Avoid Internal Loops in Steady State Flux Space Sampling

TL;DR

This paper introduces a generalized ACHR-based sampling method that effectively eliminates internal loops in steady state flux space, improving the accuracy of metabolic network analyses without compromising non-loop fluxes.

Contribution

A novel ACHR-based sampling approach that prevents internal loop formation during flux space sampling in metabolic networks.

Findings

Effective removal of internal loops in Helicobacter pylori network.

Maintains non-loop flux distributions similar to conventional methods.

Applicable across different objective functions.

Abstract

As a widely used method in metabolic network studies, Monte-Carlo sampling in the steady state flux space is known for its flexibility and convenience of carrying out different purposes, simply by alternating constraints or objective functions, or appending post processes. Recently the concept of a non-linear constraint based on the second thermodynamic law, known as "Loop Law", is challenging current sampling algorithms which will inevitably give rise to the internal loops. A generalized method is proposed here to eradicate the probability of the appearance of internal loops during sampling process. Based on Artificial Centered Hit and Run (ACHR) method, each step of the new sampling process will avoid entering "loop-forming" subspaces. This method has been applied on the metabolic network of Helicobacter pylori with three different objective functions: uniform sampling, optimizing biomass synthesis, optimizing biomass synthesis efficiency over resources ingested. Comparison between results from the new method and conventional ACHR method shows effective elimination of loop fluxes without affecting non-loop fluxes.