Consistency across multi-omics layers in a drug-perturbed gut microbial community.

Multi-omics analyses are used in microbiome studies to understand molecular changes in microbial communities exposed to different conditions. However, it is not always clear how much each omics data type contributes to our understanding and whether they are concordant with each other. Here, we map the molecular response of a synthetic community of 32 human gut bacteria to three non-antibiotic drugs by using five omics layers (16S rRNA gene profiling, metagenomics, metatranscriptomics, metaproteomics and metabolomics). We find that all the omics methods with species resolution are highly consistent in estimating relative species abundances. Furthermore, different omics methods complement each other for capturing functional changes. For example, while nearly all the omics data types captured that the antipsychotic drug chlorpromazine selectively inhibits Bacteroidota representatives in the community, the metatranscriptome and metaproteome suggested that the drug induces stress responses related to protein quality control. Metabolomics revealed a decrease in oligosaccharide uptake, likely caused by Bacteroidota depletion. Our study highlights how multi-omics datasets can be utilized to reveal complex molecular responses to external perturbations in microbial communities.

Integrating metabolome dynamics and process data to guide cell line selection in biopharmaceutical process development.

The successful development of mammalian cell culture for the production of therapeutic antibodies is a resource-intensive and multistage process which requires the selection of high performing and stable cell lines at different scale-up stages. Accordingly, science-based approaches exploiting biological information, such as metabolomics, can support and accelerate the selection of promising cell lines to progress. In fact, the integration of dynamic biological information with process data can provide valuable insights on the cell physiological changes as a consequence of the cultivation process. This work studies the industrial development of monoclonal antibodies at micro-bioreactor scale (Ambr®15) and aims at accelerating the selection of the better performing cell lines. To that end, we apply a machine learning approach to integrate time-varying process and biological information (i.e., metabolomics), explicitly exploiting their dynamics. Strikingly, cell line performance during the cultivation can be predicted from early process timepoints by exploiting the gradual temporal evolution of metabolic phenotypes. Furthermore, product titer is estimated with good accuracy at late process timepoints, providing insights into its relationship with underlying metabolic mechanisms and enabling the identification of biomarkers to be further investigated. The biological insights obtained through the proposed machine learning approach provide data-driven metabolic understanding allowing early identification of high performing cell lines. Additionally, this analysis offers the opportunity to identify key metabolites which could be used as biomarkers for industrially relevant phenotypes and onward fit into our commercial manufacturing platforms.

Metabolic memory underlying minimal residual disease in breast cancer.

Tumor relapse from treatment-resistant cells (minimal residual disease, MRD) underlies most breast cancer-related deaths. Yet, the molecular characteristics defining their malignancy have largely remained elusive. Here, we integrated multi-omics data from a tractable organoid system with a metabolic modeling approach to uncover the metabolic and regulatory idiosyncrasies of the MRD. We find that the resistant cells, despite their non-proliferative phenotype and the absence of oncogenic signaling, feature increased glycolysis and activity of certain urea cycle enzyme reminiscent of the tumor. This metabolic distinctiveness was also evident in a mouse model and in transcriptomic data from patients following neo-adjuvant therapy. We further identified a marked similarity in DNA methylation profiles between tumor and residual cells. Taken together, our data reveal a metabolic and epigenetic memory of the treatment-resistant cells. We further demonstrate that the memorized elevated glycolysis in MRD is crucial for their survival and can be targeted using a small-molecule inhibitor without impacting normal cells. The metabolic aberrances of MRD thus offer new therapeutic opportunities for post-treatment care to prevent breast tumor recurrence.

Bioaccumulation of therapeutic drugs by human gut bacteria.

Bacteria in the gut can modulate the availability and efficacy of therapeutic drugs. However, the systematic mapping of the interactions between drugs and bacteria has only started recently1 and the main underlying mechanism proposed is the chemical transformation of drugs by microorganisms (biotransformation). Here we investigated the depletion of 15 structurally diverse drugs by 25 representative strains of gut bacteria. This revealed 70 bacteria-drug interactions, 29 of which had not to our knowledge been reported before. Over half of the new interactions can be ascribed to bioaccumulation; that is, bacteria storing the drug intracellularly without chemically modifying it, and in most cases without the growth of the bacteria being affected. As a case in point, we studied the molecular basis of bioaccumulation of the widely used antidepressant duloxetine by using click chemistry, thermal proteome profiling and metabolomics. We find that duloxetine binds to several metabolic enzymes and changes the metabolite secretion of the respective bacteria. When tested in a defined microbial community of accumulators and non-accumulators, duloxetine markedly altered the composition of the community through metabolic cross-feeding. We further validated our findings in an animal model, showing that bioaccumulating bacteria attenuate the behavioural response of Caenorhabditis elegans to duloxetine. Together, our results show that bioaccumulation by gut bacteria may be a common mechanism that alters drug availability and bacterial metabolism, with implications for microbiota composition, pharmacokinetics, side effects and drug responses, probably in an individual manner.

