A multi-analytical platform approach to the metabonomic analysis of plasma from normal and Zucker (fa/fa) obese rats

Plasma obtained from 20 week old normal Wistar-derived and Zucker (fa/fa) rats was analysed using a number of different analytical methodologies to obtain global metabolite profiles as part of metabonomic investigations of animal models of diabetes. Samples were analysed without sample pre-treatment using 1H NMR spectroscopy, after acetonitrile solvent protein precipitation by ultra-performance liquid chromatography-MS (UPLC-MS) and after acetonitrile protein precipitation and derivatisation for capillary gas chromatography-MS (GC-MS). Subsequent data analysis using principal components analysis revealed that all three analytical platforms readily detected differences between the plasma metabolite profiles of the two strains of rat. There was only limited overlap between the metabolites detected by the different methodologies and the combination of all three methods of metabolite profiling therefore provided a much more comprehensive profile than would have been provided by their use individually.     

Genetic analysis of polyketide synthase and peptide synthetase genes in cyanobacteria as a mining tool for secondary metabolites

Molecular screening using degenerate PCR to determine the presence of secondary metabolite genes in cyanobacteria was performed. This revealed 18 NRPS and 19 PKS genes in the 21 new cyanobacterial strains examined, representing three families of cyanobacteria (Nostocales, Chroococales and Oscillatoriales). A BLAST analysis shows that these genes have similarities to known cyanobacterial natural products. Analysis of the NRPS adenylation domain indicates the presence of novel features previously ascribed to both proteobacteria and cyanobacteria. Furthermore, binding-pocket predictions reveal diversity in the amino acids used during the biosynthesis of compounds. A similar analysis of the PKS ketosynthase domain shows significant structural diversity and their presence in both mixed modules with NRPS domains and individually as part of a PKS module. We have been able to classify the NRPS genes on the basis of their binding-pockets. Further, we show how this data can be used to begin to link structure to function by an analysis of the compounds Scyptolin A and Hofmannolin from Scytonema sp. PCC 7110.     

Validation of Metabolic Alterations in Microscale Cell Culture Lysates Using Hydrophilic Interaction Liquid Chromatography (HILIC)-Tandem Mass Spectrometry-Based Metabolomics

By standard convention, in order to increase the efficacy of metabolite detection from cell culture lysates, metabolite extracts from a large quantity of cells are utilized for multiple reaction monitoring-based metabolomic studies. Metabolomics from a small number of cell extracts offers a potential economical alternative to increased cell numbers, in turn increasing the utility of cell culture-based metabolomics. However, the effect of reduced cell numbers on targeted metabolomic profiling is relatively unstudied. Considering the limited knowledge available of the feasibility and accuracy of microscale cell culture metabolomics, the present study analyzes differences in metabolomic profiles of different cell numbers of three pancreatic cancer cell lines. Specifically, it examines the effects of reduced cell numbers on metabolite profiles by obtaining extracts either directly from microscale culture plates or through serial dilution of increased numbers of cellular metabolite extracts. Our results indicate reduced cell numbers only modestly affect the number of metabolites detected (93% of metabolites detected in cell numbers as low as 10⁴ cells and 97% for 10⁵ cells), independent of the method used to obtain the cells. However, metabolite peak intensities were differentially affected by the reduced cell numbers, with some peak intensities inversely proportional to the cell numbers. To help eliminate such potential inverse relationships, peak intensities for increased cell numbers were excluded from the comparative analysis. Overall, metabolite profiles from microscale culture plates were observed to differ from the serial dilution samples, which may be attributable to the medium-to-cell-number ratios. Finally, findings identify perturbations in metabolomic profiling for cellular extracts from reduced cell numbers, which offer future applications in microscale metabolomic evaluations.     

Occurrence of d-α-Amino-n-butyric Acid in Legume Seedlings

Metabolomics analysis of three Saccharopolyspora spinosa strains (wild type strain WT, ultraviolet mutant strain WH124, and metabolic engineering strain LU104) with different spinosad producing levels was performed by liquid chromatograph coupled to mass spectrometry (LC-MS). The metabolite profiles were subjected to hierarchal clustering analysis (HCA) and principal component analysis (PCA). The results of HCA on a heat map revealed that the large numbers of primary metabolism detected were more abundant in WH124 and less abundant in LU104 during the early fermentation stage as compared to the WT strain. PCA separated the three strains clearly and suggested nine metabolites that contributed predominantly to the separation. These biomarkers were associated with central carbon metabolism (succinic acid, α-ketoglutarate, acetyl-CoA, and ATP), amino acid metabolism (glutamate, glutamine, and valine), and secondary metabolism (pseudoaglycone), etc. These findings provide insight into the metabolomic characteristics of the two high-yield strains and for further regulation of spinosad production.     

