aiming-lab/autoresearchclaw/metabolic-study-planner

Metabolic Study Planner

Overview

Use this skill before gsmm-builder, fba-simulator, and flux-analyzer when the project starts from a broad prompt such as "do a metabolic flux analysis paper" or "find a publishable idea in microbial metabolism".

The goal is to turn a vague topic into a concrete, executable, paper-shaped study plan:

organism + model + condition + perturbation + metric + figure set + claim

This is the MFA analogue of choosing a collider process and parameter scan before generating events.

Planning Inputs

Extract or infer the following:

If the user provides no organism, start with one of these low-risk defaults:

Prefer E. coli for fully autonomous first runs because it is fast and interpretable.

Study Archetypes

Archetype A: Knockout Strategy for Product Overproduction

Use when the topic mentions metabolic engineering, bio-production, yield, or fermentation.

Plan:

1. Select a product exchange reaction, e.g. succinate, lactate, ethanol, acetate.
2. Run WT FBA and pFBA under a defined medium.
3. Screen single reaction/gene knockouts.
4. Rank perturbations by product secretion subject to retaining growth.
5. Validate top candidates with FVA and carbon-source sensitivity.

Required metrics:

• WT growth rate
• mutant growth fraction
• product secretion flux
• product yield per glucose uptake
• robustness across oxygen/carbon-source bounds

Paper claim format:

Constraint-based screening predicts that perturbing <pathway> improves

<product> secretion while preserving <growth_fraction> of WT growth.

Archetype B: Nutrient-Condition Phase Map

Use when the topic mentions adaptation, nutrient limitation, aerobic/anaerobic growth, diauxie, or environmental stress.

Plan:

1. Choose two exchange reactions, usually glucose and oxygen.
2. Generate a 2D production envelope / phenotype phase plane.
3. Compare secretion profiles across regimes.
4. Identify transitions between respiration, overflow metabolism, and no-growth

regions.

Required metrics:

• growth flux_maximum
• glucose uptake
• oxygen uptake
• major byproduct secretion fluxes
• regime labels

Paper claim format:

A two-axis nutrient envelope reveals distinct feasible metabolic regimes and

predicts condition-specific secretion shifts.

Archetype C: Essentiality and Drug-Target Prioritisation

Use when the topic mentions antimicrobial targets, cancer metabolism, essential genes, or robustness.

Plan:

1. Select an organism/model relevant to the disease.
2. Run single gene/reaction deletion.
3. Filter essential genes/reactions.
4. Remove non-specific housekeeping artifacts where possible.
5. Prioritise targets by subsystem, growth impact, and flux centrality.

Required metrics:

• essential gene count
• essential reaction count
• subsystem enrichment
• growth fraction after deletion
• rescue condition sensitivity

Paper claim format:

FBA essentiality analysis prioritises <subsystem> as a condition-dependent

vulnerability under <medium>.

Archetype D: Method/Protocol Benchmark

Use when the topic is methodological or AutoResearchClaw asks for a benchmark.

Plan:

1. Compare FBA, pFBA, loopless FBA, and FVA-derived predictions.
2. Run across multiple models or media.
3. Evaluate stability of growth, secretion, and essentiality calls.

Required metrics:

• runtime
• solver status rate
• agreement of essential genes/reactions
• flux sparsity
• objective consistency

Paper claim format:

A standardised COBRApy protocol improves reproducibility of metabolic

phenotype predictions across models and media.

Feasibility Gate

Before committing to a study, score candidate ideas from 1-5:

Proceed only if total score is at least 18/25. Otherwise choose a simpler organism, narrower product, or smaller perturbation space.

Required Study Card

Write a study_card.md before code generation:

# Metabolic Study Card
 
## Research Question
One sentence.
 
## Hypothesis
One falsifiable claim.
 
## Model
-Organism:
-Model ID / source:
-Objective reaction:
 
## Conditions
-Medium:
-Carbon source:
-Oxygen bounds:
 
## Analyses
-FBA:
-pFBA:
-FVA:
-Knockout screen:
-Production envelope:
 
## Metrics
-Growth rate:
-Product flux:
-Yield:
-Essentiality:
-Robustness:
 
## Figures
1.WT vs perturbation flux summary
2.Product yield ranking
3.Production envelope / phase map
4.Essentiality or subsystem enrichment plot
 
## Risks
-Model curation risk:
-Solver/runtime risk:
-Biological interpretation risk:

AutoResearchClaw Guidance

When this skill is matched in AutoResearchClaw:

• In hypothesis_gen, propose hypotheses tied to a named model and analysis.
• In experiment_design, include a concrete model ID, objective reaction,

perturbation set, and metrics.

• In code_generation, generate a self-contained COBRApy script that can run

either on a local model file or on a minimal fallback toy model if the full model is unavailable.

• In result_analysis, do not overclaim experimental validation. Phrase results

as model-based predictions.

• In paper writing, explicitly state that conclusions are constraint-based

computational predictions requiring wet-lab validation.

Recommended First Autonomous Topic

If the user has no idea, start with:

Predict robust reaction knockout strategies for succinate overproduction in
E. coli using COBRApy FBA, pFBA, FVA, and oxygen/glucose production envelopes.

This topic is computationally feasible, uses a standard organism, produces multiple figures, and has an interpretable metabolic-engineering narrative.