Metabolomics in systems microbiology

Characterization and Amelioration of Filtration Difficulties Encountered in Metabolomic Studies of Clostridium thermocellum at Elevated Sugar Concentrations

Clostridium thermocellum, a promising candidate for consolidated bioprocessing, has been subjected to numerous engineering strategies for enhanced bioethanol production. Measurements of intracellular metabolites at substrate concentrations high enough (>50 g/L) to allow the production of industrially relevant titers of ethanol would inform efforts toward this end but have been difficult due to the production of a viscous substance that interferes with the filtration and quenching steps during metabolite extraction. To determine whether this problem is unique to C. thermocellum, we performed filtration experiments with other organisms that have been engineered for high-titer ethanol production, including Escherichia coli and Thermoanaerobacterium saccharolyticum. We addressed the problem through a series of improvements, including active pH control (to reduce problems with viscosity), investigation of different filter materials and pore sizes (to increase the filtration capacity), and correction for extracellular metabolite concentrations, and we developed a technique for more accurate intracellular metabolite measurements at elevated substrate concentrations. IMPORTANCE The accurate measurement of intracellular metabolites (metabolomics) is an integral part of metabolic engineering for the enhanced production of industrially important compounds and a useful technique to understand microbial physiology. Previous work tended to focus on model organisms under laboratory conditions. As we try to perform metabolomic studies with a wider range of organisms under conditions that more closely represent those found in nature or industry, we have found limitations in existing techniques. For example, fast filtration is an important step in quenching metabolism in preparation for metabolite extraction; however, it does not work for cultures of C. thermocellum at high substrate concentrations. In this work, we characterize the extent of the problem and develop techniques to overcome it.

Monitoring and modelling the dynamics of the cellular glycolysis pathway: A review and future perspectives

BACKGROUND

The dynamics of the cellular glycolysis pathway underpin cellular function and dysfunction, and therefore ultimately health, disease, diagnostic and therapeutic strategies. Evolving our understanding of this fundamental process and its dynamics remains critical.

SCOPE OF REVIEW

This paper reviews the medical relevance of glycolytic pathway in depth and explores the current state of the art for monitoring and modelling the dynamics of the process. The future perspectives of label free, vibrational microspectroscopic techniques to overcome the limitations of the current approaches are considered.

MAJOR CONCLUSIONS

Vibrational microspectroscopic techniques can potentially operate in the niche area of limitations of other omics technologies for non-destructive, real-time, in vivo label-free monitoring of glycolysis dynamics at a cellular and subcellular level.

The Impacts of Microgravity on Bacterial Metabolism

The inside of a space-faring vehicle provides a set of conditions unlike anything experienced by bacteria on Earth. The low-shear, diffusion-limited microenvironment with accompanying high levels of ionizing radiation create high stress in bacterial cells, and results in many physiological adaptations. This review gives an overview of the effect spaceflight in general, and real or simulated microgravity in particular, has on primary and secondary metabolism. Some broad trends in primary metabolic responses can be identified. These include increases in carbohydrate metabolism, changes in carbon substrate utilization range, and changes in amino acid metabolism that reflect increased oxidative stress. However, another important trend is that there is no universal bacterial response to microgravity, as different bacteria often have contradictory responses to the same stress. This is exemplified in many of the observed secondary metabolite responses where secondary metabolites may have increased, decreased, or unchanged production in microgravity. Different secondary metabolites in the same organism can even show drastically different production responses. Microgravity can also impact the production profile and localization of secondary metabolites. The inconsistency of bacterial responses to real or simulated microgravity underscores the importance of further research in this area to better understand how microbes can impact the people and systems aboard spacecraft.

Metabolic Footprinting of Microbial Systems Based on Comprehensive In Silico Predictions of MS/MS Relevant Data

Metabolic footprinting represents a holistic approach to gathering large-scale metabolomic information of a given biological system and is, therefore, a driving force for systems biology and bioprocess development. The ongoing development of automated cultivation platforms increases the need for a comprehensive and rapid profiling tool to cope with the cultivation throughput. In this study, we implemented a workflow to provide and select relevant metabolite information from a genome-scale model to automatically build an organism-specific comprehensive metabolome analysis method. Based on in-house literature and predicted metabolite information, the deduced metabolite set was distributed in stackable methods for a chromatography-free dilute and shoot flow-injection analysis multiple-reaction monitoring profiling approach. The workflow was used to create a method specific for Saccharomyces cerevisiae, covering 252 metabolites with 7 min/sample. The method was validated with a commercially available yeast metabolome standard, identifying up to 74.2% of the listed metabolites. As a first case study, three commercially available yeast extracts were screened with 118 metabolites passing quality control thresholds for statistical analysis, allowing to identify discriminating metabolites. The presented methodology provides metabolite screening in a time-optimised way by scaling analysis time to metabolite coverage and is open to other microbial systems simply starting from genome-scale model information.

Metabolomics-driven Approaches on Interactions Between Enterococcus faecalis and Candida albicans Biofilms

Objectives

This study aimed to determine the effect of Enterococcus faecalis on the cell growth and hyphal formation of Candida albicans and to understand the exact mechanism of candidal inhibition by the existence of E. faecalis by metabolomic analysis.

Materials and Methods

Single- and dual-species biofilms of E. faecalis and C. albicans were formed in a microtiter plate, and the metabolomic profiles of both biofilms was determined by gas chromatography-mass spectrometry. The hyphal cell growth of C. albicans after treatment with both the supernatant and biofilm cells of E. faecalis was examined microscopically. The expression levels of Efg1 and the images of C. albicans cell wall in single- and dual-species biofilms were determined by real-time quantitative polymerase chain reaction and transmission electron microscopy, respectively. The violacein levels produced by Chromobacterium violaceum were measured to determine the quorum sensing (QS) inhibitory activity of single- and dual-species biofilms.

Results

The biofilm cell growth, Efg1 expression, and hyphal development of C. albicans were inhibited by E. faecalis. Compared to single-species biofilms, alterations in carbohydrate, amino acid, and polyamine metabolites were observed in the dual-species biofilm for both microorganisms. Putrescine and pipecolic acid were detected at high levels in dual-species biofilm. A thicker β-glucan chitin and a denser and narrower fibrillar mannan layer of C. albicans cell wall were observed in dual-species biofilm. QS inhibitory activity was higher in dual-species biofilm suspensions of E. faecalis and C. albicans than in their single-species biofilms.