Effect of topical applications of sunflower seed oil on systemic fatty acid levels in under-two children under rehabilitation for severe acute malnutrition in Bangladesh: a randomized controlled trial.

BACKGROUND: Children with severe acute malnutrition (SAM) have inadequate levels of fatty acids (FAs) and limited capacity for enteral nutritional rehabilitation. We hypothesized that topical high-linoleate sunflower seed oil (SSO) would be effective adjunctive treatment for children with SAM. METHODS: This study tested a prespecified secondary endpoint of a randomized, controlled, unblinded clinical trial with 212 children with SAM aged 2 to 24 months in two strata (2 to < 6 months, 6 to 24 months in a 1:2 ratio) at Dhaka Hospital of icddr,b, Bangladesh between January 2016 and December 2017. All children received standard-of-care management of SAM. Children randomized to the emollient group also received whole-body applications of 3 g/kg SSO three times daily for 10 days. We applied difference-in-difference analysis and unsupervised clustering analysis using t-distributed stochastic neighbor embedding (t-SNE) to visualize changes in FA levels in blood from day 0 to day 10 of children with SAM treated with emollient compared to no-emollient. RESULTS: Emollient therapy led to systematically higher increases in 26 of 29 FAs over time compared to the control. These effects were driven primarily by changes in younger subjects (27 of 29 FAs). Several FAs, especially those most abundant in SSO showed high-magnitude but non-significant incremental increases from day 0 to day 10 in the emollient group vs. the no-emollient group; for linoleic acid, a 237 µg/mL increase was attributable to enteral feeding and an incremental 98 µg/mL increase (41%) was due to emollient therapy. Behenic acid (22:0), gamma-linolenic acid (18:3n6), and eicosapentaenoic acid (20:5n3) were significantly increased in the younger age stratum; minimal changes were seen in the older children. CONCLUSIONS: SSO therapy for SAM augmented the impact of enteral feeding in increasing levels of several FAs in young children. Further research is warranted into optimizing this novel approach for nutritional rehabilitation of children with SAM, especially those < 6 months. TRIAL REGISTRATION: ClinicalTrials.gov : NCT02616289 .

New insights into the mechanisms underlying 5-fluorouracil-induced intestinal toxicity based on transcriptomic and metabolomic responses in human intestinal organoids.

5-Fluorouracil (5-FU) is a widely used chemotherapeutical that induces acute toxicity in the small and large intestine of patients. Symptoms can be severe and lead to the interruption of cancer treatments. However, there is limited understanding of the molecular mechanisms underlying 5-FU-induced intestinal toxicity. In this study, well-established 3D organoid models of human colon and small intestine (SI) were used to characterize 5-FU transcriptomic and metabolomic responses. Clinically relevant 5-FU concentrations for in vitro testing in organoids were established using physiologically based pharmacokinetic simulation of dosing regimens recommended for cancer patients, resulting in exposures to 10, 100 and 1000 µM. After treatment, different measurements were performed: cell viability and apoptosis; image analysis of cell morphological changes; RNA sequencing; and metabolome analysis of supernatant from organoids cultures. Based on analysis of the differentially expressed genes, the most prominent molecular pathways affected by 5-FU included cell cycle, p53 signalling, mitochondrial ATP synthesis and apoptosis. Short time-series expression miner demonstrated tissue-specific mechanisms affected by 5-FU, namely biosynthesis and transport of small molecules, and mRNA translation for colon; cell signalling mediated by Rho GTPases and fork-head box transcription factors for SI. Metabolomic analysis showed that in addition to the effects on TCA cycle and oxidative stress in both organoids, tissue-specific metabolic alterations were also induced by 5-FU. Multi-omics integration identified transcription factor E2F1, a regulator of cell cycle and apoptosis, as the best key node across all samples. These results provide new insights into 5-FU toxicity mechanisms and underline the relevance of human organoid models in the safety assessment in drug development.

