Flow-injection electrospray ionization mass spectrometry of crude cell extracts for high-throughput bacterial identification

Influence of Citrus sunki and Poncirus trifoliata Root Extracts on Metabolome of Phytophthora parasitica

Phytophthora parasitica is an oomycete pathogen that infects a broad range of crops of worldwide economic interest; among them are citrus species. In general, some Citrus and the rootstocks of related genera offer considerable resistance against P. parasitica; therefore, understanding the mechanisms involved in the virulence of this pathogen is crucial. In this work, P. parasitica secondary metabolite production was studied using matrix-assisted laser desorption/ionization mass spectrometry imaging (MALDI-MSI) and ultrahigh-performance liquid chromatography coupled with electrospray ionization quadrupole time-of-flight tandem mass spectrometry (UHPLC/ESI-Q-TOF-MS) combined with chemometric tools, and its metabolic profile was evaluated under the influence of Citrus sunki (a highly susceptible host) and Poncirus trifoliata (a resistant genotype) extracts. The root extracts of Citrus sunki had an influence on the growth and hyphae morphology, and the root extracts of P. trifoliata had an influence on the zoospore behavior. In parallel, the spatial distribution of several metabolites was revealed in P. parasitica colonies using MALDI-MSI, and the metabolite ion of m/z 246 was identified as the protonated molecule of Arg-Ala. The MALDI-MSI showed variations in the surface metabolite profile of P. parasitica under the influence of the P. trifoliata extract. The P. parasitica metabolome analysis using UHPLC-ESI-Q-TOF-MS resulted in the detection of Arg-Gln (m/z 303.1775), as well as L-arginine (m/z 175.1191) and other unidentified metabolites. Significant variations in this metabolome were detected under the influence of the plant extracts when evaluated using UHPLC-ESI-Q-TOF-MS. Both techniques proved to be complementary, offering valuable insights at the molecular level when used to assess the impact of the plant extracts on microbial physiology in vitro. The metabolites identified in this study may play significant roles in the interaction or virulence of P. parasitica, but their functional characterization remains to be analyzed. Overall, these data confirm our initial hypotheses, demonstrating that P. parasitica has the capabilities of (i) recognizing host signals and altering its reproductive programing and (ii) distinguishing between hosts with varying responses in terms of reproduction and the production of secondary metabolites.

Transient Complexity of E. coli Lipidome Is Explained by Fatty Acyl Synthesis and Cyclopropanation

In the case of many bacteria, such as Escherichia coli, the composition of lipid molecules, termed the lipidome, temporally adapts to different environmental conditions and thus modifies membrane properties to permit growth and survival. Details of the relationship between the environment and lipidome composition are lacking, particularly for growing cultures under either favourable or under stress conditions. Here, we highlight compositional lipidome changes by describing the dynamics of molecular species throughout culture-growth phases. We show a steady cyclopropanation of fatty acyl chains, which acts as a driver for lipid diversity. There is a bias for the cyclopropanation of shorter fatty acyl chains (FA 16:1) over longer ones (FA 18:1), which likely reflects a thermodynamic phenomenon. Additionally, we observe a nearly two-fold increase in saturated fatty acyl chains in response to the presence of ampicillin and chloramphenicol, with consequences for membrane fluidity and elasticity, and ultimately bacterial stress tolerance. Our study provides the detailed quantitative lipidome composition of three E. coli strains across culture-growth phases and at the level of the fatty acyl chains and provides a general reference for phospholipid composition changes in response to perturbations. Thus, lipidome diversity is largely transient and the consequence of lipid synthesis and cyclopropanation.

Discrimination of bacteria using whole organism fingerprinting: the utility of modern physicochemical techniques for bacterial typing

This review compares and contrasts MALDI-MS, FT-IR spectroscopy and Raman spectroscopy for whole organism fingerprinting and bacterial typing.

Advances in Chemical and Biological Methods to Identify Microorganisms-From Past to Present

Fast detection and identification of microorganisms is a challenging and significant feature from industry to medicine. Standard approaches are known to be very time-consuming and labor-intensive (e.g., culture media and biochemical tests). Conversely, screening techniques demand a quick and low-cost grouping of bacterial/fungal isolates and current analysis call for broad reports of microorganisms, involving the application of molecular techniques (e.g., 16S ribosomal RNA gene sequencing based on polymerase chain reaction). The goal of this review is to present the past and the present methods of detection and identification of microorganisms, and to discuss their advantages and their limitations.

Metabolomics in Plant Stress Physiology

Metabolomics is an essential technology for functional genomics and systems biology. It plays a key role in functional annotation of genes and understanding towards cellular and molecular, biotic and abiotic stress responses. Different analytical techniques are used to extend the coverage of a full metabolome. The commonly used techniques are NMR, CE-MS, LC-MS, and GC-MS. The choice of a suitable technique depends on the speed, sensitivity, and accuracy. This chapter provides insight into plant metabolomic techniques, databases used in the analysis, data mining and processing, compound identification, and limitations in metabolomics. It also describes the workflow of measuring metabolites in plants. Metabolomic studies in plant responses to stress are a key research topic in many laboratories worldwide. We summarize different approaches and provide a generic overview of stress responsive metabolite markers and processes compiled from a broad range of different studies. Graphical Abstract.

