Refining antibiotic cocktail regimens for pseudo-germ-free mice and their impact on gut microbiome and pancreatic tumor proteomics

优化伪无菌小鼠的抗生素混合方案及其对肠道微生物组和胰腺肿瘤蛋白质组的影响

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Abstract

INTRODUCTION: The gut microbiome critically influences health, disease, and therapeutic responses. However, creating robust pseudo-germ-free (PGF) mouse models for microbiota-host interaction studies remains challenging due to adverse effects associated with high dosages of commonly used antibiotic cocktails. OBJECTIVES: This study aimed to refine antibiotic cocktail regimens to generate PGF mice that maintain effective bacterial clearance while minimizing toxicity, and to explore the impact of microbiota depletion on pancreatic ductal adenocarcinoma (PDAC) progression and treatment response. METHODS: Multiple antibiotic combinations were tested in C57BL/6 mice by adjusting concentrations and incorporating sweeteners. Gut microbiota depletion was assessed via 16S rRNA sequencing. Regimens were further validated in a syngeneic Panc02 PDAC model, with or without gemcitabine treatment. Proteomic analyses of tumors and plasma were performed using LC-MS/MS. Germ-free mice were also included to validate microbiota-dependent tumor responses. RESULTS: Optimized antibiotic regimens achieved substantial bacterial depletion while reducing weight loss and mortality. In PDAC-bearing mice, microbiota depletion suppressed tumor growth and significantly enhanced gemcitabine efficacy. Proteomic profiling revealed downregulation of tumor-promoting metabolic and inflammatory pathways and upregulation of apoptosis-associated pathways in antibiotic-treated mice. CONCLUSION: Refined antibiotic regimens effectively generate PGF mice with minimized side effects, enabling reproducible studies of microbiota-host interactions. Microbiota depletion alters the tumor proteomic landscape and improves chemotherapy response in PDAC, highlighting the therapeutic potential of microbiome manipulation in cancer treatment.

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