Discrimination of pathogenic clinical isolates and laboratory strains of Bacillus cereus by NMR-based metabolomic profiling

Impact of Drought Stress on Plant Growth and Its Management Using Plant Growth Promoting Rhizobacteria

Drought stress is a significant environmental challenge affecting global agriculture, leading to substantial reductions in crop yields and overall plant productivity. It induces a cascade of physiological and biochemical changes in plants, including reduced water uptake, stomatal closure, and alterations in hormonal balance, all of which contribute to impaired growth and development. Drought stress diminishes crop production by impacting crucial plant metabolic pathways. Plants possess the ability to activate or deactivate specific sets of genes, leading to changes in their physiological and morphological characteristics. This adaptive response enables plants to evade, endure, or prevent the effects of drought stress. Drought stress triggers the activation of various genes, transcription factors, and signal transduction pathways in plants. In this context, imposing plant growth-promoting rhizobacteria (PGPR) emerges as a promising strategy. PGPR, employing diverse mechanisms such as osmotic adjustments, antioxidant activity, and phytohormone production, not only ensures the plant's survival during drought conditions but also enhances its overall growth. This comprehensive review delves into the various mechanisms through which PGPR enhances drought stress resistance, offering a thorough exploration of recent molecular and omics-based approaches to unravel the role of drought-responsive genes. The manuscript encompasses a detailed mechanistic analysis, along with the development of PGPR-based drought stress management in plants.

Genome-scale metabolic modeling reveals increased reliance on valine catabolism in clinical isolates of Klebsiella pneumoniae

Infections due to carbapenem-resistant Enterobacteriaceae have recently emerged as one of the most urgent threats to hospitalized patients within the United States and Europe. By far the most common etiological agent of these infections is Klebsiella pneumoniae, frequently manifesting in hospital-acquired pneumonia with a mortality rate of ~50% even with antimicrobial intervention. We performed transcriptomic analysis of data collected previously from in vitro characterization of both laboratory and clinical isolates which revealed shifts in expression of multiple master metabolic regulators across isolate types. Metabolism has been previously shown to be an effective target for antibacterial therapy, and genome-scale metabolic network reconstructions (GENREs) have provided a powerful means to accelerate identification of potential targets in silico. Combining these techniques with the transcriptome meta-analysis, we generated context-specific models of metabolism utilizing a well-curated GENRE of K. pneumoniae (iYL1228) to identify novel therapeutic targets. Functional metabolic analyses revealed that both composition and metabolic activity of clinical isolate-associated context-specific models significantly differs from laboratory isolate-associated models of the bacterium. Additionally, we identified increased catabolism of L-valine in clinical isolate-specific growth simulations. These findings warrant future studies for potential efficacy of valine transaminase inhibition as a target against K. pneumoniae infection.

“Omic” Approaches to Bacteria and Antibiotic Resistance Identification

The quick and accurate identification of microorganisms and the study of resistance to antibiotics is crucial in the economic and industrial fields along with medicine. One of the fastest-growing identification methods is the spectrometric approach consisting in the matrix-assisted laser ionization/desorption using a time-of-flight analyzer (MALDI-TOF MS), which has many advantages over conventional methods for the determination of microorganisms presented. Thanks to the use of a multiomic approach in the MALDI-TOF MS analysis, it is possible to obtain a broad spectrum of data allowing the identification of microorganisms, understanding their interactions and the analysis of antibiotic resistance mechanisms. In addition, the literature data indicate the possibility of a significant reduction in the time of the sample preparation and analysis time, which will enable a faster initiation of the treatment of patients. However, it is still necessary to improve the process of identifying and supplementing the existing databases along with creating new ones. This review summarizes the use of “-omics” approaches in the MALDI TOF MS analysis, including in bacterial identification and antibiotic resistance mechanisms analysis.

A Critical Review of the Antimicrobial and Antibiofilm Activities of Green-Synthesized Plant-Based Metallic Nanoparticles

Metallic nanoparticles (MNPs) produced by green synthesis using plant extracts have attracted huge interest in the scientific community due to their excellent antibacterial, antifungal and antibiofilm activities. To evaluate these pharmacological properties, several methods or protocols have been successfully developed and implemented. Although these protocols were mostly inspired by the guidelines from national and international regulatory bodies, they suffer from a glaring absence of standardization of the experimental conditions. This situation leads to a lack of reproducibility and comparability of data from different study settings. To minimize these problems, guidelines for the antimicrobial and antibiofilm evaluation of MNPs should be developed by specialists in the field. Being aware of the immensity of the workload and the efforts required to achieve this, we set out to undertake a meticulous literature review of different experimental protocols and laboratory conditions used for the antimicrobial and antibiofilm evaluation of MNPs that could be used as a basis for future guidelines. This review also brings together all the discrepancies resulting from the different experimental designs and emphasizes their impact on the biological activities as well as their interpretation. Finally, the paper proposes a general overview that requires extensive experimental investigations to set the stage for the future development of effective antimicrobial MNPs using green synthesis.

