Exploring the effects of bacterial infection and antibiotic or faecal microbiota transplantation treatments on the mouse gut microbiome
Posters | 2022 | Shimadzu | ASMSInstrumentation
The gut microbiome orchestrates metabolic signaling and immune modulation. Clostridioides difficile infection (CDI) disrupts microbial balance, leading to pathological outcomes. Comparing antibiotic therapy and faecal microbiota transplantation (FMT) elucidates treatment impacts on microbial metabolome, informing therapeutic strategies and enhancing understanding of host–pathogen–microbiome interactions.
This study evaluated the metabolic consequences of CDI and subsequent treatments in a murine model. Specific aims:
A cohort of male C57BL/6 mice underwent antibiotic pretreatment and clindamycin injection, followed by CDI challenge. Treatment arms included no intervention, a 10-day metronidazole course, or 10% faecal water FMT.
Metabolite extraction entailed dual-phase solvent protocols (methanol:isopropanol:water and methanol:MTBE). Analytical platforms comprised:
This study underscores the divergent metabolic consequences of antibiotic versus FMT interventions following CDI. FMT effectively normalizes gut metabolite signatures, supporting its therapeutic potential. Integrated LC-MS/MS approaches offer comprehensive insights into microbiome-mediated metabolic dynamics.
Note: No references section as original text did not include a literature list.
LC/TOF, LC/HRMS, LC/MS, LC/MS/MS
IndustriesClinical Research
ManufacturerShimadzu
Summary
Significance of the Topic
The gut microbiome orchestrates metabolic signaling and immune modulation. Clostridioides difficile infection (CDI) disrupts microbial balance, leading to pathological outcomes. Comparing antibiotic therapy and faecal microbiota transplantation (FMT) elucidates treatment impacts on microbial metabolome, informing therapeutic strategies and enhancing understanding of host–pathogen–microbiome interactions.
Objectives and Study Overview
This study evaluated the metabolic consequences of CDI and subsequent treatments in a murine model. Specific aims:
- Assess metabolic perturbations induced by CDI in caecal tissue and fecal content.
- Compare the effects of metronidazole versus FMT on restoring metabolic profiles.
- Integrate targeted and untargeted LC-MS/MS workflows for comprehensive metabolite coverage.
Methodology and Instrumentation
A cohort of male C57BL/6 mice underwent antibiotic pretreatment and clindamycin injection, followed by CDI challenge. Treatment arms included no intervention, a 10-day metronidazole course, or 10% faecal water FMT.
Metabolite extraction entailed dual-phase solvent protocols (methanol:isopropanol:water and methanol:MTBE). Analytical platforms comprised:
- Reverse-phase LC (Acquity C18 BEH, 50°C) with 35 min gradient.
- HILIC LC (Shim-pack Velox, 40°C) with 18 min cycle.
- Shimadzu QTOF LCMS-9030, ESI positive/negative, DIA-MS/MS (m/z 40–1000).
Results and Discussion
- Metronidazole treatment elevated lysophosphatidylethanolamines (LPE 16:1, LPE 18:1), malate, proline, and creatine in caecal extracts.
- CDI increased taurocholate, creatinine, and cysteate in fecal content; FMT restored these to baseline levels.
- Infection reduced N-acyl taurines in caecum; FMT partially reversed this effect.
- Untreated infection and antibiotic profiles diverged from controls, whereas FMT-treated mice closely matched uninfected metabolomes.
Benefits and Practical Applications
- Demonstrates FMT’s capability to reestablish healthy metabolic states post-infection.
- Validates combined targeted/untargeted LC-MS/MS for robust metabolome mapping in complex biological matrices.
- Informs antibiotic stewardship by highlighting metabolic side effects of metronidazole.
Future Trends and Applications
- Advancements in multi-omics integration and AI-driven metabolite annotation will enhance identification in heterogeneous samples.
- Development of dynamic, longitudinal monitoring tools to track microbiome–host interactions in real time.
- Translating murine findings to clinical practice to optimize personalized microbiota therapies.
Conclusion
This study underscores the divergent metabolic consequences of antibiotic versus FMT interventions following CDI. FMT effectively normalizes gut metabolite signatures, supporting its therapeutic potential. Integrated LC-MS/MS approaches offer comprehensive insights into microbiome-mediated metabolic dynamics.
Note: No references section as original text did not include a literature list.
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