Isotope pattern deconvolution as a tool to study iron metabolism in plants

Isotope pattern deconvolution is a mathematical technique for isolating distinct isotope signatures from mixtures of natural abundance and enriched tracers. In iron metabolism studies measurement of all four isotopes of the element by high-resolution multicollector or collision cell ICP–MS allows the determination of the tracer/tracee ratio with simultaneous internal mass bias correction and lower uncertainties. This technique was applied here for the first time to study iron uptake by cucumber plants using ⁵⁷Fe-enriched iron chelates of the o,o and o,p isomers of ethylenediaminedi(o-hydroxyphenylacetic) acid (EDDHA) and ethylenediamine tetraacetic acid (EDTA). Samples of root, stem, leaves, and xylem sap, after exposure of the cucumber plants to the mentioned ⁵⁷Fe chelates, were collected, dried, and digested using nitric acid. The isotopic composition of iron in the samples was measured by ICP–MS using a high-resolution multicollector instrument. Mass bias correction was computed using both a natural abundance iron standard and by internal correction using isotope pattern deconvolution. It was observed that, for plants with low ⁵⁷Fe enrichment, isotope pattern deconvolution provided lower tracer/tracee ratio uncertainties than the traditional method applying external mass bias correction. The total amount of the element in the plants was determined by isotope dilution analysis, using a collision cell quadrupole ICP–MS instrument, after addition of ⁵⁷Fe or natural abundance Fe in a known amount which depended on the isotopic composition of the sample.