Meta-analysis of global metabolomic data identifies metabolites associated with life-span extension

The metabolic contribution of SKN-1/Nrf2 to the lifespan of Caenorhabditis elegans

BACKGROUND AND AIMS

SKN-1, a C. elegans transcription factor analogous to the mammalian NF-E2-related factor (Nrf2), has been known to promote oxidative stress resistance aiding nematodes' longevity. Although SKN-1's functions suggest its implication in lifespan modulation through cellular metabolism, the actual mechanism of how metabolic rearrangements contribute to SKN-1's lifespan modulation has yet to be well characterized. Therefore, we performed the metabolomic profiling of the short-lived skn-1-knockdown C. elegans.

METHODS

We analyzed the metabolic profile of the skn-1-knockdown worms with nuclear magnetic resonance (NMR) spectroscopy and liquid chromatography-tandem mass spectrometry (LC-MS/MS) and obtained distinctive metabolomic profiles compared to WT worms. We further extended our study with gene expression analysis to examine the expression level of genes encoding all metabolic enzymes.

RESULTS

A significant increase in the phosphocholine and AMP/ATP ratio, potential biomarkers of aging, was observed, accompanied by a decrease in the transsulfuration metabolites, NADPH/NADP⁺ ratio, and total glutathione (GSHt), which are known to be involved in oxidative stress defense. skn-1-RNAi worms also exhibited an impairment in the phase II detoxification system, confirmed by the lower conversion rate of paracetamol to paracetamol-glutathione. By further examining the transcriptomic profile, we found a decrease in the expression of cbl-1, gpx, T25B9.9, ugt, and gst, which are involved in GSHt and NADPH synthesis as well as in the phase II detoxification system.

CONCLUSION

Our multi-omics results consistently revealed that the cytoprotective mechanisms, including cellular redox reactions and xenobiotic detoxification system, contribute to the roles of SKN-1/Nrf2 in the lifespan of worms.

Helminth lipidomics: Technical aspects and future prospects

Lipidomics is a relatively recent molecular research field, and explores lipids (fats) and their biology using advanced mass spectrometry technologies. Although this field has expanded significantly in biomedical and biotechnological disciplines, it is still in its infancy in molecular parasitology. Our goal here is to review and discuss technical aspects of MS-based lipidomics and its recent applications to parasitic worms, as well as challenges and future directions for worm lipid research. In a multi-omic paradigm, we expect that the exploration of lipidomic data for parasitic worms will yield important insights into lipid-associated biological pathways and processes, including the regulation of essential signalling pathways, parasite invasion, establishment, adaptation and development.

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Lipids are involved in critical biological functions in parasitic worms.

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Lipidomics is an emerging research field in molecular helminthology.

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This article covers technological advances and applications to parasitic worms.

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It also discusses challenges and future directions for lipidomic research.

Using stable isotope tracers to monitor membrane dynamics in C. elegans

Membranes within an animal are composed of phospholipids, cholesterol, and proteins that together form a dynamic barrier. The types of lipids that are found within a membrane bilayer impact its biophysical properties including its fluidity, permeability, and susceptibility to damage. While membrane composition is very stable in healthy adults, aberrant membrane structure is seen in a wide and varied array of diseases as well as during natural aging. Despite the wide-reaching impacts of membrane composition, there is relatively little known about how membrane landscape is established and maintained over time. In vivo biochemical modeling of membrane lipids is needed to understand how these molecules interact in their natural configurations. Here, we have described analytical methods that increase the capacity to map the dynamics of individual membrane phospholipids using different types of mass spectrometry. Specifically, we describe novel stable isotope (¹³C and ¹⁵N) strategies to quantify the turnover of dozens of fatty acid tails and intact phospholipids simultaneously.