Progress of electrospray ionization and rapid evaporative ionization mass spectrometric techniques for the broad-range identification of microorganisms

Electrospray ionization and rapid evaporative ionization mass spectrometric techniques have attracted much attention in the identification of microorganisms, and in the diagnosis of bacterial infections from clinical samples.

High-throughput simultaneous quantitation of multi-analytes in tobacco by flow injection coupled to high-resolution mass spectrometry

The high-throughput screening by flow injection coupled to high-resolution mass spectrometry (HTS-FIA-HRMS) is a powerful technique that enables the identification of several types of samples in a short period of time, either with qualitative or quantitative purposes. Sensory attributes of tobacco are affected by its chemical composition, and it is very important to quantify multi-analytes in a high-throughput methodology. HTS-FIA-HRMS coupled to multivariate analysis was used to create calibration models for 27 analytes, or group of compounds, of tobacco sensory interest. The models were validated by different approaches, including permutation test to avoid overfitting, evaluation of the equipment repeatability by control samples, reproducibility comparison of results from two different equipment and analysts, and with a blind test analysis. All tests demonstrated a good response to the proposed method. No statistical difference between the errors of both equipment was observed, with less than 7% error from the control samples, and a blind test error between 5.96% and 20.10%. The partial least squares (O-PLS) regression models were applied to 815 samples, and a principal component analysis (PCA) was performed from the predicted concentration values, aiming at the non-supervised classification based on tobacco type. We expect that this proposed methodology shows not only the applicability in tobacco samples, but also demonstrates a guideline to an efficient performance of multi-analytes target analysis using the flow injection mass spectrometry with reliable and robust validation steps.

Current knowledge of metabolomic approach in infectious fish disease studies

The approaches of transcriptomic and proteomic have been widely used to study host-pathogen interactions in fish diseases, and this is comparable to the recently emerging application of metabolomic in elucidating disease-resistant mechanisms in fish that gives new insight into potential therapeutic strategies to improve fish health. Metabolomic is defined as the large-scale study of all metabolites within an organism and represents the frontline in the 'omics' approaches, providing direct information on the metabolic responses and perturbations in metabolic pathways. In this review, the current research in infectious fish diseases using metabolomic approach will be summarized. The metabolomic approach in economically important fish infected with viruses, bacteria and nematodes will also be discussed. The potential of the metabolomic approach for management of these infectious diseases as well as the challenges and the limitations of metabolomic in fish disease studies will be explored. Current review highlights the impacts of metabolomic studies in infectious fish diseases, which proposed the potential of new therapeutic strategies to enhance disease resistance in fish.

Gut Microbiota Profiling: Metabolomics Based Approach to Unravel Compounds Affecting Human Health

The gut microbiota is composed of a huge number of different bacteria, that produce a large amount of compounds playing a key role in microbe selection and in the construction of a metabolic signaling network. The microbial activities are affected by environmental stimuli leading to the generation of a wide number of compounds, that influence the host metabolome and human health. Indeed, metabolite profiles related to the gut microbiota can offer deep insights on the impact of lifestyle and dietary factors on chronic and acute diseases. Metagenomics, metaproteomics and metabolomics are some of the meta-omics approaches to study the modulation of the gut microbiota. Metabolomic research applied to biofluids allows to: define the metabolic profile; identify and quantify classes and compounds of interest; characterize small molecules produced by intestinal microbes; and define the biochemical pathways of metabolites. Mass spectrometry and nuclear magnetic resonance spectroscopy are the principal technologies applied to metabolomics in terms of coverage, sensitivity and quantification. Moreover, the use of biostatistics and mathematical approaches coupled with metabolomics play a key role in the extraction of biologically meaningful information from wide datasets. Metabolomic studies in gut microbiota-related research have increased, focusing on the generation of novel biomarkers, which could lead to the development of mechanistic hypotheses potentially applicable to the development of nutritional and personalized therapies.

Gut Microbiota Profiling: Metabolomics Based Approach to Unravel Compounds Affecting Human Health

The gut microbiota is composed of a huge number of different bacteria, that produce a large amount of compounds playing a key role in microbe selection and in the construction of a metabolic signaling network. The microbial activities are affected by environmental stimuli leading to the generation of a wide number of compounds, that influence the host metabolome and human health. Indeed, metabolite profiles related to the gut microbiota can offer deep insights on the impact of lifestyle and dietary factors on chronic and acute diseases. Metagenomics, metaproteomics and metabolomics are some of the meta-omics approaches to study the modulation of the gut microbiota. Metabolomic research applied to biofluids allows to: define the metabolic profile; identify and quantify classes and compounds of interest; characterize small molecules produced by intestinal microbes; and define the biochemical pathways of metabolites. Mass spectrometry and nuclear magnetic resonance spectroscopy are the principal technologies applied to metabolomics in terms of coverage, sensitivity and quantification. Moreover, the use of biostatistics and mathematical approaches coupled with metabolomics play a key role in the extraction of biologically meaningful information from wide datasets. Metabolomic studies in gut microbiota-related research have increased, focusing on the generation of novel biomarkers, which could lead to the development of mechanistic hypotheses potentially applicable to the development of nutritional and personalized therapies.

