scholarly journals Inclusion of maintenance energy improves the intracellular flux predictions of CHO

2021 ◽  
Vol 17 (6) ◽  
pp. e1009022
Author(s):  
Diana Széliová ◽  
Jerneja Štor ◽  
Isabella Thiel ◽  
Marcus Weinguny ◽  
Michael Hanscho ◽  
...  
Keyword(s):  
Growth Rates ◽  
High Throughput Screening ◽  
Energy Demand ◽  
Metabolic Flux ◽  
Chinese Hamster ◽  
Tca Cycle ◽  
Metabolic Model ◽  
Maintenance Energy ◽  
Uptake Rates ◽  
Wide Range

Chinese hamster ovary (CHO) cells are the leading platform for the production of biopharmaceuticals with human-like glycosylation. The standard practice for cell line generation relies on trial and error approaches such as adaptive evolution and high-throughput screening, which typically take several months. Metabolic modeling could aid in designing better producer cell lines and thus shorten development times. The genome-scale metabolic model (GSMM) of CHO can accurately predict growth rates. However, in order to predict rational engineering strategies it also needs to accurately predict intracellular fluxes. In this work we evaluated the agreement between the fluxes predicted by parsimonious flux balance analysis (pFBA) using the CHO GSMM and a wide range of 13C metabolic flux data from literature. While glycolytic fluxes were predicted relatively well, the fluxes of tricarboxylic acid (TCA) cycle were vastly underestimated due to too low energy demand. Inclusion of computationally estimated maintenance energy significantly improved the overall accuracy of intracellular flux predictions. Maintenance energy was therefore determined experimentally by running continuous cultures at different growth rates and evaluating their respective energy consumption. The experimentally and computationally determined maintenance energy were in good agreement. Additionally, we compared alternative objective functions (minimization of uptake rates of seven nonessential metabolites) to the biomass objective. While the predictions of the uptake rates were quite inaccurate for most objectives, the predictions of the intracellular fluxes were comparable to the biomass objective function.

scholarly journals Inclusion of maintenance energy improves the intracellular flux predictions of CHO

2020 ◽  
Author(s):  
Diana Széliová ◽  
Jerneja Štor ◽  
Isabella Thiel ◽  
Marcus Weinguny ◽  
Michael Hanscho ◽  
...  
Keyword(s):  
Growth Rates ◽  
High Throughput Screening ◽  
Energy Demand ◽  
Metabolic Flux ◽  
Chinese Hamster ◽  
Tca Cycle ◽  
Metabolic Model ◽  
Maintenance Energy ◽  
Uptake Rates ◽  
Wide Range

AbstractChinese hamster ovary (CHO) cells are the leading platform for the production of biopharmaceuticals with human-like glycosylation. The standard practice for cell line generation relies on trial and error approaches such as adaptive evolution and high-throughput screening, which typically take several months. Metabolic modeling could aid in designing better producer cell lines and thus shorten development times. The genome-scale metabolic model (GSMM) of CHO can accurately predict growth rates. However, in order to predict rational engineering strategies it also needs to accurately predict intracellular fluxes. In this work we evaluated the agreement between the fluxes predicted by pFBA using the CHO GSMM and a wide range of 13C metabolic flux data from literature. While glycolytic fluxes were predicted relatively well, the fluxes of tricarboxylic acid (TCA) cycle were vastly underestimated due to too low energy demand. Inclusion of computationally estimated maintenance energy significantly improved the overall accuracy of intracellular flux predictions. Maintenance energy was therefore determined experimentally by running continuous cultures at different growth rates and evaluating their respective energy consumption. The experimentally and computationally determined maintenance energy were in good agreement. Additionally, we compared alternative objective functions (minimization of uptake rates of seven nonessential metabolites) to the biomass objective. While the predictions of the uptake rates were quite inaccurate for most objectives, the predictions of the intracellular fluxes were comparable to the biomass objective function.

TCA cycle activity in Saccharomyces cerevisiae is a function of the environmentally determined specific growth and glucose uptake rates

Microbiology ◽  
2004 ◽  
Vol 150 (4) ◽  
pp. 1085-1093 ◽  
Author(s):  
Lars M. Blank ◽  
Uwe Sauer
Keyword(s):  
Saccharomyces Cerevisiae ◽  
Growth Rate ◽  
Glucose Uptake ◽  
Environmental Conditions ◽  
Specific Growth ◽  
Tca Cycle ◽  
Glucose Sensing ◽  
The Tca Cycle ◽  
Uptake Rates ◽  
Wide Range

