|Minimizing Carry-over for High Throughput Analysis|
Christian Berchtold1, Reto Bolliger2, Guenter Boehm2, Götz Schlotterbeck1
Minimal carry-over is a prerequisite for high throughput analysis. However, minimized carry-over and cycle time are competing and a careful optimization is mandatory. In this study the influence of wash conditions on carry-over of various compounds was investigated. A strategy to minimize carry-over was developed. The influences of different wash tasks were investigated. Finally the contribution of different system components such as injector valve or column was studied.
|A Comparison of ITEX Dynamic Headspace–GC/MS to other Enrichment Techniques for Analysis of Flavoring Compounds|
Douglas Doster1; Roger Pearson1; Sean Eppel1; Ken Rice1; Tom Flug2; Brian Peat2; Guenter Boehm2
Enrichment techniques are commonly used for the analysis of flavoring compounds in different matrices with GC/MS. Analysis of flavoring compounds is done by purge & trap, SPME or headspace, depending on requirements for sensitivity. The In-Tube Ex¬traction (ITEX) Dynamic Headspace uses a micro trap filled with an adsorbent material to efficiently extract the compounds. Here we evaluate if the ITEX can be used to effectively analyze for these compounds and reduce the analyst’s time involved.
|Automated in-gel digestion on a commercial autosampler directly coupled to nanoLC-MS/MS|
Achermann François, Bolliger Reto, Buchs Natasha, Doiron Nicholas, Lagache Braga Sophie, Heller Manfred, Boehm Guenter
SDS-PAGE separates protein samples from LC-MS incompatible contaminations, and is frequently used to fractionate proteins of entire proteomes. One disadvantage is that gel lanes have to be cut into many slices, followed by in-gel digestion of proteins and extraction of peptides. The number of these gel slices goes into the hundreds, rendering this process very repetitive and prone to mistakes and errors during sample handling. Automation reduces such risks and improves reproducibility.
|Automated sample preparation workflows for quantitative proteomics applications|
Oliver Popp1, Lucas Luethy2, Tamara Kanashova1, HaAn Nguyen1, Julia Kikuchi1, Guenter Boehm2, Thomas Blenkers3, Andreas Bruchmann3, Gunnar Dittmar1
Mass spectrometry based proteomics requires large scale identification of peptides, and depends upon efficient sample preparation. Recently, we presented two automated protein-digestion setups, in-solution and in-gel digestion. We extended these techniques by implementing dimethyl labelling (DML). Furthermore, we established an automated phospho-peptide (PP) enrichment procedure in a 96-well formate, generating phospho-proteomic data in very short time.
|Optimization of a Vacuum Ultraviolet Photoionization source for Gas Chromatography used with a High Resolution Time of Flight Mass Spectrometer|
Lloyd Allen and Viatcheslav Artaev
-Tune solution allows optimization of ion source parameters for
both proton transfer and direct ionization
-Independent ionization processes exist for M+ and MH+
-Optimizing for dopant signal intensity yields inferior results
-Degree of fragmentation remains relatively constant over a
range of source conditions
|High Performance Comprehensive Two-Dimensional Gas Chromatography Coupled with a High Resolution Multi-Reflecting TOFMS for Confident Non-Target Analyte Identification|
Scott J. Pugh, Viatcheslav Artaev, Mark F. Merrick, Jack Cochran
The use of comprehensive two-dimensional gas chromatography to help increase chromatographic resolution is a major step in tackling the problem of confident peak identification in a complex sample matrix. Combining the separation power of two-dimensional gas chromatography, with resolving power greater than 25,000, and sub ppm mass accuracies of a high resolution multi-reflecting TOFMS is the ideal solution to confident compound identification within a complex sample matrix.
|Fragmentation Trees for Automated de novo Interpretation of Impure Electron Ionization Spectra from Gas Chromatographic Complex Mixture Analysis—Chemical Deconvolution|
Kevin Siek, Vasily Makarov, Viatcheslav Artaev, Dmitry Mazur, Albert T. Lebedev
-Chemical deconvolution algorithms accurately reported independent
components of dead coelutions where such components belong to distinct chemical classes.
-Present algorithms fail to distinguish chemically similar analytes such as branched and linear alkanes, thus chemical deconvolution is not a
substitute for GCxGC.
-Chemical deconvolution algorithms accurately rejected more than 80% of spurious signals from manually curated spectra found to be contaminated with unrelated signa
|Effective Comparison of Yeast Extracts Using High Resolution GC and GCxGC-HRTOFMS|
David E. Alonso and Joe Binkley
The Pegasus GC-HRT and GC-HRT 4D instruments are effective tools for the comprehensive analysis of yeast extracts.
• Enhanced chromatographic resolution of the HRT 4D system facilitated compound characterization by improving spectral similarity scores
• High quality data resulted in excellent spectral similarity scores when compared to large, well-established databases (NIST, Wiley)
• High resolution, accurate mass data was crucial for determination of fragment, molecular, and adduct
|Performance Characteristics of a Comprehensive Two=Dimensional Gas Chromatography-High Resolution Time-of=Flight Mass Spectrometry System (GCxGC=HRTOFMS) Utilizing Chemical Ionization|
Jonelle Shiel, Mark Merrick, Scott Pugh, Matthew Soyk, and Viatcheslav Artaev
Combining comprehensive two-dimensional gas chromatography (GC×GC) with a High Resolution Time-of-Flight Mass Spectrometer and Chemical Ionization is a powerful tool for compound identification. Performance of the LECO Pegasus GC-HRT 4D using Chemical Ionization (CI) was demonstrated using Benzophenone and Diesel. GC×GC separation results in narrow peaks, therefore, a high speed detection system is necessary.