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Metabolites, Volume 7, Issue 4 (December 2017)

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Cover Story Sepsis represents a severe immune dysregulation, secondary to systemic infection. The burden of [...] Read more.
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Research

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Open AccessArticle Specificities of Human Hepatocellular Carcinoma Developed on Non-Alcoholic Fatty Liver Disease in Absence of Cirrhosis Revealed by Tissue Extracts 1H-NMR Spectroscopy
Metabolites 2017, 7(4), 49; doi:10.3390/metabo7040049
Received: 29 August 2017 / Revised: 18 September 2017 / Accepted: 20 September 2017 / Published: 22 September 2017
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Abstract
There is a rising incidence of non-alcoholic fatty liver disease (NAFLD) as well as of the frequency of Hepato-Cellular Carcinoma (HCC) associated with NAFLD. To seek for putative metabolic pathways specific of the NAFLD etiology, we performed comparative metabolomics between HCC associated
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There is a rising incidence of non-alcoholic fatty liver disease (NAFLD) as well as of the frequency of Hepato-Cellular Carcinoma (HCC) associated with NAFLD. To seek for putative metabolic pathways specific of the NAFLD etiology, we performed comparative metabolomics between HCC associated with NAFLD and HCC associated with cirrhosis. The study included 28 pairs of HCC tissue versus distant Non-Tumoral Tissue (NTT) collected from patients undergoing hepatectomy. HCC was associated with cirrhosis (n = 9), normal liver (n = 6) and NAFLD (n = 13). Metabolomics was performed using 1H-NMR Spectroscopy on tissue extracts and combined to multivariate statistical analysis. In HCC compared to NTT, statistical models showed high levels of lactate and phosphocholine, and low level of glucose. Shared and Unique Structures (SUS) plots were performed to remove the impact of underlying disease on the metabolic profile of HCC. HCC-cirrhosis was characterized by high levels of β-hydroxybutyrate, tyrosine, phenylalanine and histidine whereas HCC-NAFLD was characterized by high levels of glutamine/glutamate. In addition, the overexpression glutamine/glutamate on HCC-NAFLD was confirmed by both Glutamine Synthetase (GS) immuno-staining and NMR-spectroscopy glutamine quantification. This study provides evidence of metabolic specificities of HCC associated with non-cirrhotic NAFLD versus HCC associated with cirrhosis. These alterations could suggest activation of glutamine synthetase pathway in HCC-NAFLD and mitochondrial dysfunction in HCC-cirrhosis, that may be part of specific carcinogenic processes. Full article
(This article belongs to the Special Issue Metabolomics and Its Application in Human Diseases)
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Open AccessArticle Exometabolomic Analysis of Cross-Feeding Metabolites
Metabolites 2017, 7(4), 50; doi:10.3390/metabo7040050
Received: 12 September 2017 / Revised: 1 October 2017 / Accepted: 2 October 2017 / Published: 4 October 2017
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Abstract
Microbial consortia have the potential to perform complex, industrially important tasks. The design of microbial consortia requires knowledge of the substrate preferences and metabolic outputs of each member, to allow understanding of potential interactions such as competition and beneficial metabolic exchange. Here, we
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Microbial consortia have the potential to perform complex, industrially important tasks. The design of microbial consortia requires knowledge of the substrate preferences and metabolic outputs of each member, to allow understanding of potential interactions such as competition and beneficial metabolic exchange. Here, we used exometabolite profiling to follow the resource processing by a microbial co-culture of two biotechnologically relevant microbes, the bacterial cellulose degrader Cellulomonas fimi, and the oleaginous yeast Yarrowia lipolytica. We characterized the substrate preferences of the two strains on compounds typically found in lignocellulose hydrolysates. This allowed prediction that specific sugars resulting from hemicellulose polysaccharide degradation by C. fimi may serve as a cross-feeding metabolites to Y. lipolytica in co-culture. We also showed that products of ionic liquid-treated switchgrass lignocellulose degradation by C. fimi were channeled to Y. lipolytica in a co-culture. Additionally, we observed metabolites, such as shikimic acid accumulating in the co-culture supernatants, suggesting the potential for producing interesting co-products. Insights gained from characterizing the exometabolite profiles of individual and co-cultures of the two strains can help to refine this interaction, and guide strategies for making this an industrially viable co-culture to produce valuable products from lignocellulose material. Full article
(This article belongs to the Special Issue Environmental Metabolomics)
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Open AccessArticle Robust Regression Analysis of GCMS Data Reveals Differential Rewiring of Metabolic Networks in Hepatitis B and C Patients
Metabolites 2017, 7(4), 51; doi:10.3390/metabo7040051
Received: 11 September 2017 / Revised: 30 September 2017 / Accepted: 5 October 2017 / Published: 8 October 2017
