Fourier Transform Infrared (FT-IR) Spectroscopy and Improved Principal Component Regression (PCR) for Quantification of Solid Analytes in Microalgae and Bacteria
In bioanalytical chemistry, a detailed chemical understanding of biomaterials is often difficult to obtain due to the sheer number of analytes contained in a sample along with the samples' generally low reproducibility. This study presents a Fourier transform infrared (FT-IR) spectroscopic
technique in conjunction with innovations in sample preparation and chemometric data preprocessing to overcome these limitations. These methodologies were applied to quantitative analyses of 31 representative compounds commonly found in biomaterial, which have been incorporated into a spectroscopic
calibration database, that is, albumin (protein); D-alanine, glycine, histidine, valine, arginine, cysteine, phenylalanine, tyrosine, methionine, L-glutamine, and glutamic acid, (amino acids); glucose, fructose, galactose, mannose, sucrose, lactose, glycogen, agarose, and starch (carbohydrates);
DNA (salmon sperm), sulphonoquinovosyl diglyceride ( sulpho-lipid ), and 1,2-diacyl-sn-glycero3-phospho-L-serine ( phospho-lipid ); succinic acid and malic acid ( carboxylic acids ); glycolic acid (a -hydroxy acid), sodium pyruvate, b -carotene, frustules (microalgae silica-shells), and ammonium
formate. Two proofof-principle applications were based on calibration models incorporating these solids, i.e., characterization of E. coli and microalgae. The former aims for detection of bacterial contamination and the latter to enable investigations of changes in chemical composition of
microalgae cells in response to shifting environmental conditions. Chemometric preprocessing steps have been developed for handling sample-to-sample fluctuations of absorption path lengths and baselines; the former incorporated mass normalization while the latter utilized a novel baseline
correction method that requires no a priori information. Data preprocessing, chemometric calibration, and evaluation algorithms have been combined, together with an extensive spectral database of the aforementioned compounds (∼1500 samples), for quantitative calibration purposes through
the remotely accessible Virtual Chemometrics Lab , which can be utilized for a multitude of applications through a graphical user interface.
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