Focus on Metabolism: Spatially Resolved Plant Metabolomics: Some Potentials and Limitations of Laser-Ablation Electrospray Ionization Mass Spectrometry Metabolite Imaging

Laser-ablation electrospray ionization (LAESI)-mass spectrometry imaging has been applied to contrasting plant organs to assess its potential as a procedure for performing in vivo metabolomics in plants. In a proof-of-concept experiment, purple/white segmented Phalaenopsis spp. petals were first analyzed using standard liquid chromatography-mass spectrometry analyses of separate extracts made specifically from the purple and white regions. Discriminatory compounds were defined and putatively annotated. LAESI analyses were then performed on living tissues, and these metabolites were then relocalized within the LAESI-generated data sets of similar tissues. Maps were made to illustrate their locations across the petals. Results revealed that, as expected, anthocyanins always mapped to the purple regions. Certain other (nonvisible) polyphenols were observed to colocalize with the anthocyanins, whereas others were found specifically within the white tissues. In a contrasting example, control and Cladosporium fulvum-infected tomato (Solanum lycopersicum) leaves were subjected to the same procedures, and it could be observed that the alkaloid tomatine has clear heterogeneous distribution across the tomato leaf lamina. Furthermore, LAESI analyses revealed perturbations in alkaloid content following pathogen infection. These results show the clear potential of LAESI-based imaging approaches as a convenient and rapid way to perform metabolomics analyses on living tissues. However, a range of limitations and factors have also been identified that must be taken into consideration when interpreting LAESI-derived data. Such aspects deserve further evaluation before this approach can be applied in a routine manner.Plants are a tremendously rich source of a myriad of structurally and chemically diverse metabolites (Rao and Ravishankar, 2002; D’Auria and Gershenzon, 2005). Many of these metabolites have a (partly) known function in the plant, although our knowledge of the vast majority of plant secondary metabolites is still sparse, or even nonexistent (Rao and Ravishankar, 2002; D’Auria and Gershenzon, 2005; Fernie, 2007). Plant metabolites are also of considerable importance in a crop context. Indeed, most plant species that have undergone domestication have become crops specifically because they provide us with a source of chemicals. This is not only true for all of our food crops, but also for many other species of genera such as Pyrethrum (insecticides), Jasminium and Santalum (perfumes), Hevea (rubber), Nicotiana and Cannabis (drugs), Linum (oils), Artemisia and Taxus (pharmaceuticals), Cinnamomum (flavors), etc. However, despite the importance of plants as a source of exploitable and essential biochemicals, we often still have remarkably limited knowledge of the relevant biosynthetic pathways, the genetics behind the key enzymes, and indeed when, why, and where these metabolites are produced and stored within the plant in question (Fernie, 2007; Sumner et al., 2011; Kueger et al., 2012).The field of plant metabolomics has grown tremendously since its recent inception earlier this century (Fiehn et al., 2000; Fiehn, 2002). As an untargeted approach to gain a broad overview of the complexity of plant metabolic composition, the technology has, in a short time, made significant inroads into helping expand our knowledge of plant biochemistry (Kueger et al., 2012; Etalo et al., 2013; Hunerdosse and Nomura, 2014; Meret et al., 2014). Typically, rich metabolomics data sets already provide us with a valuable means to generate hypotheses relating to plant metabolism, which then become the focus of further, more direct investigation (Quanbeck et al., 2012). New technologies are being developed, and especially, new data-mining strategies are being designed to allow us to look deep into plant metabolism without having first to rely on preconceptions. However, there are significant limitations to the application of the technology, which still remain the topic of much research effort.Robust sampling approaches for plant biochemical analysis generally entail taking reliably measurable amounts of plant material that will yield detectable levels of the chemical components. Although for metabolomics analyses, samples of just 50 mg can often suffice, obtaining a reliable sample with minimum biological variation generally requires an initial pooling of materials