Whole-genome analysis and molecular docking reveal how nucleotide variations in the aprX gene drive the differential spoilage potential of Pseudomonas in milk.
Aug 2026· Food microbiology· Vol 141, pp.
105262
· 0 citations· 52 references
Medicine
TL;DR
At Atomic-level analysis, whole-genome sequencing, phenomics, and computational structural biology are integrated to elucidate how nucleotide variations in the aprX gene drive differences in spoilage potential-a fundamental question in the microbiology of food borne isolates.
Abstract
Pseudomonas species are major psychrotrophic spoilage agents of dairy products, yet the molecular basis of spoilage variability among closely related strains remains poorly understood. This study integrates whole-genome sequencing, phenomics, and computational structural biology to elucidate how nucleotide variations in the aprX gene drive differences in spoilage potential-a fundamental question in the microbiology of food borne isolates. Phylogenetic analysis of the aprX operon from representative Pseudomonas isolates classified them into five distinct types. Cold-storage simulation experiments identified strains TA0410 and TA0601 as potent spoilers, exhibiting rapid pH decline, reduced colloidal stability, and complete degradation of κ-casein. Molecular docking revealed that the AprX proteases from these strains formed stronger binding and more stable hydrogen-bond networks with the κ-casein cleavage site compared to weak spoilers. Atomic-level analysis further demonstrated that specific single-nucleotide polymorphisms (SNPs) induce key amino acid substitutions within functionally critical motifs-such as 'HEIGHTLGLDH' in the catalytic domain and the novel conserved motif 'SVMSY' in the substrate-binding region. These substitutions directly modulate enzyme activity by altering electrostatic and hydrophobic interactions between AprX and its ligand. Notably, the 'SVMSY' motif, consistently present in high-spoilage strains, is a precise theoretical target for developing next-generation molecular detection technologies that accurately distinguish spoilage risks. This study provides a mechanistic link between genomic variation and phenotypic outcomes, offering actionable targets for dairy quality control.
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