by Jeya Chelliah B.Vsc Ph.D.

In the vast biochemical landscape of the human body, trillions of microbes residing in our gut aren’t just passive bystanders—they’re biochemical whisperers, sending chemical messages that tweak, tune, or sometimes hijack host cellular signaling. These interactions, known as host-microbiome crosstalk, are implicated in everything from immune modulation to cancer progression to brain function.

Yet, mapping these molecular conversations remains a daunting challenge due to the sheer complexity of microbial metabolites and their potential to interact with a wide array of host pathways like Wnt, NF-κB, or mTOR. The exciting news? With the advent of Large Language Models (LLMs) like ChatGPT, scientists now have a powerful assistant to uncover, hypothesize, and even simulate hidden signaling crosstalks.

Imagine discovering that a short-chain fatty acid produced by a gut bacterium could inhibit β-catenin accumulation in colon epithelial cells—a finding with massive implications for colorectal cancer therapy. Or that tryptophan-derived indoles regulate host AhR pathways affecting neuroinflammation.

This blog presents a step-by-step scientific guide on how to use ChatGPT to map microbiome-derived metabolites to host signaling cascades, generate hypotheses, and pave the way for therapeutic interventions in chronic disease and cancer.

🧪 Step-by-Step Guide: Using ChatGPT to Map Microbiome–Host Crosstalk

Step 1: Frame Your Biological Question

Define the tissue or disease context and what kind of signaling crosstalk you’re interested in.

Example Prompts to Ask ChatGPT:
• “Act as a microbiome researcher. What microbial metabolites are known to influence Wnt signaling in colon epithelial cells?”
• “List gut microbial metabolites that modulate NF-κB pathway in immune cells.”

Step 2: Compile Known Microbial Metabolites

Ask ChatGPT to generate a comprehensive list of microbial metabolites based on taxonomy or metabolic class.

Prompt:
• “List major metabolites produced by Firmicutes and their known biological effects on mammalian cells.”

Step 3: Map to Host Pathways

Ask ChatGPT to suggest possible receptor targets or signaling nodes for each metabolite.

Prompt:
• “Which human cell signaling pathways are modulated by butyrate? Include epigenetic and receptor-mediated mechanisms.”

Step 4: Hypothesize Unknown Crosstalk (Exploratory)

Use ChatGPT to generate speculative hypotheses where literature is sparse.

Prompt:
• “Suggest hypothetical interactions between bacterial tryptophan metabolites and MAPK pathway in astrocytes.”

Step 5: Build a Mechanistic Map

Ask ChatGPT to organize findings into a logical diagram or pathway map.

Prompt:
• “Summarize all known microbial metabolites affecting Wnt/β-catenin signaling and their human receptors in tabular format.”
• “Create a mechanistic map of butyrate’s action from gut lumen to T-cell differentiation in lamina propria.”

Step 6: Suggest Experimental Approaches

Ask ChatGPT to recommend assays to test the interactions.

Prompt:
• “What experiments can confirm the interaction between propionate and mTOR signaling in hepatocytes?”

Step 7: Therapeutic Positioning

Ask therapeutic questions to link discoveries with clinical relevance.

Prompt:
• “How can targeting microbial tryptamine production help modulate serotonin signaling in patients with IBD?”
• “Suggest drug repurposing candidates that mimic indole-3-propionic acid’s anti-inflammatory effects.”

🧠 From Gut Feeling to Scientific Discovery

The microbiome is not just a community of bacteria; it’s a biochemical whisper network. By decoding its messages using AI, scientists can uncover non-obvious signaling bridges, paving the way for breakthroughs in precision medicine, immunotherapy, and even neuropsychiatric care.

🧬 Ready to Try?

Ask ChatGPT:
• “Act as a systems biologist. What orphan human receptors might be responsive to gut microbial metabolites but are poorly studied?”

And let the crosstalk begin.