An integrated multiomic and quantitative label-free microscopy-based approach to study pro-fibrotic signalling in ex vivo human precision-cut lung slices.

Fibrosis can affect any organ, resulting in the loss of tissue architecture and function with often life-threatening consequences. Pathologically, fibrosis is characterised by the expansion of connective tissue due to excessive deposition of extracellular matrix (ECM) proteins, including the fibrillar forms of collagen. A significant limitation for discovering cures for fibrosis is the availability of suitable human models and techniques to quantify mature fibrillar collagen deposition as close as possible to human physiological conditions.Here we have extensively characterised an ex vivo cultured human lung tissue-derived, precision-cut lung slices (hPCLS) model using label-free second harmonic generation (SHG) light microscopy to quantify fibrillar collagen deposition and mass spectrometry-based techniques to obtain a proteomic and metabolomic fingerprint of hPCLS in ex vivo culture.We demonstrate that hPCLS are viable and metabolically active, with mesenchymal, epithelial, endothelial and immune cell types surviving for at least 2 weeks in ex vivo culture. Analysis of hPCLS-conditioned supernatants showed a strong induction of pulmonary fibrosis-related ECM proteins upon transforming growth factor-ß1 (TGF-ß1) stimulation. This upregulation of ECM proteins was not translated into an increased deposition of fibrillar collagen. In support of this observation, we revealed the presence of a pro-ECM degradation activity in our ex vivo cultures of hPCLS, inhibition of which by a metalloproteinase inhibitor resulted in increased collagen deposition in response to TGF-ß1 stimulation.Together the data show that an integrated approach of measuring soluble pro-fibrotic markers alongside quantitative SHG-based analysis of fibrillar collagen is a valuable tool for studying pro-fibrotic signalling and testing anti-fibrotic agents.

Complementary NAD+ replacement strategies fail to functionally protect dystrophin-deficient muscle.

BACKGROUND: Duchenne muscular dystrophy (DMD) is a progressive muscle wasting disorder stemming from a loss of functional dystrophin. Current therapeutic options for DMD are limited, as small molecule modalities remain largely unable to decrease the incidence or mitigate the consequences of repetitive mechanical insults to the muscle during eccentric contractions (ECCs). METHODS: Using a metabolomics-based approach, we observed distinct and transient molecular phenotypes in muscles of dystrophin-deficient MDX mice subjected to ECCs. Among the most chronically depleted metabolites was nicotinamide adenine dinucleotide (NAD), an essential metabolic cofactor suggested to protect muscle from structural and metabolic degeneration over time. We tested whether the MDX muscle NAD pool can be expanded for therapeutic benefit using two complementary small molecule strategies: provision of a biosynthetic precursor, nicotinamide riboside, or specific inhibition of the NAD-degrading ADP-ribosyl cyclase, CD38. RESULTS: Administering a novel, potent, and orally available CD38 antagonist to MDX mice successfully reverted a majority of the muscle metabolome toward the wildtype state, with a pronounced impact on intermediates of the pentose phosphate pathway, while supplementing nicotinamide riboside did not significantly affect the molecular phenotype of the muscle. However, neither strategy sustainably increased the bulk tissue NAD pool, lessened muscle damage markers, nor improved maximal hindlimb strength following repeated rounds of eccentric challenge and recovery. CONCLUSIONS: In the absence of dystrophin, eccentric injury contributes to chronic intramuscular NAD depletion with broad pleiotropic effects on the molecular phenotype of the tissue. These molecular consequences can be more effectively overcome by inhibiting the enzymatic activity of CD38 than by supplementing nicotinamide riboside. However, we found no evidence that either small molecule strategy is sufficient to restore muscle contractile function or confer protection from eccentric injury, undermining the modulation of NAD metabolism as a therapeutic approach for DMD.

Identifying drug targets in tissues and whole blood with thermal-shift profiling.

Monitoring drug-target interactions with methods such as the cellular thermal-shift assay (CETSA) is well established for simple cell systems but remains challenging in vivo. Here we introduce tissue thermal proteome profiling (tissue-TPP), which measures binding of small-molecule drugs to proteins in tissue samples from drug-treated animals by detecting changes in protein thermal stability using quantitative mass spectrometry. We report organ-specific, proteome-wide thermal stability maps and derive target profiles of the non-covalent histone deacetylase inhibitor panobinostat in rat liver, lung, kidney and spleen and of the B-Raf inhibitor vemurafenib in mouse testis. In addition, we devised blood-CETSA and blood-TPP and applied it to measure target and off-target engagement of panobinostat and the BET family inhibitor JQ1 directly in whole blood. Blood-TPP analysis of panobinostat confirmed its binding to known targets and also revealed thermal stabilization of the zinc-finger transcription factor ZNF512. These methods will help to elucidate the mechanisms of drug action in vivo.

