Revisiting Protocols for the NMR Analysis of Bacterial Metabolomes

Establishment of a novel classification system for alveolar morphology in infants with unilateral complete cleft lip and palate

OBJECTIVES

Unilateral complete cleft lip and palate (UCCLP) is one of the most severe clinical subtypes among cleft lip and palate (CLP), making repair surgery and subsequent orthodontic treatment particularly challenging. Presurgical nasoalveolar molding (PNAM) has shown conflicting and heterogeneous results in the treatment of UCCLP patients, raising questions about whether the diversity in alveolar anatomical morphology among these patients plays a role in the effectiveness of PNAM treatment.

MATERIALS AND METHODS

We collected 90 digital maxillary models of infants with UCCLP and performed mathematical clustering analysis, including principal component analysis (PCA), decision tree modeling, and area under the ROC Curve (AUC) analysis, to classify alveolar morphology and identify key measurements. We also conducted clinical evaluations to assess the association between the alveolar morphology and CLP treatment outcomes.

RESULTS

Using mathematical clustering analysis, we classified the alveolar morphology into three distinct types: average form, horizontal form, and longitudinal form. The decision tree model, AUC analysis, and comparison analysis revealed that four measurements (Trans ACG-ACL, ML length, MG length and Inc length) were essential for clustering the alveolar morphology of infants with UCCLP. Furthermore, the blinded clinical evaluation indicated that UCCLP patients with alveolar segments of horizontal form had the lowest treatment outcomes.

CONCLUSION

Overall, our findings establish a novel quantitative classification system for the morphology of alveolar bone in infants with UCCLP and suggest that this classification may be associated with the outcomes of CLP treatment.

CLINICAL RELEVANCE

The multidisciplinary CLP team should thoroughly evaluate and classify the specific alveolar morphology when administering PNAM to infants with UCCLP.

The Development and Validation of Radiopharmaceuticals Targeting Bacterial Infection

The International Atomic Energy Agency organized a technical meeting at its headquarters in Vienna, Austria, in 2022 that included 17 experts representing 12 countries, whose research spanned the development and use of radiolabeled agents for imaging infection. The meeting focused largely on bacterial pathogens. The group discussed and evaluated the advantages and disadvantages of several radiopharmaceuticals, as well as the science driving various imaging approaches. The main objective was to understand why few infection-targeted radiotracers are used in clinical practice despite the urgent need to better characterize bacterial infections. This article summarizes the resulting consensus, at least among the included scientists and countries, on the current status of radiopharmaceutical development for infection imaging. Also included are opinions and recommendations regarding current research standards in this area. This and future International Atomic Energy Agency-sponsored collaborations will advance the goal of providing the medical community with innovative, practical tools for the specific image-based diagnosis of infection.

Advances in Microbial NMR Metabolomics

Confidently, nuclear magnetic resonance (NMR) is the most informative technique in analytical chemistry and its use as an analytical platform in metabolomics is well proven. This chapter aims to present NMR as a viable tool for microbial metabolomics discussing its fundamental aspects and applications in metabolomics using some chosen examples.

Sample Preparation in Microbial Metabolomics: Advances and Challenges

Microbial metabolomics has gained significant interest as it reflects the physiological state of microorganisms. Due to the great variability of biological organisms, in terms of physicochemical characteristics and variable range of concentration of metabolites, the choice of sample preparation methods is a crucial step in the metabolomics workflow and will reflect on the quality and reliability of the results generated. The procedures applied to the preparation of microbial samples will vary according to the type of microorganism studied, the metabolomics approach (untargeted or targeted), and the analytical platform of choice. This chapter aims to provide an overview of the sample preparation workflow for microbial metabolomics, highlighting the pre-analytical factors associated with cultivation, harvesting, metabolic quenching, and extraction. Discussions focus on obtaining intracellular and extracellular metabolites. Finally, we introduced advanced sample preparation methods based on automated systems.

Comparison of bacteria disintegration methods and their influence on data analysis in metabolomics

Metabolomic experiments usually contain many different steps, each of which can strongly influence the obtained results. In this work, metabolic analyses of six bacterial strains were performed in light of three different bacterial cell disintegration methods. Three strains were gram-negative (Pseudomonas aeruginosa, Escherichia coli, and Klebsiella pneumoniae), and three were gram-positive (Corynebacterium glutamicum, Bacillus cereus, and Enterococcus faecalis). For extraction, the methanol–water extraction method (1:1) was chosen. To compare the efficiency of different cell disintegration methods, sonication, sand mill, and tissue lyser were used. For bacterial extract metabolite analysis, ¹H NMR together with univariate and multivariate analyses were applied. The obtained results showed that metabolite concentrations are strongly dependent on the cell lysing methodology used and are different for various bacterial strains. The results clearly show that one of the disruption methods gives the highest concentration for most identified compounds (e. g. sand mill for E. faecalis and tissue lyser for B. cereus). This study indicated that the comparison of samples prepared by different procedures can lead to false or imprecise results, leaving an imprint of the disintegration method. Furthermore, the presented results showed that NMR might be a useful bacterial strain identification and differentiation method. In addition to disintegration method comparison, the metabolic profiles of each elaborated strain were analyzed, and each exhibited its metabolic profile. Some metabolites were identified by the ¹H NMR method in only one strain. The results of multivariate data analyses (PCA) show that regardless of the disintegration method used, the strain group can be identified. Presented results can be significant for all types of microbial studies containing the metabolomic targeted and non-targeted analysis.