Conclusion

E. faecalis inhibited the hyphal development and biofilm formation of C. albicans. Biofilm suspensions of C. albicans and E. faecalis showed an anti-QS activity, which increased even further in the environment where the two species coexisted. Investigation of putrescine and pipecolic acid can be an important step to understand the inhibition of C. albicans by bacteria.

LC-MS Based Metabolomics Study of the Effects of EGCG on A549 Cells

(−)-Epigallocatechin-3-gallate (EGCG) is the main bioactive catechin in green tea. The antitumor activity of EGCG has been confirmed in various types of cancer, including lung cancer. However, the precise underlying mechanisms are still largely unclear. In the present study, we investigated the metabolite changes in A549 cells induced by EGCG in vitro utilizing liquid chromatography-mass spectrometry (LC-MS)-based metabolomics. The result revealed 33 differentially expressed metabolites between untreated and 80 μM EGCG-treated A549 cells. The altered metabolites were involved in the metabolism of glucose, amino acid, nucleotide, glutathione, and vitamin. Two markedly altered pathways, including glycine, serine and threonine metabolism and alanine, aspartate and glutamate metabolism, were identified by MetaboAnalyst 5.0 metabolic pathway analysis. These results may provide potential clues for the intramolecular mechanisms of EGCG’s effect on A549 cells. Our study may contribute to future molecular mechanistic studies of EGCG and the therapeutic application of EGCG in cancer management.

Metabolic profiling of liver and faeces in mice infected with echinococcosis

Background

Echinococcosis is a severe zoonotic parasitic disease which severely affects the health of the hosts. The diagnosis of echinococcosis depends mainly on imaging examination. However, the patient is often in the late stage of the disease when the symptoms appear, thus limiting the early diagnosis of echinococcosis. The treatment and prognosis of the patients are hampered because of long-term asymptomatic latency. Metabolomics is a new discipline developed in the late 1990s. It reflects a series of biological responses in pathophysiological processes by demonstrating the changes in metabolism under the influence of internal and external factors. When the organism is invaded by pathogens, the alteration in the characteristics of metabolites in cells becomes extremely sensitive. Here, we used a metabolomics approach involving liquid chromatography coupled with tandem mass spectrometry (LC–MS/MS) to determine the molecular mechanism of cystic echinococcosis (CE) and to develop an effective method for CE diagnosis.

Methods

Twenty 8-week-old female BALB/c mice were divided into normal and Echinococcus granulosus infection groups. To develop the E. granulosus infection model, mice were infected with protoscoleces. Six weeks later, the abdomens of the mice showed significant bulging. An LC–MS/MS system-based metabolomics approach was used to analyse the liver and faeces to reveal the metabolic profiles of mice with echinococcosis.

Results

We found that the metabolism of nucleotides, alkaloids, amino acids, amides, and organic acids in mice is closely interrelated with E. granulosus infection. In the liver, the metabolic pathways of tyrosine and tryptophan biosynthesis; phenylalanine, valine, leucine and isoleucine biosynthesis; and phenylalanine metabolism were notably associated with the occurrence and development of hydatid disease, and in the faeces, pantothenate and CoA biosynthesis are thought to be closely associated with the development of CE.

Conclusion

The metabolomics approach used in this study provides a reference for a highly sensitive and specific diagnostic and screening method for echinococcosis.

Graphic Abstract

Supplementary Information

The online version contains supplementary material available at 10.1186/s13071-021-04807-1.

Metabolomics of Mycobacterium tuberculosis

Enzymes fuel the biochemical activities of all cells. Their substrates and products thus represent a potential window into the physiologic state of a cell. Metabolomics focuses on the global, or systems-level, study of small molecules in a given biological system and has thus provided an experimental tool with which to study cellular physiology, including the biochemistry within pathogenic microorganisms. While metabolomic studies of Mycobacterium tuberculosis are still in their infancy, recent studies have begun to deliver unique insights into the composition, organization, activity, and regulation of the bacterium's physiologic network not accessible by other approaches. Here, we outline practical methods for the culture, collection, and analysis of metabolomic samples from M. tuberculosis that emphasize minimally perturbing sample handling, broad and native metabolite recovery, and sensitive, biologically agnostic metabolite detection.

Streamlining the Analysis of Dynamic 13C-Labeling Patterns for the Metabolic Engineering of Corynebacterium glutamicum as l-Histidine Production Host

Today’s possibilities of genome editing easily create plentitudes of strain mutants that need to be experimentally qualified for configuring the next steps of strain engineering. The application of design-build-test-learn cycles requires the identification of distinct metabolic engineering targets as design inputs for subsequent optimization rounds. Here, we present the pool influx kinetics (PIK) approach that identifies promising metabolic engineering targets by pairwise comparison of up- and downstream ¹³C labeling dynamics with respect to a metabolite of interest. Showcasing the complex l-histidine production with engineered Corynebacterium glutamicuml-histidine-on-glucose yields could be improved to 8.6 ± 0.1 mol% by PIK analysis, starting from a base strain. Amplification of purA, purB, purH, and formyl recycling was identified as key targets only analyzing the signal transduction kinetics mirrored in the PIK values.

2,2',4,4'-tetrabromodiphenyl ether (BDE-47) induces wide metabolic changes including attenuated mitochondrial function and enhanced glycolysis in PC12 cells

Polybrominated diphenyl ethers (PBDEs) are extensively used as brominated flame retardants in various factory products. As environmental pollutants, the adverse effects of PBDEs on human health have been receiving considerable attention. However, the precise fundamental mechanisms of toxicity induced by PBDEs are still not fully understood. In this study, the mechanism of cytotoxicity induced by 2,2',4,4'-tetrabromodiphenyl ether (BDE-47) was investigated by combining Seahorse XFp analysis and mass spectrometry-based metabolomics and flux approaches in PC12 cells, one of the most widely used neuron-like cell lines for investigating cytotoxic effects. The Seahorse results suggest that BDE-47 significantly attenuated mitochondrial respiration and enhanced glycolysis in PC12 cells. Additionally, metabolomics results revealed the reduction of TCA metabolites such as citrate, succinate, aconitate, malate, fumarate, and glutamate after BDE-47 exposure. Metabolic flux analysis showed that BDE-47 exposure reduced the oxidative metabolic capacity of mitochondria in PC12 cells. Furthermore, various altered metabolites were found in multiple metabolic pathways, especially in glycine-serine-threonine metabolism and glutathione metabolism. A total of 17 metabolic features were determined in order to distinguish potentially disturbed metabolite markers of BDE-47 exposure. Our findings provide possible biomarkers of cytotoxic effects induced by BDE-47 exposure, and elicit a deeper understanding of the intramolecular mechanisms that could be used in further studies to validate the potential neurotoxicity of PBDEs in vivo. Based on our results, therapeutic approaches targeting mitochondrial function and the glycolysis pathway may be a promising direction against PBDE exposure.