Characterization of the small flavin-binding dodecin in the roseoflavin producer Streptomyces davawensis.

Genes encoding dodecin proteins are present in almost 20 % of archaeal and in more than 50 % of bacterial genomes. Archaeal dodecins bind riboflavin (vitamin B2), are thought to play a role in flavin homeostasis and possibly also help to protect cells from radical or oxygenic stress. Bacterial dodecins were found to bind riboflavin-5'-phosphate (also called flavin mononucleotide or FMN) and coenzyme A, but their physiological function remained unknown. In this study, we set out to investigate the relevance of dodecins for flavin metabolism and oxidative stress management in the phylogenetically related bacteria Streptomyces coelicolor and Streptomyces davawensis. Additionally, we explored the role of dodecins with regard to resistance against the antibiotic roseoflavin, a riboflavin analogue produced by S. davawensis. Our results show that the dodecin of S. davawensis predominantly binds FMN and is neither involved in roseoflavin biosynthesis nor in roseoflavin resistance. In contrast to S. davawensis, growth of S. coelicolor was not reduced in the presence of plumbagin, a compound, which induces oxidative stress. Plumbagin treatment stimulated expression of the dodecin gene in S. davawensis but not in S. coelicolor. Deletion of the dodecin gene in S. davawensis generated a recombinant strain which, in contrast to the wild-type, was fully resistant to plumbagin. Subsequent metabolome analyses revealed that the S. davawensis dodecin deletion strain exhibited a very different stress response when compared to the wild-type indicating that dodecins broadly affect cellular physiology.

Itaconate is an anti-inflammatory metabolite that activates Nrf2 via alkylation of KEAP1.

The endogenous metabolite itaconate has recently emerged as a regulator of macrophage function, but its precise mechanism of action remains poorly understood. Here we show that itaconate is required for the activation of the anti-inflammatory transcription factor Nrf2 (also known as NFE2L2) by lipopolysaccharide in mouse and human macrophages. We find that itaconate directly modifies proteins via alkylation of cysteine residues. Itaconate alkylates cysteine residues 151, 257, 288, 273 and 297 on the protein KEAP1, enabling Nrf2 to increase the expression of downstream genes with anti-oxidant and anti-inflammatory capacities. The activation of Nrf2 is required for the anti-inflammatory action of itaconate. We describe the use of a new cell-permeable itaconate derivative, 4-octyl itaconate, which is protective against lipopolysaccharide-induced lethality in vivo and decreases cytokine production. We show that type I interferons boost the expression of Irg1 (also known as Acod1) and itaconate production. Furthermore, we find that itaconate production limits the type I interferon response, indicating a negative feedback loop that involves interferons and itaconate. Our findings demonstrate that itaconate is a crucial anti-inflammatory metabolite that acts via Nrf2 to limit inflammation and modulate type I interferons.

An unexpected link between fatty acid synthase and cholesterol synthesis in proinflammatory macrophage activation.

Different immune activation states require distinct metabolic features and activities in immune cells. For instance, inhibition of fatty acid synthase (FASN), which catalyzes the synthesis of long-chain fatty acids, prevents the proinflammatory response in macrophages; however, the precise role of this enzyme in this response remains poorly defined. Consistent with previous studies, we found here that FASN is essential for lipopolysaccharide-induced, Toll-like receptor (TLR)-mediated macrophage activation. Interestingly, only agents that block FASN upstream of acetoacetyl-CoA synthesis, including the well-characterized FASN inhibitor C75, inhibited TLR4 signaling, while those acting downstream had no effect. We found that acetoacetyl-CoA could overcome C75's inhibitory effect, whereas other FASN metabolites, including palmitate, did not prevent C75-mediated inhibition. This suggested an unexpected role for acetoacetyl-CoA in inflammation that is independent of its role in palmitate synthesis. Our evidence further suggested that acetoacetyl-CoA arising from FASN activity promotes cholesterol production, indicating a surprising link between fatty acid synthesis and cholesterol synthesis. We further demonstrate that this process is required for TLR4 to enter lipid rafts and facilitate TLR4 signaling. In conclusion, we have uncovered an unexpected link between FASN and cholesterol synthesis that appears to be required for TLR signal transduction and proinflammatory macrophage activation.