Usnic Acid Treatment Changes the Composition of Mycobacterium tuberculosis Cell Envelope and Alters Bacterial Redox Status

Mycobacterium tuberculosis developed efficient adaptation mechanisms in response to different environmental conditions. This resulted in the ability to survive in human macrophages and in resistance to numerous antibiotics. To get insight into bacterial responses to potent antimycobacterial natural compounds, we tested how usnic acid, a lichen-derived secondary metabolite, would influence mycobacteria at transcriptomic and metabolomic levels. The analysis of expression of sigma factors revealed a profound impact of usnic acid on one of the primary genetic regulatory systems of M. tuberculosis Combined liquid chromatography-mass spectrometry and nuclear magnetic resonance analyses allowed us to observe the perturbations in metabolic pathways, as well as in lipid composition, which took place within 24 h of exposure. Early bacterial response was related to redox homeostasis, lipid synthesis, and nucleic acid repair. Usnic acid treatment provoked disturbances of redox state in mycobacterial cells and increased production of structural elements of the cell wall and cell membrane. In addition, to increase the number of molecules related to restoration of redox balance, the rearrangements of the cell envelope were the first defense mechanisms observed under usnic acid treatment.IMPORTANCE The evaluation of mechanisms of mycobacterial response to natural products has been barely studied. However, it might be helpful to reveal bacterial adaptation strategies, which are eventually crucial for the discovery of new drug targets and, hence, understanding the resistance mechanisms. This study showed that the first-line mycobacterial defense against usnic acid, a potent antimicrobial agent, is the remodeling of the cell envelope and restoring redox homeostasis. Transcriptomic data correlated with metabolomics analysis. The observed metabolic changes appeared similar to those exerted by antibiotics.

Metabolic Feedback Inhibition Influences Metabolite Secretion by the Human Gut Symbiont Bacteroides thetaiotaomicron

Bacteroides is a highly abundant taxon in the human gut, and Bacteroides thetaiotaomicron (B. theta) is a ubiquitous human symbiont that colonizes the host early in development and persists throughout its life span. The phenotypic plasticity of keystone organisms such as B. theta is important to understand in order to predict phenotype(s) and metabolic interactions under changing nutrient conditions such as those that occur in complex gut communities. Our study shows B. theta prioritizes energy conservation and suppresses secretion of “overflow metabolites” such as organic acids and amino acids when concentrations of acetate are high. Secreted metabolites, especially amino acids, can be a source of nutrients or signals for the host or other microbes in the community. Our study suggests that when metabolically stressed by acetate, B. theta stops sharing with its ecological partners.

Microbial metabolism and trophic interactions between microbes give rise to complex multispecies communities in microbe-host systems. Bacteroides thetaiotaomicron (B. theta) is a human gut symbiont thought to play an important role in maintaining host health. Untargeted nuclear magnetic resonance metabolomics revealed B. theta secretes specific organic acids and amino acids in defined minimal medium. Physiological concentrations of acetate and formate found in the human intestinal tract were shown to cause dose-dependent changes in secretion of metabolites known to play roles in host nutrition and pathogenesis. While secretion fluxes varied, biomass yield was unchanged, suggesting feedback inhibition does not affect metabolic bioenergetics but instead redirects carbon and energy to CO₂ and H₂. Flux balance analysis modeling showed increased flux through CO₂-producing reactions under glucose-limiting growth conditions. The metabolic dynamics observed for B. theta, a keystone symbiont organism, underscores the need for metabolic modeling to complement genomic predictions of microbial metabolism to infer mechanisms of microbe-microbe and microbe-host interactions.

IMPORTANCEBacteroides is a highly abundant taxon in the human gut, and Bacteroides thetaiotaomicron (B. theta) is a ubiquitous human symbiont that colonizes the host early in development and persists throughout its life span. The phenotypic plasticity of keystone organisms such as B. theta is important to understand in order to predict phenotype(s) and metabolic interactions under changing nutrient conditions such as those that occur in complex gut communities. Our study shows B. theta prioritizes energy conservation and suppresses secretion of “overflow metabolites” such as organic acids and amino acids when concentrations of acetate are high. Secreted metabolites, especially amino acids, can be a source of nutrients or signals for the host or other microbes in the community. Our study suggests that when metabolically stressed by acetate, B. theta stops sharing with its ecological partners.

Staring into the void: demystifying microbial metabolomics

Metabolites give us a window into the chemistry of microbes and are split into two subclasses: primary and secondary. Primary metabolites are required for life whereas secondary metabolites have historically been classified as those appearing after exponential growth and are not necessarily needed for survival. Many microbial species are estimated to produce hundreds of metabolites and can be affected by differing nutrients. Using various analytical techniques, metabolites can be directly detected in order to elucidate their biological significance. Currently, a single experiment can produce anywhere from megabytes to terabytes of data. This big data has motivated scientists to develop informatics tools to help target specific metabolites or sets of metabolites. Broadly, it is imperative to identify clear biological questions before embarking on a study of metabolites (metabolomics). For instance, studying the effect of a transposon insertion on phenazine biosynthesis in Pseudomonas is a very different from asking what molecules are present in a specific banana-derived strain of Pseudomonas. This review is meant to serve as a primer for a 'choose your own adventure' approach for microbiologists with limited mass spectrometry expertise, with a strong focus on liquid chromatography mass spectrometry based workflows developed or optimized within the past five years.

