| Title |
One- vs two-phase extraction: re-evaluation of sample preparation procedures for untargeted lipidomics in plasma samples
|
|---|---|
| Published in |
Analytical & Bioanalytical Chemistry, July 2018
|
| DOI | 10.1007/s00216-018-1200-x |
| Pubmed ID | |
| Authors |
Andres Gil, Wenxuan Zhang, Justina C. Wolters, Hjalmar Permentier, Theo Boer, Peter Horvatovich, M. Rebecca Heiner-Fokkema, Dirk-Jan Reijngoud, Rainer Bischoff |
| Abstract |
Lipidomics is a rapidly developing field in modern biomedical research. While LC-MS systems are able to detect most of the known lipid classes in a biological matrix, there is no single technique able to extract all of them simultaneously. In comparison with two-phase extractions, one-phase extraction systems are of particular interest, since they decrease the complexity of the experimental procedure. By using an untargeted lipidomics approach, we explored the differences/similarities between the most commonly used two-phase extraction systems (Folch, Bligh and Dyer, and MTBE) and one of the more recently introduced one-phase extraction systems for lipid analysis based on the MMC solvent mixture (MeOH/MTBE/CHCl3). The four extraction methods were evaluated and thoroughly compared against a pooled extract that qualitatively and quantitatively represents the average of the combined extractions. Our results show that the lipid profile obtained with the MMC system displayed the highest similarity to the pooled extract, indicating that it was most representative of the lipidome in the original sample. Furthermore, it showed better extraction efficiencies for moderate and highly apolar lipid species in comparison with the Folch, Bligh and Dyer, and MTBE extraction systems. Finally, the technical simplicity of the MMC procedure makes this solvent system highly suitable for automated, untargeted lipidomics analysis. |
X Demographics
The data shown below were collected from the profiles of 3 X users who shared this research output. Click here to find out more about how the information was compiled.
Geographical breakdown
| Country | Count | As % |
|---|---|---|
| Korea, Republic of | 1 | 33% |
| Unknown | 2 | 67% |
Demographic breakdown
| Type | Count | As % |
|---|---|---|
| Scientists | 2 | 67% |
| Members of the public | 1 | 33% |
Mendeley readers
The data shown below were compiled from readership statistics for 121 Mendeley readers of this research output. Click here to see the associated Mendeley record.
Geographical breakdown
| Country | Count | As % |
|---|---|---|
| Unknown | 121 | 100% |
Demographic breakdown
| Readers by professional status | Count | As % |
|---|---|---|
| Student > Ph. D. Student | 30 | 25% |
| Researcher | 27 | 22% |
| Student > Master | 10 | 8% |
| Student > Bachelor | 6 | 5% |
| Student > Postgraduate | 6 | 5% |
| Other | 12 | 10% |
| Unknown | 30 | 25% |
| Readers by discipline | Count | As % |
|---|---|---|
| Biochemistry, Genetics and Molecular Biology | 31 | 26% |
| Chemistry | 22 | 18% |
| Agricultural and Biological Sciences | 9 | 7% |
| Pharmacology, Toxicology and Pharmaceutical Science | 7 | 6% |
| Medicine and Dentistry | 5 | 4% |
| Other | 9 | 7% |
| Unknown | 38 | 31% |
Attention Score in Context
This research output has an Altmetric Attention Score of 2. This is our high-level measure of the quality and quantity of online attention that it has received. This Attention Score, as well as the ranking and number of research outputs shown below, was calculated when the research output was last mentioned on 30 August 2018.
All research outputs
#16,728,456
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Outputs from Analytical & Bioanalytical Chemistry
#5,260
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Outputs of similar age
#210,457
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Outputs of similar age from Analytical & Bioanalytical Chemistry
#76
of 175 outputs
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