Interview with TMIC Young Scientists (II)

Ryland Giebelhaus

Ryland is a second-year Ph.D. student in the Harynuk group at the University of Alberta. His research interests are primarily mass spectrometry-based metabolomics to explore human physiology. His expertise is also including metabolomics, exposomics, chromatography, and chemometrics. At the same time, he is also a graduate teaching assistant in the department of Chemistry.

His 6-minute presentation during the 4th Annual Metabolomics Association of North America (MANA) Conference was “Fluids three-ways: Comparison of dynamic headspace, solid phase microextraction, and derivatization for the untargeted GC×GC-TOFMS (Two Dimensional Gas Chromatography-time of Flight Mass Spectrometry) metabolomics of urine and human breastmilk”.

What is the key point or highlight that you want the audience to take away from your presentation?

A lot of different metabolites with a wide variety of chemical components with varying volatilities are present in the given samples. It is very challenging to capture all of those with only one method e.g. liquid chromatography (LC) and gas chromatography (GC). My work is to explore multiple techniques that are able to capture the big chunk of the chemical space and a wide range of volatile components. And we would be able to have a better understanding of how environmental exposure shapes our metabolisms. I am working on three different techniques to prepare and extract and analyze samples.

Where do you think the future of this technology lies?

Exposomics (study of how our exposures affect the metabolism) is a growing area in science and a big subset of omics studies. In my opinion, it is one of the areas that will develop really well in the near future, with that being said that my research will help us to be able to start the exposomics study and explore the exposomes accurately. The further application is very wide including maternal exposure, dietary, food & tolerances, different drugs, pharmaceutical, health products, and endless application. At the same time, GCxGC is an emerging technology and my other research is also focused on building the data tools to process the GCxGC-TOFMS data.

Exposomics: The study of how the exposures affect the metabolism
Stephanie Bishop

Dr. Stephanie Bishop is a Postdoctoral Associate at the University of Calgary under Dr. Ian Lewis’s Research Group. Her postdoctoral research explores the role of metabolism in shaping serious bacterial infections, ranging from urinary tract infections to Cystic Fibrosis infections. Using her expertise in analytical chemistry, with experience in cell culturing techniques, she is developing new tools and platforms to help us elucidate the metabolic mechanisms behind the emergence and clinical trajectory of these bacterial infections.

Stephanie introduced “SCALiR and MINNO: New applications for quantifying and interpreting metabolomics data” during the MANA Conference.

Note: SCALiR (Standard Curve Application for finding Linear Ranges) and MINNO (Metabolic Interactive Nodular Network for Omics). Both are new open-access tools in metabolomics that are developed by Lewis’s Research Group.

What is the key point or highlight that you want the audience to take away from your presentation?

We developed new open-source applications that assist users with metabolomics data quantification, visualization, and interpretation. SCALiR allows users to automatically transform mass spectrometry-based peak data into absolute quantitative data while MINNO allows users to visualize and refine metabolic networks of diverse organisms.

Can you summarize your presentation in a 30-second elevator pitch?

Some of the main challenges associated with metabolomics analyses include identifying and quantifying molecules in complex mixtures as well as projecting metabolomics data onto an organism’s entire metabolic network to interpret these data. To address these challenges, we developed two new open-source applications that (1) automatically detect the upper and lower limits of quantification in a standard dilution series to compute concentrations of metabolites in samples and (2) allow the user to visualize and refine metabolic networks of diverse organisms.

SCALiR (Standard Curve Application for finding Linear Ranges) allows the user to automatically transform mass spectrometry (MS)-based peak data into absolute quantitative data and download both the quantitative results as well as important parameters associated with the standard curves. We tested the efficacy of this tool with the quantitative analysis of over a thousand Staphylococcus aureus isolates. We found that the app produced similar results compared to manually generating standard curves and importantly, minimized the batch effects associated with variability in MS signal intensities in this large cohort study. MINNO (Metabolic Interactive Nodular Network for Omics) is a metabolic pathway mapping tool integrated with biochemical databases including KEGG and BiGG Models, which allows the user to download and refine metabolic networks for both common (e.g., mouse, human) and unusual (e.g., microbial pathogens) organisms with empirical metabolomics data. This versatile tool can be used to identify metabolic differences between related species, for example Lyme disease and relapsing fever isolates of the Borrelia genus, as well as changes in metabolism arising from polymicrobial interactions including with pathogens involved in cystic fibrosis infections. Overall, these new tools provide exciting new methods to quantify and interpret complex metabolomics data in diverse model systems.

Where do you think the future of this technology lies?

The next steps for these software tools are to open them up to the metabolomics community so diverse users can implement them in their data analysis strategies. This will allow us to determine new features to implement in the tools and open up the range of organisms that can be explored using the tools.

Scott MacKay

Scott MacKay received his undergraduate degree in Engineering Physics and his PhD in Electrical Engineering both at the University of Alberta. He works with Dr. David Wishart and Dr. Jie Chen and founded Tricca Technologies Inc. which brings metabolite research technology to the masses. Tricca’s colour sensor is proof that quantitave colour sensing works for measuring metabolites. Each reaction reacts with a sample to produce colour and the degree to which the colour has developed is directly proportional to the amount of metabolite present in the sample.

He presented integrated research that introduced an excellent alternative to traditional methods of measuring metabolites, with the title of “Development of a smart handheld device for innovative prediction of sheep pregnancy and litter size utilizing a metabolomic biomarker panel”.

