Detailed mitochondrial phenotyping by high resolution metabolomics

Unlocking the Mitochondria for Nanomedicine-based Treatments: Overcoming Biological Barriers, Improving Designs, and Selecting Verification Techniques

Enhanced targeting approaches will support the treatment of diseases associated with dysfunctional mitochondria, which play critical roles in energy generation and cell survival. Obstacles to mitochondria-specific targeting include the presence of distinct biological barriers and the need to pass through (or avoid) various cell internalization mechanisms. A range of studies have reported the design of mitochondrially-targeted nanomedicines that navigate the complex routes required to influence mitochondrial function; nonetheless, a significant journey lies ahead before mitochondrially-targeted nanomedicines become suitable for clinical use. Moving swiftly forward will require safety studies, in vivo assays confirming effectiveness, and methodologies to validate mitochondria-targeted nanomedicines' subcellular location/activity. From a nanomedicine standpoint, we describe the biological routes involved (from administration to arrival within the mitochondria), the features influencing rational design, and the techniques used to identify/validate successful targeting. Overall, rationally-designed mitochondria-targeted-based nanomedicines hold great promise for precise subcellular therapeutic delivery.

ALTERATIONS IN HISTIDINE METABOLISM IS A FEATURE OF EARLY AUTOSOMAL DOMINANT POLYCYSTIC KIDNEY DISEASE (ADPKD)

Autosomal dominant polycystic kidney disease (ADPKD) is characterized by epithelial proliferation and progressive cyst enlargement. Using a non-targeted high-resolution metabolomics approach, we analyzed biofluids from 36 ADPKD and 18 healthy controls with estimated glomerular filtration rate (eGFR) > 60 ml/min to identify features specific to ADPKD or that associate with disease severity [eGFR or height-corrected total kidney volume (htTKV)]. Multiple pathways differed between ADPKD subjects and controls, with the histidine pathway being the most highly represented. Plasma histidine, urinary N-methylhistamine, methylimidazole-acetaldehyde, and imidazole-acetaldehyde, as well as 3-methylhistidine and anserine were increased, while plasma N-acetylhistamine and urinary imidazole-acetic acid were decreased in ADPKD compared to controls. In ADPKD, urinary histidine and a histidine derivative, urocanate (a precursor of glutamate), were significantly associated. HtTKV and eGFR were inversely associated with urinary glutamine and plasma 4-imidazolone-5-propionic acid, respectively. Supernatant from cultured human ADPKD renal cystic epithelia demonstrated increased aspartate and glutamate levels at 8 and 24 hours compared to primary tubular epithelia (p < 0.001). Following exposure over 48 hours to α-fluromethylhistidine, an inhibitor of histamine production, primary human PKD1 cyst epithelia proliferation increased significantly from baseline (p < 0.01) and greater than non-cystic epithelia (p < 0.05). The histidine ammonia lyase inhibitor nitromethane reversed α-fluromethylhistidine-induced cyst epithelia proliferation indicating a role for glutamate in cyst growth. In conclusion, histidine metabolism is altered preferentially leading to glutamate production and epithelial proliferation in ADPKD and associates with disease severity.

Mitochondrial Metabolomics of Sym1-Depleted Yeast Cells Revealed Them to Be Lysine Auxotroph

Metabolomics has expanded from cellular to subcellular level to elucidate subcellular compartmentalization. By applying isolated mitochondria to metabolome analysis, the hallmark of mitochondrial metabolites has been unraveled, showing compartment-specific distribution and regulation of metabolites. This method was employed in this work to study a mitochondrial inner membrane protein Sym1, whose human ortholog MPV17 is related to mitochondria DNA depletion syndrome. Gas chromatography-mass spectrometry-based metabolic profiling was combined with targeted liquid chromatography-mass spectrometry analysis to cover more metabolites. Furthermore, we applied a workflow employing ultra-high performance liquid chromatography-quadrupole time of flight mass spectrometry with a powerful chemometrics platform, focusing on only significantly changed metabolites. This workflow highly reduced the complexity of acquired data without losing metabolites of interest. Consequently, forty-one novel metabolites were identified in addition to the combined method, of which two metabolites, 4-guanidinobutanal and 4-guanidinobutanoate, were identified for the first time in Saccharomyces cerevisiae. With compartment-specific metabolomics, we identified sym1Δ cells as lysine auxotroph. The highly reduced carbamoyl-aspartate and orotic acid indicate a potential role of the mitochondrial inner membrane protein Sym1 in pyrimidine metabolism.

Advances in measuring cancer cell metabolism with subcellular resolution

Characterizing metabolism in cancer is crucial for understanding tumor biology and for developing potential therapies. Although most metabolic investigations analyze averaged metabolite levels from all cell compartments, subcellular metabolomics can provide more detailed insight into the biochemical processes associated with the disease. Methodological limitations have historically prevented the wider application of subcellular metabolomics in cancer research. Recently, however, ways to distinguish and identify metabolic pathways within organelles have been developed, including state-of-the-art methods to monitor metabolism in situ (such as mass spectrometry-based imaging, Raman spectroscopy and fluorescence microscopy), to isolate key organelles via new approaches and to use tailored isotope-tracing strategies. Herein, we examine the advantages and limitations of these developments and look to the future of this field of research.

Subcellular metabolomics: Isolation, measurement, and applications

Metabolomics, a technique that profiles global small molecules in biological samples, has been a pivotal tool for disease diagnosis and mechanism research. The sample type in metabolomics covers a wide range, including a variety of body fluids, tissues, and cells. However, little attention was paid to the smaller, relatively independent partition systems in cells, namely the organelles. The organelles are specific compartments/places where diverse metabolic activities are happening in an orderly manner. Metabolic disorders of organelles were found to occur in various pathological conditions such as inherited metabolic diseases, diabetes, cancer, and neurodegenerative diseases. However, at the cellular level, the metabolic outcomes of organelles and cytoplasm are superimposed interactively, making it difficult to describe the changes in subcellular compartments. Therefore, characterizing the metabolic pool in the compartmentalized system is of great significance for understanding the role of organelles in physiological functions and diseases. So far, there are very few research articles or reviews related to subcellular metabolomics. In this review, subcellular fractionation and metabolite analysis methods, as well as the application of subcellular metabolomics in the physiological and pathological studies are systematically reviewed, as a practical reference to promote the continued advancement in subcellular metabolomics.

