A high-throughput method for microbial metabolome analysis using gas chromatography/mass spectrometry

Comprehensive analysis of transcriptome and metabolome analysis reveal new targets of Glaesserella parasuis glucose-specific enzyme IIBC (PtsG)

The ptsG (hpIIBC^Glc) gene, belonging to the glucose-specific phosphotransferase system, encodes the bacterial glucose-specific enzyme IIBC. In this study, the effects of a deletion of the ptsG gene were investigated by metabolome and transcriptome analyses. At the transcriptional level, we identified 970 differentially expressed genes between ΔptsG and sc1401 (Padj<0.05) and 2072 co-expressed genes. Among these genes, those involved in methane metabolism, amino sugar and nucleotide sugar metabolism, starch and sucrose metabolism, pyruvate metabolism, phosphotransferase system (PTS), biotin metabolism, Two-component system and Terpenoid backbone biosynthesis showed significant changes in the ΔptsG mutant strain. Metabolome analysis revealed that a total of 310 metabolites were identified, including 20 different metabolites (p < 0.05). Among them, 15 metabolites were upregulated and 5 were downregulated in ΔptsG mutant strain. Statistical analysis revealed there were 115 individual metabolites having correlation, of which 89 were positive and 26 negative. These metabolites include amino acids, phosphates, amines, esters, nucleotides, benzoic acid and adenosine, among which amino acids and phosphate metabolites dominate. However, not all of these changes were attributable to changes in mRNA levels and must also be caused by post-transcriptional regulatory processes. The knowledge gained from this lays the foundation for further study on the role of ptsG in the pathogenic process of Glaesserella parasuis (G.parasuis).

Peristaltic on-chip pump for tunable media circulation and whole blood perfusion in PDMS-free organ-on-chip and Organ-Disc systems

Organ-on-chip (OoC) systems have become a promising tool for personalized medicine and drug development with advantages over conventional animal models and cell assays. However, the utility of OoCs in industrial settings is still limited, as external pumps and tubing for on-chip fluid transport are dependent on error-prone, manual handling. Here, we present an on-chip pump for OoC and Organ-Disc systems, to perfuse media without external pumps or tubing. Peristaltic pumping is implemented through periodic compression of a flexible pump layer. The disc-shaped, microfluidic module contains four independent systems, each lined with endothelial cells cultured under defined, peristaltic perfusion. Both cell viability and functionality were maintained over several days shown by supernatant analysis and immunostaining. Integrated, on-disc perfusion was further used for cytokine-induced cell activation with physiologic cell responses and for whole blood perfusion assays, both demonstrating the versatility of our system for OoC applications.

The storage compounds associated with Tetrasphaera PAO metabolism and the relationship between diversity and P removal

In enhanced biological phosphorus removal (EBPR), Tetrasphaera can potentially be an abundant and important polyphosphate accumulating organism (PAO), however ongoing questions remain concerning its storage compounds, phosphorus (P) removal capabilities and metabolic behaviour. This study investigated each of these points in an enriched Tetrasphaera culture (95% biovolume). The enriched Tetrasphaera culture fermented amino acids, while also converting and storing diverse amino acids as aspartic and glutamic acid within cells. Subsequent intracellular consumption of these two amino acids during the aerobic phase supports their importance in the metabolism of Tetrasphaera. Polyhydroxyalkanoate (PHA) cycling was also observed in this study, in contrast to some previous studies on Tetrasphaera. While exhibiting anaerobic phosphorus release and aerobic uptake, the highly enriched Tetrasphaera culture was unable to completely remove phosphorus in sequencing batch reactors (SBR) cycles, with an average removal efficiency of 72.3 ± 7.8%. This is unlike a previous study containing both Tetrasphaera (70%) and Accumulibacter (22%), which regularly performed complete phosphorus removal under otherwise similar operational conditions, at efficiencies of > 99%. Notably, the phylodiversity of organisms belonging to Tetrasphaera was substantially different in the present work, consisting mainly of organisms within Clade 2, likely impacting PHA cycling. These results suggest that the contribution of Tetrasphaera towards P removal is highly dependent on the composition of its Clades within this microbial group and an observed higher abundance of Tetrasphaera in WWTPs does not necessarily imply overall higher P removal. This study improves our understanding of the role of Tetrasphaera within EBPR systems and key factors impacting its metabolism.