Comprehensive Isotopic Targeted Mass Spectrometry: Reliable Metabolic Flux Analysis with Broad Coverage

Metabolic flux analysis (MFA) is highly relevant to understanding metabolic mechanisms of various biological processes. While the pace of methodology development in MFA has been rapid, a major challenge the field continues to witness is limited metabolite coverage, often restricted to a small to moderate number of well-known compounds. In addition, isotopic peaks from an enriched metabolite tend to have low abundances, which makes liquid chromatography tandem mass spectrometry (LC-MS/MS) highly useful in MFA due to its high sensitivity and specificity. Previously we have built large-scale LC-MS/MS approaches that can be routinely used for measurement of up to ∼1,900 metabolite/feature levels [Gu et al. Anal. Chem. 2015, 87, 12355-12362. Shi et al. Anal. Chem. 2019, 91, 13737-13745.]. In this study, we aim to expand our previous studies focused on metabolite level measurements to flux analysis and establish a novel comprehensive isotopic targeted mass spectrometry (CIT-MS) method for reliable MFA analysis with broad coverage. As a proof-of-principle, we have applied CIT-MS to compare the steady-state enrichment of metabolites between Myc(oncogene)-On and Myc-Off Tet21N human neuroblastoma cells cultured with U-13C6-glucose medium. CIT-MS is operationalized using multiple reaction monitoring (MRM) mode and is able to perform MFA of 310 identified metabolites (142 reliably detected, 46 kinetically profiled) selected from >35 metabolic pathways of strong biological significance. Further, we developed a novel concept of relative flux, which eliminates the requirement of absolute quantitation in traditional MFA and thus enables comparative MFA under the pseudosteady state. As a result, CIT-MS was shown to possess the advantages of broad coverage, easy implementation, fast throughput, and more importantly, high fidelity and accuracy in MFA. In principle, CIT-MS can be easily adapted to track the flux of other labeled tracers (such as 15N-tracers) in any metabolite detectable by LC-MS/MS and in various biological models (such as mice). Therefore, CIT-MS has great potential to bring new insights to both basic and clinical metabolism research.

Glucose transporter 1 is important for the glycolytic metabolism of human endometrial stromal cells in hypoxic environment

Aim

The study aimed to elucidate the glycolytic metabolism of human endometrial stromal cells (hESCs) in hypoxic environment.

Main methods

The hESCs were cultured in hypoxic environment, and their metabolic pathways were analyzed using metabolomics. We assessed glucose uptake using 2-deoxyglucose (2-DG) assay. The expression of glucose transporters (GLUTs) required for glucose uptake was determined using real-time quantitative polymerase chain reaction (qPCR) and western blotting. Furthermore, we knocked down GLUT1 and examined the uptake of 2-DG.

Key findings

Under hypoxia, glucose-6-phosphate, fructose-6-phosphate, and fructose-1,6-diphosphate were significantly elevated in hESCs (P < 0.05). This finding indicated enhancement in glycolysis. The volume of glucose uptake increased significantly under hypoxia (P < 0.05). Hypoxia simultaneously induced the expression of GLUT1 and GLUT3 mRNA (P < 0.05) and attenuated the expression of GLUT8 (P < 0.05). Glucose uptake was significantly inhibited upon knockdown of GLUT1 (P < 0.0001).

Significance

These results demonstrated a very important role of glucose transport under hypoxia. Also, hESCs utilize glycolysis to adapt to hypoxic conditions that could occur in menstrual and implantation period. These findings pave the way to study implantation failure and tumors originating from the endometrium.

Scientific workflow managers in metabolomics: an overview

Metabolomics workflows for data processing reproducibility and accelerated clinical deployment.

Coupled metabolic-hydrodynamic modeling enabling rational scale-up of industrial bioprocesses

Metabolomics aims to address what and how regulatory mechanisms are coordinated to achieve flux optimality, different metabolic objectives as well as appropriate adaptations to dynamic nutrient availability. Recent decades have witnessed that the integration of metabolomics and fluxomics within the goal of synthetic biology has arrived at generating the desired bioproducts with improved bioconversion efficiency. Absolute metabolite quantification by isotope dilution mass spectrometry represents a functional readout of cellular biochemistry and contributes to the establishment of metabolic (structured) models required in systems metabolic engineering. In industrial practices, population heterogeneity arising from fluctuating nutrient availability frequently leads to performance losses, that is reduced commercial metrics (titer, rate, and yield). Hence, the development of more stable producers and more predictable bioprocesses can benefit from a quantitative understanding of spatial and temporal cell-to-cell heterogeneity within industrial bioprocesses. Quantitative metabolomics analysis and metabolic modeling applied in computational fluid dynamics (CFD)-assisted scale-down simulators that mimic industrial heterogeneity such as fluctuations in nutrients, dissolved gases, and other stresses can procure informative clues for coping with issues during bioprocessing scale-up. In previous studies, only limited insights into the hydrodynamic conditions inside the industrial-scale bioreactor have been obtained, which makes case-by-case scale-up far from straightforward. Tracking the flow paths of cells circulating in large-scale bioreactors is a highly valuable tool for evaluating cellular performance in production tanks. The "lifelines" or "trajectories" of cells in industrial-scale bioreactors can be captured using Euler-Lagrange CFD simulation. This novel methodology can be further coupled with metabolic (structured) models to provide not only a statistical analysis of cell lifelines triggered by the environmental fluctuations but also a global assessment of the metabolic response to heterogeneity inside an industrial bioreactor. For the future, the industrial design should be dependent on the computational framework, and this integration work will allow bioprocess scale-up to the industrial scale with an end in mind.

