Metabolomics analysis of serum in a rat heroin self-administration model undergoing reinforcement based on 1H-nuclear magnetic resonance spectra

Exploring the progression of drug dependence in a methamphetamine self-administration rat model through targeted and non-targeted metabolomics analyses

Persistent neurochemical and biological disturbances resulting from repeated cycles of drug reward, withdrawal, and relapse contribute to drug dependence. Methamphetamine (MA) is a psychostimulant with substantial abuse potential and neurotoxic effects, primarily affecting monoamine neurotransmitter systems in the brain. In this study, we aimed to explore the progression of drug dependence in rat models of MA self-administration, extinction, and reinstatement through targeted and non-targeted metabolomics analyses. Metabolic profiles were examined in rat plasma during the following phases: after 16 days of MA self-administration (Group M); after 16 days of self-administration followed by 14 days of extinction (Group MS); and after self-administration and extinction followed by a reinstatement injection of MA (Group MSM). Each group of MA self-administration, extinction, and reinstatement induces distinct changes in the metabolic pathways, particularly those related to the TCA cycle, arginine and proline metabolism, and arginine biosynthesis. Additionally, the downregulation of glycerophospholipids and sphingomyelins in Group MSM suggests their potential role in MA reinstatement. These alterations may signify the progressive deterioration of these metabolic pathways, possibly contributing to drug dependence following repeated cycles of drug reward, withdrawal, and relapse. These results provide valuable insights into the metabolic changes associated with MA use at various stages, potentially facilitating the discovery of early diagnostic biomarkers and therapeutic targets for MA use disorders.

Tackling new psychoactive substances through metabolomics: UHPLC-HRMS study on natural and synthetic opioids in male and female murine models

Novel psychoactive substances (NPS) represent a broad class of drugs new to the illicit market that often allow passing drug-screening tests. They are characterized by a variety of structures, rapid transience on the drug scene and mostly unknown metabolic profiles, thus creating an ever-changing scenario with evolving analytical targets. The present study aims at developing an indirect screening strategy for NPS monitoring, and specifically for new synthetic opioids (NSOs), based on assessing changes in endogenous urinary metabolite levels as a consequence of the systemic response following their intake. The experimental design involved in-vivo mice models: 16 animals of both sex received a single administration of morphine or fentanyl. Urine was collected before and after administration at different time points; the samples were then analysed with an untargeted metabolomics LC-HRMS workflow. According to our results, the intake of opioids resulted in an elevated energy demand, that was more pronounced on male animals, as evidenced by the increase in medium and long chain acylcarnitines levels. It was also shown that opioid administration disrupted the pathways related to catecholamines biosynthesis. The observed alterations were common to both morphine and fentanyl: this evidence indicate that they are not related to the chemical structure of the drug, but rather on the drug class. The proposed strategy may reinforce existing NPS screening approaches, by identifying indirect markers of drug assumption.

Long access heroin self-administration significantly alters gut microbiome composition and structure

Introduction

It is well known that chronic opioid use disorder is associated with alterations in gastrointestinal (GI) function that include constipation, reduced motility, and increased bacterial translocation due to compromised gut barrier function. These signs of disrupted GI function can be associated with alterations in the gut microbiome. However, it is not known if long-access opioid self-administration has effects on the gut microbiome.

Methods

We used 16S rRNA gene sequencing to investigate the gut microbiome in three independent cohorts (N=40 for each) of NIH heterogeneous stock rats before onset of long-access heroin self-administration (i.e., naïve status), at the end of a 15-day period of self-administration, and after post-extinction reinstatement. Measures of microbial α- and β-diversity were evaluated for all phases. High-dimensional class comparisons were carried out with MaAsLin2. PICRUSt2 was used for predicting functional pathways impacted by heroin based on marker gene sequences.

