SAMPLE HANDLING | Automated Sample Preparation

Author(s):  
R.D. McDowall
Fuel ◽  
2021 ◽  
Vol 305 ◽  
pp. 121399
Author(s):  
Brent A. Modereger ◽  
Sarah E. Nowling ◽  
Wan Tang Jeff Zhang ◽  
Mackenzie L. Jones ◽  
Nathan Chapman ◽  
...  

Author(s):  
Anna Bach ◽  
Heidi Fleischer ◽  
Bhagya Wijayawardena ◽  
Kerstin Thurow

Vitamin D belongs to the fat-soluble vitamins and is an integral part of bone metabolism. In the human body, a decreased vitamin D level can be an additional risk factor for diseases like cancer, diabetes, and mental diseases. As a result, an enormous increase in the demand for vitamin D testing has been observed in recent years, increasing the demand for powerful methods for vitamin D determination at the same time. Automation is the key factor in increasing sample throughput. This study compares three fully automated sample preparation methods for the determination of 25(OH)D2 and 25(OH)D3 in plasma and serum samples. Starting from a semiautomated reference method, the method is tested manually and subsequently fully automated on the Biomek i7 Workstation by integrating a centrifuge and a positive pressure extractor into the workstation. Alternatively, the centrifugation for the separation of protein aggregates and supernatant is replaced by a filter plate. Finally, the sample throughput is further increased by using phospholipid removal cartridges. The results show that phospholipid removal significantly increases the recovery rates in liquid chromatography–mass spectrometry. With the phospholipid removal cartridges, recovery rates of 97.36% for 25(OH)D2 and 102.5% for 25(OH)D3 were achieved, whereas with the automated classic automated preparation method, the recovery rates were 83.31% for 25(OH)D2 and 86.54% for 25(OH)D3. In addition to the technical evaluation, the different methods were also examined with regard to their economic efficiency. Finally, the qualitative and quantitative performance of the developed methods is benchmarked with a selected semiautomatic reference method.


Metabolites ◽  
2022 ◽  
Vol 12 (1) ◽  
pp. 52
Author(s):  
Julia M. Malinowska ◽  
Taina Palosaari ◽  
Jukka Sund ◽  
Donatella Carpi ◽  
Gavin R. Lloyd ◽  
...  

Regulatory bodies have started to recognise the value of in vitro screening and metabolomics as two types of new approach methodologies (NAMs) for chemical risk assessments, yet few high-throughput in vitro toxicometabolomics studies have been reported. A significant challenge is to implement automated sample preparation of the low biomass samples typically used for in vitro screening. Building on previous work, we have developed, characterised and demonstrated an automated sample preparation and analysis workflow for in vitro metabolomics of HepaRG cells in 96-well microplates using a Biomek i7 Hybrid Workstation (Beckman Coulter) and Orbitrap Elite (Thermo Scientific) high-resolution nanoelectrospray direct infusion mass spectrometry (nESI-DIMS), across polar metabolites and lipids. The experimental conditions evaluated included the day of metabolite extraction, order of extraction of samples in 96-well microplates, position of the 96-well microplate on the instrument’s deck and well location within a microplate. By using the median relative standard deviation (mRSD (%)) of spectral features, we have demonstrated good repeatability of the workflow (final mRSD < 30%) with a low percentage of features outside the threshold applied for statistical analysis. To improve the quality of the automated workflow further, small method modifications were made and then applied to a large cohort study (4860 sample infusions across three nESI-DIMS assays), which confirmed very high repeatability of the whole workflow from cell culturing to metabolite measurements, whilst providing a significant improvement in sample throughput. It is envisioned that the automated in vitro metabolomics workflow will help to advance the application of metabolomics (as a part of NAMs) in chemical safety, primarily as an approach for high throughput screening and prioritisation.


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