Dataset Information

Metabolomics analysis highlights Yashtimadhu (Glycyrrhiza glabra L.) mediated neuroprotection in a rotenone-induced cellular model of Parkinsons disease

ABSTRACT: In the present study we carried out global and targeted metabolomics of differentiated IMR32 cells to study the neuroprotective mechanism of Yashtimadhu (Glycyrrhiza glabra L.) in rotenone induced cellular model of parkinsons disease. Our mass spectrometry data highlighted 2403 and 2934 aligned metabolites from the positive and negative modes respectively. Among the aligned metabolites, 756 metabolites from positive and 731 metabolites from negative polarity, were mapped to a known metabolite, and the others remained unassigned. A total of 1,102 non-redundant metabolites from the positive and negative modes were assigned.

INSTRUMENT(S): QTRAP 6500

ORGANISM(S): Homo Sapiens (ncbitaxon:9606)

SUBMITTER: T. S. Keshava Prasad

PROVIDER: MSV000088036 | MassIVE | Tue Aug 31 05:24:00 BST 2021

REPOSITORIES: MassIVE

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Metabolomics analysis highlights Yashtimadhu (Glycyrrhiza glabra L.)-mediated neuroprotection in a rotenone-induced cellular model of Parkinson's disease by restoring the mTORC1-AMPK1 axis in autophagic regulation.

Karthikkeyan Gayathree G Behera Santosh Kumar SK Upadhyay Shubham Sukerndeo SS Pervaje Ravishankar R Prasad Thottethodi Subrahmanya Keshava TSK Modi Prashant Kumar PK

Phytotherapy research : PTR 20220320 5

Parkinson's disease (PD) is an age-associated progressive neurodegenerative movement disorder, and its management strategies are known to cause complications with prolonged usage. We aimed to explore the neuroprotective mechanism of the Indian traditional medicine Yashtimadhu, prepared from the dried roots of Glycyrrhiza glabra L. (licorice) in the rotenone-induced cellular model of PD. Retinoic acid-differentiated IMR-32 cells were treated with rotenone (PD model) and Yashtimadhu extract. Mass ...[more]

PMID: 35307886

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Project description:The importance of the mammalian intestinal microbiota to human health has been intensely studied over the past few years. It is now clear that the interactions between human hosts and their associated microbial communities need to be characterized in molecular detail if we are to truly understand human physiology. Additionally, the study of such host-microbe interactions is likely to provide us with new strategies to manipulate such complex systems to maintain or restore homeostasis in order to prevent or cure pathological states. We describe the use of high-throughput metabolomics to shed light on the interactions between the intestinal microbiota and the host. We show that treatment with the antibiotic streptomycin disrupts intestinal homeostasis and has a profound impact on the intestinal metabolome, affecting the levels of over 87% of all metabolites detected. Many metabolic pathways that are critical for host physiology were affected, including bile acid, eicosanoid and steroid hormone synthesis. Interestingly, many of these pathways are also affected by intestinal pathogens. Dissecting the effect of both beneficial and pathogenic bacteria on some of these pathways will be instrumental in understanding the interplay between the host, the resident microbiota and incoming pathogens and may aid in the design of new therapeutic strategies that target these interactions. Age-matched female C57BL/6 mice were used. Fresh feces were collected and stored at -80 oC. Mice were then treated with 20 mg of streptomycin through oral gavage and fresh feces were collected 24 hours after treatment and stored at -80 oC until used. To extract metabolites from feces, acetonitrile was added to samples (approximately 10-25 μL of acetonitrile per 1 mg of tissue), which were then homogenized. The samples were then cleared by centrifugation and the supernatant was collected and dried at room temperature using a centrifuge equipped with a vacuum pump. All extracts were kept at -80 oC until used. For metabolic profiling, the dried extracts from mouse feces were suspended in a 2:3 mixture of water and acetonitrile (10 μL per 1 mg of tissue), vortexed and cleared by centrifugation. Supernatants were collected and used as described below. Extracts were diluted 1:5 with 60% acetonitrile containing either 0.2% formic acid (for positive ion mode) or 0.5% ammonium hydroxide (for negative ion mode) and spiked with predefined amounts of the "ES tuning mix" solution as the internal standard for mass calibration. The solutions were then infused, using a syringe pump (KDS Scientific, Holliston, USA) at a flow rate of 2.5 µL per minute, into a 12-T Apex-Qe hybrid quadrupole-FT-ICR mass spectrometer (Bruker Daltonics, Billerica, USA) equipped with an Apollo II electrospray ionization source, a quadrupole mass filter and a hexapole collision cell. Data were recorded in positive and negative ion modes with broadband detection and an FT acquisition size of 1024 kilobytes per second, within a range of m/z 150 to 1100. Under these settings, a mass resolution of ca. 100,000 (full width at half maximum, FWHM) at m/z 400 and a mass accuracy within 2 ppm or less for all detected components, following internal mass calibration, were observed. Other experimental parameters were: capillary electrospray voltage of 3600-3750 V, spray shield voltage of 3300-3450 V, source ion accumulation time of 0.1 s and collision cell ion accumulation time of 0.2 s. To increase detection sensitivity, survey scan mass spectra in positive and negative ion modes were acquired from the accumulation of 200 scans per spectrum, and duplicate acquisitions per sample were carried out to ensure data reproducibility. Raw mass spectrometry data were processed as described elsewhere (Han et al. 2008. Metabolomics. 4:128-140). To identify differences in metabolite composition between untreated and treated samples, we first filtered our list of masses for metabolites that were present on one set of samples (untreated or treated) but not the other. Additionally, we averaged the mass intensities of metabolites in each group and calculated the ratios between averaged intensities of metabolites from untreated and treated samples. To assign possible metabolite identities to the masses present in only one of the sample groups or showing at least a 2-fold change in intensities between the sample groups, the monoisotopic neutral masses of interest were queried against MassTrix (http://masstrix.org), a free-access software designed to incorporate masses into metabolic pathways. Masses were searched against the Mus musculus database within a mass error of 3 ppm. Data were analyzed by unpaired t tests with 95% confidence intervals.

Dataset Information

Metabolomics analysis highlights Yashtimadhu (Glycyrrhiza glabra L.) mediated neuroprotection in a rotenone-induced cellular model of Parkinsons disease

Publications

Metabolomics analysis highlights Yashtimadhu (Glycyrrhiza glabra L.)-mediated neuroprotection in a rotenone-induced cellular model of Parkinson's disease by restoring the mTORC1-AMPK1 axis in autophagic regulation.

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