A targeted mining workflow is developed that screens exclusively plastic-associated datasets through multi-step bioinformatic filtering—integrating catalytic-motif screening, disulfide-topology validation, structural-similarity scoring, and phylogenetic profiling—to recover high-confidence PETase candidates, resulting in a thermostable enzyme that depolymerizes PET across a broad temperature range.
Abstract
Enzymatic depolymerization of polyethylene terephthalate (PET) has advanced rapidly, alongside a growing volume of publicly available metagenomic data from microbial communities under sustained selective pressure from plastic exposure. Reasoning that such environments may harbor underexplored polyester-active enzymes, we developed a targeted mining workflow that screens exclusively plastic-associated datasets through multi-step bioinformatic filtering—integrating catalytic-motif screening, disulfide-topology validation, structural-similarity scoring, and phylogenetic profiling—to recover high-confidence PETase candidates. Applied to 277 plastic-associated metagenomes, the pipeline yielded 21 non-redundant candidates, several of which combine the Type I catalytic motif (GHSMGGGG) with Type II-like extended loops and secondary disulfide bonds. Two candidates were experimentally confirmed as PET hydrolases; the more active, PET-KR1, is a thermostable enzyme (Tm = 66.5 °C) that depolymerizes PET across a broad temperature range, with markedly higher productivity on powdered than on film substrate. PET-KR1 achieved optimal depolymerization at 50 °C, yet at 60–65 °C, where total yields declined, the product pool was more strongly enriched in the terminal monomer TPA, suggesting that thermostability and substrate accessibility are the primary targets for further engineering. Molecular dynamics simulations revealed a conserved hydrophobic binding network around the catalytic serine, consistent with established PETase substrate-recognition modes, and rational disulfide engineering raised the melting temperature by 3.5 °C, confirming amenability to further optimization. Overall, PET-KR1 expands the scaffold space available for PETase engineering, while the discovery workflow, built entirely on publicly available tools and open-access data, provides a reproducible strategy for metagenomic mining of novel PET-degrading enzymes toward biocatalytic PET recycling.
The “Motif‐to‐Market” framework is proposed, using the M5 motif as a fingerprint to curate functional PETases for efficiency and stability, with distinct pathways for industrial and marine applications.
A metagenomic analysis of soil and rhizosphere samples from the Antarctic vascular plants Deschampsia antarctica and Colobanthus quitensis is conducted, as sources of microbial enzymes with potential PET-hydrolytic activity, demonstrating the diversity of PET-hydrolase-like genes within Antarctic rhizosphere and soil microbiomes.
Valentín Berrios-Farías, Sergio Guajardo-Leiva, Jorge Gallardo-Cerda et al.· Frontiers in Microbiology· 0 citations
ABSTRACT Polyethylene terephthalate (PET) waste represents a major environmental challenge due to limited recycling solutions. Thermophilic bacteria from geothermal environments harbor diverse enzymatic machinery adapted to extreme conditions, offering promising biocatalysts for plastic degradation; however, biological resources from Peru and other South American countries remain scarce. We characterized four bacterial strains isolated from two geothermal sites in Cajamarca, Peru, screened for PET hydrolysis at 50°C. Whole‐genome sequencing using hybrid assembly achieved near‐complete circular genomes. GTDB‐Tk classification identified three species: Neobacillus thermocopriae (strain 19A), Bacillus licheniformis (strains 16P and BI2), and Brevibacillus agri (strain BI8). Quantitative assays revealed that strain 16P achieved the highest mass loss (0.598%), followed by strain BI8 (0.449%). ATR‐FTIR analysis of the incubated sheets showed a significant reduction of the ester carbonyl index in strains 16P, 19A, and BI8 relative to both non‐incubated PET and an abiotic control, whereas strain BI2 did not differ from the controls, indicating preferential modification of ester bonds at the sheet surface. Genome mining and structure‐based homology searches identified multiple candidate enzymes similar to validated PETases and carboxylesterases, including PETase46‐like homologs in strains BI8 and 16P and a terephthalate‐active carboxylesterase homolog in strain 16P. Molecular docking supported the conservation of catalytic geometry and substrate‐binding sites in these candidates. This work represents one of the first systematic genomic and structural characterizations of putative PET‐hydrolases in Peruvian geothermal bacteria, expanding knowledge of extremophile diversity and advancing thermostable enzymes for sustainable plastic waste management.
Marco A Rivera-Jacinto, Claudia Rodríguez-Ulloa, Sara R Briones-Ramírez et al.· MicrobiologyOpen· 0 citations
Xylella fastidiosa is a xylem-limited phytopathogenic bacterium responsible for severe diseases in many economically important crops. Despite its impact, its metabolism remains poorly characterized due to fastidious growth and the limited availability of defined culture media. Here, we reconstruct the first pangenome-based genome-scale metabolic model for X. fastidiosa, integrating conserved metabolic functions from 18 strains across five subspecies. The resulting consensus model, iXfcore, is manually curated and used to explore the species' metabolic capabilities. Model simulations predict minimal nutritional requirements that guide us in the formulation of defined media to assess biofilm formation in vitro, supporting the utility of the resulting predictions. Network analysis also identifies a previously undescribed model-predicted candidate pathway for acetate assimilation, consistent with genomic evidence but requiring further empirical validation. In addition, the model predicts the overproduction of polyamines, compounds linked to virulence in other phytopathogens. Experimental analyses confirm polyamine production in multiple X. fastidiosa strains in vitro, providing the first evidence of polyamine detection in culture supernatants of this phytopathogen. Overall, iXfcore provides a systems-level framework to investigate X. fastidiosa metabolism, generate testable hypotheses on its physiology and putative virulence-associated traits, and support future strain-specific models and studies of host-pathogen metabolic interactions.
Paola Corbín-Agustí, Miguel Álvarez-Herrera, M. Román-Écija et al.· Microbiology Research· 0 citations
Abstract Motivation Functional characterization of microbiomes often relies on the sequencing of metagenomic DNA extracted from environmental samples, with current approaches using metagenome-assembled genomes (MAGs). Although glycoside hydrolases (GHs) are central to carbon cycling, accurate annotation of GHs in metagenomic datasets remains challenging due to the multidomain architecture of carbohydrate-active enzymes and the prevalence of unassembled short reads due to limitations in the MAG-generation process. Results Here, we present CAZyOGH (CAZymes Open-source GH annotation), a curated reference database for the domain-specific identification of 135 protein domains spanning 99 GH families with well-defined catalytic domain signatures. CAZyOGH focuses on individual GH domains, enabling robust annotation of both assembled and unassembled metagenomic data. We validated CAZyOGH by reanalyzing genomes listed in CAZy db, where predicted GH profiles closely matched reported values. Next, we used CAZyOGH to analyze 12 human gut metagenomes and 12 newly sequenced soil microbiomes to reveal environment-specific GH repertoires. By accurately detecting catalytic domains independent of the genomic context, CAZyOGH improves sensitivity and specificity in short-read metagenomic annotation. This framework provides a scalable and reproducible approach to investigate carbohydrate-active enzymes across ecosystems, advancing our capacity to characterize microbial functional potential in global carbon cycling. Availability and implementation CAZyOGH data is available on figshare (https://figshare.com/projects/CAZyO_GH/267770).
N. Griffin, Alison E Hughes, D. S. Erdody et al.· Bioinformatics Advances· 0 citations