A comparison of direct infusion MS and GC-MS for metabolic footprinting of yeast mutants

Recent technical advances in mass spectrometry (MS) have propelled this technology to the forefront of methods employed in metabolome analysis. Here, we compare two distinct analytical approaches based on MS for their potential in revealing specific metabolic footprints of yeast single-deletion mutants. Filtered fermentation broth samples were analyzed by GC-MS and direct infusion ESI-MS. The potential of both methods in producing specific and, therefore, discriminant metabolite profiles was evaluated using samples from several yeast deletion mutants grown in batch-culture conditions with glucose as the carbon source. The mutants evaluated were cat8, gln3, ino2, opi1, and nil1, all with deletion of genes involved in nutrient sensing and regulation. From the analysis, we found that both methods can be used to classify mutants, but the classification depends on which metabolites are measured. Thus, the GC-MS method is good for classification of mutants with altered nitrogen regulation as it primarily measures amino acids, whereas this method cannot classify mutants involved in regulation of phospholipids metabolism as well as the direct infusion MS (DI-MS) method. From the analysis, we find that it is possible to discriminate the mutants in both the exponential and stationary growth phase, but the data from the exponential growth phase provide more physiological relevant information. Based on the data, we identified metabolites that are primarily involved in discrimination of the different mutants, and hereby providing a link between high-throughput metabolome analysis, strain classification, and physiology.     

Towards high-throughput metabolomics using ultrahigh-field Fourier transform ion cyclotron resonance mass spectrometry

With unmatched mass resolution, mass accuracy, and exceptional detection sensitivity, Fourier Transform Ion Cyclotron Resonance Mass Spectrometry (FTICR-MS) has the potential to be a powerful new technique for high-throughput metabolomic analysis. In this study, we examine the properties of an ultrahigh-field 12-Tesla (12T) FTICR-MS for the identification and absolute quantitation of human plasma metabolites, and for the untargeted metabolic fingerprinting of inbred-strain mouse serum by direct infusion (DI). Using internal mass calibration (mass error ≤1 ppm), we determined the rational elemental compositions (incorporating unlimited C, H, N and O, and a maximum of two S, three P, two Na, and one K per formula) of approximately 250 out of 570 metabolite features detected in a 3-min infusion analysis of aqueous extract of human plasma, and were able to identify more than 100 metabolites. Using isotopically-labeled internal standards, we were able to obtain excellent calibration curves for the absolute quantitation of choline with sub-pmol sensitivity, using 500 times less sample than previous LC/MS analyses. Under optimized serum dilution conditions, chemical compounds spiked into mouse serum as metabolite mimics showed a linear response over a 600-fold concentration range. DI/FTICR-MS analysis of serum from 26 mice from 2 inbred strains, with and without acute trichloroethylene (TCE) treatment, gave a relative standard deviation (RSD) of 4.5%. Finally, we extended this method to the metabolomic fingerprinting of serum samples from 49 mice from 5 inbred strains involved in an acute alcohol toxicity study, using both positive and negative electrospray ionization (ESI). Using these samples, we demonstrated the utility of this method for high-throughput metabolomics, with more than 400 metabolites profiled in only 24 h. Our experiments demonstrate that DI/FTICR-MS is well-suited for high-throughput metabolomic analysis. Electronic supplementary material The online version of this article (doi:) contains supplementary material, which is available to authorized users.     

High vertical and low horizontal diversity of Prochlorococcus ecotypes in the Mediterranean Sea in summer

Natural populations of the marine cyanobacterium Prochlorococcus exist as two main ecotypes, inhabiting different layers of the ocean's photic zone. These so-called high light- (HL-) and low light (LL-) adapted ecotypes are both physiologically and genetically distinct. HL strains can be separated into two major clades (HLI and HLII), whereas LL strains are more diverse. Here, we used several molecular techniques to study the genetic diversity of natural Prochlorococcus populations during the Prosope cruise in the Mediterranean Sea in the summer of 1999. Using a dot blot hybridization technique, we found that HLI was the dominant HL group and was confined to the upper mixed layer. In contrast, LL ecotypes were only found below the thermocline. Secondly, a restriction fragment length polymorphism analysis of PCR-amplified pcb genes (encoding the major light-harvesting proteins of Prochlorococcus) suggested that there were at least four genetically different ecotypes, occupying distinct but overlapping light niches in the photic zone. At comparable depths, similar banding patterns were observed throughout the sampled area, suggesting a horizontal homogenization of ecotypes. Nevertheless, environmental pcb gene sequences retrieved from different depths at two stations proved all different at the nucleotide level, suggesting a large genetic microdiversity within those ecotypes.     