In vitro metabolomic footprint of the Echinococcus multilocularis metacestode

Alveolar echinococcosis (AE) is a zoonotic disease that is deadly if left untreated. AE is caused by the larval metacestode stage of the cestode Echinococcus multilocularis. Better knowledge on the host-parasite interface could yield novel targets for improvement of the treatment against AE. We analyzed culture media incubated with in vitro grown E. multilocularis metacestodes by 1H nuclear magnetic resonance spectroscopy to identify the unknown metabolic footprint of the parasite. Moreover, we quantitatively analyzed all amino acids, acetate, glucose, lactate, and succinate in time-course experiments using liquid chromatography and enzymatic assays. The E. multilocularis metacestodes consumed glucose and, surprisingly, threonine and produced succinate, acetate, and alanine as major fermentation products. The metabolic composition of vesicle fluid (VF) from in vitro grown E. multilocularis metacestodes was different from parasite-incubated culture medium with respect to the abundance, but not the spectrum, of metabolites, and some metabolites, in particular amino acids, accumulated in the VF. Overall, this study presents the first characterization of the in vitro metabolic footprint of E. multilocularis metacestodes and VF composition, and it provides the basis for analyses of potentially targetable pathways for future drug development.

Microfluidic Irreversible Electroporation-A Versatile Tool to Extract Intracellular Contents of Bacteria and Yeast

Exploring the dynamic behavior of cellular metabolism requires a standard laboratory method that guarantees rapid sampling and extraction of the cellular content. We propose a versatile sampling technique applicable to cells with different cell wall and cell membrane properties. The technique is based on irreversible electroporation with simultaneous quenching and extraction by using a microfluidic device. By application of electric pulses in the millisecond range, permanent lethal pores are formed in the cell membrane of Escherichia coli and Saccharomyces cerevisiae, facilitating the release of the cellular contents; here demonstrated by the measurement of glucose-6-phosphate and the activity of the enzyme glucose-6-phosphate dehydrogenase. The successful application of this device was demonstrated by pulsed electric field treatment in a flow-through configuration of the microfluidic chip in combination with sampling, inactivation, and extraction of the intracellular content in a few seconds. Minimum electric field strengths of 10 kV/cm for E. coli and 7.5 kV/cm for yeast S. cerevisiae were required for successful cell lysis. The results are discussed in the context of applications in industrial biotechnology, where metabolomics analyses are important.

Metabolic principles of persistence and pathogenicity in Mycobacterium tuberculosis

Metabolism was once relegated to the supply of energy and biosynthetic precursors, but it has now become clear that it is a specific mediator of nearly all physiological processes. In the context of microbial pathogenesis, metabolism has expanded outside its canonical role in bacterial replication. Among human pathogens, this expansion has emerged perhaps nowhere more visibly than for Mycobacterium tuberculosis, the causative agent of tuberculosis. Unlike most pathogens, M. tuberculosis has evolved within humans, which are both host and reservoir. This makes unrestrained replication and perpetual quiescence equally incompatible strategies for survival as a species. In this Review, we summarize recent work that illustrates the diversity of metabolic functions that not only enable M. tuberculosis to establish and maintain a state of chronic infection within the host but also facilitate its survival in the face of drug pressure and, ultimately, completion of its life cycle.

PAMDB: a comprehensive Pseudomonas aeruginosa metabolome database

The Pseudomonas aeruginosaMetabolome Database (PAMDB, http://pseudomonas.umaryland.edu) is a searchable, richly annotated metabolite database specific to P. aeruginosa. P. aeruginosa is a soil organism and significant opportunistic pathogen that adapts to its environment through a versatile energy metabolism network. Furthermore, P. aeruginosa is a model organism for the study of biofilm formation, quorum sensing, and bioremediation processes, each of which are dependent on unique pathways and metabolites. The PAMDB is modelled on the Escherichia coli (ECMDB), yeast (YMDB) and human (HMDB) metabolome databases and contains >4370 metabolites and 938 pathways with links to over 1260 genes and proteins. The database information was compiled from electronic databases, journal articles and mass spectrometry (MS) metabolomic data obtained in our laboratories. For each metabolite entered, we provide detailed compound descriptions, names and synonyms, structural and physiochemical information, nuclear magnetic resonance (NMR) and MS spectra, enzymes and pathway information, as well as gene and protein sequences. The database allows extensive searching via chemical names, structure and molecular weight, together with gene, protein and pathway relationships. The PAMBD and its future iterations will provide a valuable resource to biologists, natural product chemists and clinicians in identifying active compounds, potential biomarkers and clinical diagnostics.

Substrate inhibition imposes fitness penalty at high protein stability

Proteins are only moderately stable. It has long been debated whether this narrow range of stabilities is solely a result of neutral drift toward lower stability or purifying selection against excess stability-for which no experimental evidence was found so far-is also at work. Here, we show that mutations outside the active site in the essential Escherichia coli enzyme adenylate kinase (Adk) result in a stability-dependent increase in substrate inhibition by AMP, thereby impairing overall enzyme activity at high stability. Such inhibition caused substantial fitness defects not only in the presence of excess substrate but also under physiological conditions. In the latter case, substrate inhibition caused differential accumulation of AMP in the stationary phase for the inhibition-prone mutants. Furthermore, we show that changes in flux through Adk could accurately describe the variation in fitness effects. Taken together, these data suggest that selection against substrate inhibition and hence excess stability may be an important factor determining stability observed for modern-day Adk.

Toward a global picture of bacterial secondary metabolism

Bacterial metabolism is comprised of primary metabolites, the intracellular molecules of life that enable growth and proliferation, and secondary metabolites, predominantly extracellular molecules that facilitate a microbe's interaction with its environment. While our knowledge of primary metabolism and its web of interconnected intermediates is quantitative and holistic, significant knowledge gaps remain in our understanding of the secondary metabolomes of bacteria. In this Perspective, I discuss the main challenges involved in obtaining a global, comprehensive picture of bacterial secondary metabolomes, specifically in biosynthetically "gifted" microbes. Recent methodological advances that can meet these challenges will be reviewed. Applications of these methods combined with ongoing innovations will enable a detailed picture of global secondary metabolomes, which will in turn shed light onto the biology, chemistry, and enzymology underlying natural products and simultaneously aid drug discovery.

