Sean M. Schumacher, William J. Doyle, Kristina Hill, Javier Ochoa-Repáraz
{"title":"与多发性硬化症小鼠模型相关的粪便微生物组PICRUSt2分析","authors":"Sean M. Schumacher, William J. Doyle, Kristina Hill, Javier Ochoa-Repáraz","doi":"10.1096/fba.2025-00060","DOIUrl":null,"url":null,"abstract":"<p>Multiple sclerosis (MS) is a debilitating neuroinflammatory disease of the central nervous system (CNS). Approximately 2–3 million people globally are believed to have MS. There is growing interest in the mechanistic link between MS and gut microbiome composition. Experimental autoimmune encephalomyelitis (EAE) is a murine model of inflammatory demyelination of the CNS commonly used to investigate the pathology of MS in relation to the microbiome. Previous research has shown that EAE affects the gut microbiome, and the improvement of EAE can promote microbiome homeostasis. Microbiome homeostasis is crucial for host health, as it contributes to immune regulation and produces bioavailable metabolic products in the digestive tract. Several factors, including diet, genetics, and environment, influence microbiome homeostasis apart from disease state. Our lab previously demonstrated that mice of the same genetic line, sourced from different manufacturers, exhibit differences in microbiome composition despite being housed under similar conditions. Furthermore, these mice showed variations in EAE progression and severity, indicating that differences in the microbiome may contribute to the discrepancies in EAE. Here, we employ PICRUSt2 to estimate functional differences in the microbiomes of EAE mice from various sources at key time points during the EAE disease course. The reanalysis of our microbiome data reveals distinct differences in predicted gene expression of microbiomes that are disproportionately related to the metabolism of amino acids, carbohydrates, lipids, and other metabolites. Our findings support previous observations regarding microbiome alterations in the context of EAE and suggest that evaluating microbiome dynamics would benefit from both taxonomic assessment and metabolic activity, allowing for more effective and comprehensive research strategies.</p>","PeriodicalId":12093,"journal":{"name":"FASEB bioAdvances","volume":"7 7","pages":""},"PeriodicalIF":2.5000,"publicationDate":"2025-07-10","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://onlinelibrary.wiley.com/doi/epdf/10.1096/fba.2025-00060","citationCount":"0","resultStr":"{\"title\":\"PICRUSt2 Analysis of Fecal Microbiome Associated With a Murine Model of Multiple Sclerosis\",\"authors\":\"Sean M. Schumacher, William J. Doyle, Kristina Hill, Javier Ochoa-Repáraz\",\"doi\":\"10.1096/fba.2025-00060\",\"DOIUrl\":null,\"url\":null,\"abstract\":\"<p>Multiple sclerosis (MS) is a debilitating neuroinflammatory disease of the central nervous system (CNS). Approximately 2–3 million people globally are believed to have MS. There is growing interest in the mechanistic link between MS and gut microbiome composition. Experimental autoimmune encephalomyelitis (EAE) is a murine model of inflammatory demyelination of the CNS commonly used to investigate the pathology of MS in relation to the microbiome. Previous research has shown that EAE affects the gut microbiome, and the improvement of EAE can promote microbiome homeostasis. Microbiome homeostasis is crucial for host health, as it contributes to immune regulation and produces bioavailable metabolic products in the digestive tract. Several factors, including diet, genetics, and environment, influence microbiome homeostasis apart from disease state. Our lab previously demonstrated that mice of the same genetic line, sourced from different manufacturers, exhibit differences in microbiome composition despite being housed under similar conditions. Furthermore, these mice showed variations in EAE progression and severity, indicating that differences in the microbiome may contribute to the discrepancies in EAE. Here, we employ PICRUSt2 to estimate functional differences in the microbiomes of EAE mice from various sources at key time points during the EAE disease course. The reanalysis of our microbiome data reveals distinct differences in predicted gene expression of microbiomes that are disproportionately related to the metabolism of amino acids, carbohydrates, lipids, and other metabolites. Our findings support previous observations regarding microbiome alterations in the context of EAE and suggest that evaluating microbiome dynamics would benefit from both taxonomic assessment and metabolic activity, allowing for more effective and comprehensive research strategies.</p>\",\"PeriodicalId\":12093,\"journal\":{\"name\":\"FASEB bioAdvances\",\"volume\":\"7 7\",\"pages\":\"\"},\"PeriodicalIF\":2.5000,\"publicationDate\":\"2025-07-10\",\"publicationTypes\":\"Journal Article\",\"fieldsOfStudy\":null,\"isOpenAccess\":false,\"openAccessPdf\":\"https://onlinelibrary.wiley.com/doi/epdf/10.1096/fba.2025-00060\",\"citationCount\":\"0\",\"resultStr\":null,\"platform\":\"Semanticscholar\",\"paperid\":null,\"PeriodicalName\":\"FASEB bioAdvances\",\"FirstCategoryId\":\"1085\",\"ListUrlMain\":\"https://onlinelibrary.wiley.com/doi/10.1096/fba.2025-00060\",\"RegionNum\":0,\"RegionCategory\":null,\"ArticlePicture\":[],\"TitleCN\":null,\"AbstractTextCN\":null,\"PMCID\":null,\"EPubDate\":\"\",\"PubModel\":\"\",\"JCR\":\"Q3\",\"JCRName\":\"BIOCHEMISTRY & MOLECULAR BIOLOGY\",\"Score\":null,\"Total\":0}","platform":"Semanticscholar","paperid":null,"PeriodicalName":"FASEB bioAdvances","FirstCategoryId":"1085","ListUrlMain":"https://onlinelibrary.wiley.com/doi/10.1096/fba.2025-00060","RegionNum":0,"RegionCategory":null,"ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"Q3","JCRName":"BIOCHEMISTRY & MOLECULAR BIOLOGY","Score":null,"Total":0}
PICRUSt2 Analysis of Fecal Microbiome Associated With a Murine Model of Multiple Sclerosis
Multiple sclerosis (MS) is a debilitating neuroinflammatory disease of the central nervous system (CNS). Approximately 2–3 million people globally are believed to have MS. There is growing interest in the mechanistic link between MS and gut microbiome composition. Experimental autoimmune encephalomyelitis (EAE) is a murine model of inflammatory demyelination of the CNS commonly used to investigate the pathology of MS in relation to the microbiome. Previous research has shown that EAE affects the gut microbiome, and the improvement of EAE can promote microbiome homeostasis. Microbiome homeostasis is crucial for host health, as it contributes to immune regulation and produces bioavailable metabolic products in the digestive tract. Several factors, including diet, genetics, and environment, influence microbiome homeostasis apart from disease state. Our lab previously demonstrated that mice of the same genetic line, sourced from different manufacturers, exhibit differences in microbiome composition despite being housed under similar conditions. Furthermore, these mice showed variations in EAE progression and severity, indicating that differences in the microbiome may contribute to the discrepancies in EAE. Here, we employ PICRUSt2 to estimate functional differences in the microbiomes of EAE mice from various sources at key time points during the EAE disease course. The reanalysis of our microbiome data reveals distinct differences in predicted gene expression of microbiomes that are disproportionately related to the metabolism of amino acids, carbohydrates, lipids, and other metabolites. Our findings support previous observations regarding microbiome alterations in the context of EAE and suggest that evaluating microbiome dynamics would benefit from both taxonomic assessment and metabolic activity, allowing for more effective and comprehensive research strategies.