Metabolic responses of Saccharomyces cerevisiae to different physical and chemical environmental conditions were investigated in glucose batch culture by GC-MS-detected mass isotopomer distributions in proteinogenic amino acids from 13C-labelling experiments. For this purpose, GC-MS-based metabolic flux ratio analysis was extended from bacteria to the compartmentalized metabolism of S. cerevisiae. Generally, S. cerevisiae was shown to have low catabolic fluxes through the pentose phosphate pathway and the tricarboxylic acid (TCA) cycle. Notably, respiratory TCA cycle fluxes exhibited a strong correlation with the maximum specific growth rate that was attained under different environmental conditions, including a wide range of pH, osmolarity, decoupler and salt concentrations, but not temperature. At pH values of 4·0 to 6·0 with near-maximum growth rates, the TCA cycle operated as a bifurcated pathway to fulfil exclusively biosynthetic functions. Increasing or decreasing the pH beyond this physiologically optimal range, however, reduced growth and glucose uptake rates but increased the ‘cyclic’ respiratory mode of TCA cycle operation for catabolism. Thus, the results indicate that glucose repression of the TCA cycle is regulated by the rates of growth or glucose uptake, or signals derived from these. While sensing of extracellular glucose concentrations has a general influence on the in vivo TCA cycle activity, the growth-rate-dependent increase in respiratory TCA cycle activity was independent of glucose sensing.

scholarly journals Metabolic Analysis of the Asparagine and Glutamine Dynamics in an Industrial CHO Fed-Batch Process

2021 ◽  
Author(s):  
Brian Kirsch ◽  
Sandra Bennun ◽  
Adam Mendez ◽  
Amy Johnson ◽  
Hongxia Wang ◽  
...  
Keyword(s):  
Metabolic Flux ◽  
Chinese Hamster ◽  
Tca Cycle ◽  
Batch Process ◽  
Exponential Phase ◽  
Flux Analysis ◽  
Fed Batch ◽  
Cho Cell ◽  
Feed Composition ◽  
Trade Offs

Chinese Hamster Ovary (CHO) cell lines are grown in cultures with varying asparagine and glutamine concentrations, but further study is needed to characterize the interplay between these amino acids. By following 13C-glucose, 13C-glutamine, and 13C-asparagine tracers using metabolic flux analysis (MFA), CHO cell metabolism was characterized in an industrially relevant fed-batch process under glutamine supplemented and low glutamine conditions during early and late exponential growth. For both conditions MFA revealed glucose as the primary carbon source to the tricarboxylic acid (TCA) cycle followed by glutamine and asparagine as secondary sources. Early exponential phase CHO cells prefer glutamine over asparagine to support the TCA cycle under the glutamine supplemented condition, while asparagine was critical for TCA activity for the low glutamine condition. Overall TCA fluxes were similar for both conditions due to the trade-offs associated with reliance on glutamine and/or asparagine. However, glutamine supplementation increased fluxes to alanine, lactate and enrichment of glutathione, N-Acetyl-Glucosamine (NAG) and pyrimidine-containing-molecules. The late exponential phase exhibited reduced central carbon metabolism dominated by glucose, while lactate reincorporation and aspartate uptake were preferred over glutamine and asparagine. These 13C studies demonstrate that metabolic flux is process time dependent and can be modulated by varying feed composition.

scholarly journals A Metabolomics Approach to Increasing Chinese Hamster Ovary (CHO) Cell Productivity

Metabolites ◽  
2021 ◽  
Vol 11 (12) ◽  
pp. 823
Author(s):  
Grace Yao ◽  
Kathryn Aron ◽  
Michael Borys ◽  
Zhengjian Li ◽  
Girish Pendse ◽  
...  
Keyword(s):  
Chinese Hamster Ovary ◽  
Chinese Hamster ◽  
Tca Cycle ◽  
Viable Cell ◽  
Metabolic Model ◽  
Viable Cell Density ◽  
Specific Productivity ◽  
Cho Cell ◽  
High Productivity ◽  
Medium Supplementation

