Metabolic changes in temporal lobe structures measured by HR-MAS NMR at early stage of electrogenic rat epilepsy

Liu, Huilang; Fang, Fang; Zhu, Hang; Xia, Sheng-an; Han, Dong; Hu, Ling; Lei, Hao; Liu, Maili

doi:10.1016/j.expneurol.2008.04.013

Cited by 7 publications

(6 citation statements)

References 47 publications

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“…Osmolytes control the ion gradient across membranes, and modifications of their levels may facilitate neuronal discharge and epileptiform activity (Liu et al 2008), as described in the Fmr1-deficient mouse (Qiu et al 2008). …”

Section: Altered Osmolyte and Secondary Messengers Balancementioning

confidence: 99%

A metabolomic and systems biology perspective on the brain of the Fragile X syndrome mouse model

Davidovic¹,

Navratil²,

Bonaccorso³

et al. 2011

Genome Res.

104

126

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Fragile X syndrome (FXS) is the first cause of inherited intellectual disability, due to the silencing of the X-linked Fragile X Mental Retardation 1 gene encoding the RNA-binding protein FMRP. While extensive studies have focused on the cellular and molecular basis of FXS, neither human Fragile X patients nor the mouse model of FXS-the Fmr1-null mouse-have been profiled systematically at the metabolic and neurochemical level to provide a complementary perspective on the current, yet scattered, knowledge of FXS. Using proton high-resolution magic angle spinning nuclear magnetic resonance ( 1 H HR-MAS NMR)-based metabolic profiling, we have identified a metabolic signature and biomarkers associated with FXS in various brain regions of Fmr1-deficient mice. Our study highlights for the first time that Fmr1 gene inactivation has profound, albeit coordinated consequences in brain metabolism leading to alterations in: (1) neurotransmitter levels, (2) osmoregulation, (3) energy metabolism, and (4) oxidative stress response. To functionally connect Fmr1-deficiency to its metabolic biomarkers, we derived a functional interaction network based on the existing knowledge (literature and databases) and show that the FXS metabolic response is initiated by distinct mRNA targets and proteins interacting with FMRP, and then relayed by numerous regulatory proteins. This novel ''integrated metabolome and interactome mapping'' (iMIM) approach advantageously unifies novel metabolic findings with previously unrelated knowledge and highlights the contribution of novel cellular pathways to the pathophysiology of FXS. These metabolomic and integrative systems biology strategies will contribute to the development of potential drug targets and novel therapeutic interventions, which will eventually benefit FXS patients.[Supplemental material is available for this article.]Fragile X syndrome (FXS) is the most frequent cause of inherited intellectual disability (ID) and the most commonly identified genetic cause of autism (Chelly et al. 2006;Gecz et al. 2009). FXS affects 1 in 4000 males and 1 in 7000 females world-wide (Hagerman 2008) and is caused by the silencing of the X-linked Fragile X Mental Retardation 1 (FMR1) gene positioned in Xq27.3. In FXS patients, a dynamic mutation increasing abnormally the number of CGG repeats in the first exon of the FMR1 gene leads to their hypermethylation and the subsequent absence of its gene product, FMRP (Penagarikano et al. 2007). Although a monogenic disorder, FXS is a disease of complex etiology accompanied by behavioral (hyperactivity, autism), neurological (susceptibility to epileptic seizures), as well as physical abnormalities (macroorchidism, elongated face, hyperextensible finger joints) (Penagarikano et al. 2007). A mouse model of FXS knock-out (KO) for the murine homolog of FMR1, has been generated, exhibiting learning and behavioral abnormalities that recapitulate the human phenotype (The Dutch-Belgian Fragile X Consortium 1994). The absence of FMRP induces abnormal extra dendritic spines...

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Section: Altered Osmolyte and Secondary Messengers Balancementioning

confidence: 99%

A metabolomic and systems biology perspective on the brain of the Fragile X syndrome mouse model

Davidovic¹,

Navratil²,

Bonaccorso³

et al. 2011

Genome Res.