Sub-Cellular Metabolomics Contributes Mitochondria-Specific Metabolic Insights to a Mouse Model of Leigh Syndrome

Direct injury of mitochondrial respiratory chain (RC) complex I by Ndufs4 subunit mutations results in complex I deficiency (CID) and a progressive encephalomyopathy, known as Leigh syndrome. While mitochondrial, cytosolic and multi-organelle pathways are known to be involved in the neuromuscular LS pathogenesis, compartment-specific metabolomics has, to date, not been applied to murine models of CID. We thus hypothesized that sub-cellular metabolomics would be able to contribute organelle-specific insights to known Ndufs4 metabolic perturbations. To that end, whole brains and skeletal muscle from late-stage Ndufs4 mice and age/sex-matched controls were harvested for mitochondrial and cytosolic isolation. Untargeted ¹H-NMR and semi-targeted LC-MS/MS metabolomics was applied to the resulting cell fractions, whereafter important variables (VIPs) were selected by univariate statistics. A predominant increase in multiple targeted amino acids was observed in whole-brain samples, with a more prominent effect at the mitochondrial level. Similar pathways were implicated in the muscle tissue, showing a greater depletion of core metabolites with a compartment-specific distribution, however. The altered metabolites expectedly implicate altered redox homeostasis, alternate RC fueling, one-carbon metabolism, urea cycling and dysregulated proteostasis to different degrees in the analyzed tissues. A first application of EDTA-chelated magnesium and calcium measurement by NMR also revealed tissue- and compartment-specific alterations, implicating stress response-related calcium redistribution between neural cell compartments, as well as whole-cell muscle magnesium depletion. Altogether, these results confirm the ability of compartment-specific metabolomics to capture known alterations related to Ndufs4 KO and CID while proving its worth in elucidating metabolic compartmentalization in said pathways that went undetected in the diluted whole-cell samples previously studied.

Trisomy 21 results in modest impacts on mitochondrial function and central carbon metabolism

Down syndrome (DS) is the most common genetic cause of intellectual disability. Mechanistically, oxidative stress and mitochondrial dysfunction are reported to be etiological factors for many of the DS-related comorbidities and have previously been reported in a number of in vitro and in vivo models of DS. The purpose of this study was to test for the presence of mitochondrial dysfunction in fibroblast cells obtained via skin biopsy from individuals with DS, and to assess the impact of trisomy 21 on central carbon metabolism. Using extracellular flux assays in matched dermal fibroblasts from euploid and DS individuals, we found that basal mitochondrial dysfunction is quite mild. Stressing the cells with a cocktail of mitochondrial stressors revealed a significant mitochondrial deficit in DS cells compared to euploid controls. Evaluation of extracellular acidification rate did not reveal a baseline abnormality in glycolysis; however, metabolomic assessments utilizing isotopically labeled glucose and glutamine revealed altered central carbon metabolism in DS cells. Specifically, we observed greater glucose dependency, uptake and flux into the oxidative phase of the pentose phosphate pathway in DS fibroblasts. Furthermore, using induced pluripotent stem cells (iPSC) we found that mitochondrial function in DS iPSCs was similar to the previously published studies employing fetal cells. Together, these data indicate that aberrant central carbon metabolism is a candidate mechanism for stress-related mitochondrial dysfunction in DS.

Transporters at the Interface between Cytosolic and Mitochondrial Amino Acid Metabolism

Mitochondria are central organelles that coordinate a vast array of metabolic and biologic functions important for cellular health. Amino acids are intricately linked to the bioenergetic, biosynthetic, and homeostatic function of the mitochondrion and require specific transporters to facilitate their import, export, and exchange across the inner mitochondrial membrane. Here we review key cellular metabolic outputs of eukaryotic mitochondrial amino acid metabolism and discuss both known and unknown transporters involved. Furthermore, we discuss how utilization of compartmentalized amino acid metabolism functions in disease and physiological contexts. We examine how improved methods to study mitochondrial metabolism, define organelle metabolite composition, and visualize cellular gradients allow for a more comprehensive understanding of how transporters facilitate compartmentalized metabolism.

Isolation and Metabolic Assessment of Cancer Cell Mitochondria

Mitochondrial metabolism plays an essential role in various biological processes of cancer cells. Herein, we established an experimental procedure for the metabolic assessment of mitochondria in cancer cells. We examined procedures for mitochondrial isolation coupled with various mitochondrial extraction buffers in three major cancer cell lines (PANC1, A549, and MDA-MB-231) and identified a potentially optimal and generalized approach. The purity of the mitochondrial fraction isolated by the selected protocol was verified using specific protein markers of cellular components, and the ultrastructure of the isolated mitochondria was also analyzed by transmission electron microscopy. The isolation procedure, involving a bead beater for cell lysis, a modified sucrose buffer, and differential centrifugation, appeared to be a suitable method for the extraction of mitochondria from cancer cells. Electron micrographs indicated an intact two-layer membrane and inner structures of mitochondria isolated by this procedure. Metabolomic and lipidomic analyses were conducted to examine the metabolic phenotypes of the mitochondria-enriched fractions and associated bulk cancer cells. A total of 44 metabolites, including malate and succinate, occurred at significantly higher levels in the mitochondrial fractions, whereas 51 metabolites, including citrate, oxaloacetate, and fumarate of the Krebs cycle and the oncometabolites glutamine and glutamate, were reduced in mitochondria compared to that in the corresponding bulk cells of PANC1. Similar patterns were observed in mitochondria and bulk cells of MDA-MB-231 and A549 cell lines. A clear difference between the lipid profiles of bulk PANC1, MDA-MB-231, and A549 and corresponding mitochondrial fractions of these cell lines was detected by principal component analysis. In conclusion, we developed an experimental procedure for a large-scale metabolic assessment for suborganelle metabolic profiling and multiple omics data integration in cancer cells with broad applications.