Untargetted Metabolomic Exploration of the Mycobacterium tuberculosis Stress Response to Cinnamon Essential Oil

The antimycobacterial activity of cinnamaldehyde has already been proven for laboratory strains and for clinical isolates. What is more, cinnamaldehyde was shown to threaten the mycobacterial plasma membrane integrity and to activate the stress response system. Following promising applications of metabolomics in drug discovery and development we aimed to explore the mycobacteria response to cinnamaldehyde within cinnamon essential oil treatment by untargeted liquid chromatography–mass spectrometry. The use of predictive metabolite pathway analysis and description of produced lipids enabled the evaluation of the stress symptoms shown by bacteria. This study suggests that bacteria exposed to cinnamaldehyde could reorganize their outer membrane as a physical barrier against stress factors. They probably lowered cell wall permeability and inner membrane fluidity, and possibly redirected carbon flow to store energy in triacylglycerols. Being a reactive compound, cinnamaldehyde may also contribute to disturbances in bacteria redox homeostasis and detoxification mechanisms.

The impact of p53 on aristolochic acid I-induced nephrotoxicity and DNA damage in vivo and in vitro

Exposure to aristolochic acid (AA) is associated with human nephropathy and urothelial cancer. The tumour suppressor TP53 is a critical gene in carcinogenesis and frequently mutated in AA-induced urothelial tumours. We investigated the impact of p53 on AAI-induced nephrotoxicity and DNA damage in vivo by treating Trp53(+/+), Trp53(+/-) and Trp53(-/-) mice with 3.5 mg/kg body weight (bw) AAI daily for 2 or 6 days. Renal histopathology showed a gradient of intensity in proximal tubular injury from Trp53(+/+) to Trp53(-/-) mice, especially after 6 days. The observed renal injury was supported by nuclear magnetic resonance (NMR)-based metabonomic measurements, where a consistent Trp53 genotype-dependent trend was observed for urinary metabolites that indicate aminoaciduria (i.e. alanine), lactic aciduria (i.e. lactate) and glycosuria (i.e. glucose). However, Trp53 genotype had no impact on AAI-DNA adduct levels, as measured by 32P-postlabelling, in either target (kidney and bladder) or non-target (liver) tissues, indicating that the underlying mechanisms of p53-related AAI-induced nephrotoxicity cannot be explained by differences in AAI genotoxicity. Performing gas chromatography-mass spectrometry (GC-MS) on kidney tissues showed metabolic pathways affected by AAI treatment, but again Trp53 status did not clearly impact on such metabolic profiles. We also cultured primary mouse embryonic fibroblasts (MEFs) derived from Trp53(+/+), Trp53(+/-) and Trp53(-/-) mice and exposed them to AAI in vitro (50 µM for up to 48 h). We found that Trp53 genotype impacted on the expression of NAD(P)H:quinone oxidoreductase (Nqo1), a key enzyme involved in AAI bioactivation. Nqo1 induction was highest in Trp53(+/+) MEFs and lowest in Trp53(-/-) MEFs; and it correlated with AAI-DNA adduct formation, with lowest adduct levels being observed in AAI-exposed Trp53(-/-) MEFs. Overall, our results clearly demonstrate that p53 status impacts on AAI-induced renal injury, but the underlying mechanism(s) involved remain to be further explored. Despite the impact of p53 on AAI bioactivation and DNA damage in vitro, such effects were not observed in vivo.

NMR Metabolomics Protocols for Drug Discovery

Drug discovery is an extremely difficult and challenging endeavor with a very high failure rate. The task of identifying a drug that is safe, selective, and effective is a daunting proposition because disease biology is complex and highly variable across patients. Metabolomics enables the discovery of disease biomarkers, which provides insights into the molecular and metabolic basis of disease and may be used to assess treatment prognosis and outcome. In this regard, metabolomics has evolved to become an important component of the drug discovery process to resolve efficacy and toxicity issues and as a tool for precision medicine. A detailed description of an experimental protocol is presented that outlines the application of NMR metabolomics to the drug discovery pipeline. This includes (1) target identification by understanding the metabolic dysregulation in diseases, (2) predicting the mechanism of action of newly discovered or existing drug therapies, (3) and using metabolomics to screen a chemical lead to assess biological activity. Unlike other OMICS approaches, the metabolome is "fragile" and may be negatively impacted by improper sample collection, storage, and extraction procedures. Similarly, biologically irrelevant conclusions may result from incorrect data collection, preprocessing or processing procedures, or the erroneous use of univariate and multivariate statistical methods. These critical concerns are also addressed in the protocol.

Metabolomics Analyses from Tissues in Parkinson's Disease

Metabolomics has been successfully applied to study neurological and neurodegenerative disorders including Parkinson's disease for (1) the identification of potential biomarkers of onset and disease progression; (2) the identification of novel mechanisms of disease progression; and (3) the assessment of treatment prognosis and outcome. Reproducible and efficient extraction of metabolites is imperative to the success of any metabolomics investigation. Unlike other omics techniques, the composition of the metabolome can be negatively impacted by the preparation, processing, and handling of these samples. The proper choice of data collection, preprocessing, and processing protocols is similarly important to the design of an effective metabolomics experiment. Likewise, the correct application of univariate and multivariate statistical methods is essential for providing biologically relevant insights. In this chapter, we have outlined a detailed metabolomics workflow that addresses all of these issues. A step-by-step protocol from the preparation of neuronal cells and metabolomic tissue samples to their metabolic analyses using nuclear magnetic resonance, mass spectrometry, and chemometrics is presented.

