Gut-derived bacterial LPS attenuates incubation of methamphetamine craving via modulating microglia

Notoginsenoside R1 alleviates cerebral ischemia/reperfusion injury by inhibiting the TLR4/MyD88/NF-κB signaling pathway through microbiota-gut-brain axis

BACKGROUND

Ischemic stroke (IS) ranks as the second common cause of death worldwide. However, a narrow thrombolysis timeframe and ischemia-reperfusion (I/R) injury limits patient recovery. Moreover, anticoagulation and antithrombotic drugs do not meet the clinical requirements. Studies have demonstrated close communication between the brain and gut microbiota in IS. Notoginsenoside R1 (NG-R1), a significant component of the total saponins from Panax notoginseng, has been demonstrated to be effective against cerebral I/R injury. Total saponins have been used to treat IS in Chinese pharmacopoeia. Furthermore, previous research has indicated that the absorption of NG-R1 was controlled by gut microbiota.

STUDY DESIGN

This study aimed to access the impact of NG-R1 treatment on neuroinflammation and investigate the microbiota-related mechanisms.

RESULTS

NG-R1 significantly reduced neuronal death and neuroinflammation in middle cerebral artery occlusion/reperfusion (MCAO/R) models. 16S rRNA sequencing revealed that NG-R1 treatment displayed the reversal of microbiota related with MCAO/R models. Additionally, NG-R1 administration attenuated intestinal inflammation, gut barrier destruction, and systemic inflammation. Furthermore, microbiota transplantation from NG-R1 exhibited a similar effect in the MCAO/R models.

CONCLUSION

In summary, NG-R1 treatment resulted in the restoration of the structure of the blood-brain barrier (BBB) and reduction in neuroinflammation via suppressing the stimulation of astrocytes and microglia in the cerebral ischemic area. Mechanistic research demonstrated that NG-R1 treatment suppressed the toll-like receptor 4/myeloid differentiation primary response 88/nuclear factor kappa B (TLR4/MyD88/NF-κB) signaling pathway in both the ischemic brain and colon. NG-R1 treatment enhanced microbiota dysbiosis by inhibiting the TLR4 signaling pathway to protect MCAO/R models. These findings elucidate the mechanisms by which NG-R1 improve stroke outcomes and provide some basis for Panax notoginseng saponins in clinical treatment.

Gut microbiota-derived short-chain fatty acids and depression: deep insight into biological mechanisms and potential applications

The gut microbiota is a complex and dynamic ecosystem known as the 'second brain'. Composing the microbiota-gut-brain axis, the gut microbiota and its metabolites regulate the central nervous system through neural, endocrine and immune pathways to ensure the normal functioning of the organism, tuning individuals' health and disease status. Short-chain fatty acids (SCFAs), the main bioactive metabolites of the gut microbiota, are involved in several neuropsychiatric disorders, including depression. SCFAs have essential effects on each component of the microbiota-gut-brain axis in depression. In the present review, the roles of major SCFAs (acetate, propionate and butyrate) in the pathophysiology of depression are summarised with respect to chronic cerebral hypoperfusion, neuroinflammation, host epigenome and neuroendocrine alterations. Concluding remarks on the biological mechanisms related to gut microbiota will hopefully address the clinical value of microbiota-related treatments for depression.

Microglia contribute to methamphetamine reinforcement and reflect persistent transcriptional and morphological adaptations to the drug

Methamphetamine use disorder (MUD) is a chronic, relapsing disease that is characterized by repeated drug use despite negative consequences and for which there are currently no FDA-approved cessation therapeutics. Repeated methamphetamine (METH) use induces long-term gene expression changes in brain regions associated with reward processing and drug-seeking behavior, and recent evidence suggests that methamphetamine-induced neuroinflammation may also shape behavioral and molecular responses to the drug. Microglia, the resident immune cells in the brain, are principal drivers of neuroinflammatory responses and contribute to the pathophysiology of substance use disorders. Here, we investigated transcriptional and morphological changes in dorsal striatal microglia in response to methamphetamine-taking and during methamphetamine abstinence, as well as their functional contribution to drug-taking behavior. We show that methamphetamine self-administration induces transcriptional changes associated with protein folding, mRNA processing, immune signaling, and neurotransmission in dorsal striatal microglia. Importantly, many of these transcriptional changes persist through abstinence, a finding supported by morphological analyses. Functionally, we report that microglial ablation increases methamphetamine-taking, possibly involving neuroimmune and neurotransmitter regulation, and that post-methamphetamine microglial repopulation attenuates drug-seeking following a 21-day period of abstinence. In contrast, microglial depletion during abstinence did not alter methamphetamine-seeking. Taken together, these results suggest that methamphetamine induces both short and long-term changes in dorsal striatal microglia that contribute to altered drug-taking behavior and may provide valuable insights into the pathophysiology of MUD.