Using diphenyleneiodonium to induce a viable but non-culturable phenotype in Mycobacterium tuberculosis and its metabolomics analysis

Depletion of oxygen levels is a well-accepted model for induction of non-replicating, persistent states in mycobacteria. Increasing the stress levels in mycobacterium bacilli facilitates their entry into a non-cultivable, dormant state. In this study, it was shown that diphenyleneiodonium, an inhibitor of NADH oxidase, induced a viable, but non-culturable state in mycobacteria, having similar features to dormant bacilli, like loss of acid-fastness, upregulation of stress-regulated genes and decreased superoxide levels as compared to actively growing bacilli. Comprehensive, untargeted metabolic profiling also confirmed a decrease in biogenesis of amino acids, NAD, unsaturated fatty acids and nucleotides. Additionally, an increase in the level of lactate, fumarate, succinate and pentose phosphate pathways along with increased mycothiol and sulfate metabolites, similar to dormant bacilli, was observed in the granuloma. These non-cultivable bacilli were resuscitated by supplementation of fetal bovine serum, regaining their culturability in liquid as well as on agar medium. This study focused on the effect of diphenyleneiodonium treatment in causing mycobacteria to rapidly transition from an active state into a viable, but non-cultivable state, and comparing their characteristics with dormant phenotypes.

Identification of bioactive metabolites using activity metabolomics

The metabolome, the collection of small-molecule chemical entities involved in metabolism, has traditionally been studied with the aim of identifying biomarkers in the diagnosis and prediction of disease. However, the value of metabolome analysis (metabolomics) has been redefined from a simple biomarker identification tool to a technology for the discovery of active drivers of biological processes. It is now clear that the metabolome affects cellular physiology through modulation of other 'omics' levels, including the genome, epigenome, transcriptome and proteome. In this Review, we focus on recent progress in using metabolomics to understand how the metabolome influences other omics and, by extension, to reveal the active role of metabolites in physiology and disease. This concept of utilizing metabolomics to perform activity screens to identify biologically active metabolites - which we term activity metabolomics - is already having a broad impact on biology.

IDH-1 deficiency induces growth defects and metabolic alterations in GSPD-1-deficient Caenorhabditis elegans

NADPH is a reducing equivalent that maintains redox homeostasis and supports reductive biosynthesis. Lack of major NADPH-producing enzymes predisposes cells to growth retardation and demise. It was hypothesized that double deficiency of the NADPH-generating enzymes, GSPD-1 (Glucose-6-phosphate 1-dehydrogenase), a functional homolog of human glucose-6-phosphate dehydrogenase (G6PD), the rate-limiting enzyme of the pentose phosphate pathway, and IDH-1 (isocitrate dehydrogenase-1) affect growth and development in the nematode, Caenorhabditis elegans (C. elegans). The idh-1;gspd-1(RNAi) double-deficient C. elegans model displayed shrinkage of body size, growth retardation, slowed locomotion, and impaired molting. Global metabolomic analysis was employed to address whether or not metabolic pathways were altered by severe NADPH insufficiency by the idh-1;gspd-1(RNAi) double-deficiency. The principal component analysis (PCA) points to a distinct metabolomic profile of idh-1;gspd-1(RNAi) double-deficiency. Further metabolomic analysis revealed that NADPH-dependent and glutamate-dependent amino acid biosynthesis were significantly affected. The reduced pool of amino acids may affect protein synthesis, as indicated by the absence of NAS-37 expression during the molting process. In short, double deficiency of GSPD-1 and IDH-1 causes growth retardation and molting defects, which are, in part, attributed to defective protein synthesis, possibly mediated by altered amino acid biosynthesis and metabolism in C. elegans.

Emerging Omics Approaches in Aging Research

SIGNIFICANCE

Aging is a complex trait that is influenced by a combination of genetic and environmental factors. Although many cellular and physiological changes have been described to occur with aging, the precise molecular causes of aging remain unknown. Given the biological complexity and heterogeneity of the aging process, understanding the mechanisms that underlie aging requires integration of data about age-dependent changes that occur at the molecular, cellular, tissue, and organismal levels. Recent Advances: The development of high-throughput technologies such as next-generation sequencing, proteomics, metabolomics, and automated imaging techniques provides researchers with new opportunities to understand the mechanisms of aging. Using these methods, millions of biological molecules can be simultaneously monitored during the aging process with high accuracy and specificity.

CRITICAL ISSUES

Although the ability to produce big data has drastically increased over the years, integration and interpreting of high-throughput data to infer regulatory relationships between biological factors and identify causes of aging remain the major challenges. In this review, we describe recent advances and survey emerging omics approaches in aging research. We then discuss their limitations and emphasize the need for the further development of methods for the integration of different types of data.

