分子生物学
IVD分子诊断
细胞培养与分析
蛋白研究
细胞因子
重组蛋白
抗体
高通量测序建库
病原检测UCF系列
生物医药
工具酶
抑制剂激活剂与常用试剂
仪器
耗材

Transcriptomics-based analysis to explore the effects of culture media and cell models on the function of B. pseudocatenulatum strains of intestinal origin

Peng Du, Rong Guo, Ya Dong Yao, Jun Min Zhu, Jian Gang Feng, Hui Sun, Jie Mao

Journal:BMC GENOMICS

IF:3.9

DOI:10.1186/s12864-026-13067-1

PMID:42469641

Published:2026-07-17

research field:生物材料生物医学工程牙科药物递送组织工程伤口愈合

Abstract

Background: The gut microbiota plays a pivotal role in maintaining host health by modulating metabolic pathways and immune functions. Although its biological significance is well recognized, systematic research into the functional characterization of intestinal bacteria remains scarce, particularly concerning the impact of culture environments and host cell model selection on functional assessment. This study focused on a strain of Bifidobacterium pseudocatenulatum isolated from the feces of healthy individuals. The objective was to investigate the regulatory effects of its metabolites, produced under different medium conditions, on gene expression across multiple host cell models. Results: Metabolomic analysis revealed that the choice of culture medium (BHI vs. GAM) significantly reshaped the metabolic profiles of B. pseudocatenulatum. Transcriptomic data demonstrated that metabolites induced by different media led to markedly distinct gene expression patterns within the same host cell line. Furthermore, even under identical metabolite exposure conditions, the four cell models (MODE-K, NCM460, Henle-407, and HEK-293T) exhibited highly divergent and cell-line-specific regulatory responses. Conclusions: These findings highlight the decisive influence of both medium composition and cell model selection on the outcomes of functional studies concerning gut commensal bacteria. This research not only provides a scientific basis for optimizing experimental designs in microbial functional studies but also underscores the necessity of rigorously evaluating culture conditions and model suitability in microbiota research.

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