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Dozens of computational methods are developed to identify species present in a metagenomic dataset. Many of these computational methods depend on available sequenced microbial species, which are still far from being representative. To see how newly sequenced genomes affect the analysis results, we re-analyzed a shotgun metagenomic dataset composed of twelve colitis free metagenomic samples and ten colitis-related metagenomic samples. Unexpectedly, we identified at least two new phyla that may relate to colitis development in patients, together with the phylum identified previously. Compared with the previously identified phylum that differed between the two types of samples, the differences associated with the two new phyla are statistically more significant. Moreover, the abundance of the two new phyla correlates more with the severity of colitis. Surprisingly, even by repeating the analyses implemented in the previous study, we found that at least one main conclusion in the previous study is not supported. Our study indicates the importance of re-analysis of the generated metagenomic datasets and the necessity of considering multiple updated tools in metagenomic studies. It also sheds light on the limitations of the popular tools used currently and the importance to infer the presence of taxa without relying upon available sequenced genomes.

When old metagenomic data meet newly sequenced genomes, a case study