FUTURE DIRECTIONS

Combining omics approaches and novel methods for single-cell analysis with systems biology tools would allow building interaction networks and investigate how these networks are perturbed with aging and disease states. Together, these studies are expected to provide a better understanding of the aging process and could provide insights into the pathophysiology of many age-associated human diseases. Antioxid. Redox Signal. 29, 985-1002.

Identifying metabolites by integrating metabolome databases with mass spectrometry cheminformatics

Novel metabolites distinct from canonical pathways can be identified through the integration of three cheminformatics tools: BinVestigate, which queries the BinBase gas chromatography-mass spectrometry (GC-MS) metabolome database to match unknowns with biological metadata across over 110,000 samples; MS-DIAL 2.0, a software tool for chromatographic deconvolution of high-resolution GC-MS or liquid chromatography-mass spectrometry (LC-MS); and MS-FINDER 2.0, a structure-elucidation program that uses a combination of 14 metabolome databases in addition to an enzyme promiscuity library. We showcase our workflow by annotating N-methyl-uridine monophosphate (UMP), lysomonogalactosyl-monopalmitin, N-methylalanine, and two propofol derivatives.

Metabolic drift in the aging brain

Brain function is highly dependent upon controlled energy metabolism whose loss heralds cognitive impairments. This is particularly notable in the aged individuals and in age-related neurodegenerative diseases. However, how metabolic homeostasis is disrupted in the aging brain is still poorly understood. Here we performed global, metabolomic and proteomic analyses across different anatomical regions of mouse brain at different stages of its adult lifespan. Interestingly, while severe proteomic imbalance was absent, global-untargeted metabolomics revealed an energy metabolic drift or significant imbalance in core metabolite levels in aged mouse brains. Metabolic imbalance was characterized by compromised cellular energy status (NAD decline, increased AMP/ATP, purine/pyrimidine accumulation) and significantly altered oxidative phosphorylation and nucleotide biosynthesis and degradation. The central energy metabolic drift suggests a failure of the cellular machinery to restore metabostasis (metabolite homeostasis) in the aged brain and therefore an inability to respond properly to external stimuli, likely driving the alterations in signaling activity and thus in neuronal function and communication.

Lipidomic Analysis of Caenorhabditis elegans Embryos

Metabolomic is an emerging field of system biology. Lipidomic, a branch of metabolomic, aims to characterize lipophilic metabolites in biological systems. Caenorhabditis elegans (C. elegans) is a genetically tractable and versatile animal model for novel discovery of lipid metabolism. In addition, C. elegans embryo is simple and homogeneous. Here, we demonstrate detailed procedures of C. elegans culture, embryo isolation, lipid extraction and metabolomic data analysis.

Effect of Major Royal Jelly Proteins on Spatial Memory in Aged Rats: Metabolomics Analysis in Urine

Royal jelly (RJ) produced by worker honeybees is the sole food for the queen bee throughout her life as well as the larvae of worker bees for the first 3 days after hatching. Supplementation of RJ in the diet has been shown to increase spatial memory in rodents. However, the key constituents in RJ responsible for improvement of cognitive function are unknown. Our objective was to determine if the major royal jelly proteins (MRJPs) extracted from RJ can improve the spatial memory of aged rats. The spatial memory assay using the Morris water maze test was administered once to rats after a 14-week feeding. Metabolomics analysis based on quadrupole time-of-flight mass spectrometry was conducted to examine the differences in compounds from urine. Aged male rats fed MRJPs showed improved spatial memory up to 48.5% when compared to the control male aged rats fed distilled water. The metabolite pattern of the MRJPs-fed aged rats was regressed to that of the young rats. Compounds altered by MRJPs were mapped to nicotinate and nicotinamide metabolism, cysteine taurine metabolism, and energy metabolism pathways. In summary, MRJPs may improve spatial memory and possess the potential for prevention of cognitive impairment via the cysteine and taurine metabolism and energy metabolism pathways in aged rats.