Gut Microbiota Profiling: Metabolomics Based Approach to Unravel Compounds Affecting Human Health

The gut microbiota is composed of a huge number of different bacteria, that produce a large amount of compounds playing a key role in microbe selection and in the construction of a metabolic signaling network. The microbial activities are affected by environmental stimuli leading to the generation of a wide number of compounds, that influence the host metabolome and human health. Indeed, metabolite profiles related to the gut microbiota can offer deep insights on the impact of lifestyle and dietary factors on chronic and acute diseases. Metagenomics, metaproteomics and metabolomics are some of the meta-omics approaches to study the modulation of the gut microbiota. Metabolomic research applied to biofluids allows to: define the metabolic profile; identify and quantify classes and compounds of interest; characterize small molecules produced by intestinal microbes; and define the biochemical pathways of metabolites. Mass spectrometry and nuclear magnetic resonance spectroscopy are the principal technologies applied to metabolomics in terms of coverage, sensitivity and quantification. Moreover, the use of biostatistics and mathematical approaches coupled with metabolomics play a key role in the extraction of biologically meaningful information from wide datasets. Metabolomic studies in gut microbiota-related research have increased, focusing on the generation of novel biomarkers, which could lead to the development of mechanistic hypotheses potentially applicable to the development of nutritional and personalized therapies.

Instrumental improvements and sample preparations that enable reproducible, reliable acquisition of mass spectra from whole bacterial cells

RATIONALE

Rapid sub-species characterization of pathogens is required for timely responses in outbreak situations. Pyrolysis mass spectrometry (PyMS) has the potential to be used for this purpose.

METHODS

However, in order to make PyMS practical for traceback applications, certain improvements related to spectrum reproducibility and data acquisition speed were required. The main objectives of this study were to facilitate fast detection (<30 min to analyze 6 samples, including preparation) and sub-species-level bacterial characterization based on pattern recognition of mass spectral fingerprints acquired from whole cells volatilized and ionized at atmospheric pressure. An AccuTOF DART mass spectrometer was re-engineered to permit ionization of low-volatility bacteria by means of Plasma Jet Ionization (PJI), in which an electric discharge, and, by extension, a plasma beam, impinges on sample cells.

RESULTS

Instrumental improvements and spectral acquisition methodology are described. Performance of the re-engineered system was assessed using a small challenge set comprised of assorted bacterial isolates differing in identity by varying amounts. In general, the spectral patterns obtained allowed differentiation of all samples tested, including those of the same genus and species but different serotypes.

CONCLUSIONS

Fluctuations of ±15% in bacterial cell concentrations did not substantially compromise replicate spectra reproducibility.

[Metabolic profiling of human blood]

Metabolomics is a novel "omics" branch of science intended for studying a comprehensive set of low molecular weight substances (metabolites) of various biological objects. Metabolite profiles represent a molecular phenotype of biological systems and reflect information encoded at the genome level and realized at the transcriptome and proteome levels. Analysis of human blood metabolic profile is universal and promising tool for clinical applications because it is a sensitive measure of both endogenous and exogenous (environmental) factors affected on the patient's organism. Technical implementation of metabolic profiling of blood and statistic analysis of metabolite profiles for effective diagnostics and risk assessments of diseases are discussed in this review.

Multiple metabolomics of uropathogenic E. coli reveal different information content in terms of metabolic potential compared to virulence factors

No single analytical method can cover the whole metabolome and the choice of which platform to use may inadvertently introduce chemical selectivity.

Postgenomics diagnostics: metabolomics approaches to human blood profiling

We live in exciting times with the prospects of postgenomics diagnostics. Metabolomics is a novel "omics" data-intensive science that is accelerating the development of postgenomics diagnostics, particularly with use of accessible peripheral tissue compartments. Metabolomics involves the study of a comprehensive set of low molecular weight substances (metabolites) present in biological systems. The metabolite profiles represent the molecular phenotype of biological systems and reflect the information encoded at the genomic level and implemented at the transcriptomic and proteomic levels. Analysis of the human blood metabolite profile is a universal and highly promising tool for clinical postgenomics applications because it reflects both the endogenous and exogenous (environmental) factors influencing an individual organism. This article presents a critical synthesis and original analysis of both the technical implementation of metabolic profiling of blood and statistical analysis of metabolite profiles for effective disease diagnostics and risk assessment in the present postgenomics era.

Evaluation of flow-injection tandem mass spectrometry for rapid and high-throughput quantitative determination of B vitamins in nutritional supplements

The use of flow-injection electrospray ionization tandem mass spectrometry for rapid and high-throughput mass spectral analysis of selected B vitamins, viz., B1, B2, B3, B5, and B6, in nutritional formulations was demonstrated. A simple and rapid (~5 min) in-tube sample preparation was performed. Automated flow injection introduced 1 μL of the extracts directly into the mass spectrometer ion source without chromatographic separation. Sample-to-sample analysis time was 60 s. Quantitative capabilities of the flow-injection analysis were tested using the method of standard additions and SRM 3280. The quantity determined for each B vitamin in SRM 3280 was within the statistical range provided for the respective certified values. This approach was also applied to two different commercial vitamin supplement tablets and proved to be successful in the quantification of the selected B vitamins, as evidenced by an agreement with the label values and the results obtained using isotope dilution liquid chromatography/mass spectrometry.

