Single-cell proteomic analysis of glucosinolate-rich S-cells in Arabidopsis thaliana

Single-cell analysis is essential for understanding the processes of cell differentiation and metabolic specialisation in rare cell types. The amount of single proteins in single cells can be as low as one copy per cell and is for most proteins in the attomole range or below; usually considered as insufficient for proteomic analysis. The development of modern mass spectrometers possessing increased sensitivity and mass accuracy in combination with nano-LC-MS/MS now enables the analysis of single-cell contents. In Arabidopsis thaliana, we have successfully identified nine unique proteins in a single-cell sample and 56 proteins from a pool of 15 single-cell samples from glucosinolate-rich S-cells by nanoLC-MS/MS proteomic analysis, thus establishing the proof-of-concept for true single-cell proteomic analysis. Dehydrin (ERD14_ARATH), two myrosinases (BGL37_ARATH and BGL38_ARATH), annexin (ANXD1_ARATH), vegetative storage proteins (VSP1_ARATH and VSP2_ARATH) and four proteins belonging to the S-adenosyl-l-methionine cycle (METE_ARATH, SAHH1_ARATH, METK4_ARATH and METK1/3_ARATH) with associated adenosine kinase (ADK1_ARATH), were amongst the proteins identified in these single-S-cell samples. Comparison of the functional groups of proteins identified in S-cells with epidermal/cortical cells and whole tissue provided a unique insight into the metabolism of S-cells. We conclude that S-cells are metabolically active and contain the machinery for de novo biosynthesis of methionine, a precursor for the most abundant glucosinolate glucoraphanine in these cells. Moreover, since abundant TGG2 and TGG1 peptides were consistently found in single-S-cell samples, previously shown to have high amounts of glucosinolates, we suggest that both myrosinases and glucosinolates can be localised in the same cells, but in separate subcellular compartments. The complex membrane structure of S-cells was reflected by the presence of a number of proteins involved in membrane maintenance and cellular organisation.

Calpain-10 interacts with plasma saturated fatty acid concentrations to influence insulin resistance in individuals with the metabolic syndrome

Background: Calpain-10 protein (intracellular Ca2+-dependent cysteine protease) may play a role in glucose metabolism, pancreatic β cell function, and regulation of thermogenesis. Several CAPN10 polymorphic sites have been studied for their potential use as risk markers for type 2 diabetes and the metabolic syndrome (MetS). Fatty acids are key metabolic regulators that may interact with genetic factors and influence glucose metabolism. Objective: The objective was to examine whether the genetic variability at the CAPN10 gene locus is associated with the degree of insulin resistance and plasma fatty acid concentrations in subjects with MetS. Design: The insulin sensitivity index, glucose effectiveness, insulin resistance [homeostasis model assessment of insulin resistance (HOMA-IR)], insulin secretion (disposition index, acute insulin response, and HOMA of β cell function), plasma fatty acid composition, and 5 CAPN10 single nucleotide polymorphisms (SNPs) were determined in a cross-sectional analysis of 452 subjects with MetS participating in the LIPGENE dietary intervention cohort. Results: The rs2953171 SNP interacted with plasma total saturated fatty acid (SFA) concentrations, which were significantly associated with insulin sensitivity (P < 0.031 for fasting insulin, P < 0.028 for HOMA-IR, and P < 0.012 for glucose effectiveness). The G/G genotype was associated with lower fasting insulin concentrations, lower HOMA-IR, and higher glucose effectiveness in subjects with low SFA concentrations (below the median) than in subjects with the minor A allele (G/A and A/A). In contrast, subjects with the G/G allele with the highest SFA concentrations (above the median) had higher fasting insulin and HOMA-IR values and lower glucose effectiveness than did subjects with the A allele. Conclusion: The rs2953171 polymorphism at the CAPN10 gene locus may influence insulin sensitivity by interacting with the plasma fatty acid composition in subjects with MetS. This trial was registered at clinicaltrials.gov as NCT00429195.