Current perspectives on microglia-neuron communication in the central nervous system: Direct and indirect modes of interaction

BACKGROUND

The incessant communication that takes place between microglia and neurons is essential the development, maintenance, and pathogenesis of the central nervous system (CNS). As mobile phagocytic cells, microglia serve a critical role in surveilling and scavenging the neuronal milieu to uphold homeostasis.

AIM OF REVIEW

This review aims to discuss the various mechanisms that govern the interaction between microglia and neurons, from the molecular to the organ system level, and to highlight the importance of these interactions in the development, maintenance, and pathogenesis of the CNS.

KEY SCIENTIFIC CONCEPTS OF REVIEW

Recent research has revealed that microglia-neuron interaction is vital for regulating fundamental neuronal functions, such as synaptic pruning, axonal remodeling, and neurogenesis. The review will elucidate the intricate signaling pathways involved in these interactions, both direct and indirect, to provide a better understanding of the fundamental mechanisms of brain function. Furthermore, gaining insights into these signals could lead to the development of innovative therapies for neural disorders.

Modeling methamphetamine use disorder and relapse in animals: short- and long-term epigenetic, transcriptional., and biochemical consequences in the rat brain

Methamphetamine use disorder (MUD) is a neuropsychiatric disorder characterized by binge drug taking episodes, intervals of abstinence, and relapses to drug use even during treatment. MUD has been modeled in rodents and investigators are attempting to identify its molecular bases. Preclinical experiments have shown that different schedules of methamphetamine self-administration can cause diverse transcriptional changes in the dorsal striatum of Sprague-Dawley rats. In the present review, we present data on differentially expressed genes (DEGs) identified in the rat striatum following methamphetamine intake. These include genes involved in transcription regulation, potassium channel function, and neuroinflammation. We then use the striatal data to discuss the potential significance of the molecular changes induced by methamphetamine by reviewing concordant or discordant data from the literature. This review identified potential molecular targets for pharmacological interventions. Nevertheless, there is a need for more research on methamphetamine-induced transcriptional consequences in various brain regions. These data should provide a more detailed neuroanatomical map of methamphetamine-induced changes and should better inform therapeutic interventions against MUD.

The gut microbiota as a potential biomarker for methamphetamine use disorder: evidence from two independent datasets

Background

Methamphetamine use disorder (MUD) poses a considerable public health threat, and its identification remains challenging due to the subjective nature of the current diagnostic system that relies on self-reported symptoms. Recent studies have suggested that MUD patients may have gut dysbiosis and that gut microbes may be involved in the pathological process of MUD. We aimed to examine gut dysbiosis among MUD patients and generate a machine-learning model utilizing gut microbiota features to facilitate the identification of MUD patients.

Method

Fecal samples from 78 MUD patients and 50 sex- and age-matched healthy controls (HCs) were analyzed by 16S rDNA sequencing to identify gut microbial characteristics that could help differentiate MUD patients from HCs. Based on these microbial features, we developed a machine learning model to help identify MUD patients. We also used public data to verify the model; these data were downloaded from a published study conducted in Wuhan, China (with 16 MUD patients and 14 HCs). Furthermore, we explored the gut microbial features of MUD patients within the first three months of withdrawal to identify the withdrawal period of MUD patients based on microbial features.

Results

MUD patients exhibited significant gut dysbiosis, including decreased richness and evenness and changes in the abundance of certain microbes, such as Proteobacteria and Firmicutes. Based on the gut microbiota features of MUD patients, we developed a machine learning model that demonstrated exceptional performance with an AUROC of 0.906 for identifying MUD patients. Additionally, when tested using an external and cross-regional dataset, the model achieved an AUROC of 0.830. Moreover, MUD patients within the first three months of withdrawal exhibited specific gut microbiota features, such as the significant enrichment of Actinobacteria. The machine learning model had an AUROC of 0.930 for identifying the withdrawal period of MUD patients.

Conclusion

In conclusion, the gut microbiota is a promising biomarker for identifying MUD and thus represents a potential approach to improving the identification of MUD patients. Future longitudinal studies are needed to validate these findings.