European Journal Of Lipid Science And Technology Pdf

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Blood plasma has gained protagonism in lipidomics studies due to its availability, uncomplicated collection and preparation, and informative readout of physiological status. To tackle these issues, we developed a comprehensive, high throughput, and quantitative mass spectrometry-based shotgun lipidomics platform for blood plasma lipid analyses.

Moreover, we thoroughly assessed the influence of blood stabilization with different anticoagulants and freeze-thaw cycles to exclude artifacts generated by sample preparation.

Practical applications: This shotgun lipidomics platform can be implemented in different laboratories without compromising reproducibility, allowing multi-site studies and inter-laboratory comparisons. This possibility combined with the high-throughput, broad lipidomic coverage and absolute quantification are important aspects for clinical applications and biomarker research. Lipidomics is the systematic study of pathways and networks of cellular lipids by profiling and understanding the role of lipids in biological systems 1.

Blood plasma is widely used in lipidomics studies mainly due to its availability. Furthermore, it carries the lipids incorporated into lipoproteins over the circulatory system from the intestine and liver to all the tissues in the body 2.

Because this fluid has access to peripheral tissues, and its lipoproteins exchange lipids with them, its lipid composition should contain a detailed picture of the individual metabolic state 3 , 4.

This makes plasma a prime target for diagnostic research but at the same time very challenging due to its compositional complexity 5. In order to establish reliable lipid diagnostic biomarkers, one needs to dissect the many factors affecting the plasma lipidome which are not necessarily disease-related, e. This creates a severe problem and often plasma lipidomics studies are either performed in a high-throughput manner but targeting only a subset of the lipidome 12 or they cover the whole lipidome for a small sample set 5.

In lipidomics methodologies, like in other omics techniques, there is an inverse correlation between a method's throughput versus lipidomic structural elucidation and coverage The most comprehensive plasma lipidomic coverage available, offered by the LipidMaps consortium 5 , is achieved by the combination of multiple analytical set-ups running in different laboratories 14 which greatly reduces the throughput and feasibility.

On the other hand, one-step chromatography-based approaches offer improved throughput at the expense of lower lipidomic coverage 15 — Nowadays, the available shotgun lipidomics methodologies offer the highest throughput. This is achieved by direct infusion of the extract without previous chromatographic separation with the drawbacks of not providing details about lipid molecular species 20 or limited lipidomic coverage In this paper, we developed a high throughput mass spectrometry MS -based shotgun lipidomics platform that offers quantitative and extended lipidomic coverage down to the molecular lipid species level for systematic lipidomic profiling of large populations.

In order to achieve this performance, we optimized the sample preparation, MS acquisition, and lipid identification approaches. All sample preparation steps were automatized for increased throughput and precision. On the instrumentation side, we took advantage of the configuration of the quadrupole-Orbitrap hardware that allows fast polarity switching, safe precursor selection for MSMS fragmentation analysis, and high mass accuracy and resolution.

The combination of these features allows for obtaining multiple complementary MS scans in the same acquisition that enabled us to cover the full spectrum of intact lipids. The increase in sample number and spectral complexity inclusion of MSMS spectra greatly inflates the information to be processed.

To handle this, we developed a new approach for individual molecular species identification and quantification. Lipid species from high resolution MS spectrum are identified and quantified followed by deconvolution of these lipid species into the different lipid molecular species using the corresponding tandem MS fragments. In addition to the high coverage and throughput, this technology is also very robust.

We observed very small technical variation within the same day, between different days of acquisition and between different acquisition sites. We present, for the first time, a technology so robust that it can be implemented in other laboratories without any compromise in precision. These are important features required in clinical diagnostics screens.

Moreover, we assess the impact of sample collection and storage on the plasma lipidome stability. Water, propanol, and methanol were purchased from Fischer Scientific. Methyl tert-butyl ether, chloroform, ammonium bicarbonate, and ammonium acetate were purchased from Sigma—Aldrich. All chemicals were analytical grade.

It was used to prepare the reference samples, where plasma from three healthy, unfasted donors was combined in equivolumetric ratios separated in batches according to the anticoagulant used.

For all analysis, except the comparison of anticoagulants, the plasma derived from EDTA-stabilized blood samples was used and all samples measured were coming from the same batch of reference samples.

For the anticoagulation comparison, blood was collected into S-Monovette EDTA K3, sodium citrate, and lithium—heparin all Sarstedt anticoagulant vacutainers each donor donated blood to all three containers according to the producer's manual.

One freeze and thaw cycle was performed on a daily basis and immediately after all cycles were completed samples were extracted and analyzed. The lipid extraction adapted from Matyash et al.

Twenty-one microliters of internal standard mixture was pre-mixed with the organic solvents mixture. Hundred microliters of the organic phase was transferred to an infusion plate and dried in a speed vacuum concentrator. Five microliters were infused with gas pressure and voltage set to 1. Samples were analyzed in both polarities in a single acquisition. The inclusion list contains all the masses from The isolation width was set to 1.

This inclusion list contains all the masses from Isolation width was set to 1. All data were analyzed with an in-house developed lipid identification software based on LipidXplorer 24 , All Molecular Fragmentation Query Language queries used in this work are available and can be found in Supplementary Material 1. Data post-processing and normalization were performed using an in-house developed data management system.

Data visualization, linear regression linear least squares method , and correlation two-tailed Pearson correlation calculations were performed on Prism 6. Automation is essential in order to handle large number of samples because it increases the speed and throughput of the method, makes it more cost-efficient, and most importantly it improves reproducibility 26 see section 3.