NMR insights on nano silver post-surgical treatment of superficial caseous lymphadenitis in small ruminants

Caseous lymphadenitis (CL), caused by a pathogen of the second class of biosafety – Corynebacterium pseudotuberculosis, is a chronic and severe infectious disease that affects small ruminants and requires long, ineffective treatment which generally leads to animal sacrifice so as to stop the disease spreading. The infected animals suffer the excision of affected superficial lymph nodes and post-surgical treatment with iodine (10% solution in ethanol) and, sometimes, prolonged antibiotic use, but only if the sick animals are of great importance to breeding. Herein, we propose a cheap and easy to apply treatment of CL with excellent results using biogenic silver nanoparticles (AgNP) based technology. AgNP antibacterial properties were investigated in vitro against Corynebacterium pseudotuberculosis cells and in vivo on small ruminants with CL. Treatment of surgical wounds resulting from the excision of superficial CL lesions with a AgNP-based cream was compared to the standard post-surgical treatment method by iodine. Also, the effects of AgNP-based cream treatment were evaluated and compared with the effects of the iodine CL treatment by serum NMR-based metabolomics. Serum samples were collected from 29 animals, 9 sheep and 20 goats, during the treatments and analyzed. All animals showed stable serum metabolomes when iodine or AgNP-based cream effects were compared. The AgNP-based cream treatment showed excellent results, especially in accelerating the healing of wounds, which occurred two to three times faster in comparison with the iodine treatment. AgNP-based cream treatment also prevented CL reappearance and did not cause any side effects on animals. This is the first report on very effective post-surgical treatment of superficial CL in small ruminants based on biogenic silver nanoparticles, which might open up the possibility for a safe veterinary application of AgNP-based cream.

Biogenic nanosilver in a pharmaceutical cream for wound healing in animal and human healthcare.

Application of metabolomics to drug discovery and understanding the mechanisms of action of medicinal plants with anti-tuberculosis activity

Human tuberculosis (TB) is amongst the oldest and deadliest human bacterial diseases that pose major health, social and economic burden at a global level. Current regimens for TB treatment are lengthy, expensive and ineffective to emerging drug resistant strains. Thus, there is an urgent need for identification and development of novel TB drugs and drug regimens with comprehensive and specific mechanisms of action. Many medicinal plants are traditionally used for TB treatment. While some of their phytochemical composition has been elucidated, their mechanisms of action are not well understood. Insufficient knowledge on Mycobacterium tuberculosis (M.tb) biology and the complex nature of its infection limit the effectiveness of current screening-based methods used for TB drug discovery. Nonetheless, application of metabolomics tools within the 'omics' approaches, could provide an alternative method of elucidating the mechanism of action of medicinal plants. Metabolomics aims at high throughput detection, quantification and identification of metabolites in biological samples. Changes in the concentration of specific metabolites in a biological sample indicate changes in the metabolic pathways. In this paper review and discuss novel methods that involve application of metabolomics to drug discovery and the understanding of mechanisms of action of medicinal plants with anti-TB activity. Current knowledge on TB infection, anti-TB drugs and mechanisms of action are also included. We further highlight metabolism of M. tuberculosis and the potential drug targets, as well as current approaches in the development of anti-TB drugs.

Comparing normalization methods and the impact of noise

INTRODUCTION

Failure to properly account for normal systematic variations in OMICS datasets may result in misleading biological conclusions. Accordingly, normalization is a necessary step in the proper preprocessing of OMICS datasets. In this regards, an optimal normalization method will effectively reduce unwanted biases and increase the accuracy of downstream quantitative analyses. But, it is currently unclear which normalization method is best since each algorithm addresses systematic noise in different ways.

OBJECTIVE

Determine an optimal choice of a normalization method for the preprocessing of metabolomics datasets.

METHODS

Nine MVAPACK normalization algorithms were compared with simulated and experimental NMR spectra modified with added Gaussian noise and random dilution factors. Methods were evaluated based on an ability to recover the intensities of the true spectral peaks and the reproducibility of true classifying features from orthogonal projections to latent structures-discriminant analysis model (OPLS-DA).

RESULTS

Most normalization methods (except histogram matching) performed equally well at modest levels of signal variance. Only probabilistic quotient (PQ) and constant sum (CS) maintained the highest level of peak recovery (> 67%) and correlation with true loadings (> 0.6) at maximal noise.

CONCLUSION

PQ and CS performed the best at recovering peak intensities and reproducing the true classifying features for an OPLS-DA model regardless of spectral noise level. Our findings suggest that performance is largely determined by the level of noise in the dataset, while the effect of dilution factors was negligible. A minimal allowable noise level of 20% was also identified for a valid NMR metabolomics dataset.

Metabolomics Uncovers the Regulatory Pathway of Acyl-homoserine Lactones Based Quorum Sensing in Anammox Consortia

Acyl-homoserine lactones (AHLs)-mediated quorum sensing in bacterial communities have been extensively observed. However, the metabolic pathways regulated by AHLs in bacteria remain elusive. Here, we combined long-term reactor operation with microbiological and metabolomics analyses to explore the regulatory pathways for different AHLs in anammox consortia, which perform promising nitrogen removal for wastewater treatment. The results showed that no obvious shifts induced by exogenous AHLs occurred in the microbial community and, mainly, dosing AHLs induced changes in the metabolites. 3OC6-HSL, C6-HSL, and C8-HSL controlled the electron transport carriers that influence the bacterial activity. In contrast, only 3OC6-HSL regulated LysoPC(20:0) metabolism, which affected bacterial growth. AHLs mainly regulated the synthesis of the amino acids Ala, Val, and Glu and selectively regulated Asp and Leu to affect extracellular proteins. Simultaneously, all the AHLs regulated the ManNAc biosynthetic pathways, while OC6-HSL, OC8-HSL, and C6-HSL particularly enriched the UDP-GlcNAc pathway to promote exopolysaccharides, resulting in different aggregation levels of the anammox consortia. Our results not only provide the first metabolic insights into the means by which AHLs affect anammox consortia but also hint at potential strategies for overcoming the limitations of the long start-up period required for wastewater treatment by anammox processing.