Yeast Creates a Niche for Symbiotic Lactic Acid Bacteria through Nitrogen Overflow.

Many microorganisms live in communities and depend on metabolites secreted by fellow community members for survival. Yet our knowledge of interspecies metabolic dependencies is limited to few communities with small number of exchanged metabolites, and even less is known about cellular regulation facilitating metabolic exchange. Here we show how yeast enables growth of lactic acid bacteria through endogenous, multi-component, cross-feeding in a readily established community. In nitrogen-rich environments, Saccharomyces cerevisiae adjusts its metabolism by secreting a pool of metabolites, especially amino acids, and thereby enables survival of Lactobacillus plantarum and Lactococcus lactis. Quantity of the available nitrogen sources and the status of nitrogen catabolite repression pathways jointly modulate this niche creation. We demonstrate how nitrogen overflow by yeast benefits L. plantarum in grape juice, and contributes to emergence of mutualism with L. lactis in a medium with lactose. Our results illustrate how metabolic decisions of an individual species can benefit others.

Metabolic network segmentation: A probabilistic graphical modeling approach to identify the sites and sequential order of metabolic regulation from non-targeted metabolomics data.

In recent years, the number of large-scale metabolomics studies on various cellular processes in different organisms has increased drastically. However, it remains a major challenge to perform a systematic identification of mechanistic regulatory events that mediate the observed changes in metabolite levels, due to complex interdependencies within metabolic networks. We present the metabolic network segmentation (MNS) algorithm, a probabilistic graphical modeling approach that enables genome-scale, automated prediction of regulated metabolic reactions from differential or serial metabolomics data. The algorithm sections the metabolic network into modules of metabolites with consistent changes. Metabolic reactions that connect different modules are the most likely sites of metabolic regulation. In contrast to most state-of-the-art methods, the MNS algorithm is independent of arbitrary pathway definitions, and its probabilistic nature facilitates assessments of noisy and incomplete measurements. With serial (i.e., time-resolved) data, the MNS algorithm also indicates the sequential order of metabolic regulation. We demonstrated the power and flexibility of the MNS algorithm with three, realistic case studies with bacterial and human cells. Thus, this approach enables the identification of mechanistic regulatory events from large-scale metabolomics data, and contributes to the understanding of metabolic processes and their interplay with cellular signaling and regulation processes.

Genomewide landscape of gene-metabolome associations in Escherichia coli.

Metabolism is one of the best-understood cellular processes whose network topology of enzymatic reactions is determined by an organism's genome. The influence of genes on metabolite levels, however, remains largely unknown, particularly for the many genes encoding non-enzymatic proteins. Serendipitously, genomewide association studies explore the relationship between genetic variants and metabolite levels, but a comprehensive interaction network has remained elusive even for the simplest single-celled organisms. Here, we systematically mapped the association between > 3,800 single-gene deletions in the bacterium Escherichia coli and relative concentrations of > 7,000 intracellular metabolite ions. Beyond expected metabolic changes in the proximity to abolished enzyme activities, the association map reveals a largely unknown landscape of gene-metabolite interactions that are not represented in metabolic models. Therefore, the map provides a unique resource for assessing the genetic basis of metabolic changes and conversely hypothesizing metabolic consequences of genetic alterations. We illustrate this by predicting metabolism-related functions of 72 so far not annotated genes and by identifying key genes mediating the cellular response to environmental perturbations.

Nontargeted in vitro metabolomics for high-throughput identification of novel enzymes in Escherichia coli.

Our understanding of metabolism is limited by a lack of knowledge about the functions of many enzymes. Here, we develop a high-throughput mass spectrometry approach to comprehensively profile proteins for in vitro enzymatic activity. Overexpressed or purified proteins are incubated in a supplemented metabolome extract containing hundreds of biologically relevant candidate substrates, and accumulating and depleting metabolites are determined by nontargeted mass spectrometry. By combining chemometrics and database approaches, we established an automated pipeline for unbiased annotation of the functions of novel enzymes. In screening all 1,275 functionally uncharacterized Escherichia coli proteins, we discovered 241 potential novel enzymes, 12 of which we experimentally validated. Our high-throughput in vitro metabolomics method is generally applicable to any purified protein or crude cell lysate of its overexpression host and enables performing up to 1,200 nontargeted enzyme assays per working day.

Global Metabolic Responses to Salt Stress in Fifteen Species.