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Abstract
About one in 15 of the world’s population is chronically infected with either hepatitis virus B (HBV) or C (HCV), with enormous public health consequences. The metabolic alterations caused by these infections have never been directly compared and contrasted. We investigated groups of
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About one in 15 of the world’s population is chronically infected with either hepatitis virus B (HBV) or C (HCV), with enormous public health consequences. The metabolic alterations caused by these infections have never been directly compared and contrasted. We investigated groups of HBV-positive, HCV-positive, and uninfected healthy controls using gas chromatography-mass spectrometry analyses of their plasma and urine. A robust regression analysis of the metabolite data was conducted to reveal correlations between metabolite pairs. Ten metabolite correlations appeared for HBV plasma and urine, with 18 for HCV plasma and urine, none of which were present in the controls. Metabolic perturbation networks were constructed, which permitted a differential view of the HBV- and HCV-infected liver. HBV hepatitis was consistent with enhanced glucose uptake, glycolysis, and pentose phosphate pathway metabolism, the latter using xylitol and producing threonic acid, which may also be imported by glucose transporters. HCV hepatitis was consistent with impaired glucose uptake, glycolysis, and pentose phosphate pathway metabolism, with the tricarboxylic acid pathway fueled by branched-chain amino acids feeding gluconeogenesis and the hepatocellular loss of glucose, which most probably contributed to hyperglycemia. It is concluded that robust regression analyses can uncover metabolic rewiring in disease states. Full article
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Open AccessArticle Bacterial Substrate Transformation Tracked by Stable-Isotope-Guided NMR Metabolomics: Application in a Natural Aquatic Microbial Community
Metabolites 2017, 7(4), 52; doi:10.3390/metabo7040052
Received: 12 September 2017 / Revised: 8 October 2017 / Accepted: 16 October 2017 / Published: 19 October 2017
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Abstract
The transformation of organic substrates by heterotrophic bacteria in aquatic environments constitutes one of the key processes in global material cycles. The development of procedures that would enable us to track the wide range of organic compounds transformed by aquatic bacteria would greatly
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The transformation of organic substrates by heterotrophic bacteria in aquatic environments constitutes one of the key processes in global material cycles. The development of procedures that would enable us to track the wide range of organic compounds transformed by aquatic bacteria would greatly improve our understanding of material cycles. In this study, we examined the applicability of nuclear magnetic resonance spectroscopy coupled with stable-isotope labeling to the investigation of metabolite transformation in a natural aquatic bacterial community. The addition of a model substrate (13C6–glucose) to a coastal seawater sample and subsequent incubation resulted in the detection of >200 peaks and the assignment of 22 metabolites from various chemical classes, including amino acids, dipeptides, organic acids, nucleosides, nucleobases, and amino alcohols, which had been identified as transformed from the 13C6–glucose. Additional experiments revealed large variability in metabolite transformation and the key compounds, showing the bacterial accumulation of glutamate over the incubation period, and that of 3-hydroxybutyrate with increasing concentrations of 13C6–glucose added. These results suggest the potential ability of our approach to track substrate transformation in aquatic bacterial communities. Further applications of this procedure may provide substantial insights into the metabolite dynamics in aquatic environments. Full article
(This article belongs to the Special Issue Isotope Guided Metabolomics and Flux Analysis)
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Open AccessArticle Modelling of Hydrophilic Interaction Liquid Chromatography Stationary Phases Using Chemometric Approaches
Metabolites 2017, 7(4), 54; doi:10.3390/metabo7040054
Received: 15 July 2017 / Revised: 11 October 2017 / Accepted: 21 October 2017 / Published: 24 October 2017
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Abstract
Metabolomics is a powerful and widely used approach that aims to screen endogenous small molecules (metabolites) of different families present in biological samples. The large variety of compounds to be determined and their wide diversity of physical and chemical properties have promoted the
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Metabolomics is a powerful and widely used approach that aims to screen endogenous small molecules (metabolites) of different families present in biological samples. The large variety of compounds to be determined and their wide diversity of physical and chemical properties have promoted the development of different types of hydrophilic interaction liquid chromatography (HILIC) stationary phases. However, the selection of the most suitable HILIC stationary phase is not straightforward. In this work, four different HILIC stationary phases have been compared to evaluate their potential application for the analysis of a complex mixture of metabolites, a situation similar to that found in non-targeted metabolomics studies. The obtained chromatographic data were analyzed by different chemometric methods to explore the behavior of the considered stationary phases. ANOVA-simultaneous component analysis (ASCA), principal component analysis (PCA) and partial least squares regression (PLS) were used to explore the experimental factors affecting the stationary phase performance, the main similarities and differences among chromatographic conditions used (stationary phase and pH) and the molecular descriptors most useful to understand the behavior of each stationary phase. Full article
