M. tuberculosis condition-specific essentiality and metabolic drug-target prioritisation
Domain: biology (systems-biology, drug-target-prioritisation, constraint-based-modelling)
Topic: M. tuberculosis condition-specific essentiality and metabolic drug-target prioritisation
Venue: ARC-Bench Biology 2026
Headline metric: primary_metric (maximize)

Research briefing:
Constraint-based essentiality analysis can prioritise metabolic drug-target
hypotheses in pathogen models. A credible study loads an M. tuberculosis GSMM
such as iNJ661 when available, validates biomass production under a documented
medium, performs single-gene and/or single-reaction deletion, and ranks
essential targets by growth impact and subsystem interpretability.

Hypotheses:
statement: The selected M. tuberculosis model produces positive biomass under the documented reference medium., statement: Single-gene or single-reaction deletion identifies a non-empty set of essential metabolic targets under the reference condition., statement: Prioritised targets are enriched in interpretable core metabolic subsystems such as cell-wall precursor, cofactor, lipid, energy, or amino-acid metabolism.

Experiment design:
research_question: Which condition-specific metabolic genes or reactions are predicted essential in M. tuberculosis and are plausible drug-target hypotheses?
conditions: name: mtb_reference_medium
description: M. tuberculosis iNJ661 or comparable model under a documented reference medium., name: single_gene_deletion
description: Single-gene deletion screen when GPR rules are available., name: single_reaction_deletion
description: Single-reaction deletion screen as a fallback or complementary target set.
baselines: Wild-type reference growth., Nonessential deletion growth distribution.
metrics: name: wt_growth_rate_1_per_h
direction: maximize
description: Reference biomass flux., name: growth_fraction_after_deletion
direction: minimize
description: Deletion biomass divided by WT biomass., name: essential_target_count
direction: characterize
description: Count of genes/reactions below essentiality threshold., name: subsystem_enrichment
direction: characterize
description: Subsystem distribution among essential targets.
datasets: name: M. tuberculosis GSMM
source: BIGG iNJ661 or documented local SBML/JSON model.
compute_requirements: gpu_required: no
estimated_wall_clock_sec: 2400

Requirements:
type: artifact
description: results.json contains model ID, WT growth, essential target counts, top targets, and hypothesis verdicts., type: artifact
description: A gene or reaction deletion table exists with target ID, status, growth, growth_fraction, and essential flag., type: discussion
description: Top 10 prioritised essential targets are reported with subsystem/pathway and rationale., type: artifact
description: At least one essentiality distribution or subsystem-enrichment figure exists., 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 essential target hypotheses are framed mechanistically — naming the metabolic subsystem each target belongs to and why its disruption is predicted lethal under the reference medium. Claims must be framed as computational hypotheses, not validated drugs. 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 M. tuberculosis essentiality study using COBRApy that validates a pathogen GSMM, runs single-gene and/or single-reaction deletions, identifies essential targets, and prioritises interpretable drug-target hypotheses.
judging_note: Accept gene deletions, reaction deletions, or both depending on model GPR support. Penalize unsupported biological claims more than absence of external drug databases.
sub_tasks: requirements: The code loads the pathogen model, validates medium, runs deletion screens, and annotates essential targets.
sub_tasks: requirements: Loads iNJ661 or a documented M. tuberculosis GSMM, defines medium/objective, and validates positive WT biomass.
task_category: Code Development
finegrained_task_category: Method Implementation, requirements: Runs single-gene deletion when GPR rules are usable, or single-reaction deletion as an explicit fallback/complement.
task_category: Code Development
finegrained_task_category: Method Implementation, requirements: Defines essentiality threshold such as growth <5% or <10% of WT and applies it consistently.
task_category: Code Development
finegrained_task_category: Evaluation, Metrics & Benchmarking, requirements: Extracts subsystem, reaction name, gene name, GPR, or other model-native annotations for top targets.
task_category: Code Development
finegrained_task_category: Logging, Analysis & Presentation, requirements: Deletion runs complete with interpretable status handling and structured outputs.
sub_tasks: requirements: WT reference condition is optimal and at least 85% of deletion simulations solve or are explicitly marked infeasible/lethal.
task_category: Code Execution
finegrained_task_category: Evaluation, Metrics & Benchmarking, requirements: Mass-balance check passes for the loaded pathogen GSMM; WT biomass is positive under the documented medium; deletion table contains no negative growth values; model GPR rules produce logically consistent essential gene predictions. 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 plus deletion table with growth, growth_fraction, status, and essential flag.
task_category: Code Execution
finegrained_task_category: Logging, Analysis & Presentation, requirements: Results identify essential targets and provide conservative biological interpretation.
sub_tasks: requirements: Reports WT growth, medium, model ID, and validation caveats. Score 100% if positive WT biomass flux is reported under the documented medium with optimal solver status and model ID named; 67% if growth is positive but medium is not explicitly documented; 33% if feasibility is stated without a numeric value; 0% otherwise.
task_category: Result Analysis
finegrained_task_category: Logging, Analysis & Presentation, requirements: Reports essential target count and distribution of growth fractions after deletion. Score 100% if ≥5 essential genes/reactions are identified with growth fractions below the stated threshold and the deletion table covers ≥50 candidates; 67% if essential targets are identified but the candidate set covers fewer than 50 entries; 33% if essential targets are named without a deletion table; 0% otherwise.
task_category: Result Analysis
finegrained_task_category: Logging, Analysis & Presentation, requirements: Top 10 targets include subsystem/pathway and one-sentence rationale; claims are framed as modelling hypotheses, not validated drugs. Score 100% if ≥3 of the top-10 prioritised targets belong to named core metabolic subsystems (cell-wall precursor, cofactor, lipid, energy, or amino-acid biosynthesis) with at least a one-sentence pathway rationale; 67% if 2 of 10 with rationale; 33% if 1 of 10 with rationale; 0% otherwise.
task_category: Result Analysis
finegrained_task_category: Logging, Analysis & Presentation, requirements: Produces a labelled essentiality histogram, target ranking plot, or subsystem enrichment chart.
task_category: Result Analysis
finegrained_task_category: Logging, Analysis & Presentation, requirements: The README or results writeup discusses each hypothesis outcome, names the top prioritised essential targets with subsystem/enzyme identity, and gives a one-paragraph mechanistic rationale for why each target's disruption is lethal. Claims are explicitly framed as computational hypotheses requiring wet-lab validation.
task_category: Result Analysis
finegrained_task_category: Logging, Analysis & Presentation, requirements: Model, medium, deletion type, threshold, solver, and annotations are reproducibly recorded.
sub_tasks: requirements: The loaded M. tuberculosis GSMM is either persisted (models/<model_id>.json) or pinned by BIGG model ID, version, or local file hash in the writeup; a downstream user can locate the exact model object used.
task_category: Code Development
finegrained_task_category: Reproducibility, requirements: Saves model source, medium bounds, objective, deletion mode, and essentiality threshold.
task_category: Code Development
finegrained_task_category: Reproducibility, requirements: Records COBRApy/solver versions and confirms rerun consistency for WT growth and essential count.
task_category: Code Development
finegrained_task_category: Reproducibility