104

126

View full text Add to dashboard Cite

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“…HRMAS has been previously used in several studies of brain tumour tissue [5-11] and the concentrations of the main tumour metabolites that are measured show good agreement between in-vivo MRS and ex-vivo HRMAS for several tumour types [10,12-14]. Other pathologies have also been investigated using quantitative ex-vivo HRMAS [15,16]. This paper provides assignments for metabolites that are observable for the most common histopathological types of adult intracranial tumour (gliomas of grade II to IV, meningiomas, metastases and also lymphomas) and reports their quantitation.…”

Section: Introductionmentioning

confidence: 99%

Ex-vivo HRMAS of adult brain tumours: metabolite quantification and assignment of tumour biomarkers

et al. 2010

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BackgroundHigh-resolution magic angle spinning (HRMAS) NMR spectroscopy allows detailed metabolic analysis of whole biopsy samples for investigating tumour biology and tumour classification. Accurate biochemical assignment of small molecule metabolites that are "NMR visible" will improve our interpretation of HRMAS data and the translation of NMR tumour biomarkers to in-vivo studies.Results1D and 2D 1H HRMAS NMR was used to determine that 29 small molecule metabolites, along with 8 macromolecule signals, account for the majority of the HRMAS spectrum of the main types of brain tumour (astrocytoma grade II, grade III gliomas, glioblastomas, metastases, meningiomas and also lymphomas). Differences in concentration of 20 of these metabolites were statistically significant between these brain tumour types. During the course of an extended 2D data acquisition the HRMAS technique itself affects sample analysis: glycine, glutathione and glycerophosphocholine all showed small concentration changes; analysis of the sample after HRMAS indicated structural damage that may affect subsequent histopathological analysis.ConclusionsA number of small molecule metabolites have been identified as potential biomarkers of tumour type that may enable development of more selective in-vivo 1H NMR acquisition methods for diagnosis and prognosis of brain tumours.

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“…Changes in the hippocampal metabolic profile were observed in different brain regions of epilepsy models at 4–5 weeks post‐kindling compared to the control group by metabolomic and lipidomic analysis (Carmody & Brennan, 2010; Qiu et al, 2020). Studies in electric‐kindled rats using high‐resolution magic‐angle‐spinning nuclear magnetic resonance (HR‐MAS NMR) spectroscopy had also revealed metabolic changes in temporal lobe regions at early stages of epileptogenesis in rats (H. Liu et al, 2008). In addition, a distinct metabolic profile was observed in the serum of epilepsy patients compared to that of healthy individuals (Boguszewicz et al, 2019; Wang et al, 2016; Wei et al, 2012).…”

Section: Discussionmentioning

confidence: 99%

Hippocampal metabolic profile during epileptogenesis in the pilocarpine model of epilepsy

Meier,

Bruginski,

Marafiga

et al. 2023

Biomedical Chromatography

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Temporal lobe epilepsy (TLE) is a common form of refractory epilepsy in adulthood. The metabolic profile of epileptogenesis is still poorly investigated. Elucidation of such a metabolic profile using animal models of epilepsy could help identify new metabolites and pathways involved in the mechanisms of epileptogenesis process. In this study, we evaluated the metabolic profile during the epileptogenesis periods. Using a pilocarpine model of epilepsy, we analyzed the global metabolic profile of hippocampal extracts by untargeted metabolomics based on ultra‐performance liquid chromatography–high‐resolution mass spectrometry, at three time points (3 h, 1 week, and 2 weeks) after status epilepticus (SE) induction. We demonstrated that epileptogenesis periods presented different hippocampal metabolic profiles, including alterations of metabolic pathways of amino acids and lipid metabolism. Six putative metabolites (tryptophan, N‐acetylornithine, N‐acetyl‐L‐aspartate, glutamine, adenosine, and cholesterol) showed significant different levels during epileptogenesis compared to their respective controls. These putative metabolites could be associated with the imbalance of neurotransmitters, mitochondrial dysfunction, and cell loss observed during both epileptogenesis and epilepsy. With these findings, we provided an overview of hippocampal metabolic profiles during different stages of epileptogenesis that could help investigate pathways and respective metabolites as predictive tools in epilepsy.

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Metabolic changes in temporal lobe structures measured by HR-MAS NMR at early stage of electrogenic rat epilepsy

Cited by 7 publications

References 47 publications

A metabolomic and systems biology perspective on the brain of the Fragile X syndrome mouse model

A metabolomic and systems biology perspective on the brain of the Fragile X syndrome mouse model

Ex-vivo HRMAS of adult brain tumours: metabolite quantification and assignment of tumour biomarkers

Hippocampal metabolic profile during epileptogenesis in the pilocarpine model of epilepsy

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