Metabolomic analysis by LC-HRMS of xenobiotic metabolism by the gut microbiota.

Júlia Santos Nunes1,2, VITÓRIA NOGUEIRA FERNANDES1, TADEU LIMA MONTAGNOLI1,3, RODRIGO OCTÁVIO MENDONÇA ALVES DE SOUZA 3, Gisele Zapata-Sudo1,4, Marina Amaral Alves5

1. UFRJ, Universidade Federal do Rio de Janeiro; R. Antônio Barros de Castro, 119 - Cidade Universitária, Rio de Janeiro
2. FF, Faculdade de Farmácia; R. Antônio Barros de Castro, 119 - Cidade Universitária, Rio de Janeiro
3. IQ, Instituto de Quimica; Avenida Athos da Silveira Ramos, nº 149, Bloco A – 7º andar Centro de Tecnologia
4. ICB, Instituto de Ciências Biomédicas; R. Antônio Barros de Castro, 119 - Cidade Universitária, Rio de Janeiro
5. IPPN, Instituto de Pesquisas de Produtos Naturais Walter Mors ; Av. Carlos Chagas Filho, 373 - Bloco H - Cidade Universitária, Rio de Janeiro

The gut microbiota is composed of microorganisms that inhabit the digestive tract and perform essential functions for the host\'s health. In addition to participating in digestion and the synthesis of bioactive metabolites, these microorganisms interact with exogenous compounds, such as food, pollutants, and drugs, known as xenobiotics. The microbiota is capable of performing biotransformations that can completely alter the biological activity of these xenobiotics. These modifications can directly affect the half-life, bioavailability, toxicity, and pharmacological efficacy of the compounds, thus being an essential factor in the therapeutic response. The growing understanding of this interaction has highlighted the role of the microbiota-gut-brain axis in complex conditions, such as neuropathic pain.

Neuropathic pain (NP) is caused by injury or dysfunction of the central or peripheral nervous system and affects millions of people worldwide, being characterized by symptoms such as allodynia, hyperalgesia, and persistent chronic pain. Its treatment, to date, presents a clinical challenge, as current therapies are often ineffective and associated with significant adverse effects. It is estimated that only one-third of treated patients show significant improvement, a factor that highlights the urgent need for new therapeutic approaches. In this context, cannabinoids, especially cannabidiol (CBD), have emerged as promising alternatives due to their anti-inflammatory, immunomodulatory, and analgesic properties. However, the effects of CBD can be modulated by the gut microbiota, which makes it essential to study the metabolic pathways involved in its action.

This work aims to investigate, through advanced non-targeted metabolomics strategies, the influence of the gut microbiota on the biotransformation and analgesic effects of CBD oil and its metabolites, in an animal model of diabetes-induced neuropathic pain. For this, a model of diabetes-induced neuropathic pain was established. Fecal and plasma samples were collected from the experimental groups, consisting of control animals (no treatment), vehicle-treated controls, and CBD-treated animals. The collected fecal and plasma samples were analyzed using a non-targeted metabolomics strategy on an ultra-performance liquid chromatography coupled to high-resolution mass spectrometry (UPLC-HRMS) platform. Using bioinformatics tools such as MS-DIAL and GNPS, metabolites were identified, and molecular networks were constructed, which are being used for the characterization of these metabolites. Subsequently, the data will be interpreted to assess whether the identified metabolites are active or toxic, aiming to understand the mechanisms of action involved in pain relief.

 

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