Remarkably, most lipidomics studies still use one of almost 60 years old classical extraction protocols at times with minor modifications 27 , More recently, Matyash et al. This extraction achieves high recovery of multiple lipid classes with several important advantages MTBE, compared to chloroform, is non-toxic and non-carcinogenic. The organic lipid-containing phase remains on top of the aqueous phase, reducing the water-soluble contaminants during extract collection.

All these factors put together greatly facilitate automated sample handling procedures. For this study, we defined the optimal time of MTBE-based lipid extraction at which maximum lipid recovery is achieved. To this end, a mixture containing standards representing the most abundant lipid classes was added post-extraction to blood plasma lipids extracted for different times.

The quadrupole-Orbitrap configuration allows multiple possibilities for lipid identification. Besides the consecutive acquisition in both positive and negative ion mode 20 , some lipids can be detected by a top-down approach where the unambiguous identification is possible due to the high resolution of the detector, relying solely on the precursor mass accuracy In order to increase the identification specificity, it can also be combined to a bottom-up approach by introducing fragmentation experiments made possible by the presence of the quadrupole.

Moreover, this bottom-up approach allows additional structural elucidation which enables molecular lipid species identification 30 , To date, molecular lipid species identification and quantification required multiple rounds of long tandem MS acquisitions in order to obtain the statistics for an accurate measurement.

To bypass this and decrease the acquisition time, we propose a new approach that takes advantage of the Q-Orbitrap features. Firstly, from the FTMS high-resolution spectrum, we normalize the de-isotoped type I and II intensity of the monoisotopic peak of an endogenous species to the de-isotoped type I and II intensity of the monoisotopic peak of the standard of the same class to obtain absolute quantification at the species level:.

After quantification at the species level, the amounts of all x molecular phospholipid species with overlapping sum compositions, can then be deconvoluted from the n acyl anions fragmentation information contained in the tandem MS data, as follows:. With this approach, we circumvent the need for multiple cycles of MSMS in order to achieve accurate quantification greatly reducing the time of acquisition.

Phospholipids display variable but in general efficient fragmentation that allows the elucidation of the fatty acid composition 31 , but other lipid classes can be more difficult to assess.

For example, because triacylglycerides contain combinations of three fatty acids, this makes the assignment of molecular lipid species without chromatographic separation and MS n type of experiments virtually impossible Also, the fragmentation of sphingolipids is very inefficient and not suitable for structure elucidation.

The most notable case is sphingomyelin. It presents only one abundant phosphocholine fragment in positive mode that does not give any additional structural information.

Conversely, in negative ion mode there is a fragment corresponding to the loss of the amide-linked fatty acid allowing the molecular lipid species elucidation but it cannot be used for identification due to its low intensity. In Table 1 , we present a strategy to identify each lipid class and the level of structural detail that can be achieved. Mode of acquisition and identification see section 2.

S1 and S3 for additional information. One of the biggest challenges of comprehensive lipid analysis is the huge dynamic range of lipid abundances observed in biological samples like blood plasma. Chromatographic techniques minimize the ion suppression effect of highly abundant lipid species by resolving the different lipids in a temporal dimension This allows for extracting a wide range of sample amounts that to some extent can be tuned for the detection of low abundant species.

In a shotgun lipidomics approach, sample infusion is continuous and the acquisition is done simultaneously for all the different lipid classes, which makes it more susceptible to ion suppression To minimize this, the fine tuning of the sample amount to be extracted is of paramount importance for shotgun-based experiments We extracted different sample amounts together with fixed amounts of internal standards in order to determine the minimum and maximum amounts that give reliable lipid compositions.

We observed that most lipid classes give a linear response over two orders of magnitude of sample amount 0. It is important to note that this amount is optimized for healthy individuals and needs to be carefully assessed in metabolically challenged conditions where the concentration of specific lipid classes such as triglycerides in blood can increase significantly.

For quantification, we used one internal standard per lipid class. These internal standards were chosen based on two criteria: first, its absence in plasma samples and second, its similarity to the structure and properties e. This approach is valid due to the fact that the recovery and ionization efficiency of different lipid species within a lipid class is predominantly dependent on their charged head group while their differential acyl chains only minimally alter their ionization at low lipid concentrations 35 , 36 Fig.

Two notable exceptions are present in the SM profile. SM ;2 apparent relative decrease with sample amount increase is explained by a small background peak of a similar overlapping mass observed already in the blank samples.

Importantly, this effect is only significant at very low sample amounts and its impact at the optimal sample amount is minimal. Although this is a significant difference, it is not observed in other SM species. This effect is most likely related to differential matrix effects introduced by variable amounts of plasma sample extracted and its impact is irrelevant when we fix the sample amount. In conclusion, we obtain identical lipid species profiles at different sample concentrations, confirming the assumption that ionization within a lipid class is not lipid species specific for the sample amounts tested allowing to express the quantities in molar amounts.

This observation allows us to conclude that, for the optimal sample amount, all lipid species measured within a lipid class have similar response factors enabling absolute quantification with a single standard addition per lipid class.

Different lipid classes exhibit different extraction, ionization, and fragmentation efficiencies, so the limit of quantification LOQ and dynamic ranges are lipid class-specific. Interestingly, they are all acquired in positive ion mode as an ammonium adduct, so an increase in the ammonium acetate concentration in the MS-infusion mixture can potentially improve their detection sensitivity, if required.

We conclude that the absence or low number of lipid species identified in some classes such as HexCer, LPA, LPS, and PA is due to their low abundance in this particular sample rather than low sensitivity for these lipid classes.

In this work, we aimed at maximizing method reproducibility by automation of most of the sample preparation, extraction, data acquisition and, to some extent, lipid identification, and post-processing of the data.

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  1. Rinaldo M.

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