were used as analytical techniques. The last stage of the thesis deals with I and Br bioavailability in seaweeds. For this purpose an in vitro method based on the iodine dialyzability was investigated. The total I and Br content and the concentration of iodinated and brominated species were determined by ICP-MS and HPLC-ICP/MS, respectively, analyzing statistically the correlation with major nutrient constituents as proteins, carbohydrates, fat and dietary fibre.