Phenotypic responses in Caenorhabditis elegans following chronic low-level exposures to inorganic and organic compounds

Responses of organisms to sublethal exposure of environmental stressors can be difficult to detect. We investigated phenotypic changes in the tissue of Caenorhabditis elegans via Raman spectroscopy, as well as survival and reproductive output when exposed to chronic low doses of metals (copper, zinc, or silver), an herbicide (diuron), and a pesticide (imidacloprid). Raman spectroscopy measures changes in phenotype by providing information about the molecular composition and relative abundance of biomolecules. Multivariate analysis was used to evaluate the significance of treatment phenotype segregation plots compared with controls. Dose-dependent responses were observed for copper, zinc, silver, and diuron, whereas imidacloprid exposure resulted in a small response over the tested concentrations. Concentration-dependent shifts in nematode biomolecular phenotype were observed for copper. Despite having a dose-dependent reproductive response, silver, diuron, and imidacloprid produced inconsistent biological phenotype patterns. In contrast, there was a clear stepwise change between low concentrations (0.00625-0.5 mg/L) and higher concentration (1-2 mg/L) of ionic zinc. The findings demonstrate that measuring phenotypic responses via Raman spectroscopy can provide insights into the biomolecular mechanisms of toxicity. Despite the lack of consistency between survival and Raman-measured phenotypic changes, the results support the effectiveness of Raman spectroscopy and multivariate analysis to detect sublethal responses of chemicals in whole organisms and to identify toxic effect thresholds. Environ Toxicol Chem 2018;37:920-930. © 2017 SETAC.

Metabolism and ecological niche of Tetrasphaera and Ca. Accumulibacter in enhanced biological phosphorus removal

Tetrasphaera and Candidatus Accumulibacter are two abundant polyphosphate accumulating organisms in full-scale enhanced biological phosphorus removal (EBPR) systems. However, little is known about the metabolic behaviour and ecological niche that each organism exhibits in mixed communities. In this study, an enriched culture of Tetrasphaera and Ca. Accumulibacter was obtained using casein hydrolysate as sole carbon source. This culture was able to achieve a high phosphorus removal efficiency (>99%), storing polyphosphate while consuming amino acids anaerobically. Microautoradiography and fluorescence in situ hybridisation confirmed that more than 90% Tetrasphaera cells were responsible for amino acid consumption while Ca. Accumulibacter likely survived on fermentation products. Tetrasphaera performed the majority of the P removal (approximately 80%) in this culture, and batch tests showed that the metabolism of some carbon sources could actually lead to anaerobic orthophosphate (Pi) uptake (9.0 ± 2.1 mg-P/L) through energy generated by fermentation of glucose and amino acids. This anaerobic Pi uptake may lead to lower net Pi release to C uptake ratios and reduce the Pi needed to be removed aerobically in WWTPs. Intracellular metabolites such as amino acids, sugars, volatile fatty acids and small amines were observed as potential storage products, which may serve as energy sources in the aerobic phase. Evidence of the urea cycle was found, which could be involved in reducing the intracellular nitrogen content. This study improves our understanding of how phosphorus is removed in EBPR systems and can enable novel process optimisation strategies.

Microbiome, Metabolome and Inflammatory Bowel Disease

Inflammatory Bowel Disease (IBD) is a multifactorial disorder that conceptually occurs as a result of altered immune responses to commensal and/or pathogenic gut microbes in individuals most susceptible to the disease. During Crohn’s Disease (CD) or Ulcerative Colitis (UC), two components of the human IBD, distinct stages define the disease onset, severity, progression and remission. Epigenetic, environmental (microbiome, metabolome) and nutritional factors are important in IBD pathogenesis. While the dysbiotic microbiota has been proposed to play a role in disease pathogenesis, the data on IBD and diet are still less convincing. Nonetheless, studies are ongoing to examine the effect of pre/probiotics and/or FODMAP reduced diets on both the gut microbiome and its metabolome in an effort to define the healthy diet in patients with IBD. Knowledge of a unique metabolomic fingerprint in IBD could be useful for diagnosis, treatment and detection of disease pathogenesis.