from which a representative sample is then taken. We therefore treat plant tissue as being homogeneous, but this is clearly a gross oversimplification (Fernie, 2007). Plants have been considered to be composed of roughly 40 different cell types, and a plant organ such as a leaf will generally contain up to 15 different cell types (Martin et al., 2001). Different morphologies also parallel different biochemical composition. Even directly neighboring cells within an organ, for example, a leaf epidermis that often comprises pavement, guard, trichome, and glandular hair cells, are formed from cells already known to have distinctly different biochemistries. Making an extract, for any kind of metabolomics or standard biochemical analysis, therefore entails that we immediately lose most intercellular and intertissue resolution. However, our knowledge is growing in that, in addition to known or expected biochemical differences between cell types, metabolite accumulation across organs can be far from uniform; indeed, islands of higher and lower concentrations of particular metabolites have been observed. This is of course immediately visible when the metabolites concerned can be seen by the naked eye; anthocyanins, for example, are often found to be heterogeneously distributed across leaves, fruits, and flower petals, creating clear phenotypic patterns. The same may also be true of other compounds that are invisible to the human eye but that, in contrast, may still be detectable by insects (e.g. through their fluorescence capacity; see http://www.naturfotograf.com/UV_flowers_list.html; Gronquist et al., 2001).In an ideal situation, we would like to be able to look directly into a plant tissue and be able to analyze the biochemical composition at the single cell level. Some so-called metabolite imaging technologies, usually based on mass spectrometric detection (mass spectrometry imaging [MSI]), have recently been introduced as a step toward this optimistic goal. Included here are matrix-assisted laser desorption/ionization (MALDI)-MSI, direct analysis in real time, and desorption electrospray ionization approaches (Cody et al., 2005; Cornett et al., 2007; Ifa et al., 2010). Early examples of MALDI-MSI have shown not only how primary metabolites such as sugars can be strongly localized within plant organs (Rolletschek et al., 2011), but also how the heterogeneous distribution of glucosinolates in Arabidopsis (Arabidopsis thaliana) can potentially determine grazing behavior of caterpillars (Shroff et al., 2008). This technology continues to improve, and recent exciting developments have resulted in cellular and subcellular imaging of metabolites at a resolution of 5 to 9 µm using MALDI (Korte et al., 2015). However, some key practical limitations of MALDI-based approaches are centered around the need to initially have to pretreat/dehydrate the tissue prior to applying the required matrix solution and the requirement of applying a vacuum during the biochemical analysis. Recently, a new technology has been introduced, laser ablation electrospray ionization (LAESI), which can potentially overcome some of these limitations, given that measurements can be made on fresh, living tissue without the need for a vacuum, thus creating the potential for high-resolution in vivo metabolomics.Here, we report on a set of experiments performed to assess both the potential and limitations of using LAESI-based MSI approaches to perform metabolic mapping on living plant tissues. While identifying a number of technological challenges that still need to be tackled, we were able to show that it is possible to use LAESI-MSI to map metabolites directly onto their known location (in this case, by exploiting the visibility of anthocyanins) as well as localize invisible metabolites in the same tissue. Results have revealed that in plants, for both petal and leaf tissue, the distribution of metabolites can be highly heterogeneous, and that this heterogeneity is of potential relevance to our gaining a broader, more detailed understanding of the overall molecular organization and phenotypic features of plant tissues. Furthermore, knowledge of the nature and extent of this heterogeneity has particular relevance and importance when trying to understand how a plant functions as a system, interacting with its environment. We predict that a higher resolution understanding of plant biochemistry will lead to an increasingly discriminatory capacity in our ability to define more accurately the spatial complexity of plant molecular organization.     

