Biology subjects

Betenbaugh, M. J.

Publications and source records attributed to Betenbaugh, M. J..

6 recordsLinked to original sources

bioRxiv2026

Exhaustive Isotope Tracing Reveals the Butterfly Effect of Mammalian Producer Cell Line Selection for Biomanufacturing

Chinese hamster ovary (CHO) cells are the dominant platform for recombinant biotherapeutics, yet the impact of producer cell line selection on mammalian cell metabolism remains poorly understood. Here, we performed 41 independent 13C-tracer experiments using uniformly labeled glucose or individual amino acids to comprehensively map carbon utilization in the two principal CHO production platforms: methotrexate-selected CHO-K1 and glutamine synthetase-selected CHO-GS cells. Time-resolved GC-MS analysis revealed distinct metabolic phenotypes spanning central carbon metabolism, amino acid interconversion, lipid biosynthesis, and one-carbon metabolism. CHO-K1 cells exhibited extensive reductive carboxylation and pyruvate carboxylase-mediated anaplerosis, whereas CHO-GS cells redirected glutamate toward glutamine synthesis and relied on asparagine and aspartate to support TCA cycle activity. Isotopomer analysis uncovered substantial intracellular-extracellular cycling of alanine, glycine, glutamate, and serine despite contrasting uptake profiles and quantified differential amino acid contributions to fatty acids and cholesterol. Serine, glycine, and methionine labeling revealed active folate-cycle interconversion in CHO-K1 and enhanced methionine-cycle activity in CHO-GS. Aspartate is identified as a key redox exchange factor and uniquely informative tracer for pathway characterization following glutamine depletion. Together, this exhaustive isotope-tracing framework establishes how producer cell line selection rewires mammalian metabolism and provides a foundation for cell engineering, media optimization, metabolic modeling, and next-generation biomanufacturing.

cell biology↗

bioRxiv2026

Drug-tolerant persister cells reallocate carbon sources to fuel antioxidant metabolism for survival

Therapy resistance is the leading cause of cancer-related deaths. Drug-tolerant persister cells (DTPs) represent a major barrier to cancer cure, mediating resistance through adaptive cell state transitions and driving tumor progression. Here, we investigate metabolic differences between DTPs and drug-sensitive cancer cells using integrated fluxomics. Proteomic profiling and extracellular flux analyses revealed that DTPs upregulate glycolysis and gluconeogenesis while reducing oxidative phosphorylation, indicating a shift in central carbon metabolism. Isotope tracing and metabolic modeling demonstrate that DTPs utilize glucose to fuel the pentose phosphate pathway (PPP) to generate NADPH and metabolize glutamine to provide carbons for the PPP via gluconeogenesis. Integrating our multi-omic datasets into a genome-scale model identified that DTPs sustain antioxidant metabolism by decreasing fluxes of other NADPH-consuming reactions upon in silico PPP knockout. These findings reveal a systems-level shift in DTP metabolism that maintains antioxidant activity for cell survival, highlighting potential new targets and treatment paradigms to overcome therapy resistance.

cancer biology↗

bioRxiv2026

MCBO: Mammalian Cell Bioprocessing Ontology, A Hub-and-Spoke, IOF-Anchored Application Ontology