Glucokinase Regulatory Protein genetic variant interacts with omega-3 PUFA to influence insulin resistance and inflammation in metabolic syndrome

Glucokinase Regulatory Protein (GCKR) plays a central role regulating both hepatic triglyceride and glucose metabolism. Fatty acids are key metabolic regulators, which interact with genetic factors and influence glucose metabolism and other metabolic traits. Omega-3 polyunsaturated fatty acids (n-3 PUFA) have been of considerable interest, due to their potential to reduce metabolic syndrome (MetS) risk. Objective To examine whether genetic variability at the GCKR gene locus was associated with the degree of insulin resistance, plasma concentrations of C-reactive protein (CRP) and n-3 PUFA in MetS subjects. Design Homeostasis model assessment of insulin resistance (HOMA-IR), HOMA-B, plasma concentrations of C-peptide, CRP, fatty acid composition and the GCKR rs1260326-P446L polymorphism, were determined in a cross-sectional analysis of 379 subjects with MetS participating in the LIPGENE dietary cohort. Results Among subjects with n-3 PUFA levels below the population median, carriers of the common C/C genotype had higher plasma concentrations of fasting insulin (P = 0.019), C-peptide (P = 0.004), HOMA-IR (P = 0.008) and CRP (P = 0.032) as compared with subjects carrying the minor T-allele (Leu446). In contrast, homozygous C/C carriers with n-3 PUFA levels above the median showed lower plasma concentrations of fasting insulin, peptide C, HOMA-IR and CRP, as compared with individuals with the T-allele. Conclusions We have demonstrated a significant interaction between the GCKR rs1260326-P446L polymorphism and plasma n-3 PUFA levels modulating insulin resistance and inflammatory markers in MetS subjects. Further studies are needed to confirm this gene-diet interaction in the general population and whether targeted dietary recommendations can prevent MetS in genetically susceptible individuals.

A sequential two meal challenge reveals abnormalities in postprandial TAG but not glucose in men with increasing numbers of metabolic syndrome components

Objective To examine the impact of increasing numbers of metabolic syndrome (MetS) components on postprandial lipaemia. Methods Healthy men (n = 112) underwent a sequential meal postprandial investigation, in which blood samples were taken at regular intervals after a test breakfast (0 min) and lunch (330 min). Lipids and glucose were measured in the fasting sample, with triacylglycerol (TAG), non-esterified fatty acids and glucose analysed in the postprandial samples. Results Subjects were grouped according to the number of MetS components regardless of the combinations of components (0/1, 2, 3 and 4/5). As expected, there was a trend for an increase in body mass index, blood pressure, fasting TAG, glucose and insulin, and a decrease in fasting high-density lipoprotein cholesterol with increasing numbers of MetS components (P≤0.0004). A similar trend was observed for the summary measures of the postprandial TAG and glucose responses. For TAG, the area under the curve (AUC) and maximum concentration (maxC) were significantly greater in men with ≥ 3 than < 3 components (P < 0.001), whereas incremental AUC was greater in those with 3 than 0/1 and 2, and 4/5 compared with 2 components (P < 0.04). For glucose, maxC after the test breakfast (0-330 min) and total AUC (0-480 min) were higher in men with ≥ 3 than < 3 components (P≤0.001). Conclusions Our data analysis has revealed a linear trend between increasing numbers of MetS components and magnitude (AUC) of the postprandial TAG and glucose responses. Furthermore, the two meal challenge discriminated a worsening of postprandial lipaemic control in subjects with ≥ 3 MetS components.

A metabolic system-wide characterisation of the pig: a model for human physiology

The pig is a single-stomached omnivorous mammal and is an important model of human disease and nutrition. As such, it is necessary to establish a metabolic framework from which pathology-based variation can be compared. Here, a combination of one and two-dimensional (1)H and (13)C nuclear magnetic resonance spectroscopy (NMR) and high-resolution magic angle spinning (HR-MAS) NMR was used to provide a systems overview of porcine metabolism via characterisation of the urine, serum, liver and kidney metabolomes. The metabolites observed in each of these biological compartments were found to be qualitatively comparable to the metabolic signature of the same biological matrices in humans and rodents. The data were modelled using a combination of principal components analysis and Venn diagram mapping. Urine represented the most metabolically distinct biological compartment studied, with a relatively greater number of NMR detectable metabolites present, many of which are implicated in gut-microbial co-metabolic processes. The major inter-species differences observed were in the phase II conjugation of extra-genomic metabolites; the pig was observed to conjugate p-cresol, a gut microbial metabolite of tyrosine, with glucuronide rather than sulfate as seen in man. These observations are important to note when considering the translatability of experimental data derived from porcine models.

