{ "id": "AIBD-0045", "title": "FAST-PETase, a machine-learning-engineered enzyme, depolymerised post-consumer PET and was reused by an independent lab", "summary": "A 3D-CNN ensemble engineered FAST-PETase, which degraded 51 post-consumer PET products in a week; Texas A&M later reported complete depolymerisation using it with MHETase.", "date_observed": "2022-04-27", "date_basis": "unassessed", "date_precision": "unassessed", "benefit_status": null, "source_collection": null, "source_entry": null, "account": "In a Nature paper of 27 April 2022, researchers at the University of Texas at Austin used a structure-based machine-learning algorithm. The algorithm, an ensemble of three three-dimensional convolutional neural networks, selected stabilizing mutations in a polyethylene terephthalate (PET) hydrolase, producing FAST-PETase. They reported that untreated post-consumer PET from 51 different thermoformed products was almost completely degraded within one week at 50 degrees Celsius. The enzyme outperformed wild-type and engineered alternatives between 30 and 50 degrees Celsius. They closed the loop by resynthesizing PET from the recovered monomers. An independent group at Texas A&M University used FAST-PETase together with MHETase in a yeast whole-cell biocatalyst (Environmental Science and Technology Letters, 19 March 2025). It reported complete depolymerization of a PET film in seven days at 30 degrees Celsius.", "category": "benefit created", "unexpected": false, "purpose": "Use a structure-based machine-learning model to predict stabilizing mutations that make a PET hydrolase active and robust at moderate temperatures.", "system": "Structure-based machine-learning mutation predictor (ensemble of three 3D convolutional neural networks) applied to PETase engineering", "model_version": "MutCompute", "developer": "University of Texas at Austin (Alper and Ellington groups)", "deployer": "University of Texas at Austin; subsequently Texas A&M University", "location": "Austin, Texas, United States", "domain": "Enzyme engineering / plastic degradation", "segment": null, "benefit_type": "Improved Environmental Sustainability", "taxonomy_note": null, "registry_ids": {}, "ratings": [ { "group": "organizational", "depth": 1, "reason": "A laboratory-scale enzyme that an independent group could pick up and reuse successfully; the sources report bench work, not production deployment." }, { "group": "societal", "depth": 1, "reason": "Complete depolymerization of untreated post-consumer PET was shown only in the laboratory in both the original and the independent study. Neither source reports industrial-scale recycling." } ], "ai_role": { "status": "assessed", "statement": "The machine-learning model chose which mutations to introduce. The designers measured the enzymatic activity experimentally. A separate group at another institution later reproduced it, using FAST-PETase as a component of its own system." }, "evidence": [ { "kind": "peer-reviewed study", "citation": "Lu H, Diaz DJ, Czarnecki NJ, et al. (2022). Machine learning-aided engineering of hydrolases for PET depolymerization. Nature.", "title": "Machine learning-aided engineering of hydrolases for PET depolymerization", "url": "https://www.nature.com/articles/s41586-022-04599-z", "date": "2022-04-27", "written_by": "makers", "quote": "untreated, postconsumer-PET from 51 different thermoformed products can all be almost completely degraded by FAST-PETase in 1 week" }, { "kind": "peer-reviewed study", "citation": "Gulati S, Sun Q (2025). Complete Enzymatic Depolymerization of Polyethylene Terephthalate (PET) Plastic Using a Saccharomyces cerevisiae-Based Whole-Cell Biocatalyst. Environ Sci Technol Lett.", "title": "Complete Enzymatic Depolymerization of Polyethylene Terephthalate (PET) Plastic Using a Saccharomyces cerevisiae-Based Whole-Cell Biocatalyst", "url": "https://pmc.ncbi.nlm.nih.gov/articles/PMC11984091/", "date": "2025-03-19", "written_by": "deployer", "quote": "a TPA yield of 4.95 mM was obtained after incubation with the PET film for 7 days" } ], "replication": { "produced_by": [ "A structure-based machine-learning model trained to predict stabilizing mutations", "A wild-type PET hydrolase as the starting