Metabolic programming a lean phenotype by deregulation of RNA polymerase III

As a master negative regulator of RNA polymerase (Pol) III, Maf1 modulates transcription in response to nutrients and stress to balance the production of highly abundant tRNAs, 5S rRNA, and other small noncoding RNAs with cell growth and maintenance. This regulation of Pol III transcription is important for energetic economy as mice lacking Maf1 are lean and resist weight gain on normal and high fat diets. The lean phenotype of Maf1 knockout (KO) mice is attributed in part to metabolic inefficiencies which increase the demand for cellular energy and elevate catabolic processes, including autophagy/lipophagy and lipolysis. A futile RNA cycle involving increased synthesis and turnover of Pol III transcripts has been proposed as an important driver of these changes. Here, using targeted metabolomics, we find changes in the liver of fed and fasted Maf1 KO mice consistent with the function of mammalian Maf1 as a chronic Pol III repressor. Differences in long-chain acylcarnitine levels suggest that energy demand is higher in the fed state of Maf1 KO mice versus the fasted state. Quantitative metabolite profiling supports increased activity in the TCA cycle, the pentose phosphate pathway, and the urea cycle and reveals changes in nucleotide levels and the creatine system. Metabolite profiling also confirms key predictions of the futile RNA cycle hypothesis by identifying changes in many metabolites involved in nucleotide synthesis and turnover. Thus, constitutively high levels of Pol III transcription in Maf1 KO mice reprogram central metabolic pathways and waste metabolic energy through a futile RNA cycle.

Promises and pitfalls of untargeted metabolomics

Metabolomics is one of the newer omics fields, and has enabled researchers to complement genomic and protein level analysis of disease with both semi-quantitative and quantitative metabolite levels, which are the chemical mediators that constitute a given phenotype. Over more than a decade, methodologies have advanced for both targeted (quantification of specific analytes) as well as untargeted metabolomics (biomarker discovery and global metabolite profiling). Untargeted metabolomics is especially useful when there is no a priori metabolic hypothesis. Liquid chromatography coupled to mass spectrometry (LC-MS) has been the preferred choice for untargeted metabolomics, given the versatility in metabolite coverage and sensitivity of these instruments. Resolving and profiling many hundreds to thousands of metabolites with varying chemical properties in a biological sample presents unique challenges, or pitfalls. In this review, we address the various obstacles and corrective measures available in four major aspects associated with an untargeted metabolomics experiment: (1) experimental design, (2) pre-analytical (sample collection and preparation), (3) analytical (chromatography and detection), and (4) post-analytical (data processing).

A Metabolomics Approach Uncovers Differences between Traditional and Commercial Dairy Products in Buryatia (Russian Federation)

Commercially available and traditional dairy products differ in terms of their manufacturing processes. In this study, commercially available and traditionally fermented cheese, yogurt, and milk beverages were analyzed and compared. The metabolomic technique of ultra-performance liquid chromatography-quadrupole-time of flight mass spectrometry (UPLC-Q-TOF) in the MS^E mode was used in combination with statistical methods, including univariate analysis and chemometric analysis, to determine the differences in metabolite profiles between commercially and traditionally fermented dairy products. The experimental results were analyzed statistically and showed that traditional and commercial dairy products were well differentiated in both positive and negative ion modes, with significant differences observed between the samples. After screening for metabolite differences, we detected differences between traditional milk beverages and yogurt and their commercial counterparts in terms of the levels of compounds such as l-lysine, l-methionine, l-citrulline, l-proline, l-serine, l-valine and l-homocysteine, and of short peptides such as Asp-Arg, Gly-Arg, His-Pro, Pro-Asn. The greatest difference between commercially available and traditional cheese was in the short peptide composition, as commercially available and traditional cheese is rich in short peptides.

Balanced trafficking between the ER and the Golgi apparatus increases protein secretion in yeast

The yeast Saccharomyces cerevisiae is widely used as a cell factory to produce recombinant proteins. However, S. cerevisiae naturally secretes only a few proteins, such as invertase and the mating alpha factor, and its secretory capacity is limited. It has been reported that engineering protein anterograde trafficking from the endoplasmic reticulum to the Golgi apparatus by the moderate overexpression of SEC16 could increase recombinant protein secretion in S. cerevisiae. In this study, the retrograde trafficking in a strain with moderate overexpression of SEC16 was engineered by overexpression of ADP-ribosylation factor GTP activating proteins, Gcs1p and Glo3p, which are involved in the process of COPI-coated vesicle formation. Engineering the retrograde trafficking increased the secretion of α-amylase but did not induce production of reactive oxygen species. An expanded ER membrane was detected in both the GCS1 and GLO3 overexpression strains. Physiological characterizations during batch fermentation showed that GLO3 overexpression had better effect on recombinant protein secretion than GCS1 overexpression. Additionally, the GLO3 overexpression strain had higher secretion of two other recombinant proteins, endoglucanase I from Trichoderma reesei and glucan-1,4-α-glucosidase from Rhizopus oryzae, indicating overexpression of GLO3 in a SEC16 moderate overexpression strain might be a general strategy for improving production of secreted proteins by yeast.

Biological and chemical strategies for exploring inter- and intra-kingdom communication mediated via bacterial volatile signals

Airborne chemical signals emitted by bacteria influence the behavior of other bacteria and plants. We present an overview of in vitro methods for evaluating bacterial and plant responses to bacterial volatile compounds (BVCs). Three types of equipment have been used to physically separate the bacterial test strains from either other bacterial strains or plants (in our laboratory we use either Arabidopsis or tobacco plant seedlings): a Petri dish containing two compartments (BI Petri dish); two Petri dishes connected with tubing; and a microtiter-based assay. The optimized procedure for the BI Petri dish system is described in this protocol and can be widely used for elucidation of potential function in interactions between diverse microbes and those plant and chemical volatiles emitted by bacteria that are most likely to mediate bacterial or plant responses to BVCs. We also describe a procedure for metabolome-based BVC profiling via dynamic (i.e., continuous airflow) or static headspace sampling using solid-phase microextraction (SPME). Using both these procedures, bacteria-bacteria communications and bacteria-plant interactions mediated by BVCs can be rapidly investigated (within 1-4 weeks).

Serum metabolomics analysis for early detection of colorectal cancer

BACKGROUND

Although colorectal cancer (CRC) is one of the most common causes of cancer mortality, early-stage detection improves survival rates dramatically. Because cancer impacts important metabolic pathways, the alteration of metabolite levels as a potential biomarker of early-stage cancer has been the focus of many studies. Here, we used CE-TOFMS, a novel and promising method with small injection volume and high resolution, to separate and detect ionic compounds based on the different migration rates of charged metabolites in order to detect metabolic biomarkers in patients with CRC.

METHODS

A total of 56 patients with CRC (n = 14 each of Stages I-IV), 60 healthy controls, and 59 patients with colonic adenoma were included in this study. Metabolome analysis was conducted by CE-TOFMS on serum samples of patients and controls using the Advanced Scan package (Human Metabolome Technologies).