Metabolic Mitigation of Staphylococcus aureus Vancomycin Intermediate-Level Susceptibility

Staphylococcus aureus is a major human pathogen whose infections are increasingly difficult to treat due to increased antibiotic resistance, including resistance to vancomycin. Vancomycin-intermediate S. aureus (VISA) strains develop resistance to vancomycin through adaptive changes that are incompletely understood. Central to this adaptation are metabolic changes that permit growth in the presence of vancomycin. To define the metabolic changes associated with adaptive resistance to vancomycin in S. aureus, the metabolomes of a vancomycin-sensitive and VISA strain pair isolated from the same patient shortly after vancomycin therapy began and following vancomycin treatment failure were analyzed. The metabolic adaptations included increases in acetogenesis, carbon flow through the pentose phosphate pathway, wall teichoic acid and peptidoglycan precursor biosynthesis, purine biosynthesis, and decreased tricarboxylic acid (TCA) cycle activity. The significance of these metabolic pathways for vancomycin-intermediate susceptibility was determined by assessing the synergistic potential of human-use-approved inhibitors of these pathways in combination with vancomycin against VISA strains. Importantly, inhibitors of amino sugar and purine biosynthesis acted synergistically with vancomycin to kill a diverse set of VISA strains, suggesting that combinatorial therapy could augment the efficacy of vancomycin even in patients infected with VISA strains.

GPR55 receptor antagonist decreases glycolytic activity in PANC-1 pancreatic cancer cell line and tumor xenografts

The Warburg effect is a predominant metabolic pathway in cancer cells characterized by enhanced glucose uptake and its conversion to l-lactate and is associated with upregulated expression of HIF-1α and activation of the EGFR-MEK-ERK, Wnt-β-catenin, and PI3K-AKT signaling pathways. (R,R')-4'-methoxy-1-naphthylfenoterol ((R,R')-MNF) significantly reduces proliferation, survival, and motility of PANC-1 pancreatic cancer cells through inhibition of the GPR55 receptor. We examined (R,R')-MNF's effect on glycolysis in PANC-1 cells and tumors. Global NMR metabolomics was used to elucidate differences in the metabolome between untreated and (R,R')-MNF-treated cells. LC/MS analysis was used to quantify intracellular concentrations of β-hydroxybutyrate, carnitine, and l-lactate. Changes in target protein expression were determined by Western blot analysis. Data was also obtained from mouse PANC-1 tumor xenografts after administration of (R,R')-MNF. Metabolomics data indicate that (R,R')-MNF altered fatty acid metabolism, energy metabolism, and amino acid metabolism and increased intracellular concentrations of β-hydroxybutyrate and carnitine while reducing l-lactate content. The cellular content of phosphoinositide-dependent kinase-1 and hexokinase 2 was reduced consistent with diminished PI3K-AKT signaling and glucose metabolism. The presence of the GLUT8 transporter was established and found to be attenuated by (R,R')-MNF. Mice treated with (R,R')-MNF had significant accumulation of l-lactate in tumor tissue relative to vehicle-treated mice, together with reduced levels of the selective l-lactate transporter MCT4. Lower intratumoral levels of EGFR, pyruvate kinase M2, β-catenin, hexokinase 2, and p-glycoprotein were also observed. The data suggest that (R,R')-MNF reduces glycolysis in PANC-1 cells and tumors through reduced expression and function at multiple controlling sites in the glycolytic pathway.

Fast 2D NMR Spectroscopy for In vivo Monitoring of Bacterial Metabolism in Complex Mixtures

The biological toolbox is full of techniques developed originally for analytical chemistry. Among them, spectroscopic experiments are very important source of atomic-level structural information. Nuclear magnetic resonance (NMR) spectroscopy, although very advanced in chemical and biophysical applications, has been used in microbiology only in a limited manner. So far, mostly one-dimensional ¹H experiments have been reported in studies of bacterial metabolism monitored in situ. However, low spectral resolution and limited information on molecular topology limits the usability of these methods. These problems are particularly evident in the case of complex mixtures, where spectral peaks originating from many compounds overlap and make the interpretation of changes in a spectrum difficult or even impossible. Often a suite of two-dimensional (2D) NMR experiments is used to improve resolution and extract structural information from internuclear correlations. However, for dynamically changing sample, like bacterial culture, the time-consuming sampling of so-called indirect time dimensions in 2D experiments is inefficient. Here, we propose the technique known from analytical chemistry and structural biology of proteins, i.e., time-resolved non-uniform sampling. The method allows application of 2D (and multi-D) experiments in the case of quickly varying samples. The indirect dimension here is sparsely sampled resulting in significant reduction of experimental time. Compared to conventional approach based on a series of 1D measurements, this method provides extraordinary resolution and is a real-time approach to process monitoring. In this study, we demonstrate the usability of the method on a sample of Escherichia coli culture affected by ampicillin and on a sample of Propionibacterium acnes, an acne causing bacterium, mixed with a dose of face tonic, which is a complicated, multi-component mixture providing complex NMR spectrum. Through our experiments we determine the exact concentration and time at which the anti-bacterial agents affect the bacterial metabolism. We show, that it is worth to extend the NMR toolbox for microbiology by including techniques of 2D z-TOCSY, for total "fingerprinting" of a sample and 2D ¹³C-edited HSQC to monitor changes in concentration of metabolites in selected metabolic pathways.

