Spatial metabolic fingerprinting using FT-IR spectroscopy: investigating abiotic stresses on Micrasterias hardyi

文献信息

发布日期 2008-10-21
DOI 10.1039/B809441A
影响因子 4.616
作者

Soyab A. Patel, Felicity Currie, Nalin Thakker, Royston Goodacre


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摘要

The release of active pharmaceutical ingredients (APIs) into the environment is an ecologically important topic for study because, whilst APIs have been designed to have a wide range of biological properties for the target of interest (usually in man), little information on potential ecological risks is currently available regarding their effects on the organisms that inhabit the environment. In this study, the algae Micrasterias hardyi was exposed to propranolol, metoprolol (beta-adrenergic receptor agonist drugs) and mefenamic acid (a non steroidal anti-inflammatory drug), at concentrations ranging between 0.002–0.2 mM. Initial studies showed that Fourier transform infrared (FT-IR) spectroscopy on algal homogenates illustrated that all three APIs had a quantitative effect on the metabolism of the organisms and it was possible to estimate the level of API exposure from the FT-IR metabolic fingerprints using partial least squares (PLS) regression. From the inspection of the PLS loadings matrices it was possible to elucidate that all drugs caused effects on protein and lipid levels. Most strikingly propranolol had significant effects on the lipid components of the cell. These were dramatically reduced possibly as a consequence of loss of membrane integrity. In order to investigate this further, FT-IR microspectroscopy was used to generate detailed metabolic fingerprinting maps. These chemical maps revealed that all the drugs had a dramatic effect on the distribution of various chemical species throughout the algae, and that all drugs had an affect on protein and lipid levels. In particular, as noted in the PLS analyses for propranolol treated cells, the lipid complement found in the lipid storage areas in the processes of M. hardyi was greatly reduced. This illustrates the power of spatial metabolic fingerprinting for investigating abiotic stresses on complex biological species.

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