Gene regulatory and metabolic adaptation processes of Dinoroseobacter shibae DFL12T during oxygen depletion

Metabolic flexibility is the key to the ecological success of the marine Roseobacter clade bacteria. We investigated the metabolic adaptation and the underlying changes in gene expression of Dinoroseobacter shibae DFL12(T) to anoxic life by a combination of metabolome, proteome, and transcriptome analyses. Time-resolved studies during continuous oxygen depletion were performed in a chemostat using nitrate as the terminal electron acceptor. Formation of the denitrification machinery was found enhanced on the transcriptional and proteome level, indicating that D. shibae DFL12(T) established nitrate respiration to compensate for the depletion of the electron acceptor oxygen. In parallel, arginine fermentation was induced. During the transition state, growth and ATP concentration were found to be reduced, as reflected by a decrease of A578 values and viable cell counts. In parallel, the central metabolism, including gluconeogenesis, protein biosynthesis, and purine/pyrimidine synthesis was found transiently reduced in agreement with the decreased demand for cellular building blocks. Surprisingly, an accumulation of poly-3-hydroxybutanoate was observed during prolonged incubation under anoxic conditions. One possible explanation is the storage of accumulated metabolites and the regeneration of NADP(+) from NADPH during poly-3-hydroxybutanoate synthesis (NADPH sink). Although D. shibae DFL12(T) was cultivated in the dark, biosynthesis of bacteriochlorophyll was increased, possibly to prepare for additional energy generation via aerobic anoxygenic photophosphorylation. Overall, oxygen depletion led to a metabolic crisis with partly blocked pathways and the accumulation of metabolites. In response, major energy-consuming processes were reduced until the alternative respiratory denitrification machinery was operative.

High-throughput screening of a Corynebacterium glutamicum mutant library on genomic and metabolic level

Due to impressive achievements in genomic research, the number of genome sequences has risen quickly, followed by an increasing number of genes with unknown or hypothetical function. This strongly calls for development of high-throughput methods in the fields of transcriptomics, proteomics and metabolomics. Of these platforms, metabolic profiling has the strongest correlation with the phenotype. We previously published a high-throughput metabolic profiling method for C. glutamicum as well as the automatic GC/MS processing software MetaboliteDetector. Here, we added a high-throughput transposon insertion determination for our C. glutamicum mutant library. The combination of these methods allows the parallel analysis of genotype/phenotype correlations for a large number of mutants. In a pilot project we analyzed the insertion points of 722 transposon mutants and found that 36% of the affected genes have unknown functions. This underlines the need for further information gathered by high-throughput techniques. We therefore measured the metabolic profiles of 258 randomly chosen mutants. The MetaboliteDetector software processed this large amount of GC/MS data within a few hours with a low relative error of 11.5% for technical replicates. Pairwise correlation analysis of metabolites over all genotypes showed dependencies of known and unknown metabolites. For a first insight into this large data set, a screening for interesting mutants was done by a pattern search, focusing on mutants with changes in specific pathways. We show that our transposon mutant library is not biased with respect to insertion points. A comparison of the results for specific mutants with previously published metabolic results on a deletion mutant of the same gene confirmed the concept of high-throughput metabolic profiling. Altogether the described method could be applied to whole mutant libraries and thereby help to gain comprehensive information about genes with unknown, hypothetical and known functions.

