Previous fundamental and clinical research has shown that electroacupuncture (EA) at the acupoints of Quchi (LI11) and Zusanli (ST36) can successfully alleviate motor dysfunction following stroke. Additionally, it has been discovered that gut microbiota and their metabolites play an essential role in stroke. However, the relationship between the metabolites of gut microbiota and the efficacy of EA is still unclear. Therefore, the aim of this study was to evaluate the mechanism of EA at LI11 and ST36 in the treatment of motor dysfunction after middle cerebral artery occlusion/reperfusion (MCAO/R) in model rats by comparing the differences and correlation between different short-chain fatty acids (SCFAs) and the recovery of motor function. The results indicated that EA at LI11 and ST36 acupoints enhanced the neurological function, motor function, and infarct volume of MCAO/R rats. The levels of acetic acid, propionic acid, and total SCFAs were considerably lower in the MCAO/R group than in the sham group ( P < 0.05 ). Acetic acid, propionic acid, and total SCFA concentrations were substantially higher in the MCAO/R + EA group than in the MCAO/R group ( P < 0.05 ). Finally, Pearson correlation analysis revealed that the propionic acid concentration was substantially favorably connected with the duration on the rotarod ( r = 0.633 and P < 0.05 ) and highly negatively correlated with the modified neurological severity score (mNSS) ( r = − 0.698 and P < 0.05 ) and the percentage of cerebral infarct volume ( r = − 0.729 and P < 0.05 ). Taken together, these findings indicate that the increase in propionic acid may be one of the mechanisms and targets of EA at LI11 and ST36 acupoints to improve poststroke motor dysfunction in MCAO/R rats.
IntroductionBrain tissue damage caused by ischemic stroke can trigger changes in the body’s metabolic response, and understanding the changes in the metabolic response of the gut after stroke can contribute to research on poststroke brain function recovery. Despite the increase in international research on poststroke metabolic mechanisms and the availability of powerful research tools in recent years, there is still an urgent need for poststroke metabolic studies. Metabolomic examination of feces from a cerebral ischemia–reperfusion rat model can provide new insights into poststroke metabolism and identify key metabolic pathways, which will help reveal diagnostic and therapeutic targets as well as inspire pathophysiological studies after stroke.MethodsWe randomly divided 16 healthy adult pathogen-free male Sprague–Dawley (SD) rats into the normal group and the study group, which received middle cerebral artery occlusion/reperfusion (MCAO/R). Ultra-performance liquid chromatography–tandem mass spectrometry (UPLCMS/MS) was used to determine the identities and concentrations of metabolites across all groups, and filtered high-quality data were analyzed for differential screening and differential metabolite functional analysis.ResultsAfter 1 and 14 days of modeling, compared to the normal group, rats in the study group showed significant neurological deficits (p < 0.001) and significantly increased infarct volume (day 1: p < 0.001; day 14: p = 0.001). Mass spectra identified 1,044 and 635 differential metabolites in rat feces in positive and negative ion modes, respectively, which differed significantly between the normal and study groups. The metabolites with increased levels identified in the study group were involved in tryptophan metabolism (p = 0.036678, p < 0.05), arachidonic acid metabolism (p = 0.15695), cysteine and methionine metabolism (p = 0.24705), and pyrimidine metabolism (p = 0.3413), whereas the metabolites with decreased levels were involved in arginine and proline metabolism (p = 0.15695) and starch and sucrose metabolism (p = 0.52256).DiscussionWe determined that UPLC–MS/MS could be employed for untargeted metabolomics research. Moreover, tryptophan metabolic pathways may have been disordered in the study group. Alterations in the tryptophan metabolome may provide additional theoretical and data support for elucidating stroke pathogenesis and selecting pathways for intervention.
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