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Updated: Feb 24, 2026

Microbiota Analysis Using Two-step PCR and Next-generation 16S rRNA Gene Sequencing
Published on: October 15, 2019
Oxalobacter formigenes-associated host features and microbial community structures examined using the American Gut
Menghan Liu1,2,3, Hyunwook Koh4, Zachary D Kurtz2,3
1Sackler Institute of Graduate Biomedical Sciences, New York University School of Medicine, New York, NY, 10016, USA.
Background:
Increasing evidence shows the importance of the commensal microbe Oxalobacter formigenes in regulating host oxalate homeostasis, with effects against calcium oxalate kidney stone formation, and other oxalate-associated pathological conditions. However, limited understanding of O. formigenes in humans poses difficulties for designing targeted experiments to assess its definitive effects and sustainable interventions in clinical settings. We exploited the large-scale dataset from the American Gut Project (AGP) to study O. formigenes colonization in the human gastrointestinal (GI) tract and to explore O. formigenes-associated ecology and the underlying host-microbe relationships.
Results:
In >8000 AGP samples, we detected two dominant, co-colonizing O. formigenes operational taxonomic units (OTUs) in fecal specimens. Multivariate analysis suggested that O. formigenes abundance was associated with particular host demographic and clinical features, including age, sex, race, geographical location, BMI, and antibiotic history. Furthermore, we found that O. formigenes presence was an indicator of altered host gut microbiota structure, including higher community diversity, global network connectivity, and stronger resilience to simulated disturbances.
Conclusions:
Through this study, we identified O. formigenes colonizing patterns in the human GI tract, potential underlying host-microbe relationships, and associated microbial community structures. These insights suggest hypotheses to be tested in future experiments. Additionally, we proposed a systematic framework to study any bacterial taxa of interest to computational biologists, using large-scale public data to yield novel biological insights.
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