Exploring the Genetic Landscape of Metabolic Phenotypes with MetaboSignal

Measurement of Volatile Compounds for Real-Time Analysis of Soil Microbial Metabolic Response to Simulated Snowmelt

Snowmelt dynamics are a significant determinant of microbial metabolism in soil and regulate global biogeochemical cycles of carbon and nutrients by creating seasonal variations in soil redox and nutrient pools. With an increasing concern that climate change accelerates both snowmelt timing and rate, obtaining an accurate characterization of microbial response to snowmelt is important for understanding biogeochemical cycles intertwined with soil. However, observing microbial metabolism and its dynamics non-destructively remains a major challenge for systems such as soil. Microbial volatile compounds (mVCs) emitted from soil represent information-dense signatures and when assayed non-destructively using state-of-the-art instrumentation such as Proton Transfer Reaction-Time of Flight-Mass Spectrometry (PTR-TOF-MS) provide time resolved insights into the metabolism of active microbiomes. In this study, we used PTR-TOF-MS to investigate the metabolic trajectory of microbiomes from a subalpine forest soil, and their response to a simulated wet-up event akin to snowmelt. Using an information theory approach based on the partitioning of mutual information, we identified mVC metabolite pairs with robust interactions, including those that were non-linear and with time lags. The biological context for these mVC interactions was evaluated by projecting the connections onto the Kyoto Encyclopedia of Genes and Genomes (KEGG) network of known metabolic pathways. Simulated snowmelt resulted in a rapid increase in the production of trimethylamine (TMA) suggesting that anaerobic degradation of quaternary amine osmo/cryoprotectants, such as glycine betaine, may be important contributors to this resource pulse. Unique and synergistic connections between intermediates of methylotrophic pathways such as dimethylamine, formaldehyde and methanol were observed upon wet-up and indicate that the initial pulse of TMA was likely transformed into these intermediates by methylotrophs. Increases in ammonia oxidation signatures (transformation of hydroxylamine to nitrite) were observed in parallel, and while the relative role of nitrifiers or methylotrophs cannot be confirmed, the inferred connection to TMA oxidation suggests either a direct or indirect coupling between these processes. Overall, it appears that such mVC time-series from PTR-TOF-MS combined with causal inference represents an attractive approach to non-destructively observe soil microbial metabolism and its response to environmental perturbation.

Identifying unknown metabolites using NMR-based metabolic profiling techniques

Metabolic profiling of biological samples provides important insights into multiple physiological and pathological processes but is hindered by a lack of automated annotation and standardized methods for structure elucidation of candidate disease biomarkers. Here we describe a system for identifying molecular species derived from nuclear magnetic resonance (NMR) spectroscopy-based metabolic phenotyping studies, with detailed information on sample preparation, data acquisition and data modeling. We provide eight different modular workflows to be followed in a recommended sequential order according to their level of difficulty. This multi-platform system involves the use of statistical spectroscopic tools such as Statistical Total Correlation Spectroscopy (STOCSY), Subset Optimization by Reference Matching (STORM) and Resolution-Enhanced (RED)-STORM to identify other signals in the NMR spectra relating to the same molecule. It also uses two-dimensional NMR spectroscopic analysis, separation and pre-concentration techniques, multiple hyphenated analytical platforms and data extraction from existing databases. The complete system, using all eight workflows, would take up to a month, as it includes multi-dimensional NMR experiments that require prolonged experiment times. However, easier identification cases using fewer steps would take 2 or 3 days. This approach to biomarker discovery is efficient and cost-effective and offers increased chemical space coverage of the metabolome, resulting in faster and more accurate assignment of NMR-generated biomarkers arising from metabolic phenotyping studies. It requires a basic understanding of MATLAB to use the statistical spectroscopic tools and analytical skills to perform solid phase extraction (SPE), liquid chromatography (LC) fraction collection, LC-NMR-mass spectroscopy and one-dimensional and two-dimensional NMR experiments.

The translational regulator FMRP controls lipid and glucose metabolism in mice and humans

Objectives

The Fragile X Mental Retardation Protein (FMRP) is a widely expressed RNA-binding protein involved in translation regulation. Since the absence of FMRP leads to Fragile X Syndrome (FXS) and autism, FMRP has been extensively studied in brain. The functions of FMRP in peripheral organs and on metabolic homeostasis remain elusive; therefore, we sought to investigate the systemic consequences of its absence.

Methods

Using metabolomics, in vivo metabolic phenotyping of the Fmr1-KO FXS mouse model and in vitro approaches, we show that the absence of FMRP induced a metabolic shift towards enhanced glucose tolerance and insulin sensitivity, reduced adiposity, and increased β-adrenergic-driven lipolysis and lipid utilization.

Results

Combining proteomics and cellular assays, we highlight that FMRP loss increased hepatic protein synthesis and impacted pathways notably linked to lipid metabolism. Mapping metabolomic and proteomic phenotypes onto a signaling and metabolic network, we predicted that the coordinated metabolic response to FMRP loss was mediated by dysregulation in the abundances of specific hepatic proteins. We experimentally validated these predictions, demonstrating that the translational regulator FMRP associates with a subset of mRNAs involved in lipid metabolism. Finally, we highlight that FXS patients mirror metabolic variations observed in Fmr1-KO mice with reduced circulating glucose and insulin and increased free fatty acids.

Conclusions

Loss of FMRP results in a widespread coordinated systemic response that notably involves upregulation of protein translation in the liver, increased utilization of lipids, and significant changes in metabolic homeostasis. Our study unravels metabolic phenotypes in FXS and further supports the importance of translational regulation in the homeostatic control of systemic metabolism.

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Loss of the translational regulator FMRP impacts glucose and lipid homeostasis in mouse and human.

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FMR1-deficiency modifies blood metabolic markers.

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Loss of FMRP enhances the insulin response and lipolysis.

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Loss of FMRP exaggerates hepatic protein synthesis.

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FMRP controls the translation of key hepatic proteins involved in lipid metabolism.

Tools and resources for metabolomics research community: A 2017-2018 update

The scale at which MS- and NMR-based platforms generate metabolomics datasets for both research, core, and clinical facilities to address challenges in the various sciences-ranging from biomedical to agricultural-is underappreciated. Thus, metabolomics efforts spanning microbe, environment, plant, animal, and human systems have led to continual and concomitant growth of in silico resources for analysis and interpretation of these datasets. These software tools, resources, and databases drive the field forward to help keep pace with the amount of data being generated and the sophisticated and diverse analytical platforms that are being used to generate these metabolomics datasets. To address challenges in data preprocessing, metabolite annotation, statistical interrogation, visualization, interpretation, and integration, the metabolomics and informatics research community comes up with hundreds of tools every year. The purpose of the present review is to provide a brief and useful summary of more than 95 metabolomics tools, software, and databases that were either developed or significantly improved during 2017-2018. We hope to see this review help readers, developers, and researchers to obtain informed access to these thorough lists of resources for further improvisation, implementation, and application in due course of time.