E. coli succinate-production strain optimization via constraint-based knockout screen
Domain: biology (systems-biology, metabolic-engineering, constraint-based-modelling)
Topic: E. coli succinate-production strain optimization via constraint-based knockout screen on iAF1260
Venue: ARC-Bench Biology 2026
Headline metric: primary_metric (maximize)

Research briefing:
Succinate is a top-12 platform chemical and a recurring case study in
metabolic engineering. The standard genome-scale model E. coli iAF1260
(2382 reactions, 1668 metabolites, 1261 genes) provides a well-validated
testbed for in-silico strain design: from a fixed glucose-minimal medium
one can predict (a) the maximum aerobic biomass growth rate, (b) the
maximum theoretical succinate secretion flux once growth is held at a feasible
fraction of optimum, (c) the set of single- and double-gene knockouts
that decouple biomass from succinate secretion enough to push the strain
toward a high-secretion non-growth-coupled phenotype.

A credible CPU-scale study of this topic (a) loads iAF1260 from BIGG and
validates aerobic biomass > 0.7 1/h on glucose-minimal medium, (b) runs
parsimonious FBA (pFBA) at the wild-type optimum and reports the central
carbon flux distribution, (c) sweeps the production envelope (biomass vs
succinate secretion) using flux variability analysis (FVA) on the
succinate exchange across a grid of biomass-fraction-of-optimum values,
(d) runs a single-gene knockout screen (≤100 candidate genes drawn from
central carbon metabolism, fermentation, and TCA cycle) and ranks each KO
by post-KO succinate secretion flux at 50% of WT growth, (e) reports the top three
KO strains with mechanistic explanation tied to the network topology.

The research question is: *which single-gene knockouts of central carbon
metabolism in E. coli iAF1260 produce the largest predicted succinate
secretion flux while preserving at least 50% of wild-type biomass growth, and what
is the mechanistic role of each in shifting flux toward succinate?*

Hypotheses:
statement: Wild-type aerobic E. coli iAF1260 on glucose-minimal medium predicts a biomass growth rate within ±10% of 0.736 1/h (the published BIGG iAF1260 reference value)., statement: The biomass-vs-succinate production envelope, computed via FVA at biomass fractions from 0.1 to 1.0 of WT optimum, is monotonically non-increasing in succinate as biomass approaches the WT optimum (i.e., succinate is growth-competing under aerobic glucose conditions)., statement: At least 3 of the top-5 single-gene knockouts identified by the screen as maximizing succinate secretion flux at 50% WT-growth disrupt canonical competing by-product or respiration pathways described in the metabolic-engineering literature (e.g., pyruvate-formate-lyase pflB, lactate dehydrogenase ldhA, alcohol dehydrogenase adhE, acetate kinase ackA, phosphate acetyltransferase pta, or their isozymes), or are accompanied by a mechanistic explanation for why the knockout redirects flux toward succinate under the chosen medium.

Experiment design:
research_question: Which single-gene knockouts of central carbon metabolism in E. coli iAF1260 produce the largest predicted succinate secretion flux while preserving at least 50% of wild-type biomass growth, and what is the mechanistic role of each in shifting flux toward succinate?
conditions: name: wt_aerobic_glucose
description: Wild-type iAF1260 on glucose-minimal medium with O2 unconstrained. Reference condition., name: wt_aerobic_glucose_pfba
description: Same as wt_aerobic_glucose but with pFBA (parsimonious FBA) for unique flux distribution., name: production_envelope_succinate
description: FVA on succinate exchange across biomass-fraction-of-optimum grid {0.1, 0.2, ..., 1.0}., name: single_ko_screen_central_carbon
description: Single-gene knockouts on a curated set of ≤100 central-carbon / fermentation / TCA genes (glycolysis, PPP, TCA, anaplerotic, fermentation by-products); for each, FBA at fixed biomass = 0.5 × WT optimum; record succinate exchange flux.
baselines: wt_aerobic_glucose (no perturbation) is the no-engineering baseline, Published BIGG iAF1260 reference growth rate (0.736 1/h on glucose-minimal aerobic) — the model-validity gate
metrics: name: wt_growth_rate
direction: match_reference
description: Wild-type biomass exchange flux (1/h) on glucose-minimal aerobic; reference value 0.736., name: max_succinate_flux_mmol_gDW_h_at_zero_growth
direction: maximize
description: Succinate exchange flux (mmol/gDW/h) at biomass = 0 (theoretical maximum)., name: succinate_flux_mmol_gDW_h_at_half_growth
direction: maximize
description: Succinate exchange flux at biomass = 0.5 × WT optimum, wild-type strain., name: best_ko_succinate_flux_mmol_gDW_h
direction: maximize
description: Maximum succinate exchange flux over the single-KO screen at biomass = 0.5 × WT optimum.
datasets: name: iAF1260
source: BIGG database (http://bigg.ucsd.edu/models/iAF1260) via cobra.io.load_model('iAF1260')
compute_requirements: gpu_required: no
estimated_wall_clock_sec: 1800