RESULTS

We obtained 334 metabolites in the serum, of which 139 were identified as known substances. Among these 139 known metabolites, 16 were correlated with CRC stage by upregulation and 44 by downregulation, with benzoic acid (r = -0.649, t = 11.653, p = 6.07599E-24), octanoic acid (r = 0.557, t = 9.183, p = 7.9557E-17), decanoic acid (r = 0.539, t = 8.749, p = 1.24352E-15), and histidine (r = -0.513, t = 8.194, p = 3.90224E-14) exhibiting significant correlation.

CONCLUSIONS

To the best of our knowledge, this is the first report to determine the correlation between serum metabolites and CRC stage using CE-TOFMS. Our results show that benzoic acid exhibited excellent diagnostic power and could potentially serve as a novel disease biomarker for CRC diagnosis.

Development of a core Clostridium thermocellum kinetic metabolic model consistent with multiple genetic perturbations

BACKGROUND

Clostridium thermocellum is a Gram-positive anaerobe with the ability to hydrolyze and metabolize cellulose into biofuels such as ethanol, making it an attractive candidate for consolidated bioprocessing (CBP). At present, metabolic engineering in C. thermocellum is hindered due to the incomplete description of its metabolic repertoire and regulation within a predictive metabolic model. Genome-scale metabolic (GSM) models augmented with kinetic models of metabolism have been shown to be effective at recapitulating perturbed metabolic phenotypes.

RESULTS

In this effort, we first update a second-generation genome-scale metabolic model (iCth446) for C. thermocellum by correcting cofactor dependencies, restoring elemental and charge balances, and updating GAM and NGAM values to improve phenotype predictions. The iCth446 model is next used as a scaffold to develop a core kinetic model (k-ctherm118) of the C. thermocellum central metabolism using the Ensemble Modeling (EM) paradigm. Model parameterization is carried out by simultaneously imposing fermentation yield data in lactate, malate, acetate, and hydrogen production pathways for 19 measured metabolites spanning a library of 19 distinct single and multiple gene knockout mutants along with 18 intracellular metabolite concentration data for a Δgldh mutant and ten experimentally measured Michaelis-Menten kinetic parameters.

CONCLUSIONS

The k-ctherm118 model captures significant metabolic changes caused by (1) nitrogen limitation leading to increased yields for lactate, pyruvate, and amino acids, and (2) ethanol stress causing an increase in intracellular sugar phosphate concentrations (~1.5-fold) due to upregulation of cofactor pools. Robustness analysis of k-ctherm118 alludes to the presence of a secondary activity of ketol-acid reductoisomerase and possible regulation by valine and/or leucine pool levels. In addition, cross-validation and robustness analysis allude to missing elements in k-ctherm118 and suggest additional experiments to improve kinetic model prediction fidelity. Overall, the study quantitatively assesses the advantages of EM-based kinetic modeling towards improved prediction of C. thermocellum metabolism and develops a predictive kinetic model which can be used to design biofuel-overproducing strains.

Hepatitis B virus X protein (HBx)-induced abnormalities of nucleic acid metabolism revealed by (1)H-NMR-based metabonomics

Hepatitis B virus X protein (HBx) plays an important role in HBV-related hepatocarcinogenesis; however, mechanisms underlying HBx-mediated carcinogenesis remain unclear. In this study, an NMR-based metabolomics approach was applied to systematically investigate the effects of HBx on cell metabolism. EdU incorporation assay was conducted to examine the effects of HBx on DNA synthesis, an important feature of nucleic acid metabolism. The results revealed that HBx disrupted metabolism of glucose, lipids, and amino acids, especially nucleic acids. To understand the potential mechanism of HBx-induced abnormalities of nucleic acid metabolism, gene expression profiles of HepG2 cells expressing HBx were investigated. The results showed that 29 genes involved in DNA damage and DNA repair were differentially expressed in HBx-expressing HepG2 cells. HBx-induced DNA damage was further demonstrated by karyotyping, comet assay, Western blotting, immunofluorescence and immunohistochemistry analyses. Many studies have previously reported that DNA damage can induce abnormalities of nucleic acid metabolism. Thus, our results implied that HBx initially induces DNA damage, and then disrupts nucleic acid metabolism, which in turn blocks DNA repair and induces the occurrence of hepatocellular carcinoma (HCC). These findings further contribute to our understanding of the occurrence of HCC.

Human Cytomegalovirus: Coordinating Cellular Stress, Signaling, and Metabolic Pathways

Viruses face a multitude of challenges when they infect a host cell. Cells have evolved innate defenses to protect against pathogens, and an infecting virus may induce a stress response that antagonizes viral replication. Further, the metabolic, oxidative, and cell cycle state may not be conducive to the viral infection. But viruses are fabulous manipulators, inducing host cells to use their own characteristic mechanisms and pathways to provide what the virus needs. This article centers on the manipulation of host cell metabolism by human cytomegalovirus (HCMV). We review the features of the metabolic program instituted by the virus, discuss the mechanisms underlying these dramatic metabolic changes, and consider how the altered program creates a synthetic milieu that favors efficient HCMV replication and spread.

Metabolomics of Mycobacterium tuberculosis

Enzymes fuel the biochemical activities of all cells. Their substrates and products thus offer a potential window into the physiologic state of a cell. Metabolomics focuses on the global, or systems-level, study of small molecules in a given biological system and thus provided an experimental tool with which to study cellular physiology on a global biochemical scale. While metabolomic studies of Mycobacterium tuberculosis are still in their infancy, recent studies have begun to deliver unique insights into the composition, organization, activity, and regulation of M. tuberculosis' physiologic network. Here, we outline practical methods for the culture, collection, and analysis of metabolomic samples from Mycobacterium tuberculosis that emphasize minimal sample perturbation, broad and native metabolite recovery, and sensitive, biologically agnostic metabolite detection.