scaffold", "Untreated post-consumer PET tested at moderate temperatures" ], "must_hold": [ "Moderate reaction temperatures (roughly 30–50 degrees Celsius)", "Amorphous or thermoformed PET substrate", "Enzyme expressed and purified or displayed at sufficient activity" ], "echoes": [ { "date": "2025-03-19", "setting": "Texas A&M University, FAST-PETase co-immobilised on a scaffoldin in a yeast whole-cell biocatalyst", "model_version": null, "outcome": "recurred", "source": "Gulati S, Sun Q. Environ Sci Technol Lett 2025. https://pmc.ncbi.nlm.nih.gov/articles/PMC11984091/" } ] }, "paired_incident": null, "headline": "FAST-PETase degrades 51 post-consumer PET products in a week", "metric": "degraded 51 post-consumer PET products in a week", "comparator": { "against": "wild-type PETase and previously engineered PET hydrolases", "before": null, "after": "superior PET-hydrolytic activity relative to both wild-type and engineered alternatives between 30 and 50 °C and a range of pH levels", "basis": "measured", "quote": "Our mutant and scaffold combination (FAST-PETase: functional, active, stable and tolerant PETase) contains five mutations compared to wild-type PETase (N233K/R224Q/S121E from prediction and D186H/R280A from scaffold) and shows superior PET-hydrolytic activity relative to both wild-type and engineered alternatives between 30 and 50 °C and a range of pH levels.", "url": "https://www.nature.com/articles/s41586-022-04599-z" }, "later": { "status": "persisted", "date": "2025-03-19", "note": "An independent Texas A&M group adopted FAST-PETase in a yeast whole-cell biocatalyst and reported complete depolymerization of a PET film in seven days.", "quote": "Co-immobilization of FAST-PETase and MHETase on a surface-displayed trifunctional scaffoldin led to complete depolymerization of PET into its constituent monomers TPA and EG, with no accumulation of reaction intermediates. In our system, the presence of MHETase along with FAST-PETase led to a nearly 5-fold boost in product formation, and attachment of FAST-PETase at two sites on the trifunctional scaffoldin further boosted yields by up to 1.8-fold. TPA yields of 4.95 mM were obtained in 7 days on an amorphous PET film with no pretreatment requirement.", "url": "https://pmc.ncbi.nlm.nih.gov/articles/PMC11984091/" }, "value": null, "developer_country": "United States", "deployer_country": "United States", "unrated_because": null, "brief_notes": null, "brief": null, "revisions": [ { "date": "2026-10-20", "change": "Record drafted from the cited sources.", "source": null, "editor": "AIBD" }, { "date": "2026-10-20", "change": "Corrected the temperature of the 51-product degradation experiment to 50 degrees Celsius (30 to 50 degrees Celsius is the range over which FAST-PETase outperformed alternatives, a different claim), credited the complete depolymerisation to FAST-PETase co-immobilised with MHETase rather than to FAST-PETase alone, and used the exact title of the ESTL paper.", "source": "Lu H, et al. Nature 2022 (https://www.nature.com/articles/s41586-022-04599-z); Gulati S, Sun Q. Environ Sci Technol Lett 2025 (https://pmc.ncbi.nlm.nih.gov/articles/PMC11984091/)", "editor": "AIBD" }, { "date": "2026-10-21", "change": "Added what the benefit is measured against, the model version from the cited sources.", "source": "https://www.nature.com/articles/s41586-022-04599-z; https://www.nature.com/articles/s41586-022-04599-z", "editor": "AIBD" }, { "date": "2026-10-21", "change": "Country of the developer and the deployer added from the organization's own site or a registry.", "source": "https://en.wikipedia.org/wiki/University_of_Texas_at_Austin; https://en.wikipedia.org/wiki/University_of_Texas_at_Austin", "editor": "AIBD" }, { "date": "2026-10-21", "change": "Prose pass: a rating reason, account, the replication conditions, the system's part rewritten in shorter sentences with abbreviations expanded; facts, figures and quotations unchanged.", "source": null, "editor": "AIBD" } ], "confidence": "claimed", "shade": "low", "claim_status": "The deployer's account", "claim_basis": "Sources: the makers' peer-reviewed study and the deployer's peer-reviewed study. The cited evidence includes no independent source and no finding