Biological and environmental influence on Mediterranean corals calcium carbonate precipitation

Abstract

Microsymposia C47MS 360 samples per day or collection of up to 130 X-ray diffraction datasets per day. Turnaround of structural data from LRL-CAT averages less than 2.3 days from the time the crystal was created and shipped to the beamline. Keywords: automation, synchrotron, protein MS.13.5Acta Cryst. (2011) A67, C47Optimising X-ray experiment strategy on-the-fly based on feedback from automated structure solution Richard Cooper, Department of Chemistry, University of Oxford, Chemistry Research Laboratory, Mansfield Road, Oxford (UK). Email: richard.cooper@chem.ox.ac.ukThe EDNA framework [1] is helping us to develop and run an automated structure solution and refinement pipeline during small molecule X-ray data collections. The partial results can be used to modify the X-ray experiment strategy on-the-fly, and so target the data which provides the best possible answer to a specific problem.X-ray experiment strategies typically optimise the time taken to collect a unique set of data (within specified limits) followed by efficient collection of data to provide maximum possible redundancy within a given time. However -if the structure can be determined and refined early in the data collection process -information can potentially be fed back to modify the data collection in order to collect the most valuable or useful data in the remaining time. Analysis of the leastsquares fit of the model to the data can quickly determine the few observations which may be profitably re-measured to most improve the estimated variance of a given model parameter [2]. Extension of this analysis allows the identification of observations whose remeasurement will most improve the estimated variance of arbitrary functions of parameters (for example: distances; angles; planes; sums and differences of occupancies etc.).If the crystal structure is as expected, the experimentalist can specify particular parameters or functions of interest, in order to generate an updated data collection strategy for the remainder of the experiment. Calcite, rhombohedral CaCO 3 , forms easily in nature, as stalagmites and stalactites, as veins in rocks, as sediments in warm seas and in pipes that distribute water to our homes. In veins, it can form large, beautiful crystals, but even in supersaturated laboratory solutions, the most favoured crystal form is the rhomb. Many organisms produce calcite, such as oysters and coral. Earthworms excrete tiny spherules, wood lice store it on their tummies and perhaps the simplest organism, one-celled algae, create exquisite platelets called coccoliths from 20 to 60 individual calcite elements that are less than a micrometer in the longest dimension. As a biomineral, calcite rarely takes the form of a rhomb. Organisms produce complicated organic molecules that adhere to the calcite surface, inhibiting growth at some sites, thus enhancing it at others. Depending on the ecological niche the organism inhabits, it can tailor the calcite to its specific needs.We learn more about biomineralisation by studying the mineral remai...