Space exploration by dendritic cells requires maintenance of myosin II activity by IP3 receptor 1

Dendritic cells (DCs) patrol the interstitial space of peripheral tissues. The mechanisms that regulate their migration in such constrained environment remain unknown. We here investigated the role of calcium in immature DCs migrating in confinement. We found that they displayed calcium oscillations that were independent of extracellular calcium and more frequently observed in DCs undergoing strong speed fluctuations. In these cells, calcium spikes were associated with fast motility phases. IP₃ receptors (IP₃Rs) channels, which allow calcium release from the endoplasmic reticulum, were identified as required for immature DCs to migrate at fast speed. The IP₃R1 isoform was further shown to specifically regulate the locomotion persistence of immature DCs, that is, their capacity to maintain directional migration. This function of IP₃R1 results from its ability to control the phosphorylation levels of myosin II regulatory light chain (MLC) and the back/front polarization of the motor protein. We propose that by upholding myosin II activity, constitutive calcium release from the ER through IP₃R1 maintains DC polarity during migration in confinement, facilitating the exploration of their environment.     

Dynamic Mechanisms of the Bactericidal Action of an Al2O3-TiO2-Ag Granular Material on an Escherichia coli Strain

The bactericidal activity of an Al₂O₃-TiO₂-Ag granular material against an Escherichia coli strain was confirmed by a culture-based method. In particular, 100% of microorganisms were permanently inactivated in 30 to 45 min. The present work aimed to investigate the mechanisms of the bactericidal action of this material and their dynamics on Escherichia coli using different techniques. Observations by transmission electron microscopy (TEM) at different times of disinfection revealed morphological changes in the bacteria as soon as they were put in contact with the material. Notably highlighted were cell membrane damage; cytoplasm detachment; formation of vacuoles, possibly due to DNA condensation, in association with regions exhibiting different levels of electron density; and membrane lysis. PCR and flow cytometry analyses were used to confirm and quantify the observations of cell integrity. The direct exposure of cells to silver, combined with the oxidative stress induced by the reactive oxygen species (ROS) generated, was identified to be responsible for these morphological alterations. From the first 5 min of treatment with the Al₂O₃-TiO₂-Ag material, 98% of E. coli isolates were lysed. From 30 min, cell viability decreased to reach total inactivation, although approximately 1% of permeable E. coli cells and 1% of intact cells (10⁵ genomic units · ml⁻¹) were evidenced. This study demonstrates that the bactericidal effect of the material results from a synergic action of desorbed and supported silver. Supported silver was shown to generate the ROS evidenced.     

Avoidable errors in the modelling of outbreaks of emerging pathogens, with special reference to Ebola

As an emergent infectious disease outbreak unfolds, public health response is reliant on information on key epidemiological quantities, such as transmission potential and serial interval. Increasingly, transmission models fit to incidence data are used to estimate these parameters and guide policy. Some widely used modelling practices lead to potentially large errors in parameter estimates and, consequently, errors in model-based forecasts. Even more worryingly, in such situations, confidence in parameter estimates and forecasts can itself be far overestimated, leading to the potential for large errors that mask their own presence. Fortunately, straightforward and computationally inexpensive alternatives exist that avoid these problems. Here, we first use a simulation study to demonstrate potential pitfalls of the standard practice of fitting deterministic models to cumulative incidence data. Next, we demonstrate an alternative based on stochastic models fit to raw data from an early phase of 2014 West Africa Ebola virus disease outbreak. We show not only that bias is thereby reduced, but that uncertainty in estimates and forecasts is better quantified and that, critically, lack of model fit is more readily diagnosed. We conclude with a short list of principles to guide the modelling response to future infectious disease outbreaks.     

Molecular Simulations of Gram-Negative Bacterial Membranes: A Vignette of Some Recent Successes

In the following review we use recent examples from the literature to discuss progress in the area of atomistic and coarse-grained molecular dynamics simulations of selected bacterial membranes and proteins, with a particular focus on Gram-negative bacteria. As structural biology continues to provide increasingly high-resolution data on the proteins that reside within these membranes, simulations have an important role to play in linking these data with the dynamical behavior and function of these proteins. In particular, in the last few years there has been significant progress in addressing the issue of biochemical complexity of bacterial membranes such that the heterogeneity of the lipid and protein components of these membranes are now being incorporated into molecular-level models. Thus, in future we can look forward to complementary data from structural biology and molecular simulations combining to provide key details of structure-dynamics-function relationships in bacterial membranes.     