Results

Community α-diversity was not altered by heroin at any of the three phases by comparison to saline-yoked controls. Analyses of β-diversity showed that the heroin and saline-yoked groups clustered significantly apart from each other using the Bray-Curtis (community structure) index. Heroin caused significant alterations at the ASV level at the self-administration and extinction phases. At the phylum level, the relative abundance of Firmicutes was increased at the self-administration phase. Deferribacteres was decreased in heroin whereas Patescibacteria was increased in heroin at the extinction phase. Potential biomarkers for heroin emerged from the MaAsLin2 analysis. Bacterial metabolomic pathways relating to degradation of carboxylic acids, nucleotides, nucleosides, carbohydrates, and glycogen were increased by heroin while pathways relating to biosynthesis of vitamins, propionic acid, fatty acids, and lipids were decreased.

Discussion

These findings support the view that long access heroin self-administration significantly alters the structure of the gut microbiome by comparison to saline-yoked controls. Inferred metabolic pathway alterations suggest the development of a microbial imbalance favoring gut inflammation and energy expenditure. Potential microbial biomarkers and related functional pathways likely invoked by heroin self-administration could be targets for therapeutic intervention.

Liver Metabolomics and Inflammatory Profiles in Mouse Model of Fentanyl Overdose Treated with Beta-Lactams

Fentanyl is a highly potent opioid analgesic that is approved medically to treat acute and chronic pain. There is a high potential for overdose-induced organ toxicities, including liver toxicity, and this might be due to the increase of recreational use of opioids. Several preclinical studies have demonstrated the efficacy of beta-lactams in modulating the expression of glutamate transporter-1 (GLT-1) in different body organs, including the liver. The upregulation of GLT-1 by beta-lactams is associated with the attenuation of hyperglutamatergic state, which is a characteristic feature of opioid use disorders. A novel experimental beta-lactam compound with no antimicrobial properties, MC-100093, has been developed to attenuate dysregulation of glutamate transport, in part by normalizing GLT-1 expression. A previous study showed that MC-100093 modulated hepatic GLT-1 expression with subsequent attenuation of alcohol-increased fat droplet content in the liver. In this study, we investigated the effects of fentanyl overdose on liver metabolites, and determined the effects of MC-100093 and ceftriaxone in the liver of a fentanyl overdose mouse model. Liver samples from control, fentanyl overdose, and fentanyl overdose ceftriaxone- or MC-100093-treated mice were analyzed for metabolomics using gas chromatography-mass spectrometry. Heatmap analysis revealed that both MC-100093 and ceftriaxone attenuated the effects of fentanyl overdose on several metabolites, and MC-100093 showed superior effects. Statistical analysis showed that MC-100093 reversed the effects of fentanyl overdose in some metabolites. Moreover, enrichment analysis revealed that the altered metabolites were strongly linked to the glucose-alanine cycle, the Warburg effect, gluconeogenesis, glutamate metabolism, lactose degradation, and ketone body metabolism. The changes in liver metabolites induced by fentanyl overdose were associated with liver inflammation, an effect attenuated with ceftriaxone pre-treatments. Ceftriaxone normalized fentanyl-overdose-induced changes in liver interleukin-6 and cytochrome CYP3A11 (mouse homolog of human CYP3A4) expression. Our data indicate that fentanyl overdose impaired liver metabolites, and MC-100093 restored certain metabolites.

Kratom (M. speciosa) exposure during adolescence caused long-lasting cognitive behavioural deficits associated with perturbated brain metabolism pathways in adult rats

Kratom (M. speciosa Korth) is an herbal plant native to Southeast Asia. The leaves have been widely used to alleviate pain and opioid withdrawal symptoms. However, the increasing trend of recreational use of kratom among youth is concerning because substance abuse may render the adolescent brain more susceptible to neuropathological processes, causing dramatic consequences that persist into adulthood. Therefore, the present study aimed to investigate the long-term effects of mitragynine, the main alkaloid and lyophilized kratom decoction (LKD) exposure during adolescence on cognitive behaviours and brain metabolite profiles in adult rats. Adolescent male Sprague-Dawley rats were given mitragynine (3, 10 or 30mg/kg) or LKD orally for 15 consecutive days during postnatal days 31-45 (PND31-45). Behavioural testing was performed during adulthood (PND70-84) and the brains were subjected to metabolomic analysis. The results show that a high dose of mitragynine impaired long-term object recognition memory. Social behaviour and spatial learning were not affected, but both mitragynine and LKD impaired reference memory. Brain metabolomic study revealed several altered metabolic pathways that may be involved in the cognitive behavioural effects of LKD and mitragynine exposure. These pathways include arachidonic acid, taurine and hypotaurine, pantothenate and CoA biosynthesis, and tryptophan metabolism, while the N-isovalerylglycine was identified as the potential biomarker. In summary, adolescent kratom exposure can cause long-lasting cognitive behavioural deficits and alter brain metabolite profiles that are still evident in adulthood. This finding also indicates that the adolescent brain is vulnerable to the impact of early kratom use.