What is the key point or highlight that you want the audience to take away from your presentation?

It’s possible to make metabolomic applications accessible and practical.

Can you summarize your presentation in a 30-second elevator pitch?

We are developing a colour-based sensor system for ranchers to detect sheep pregnancy themselves based on a blood metabolite panel, eliminating the need for on-site veterinary visits. Quantitative colour reactions based on in-lab enzymes have been made for the target metabolites. These reactions are simplified, dried for better storage and lifetime and combined with our quantitative colour biosensor system and automation fluidics to make a sensor test that can be done by ranchers on-site. Work is ongoing in finalizing the reactions and hardware before testing the pen-side with sheep by the end of the year.

Where do you think the future of this technology lies?

While the primary goal is creating a sensor product for sheep pregnancy and litter size detection, the different elements of this technology have numerous applications outside of sheep pregnancy. The colour reactions for specific metabolites can be used for other animal samples, and human samples (blood, urine, etc.). The quantitative colour sensor we made can be used in and out of the lab for quantitative detection of any visible colour, and the automated sample processing techniques discovered for this project have applications in human blood testing for point-of-care and remote testing applications.

deema Qasrawi

Deema is a Clinical Laboratory Scientist at Lady Davis Institute – Segal Cancer Proteomics Centre, under Dr. Borchers’ Node. She is experienced with a demonstrated history of working in research and development. Skilled in Liquid Chromatography-Tandem Mass Spectrometry (LC-MS/MS), Laboratory Medicine, Gas Chromatography, Liquid Chromatography, and dried blood spot (DBS) analysis.
Her recent oral presentation at the MANA Conference entitled “Multiplexed dilute-and-shoot LC-MRM-MS clinical assay for determination of the metanephrines and catecholamines in human urine”. [LC-MRM-MS : Liquid chromatography– Multiple reaction monitoring -mass spectrometry]

What is the key point or highlight that you want the audience to take away from your presentation?

  • A LC/MRM-MS assay for urinary catecholamines and metanephrines was developed.
  • The method uses a simple dilute-and-shoot sample preparation without derivatization.
  • The assay was validated according to the Clinical and Laboratory Standards Institute (CLSI) guidelines.
  • The method correlated well with an established HPLC-ECD reference method (HPLC-ECD: High-performance liquid chromatography with electrochemical detection)
  • This method improved sensitivity and specificity with a 5x less analysis time.

Can you summarize your presentation in a 30-second elevator pitch?

Quantifying urinary catecholamines and metanephrines is essential for the clinical screening and diagnosis of neuroendocrine tumors such as pheochromocytoma and paragangliomas. We have developed a simple and rapid dilute and-shoot liquid chromatograph-multiple reaction monitoring mass spectrometry (LC-MRM-MS) assay to measure catecholamines and metanephrines accurately and precisely in urine samples. This assay was validated according to the CLSI guidelines for routine clinical applications. This method offers improved sensitivity and specificity, a 5-fold decrease in analysis time, and minimal pre-column sample manipulation. Implementation of this assay in clinical laboratories will facilitate early and accurate diagnosis.

Where do you think the future of this technology lies?

This technique is crucial in the clinical application to analyze catecholamines and metanephrines in the urine sample with enhanced sensitivity and less time.

Deema presented the Multiplexed dilute-and-shoot LC-MRM-MS clinical assay at MANA 2022

We have introduced young scientists from the different nodes of TMIC. Let’s learn more about the research interest and assays offered by each node mentioned:

Harynuk Node

Dr. Harynuk’s Lab at the University of Alberta utilizes a powerful separation analytical platform – two-dimensional gas chromatography coupled to time-of-flight mass spectrometry (GCxGC-TOFMS). This technology offers superior analytical performance, including enhanced sensitivity and dynamic range compared to one-dimensional GC, and is well suited for the analysis of complex mixtures such as feces. His Untargeted Metabolomics by GCxGC TOF MS is a semi-quantitative method for known and unknown metabolite profiling that is an ideal discovery platform for the analysis of volatile and semi-volatile compounds.

Lewis Node

Dr. Lewis is leading TMIC’s Node at the University of Calgary (Alberta, Canada). He specializes in unravelling the complex metabolic underpinnings of host/microbe dynamics using a suite of microbiology, engineering, and analytical laboratories that were specifically built for studying microbial metabolism. His group is currently for postdoctoral fellows to aid in a large Precision Infection Management project related to microbial infections.

Wishart Node

Dr. Wishart’s Group is focused on the assays with an absolute quantification. His team has a new offer which is based on the use of their proprietary TMIC MEGA assays and overall of 28 assays. Clinical Biomarker Assay 2.0 (TMIC MEGA) – which quantifies up to 900 metabolites and ratios, and is validated for blood, serum and plasma. Microbiome Metabolism Assay (TMIC MEGA) – it quantifies up to 900 metabolites and ratios in fecal material, and up to 350 metabolites and ratios in urine, and is validated for urine, fecal extract and more

Borchers Node

Dr. Borchers’ Node at McGill University offers the Development and implementation of the custom targeted clinical LC-MS assays for drugs, hormones and metabolites. His laboratory also offers a comprehensive identification of drug metabolites (MetID – metabolites identification). His lab is interested in multi-omics work (combining proteomics and metabolomics), and provides an integration of machine learning to data analysis.

If you are interested in any of the studies– contact us directly

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