Browsing by Author "Hu, Wei-Shou"
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Item GlycoVis: Visualizing Glycan Distribution in the Protein N-Glycosylation Pathwayin Mammalian Cells(2016-12-19) Hossler, Patrick; Hu, Wei-Shou; acre@umn.edu; Hu, Wei-Shou; Department of Chemical Engineering and Materials Science, University of MinnesotaGlycosylation pattern is an important quality attribute of protein therapeutics. It affects protein stability, half-life and even biological functions. The N-glycosylation pathway is a highly branched network. Although only a relative small number of enzymes involved in the pathway, a multitude of glycan intermediates can be produced. In order to study this network, GlycoVis was created to visualize the distribution of glycans and potential reaction paths leading to each glycan in the N-glycosylation network. The program was written in Matlab, interfacing with Graphviz. It incorporates substrate specificity of the enzymes involved in the pathway in a relationship matrix. Given an input of glycan distribution data, the program traces all the potential reaction paths leading to each glycan, and outputs pathway maps with glycans colored in line with their relative abundances.Item Letter to the University President from University Professors endorsing Strategic Positioning(2005-04-08) Andow, David; Barany, George; Bates, Frank; Bernlohr, David; Candler, Graham; Clayton, Tom; Crick, Nicki; Edwards, R. Lawrence; Foufoula-Georgiou, Efi; Freeman, John; Gunnar, Megan; Hu, Wei-Shou; Iacono, William; James, Richard; Jenkins, Marc; Legge, Gordon; Lodge, Tim; Masten, Ann; Olive, Keith; Phillips, Ronald; Pui, David; Pusey, Ann; Reich, Peter; Sadowsky, Michael; Schmidt, Lanny; Shekhar, Shashi; Sullivan, John; Tolman, William; Tranquillo, Robert T; Young, NevinItem A mechanistic-empirical model of central metabolism, signaling, and the reactor environment for bioprocesses(2020-10-07) O'Brien, Conor M; Hu, Wei-Shou; acre@umn.edu; Hu, Wei-ShouThis model was built and optimized to reproduce the variability inherent to many industrial cell-culture processes. Classically, fed-batch Chinese Hamster Ovary (CHO) cell cultures will initially produce lactate in the early phase of culture before switching to lactate consumption. However, some processes may revert to lactate production in the late stage of culture, driving up osmolarity while reducing viable cell density, and ultimately lowering process performance. This phenomenon may occur in only some runs of a manufacturing processes and even may differ among runs with similar initial conditions and trajectories, leading to longstanding questions about the mechanisms driving this switch. By simulating cultures which were exposed to different amounts of stress before the production bioreactor we show that similar starting conditions in the bioreactor environment can lead to variability in metabolic shift. We provide this model as a tool to demonstrate this metabolic variability and provide a platform for hypothesis testing, in silico bioprocess optimization, and simulation of reactor scale-up and scale-down.Item Modeling the Effects of Small Molecule Therapeutics on Glycolysis and Lactate Flux(2018-09) Schroeder, Joseph S; O'Brien, Conor M; Hu, Wei-ShouChinese Hamster Ovary (CHO) cells are widely used in the industrial production of commercial therapeutics. One key aspect to the productivity of these cells is their high rate of glucose consumption. The high rate of glucose consumption is paired with a high output of lactate which can lead to negative culture performance. The rate of glucose consumption and lactate production can be modulated by a number of chemicals, some of which are being explored as therapeutic drugs, which affect the activities of the enzymes involved in glucose metabolism. This research aimed to evaluate the effects caused by small molecule therapeutics on CHO cells’ metabolism using a mathematic model of glucose metabolism. To model the therapeutics, established kinetic information for these therapeutics was implemented into a metabolic model. Then different concentrations of therapeutics were explored to assess their effects on metabolism. In addition, combinations of therapeutics were examined to study the effects of more drastic changes to metabolism. These therapeutics showed a large impact to the bistability of glucose metabolism as well as the lactate flux. These outcomes were important due to the potential to increase the productivity of CHO cells for industrial use as well as decreasing cell death. Thus, these therapeutics could be used to reduce lactate production in cells allowing for higher productivity.Item Regions of High Confidence in Chinese Hamster and CHO-K1 Genome Assemblies(2016-04-20) Vishwanathan, Nandita; Bandyopadhyay, Arpan; Fu, Hsu-Yuan; Sharma, Mohit; Johnson, Kathryn; Mudge, Joann; Ramaraj, Thiruvarangan; Onsongo, Getiria; Silverstein, Kevin A. T.; Jacob, Nitya M.; Le, Huong; Karypis, George; Hu, Wei-Shou; wshu@umn.edu; Hu, Wei-ShouChinese hamster Ovary (CHO) cell lines are the dominant industrial workhorses for therapeutic recombinant protein production. The availability of the genome sequence of Chinese hamster and CHO cells will spur further genome and RNA sequencing of producing cell lines. However, the mammalian genomes assembled using shot-gun sequencing data still contain regions of uncertain quality due to assembly errors. Identifying high confidence regions in the assembled genome will facilitate its use for cell engineering and genome engineering. This dataset includes two genome annotation files that identify the 'high confidence regions' shared by the genome assemblies in comparison. The potential use of these files are to find locations in the publically available genome which are likely to be assembled correctly. These regions can be used confidently for genome engineering.Item SAM Filtering Pipeline (SFP): Algorithm for the determination of integration sites from next generation sequencing data(2019-07-16) O'Brien, Sofie A; Hu, Wei-Shou; acre@umn.edu; Hu, Wei-ShouThe locus at which a vector harboring a product transgene integrates into the genome can have a profound effect on the transgene’s transcript level and the stability of the resulting cell line. In order to identify integration site(s) of a transfected vector from next generation genome sequencing data, the SAM filtering pipeline (SFP) was created. It is best suited for targeted sequence data, such as that from sequence capture of probed vector regions. However, it will also work for whole genome sequencing data, though the memory requirements are large (the more reads in your data set, the larger the memory requirements). A bwa-mem mapped .sam file is required as input to the pipeline.