NMR Hydrophilic Metabolomic Analysis of Bacterial Resistance Pathways Using Multivalent Antimicrobials with Challenged and Unchallenged Wild Type and Mutated Gram-Positive Bacteria

Multivalent membrane disruptors are a relatively new antimicrobial scaffold that are difficult for bacteria to develop resistance to and can act on both Gram-positive and Gram-negative bacteria. Proton Nuclear Magnetic Resonance (¹H NMR) metabolomics is an important method for studying resistance development in bacteria, since this is both a quantitative and qualitative method to study and identify phenotypes by changes in metabolic pathways. In this project, the metabolic differences between wild type Bacillus cereus (B. cereus) samples and B. cereus that was mutated through 33 growth cycles in a nonlethal dose of a multivalent antimicrobial agent were identified. For additional comparison, samples for analysis of the wild type and mutated strains of B. cereus were prepared in both challenged and unchallenged conditions. A C₁₆-DABCO (1,4-diazabicyclo-2,2,2-octane) and mannose functionalized poly(amidoamine) dendrimer (DABCOMD) were used as the multivalent quaternary ammonium antimicrobial for this hydrophilic metabolic analysis. Overall, the study reported here indicates that B. cereus likely change their peptidoglycan layer to protect themselves from the highly positively charged DABCOMD. This membrane fortification most likely leads to the slow growth curve of the mutated, and especially the challenged mutant samples. The association of these sample types with metabolites associated with energy expenditure is attributed to the increased energy required for the membrane fortifications to occur as well as to the decreased diffusion of nutrients across the mutated membrane.

Transcriptomic and Metabolomic Approaches Deepen Our Knowledge of Plant-Endophyte Interactions

In natural systems, plant-symbiont-pathogen interactions play important roles in mitigating abiotic and biotic stresses in plants. Symbionts have their own special recognition ways, but they may share some similar characteristics with pathogens based on studies of model microbes and plants. Multi-omics technologies could be applied to study plant-microbe interactions, especially plant-endophyte interactions. Endophytes are naturally occurring microbes that inhabit plants, but do not cause apparent symptoms in them, and arise as an advantageous source of novel metabolites, agriculturally important promoters, and stress resisters in their host plants. Although biochemical, physiological, and molecular investigations have demonstrated that endophytes confer benefits to their hosts, especially in terms of promoting plant growth, increasing metabolic capabilities, and enhancing stress resistance, plant-endophyte interactions consist of complex mechanisms between the two symbionts. Further knowledge of these mechanisms may be gained by adopting a multi-omics approach. The involved interaction, which can range from colonization to protection against adverse conditions, has been investigated by transcriptomics and metabolomics. This review aims to provide effective means and ways of applying multi-omics studies to solve the current problems in the characterization of plant-microbe interactions, involving recognition and colonization. The obtained results should be useful for identifying the key determinants in such interactions and would also provide a timely theoretical and material basis for the study of interaction mechanisms and their applications.

Untargeted LC-MS Metabolomics Differentiates Between Virulent and Avirulent Clinical Strains of Pseudomonas aeruginosa

Pseudomonas aeruginosa is a facultative pathogen that can cause, inter alia, acute or chronic pneumonia in predisposed individuals. The gram-negative bacterium displays considerable genomic and phenotypic diversity that is also shaped by small molecule secondary metabolites. The discrimination of virulence phenotypes is highly relevant to the diagnosis and prognosis of P. aeruginosa infections. In order to discover small molecule metabolites that distinguish different virulence phenotypes of P. aeruginosa, 35 clinical strains were cultivated under standard conditions, characterized in terms of virulence and biofilm phenotype, and their metabolomes were investigated by untargeted liquid chromatography-mass spectrometry. The data was both mined for individual candidate markers as well as used to construct statistical models to infer the virulence phenotype from metabolomics data. We found that clinical strains that differed in their virulence and biofilm phenotype also had pronounced divergence in their metabolomes, as underlined by 332 features that were significantly differentially abundant with fold changes greater than 1.5 in both directions. Important virulence-associated secondary metabolites like rhamnolipids, alkyl quinolones or phenazines were found to be strongly upregulated in virulent strains. In contrast, we observed little change in primary metabolism. A hitherto novel cationic metabolite with a sum formula of C₁₂H₁₅N₂ could be identified as a candidate biomarker. A random forest model was able to classify strains according to their virulence and biofilm phenotype with an area under the Receiver Operation Characteristics curve of 0.84. These findings demonstrate that untargeted metabolomics is a valuable tool to characterize P. aeruginosa virulence, and to explore interrelations between clinically important phenotypic traits and the bacterial metabolome.

Bioinformatics Resources for Plant Abiotic Stress Responses: State of the Art and Opportunities in the Fast Evolving -Omics Era

Abiotic stresses are among the principal limiting factors for productivity in agriculture. In the current era of continuous climate changes, the understanding of the molecular aspects involved in abiotic stress response in plants is a priority. The rise of -omics approaches provides key strategies to promote effective research in the field, facilitating the investigations from reference models to an increasing number of species, tolerant and sensitive genotypes. Integrated multilevel approaches, based on molecular investigations at genomics, transcriptomics, proteomics and metabolomics levels, are now feasible, expanding the opportunities to clarify key molecular aspects involved in responses to abiotic stresses. To this aim, bioinformatics has become fundamental for data production, mining and integration, and necessary for extracting valuable information and for comparative efforts, paving the way to the modeling of the involved processes. We provide here an overview of bioinformatics resources for research on plant abiotic stresses, describing collections from -omics efforts in the field, ranging from raw data to complete databases or platforms, highlighting opportunities and still open challenges in abiotic stress research based on -omics technologies.

