E. coli carbon-source robustness and condition-dependent essential genes
Domain: biology (systems-biology, essentiality-analysis, constraint-based-modelling)
Topic: E. coli carbon-source robustness and condition-dependent essential genes
Venue: ARC-Bench Biology 2026
Headline metric: primary_metric (maximize)

Research briefing:
Carbon-source swaps are a direct mfa-agent capability and produce interpretable
condition-dependent phenotypes. A credible study loads an E. coli GSMM, defines
a base minimal medium, tests multiple single-carbon sources, runs essentiality
analysis on a focused gene set under each feasible source, and identifies genes
whose essentiality changes with carbon source.

Hypotheses:
statement: The model predicts positive growth on glucose and at least two additional supported carbon sources., statement: Growth rates and secretion profiles differ substantially across carbon sources., statement: A focused central-carbon gene set contains condition-dependent essential genes whose deletion effects vary by carbon source.

Experiment design:
research_question: Which E. coli metabolic vulnerabilities are carbon-source dependent across glucose, glycerol, acetate, succinate, and fructose-like conditions?
conditions: name: carbon_source_panel
description: Close background carbon uptake, open one carbon source at a time, and run FBA/pFBA., name: focused_gene_essentiality_by_carbon
description: For feasible carbon sources, delete a focused set of central-carbon genes and record growth fractions.
baselines: Glucose-minimal medium., Wild-type growth for each carbon source.
metrics: name: growth_rate_by_carbon
direction: characterize
description: WT biomass flux per carbon source., name: major_secretions_by_carbon
direction: characterize
description: Positive exchange fluxes under pFBA., name: condition_dependent_essential_count
direction: maximize
description: Genes essential under one source but not another.
datasets: name: E. coli GSMM
source: BIGG iJO1366 or iAF1260 via cobra.io.load_model
compute_requirements: gpu_required: no
estimated_wall_clock_sec: 2400

Requirements:
type: artifact
description: results.json contains carbon-source growth table summary, essentiality counts, hypothesis verdicts, and summary., type: artifact
description: A carbon-source comparison table exists with source, exchange reaction, status, growth, and secretion profile fields., type: artifact
description: A gene-by-carbon essentiality/growth-fraction matrix exists for feasible carbon sources., type: artifact
description: A heatmap or clustered plot of condition-dependent gene essentiality exists with labelled axes., type: discussion
description: Each of hypotheses.h1, hypotheses.h2, hypotheses.h3 in results.json MUST have an explicit `supported` boolean and a `details` string of at least 40 characters describing the evidence used to reach that verdict.
, type: discussion
description: Top-3 condition-dependent essential genes are explained mechanistically — why each gene is essential under one carbon source but not another, referencing the metabolic pathway context. Acceptable inside summary, structured_results, or a separate writeup field., type: discussion
description: The solver backend (cobra optlang interface name + version) and COBRApy version are reported in results.json. Required for reproducibility but not for scientific correctness.

Scoring rubric:
requirements: A credible E. coli carbon-source robustness study that loads a validated GSMM, swaps carbon sources, reports growth/secretion profiles, and identifies condition-dependent essential genes from a focused gene set.
judging_note: Score explicit medium handling and condition-dependent interpretation. It is acceptable if some carbon sources are unsupported, provided they are recorded and not silently dropped.
sub_tasks: requirements: The code implements carbon-source medium swaps, FBA/pFBA, and focused essentiality comparison.
sub_tasks: requirements: Loads E. coli BIGG model, identifies biomass and candidate carbon exchange reactions, and defines a minimal medium policy.
task_category: Code Development
finegrained_task_category: Experimental Setup, requirements: Closes background carbon uptake and opens one carbon source at a time with documented uptake bounds.
task_category: Code Development
finegrained_task_category: Experimental Setup, requirements: Runs FBA/pFBA per source and records major positive exchange fluxes.
task_category: Code Development
finegrained_task_category: Method Implementation, requirements: Runs focused single-gene deletions for feasible carbon sources and computes growth fractions relative to each source-specific WT.
task_category: Code Development
finegrained_task_category: Method Implementation, requirements: Execution produces carbon-source and essentiality artifacts.
sub_tasks: requirements: Glucose reference is optimal and at least two non-glucose sources are either feasible or clearly marked unsupported/infeasible.
task_category: Code Execution
finegrained_task_category: Evaluation, Metrics & Benchmarking, requirements: Mass-balance check passes for the E. coli GSMM under each tested carbon source; no carbon source produces negative biomass or non-physical secretion without explicit handling; model state is restored between carbon-source conditions. This is the biology-validity gate equivalent to physics-validity checks in the physics rubric.
task_category: Code Execution
finegrained_task_category: Evaluation, Metrics & Benchmarking, requirements: Writes results.json, carbon-source table, and gene-by-condition growth-fraction matrix.
task_category: Code Execution
finegrained_task_category: Logging, Analysis & Presentation, requirements: Results compare carbon sources and identify condition-dependent vulnerabilities.
sub_tasks: requirements: Reports feasible carbon-source count and growth rates, including unsupported-source handling. Score 100% if ≥3 carbon sources including glucose support positive biomass growth with explicit exchange bounds documented; 67% if 2 sources support positive growth; 33% if only glucose is feasible with explicit confirmation that other sources are infeasible or unsupported; 0% otherwise.
task_category: Result Analysis
finegrained_task_category: Logging, Analysis & Presentation, requirements: Compares secretion profiles and growth rates across sources with quantitative differences. Score 100% if growth rates differ by >10% between at least 2 feasible carbon sources AND major secretion fluxes differ qualitatively across sources; 67% if growth rate differences are reported without secretion-profile comparison; 33% if differences are noted qualitatively without quantification; 0% otherwise.
task_category: Result Analysis
finegrained_task_category: Logging, Analysis & Presentation, requirements: Identifies genes with large growth-fraction changes across carbon sources and explains pathway context for top hits. Score 100% if ≥3 genes with condition-dependent essentiality changes (essential under one carbon source but not another) are identified with pathway context; 67% if 2 genes are identified; 33% if 1 gene is identified with pathway context; 0% otherwise.
task_category: Result Analysis
finegrained_task_category: Logging, Analysis & Presentation, requirements: Produces labelled bar plots and/or heatmaps for growth, secretion, and condition-dependent essentiality.
task_category: Result Analysis
finegrained_task_category: Logging, Analysis & Presentation, requirements: The README or results writeup discusses each hypothesis outcome, names supported and unsupported carbon sources, identifies condition-dependent essential genes, and gives a one-paragraph mechanistic interpretation linking carbon-source specific metabolism to the observed vulnerability changes.
task_category: Result Analysis
finegrained_task_category: Logging, Analysis & Presentation, requirements: Carbon-source definitions, gene set, thresholds, solver, and model are documented.
sub_tasks: requirements: The loaded E. coli GSMM is either persisted (models/<model_id>.json) or pinned by BIGG model ID and source URL in the writeup; a downstream user can locate the exact model object and reproduce each carbon-source medium setup.
task_category: Code Development
finegrained_task_category: Reproducibility, requirements: Saves carbon exchange IDs, uptake bounds, oxygen setting, gene list, and essentiality threshold.
task_category: Code Development
finegrained_task_category: Reproducibility, requirements: Records COBRApy/solver versions and rerun consistency for glucose and at least one non-glucose source.
task_category: Code Development
finegrained_task_category: Reproducibility