Ulf Sommer

Characterization of Isotopic Abundance Measurements in High Resolution FT-ICR and Orbitrap Mass Spectra for Improved Confidence of Metabolite Identification

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.

Structure and function of BamE within the outer membrane and the β‐barrel assembly machine

Insertion of folded proteins into the outer membrane of Gram‐negative bacteria is mediated by the essential β‐barrel assembly machine (Bam). Here, we report the native structure and mechanism of a core component of this complex, BamE, and show that it is exclusively monomeric in its native environment of the periplasm, but is able to adopt a distinct dimeric conformation in the cytoplasm. BamE is shown to bind specifically to phosphatidylglycerol, and comprehensive mutagenesis and interaction studies have mapped key determinants for complex binding, outer membrane integrity and cell viability, as well as revealing the role of BamE within the Bam complex.

Mass spectrometry based environmental metabolomics: a primer and review

Environmental metabolomics can be described as the study of the interactions of living organisms with their natural environments at the metabolic level. Until recently, nuclear magnetic resonance (NMR) spectroscopy has been the primary bioanalytical tool for measuring metabolite levels in this field. While NMR has some specific advantages, the higher sensitivity offered by mass spectrometry (MS) is beginning to revolutionise our ability to probe environmental metabolomes. This review provides the first comprehensive overview of the use and capabilities of MS within environmental metabolomics. Its primary aims are to introduce environmental scientists to the range of MS approaches used in metabolomics and to highlight the breadth and diversity of environmental and ecological research conducted, from ecophysiology and ecotoxicology to chemical ecology. The review is structured around MS approaches: non-targeted gas chromatography–MS, non-targeted directed infusion MS, and both non-targeted and targeted liquid chromatography–MS. Each section begins with a brief introduction to the analytical method, including some advantages and limitations in the context of metabolomics research, and then exemplifies the use of that technique in environmental metabolomics. The review concludes with a discussion on some of the challenges that remain in MS based environmental metabolomics and provides recommendations for the path ahead.

Anaerobic Metabolism at Thermal Extremes: A Metabolomic Test of the Oxygen Limitation Hypothesis in an Aquatic Insect

Thermal limits in ectotherms may arise through a mismatch between supply and demand of oxygen. At higher temperatures, the ability of their cardiac and ventilatory activities to supply oxygen becomes insufficient to meet their elevated oxygen demand. Consequently, higher levels of oxygen in the environment are predicted to enhance tolerance of heat, whereas reductions in oxygen are expected to reduce thermal limits. Here, we extend previous research on thermal limits and oxygen limitation in aquatic insect larvae and directly test the hypothesis of increased anaerobic metabolism and lower energy status at thermal extremes. We quantified metabolite profiles in stonefly nymphs under varying temperatures and oxygen levels. Under normoxia, the concept of oxygen limitation applies to the insects studied. Shifts in the metabolome of heat-stressed stonefly nymphs clearly indicate the onset of anaerobic metabolism (e.g., accumulation of lactate, acetate, and alanine), a perturbation of the tricarboxylic acid cycle (e.g., accumulation of succinate and malate), and a decrease in energy status (e.g., ATP), with corresponding decreases in their ability to survive heat stress. These shifts were more pronounced under hypoxic conditions, and negated by hyperoxia, which also improved heat tolerance. Perturbations of metabolic pathways in response to either heat stress or hypoxia were found to be somewhat similar but not identical. Under hypoxia, energy status was greatly compromised at thermal extremes, but energy shortage and anaerobic metabolism could not be conclusively identified as the sole cause underlying thermal limits under hyperoxia. Metabolomics proved useful for suggesting a range of possible mechanisms to explore in future investigations, such as the involvement of leaking membranes or free radicals. In doing so, metabolomics provided a more complete picture of changes in metabolism under hypoxia and heat stress.

Non-targeted UHPLC-MS metabolomic data processing methods: a comparative investigation of normalisation, missing value imputation, transformation and scaling

IntroductionThe 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.ObjectivesCurrently, 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.MethodsWe 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.ResultsOur 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.ConclusionThe 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.