Advances in mass spectrometry for the identification of pathogens

Mass spectrometry (MS) has become an important technique to identify microbial biomarkers. The rapid and accurate MS identification of microorganisms without any extensive pretreatment of samples is now possible. This review summarizes MS methods that are currently utilized in microbial analyses. Affinity methods are effective to clean, enrich, and investigate microorganisms from complex matrices. Functionalized magnetic nanoparticles might concentrate traces of target microorganisms from sample solutions. Therefore, nanoparticle-based techniques have a favorable detection limit. MS coupled with various chromatographic techniques, such as liquid chromatography and capillary electrophoresis, reduces the complexity of microbial biomarkers and yields reliable results. The direct analysis of whole pathogenic microbial cells with matrix-assisted laser desorption/ionization MS without sample separation reveals specific biomarkers for taxonomy, and has the advantages of simplicity, rapidity, and high-throughput measurements. The MS detection of polymerase chain reaction (PCR)-amplified microbial nucleic acids provides an alternative to biomarker analysis. This review will conclude with some current applications of MS in the identification of pathogens.

Metabolic footprinting of the anaerobic bacterium Fusobacterium varium using 1H NMR spectroscopy

Metabolic footprinting of the anaerobic bacterium Fusobacterium varium demonstrated the accumulation of six carboxylic acids as metabolic end-products and revealed specific growth requirements and utilization capabilities towards amino acids. Guided by (1)H NMR determinations of residual amino acids in spent medium, a modified chemically defined minimal medium (CDMM*) was developed by minimizing the amino acid composition while satisfying nutritional requirements to support abundant growth of F. varium. Quantitative determinations of carboxylate salts and residual substrates were readily performed by (1)H NMR analysis of lyophilized residues from CDMM* cultures without interference from initial medium components. Only small concentrations of alanine, arginine, glycine, isoleucine, leucine, methionine, proline and valine were required to support growth of F. varium, whereas larger quantities of aspartate, asparagine, cysteine, glutamine, glutamate, histidine, lysine, serine and threonine were utilized, most likely as energy sources. Both bacterial growth and the distribution of carboxylate end-products depended on the composition of the chemically defined medium. In cultures provided with glucose as the primary energy source, the accumulation of butyrate and lactate correlated with growth, consistent with the regeneration of reduced coenzyme formed by the oxidative steps of glucose catabolism.

Systems level studies of mammalian metabolomes: the roles of mass spectrometry and nuclear magnetic resonance spectroscopy

The study of biological systems in a holistic manner (systems biology) is increasingly being viewed as a necessity to provide qualitative and quantitative descriptions of the emergent properties of the complete system. Systems biology performs studies focussed on the complex interactions of system components; emphasising the whole system rather than the individual parts. Many perturbations to mammalian systems (diet, disease, drugs) are multi-factorial and the study of small parts of the system is insufficient to understand the complete phenotypic changes induced. Metabolomics is one functional level tool being employed to investigate the complex interactions of metabolites with other metabolites (metabolism) but also the regulatory role metabolites provide through interaction with genes, transcripts and proteins (e.g. allosteric regulation). Technological developments are the driving force behind advances in scientific knowledge. Recent advances in the two analytical platforms of mass spectrometry (MS) and nuclear magnetic resonance (NMR) spectroscopy have driven forward the discipline of metabolomics. In this critical review, an introduction to metabolites, metabolomes, metabolomics and the role of MS and NMR spectroscopy will be provided. The applications of metabolomics in mammalian systems biology for the study of the health-disease continuum, drug efficacy and toxicity and dietary effects on mammalian health will be reviewed. The current limitations and future goals of metabolomics in systems biology will also be discussed (374 references).

Functional genomics via metabolic footprinting: monitoring metabolite secretion by Escherichia coli tryptophan metabolism mutants using FT-IR and direct injection electrospray mass spectrometry

We sought to test the hypothesis that mutant bacterial strains could be discriminated from each other on the basis of the metabolites they secrete into the medium (their ‘metabolic footprint’), using two methods of ‘global’ metabolite analysis (FT–IR and direct injection electrospray mass spectrometry). The biological system used was based on a published study of Escherichia coli tryptophan mutants that had been analysed and discriminated by Yanofsky and colleagues using transcriptome analysis. Wild-type strains supplemented with tryptophan or analogues could be discriminated from controls using FT–IR of 24 h broths, as could each of the mutant strains in both minimal and supplemented media. Direct injection electrospray mass spectrometry with unit mass resolution could also be used to discriminate the strains from each other, and had the advantage that the discrimination required the use of just two or three masses in each case. These were determined via a genetic algorithm. Both methods are rapid, reagentless, reproducible and cheap, and might beneficially be extended to the analysis of gene knockout libraries.

