Computational framework for predictive biodegradation

Abstract

As increasing amounts of anthropogenic chemicals are released into the environment, it is vital to human health and the preservation of ecosystems to evaluate the fate of these chemicals in the environment. It is useful to predict whether a particular compound is biodegradable and if alternate routes can be engineered for compounds already known to be biodegradable. In this work, we describe a computational framework (called BNICE) that can be used for the prediction of novel biodegradation pathways of xenobiotics. The framework was applied to 4-chlorobiphenyl, phenanthrene, gamma-hexachlorocyclohexane, and 1,2,4-trichlorobenzene, compounds representing various classes of xenobiotics with known biodegradation routes. BNICE reproduced the proposed biodegradation routes found experimentally, and in addition, it expanded the biodegradation reaction networks through the generation of novel compounds and reactions. The novel reactions involved in the biodegradation of 1,2,4-trichlorobenzene were studied in depth, where pathway and thermodynamic analyses were performed. This work demonstrates that BNICE can be applied to generate novel pathways to degrade xenobiotic compounds that are thermodynamically feasible alternatives to known biodegradation routes and attractive targets for metabolic engineering.

Figure 1

Flow chart of the reaction mapping algorithm. BNICE is used to generate a set of candidate reactions. If one of the candidate reactions is an exact match, the algorithm stops and maps the reaction rule used to generate the match to the target reaction. If no exact match is found, the algorithm searches for a near match. If a single reaction does not match the target reaction, metabolic flux analysis (MFA) is used to determine if a set of candidate reactions can combine to reproduce the target reaction. If the MFA procedure succeeds, mixed integer linear programming (MILP) is used to identify all unique, minimal combinations of candidate reactions that combine to match the target reaction. Reaction rule(s) used to generate the candidate reactions are mapped to the target reaction.

Figure 2

Number of compounds (solid diamonds) and reactions (open squares) at each application of the reaction rules. A: 4-chlorobiphenyl; (B) phenanthrene; (C) γ-hexachlorocyclohexane; (D) 1,2,4-trichlorobenzene.

Figure 3

Distribution of pathways from 1,2,4-trichlorobenzene to termination compounds. A: Pathways to endpoints of the known pathways: glycolate (solid diamonds), succinate (solid squares), and both glycolate and succinate (open circles); (B) pathways to additional termination compounds.

Figure 4

Fifteen novel biodegradation routes of 1,2,4-trichlorobenzene (TCB). Pathways shown were shorter than or equal in length compared to the known pathway and did not involve any novel intermediates. Fum, fumarate; Glyc, glycolate; Succ, succinate. Shading indicates the known pathway and portions of the pathway outlined in dotted boxes show reactions that were decomposed into two enzyme reaction rules. Enzyme classes in dashed boxes denote the reactions common to all of the pathways.

Figure 5

Thermodynamic landscape of alternative novel biodegradation pathways for 1,2,4-TCB. The fifteen pathways examined in-depth are shown: dotted line, 8 reaction steps; solid line, 9 reaction steps; dashed line, 10 reaction steps. Blue lines represent pathways that correspond to overall reaction [1]; Black lines represent pathways with overall reaction [2]. Shaded gray line indicates the free energy landscape of the known pathway.