Metabolic Modelling as a Framework for Metabolomics Data Integration and Analysis

Metabolic networks are regulated to ensure the dynamic adaptation of biochemical reaction fluxes to maintain cell homeostasis and optimal metabolic fitness in response to endogenous and exogenous perturbations. To this end, metabolism is tightly controlled by dynamic and intricate regulatory mechanisms involving allostery, enzyme abundance and post-translational modifications. The study of the molecular entities involved in these complex mechanisms has been boosted by the advent of high-throughput technologies. The so-called omics enable the quantification of the different molecular entities at different system layers, connecting the genotype with the phenotype. Therefore, the study of the overall behavior of a metabolic network and the omics data integration and analysis must be approached from a holistic perspective. Due to the close relationship between metabolism and cellular phenotype, metabolic modelling has emerged as a valuable tool to decipher the underlying mechanisms governing cell phenotype. Constraint-based modelling and kinetic modelling are among the most widely used methods to study cell metabolism at different scales, ranging from cells to tissues and organisms. These approaches enable integrating metabolomic data, among others, to enhance model predictive capabilities. In this review, we describe the current state of the art in metabolic modelling and discuss future perspectives and current challenges in the field.

Novel mitochondrial and cytosolic purification pipeline for compartment-specific metabolomics in mammalian disease model tissues

INTRODUCTION

Mitochondria represent an important milieu for studying the pathogenesis of several major diseases. The need for organelle-level metabolic resolution exists, as mitochondrial/cytosolic metabolites are often diluted beyond detection limits in complex samples. Compartment-specific studies are still hindered by the lack of efficient, cost-effective fractioning methods-applicable to laboratories of all financial/analytical standing.

OBJECTIVES

We established a novel mitochondrial/cytosolic purification pipeline for complimentary GC-TOF-MS and ¹H-NMR metabolomics using robust, commercially available fractionation strategies.

METHODS

Magnetic based mitochondria isolation kits (MACS) were adapted for this purpose, accompanied by cytosolic filtering. Yield was assessed through the percentage recovery of citrate synthase (CS; a mitochondrial marker), purity by immunoblotting against compartment-specific proteins and integrity interrogated through the respiratory coupling ratio (RCR). The effects of the kit-based buffers on MS/NMR analyses of pure metabolite standards were evaluated. Finally, biological applicability to mammalian disease models was shown using Ndufs4 mouse brain tissue.

RESULTS

With minor modifications, MACS produced around 60% more mitochondria compared to a differential centrifugation method. Less than 15% of lysosomal LAMP-2 protein was found in the MACS isolates, confirming relative purity-while RCR's above 6 indicate sufficient mitochondrial integrity. The filtering approach effectively depleted mitochondria from the cytosolic fraction, as indicated by negligible Hsp60 and CS levels. Our GC-MS pilot yielded 60-70 features per fraction, while NMR analyses could quantify 6-10 of the most abundant compounds in each fraction.

CONCLUSION

This study provides a simple and flexible solution for mitochondrial and cytosolic metabolomics in animal model tissues, towards large-scale application of such methodologies in disease research.

Omics Integration for Mitochondria Systems Biology

Significance: Elucidation of the central importance of mitophagy in homeostasis of cells and organisms emphasizes that mitochondrial functions extend far beyond short-term needs for energy production. In mitochondria systems biology, the mitochondrial genome, proteome, and metabolome operate as a functional network in coordination of cell activities. Organization occurs through subnetworks that are interconnected by membrane potential, transport activities, allosteric and cooperative interactions, redox signaling mechanisms, rheostatic control by post-translational modifications, and metal ion homeostasis. These subnetworks enable use of varied energy precursors, defense against environmental stressors, and macromolecular rewiring to titrate energy production, biosynthesis, and detoxification according to cell-specific needs. Rewiring mechanisms, termed mitochondrial reprogramming, enhance fitness to respond to metabolic resources and challenges from the environment. Maladaptive responses can cause cell death. Maladaptive rewiring can cause disease. In cancer, adaptive rewiring can interfere with effective treatment. Recent Advances: Many recent advances have been facilitated by the development of new omics tools, which create opportunities to use data-driven analysis of omics data to address these complex adaptive and maladaptive mechanisms of mitochondrial reprogramming in human disease. Critical Issues: Application of omics integration to model systems reveals a critical role for metal ion homeostasis broadly impacting mitochondrial reprogramming. Importantly, data show that trans-omics associations are more robust and biologically relevant than single omics associations. Future Directions: Application of omics integration to mitophagy research creates new opportunities to link the complex, interactive functions of mitochondrial form and function in mitochondria systems biology.

Integrative omics approaches provide biological and clinical insights: examples from mitochondrial diseases

High-throughput technologies for genomics, transcriptomics, proteomics, and metabolomics, and integrative analysis of these data, enable new, systems-level insights into disease pathogenesis. Mitochondrial diseases are an excellent target for hypothesis-generating omics approaches, as the disease group is mechanistically exceptionally complex. Although the genetic background in mitochondrial diseases is in either the nuclear or the mitochondrial genome, the typical downstream effect is dysfunction of the mitochondrial respiratory chain. However, the clinical manifestations show unprecedented variability, including either systemic or tissue-specific effects across multiple organ systems, with mild to severe symptoms, and occurring at any age. So far, the omics approaches have provided mechanistic understanding of tissue-specificity and potential treatment options for mitochondrial diseases, such as metabolome remodeling. However, no curative treatments exist, suggesting that novel approaches are needed. In this Review, we discuss omics approaches and discoveries with the potential to elucidate mechanisms of and therapies for mitochondrial diseases.

Should we consider subcellular compartmentalization of metabolites, and if so, how do we measure them?

PURPOSE OF REVIEW

To examine the consequences of metabolism compartmentalized at the subcellular level, provide prototypical examples of compartmentalized metabolism, and describe methods to examine compartmentalized metabolism.