Physiological and environmental parameters associated with mass spectrometry-based salivary metabolomic profiles

Mass spectrometry (MS)-based metabolomic methods enable simultaneous profiling of hundreds of salivary metabolites, and may be useful to diagnose a wide range of diseases using saliva. However, few studies have evaluated the effects of physiological or environmental factors on salivary metabolomic profiles. Therefore, we used capillary electrophoresis-MS to analyze saliva metabolite profiles in 155 subjects with reasonable oral hygiene, and examined the effects of physiological and environmental factors on the metabolite profiles. Overall, 257 metabolites were identified and quantified. The global profiles and individual metabolites were evaluated by principle component analysis and univariate tests, respectively. Collection method, collection time, sex, body mass index, and smoking affected the global metabolite profiles. However, age also might contribute to the bias in sex and collection time. The profiles were relatively unaffected by other parameters, such as alcohol consumption and smoking, tooth brushing, or the use of medications or nutritional supplements. Temporomandibular joint disorders had relatively greater effects on salivary metabolites than other dental abnormalities (e.g., stomatitis, tooth alignment, and dental caries). These findings provide further insight into the diversity and stability of salivary metabolomic profiles, as well as the generalizability of disease-specific biomarkers.     

Rice-<Emphasis Type="Italic">Arabidopsis</Emphasis> FOX line screening with FT-NIR-based fingerprinting for GC-TOF/MS-based metabolite profiling

The full-length cDNA over-expressing (FOX) gene hunting system is useful for genome-wide gain-of-function analysis. The screening of FOX lines requires a high-throughput metabolomic method that can detect a wide range of metabolites. Fourier transform-near-infrared (FT-NIR) spectroscopy in combination with the chemometric approach has been used to analyze metabolite fingerprints. Since FT-NIR spectroscopy can be used to analyze a solid sample without destructive extraction, this technique enables untargeted analysis and high-throughput screening focusing on the alteration of metabolite composition. We performed non-destructive FT-NIR-based fingerprinting to screen seed samples of 3000 rice-Arabidopsis FOX lines; the samples were obtained from transgenic Arabidopsis thaliana lines that overexpressed rice full-length cDNA. Subsequently, the candidate lines exhibiting alteration in their metabolite fingerprints were analyzed by gas chromatography-time-of-flight/mass spectrometry (GC-TOF/MS) in order to assess their metabolite profiles. Finally, multivariate regression using orthogonal projections to latent structures (O2PLS) was used to elucidate the predictive metabolites obtained in FT-NIR analysis by integration of the datasets obtained from FT-NIR and GC-TOF/MS analyses. FT-NIR-based fingerprinting is a technically efficient method in that it facilitates non-destructive analysis in a high-throughput manner. Furthermore, with the integrated analysis used here, we were able to discover unique metabotypes in rice-Arabidopsis FOX lines; thus, this approach is beneficial for investigating the function of rice genes related to metabolism.     

1H-NMR metabolite profiles of different strains of Plasmodium falciparum

Although efforts to understand the basis for inter-strain phenotypic variation in the most virulent malaria species, Plasmodium falciparum, have benefited from advances in genomic technologies, there have to date been few metabolomic studies of this parasite. Using ¹H-NMR spectroscopy, we have compared the metabolite profiles of red blood cells infected with different P. falciparum strains. These included both chloroquine-sensitive and chloroquine-resistant strains, as well as transfectant lines engineered to express different isoforms of the chloroquine-resistance-conferring pfcrt (P. falciparum chloroquine resistance transporter). Our analyses revealed strain-specific differences in a range of metabolites. There was marked variation in the levels of the membrane precursors choline and phosphocholine, with some strains having >30-fold higher choline levels and >5-fold higher phosphocholine levels than others. Chloroquine-resistant strains showed elevated levels of a number of amino acids relative to chloroquine-sensitive strains, including an approximately 2-fold increase in aspartate levels. The elevation in amino acid levels was attributable to mutations in pfcrt. Pfcrt-linked differences in amino acid abundance were confirmed using alternate extraction and detection (HPLC) methods. Mutations acquired to withstand chloroquine exposure therefore give rise to significant biochemical alterations in the parasite.     