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Open AccessArticle Metabolic Profile of the Cellulolytic Industrial Actinomycete Thermobifida fusca
Metabolites 2017, 7(4), 57; doi:10.3390/metabo7040057
Received: 30 September 2017 / Revised: 3 November 2017 / Accepted: 8 November 2017 / Published: 11 November 2017
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Abstract
Actinomycetes have a long history of being the source of numerous valuable natural products and medicinals. To expedite product discovery and optimization of biochemical production, high-throughput technologies can now be used to screen the library of compounds present (or produced) at a given
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Actinomycetes have a long history of being the source of numerous valuable natural products and medicinals. To expedite product discovery and optimization of biochemical production, high-throughput technologies can now be used to screen the library of compounds present (or produced) at a given time in an organism. This not only facilitates chemical product screening, but also provides a comprehensive methodology to the study cellular metabolic networks to inform cellular engineering. Here, we present some of the first metabolomic data of the industrial cellulolytic actinomycete Thermobifida fusca generated using LC-MS/MS. The underlying objective of conducting global metabolite profiling was to gain better insight on the innate capabilities of T. fusca, with a long-term goal of facilitating T. fusca-based bioprocesses. The T. fusca metabolome was characterized for growth on two cellulose-relevant carbon sources, cellobiose and Avicel. Furthermore, the comprehensive list of measured metabolites was computationally integrated into a metabolic model of T. fusca, to study metabolic shifts in the network flux associated with carbohydrate and amino acid metabolism. Full article
(This article belongs to the Special Issue Metabolic Network Models Volume 2)
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Open AccessArticle Metabolomic Modularity Analysis (MMA) to Quantify Human Liver Perfusion Dynamics
Metabolites 2017, 7(4), 58; doi:10.3390/metabo7040058
Received: 18 August 2017 / Revised: 24 October 2017 / Accepted: 8 November 2017 / Published: 13 November 2017
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Abstract
Large-scale -omics data are now ubiquitously utilized to capture and interpret global responses to perturbations in biological systems, such as the impact of disease states on cells, tissues, and whole organs. Metabolomics data, in particular, are difficult to interpret for providing physiological insight
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Large-scale -omics data are now ubiquitously utilized to capture and interpret global responses to perturbations in biological systems, such as the impact of disease states on cells, tissues, and whole organs. Metabolomics data, in particular, are difficult to interpret for providing physiological insight because predefined biochemical pathways used for analysis are inherently biased and fail to capture more complex network interactions that span multiple canonical pathways. In this study, we introduce a nov-el approach coined Metabolomic Modularity Analysis (MMA) as a graph-based algorithm to systematically identify metabolic modules of reactions enriched with metabolites flagged to be statistically significant. A defining feature of the algorithm is its ability to determine modularity that highlights interactions between reactions mediated by the production and consumption of cofactors and other hub metabolites. As a case study, we evaluated the metabolic dynamics of discarded human livers using time-course metabolomics data and MMA to identify modules that explain the observed physiological changes leading to liver recovery during subnormothermic machine perfusion (SNMP). MMA was performed on a large scale liver-specific human metabolic network that was weighted based on metabolomics data and identified cofactor-mediated modules that would not have been discovered by traditional metabolic pathway analyses. Full article
(This article belongs to the Special Issue Metabolomics Modelling)
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Open AccessArticle Cell-Type Specific Metabolic Flux Analysis: A Challenge for Metabolic Phenotyping and a Potential Solution in Plants
Metabolites 2017, 7(4), 59; doi:10.3390/metabo7040059
Received: 27 September 2017 / Revised: 9 November 2017 / Accepted: 10 November 2017 / Published: 13 November 2017
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Abstract
Stable isotope labelling experiments are used routinely in metabolic flux analysis (MFA) to determine the metabolic phenotype of cells and tissues. A complication arises in multicellular systems because single cell measurements of transcriptomes, proteomes and metabolomes in multicellular organisms suggest that the metabolic