RECENT FINDINGS

Progress in metabolomics and isotope tracing has underscored the importance of subcellular compartments of metabolism. The discovery of biological effects of metabolites as bioenergetic intermediates, anabolic building blocks, signaling mediators, and effectors in posttranslation modifications of proteins and nucleic acids have highlighted the role of compartmentalization in determining metabolic fate. Recent advances in both direct and indirect methods to quantify compartmentalized metabolism have improved upon historical approaches. Genetically encoded metabolite sensors, chemical probes, immunoaffinity purification, and compartment-resolved metabolic modeling have all been recently applied to study compartmentalization.

SUMMARY

Accurate measurement of metabolites in distinct subcellular compartments is important for understanding and pharmacologically targeting metabolic pathways in diverse disease contexts, including cancer, diabetes, heart failure, obesity, and regulation of the immune system. Direct and indirect approaches to quantify compartmentalized metabolism are advancing rapidly. Yet, major challenges remain in the generalizability, rigor, and interpretation of data from the available methods to quantify compartmentalized metabolism.

A biplot correlation range for group-wise metabolite selection in mass spectrometry

Background

Analytic methods are available to acquire extensive metabolic information in a cost-effective manner for personalized medicine, yet disease risk and diagnosis mostly rely upon individual biomarkers based on statistical principles of false discovery rate and correlation. Due to functional redundancies and multiple layers of regulation in complex biologic systems, individual biomarkers, while useful, are inherently limited in disease characterization. Data reduction and discriminant analysis tools such as principal component analysis (PCA), partial least squares (PLS), or orthogonal PLS (O-PLS) provide approaches to separate the metabolic phenotypes, but do not offer a statistical basis for selection of group-wise metabolites as contributors to metabolic phenotypes.

Methods

We present a dimensionality-reduction based approach termed ‘biplot correlation range (BCR)’ that uses biplot correlation analysis with direct orthogonal signal correction and PLS to provide the group-wise selection of metabolic markers contributing to metabolic phenotypes.

Results

Using a simulated multiple-layer system that often arises in complex biologic systems, we show the feasibility and superiority of the proposed approach in comparison of existing approaches based on false discovery rate and correlation. To demonstrate the proposed method in a real-life dataset, we used LC-MS based metabolomics to determine spectrum of metabolites present in liver mitochondria from wild-type (WT) mice and thioredoxin-2 transgenic (TG) mice. We select discriminatory variables in terms of increased score in the direction of class identity using BCR. The results show that BCR provides means to identify metabolites contributing to class separation in a manner that a statistical method by false discovery rate or statistical total correlation spectroscopy can hardly find in complex data analysis for predictive health and personalized medicine.

Electronic supplementary material

The online version of this article (10.1186/s13040-019-0191-2) contains supplementary material, which is available to authorized users.

MITO-Tag Mice enable rapid isolation and multimodal profiling of mitochondria from specific cell types in vivo

Mitochondria are metabolic organelles that are essential for mammalian life, but the dynamics of mitochondrial metabolism within mammalian tissues in vivo remains incompletely understood. While whole-tissue metabolite profiling has been useful for studying metabolism in vivo, such an approach lacks resolution at the cellular and subcellular level. In vivo methods for interrogating organellar metabolites in specific cell types within mammalian tissues have been limited. To address this, we built on prior work in which we exploited a mitochondrially localized 3XHA epitope tag (MITO-Tag) for the fast isolation of mitochondria from cultured cells to generate MITO-Tag Mice. Affording spatiotemporal control over MITO-Tag expression, these transgenic animals enable the rapid, cell-type-specific immunoisolation of mitochondria from tissues, which we verified using a combination of proteomic and metabolomic approaches. Using MITO-Tag Mice and targeted and untargeted metabolite profiling, we identified changes during fasted and refed conditions in a diverse array of mitochondrial metabolites in hepatocytes and found metabolites that behaved differently at the mitochondrial versus whole-tissue level. MITO-Tag Mice should have utility for studying mitochondrial physiology, and our strategy should be generally applicable for studying other mammalian organelles in specific cell types in vivo.

Stereochemical and structural effects of (2R,6R)-hydroxynorketamine on the mitochondrial metabolome in PC-12 cells

BACKGROUND

Impairment in mitochondrial biogenesis and function plays a key role in depression and anxiety, both of which being associated with changes in fatty acid and phospholipid metabolism. The antidepressant effects of (R,S)-ketamine have been linked to its conversion into (2S,6S;2R,6R)-hydroxynorketamine (HNK); however, the connection between structure and stereochemistry of ketamine and HNK in the mitochondrial homeostatic response has not yet been fully elucidated at a metabolic level.

METHODS

We used a multi-platform, non-targeted metabolomics approach to study the change in mitochondrial metabolome of PC-12 cells treated with ketamine and HNK enantiomers. The identified metabolites were grouped into pathways in order to assess global responses.

RESULTS

Treatment with (2R,6R)-HNK elicited the significant change in 49 metabolites and associated pathways implicated in fundamental mitochondrial functions such as TCA cycle, branched-chain amino acid biosynthetic pathway, glycoxylate metabolic pathway, and fatty acid β-oxidation. The affected metabolites included glycerate, citrate, leucine, N,N-dimethylglycine, 3-hexenedioic acid, and carnitine and attenuated signals associated with 9 fatty acids and elaidic acid. Important metabolites involved in the purine and pyrimidine pathways were also affected by (2R-6R)-HNK. This global metabolic profile was not as strongly impacted by treatment with (2S,6S)-HNK, (R)- and (S)-ketamine and in some instances opposite effects were observed.

CONCLUSIONS

The present data provide an overall view of the metabolic changes in mitochondrial function produced by (2R,6R)-HNK and related ketamine compounds and offer an insight into the source of the observed variance in antidepressant response elicited by the compounds.

Metabolic profiling of isolated mitochondria and cytoplasm reveals compartment-specific metabolic responses

INTRODUCTION

Subcellular compartmentalization enables eukaryotic cells to carry out different reactions at the same time, resulting in different metabolite pools in the subcellular compartments. Thus, mutations affecting the mitochondrial energy metabolism could cause different metabolic alterations in mitochondria compared to the cytoplasm. Given that the metabolite pool in the cytosol is larger than that of other subcellular compartments, metabolic profiling of total cells could miss these compartment-specific metabolic alterations.