The role of atmosphere feedbacks during ENSO in the CMIP3 models. Part II: using AMIP runs to understand the heat flux feedback mechanisms

Several studies using ocean–atmosphere general circulation models (GCMs) suggest that the atmospheric component plays a dominant role in the modelled El Niño-Southern Oscillation (ENSO). To help elucidate these findings, the two main atmosphere feedbacks relevant to ENSO, the Bjerknes positive feedback (μ) and the heat flux negative feedback (α), are here analysed in nine AMIP runs of the CMIP3 multimodel dataset. We find that these models generally have improved feedbacks compared to the coupled runs which were analysed in part I of this study. The Bjerknes feedback, μ, is increased in most AMIP runs compared to the coupled run counterparts, and exhibits both positive and negative biases with respect to ERA40. As in the coupled runs, the shortwave and latent heat flux feedbacks are the two dominant components of α in the AMIP runs. We investigate the mechanisms behind these two important feedbacks, in particular focusing on the strong 1997–1998 El Niño. Biases in the shortwave flux feedback, α SW, are the main source of model uncertainty in α. Most models do not successfully represent the negative αSW in the East Pacific, primarily due to an overly strong low-cloud positive feedback in the far eastern Pacific. Biases in the cloud response to dynamical changes dominate the modelled α SW biases, though errors in the large-scale circulation response to sea surface temperature (SST) forcing also play a role. Analysis of the cloud radiative forcing in the East Pacific reveals model biases in low cloud amount and optical thickness which may affect α SW. We further show that the negative latent heat flux feedback, α LH, exhibits less diversity than α SW and is primarily driven by variations in the near-surface specific humidity difference. However, biases in both the near-surface wind speed and humidity response to SST forcing can explain the inter-model αLH differences.

Spatio-temporal surface soil heat flux estimates from satellite data: results for the AMMA experiment at the Fakara (Niger) supersite

This paper describes a method that employs Earth Observation (EO) data to calculate spatiotemporal estimates of soil heat flux, G, using a physically-based method (the Analytical Method). The method involves a harmonic analysis of land surface temperature (LST) data. It also requires an estimate of near-surface soil thermal inertia; this property depends on soil textural composition and varies as a function of soil moisture content. The EO data needed to drive the model equations, and the ground-based data required to provide verification of the method, were obtained over the Fakara domain within the African Monsoon Multidisciplinary Analysis (AMMA) program. LST estimates (3 km × 3 km, one image 15 min−1) were derived from MSG-SEVIRI data. Soil moisture estimates were obtained from ENVISAT-ASAR data, while estimates of leaf area index, LAI, (to calculate the effect of the canopy on G, largely due to radiation extinction) were obtained from SPOT-HRV images. The variation of these variables over the Fakara domain, and implications for values of G derived from them, were discussed. Results showed that this method provides reliable large-scale spatiotemporal estimates of G. Variations in G could largely be explained by the variability in the model input variables. Furthermore, it was shown that this method is relatively insensitive to model parameters related to the vegetation or soil texture. However, the strong sensitivity of thermal inertia to soil moisture content at low values of relative saturation (<0.2) means that in arid or semi-arid climates accurate estimates of surface soil moisture content are of utmost importance, if reliable estimates of G are to be obtained. This method has the potential to improve large-scale evaporation estimates, to aid land surface model prediction and to advance research that aims to explain failure in energy balance closure of meteorological field studies.

