Spectral deconvolution for overlapping GC/MS components

Comprehensive two-dimensional gas chromatography (GCxGC) is an emerging technology for chemical separation that provides an order-of-magnitude increase in separation capacity over traditional gas chromatography. GCxGC separates chemical species with two capillary columns interfaced by two-stage thermal desorption. Because GCxGC is comprehensive and has high separation capacity, it can perform multiple traditional analytical methods with a single analysis. GCxGC has great potential for a wide variety of environmental sensing applications, including detection of chemical warfare agents (CWA) and other harmful chemicals.This paper demonstrates separation of nerve agents sarin and soman from a matrix of gasoline and diesel fuel. Using a combination of an initial column separating on the basis of boiling point and a second column separating on the basis of polarity, GCxGC clearly separates the nerve agents from the thousands of other chemicals in the sample. The GCxGC data is visualized, processed, and analyzed as a two-dimensional digital image using a software system for GCxGC image processing developed at the University of Nebraska -Lincoln.

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“…13 One of the problems with GC-MS is the unmixing of a mass spectrum for co-eluted analytes. 14,15 This problem is greatly reduced in GCxGC.…”

Section: Resultsmentioning

confidence: 99%

Chemical warfare agent detection in complex environments with comprehensive two-dimensional gas chromatography

Reichenbach

Kottapalli

et al. 2003

SPIE Proceedings

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“…This idea was later improved by considering the time shift between the measurement of high and low masses by scanning mass spectrometers [96]. The ''model peak method'' is a more sophisticated algorithm using also maxima of ion chromatograms to detect components [97].…”

Section: Gc-ms Deconvolutionmentioning

confidence: 99%

Mass Spectrometry

Werther¹

2014

Handbook of Spectroscopy

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“…it is common to encounter situations where two or more components elute with a similar retention time [10,36].…”

Section: When Analyzing Complex Mixtures Like Metabolomesmentioning

confidence: 99%

Microbial metabolomics: replacing trial-and-error by the unbiased selection and ranking of targets

Werf

Jellema

Hankemeier

2005

J IND MICROBIOL BIOTECHNOL

127

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Microbial production strains are currently improved using a combination of random and targeted approaches. In the case of a targeted approach, potential bottlenecks, feed-back inhibition, and side-routes are removed, and other processes of interest are targeted by overexpressing or knocking-out the gene(s) of interest. To date, the selection of these targets has been based at its best on expert knowledge, but to a large extent also on 'educated guesses' and 'gut feeling'. Therefore, time and thus money is wasted on targets that later prove to be irrelevant or only result in a very minor improvement. Moreover, in current approaches, biological processes that are not known to be involved in the formation of a specific product are overlooked and it is impossible to rank the relative importance of the different targets postulated. Metabolomics, a technology that involves the non-targeted, holistic analysis of the changes in the complete set of metabolites in the cell in response to environmental or cellular changes, in combination with multivariate data analysis (MVDA) tools like principal component discriminant analysis and partial least squares, allow the replacement of current empirical approaches by a scientific approach towards the selection and ranking of targets. In this review, we describe the technological challenges in setting up the novel metabolomics technology and the principle of MVDA algorithms in analyzing biomolecular data sets. In addition to strain improvement, the combined metabolomics and MVDA approach can also be applied to growth medium optimization, predicting the effect of quality differences of different batches of complex media on productivity, the identification of bioactives in complex mixtures, the characterization of mutant strains, the exploration of the production potential of strains, the assignment of functions to orphan genes, the identification of metabolite-dependent regulatory interactions, and many more microbiological issues.

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Spectral deconvolution for overlapping GC/MS components

Cited by 52 publications

References 2 publications

Chemical warfare agent detection in complex environments with comprehensive two-dimensional gas chromatography

Chemical warfare agent detection in complex environments with comprehensive two-dimensional gas chromatography

Mass Spectrometry

Microbial metabolomics: replacing trial-and-error by the unbiased selection and ranking of targets

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