Enzyme electrophoresis combined with serogrouping for improved differentiation of Clostridium difficile strains

Abstract We used enzyme electrophoresis to study a set of epidemiologically related and unrelated isolates of Clostridium difficile . The 53 strains belonged to the most frequent serogroups (A1, C, G, H and K). Nine electrophoretic profiles were defined on the basis of five enzymes, and two were characteristic of a single strain. Each serogroup was resolved into two or three different enzyme patterns. By combining the two methods we were able to resolve the strains into 12 types. There was an excellent correlation between enzyme electrophoresis and serogrouping data. This method may be of use in investigating nosocomial transmission.     

PAXgene fixation enables comprehensive metabolomic and proteomic analyses of tissue specimens by MALDI MSI

An alcohol-based non-crosslinking tissue fixative, PAXgene Tissue System, has been proposed as alternative fixation method to formalin, providing superior and morphological preservation. To date, metabolites have not been assessed in PAXgene-fixed tissues. The study focuses on a comparison between PAXgene and standard formalin fixation for metabolomic analysis by MALDI mass spectrometry imaging. Therefore, fifty-six samples from seven mice organs were fixed with PAXgene (PFPE) or formalin (FFPE), embedded in paraffin, and processed to a tissue microarray. PAXgene was able to spatially preserve metabolites in organs achieving an overlap of common metabolites ranging from 34 to 78% with FFPE. Highly similar signal intensities and visualization of molecules demonstrated negligible differences for metabolite imaging on PFPE compared to FFPE tissues. In addition, we performed proteomic analysis of intact proteins and peptides derived from enzymatic digestion. An overlap of 33 to 58% was found between FFPE and PFPE tissue samples in peptide analysis with a higher number of PFPE-specific peaks. Analysis of intact proteins achieved an overlap in the range of 0 to 28% owing to the poor detectability of cross-linked proteins in formalin-fixed tissues. Furthermore, metabolite and peptide profiles obtained from PFPE tissues were able to correctly classify organs independent of the fixation method, whereas a distinction of organs by protein profiles was only achieved by PAXgene fixation. Finally, we applied MALDI MSI to human biopsies by sequentially analyzing metabolites and peptides within the same tissue section. Concerning prospective studies, PAXgene can be used as an alternative fixative for multi-omic tissue analysis.     

Metabolomic Profiling of 13 Diatom Cultures and Their Adaptation to Nitrate-Limited Growth Conditions

Diatoms are very efficient in their use of available nutrients. Changes in nutrient availability influence the metabolism and the composition of the cell constituents. Since diatoms are valuable candidates to search for oil producing algae, measurements of diatom-produced compounds can be very useful for biotechnology. In order to explore the diversity of lipophilic compounds produced by diatoms, we describe the results from an analysis of 13 diatom strains. With the help of a lipidomics platform, which combines an UPLC separation with a high resolution/high mass accuracy mass spectrometer, we were able to measure and annotate 142 lipid species. Out of these, 32 were present in all 13 cultures. The annotated lipid features belong to six classes of glycerolipids. The data obtained from the measurements were used to create lipidomic profiles. The metabolomic overview of analysed cultures is amended by the measurement of 96 polar compounds. To further increase the lipid diversity and gain insight into metabolomic adaptation to nitrogen limitation, diatoms were cultured in media with high and low concentrations of nitrate. The growth in nitrogen-deplete or nitrogen-replete conditions affects metabolite accumulation but has no major influence on the species-specific metabolomic profile. Thus, the genetic component is stronger in determining metabolic patterns than nitrogen levels. Therefore, lipid profiling is powerful enough to be used as a molecular fingerprint for diatom cultures. Furthermore, an increase of triacylglycerol (TAG) accumulation was observed in low nitrogen samples, although this trend was not consistent across all 13 diatom strains. Overall, our results expand the current understanding of metabolomics diversity in diatoms and confirm their potential value for producing lipids for either bioenergy or as feed stock.     

A Metabolomic Approach to Animal Vitreous Humor Topographical Composition: A Pilot Study

The purpose of this study was to evaluate the feasibility of a ¹H-NMR-based metabolomic approach to explore the metabolomic signature of different topographical areas of vitreous humor (VH) in an animal model. Five ocular globes were enucleated from five goats and immediately frozen at −80°C. Once frozen, three of them were sectioned, and four samples corresponding to four different VH areas were collected: the cortical, core, and basal, which was further divided into a superior and an inferior fraction. An additional two samples were collected that were representative of the whole vitreous body. ¹H-NMR spectra were acquired for twenty-three goat vitreous samples with the aim of characterizing the metabolomic signature of this biofluid and identifying whether any site-specific patterns were present. Multivariate statistical analysis (MVA) of the spectral data were carried out, including Principal Component Analysis (PCA), Hierarchical Cluster Analysis (HCA), and Partial Least Squares Discriminant Analysis (PLS-DA). A unique metabolomic signature belonging to each area was observed. The cortical area was characterized by lactate, glutamine, choline, and its derivatives, N-acetyl groups, creatine, and glycerol; the core area was characterized by glucose, acetate, and scyllo-inositol; and the basal area was characterized by branched-chain amino acids (BCAA), betaine, alanine, ascorbate, lysine, and myo-inositol. We propose a speculative approach on the topographic role of these molecules that are mainly responsible for metabolic differences among the as-identified areas. ¹H-NMR-based metabolomic analysis has shown to be an important tool for investigating the VH. In particular, this approach was able to assess in the samples here analyzed the presence of different functional areas on the basis of a different metabolite distribution.     