Metabolomic signature associated with reproduction-regulated aging in Caenorhabditis elegans

In Caenorhabditis elegans (C. elegans), ablation of germline stem cells (GSCs) leads to infertility, which extends lifespan. It has been reported that aging and reproduction are both inextricably associated with metabolism. However, few studies have investigated the roles of polar small molecules metabolism in regulating longevity by reproduction. In this work, we combined the nuclear magnetic resonance (NMR) and ultra-performance liquid chromatography-mass spectrometry (UPLC-MS) to profile the water-soluble metabolome in C. elegans. Comparing the metabolic fingerprint between two physiological ages among different mutants, our results demonstrate that aging is characterized by metabolome remodeling and metabolic decline. In addition, by analyzing the metabolic profiles of long-lived germline-less glp-1 mutants, we discovered that glp-1 mutants regulate the levels of many age-variant metabolites to attenuate aging, including elevated concentrations of the pyrimidine and purine metabolism intermediates and decreased concentrations of the citric acid cycle intermediates. Interestingly, by analyzing the metabolome of daf-16;glp-1 double mutants, our results revealed that some metabolic exchange contributing to germline-mediated longevity was mediated by transcription factor FOXO/DAF-16, including pyrimidine metabolism and the TCA cycle. Based on a comprehensive metabolic analysis, we provide novel insight into the relationship between longevity and metabolism regulated by germline signals in C. elegans.

The Role of Dafachronic Acid Signaling in Development and Longevity in Caenorhabditis elegans: Digging Deeper Using Cutting-Edge Analytical Chemistry

Steroid hormones regulate physiological processes in species ranging from plants to humans. A wide range of steroid hormones exist, and their contributions to processes, such as growth, reproduction, development, and aging, is almost always complex. Understanding the biosynthetic pathways that generate steroid hormones and the signaling pathways that mediate their effects is thus of fundamental importance. In this work, we review recent advances in (i) the biological role of steroid hormones in the roundworm Caenorhabditis elegans and (ii) the development of novel methods to facilitate the detection and identification of these molecules. Our current understanding of steroid signaling in this simple organism serves to illustrate the challenges we face moving forward. First, it seems clear that we have not yet identified all of the enzymes responsible for steroid biosynthesis and/or degradation. Second, perturbation of steroid signaling affects a wide range of phenotypes, and subtly different steroid molecules can have distinct effects. Finally, steroid hormone levels are critically important, and minute variations in quantity can profoundly impact a phenotype. Thus, it is imperative that we develop innovative analytical tools and combine them with cutting-edge approaches including comprehensive and highly selective liquid chromatography coupled to mass spectrometry based on new methods such as supercritical fluid chromatography coupled to mass spectrometry (SFC-MS) if we are to obtain a better understanding of the biological functions of steroid signaling.

A roadmap for the XCMS family of software solutions in metabolomics

Global profiling of metabolites in biological samples by liquid chromatography/mass spectrometry results in datasets too large to evaluate manually. Fortunately, a variety of software programs are now available to automate the data analysis. Selection of the appropriate processing solution is dependent upon experimental design. Most metabolomic studies a decade ago had a relatively simple experimental design in which the intensities of compounds were compared between only two sample groups. More recently, however, increasingly sophisticated applications have been pursued. Examples include comparing compound intensities between multiple sample groups and unbiasedly tracking the fate of specific isotopic labels. The latter types of applications have necessitated the development of new software programs, which have introduced additional functionalities that facilitate data analysis. The objective of this review is to provide an overview of the freely available bioinformatic solutions that are either based upon or are compatible with the algorithms in XCMS, which we broadly refer to here as the 'XCMS family' of software. These include CAMERA, credentialing, Warpgroup, metaXCMS, X(13)CMS, and XCMS Online. Together, these informatic technologies can accommodate most cutting-edge metabolomic applications and offer unique advantages when compared to the original XCMS program.

