Integrated 16S rRNA Gene Sequencing and LC-MS Analysis Revealed the Interplay Between Gut Microbiota and Plasma Metabolites in Rats With Ischemic Stroke
Abstract Gut microbiome and plasma metabolome serve a role in the pathogenesis of ischemic stroke (IS). However, the relationship between the microbiota and metabolites remains unclear. This study aimed to reveal the specific asso-ciation between the microbiota and the metabolites in IS using integr...
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| Autor*in: |
Wu, Wanfeng [verfasserIn] Sun, Yihang [verfasserIn] Luo, Ning [verfasserIn] Cheng, Cheng [verfasserIn] Jiang, Chengting [verfasserIn] Yu, Qingping [verfasserIn] Cheng, Shaowu [verfasserIn] Ge, Jinwen [verfasserIn] |
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| Format: |
E-Artikel |
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| Sprache: |
Englisch |
| Erschienen: |
2021 |
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© The Author(s), under exclusive licence to Springer Science+Business Media, LLC, part of Springer Nature 2021 |
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| Übergeordnetes Werk: |
Enthalten in: Journal of molecular neuroscience - New York, NY : Springer, 1998, 71(2021), 10 vom: 06. Mai, Seite 2095-2106 |
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| Übergeordnetes Werk: |
volume:71 ; year:2021 ; number:10 ; day:06 ; month:05 ; pages:2095-2106 |
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| DOI / URN: |
10.1007/s12031-021-01828-4 |
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SPR045250901 |
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| 520 | |a Abstract Gut microbiome and plasma metabolome serve a role in the pathogenesis of ischemic stroke (IS). However, the relationship between the microbiota and metabolites remains unclear. This study aimed to reveal the specific asso-ciation between the microbiota and the metabolites in IS using integrated 16S rRNA gene sequencing and liquid chromatography-mass spectrometry (LC-MS) analysis. Male Sprague Dawley (SD) rats were divided into three groups: normal group (n = 8, Normal), model group (n = 9, IS), and sham-operated group (n = 8, Sham). Rats in the IS group were induced by middle cerebral artery occlusion (MCAO), and rats in the Sham group received an initial anesthesia and neck incision only. A neurological function test and 2,3,5-triphenyltetrazolium chloride (TTC) staining were used to assess the IS rat model. Then, the plasma samples were analyzed using untargeted LC-MS. The cecum samples were collected and analyzed using 16S rRNA sequencing. Pearson correlation analysis was performed to explore the association between the gut microbiota and the plasma metabolites. The 16S rRNA sequencing showed that the composition and diversity of the microbiota in the IS and control rats were significantly different. Compared with the Sham group, the abundance of the Firmicutes phylum was decreased, whereas Proteobacteria and Deferribacteres were increased in the IS group. Ruminococcus_sp_15975 and Lachnospiraceae_UCG_001 might be considered as biomarkers for the IS and Sham groups, respectively. LC-MS analysis revealed that many metabolites, such as L-leucine, L-valine, and L-phenylalanine, displayed different patterns between the IS and Sham groups. Pathway analysis indicated that these metabolites were mainly involved in mineral absorption and cholinergic synapse. Furthermore, integrated analysis correlated IS-related microbes with metabolites. For example, Proteobacteria were positively correlated with L-phenylalanine, while they were negatively correlated with eicosapentaenoic acid (EPA). Our results provided evidence of the relationship between the gut microbiome and plasma metabolome in IS, suggesting that these microflora-related metabolites might serve as potential diagnostic and therapeutic markers. | ||
| 650 | 4 | |a Ischemic stroke |7 (dpeaa)DE-He213 | |
| 650 | 4 | |a Gut microbiota |7 (dpeaa)DE-He213 | |
| 650 | 4 | |a Plasma metabolomics |7 (dpeaa)DE-He213 | |
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| 700 | 1 | |a Cheng, Shaowu |e verfasserin |4 aut | |
| 700 | 1 | |a Ge, Jinwen |e verfasserin |4 aut | |
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10.1007/s12031-021-01828-4 doi (DE-627)SPR045250901 (SPR)s12031-021-01828-4-e DE-627 ger DE-627 rakwb eng 610 ASE 44.90 bkl Wu, Wanfeng verfasserin aut Integrated 16S rRNA Gene Sequencing and LC-MS Analysis Revealed the Interplay Between Gut Microbiota and Plasma Metabolites in Rats With Ischemic Stroke 2021 Text txt rdacontent Computermedien c rdamedia Online-Ressource cr rdacarrier © The Author(s), under exclusive licence to Springer Science+Business Media, LLC, part of Springer Nature 2021 Abstract Gut microbiome and plasma metabolome serve a role in the pathogenesis of ischemic stroke (IS). However, the relationship between the microbiota and metabolites remains unclear. This study aimed to reveal the specific asso-ciation between the microbiota and the metabolites in IS using integrated 16S rRNA gene sequencing and liquid chromatography-mass spectrometry (LC-MS) analysis. Male Sprague Dawley (SD) rats were divided into three groups: normal group (n = 8, Normal), model group (n = 9, IS), and sham-operated group (n = 8, Sham). Rats in the IS group were induced by middle cerebral artery occlusion (MCAO), and rats in the Sham group received an initial anesthesia and neck incision only. A neurological function test and 2,3,5-triphenyltetrazolium chloride (TTC) staining were used to assess the IS rat model. Then, the plasma samples were analyzed using untargeted LC-MS. The cecum samples were collected and analyzed using 16S rRNA sequencing. Pearson correlation analysis was performed to explore the association between the gut microbiota and the plasma metabolites. The 16S rRNA sequencing showed that the composition and diversity of the microbiota in the IS and control rats were significantly different. Compared with the Sham group, the abundance of the Firmicutes phylum was decreased, whereas Proteobacteria and Deferribacteres were increased in the IS group. Ruminococcus_sp_15975 and Lachnospiraceae_UCG_001 might be considered as biomarkers for the IS and Sham groups, respectively. LC-MS analysis revealed that many metabolites, such as L-leucine, L-valine, and L-phenylalanine, displayed different patterns between the IS and Sham groups. Pathway analysis indicated that these metabolites were mainly involved in mineral absorption and cholinergic synapse. Furthermore, integrated analysis correlated IS-related microbes with metabolites. For example, Proteobacteria were positively correlated with L-phenylalanine, while they were negatively correlated with eicosapentaenoic acid (EPA). Our results provided evidence of the relationship between the gut microbiome and plasma metabolome in IS, suggesting that these microflora-related metabolites might serve as potential diagnostic and therapeutic markers. Ischemic stroke (dpeaa)DE-He213 Gut microbiota (dpeaa)DE-He213 Plasma metabolomics (dpeaa)DE-He213 16S rRNA sequencing (dpeaa)DE-He213 LC-MS analysis (dpeaa)DE-He213 Sun, Yihang verfasserin aut Luo, Ning verfasserin aut Cheng, Cheng verfasserin aut Jiang, Chengting verfasserin aut Yu, Qingping verfasserin aut Cheng, Shaowu verfasserin aut Ge, Jinwen verfasserin aut Enthalten in Journal of molecular neuroscience New York, NY : Springer, 1998 71(2021), 10 vom: 06. Mai, Seite 2095-2106 (DE-627)342319477 (DE-600)2071508-0 1559-1166 nnns volume:71 year:2021 number:10 day:06 month:05 pages:2095-2106 https://dx.doi.org/10.1007/s12031-021-01828-4 lizenzpflichtig Volltext GBV_USEFLAG_A SYSFLAG_A GBV_SPRINGER SSG-OLC-PHA GBV_ILN_11 GBV_ILN_20 GBV_ILN_22 GBV_ILN_23 GBV_ILN_24 GBV_ILN_31 GBV_ILN_32 GBV_ILN_39 GBV_ILN_40 GBV_ILN_60 GBV_ILN_62 GBV_ILN_63 GBV_ILN_65 GBV_ILN_69 GBV_ILN_70 GBV_ILN_73 GBV_ILN_74 GBV_ILN_90 GBV_ILN_95 GBV_ILN_100 GBV_ILN_101 GBV_ILN_105 GBV_ILN_110 GBV_ILN_120 GBV_ILN_138 GBV_ILN_150 GBV_ILN_151 GBV_ILN_152 GBV_ILN_161 GBV_ILN_170 GBV_ILN_171 GBV_ILN_187 GBV_ILN_213 GBV_ILN_224 GBV_ILN_230 GBV_ILN_250 GBV_ILN_281 GBV_ILN_285 GBV_ILN_293 GBV_ILN_370 GBV_ILN_602 GBV_ILN_636 GBV_ILN_702 GBV_ILN_2001 GBV_ILN_2003 GBV_ILN_2004 GBV_ILN_2005 GBV_ILN_2006 GBV_ILN_2007 GBV_ILN_2008 GBV_ILN_2009 GBV_ILN_2010 GBV_ILN_2011 GBV_ILN_2014 GBV_ILN_2015 GBV_ILN_2020 GBV_ILN_2021 GBV_ILN_2025 GBV_ILN_2026 GBV_ILN_2027 GBV_ILN_2031 GBV_ILN_2034 GBV_ILN_2037 GBV_ILN_2038 GBV_ILN_2039 GBV_ILN_2044 GBV_ILN_2048 GBV_ILN_2049 GBV_ILN_2050 GBV_ILN_2055 GBV_ILN_2056 GBV_ILN_2057 GBV_ILN_2059 GBV_ILN_2061 GBV_ILN_2064 GBV_ILN_2065 GBV_ILN_2068 GBV_ILN_2088 GBV_ILN_2093 GBV_ILN_2106 GBV_ILN_2107 GBV_ILN_2108 GBV_ILN_2110 GBV_ILN_2111 GBV_ILN_2112 GBV_ILN_2113 GBV_ILN_2118 GBV_ILN_2122 GBV_ILN_2129 GBV_ILN_2143 GBV_ILN_2144 GBV_ILN_2147 GBV_ILN_2148 GBV_ILN_2152 GBV_ILN_2153 GBV_ILN_2188 GBV_ILN_2190 GBV_ILN_2232 GBV_ILN_2336 GBV_ILN_2446 GBV_ILN_2470 GBV_ILN_2472 GBV_ILN_2507 GBV_ILN_2522 GBV_ILN_2548 GBV_ILN_4035 GBV_ILN_4037 GBV_ILN_4046 GBV_ILN_4112 GBV_ILN_4125 GBV_ILN_4126 GBV_ILN_4242 GBV_ILN_4246 GBV_ILN_4249 GBV_ILN_4251 GBV_ILN_4305 GBV_ILN_4306 GBV_ILN_4307 GBV_ILN_4313 GBV_ILN_4322 GBV_ILN_4323 GBV_ILN_4324 GBV_ILN_4325 GBV_ILN_4326 GBV_ILN_4328 GBV_ILN_4333 GBV_ILN_4334 GBV_ILN_4335 GBV_ILN_4336 GBV_ILN_4338 GBV_ILN_4393 GBV_ILN_4700 44.90 ASE AR 71 2021 10 06 05 2095-2106 |
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10.1007/s12031-021-01828-4 doi (DE-627)SPR045250901 (SPR)s12031-021-01828-4-e DE-627 ger DE-627 rakwb eng 610 ASE 44.90 bkl Wu, Wanfeng verfasserin aut Integrated 16S rRNA Gene Sequencing and LC-MS Analysis Revealed the Interplay Between Gut Microbiota and Plasma Metabolites in Rats With Ischemic Stroke 2021 Text txt rdacontent Computermedien c rdamedia Online-Ressource cr rdacarrier © The Author(s), under exclusive licence to Springer Science+Business Media, LLC, part of Springer Nature 2021 Abstract Gut microbiome and plasma metabolome serve a role in the pathogenesis of ischemic stroke (IS). However, the relationship between the microbiota and metabolites remains unclear. This study aimed to reveal the specific asso-ciation between the microbiota and the metabolites in IS using integrated 16S rRNA gene sequencing and liquid chromatography-mass spectrometry (LC-MS) analysis. Male Sprague Dawley (SD) rats were divided into three groups: normal group (n = 8, Normal), model group (n = 9, IS), and