Host-microbe interactions: Profiles in the transcriptome, the proteome, and the metabolome

Periodontal studies using transcriptomics, proteomics, and metabolomics encompass the collection of mRNA transcripts, proteins, and small-molecule chemicals in the context of periodontal health and disease. The number of studies using these approaches has significantly increased in the last decade and they have provided new insight into the pathogenesis and host-microbe interactions that define periodontal diseases. This review provides an overview of current molecular findings using -omic approaches that underlie periodontal disease, including modulation of the host immune response, tissue homeostasis, and complex metabolic processes of the host and the oral microbiome. Integration of these -omic approaches will broaden our perspective of the molecular mechanisms involved in periodontal disease, advancing and improving the diagnosis and treatment of various stages and forms of periodontal disease.

Improving cadmium mobilization by phosphate-solubilizing bacteria via regulating organic acids metabolism with potassium

Organic acids secreted by phosphorus-solubilizing bacteria (PSB) is one of the main biological metabolites with cadmium (Cd) mobilization capacity in the conversion of insoluble precipitate forms to bioavailable forms in contaminated soil. However, the fluctuating concentrations of nutrient elements caused by agricultural activities may result in the substantial variances of carbohydrate metabolism of microorganisms involved in Cd remediation, it is therefore essential to study how metabolic strategies, especially for organic acids, affected by the environmentally friendly fertilizers, such as potassium (K). In this study, adding K⁺ (KCl) concentrations from 0.0 to 100.0 mg/L in medium clearly accelerated Cd mobilization from 15.9 to 35.9 mg/L via inducing the secretion of tartaric acid, 3-hydroxybutyrate, fumaric and succinic acids, increased by 10.0-, 7.5-, 4.3- and 4.1-fold changes, respectively. Current data revealed that the significant differences of metabolic pathways and genes expressions with the varied K⁺ concentrations included: ⅰ) K⁺ induces a substantial up-regulation in metabolic pathway of pyruvic acid to oxaloacetate and tartaric acids; ⅱ) the varied expression of genes involved in encoding enzymes of tricarboxylic acid cycle result in the up-regulated fumaric acid, succinic acid and 3-hydroxybutyrate; ⅲ) the expression of genes related enzyme cysteine and glutamate metabolism processes promoted with the increasing bioavailable Cd concentrations. Besides, P-type ATPase activity increased with K⁺ levels, indicating that H⁺ efflux and medium acidification were strengthened. In general, an appropriate enhancement of K based fertilizer is an effective manner for soil Cd remediation via the regulation of organic acids metabolism and H⁺ secretion of PSB.

Part II: Minimum Quality Threshold in Preclinical Sepsis Studies (MQTiPSS) for Types of Infections and Organ Dysfunction Endpoints

Although the clinical definitions of sepsis and recommended treatments are regularly updated, a systematic review has not been done for preclinical models. To address this deficit, a Wiggers-Bernard Conference on preclinical sepsis modeling reviewed the 260 most highly cited papers between 2003 and 2012 using sepsis models to create a series of recommendations. This Part II report provides recommendations for the types of infections and documentation of organ injury in preclinical sepsis models. Concerning the types of infections, the review showed that the cecal ligation and puncture model was used for 44% of the studies while 40% injected endotoxin. Recommendation #8 (numbered sequentially from Part I): endotoxin injection should not be considered as a model of sepsis; live bacteria or fungal strains derived from clinical isolates are more appropriate. Recommendation #9: microorganisms should replicate those typically found in human sepsis. Sepsis-3 states that sepsis is life-threatening organ dysfunction caused by a dysregulated host response to infection, but the review of the papers showed limited attempts to document organ dysfunction. Recommendation #10: organ dysfunction definitions should be used in preclinical models. Recommendation #11: not all activities in an organ/system need to be abnormal to verify organ dysfunction. Recommendation #12: organ dysfunction should be measured in an objective manner using reproducible scoring systems. Recommendation #13: not all experiments must measure all parameters of organ dysfunction, but investigators should attempt to fully capture as much information as possible. These recommendations are proposed as "best practices" for animal models of sepsis.

Discrimination of Escherichia coli and Shigella spp. by Nuclear Magnetic Resonance Based Metabolomic Characterization of Culture Media

Dysentery is a major health threat that dramatically impacts childhood morbidity and mortality in developing countries. Various pathogenic agents cause dysentery, such as Shigella spp. and Escherichia coli, which are very closely related if not identical species. Sensitive and precise detection and identification of the infectious agent is important to target the best therapeutic strategy, but the differential diagnosis of these two groups remains a challenge using conventional methods. Here, we present a nuclear magnetic resonance (NMR) based multivariate classification model employing bacterial metabolic footprints in postculture growth media with remarkable segregation capability, including the discrimination of lactose negative E. coli and Shigella spp. Our results confirm the potential of metabolomic markers in the field of bacterial identification for the distinction of even very closely related species.

