A high-throughput platform for detailed lipidomic analysis of a range of mouse and human tissues.
Samuel FurseDenise S Fernandez-TwinnBenjamin JenkinsClaire L MeekHuw E L WilliamsGordon C S SmithD Stephen Charnock-JonesSusan E OzanneAlbert KoulmanPublished in: Analytical and bioanalytical chemistry (2020)
Lipidomics is of increasing interest in studies of biological systems. However, high-throughput data collection and processing remains non-trivial, making assessment of phenotypes difficult. We describe a platform for surveying the lipid fraction for a range of tissues. These techniques are demonstrated on a set of seven different tissues (serum, brain, heart, kidney, adipose, liver, and vastus lateralis muscle) from post-weaning mouse dams that were either obese (> 12 g fat mass) or lean (<5 g fat mass). This showed that the lipid metabolism in some tissues is affected more by obesity than others. Analysis of human serum (healthy non-pregnant women and pregnant women at 28 weeks' gestation) showed that the abundance of several phospholipids differed between groups. Human placenta from mothers with high and low BMI showed that lean placentae contain less polyunsaturated lipid. This platform offers a way to map lipid metabolism with immediate application in metabolic research and elsewhere. Graphical abstract.
Keyphrases
- high throughput
- fatty acid
- pregnant women
- adipose tissue
- gene expression
- endothelial cells
- metabolic syndrome
- insulin resistance
- single cell
- weight loss
- type diabetes
- induced pluripotent stem cells
- weight gain
- heart failure
- body mass index
- pluripotent stem cells
- skeletal muscle
- white matter
- machine learning
- bone mineral density
- electronic health record
- physical activity
- body composition
- intensive care unit
- functional connectivity
- big data
- pregnancy outcomes
- resting state
- high density
- multiple sclerosis
- antibiotic resistance genes
- blood brain barrier
- subarachnoid hemorrhage
- wastewater treatment