The N-Glycan Cluster from Xanthomonas campestris pv. campestris: A TOOLBOX FOR SEQUENTIAL PLANT N-GLYCAN PROCESSING*

N-Glycans are widely distributed in living organisms but represent only a small fraction of the carbohydrates found in plants. This probably explains why they have not previously been considered as substrates exploited by phytopathogenic bacteria during plant infection. Xanthomonas campestris pv. campestris, the causal agent of black rot disease of Brassica plants, possesses a specific system for GlcNAc utilization expressed during host plant infection. This system encompasses a cluster of eight genes (nixE to nixL) encoding glycoside hydrolases (GHs). In this paper, we have characterized the enzymatic activities of these GHs and demonstrated their involvement in sequential degradation of a plant N-glycan using a N-glycopeptide containing two GlcNAcs, three mannoses, one fucose, and one xylose (N₂M₃FX) as a substrate. The removal of the α-1,3-mannose by the α-mannosidase NixK (GH92) is a prerequisite for the subsequent action of the β-xylosidase NixI (GH3), which is involved in the cleavage of the β-1,2-xylose, followed by the α-mannosidase NixJ (GH125), which removes the α-1,6-mannose. These data, combined to the subcellular localization of the enzymes, allowed us to propose a model of N-glycopeptide processing by X. campestris pv. campestris. This study constitutes the first evidence suggesting N-glycan degradation by a plant pathogen, a feature shared with human pathogenic bacteria. Plant N-glycans should therefore be included in the repertoire of molecules putatively metabolized by phytopathogenic bacteria during their life cycle.     

Structural Basis for the Discriminative Recognition of N6-Methyladenosine RNA by the Human YT521-B Homology Domain Family of Proteins

N⁶-Methyladenosine (m⁶A) is the most abundant internal modification in RNA and is specifically recognized by YT521-B homology (YTH) domain-containing proteins. Recently we reported that YTHDC1 prefers guanosine and disfavors adenosine at the position preceding the m⁶A nucleotide in RNA and preferentially binds to the GG(m⁶A)C sequence. Now we systematically characterized the binding affinities of the YTH domains of three other human proteins and yeast YTH domain protein Pho92 and determined the crystal structures of the YTH domains of human YTHDF1 and yeast Pho92 in complex with a 5-mer m⁶A RNA, respectively. Our binding and structural data revealed that the YTH domain used a conserved aromatic cage to recognize m⁶A. Nevertheless, none of these YTH domains, except YTHDC1, display sequence selectivity at the position preceding the m⁶A modification. Structural comparison of these different YTH domains revealed that among those, only YTHDC1 harbors a distinctly selective binding pocket for the nucleotide preceding the m⁶A nucleotide.     

Blood and cloacal swab sampling for avian influenza monitoring has no effect on survival rates of free‐ranging ducks

Concerns about the spread of avian influenza viruses (AIVs) have led to cloacal swab sampling of hundreds of thousands of birds worldwide as part of AIV surveillance schemes, but the effects of cloacal swabbing have not been adequately evaluated. We tested for differences between swabbed, swabbed and bled, and non‐sampled wild ducks in terms of live re‐encounter and dead recoveries for Common Pochard Aythya ferina and Tufted Duck Aythya fuligula, and also determined re‐encounter and recovery rates for Mallard Anas platyrhynchos and Common Teal Anas crecca. No effects of sampling methods were detected, except in Teal. Re‐encounter rates were lower in sampled Teal than in controls, with annual re‐encounter probabilities being 25% and 35% lower in males and females, respectively. Teal possibly left or avoided sampling sites, or sought sites where they were less detectable after sampling. In general, no deleterious effects were found, suggesting that cloacal swabbing and blood sampling are suitable methods for conducting AIV surveillance in ducks.     