Chicken, beams, and Campylobacter: rapid differentiation of foodborne bacteria via vibrational spectroscopy and MALDI-mass spectrometry

Campylobacter species are one of the main causes of food poisoning worldwide. Despite the availability of established culturing and molecular techniques, due to the fastidious nature of these microorganisms, simultaneous detection and species differentiation still remains challenging. This study focused on the differentiation of eleven Campylobacter strains from six species, using Fourier transform infrared (FT-IR) and Raman spectroscopies, together with matrix-assisted laser desorption ionisation-time of flight-mass spectrometry (MALDI-TOF-MS), as physicochemical approaches for generating biochemical fingerprints. Cluster analysis of data from each of the three analytical approaches provided clear differentiation of each Campylobacter species, which was generally in agreement with a phylogenetic tree based on 16S rRNA gene sequences. Notably, although C. fetus subspecies fetus and venerealis are phylogenetically very closely related, using FT-IR and MALDI-TOF-MS data these subspecies were readily differentiated based on differences in the lipid (2920 and 2851 cm(-1)) and fingerprint regions (1500-500 cm(-1)) of the FT-IR spectra, and the 500-2000 m/z region of the MALDI-TOF-MS data. A finding that was further investigated with targeted lipidomics using liquid chromatography-mass spectrometry (LC-MS). Our results demonstrate that such metabolomics approaches combined with molecular biology techniques may provide critical information and knowledge related to the risk factors, virulence, and understanding of the distribution and transmission routes associated with different strains of foodborne Campylobacter spp.

Analytics for Metabolic Engineering

Realizing the promise of metabolic engineering has been slowed by challenges related to moving beyond proof-of-concept examples to robust and economically viable systems. Key to advancing metabolic engineering beyond trial-and-error research is access to parts with well-defined performance metrics that can be readily applied in vastly different contexts with predictable effects. As the field now stands, research depends greatly on analytical tools that assay target molecules, transcripts, proteins, and metabolites across different hosts and pathways. Screening technologies yield specific information for many thousands of strain variants, while deep omics analysis provides a systems-level view of the cell factory. Efforts focused on a combination of these analyses yield quantitative information of dynamic processes between parts and the host chassis that drive the next engineering steps. Overall, the data generated from these types of assays aid better decision-making at the design and strain construction stages to speed progress in metabolic engineering research.

White biotechnology: State of the art strategies for the development of biocatalysts for biorefining

White biotechnology is a term that is now often used to describe the implementation of biotechnology in the industrial sphere. Biocatalysts (enzymes and microorganisms) are the key tools of white biotechnology, which is considered to be one of the key technological drivers for the growing bioeconomy. Biocatalysts are already present in sectors such as the chemical and agro-food industries, and are used to manufacture products as diverse as antibiotics, paper pulp, bread or advanced polymers. This review proposes an original and global overview of highly complementary fields of biotechnology at both enzyme and microorganism level. A certain number of state of the art approaches that are now being used to improve the industrial fitness of biocatalysts particularly focused on the biorefinery sector are presented. The first part deals with the technologies that underpin the development of industrial biocatalysts, notably the discovery of new enzymes and enzyme improvement using directed evolution techniques. The second part describes the toolbox available by the cell engineer to shape the metabolism of microorganisms. And finally the last part focuses on the 'omic' technologies that are vital for understanding and guide microbial engineering toward more efficient microbial biocatalysts. Altogether, these techniques and strategies will undoubtedly help to achieve the challenging task of developing consolidated bioprocessing (i.e. CBP) readily available for industrial purpose.

A roadmap for interpreting (13)C metabolite labeling patterns from cells

Measuring intracellular metabolism has increasingly led to important insights in biomedical research. (13)C tracer analysis, although less information-rich than quantitative (13)C flux analysis that requires computational data integration, has been established as a time-efficient method to unravel relative pathway activities, qualitative changes in pathway contributions, and nutrient contributions. Here, we review selected key issues in interpreting (13)C metabolite labeling patterns, with the goal of drawing accurate conclusions from steady state and dynamic stable isotopic tracer experiments.

Overview of mass spectrometry-based metabolomics: opportunities and challenges

The field of metabolomics has witnessed an exponential growth in the last decade driven by important applications spanning a wide range of areas in the basic and life sciences and beyond. Mass spectrometry in combination with chromatography and nuclear magnetic resonance are the two major analytical avenues for the analysis of metabolic species in complex biological mixtures. Owing to its inherent significantly higher sensitivity and fast data acquisition, MS plays an increasingly dominant role in the metabolomics field. Propelled by the need to develop simple methods to diagnose and manage the numerous and widespread human diseases, mass spectrometry has witnessed tremendous growth with advances in instrumentation, experimental methods, software, and databases. In response, the metabolomics field has moved far beyond qualitative methods and simple pattern recognition approaches to a range of global and targeted quantitative approaches that are now routinely used and provide reliable data, which instill greater confidence in the derived inferences. Powerful isotope labeling and tracing methods have become very popular. The newly emerging ambient ionization techniques such as desorption ionization and rapid evaporative ionization have allowed direct MS analysis in real time, as well as new MS imaging approaches. While the MS-based metabolomics has provided insights into metabolic pathways and fluxes, and metabolite biomarkers associated with numerous diseases, the increasing realization of the extremely high complexity of biological mixtures underscores numerous challenges including unknown metabolite identification, biomarker validation, and interlaboratory reproducibility that need to be dealt with for realization of the full potential of MS-based metabolomics. This chapter provides a glimpse at the current status of the mass spectrometry-based metabolomics field highlighting the opportunities and challenges.

Exploring Metabolic Profile Differences between Colorectal Polyp Patients and Controls Using Seemingly Unrelated Regression

Despite the fact that colorectal cancer (CRC) is one of the most prevalent and deadly cancers in the world, the development of improved and robust biomarkers to enable screening, surveillance, and therapy monitoring of CRC continues to be evasive. In particular, patients with colon polyps are at higher risk of developing colon cancer; however, noninvasive methods to identify these patients suffer from poor performance. In consideration of the challenges involved in identifying metabolite biomarkers in individuals with high risk for colon cancer, we have investigated NMR-based metabolite profiling in combination with numerous demographic parameters to investigate the ability of serum metabolites to differentiate polyp patients from healthy subjects. We also investigated the effect of disease risk on different groups of biologically related metabolites. A powerful statistical approach, seemingly unrelated regression (SUR), was used to model the correlated levels of metabolites in the same biological group. The metabolites were found to be significantly affected by demographic covariates such as gender, BMI, BMI(2), and smoking status. After accounting for the effects of the confounding factors, we then investigated potential of metabolites from serum to differentiate patients with polyps and age matched healthy controls. Our results showed that while only valine was slightly associated, individually, with polyp patients, a number of biologically related groups of metabolites were significantly associated with polyps. These results may explain some of the challenges and promise a novel avenue for future metabolite profiling methodologies.