Bioinformatics for Marine Products: An Overview of Resources, Bottlenecks, and Perspectives

The sea represents a major source of biodiversity. It exhibits many different ecosystems in a huge variety of environmental conditions where marine organisms have evolved with extensive diversification of structures and functions, making the marine environment a treasure trove of molecules with potential for biotechnological applications and innovation in many different areas. Rapid progress of the omics sciences has revealed novel opportunities to advance the knowledge of biological systems, paving the way for an unprecedented revolution in the field and expanding marine research from model organisms to an increasing number of marine species. Multi-level approaches based on molecular investigations at genomic, metagenomic, transcriptomic, metatranscriptomic, proteomic, and metabolomic levels are essential to discover marine resources and further explore key molecular processes involved in their production and action. As a consequence, omics approaches, accompanied by the associated bioinformatic resources and computational tools for molecular analyses and modeling, are boosting the rapid advancement of biotechnologies. In this review, we provide an overview of the most relevant bioinformatic resources and major approaches, highlighting perspectives and bottlenecks for an appropriate exploitation of these opportunities for biotechnology applications from marine resources.

Elucidating the survival and response of carbapenem resistant Klebsiella pneumoniae after exposure to imipenem at sub-lethal concentrations

The increasing prevalence of antibiotic resistant pathogens poses a serious threat to global health. However, less emphasis has been placed to co-relate the gene expression and metabolism of antibiotic resistant pathogens. This study aims to elucidate gene expression and variations in metabolism of multidrug resistant Klebsiella pneumoniae after exposure to antibiotics. Phenotypic responses of three genotypically distinct carbapenem resistant Klebsiella pneumoniae (CRKP) strains untreated and treated with sub-lethal concentrations of imipenem were investigated via phenotype microarrays (PM). The gene expression and metabolism of the strain harboring bla_NDM-1 before and after exposure to sub-lethal concentration of imipenem were further investigated by RNA-sequencing (RNA-Seq) and ¹H NMR spectroscopy respectively. Most genes related to cell division, central carbon metabolism and nucleotide metabolism were downregulated after imipenem treatment. Similarly, ¹H NMR spectra obtained from treated CRKP showed decrease in levels of bacterial end products (acetate, pyruvate, succinate, formate) and metabolites involved in nucleotide metabolism (uracil, xanthine, hypoxanthine) but elevated levels of glycerophosphocholine. The presence of anserine was also observed for the treated CRKP while FAPγ-adenine and methyladenine were only present in untreated bacterial cells. As a conclusion, the studied CRKP strain exhibited decrease in central carbon metabolism, cell division and nucleotide metabolism after exposure to sub-lethal concentrations of imipenem. The understanding of the complex biological system of this multidrug resistant bacterium may help in the development of novel strategies and potential targets for the management of the infections.

Abiotic Stress Responses and Microbe-Mediated Mitigation in Plants: The Omics Strategies

Abiotic stresses are the foremost limiting factors for agricultural productivity. Crop plants need to cope up adverse external pressure created by environmental and edaphic conditions with their intrinsic biological mechanisms, failing which their growth, development, and productivity suffer. Microorganisms, the most natural inhabitants of diverse environments exhibit enormous metabolic capabilities to mitigate abiotic stresses. Since microbial interactions with plants are an integral part of the living ecosystem, they are believed to be the natural partners that modulate local and systemic mechanisms in plants to offer defense under adverse external conditions. Plant-microbe interactions comprise complex mechanisms within the plant cellular system. Biochemical, molecular and physiological studies are paving the way in understanding the complex but integrated cellular processes. Under the continuous pressure of increasing climatic alterations, it now becomes more imperative to define and interpret plant-microbe relationships in terms of protection against abiotic stresses. At the same time, it also becomes essential to generate deeper insights into the stress-mitigating mechanisms in crop plants for their translation in higher productivity. Multi-omics approaches comprising genomics, transcriptomics, proteomics, metabolomics and phenomics integrate studies on the interaction of plants with microbes and their external environment and generate multi-layered information that can answer what is happening in real-time within the cells. Integration, analysis and decipherization of the big-data can lead to a massive outcome that has significant chance for implementation in the fields. This review summarizes abiotic stresses responses in plants in-terms of biochemical and molecular mechanisms followed by the microbe-mediated stress mitigation phenomenon. We describe the role of multi-omics approaches in generating multi-pronged information to provide a better understanding of plant-microbe interactions that modulate cellular mechanisms in plants under extreme external conditions and help to optimize abiotic stresses. Vigilant amalgamation of these high-throughput approaches supports a higher level of knowledge generation about root-level mechanisms involved in the alleviation of abiotic stresses in organisms.

Identification of bacterial species by untargeted NMR spectroscopy of the exo-metabolome

Identification of bacterial species is a crucial bottleneck for clinical diagnosis of infectious diseases. Quick and reliable identification is a key factor to provide suitable antibiotherapies and avoid the development of multiple-drug resistance. We propose a novel nuclear magnetic resonance (NMR)-based metabolomics strategy for rapid discrimination and identification of several bacterial species that relies on untargeted metabolic profiling of supernatants from bacterial culture media. We show that six bacterial species (Gram negative: Escherichia coli, Pseudomonas aeruginosa, Proteus mirabilis; Gram positive: Enterococcus faecalis, Staphylococcus aureus, and Staphylococcus saprophyticus) can be well discriminated from multivariate statistical analysis, opening new prospects for NMR applications to microbial clinical diagnosis.

