title: Gene expression profiling gut microbiota in different races of humans.
abstract: The gut microbiome is shaped and modified by the polymorphisms of microorganisms in the intestinal tract. Its composition shows strong individual specificity and may play a crucial role in the human digestive system and metabolism. Several factors can affect the composition of the gut microbiome, such as eating habits, living environment, and antibiotic usage. Thus, various races are characterized by different gut microbiome characteristics. In this present study, we studied the gut microbiomes of three different races, including individuals of Asian, European and American races. The gut microbiome and the expression levels of gut microbiome genes were analyzed in these individuals. Advanced feature selection methods (minimum redundancy maximum relevance and incremental feature selection) and four machine-learning algorithms (random forest, nearest neighbor algorithm, sequential minimal optimization, Dagging) were employed to capture key differentially expressed genes. As a result, sequential minimal optimization was found to yield the best performance using the 454 genes, which could effectively distinguish the gut microbiomes of different races. Our analyses of extracted genes support the widely accepted hypotheses that eating habits, living environments and metabolic levels in different races can influence the characteristics of the gut microbiome.
authors.affiliation: School of Life Sciences, Shanghai University, Shanghai 200444, People's Republic of China.|College of Information Engineering, Shanghai Maritime University, Shanghai 201306, People's Republic of China.
authors.forename: Lei
authors.initials: L
authors.lastname: Chen
authors.affiliation: Institute of Health Sciences, Shanghai Institutes for Biological Sciences, Chinese Academy of Sciences, Shanghai 200031, People's Republic of China.
authors.forename: Yu-Hang
authors.initials: YH
authors.lastname: Zhang
authors.affiliation: Institute of Health Sciences, Shanghai Institutes for Biological Sciences, Chinese Academy of Sciences, Shanghai 200031, People's Republic of China.
authors.forename: Tao
authors.initials: T
authors.lastname: Huang
authors.affiliation: School of Life Sciences, Shanghai University, Shanghai 200444, People's Republic of China.
authors.forename: Yu-Dong
authors.initials: YD
authors.lastname: Cai
mesh_terms: D000465:Algorithms; D044466:Asian People; D002681:China; D016000:Cluster Analysis; D005060:Europe; D005247:Feeding Behavior / Q000208:ethnology; D000069196:Gastrointestinal Microbiome / Q000235:genetics*; D020869:Gene Expression Profiling / Q000379:methods*; D006801:Humans; D000069550:Machine Learning; D054892:Metagenome / Q000235:genetics*; D056186:Metagenomics / Q000379:methods*; D020411:Oligonucleotide Array Sequence Analysis / Q000379:methods; D014481:United States; D044465:White People