Search Results (11)

Three different vegetable oils, namely coconut oil, palm olein and olive oil, were analyzed for mineral oil hydrocarbons (MOHs) in our laboratory and in five commercial laboratories well recognized for their expertise in this field. The analysis consisted of a preliminary quantitative estimation of MOH content by hyphenated liquid chromatography–gas chromatography with flame ionization detection (LC-GC-FID), followed by a confirmatory analysis of MOH components by two-dimensional gas chromatography with time-of-flight mass spectrometry (GCxGC-ToF). The results provided by the six laboratories were compared to check their consistency, which would have led to a hypothetical commercial agreement or dispute scenarios, for instance. The comparison was based merely on information provided by the laboratories in their analytical reports (i.e., the methodology was not challenged, and chromatograms were not reviewed). Additionally, some of the laboratories were willing to provide some more information or details of the analysis. Similar quantitative results were provided by all six laboratories, emphasizing the utility of the current available harmonized guidelines and official standards for this method. However, as regards confirmatory results, discrepancies were observed among some laboratories in terms of the detection of MOH markers at low levels and the interpretation of GCxGC-ToF information. Even taking into account the limitation of this study as regards the reduced number of laboratories included, it highlights the need for harmonizing the GCxGC-ToF confirmatory method for MOHs in order to increase the alignment of results between laboratories for this kind of analysis. Full article

Snakebite is a serious health issue in tropical and subtropical areas of the world and results in various pathologies, such as hemotoxicity, neurotoxicity, and local swelling, blistering, and tissue necrosis around the bite site. These pathologies may ultimately lead to permanent morbidity and may even be fatal. Understanding the chemical and biological properties of individual snake venom toxins is of great importance when developing a newer generation of safer and more effective snakebite treatments. Two main approaches to ionizing toxins prior to mass spectrometry (MS) analysis are electrospray ionization (ESI) and matrix-assisted laser desorption ionization (MALDI). In the present study, we investigated the use of both ESI-MS and MALDI-MS as complementary techniques for toxin characterization in venom research. We applied nanofractionation analytics to separate crude elapid venoms using reversed-phase liquid chromatography (RPLC) and high-resolution fractionation of the eluting toxins into 384-well plates, followed by online LC-ESI-MS measurements. To acquire clear comparisons between the two ionization approaches, offline MALDI-MS measurements were performed on the nanofractionated toxins. For comparison to the LC-ESI-MS data, we created so-called MALDI-MS chromatograms of each toxin. We also applied plasma coagulation assaying on 384-well plates with nanofractionated toxins to demonstrate parallel biochemical profiling within the workflow. The plotting of post-column acquired MALDI-MS data as so-called plotted MALDI-MS chromatograms to directly align the MALDI-MS data with ESI-MS extracted ion chromatograms allows the efficient correlation of intact mass toxin results from the two MS-based soft ionization approaches with coagulation bioassay chromatograms. This facilitates the efficient correlation of chromatographic bioassay peaks with the MS data. The correlated toxin masses from ESI-MS and/or MALDI-MS were all around 6–8 or 13–14 kDa, with one mass around 20 kDa. Between 24 and 67% of the toxins were observed with good intensity from both ionization methods, depending on the venom analyzed. All Naja venoms analyzed presented anticoagulation activity, whereas pro-coagulation was only observed for the Pseudonaja textillis venom. The data of MALDI-MS can provide complementary identification and characterization power for toxin research on elapid venoms next to ESI-MS. Full article

Retention time drift caused by fluctuations in physical factors such as temperature ramping rate and carrier gas flow rate is ubiquitous in chromatographic measurements. Proper peak matching and identification across different chromatograms is critical prior to any subsequent analysis but is challenging without using mass spectrometry. The purpose of this work was to describe and validate a peak matching and identification method called retention time trajectory (RTT) matching that can be used in targeted analyses free of mass spectrometry. This method uses chromatographic retention times as the only input and identifies peaks associated with any subset of a predefined set of target compounds. An RTT is a two-dimensional (2D) curve formed uniquely by the retention times of the chromatographic peaks. The RTTs obtained from the chromatogram of a sample under test and those pre-installed in a library are matched and statistically compared. The best matched pair implies identification. Unlike most existing peak-alignment methods, no mathematical warping or transformation is involved. Based on the experimentally characterized RTT, an RTT hybridization method was also developed to rapidly generate more RTTs and expand the library without performing actual time-consuming chromatographic measurements, which enables successful peak matching even for chromatograms with severe retention time drifts. Additionally, 3.15 × 10⁵ tests using experimentally obtained gas chromatograms and 2 × 10¹² tests using two publicly available fruit metabolomics datasets validated the proposed method, demonstrating real-time peak/interferent identification. Full article