A high-resolution LC-MS-based secondary metabolite fingerprint database of marine bacteria

Marine bacteria are the most widely distributed organisms in the ocean environment and produce a wide variety of secondary metabolites. However, traditional screening for bioactive natural compounds is greatly hindered by the lack of a systematic way of cataloguing the chemical profiles of bacterial strains found in nature. Here we present a chemical fingerprint database of marine bacteria based on their secondary metabolite profiles, acquired by high-resolution LC-MS. Till now, 1,430 bacterial strains spanning 168 known species collected from different marine environments were cultured and profiled. Using this database, we demonstrated that secondary metabolite profile similarity is approximately, but not always, correlated with taxonomical similarity. We also validated the ability of this database to find species-specific metabolites, as well as to discover known bioactive compounds from previously unknown sources. An online interface to this database, as well as the accompanying software, is provided freely for the community to use.

Microbial metabolomics

Microbial metabolomics constitutes an integrated component of systems biology. By studying the complete set of metabolites within a microorganism and monitoring the global outcome of interactions between its development processes and the environment, metabolomics can potentially provide a more accurate snap shot of the actual physiological state of the cell. Recent advancement of technologies and post-genomic developments enable the study and analysis of metabolome. This unique contribution resulted in many scientific disciplines incorporating metabolomics as one of their “omics” platforms. This review focuses on metabolomics in microorganisms and utilizes selected topics to illustrate its impact on the understanding of systems microbiology.

Unraveling the concentration-dependent metabolic response of Pseudomonas sp. HF-1 to nicotine stress by ¹H NMR-based metabolomics

Nicotine can cause oxidative damage to organisms; however, some bacteria, for example Pseudomonas sp. HF-1, are resistant to such oxidative stress. In the present study, we analyzed the concentration-dependent metabolic response of Pseudomonas sp. HF-1 to nicotine stress using ¹H NMR spectroscopy coupled with multivariate data analysis. We found that the dominant metabolites in Pseudomonas sp. HF-1 were eight aliphatic organic acids, six amino acids, three sugars and 11 nucleotides. After 18 h of cultivation, 1 g/L nicotine caused significant elevation of sugar (glucose, trehalose and maltose), succinate and nucleic acid metabolites (cytidine, 5'-CMP, guanine 2',3'-cyclic phosphate and adenosine 2',3'-cyclic phosphate), but decrease of glutamate, putrescine, pyrimidine, 2-propanol, diethyl ether and acetamide levels. Similar metabolomic changes were induced by 2 g/L nicotine, except that no significant change in trehalose, 5'-UMP levels and diethyl ether were found. However, 3 g/L nicotine led to a significant elevation in the two sugars (trehalose and maltose) levels and decrease in the levels of glutamate, putrescine, pyrimidine and 2-propanol. Our findings indicated that nicotine resulted in the enhanced nucleotide biosynthesis, decreased glucose catabolism, elevated succinate accumulation, severe disturbance in osmoregulation and complex antioxidant strategy. And a further increase of nicotine level was a critical threshold value that triggered the change of metabolic flow in Pseudomonas sp. HF-1. These findings revealed the comprehensive insights into the metabolic response of nicotine-degrading bacteria to nicotine-induced oxidative toxicity.

A metabolomics based test of independent action and concentration addition using the earthworm Lumbricus rubellus

A major challenge in ecotoxicology is to understand the effects of multiple toxicants on organisms. Here we assess the effects on survival, weight change, cocoon production and metabolism caused by exposure to two similarly acting (imidacloprid/thiacloprid) and two dissimilarly acting (chlorpyrifos/Nickel) chemicals on the earthworm Lumbricus rubellus. We assessed the standard models of concentration addition (CA) and independent action (IA), in conjunction with a metabolomics based approach to elucidate mechanisms of effect. For imidacloprid and thiacloprid the reproductive effects indicated probable additivity. Although this suggests joint effects through a similar mechanism, metabolite changes for each pesticide actually indicated distinct effects. Further, earthworms exposed to a 0.5 toxic unit equitoxic mixture demonstrated metabolic effects intermediate between those for each pesticide, indicating a non-interactive, independent joint effect. For higher effect level mixtures (1 and 1.5 toxic units), metabolite changes associated with thiacloprid exposure began to dominate. The metabolomic effects of the two dissimilarly acting chemicals were distinct, confirming separate modes of action and both proved more toxic than anticipated from previous studies. In the mixtures, phenotypic effects were in accordance with IA estimates, while metabolite changes were dominated by Ni effects, even though chlorpyrifos contributed most to reproductive toxicity. This could be attributed to the greater systematic effect of Ni when compared to the more specifically acting chlorpyrifos.