OBJECTIVES

To reveal compartment-specific metabolic differences, mitochondria and the cytoplasmic fraction of baker's yeast Saccharomyces cerevisiae were isolated and subjected to metabolic profiling.

METHODS

Mitochondria were isolated through differential centrifugation and were analyzed together with the remaining cytoplasm by gas chromatography-mass spectrometry (GC-MS) based metabolic profiling.

RESULTS

Seventy-two metabolites were identified, of which eight were found exclusively in mitochondria and sixteen exclusively in the cytoplasm. Based on the metabolic signature of mitochondria and of the cytoplasm, mutants of the succinate dehydrogenase (respiratory chain complex II) and of the F_OF₁-ATP-synthase (complex V) can be discriminated in both compartments by principal component analysis from wild-type and each other. These mitochondrial oxidative phosphorylation machinery mutants altered not only citric acid cycle related metabolites but also amino acids, fatty acids, purine and pyrimidine intermediates and others.

CONCLUSION

By applying metabolomics to isolated mitochondria and the corresponding cytoplasm, compartment-specific metabolic signatures can be identified. This subcellular metabolomics analysis is a powerful tool to study the molecular mechanism of compartment-specific metabolic homeostasis in response to mutations affecting the mitochondrial metabolism.

Recent advances in using mass spectrometry for mitochondrial metabolomics and lipidomics - A review

Metabolomics and lipidomics generally targets a huge number of intermediate and end products of cellular metabolism in body fluids, tissues, and cells etc. At present, mass spectrometry (MS) based metabolic or lipid profiling of routine biological specimens including the whole cells, tissues, plasma, serum and urine etc., can cover hundreds of metabolites or lipid species in one analysis, which has qualified deep elucidation of global metabolic and lipid networks. Mitochondria are important intracellular organelles and many critical biochemical reactions occur here, they provide building block for new cells, control redox balance, participate in apoptosis and behave as a signalling platform. Evidence suggests high prevalence of mitochondrial dysfunction occurs in a variety of cancers and other diseases, thus there is an urgent demand for investigating and clarifying mitochondrial metabolic and lipid alterations induced by diseases. Nevertheless, mitochondria contribute a small fraction to cellular contents, profiling of whole cell is probably unsuitable for monitoring alterations in mitochondria. Therefore, metabolomics and lipidomics analyses specially for mitochondria are necessary to understand disturbed metabolic and lipid pathways induced by environment and diseases. However, methods for comprehensively profiling metabolites and lipids in mitochondria have been limited at present. This review summarizes the current states and progress of MS-based mitochondrial metabolomics and lipidomics study. Details of mitochondrial isolation procedure, analytical methods and their applications are described. The challenges and opportunities are also given.

Cellular and mitochondrial determination of low molecular mass organic acids by LC-MS/MS

A selective and sensitive method for the determination of low molecular mass organic acids (LMMOAs) in cell and mitochondrial extracts is presented. The analytical method consists in the separation by reversed phase liquid chromatography and detection with tandem mass spectrometry (LC-MS/MS) of the LMMOAs like malic, succinic, formic and citric acids. These acids are among the cellular intermediates of the tricarboxylic acid cycle (TCA), thus their quantitation can provide essential information about the catabolic and anabolic processes occurring in cells under physiological and pathological conditions. The analytical method was fully validated in terms of linearity, detection and quantification limits, recovery and precision. Detection limits (LOD) for malic, succinic and fumaric acids were in the range of 1-10nM, while 20nM was obtained for citric acid. Analytical recovery in cell and mitochondrial extracts was found between 88 and 105% (CV% ≤7.1) and matrix effect was estimated to be less than 108%. The LC-MS/MS method applied to the quantification of TCA cycle metabolites revealed a different distribution of the four acids in cells and mitochondria, and it could be used to monitoring metabolic alterations associated with TCA cycle and oxidative phosphorylation dysfunctions.

Rapid immunopurification of mitochondria for metabolite profiling and absolute quantification of matrix metabolites

Mitochondria carry out numerous metabolic reactions that are critical to cellular homeostasis. Here we present a protocol for interrogating mitochondrial metabolites and measuring their matrix concentrations. Our workflow uses high-affinity magnetic immunocapture to rapidly purify HA-tagged mitochondria from homogenized mammalian cells in ∼12 min. These mitochondria are extracted with methanol and water. Liquid chromatography and mass spectrometry (LC/MS) is used to determine the identities and mole quantities of mitochondrial metabolites using authentic metabolite standards and isotopically labeled internal standards, whereas the corresponding mitochondrial matrix volume is determined via immunoblotting, confocal microscopy of intact cells, and volumetric analysis. Once all values have been obtained, the matrix volume is combined with the aforementioned mole quantities to calculate the matrix concentrations of mitochondrial metabolites. With shortened isolation times and improved mitochondrial purity when compared with alternative methods, this LC/MS-compatible workflow allows for robust profiling of mitochondrial metabolites and serves as a strategy generalizable to the study of other mammalian organelles. Once all the necessary reagents have been prepared, quantifying the matrix concentrations of mitochondrial metabolites can be accomplished within a week.

The rise of mitochondria in medicine

Once considered exclusively the cell's powerhouse, mitochondria are now recognized to perform multiple essential functions beyond energy production, impacting most areas of cell biology and medicine. Since the emergence of molecular biology and the discovery of pathogenic mitochondrial DNA defects in the 1980's, research advances have revealed a number of common human diseases which share an underlying pathogenesis involving mitochondrial dysfunction. Mitochondria undergo function-defining dynamic shape changes, communicate with each other, regulate gene expression within the nucleus, modulate synaptic transmission within the brain, release molecules that contribute to oncogenic transformation and trigger inflammatory responses systemically, and influence the regulation of complex physiological systems. Novel mitopathogenic mechanisms are thus being uncovered across a number of medical disciplines including genetics, oncology, neurology, immunology, and critical care medicine. Increasing knowledge of the bioenergetic aspects of human disease has provided new opportunities for diagnosis, therapy, prevention, and in connecting various domains of medicine. In this article, we overview specific aspects of mitochondrial biology that have contributed to - and likely will continue to enhance the progress of modern medicine.