Programming stress-induced altruistic death in engineered bacteria

Programmed death is often associated with a bacterial stress response. This behavior appears paradoxical, as it offers no benefit to the individual. This paradox can be explained if the death is 'altruistic': the killing of some cells can benefit the survivors through release of 'public goods'. However, the conditions where bacterial programmed death becomes advantageous have not been unambiguously demonstrated experimentally. Here, we determined such conditions by engineering tunable, stress-induced altruistic death in the bacterium Escherichia coli. Using a mathematical model, we predicted the existence of an optimal programmed death rate that maximizes population growth under stress. We further predicted that altruistic death could generate the 'Eagle effect', a counter-intuitive phenomenon where bacteria appear to grow better when treated with higher antibiotic concentrations. In support of these modeling insights, we experimentally demonstrated both the optimality in programmed death rate and the Eagle effect using our engineered system. Our findings fill a critical conceptual gap in the analysis of the evolution of bacterial programmed death, and have implications for a design of antibiotic treatment.

Mass spectrometry-based technologies for high-throughput metabolomics

The metabolome is composed of a vast number of small-molecule metabolites that exhibit a diversity of physical and chemical properties and exist over a wide dynamic range in biological samples. Multiple analytical techniques, used in a complementary manner, are required to achieve high coverage of the metabolome. MS is playing a central role in metabolomics research. Herein, we present a brief overview of the MS-based technologies employed for high-throughput metabolomics. These technologies range from chromatography-MS techniques, such as GC-MS and LC-MS, to chromatography-free techniques, such as direct infusion, matrix-assisted and matrix-free laser desorption/ionization, imaging and some new ambient ionization approaches. Chemoinformatics and bioinformatics tools are widely available to facilitate successful metabolomics studies by turning the complex metabolomics data into biological information through streamlined data processing, analysis and interpretation.

Nontargeted elucidation of metabolic pathways using stable-isotope tracers and mass spectrometry

Systems level tools for the quantitative analysis of metabolic networks are required to engineer metabolism for biomedical and industrial applications. While current metabolomics techniques enable high-throughput quantification of metabolites, these methods provide minimal information on the rates and connectivity of metabolic pathways. Here we present a new method, nontargeted tracer fate detection (NTFD), that expands upon the concept of metabolomics to solve the above problems. Through the combined use of stable isotope tracers and chromatography coupled to mass spectrometry, our computational analysis enables the quantitative detection of all measurable metabolites derived from a specific labeled compound. Without a priori knowledge of a reaction network or compound library, NTFD provides information about relative flux magnitudes into each metabolite pool by determining the mass isotopomer distribution for all labeled compounds. This novel method adds a new dimension to the metabolomics tool box and provides a framework for global analysis of metabolic fluxes.

Analysis and engineering of metabolic pathway fluxes in Corynebacterium glutamicum

The Gram-positive soil bacterium Corynebacterium glutamicum was discovered as a natural overproducer of glutamate about 50 years ago. Linked to the steadily increasing economical importance of this microorganism for production of glutamate and other amino acids, the quest for efficient production strains has been an intense area of research during the past few decades. Efficient production strains were created by applying classical mutagenesis and selection and especially metabolic engineering strategies with the advent of recombinant DNA technology. Hereby experimental and computational approaches have provided fascinating insights into the metabolism of this microorganism and directed strain engineering. Today, C. glutamicum is applied to the industrial production of more than 2 million tons of amino acids per year. The huge achievements in recent years, including the sequencing of the complete genome and efficient post genomic approaches, now provide the basis for a new, fascinating era of research - analysis of metabolic and regulatory properties of C. glutamicum on a global scale towards novel and superior bioprocesses.

