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Biology subjects

Hepburn, M.

Publications and source records attributed to Hepburn, M..

2 recordsLinked to original sources

LAMPrEY: a Python-based automated quality control tool for large-scale proteomics datasets

Over the past years, proteomics has moved increasingly towards the analysis of large cohorts of biological specimens. This has been made possible by significant improvements in mass spectrometry technology, chromatographic separation methods, and improved data acquisition strategies. These technological advances now routinely enable experiments that yield vast datasets that substantially outstrip the capacity of existing proteomics data analysis approaches. Processing such large datasets requires purpose-built, quality control tools designed to organize and analyze the data while recording all processing parameters for reproducibility. To address this need, we developed an open-source, Python-based software platform, Large-scale Automated Multi-level Proteomics Evaluation by Python (LAMPrEY), a comprehensive quality-control pipeline for quantitative proteomics analyses of large cohorts of samples. LAMPrEY features GUI-based file submission, automated processing with MaxQuant and RawTools, an interactive analytics dashboard, and an application programming interface (API) for programmatic usage that collectively enable rapid, reproducible analysis and interpretation of proteomics data. We demonstrate the longitudinal monitoring and analytical capabilities of LAMPrEY using TMT11 quantitative proteomics data generated from 910 Enterococcus faecium isolates collected from bloodstream infection patients. LAMPrEY is an open-source software that can be accessed at www.lewisresearchgroup.org/software.

bioinformatics↗

Recommendations for Automating Hydrogen/Deuterium Exchange Mass Spectrometry Measurements using Data-Independent Acquisition Methods

Hydrogen/deuterium exchange mass spectrometry (HX-MS) is a method used to study solution-phase protein structure and dynamics. Despite its many applications, HX-MS is limited in throughput because manual data analysis is still the norm. We previously developed HX-MS2 technology to add a second dimension of deuteration data and promote automated data processing. Data-independent acquisition (DIA) techniques enable this approach, but we require optimized methods for best performance. Using an Orbitrap Eclipse for illustration, we show that ion optics and collision energy settings typical of a proteomics DIA experiment generate maximal peptide retrieval from the DIA library. As few as three MS2 sequence ions are sufficient to generate a deuteration measurement with a precision that exceeds what is possible in traditional HX-MS. DIA window sizes are based on the chromatographic resolution of the method. An inter-scan window offset method is the recommended default configuration for most HX-DIA applications, but an intra-scan overlap method can be tuned for highest performance and is recommended when maximum peptide retrieval is desired. A fully automated HX-MS2 solution consists of Trajan HDX automation technology, an Orbitrap Eclipse mass spectrometer and AutoHX software. We demonstrate its robustness on an extensive time-course analysis of phosphorylase B and an epitope analysis of single domain antibodies (VHHs, nanobodies) specific to the receptor binding domain of SARS-CoV2 spike protein.

biochemistry↗