Metabolomics method to comprehensively analyze amino acids in different domains

Amino acids play essential roles in both metabolism and the proteome. Many studies have profiled free amino acids (FAAs) or proteins; however, few have connected the measurement of FAA with individual amino acids in the proteome. In this study, we developed a metabolomics method to comprehensively analyze amino acids in different domains, using two examples of different sample types and disease models. We first examined the responses of FAAs and insoluble-proteome amino acids (IPAAs) to the Myc oncogene in Tet21N human neuroblastoma cells. The metabolic and proteomic amino acid profiles were quite different, even under the same Myc condition, and their combination provided a better understanding of the biological status. In addition, amino acids were measured in 3 domains (FAAs, free and soluble-proteome amino acids (FSPAAs), and IPAAs) to study changes in serum amino acid profiles related to colon cancer. A penalized logistic regression model based on the amino acids from the three domains had better sensitivity and specificity than that from each individual domain. To the best of our knowledge, this is the first study to perform a combined analysis of amino acids in different domains, and indicates the useful biological information available from a metabolomics analysis of the protein pellet. This study lays the foundation for further quantitative tracking of the distribution of amino acids in different domains, with opportunities for better diagnosis and mechanistic studies of various diseases.

Colorectal cancer detection using targeted serum metabolic profiling

Colorectal cancer (CRC) is one of the most prevalent and deadly cancers in the world. Despite an expanding knowledge of its molecular pathogenesis during the past two decades, robust biomarkers to enable screening, surveillance, and therapy monitoring of CRC are still lacking. In this study, we present a targeted liquid chromatography-tandem mass spectrometry-based metabolic profiling approach for identifying biomarker candidates that could enable highly sensitive and specific CRC detection using human serum samples. In this targeted approach, 158 metabolites from 25 metabolic pathways of potential significance were monitored in 234 serum samples from three groups of patients (66 CRC patients, 76 polyp patients, and 92 healthy controls). Partial least-squares-discriminant analysis (PLS-DA) models were established, which proved to be powerful for distinguishing CRC patients from both healthy controls and polyp patients. Receiver operating characteristic curves generated based on these PLS-DA models showed high sensitivities (0.96 and 0.89, respectively, for differentiating CRC patients from healthy controls or polyp patients), good specificities (0.80 and 0.88), and excellent areas under the curve (0.93 and 0.95). Monte Carlo cross validation was also applied, demonstrating the robust diagnostic power of this metabolic profiling approach.

Metabolomics: a window into the adaptive physiology of Mycobacterium tuberculosis

Mycobacterium tuberculosis is the causative agent of tuberculosis (TB) and second leading cause of human mortality due to a single infectious agent. This is mostly because of M. tuberculosis' ability to adapt its metabolism to the host environment and regulate entry into and exit from cell cycle. Knowledge of the specific metabolic changes accompanying these transitions however is incomplete. Metabolomics has emerged as a new biochemical window into M. tuberculosis physiology. This review highlights recent insights from the application of such technologies to studies of the M. tuberculosis lifecycle.

Microbial metabolomics: innovation, application, insight

Most textbooks depict metabolism as a well understood housekeeping function of cells. However, organisms vary in their metabolic needs according to the specific niches they reside in and selective pressures encountered therein. Recent advances in analytical chemistry have begun to reveal an unexpected diversity in the composition, structure and regulation of metabolic networks. Here, we review key technological developments in the area of metabolism and their impact on our understanding of the fundamental roles of metabolism in cellular physiology.

Rationales and approaches for studying metabolism in eukaryotic microalgae

The generation of efficient production strains is essential for the use of eukaryotic microalgae for biofuel production. Systems biology approaches including metabolite profiling on promising microalgal strains, will provide a better understanding of their metabolic networks, which is crucial for metabolic engineering efforts. Chlamydomonas reinhardtii represents a suited model system for this purpose. We give an overview to genetically amenable microalgal strains with the potential for biofuel production and provide a critical review of currently used protocols for metabolite profiling on Chlamydomonas. We provide our own experimental data to underpin the validity of the conclusions drawn.

Computer-aided design for metabolic engineering

The development and application of biotechnology-based strategies has had a great socio-economical impact and is likely to play a crucial role in the foundation of more sustainable and efficient industrial processes. Within biotechnology, metabolic engineering aims at the directed improvement of cellular properties, often with the goal of synthesizing a target chemical compound. The use of computer-aided design (CAD) tools, along with the continuously emerging advanced genetic engineering techniques have allowed metabolic engineering to broaden and streamline the process of heterologous compound-production. In this work, we review the CAD tools available for metabolic engineering with an emphasis, on retrosynthesis methodologies. Recent advances in genetic engineering strategies for pathway implementation and optimization are also reviewed as well as a range of bionalytical tools to validate in silico predictions. A case study applying retrosynthesis is presented as an experimental verification of the output from Retropath, the first complete automated computational pipeline applicable to metabolic engineering. Applying this CAD pipeline, together with genetic reassembly and optimization of culture conditions led to improved production of the plant flavonoid pinocembrin. Coupling CAD tools with advanced genetic engineering strategies and bioprocess optimization is crucial for enhanced product yields and will be of great value for the development of non-natural products through sustainable biotechnological processes.

Overview of mass spectrometry-based metabolomics: opportunities and challenges

The field of metabolomics has witnessed an exponential growth in the last decade driven by important applications spanning a wide range of areas in the basic and life sciences and beyond. Mass spectrometry in combination with chromatography and nuclear magnetic resonance are the two major analytical avenues for the analysis of metabolic species in complex biological mixtures. Owing to its inherent significantly higher sensitivity and fast data acquisition, MS plays an increasingly dominant role in the metabolomics field. Propelled by the need to develop simple methods to diagnose and manage the numerous and widespread human diseases, mass spectrometry has witnessed tremendous growth with advances in instrumentation, experimental methods, software, and databases. In response, the metabolomics field has moved far beyond qualitative methods and simple pattern recognition approaches to a range of global and targeted quantitative approaches that are now routinely used and provide reliable data, which instill greater confidence in the derived inferences. Powerful isotope labeling and tracing methods have become very popular. The newly emerging ambient ionization techniques such as desorption ionization and rapid evaporative ionization have allowed direct MS analysis in real time, as well as new MS imaging approaches. While the MS-based metabolomics has provided insights into metabolic pathways and fluxes, and metabolite biomarkers associated with numerous diseases, the increasing realization of the extremely high complexity of biological mixtures underscores numerous challenges including unknown metabolite identification, biomarker validation, and interlaboratory reproducibility that need to be dealt with for realization of the full potential of MS-based metabolomics. This chapter provides a glimpse at the current status of the mass spectrometry-based metabolomics field highlighting the opportunities and challenges.