Here at Nonlinear, we love to learn about how researchers use Progenesis QI and how it helps them in their day-to-day lives. Below, Dr. Daniel Carrizo tells us in his own words about his use of Progenesis QI to assess exposure to persistent organic pollutants (POPs).
Daniel has two affiliations:
|Astrobiology Centre (CSIC-INTA)
Dept of Planetology and Habitability
Torrejón de Ardóz 28850
|Institute for Global Food Security
Queen’s University Belfast
“I am working with human samples exposed to background levels of contamination. There are two conditions; high and low levels of exposure to organic pollutants. By comparing the lipidomic profile in human serum samples, I try to find any significant differences and ascertain whether they are related to different levels of exposure. Of course, the idea is to find a biomarker or metabolites for this exposure, in this case, high exposure to POPs.
In this experiment, I used liquid chromatography-quadrupole time-of-flight-mass spectrometry in ESI (− and +). At the beginning of the experiment, I used 10 pooled samples representative of all the sample set, so if I had 100 samples, I took 10 µl of each, I then homogenized the pooled sample and took an aliquot (300 µl approx.). Then from the 10 target samples I ran 2 of these pooled samples, as a QA/QC routine. I ran 3 replicates of each target sample, which amounted to between 300 and 500 runs ready for analysis.
Of course, the data generated is too complex to analyse without specific software like Progenesis. When you have 3000 or 4000 ions of interest and 300 samples, it is impossible to manage this amount of data with normal software. I have found Progenesis QI is robust and easy to use and the technical support is excellent.
Progenesis QI helps me to overcome problems with background peaks, experimental design, I can search easily for potential identified compounds.
The most important aspect is the power of the analysis and robustness of the data generated, as well the easy design for setting up experiments within the software. With Progenesis QI, you can do or redo the experimental setup on imported data as you need and explore the data generated over time. Progenesis QI has helped hugely in the identification of key compounds linked to lipid metabolism, which were responsible for the homeostasis of the metabolism.
Looking ahead to our use of Progenesis QI in the future, I think the key point is the robustness of the data. Firstly, we find important evidence of novel biomarkers related to our experimental conditions; that is, high vs. low exposure levels. Then, as we have this nice and sharp data, we will design and explore other types of samples and analysis/conditions.
I advise people to try Progenesis QI because of its robustness and easy to design experiments. Another important feature about this software, from my experience, is the simple process to find real identification of the possible metabolites or biomarkers you find.”
So that was Daniel’s story; how about you?
- Do you have a research story involving Progenesis QI that you’d like to share with us? Please contact us – we’d be happy to hear from you.
- Having read this account of Daniel’s work, would you like try Progenesis QI yourself? Download it here.
- Would you like to read more stories about people using Progenesis QI? Here are 3 recent blog posts relating to researchers’ experiences with Progenesis QI:
The Good, the Better, and the Best of Progenesis QI
Kai P. Law & Ting-Li Han
China-Canada-New Zealand Joint Laboratory of Maternal and Fetal Medicine
Chongqing Medical University and Auckland University
Progenesis QI helps streamline data processing for lipidomics research
Jace W. Jones, PhD
Research Assistant Professor of Pharmaceutical Sciences
How Progenesis QI helps to rapidly quantify and effectively identify compounds in complex metabolomes such as Garcinia buchananii samples
Dr. Timo Stark
Food Chemistry & Molecular Sensory Science
Technische Universität München
It just remains for me to say a big “Thank you!” to Daniel for sharing his research with us. 🙂