Biology subjects

Voldborg, B.

Publications and source records attributed to Voldborg, B..

2 recordsLinked to original sources

bioRxiv2026

The Role of Glycan Structures in Modulating GM-CSF Bioactivity: Insights from Glycoengineering

Granulocyte-macrophage colony-stimulating factor (GM-CSF) is a glycoprotein cytokine with therapeutic potential in cancer and neutropenia treatment. While glycosylation of GM-CSF reduces immunogenicity and enhances serum bioavailability, it can also diminish receptor binding and bioactivity. Based on transcriptomic analysis of human T lymphocytes reported previously, GM-CSF-producing cells exhibit elevated expression of Alpha-1,6-Mannosylglycoprotein 6-Beta-N-Acetylglucosaminyltransferase (MGAT5), which encodes N-acetylglucosaminyltransferase V, an enzyme involved in N-glycan branching. Given this role of MGAT5 in glycosylation, we produced GM-CSF variants using glycoengineered Chinese hamster ovary cells to generate diverse glycoforms and assessed their bioactivity. Testing their activity on TF-1 cell proliferation, we found that decreases in GM-CSF N-glycan branching significantly suppressed its activity. These findings underscore the importance of glycosylation in modulating the efficacy and safety of GM-CSF-based therapeutics, suggesting that precise glycoengineering may be key to optimizing GM-CSF performance in clinical applications.

bioengineering↗

bioRxiv2018

Genome-scale reconstructions of the mammalian secretory pathway predict metabolic costs and limitations of protein secretion

In mammalian cells, >25% of synthesized proteins are exported through the secretory pathway. The pathway complexity, however, obfuscates its impact on the secretion of different proteins. Unraveling its impact on diverse proteins is particularly important for biopharmaceutical production. Here we delineate the core secretory pathway functions and integrate them with genome-scale metabolic reconstructions of human, mouse, and Chinese hamster cells. The resulting reconstructions enable the computation of energetic costs and machinery demands of each secreted protein. By integrating additional omics data, we find that highly secretory cells have adapted to reduce expression and secretion of other expensive host cell proteins. Furthermore, we predict metabolic costs and maximum productivities of biotherapeutic proteins and identify protein features that most significantly impact protein secretion. Finally, the model successfully predicts the increase in secretion of a monoclonal antibody after silencing a highly expressed selection marker. This work represents a knowledgebase of the mammalian secretory pathway that serves as a novel tool for systems biotechnology.

systems biology↗