Identification of pathogens by mass spectrometry

BACKGROUND

Mass spectrometry (MS) is a suitable technology for microorganism identification and characterization.

CONTENT

This review summarizes the MS-based methods currently used for the analyses of pathogens. Direct analysis of whole pathogenic microbial cells using MS without sample fractionation reveals specific biomarkers for taxonomy and provides rapid and high-throughput capabilities. MS coupled with various chromatography- and affinity-based techniques simplifies the complexity of the signals of the microbial biomarkers and provides more accurate results. Affinity-based methods, including those employing nanotechnology, can be used to concentrate traces of target microorganisms from sample solutions and, thereby, improve detection limits. Approaches combining amplification of nucleic acid targets from pathogens with MS-based detection are alternatives to biomarker analyses. Many data analysis methods, including multivariate analysis and bioinformatics approaches, have been developed for microbial identification. The review concludes with some current clinical applications of MS in the identification and typing of infectious microorganisms, as well as some perspectives.

SUMMARY

Advances in instrumentation (separation and mass analysis), ionization techniques, and biological methodologies will all enhance the capabilities of MS for the analysis of pathogens.

Measurement of dietary exposure: a challenging problem which may be overcome thanks to metabolomics?

The diet is an important environmental exposure, and its measurement is an essential component of much health-related research. However, conventional tools for measuring dietary exposure have significant limitations being subject to an unknown degree of misreporting and dependent upon food composition tables to allow estimation of intakes of energy, nutrients and non-nutrient food constituents. In addition, such tools may be inappropriate for use with certain groups of people. As an alternative approach, the recent techniques of metabolite profiling or fingerprinting, which allows simultaneous monitoring of multiple and dynamic components of biological fluids, may provide metabolic signals indicative of food intake. Samples can be analysed through numerous analytical platforms, followed by multivariate data analysis. In humans, metabolomics has been applied successfully in pharmacology, toxicology and medical screening, but nutritional metabolomics is still in its infancy. Biomarkers of a small number of specific foods and nutrients have been developed successfully but less targeted and more high-throughput methods, that do not need prior knowledge of which signals might be discriminatory, and which may allow a more global characterisation of dietary intake, remain to be tested. A proof a principle project (the MEDE Study) is currently underway in our laboratories to test the hypothesis that high-throughput, non-targeted metabolite fingerprinting using flow injection electrospray mass spectrometry can be applied to human biofluids (blood and urine) to characterise dietary exposure in humans.

Preprocessing, classification modeling and feature selection using flow injection electrospray mass spectrometry metabolite fingerprint data

Metabolome analysis by flow injection electrospray mass spectrometry (FIE-MS) fingerprinting generates measurements relating to large numbers of m/z signals. Such data sets often exhibit high variance with a paucity of replicates, thus providing a challenge for data mining. We describe data preprocessing and modeling methods that have proved reliable in projects involving samples from a range of organisms. The protocols interact with software resources specifically for metabolomics provided in a Web-accessible data analysis package FIEmspro (http://users.aber.ac.uk/jhd) written in the R environment and requiring a moderate knowledge of R command-line usage. Specific emphasis is placed on describing the outcome of modeling experiments using FIE-MS data that require further preprocessing to improve quality. The salient features of both poor and robust (i.e., highly generalizable) multivariate models are outlined together with advice on validating classifiers and avoiding false discovery when seeking explanatory variables.

Metabolic fingerprinting as a diagnostic tool

Within the framework of systems biology, functional analyses at all 'omic levels have seen an intense level of activity during the first decade of the twenty-first century. These include genomics, transcriptomics, proteomics, metabolomics and lipidomics. It could be said that metabolomics offers some unique advantages over the other 'omics disciplines and one of the core approaches of metabolomics for disease diagnostics is metabolic fingerprinting. This review provides an overview of the main metabolic fingerprinting approaches used for disease diagnostics and includes: infrared and Raman spectroscopy, Nuclear magnetic resonance (NMR) spectroscopy, followed by an introduction to a wide range of novel mass spectrometry-based methods, which are currently under intense investigation and developmental activity in laboratories worldwide. It is hoped that this review will act as a springboard for researchers and clinicians across a wide range of disciplines in this exciting era of multidisciplinary and novel approaches to disease diagnostics.

Metabolomic technologies and their application to the study of plants and plant-host interactions

Metabolomics is perhaps the ultimate level of post-genomic analysis as it can reveal changes in metabolite fluxes that are controlled by only minor changes within gene expression measured using transcriptomics and/or by analysing the proteome that elucidates post-translational control over enzyme activity. Metabolic change is a major feature of plant genetic modification and plant interactions with pathogens, pests, and their environment. In the assessment of genetically modified plant tissues, metabolomics has been used extensively to explore by-products resulting from transgene expression and scenarios of substantial equivalence. Many studies have concentrated on the physiological development of plant tissues as well as on the stress responses involved in heat shock or treatment with stress-eliciting molecules such as methyl jasmonic acid, yeast elicitor or bacterial lipopolysaccharide. Plant-host interactions represent one of the most biochemically complex and challenging scenarios that are currently being assessed by metabolomic approaches. For example, the mixtures of pathogen-colonised and non-challenged plant cells represent an extremely heterogeneous and biochemically rich sample; there is also the further complication of identifying which metabolites are derived from the plant host and which are from the interacting pathogen. This review will present an overview of the analytical instrumentation currently applied to plant metabolomic analysis, literature within the field will be reviewed paying particular regard to studies based on plant-host interactions and finally the future prospects on the metabolomic analysis of plants and plant-host interactions will be discussed.

