{"database":"biostudies-literature","file_versions":[],"scores":null,"additional":{"submitter":["Lin PT"],"funding":["Ministry of Science and Technology, Taiwan","Taipei Medical University-National Taiwan University of Science and Technology Joint Research Program"],"pagination":["1418"],"full_dataset_link":["https://www.ebi.ac.uk/biostudies/studies/S-EPMC12449802"],"repository":["biostudies-literature"],"omics_type":["Unknown"],"volume":["25(Suppl 2)"],"pubmed_abstract":["Background
Recent microbiome studies have established the association between the composition of gut microbiota and various diseases. Since 16S ribosomal RNA sequencing may suffer from problems such as lower taxonomic resolution or limited sensitivity, more and more studies embraced whole-metagenome approach, which has the potential of sequencing everything in the target microbiome, to conduct microbial association analysis. However, species profiling, which is the most popular analysis technique for whole-metagenome analysis, cannot detect uncultivated species. Since uncultivated species may also be indispensable in the gut environments, it is crucial to identify those uncultivated species and evaluate their importance in discerning disease samples from healthy ones.Results
After conducting de novo co-assembly and genome binning procedures on two colorectal cancer (CRC) cohorts, in which one of them was from the Asian population while the other was from the Caucasian population, we identified that the Asian and Caucasian cohorts shared a significant amount of microbial species in their microbiota. In addition we found that low abundance genomes may be more important in classifying disease and healthy metagenomes. By sorting the genomes based on their random forest importance scores in differentiating disease and healthy samples and cumulatively evaluating the genome subsets in predicting CRC status, we identified dozens of \"important\" genomes for each of the cohorts that were able to predict CRC with very high accuracy (0.90 and 0.98 AUROC for the Asian and Caucasian cohorts respectively). Uncultivated species were also identified among the selected genomes, highlighting the importance of including the uncultivated species in order to build better disease prediction models and evaluate the roles of the uncultivated species in the disease formation or progression. Finally we found that the \"important\" species for both cohorts did not overlap with each other, hinting that the species highly associated with CRC disease may be different between the Eastern and Western populations.Conclusion
In this study we demonstrated the importance of recovering and analyzing low abundance uncultivated species to identify their associations with colorectal cancer. We hope this work shed new light on a more comprehensive understanding of how our gut microbes are correlated with diseases."],"journal":["BMC cancer"],"pubmed_title":["Highly-accurate prediction of colorectal cancer through low abundance uncultivated genomes recovered using metagenomic co-assembly and binning approach."],"pmcid":["PMC12449802"],"funding_grant_id":["MOST111-2221-E-038-023-MY3","grant TMU-NTUST-108-08","MOST110-2221-E-038-019-MY3"],"pubmed_authors":["Lin PT","Wu YW"],"additional_accession":[]},"is_claimable":false,"name":"Highly-accurate prediction of colorectal cancer through low abundance uncultivated genomes recovered using metagenomic co-assembly and binning approach.","description":"Background
Recent microbiome studies have established the association between the composition of gut microbiota and various diseases. Since 16S ribosomal RNA sequencing may suffer from problems such as lower taxonomic resolution or limited sensitivity, more and more studies embraced whole-metagenome approach, which has the potential of sequencing everything in the target microbiome, to conduct microbial association analysis. However, species profiling, which is the most popular analysis technique for whole-metagenome analysis, cannot detect uncultivated species. Since uncultivated species may also be indispensable in the gut environments, it is crucial to identify those uncultivated species and evaluate their importance in discerning disease samples from healthy ones.Results
After conducting de novo co-assembly and genome binning procedures on two colorectal cancer (CRC) cohorts, in which one of them was from the Asian population while the other was from the Caucasian population, we identified that the Asian and Caucasian cohorts shared a significant amount of microbial species in their microbiota. In addition we found that low abundance genomes may be more important in classifying disease and healthy metagenomes. By sorting the genomes based on their random forest importance scores in differentiating disease and healthy samples and cumulatively evaluating the genome subsets in predicting CRC status, we identified dozens of \"important\" genomes for each of the cohorts that were able to predict CRC with very high accuracy (0.90 and 0.98 AUROC for the Asian and Caucasian cohorts respectively). Uncultivated species were also identified among the selected genomes, highlighting the importance of including the uncultivated species in order to build better disease prediction models and evaluate the roles of the uncultivated species in the disease formation or progression. Finally we found that the \"important\" species for both cohorts did not overlap with each other, hinting that the species highly associated with CRC disease may be different between the Eastern and Western populations.Conclusion
In this study we demonstrated the importance of recovering and analyzing low abundance uncultivated species to identify their associations with colorectal cancer. We hope this work shed new light on a more comprehensive understanding of how our gut microbes are correlated with diseases.","dates":{"release":"2025-01-01T00:00:00Z","publication":"2025 Sep","modification":"2026-06-29T03:22:26.28Z","creation":"2026-06-29T03:19:44.618Z"},"accession":"S-EPMC12449802","cross_references":{"pubmed":["40973961"],"doi":["10.1186/s12885-025-14787-5"]}}