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Stable isotope labelling experiments are used routinely in metabolic flux analysis (MFA) to determine the metabolic phenotype of cells and tissues. A complication arises in multicellular systems because single cell measurements of transcriptomes, proteomes and metabolomes in multicellular organisms suggest that the metabolic phenotype will differ between cell types. In silico analysis of simulated metabolite isotopomer datasets shows that cellular heterogeneity confounds conventional MFA because labelling data averaged over multiple cell types does not necessarily yield averaged flux values. A potential solution to this problem—the use of cell-type specific reporter proteins as a source of cell-type specific labelling data—is proposed and the practicality of implementing this strategy in the roots of Arabidopsis thaliana seedlings is explored. A protocol for the immunopurification of ectopically expressed green fluorescent protein (GFP) from Arabidopsis thaliana seedlings using a GFP-binding nanobody is developed, and through GC-MS analysis of protein hydrolysates it is established that constitutively expressed GFP reports accurately on the labelling of total protein in root tissues. It is also demonstrated that the constitutive expression of GFP does not perturb metabolism. The principal obstacle to the implementation of the method in tissues with cell-type specific GFP expression is the sensitivity of the GC-MS system. Full article
(This article belongs to the Special Issue Isotope Guided Metabolomics and Flux Analysis)
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Open AccessCommunication NMR-Based Identification of Metabolites in Polar and Non-Polar Extracts of Avian Liver
Metabolites 2017, 7(4), 61; doi:10.3390/metabo7040061
Received: 3 October 2017 / Revised: 7 November 2017 / Accepted: 8 November 2017 / Published: 16 November 2017
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Abstract
Metabolites present in liver provide important clues regarding the physiological state of an organism. The aim of this work was to evaluate a protocol for high-throughput NMR-based analysis of polar and non-polar metabolites from a small quantity of liver tissue. We extracted the
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Metabolites present in liver provide important clues regarding the physiological state of an organism. The aim of this work was to evaluate a protocol for high-throughput NMR-based analysis of polar and non-polar metabolites from a small quantity of liver tissue. We extracted the tissue with a methanol/chloroform/water mixture and isolated the polar metabolites from the methanol/water layer and the non-polar metabolites from the chloroform layer. Following drying, we re-solubilized the fractions for analysis with a 600 MHz NMR spectrometer equipped with a 1.7 mm cryogenic probe. In order to evaluate the feasibility of this protocol for metabolomics studies, we analyzed the metabolic profile of livers from house sparrow (Passer domesticus) nestlings raised on two different diets: livers from 10 nestlings raised on a high protein diet (HP) for 4 d and livers from 12 nestlings raised on the HP diet for 3 d and then switched to a high carbohydrate diet (HC) for 1 d. The protocol enabled the detection of 52 polar and nine non-polar metabolites in 1H NMR spectra of the extracts. We analyzed the lipophilic metabolites by one-way ANOVA to assess statistically significant concentration differences between the two groups. The results of our studies demonstrate that the protocol described here can be exploited for high-throughput screening of small quantities of liver tissue (approx. 100 mg wet mass) obtainable from small animals. Full article
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Open AccessArticle Metabolic Perturbations in a Bacillus subtilis clpP Mutant during Glucose Starvation
Metabolites 2017, 7(4), 63; doi:10.3390/metabo7040063
Received: 7 September 2017 / Revised: 19 November 2017 / Accepted: 21 November 2017 / Published: 24 November 2017
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Abstract
Proteolysis is essential for all living organisms to maintain the protein homeostasis and to adapt to changing environmental conditions. ClpP is the main protease in Bacillus subtilis, and forms complexes with different Clp ATPases. These complexes play crucial roles during heat stress,
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Proteolysis is essential for all living organisms to maintain the protein homeostasis and to adapt to changing environmental conditions. ClpP is the main protease in Bacillus subtilis, and forms complexes with different Clp ATPases. These complexes play crucial roles during heat stress, but also in sporulation or cell morphology. Especially enzymes of cell wall-, amino acid-, and nucleic acid biosynthesis are known substrates of the protease ClpP during glucose starvation. The aim of this study was to analyze the influence of a clpP mutation on the metabolism in different growth phases and to search for putative new ClpP substrates. Therefore, B. subtilis 168 cells and an isogenic ∆clpP mutant were cultivated in a chemical defined medium, and the metabolome was analyzed by a combination of 1H-NMR, HPLC-MS, and GC-MS. Additionally, the cell morphology was investigated by electron microscopy. The clpP mutant showed higher levels of most glycolytic metabolites, the intermediates of the citric acid cycle, amino acids, and peptidoglycan precursors when compared to the wild-type. A strong secretion of overflow metabolites could be detected in the exo-metabolome of the clpP mutant. Furthermore, a massive increase was observed for the teichoic acid metabolite CDP-glycerol in combination with a swelling of the cell wall. Our results show a recognizable correlation between the metabolome and the corresponding proteome data of B. subtilis clpP mutant. Moreover, our results suggest an influence of ClpP on Tag proteins that are responsible for teichoic acids biosynthesis. Full article