Mammalian cell-based biopharmaceutical manufacturing generates vast, heterogeneous datasets that remain fragmented due to the lack of a standardized metadata framework. A key challenge in biologics manufacturing is linking bioreactor conditions, cell line characteristics and recombinant product production. A datahub for mammalian cell bioprocessing, integrated by semantic technologies, will serve as a tool to understand and query the connections between these complex datasets. While existing ontologies cover general biological and experimental concepts, they often lack the operational specificity required to harmonize bioreactor conditions, cell line engineering, and product quality metrics. To address this specific gap, we present the Mammalian Cell Bioprocessing Ontology (MCBO), a hub-and-spoke application ontology built on Basic Formal Ontology (BFO) foundations and anchored to the Industrial Ontology Foundry (IOF) Core. MCBO formalizes the process-participant-quality modeling pattern, enabling precise tracking of culture environmental conditions as qualities of the physical culture system. We demonstrate the utility of MCBO through a central datahub populated with 723 curated cell culture process instances and 325 unique bioprocess samples from published studies. The framework is validated against eight competency questions implemented via SPARQL, demonstrating efficient cross-study querying of culture optimization, cell line engineering, and multi-omics integration. By providing a stable, schema-independent substrate for data harmonization, MCBO enables AI agent-powered, human-in-the-loop workflows and facilitates LLM-assisted extraction of structured metadata from legacy records. MCBO is open-source and designed for deployment behind institutional firewalls to support interoperable biomanufacturing intelligence while maintaining intellectual property sensitivity. MCBO is supported by the International Biomanufacturing Network (IBioNe), which aims to accelerate discoveries and developments by providing a network of biomanufacturing training and workforce development to educate the next generation of biomanufacturing experts. MCBO is evaluated using over 700 curated cell culture processes, validated against eight competency questions, and quality-controlled using automated ontology checks. Evaluation results and formal reasoning validation are provided in the Supplementary Materials. Availability: https://github.com/lewiscelllabs/mcbo

bioinformatics↗

bioRxiv2025

A community-consensus reconstruction of Chinese Hamster metabolism enables structural systems biology analyses to decipher metabolic rewiring in lactate-free CHO cells

Genome-scale metabolic models (GEMs) are indispensable for studying and engineering cellular metabolism. Here, we present iCHO3K, a community-consensus, manually-curated reconstruction of the Chinese Hamster metabolic network. In addition to accounting for 11004 reactions associated with 3597 genes, iCHO3K includes 3489 protein structures and structural descriptors for >70% of its 7377 metabolites, enabling deeper exploration of the link between molecular structure and cellular metabolism. We used iCHO3K to contextualize transcriptomics and metabolomics data from a CHO cell line in which lactate secretion is abolished. We found the reduced glycolytic flux and enhanced TCA cycle flux were accompanied by an elevated NADH and PEP levels in these cells, consistent with experimental measurements. Leveraging iCHO3Ks structural annotations, we identified candidate binding interactions of NADH and PEP with glycolytic enzymes showing model-predicted differential flux, suggesting novel allosteric regulation associated with the observed decrease in glucose uptake and glycolysis. Overall, iCHO3K offers a valuable framework for systematic integration of omics data, improved flux predictions, and structure-guided insights, thus advancing CHO cell engineering and enhancing biomanufacturing efficiency.

systems biology↗

bioRxiv2020

Comparison of three glycoproteomic methods for the analysis of CHO cells treated with 1,3,4-O-Bu3ManNAc

Comprehensive analysis of the glycoproteome is critical due to the widespread importance of this post-translational modification to protein function, and difficult because of the tremendous complexity it exhibits. Here we compared three glycoproteomic analysis methods, a recently described chemoenzymatic glycoproteome analysis methods, N-linked glycans and glycosite containing peptides (NGAG), Solid-phase extraction of N-linked glycoproteins (SPEG), and hydrophilic interaction liquid chromatography (HILIC), for the analysis of N-linked glycosites of Chinese hamster ovarian (CHO) cells treated with 1,3,4-O-Bu3ManNAc. The NGAG protocol resulted in substantially increased glycosite identifications over both SPEG and HILIC. Interestingly, while the glycosites identified by SPEG and HILIC overlapped strongly, NGAG identified many glycosites not observed in either of the other two methods. Further, utilizing the enhanced intact glycopeptide identification afforded by the NGAG workflow, we also found that of the sugar analog 1,3,4-O-Bu3ManNAc increases sialylation of proteins secreted by CHO cells, including an ectopically expressed human proteins.

biochemistry↗

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↗