Requirements:
type: artifact
description: A canonical results.json file exists at the workspace root with at least the keys: primary_metric (number), metrics (object of numeric keys), hypotheses (object with h1/h2/h3 entries each carrying a `supported` boolean), summary (non-empty string)., type: numeric
description: results.json metrics MUST contain a numeric value for `wt_growth_observed_1_per_h` (or an equivalent wt_growth_*_1_per_h key) that is non-null and finite. The wild-type growth rate must be reported, otherwise H1 cannot be evaluated., type: discussion
description: results.json structured_results MUST contain a list of the top 5 ranked single-gene knockouts with at least {gene_id, gene_name, ko_succinate_flux_mmol_gDW_h, is_canonical} fields each. The list need not include the textbook canonical genes — but it MUST exist and identify at least 5 candidates., type: artifact
description: A production-envelope figure (biomass-vs-succinate, or analogous) must exist under figures/ or analysis/ in PDF or PNG format with axes labeled and units shown. Either a single multi-curve figure or per-condition figures both qualify., 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 KO targets are discussed mechanistically — naming the pathway each KO disables and a one-sentence rationale for why the disruption redirects flux to succinate.  Acceptable inside summary, structured_results, or a separate writeup field., type: discussion
description: The solver backend (cobra optlang interface name + version) and any RNG seeds used (e.g. for sampling) are reported in results.json. Required for reproducibility but not for scientific correctness.