by a regulator or court.", "profile": { "case_id": "AIBD-0045", "catalog_version": "1.0.0", "source_fingerprint": "d86cb258dc3a92e131233909ca6e1de0f131fae1027df04847983abbe5e9d70d", "collection_refs": [ { "collection_id": "aibd", "version": "snapshot-8bf7cfec9cb185aa" }, { "collection_id": "aibd", "version": "2026-10-25" } ], "source_ids": [ "AIBD-0045-source-0001", "AIBD-0045-source-0002" ], "families": { "strategic assessments": { "state": "not_assessed", "review_state": "not_assessed", "coverage": "partial", "record_ids": [] }, "evaluations": { "state": "not_assessed", "review_state": "not_assessed", "coverage": "partial", "record_ids": [] }, "monetary observations": { "state": "not_assessed", "review_state": "not_assessed", "coverage": "partial", "record_ids": [] }, "institutional decisions": { "state": "not_assessed", "review_state": "not_assessed", "coverage": "partial", "record_ids": [] } }, "fields": { "actors[]": { "state": "value_present", "value": { "kind": "record_fields", "fields": { "developer": "University of Texas at Austin (Alper and Ellington groups)", "deployer": "University of Texas at Austin; subsequently Texas A&M University" } }, "provenance": { "kind": "legacy_record", "basis": "Preserved from the existing AIBD record; external sources were not rechecked.", "record_fields": [ "developer", "deployer" ], "source_refs": [] }, "review_state": "record_mapped", "coverage": "partial" }, "actors[].ownership_control": { "state": "not_assessed", "review_state": "not_assessed", "coverage": "partial" }, "ai_contribution": { "state": "value_present", "value": { "kind": "record_fields", "fields": { "ai_role": { "status": "assessed", "statement": "The machine-learning model chose which mutations to introduce. The designers measured the enzymatic activity experimentally. A separate group at another institution later reproduced it, using FAST-PETase as a component of its own system." } } }, "provenance": { "kind": "legacy_record", "basis": "Preserved from the existing AIBD record; external sources were not rechecked.", "record_fields": [ "ai_role" ], "source_refs": [] }, "review_state": "record_mapped", "coverage": "partial" }, "ai_relationship": { "state": "value_present", "value": { "kind": "record_fields", "fields": { "category": "benefit created", "ai_role": { "status": "assessed", "statement": "The machine-learning model chose which mutations to introduce. The designers measured the enzymatic activity experimentally. A separate group at another institution later reproduced it, using FAST-PETase as a component of its own system." } } }, "provenance": { "kind": "legacy_record", "basis": "Preserved from the existing AIBD record; external sources were not rechecked.", "record_fields": [ "ai_role", "category" ], "source_refs": [] }, "review_state": "record_mapped", "coverage": "partial" }, "assessments[].alternatives": { "state": "not_assessed", "review_state": "not_assessed", "coverage": "partial" }, "assessments[].assessor_date": { "state": "not_assessed", "review_state": "not_assessed", "coverage": "partial" }, "assessments[].depth": { "state": "value_present", "value": { "kind": "record_fields", "fields": { "ratings": [ { "group": "organizational", "depth": 1, "reason": "A laboratory-scale enzyme that an independent group could pick up and reuse successfully; the sources report bench work, not production deployment." }, { "group": "societal", "depth": 1, "reason": "Complete depolymerization of untreated post-consumer PET was shown only in the laboratory in both the original and the independent study. Neither source reports industrial-scale recycling." } ] } }, "provenance": { "kind": "legacy_record", "basis": "Preserved from the existing AIBD record; external sources were not rechecked.", "record_fields": [ "ratings" ], "source_refs": [] }, "review_state": "record_mapped", "coverage": "partial" }, "assessments[].display_confidence": { "state": "value_present", "value": { "kind": "structured", "data": { "confidence": "low", "evidence_word": "claimed", "claim_status": "The deployer's account", "basis": "Sources: the makers' peer-reviewed study and the deployer's peer-reviewed study. 