Metabolome and proteome changes with aging in Caenorhabditis elegans

To expand the understanding of aging in the model organism Caenorhabditis elegans, global quantification of metabolite and protein levels in young and aged nematodes was performed using mass spectrometry. With age, there was a decreased abundance of proteins functioning in transcription termination, mRNA degradation, mRNA stability, protein synthesis, and proteasomal function. Furthermore, there was altered S-adenosyl methionine metabolism as well as a decreased abundance of the S-adenosyl methionine synthetase (SAMS-1) protein. Other aging-related changes included alterations in free fatty acid levels and composition, decreased levels of ribosomal proteins, decreased levels of NADP-dependent isocitrate dehydrogenase (IDH1), a shift in the cellular redox state, an increase in sorbitol content, alterations in free amino acid levels, and indications of altered muscle function and sarcoplasmic reticulum Ca(2+) homeostasis. There were also decreases in pyrimidine and purine metabolite levels, most markedly nitrogenous bases. Supplementing the culture medium with cytidine (a pyrimidine nucleoside) or hypoxanthine (a purine base) increased lifespan slightly, suggesting that aging-induced alterations in ribonucleotide metabolism affect lifespan. An age-related increase in body size, lipotoxicity from ectopic yolk lipoprotein accumulation, a decline in NAD(+) levels, and mitochondrial electron transport chain dysfunction may explain many of these changes. In addition, dietary restriction in aged worms resulting from sarcopenia of the pharyngeal pump likely decreases the abundance of SAMS-1, possibly leading to decreased phosphatidylcholine levels, larger lipid droplets, and ER and mitochondrial stress. The complementary use of proteomics and metabolomics yielded unique insights into the molecular processes altered with age in C. elegans.

Stress signaling between organs in metazoa

Many organisms have developed a robust ability to adapt and survive in the face of environmental perturbations that threaten the integrity of their genome, proteome, or metabolome. Studies in multiple model organisms have shown that, in general, when exposed to stress, cells activate a complex prosurvival signaling network that includes immune and DNA damage response genes, chaperones, antioxidant enzymes, structural proteins, metabolic enzymes, and noncoding RNAs. The manner of activation runs the gamut from transcriptional induction of genes to increased stability of transcripts to posttranslational modification of important biosynthetic proteins within the stressed tissue. Superimposed on these largely autonomous effects are nonautonomous responses in which the stressed tissue secretes peptides and other factors that stimulate tissues in different organs to embark on processes that ultimately help the organism as a whole cope with stress. This review focuses on the mechanisms by which tissues in one organ adapt to environmental challenges by regulating stress responses in tissues of different organs.

Interactive XCMS Online: simplifying advanced metabolomic data processing and subsequent statistical analyses

XCMS Online (xcmsonline.scripps.edu) is a cloud-based informatic platform designed to process and visualize mass-spectrometry-based, untargeted metabolomic data. Initially, the platform was developed for two-group comparisons to match the independent, "control" versus "disease" experimental design. Here, we introduce an enhanced XCMS Online interface that enables users to perform dependent (paired) two-group comparisons, meta-analysis, and multigroup comparisons, with comprehensive statistical output and interactive visualization tools. Newly incorporated statistical tests cover a wide array of univariate analyses. Multigroup comparison allows for the identification of differentially expressed metabolite features across multiple classes of data while higher order meta-analysis facilitates the identification of shared metabolic patterns across multiple two-group comparisons. Given the complexity of these data sets, we have developed an interactive platform where users can monitor the statistical output of univariate (cloud plots) and multivariate (PCA plots) data analysis in real time by adjusting the threshold and range of various parameters. On the interactive cloud plot, metabolite features can be filtered out by their significance level (p-value), fold change, mass-to-charge ratio, retention time, and intensity. The variation pattern of each feature can be visualized on both extracted-ion chromatograms and box plots. The interactive principal component analysis includes scores, loadings, and scree plots that can be adjusted depending on scaling criteria. The utility of XCMS functionalities is demonstrated through the metabolomic analysis of bacterial stress response and the comparison of lymphoblastic leukemia cell lines.

After the feature presentation: technologies bridging untargeted metabolomics and biology

Liquid chromatography/mass spectrometry-based untargeted metabolomics is now an established experimental approach that is being broadly applied by many laboratories worldwide. Interpreting untargeted metabolomic data, however, remains a challenge and limits the translation of results into biologically relevant conclusions. Here we review emerging technologies that can be applied after untargeted profiling to extend biological interpretation of metabolomic data. These technologies include advances in bioinformatic software that enable identification of isotopes and adducts, comprehensive pathway mapping, deconvolution of MS(2) data, and tracking of isotopically labeled compounds. There are also opportunities to gain additional biological insight by complementing the metabolomic analysis of homogenized samples with recently developed technologies for metabolite imaging of intact tissues. To maximize the value of these emerging technologies, a unified workflow is discussed that builds on the traditional untargeted metabolomic pipeline. Particularly when integrated together, the combination of the advances highlighted in this review helps transform lists of masses and fold changes characteristic of untargeted profiling results into structures, absolute concentrations, pathway fluxes, and localization patterns that are typically needed to understand biology.