High-throughput, nontargeted metabolite fingerprinting using nominal mass flow injection electrospray mass spectrometry

Flow injection electrospray-mass spectrometry (FIE-MS) is finding utility as a first-pass metabolite fingerprinting tool in many research fields. We provide a protocol that has proved reliable in large-scale research projects involving diverse sample matrices originating from plants, microbes and mammalian biofluids. Using Brachypodium leaf material as an example matrix all steps are summarized from sample extraction to data quality assessment. Alternative procedures for dealing with other common matrices such as bloods and urine are included. With little sample pretreatment, no chromatography and instrument cycle times of <5 min it is feasible to analyze >1,000 samples per week. Analysis of a typical batch of 240 samples (including first-pass data analysis) can be accomplished within 48 h.

Desorption electrospray ionization mass spectrometry of intact bacteria

Desorption electrospray ionization (DESI) mass spectrometry (MS) was used to differentiate seven bacteria species on the basis of their measured DESI-mass spectral profile. Both gram-positive and gram-negative bacteria were tested and included Escherichia coli, Staphyloccocus aureus, Enterococcus sp., Bordetella bronchiseptica, Bacillus thuringiensis, Bacillus subtilis and Salmonella typhimurium. Distinct DESI-mass spectra, in the mass range of 50-500 u, were obtained from whole bacteria in either positive or negative ion modes in less than 2 mins analysis time. Positive ion DESI-mass spectral fingerprints were compared using principal components analysis (PCA) to investigate reproducibility for the intraday and the day-to-day measurements and the method selectivity to differentiate the bacteria studied. Detailed study of variances in the assay revealed that a large contribution to the DESI-mass spectral fingerprint variation was the growth media preparation procedure. Specifically, experiments conducted with the growth media prepared using the same batch yielded highly reproducible DESI-mass spectra, both in intraday and in day-to-day analyses (i.e. one batch of growth media used over a 3-day period versus a new batch every day over the same 3-day period). Conclusions are drawn from our findings in terms of strategies for rapid biodetection with DESI-MS.

Preliminary phenotypic characterization of newly isolated halophilic microorganisms by footprinting: a rapid metabolome analysis

The emerging need for rapid screening and identification methods for microbiological purposes necessitates the combined uses of high-tech instruments. In this work, electrospray ionization mass spectrometry was used to visualize the relation of ten newly isolated moderately halophilic microorganisms, to Halomonas salina DSMZ 5,928 and Halomonas halophila DSMZ 4,770. The method was based on the global analysis of the metabolites in culture media and is termed as metabolic footprinting. Since it was not possible to gain insight into the similarities solely based on the visual inspection of the chromatograms, principal component (PC) analysis was applied on the data. Three PCs alone were able to explain 99% of the information in the data set. The score plots revealed the relation of the new isolates to the two type strains whereas the loading plots gave important clues on the significant ions responsible for the observed clustering. Loading plots also indicated inversely correlated ions that give clues on differing metabolic pathways. The work described here offers a potentially useful way for preliminary rapid phenotypic characterization of new and closely related isolates and a method for screening of similar microorganisms for different and valuable secondary metabolites.

Discrimination of bacteria and bacteriophages by Raman spectroscopy and surface-enhanced Raman spectroscopy

Detection of pathogenic organisms in the environment presents several challenges due to the high cost and long times typically required for identification and quantification. Polymerase chain reaction (PCR) based methods are often hindered by the presence of polymerase inhibiting compounds and so direct methods of quantification that do not require enrichment or amplification are being sought. This work presents an analysis of pathogen detection using Raman spectroscopy to identify and quantify microorganisms without drying. Confocal Raman measurements of the bacterium Escherichia coli and of two bacteriophages, MS2 and PRD1, were analyzed for characteristic peaks and to estimate detection limits using traditional Raman and surface-enhanced Raman spectroscopy (SERS). MS2, PRD1, and E. coli produced differentiable Raman spectra with approximate detection limits for PRD1 and E. coli of 10(9) pfu/mL and 10(6) cells/mL, respectively. These high detection concentration limits are partly due to the small sampling volume of the confocal system but translate to quantification of as little as 100 bacteriophages to generate a reliable spectral signal. SERS increased signal intensity 10(3) fold and presented peaks that were visible using 2-second acquisitions; however, peak locations and intensities were variable, as typical with SERS. These results demonstrate that Raman spectroscopy and SERS have potential as a pathogen monitoring platform.