Transcriptomics and metabolomics together reveal the underlying mechanism of heroin hepatotoxicity

Researches on heroin are more about addiction and some infectious diseases it causes, but liver fibrosis caused by heroin abuse and the mechanism of heroin hepatotoxicity in addicts are ignored. To explore the mechanism of heroin hepatotoxicity, mice in heroin group were intraperitoneally injected by heroin (10 mg/kg) once a day for 14 consecutive days, while mice in heroin withdraw group underwent another 7 days without heroin administration after the same treatment as heroin group. The levels of alanine aminotransferase （ALT）and aspartate aminotransferase （AST） in serum, as biochemical indexes, were applied to evaluate liver damage. H & E staining and oil red O staining were used to observe the pathological changes of liver. Transcriptomics and metabolomics were applied to detect genes and metabolites in livers. The results of biochemical analysis and pathological examination showed that heroin induced liver damage and lipid loss in mice, and these mice did not return to normal completely after a short-term withdrawal. A total of 511 differential genes and 78 differential metabolites were identified by transcriptomics and metabolomics. These differential genes and metabolites were significantly enriched in pathways like lipid metabolism, arachidonic acid metabolism, glutathione metabolism, TCA cycle. And after undergoing 7-day withdrawal of heroin, most of the above differential genes and metabolites did not return to normal. Our study revealed the hepatotoxicity of heroin and that short-term withdrawal of heroin did not fully restore liver function. In addition, transcriptomics and metabolomics revealed that lipid metabolism and arachidonic acid metabolism may be potential therapeutic targets of heroin hepatotoxicity, providing a basis for the treatment of heroin addiction patients in the future.

Dynamic Changes in Plasma Metabolic Profiles Reveal a Potential Metabolite Panel for Interpretation of Fatal Intoxication by Chlorpromazine or Olanzapine in Mice

Diagnosing the cause of fatal intoxication by antipsychotic agents is an important task in forensic practice. In the 2020 Annual Report of the American Association of Poison Control Centers, among 40 deaths caused by antipsychotics, 21 cases were diagnosed as "probably responsible", thereby indicating that more objective diagnostic tools are needed. We used liquid chromatography-mass spectrometry-based integrated metabolomics analysis to measure changes in metabolic profiles in the plasma of mice that died from fatal intoxication due to chlorpromazine (CPZ) or olanzapine (OLA). These results were used to construct a stable discriminative classification model (DCM) comprising L-acetylcarnitine, succinic acid, and propionylcarnitine between fatal intoxication caused by CPZ/OLA and cervical dislocation (control). Performance evaluation of the classification model in mice that suffered fatal intoxication showed relative specificity for different pharmacodynamic drugs and relative sensitivity in different life states (normal, intoxication, fatal intoxication). A stable level of L-acetylcarnitine and variable levels of succinic acid and propionylcarnitine between fatal-intoxication and intoxication groups revealed procedural perturbations in metabolic pathways related to fatal intoxication by CPZ/OLA. Additional stability studies revealed that decomposition of succinic acid in fatal-intoxication samples (especially in the OLA group) could weaken the prediction performance of the binary-classification model; however, levels of these three potential metabolites measured within 6 days in fresh samples kept at 4 °C revealed a good performance of our model. Our findings suggest that metabolomics analysis can be used to explore metabolic alterations during fatal intoxication due to use of antipsychotic agents and provide evidence for the cause of death.

