Designing new enzymes for sustainable fertilizer

$122,000
Raised of $122,000 Goal
100%
Funded on 10/21/23
Successfully Funded
  • $122,000
    pledged
  • 100%
    funded
  • Funded
    on 10/21/23

About This Project

Agriculture relies on phosphorous (P) fertilizer, which generates algae blooms and significant GHG emissions. Phytase enzymes release P from phytate, the primary source of organic P in soil and manure. Phytases function inefficiently at neutral pH and low temperature, and most phytate is inaccessibly bound to minerals. Using automation-enhanced protein design and testing, we will generate phytase enzymes optimized to increase bioavailable P in soil and manure, reducing the need for P fertilizer.

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What is the context of this research?

Global agriculture relies on synthetic fertilizers to deliver bioavailable nutrients to growing plants. Unlike nitrogen, phosphorus (P) is not cycled through the atmosphere, with most P locked in minerals that take >104 years to be released by geologic processes (1). Over 70% of P minerals used for fertilizer are in a single country, Morocco, and the global extraction and transport contributes >1 kg CO2 per kg of fertilizer (2,3). P fertilizer runoff also causes water eutrophication in ecosystems around the world (1). Inorganic P resources are finite, harm the environment, and demand is steadily increasing (3). A renewable, accessible source of bioavailable P would improve food security and reduce the environmental impact of agriculture worldwide.

What is the significance of this project?

Phytase enzymes release P from phytate, the primary reservoir of organic P in soil and manure, making it bioavailable to plants and microbes (4). Protein engineering of phytases has focused on function at low pH or high temperature during grain processing and animal digestion (5), not for the neutral/alkaline pH and lower temperature of soil and manure. Most phytate is also inaccessible to phytases, as phytate readily forms stable complexes with minerals (4). Protein design (PD) enables the creation of new-to-nature enzymes with desired properties (6,7). By harnessing PD to optimize phytase activity and stability in soil and manure, engineered phytase could reduce global dependency on synthetic P fertilizer.

What are the goals of the project?

As manure treatments have established enzyme additives (8), and the environment is more controlled versus soil, our goals are focused on this application. Using recent PD tools (9), new-to-nature phytases will be designed then filtered in silico based on predicted physiochemical properties. Candidate phytases will be expressed using a microbial chassis, then screened in high-throughput using purpose-built laboratory automation. Phytases will be characterized across a matrix of experimental conditions to determine success of these goals:

- >80% activity at pH (6-8) and temperatures (15-50oC) found during manure treatment (8)

- >50% activity after 7 days at 37oC, to evaluate catalytic cycles until replacement (10)

- Ability to release bioavailable P from mineral-phytate complexes (4)

Budget

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Total budget listed. Detailed breakdown in the Solution Statement.

Project Timeline

Total of six months, split between in silico and laboratory experiments (Dec 2023-June 2024). Two months will be dedicated to protein design work, to create and apply an in silico workflow for generating and filtering novel phytase enzymes based on predicted function. Over the following four months, designed phytases will be expressed using a microbial host, and protein function will be characterized across relevant experimental conditions.

Dec 15, 2023

Literature and metagenomics review

Jan 26, 2024

Protein design and analysis pipeline

Feb 09, 2024

Design and ranking of phytases

Feb 16, 2024

Design of cloning and sequence diversity methods, order synthetic phytase genes

Mar 15, 2024

Cloning of phytase genes, generate sequence diversity, test expression in microbial host

Meet the Team

Benjamin Scott
Benjamin Scott
Platform Lead, Engineering Biology

Affiliates

Global Institute for Food Security
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Megha Bajaj
Megha Bajaj
Business Lead, Engineering Biology

Affiliates

Global Institute for Food Security
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Nikki Forsberg
Nikki Forsberg
Laboratory Technician, Engineering Biology & Omics and Precision Agriculture Laboratory

Affiliates

Global Institute of Food Security
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Aren Boulet
Aren Boulet
Bioinformatic Technician, Data Management and Analytics

Affiliates

Global Institute for Food Security
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Josh Pickering
Josh Pickering
Laboratory Automation Engineer, Engineering Biology

Affiliates

Global Institute for Food Security
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Kevin Koh
Kevin Koh
Platform Lead, Data Management and Analytics

Affiliates

Global Institute for Food Security
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Team Bio

The Global Institute for Food Security is a not-for-profit research institute in Saskatoon, Canada. Our vision is a world where everyone has access to safe and nutritious food. This team is comprised of experts from our Data Management & Analytics and Engineering Biology platforms, who are passionate about creating agricultural enzymes to make food production more sustainable.

Benjamin Scott

Dr. Benjamin Scott has over 10 years’ experience in protein engineering and laboratory automation. His research has focused on high-throughput approaches to protein engineering, which involved generating and screening large libraries of protein variants for desired function, using a variety of directed evolution approaches. He has extensive experience with laboratory automation which is directly relevant to the proposed project, including for high-throughput microbial growth, characterization, and DNA assembly and extraction.

Megha Bajaj

Megha holds a PhD in Cellular and Molecular Biology. She has over 7 years’ experience in business development and intellectual property management. She has successfully set up productive collaborations with multiple stakeholders, negotiated legal and financial terms in revenue bearing agreements, and helped researchers commercialize their inventions. At GIFS, Megha leads the business development initiatives for the engineering biology platform and is responsible for industry outreach, marketing, contract and project management, and supporting grant writing.

Nikki Forsberg

Nikki is a passionate biochemist with 7 years of hands-on laboratory experience in biomedical research. Her versatile skills span diverse fields, including biomarker discovery, protein interaction networks, and vaccine development. She has designed workflows and protocols in the realm of proteomics. Nikki has joined GIFS with the desire to work near the frontier of engineering biology, with the goal of developing safe and sustainable methods regarding food security.

Aren Boulet

Aren has amassed extensive research experience in characterizing proteomic changes stemming from rare genetic mutations. By employing techniques such as site-directed mutagenesis, affinity purification, and fusion protein expression across bacterial, yeast, and mammalian biological systems, Aren has successfully characterized novel protein functions and interactions. Leveraging this foundation in genomics and proteomics, Aren has transitioned into next-generation sequencing project development and bioinformatic analysis. Presently, Aren actively applies his expertise to support large-scale sequencing projects at GIFS, making contributions to data processing and analysis.

Josh Pickering

Josh has over 7 years of general laboratory and research experience in topics ranging from cancer, nutrition, ageing, and genome topology. His background also includes 3 years of experience in fermentation utilizing over 20 types of yeast and several years experience in high throughput automation. He brings experience with everything from E. coli, to yeast, to multiple species of plants, and to human cancer and primary tissue cell culture.

Kevin Koh

Kevin Koh received his BSc (Hons) in Biochemistry and Software Engineering in 2002, and his MSc in Computer Science from the University of Saskatchewan in 2008. Kevin has more than 15 years of experience in building data analytics pipelines for large-scale genomics and genetics projects including reference and pan-genome sequencing of major and niche crops. He enjoys building software algorithms and tools for analysis of big data and is experienced working in multidisciplinary plant genomics and bioinformatics research teams.


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