Identifying bacterial species using CE–MS and SEQUEST with an empirical scoring function

CE-MS/MS analysis of proteolytic digests of bacterial cell extracts was combined with SEQUEST searching and a new scoring system to identify bacteria species in bacterial mixtures. Searches of MS/MS spectra against protein databases enabled the identification of bacterial species by the matching of the proteins associated with the corresponding species. An empirical scoring function was obtained by evaluating the SEQUEST search results of 38 samples that contained single bacterial species. The scoring by the empirical function helped move up the positive identification results from their original positions in the ranking based on Xcorr values alone. Therefore, the identification of bacteria in the samples that contained bacterial mixtures was improved. Bacterial species in 20 bacterial mixtures, including one real sample, were correctly identified by database searches and the new scoring function.

Identification of microbial mixtures by capillary electrophoresis/selective tandem mass spectrometry

In this paper, we propose a new strategy for identifying specific bacteria in bacterial mixtures by using CE-selective MS/MS of peptide marker ions associated with the bacteria of interest. We searched the CE-MS/MS spectra acquired from the proteolytic digests of pure bacterial cell extracts against protein databases. The identified peptides that match the protein associated with the corresponding species were selected as marker ions for bacterial identification. Specific peptide marker ions were obtained for each of the following three pathogens: Pseudomonas aeruginasa, Staphylococcus aureus, and Staphylococcus epidermidis. To identify a bacterial species in a sample, we performed CE-MS/MS analysis of the selected marker ions in the proteolytic digest of the cell extract and then performed protein database searches. The selected peptides that we identified correctly from Xcorr values ranking at the top of the search results allowed us to identify the corresponding bacterial species present in the sample. We have applied this method successfully to the identification of various mixtures of the three pathogens. Even minor bacterial species present at a concentration of 1% can be identified with great confidence. This method for CE-MS/MS analysis of bacteria-specific marker peptides provides excellent selectivity and high accuracy when identifying bacterial species in complex systems. In addition, we have used this approach to identify P. aeruginasa in a saliva sample spiked with E.coli and P. aeruginasa.

Mass spectrometry-based metabolomics

This review presents an overview of the dynamically developing field of mass spectrometry-based metabolomics. Metabolomics aims at the comprehensive and quantitative analysis of wide arrays of metabolites in biological samples. These numerous analytes have very diverse physico-chemical properties and occur at different abundance levels. Consequently, comprehensive metabolomics investigations are primarily a challenge for analytical chemistry and specifically mass spectrometry has vast potential as a tool for this type of investigation. Metabolomics require special approaches for sample preparation, separation, and mass spectrometric analysis. Current examples of those approaches are described in this review. It primarily focuses on metabolic fingerprinting, a technique that analyzes all detectable analytes in a given sample with subsequent classification of samples and identification of differentially expressed metabolites, which define the sample classes. To perform this complex task, data analysis tools, metabolite libraries, and databases are required. Therefore, recent advances in metabolomics bioinformatics are also discussed.

Elucidating the mode-of-action of compounds from metabolite profiling studies

Metabolite profiling has been carried out for decades and is as such not a new research area. However, the field has attracted increasing attention in the last couple of years, and the term metabolome is now often used to describe the complete pool of metabolites associated with an organism at any given time. Mass spectrometry (MS) and nuclear magnetic resonance (NMR) spectroscopy are the best candidates for comprehensive analysis of the metabolome and the application of these technologies is presented in this chapter. In this relation, the importance of efficient metabolite screening for discovery of novel drugs is discussed. Related to metabolite profiling, the principals underlying the application of labeled substrates to quantify in vivo metabolic fluxes are introduced, and the chapter is concluded by discussing the perspectives of metabolite measurements in systems biology.

Metabolomics of a superorganism

The human can be thought of as a human-microbe hybrid, and the health of this superorganism will be affected by intrinsic properties such as human genetics, diurnal cycles, and age and by extrinsic factors such as lifestyle choices (food and drink, drug intake) and the acquisition of a stable "healthy" gut microflora (the so-called microbiome). Alterations in this superorganism will be manifest in the metabolite complement within its serum and urine samples. The unraveling of this metabolic compartmentalization in this complex ecosystem will certainly be a challenge for systems biology and necessary for defining human health at the molecular level. Within the systems biology framework, functional analyses at the level of gene expression (transcriptomics), protein translation (proteomics), and, more recently, the metabolite network (metabolomics) have become increasingly popular. Metabolomics experiments aim to quantify all metabolites in a cellular system (cell or tissue) under defined states and at different time points so that the dynamics of any biotic, abiotic, or genetic perturbation can be accurately assessed. This article provides an overview of metabolomics and discusses how data are generated and analyzed within a systems biology framework. The role of metabolomics in nutrigenomics is also discussed, as are the concepts of the human being a superorganism and the complexities required to be overcome to understand human health and disease.