Exometabolome analysis identifies pyruvate dehydrogenase as a target for the antibiotic triphenylbismuthdichloride in multiresistant bacterial pathogens

The desperate need for new therapeutics against notoriously antibiotic-resistant bacteria has led to a quest for novel antibacterial target structures and compounds. Moreover, defining targets and modes of action of new antimicrobial compounds remains a major challenge with standard technologies. Here we characterize the antibacterial properties of triphenylbismuthdichloride (TPBC), which has recently been successfully used against device-associated infections. We demonstrate that TPBC has potent antimicrobial activity against many bacterial pathogens. Using an exometabolome profiling approach, a unique TPBC-mediated change in the metabolites of Staphylococcus aureus was identified, indicating that TPBC blocks bacterial pyruvate catabolism. Enzymatic studies showed that TPBC is a highly efficient, uncompetitive inhibitor of the bacterial pyruvate dehydrogenase complex. Our study demonstrates that metabolomics approaches can offer new avenues for studying the modes of action of antimicrobial compounds, and it indicates that inhibition of the bacterial pyruvate dehydrogenase complex may represent a promising strategy for combating multidrug-resistant bacteria.

Metabolomics and its application to studying metal toxicity

Here we explain the omics approach of metabolomics and how it can be applied to study a physiological response to toxic metal exposure. This review aims to educate the metallomics field to the tool of metabolomics. Metabolomics is becoming an increasingly used tool to compare natural and challenged states of various organisms, from disease states in humans to toxin exposure to environmental systems. This approach is key to understanding and identifying the cellular or biochemical targets of metals and the underlying physiological response. Metabolomics steps are described and overviews of its application to metal toxicity to organisms are given. As this approach is very new there are yet only a small number of total studies and therefore only a brief overview of some metal metabolomics studies is described. A frank critical evaluation of the approach is given to provide newcomers to the method a clear idea of the challenges and the rewards of applying metabolomics to their research.

Technologies and approaches to elucidate and model the virulence program of salmonella

Salmonella is a primary cause of enteric diseases in a variety of animals. During its evolution into a pathogenic bacterium, Salmonella acquired an elaborate regulatory network that responds to multiple environmental stimuli within host animals and integrates them resulting in fine regulation of the virulence program. The coordinated action by this regulatory network involves numerous virulence regulators, necessitating genome-wide profiling analysis to assess and combine efforts from multiple regulons. In this review we discuss recent high-throughput analytic approaches used to understand the regulatory network of Salmonella that controls virulence processes. Application of high-throughput analyses have generated large amounts of data and necessitated the development of computational approaches for data integration. Therefore, we also cover computer-aided network analyses to infer regulatory networks, and demonstrate how genome-scale data can be used to construct regulatory and metabolic systems models of Salmonella pathogenesis. Genes that are coordinately controlled by multiple virulence regulators under infectious conditions are more likely to be important for pathogenesis. Thus, reconstructing the global regulatory network during infection or, at the very least, under conditions that mimic the host cellular environment not only provides a bird's eye view of Salmonella survival strategy in response to hostile host environments but also serves as an efficient means to identify novel virulence factors that are essential for Salmonella to accomplish systemic infection in the host.

Metabolomics and malaria biology

Metabolomics has ushered in a novel and multi-disciplinary realm in biological research. It has provided researchers with a platform to combine powerful biochemical, statistical, computational, and bioinformatics techniques to delve into the mysteries of biology and disease. The application of metabolomics to study malaria parasites represents a major advance in our approach towards gaining a more comprehensive perspective on parasite biology and disease etiology. This review attempts to highlight some of the important aspects of the field of metabolomics, and its ongoing and potential future applications to malaria research.

Analytical platform for metabolome analysis of microbial cells using methyl chloroformate derivatization followed by gas chromatography-mass spectrometry

This protocol describes an analytical platform for the analysis of intra- and extracellular metabolites of microbial cells (yeast, filamentous fungi and bacteria) using gas chromatography-mass spectrometry (GC-MS). The protocol is subdivided into sampling, sample preparation, chemical derivatization of metabolites, GC-MS analysis and data processing and analysis. This protocol uses two robust quenching methods for microbial cultures, the first of which, cold glycerol-saline quenching, causes reduced leakage of intracellular metabolites, thus allowing a more reliable separation of intra- and extracellular metabolites with simultaneous stopping of cell metabolism. The second, fast filtration, is specifically designed for quenching filamentous micro-organisms. These sampling techniques are combined with an easy sample-preparation procedure and a fast chemical derivatization reaction using methyl chloroformate. This reaction takes place at room temperature, in aqueous medium, and is less prone to matrix effect compared with other derivatizations. This protocol takes an average of 10 d to complete and enables the simultaneous analysis of hundreds of metabolites from the central carbon metabolism (amino and nonamino organic acids, phosphorylated organic acids and fatty acid intermediates) using an in-house MS library and a data analysis pipeline consisting of two free software programs (Automated Mass Deconvolution and Identification System (AMDIS) and R).

