Dataset Information

Methodology for non-target screening of sewage sludge using comprehensive two-dimensional gas chromatography coupled to high-resolution mass spectrometry.

ABSTRACT: To investigate the wide range of pollutants occurring in sewage sludge, an analytical method for comprehensive non-target screening is needed. To the best of our knowledge, no procedures currently exist for the full screening of organic contaminants in sewage sludge, which is the ultimate goal of this project. We developed non-discriminating sample preparation methods for gas chromatography-mass spectrometry (GC-MS) analysis. Pressurized liquid extraction (PLE) was used for extraction, with in-line (silica gel selective PLE, SPLE) or off-line clean-up (gel permeation chromatography, GPC). This combination allowed the analysis of non-polar compounds of all sizes and small semi-polar and non-polar compounds. The results show that the combination of SPLE and PLE with GPC is suitable for analysis of established as well as new contaminants. Both methods were validated for 99 compounds with different properties. For all GC suitable analytes, either one of the methods produced acceptable recoveries (64 to 136%). As a test, the two methods were used for non-target screening of Swedish sewage sludge. A tiered approach was used to tentatively identify the sludge contaminants. In total, 1865 and 1593 compounds were found of which 321 and 192 compounds were tentatively identified for the PLE and SPLE method, respectively. For a comprehensive coverage of contaminants, the two methods should be used together, with the PLE method covering a wider polarity range and the SPLE method a wider size range. In addition, polar substances will require liquid chromatography-mass spectrometry analysis, the method for which will be developed soon.

SUBMITTER: Veenaas C

PROVIDER: S-EPMC5519657 | biostudies-literature | 2017 Aug

REPOSITORIES: biostudies-literature

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Methodology for non-target screening of sewage sludge using comprehensive two-dimensional gas chromatography coupled to high-resolution mass spectrometry.

Veenaas Cathrin C Haglund Peter P

Analytical and bioanalytical chemistry 20170623 20

To investigate the wide range of pollutants occurring in sewage sludge, an analytical method for comprehensive non-target screening is needed. To the best of our knowledge, no procedures currently exist for the full screening of organic contaminants in sewage sludge, which is the ultimate goal of this project. We developed non-discriminating sample preparation methods for gas chromatography-mass spectrometry (GC-MS) analysis. Pressurized liquid extraction (PLE) was used for extraction, with in-l ...[more]

PMID: 28646300

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Project description:BackgroundComprehensive two-dimensional gas chromatography coupled with mass spectrometry (GC × GC-MS) is a powerful technique which has gained increasing attention over the last two decades. The GC × GC-MS provides much increased separation capacity, chemical selectivity and sensitivity for complex sample analysis and brings more accurate information about compound retention times and mass spectra. Despite these advantages, the retention times of the resolved peaks on the two-dimensional gas chromatographic columns are always shifted due to experimental variations, introducing difficulty in the data processing for metabolomics analysis. Therefore, the retention time variation must be adjusted in order to compare multiple metabolic profiles obtained from different conditions.ResultsWe developed novel peak alignment algorithms for both homogeneous (acquired under the identical experimental conditions) and heterogeneous (acquired under the different experimental conditions) GC × GC-MS data using modified Smith-Waterman local alignment algorithms along with mass spectral similarity. Compared with literature reported algorithms, the proposed algorithms eliminated the detection of landmark peaks and the usage of retention time transformation. Furthermore, an automated peak alignment software package was established by implementing a likelihood function for optimal peak alignment.ConclusionsThe proposed Smith-Waterman local alignment-based algorithms are capable of aligning both the homogeneous and heterogeneous data of multiple GC × GC-MS experiments without the transformation of retention times and the selection of landmark peaks. An optimal version of the SW-based algorithms was also established based on the associated likelihood function for the automatic peak alignment. The proposed alignment algorithms outperform the literature reported alignment method by analyzing the experiment data of a mixture of compound standards and a metabolite extract of mouse plasma with spiked-in compound standards.

Dataset Information

Methodology for non-target screening of sewage sludge using comprehensive two-dimensional gas chromatography coupled to high-resolution mass spectrometry.

Publications

Methodology for non-target screening of sewage sludge using comprehensive two-dimensional gas chromatography coupled to high-resolution mass spectrometry.

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