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Grant: Project Grant

University of Toronto

$1,216,350.00

Catalyzing a Microplastic-Free Future: Discovering Ultra-Efficient and Safe PET-Degrading Enzymes through AI-Guided Functional Genomics

EF 2024-25

Résumé
Since the mid-20th century, humans have produced 10 billion tonnes of plastic-or the weight of a Mini Cooper for each living person. We utilize these petroleum-based materials for packaging, manufacturing, and medicine, but 79% of plastics end up as waste. There, they break down into microplastics that spread throughout our ecosystem and accumulate in the food chain. Each person ingests about 11,000 microplastics per year, which deposit in our tissues such as the brain, testes, arteries, breast milk, and placenta. Microplastics are toxic. Their large surface area leaches harmful chemicals like BPA, an endocrine disruptor, affecting health and fertility. It is imperative we develop new technologies to reduce the global health burden of microplastics. In 2016, a Japanese team discovered a microbe that breaks down water bottle plastic (PET) using an enzyme called PETase, allowing it to use PET-byproducts for its growth and suggesting microplastics can be detoxified by converting them into biomass. To address the problem of global microplastic contamination, we combine ultra large-scale computing and artificial intelligence (AI) with high-throughput robotics and molecular assays to identify more efficient and safe PET-degrading enzymes. We re-analyze 100 million gigabytes of public DNA sequencing data to uncover millions of new potential plastic-degrading enzymes. We develop an AI model to predict which enzymes are active. Then, we will synthesize and test thousands of enzymes, and test that the enzymatic byproducts are safe for human cells. We will continually RECYCLE data to improve the AI model, which will guide us in designing our high-throughput experiments. This approach will REDUCE experimental costs, and our open-source project will enable researchers worldwide to REUSE these enzymes. Our goal is to enable a new generation of open-source PETase technologies to safely and efficiently mitigate microplastic toxicity, protecting Canadian and Global Health.
Programme
Project Grant
Bénéficiaire
Emplacement
Ontario, Canada
Type de bénéficiaire
Academia
Type
Grant
Source
CIHR Funding Decisions Database

Tel que publié

Id
524449
Name
Babaian Artem
Region
Ontario
Country
Canada
Orgtype
Institution Paid; Research Institution
Instname2
Genetics
Theme2
Biomedical
Prcname2
Genomics: Systems and computational biology
Projecttitle
Catalyzing a Microplastic-Free Future: Discovering Ultra-Efficient and Safe PET-Degrading Enzymes through AI-Guided Functional Genomics
Programtype2
Operating Grants
Orgnameinp2
University of Toronto
Cihramount2
$1,216,350
Cihrequipment2
$0
Programname2
Project Grant
Keyworddelim
Bioinformatics; Functional Genomics; High-Throughput Screening; Microplastics; Yeast
Abstract
Since the mid-20th century, humans have produced 10 billion tonnes of plastic-or the weight of a Mini Cooper for each living person. We utilize these petroleum-based materials for packaging, manufacturing, and medicine, but 79% of plastics end up as waste. There, they break down into microplastics that spread throughout our ecosystem and accumulate in the food chain. Each person ingests about 11,000 microplastics per year, which deposit in our tissues such as the brain, testes, arteries, breast milk, and placenta. Microplastics are toxic. Their large surface area leaches harmful chemicals like BPA, an endocrine disruptor, affecting health and fertility. It is imperative we develop new technologies to reduce the global health burden of microplastics. In 2016, a Japanese team discovered a microbe that breaks down water bottle plastic (PET) using an enzyme called PETase, allowing it to use PET-byproducts for its growth and suggesting microplastics can be detoxified by converting them into biomass. To address the problem of global microplastic contamination, we combine ultra large-scale computing and artificial intelligence (AI) with high-throughput robotics and molecular assays to identify more efficient and safe PET-degrading enzymes. We re-analyze 100 million gigabytes of public DNA sequencing data to uncover millions of new potential plastic-degrading enzymes. We develop an AI model to predict which enzymes are active. Then, we will synthesize and test thousands of enzymes, and test that the enzymatic byproducts are safe for human cells. We will continually RECYCLE data to improve the AI model, which will guide us in designing our high-throughput experiments. This approach will REDUCE experimental costs, and our open-source project will enable researchers worldwide to REUSE these enzymes. Our goal is to enable a new generation of open-source PETase technologies to safely and efficiently mitigate microplastic toxicity, protecting Canadian and Global Health.
Competitiondate
202503
Approvedterm2
5 yrs 0 mth
Pinamesdelim
Babaian, Artem
Approvedterm
5 ans 0 mois
Cihrcontribution2
~ $1,216,350~ $0~