Identification of Morphine and Heroin-Treatment in Mice Using Metabonomics

Although heroin and morphine are structural analogues and morphine is a metabolite of heroin, it is not known how the effect of each substance on metabolites in vivo differs. Heroin and morphine were administered to C57BL/6J mice in increasing doses from 2 to 25 and 3 to 9 mg kg⁻¹ (twice a day, i.p.), respectively, for 20 days. The animals underwent withdrawal for 5 days and were readministered the drugs after 10 days. Serum and urine analytes were profiled using gas chromatography-mass spectrometry (GC-MS), and metabolic patterns were evaluated based on metabonomics data. Metabonomics data showed that heroin administration changed metabolic pattern, and heroin withdrawal did not quickly restore it to baseline levels. A relapse of heroin exposure changed metabolic pattern again. In contrast, although the administration of morphine changed metabolic pattern, whether from morphine withdrawal or relapse, metabolic pattern was similar to control levels. The analysis of metabolites showed that both heroin and morphine interfered with lipid metabolism, the tricarboxylic acid (TCA) cycle and amino acid metabolism. In addition, both heroin and morphine increased the levels of 3-hydroxybutyric acid and citric acid but decreased the serum levels of 2-ketoglutaric acid and tryptophan. Moreover, heroin and morphine reduced the levels of aconitic acid, cysteine, glycine, and oxalic acid in urine. The results show 3-Hydroxybutyric acid, tryptophan, citric acid and 2-ketoglutaric acid can be used as potential markers of opiate abuse in serum, while oxalic acid, aconitic acid, cysteine, and glycine can be used as potential markers in urine.

Untargeted Metabolomics in Forensic Toxicology: A New Approach for the Detection of Fentanyl Intake in Urine Samples

The misuse of fentanyl, and novel synthetic opioids (NSO) in general, has become a public health emergency, especially in the United States. The detection of NSO is often challenged by the limited diagnostic time frame allowed by urine sampling and the wide range of chemically modified analogues, continuously introduced to the recreational drug market. In this study, an untargeted metabolomics approach was developed to obtain a comprehensive "fingerprint" of any anomalous and specific metabolic pattern potentially related to fentanyl exposure. In recent years, in vitro models of drug metabolism have emerged as important tools to overcome the limited access to positive urine samples and uncertainties related to the substances actually taken, the possible combined drug intake, and the ingested dose. In this study, an in vivo experiment was designed by incubating HepG2 cell lines with either fentanyl or common drugs of abuse, creating a cohort of 96 samples. These samples, together with 81 urine samples including negative controls and positive samples obtained from recent users of either fentanyl or "traditional" drugs, were subjected to untargeted analysis using both UHPLC reverse phase and HILIC chromatography combined with QTOF mass spectrometry. Data independent acquisition was performed by SWATH in order to obtain a comprehensive profile of the urinary metabolome. After extensive processing, the resulting datasets were initially subjected to unsupervised exploration by principal component analysis (PCA), yielding clear separation of the fentanyl positive samples with respect to both controls and samples positive to other drugs. The urine datasets were then systematically investigated by supervised classification models based on soft independent modeling by class analogy (SIMCA) algorithms, with the end goal of identifying fentanyl users. A final single-class SIMCA model based on an RP dataset and five PCs yielded 96% sensitivity and 74% specificity. The distinguishable metabolic patterns produced by fentanyl in comparison to other opioids opens up new perspectives in the interpretation of the biological activity of fentanyl.

Endogenous opiates and behavior: 2019

This paper is the forty-second consecutive installment of the annual anthological review of research concerning the endogenous opioid system, summarizing articles published during 2019 that studied the behavioral effects of molecular, pharmacological and genetic manipulation of opioid peptides and receptors as well as effects of opioid/opiate agonists and antagonists. The review is subdivided into the following specific topics: molecular-biochemical effects and neurochemical localization studies of endogenous opioids and their receptors (1), the roles of these opioid peptides and receptors in pain and analgesia in animals (2) and humans (3), opioid-sensitive and opioid-insensitive effects of nonopioid analgesics (4), opioid peptide and receptor involvement in tolerance and dependence (5), stress and social status (6), learning and memory (7), eating and drinking (8), drug abuse and alcohol (9), sexual activity and hormones, pregnancy, development and endocrinology (10), mental illness and mood (11), seizures and neurologic disorders (12), electrical-related activity and neurophysiology (13), general activity and locomotion (14), gastrointestinal, renal and hepatic functions (15), cardiovascular responses (16), respiration and thermoregulation (17), and immunological responses (18).

