| Gut microbiota have become one of the hottest research topics in recent years.More and more evidences have revealed the relationships between gut microbiota and nutrition or diseases,which has changed our views on the prevention or treatment of diseases.High throughput sequencing based metagenomics has become the most popular technology for studies on gut microbiota since 2006.16S rRNA amplicon sequencing and shotgun sequencing are two major sequencing methods,with the former to study community structures of gut microbiota,and the latter to study both functional genes and community structures of gut microbiota.When it comes to the experimental design of metagenomics,"Top-down" and "Bottom-up" are two major strategies of metagenomics.Top-down metagenomics directly draws the hypothesis from sequencing data,while Bottom-up metagenomics draws the hypothesis from existing knowledge and database about gut microbiota,and verifies the hypothesis by sequencing data.In this study,we first used these two strategies of metagenomics to study the relationship of gut microbiota with different diseases,and then developed new sequencing technology and new bioinformatic methods to make the metagenomics more accurate and to provide more information.The main contents of this study are as follows:1.We used Top-down metagenomics to analyze the roles of gut microbiota in ochratoxin A(OTA)subchronic toxicity rat model.The results of 16S rRNA amplicon sequencing showed that OTA caused the changes of structure and diversity of microbiota,with most of genera decreased and the genus Lactobacillus increased.The results of Shotgun sequencing showed that OTA also caused the disorder of the microbial functional genes,such as genes related to the DNA repairment,Carbohydrate transport and metabolism,which might be the pathways by which OTA caused gut microbiota dysfunction.The Lactobacillus showed high resistance to OTA in gut.We isolated one Lactobacillus plantarum strain from the rat feces,and this strain showed detoxification effect on OTA.2.We used Bottom-up metagenomics to analyze the relationships between neonatal jaundice and gut microbiota.After the analysis of existing articles and database,we proposed the hypothesis that gut microbial strains containing β-glucuronidase genes might be positively related to the risk of jaundice,while some strains known to be able to reduce the bilirubin might be negatively related to the risk of jaundice.This hypothesis was confirmed by 16S rRNA amplicon sequencing of gut microbiota from jaundice and healthy infants.The AUC of combination microbial biomarkers established in this study could reach 0.951 for diagnosis of neonatal jaundice.3.We developed the vitality-distinguished high throughput sequencing method by using the DNA binding dye EMA and artificial internal control 16S rRNA.Each sample was divided into two aliquots,with one adding EMA to sequence the DNA of viable microbiota,and the other not adding EMA to sequence DNA of both viable and dead microbiota.By using artificial internal control 16S rRNA,this two sequencing results could be directly compared.This new sequencing method was used to study the gut microbiota of diarrhea infants,and find the viable pathogens.Our results showed that the vitality-distinguished high throughput sequencing method could achieve more accurate diagnosis for gut microbiota related diseases.4.We established the Gut Microbiota and Human Diseases Database and Enrichment analysis algorithm for the bioinforma tic analysis of 16S rRNA amplicon sequencing.We extracted information from more than 2000 articles related to the relationships between gut microbiota and human diseases,and calculated the relationship index by the Reliability Score of Relationship model.These information was used to construct gut microbiota and diseases relationship maps.Based on these relationship maps,we further developed the enrichment analysis algorithm,which could help to analyze the differential taxa to directly find the potential related diseases. |
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