Absolute Quantification of Matrix Metabolites Reveals the Dynamics of Mitochondrial Metabolism

Mitochondria house metabolic pathways that impact most aspects of cellular physiology. While metabolite profiling by mass spectrometry is widely applied at the whole-cell level, it is not routinely possible to measure the concentrations of small molecules in mammalian organelles. We describe a method for the rapid and specific isolation of mitochondria and use it in tandem with a database of predicted mitochondrial metabolites ("MITObolome") to measure the matrix concentrations of more than 100 metabolites across various states of respiratory chain (RC) function. Disruption of the RC reveals extensive compartmentalization of mitochondrial metabolism and signatures unique to the inhibition of each RC complex. Pyruvate enables the proliferation of RC-deficient cells but has surprisingly limited effects on matrix contents. Interestingly, despite failing to restore matrix NADH/NAD balance, pyruvate does increase aspartate, likely through the exchange of matrix glutamate for cytosolic aspartate. We demonstrate the value of mitochondrial metabolite profiling and describe a strategy applicable to other organelles.

Deployment-Associated Exposure Surveillance With High-Resolution Metabolomics

OBJECTIVE

The aim of this study was to assess the suitability of high-resolution metabolomics (HRM) for measure of internal exposure and effect biomarkers from deployment-related environmental hazards.

METHODS

HRM provides extensive coverage of metabolism and data relevant to a broad spectrum of environmental exposures. This review briefly describes the analytic platform, workflow, and recent applications of HRM as a prototype environmental exposure surveillance system.

RESULTS

Building upon techniques available for contemporary occupational medicine and exposure sciences, HRM methods are able to integrate external exposures, internal body burden of environmental agents, and relevant biological responses with health outcomes.

CONCLUSIONS

Systematic analysis of existing Department of Defense Serum Repository samples will provide a high-quality, cross-sectional reference dataset for deployment-associated exposures while at the same time establishing a foundation for precision medicine.

Plasma Metabolomics of Common Marmosets (Callithrix jacchus) to Evaluate Diet and Feeding Husbandry

Common marmosets (Callithrix jacchus) are an important NHP model for the study of human aging and age-related diseases. However, the full potential of marmosets as a research model has not been realized due to a lack of evidence-based, standardized procedures for their captive management, especially regarding diet and feeding husbandry. In the present study, we conducted a high-resolution metabolomics analysis of plasma from marmosets from a 3-mo dietary crossover study to determine whether significant metabolic differences occur with a semisynthetic chemically defined (purified) diet as needed for controlled nutrition research. Marmosets were fed a standard, diverse-ingredient diet, followed by a semisynthetic purified diet, and then were switched back to the standard diet. The standard diet used in this analysis was specific to the animal facility, but it is similar in content to the diets currently used for other marmoset colonies. High-resolution metabolomics of plasma with liquid chromatography-mass spectrometry and bioinformatics was used to measure metabolic differences. The concentration of the essential amino acids methionine, leucine/isoleucine, lysine, and threonine were higher when marmosets were fed the purified diet. In contrast, phenylalanine concentrations were higher during exposure to the standard diet. In addition, metabolic pathway enrichment and analysis revealed differences among metabolites associated with dopamine metabolism and the carnitine shuttle. These results show that diet-associated differences in metabolism occur in marmosets and suggest that additional nutritional studies with detailed physiologic characterization are needed to optimize standard and purified diets for common marmosets.

Preparation of Mitochondrial Enriched Fractions for Metabolic Analysis in Drosophila

Since mitochondria play roles in amino acid metabolism, carbohydrate metabolism and fatty acid oxidation, defects in mitochondrial function often compromise the lives of those who suffer from these complex diseases. Detecting mitochondrial metabolic changes is vital to the understanding of mitochondrial disorders and mitochondrial responses to pharmacological agents. Although mitochondrial metabolism is at the core of metabolic regulation, the detection of subtle changes in mitochondrial metabolism may be hindered by the overrepresentation of other cytosolic metabolites obtained using whole organism or whole tissue extractions. Here we describe an isolation method that detected pronounced mitochondrial metabolic changes in Drosophila that were distinct between whole-fly and mitochondrial enriched preparations. To illustrate the sensitivity of this method, we used a set of Drosophila harboring genetically diverse mitochondrial DNAs (mtDNA) and exposed them to the drug rapamycin. Using this method we showed that rapamycin modifies mitochondrial metabolism in a mitochondrial-genotype-dependent manner. However, these changes are much more distinct in metabolomics studies when metabolites were extracted from mitochondrial enriched fractions. In contrast, whole tissue extracts only detected metabolic changes mediated by the drug rapamycin independently of mtDNAs.

Metabolomics – the complementary field in systems biology: a review on obesity and type 2 diabetes

This paper highlights the metabolomic roles in systems biology towards the elucidation of metabolic mechanisms in obesity and type 2 diabetes.

Short-term oral atrazine exposure alters the plasma metabolome of male C57BL/6 mice and disrupts α-linolenate, tryptophan, tyrosine and other major metabolic pathways

Overexposure to the commonly used herbicide atrazine (ATR) affects several organ systems, including the brain. Previously, we demonstrated that short-term oral ATR exposure causes behavioral deficits and dopaminergic and serotonergic dysfunction in the brains of mice. Using adult male C57BL/6 mice, the present study aimed to investigate effects of a 10-day oral ATR exposure (0, 5, 25, 125, or 250mg/kg) on the mouse plasma metabolome and to determine metabolic pathways affected by ATR that may be reflective of ATR's effects on the brain and useful to identify peripheral biomarkers of neurotoxicity. Four hours after the last dosing on day 10, plasma was collected and analyzed with high-performance, dual chromatography-Fourier-transform mass spectrometry that was followed by biostatistical and bioinformatic analyses. ATR exposure (≥5mg/kg) significantly altered plasma metabolite profile and resulted in a dose-dependent increase in the number of metabolites with ion intensities significantly different from the control group. Pathway analyses revealed that ATR exposure strongly correlated with and disrupted multiple metabolic pathways. Tyrosine, tryptophan, linoleic acid and α-linolenic acid metabolic pathways were among the affected pathways, with α-linolenic acid metabolism being affected to the greatest extent. Observed effects of ATR on plasma tyrosine and tryptophan metabolism may be reflective of the previously reported perturbations of brain dopamine and serotonin homeostasis, respectively. ATR-caused alterations in the plasma profile of α-linolenic acid metabolism are a potential novel and sensitive plasma biomarker of ATR effect and plasma metabolomics could be used to better assess the risks, including to the brain, associated with ATR overexposure.