Metabolomics, a New Promising Technology for Toxicological Research

Metabolomics which deals with the biological metabolite profile produced in the body and its relation to disease state is a relatively recent research area for drug discovery and biological sciences including toxicology and pharmacology. Metabolomics, based on analytical method and multivariate analysis, has been considered a promising technology because of its advantage over other toxicogenomic and toxicoproteomic approaches. The application of metabolomics includes the development of biomarkers associated with the pathogenesis of various diseases, alternative toxicity tests, high-throughput screening (HTS), and risk assessment, allowing the simultaneous acquisition of multiple biochemical parameters in biological samples. The metabolic profile of urine, in particular, often shows changes in response to exposure to xenobiotics or disease-induced stress, because of the biological system's attempt to maintain homeostasis. In this review, we focus on the most recent advances and applications of metabolomics in toxicological research.

Metabolic footprinting study of white spruce somatic embryogenesis using NMR spectroscopy

White spruce is an important commercial species for reforestation. The success in its propagation through somatic embryogenesis is well documented; however the physiological processes involved are poorly understood and remain unoptimized. The variable quality embryos generated in vitro from the same genotype suggest control at the protein and metabolite level. In order to probe metabolic changes, we have conducted a "metabolic footprinting" study, whereby culture media from growing cells was quantitatively analyzed to determine which metabolites were consumed and excreted. Such experiments are advantageous in that there is no need to quench cellular metabolism or extract intracellular metabolites through time-consuming protocols. In this paper we demonstrate the application of the footprinting assay to somatic embryo cells of white spruce (Picea glauca) using 1D (1)H NMR spectroscopy. We have surveyed embryogenesis metabolism in two types of media, maintenance (MN) and maturation (MT). MN medium does not result in shoot apical meristem (SAM) formation, while MT medium induces the necessary changes leading to fully developed somatic embryos. The two types of media were easily distinguished using metabolomics analysis, namely multivariate pattern recognition statistics (orthogonal partial least squares discriminatory analysis). From this analysis, we have identified numerous compounds involved with branched chain amino acid pathways such as valine and isoleucine. These results are explained on the basis of known metabolic pathways implicated in plant and animal developmental processes, and ultimately implicate altered CoA biosynthesis.

Time-resolved metabolic footprinting for nonlinear modeling of bacterial substrate utilization

Untargeted profiling of small-molecule metabolites from microbial culture supernatants (metabolic footprinting) has great potential as a phenotyping tool. We used time-resolved metabolic footprinting to compare one Escherichia coli and three Pseudomonas aeruginosa strains growing on complex media and show that considering metabolite changes over the whole course of growth provides much more information than analyses based on data from a single time point. Most strikingly, there was pronounced selectivity in metabolite uptake, even when the bacteria were growing apparently exponentially, with certain groups of metabolites not taken up until others had been entirely depleted from the medium. In addition, metabolite excretion showed some complex patterns. Fitting nonlinear equations (four-parameter sigmoids) to individual metabolite data allowed us to model these changes for metabolite uptake and visualize them by back-projecting the curve-fit parameters onto the original growth curves. These "uptake window" plots clearly demonstrated strain differences, with the uptake of some compounds being reversed in order between different strains. Comparison of an undefined rich medium with a defined complex medium designed to mimic cystic fibrosis sputum showed many differences, both qualitative and quantitative, with a greater proportion of excreted to utilized metabolites in the defined medium. Extending the strain comparison to a more closely related set of isolates showed that it was possible to discriminate two species of the Burkholderia cepacia complex based on uptake dynamics alone. We believe time-resolved metabolic footprinting could be a valuable tool for many questions in bacteriology, including isolate comparisons, phenotyping deletion mutants, and as a functional complement to taxonomic classifications.

Metabolomic investigation of the bacterial response to a metal challenge

Pseudomonas pseudoalcaligenes KF707 is naturally resistant to the toxic metalloid tellurite, but the mechanisms of resistance are not known. In this study we report the isolation of a KF707 mutant (T5) with hyperresistance to tellurite. In order to characterize the bacterial response and the pathways leading to tolerance, we utilized Phenotype MicroArray technology (Biolog) and a metabolomic technique based on nuclear magnetic resonance spectroscopy. The physiological states of KF707 wild-type and T5 cells exposed to tellurite were also compared in terms of viability and reduced thiol content. Our analyses showed an extensive change in metabolism upon the addition of tellurite to KF707 cultures as well as different responses when the wild-type and T5 strains were compared. Even in the absence of tellurite, T5 cells displayed a "poised" physiological status, primed for tellurite exposure and characterized by altered intracellular levels of glutathione, branched-chain amino acids, and betaine, along with increased resistance to other toxic metals and metabolic inhibitors. We conclude that hyperresistance to tellurite in P. pseudoalcaligenes KF707 is correlated with the induction of the oxidative stress response, resistance to membrane perturbation, and reconfiguration of cellular metabolism.

Inhibitors of pathogen intercellular signals as selective anti-infective compounds

Long-term antibiotic use generates pan-resistant super pathogens. Anti-infective compounds that selectively disrupt virulence pathways without affecting cell viability may be used to efficiently combat infections caused by these pathogens. A candidate target pathway is quorum sensing (QS), which many bacterial pathogens use to coordinately regulate virulence determinants. The Pseudomonas aeruginosa MvfR-dependent QS regulatory pathway controls the expression of key virulence genes; and is activated via the extracellular signals 4-hydroxy-2-heptylquinoline (HHQ) and 3,4-dihydroxy-2-heptylquinoline (PQS), whose syntheses depend on anthranilic acid (AA), the primary precursor of 4-hydroxy-2-alkylquinolines (HAQs). Here, we identified halogenated AA analogs that specifically inhibited HAQ biosynthesis and disrupted MvfR-dependent gene expression. These compounds restricted P. aeruginosa systemic dissemination and mortality in mice, without perturbing bacterial viability, and inhibited osmoprotection, a widespread bacterial function. These compounds provide a starting point for the design and development of selective anti-infectives that restrict human P. aeruginosa pathogenesis, and possibly other clinically significant pathogens.