Implications of non-cylindrical flux ropes for magnetic cloud reconstruction techniques and the interpretation of double flux rope events

Magnetic clouds (MCs) are a subset of interplanetary coronal mass ejections (ICMEs) which exhibit signatures consistent with a magnetic flux rope structure. Techniques for reconstructing flux rope orientation from single-point in situ observations typically assume the flux rope is locally cylindrical, e.g., minimum variance analysis (MVA) and force-free flux rope (FFFR) fitting. In this study, we outline a non-cylindrical magnetic flux rope model, in which the flux rope radius and axial curvature can both vary along the length of the axis. This model is not necessarily intended to represent the global structure of MCs, but it can be used to quantify the error in MC reconstruction resulting from the cylindrical approximation. When the local flux rope axis is approximately perpendicular to the heliocentric radial direction, which is also the effective spacecraft trajectory through a magnetic cloud, the error in using cylindrical reconstruction methods is relatively small (≈ 10∘). However, as the local axis orientation becomes increasingly aligned with the radial direction, the spacecraft trajectory may pass close to the axis at two separate locations. This results in a magnetic field time series which deviates significantly from encounters with a force-free flux rope, and consequently the error in the axis orientation derived from cylindrical reconstructions can be as much as 90∘. Such two-axis encounters can result in an apparent ‘double flux rope’ signature in the magnetic field time series, sometimes observed in spacecraft data. Analysing each axis encounter independently produces reasonably accurate axis orientations with MVA, but larger errors with FFFR fitting.

The gut microbiota elicits a profound metabolic reorientation in the mouse jejunal mucosa during conventionalisation

Objective: Proper interactions between the intestinal mucosa, gut microbiota and nutrient flow are required to establish homoeostasis of the host. Since the proximal part of the small intestine is the first region where these interactions occur, and since most of the nutrient absorption occurs in the jejunum, it is important to understand the dynamics of metabolic responses of the mucosa in this intestinal region.Design: Germ-free mice aged 8-10 weeks were conventionalised with faecal microbiota, and responses of the jejunal mucosa to bacterial colonisation were followed over a 30-day time course. Combined transcriptome, histology, (1)H NMR metabonomics and microbiota phylogenetic profiling analyses were used.Results: The jejunal mucosa showed a two-phase response to the colonising microbiota. The acute-phase response, which had already started 1 day after conventionalisation, involved repression of the cell cycle and parts of the basal metabolism. The secondary-phase response, which was consolidated during conventionalisation (days 4-30), was characterised by a metabolic shift from an oxidative energy supply to anabolic metabolism, as inferred from the tissue transcriptome and metabonome changes. Detailed transcriptome analysis identified tissue transcriptional signatures for the dynamic control of the metabolic reorientation in the jejunum. The molecular components identified in the response signatures have known roles in human metabolic disorders, including insulin sensitivity and type 2 diabetes mellitus.Conclusion: This study elucidates the dynamic jejunal response to the microbiota and supports a prominent role for the jejunum in metabolic control, including glucose and energy homoeostasis. The molecular signatures of this process may help to find risk markers in the declining insulin sensitivity seen in human type 2 diabetes mellitus, for instance.

The role of atmosphere feedbacks during ENSO in the CMIP3 models. Part III: the shortwave flux feedback

Previous studies using coupled general circulation models (GCMs) suggest that the atmosphere model plays a dominant role in the modeled El Nin ̃ o–Southern Oscillation (ENSO), and that intermodel differences in the thermodynamical damping of sea surface temperatures (SSTs) are a dominant contributor to the ENSO amplitude diversity. This study presents a detailed analysis of the shortwave flux feedback (aSW) in 12 Coupled Model Intercomparison Project phase 3 (CMIP3) simulations, motivated by findings that aSW is the primary contributor to model thermodynamical damping errors. A ‘‘feedback decomposition method,’’ developed to elucidate the aSW biases, shows that all models un- derestimate the dynamical atmospheric response to SSTs in the eastern equatorial Pacific, leading to un- derestimated aSW values. Biases in the cloud response to dynamics and the shortwave interception by clouds also contribute to errors in aSW. Changes in the aSW feedback between the coupled and corresponding atmosphere-only simulations are related to changes in the mean dynamics. A large nonlinearity is found in the observed and modeled SW flux feedback, hidden when linearly cal- culating aSW. In the observations, two physical mechanisms are proposed to explain this nonlinearity: 1) a weaker subsidence response to cold SST anomalies than the ascent response to warm SST anomalies and 2) a nonlinear high-level cloud cover response to SST. The shortwave flux feedback nonlinearity tends to be underestimated by the models, linked to an underestimated nonlinearity in the dynamical response to SST. The process-based methodology presented in this study may help to correct model ENSO atmospheric biases, ultimately leading to an improved simulation of ENSO in GCMs.