sham-operated group (n = 8, Sham). Rats in the IS group were induced by middle cerebral artery occlusion (MCAO), and rats in the Sham group received an initial anesthesia and neck incision only. A neurological function test and 2,3,5-triphenyltetrazolium chloride (TTC) staining were used to assess the IS rat model. Then, the plasma samples were analyzed using untargeted LC-MS. The cecum samples were collected and analyzed using 16S rRNA sequencing. Pearson correlation analysis was performed to explore the association between the gut microbiota and the plasma metabolites. The 16S rRNA sequencing showed that the composition and diversity of the microbiota in the IS and control rats were significantly different. Compared with the Sham group, the abundance of the Firmicutes phylum was decreased, whereas Proteobacteria and Deferribacteres were increased in the IS group. Ruminococcus_sp_15975 and Lachnospiraceae_UCG_001 might be considered as biomarkers for the IS and Sham groups, respectively. LC-MS analysis revealed that many metabolites, such as L-leucine, L-valine, and L-phenylalanine, displayed different patterns between the IS and Sham groups. Pathway analysis indicated that these metabolites were mainly involved in mineral absorption and cholinergic synapse. Furthermore, integrated analysis correlated IS-related microbes with metabolites. For example, Proteobacteria were positively correlated with L-phenylalanine, while they were negatively correlated with eicosapentaenoic acid (EPA). Our results provided evidence of the relationship between the gut microbiome and plasma metabolome in IS, suggesting that these microflora-related metabolites might serve as potential diagnostic and therapeutic markers. Ischemic stroke (dpeaa)DE-He213 Gut microbiota (dpeaa)DE-He213 Plasma metabolomics (dpeaa)DE-He213 16S rRNA sequencing (dpeaa)DE-He213 LC-MS analysis (dpeaa)DE-He213 Sun, Yihang verfasserin aut Luo, Ning verfasserin aut Cheng, Cheng verfasserin aut Jiang, Chengting verfasserin aut Yu, Qingping verfasserin aut Cheng, Shaowu verfasserin aut Ge, Jinwen verfasserin aut Enthalten in Journal of molecular neuroscience New York, NY : Springer, 1998 71(2021), 10 vom: 06. Mai, Seite 2095-2106 (DE-627)342319477 (DE-600)2071508-0 1559-1166 nnns volume:71 year:2021 number:10 day:06 month:05 pages:2095-2106 https://dx.doi.org/10.1007/s12031-021-01828-4 lizenzpflichtig Volltext GBV_USEFLAG_A SYSFLAG_A GBV_SPRINGER SSG-OLC-PHA GBV_ILN_11 GBV_ILN_20 GBV_ILN_22 GBV_ILN_23 GBV_ILN_24 GBV_ILN_31 GBV_ILN_32 GBV_ILN_39 GBV_ILN_40 GBV_ILN_60 GBV_ILN_62 GBV_ILN_63 GBV_ILN_65 GBV_ILN_69 GBV_ILN_70 GBV_ILN_73 GBV_ILN_74 GBV_ILN_90 GBV_ILN_95 GBV_ILN_100 GBV_ILN_101 GBV_ILN_105 GBV_ILN_110 GBV_ILN_120 GBV_ILN_138 GBV_ILN_150 GBV_ILN_151 GBV_ILN_152 GBV_ILN_161 GBV_ILN_170 GBV_ILN_171 GBV_ILN_187 GBV_ILN_213 GBV_ILN_224 GBV_ILN_230 GBV_ILN_250 GBV_ILN_281 GBV_ILN_285 GBV_ILN_293 GBV_ILN_370 GBV_ILN_602 GBV_ILN_636 GBV_ILN_702 GBV_ILN_2001 GBV_ILN_2003 GBV_ILN_2004 GBV_ILN_2005 GBV_ILN_2006 GBV_ILN_2007 GBV_ILN_2008 GBV_ILN_2009 GBV_ILN_2010 GBV_ILN_2011 GBV_ILN_2014 GBV_ILN_2015 GBV_ILN_2020 GBV_ILN_2021 GBV_ILN_2025 GBV_ILN_2026 GBV_ILN_2027 GBV_ILN_2031 GBV_ILN_2034 GBV_ILN_2037 GBV_ILN_2038 GBV_ILN_2039 GBV_ILN_2044 GBV_ILN_2048 GBV_ILN_2049 GBV_ILN_2050 GBV_ILN_2055 GBV_ILN_2056 GBV_ILN_2057 GBV_ILN_2059 GBV_ILN_2061 GBV_ILN_2064 GBV_ILN_2065 GBV_ILN_2068 GBV_ILN_2088 GBV_ILN_2093 GBV_ILN_2106 GBV_ILN_2107 GBV_ILN_2108 GBV_ILN_2110 GBV_ILN_2111 GBV_ILN_2112 GBV_ILN_2113 GBV_ILN_2118 GBV_ILN_2122 GBV_ILN_2129 GBV_ILN_2143 GBV_ILN_2144 GBV_ILN_2147 GBV_ILN_2148 GBV_ILN_2152 GBV_ILN_2153 GBV_ILN_2188 GBV_ILN_2190 GBV_ILN_2232 GBV_ILN_2336 GBV_ILN_2446 GBV_ILN_2470 GBV_ILN_2472 GBV_ILN_2507 GBV_ILN_2522 GBV_ILN_2548 GBV_ILN_4035 GBV_ILN_4037 GBV_ILN_4046 GBV_ILN_4112 GBV_ILN_4125 GBV_ILN_4126 GBV_ILN_4242 GBV_ILN_4246 GBV_ILN_4249 GBV_ILN_4251 GBV_ILN_4305 GBV_ILN_4306 GBV_ILN_4307 GBV_ILN_4313 GBV_ILN_4322 GBV_ILN_4323 GBV_ILN_4324 GBV_ILN_4325 GBV_ILN_4326 GBV_ILN_4328 GBV_ILN_4333 GBV_ILN_4334 GBV_ILN_4335 GBV_ILN_4336 GBV_ILN_4338 GBV_ILN_4393 GBV_ILN_4700 44.90 ASE AR 71 2021 10 06 05 2095-2106 |
| allfields_unstemmed |
10.1007/s12031-021-01828-4 doi (DE-627)SPR045250901 (SPR)s12031-021-01828-4-e DE-627 ger DE-627 rakwb eng 610 ASE 44.90 bkl Wu, Wanfeng verfasserin aut Integrated 16S rRNA Gene Sequencing and LC-MS Analysis Revealed the Interplay Between Gut Microbiota and Plasma Metabolites in Rats With Ischemic Stroke 2021 Text txt rdacontent Computermedien c rdamedia Online-Ressource cr rdacarrier © The Author(s), under exclusive licence to Springer Science+Business Media, LLC, part of Springer Nature 2021 Abstract Gut microbiome and plasma metabolome serve a role in the pathogenesis of ischemic stroke (IS). However, the relationship between the microbiota and metabolites remains unclear. This study aimed to reveal the specific asso-ciation between the microbiota and the metabolites in IS using integrated 16S rRNA gene sequencing and liquid chromatography-mass spectrometry (LC-MS) analysis. Male Sprague Dawley (SD) rats were divided into three groups: normal group (n = 8, Normal), model group (n = 9, IS), and sham-operated group (n = 8, Sham). Rats in the IS group were induced by