About this Research Topic
The human gut microbiota is the microbe population (involving bacteria, archaea, and eukarya) that inhabits our intestine, and has co-evolved with the host to live together. According to the latest estimation, the number of bacterial cells in the colon has reached 4x1013, which is approximately equal to the number of human cells. With the development and application of sequencing technologies (16S rRNA/rDNA gene sequencing and metagenomics sequencing methods) it is easier for us to reveal microbial taxonomy and their composition in the human body. Since the start of Human Microbiome Project in 2008 thousands of bacterial taxa have been identified.
In recent years, research on the function of gut microbiota attracted much more attention. Dysbiosis of gut microbiota was identified in metabolic disease, neurodegenerative disease, and cancer. And the beneficial effects of drugs, foods and other intervention measures on disorders could be microbially mediated. Despite the success of current research, the roles of the gut microbiota are worthy of further investigation. Further researches show that the metabolites of gut microbiota affect the biological processes, which could be the molecular mechanism of the roles of gut microbiota. Whereas, it is not easy to identify metabolites of microbiota and biological processes that metabolites regulated. To solve this problem it is very important to integrate priori resources to predict potential pathways of gut microbiota and metabolites, and accelerate the process of identifying metabolic influences in wet lab.
The subtopics include, but are not limited to:
• Identification of dysbiosis of the gut microbiota in metabolic disease
• Statistical methods and machine learning models for integrating priori resources to mine potential metabolites of the gut microbiota
• Statistical methods and machine learning models for integrating priori resources to mine potential immune statuses linked with the gut microbiota
• Pipeline for analyzing 16s rDNA/rRNA and metagenomics sequencing data
• Tools for analyzing 16s rDNA/rRNA and metagenomics sequencing data
In recent years, research on the function of gut microbiota attracted much more attention. Dysbiosis of gut microbiota was identified in metabolic disease, neurodegenerative disease, and cancer. And the beneficial effects of drugs, foods and other intervention measures on disorders could be microbially mediated. Despite the success of current research, the roles of the gut microbiota are worthy of further investigation. Further researches show that the metabolites of gut microbiota affect the biological processes, which could be the molecular mechanism of the roles of gut microbiota. Whereas, it is not easy to identify metabolites of microbiota and biological processes that metabolites regulated. To solve this problem it is very important to integrate priori resources to predict potential pathways of gut microbiota and metabolites, and accelerate the process of identifying metabolic influences in wet lab.
The subtopics include, but are not limited to:
• Identification of dysbiosis of the gut microbiota in metabolic disease
• Statistical methods and machine learning models for integrating priori resources to mine potential metabolites of the gut microbiota
• Statistical methods and machine learning models for integrating priori resources to mine potential immune statuses linked with the gut microbiota
• Pipeline for analyzing 16s rDNA/rRNA and metagenomics sequencing data
• Tools for analyzing 16s rDNA/rRNA and metagenomics sequencing data
Keywords: gut microbiota, sequencing technologies, metabolite, immune status
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