Landscape, regional and global estimates of nitrogen flux from land to sea: errors and uncertainties

Regional to global scale modelling of N flux from land to ocean has progressed to date through the development of simple empirical models representing bulk N flux rates from large watersheds, regions, or continents on the basis of a limited selection of model parameters. Watershed scale N flux modelling has developed a range of physically-based approaches ranging from models where N flux rates are predicted through a physical representation of the processes involved, through to catchment scale models which provide a simplified representation of true systems behaviour. Generally, these watershed scale models describe within their structure the dominant process controls on N flux at the catchment or watershed scale, and take into account variations in the extent to which these processes control N flux rates as a function of landscape sensitivity to N cycling and export. This paper addresses the nature of the errors and uncertainties inherent in existing regional to global scale models, and the nature of error propagation associated with upscaling from small catchment to regional scale through a suite of spatial aggregation and conceptual lumping experiments conducted on a validated watershed scale model, the export coefficient model. Results from the analysis support the findings of other researchers developing macroscale models in allied research fields. Conclusions from the study confirm that reliable and accurate regional scale N flux modelling needs to take account of the heterogeneity of landscapes and the impact that this has on N cycling processes within homogenous landscape units.

Ethnic differences in beta-cell function, dietary intake and expression of the metabolic syndrome among UK adults of south Asian, black African-Caribbean and white-European origin at high risk of metabolic syndrome

A cross-sectional analysis of ethnic differences in dietary intake, insulin sensitivity and beta-cell function, using the intravenous glucose tolerance test (IVGTT), was conducted on 497 healthy adult participants of the ‘Reading, Imperial, Surrey, Cambridge, and Kings’ (RISCK) study. Insulin sensitivity (Si) was significantly lower in African-Caribbean (AC) and South Asian (SA) participants [IVGTT-Si; AC: 2.13 vs SA: 2.25 vs white-European (WE): 2.84 (×10−4 mL µU min)2, p < 0.001]. AC participants had a higher prevalence of anti-hypertensive therapy (AC: 19.7% vs SA: 7.5%), the most cardioprotective lipid profile [total:high-density lipoprotein (HDL); AC: 3.52 vs SA: 4.08 vs WE: 3.83, p = 0.03] and more pronounced hyperinsulinaemia [IVGTT–acute insulin response (AIR)] [AC: 575 vs SA: 428 vs WE: 344 mL/µU/min)2, p = 0.002], specifically in female participants. Intake of saturated fat and carbohydrate was lower and higher in AC (10.9% and 50.4%) and SA (11.1% and 52.3%), respectively, compared to WE (13.6% and 43.8%, p < 0.001). Insulin resistance in ACs is characterised by ‘normal’ lipid profiles but high rates of hypertension and pronounced hyperinsulinaemia.

Pharmacometabonomic characterization of xenobiotic and endogenous metabolic phenotypes that account for inter-individual variation in isoniazid-induced toxicological response