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Review

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Open AccessReview Analysis of Intracellular Metabolites from Microorganisms: Quenching and Extraction Protocols
Metabolites 2017, 7(4), 53; doi:10.3390/metabo7040053
Received: 1 September 2017 / Revised: 11 October 2017 / Accepted: 21 October 2017 / Published: 23 October 2017
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Abstract
Sample preparation is one of the most important steps in metabolome analysis. The challenges of determining microbial metabolome have been well discussed within the research community and many improvements have already been achieved in last decade. The analysis of intracellular metabolites is particularly
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Sample preparation is one of the most important steps in metabolome analysis. The challenges of determining microbial metabolome have been well discussed within the research community and many improvements have already been achieved in last decade. The analysis of intracellular metabolites is particularly challenging. Environmental perturbations may considerably affect microbial metabolism, which results in intracellular metabolites being rapidly degraded or metabolized by enzymatic reactions. Therefore, quenching or the complete stop of cell metabolism is a pre-requisite for accurate intracellular metabolite analysis. After quenching, metabolites need to be extracted from the intracellular compartment. The choice of the most suitable metabolite extraction method/s is another crucial step. The literature indicates that specific classes of metabolites are better extracted by different extraction protocols. In this review, we discuss the technical aspects and advancements of quenching and extraction of intracellular metabolite analysis from microbial cells. Full article
(This article belongs to the Special Issue Microbial Metabolomics Volume 2)
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Open AccessReview Parameters of the Endocannabinoid System as Novel Biomarkers in Sepsis and Septic Shock
Metabolites 2017, 7(4), 55; doi:10.3390/metabo7040055
Received: 11 October 2017 / Revised: 26 October 2017 / Accepted: 30 October 2017 / Published: 1 November 2017
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Abstract
Sepsis represents a dysregulated immune response to infection, with a continuum of severity progressing to septic shock. This dysregulated response generally follows a pattern by which an initial hyperinflammatory phase is followed by a state of sepsis-associated immunosuppression. Major challenges in improving sepsis
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Sepsis represents a dysregulated immune response to infection, with a continuum of severity progressing to septic shock. This dysregulated response generally follows a pattern by which an initial hyperinflammatory phase is followed by a state of sepsis-associated immunosuppression. Major challenges in improving sepsis care include developing strategies to ensure early and accurate identification and diagnosis of the disease process, improving our ability to predict outcomes and stratify patients, and the need for novel sepsis-specific treatments such as immunomodulation. Biomarkers offer promise with all three of these challenges and are likely also to be the solution to determining a patient’s immune status; something that is critical in guiding effective and safe immunomodulatory therapy. Currently available biomarkers used in sepsis lack sensitivity and specificity, among other significant shortcomings. The endocannabinoid system (ECS) is an emerging topic of research with evidence suggesting a ubiquitous presence on both central and peripheral tissues, including an intrinsic link with immune function. This review will first discuss the state of sepsis biomarkers and lack of available treatments, followed by an introduction to the ECS and a discussion of its potential to provide novel biomarkers and treatments. Full article
(This article belongs to the Special Issue Metabolomics and/or Biomarkers for Drug Discovery)
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Open AccessReview An Overview of the Bacterial Carbonic Anhydrases
Metabolites 2017, 7(4), 56; doi:10.3390/metabo7040056
Received: 25 October 2017 / Revised: 8 November 2017 / Accepted: 8 November 2017 / Published: 11 November 2017
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Abstract
Bacteria encode carbonic anhydrases (CAs, EC 4.2.1.1) belonging to three different genetic families, the α-, β-, and γ-classes. By equilibrating CO2 and bicarbonate, these metalloenzymes interfere with pH regulation and other crucial physiological processes of these organisms. The detailed investigations of many
[...] Read more.
