Nichole Reisdorph

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Dr Nichole Reisdorph

Short Biography

Dr Nichole Reisdorph is an Associate Professor in the Department of Pharmaceutical Sciences at the University of Colorado Anschutz Medical Campus. She is also the Director of the Skaggs School of Pharmacy Mass Spectrometry Facility and serves as Treasurer on the Metabolomics Society Board of Directors. Nichole’s main interest lies in applying mass spectrometry approaches to projects that may lead to new information and are of therapeutic relevance to human diseases. Her research program focuses on discovering mechanisms and markers of lung diseases including asthma and chronic obstructive pulmonary disease (COPD). Both lines of research have led to understanding how lipids are involved in the inflammatory aspects of these diseases. This has, in turn, led to deeper understanding of PUFA metabolism, with a focus on the resulting bioactive lipid mediators. One major question is whether dietary interventions using n-3 PUFAs, or their metabolites, can alter the course of disease. In addition to her lung and lipid research, Nichole is part of a Multi-PI grant that focuses on associating and then testing food specific biomarkers with health outcomes. As a Core Director, Nichole collaborates on clinical projects spanning from epilepsy and diabetes to nutrition and ageing; giving Nichole a broad perspective on several human diseases. Finally, Nichole’s lab offers training in the fields of proteomics and metabolomics. Their hands on workshops have reached over 400 international participants since 2004.

Expert Opinion

When and why did you start using metabolomics in your investigations?

I did my postdoc in Dr Gary Siuzdak’s laboratory at The Scripps Research Institute in La Jolla, CA, USA. I was responsible for setting up a proteomics workflow; however, I also helped a colleague, Dr Elizabeth Want, evaluate several protein precipitation methods as part of a new direction the lab was taking, namely metabolomics. Everything was very new, including Gary’s visions for Metlin and XCMS. When I started my own mass spectrometry lab at the University of Colorado in 2004, metabolomics was a natural complement to our proteomics work. The power of metabolomics, in our case when applied to human health, was immediately clear and became my focus. While discovery-based metabolomics offered us a means of generating new hypotheses, we also developed a series of targeted assays to more deeply explore certain pathways and molecular classes. We spent the first few years developing and validating robust and reproducible assays and informatics workflows. While we now focus predominantly on metabolomics and lipidomics, we still do some proteomics.

What have you been working on recently?

My research focuses on applying metabolomics to projects that are of therapeutic relevance to human diseases. My focus has primarily been on lung diseases, including asthma and chronic obstructive pulmonary disease (COPD). This research has shifted from predominantly clinical work to animal models, which is a new area for me. We are also busy developing sample type specific databases for plasma and cells using our ion mobility QTOF instrument. More recently, we’ve applied metabolomics to nutrition studies, i.e. nutrimetabolomics, which represents the intersection of clinical nutrition research and metabolomics. This has led to some excellent collaborations with our microbiome colleagues and there is a natural fit between microbiome research and metabolomics. As part of this, we’ve recently begun looking at how the host:microbiome metabolism of foods and natural products, including green tea and cannabis, affects behavior and specific metabolic pathways. It’s truly exciting research!

You have been using metabolomics to study human diseases (e.g. Chronic Obstructive Pulmonary Disease); what are the biggest challenges of using metabolomics in this area?

Both COPD and asthma are complex, heterogeneous disorders. Our pilot metabolomics studies, utilizing 100-300 patients, have been successful in identifying candidate markers of, for example, clinical phenotypes. However, it’s becoming clear that very large cohorts, for example over 1,000 patients, will likely be necessary to find clinically relevant biomarkers. Analysis of such numbers is challenging from a data analysis standpoint, where confounders such as batch effects and clinical site differences are a reality and computational power is required to extract and analyze these large datasets. While we’ve learned to adjust for and handle those elements and have robust quality control practices in place, there are practical aspects to running over 1000 samples that aren’t discussed much. For example, our laboratory also performs both discovery-based and targeted lipidomics, so we require strong solvents to more completely extract lipids. The robotics we’ve evaluated can’t handle those strong solvents so we are limited to a methanol extraction for these large sample sets, which in turn severely limits coverage of lipids. So comprehensive lipid coverage and identification, is a major issue we’ve encountered when dealing with large clinical datasets. Finally, when metadata comprises over 100 clinical characteristics, we have to be very choosy about what clinical data we include in our analyses. We’ve learned that we have to ask very specific questions of our metabolomics data!

In your research you have been using animal models to study human diseases; what are the advantages and disadvantages of using animals for this purpose?

As mentioned above, the variability found in human samples can be immense, which means that we need several hundred samples to reach statistical significance, perhaps even more when there is a potentially small effect size. There is much less variability when using an animal model so we are able to find important and significant differences with fewer samples. Depending on the model, there is also very good overlap with human disease which means that results are often directly translatable to humans. Because effects can be diluted in plasma, and human organs are difficult to obtain, animal models allow us to analyze disease processes directly in the target organ. Disadvantages include the fact that there are many different mouse strains and results may not translate from one to another. We also generally run both discovery and targeted assays and sample volume can be an issue.

You co-founded the Colorado Biological Mass Spectrometry Society; what skills did you develop undertaking this project and how has this shaped your career?

This is a great question! Although I’m not sure fearlessness is considered a skill, to undertake such a project I had to set aside any fears of making mistakes or of the unknown. I have a minor in business and have taken some entrepreneurial classes, but there isn’t a published workflow for starting a non-profit scientific society! I had to be resourceful and gather information from a variety of sources, including government agencies, lawyers, and websites. Writing a business plan helped me learn budgeting and organizational skills, which has helped immensely in administering grants and operating a core facility. Setting up CBMSS and serving as Treasurer for CBMSS directly led to my running for the Metabolomics Society Board of Directors and to my serving as Treasurer. Being on the Metabolomics Society BOD has helped me become more immersed in our Metabolomics Community and to try to exert positive influence through serving on Society Committees such as the Training Committee and Industry Task Group. It’s wonderful to be part of an international group and to see everything that our colleagues are doing! On the local side, I feel that the CBMSS has helped our regional community grow through providing opportunities for training, collaboration, and networking. Societies give scientists a chance to learn, to teach, and to communicate, all necessary skills. Perhaps there aren’t many tangible effects that starting CBMSS and serving as Treasurer have had on shaping my career, but the indirect effects of being part of local and international groups are immeasurable.

You have been involved in providing hands-on workshops in omics; what is your view of current training offerings in this area? How could this be improved?

There are a few groups who offer hands on training and we all, in my humble opinion, do a very good job. Unfortunately “few” is the operative word here, because there aren’t many groups offering hands on training on instruments and software. This is in part due to the fact that considerable resources go into developing and offering training. In our case, class sizes are limited so that participants have a chance for one-on-one time with instructors. We’ve offered to “train the trainer” and disseminate our training material but even that requires dedication and commitment from new training sites. My personal opinion is that we need to have Industry and Community partners, such as Universities, to make training more accessible. We’ve discussed this within the Metabolomics Society Training Committee and I feel that Society resources, including people power and funding, could be used to seed new training centers across the globe. In addition to hands on training, we have tremendous electronic resources available to us, including the ability to offer recorded training sessions and conduct live training via the web. This is especially feasible for bioinformatics and data analysis training. Again, it’s a matter of funding and committed people to get web-based training started; once started I am confident that training becomes self-sufficient. As evidence of that, we’ve been conducting hands on workshops in proteomics and metabolomics in our lab since 2005, and we rarely even advertise!

See also