Cells constantly adapt to unpredictably changing extracellular solute concentrations. A cornerstone of the cellular osmotic stress response is the metabolic supply of energy and building blocks to mount appropriate defenses. Yet, the extent to which osmotic stress impinges on the metabolic network remains largely unknown. Moreover, it is mostly unclear which, if any, of the metabolic responses to osmotic stress are conserved among diverse organisms or confined to particular groups of species. Here we investigate the global metabolic responses of twelve bacteria, two yeasts and two human cell lines exposed to sustained hyperosmotic salt stress by measuring semiquantitative levels of hundreds of cellular metabolites using nontargeted metabolomics. Beyond the accumulation of osmoprotectants, we observed significant changes of numerous metabolites in all species. Global metabolic responses were predominantly species-specific, yet individual metabolites were characteristically affected depending on species' taxonomy, natural habitat, envelope structure or salt tolerance. Exploiting the breadth of our dataset, the correlation of individual metabolite response magnitudes across all species implicated lower glycolysis, tricarboxylic acid cycle, branched-chain amino acid metabolism and heme biosynthesis to be generally important for salt tolerance. Thus, our findings place the global metabolic salt stress response into a phylogenetic context and provide insights into the cellular phenotype associated with salt tolerance.

Life span extension by targeting a link between metabolism and histone acetylation in Drosophila.

Old age is associated with a progressive decline of mitochondrial function and changes in nuclear chromatin. However, little is known about how metabolic activity and epigenetic modifications change as organisms reach their midlife. Here, we assessed how cellular metabolism and protein acetylation change during early aging in Drosophila melanogaster. Contrary to common assumptions, we find that flies increase oxygen consumption and become less sensitive to histone deacetylase inhibitors as they reach midlife. Further, midlife flies show changes in the metabolome, elevated acetyl-CoA levels, alterations in protein-notably histone-acetylation, as well as associated transcriptome changes. Based on these observations, we decreased the activity of the acetyl-CoA-synthesizing enzyme ATP citrate lyase (ATPCL) or the levels of the histone H4 K12-specific acetyltransferase Chameau. We find that these targeted interventions both alleviate the observed aging-associated changes and promote longevity. Our findings reveal a pathway that couples changes of intermediate metabolism during aging with the chromatin-mediated regulation of transcription and changes in the activity of associated enzymes that modulate organismal life span.

A dual control mechanism synchronizes riboflavin and sulphur metabolism in Bacillus subtilis.

Flavin mononucleotide (FMN) riboswitches are genetic elements, which in many bacteria control genes responsible for biosynthesis and/or transport of riboflavin (rib genes). Cytoplasmic riboflavin is rapidly and almost completely converted to FMN by flavokinases. When cytoplasmic levels of FMN are sufficient ("high levels"), FMN binding to FMN riboswitches leads to a reduction of rib gene expression. We report here that the protein RibR counteracts the FMN-induced "turn-off" activities of both FMN riboswitches in Bacillus subtilis, allowing rib gene expression even in the presence of high levels of FMN. The reason for this secondary metabolic control by RibR is to couple sulfur metabolism with riboflavin metabolism.

The neurometabolic fingerprint of excessive alcohol drinking.

'Omics' techniques are widely used to identify novel mechanisms underlying brain function and pathology. Here we applied a novel metabolomics approach to further ascertain the role of frontostriatal brain regions for the expression of addiction-like behaviors in rat models of alcoholism. Rats were made alcohol dependent via chronic intermittent alcohol vapor exposure. Following a 3-week abstinence period, rats had continuous access to alcohol in a two-bottle, free-choice paradigm for 7 weeks. Nontargeted flow injection time-of-flight mass spectrometry was used to assess global metabolic profiles of two cortical (prelimbic and infralimbic) and two striatal (accumbens core and shell) brain regions. Alcohol consumption produces pronounced global effects on neurometabolomic profiles leading to a clear separation of metabolic phenotypes between treatment groups, particularly. Further comparisons of regional tissue levels of various metabolites, most notably dopamine and Met-enkephalin, allow the extrapolation of alcohol consumption history. Finally, a high-drinking metabolic fingerprint was identified indicating a distinct alteration of central energy metabolism in the accumbens shell of excessively drinking rats that could indicate a so far unrecognized pathophysiological mechanism in alcohol addiction. In conclusion, global metabolic profiling from distinct brain regions by mass spectrometry identifies profiles reflective of an animal's drinking history and provides a versatile tool to further investigate pathophysiological mechanisms in alcohol dependence.