Metabolic Investigations of the Molecular Mechanisms Associated with Parkinson's Disease

Parkinson’s disease (PD) is a neurodegenerative disorder characterized by fibrillar cytoplasmic aggregates of α-synuclein (i.e., Lewy bodies) and the associated loss of dopaminergic cells in the substantia nigra. Mutations in genes such as α-synuclein (SNCA) account for only 10% of PD occurrences. Exposure to environmental toxicants including pesticides and metals (e.g., paraquat (PQ) and manganese (Mn)) is also recognized as an important PD risk factor. Thus, aging, genetic alterations, and environmental factors all contribute to the etiology of PD. In fact, both genetic and environmental factors are thought to interact in the promotion of idiopathic PD, but the mechanisms involved are still unclear. In this study, we summarize our findings to date regarding the toxic synergistic effect between α-synuclein and paraquat treatment. We identified an essential role for central carbon (glucose) metabolism in dopaminergic cell death induced by paraquat treatment that is enhanced by the overexpression of α-synuclein. PQ “hijacks” the pentose phosphate pathway (PPP) to increase NADPH reducing equivalents and stimulate paraquat redox cycling, oxidative stress, and cell death. PQ also stimulated an increase in glucose uptake, the translocation of glucose transporters to the plasma membrane, and AMP-activated protein kinase (AMPK) activation. The overexpression of α-synuclein further stimulated an increase in glucose uptake and AMPK activity, but impaired glucose metabolism, likely directing additional carbon to the PPP to supply paraquat redox cycling.

Beyond the paradigm: Combining mass spectrometry and nuclear magnetic resonance for metabolomics

Metabolomics is undergoing tremendous growth and is being employed to solve a diversity of biological problems from environmental issues to the identification of biomarkers for human diseases. Nuclear magnetic resonance (NMR) and mass spectrometry (MS) are the analytical tools that are routinely, but separately, used to obtain metabolomics data sets due to their versatility, accessibility, and unique strengths. NMR requires minimal sample handling without the need for chromatography, is easily quantitative, and provides multiple means of metabolite identification, but is limited to detecting the most abundant metabolites (⩾1μM). Conversely, mass spectrometry has the ability to measure metabolites at very low concentrations (femtomolar to attomolar) and has a higher resolution (∼10³-10⁴) and dynamic range (∼10³-10⁴), but quantitation is a challenge and sample complexity may limit metabolite detection because of ion suppression. Consequently, liquid chromatography (LC) or gas chromatography (GC) is commonly employed in conjunction with MS, but this may lead to other sources of error. As a result, NMR and mass spectrometry are highly complementary, and combining the two techniques is likely to improve the overall quality of a study and enhance the coverage of the metabolome. While the majority of metabolomic studies use a single analytical source, there is a growing appreciation of the inherent value of combining NMR and MS for metabolomics. An overview of the current state of utilizing both NMR and MS for metabolomics will be presented.

Assessment of Metabolic Changes in Mycobacterium smegmatis Wild-Type and alr Mutant Strains: Evidence of a New Pathway of d-Alanine Biosynthesis

In mycobacteria, d-alanine is an essential precursor for peptidoglycan biosynthesis. The only confirmed enzymatic pathway to form d-alanine is through the racemization of l-alanine by alanine racemase (Alr, EC 5.1.1.1). Nevertheless, the essentiality of Alr in Mycobacterium tuberculosis and Mycobacterium smegmatis for cell survivability in the absence of d-alanine has been a point of controversy with contradictory results reported in the literature. To address this issue, we examined the effects of alr inactivation on the cellular metabolism of M. smegmatis. The M. smegmatis alr insertion mutant TAM23 exhibited essentially identical growth to wild-type mc²155 in the absence of d-alanine. NMR metabolomics revealed drastically distinct phenotypes between mc²155 and TAM23. A metabolic switch was observed for TAM23 as a function of supplemented d-alanine. In the absence of d-alanine, the metabolic response directed carbon through an unidentified transaminase to provide the essential d-alanine required for survival. The process is reversed when d-alanine is available, in which the d-alanine is directed to peptidoglycan biosynthesis. Our results provide further support for the hypothesis that Alr is not an essential function of M. smegmatis and that specific Alr inhibitors will have no bactericidal action.

The future of NMR-based metabolomics

The two leading analytical approaches to metabolomics are mass spectrometry (MS) and nuclear magnetic resonance (NMR) spectroscopy. Although currently overshadowed by MS in terms of numbers of compounds resolved, NMR spectroscopy offers advantages both on its own and coupled with MS. NMR data are highly reproducible and quantitative over a wide dynamic range and are unmatched for determining structures of unknowns. NMR is adept at tracing metabolic pathways and fluxes using isotope labels. Moreover, NMR is non-destructive and can be utilized in vivo. NMR results have a proven track record of translating in vitro findings to in vivo clinical applications.

Redox Imbalance Underlies the Fitness Defect Associated with Inactivation of the Pta-AckA Pathway in Staphylococcus aureus

The phosphotransacetylase-acetate kinase (Pta-AckA) pathway is thought to be a vital ATP generating pathway for Staphylococcus aureus. Disruption of the Pta-AckA pathway during overflow metabolism causes significant reduction in growth rate and viability, albeit not due to intracellular ATP depletion. Here, we demonstrate that toxicity associated with inactivation of the Pta-AckA pathway resulted from an altered intracellular redox environment. Growth of the pta and ackA mutants under anaerobic conditions partially restored cell viability. NMR metabolomics analyses and (13)C6-glucose metabolism tracing experiments revealed the activity of multiple pathways that promote redox (NADH/NAD(+)) turnover to be enhanced in the pta and ackA mutants during anaerobic growth. Restoration of redox homeostasis in the pta mutant by overexpressing l- lactate dehydrogenase partially restored its viability under aerobic conditions. Together, our findings suggest that during overflow metabolism, the Pta-AckA pathway plays a critical role in preventing cell viability defects by promoting intracellular redox homeostasis.

