Phospholipid fatty acids in soil—drawbacks and future prospects

The current opinion and position paper highlights (1) correct assignation of indicator phospholipid fatty acids (PLFA), (2) specificity and recycling of PLFA in microorganisms, and (3) complete extraction and detection of PLFA. The straight-chain PLFA 14:0, 15:0, 16:0, and 17:0 occur in all microorganisms, i.e., also in fungi and not only in bacteria. If the phylum Actinobacteria is excluded from the group of Gram-positive bacteria, all remaining bacteria belong to the bacterial phylum Firmicutes, which should be considered. The PLFA 16:1ω5 should be used as an indicator for the biomass of arbuscular mycorrhizal fungi (AMF) as there is no experimental evidence that they occur in marked amounts in Gram-negative bacteria. Fungal PLFA should embrace the AMF-specific 16:1ω5. In the presence of plants, ergosterol should be used instead of the PLFA 18:2ω6,9 and 18:1ω9 as fungal indicators for Mucoromycotina, Ascomycota, and Basidiomycota. The majority of indicator PLFA are not fully specific for a certain microbial group. This problem might be intensified by recycling processes during decomposition to an unknown extent. Soil handling and extraction conditions should be further optimized. The reliability and accuracy of gas chromatographic separation need to be regularly checked against unintentional variations. PLFA analysis will still be of interest over the next decades as an important independent control of DNA-based methods.

Absolute Configuration of Bromofluoroiodomethane after Preparative Gas Chromatographic Separation

The enantiomers of bromofluoroiodomethane (CHBrFI) were separated on a preparative scale using gas chromatography (GC). The collected single enantiomers were analysed by vibrational circular dichroism spectroscopy and polarimetry in combination with ab initio calculations to determine the respective absolute configuration.

Volatilomics of Natural Products: Whispers from Nature

Volatilomics studies the emission of volatile compounds from living organisms like plants, flowers, animals, fruits, and microorganisms, using metabolomics tools to characterize the analytes. This is a complex process that involves several steps like sample preparation, extraction, instrumental analysis, and data processing. In this chapter, we provide balanced coverage of the different theoretical and practical aspects of the study of the volatilome. Static and dynamic headspace techniques for volatile capture will be discussed. Then, the main techniques for volatilome profiling, separation, and detection will be addressed, emphasizing gas chromatographic separation, mass spectrometry detection, and non-separative techniques using mass spectrometry. Finally, the whole volatilome data pre-processing and multivariate statistics for data interpretation will be introduced. We hope that this chapter can provide the reader with an overview of the research process in the study of volatile organic compounds (VOCs) and serve as a guide in the development of future volatilomics studies.

Determination of Polycyclic Aromatic Hydrocarbons in Agricultural Products

The procedure for the determination of polycyclic aromatic hydrocarbons (PAH) in agricultural products on the example of five crops (rapeseed, sunflower, flax, corn, soybeans) by gas chromatography mass spectrometry (GC-MS) was developed. It was showed the advantage of using binary mixtures of organic solvents "hexanedichloromethane" for PAH extraction. The time of Soxhlet extraction is from 6 to 8 hours at optimized conditions. The fractionation and purification of extracts by column chromatography on deactivated alumina was optimized. The article presents the optimization of sample injection in the programmed temperature vaporization (PTV) mode, parameters of gas chromatographic separation and mass spectrometric detection in determining 16 priority PAH in agricultural products. The recoveries, correctness and accuracy of the proposed method were checked by “spikes” with concentrations 0.5, 1.0, 2.5, 5.0 μg kg-1. The linearity of the method was determined by calibration curves obtained for three measurements of calibration solutions with concentrations of 0.5-100 ng mL-1. The effectiveness of the proposed combination of sample preparation and analysis by PTV-GC-MS was studied for linearity, accuracy, matrix effects and reproducibility. The method was validated by linearity, accuracy, matrix effect and reproducibility.