Bile acid aspiration associated with lung chemical profile linked to other biomarkers of injury after lung transplantation

Aspiration of gastrointestinal contents has been linked to worse outcomes following lung transplantation but uncertainty exists about underlying mechanisms. We applied high-resolution metabolomics of bronchoalveolar lavage fluid (BALF) in patients with episodic aspiration (defined by bile acids in the BALF) to identify potential metabolic changes associated with aspiration. Paired samples, one with bile acids and another without, from 29 stable lung transplant patients were studied. Liquid chromatography coupled to high-resolution mass spectroscopy was used to interrogate metabolomic contents of these samples. Data were obtained for 7068 ions representing intermediary metabolites, environmental agents and chemicals associated with microbial colonization. A substantial number (2302) differed between bile acid positive and negative samples when analyzed by false discovery rate at q = 0.01. These included pathways associated with microbial metabolism. Hierarchical cluster analysis defined clusters of chemicals associated with bile acid aspiration that were correlated to previously reported biomarkers of lung injury including T cell granzyme B level and the chemoattractants CXCL9 and CXCL10. These data specifically link bile acids presence in lung allografts to inflammatory pathways known to segregate with worsening allograft outcome, and provide additional mechanistic insight into the association between reflux and lung allograft injury.

Integrated redox proteomics and metabolomics of mitochondria to identify mechanisms of cd toxicity

Cadmium (Cd) exposure contributes to human diseases affecting liver, kidney, lung, and other organ systems, but mechanisms underlying the pleotropic nature of these toxicities are poorly understood. Cd accumulates in humans from dietary, environmental (including cigarette smoke), and occupational sources, and has a twenty-year biologic half-life. Our previous mouse and cell studies showed that environmental low-dose Cd exposure altered protein redox states resulting in stimulation of inflammatory signaling and disruption of the actin cytoskeleton system, suggesting that Cd could impact multiple mechanisms of disease. In the current study, we investigated the effects of acute Cd exposure on the redox proteome and metabolome of mouse liver mitochondria to gain insight into associated toxicological mechanisms and functions. We analyzed redox states of liver mitochondrial proteins by redox proteomics using isotope coded affinity tag (ICAT) combined mass spectrometry. Redox ICAT identified 2687 cysteine-containing peptides (peptidyl Cys) of which 1667 peptidyl Cys (657 proteins) were detected in both control and Cd-exposed samples. Of these, 46% (1247 peptidyl Cys, 547 proteins) were oxidized by Cd more than 1.5-fold relative to controls. Bioinformatics analysis using MetaCore software showed that Cd affected 86 pathways, including 24 Cys in proteins functioning in branched chain amino acid (BCAA) and 14 Cys in proteins functioning in fatty acid (acylcarnitine/carnitine) metabolism. Consistently, high-resolution metabolomics data showed that Cd treatment altered levels of BCAA and carnitine metabolites. Together, these results show that mitochondrial protein redox and metabolites are targets in Cd-induced hepatotoxicity. The results further indicate that redox proteomics and metabolomics can be used in an integrated systems approach to investigate complex disease mechanisms.

Mitochondrial metabolomics using high-resolution Fourier-transform mass spectrometry

High-resolution Fourier-transform mass spectrometry (FTMS) provides important advantages in studies of metabolism because more than half of common intermediary metabolites can be measured in 10 min with minimal pre-detector separation and without ion dissociation. This capability allows unprecedented opportunity to study complex metabolic systems, such as mitochondria. Analysis of mouse liver mitochondria using FTMS with liquid chromatography shows that sex and genotypic differences in mitochondrial metabolism can be readily distinguished. Additionally, differences in mitochondrial function are readily measured, and many of the mitochondria-related metabolites are also measurable in plasma. Thus, application of high-resolution mass spectrometry provides an approach for integrated studies of complex metabolic processes of mitochondrial function and dysfunction in disease.

Metabolomics in toxicology and preclinical research

Metabolomics, the comprehensive analysis of metabolites in a biological system, provides detailed information about the biochemical/physiological status of a biological system, and about the changes caused by chemicals. Metabolomics analysis is used in many fields, ranging from the analysis of the physiological status of genetically modified organisms in safety science to the evaluation of human health conditions. In toxicology, metabolomics is the -omics discipline that is most closely related to classical knowledge of disturbed biochemical pathways. It allows rapid identification of the potential targets of a hazardous compound. It can give information on target organs and often can help to improve our understanding regarding the mode-of-action of a given compound. Such insights aid the discovery of biomarkers that either indicate pathophysiological conditions or help the monitoring of the efficacy of drug therapies. The first toxicological applications of metabolomics were for mechanistic research, but different ways to use the technology in a regulatory context are being explored. Ideally, further progress in that direction will position the metabolomics approach to address the challenges of toxicology of the 21st century. To address these issues, scientists from academia, industry, and regulatory bodies came together in a workshop to discuss the current status of applied metabolomics and its potential in the safety assessment of compounds. We report here on the conclusions of three working groups addressing questions regarding 1) metabolomics for in vitro studies 2) the appropriate use of metabolomics in systems toxicology, and 3) use of metabolomics in a regulatory context.