Metabolic phenotyping of opioid and psychostimulant addiction: A novel approach for biomarker discovery and biochemical understanding of the disorder

Despite the progress in characterising the pharmacological profile of drugs of abuse, their precise biochemical impact remains unclear. The metabolome reflects the multifaceted biochemical processes occurring within a biological system. This includes those encoded in the genome but also those arising from environmental/exogenous exposures and interactions between the two. Using metabolomics, the biochemical derangements associated with substance abuse can be determined as the individual transitions from recreational drug to chronic use (dependence). By understanding the biomolecular perturbations along this time course and how they vary across individuals, metabolomics can elucidate biochemical mechanisms of the addiction cycle (dependence/withdrawal/relapse) and predict prognosis (recovery/relapse). In this review, we summarise human and animal metabolomic studies in the field of opioid and psychostimulant addiction. We highlight the importance of metabolomics as a powerful approach for biomarker discovery and its potential to guide personalised pharmacotherapeutic strategies for addiction targeted towards the individual's metabolome.

Escalating morphine dosing in HIV-1 Tat transgenic mice with sustained Tat exposure reveals an allostatic shift in neuroinflammatory regulation accompanied by increased neuroprotective non-endocannabinoid lipid signaling molecules and amino acids

BACKGROUND

Human immunodeficiency virus type-1 (HIV-1) and opiates cause long-term inflammatory insult to the central nervous system (CNS) and worsen disease progression and HIV-1-related neuropathology. The combination of these proinflammatory factors reflects a devastating problem as opioids have high abuse liability and continue to be prescribed for certain patients experiencing HIV-1-related pain.

METHODS

Here, we examined the impact of chronic (3-month) HIV-1 transactivator of transcription (Tat) exposure to short-term (8-day), escalating morphine in HIV-1 Tat transgenic mice that express the HIV-1 Tat protein in a GFAP promoter-regulated, doxycycline (DOX)-inducible manner. In addition to assessing morphine-induced tolerance in nociceptive responses organized at spinal (i.e., tail-flick) and supraspinal (i.e., hot-plate) levels, we evaluated neuroinflammation via positron emission tomography (PET) imaging using the [18F]-PBR111 ligand, immunohistochemistry, and cytokine analyses. Further, we examined endocannabinoid (eCB) levels, related non-eCB lipids, and amino acids via mass spectrometry.  RESULTS: Tat-expressing [Tat(+)] transgenic mice displayed antinociceptive tolerance in the tail withdrawal and hot-plate assays compared to control mice lacking Tat [Tat(-)]. This tolerance was accompanied by morphine-dependent increases in Iba-1 ± 3-nitrotryosine immunoreactive microglia, and alterations in pro- and anti-inflammatory cytokines, and chemokines in the spinal cord and striatum, while increases in neuroinflammation were absent by PET imaging of [18F]-PBR111 uptake. Tat and morphine exposure differentially affected eCB levels, non-eCB lipids, and specific amino acids in a region-dependent manner. In the striatum, non-eCB lipids were significantly increased by short-term, escalating morphine exposure, including peroxisome proliferator activator receptor alpha (PPAR-α) ligands N-oleoyl ethanolamide (OEA) and N-palmitoyl ethanolamide (PEA), as well as the amino acids phenylalanine and proline. In the spinal cord, Tat exposure increased amino acids leucine and valine, while morphine decreased levels of tyrosine and valine but did not affect eCBs or non-eCB lipids.

CONCLUSION

Overall results demonstrate that 3 months of Tat exposure increased morphine tolerance and potentially innate immune tolerance evidenced by reductions in specific cytokines (e.g., IL-1α, IL-12p40) and microglial reactivity. In contrast, short-term, escalating morphine exposure acted as a secondary stressor revealing an allostatic shift in CNS baseline inflammatory responsiveness from sustained Tat exposure.