Metabolomics: current technologies and future trends

The ability to sequence whole genomes has taught us that our knowledge with respect to gene function is rather limited with typically 30-40% of open reading frames having no known function. Thus, within the life sciences there is a need for determination of the biological function of these so-called orphan genes, some of which may be molecular targets for therapeutic intervention. The search for specific mRNA, proteins, or metabolites that can serve as diagnostic markers has also increased, as has the fact that these biomarkers may be useful in following and predicting disease progression or response to therapy. Functional analyses have become increasingly popular. They include investigations at the level of gene expression (transcriptomics), protein translation (proteomics) and more recently the metabolite network (metabolomics). This article provides an overview of metabolomics and discusses its complementary role with transcriptomics and proteomics, and within system biology. It highlights how metabolome analyses are conducted and how the highly complex data that are generated are analysed. Non-invasive footprinting analysis is also discussed as this has many applications to in vitro cell systems. Finally, for studying biotic or abiotic stresses on animals, plants or microbes, we believe that metabolomics could very easily be applied to large populations, because this approach tends to be of higher throughput and generally lower cost than transcriptomics and proteomics, whilst also providing indications of which area of metabolism may be affected by external perturbation.

Identification of microbial mixtures by LC-selective proteotypic-peptide analysis (SPA)

This paper describes a method--using a combination of LC-MS/MS of selected bacteria-specific peptides and database search--for determining the species of bacteria present in a mixture. We identified the proteotypic peptides that were associated with specific bacteria by searching protein databases for the LC-MS/MS data. The retention time windows for specific peptide markers were used as an extra constraint so that the peptide markers of many bacterial species could be analyzed in a single LC-selective proteotypic-peptide analysis (SPA). We performed LC-MS/MS analyses on the proteolytic digest of cell extracts and monitored only the selected marker peptide ions at given elution time windows. The corresponding bacterial species could be characterized when the selected peptides that eluted at expected elution windows were identified correctly from the database. We managed to identify up to eight bacterial species simultaneously during a single LC-MS/MS analysis, as well as bacteria mixed in various abundances. Two marker ions having similar values of m/z, but obtained from two different bacterial samples, which would otherwise be selected as precursors within mass tolerance and would complicate the MS/MS data, were time-resolved using LC and then used to correctly identify their bacterial sources. The coupling of selective MS/MS monitoring with separation methods, such as LC, provides a highly selective and accurate analytical method for characterizing complex mixtures of bacterial species.

Using Capillary Electrophoresis−Selective Tandem Mass Spectrometry To Identify Pathogens in Clinical Samples

Analysis of microbial mixtures in complex systems, such as clinical samples, using mass spectrometry can be challenging because the specimens may contain mixtures of several pathogens or both pathogens and nonpathogens. We have successfully applied capillary electrophoresis-selective MS/MS of unique peptide marker ions to the identification of common pathogens in clinical diagnosis. We searched the CE-MS/MS spectra acquired from the proteolytic digests of pure bacterial cell extracts against protein databases. The identified peptides that matched a protein associated with a particular pathogen were selected as marker ions to identify that bacterium in clinical specimens. Thirty-four clinical specimens, obtained from pus, wound, sputum, and urine samples, were analyzed using both biochemical and selective MS/MS methods. The bacteria in these clinical samples were cultivated directly, without prior isolation of a pure colony, before performing the selective MS/MS analyses. The bacteria analyzed included both Gram-positive and -negative strains. The match with respect to the pathogens identified was good between the biochemical and the selective MS/MS methods; the matching rate was 91%. The rate was as high as 97% when not considering two specimens for which the bacteria were not grown successfully. Two of the specimens that we identified using the biochemical method as containing two bacterial species were confirmed also through selective tandem MS analysis.

Metabolomic approaches reveal that phosphatidic and phosphatidyl glycerol phospholipids are major discriminatory non-polar metabolites in responses by Brachypodium distachyon to challenge by Magnaporthe grisea

Metabolomic approaches were used to elucidate some key metabolite changes occurring during interactions of Magnaporthe grisea--the cause of rice blast disease--with an alternate host, Brachypodium distachyon. Fourier-transform infrared (FT-IR) spectroscopy provided a high-throughput metabolic fingerprint of M. grisea interacting with the B. distachyon accessions ABR1 (susceptible) and ABR5 (resistant). Principal component-discriminant function analysis (PC-DFA) allowed the differentiation between developing disease symptoms and host resistance. Alignment of projected 'test-set' on to 'training-set' data indicated that our experimental approach produced highly reproducible data. Examination of PC-DFA loading plots indicated that fatty acids were one chemical group that discriminated between responses by ABR1 and ABR5 to M. grisea. To identify these, non-polar extracts of M. grisea-challenged B. distachyon were directly infused into an electrospray ionization mass spectrometer (ESI-MS). PC-DFA indicated that M. grisea-challenged ABR1 and ABR5 were differentially clustered away from healthy material. Subtraction spectra and PC-DFA loadings plots revealed discriminatory analytes (m/z) between each interaction and seven metabolites were subsequently identified as phospholipids (PLs) by ESI-MS-MS. Phosphatidyl glycerol (PG) PLs were suppressed during both resistant and susceptible responses. By contrast, different phosphatidic acid PLs either increased or were reduced during resistance or during disease development. This suggests considerable and differential PL processing of membrane lipids during each interaction which may be associated with the elaboration/suppression of defence mechanisms or developing disease symptoms.