middle cerebral artery occlusion (MCAO), and rats in the Sham group received an initial anesthesia and neck incision only. A neurological function test and 2,3,5-triphenyltetrazolium chloride (TTC) staining were used to assess the IS rat model. Then, the plasma samples were analyzed using untargeted LC-MS. The cecum samples were collected and analyzed using 16S rRNA sequencing. Pearson correlation analysis was performed to explore the association between the gut microbiota and the plasma metabolites. The 16S rRNA sequencing showed that the composition and diversity of the microbiota in the IS and control rats were significantly different. Compared with the Sham group, the abundance of the Firmicutes phylum was decreased, whereas Proteobacteria and Deferribacteres were increased in the IS group. Ruminococcus_sp_15975 and Lachnospiraceae_UCG_001 might be considered as biomarkers for the IS and Sham groups, respectively. LC-MS analysis revealed that many metabolites, such as L-leucine, L-valine, and L-phenylalanine, displayed different patterns between the IS and Sham groups. Pathway analysis indicated that these metabolites were mainly involved in mineral absorption and cholinergic synapse. Furthermore, integrated analysis correlated IS-related microbes with metabolites. For example, Proteobacteria were positively correlated with L-phenylalanine, while they were negatively correlated with eicosapentaenoic acid (EPA). Our results provided evidence of the relationship between the gut microbiome and plasma metabolome in IS, suggesting that these microflora-related metabolites might serve as potential diagnostic and therapeutic markers. Ischemic stroke (dpeaa)DE-He213 Gut microbiota (dpeaa)DE-He213 Plasma metabolomics (dpeaa)DE-He213 16S rRNA sequencing (dpeaa)DE-He213 LC-MS analysis (dpeaa)DE-He213 Sun, Yihang verfasserin aut Luo, Ning verfasserin aut Cheng, Cheng verfasserin aut Jiang, Chengting verfasserin aut Yu, Qingping verfasserin aut Cheng, Shaowu verfasserin aut Ge, Jinwen verfasserin aut Enthalten in Journal of molecular neuroscience New York, NY : Springer, 1998 71(2021), 10 vom: 06. Mai, Seite 2095-2106 (DE-627)342319477 (DE-600)2071508-0 1559-1166 nnns volume:71 year:2021 number:10 day:06 month:05 pages:2095-2106 https://dx.doi.org/10.1007/s12031-021-01828-4 lizenzpflichtig Volltext GBV_USEFLAG_A SYSFLAG_A GBV_SPRINGER SSG-OLC-PHA GBV_ILN_11 GBV_ILN_20 GBV_ILN_22 GBV_ILN_23 GBV_ILN_24 GBV_ILN_31 GBV_ILN_32 GBV_ILN_39 GBV_ILN_40 GBV_ILN_60 GBV_ILN_62 GBV_ILN_63 GBV_ILN_65 GBV_ILN_69 GBV_ILN_70 GBV_ILN_73 GBV_ILN_74 GBV_ILN_90 GBV_ILN_95 GBV_ILN_100 GBV_ILN_101 GBV_ILN_105 GBV_ILN_110 GBV_ILN_120 GBV_ILN_138 GBV_ILN_150 GBV_ILN_151 GBV_ILN_152 GBV_ILN_161 GBV_ILN_170 GBV_ILN_171 GBV_ILN_187 GBV_ILN_213 GBV_ILN_224 GBV_ILN_230 GBV_ILN_250 GBV_ILN_281 GBV_ILN_285 GBV_ILN_293 GBV_ILN_370 GBV_ILN_602 GBV_ILN_636 GBV_ILN_702 GBV_ILN_2001 GBV_ILN_2003 GBV_ILN_2004 GBV_ILN_2005 GBV_ILN_2006 GBV_ILN_2007 GBV_ILN_2008 GBV_ILN_2009 GBV_ILN_2010 GBV_ILN_2011 GBV_ILN_2014 GBV_ILN_2015 GBV_ILN_2020 GBV_ILN_2021 GBV_ILN_2025 GBV_ILN_2026 GBV_ILN_2027 GBV_ILN_2031 GBV_ILN_2034 GBV_ILN_2037 GBV_ILN_2038 GBV_ILN_2039 GBV_ILN_2044 GBV_ILN_2048 GBV_ILN_2049 GBV_ILN_2050 GBV_ILN_2055 GBV_ILN_2056 GBV_ILN_2057 GBV_ILN_2059 GBV_ILN_2061 GBV_ILN_2064 GBV_ILN_2065 GBV_ILN_2068 GBV_ILN_2088 GBV_ILN_2093 GBV_ILN_2106 GBV_ILN_2107 GBV_ILN_2108 GBV_ILN_2110 GBV_ILN_2111 GBV_ILN_2112 GBV_ILN_2113 GBV_ILN_2118 GBV_ILN_2122 GBV_ILN_2129 GBV_ILN_2143 GBV_ILN_2144 GBV_ILN_2147 GBV_ILN_2148 GBV_ILN_2152 GBV_ILN_2153 GBV_ILN_2188 GBV_ILN_2190 GBV_ILN_2232 GBV_ILN_2336 GBV_ILN_2446 GBV_ILN_2470 GBV_ILN_2472 GBV_ILN_2507 GBV_ILN_2522 GBV_ILN_2548 GBV_ILN_4035 GBV_ILN_4037 GBV_ILN_4046 GBV_ILN_4112 GBV_ILN_4125 GBV_ILN_4126 GBV_ILN_4242 GBV_ILN_4246 GBV_ILN_4249 GBV_ILN_4251 GBV_ILN_4305 GBV_ILN_4306 GBV_ILN_4307 GBV_ILN_4313 GBV_ILN_4322 GBV_ILN_4323 GBV_ILN_4324 GBV_ILN_4325 GBV_ILN_4326 GBV_ILN_4328 GBV_ILN_4333 GBV_ILN_4334 GBV_ILN_4335 GBV_ILN_4336 GBV_ILN_4338 GBV_ILN_4393 GBV_ILN_4700 44.90 ASE AR 71 2021 10 06 05 2095-2106 |
| allfieldsGer |
10.1007/s12031-021-01828-4 doi (DE-627)SPR045250901 (SPR)s12031-021-01828-4-e DE-627 ger DE-627 rakwb eng 610 ASE 44.90 bkl Wu, Wanfeng verfasserin aut Integrated 16S rRNA Gene Sequencing and LC-MS Analysis Revealed the Interplay Between Gut Microbiota and Plasma Metabolites in Rats With Ischemic Stroke 2021 Text txt rdacontent Computermedien c rdamedia Online-Ressource cr rdacarrier © The Author(s), under exclusive licence to Springer Science+Business Media, LLC, part of Springer Nature 2021 Abstract Gut microbiome and plasma metabolome serve a role in the pathogenesis of ischemic stroke (IS). However, the relationship between the microbiota and metabolites remains unclear. This study aimed to reveal the specific asso-ciation between the microbiota and the metabolites in IS using integrated 16S rRNA gene sequencing and liquid chromatography-mass spectrometry (LC-MS) analysis. Male Sprague Dawley (SD) rats were divided into three groups: normal group (n = 8, Normal), model group (n = 9, IS), and sham-operated group (n = 8, Sham). Rats in the IS group were induced by middle cerebral artery occlusion (MCAO), and rats in the Sham group received an