Nanoparticle-Assisted Removal of Protein in Human Serum for Metabolomics Studies

Among human body fluids, serum plays a key role for diagnostic tests and, increasingly, for metabolomics analysis. However, the high protein content of serum poses significant challenges for nuclear magnetic resonance (NMR)-based metabolomics studies because it can strongly interfere with metabolite signal detection and quantitation. Although several methods for protein removal have been proposed, including ultrafiltration and organic-solvent-induced protein precipitation, there is currently no standard operating procedure for the elimination of protein from human serum samples. Here, we introduce novel procedures for the removal of protein from serum by the addition of nanoparticles. It is demonstrated how serum protein can be efficiently, cost-effectively, and environmentally friendly removed at physiological pH (pH 7.4) through attractive interactions with silica nanoparticles. It is further shown how serum can be processed with nanoparticles prior to ultrafiltration or organic-solvent-induced protein precipitation for optimal protein removal. After examination of all of the procedures, the combination of nanoparticle treatment and ultrafiltration is found to have a minimal effect on the metabolite content, leading to remarkably clean homo- and heteronuclear NMR spectra of the serum metabolome that compare favorably to other methods for protein removal.

Staphylococcus aureus metabolic adaptations during the transition from a daptomycin susceptibility phenotype to a daptomycin nonsusceptibility phenotype

Staphylococcus aureus is a major cause of nosocomial and community-acquired infections. The success of S. aureus as a pathogen is due in part to its many virulence determinants and resistance to antimicrobials. In particular, methicillin-resistant S. aureus has emerged as a major cause of infections and led to increased use of the antibiotics vancomycin and daptomycin, which has increased the isolation of vancomycin-intermediate S. aureus and daptomycin-nonsusceptible S. aureus strains. The most common mechanism by which S. aureus acquires intermediate resistance to antibiotics is by adapting its physiology and metabolism to permit growth in the presence of these antibiotics, a process known as adaptive resistance. To better understand the physiological and metabolic changes associated with adaptive resistance, six daptomycin-susceptible and -nonsusceptible isogenic strain pairs were examined for changes in growth, competitive fitness, and metabolic alterations. Interestingly, daptomycin nonsusceptibility coincides with a slightly delayed transition to the postexponential growth phase and alterations in metabolism. Specifically, daptomycin-nonsusceptible strains have decreased tricarboxylic acid cycle activity, which correlates with increased synthesis of pyrimidines and purines and increased carbon flow to pathways associated with wall teichoic acid and peptidoglycan biosynthesis. Importantly, these data provided an opportunity to alter the daptomycin nonsusceptibility phenotype by manipulating bacterial metabolism, a first step in developing compounds that target metabolic pathways that can be used in combination with daptomycin to reduce treatment failures.

Combining DI-ESI-MS and NMR datasets for metabolic profiling

Metabolomics datasets are commonly acquired by either mass spectrometry (MS) or nuclear magnetic resonance spectroscopy (NMR), despite their fundamental complementarity. In fact, combining MS and NMR datasets greatly improves the coverage of the metabolome and enhances the accuracy of metabolite identification, providing a detailed and high-throughput analysis of metabolic changes due to disease, drug treatment, or a variety of other environmental stimuli. Ideally, a single metabolomics sample would be simultaneously used for both MS and NMR analyses, minimizing the potential for variability between the two datasets. This necessitates the optimization of sample preparation, data collection and data handling protocols to effectively integrate direct-infusion MS data with one-dimensional (1D) 1H NMR spectra. To achieve this goal, we report for the first time the optimization of (i) metabolomics sample preparation for dual analysis by NMR and MS, (ii) high throughput, positive-ion direct infusion electrospray ionization mass spectrometry (DI-ESI-MS) for the analysis of complex metabolite mixtures, and (iii) data handling protocols to simultaneously analyze DI-ESI-MS and 1D 1H NMR spectral data using multiblock bilinear factorizations, namely multiblock principal component analysis (MB-PCA) and multiblock partial least squares (MB-PLS). Finally, we demonstrate the combined use of backscaled loadings, accurate mass measurements and tandem MS experiments to identify metabolites significantly contributing to class separation in MB-PLS-DA scores. We show that integration of NMR and DI-ESI-MS datasets yields a substantial improvement in the analysis of neurotoxin involvement in dopaminergic cell death.

Metabolic reprogramming induced by ketone bodies diminishes pancreatic cancer cachexia

Background

Aberrant energy metabolism is a hallmark of cancer. To fulfill the increased energy requirements, tumor cells secrete cytokines/factors inducing muscle and fat degradation in cancer patients, a condition known as cancer cachexia. It accounts for nearly 20% of all cancer-related deaths. However, the mechanistic basis of cancer cachexia and therapies targeting cancer cachexia thus far remain elusive. A ketogenic diet, a high-fat and low-carbohydrate diet that elevates circulating levels of ketone bodies (i.e., acetoacetate, β-hydroxybutyrate, and acetone), serves as an alternative energy source. It has also been proposed that a ketogenic diet leads to systemic metabolic changes. Keeping in view the significant role of metabolic alterations in cancer, we hypothesized that a ketogenic diet may diminish glycolytic flux in tumor cells to alleviate cachexia syndrome and, hence, may provide an efficient therapeutic strategy.

