scholarly journals Comparison of commercial nanoliquid chromatography columns for fast, targeted mass spectrometry-based proteomics

2016 ◽  
Vol 2 (2) ◽  
Author(s):  
Tore Vehus ◽  
Kristina Erikstad Seterdal ◽  
Stefan Krauss ◽  
Elsa Lundanes ◽  
Steven R Wilson
Keyword(s):  
Mass Spectrometry ◽  
Chromatography Columns ◽  
Nanoliquid Chromatography

scholarly journals Retention Time Standardization and Registration (RTStaR): An algorithm that matches corresponding and identifies unique species in nanoliquid chromatography-nanoelectrospray ionization-mass spectrometry lipidomic datasets

2021 ◽  
Author(s):  
Alexandre P Blanchard ◽  
Yun Wang ◽  
Graeme P Taylor ◽  
Matthew W Granger ◽  
Stephen Fai ◽  
...  
Keyword(s):  
Mass Spectrometry ◽  
Retention Time ◽  
Population Based ◽  
Ionization Mass ◽  
Serum Samples ◽  
Bioinformatic Tools ◽  
Nanoelectrospray Ionization ◽  
Large Numbers ◽  
Lipid Species ◽  
Nanoliquid Chromatography

Bioinformatic tools capable of registering, rapidly and reproducibly, large numbers of nanoliquid chromatography-nanoelectrospray ionization-tandem mass spectrometry (nLC-nESI-MS/MS) lipidomic datasets are lacking. We provide here a freely available Retention Time Standardization and Registration (RTStaR) algorithm that aligns nLC-nESI-MS/MS spectra within a single dataset and compares these aligned retention times across multiple datasets. This two-step calibration matches cor-responding and identifies unique lipid species in different lipidomes from different matrices and organisms. RTStaR was developed using a population-based study of 1001 human serum samples composed of 71 distinct glycerophosphocholine metabolites comprising a total of 68,572 analytes. Platform and matrix independence were validated using different MS instruments, nLC methodologies, and mammalian lipidomes. The complete algorithm is packaged in two modular ExcelTM workbook templates for easy implementation. RTStaR is freely available from the India Taylor Lipidomics Research Platform http://www.neurolipidomics.ca/rtstar/rtstar.html. Technical support is provided through [email protected]

scholarly journals Human Tear Metabolomics Using Liquid Chromatography-Q Exactive-HF Mass Spectrometry

2021 ◽  
Author(s):  
Gauri Shankar Shrestha ◽  
Ajay Kumar Vijay ◽  
Fiona Stapleton ◽  
Russell Pickford ◽  
Nicole Carnt
Keyword(s):  
Mass Spectrometry ◽  
Amino Acids ◽  
Liquid Chromatography ◽  
Data Analysis ◽  
Mass Spectra ◽  
Reversed Phase ◽  
Charged Surface ◽  
Hydrophilic Interaction ◽  
Q Exactive ◽  
Chromatography Columns

AbstractAimTo putatively identify and characterise human tear metabolites in a normal subject on an untargeted platform of liquid chromatography-Q exactive-HF mass spectrometry.MethodsFour samples of unstimulated tears were collected from both eyes on four consecutive days between 1 – 2 pm using a microcapillary tube and pooled from both eyes each day. Untargeted analysis of the tears was performed by chromatographic separation of constituent metabolites in both CSH-C18RP (Charged Surface Hybrid-C18 Reversed Phase) and SeQuant ZIC-pHILIC (Zwitterionic-polymeric Hydrophilic Interaction Liquid Chromatography) columns, followed by heated electrospray ionization (HESI) and the acquisition of mass spectra using QExactive-HF mass spectrometer. Compound Discoverer software (v2.0) was used for data analysis.ResultEighty-two metabolites were tentatively identified. Seventy compounds (85.4 %) were observed in all four samples with a coefficient of variation (CV) less than 25 %. Fifty-nine metabolites (71.9 %) were novel in the healthy tears. Amino acids were the most frequently detected metabolites in the tears (28 %), followed by carbohydrates (12.2 %), carboxylic acids (8.5 %), carnitines (6.1 %) and glycerophospholipids (4.9 %), respectively.ConclusionThe current untargeted platform is capable of detecting a range of tear metabolites across several biological categories. This study provides a baseline for further ocular surface studies.

Development and performance evaluation of an ultralow flow nanoliquid chromatography-tandem mass spectrometry set-up

PROTEOMICS ◽  
2014 ◽  
Vol 14 (17-18) ◽  
pp. 1999-2007 ◽  
Author(s):  
Thomas Köcher ◽  
Peter Pichler ◽  
Mauro De Pra ◽  
Laurent Rieux ◽  
Remco Swart ◽  
...  
Keyword(s):  
Mass Spectrometry ◽  
Performance Evaluation ◽  
Tandem Mass Spectrometry ◽  
Tandem Mass ◽  
Chromatography Tandem Mass Spectrometry ◽  
Nanoliquid Chromatography ◽  
And Performance ◽  
Set Up

Analysis of theListeriacell wall proteome by two-dimensional nanoliquid chromatography coupled to mass spectrometry

PROTEOMICS ◽  
2005 ◽  
Vol 5 (2) ◽  
pp. 433-443 ◽  
Author(s):  
Enrique Calvo ◽  
M. Graciela Pucciarelli ◽  
Hélène Bierne ◽  
Pascale Cossart ◽  
Juan Pablo Albar ◽  
...  
Keyword(s):  
Mass Spectrometry ◽  
Two Dimensional ◽  
Nanoliquid Chromatography
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