initial anesthesia and neck incision only. A neurological function test and 2,3,5-triphenyltetrazolium chloride (TTC) staining were used to assess the IS rat model. Then, the plasma samples were analyzed using untargeted LC-MS. The cecum samples were collected and analyzed using 16S rRNA sequencing. Pearson correlation analysis was performed to explore the association between the gut microbiota and the plasma metabolites. The 16S rRNA sequencing showed that the composition and diversity of the microbiota in the IS and control rats were significantly different. Compared with the Sham group, the abundance of the Firmicutes phylum was decreased, whereas Proteobacteria and Deferribacteres were increased in the IS group. Ruminococcus_sp_15975 and Lachnospiraceae_UCG_001 might be considered as biomarkers for the IS and Sham groups, respectively. LC-MS analysis revealed that many metabolites, such as L-leucine, L-valine, and L-phenylalanine, displayed different patterns between the IS and Sham groups. Pathway analysis indicated that these metabolites were mainly involved in mineral absorption and cholinergic synapse. Furthermore, integrated analysis correlated IS-related microbes with metabolites. For example, Proteobacteria were positively correlated with L-phenylalanine, while they were negatively correlated with eicosapentaenoic acid (EPA). Our results provided evidence of the relationship between the gut microbiome and plasma metabolome in IS, suggesting that these microflora-related metabolites might serve as potential diagnostic and therapeutic markers. Ischemic stroke (dpeaa)DE-He213 Gut microbiota (dpeaa)DE-He213 Plasma metabolomics (dpeaa)DE-He213 16S rRNA sequencing (dpeaa)DE-He213 LC-MS analysis (dpeaa)DE-He213 Sun, Yihang verfasserin aut Luo, Ning verfasserin aut Cheng, Cheng verfasserin aut Jiang, Chengting verfasserin aut Yu, Qingping verfasserin aut Cheng, Shaowu verfasserin aut Ge, Jinwen verfasserin aut Enthalten in Journal of molecular neuroscience New York, NY : Springer, 1998 71(2021), 10 vom: 06. Mai, Seite 2095-2106 (DE-627)342319477 (DE-600)2071508-0 1559-1166 nnns volume:71 year:2021 number:10 day:06 month:05 pages:2095-2106 https://dx.doi.org/10.1007/s12031-021-01828-4 lizenzpflichtig Volltext GBV_USEFLAG_A SYSFLAG_A GBV_SPRINGER SSG-OLC-PHA GBV_ILN_11 GBV_ILN_20 GBV_ILN_22 GBV_ILN_23 GBV_ILN_24 GBV_ILN_31 GBV_ILN_32 GBV_ILN_39 GBV_ILN_40 GBV_ILN_60 GBV_ILN_62 GBV_ILN_63 GBV_ILN_65 GBV_ILN_69 GBV_ILN_70 GBV_ILN_73 GBV_ILN_74 GBV_ILN_90 GBV_ILN_95 GBV_ILN_100 GBV_ILN_101 GBV_ILN_105 GBV_ILN_110 GBV_ILN_120 GBV_ILN_138 GBV_ILN_150 GBV_ILN_151 GBV_ILN_152 GBV_ILN_161 GBV_ILN_170 GBV_ILN_171 GBV_ILN_187 GBV_ILN_213 GBV_ILN_224 GBV_ILN_230 GBV_ILN_250 GBV_ILN_281 GBV_ILN_285 GBV_ILN_293 GBV_ILN_370 GBV_ILN_602 GBV_ILN_636 GBV_ILN_702 GBV_ILN_2001 GBV_ILN_2003 GBV_ILN_2004 GBV_ILN_2005 GBV_ILN_2006 GBV_ILN_2007 GBV_ILN_2008 GBV_ILN_2009 GBV_ILN_2010 GBV_ILN_2011 GBV_ILN_2014 GBV_ILN_2015 GBV_ILN_2020 GBV_ILN_2021 GBV_ILN_2025 GBV_ILN_2026 GBV_ILN_2027 GBV_ILN_2031 GBV_ILN_2034 GBV_ILN_2037 GBV_ILN_2038 GBV_ILN_2039 GBV_ILN_2044 GBV_ILN_2048 GBV_ILN_2049 GBV_ILN_2050 GBV_ILN_2055 GBV_ILN_2056 GBV_ILN_2057 GBV_ILN_2059 GBV_ILN_2061 GBV_ILN_2064 GBV_ILN_2065 GBV_ILN_2068 GBV_ILN_2088 GBV_ILN_2093 GBV_ILN_2106 GBV_ILN_2107 GBV_ILN_2108 GBV_ILN_2110 GBV_ILN_2111 GBV_ILN_2112 GBV_ILN_2113 GBV_ILN_2118 GBV_ILN_2122 GBV_ILN_2129 GBV_ILN_2143 GBV_ILN_2144 GBV_ILN_2147 GBV_ILN_2148 GBV_ILN_2152 GBV_ILN_2153 GBV_ILN_2188 GBV_ILN_2190 GBV_ILN_2232 GBV_ILN_2336 GBV_ILN_2446 GBV_ILN_2470 GBV_ILN_2472 GBV_ILN_2507 GBV_ILN_2522 GBV_ILN_2548 GBV_ILN_4035 GBV_ILN_4037 GBV_ILN_4046 GBV_ILN_4112 GBV_ILN_4125 GBV_ILN_4126 GBV_ILN_4242 GBV_ILN_4246 GBV_ILN_4249 GBV_ILN_4251 GBV_ILN_4305 GBV_ILN_4306 GBV_ILN_4307 GBV_ILN_4313 GBV_ILN_4322 GBV_ILN_4323 GBV_ILN_4324 GBV_ILN_4325 GBV_ILN_4326 GBV_ILN_4328 GBV_ILN_4333 GBV_ILN_4334 GBV_ILN_4335 GBV_ILN_4336 GBV_ILN_4338 GBV_ILN_4393 GBV_ILN_4700 44.90 ASE AR 71 2021 10 06 05 2095-2106 |
| allfieldsSound |
10.1007/s12031-021-01828-4 doi (DE-627)SPR045250901 (SPR)s12031-021-01828-4-e DE-627 ger DE-627 rakwb eng 610 ASE 44.90 bkl Wu, Wanfeng verfasserin aut Integrated 16S rRNA Gene Sequencing and LC-MS Analysis Revealed the Interplay Between Gut Microbiota and Plasma Metabolites in Rats With Ischemic Stroke 2021 Text txt rdacontent Computermedien c rdamedia Online-Ressource cr rdacarrier © The Author(s), under exclusive licence to Springer Science+Business Media, LLC, part of Springer Nature 2021 Abstract Gut microbiome and plasma metabolome serve a role in the pathogenesis of ischemic stroke (IS). However, the relationship between the microbiota and metabolites remains unclear. This study aimed to reveal the specific asso-ciation between the microbiota and the metabolites in IS using integrated 16S rRNA gene sequencing and liquid chromatography-mass spectrometry (LC-MS) analysis. Male Sprague Dawley (SD) rats were divided into three groups: normal group (n = 8, Normal), model group (n = 9, IS), and sham-operated group (n = 8, Sham). Rats in the IS group were induced by middle cerebral artery occlusion (MCAO), and rats in the Sham group received an initial anesthesia and neck incision only. A neurological function test and 