Introduction The generic metabolomics data processing workflow is constructed with a serial set of processes including peak picking, quality assurance, normalisation, missing value imputation, transformation and scaling. The combination of these processes should present the experimental data in an appropriate structure so to identify the biological changes in a valid and robust manner. Objectives Currently, different researchers apply different data processing methods and no assessment of the permutations applied to UHPLC-MS datasets has been published. Here we wish to define the most appropriate data processing workflow. Methods We assess the influence of normalisation, missing value imputation, transformation and scaling methods on univariate and multivariate analysis of UHPLC-MS datasets acquired for different mammalian samples.Results Our studies have shown that once data are filtered, missing values are not correlated with m/z, retention time or response. Following an exhaustive evaluation, we recommend PQN normalisation with no missing value imputation and no transformation or scaling for univariate analysis. For PCA we recommend applying PQN normalisation with Random Forest missing value imputation, glog transformation and no scaling method. For PLS-DA we recommend PQN normalisation, KNN as the missing value imputation method, generalised logarithm transformation and no scaling. These recommendations are based on searching for the biologically important metabolite features independent of their measured abundance. Conclusion The appropriate choice of normalisation, missing value imputation, transformation and scaling methods differs depending on the data analysis method and the choice of method is essential to maximise the biological derivations from UHPLC-MS datasets.

A simple and robust LC-MS-based methodology for the investigation of lipid mixtures is described, and its application to the analysis of human lipoprotein-associated lipids is demonstrated. After an optional initial fractionation on Silica 60, normal-phase HPLC-MS on a YMC PVA-Sil column is used first for class separation, followed by reversedphase LC-MS or LC-tandem mass spectrometry using an Atlantis dC18 capillary column, and/or nanospray MS, to fully characterize the individual lipids. The methodology is applied here for the analysis of human apolipoprotein Bassociated lipids. This approach allows for the determination of even low percentages of lipids of each molecular species and showed clear differences between lipids associated with apolipoprotein B-100-LDL isolated from a normal individual and those associated with a truncated version, apolipoprotein B-67-containing lipoproteins, isolated from a homozygote patient with familial hypobetalipoproteinemia. The methods described should be easily adaptable to most modern MS instrumentation. A large variety of methods have been published for the separation of lipids, either by TLC or by LC; the methods have usually been described for the analysis of specific classes of compounds (www.cyberlipid.org). MS methods for the characterization of lipid mixtures have also been published in recent years, most of them centered on the use of matrix-assisted laser desorption/ionization time-offlight (MALDI-TOF) MS and electrospray ionization (ESI) MS (1) (in addition to the references cited in the text, important Web-based sources of information were www. cyberlipid.org, www.lipidlibrary.co.uk, and www.lipidmaps. org). Sophisticated methods like the characterization of complex glycolipids directly from TLC plates by vibrationally cooled MALDI Fourier transform-ion cyclotron resonance MS (2) require instrumentation that is not yet widely available. A variety of elegant nanospray MS methods have been described (3-5) that are generally a good choice for the characterization of lipids, but they may not be fully capable of both qualitative and quantitative analysis of highly complex mixtures. LC-MS offers possibilities for a better determination of minor compounds whose signals might otherwise be suppressed. It also allows for an additional level of characterization of components based on their chromatographic behavior as well as the MS results.Existing HPLC methods for the separation of lipids are limited, however, in that they either target only selected classes or are not compatible with subsequent MS. Pulfer and Murphy (6) suggested that, for a complete separation of lipids, normal-and reversed-phase chromatography should be combined. Because of its high sensitivity and the additional information it provides, MS is widely recognized as a superior detection method compared with the classic methods of ultraviolet or light scattering. We demonstrate here a simple, robust, and reproducible methodology for lipid analysis, which has been achieved by adapting to LC-MS sev...

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Currently there is limited information available on the accuracy and precision of relative isotopic abundance (RIA) measurements using high-resolution direct-infusion mass spectrometry (HR DIMS), and it is unclear if this information can benefit automated peak annotation in metabolomics. Here we characterize the accuracy of RIA measurements on the Thermo LTQ FT Ultra (resolution of 100,000-750,000) and LTQ Orbitrap (R = 100,000) mass spectrometers. This first involved reoptimizing the SIM-stitching method (Southam, A. D. Anal. Chem. 2007, 79, 4595-4602) for the LTQ FT Ultra, which achieved a ca. 3-fold sensitivity increase compared to the original method while maintaining a root-mean-squared mass error of 0.16 ppm. Using this method, we show the quality of RIA measurements is highly dependent on signal-to-noise ratio (SNR), with RIA accuracy increasing with higher SNR. Furthermore, a negative offset between the theoretical and empirically calculated numbers of carbon atoms was observed for both mass spectrometers. Increasing the resolution of the LTQ FT Ultra lowered both the sensitivity and the quality of RIA measurements. Overall, although the errors in the empirically calculated number of carbons can be large (e.g., 10 carbons), we demonstrate that RIA measurements do improve automated peak annotation, increasing the number of single empirical formula assignments by >3-fold compared to using accurate mass alone.

Certain strains of the intracellular endosymbiont Wolbachia can strongly inhibit or block the transmission of viruses such as dengue virus (DENV) by Aedes mosquitoes, and the mechanisms responsible are still not well understood. Direct infusion and liquid chromatography-Fourier transform ion cyclotron resonance (FT-ICR) mass spectrometry-based lipidomics analyses were conducted using Aedes albopictus Aa23 cells that were infected with the wMel and wMelPop strains of Wolbachia in comparison to uninfected Aa23-T cells. Substantial shifts in the cellular lipid profile were apparent in the presence of Wolbachia. Most significantly, almost all sphingolipid classes were depleted, and some reductions in diacylglycerols and phosphatidylcholines were also observed. These lipid classes have previously been shown to be selectively enriched in DENV-infected mosquito cells, suggesting that Wolbachia may produce a cellular lipid environment that is antagonistic to viral replication. The data improve our understanding of the intracellular interactions between Wolbachia and mosquitoes.IMPORTANCE Mosquitoes transmit a variety of important viruses to humans, such as dengue virus and Zika virus. Certain strains of the intracellular bacterial genus called Wolbachia found in or introduced into mosquitoes can block the transmission of viruses, including dengue virus, but the mechanisms responsible are not well understood. We found substantial shifts in the cellular lipid profiles in the presence of these bacteria. Some lipid classes previously shown to be enriched in dengue virus-infected mosquito cells were depleted in the presence of Wolbachia, suggesting that Wolbachia may produce a cellular lipid environment that inhibits mosquito-borne viruses.