In Silico Elucidation of Direct Versus Indirect Pesticide Inhibition of Ammonia-Oxidizing Microorganisms: A Genome Vulnerability and Network Exposure Analysis

Abstract

Ammonia-oxidizing microorganisms (AOMs) — comprising ammonia-oxidizing archaea (AOA) and bacteria (AOB) — catalyse the rate-limiting first step of nitrification and are the most consistently affected soil microbial indicators of pesticide exposure, as established by the landmark meta-analysis of Swaine et al. (2025). Despite this empirical foundation, the mechanistic basis of differential AOM sensitivity — whether inhibition operates via direct genomic targeting of AOM metabolic machinery or through indirect, network-mediated pathways — has remained unresolved. This study addresses that gap through a three-module, fully in silico computational pipeline applied to ten environmentally relevant pesticides across eight AOM genomes.

Module 1 employed protein BLAST and profile Hidden Markov Model (HMM) analysis to quantify sequence-level similarity between pesticide target genes and AOM genomic content, yielding composite homology scores across four Nitrososphaera (AOA) and four Nitrosomonas (AOB) genomes.

Module 2 integrated homology data with KEGG pathway essentiality weighting and predicted binding affinity corrections to compute a Genome Vulnerability Score (GVS; range 0–1) reflecting direct inhibition potential.

Module 3 constructed a soil co-occurrence network from SparCC-derived correlations in tebuconazole-treated soil, enabling calculation of an Indirect Exposure Score (IES) representing network-propagated inhibitory pressure on AOM.

Integration of GVS and IES into a Combined Risk Score (CRS) and a mechanistic classification framework identified twenty high-priority pesticide × AOM combinations. The highest-risk pairings were glyphosate–AOB (CRS = 0.830; dual direct and indirect mechanisms) and tebuconazole–AOB (CRS = 0.771; dual mechanisms). Critically, tebuconazole–AOA exhibited the maximum dataset IES value (1.000) paired with a low GVS (0.219), providing the first quantitative computational evidence that tebuconazole inhibits archaeal ammonia oxidation via indirect, network-mediated pathways rather than direct genomic binding — thereby resolving the central mechanistic paradox identified in Swaine et al. (2025). Trifloxystrobin was identified as a potential direct AOA inhibitor (GVS_norm = 0.69), while insecticides generated near-zero scores across all AOM combinations. Regulatory implications include mandatory amoA qPCR monitoring and PECsoil re-evaluation for compounds with CRS > 0.55.