Biology subjects

Hansen, A. H.

Publications and source records attributed to Hansen, A. H..

6 recordsLinked to original sources

bioRxiv2026

Delineating the Transcriptional and Phenotypic Impact from Biotherapeutic Glycoengineering

Glycosylation is critical to biopharmaceutical activity, stability, and pharmacokinetics. While production cells can be engineered to produce better protein glycoforms, glycans decorate thousands of host cell proteins, and it remains unclear how glycoengineering impacts the host cell. To decipher the cell response to glycoengineering, we studied a library of 166 glycoengineered CHO-K1 cell clones representing 54 different glycosyltransferase modifications. Through integrated analysis of glycomics, RNA-Seq, and phenotypic data, we discovered that glycoengineered mutants clustered into three distinct groups (wild-type-like, Moderate, and Substantial) based on their glycosylation patterns. Different glycosyltransferase families exhibited distinct phenotypic signatures: St3gal modifications increased growth rate and cell density, B4galt knockouts affected cell size, and Mgat knockouts enhanced cell viability. Notably, we found specific cellular reprogramming associated with each glycosyltransferase family, including alterations in energy metabolism, stress responses, and DNA repair mechanisms. These findings were validated in an independent set of 30 glycoengineered CHO-S cell lines, expressing a panel of 10 recombinant proteins. Our extensive analysis reveals phenotypic changes resulting from glycoengineering, identifies their molecular bases, and provides crucial insights for controlling glycosylation during therapeutic protein production.

synthetic biology↗

bioRxiv2024

Multiplex genome editing eliminates the Warburg Effect without impacting growth rate in mammalian cells

The Warburg effect is ubiquitous in proliferative mammalian cells, including cancer cells, but poses challenges for biopharmaceutical production, as lactate accumulation inhibits cell growth and protein production. Previous efforts to eliminate lactate production via knockout have failed in mammalian bioprocessing since lactate dehydrogenase has proven essential. However, here we eliminated the Warburg effect in Chinese hamster ovary (CHO) and HEK293 cells by simultaneously knocking out lactate dehydrogenase and regulators involved in a negative feedback loop that typically inhibits pyruvate conversion to acetyl-CoA. In contrast to long-standing assumptions about the role of aerobic glycolysis, Warburg-null cells maintain wildtype growth rate while producing negligible lactate. Further characterization of Warburg-null CHO cells showed a compensatory increase in oxygen consumption, a near total reliance on oxidative metabolism, and higher cell densities in fed-batch cell culture. These cells remained amenable for production of diverse biotherapeutic proteins, reaching industrially relevant titers and maintaining product glycosylation. Thus, the ability to eliminate the Warburg effect is an important development for biotherapeutic production and provides a tool for investigating a near-universal metabolic phenomenon.

bioengineering↗

bioRxiv2024

LeGenD: determining N-glycoprofiles using an explainable AI-leveraged model with lectin profiling

Glycosylation affects many vital functions of organisms. Therefore, its surveillance is critical from basic science to biotechnology, including biopharmaceutical development and clinical diagnostics. However, conventional glycan structure analysis faces challenges with throughput and cost. Lectins offer an alternative approach for analyzing glycans, but they only provide glycan epitopes and not full glycan structure information. To overcome these limitations, we developed LeGenD, a lectin and AI-based approach to predict N-glycan structures and determine their relative abundance in purified proteins based on lectin-binding patterns. We trained the LeGenD model using 309 glycoprofiles from 10 recombinant proteins, produced in 30 glycoengineered CHO cell lines. Our approach accurately reconstructed experimentally-measured N-glycoprofiles of bovine Fetuin B and IgG from human sera. Explanatory AI analysis with SHapley Additive exPlanations (SHAP) helped identify the critical lectins for glycoprofile predictions. Our LeGenD approach thus presents an alternative approach for N-glycan analysis. Graphical Abstract O_FIG O_LINKSMALLFIG WIDTH=200 HEIGHT=136 SRC="FIGDIR/small/587044v1_ufig1.gif" ALT="Figure 1"> View larger version (27K): org.highwire.dtl.DTLVardef@11687e4org.highwire.dtl.DTLVardef@33b146org.highwire.dtl.DTLVardef@1bb6bcborg.highwire.dtl.DTLVardef@1a1e47e_HPS_FORMAT_FIGEXP M_FIG C_FIG

bioengineering↗

bioRxiv2022

Tissue-wide Effects Overrule Cell-intrinsic Gene Function in Cortical Projection Neuron Migration