Peak overlapping is a common problem in chromatography, mainly in the case of complex biological mixtures, i.e., metabolites. Due to the existence of the phenomenon of co-elution of different compounds with similar chromatographic properties, peak separation becomes challenging. In this paper, two computational methods of separating peaks, applied, for the first time, to large chromatographic datasets, are described, compared, and experimentally validated. The methods lead from raw observations to data that can form inputs for statistical analysis. First, in both methods, data are normalized by the mass of sample, the baseline is removed, retention time alignment is conducted, and detection of peaks is performed. Then, in the first method, clustering is used to separate overlapping peaks, whereas in the second method, functional principal component analysis (FPCA) is applied for the same purpose. Simulated data and experimental results are used as examples to present both methods and to compare them. Real data were obtained in a study of metabolomic changes in barley (Hordeum vulgare) leaves under drought stress. The results suggest that both methods are suitable for separation of overlapping peaks, but the additional advantage of the FPCA is the possibility to assess the variability of individual compounds present within the same peaks of different chromatograms. Full article

This study applied an untargeted–targeted (UT) fingerprinting approach, based on comprehensive two-dimensional gas chromatography-time-of-flight mass spectrometry (GC×GC-TOF MS), to assess the effects of rainfall and temperature (both seasonal and elevational) on the tea metabolome. By this strategy, the same compound found in multiple samples need only to be identified once, since chromatograms and mass spectral features are aligned in the data analysis process. Primary and specialized metabolites of leaves from two Chinese provinces, Yunnan (pu′erh) and Fujian (oolong), and a farm in South Carolina (USA, black tea) were studied. UT fingerprinting provided insight into plant metabolism activation/inhibition, taste and trigeminal sensations, and antioxidant properties, not easily attained by other analytical approaches. For example, pu′erh and oolong contained higher relative amounts of amino acids, organic acids, and sugars. Conversely, black tea contained less of all targeted compounds except fructose and glucose, which were more similar to oolong tea. Findings revealed compounds statistically different between spring (pre-monsoon) and summer (monsoon) in pu′erh and oolong teas as well as compounds that exhibited the greatest variability due to seasonal and elevational differences. The UT fingerprinting approach offered unique insights into how differences in growing conditions and commercial processing affect the nutritional benefits and sensory characteristics of tea beverages. Full article

This case study describes data analysis of a chromatogram distributed for the 2019 GC×GC Data Challenge for the Tenth Multidimensional Chromatography Workshop (Liege, Belgium). The chromatogram resulted from chemical analysis of a terpene-standards sample by comprehensive two-dimensional chromatography with mass spectrometry (GC×GC-MS). First, several aspects of the data quality are assessed, including detector saturation and oscillation, and operations to prepare the data for analyte detection and identification are described, including phase roll for modulation-cycle alignment and baseline correction to account for the non-zero detector baseline. Then, the case study presents operations for analyte detection with filtering, a new method to flag false detections, interactive review to confirm detected peaks, and ion-peaks detection to reveal peaks that are obscured by noise or coelution. Finally, the case study describes analyte identification including mass-spectral library search with a new method for optimizing spectra extraction, retention-index calibration from preliminary identifications, and expression-based identification checks. Processing of the first 40 min of data detected 144 analytes, 21 of which have at least one percent response, plus an additional 20 trace and/or coeluted analytes. Full article

In this work, a statistical metric called the Mahalanobis distance (MD) is used to compare gas chromatography separation conditions. In the two-sample case, the MD computes the distance between the means of the multivariate probability distributions of two groups. Two gas chromatography columns of the same polarity but differing length and film thickness were utilized for the analysis of fatty acid methyl esters in biodiesel fuels. Biodiesel feedstock samples representing classes of canola, coconut, flaxseed, palm kernal, safflower, soy, soyabean, sunflower, tallow, and waste grease were used in our experiments. Data sets measured from each column were aligned with the correlated optimized warping (COW) algorithm prior to principal components analysis (PCA). The PC scores were then used to compute the MD. Differences between the data produced by each column were determined by converting the MD to its corresponding p-value using the F-distribution. The combination of COW parameters that maximized the p-value were determined for each feedstock separately. The results demonstrate that chromatograms from each column could be optimally aligned to minimize the MD derived from the PC-transformed data. The corresponding p-values for each feedstock type indicated that the two column conditions could produce data that were not statistically different. As a result, the slight loss of resolution using a faster column may be acceptable based on the application for which the data are used. Full article