2,3,5-triphenyltetrazolium chloride (TTC) staining were used to assess the IS rat model. Then, the plasma samples were analyzed using untargeted LC-MS. The cecum samples were collected and analyzed using 16S rRNA sequencing. Pearson correlation analysis was performed to explore the association between the gut microbiota and the plasma metabolites. The 16S rRNA sequencing showed that the composition and diversity of the microbiota in the IS and control rats were significantly different. Compared with the Sham group, the abundance of the Firmicutes phylum was decreased, whereas Proteobacteria and Deferribacteres were increased in the IS group. Ruminococcus_sp_15975 and Lachnospiraceae_UCG_001 might be considered as biomarkers for the IS and Sham groups, respectively. LC-MS analysis revealed that many metabolites, such as L-leucine, L-valine, and L-phenylalanine, displayed different patterns between the IS and Sham groups. Pathway analysis indicated that these metabolites were mainly involved in mineral absorption and cholinergic synapse. Furthermore, integrated analysis correlated IS-related microbes with metabolites. For example, Proteobacteria were positively correlated with L-phenylalanine, while they were negatively correlated with eicosapentaenoic acid (EPA). Our results provided evidence of the relationship between the gut microbiome and plasma metabolome in IS, suggesting that these microflora-related metabolites might serve as potential diagnostic and therapeutic markers. Ischemic stroke (dpeaa)DE-He213 Gut microbiota (dpeaa)DE-He213 Plasma metabolomics (dpeaa)DE-He213 16S rRNA sequencing (dpeaa)DE-He213 LC-MS analysis (dpeaa)DE-He213 Sun, Yihang verfasserin aut Luo, Ning verfasserin aut Cheng, Cheng verfasserin aut Jiang, Chengting verfasserin aut Yu, Qingping verfasserin aut Cheng, Shaowu verfasserin aut Ge, Jinwen verfasserin aut Enthalten in Journal of molecular neuroscience New York, NY : Springer, 1998 71(2021), 10 vom: 06. Mai, Seite 2095-2106 (DE-627)342319477 (DE-600)2071508-0 1559-1166 nnns volume:71 year:2021 number:10 day:06 month:05 pages:2095-2106 https://dx.doi.org/10.1007/s12031-021-01828-4 lizenzpflichtig Volltext GBV_USEFLAG_A SYSFLAG_A GBV_SPRINGER SSG-OLC-PHA GBV_ILN_11 GBV_ILN_20 GBV_ILN_22 GBV_ILN_23 GBV_ILN_24 GBV_ILN_31 GBV_ILN_32 GBV_ILN_39 GBV_ILN_40 GBV_ILN_60 GBV_ILN_62 GBV_ILN_63 GBV_ILN_65 GBV_ILN_69 GBV_ILN_70 GBV_ILN_73 GBV_ILN_74 GBV_ILN_90 GBV_ILN_95 GBV_ILN_100 GBV_ILN_101 GBV_ILN_105 GBV_ILN_110 GBV_ILN_120 GBV_ILN_138 GBV_ILN_150 GBV_ILN_151 GBV_ILN_152 GBV_ILN_161 GBV_ILN_170 GBV_ILN_171 GBV_ILN_187 GBV_ILN_213 GBV_ILN_224 GBV_ILN_230 GBV_ILN_250 GBV_ILN_281 GBV_ILN_285 GBV_ILN_293 GBV_ILN_370 GBV_ILN_602 GBV_ILN_636 GBV_ILN_702 GBV_ILN_2001 GBV_ILN_2003 GBV_ILN_2004 GBV_ILN_2005 GBV_ILN_2006 GBV_ILN_2007 GBV_ILN_2008 GBV_ILN_2009 GBV_ILN_2010 GBV_ILN_2011 GBV_ILN_2014 GBV_ILN_2015 GBV_ILN_2020 GBV_ILN_2021 GBV_ILN_2025 GBV_ILN_2026 GBV_ILN_2027 GBV_ILN_2031 GBV_ILN_2034 GBV_ILN_2037 GBV_ILN_2038 GBV_ILN_2039 GBV_ILN_2044 GBV_ILN_2048 GBV_ILN_2049 GBV_ILN_2050 GBV_ILN_2055 GBV_ILN_2056 GBV_ILN_2057 GBV_ILN_2059 GBV_ILN_2061 GBV_ILN_2064 GBV_ILN_2065 GBV_ILN_2068 GBV_ILN_2088 GBV_ILN_2093 GBV_ILN_2106 GBV_ILN_2107 GBV_ILN_2108 GBV_ILN_2110 GBV_ILN_2111 GBV_ILN_2112 GBV_ILN_2113 GBV_ILN_2118 GBV_ILN_2122 GBV_ILN_2129 GBV_ILN_2143 GBV_ILN_2144 GBV_ILN_2147 GBV_ILN_2148 GBV_ILN_2152 GBV_ILN_2153 GBV_ILN_2188 GBV_ILN_2190 GBV_ILN_2232 GBV_ILN_2336 GBV_ILN_2446 GBV_ILN_2470 GBV_ILN_2472 GBV_ILN_2507 GBV_ILN_2522 GBV_ILN_2548 GBV_ILN_4035 GBV_ILN_4037 GBV_ILN_4046 GBV_ILN_4112 GBV_ILN_4125 GBV_ILN_4126 GBV_ILN_4242 GBV_ILN_4246 GBV_ILN_4249 GBV_ILN_4251 GBV_ILN_4305 GBV_ILN_4306 GBV_ILN_4307 GBV_ILN_4313 GBV_ILN_4322 GBV_ILN_4323 GBV_ILN_4324 GBV_ILN_4325 GBV_ILN_4326 GBV_ILN_4328 GBV_ILN_4333 GBV_ILN_4334 GBV_ILN_4335 GBV_ILN_4336 GBV_ILN_4338 GBV_ILN_4393 GBV_ILN_4700 44.90 ASE AR 71 2021 10 06 05 2095-2106 |
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Enthalten in Journal of molecular neuroscience 71(2021), 10 vom: 06. Mai, Seite 2095-2106 volume:71 year:2021 number:10 day:06 month:05 pages:2095-2106 |
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However, the relationship between the microbiota and metabolites remains unclear. This study aimed to reveal the specific asso-ciation between the microbiota and the metabolites in IS using integrated 16S rRNA gene sequencing and liquid chromatography-mass spectrometry (LC-MS) analysis. Male Sprague Dawley (SD) rats were divided into three groups: normal group (n = 8, Normal), model group (n = 9, IS), and sham-operated group (n = 8, Sham). Rats in the IS group were induced by middle cerebral artery occlusion (MCAO), and rats in the Sham group received an initial anesthesia and neck incision only. A neurological function test and 2,3,5-triphenyltetrazolium chloride (TTC) staining were used to assess the IS rat model. Then, the plasma samples were analyzed using untargeted LC-MS. The cecum samples were collected and analyzed using 16S rRNA sequencing. Pearson correlation analysis was performed to explore the association between the gut microbiota and the plasma metabolites. The 16S rRNA sequencing showed that the composition and diversity of the microbiota in the IS