Results

We observed reduced glycolytic flux in tumor cells upon treatment with ketone bodies. Ketone bodies also diminished glutamine uptake, overall ATP content, and survival in multiple pancreatic cancer cell lines, while inducing apoptosis. A decrease in levels of c-Myc, a metabolic master regulator, and its recruitment on glycolytic gene promoters, was in part responsible for the metabolic phenotype in tumor cells. Ketone body-induced intracellular metabolomic reprogramming in pancreatic cancer cells also leads to a significantly diminished cachexia in cell line models. Our mouse orthotopic xenograft models further confirmed the effect of a ketogenic diet in diminishing tumor growth and cachexia.

Conclusions

Thus, our studies demonstrate that the cachectic phenotype is in part due to metabolic alterations in tumor cells, which can be reverted by a ketogenic diet, causing reduced tumor growth and inhibition of muscle and body weight loss.

MVAPACK: a complete data handling package for NMR metabolomics

Data handling in the field of NMR metabolomics has historically been reliant on either in-house mathematical routines or long chains of expensive commercial software. Thus, while the relatively simple biochemical protocols of metabolomics maintain a low barrier to entry, new practitioners of metabolomics experiments are forced to either purchase expensive software packages or craft their own data handling solutions from scratch. This inevitably complicates the standardization and communication of data handling protocols in the field. We report a newly developed open-source platform for complete NMR metabolomics data handling, MVAPACK, and describe its application on an example metabolic fingerprinting data set.

Influence of iron and aeration on Staphylococcus aureus growth, metabolism, and transcription

Staphylococcus aureus is a prominent nosocomial pathogen and a major cause of biomaterial-associated infections. The success of S. aureus as a pathogen is due in part to its ability to adapt to stressful environments. As an example, the transition from residing in the nares to residing in the blood or deeper tissues is accompanied by changes in the availability of nutrients and elements such as oxygen and iron. As such, nutrients, oxygen, and iron are important determinants of virulence factor synthesis in S. aureus. In addition to influencing virulence factor synthesis, oxygen and iron are critical cofactors in enzymatic and electron transfer reactions; thus, a change in iron or oxygen availability alters the bacterial metabolome. Changes in metabolism create intracellular signals that alter the activity of metabolite-responsive regulators such as CodY, RpiRc, and CcpA. To assess the extent of metabolomic changes associated with oxygen and iron limitation, S. aureus cells were cultivated in iron-limited medium and/or with decreasing aeration, and the metabolomes were examined by nuclear magnetic resonance (NMR) spectroscopy. As expected, oxygen and iron limitation dramatically decreased tricarboxylic acid (TCA) cycle activity, creating a metabolic block and significantly altering the metabolome. These changes were most prominent during post-exponential-phase growth, when TCA cycle activity was maximal. Importantly, many of the effects of iron limitation were obscured by aeration limitation. Aeration limitation not only obscured the metabolic effects of iron limitation but also overrode the transcription of iron-regulated genes. Finally, in contrast to previous speculation, we confirmed that acidification of the culture medium occurs independent of the availability of iron.

The current state of drug discovery and a potential role for NMR metabolomics

The pharmaceutical industry has significantly contributed to improving human health. Drugs have been attributed to both increasing life expectancy and decreasing health care costs. Unfortunately, there has been a recent decline in the creativity and productivity of the pharmaceutical industry. This is a complex issue with many contributing factors resulting from the numerous mergers, increase in out-sourcing, and the heavy dependency on high-throughput screening (HTS). While a simple solution to such a complex problem is unrealistic and highly unlikely, the inclusion of metabolomics as a routine component of the drug discovery process may provide some solutions to these problems. Specifically, as the binding affinity of a chemical lead is evolved during the iterative structure-based drug design process, metabolomics can provide feedback on the selectivity and the in vivo mechanism of action. Similarly, metabolomics can be used to evaluate and validate HTS leads. In effect, metabolomics can be used to eliminate compounds with potential efficacy and side effect problems while prioritizing well-behaved leads with druglike characteristics.

Catabolite control protein E (CcpE) is a LysR-type transcriptional regulator of tricarboxylic acid cycle activity in Staphylococcus aureus

The tricarboxylic acid cycle (TCA cycle) is a central metabolic pathway that provides energy, reducing potential, and biosynthetic intermediates. In Staphylococcus aureus, TCA cycle activity is controlled by several regulators (e.g. CcpA, CodY, and RpiRc) in response to the availability of sugars, amino acids, and environmental stress. Developing a bioinformatic search for additional carbon catabolite-responsive regulators in S. aureus, we identified a LysR-type regulator, catabolite control protein E (CcpE), with homology to the Bacillus subtilis CcpC regulator. Inactivation of ccpE in S. aureus strain Newman revealed that CcpE is a positive transcriptional effector of the first two enzymes of the TCA cycle, aconitase (citB) and to a lesser extent citrate synthase (citZ). Consistent with the transcriptional data, aconitase activity dramatically decreased in the ccpE mutant relative to the wild-type strain. The effect of ccpE inactivation on citB transcription and the lesser effect on citZ transcription were also reflected in electrophoretic mobility shift assays where CcpE bound to the citB promoter but not the citZ promoter. Metabolomic studies showed that inactivation of ccpE resulted in increased intracellular concentrations of acetate, citrate, lactate, and alanine, consistent with a redirection of carbon away from the TCA cycle. Taken together, our data suggest that CcpE is a major direct positive regulator of the TCA cycle gene citB.