MSACL 2017 EU Abstract

Pre-Analytic Evaluation of Volumetric Absorptive Microsampling and Integration in a Mass Spectrometry Based Metabolomics Workflow

Giuseppe Paglia (Presenter)
EURAC Research

Bio: Giuseppe Paglia is a Researcher at the Institute of Biomedicine, EURAC research. His research interests include lipidomics and metabolomics, as applied to epidemiological studies, translational medicine and biomarker discovery.

Authorship: Chiara Volani (1,2), Giulia Caprioli (1), Giovanni Calderisi (1), Baldur B. Sigurdsson (1), Johannes Rainer (1), Ivo Gentilini (3), Andrew A. Hicks (1), Peter P. Pramstaller (1), Guenter Weiss (2), Sigurdur V. Smarason (1), Giuseppe Paglia (1)
(1) Institute for Biomedicine, Eurac Research, Bolzano, Italy. (2) Medical University of Innsbruck, Innsbruck, Austria. (3) Transfusion Center of the Hospital of Bolzano, Bolzano, Italy.

Short Abstract

Integration of volumetric absorptive microsampling (VAMS) with mass spectrometry (MS) is an attractive solution for metabolomics studies. In this work, we integrated VAMS in a MS-based metabolomics workflow and investigated pre-analytical strategies such as sample extraction procedures and metabolome stability at different storage conditions. We found that the highest number and amount of metabolites were recovered upon extraction with acetonitrile:water. Prolonged storage of VAMS samples at room temperature caused significant changes in metabolome composition, but VAMS devices remained stable for up to six months at -80°C. The time used for drying the sample did also affect the metabolome. We finally employed the developed VAMS metabolomics workflow for investigating the alteration of iron homeostasis in mice fed diet rich in iron vs controls.

Long Abstract


Volumetric absorptive microsampling (VAMS) is a novel approach that allows single drop blood collection. Besides showing all the recognized advantages of dried blood spot sampling, it overcomes the issues associated with hematocrit and homogeneity.

Metabolomics is a fast-growing strategy in the analytical community and can benefit from microsampling in many ways. Most notably, it makes easier to increase cohort size for biomarker discovery and it facilitates the collection of repeated samples in challenge-response experimental design. Moreover, the use of microsampling in animal studies supports the principle of the three Rs by reducing the animal sample size and minimizing potential pain for the animal.

In this study, we investigated the possibility of integrating VAMS with a typical mass spectrometry (MS)-based metabolomics approach. In particular, we evaluated some key pre-analytical strategies that are pivotal in metabolomics studies.

We finally employed the developed VAMS metabolomics workflow for investigating the alteration of iron homeostasis in mice fed diet rich in iron vs controls.


Whole blood was collected in EDTA tubes from the Bolzano Hospital and sampled using VAMS devices (Neoteryx). The first set of samples was used to assess the extraction strategy by exploring six different extraction procedures, using acetonitrile, methanol, acetonitrile-water (70:30 v:v) and methanol-water (70:30 v:v) at pH=7, pH=3 and pH=9.

The second set of samples was used to investigate sample stability at different storage conditions. Samples were stored for six month at room temperature and at -80°C after drying for 2 hours, for 24 hours for 48 hours respectively.

Wild-type C57BL/6N male mice were used in this study for the application study. At age 10-11 weeks mice were randomly assigned either to the control group or the treatment group. The control group received a standard chow diet (Sniff) for 2 weeks, the treatment group received 5g/kg high iron diet the first week followed by 25g/kg high iron diet the second week. At day 0, 7 and 14 one drop of blood was collected from the mouse facial vein and absorbed onto a VAMS device.

All samples were analyzed by using ultra high performance liquid chromatography (UHPLC) (Agilent 1290) coupled with a Q-TOF mass spectrometer (MS) (Triple TOF 5600+, AB Sciex). The chromatographic separation was based on hydrophilic interaction liquid chromatograph (HILIC) and was performed by using an Acquity BEH amide, 100x2.1 mm column (Waters).


The aim of this study was to develop a suitable protocol for integrating VAMS technology in a typical untargeted metabolomics workflow for polar metabolites.

We first evaluated the best extraction procedure by comparing six different protocols. We found that the highest number and amount of metabolites was extracted using acetonitrile:water (70:30) or methanol:water (70:30). Modification of the pH in order to get an acidic (pH=3) or basic (pH=9) extraction solution resulted in lower recovery. Moreover, basic conditions extracted a very different metabolome compared to other conditions, with higher content of intracellular metabolites coming from red blood cells, such as heme, AMP and glucose-6-phosphate.

Extraction protocols employing only organic solvents (methanol) extracted more efficiently lipids, but less polar metabolites.

Considering that the UHPLC-HILIC-MS method employed is optimized for polar metabolites and uses high content of acetonitrile in the mobile phase, acetonitrile:water (70:30) was selected as the extraction protocol.

We then tested the recovery of the metabolome with increasing number of extraction steps. Using acetonitrile:water (70:30) we extracted the metabolome three times successively from the same VAMS device, and we analyzed each extract separately. Most of the polar metabolites, such as carnitines, aminoacids and carboxylic acids were mainly extracted during the first step (around 80% of the total content). On the other hand, lipids required more than one-step (85% of the total content recovered from the first two extractions).

In the next experiment we stored multiple samples at different storage conditions. The first set of samples was stored at room temperature for up to 6 months. Three more sets of samples were stored at -80°C after drying for 2 hours, 24 hours and 48 hours, respectively

The storage at room temperature affect the metabolome. In fact, around 75% of the annotated metabolites changed significantly over time (one way Anova, p<0.005).

Some metabolites, such as histidine, glutamine and asparagine underwent to a degradation process overtime. However, the degradation process was not the same for all metabolites. For instance, the degradation of histidine started after 2 hours of storage and continued until 3 weeks of storage, whereas the degradation of asparagine started to be important after 1 week of storage.

Other metabolites, such as glutamic acid, glyceric acid and methionine sulfoxide increased overtime.

While the storage at room temperature causes significant changes in the composition of the metabolome, VAMS samples are stable when stored at -80°C. However, it is worth to stress that the time of drying after the microsampling collection can affect the final metabolome. In fact, some metabolites are rapidly degraded or generated over the first 48 hours at room temperature

Based on the these results, we suggest drying VAMS device for two hours, then immediately freeze, and store the sample at -80°C for untargeted metabolomics.

We finally employed the developed VAMS metabolomics workflow for investigating the alteration of iron homeostasis in mice fed diet rich in iron vs controls.

Several metabolic pathways were affected by high intake of iron, such as urea cycle, purine metabolism and beta-oxidation.

Moreover, in the high iron diet, we detected increased blood level of pyruvate and glucose suggesting that high iron intake affects systemic glucose homeostasis.

Conclusions & Discussion

In this study, we developed for the first time a workflow integrating VAMS with MS-based metabolomics.

For untargeted metabolomics studies we suggest to dry VAMS samples for 2 hours subsequently store them at -80°C. For targeted metabolomics, we suggest to carefully evaluate the stability of the selected metabolites.

Nonetheless, we have shown that VAMS sampling can be successfully incorporated in the metabolomics workflow if standardized procedures such as the one described in this study are used.

References & Acknowledgements:

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