and control rats were significantly different. Compared with the Sham group, the abundance of the Firmicutes phylum was decreased, whereas Proteobacteria and Deferribacteres were increased in the IS group. Ruminococcus_sp_15975 and Lachnospiraceae_UCG_001 might be considered as biomarkers for the IS and Sham groups, respectively. LC-MS analysis revealed that many metabolites, such as L-leucine, L-valine, and L-phenylalanine, displayed different patterns between the IS and Sham groups. Pathway analysis indicated that these metabolites were mainly involved in mineral absorption and cholinergic synapse. Furthermore, integrated analysis correlated IS-related microbes with metabolites. For example, Proteobacteria were positively correlated with L-phenylalanine, while they were negatively correlated with eicosapentaenoic acid (EPA). 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Wu, Wanfeng |
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Wu, Wanfeng ddc 610 bkl 44.90 misc Ischemic stroke misc Gut microbiota misc Plasma metabolomics misc 16S rRNA sequencing misc LC-MS analysis Integrated 16S rRNA Gene Sequencing and LC-MS Analysis Revealed the Interplay Between Gut Microbiota and Plasma Metabolites in Rats With Ischemic Stroke |
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610 ASE 44.90 bkl Integrated 16S rRNA Gene Sequencing and LC-MS Analysis Revealed the Interplay Between Gut Microbiota and Plasma Metabolites in Rats With Ischemic Stroke Ischemic stroke (dpeaa)DE-He213 Gut microbiota (dpeaa)DE-He213 Plasma metabolomics (dpeaa)DE-He213 16S rRNA sequencing (dpeaa)DE-He213 LC-MS analysis (dpeaa)DE-He213 |
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ddc 610 bkl 44.90 misc Ischemic stroke misc Gut microbiota misc Plasma metabolomics misc 16S rRNA sequencing misc LC-MS analysis |
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ddc 610 bkl 44.90 misc Ischemic stroke misc Gut microbiota misc Plasma metabolomics misc 16S rRNA sequencing misc LC-MS analysis |
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Integrated 16S rRNA Gene Sequencing and LC-MS Analysis Revealed the Interplay Between Gut Microbiota and Plasma Metabolites in Rats With Ischemic Stroke |
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Integrated 16S rRNA Gene Sequencing and LC-MS Analysis Revealed the Interplay Between Gut Microbiota and Plasma Metabolites in Rats With Ischemic Stroke |
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Wu, Wanfeng |
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Wu, Wanfeng Sun, Yihang Luo, Ning Cheng, Cheng Jiang, Chengting Yu, Qingping Cheng, Shaowu Ge, Jinwen |
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integrated 16s rrna gene sequencing and lc-ms analysis revealed the interplay between gut microbiota and plasma metabolites in rats with ischemic stroke |
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Integrated 16S rRNA Gene Sequencing and LC-MS Analysis Revealed the Interplay Between Gut Microbiota and Plasma Metabolites in Rats With Ischemic Stroke |
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Abstract Gut microbiome and plasma metabolome serve a role in the pathogenesis of ischemic stroke (IS). However, the relationship between the microbiota and metabolites remains unclear. This study aimed to reveal the specific asso-ciation between the microbiota and the metabolites in IS using integrated 16S rRNA gene sequencing and liquid chromatography-mass spectrometry (LC-MS) analysis. Male Sprague Dawley (SD) rats were divided into three groups: normal group (n = 8, Normal), model group (n = 9, IS), and sham-operated group (n = 8, Sham). Rats in the IS group were induced by middle cerebral artery occlusion (MCAO), and rats in the Sham group received an initial anesthesia and neck incision only. A neurological function test and 2,3,5-triphenyltetrazolium chloride (TTC) staining were used to assess the IS rat model. Then, the plasma samples were analyzed using untargeted LC-MS. The cecum samples were collected and analyzed using 16S rRNA sequencing. Pearson correlation analysis was performed to explore the association between the gut microbiota and the plasma metabolites. The 16S rRNA sequencing showed that the composition and diversity of the microbiota in the IS and control rats were significantly different. Compared with the Sham group, the abundance of the Firmicutes phylum was decreased, whereas Proteobacteria and Deferribacteres were increased in the IS group. Ruminococcus_sp_15975 and Lachnospiraceae_UCG_001 might be considered as biomarkers for the IS and Sham groups, respectively. LC-MS analysis revealed that many metabolites, such as L-leucine, L-valine, and L-phenylalanine, displayed different patterns between the IS and Sham groups. Pathway analysis indicated that these metabolites were mainly involved in mineral absorption and cholinergic synapse. Furthermore, integrated analysis correlated IS-related microbes with metabolites. For example, Proteobacteria were positively correlated with L-phenylalanine, while they were negatively correlated with eicosapentaenoic acid (EPA). Our results provided evidence of the relationship between the gut microbiome and plasma metabolome in IS, suggesting that these microflora-related metabolites might serve as potential diagnostic and therapeutic markers. © The Author(s), under exclusive licence to Springer Science+Business Media, LLC, part of Springer Nature 2021 |