1H NMR Metabolomics Reveals Contrasting Response by Male and Female Mussels Exposed to Reduced Seawater pH, Increased Temperature, and a Pathogen

Human activities are fundamentally altering the chemistry of the worlds oceans. Ocean acidification (OA) is occurring against a background of warming and an increasing occurrence of disease outbreaks, posing a significant threat to marine organisms, communities, and ecosystems. In the current study, (1)H NMR spectroscopy was used to investigate the response of the blue mussel, Mytilus edulis, to a 90-day exposure to reduced seawater pH and increased temperature, followed by a subsequent pathogenic challenge. Analysis of the metabolome revealed significant differences between male and female organisms. Furthermore, males and females are shown to respond differently to environmental stress. While males were significantly affected by reduced seawater pH, increased temperature, and a bacterial challenge, it was only a reduction in seawater pH that impacted females. Despite impacting males and females differently, stressors seem to act via a generalized stress response impacting both energy metabolism and osmotic balance in both sexes. This study therefore has important implications for the interpretation of metabolomic data in mussels, as well as the impact of environmental stress in marine invertebrates in general.

Wolbachia Modulates Lipid Metabolism in Aedes albopictus Mosquito Cells

ABSTRACT 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.

The metabolic response of marine copepods to environmental warming and ocean acidification in the absence of food

Marine copepods are central to the productivity and biogeochemistry of marine ecosystems. Nevertheless, the direct and indirect effects of climate change on their metabolic functioning remain poorly understood. Here, we use metabolomics, the unbiased study of multiple low molecular weight organic metabolites, to examine how the physiology of Calanus spp. is affected by end-of-century global warming and ocean acidification scenarios. We report that the physiological stresses associated with incubation without food over a 5-day period greatly exceed those caused directly by seawater temperature or pH perturbations. This highlights the need to contextualise the results of climate change experiments by comparison to other, naturally occurring stressors such as food deprivation, which is being exacerbated by global warming. Protein and lipid metabolism were up-regulated in the food-deprived animals, with a novel class of taurine-containing lipids and the essential polyunsaturated fatty acids (PUFAs), eicosapentaenoic acid and docosahexaenoic acid, changing significantly over the duration of our experiment. Copepods derive these PUFAs by ingesting diatoms and flagellated microplankton respectively. Climate-driven changes in the productivity, phenology and composition of microplankton communities, and hence the availability of these fatty acids, therefore have the potential to influence the ability of copepods to survive starvation and other environmental stressors.

Statistical Correlations between NMR Spectroscopy and Direct Infusion FT-ICR Mass Spectrometry Aid Annotation of Unknowns in Metabolomics

NMR spectroscopy and mass spectrometry are the two major analytical platforms for metabolomics, and both generate substantial data with hundreds to thousands of observed peaks for a single sample. Many of these are unknown, and peak assignment is generally complex and time-consuming. Statistical correlations between data types have proven useful in expediting this process, for example, in prioritizing candidate assignments. However, this approach has not been formally assessed for the comparison of direct-infusion mass spectrometry (DIMS) and NMR data. Here, we present a systematic analysis of a sample set (tissue extracts), and the utility of a simple correlation threshold to aid metabolite identification. The correlations were surprisingly successful in linking structurally related signals, with 15 of 26 NMR-detectable metabolites having their highest correlation to a cognate MS ion. However, we found that the distribution of the correlations was highly dependent on the nature of the MS ion, such as the adduct type. This approach should help to alleviate this important bottleneck where both 1D NMR and DIMS data sets have been collected.

A stable-isotope mass spectrometry-based metabolic footprinting approach to analyze exudates from phytoplankton.

Phytoplankton exudates play an important role in pelagic ecology and biogeochemical cycles of elements. Exuded compounds fuel the microbial food web and often encompass bioactive secondary metabolites like sex pheromones, allelochemicals, antibiotics, or feeding attractants that mediate biological interactions. Despite this importance, little is known about the bioactive compounds present in phytoplankton exudates. We report a stable-isotope metabolic footprinting method to characterise exudates from aquatic autotrophs. Exudates from 13C-enriched alga were concentrated by solid phase extraction and analysed by high-resolution Fourier transform ion cyclotron resonance mass spectrometry. We used the harmful algal bloom forming dinoflagellate Alexandrium tamarense to prove the method. An algorithm was developed to automatically pinpoint just those metabolites with highly 13C-enriched isotope signatures, allowing us to discover algal exudates from the complex seawater background. The stable-isotope pattern (SIP) of the detected metabolites then allowed for more accurate assignment to an empirical formula, a critical first step in their identification. This automated workflow provides an effective way to explore the chemical nature of the solutes exuded from phytoplankton cells and will facilitate the discovery of novel dissolved bioactive compounds.