Philipp Spahn, Ph.D.

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In my research, I like to combine computational approaches with cellular and molecular biology. My current interest lies in the quantification and engineering of genomic stability in CHO cells.


Improving genomic stability in CHO cells

CHO cells are the primary production host of therapeutic proteins. However, their inherent genomic instability poses a problem for protein manufacturing since it negatively affects culture viability, productivity and product quality. The primary cause of genomic instability is deficient DNA repair, in particular repair of double-strand breaks. This project aims at quantification of DNA repair capabilities in various CHO cell lines, and the identification of targets whose genetic engineering has a potential to enhance DNA repair, improve genomic stability, and thereby greatly facilitate industrial protein manufacturing.


Automated analysis of sequencing data from CRISPR/Cas9 screens

CRISPR/Cas9 screens have become an extremely popular tool for biomedical discovery, but processing and analysis of the sequencing data produced by these screens pose a significant challenge for researchers lacking computational support. In this project, we developed PinAPL-Py, an online workflow for the analysis of such screens that can be operated through easy drag-and-drop and run without bioinformatic expertise.


Unraveling the genetic control of Heparan-sulfate proteoglycans using genome-wide screens

Heparan-sulfate proteoglycans (HSPGs) are major components of the extracellular matrix and involved in a wide variety of cellular functions, e.g. as co-receptors for EGF-related signaling pathways. Although its biosynthesis is fairly well understood, very little is known about its genetic control and tissue-specific expression. In collaboration with the Esko laboratory, we utilize genome-wide CRISPR/Cas9 knock-out screens to find genes controlling HSPG assembly and modification.

Glycoengineering in CHO cells

Glycosylation of therapeutic proteins is a critical quality attribute in their manufacturing due to its role in protein folding, stability, and efficacy. Since glycosylation does not follow a direct template, but instead is the result of a stochastic reaction network in the Golgi, its tailoring and experimental manipulation (“glycoengineering”) is a primary challenge in industrial production. This project aims at the development and application of stochastic glycosylation models to pave the way for a more rational and efficient approach to glycoengineering.



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contact: pspahn at eng dot ucsd dot edu