Scoring rubric:
requirements: A credible constraint-based experiment on E. coli iAF1260 that (a) loads the BIGG model and validates wild-type growth, (b) computes a flux distribution under the standard objective, (c) characterises the biomass-vs-succinate production envelope, (d) runs a single-gene knockout screen targeted at central carbon metabolism, and (e) ties the top-ranked knockouts to the network mechanism. Partial but well-motivated evidence deserves partial credit; rigid wording or naming should not penalize a substantively correct experiment.
judging_note: Score on biological substance and quantitative correctness, not exact threshold satisfaction. Reproducing canonical FBA numbers (WT growth ~0.7, well-known knockouts like pflB/ldhA/adhE/ackA-pta) is strong evidence; novel-but-coherent design choices are acceptable.
sub_tasks: requirements: The constraint-based pipeline is implemented with COBRApy and a BIGG genome-scale model.
sub_tasks: requirements: The submission loads E. coli iAF1260 (or a comparable validated genome-scale metabolic model) from BIGG via COBRApy, with the medium constraints (glucose uptake, O2 availability) explicitly set and the biomass objective explicitly named.
task_category: Code Development
finegrained_task_category: Method Implementation, requirements: FBA and pFBA are invoked correctly to obtain wild-type growth and a unique flux distribution; output flux table covers exchange + central-carbon reactions at minimum.
task_category: Code Development
finegrained_task_category: Method Implementation, requirements: The biomass-vs-succinate production envelope is computed by sweeping a fraction-of-optimum biomass constraint and running FVA (or two-step FBA) on the succinate exchange at each grid point.
task_category: Code Development
finegrained_task_category: Experimental Setup, requirements: The single-gene knockout screen iterates over a curated central-carbon / fermentation / TCA gene set (≤100), applies model.genes.<g>.knock_out() (or equivalent reaction-bound deletion), and records succinate flux at fixed biomass = 0.5 × WT optimum.
task_category: Code Development
finegrained_task_category: Method Implementation, requirements: Execution produces the FBA / FVA / KO numbers needed to evaluate the hypotheses without crashing.
sub_tasks: requirements: Solver returns optimal status for the wild-type FBA and at least 90% of the KO conditions; no negative biomass or non-physical fluxes (succinate secretion negative under aerobic glucose, etc.) appear without explanation.
task_category: Code Execution
finegrained_task_category: Evaluation, Metrics & Benchmarking, requirements: Mass balance, charge balance, and biomass-positive checks pass for the loaded model; this is the biology-validity gate analogous to physics-validity (gauge invariance, unitarity) in the physics rubric.
task_category: Code Execution
finegrained_task_category: Evaluation, Metrics & Benchmarking, requirements: A machine-readable results artifact (results.json or simulations/*.csv) records WT growth rate, the production-envelope grid (biomass fraction → succinate secretion flux in mmol/gDW/h), and a per-KO succinate-flux table. If yield is reported, define it separately as succinate secretion flux divided by glucose uptake flux.
task_category: Code Execution
finegrained_task_category: Logging, Analysis & Presentation, requirements: The results analysis addresses the three hypotheses with quantitative evidence and a clear narrative tied to network mechanism.
sub_tasks: requirements: Quantitative test of H1: predicted WT aerobic growth rate is reported and compared to the published BIGG reference 0.736 1/h. Score 100% if relative error < 3%, 67% if < 10%, 33% if < 30%, 0% otherwise.
task_category: Result Analysis
finegrained_task_category: Logging, Analysis & Presentation, requirements: Quantitative test of H2: production envelope shows succinate is growth-competing — succinate flux is non-increasing as biomass approaches WT optimum. Score 100% if monotonic over ≥8 of 10 grid points, 67% if ≥6 of 10, 33% if ≥4 of 10.
task_category: Result Analysis
finegrained_task_category: Logging, Analysis & Presentation, requirements: Quantitative test of H3: among the top-5 KO ranked by succinate secretion flux at 0.5 × WT growth, count how many disrupt canonical competing by-product or respiration pathways for succinate-overproduction logic, such as {pflB, ldhA, adhE, ackA, pta, acetate/ethanol/lactate branch competitors, oxygen-respiration competitors}, or include a specific mechanistic explanation for redirecting flux toward succinate under the chosen medium. Score 100% if ≥3 of 5 meet this canonical-or-mechanistic criterion, 67% if 2 of 5, 33% if 1 of 5, 0% otherwise.
task_category: Result Analysis
finegrained_task_category: Logging, Analysis & Presentation, requirements: At least one publication-quality figure is produced — typically the production envelope (biomass on x, succinate secretion flux on y, with WT and best KO overlaid) and/or the KO essentiality / flux heatmap. Axes labeled with units (1/h, mmol/gDW/h), legend present.
task_category: Result Analysis
finegrained_task_category: Logging, Analysis & Presentation, requirements: The README or results writeup discusses each hypothesis outcome, names the top knockouts with their gene/enzyme identity, and gives a one-paragraph mechanistic interpretation (which competing pathways the KOs disable, why this redirects flux to succinate).
task_category: Result Analysis
finegrained_task_category: Logging, Analysis & Presentation, requirements: Reproducibility: the model, run cards, and seeds are checked into artifacts so a fresh clone can rerun and obtain matching numbers.
sub_tasks: requirements: The loaded GSMM is either persisted (models/iAF1260.json) or pinned by version + BIGG URL in the writeup; a downstream user can locate the exact model object used.
task_category: Code Development
finegrained_task_category: Reproducibility, requirements: The medium definition (exchange bounds), objective function, FVA fraction-of-optimum, and KO gene list are saved to a config / params file (not only inline in code).
task_category: Code Development
finegrained_task_category: Reproducibility, requirements: Solver settings (LP backend name + version, tolerance) are recorded; if any sampling step is used, the RNG seed is logged. A second run reproduces the central WT growth rate to within solver tolerance.
task_category: Code Development
finegrained_task_category: Reproducibility