Dataset Information

New gene markers for classification and quantification of Faecalibacterium spp. in the human gut.

ABSTRACT: Faecalibacterium prausnitzii is a promising biomarker of a healthy human microbiota. However, previous studies reported the heterogeneity of this species and found the presence of several distinct groups at the species level among F. prausnitzii strains. Our recent study revealed that methods previously developed for quantification of F. prausnitzii were not specific to the species level because of the heterogeneity within the F. prausnitzii species and the application of 16S rRNA gene, which is an invalid genetic marker for the species. Therefore, previously available data failed to provide information on different groups, which limits our understanding of the importance of this organism for host health. Here, we propose an alternative gene marker for quantification of F. prausnitzii-related taxa. A total of nine group-specific primer pairs were designed by targeting rpoA gene sequences. The newly developed rpoA-based qPCR successfully quantified targeted groups. Application of the developed qPCR assay in six healthy adults revealed marked differences in abundance and prevalence among the different targeted groups in stool samples. The developed assay will facilitate detailed understanding of the impact of Faecalibacterium populations at the group level on human health and to understand the links between depletion of specific groups in Faecalibacterium and different human disorders.

SUBMITTER: Tanno H

PROVIDER: S-EPMC10093996 | biostudies-literature | 2023 Apr

REPOSITORIES: biostudies-literature

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New gene markers for classification and quantification of Faecalibacterium spp. in the human gut.

Tanno Hiroki H Chatel Jean-Marc JM Martin Rebeca R Mariat Denis D Sakamoto Mitsuo M Yamazaki Masao M Salminen Seppo S Gueimonde Miguel M Endo Akihito A

FEMS microbiology ecology 20230401 5

Faecalibacterium prausnitzii is a promising biomarker of a healthy human microbiota. However, previous studies reported the heterogeneity of this species and found the presence of several distinct groups at the species level among F. prausnitzii strains. Our recent study revealed that methods previously developed for quantification of F. prausnitzii were not specific to the species level because of the heterogeneity within the F. prausnitzii species and the application of 16S rRNA gene, which is ...[more]

PMID: 36990641

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Project description:The gut microbiota (GM) is related to obesity and other metabolic diseases. To detect GM markers for obesity in patients with different metabolic abnormalities and investigate their relationships with clinical indicators, 1,914 Chinese adults were enrolled for 16S rRNA gene sequencing in this retrospective study. Based on GM composition, Random forest classifiers were constructed to screen the obesity patients with (Group OA) or without metabolic diseases (Group O) from healthy individuals (Group H), and high accuracies were observed for the discrimination of Group O and Group OA (areas under the receiver operating curve (AUC) equal to 0.68 and 0.76, respectively). Furthermore, six GM markers were shared by obesity patients with various metabolic disorders (Bacteroides, Parabacteroides, Blautia, Alistipes, Romboutsia and Roseburia). As for the discrimination with Group O, Group OA exhibited low accuracy (AUC = 0.57). Nonetheless, GM classifications to distinguish between Group O and the obese patients with specific metabolic abnormalities were not accurate (AUC values from 0.59 to 0.66). Common biomarkers were identified for the obesity patients with high uric acid, high serum lipids and high blood pressure, such as Clostridium XIVa, Bacteroides and Roseburia. A total of 20 genera were associated with multiple significant clinical indicators. For example, Blautia, Romboutsia, Ruminococcus2, Clostridium sensu stricto and Dorea were positively correlated with indicators of bodyweight (including waistline and body mass index) and serum lipids (including low density lipoprotein, triglyceride and total cholesterol). In contrast, the aforementioned clinical indicators were negatively associated with Bacteroides, Roseburia, Butyricicoccus, Alistipes, Parasutterella, Parabacteroides and Clostridium IV. Generally, these biomarkers hold the potential to predict obesity-related metabolic abnormalities, and interventions based on these biomarkers might be beneficial to weight loss and metabolic risk improvement.

Dataset Information

New gene markers for classification and quantification of Faecalibacterium spp. in the human gut.

Publications

New gene markers for classification and quantification of Faecalibacterium spp. in the human gut.

Similar Datasets

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