Growth phase-dependent global protein and metabolite profiles of Phaeobacter gallaeciensis strain DSM 17395, a member of the marine Roseobacter-clade

The marine heterotrophic roseobacter Phaeobacter gallaeciensis DSM 17395 was grown with glucose in defined mineral medium. Relative abundance changes of global protein (2-D DIGE) and metabolite (GC-MS) profiles were determined across five different time points of growth. In total, 215 proteins were identified and 147 metabolites detected (101 structurally identified), among which 60 proteins and 87 metabolites displayed changed abundances upon entry into stationary growth phase. Glucose breakdown to pyruvate apparently proceeds via the Entner-Doudoroff (ED) pathway, since phosphofructokinase of the Embden-Meyerhof-Parnas pathway is missing and the key metabolite of the ED-pathway, 2-keto-3-desoxygluconate, was detected. The absence of pfk in other genome-sequenced roseobacters suggests that the use of the ED pathway is an important physiological property among these heterotrophic marine bacteria. Upon entry into stationary growth phase (due to glucose starvation), sulfur assimilation (including cysteine biosynthesis) and parts of cell envelope synthesis (e.g. the lipid precursor 1-monooleoylglycerol) were down-regulated and cadaverine formation up-regulated. In contrast, central carbon catabolism remained essentially unchanged, pointing to a metabolic "stand-by" modus as an ecophysiological adaptation strategy. Stationary phase response of P. gallaeciensis differs markedly from that of standard organisms such as Escherichia coli, as evident e.g. by the absence of an rpoS gene.

Evaluation of 13C isotopic tracers for metabolic flux analysis in mammalian cells

(13)C metabolic flux analysis (MFA) is the most comprehensive means of characterizing cellular metabolic states. Uniquely labeled isotopic tracers enable more focused analyses to probe specific reactions within the network. As a result, the choice of tracer largely determines the precision with which one can estimate metabolic fluxes, especially in complex mammalian systems that require multiple substrates. Here we have experimentally determined metabolic fluxes in a tumor cell line, successfully recapitulating the hallmarks of cancer cell metabolism. Using these data, we computationally evaluated specifically labeled (13)C glucose and glutamine tracers for their ability to precisely and accurately estimate fluxes in central carbon metabolism. These methods enabled us to identify the optimal tracer for analyzing individual fluxes, specific pathways, and central carbon metabolism as a whole. [1,2-(13)C(2)]glucose provided the most precise estimates for glycolysis, the pentose phosphate pathway, and the overall network. Tracers such as [2-(13)C]glucose and [3-(13)C]glucose also outperformed the more commonly used [1-(13)C]glucose. [U-(13)C(5)]glutamine emerged as the preferred isotopic tracer for the analysis of the tricarboxylic acid (TCA) cycle. These results provide valuable, quantitative information on the performance of (13)C-labeled substrates and can aid in the design of more informative MFA experiments in mammalian cell culture.

MetaboliteDetector: comprehensive analysis tool for targeted and nontargeted GC/MS based metabolome analysis

We have developed a new software, MetaboliteDetector, for the efficient and automatic analysis of GC/MS-based metabolomics data. Starting with raw MS data, the program detects and subsequently identifies potential metabolites. Moreover, a comparative analysis of a large number of chromatograms can be performed in either a targeted or nontargeted approach. MetaboliteDetector automatically determines appropriate quantification ions and performs an integration of single ion peaks. The analysis results can directly be visualized with a principal component analysis. Since the manual input is limited to absolutely necessary parameters, the program is also usable for the analysis of high-throughput data. However, the intuitive graphical user interface of MetaboliteDetector additionally allows for a detailed examination of a single GC/MS chromatogram including single ion chromatograms, recorded mass spectra, and identified metabolite spectra in combination with the corresponding reference spectra obtained from a reference library. MetaboliteDetector offers the ability to operate with highly resolved profile mass data. Finally, all analysis results can be exported to tab delimited tables. The features of MetaboliteDetector are demonstrated by the analysis of two experimental metabolomics data sets. MetaboliteDetector is freely available under the GNU public license (GPL) at http://metabolitedetector.tu-bs.de.

