KOL VOICES | ACADEMIC BIOANALYTICAL MS

From plasma discovery to quantitative confidence:

qRePS-supported workflows in liver disease research

Discovery proteomics is powerful for finding candidate signals, but follow-up studies require measurements that are robust across batches and cohorts. In this Q&A, Professor Lekha Sleno of UQAM discusses how her group combines untargeted and targeted workflows, including ProteomEdge DiscoveryEdge™175, to investigate liver disease biology and improve quantitative confidence in plasma proteomics.

Stakeholder lens	Academic bioanalytical mass spectrometry and translational proteomics
ProteomEdge technology used	DiscoveryEdge™175 qRePS™-supported absolute quantification
Key publication / use case	ASMS poster by Carina Lima on nanoparticle enrichment and isotope-enabled quantification for biomarker discovery in liver disease using DiscoveryEdge™175.
Application area	Plasma proteomics, liver disease biomarker discovery, cohort/batch comparability and multi-omics workflows.

Q: Can you briefly introduce yourself, your research group at UQAM and the main focus of your work in bioanalytical mass spectrometry?

A: I am a full professor in the chemistry department of the University of Quebec in Montreal. My research group specializes in developing bioanalytical mass spectrometry methods for diverse applications. We use targeted quantitative methods and untargeted approaches for answering biological questions involving human diseases, metabolism, and different chemical exposures.

Q: Your group develops MS-based approaches for proteomics and metabolomics to study biological pathways and their perturbations. What scientific questions are most important to your lab right now?

A: Currently many of our projects are looking at perturbations involving different diseases or disease models, at both metabolite and protein levels. We are focused on improving data robustness and workflows for digging deeper into what we can uncover as differences. We have seen that combining both metabolomics and proteomics on the same samples can often help uncover biologically-relevant pathways in this context.

Q: For readers who are not mass spectrometry specialists, why are protein-level measurements valuable for understanding metabolism, toxicity and disease?

A: Our bodies or cells can adapt to different conditions, including disease or stress, and the way these changes happen are very often by increasing or blocking certain biological (signaling or metabolic) pathways. Proteins are at the heart of these changes so by being able to measure specific levels or modifications on proteins, we can gather information on these responses. For example, we can uncover potential therapeutic targets for a disease by studying these protein-level changes.

Q: Carina Lima presented work at ASMS on nanoparticle enrichment and isotope-enabled quantification for biomarker discovery in liver disease, with data generated using ProteomEdge DiscoveryEdge175. What scientific question is this work addressing?

A: Carina’s poster at ASMS was centered on testing workflows for addressing two important problems for plasma proteomics, one being the limited depth of coverage due to a very large dynamic range covered by different proteins in plasma, where the major proteins usually cause suppression of the signals of biologically-relevant signals. The other is the challenge of robust quantitation in very complex biological samples, such as plasma.

The latter issue is one where we tested the use of ProteomEdge DiscoveryEdge175, where we were able to apply absolute quantitation to our samples in a small cohort of healthy individuals compared to patients with liver disease. Many notable changes were seen in this cohort, opening up many follow-up questions we are working towards.

A big advantage of using the isotope-labeled standards from ProteomEdge allows us to combine data from different cohorts or batches of samples that is not usually possible when we apply traditional untargeted bottom-up proteomics without the use of any labeled standards.

Q: The ASMS poster combines untargeted and targeted LC-HRMS/MS. How do these two approaches complement each other, and how can qRePS help move from candidate discovery to targeted quantitative measurements?

A: Untargeted workflows are great for a discovery phase where depth of coverage is important, and we want to uncover changes without a specific hypothesis in mind. A good way of validating what we find through untargeted workflows, is by following up with a targeted approach where specific proteins of interest are selected to confirm the changes seen in the discovery phase. qRePS helps increasing quantitative robustness in both untargeted and targeted workflows.

Q: Where does nanoparticle enrichment add value, and what analytical challenges is it designed to address?

A: The nanoparticle enrichment allows us to reduce some of the interfering highly concentrated proteins in plasma to allow a better depth of coverage through our LC-MS/MS analyses. This enables us to detect proteins that we cannot identify without this step of enrichment. For example, in our data, we saw an increase of about 2.5x in both protein identifications as well as the same increase in statistically-significantly changing proteins between healthy and liver disease plasma sample groups.

Q: Looking ahead, what do you hope qRePS-supported workflows can enable for liver disease biomarker research or broader bioanalytical MS applications?

A: We are looking towards being able to apply real quantitative proteomics in large cohorts and comparing longitudinally. The more robust and comparable data we can have the better our biological insights will be.