How was Progenesis QI used in an untargeted lipidomics workflow?

Following on from last month’s blog post, I’d like to continue with the other exciting video presentation from ASMS 2019. Dr. Jace Jones from the University of Maryland, School of Pharmacy, Department of Pharmaceutical Sciences in Baltimore, Maryland gave a very interesting talk on how the Progenesis QI software was used effectively and robustly to process a variety of lipidomic datasets from a traumatic brain injury model. His talk was entitled: The Use of Progenesis QI to Efficiently Process Lipidomic Data: Application to Traumatic Brain Injury

At a first glance, people only see what they want to see as we are preprogrammed to view things from our own perspective. The same can happen in science where we look at what we know over and above what we don’t. Dr. Jones highlighted the fact that the Progenesis QI software facilitates a process for them to be able to see what is not always visible at first so they could focus on groups that may not have been obvious.

After using the Progenesis QI software in his discovery workflow he then went on to do his quantitation workflow which corresponded well with the discovery results. This gave him great confidence that his workflows were robust in that he could go back and forth between discovery and quantitation.

The abstract for the talk Dr. Jones gave is below, but I again highly recommend you watch the video as the work they are doing can have a big impact on how we treat traumatic brain injuries moving forward.   

Presentation of the lipidomics talk presented by Dr. Jace Jones

Abstract

The Use of Progenesis QI to Efficiently Process Lipidomic Data: Application to Traumatic Brain Injury

Jace W. Jones, Ph.D.

University of Maryland, School of Pharmacy, Department of Pharmaceutical Sciences, Baltimore, MD

Lipids have significant potential to inform on disease and injury due to the pivotal role they play in many biological processes including cellular integrity and permeability, energy storage and metabolism, and signaling pathways. Heightened interest in the mechanism by which disruption of lipid metabolism and homeostasis contributes to a variety of human diseases and injuries (e.g., cancer, diabetes, neurodegenerative disorders, infectious diseases, and pulmonary conditions) has led to a substantial increase in lipidomic research. The field of lipidomics, broadly described as the comprehensive biochemical characterization of “all” lipids (referred to as the lipidome) within a cell, tissue, or organism presents a variety of analytical and data processing challenges. The analytical challenges result primarily from the dynamic range, vast structural diversity, and sheer number of biological lipids. These challenges have been commonly addressed using liquid chromatography coupled to high resolution tandem mass spectrometry. This workflow results in an information-rich data matrix that must be processed for retention time alignment, peak picking, adduct deconvolution, abundance, identification, and statistical analysis. Successful implementation of the aforementioned lipidomic workflow in a model system where two appropriate cohorts (e.g., disease vs control) are comparatively analyzed yields differential expression data delineating lipid profiles between the two groups and abundance of individual lipids.

The data processing challenges associated with efficiently and properly handling lipidomic data is not trivial and has been meet with a variety of software solutions. One such software solution is Progenesis QI from Nonlinear Dynamics (Waters). Progenesis QI offers a comprehensive workflow for efficiently processing LC-MS/MS generated lipidomic datasets. Progenesis QI is streamlined to handle multidimensional data in the form of chromatographic retention time, ion mobility, accurate mass, and data-independent acquisition. Data will be presented detailing the use of Progenesis QI to effectively and robustly process a variety of lipidomic datasets from a traumatic brain injury model.  

Try it for yourself

Now you can see how our Progenesis QI users are having success with the software in their research, why don’t you see how the software can help you in your research? The Progenesis QI team are more than willing to work with you to see how you can transform your results. We would like to help you see results in your workflows that you may not already be seeing. Please get in touch or comment below.

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