Much progress has been made in improving the viable cell density of bioreactor cultures in monoclonal antibody production from Chinese hamster ovary (CHO) cells; however, specific productivity (qP) has not been increased to the same degree. In this work, we analyzed a library of 24 antibody-expressing CHO cell clones to identify metabolites that positively associate with qP and could be used for clone selection or medium supplementation. An initial library of 12 clones, each producing one of two antibodies, was analyzed using untargeted LC-MS experiments. Metabolic model-based annotation followed by correlation analysis detected 73 metabolites that significantly correlated with growth, qP, or both. Of these, metabolites in the alanine, aspartate, and glutamate metabolism pathway, and the TCA cycle showed the strongest association with qP. To evaluate whether these metabolites could be used as indicators to identify clones with potential for high productivity, we performed targeted LC-MS experiments on a second library of 12 clones expressing a third antibody. These experiments found that aspartate and cystine were positively correlated with qP, confirming the results from untargeted analysis. To investigate whether qP correlated metabolites reflected endogenous metabolic activity beneficial for productivity, several of these metabolites were tested as medium additives during cell culture. Medium supplementation with citrate improved qP by up to 490% and more than doubled the titer. Together, these studies demonstrate the potential for using metabolomics to discover novel metabolite additives that yield higher volumetric productivity in biologics production processes.

scholarly journals The IDEAL household energy dataset, electricity, gas, contextual sensor data and survey data for 255 UK homes

2021 ◽  
Vol 8 (1) ◽  
Author(s):  
Martin Pullinger ◽  
Jonathan Kilgour ◽  
Nigel Goddard ◽  
Niklas Berliner ◽  
Lynda Webb ◽  
...  
Keyword(s):  
Survey Data ◽  
Energy Demand ◽  
Secondary Data ◽  
Hot Water ◽  
Power Measurement ◽  
Sensor Data ◽  
Energy Awareness ◽  
Household Energy ◽  
Wide Range ◽  
The Ideal

AbstractThe IDEAL household energy dataset described here comprises electricity, gas and contextual data from 255 UK homes over a 23-month period ending in June 2018, with a mean participation duration of 286 days. Sensors gathered 1-second electricity data, pulse-level gas data, 12-second temperature, humidity and light data for each room, and 12-second temperature data from boiler pipes for central heating and hot water. 39 homes also included plug-level monitoring of selected electrical appliances, real-power measurement of mains electricity and key sub-circuits, and more detailed temperature monitoring of gas- and heat-using equipment, including radiators and taps. Survey data included occupant demographics, values, attitudes and self-reported energy awareness, household income, energy tariffs, and building, room and appliance characteristics. Linked secondary data comprises weather and level of urbanisation. The data is provided in comma-separated format with a custom-built API to facilitate usage, and has been cleaned and documented. The data has a wide range of applications, including investigating energy demand patterns and drivers, modelling building performance, and undertaking Non-Intrusive Load Monitoring research.

scholarly journals Identification of potential drug targets in Salmonella enterica sv. Typhimurium using metabolic modelling and experimental validation

Microbiology ◽  
2014 ◽  
Vol 160 (6) ◽  
pp. 1252-1266 ◽  
Author(s):  
Hassan B. Hartman ◽  
David A. Fell ◽  
Sergio Rossell ◽  
Peter Ruhdal Jensen ◽  
Martin J. Woodward ◽  
...  
Keyword(s):  
Salmonella Enterica ◽  
Energy Demand ◽  
Drug Targets ◽  
Minimal Medium ◽  
Model Organism ◽  
Metabolic Model ◽  
Scale Model ◽  
Glucose Minimal Medium ◽  
A Genome ◽  
Genome Scale

Salmonella enterica sv. Typhimurium is an established model organism for Gram-negative, intracellular pathogens. Owing to the rapid spread of resistance to antibiotics among this group of pathogens, new approaches to identify suitable target proteins are required. Based on the genome sequence of S. Typhimurium and associated databases, a genome-scale metabolic model was constructed. Output was based on an experimental determination of the biomass of Salmonella when growing in glucose minimal medium. Linear programming was used to simulate variations in the energy demand while growing in glucose minimal medium. By grouping reactions with similar flux responses, a subnetwork of 34 reactions responding to this variation was identified (the catabolic core). This network was used to identify sets of one and two reactions that when removed from the genome-scale model interfered with energy and biomass generation. Eleven such sets were found to be essential for the production of biomass precursors. Experimental investigation of seven of these showed that knockouts of the associated genes resulted in attenuated growth for four pairs of reactions, whilst three single reactions were shown to be essential for growth.