Phenotypic heterogeneity of Pseudomonas corrugata strains from southern Italy

Fifty-five strains of Pseudomonas corrugata isolated in southern Italy were characterized phenotypically and compared with 23 strains of different origins. At least two main cultural types with rough or smooth colonies were observed. Strains with rough colonies produced a diffusible pigment in culture. On the basis of their nutritional profiles, Ps. corrugata strains formed a distinct phenon most closely related to fluorescent Pseudomonas spp. isolated from tomato pith necrosis-diseased plants. Three major groups of strains were differentiated within the Ps. corrugata phenon on the basis of utilization of 2-ketogluconate, meso-tartrate, hystamine, DL- glycerate and induction of a hypersensitive reaction on tobacco. Some Ps. corrugata strains belonging to group 1 and 3 which did not produce pigment in culture produced IAA in a colorimetric test. Variability in the serological reaction of the Italian strain was observed. None of the three antisera utilized reacted with all strains. Some strains isolated from diseased plants from the same greenhouse showed different nutritional profiles and reacted with different antisera. Fifteen lipopolysaccharide (LPS) patterns were observed. Strains were divided into two groups on the basis of their protein profiles. The heterogeneity which had already been observed in a world-wide study on Ps. corrugata was confirmed in strains from this restricted area.     

Soils of the Chinese Hubei province show a very high diversity of Sinorhizobium fredii strains

Biodiversity studies of native soybean-nodulating rhizobia in soils from the Chinese Hubei province (Honghu county; pH 8, alluvial soil) have been carried out. Inoculation of an American (Williams) and an Asiatic (Peking) soybean cultivar with eleven soil samples led to the isolation of 167 rhizobia strains. The ratio (%) of slow-/fast-growing isolates was different depending on the trap plant used. All isolates were able to nodulate both cultivars, although the N2-fixation efficiency (measured as plant-top dry weight) was different among them. A total of thirty-three isolates were selected for further characterisation on the basis of physiological parameters, PCR-RFLP of symbiotic genes and Low Molecular Weight RNA, lipopolysaccharide, protein and plasmid profiles. Low Molecular Weight RNA profiling indicates that all the isolates belong to species Sinorhizobium fredii. The dendrogram obtained with the physiological parameters has been useful to classify the isolates at strain level, although plasmid profiling was the most discriminating technique to detect differences among the analysed soybean-rhizobia isolates, showing there is not two isolates identical each other. Plasmid profile analyses also revealed that some of the investigated strains contain low molecular weight plasmids (7-8-kb). They are, to our knowledge, the smallest ever found in rhizobia and they could be the starting point for the construction of the first group of vectors based on a native rhizobia replicon.     

Headspace sorptive extraction and GC-TOFMS for the identification of volatile fungal metabolites

Volatiles from fungi cultivated in Petri dishes were collected by a simple headspace polydimethylsiloxane (PDMS) sorptive extraction technique (HSSE), thermally desorbed into a gas chromatographic capillary column and detected and identified by gas chromatography-time-of-flight mass spectrometry (GC-TOFMS). The method was used to compare metabolite profiles of seven species of fungi grown on two types of sterile agars - potato dextrose and Sabouraud dextrose. Three species from the genus Penicillium (P. italicum, P. camemberti, and P. roqueforti) and four outgroups, each from a different phylum (Saprolegnia sp.; Sordaria fimicola, wild-type; Coprinus cinereus; and Rhizopus stolonifer) were grown on the two types of agars and analyzed. Multivariate analysis (PCA) was used to determine whether separate classes of fungi can be distinguished from one another based on their metabolite profiles. PCA showed clear class separation between the three Penicillium samples and the outgroups. Slight differences were observed in metabolite profiles as a function of growth medium. HSSE/GC-TOFMS appears to be a relatively simple and accurate technique for classification of fungi based on their volatile metabolite profiles. The volatiles sampling technique reported here is non-destructive, so it can be applied with traditional methods for studying fungal growth and metabolism.