| abstractGer |
Abstract Gut microbiome and plasma metabolome serve a role in the pathogenesis of ischemic stroke (IS). However, the relationship between the microbiota and metabolites remains unclear. This study aimed to reveal the specific asso-ciation between the microbiota and the metabolites in IS using integrated 16S rRNA gene sequencing and liquid chromatography-mass spectrometry (LC-MS) analysis. Male Sprague Dawley (SD) rats were divided into three groups: normal group (n = 8, Normal), model group (n = 9, IS), and sham-operated group (n = 8, Sham). Rats in the IS group were induced by middle cerebral artery occlusion (MCAO), and rats in the Sham group received an initial anesthesia and neck incision only. A neurological function test and 2,3,5-triphenyltetrazolium chloride (TTC) staining were used to assess the IS rat model. Then, the plasma samples were analyzed using untargeted LC-MS. The cecum samples were collected and analyzed using 16S rRNA sequencing. Pearson correlation analysis was performed to explore the association between the gut microbiota and the plasma metabolites. The 16S rRNA sequencing showed that the composition and diversity of the microbiota in the IS and control rats were significantly different. Compared with the Sham group, the abundance of the Firmicutes phylum was decreased, whereas Proteobacteria and Deferribacteres were increased in the IS group. Ruminococcus_sp_15975 and Lachnospiraceae_UCG_001 might be considered as biomarkers for the IS and Sham groups, respectively. LC-MS analysis revealed that many metabolites, such as L-leucine, L-valine, and L-phenylalanine, displayed different patterns between the IS and Sham groups. Pathway analysis indicated that these metabolites were mainly involved in mineral absorption and cholinergic synapse. Furthermore, integrated analysis correlated IS-related microbes with metabolites. For example, Proteobacteria were positively correlated with L-phenylalanine, while they were negatively correlated with eicosapentaenoic acid (EPA). Our results provided evidence of the relationship between the gut microbiome and plasma metabolome in IS, suggesting that these microflora-related metabolites might serve as potential diagnostic and therapeutic markers. © The Author(s), under exclusive licence to Springer Science+Business Media, LLC, part of Springer Nature 2021 |
| abstract_unstemmed |
Abstract Gut microbiome and plasma metabolome serve a role in the pathogenesis of ischemic stroke (IS). However, the relationship between the microbiota and metabolites remains unclear. This study aimed to reveal the specific asso-ciation between the microbiota and the metabolites in IS using integrated 16S rRNA gene sequencing and liquid chromatography-mass spectrometry (LC-MS) analysis. Male Sprague Dawley (SD) rats were divided into three groups: normal group (n = 8, Normal), model group (n = 9, IS), and sham-operated group (n = 8, Sham). Rats in the IS group were induced by middle cerebral artery occlusion (MCAO), and rats in the Sham group received an initial anesthesia and neck incision only. A neurological function test and 2,3,5-triphenyltetrazolium chloride (TTC) staining were used to assess the IS rat model. Then, the plasma samples were analyzed using untargeted LC-MS. The cecum samples were collected and analyzed using 16S rRNA sequencing. Pearson correlation analysis was performed to explore the association between the gut microbiota and the plasma metabolites. The 16S rRNA sequencing showed that the composition and diversity of the microbiota in the IS and control rats were significantly different. Compared with the Sham group, the abundance of the Firmicutes phylum was decreased, whereas Proteobacteria and Deferribacteres were increased in the IS group. Ruminococcus_sp_15975 and Lachnospiraceae_UCG_001 might be considered as biomarkers for the IS and Sham groups, respectively. LC-MS analysis revealed that many metabolites, such as L-leucine, L-valine, and L-phenylalanine, displayed different patterns between the IS and Sham groups. Pathway analysis indicated that these metabolites were mainly involved in mineral absorption and cholinergic synapse. Furthermore, integrated analysis correlated IS-related microbes with metabolites. For example, Proteobacteria were positively correlated with L-phenylalanine, while they were negatively correlated with eicosapentaenoic acid (EPA). Our results provided evidence of the relationship between the gut microbiome and plasma metabolome in IS, suggesting that these microflora-related metabolites might serve as potential diagnostic and therapeutic markers. © The Author(s), under exclusive licence to Springer Science+Business Media, LLC, part of Springer Nature 2021 |
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Integrated 16S rRNA Gene Sequencing and LC-MS Analysis Revealed the Interplay Between Gut Microbiota and Plasma Metabolites in Rats With Ischemic Stroke |
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| score |
7.400918 |