Traceable Claims in Biochemistry

 Quick Analysis Plan Copied

 Long Analysis Plan

Evidence Base Supporting the Two-Layered ATP Model

Layer 1 — chemomechanical currency via rotary F1Fo: The E. coli F1Fo mechanism is well characterized — γ rotation within α3β3 drives sequential β-site changes, transmitting torque from Fo proton translocation through the γε stalk, with Asp61 as the c-ring proton-binding site and ~4 H+/ATP coupling F1Fo rotary coupling mechanism review. Membrane potential Δψ is indispensable for ATP synthesis; ΔpH alone cannot sustain production Membrane potential requirement for ATP synthesis. Catalytic rate acceleration reaches ~10^11-fold via trisite catalysis (~100 s⁻¹) driven by β-Lys155, β-Arg182, α-Arg376, β-Glu181 and Mg²⁺ coordination Rate acceleration of F1Fo ATP hydrolysis.

Layer 2 — millimolar ATP as hydrotrope/structural tether: The E. coli growth-condition study is the most relevant in vivo dataset — intracellular ATP declines from ~1.32 mM (glucose-rich) to ~0.48 mM (no glucose) uncoupler-sensitive dependence, yet substrate-level ATP persists even when PMF is fully depleted by CCCP PMF-ATP coupling by growth conditions. This provides the quantitative ATP range over which non-energetic hypotheses (hydrotrope solubilization, protein aggregation suppression, structural tethering) must be tested causally.

Layer 2's causal status is the weakest link: no direct in vivo perturbation of ATP concentration at constant energy charge has been reported in these sources. Imaging data show ATP synthase mobility/activity-linked subpopulations but are correlative Single-molecule ATP synthase organization.

Bioinformatics/Coding/Analysis Plan

• M1 — Proteome-scale hydrotrope analysis: Use E. coli K-12 proteomics + solubility data to compute proteins whose solubility depends on ATP concentration in the 0.2–1.3 mM reported range; compare against ∆F1Fo vs WT conditions using the growth-rate/yield ratios (glycerol 0.64/0.48; succinate 0.25/0.25; sugars 0.72–0.82/0.78–0.98).
• M2 — Genotype-condition matrix modeling: Fit a logistic model predicting ∆F1Fo growth defect from carbon-source energetics (substrate-level ATP vs oxidative phosphorylation contribution, per supplementary Table SI 1 ranges).
• M3 — Structure-function mining: Use 3Dmol/PDB structures (e.g., 5O4R-type F1Fo) to map Asp61, Arg210, catalytic residues (β-Lys155, β-Glu181) against δPKC-dF1Fo inhibitor binding (10 and 50 nM protective, 100 nM not) Cardioprotective δPKC-dF1Fo inhibitor.
• M4 — Causal in vivo test design: Use ATP-synthase mutants with preserved energy charge but altered millimolar ATP buffering (e.g., Mg²⁺/ADP-regulatory mutants) in carbon-limitation conditions; readout = growth, protein solubility, hydrotrope-dependent aggregation.