A combination of metabolome and transcriptome analyses reveals new targets of the Corynebacterium glutamicum nitrogen regulator AmtR

The effects of a deletion of the amtR gene, encoding the master regulator of nitrogen control in Corynebacterium glutamicum, were investigated by metabolome and transcriptome analyses. Compared to the wild type, different metabolite patterns were observed in respect to glycolysis, pentose phosphate pathway, citric acid cycle, and most amino acid pools. Not all of these alterations could be attributed to changes at the level of mRNA and must be caused by posttranscriptional regulatory processes. However, subsequently carried out transcriptome analyses, which were confirmed by gel retardation experiments, revealed two new targets of AmtR, the dapD gene, encoding succinylase involved in m-diaminopimelate synthesis, and the mez gene, coding for malic enzyme. The regulation of dapD connects the AmtR-dependent nitrogen control with l-lysine biosynthesis, the regulation of mez with carbon metabolism. An increased l-glutamine pool in the amtR mutant compared to the wild type was correlated with deregulated expression of the AmtR-regulated glnA gene and an increased glutamine synthetase activity. The glutamate pool was decreased in the mutant and also glutamate excretion was impaired.

Building blocks for automated elucidation of metabolites: machine learning methods for NMR prediction

Background

Current efforts in Metabolomics, such as the Human Metabolome Project, collect structures of biological metabolites as well as data for their characterisation, such as spectra for identification of substances and measurements of their concentration. Still, only a fraction of existing metabolites and their spectral fingerprints are known. Computer-Assisted Structure Elucidation (CASE) of biological metabolites will be an important tool to leverage this lack of knowledge. Indispensable for CASE are modules to predict spectra for hypothetical structures. This paper evaluates different statistical and machine learning methods to perform predictions of proton NMR spectra based on data from our open database NMRShiftDB.

Results

A mean absolute error of 0.18 ppm was achieved for the prediction of proton NMR shifts ranging from 0 to 11 ppm. Random forest, J48 decision tree and support vector machines achieved similar overall errors. HOSE codes being a notably simple method achieved a comparatively good result of 0.17 ppm mean absolute error.

Conclusion

NMR prediction methods applied in the course of this work delivered precise predictions which can serve as a building block for Computer-Assisted Structure Elucidation for biological metabolites.

Comprehensive analysis of the metabolome of Pseudomonas putida S12 grown on different carbon sources

Metabolomics is an emerging, powerful, functional genomics technology that involves the comparative non-targeted analysis of the complete set of metabolites in an organism. We have set-up a robust quantitative metabolomics platform that allows the analysis of 'snapshot' metabolomes. In this study, we have applied this platform for the comprehensive analysis of the metabolite composition of Pseudomonas putida S12 grown on four different carbon sources, i.e. fructose, glucose, gluconate and succinate. This paper focuses on the microbial aspects of analyzing comprehensive metabolomes, and demonstrates that metabolomes can be analyzed reliably. The technical (i.e. sample work-up and analytical) reproducibility was on average 10%, while the biological reproducibility was approximately 40%. Moreover, the energy charge values of the microbial samples generated were determined, and indicated that no biotic or abiotic changes had occurred during sample work-up and analysis. In general, the metabolites present and their concentrations were very similar after growth on the different carbon sources. However, specific metabolites showed large differences in concentration, especially the intermediates involved in the degradation of the carbon sources studied. Principal component discriminant analysis was applied to identify metabolites that are specific for, i.e. not necessarily the metabolites that show those largest differences in concentration, cells grown on either of these four carbon sources. For selected enzymatic reactions, i.e. the glucose-6-phosphate isomerase, triosephosphate isomerase and phosphoglyceromutase reactions, the apparent equilibrium constants (K(app)) were calculated. In several instances a carbon source-dependent deviation between the apparent equilibrium constant (K(app)) and the thermodynamic equilibrium constant (K(eq)) was observed, hinting towards a potential point of metabolic regulation or towards bottlenecks in biosynthesis routes. For glucose-6-phosphate isomerase and phosphoglyceromutase, the K(app) was larger than K(eq), and the results suggested that the specific enzymatic activities of these two enzymes were too low to reach the thermodynamic equilibrium in growing cells. In contrast, with triosephosphate isomerase the K(app) was smaller than K(eq), and the results suggested that this enzyme is kinetically controlled.