What is the focus of your lab’s research?
Almost exclusively high throughput lipid profiling of samples from large epidemiological studies, where we study gene-lifestyle interactions. The method works with plasma samples as well as dried blood spots. The method is also applied to small-scale studies of specific disease groups, dietary interventions and model systems such as yeast. The TriVersa NanoMate® is also used to study the lipid composition of tissues analyzed by LESA®.
Why did you incorporate the TriVersa NanoMate® into your laboratory?
The TriVersa NanoMate® is essential to efficiently analyze large-scale studies. It offers a really robust method for high throughput studies with minimal carryover.
Who would you recommend to purchase the TriVersa NanoMate®?
I recommend the TriVersa NanoMate® to laboratories with a large number of samples requiring a robust and reliable delivery system. The TriVersa NanoMate® eliminates typical nanoelectrospray ionization challenges.
Do you have any publications or presentations using the TriVersa NanoMate®?
Development and Application of High-Throughput Single Cell Lipid Profiling: A Study of SNCA-A53T Human Dopamine Neurons
Snowden, et al. iScience, 2020, 23(10), 101703
Combining FACS and LESA-MS to establish high-throughput single cell lipid profiling. Research identifies lipid differences found within and between populations of human dopamine neurons.
- Snowden et al. Combining lipidomics and machine learning to measure clinical lipids in dried blood spots. Metabolomics. DOI: 10.1007/s11306-020-01703-0
- Koulman et al. The development and validation of a fast and robust dried blood spot based lipid profiling method to study infant metabolism. Metabolomics. DOI: 10.1007/s11306-014-0628-z
- Furse et al. A high-throughput platform for detailed lipidomic analysis of a range of mouse and human tissues. Analytical and Bioanalytical Chemistry. DOI: 10.1007/s00216-020-02511-0
- Harshfield et al. An unbiased lipid phenotyping approach to study the genetic determinants of lipids and their associations with coronary heart disease risk factors. J Proteom Res. DOI: 10.1021/acs.jproteome.8b00786
- Mann et al. Insights into genetic variants associated with NASH-fibrosis from metabolite profiling. Hum Mol Genet. DOI: 10.1093/hmg/ddaa162