Forensic NMR metabolomics: one more arrow in the quiver

INTRODUCTION

NMR metabolomics is increasingly used in forensics, due to the possibility of investigating both endogenous metabolic profiles and exogenous molecules that may help to describe metabolic patterns and their modifications associated to specific conditions of forensic interest.

OBJECTIVES

The aim of this work was to review the recent literature and depict the information provided by NMR metabolomics. Attention has been devoted to the identification of peculiar metabolic signatures and specific ante-mortem and post-mortem profiles or biomarkers related to different conditions of forensic concern, such as the identification of biological traces, the estimation of the time since death, and the exposure to drugs of abuse.

RESULTS AND CONCLUSION

The results of the described studies highlight how forensics can benefit from NMR metabolomics by gaining additional information that may help to shed light in several forensic issues that still deserve to be further elucidated.

Metabolomics in pharmacology - a delve into the novel field of pharmacometabolomics

Introduction: Pharmacometabolomics is an emerging science pursuing the application of precision medicine. Combining both genetic and environmental factors, the so-called pharmacometabolomic approach guides patient selection and stratification in clinical trials and optimizes personalized drug dosage, improving efficacy and safety.Areas covered: This review illustrates the progressive introduction of pharmacometabolomics as an innovative solution for enhancing the discovery of novel drugs and improving research and development (R&D) productivity of the pharmaceutical industry. An extended analysis on published pharmacometabolomics studies both in animal models and humans includes results obtained in several areas such as hepatology, gastroenterology, nephrology, neuropsychiatry, oncology, drug addiction, embryonic cells, neonatology, and microbiomics.Expert opinion: a tailored, individualized therapy based on the optimization of pharmacokinetics and pharmacodynamics, the improvement of drug efficacy, and the abolition of drug toxicity and adverse drug reactions is a key issue in precision medicine. Genetics alone has become insufficient for deciphring intra- and inter-individual variations in drug-response, since they originate both from genetic and environmental factors, including human microbiota composition. The association between pharmacogenomics and pharmacometabolomics may be considered the new strategy for an in-deep knowledge on changes and alterations in human and microbial metabolic pathways due to the action of a drug.

Metabolomic Strategies in Biomarker Research-New Approach for Indirect Identification of Drug Consumption and Sample Manipulation in Clinical and Forensic Toxicology?

Drug of abuse (DOA) consumption is a growing problem worldwide, particularly with increasing numbers of new psychoactive substances (NPS) entering the drug market. Generally, little information on their adverse effects and toxicity are available. The direct detection and identification of NPS is an analytical challenge due to their ephemerality on the drug scene. An approach that does not directly focus on the structural detection of an analyte or its metabolites, would be beneficial for this complex analytical scenario and the development of alternative screening methods could help to provide fast response on suspected NPS consumption. A metabolomics approach might represent such an alternative strategy for the identification of biomarkers for different questions in DOA testing. Metabolomics is the monitoring of changes in small (endogenous) molecules (<1,000 Da) in response to a certain stimulus, e.g., DOA consumption. For this review, a literature search targeting "metabolomics" and different DOAs or NPS was conducted. Thereby, different applications of metabolomic strategies in biomarker research for DOA identification were identified: (a) as an additional tool for metabolism studies bearing the major advantage that particularly a priori unknown or unexpected metabolites can be identified; and (b) for identification of endogenous biomarker or metabolite patterns, e.g., for synthetic cannabinoids or also to indirectly detect urine manipulation attempts by chemical adulteration or replacement with artificial urine samples. The majority of the currently available literature in that field, however, deals with metabolomic studies for DOAs to better assess their acute or chronic effects or to find biomarkers for drug addiction and tolerance. Certain changes in endogenous compounds are detected for all studied DOAs, but often similar compounds/pathways are influenced. When evaluating these studies with regard to possible biomarkers for drug consumption, the observed changes appear, albeit statistically significant, too small to reliably work as biomarker for drug consumption. Further, different drugs were shown to affect the same pathways. In conclusion, metabolomic approaches possess potential for detection of biomarkers indicating drug consumption. More studies, including more sensitive targeted analyses, multi-variant statistical models or deep-learning approaches are needed to fully explore the potential of omics science in DOA testing.