The mammalian neocortex is composed of diverse neuronal and glial cell classes that broadly arrange in six distinct laminae. Cortical layers emerge during development and defects in the developmental programs that orchestrate cortical lamination are associated with neurodevelopmental diseases. The developmental principle of cortical layer formation is based on concerted radial projection neuron migration, from their birthplace to their final target position. Radial migration occurs in defined sequential steps that are regulated by a large array of signaling pathways. However, based on genetic loss-of-function experiments, most studies have thus far focused on the role of cell-autonomous gene function. Yet, cortical neuron migration in situ is a complex process and migrating neurons traverse along diverse cellular compartments and environments. The role of tissue-wide properties and genetic state in radial neuron migration is however not well understood. Here, we utilized Mosaic Analysis with Double Markers (MADM) technology to either sparsely or globally delete gene function followed by quantitative single cell phenotyping. The MADM-based gene ablation paradigms in combination with computational modeling demonstrated that global tissue-wide effects predominate cell-autonomous gene function albeit in a gene-specific manner. Our results thus suggest that the genetic landscape in a tissue critically impacts the overall migration phenotype of individual cortical projection neurons. In a broader context our findings imply that global tissue-wide effects represent an essential component of the underlying etiology associated with focal malformations of cortical development (FMCD) in particular, and neurological diseases in general. LAY SUMMARYThe assembly of the mammalian brain is a complex process and depends on tightly regulated developmental and genetic programs. The coordinated process of nerve cell (neuron) migration is essential to home neurons into their correct position which is vital for normal brain development. Disturbance of the neuron migration process at any point of development leads to severe brain malformations which result in devastating disease. To date, studies have mainly focused on cell-intrinsic gene functions controlling neuronal migration. Therefore, very little is known about the possible contribution of the cellular surrounding and tissue-wide effects. The scale and nature of such global tissue-wide effects remain completely unclear. We thus established genetic platforms based on Mosaic Analysis with Double Markers (MADM) to visualize and quantify tissue-wide effects in a defined genetic context and at single cell resolution. We found a critical predominant role of the genetic landscape and state of cellular environment affecting overall neuron migration properties. In a broader context our results suggest that global tissue-wide effects are a major component of the underlying etiology of neurological diseases such as focal malformations of cortical development (FMCD).

neuroscience↗

bioRxiv2020

A Chinese hamster transcription start site atlas that enables targeted editing of CHO cells

Chinese hamster ovary (CHO) cells, with their human-compatible glycosylation and high protein titers, are the most widely used cells for producing biopharmaceuticals. Engineering gene expression in CHO is key to improving drug quality and affordability. However, engineering gene expression or activating silent genes requires accurate annotation of the underlying regulatory elements and transcription start sites (TSSs). Unfortunately, most TSSs in the Chinese hamster genome were computationally predicted and are frequently inaccurate. Here, we revised TSS annotations for 15,308 Chinese hamster genes and 4,478 non-coding RNAs based on experimental data from CHO-K1 cells and 10 hamster tissues. The experimental realignment and discovery of TSSs now expose previously hidden motifs, such as the TATA box. We further demonstrate, by targeting the glycosyltransferase gene Mgat3, how accurate annotations readily facilitate activating silent genes by CRISPRa to obtain more human-like glycosylation. Together, we envision our annotation and data will provide a rich resource for the CHO community, improve genome engineering efforts and aid comparative and evolutionary studies.

genomics↗

bioRxiv2020

A Genome-wide Library of MADM Mice for Single-Cell Genetic Mosaic Analysis

Mosaic Analysis with Double Markers (MADM) offers a unique approach to visualize and concomitantly manipulate genetically-defined cells in mice with single-cell resolution. MADM applications include the analysis of lineage; single-cell morphology and physiology; genomic imprinting phenotypes; and dissection of cell-autonomous gene functions in vivo in health and disease. Yet, MADM could only be applied to <25% of all mouse genes on select chromosomes thus far. To overcome this limitation, we generated transgenic mice with knocked-in MADM cassettes near the centromeres of all 19 autosomes and validated their use across organs. With this resource, >96% of the entire mouse genome can now be subjected to single-cell genetic mosaic analysis. Beyond proof-of-principle, we applied our MADM library to systematically trace sister chromatid segregation in distinct mitotic cell lineages. We found striking chromosome-specific biases in segregation patterns, reflecting a putative mechanism for the asymmetric segregation of genetic determinants in somatic stem cell division.

developmental biology↗