The rôles of photoperiod and nutrition in the seasonal increases in growth and insulin-like growth factor-1 secretion in male red deer

2001 ◽  
Vol 73 (2) ◽  
pp. 305-311 ◽  
Author(s):  
J. R. Webster ◽  
I. D. Corson ◽  
R. P. Littlejohn ◽  
S. K. Martin ◽  
J. M. Suttie
Keyword(s):  
Growth Factor ◽  
Food Intake ◽  
Growth Rates ◽  
Energy Demand ◽  
Red Deer ◽  
Young Male ◽  
Live Weight ◽  
Metabolizable Energy ◽  
Plasma Prolactin ◽  
Insulin Like Growth Factor

AbstractYoung male red deer follow a seasonal growth pattern that can be shifted by altering the photoperiod they experience. An increase in photoperiod to 16 h of light per day (16L : 8D) during winter advances the onset of rapid growth and high food intake that normally commences in spring. These changes are associated with increased growth hormone (GH) and insulin-like growth factor-1 (IGF-1) secretion. The GH/IGF-1 axis is acutely sensitive to the level of nutrition and the relative rôles of photoperiod and nutrition in determining the spring IGF-1 rise is unknown. The present experiment set out to examine this by exposing two groups of deer (no. = 8 per group) to a photoperiod shift during their 1st year of life (16L : 8D from 2 June), designed to cause accelerated growth and increased food intake after approximately 7 weeks. However, after 6 weeks the food intake (pellets containing 11 MJ metabolizable energy and 160 g crude protein per kg dry matter (DM)) of one group (LDRES) was clamped, thereby preventing the intake component of the response. The intake of the other group (LDAL) remained ad libitum for a further 12 weeks until 6 October, when the experiment concluded.During the first 6 weeks of 16L : 8D, growth rate (118 (s.e. 15·4) g/day) and food intake (1·37 (s.e. 0·031) kg DM per head per day) did not differ between the groups. Food intake following the clamp in LDRES averaged 1·40 (s.e. 0·015) kg per head per day. The intake of LDAL increased 2 weeks after the clamp and thereafter was higher than LDRES (P < 0·001). Food intake of LDAL averaged 2·13 (s.e. 0·051) kg during the nutritional clamp period. Growth rates increased in both groups during the first 3 weeks of the clamp, averaging 237 (s.e. 25·0) g/day, then growth slowed in LDRES and live weights diverged. Growth rates until the end of the experiment (147 (s.e.23·0) g/ day v. 299 (s.e. 12·5) g/day, P < 0·001) and mean live weight over the last 5 weeks of the experiment were lower (P < 0·05) in LDRES than LDAL, weights reaching 88·3 (s.e. 1·86) kg and 97·9 (s.e. 2·74) kg respectively on the final sampling date. Metatarsal bone length grew more in LDAL than in LDRES (3·1 v. 2·2 cm, s.e.d. = 0·23, P < 0·01). Prior to the nutritional clamp, mean plasma prolactin and IGF-1 concentrations increased at 3 and 6 weeks after 16L : 8D respectively, in both groups. Prolactin concentrations were lower in LDRES than LDAL on two occasions, at weeks 3 and 7 after the onset of the nutritional clamp, and IGF-1 concentrations were lower in LDRES than LDAL (676 v. 872 ng/ml, s.e.d. = 73·8, P < 0·05) over the last 7 weeks of sampling.In summary, a photoperiodically driven increase in IGF-1 occurred even when the usual associated increase in food intake was prevented. This indicates that the seasonal IGF-1 rise in red deer is not a consequence of the increased food intake, although the latter appears necessary to maintain elevated IGF-1 concentrations. The rise in IGF-1 may therefore be considered as a component of the photoperiodically entrained seasonal drive to grow, and the increase in food intake a response to satisfy the increased energy demand.

scholarly journals Adaptation limits ecological diversification and promotes ecological tinkering during the competition for substitutable resources

2018 ◽  
Vol 115 (44) ◽  
pp. E10407-E10416 ◽  
Author(s):  
Benjamin H. Good ◽  
Stephen Martis ◽  
Oskar Hallatschek
Keyword(s):  
Evolutionary Dynamics ◽  
Competitive Exclusion ◽  
Directional Selection ◽  
Ecological Niches ◽  
Ecological Diversification ◽  
Effective Competition ◽  
Uptake Rates ◽  
Wide Range ◽  
Dynamical Features ◽  
Adaptation Limits

Microbial communities can evade competitive exclusion by diversifying into distinct ecological niches. This spontaneous diversification often occurs amid a backdrop of directional selection on other microbial traits, where competitive exclusion would normally apply. Yet despite their empirical relevance, little is known about how diversification and directional selection combine to determine the ecological and evolutionary dynamics within a community. To address this gap, we introduce a simple, empirically motivated model of eco-evolutionary feedback based on the competition for substitutable resources. Individuals acquire heritable mutations that alter resource uptake rates, either by shifting metabolic effort between resources or by increasing the overall growth rate. While these constitutively beneficial mutations are trivially favored to invade, we show that the accumulated fitness differences can dramatically influence the ecological structure and evolutionary dynamics that emerge within the community. Competition between ecological diversification and ongoing fitness evolution leads to a state of diversification–selection balance, in which the number of extant ecotypes can be pinned below the maximum capacity of the ecosystem, while the ecotype frequencies and genealogies are constantly in flux. Interestingly, we find that fitness differences generate emergent selection pressures to shift metabolic effort toward resources with lower effective competition, even in saturated ecosystems. We argue that similar dynamical features should emerge in a wide range of models with a mixture of directional and diversifying selection.