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EG, with no accumulation of reaction intermediates. In our system, the presence of MHETase along with FAST-PETase led to a nearly 5-fold boost in product formation, and attachment of FAST-PETase at two sites on the trifunctional scaffoldin further boosted yields by up to 1.8-fold. TPA yields of 4.95 mM were obtained in 7 days on an amorphous PET film with no pretreatment requirement.", "url": "https://pmc.ncbi.nlm.nih.gov/articles/PMC11984091/" } } }, "provenance": { "kind": "legacy_record", "basis": "Preserved from the existing AIBD record; external sources were not rechecked.", "record_fields": [ "later" ], "source_refs": [] }, "review_state": "record_mapped", "coverage": "partial" }, "human_oversight": { "state": "not_assessed", "review_state": "not_assessed", "coverage": "partial" }, "id": { "state": "value_present", "value": { "kind": "record_fields", "fields": { "id": "AIBD-0045" } }, "provenance": { "kind": "legacy_record", "basis": "Preserved from the existing AIBD record; external sources were not rechecked.", "record_fields": [ "id" ], "source_refs": [] }, "review_state": "record_mapped", "coverage": "partial" }, "infrastructure_dependencies[]": { "state": "not_assessed", "review_state": "not_assessed", "coverage": "partial" }, "outcomes[].beneficiaries": { "state": "not_assessed", "review_state": "not_assessed", "coverage": "partial" }, "outcomes[].beneficiary_count": { "state": "not_assessed", "review_state": "not_assessed", "coverage": "partial" }, "outcomes[].benefit_type": { "state": "value_present", "value": { "kind": "record_fields", "fields": { "benefit_type": "Improved Environmental Sustainability" } }, "provenance": { "kind": "legacy_record", "basis": "Preserved from the existing AIBD record; external sources were not rechecked.", "record_fields": [ "benefit_type" ], "source_refs": [] }, "review_state": "record_mapped", "coverage": "partial" }, "outcomes[].claim": { "state": "value_present", "value": { "kind": "record_fields", "fields": { "account": "In a Nature paper of 27 April 2022, researchers at the University of Texas at Austin used a structure-based machine-learning algorithm. The algorithm, an ensemble of three three-dimensional convolutional neural networks, selected stabilizing mutations in a polyethylene terephthalate (PET) hydrolase, producing FAST-PETase. They reported that untreated post-consumer PET from 51 different thermoformed products was almost completely degraded within one week at 50 degrees Celsius. The enzyme outperformed wild-type and engineered alternatives between 30 and 50 degrees Celsius. They closed the loop by resynthesizing PET from the recovered monomers. An independent group at Texas A&M University used FAST-PETase together with MHETase in a yeast whole-cell biocatalyst (Environmental Science and Technology Letters, 19 March 2025). It reported complete depolymerization of a PET film in seven days at 30 degrees Celsius.", "benefit_type": "Improved Environmental Sustainability" } }, "provenance": { "kind": "legacy_record", "basis": "Preserved from the existing AIBD record; external sources were not rechecked.", "record_fields": [ "account", "benefit_type" ], "source_refs": [] }, "review_state": "record_mapped", "coverage": "partial" }, "outcomes[].distribution": { "state": "not_assessed", "review_state": "not_assessed", "coverage": "partial" }, "outcomes[].duration": { "state": "not_assessed", "review_state": "not_assessed", "coverage": "partial" }, "outcomes[].id": { "state": "not_assessed", "review_state": "not_assessed", "coverage": "partial" }, "outcomes[].stakeholder_group": { "state": "value_present", "value": { "kind": "record_fields", "fields": { "ratings": [ { "group": "organizational", "depth": 1, "reason": "A laboratory-scale enzyme that an independent group could pick up and reuse successfully; the sources report bench work, not production deployment." }, { "group": "societal", "depth": 1, "reason": "Complete depolymerization of untreated post-consumer PET was shown only in the laboratory in both the original and the independent study. 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Nature 2022 (https://www.nature.com/articles/s41586-022-04599-z); Gulati S, Sun Q. 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