|Automatic Characterization of Lipids Using Charge Remote Fragmentation Ions and Peaks Characteristic of Fatty Acid Fragmentation From MALDI MS/MS Data|
Ningombam Sanjib Meitei*(1); Arun Apte(2); Dietmar Waidelich(3); Fadi Abdi(4); Matthias Glueckmann(3)
Automated identification of lipids using CRF ions and high energy MS/MS fragment ions and novel software.
|Utilization of Hydrogen Carrier Gas on a High Resolution GC-TOFMS System: An Application Compendium|
Joe Binkley, David Alonso
GC-HRT methods utilizing hydrogen carrier gas were developed for analysis of representative specialty chemical, forensic, and metabolomic markets.
|Integrated platform including automated bligh and dyer extraction and dual-column|
Emmanuel Varesio, Guenter Boehm, Sandra Jahn, Renzo Picenoni, Gérard Hopfgartner
• Automated Bligh and Dyer extraction for metabolomic studies.
• Dual-column UHPLC setup for the analysis of the polar and lipidic fractions.
• Alternating acidic and basic mobile phase for the separation of the polar fraction.
• Identification of unknown compounds by SWATH HR MS2 spectra acquisition.
|Deciphering Regulatory Mechanisms in M. xanthus Using IsotopicRatio Outlier Analysis (IROA) for Metabolome-wide Quantitation|
Daniel Krug 1,2, Carsten Volz 1, Aiko Barsch 3, Chris Beecher 4, Felice de Jong 4, Rolf Müller 1,2
Comprehensive study of regulation in myxobacteria with an untargeted metabolomics setup using Isotopic Ratio Outlier Analysis (IROA) and UHR-Q-TOF
Reliable relative quantitation of known and unknown metabolites from a myxobacterial mutant strain in response to induction of the transcriptional antirepressor taA
Compound identification facilitated by the use of ultra-high resolution MS and the knowledge of the number of carbons in each molecule due to IROA
|Identification and classification of antifouling compounds secreted by anti MIC microorganisms. A metabolomic analysis.|
Albillos SM; Balaña-Fouce R; Montero O; Barreiro-Mendez C; Blas-Galindo E; Barros-García R; Guedella-Bustamante E; Ullán RV
BIOCORIN project, aims to develop a green alternative to the coatings and solutions used up to date for MIC corrosion control. Some of the results of this project are presented here, with the identification of several relevant antifouling compounds secreted by environmentally isolated anti-MIC strains of microorganisms via a metabolomic approach.
|Rapid Identification of Microorganisms by Touch Spray and Paper Spray Ambient Ionization|
Ahmed M. Hamid, Alan K. Jarmusch, Valentina Pirro and R. Graham Cooks
The rapid and accurate identification of microorganisms is necessary in order to improve public health. Molecular-based identification allows for rapid patient treatment and provides more accurate diagnoses, two crucial aspects for successful treatment, yet a great challenge. In this work PS-MS, an existing ambient method, and TS-MS, a newly developed technique, are being utilized in the rapid discrimination of microorganisms (<2 min).
|Molecular Dynamics Simulation Study of Pulmonary Surfactant Interacting With Nanoparticles|
Syed Kashif Zafar, Syed Tarique Moin and Zaheer-ul-Haq
MD simulation studies using NAMD of lipid bilayers supported on alpha-quartz (nanoparticles) and kaolinite with explicit water molecules will be presented to understand the physiochemical effects of nanoparticles on pulmonary surfactant.
|Transforming Analytical Data into Knowledge with Software for Metabolite Studies|
Tara Sinclair, Graham A. McGibbon and Susan Ling
ACD/Labs has been developing specialized software for chemical and pharmaceutical research for over 16 years. Their expertise includes multi-technique, multi-instrument data handling, knowledge management of analytical and separations data, chemical drawing, and prediction software for a range of chemical properties as well as spectra and chromatograms.
|QSAR Model of Regioselectivity of Metabolism in Human Liver Microsomes: Development, Validation, Comparison and Adaptation to Novel Compounds|
Justas Dapkunas, Andrius Sazonovas and Pranas Japertas
Analytical identification of metabolites for a drug candidate is usually a time consuming and low-throughput task which is performed only in late drug development phases. Therefore the ability to predict possible sites of human liver microsomal metabolism using in silico techniques would be highly beneficial for any medicinal chemist.