scholarly journals Sirt5 deficiency causes post-translational protein malonylation and dysregulated cellular metabolism in chondrocytes under obesity conditions

2020 ◽  
Author(s):  
Shouan Zhu ◽  
Albert Batushansky ◽  
Anita Jopkiewicz ◽  
Dawid Makosa ◽  
Kenneth M. Humphries ◽  
...  
Keyword(s):  
Cellular Metabolism ◽  
Tca Cycle ◽  
Gas Chromatography Mass Spectrometry ◽  
Dependent Manner ◽  
Joint Injury ◽  
Primary Chondrocytes ◽  
Wide Range ◽  
Chondrocyte Metabolism ◽  
High Concentrations

ABSTRACTObjectiveObesity accelerates the development of osteoarthritis (OA) during aging and is associated with altered chondrocyte cellular metabolism. The objective of this study was to investigate the role of sirtuin 5 (SIRT5) in regulating chondrocyte protein lysine malonylation (MaK) and cellular metabolism under obesity-related conditions.MethodsMaK and SIRT5 were immunostained in knee articular cartilage of obese db/db mice and different aged C57BL6 mice with or without destabilization of the medial meniscus (DMM) surgery to induce OA. Primary chondrocytes were isolated from 7-day-old WT and Sirt5−/− mice and treated with varying concentrations of glucose and insulin to mimic obesity. Sirt5-dependent effects on MaK and metabolism were evaluated by Western blot, Seahorse Respirometry, and gas/chromatography-mass/spectrometry (GC-MS) metabolic profiling.ResultsMaK was significantly increased in cartilage of db/db mice and in chondrocytes treated with high concentrations of glucose and insulin (GluhiInshi). Sirt5 protein was increased in an age-dependent manner following joint injury, and Sirt5 deficient primary chondrocytes had increased MaK, decreased glycolysis rate, and reduced basal mitochondrial respiration. GC-MS identified 41 metabolites. Sirt5 deficiency altered 13 distinct metabolites under basal conditions and 18 metabolites under GluhiInshi treatment. Pathway analysis identified a wide range of Sirt5-dependent altered metabolic pathways that include amino acid metabolism, TCA cycle, and glycolysis.ConclusionThis study provides the first evidence that Sirt5 broadly regulates chondrocyte metabolism. We observed changes in Sirt5 and MaK levels in cartilage with obesity and joint injury, suggesting that the Sirt5-MaK pathway may contribute to altered chondrocyte metabolism that occurs during OA development.

scholarly journals Constraint-based metabolic control analysis for rational strain engineering

2020 ◽  
Author(s):  
Sophia Tsouka ◽  
Meric Ataman ◽  
Tuure Hameri ◽  
Ljubisa Miskovic ◽  
Vassily Hatzimanikatis
Keyword(s):  
Metabolic Engineering ◽  
Genome Editing ◽  
Metabolic Control ◽  
Metabolic Flux ◽  
Strain Engineering ◽  
Metabolic Control Analysis ◽  
Physiological Data ◽  
Response Analysis ◽  
Control Analysis ◽  
Wide Range

AbstractThe advancements in genome editing techniques over the past years have rekindled interest in rational metabolic engineering strategies. While Metabolic Control Analysis (MCA) is a well-established method for quantifying the effects of metabolic engineering interventions on flows in metabolic networks and metabolic concentrations, it fails to account for the physiological limitations of the cellular environment and metabolic engineering design constraints. We report here a constraint-based framework based on MCA, Network Response Analysis (NRA), for the rational genetic strain design that incorporates biologically relevant constraints, as well as genome editing restrictions. The NRA core constraints being similar to the ones of Flux Balance Analysis, allow it to be used for a wide range of optimization criteria and with various physiological constraints. We show how the parametrization and introduction of biological constraints enhance the NRA formulation compared to the classical MCA approach, and we demonstrate its features and its ability to generate multiple alternative optimal strategies given several user-defined boundaries and objectives. In summary, NRA is a sophisticated alternative to classical MCA for rational metabolic engineering that accommodates the incorporation of physiological data at metabolic flux, metabolite concentration, and enzyme expression levels.

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