SBIR/STTR Research Award

Improving gene expression via Massively Parallel Synonymous Codon Variant Screening

Award identifier 6e1161d5c7d7e62115ed6d652e2e389668d4fa9d2c8705fbf900ea563e4b580eAwarding agency Department of Health and Human Services · National Institutes of Health

Award amount

$298,634

Program and phase

SBIR · Phase I

Award year

2020

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Award details

Awarding agency
Department of Health and Human Services
Branch
National Institutes of Health
Recipient company
Planet Biotechnology Incorporated
Proposal award date
2020-03-01
Contract end date
2021-02-28
UEI
KTJKPBE2H5H3
Solicitation number
PA18-574
Topic code
400

Research abstract

Our overall goal is to reduce to practice an innovative new method for empirically identifying the optimal codon usage for any gene where the intent is to maximize protein accumulation, in either heterologous or homologous expression systems. In this Phase I project we explain how this method will work and demonstrate its usefulness by identifying highly expressing codon variants of a human Factor IX gene in both plant and mammalian expression systems. Our method is based on the observation that there is a high degree of correlation between accumulation of mRNA and protein in our plant transient expression system and there is literature support for such a correlation in mammalian and yeast systems as well. We recently found that when four divergent synonymous codon variants of one immunoglobulin heavy chain were expressed together in the same plant, the relative abundance of the four mRNAs was a close match for their relative abundance when expressed separately. From this we conceived of a new method that we call Massively Parallel Synonymous Codon Variant Screening (MPSCVS), which should allow the comparison of a very large number of different gene variants in a single experiment.Demonstration of our system will begin with a library of approximately 59,000 synonymous codon variants of Factor IX in an adeno-associated virus (AAV) gene therapy vector. We will use the AAV library to transduce the livers of mice in vivo. RNA will be isolated from the mouse livers. We will subclone an aliquot of the library into a plant expression vector and use that to transform Agrobacterium tumefaciens, which is used for plant (Nicotiana benthamiana) transformation. We will express the library transiently in tobacco leaves, harvest leaf tissue and isolate total RNA. The mRNA from both plants and human cells will be used to produce double stranded cDNA, which will be “counted” by next generation sequencing to identify the most abundant mRNAs in both systems. Clones of high-expressing codon variants will be tested for protein and RNA expression individually in the appropriate expression system. We will then analyze the degree of correlation between RNA and protein expression and determine the overall efficiency of MPSCVS in identifying the best expressing variants.Improving protein expression is of considerable practical importance in every recombinant protein production platform, and many researchers have found that codon usage and its impact on mRNA levels plays a crucial role in maximizing expression. We have developed an innovative new method for empirically identifying the optimal codon usage for any gene where the intent is to maximize protein accumulation, in either heterologous or homologous expression systems. Commercialization of this system will impact recombinant protein production for recombinant therapeutics, gene therapy, vaccines and any application that depends on optimizing protein production in vitro or in vivo.

Technology keywords

Not reported

Other awards by this recipient

Verified by the same UEI. These are other public SBIR/STTR award pages, not a merged company record.

Awards with the same topic code

Verified by an exact topic code match. This is not a text-similarity match.

Research funding history

38 SBIR/STTR records share this UEI (2000–2024). Reported award amounts total $26,790,475. Reported amounts are not federal obligations.

Phases: Phase I, Phase II

Agencies: Department of Health and Human Services, Department of Defense, Department of Agriculture

Agency intelligence

Department of Health and Human Services

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