Serum metabolomics of slow vs. rapid motor progression Parkinson's disease: a pilot study

Progression of Parkinson's disease (PD) is highly variable, indicating that differences between slow and rapid progression forms could provide valuable information for improved early detection and management. Unfortunately, this represents a complex problem due to the heterogeneous nature of humans in regards to demographic characteristics, genetics, diet, environmental exposures and health behaviors. In this pilot study, we employed high resolution mass spectrometry-based metabolic profiling to investigate the metabolic signatures of slow versus rapidly progressing PD present in human serum. Archival serum samples from PD patients obtained within 3 years of disease onset were analyzed via dual chromatography-high resolution mass spectrometry, with data extraction by xMSanalyzer and used to predict rapid or slow motor progression of these patients during follow-up. Statistical analyses, such as false discovery rate analysis and partial least squares discriminant analysis, yielded a list of statistically significant metabolic features and further investigation revealed potential biomarkers. In particular, N8-acetyl spermidine was found to be significantly elevated in the rapid progressors compared to both control subjects and slow progressors. Our exploratory data indicate that a fast motor progression disease phenotype can be distinguished early in disease using high resolution mass spectrometry-based metabolic profiling and that altered polyamine metabolism may be a predictive marker of rapidly progressing PD.

Metabolome-wide association study of neovascular age-related macular degeneration

PURPOSE

To determine if plasma metabolic profiles can detect differences between patients with neovascular age-related macular degeneration (NVAMD) and similarly-aged controls.

METHODS

Metabolomic analysis using liquid chromatography with Fourier-transform mass spectrometry (LC-FTMS) was performed on plasma samples from 26 NVAMD patients and 19 controls. Data were collected from mass/charge ratio (m/z) 85 to 850 on a Thermo LTQ-FT mass spectrometer, and metabolic features were extracted using an adaptive processing software package. Both non-transformed and log2 transformed data were corrected using Benjamini and Hochberg False Discovery Rate (FDR) to account for multiple testing. Orthogonal Partial Least Squares-Discriminant Analysis was performed to determine metabolic features that distinguished NVAMD patients from controls. Individual m/z features were matched to the Kyoto Encyclopedia of Genes and Genomes database and the Metlin metabolomics database, and metabolic pathways associated with NVAMD were identified using MetScape.

RESULTS

Of the 1680 total m/z features detected by LC-FTMS, 94 unique m/z features were significantly different between NVAMD patients and controls using FDR (q = 0.05). A comparison of these features to those found with log2 transformed data (n = 132, q = 0.2) revealed 40 features in common, reaffirming the involvement of certain metabolites. Such metabolites included di- and tripeptides, covalently modified amino acids, bile acids, and vitamin D-related metabolites. Correlation analysis revealed associations among certain significant features, and pathway analysis demonstrated broader changes in tyrosine metabolism, sulfur amino acid metabolism, and amino acids related to urea metabolism.

CONCLUSIONS

These data suggest that metabolomic analysis can identify a panel of individual metabolites that differ between NVAMD cases and controls. Pathway analysis can assess the involvement of certain metabolic pathways, such as tyrosine and urea metabolism, and can provide further insight into the pathophysiology of AMD.

The redox proteome

The redox proteome consists of reversible and irreversible covalent modifications that link redox metabolism to biologic structure and function. These modifications, especially of Cys, function at the molecular level in protein folding and maturation, catalytic activity, signaling, and macromolecular interactions and at the macroscopic level in control of secretion and cell shape. Interaction of the redox proteome with redox-active chemicals is central to macromolecular structure, regulation, and signaling during the life cycle and has a central role in the tolerance and adaptability to diet and environmental challenges.

Predicting network activity from high throughput metabolomics

The functional interpretation of high throughput metabolomics by mass spectrometry is hindered by the identification of metabolites, a tedious and challenging task. We present a set of computational algorithms which, by leveraging the collective power of metabolic pathways and networks, predict functional activity directly from spectral feature tables without a priori identification of metabolites. The algorithms were experimentally validated on the activation of innate immune cells.

Mass spectrometry based untargeted metabolomics can now profile several thousand of metabolites simultaneously. However, these metabolites have to be identified before any biological meaning can be drawn from the data. Metabolite identification is a challenging and low throughput process, therefore becomes the bottleneck of the filed. We report here a novel approach to predict biological activity directly from mass spectrometry data without a priori identification of metabolites. By unifying network analysis and metabolite prediction under the same computational framework, the organization of metabolic networks and pathways helps resolve the ambiguity in metabolite prediction to a large extent. We validated our algorithms on a set of activation experiment of innate immune cells. The predicted activities were confirmed by both gene expression and metabolite identification. This method shall greatly accelerate the application of high throughput metabolomics, as the tedious task of identifying hundreds of metabolites upfront can be shifted to a handful of validation experiments after our computational prediction.

Cancer cell growth and survival as a system-level property sustained by enhanced glycolysis and mitochondrial metabolic remodeling

Systems Biology holds that complex cellular functions are generated as system-level properties endowed with robustness, each involving large networks of molecular determinants, generally identified by “omics” analyses. In this paper we describe four basic cancer cell properties that can easily be investigated in vitro: enhanced proliferation, evasion from apoptosis, genomic instability, and inability to undergo oncogene-induced senescence. Focusing our analysis on a K-ras dependent transformation system, we show that enhanced proliferation and evasion from apoptosis are closely linked, and present findings that indicate how a large metabolic remodeling sustains the enhanced growth ability. Network analysis of transcriptional profiling gives the first indication on this remodeling, further supported by biochemical investigations and metabolic flux analysis (MFA). Enhanced glycolysis, down-regulation of TCA cycle, decoupling of glucose and glutamine utilization, with increased reductive carboxylation of glutamine, so to yield a sustained production of growth building blocks and glutathione, are the hallmarks of enhanced proliferation. Low glucose availability specifically induces cell death in K-ras transformed cells, while PKA activation reverts this effect, possibly through at least two mitochondrial targets. The central role of mitochondria in determining the two investigated cancer cell properties is finally discussed. Taken together the findings reported herein indicate that a system-level property is sustained by a cascade of interconnected biochemical pathways that behave differently in normal and in transformed cells.