Investigation on response of the metabolites in tricarboxylic acid cycle of Escherichi coli and Pseudomonas aeruginosa to antibiotic perturbation by capillary electrophoresis

Metabolomics is a new branch of systems biology exerting its influence in many aspects. In order to appraise the effects of antibiotics on central carbon metabolism, a CE based method was set up. With this platform, we estimated the organic acid metabolite pools' fluctuation of Escherichia coli and Pseudomonas aeruginosa cultured under 11 different antibiotics' stimuli. Multivariate data analysis showed that different antibiotics had clustered distributions for each strain and could be easily distinguished. Genetic, metabolic and antibiotic mechanism differences could also be deduced by the aid of further correlation analysis. For P. aeruginosa, even synergy action amid antibiotics could be ascertained.

NMR metabolic profiling of Aspergillus nidulans to monitor drug and protein activity

We describe a general protocol for using comparative NMR metabolomics data to infer in vivo efficacy, specificity and toxicity of chemical leads within a drug discovery program. The methodology is demonstrated using Aspergillus nidulans to monitor the activity of urate oxidase and orotidine-5'-phosphate decarboxylase and the impact of 8-azaxanthine, an inhibitor of urate oxidase. 8-azaxanthine is shown to inhibit A. nidulans hyphal growth by in vivo inactivation of urate oxidase.

The Cinderella story of metabolic profiling: does metabolomics get to go to the functional genomics ball?

To date most global approaches to functional genomics have centred on genomics, transcriptomics and proteomics. However, since a number of high-profile publications, interest in metabolomics, the global profiling of metabolites in a cell, tissue or organism, has been rapidly increasing. A range of analytical techniques, including 1H NMR spectroscopy, gas chromatography-mass spectrometry (GC-MS), liquid chromatography-mass spectrometry (LC-MS), Fourier Transform mass spectrometry (FT-MS), high performance liquid chromatography (HPLC) and electrochemical array (EC-array), are required in order to maximize the number of metabolites that can be identified in a matrix. Applications have included phenotyping of yeast, mice and plants, understanding drug toxicity in pharmaceutical drug safety assessment, monitoring tumour treatment regimes and disease diagnosis in human populations. These successes are likely to be built on as other analytical and bioinformatic approaches are developed to fully exploit the information obtained in metabolic profiles. To assist in this process, databases of metabolomic data will be necessary to allow the passage of information between laboratories. In this prospective review, the capabilities of metabolomics in the field of medicine will be assessed in an attempt to predict the impact this 'Cinderella approach' will have at the 'functional genomic ball'.

Genomic medicine: genetic variation and its impact on the future of health care

Advances in genome technology and other fruits of the Human Genome Project are playing a growing role in the delivery of health care. With the development of new technologies and opportunities for large-scale analysis of the genome, transcriptome, proteome and metabolome, the genome sciences are poised to have a profound impact on clinical medicine. Cancer prognostics will be among the first major test cases for a genomic medicine paradigm, given that all cancer is caused by genomic instability, and microarrays allow assessment of patients' entire expressed genomes. Analysis of breast cancer patients' expression patterns can already be highly correlated with recurrence risks. By integrating clinical data with gene expression profiles, imaging, metabolomic profiles and proteomic data, the prospect for developing truly individualized care becomes ever more real. Notwithstanding these promises, daunting challenges remain for genomic medicine. Success will require planning robust prospective trials, analysing health care economic and outcome data, assuaging insurance and privacy concerns, developing health delivery models that are commercially viable and scaling up to meet the needs of the whole population.

Metabolomics reviewed: a new "omics" platform technology for systems biology and implications for natural products research

Metabolomics is the study of global metabolite profiles in a system (cell, tissue, or organism) under a given set of conditions. The analysis of the metabolome is particularly challenging due to the diverse chemical nature of metabolites. Metabolites are the result of the interaction of the system's genome with its environment and are not merely the end product of gene expression but also form part of the regulatory system in an integrated manner. Metabolomics has its roots in early metabolite profiling studies but is now a rapidly expanding area of scientific research in its own right. Metabolomics (or metabonomics) has been labeled one of the new "omics", joining genomics, transcriptomics, and proteomics as a science employed toward the understanding of global systems biology. Metabolomics is fast becoming one of the platform sciences of the "omics", with the majority of the papers in this field having been published only in the last two years. In this review metabolomic methodologies are discussed briefly followed by a more detailed review of the use of metabolomics in integrated applications where metabolomics information has been combined with other "omic" data sets (proteomics, transcriptomics) to enable greater understanding of a biological system. The potential of metabolomics for natural product drug discovery and functional food analysis, primarily as incorporated into broader "omic" data sets, is discussed.