This study presents a comparative analysis of human gut microbiota using barcoded pyrosequencing of the hyper-variable region of the 16S rRNA gene. The method, which combines PCR amplification with sample-specific barcode sequences, allows for high-throughput and cost-effective analysis of microbial communities in various samples, including throat, stomach, and fecal samples. In silico modeling demonstrated that the method accurately describes microbial communities down to phylotypes below the genus level. The results show that the method is robust and can be used to explore the diversity within human gut ecosystems. The analysis revealed that the fecal samples had the highest diversity, while the throat samples displayed the lowest phylotype richness and the highest similarity between individuals. The stomach samples showed a diverse microbial community, with a significant presence of Actinobacteria, which was unexpected given previous studies. The study also highlighted the dominance of *Helicobacter pylori* in infected stomach samples, reducing microbial diversity. Overall, the high-throughput methodology demonstrated here provides a valuable tool for large-scale epidemiological studies to investigate the association between microbial gut ecology and diseases.This study presents a comparative analysis of human gut microbiota using barcoded pyrosequencing of the hyper-variable region of the 16S rRNA gene. The method, which combines PCR amplification with sample-specific barcode sequences, allows for high-throughput and cost-effective analysis of microbial communities in various samples, including throat, stomach, and fecal samples. In silico modeling demonstrated that the method accurately describes microbial communities down to phylotypes below the genus level. The results show that the method is robust and can be used to explore the diversity within human gut ecosystems. The analysis revealed that the fecal samples had the highest diversity, while the throat samples displayed the lowest phylotype richness and the highest similarity between individuals. The stomach samples showed a diverse microbial community, with a significant presence of Actinobacteria, which was unexpected given previous studies. The study also highlighted the dominance of *Helicobacter pylori* in infected stomach samples, reducing microbial diversity. Overall, the high-throughput methodology demonstrated here provides a valuable tool for large-scale epidemiological studies to investigate the association between microbial gut ecology and diseases.