Due to its unsurpassed sensitivity and selectivity, LC-HRMS is one of the major analytical techniques in metabolomics research. However, limited stability of experimental and instrument parameters may cause shifts and drifts of retention time and mass accuracy or the formation of different ion species, thus complicating conclusive interpretation of the raw data, especially when generated in different analytical batches. Here, a novel software tool for the semi-automated alignment of different measurement sequences is presented. The tool is implemented in the Java programming language, it features an intuitive user interface and its main goal is to facilitate the comparison of data obtained from different metabolomics experiments. Based on a feature list (i.e., processed LC-HRMS chromatograms with mass-to-charge ratio (m/z) values and retention times) that serves as a reference, the tool recognizes both m/z and retention time shifts of single or multiple analytical datafiles/batches of interest. MetMatch is also designed to account for differently formed ion species of detected metabolites. Corresponding ions and metabolites are matched and chromatographic peak areas, m/z values and retention times are combined into a single data matrix. The convenient user interface allows for easy manipulation of processing results and graphical illustration of the raw data as well as the automatically matched ions and metabolites. The software tool is exemplified with LC-HRMS data from untargeted metabolomics experiments investigating phenylalanine-derived metabolites in wheat and T-2 toxin/HT-2 toxin detoxification products in barley. Full article

At present, gas chromatography–quadrupole mass spectrometry (GC-qMS) is considered the gold standard amongst analytical techniques for fire debris analysis in forensic laboratories worldwide, specifically for the detection and classification of ignitable liquids. Due to the highly complex and unpredictable nature of fire debris, traditional one-dimensional GC-qMS often produces chromatograms that display an unresolved complex mixture containing only trace levels of the ignitable liquid among numerous background pyrolysis products that interfere with pattern recognition necessary to verify the presence and identification of the ignitable liquid. To combat these challenges, this study presents a method optimized to achieve a near-theoretical maximum in peak capacity gain using comprehensive two-dimensional gas chromatography (GC×GC) coupled to time-of-flight mass spectrometry (TOFMS) for the forensic analysis of petroleum-based ignitable liquids. An overall peak capacity gain of ~9.3 was achieved, which is only ~17% below the system’s theoretical maximum of ~11.2. In addition, through the preservation of efficient separation in the first dimension and optimal stationary phase selection in the second dimension, the presented method demonstrated improved resolution, enhanced sensitivity, increased peak detectability and structured chromatograms well-suited for the rapid classification of ignitable liquids. As a result, the method generated extremely detailed fingerprints of petroleum-based ignitable liquids including gasoline, kerosene, mineral spirits and diesel fuel. The resultant data was also shown to be amenable to chromatographic alignment and multivariate statistical analysis for future evaluation of chemometric models for the rapid, objective and automated classification of ignitable liquids in fire debris extracts. Full article

DNA sequence analysis is undertaken in many biological research laboratories. The workflow consists of several steps involving the bioinformatic processing of biological data. We have developed a suite of web-based online bioinformatic tools to assist with processing, analysis and curation of DNA sequence data. Most of these tools are genome-agnostic, with two tools specifically designed for hepatitis B virus sequence data. Tools in the suite are able to process sequence data from Sanger sequencing, ultra-deep amplicon resequencing (pyrosequencing) and chromatograph (trace files), as appropriate. The tools are available online at no cost and are aimed at researchers without specialist technical computer knowledge.
The tools can be accessed at http://hvdr.bioinf.wits.ac.za/SmallGenomeTools, and the source code is available online at https://github.com/DrTrevorBell/SmallGenomeTools. Full article

While PCR amplicons extend to a few thousand bases, the length of sequences from direct Sanger sequencing is limited to 500–800 nucleotides. Therefore, several fragments may be required to cover an amplicon, a gene or an entire genome. These fragments are typically sequenced in an overlapping fashion and assembled by manually sliding and aligning the sequences visually. This is time-consuming, repetitive and error-prone, and further complicated by circular genomes. An online tool merging two to twelve long overlapping sequence fragments was developed. Either chromatograms or FASTA files are submitted to the tool, which trims poor quality ends of chromatograms according to user-specified parameters. Fragments are assembled into a single sequence by repeatedly calling the EMBOSS merger tool in a consecutive manner. Output includes the number of trimmed nucleotides, details of each merge, and an optional alignment to a reference sequence. The final merge sequence is displayed and can be downloaded in FASTA format. All output files can be downloaded as a ZIP archive. This tool allows for easy and automated assembly of overlapping sequences and is aimed at researchers without specialist computer skills. The tool is genome- and organism-agnostic and has been developed using hepatitis B virus sequence data. Full article