Plasma Membrane Tetraspanin CD81 Complexes with Proprotein Convertase Subtilisin/Kexin Type 9 (PCSK9) and Low Density Lipoprotein Receptor (LDLR), and Its Levels Are Reduced by PCSK9

Proprotein convertase subtilisin/kexin type 9 (PCSK9) is an important factor in plasma cholesterol regulation through modulation of low density lipoprotein receptor (LDLR) levels. Naturally occurring mutations can lead to hyper- or hypocholesterolemia in human. Recently, we reported that PCSK9 was also able to modulate CD81 in Huh7 cells. In the present study, several gain-of-function and loss-of-function mutants as well as engineered mutants of PCSK9 were compared for their ability to modulate the cell surface expression of LDLR and CD81. Although PCSK9 gain-of-function D374Y enhanced the degradation both receptors, D374H and D129N seemed to only reduce LDLR levels. In contrast, mutations in the C-terminal hinge-cysteine-histidine-rich domain segment primarily affected the PCSK9-induced CD81 degradation. Furthermore, when C-terminally fused to an ACE2 transmembrane anchor, the secretory N-terminal catalytic or hinge-cysteine-histidine-rich domain domains of PCSK9 were able to reduce CD81 and LDLR levels. These data confirm that PCSK9 reduces CD81 levels via an intracellular pathway as reported for LDLR. Using immunocytochemistry, a proximity ligation assay, and co-immunoprecipitation, we found that the cell surface level of PCSK9 was enhanced upon overexpression of CD81 and that both PCSK9 and LDLR interact with this tetraspanin protein. Interestingly, using CHO-A7 cells lacking LDLR expression, we revealed that LDLR was not required for the degradation of CD81 by PCSK9, but its presence strengthened the PCSK9 effect.     

Identification of NF-κB and PLCL2 as new susceptibility genes and highlights on a potential role of IRF8 through interferon signature modulation in systemic sclerosis

IntroductionSystemic sclerosis (SSc) and primary biliary cirrhosis (PBC) are rare polygenic autoimmune diseases (AIDs) characterized by fibroblast dysfunction. Furthermore, both diseases share some genetic bases with other AIDs, as evidenced by autoimmune gene pleiotropism. The present study was undertaken to investigate whether single-nucleotide polymorphisms (SNPs) identified by a large genome-wide association study (GWAS) in PBC might contribute to SSc susceptibility.MethodsSixteen PBC susceptibility SNPs were genotyped in a total of 1,616 patients with SSc and 3,621 healthy controls from two European populations (France and Italy).ResultsWe observed an association between PLCL2 rs1372072 (odds ratio (OR) = 1.22, 95% confidence interval (CI) 1.12 to 1.33, P_adj = 7.22 × 10⁻⁵), nuclear factor-kappa-B (NF-κB) rs7665090 (OR = 1.15, 95% CI 1.06 to 1.25, P_adj = 0.01), and IRF8 rs11117432 (OR = 0.75, 95% CI 0.67 to 0.86, P_adj = 2.49 × 10⁻⁴) with SSc susceptibility. Furthermore, phenotype stratification showed an association between rs1372072 and rs11117432 with the limited cutaneous subgroup (lcSSc) (P_adj = 4.45 × 10⁻⁴ and P_adj = 0.001), whereas rs7665090 was associated with the diffuse cutaneous subtype (dcSSc) (P_adj = 0.003). Genotype-mRNA expression correlation analysis revealed that the IRF8 protective allele was associated with increased interferon-gamma (IFN-γ) expression (P = 0.03) in patients with SSc but decreased type I IFN (IFIT1) expression in patients and controls (P = 0.02). In addition, we found an epistatic interaction between NF-κB and IRF8 (OR = 0.56, 95% CI 0.00 to 0.74, P = 4 × 10⁻⁴) which in turn revealed that the IRF8 protective effect is dependent on the presence of the NF-κB susceptibility allele.ConclusionsAn analysis of pleiotropic genes identified two new susceptibility genes for SSc (NF-κB and PLCL2) and confirmed the IRF8 locus. Furthermore, the IRF8 variant influenced the IFN signature, and we found an interaction between IRF8 and NF-κB gene variants that might play a role in SSc susceptibility.

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