An NMR-based pharmacometabonomic approach was applied to investigate inter-animal variation in response to isoniazid (INH; 200 and 400 mg/kg) in male Sprague-Dawley rats, alongside complementary clinical chemistry and histopathological analysis. Marked inter-animal variability in central nervous system (CNS) toxicity was identified following administration of a high dose of INH, which enabled characterization of CNS responders and CNS non-responders. High-resolution post-dose urinary (1)H NMR spectra were modeled both by their xenobiotic and endogenous metabolic information sets, enabling simultaneous identification of the differential metabolic fate of INH and its associated endogenous metabolic consequences in CNS responders and CNS non-responders. A characteristic xenobiotic metabolic profile was observed for CNS responders, which revealed higher urinary levels of pyruvate isonicotinylhydrazone and β-glucosyl isonicotinylhydrazide and lower levels of acetylisoniazid compared to CNS non-responders. This suggested that the capacity for acetylation of INH was lower in CNS responders, leading to increased metabolism via conjugation with pyruvate and glucose. In addition, the endogenous metabolic profile of CNS responders revealed higher urinary levels of lactate and glucose, in comparison to CNS non-responders. Pharmacometabonomic analysis of the pre-dose (1)H NMR urinary spectra identified a metabolic signature that correlated with the development of INH-induced adverse CNS effects and may represent a means of predicting adverse events and acetylation capacity when challenged with high dose INH. Given the widespread use of INH for the treatment of tuberculosis, this pharmacometabonomic screening approach may have translational potential for patient stratification to minimize adverse events.

Greater impairment of postprandial triacylglycerol than glucose response in metabolic syndrome subjects with fasting hyperglycaemia

Abstract Objective: Studies have started to question whether a specific component or combinations of metabolic syndrome (MetS) components may be more important in relation to cardiovascular disease risk. Our aim was to examine the impact of the presence of raised fasting glucose as a MetS component on postprandial lipaemia. Methods: Men classified with the MetS underwent a sequential test meal investigation, in which blood samples were taken at regular intervals after a test breakfast (t=0 min) and lunch (t=330 min). Lipids, glucose and insulin were measured in the fasting and postprandial samples. Results: MetS subjects with 3 or 4 components were subdivided into those without (n=34) and with (n=23) fasting hyperglycaemia (≥ 5.6 mmol/l), irrespective of the combination of components. Fasting lipids and insulin were similar in the two groups, with glucose significantly higher in the men with glucose as a MetS component (P<0.001). Following the test meals, there was a higher maximum concentration (maxC), area under the curve (AUC) and incremental AUC (P≤0.016) for the postprandial triacylglycerol (TAG) response in men with fasting hyperglycaemia. Greater glucose AUC (P<0.001) and insulin maxC (P=0.010) was also observed in these individuals after the test meals. Multivariate regression analysis revealed fasting glucose to be an important predictor of the postprandial TAG and glucose response. Conclusion: Our data analysis has revealed a greater impairment of postprandial TAG than glucose response in MetS subjects with raised fasting glucose. The worsening of postprandial lipaemic control may contribute to the greater CVD risk reported in individuals with MetS component combinations which include hyperglycaemia.

Anionic metabolic profiling of urine from antibiotic-treated rats by capillary electrophoresis–mass spectrometry

A recently developed capillary electrophoresis (CE)-negative-ionisation mass spectrometry (MS) method was used to profile anionic metabolites in a microbial-host co-metabolism study. Urine samples from rats receiving antibiotics (penicillin G and streptomycin sulfate) for 0, 4, or 8 days were analysed. A quality control sample was measured repeatedly to monitor the performance of the applied CE-MS method. After peak alignment, relative standard deviations (RSDs) for migration time of five representative compounds were below 0.4 %, whereas RSDs for peak area were 7.9–13.5 %. Using univariate and principal component analysis of obtained urinary metabolic profiles, groups of rats receiving different antibiotic treatment could be distinguished based on 17 discriminatory compounds, of which 15 were downregulated and 2 were upregulated upon treatment. Eleven compounds remained down- or upregulated after discontinuation of the antibiotics administration, whereas a recovery effect was observed for others. Based on accurate mass, nine compounds were putatively identified; these included the microbial-mammalian co-metabolites hippuric acid and indoxyl sulfate. Some discriminatory compounds were also observed by other analytical techniques, but CE-MS uniquely revealed ten metabolites modulated by antibiotic exposure, including aconitic acid and an oxocholic acid. This clearly demonstrates the added value of CE-MS for nontargeted profiling of small anionic metabolites in biological samples.