Bacteria encode carbonic anhydrases (CAs, EC 4.2.1.1) belonging to three different genetic families, the α-, β-, and γ-classes. By equilibrating CO2 and bicarbonate, these metalloenzymes interfere with pH regulation and other crucial physiological processes of these organisms. The detailed investigations of many such enzymes from pathogenic and non-pathogenic bacteria afford the opportunity to design both novel therapeutic agents, as well as biomimetic processes, for example, for CO2 capture. Investigation of bacterial CA inhibitors and activators may be relevant for finding antibiotics with a new mechanism of action. Full article
(This article belongs to the Special Issue Carbonic Anhydrases and Metabolism)
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Open AccessReview Monitoring for Response to Antineoplastic Drugs: The Potential of a Metabolomic Approach
Metabolites 2017, 7(4), 60; doi:10.3390/metabo7040060
Received: 28 August 2017 / Revised: 9 October 2017 / Accepted: 13 November 2017 / Published: 16 November 2017
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Abstract
For most cancers, chemotherapeutic options are rapidly expanding, providing the oncologist with substantial choices. Therefore, there is a growing need to select the best systemic therapy, for any individual, that effectively halts tumor progression with minimal toxicity. Having the capability to predict benefit
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For most cancers, chemotherapeutic options are rapidly expanding, providing the oncologist with substantial choices. Therefore, there is a growing need to select the best systemic therapy, for any individual, that effectively halts tumor progression with minimal toxicity. Having the capability to predict benefit and to anticipate toxicity would be ideal, but remains elusive at this time. An alternative approach is an adaptive approach that involves close observation for treatment response and emergence of resistance. Currently, response to systemic therapy is estimated using radiographic tests. Unfortunately, radiographic estimates of response are imperfect and radiographic signs of response can be delayed. This is particularly problematic for targeted agents, as tumor shrinkage is often not apparent with these drugs. As a result, patients are exposed to prolonged courses of toxic drugs that may ultimately be found to be ineffective. A biomarker-based adaptive strategy that involves the serial analysis of the metabolome is attractive. The metabolome changes rapidly with changes in physiology. Changes in the circulating metabolome associated with various antineoplastic agents have been described, but further work will be required to understand what changes signify clinical benefit. We present an investigative approach for the discovery and validation of metabolomic response biomarkers, which consists of serial analysis of the metabolome and linkage of changes in the metabolome to measurable therapeutic benefit. Potential pitfalls in the development of metabolomic biomarkers of response and loss of response are reviewed. Full article
(This article belongs to the Special Issue Metabolomics and/or Biomarkers for Drug Discovery)
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Open AccessReview Computational Approaches for Integrative Analysis of the Metabolome and Microbiome
Metabolites 2017, 7(4), 62; doi:10.3390/metabo7040062
Received: 26 October 2017 / Revised: 14 November 2017 / Accepted: 16 November 2017 / Published: 18 November 2017
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Abstract
The study of the microbiome, the totality of all microbes inhabiting the host or an environmental niche, has experienced exponential growth over the past few years. The microbiome contributes functional genes and metabolites, and is an important factor for maintaining health. In this
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The study of the microbiome, the totality of all microbes inhabiting the host or an environmental niche, has experienced exponential growth over the past few years. The microbiome contributes functional genes and metabolites, and is an important factor for maintaining health. In this context, metabolomics is increasingly applied to complement sequencing-based approaches (marker genes or shotgun metagenomics) to enable resolution of microbiome-conferred functionalities associated with health. However, analyzing the resulting multi-omics data remains a significant challenge in current microbiome studies. In this review, we provide an overview of different computational approaches that have been used in recent years for integrative analysis of metabolome and microbiome data, ranging from statistical correlation analysis to metabolic network-based modeling approaches. Throughout the process, we strive to present a unified conceptual framework for multi-omics integration and interpretation, as well as point out potential future directions. Full article
(This article belongs to the Section Thematic Reviews)
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