Predicting the fitness of a CHO cell
DNA methylation analysis of specific CpG sites in CHO cells predicts phenotypes of interest, addressing inefficiencies in CHO cell fitness assessment and ensuring stable protein production through penalized regression.
AU2024386260A1Pending Publication Date: 2026-07-09EVONIK OPERATIONS GMBH
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Patent Information
- Application Number
- AU2024386260
- Authority / Receiving Office
- AU · AU
- Patent Type
- Applications
- Current Assignee / Owner
- Priority Date
- 2023-11-24
- Filing Date
- 2024-11-13
- Publication Date
- 2026-07-09
AI Technical Summary
Technical Problem
Current methods for assessing CHO cell fitness for bioprocessing are time-consuming, non-specific, and fail to account for the interplay between cell genotype and environment, leading to inefficiencies and financial losses in protein production.
Method used
A method using DNA methylation analysis of specific CpG sites in CHO cells to predict phenotypes of interest through penalized regression, providing a biomarker for cell fitness that ensures stability and efficiency in protein production.
Benefits of technology
Enables accurate, early-stage identification of CHO cells suitable for genetic modifications and protein production, ensuring consistency and reducing financial losses by quantitatively assessing cell fitness.
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Abstract
The present invention relates to a method of establishing a biomarker for a first phenotype of interest of a CHO cell, the method comprising the steps of: (a) determining methylation values of CpG sites within genomic DNA obtained from a population of CHO cells that are a representation of the first phenotype of interest and are part of the training samples, (b) defining a set of specific CpG sites having reliable methylation values in the training samples of step (a); and (c) performing a penalized regression using the methylation values of step (b) as input and phenotype of interest correlated to the training samples as dependent variable, by applying a penalized regression model; thereby obtaining the specific CpG sites with corresponding weighting factors and intercept of the linear model equation as parameters defining the biomarker for the first phenotype of interest.
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