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Glycosylation flux analysis reveals dynamic changes of intracellular glycosylation flux distribution in Chinese hamster ovary fed-batch cultures

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METABOLIC ENGINEERING 2017年第PartA期43卷 9-20页

作者： Hutter, Sandro Villiger, Thomas K. Bruhlmann, David Stettler, Matthieu Broly, Herve Soos, Miroslav Gunawan, Rudiyanto Swiss Fed Inst Technol Dept Chem & Appl Biosci Inst Chem & Bioengn CH-8093 Zurich Switzerland Swiss Inst Bioinformat CH-1015 Lausanne Switzerland Merck Biopharma Biotech Proc Sci CH-1804 Corsier Sur Vevey Switzerland Univ Chem & Technol Dept Chem Engn Prague 16628 Czech Republic

N-linked glycosylation of proteins has both functional and structural significance. Importantly, the glycan structure of a therapeutic protein influences its efficacy, pharmacokinetics, pharmacodynamics and immunogenicity. In this work, we developed glycosylation flux analysis (GFA) for predicting intracellular production and consumption rates (fluxes) of glycoforms, and applied this analysis to CHO fed-batch immunoglobulin G (IgG) production using two different media compositions, with and without additional manganese feeding. The GFA is based on a constraint-based modeling of the glycosylation network, employing a pseudo steady state assumption. While the glycosylation fluxes in the network are balanced at each time point, the GFA allows the fluxes to vary with time by way of two scaling factors: (1) an enzyme-specific factor that captures the temporal changes among glycosylation reactions catalysed by the same enzyme, and (2) the cell specific productivity factor that accounts for the dynamic changes in the IgG production rate. The GFA of the CHO fed-batch cultivations showed that regardless of the media composition, galactosylation fluxes decreased with the cultivation time more significantly than the other glycosylation reactions. Furthermore, the GFA showed that the addition of Mn, a cofactor of galactosyltransferase, has the effect of increasing the galactosylation fluxes but only during the beginning of the cultivation period. The results thus demonstrated the power of the GFA in delineating the dynamic alterations of the glycosylation fluxes by local (enzyme-specific) and global (cell specific productivity) factors.

关键词： N-linked glycosylation Flux analysis CHO cells constraint-based modeling Monoclonal antibody

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From Network Analysis to Functional Metabolic modeling of the Human Gut Microbiota

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MSYSTEMS 2018年第3期3卷 e00209-17页

作者： Bauer, Eugen Thiele, Ines Univ Luxembourg Luxembourg Ctr Syst Biomed Esch Sur Alzette Luxembourg

An important hallmark of the human gut microbiota is its species diversity and complexity. Various diseases have been associated with a decreased diversity leading to reduced metabolic functionalities. Common approaches to investigate the human microbiota include high-throughput sequencing with subsequent correlative analyses. However, to understand the ecology of the human gut microbiota and consequently design novel treatments for diseases, it is important to represent the different interactions between microbes with their associated metabolites. Computational systems biology approaches can give further mechanistic insights by constructing data-or knowledge-driven networks that represent microbe interactions. In this minireview, we will discuss current approaches in systems biology to analyze the human gut microbiota, with a particular focus on constraint-based modeling. We will discuss various community modeling techniques with their advantages and differences, as well as their application to predict the metabolic mechanisms of intestinal microbial communities. Finally, we will discuss future perspectives and current challenges of simulating realistic and comprehensive models of the human gut microbiota.

关键词： computational modeling constraint-based modeling gut microbiome metabolic modeling network approaches

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A Systematic Evaluation of Methods for Tailoring Genome-Scale Metabolic Models

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CELL SYSTEMS 2017年第3期4卷 318-329页

作者： Opdam, Sjoerd Richelle, Anne Kellman, Benjamin Li, Shanzhong Zielinski, Daniel C. Lewis, Nathan E. Eindhoven Univ Technol Dept Biomed Engn Computat Biol NL-5612 AZ Eindhoven Netherlands Univ Calif San Diego Novo Nordisk Fdn Ctr Biosustainabil La Jolla CA 92093 USA Univ Calif San Diego Sch Med Dept Pediat La Jolla CA 92093 USA Univ Calif San Diego Bioinformat & Syst Biol Program La Jolla CA 92093 USA Univ Calif San Diego Dept Bioengn La Jolla CA 92093 USA

Genome-scale models of metabolism can illuminate the molecular basis of cell phenotypes. Since some enzymes are only active in specific cell types, several algorithms use omics data to construct cell-line-and tissue-specific metabolic models from genome-scale models. However, these methods are often not rigorously benchmarked, and it is unclear how algorithm and parameter selection (e.g., gene expression thresholds, metabolic constraints) affects model content and predictive accuracy. To investigate this, we built hundreds of models of four different cancer cell lines using six algorithms, four gene expression thresholds, and three sets of metabolic constraints. Model content varied substantially across different parameter sets, but the algorithms generally increased accuracy in gene essentiality predictions. However, model extraction method choice had the largest impact on model accuracy. We further highlight how assumptions during model development influence model prediction accuracy. These insights will guide further development of context-specific models, thus more accurately resolving genotype-phenotype relationships.

关键词： constraint-based modeling genome-scale model metabolism model extraction method systems biology tissue-specific

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A Graph based Approach to Analyse Metabolic Networks for Strain Engineering

A Graph Based Approach to Analyse Metabolic Networks for Str...

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Iranian Conference on Electrical Engineering

作者： Leila Hassani Mohammad R. Moosavi Payam Setoodeh Dept. of Computer Science and Engineering Shiraz University Shiraz Iran Dept. of Chemical Engineering Shiraz University Shiraz Iran

Recently, there has been great interest in the field of metabolic engineering. Engineered microorganisms such as bacteria can be exploited to synthesize value-added bioproducts. Conversely, optimal genetic manipulations to reach to operative engineered cells is very costly;hence, regarding whole-cell functionalities, a number of proficient simulation algorithms have been developed and widely applied for systems-level analyses, and as a consequence, systems metabolic engineering. However, most of the currently-used in silico algorithms are usually time-consuming. In other words, it is requisite that computer scientists gain prior knowledge of molecular biology and biochemistry to be able to develop more effective algorithms in this field. Here, in the current study, we regard the metabolic network of interest as a general graph to present algorithmic perspective of the complex metabolic systems. A cell's metabolism is modeled in the form of a metabolic network. This way, the major problems in the field of metabolic engineering can be tackled using graph theory and graph mining algorithms. For this purpose, we reconstruct the metabolic network as a general graph, redefine the metabolic engineering problems accordingly, and finally, solve one of them as a sample.

关键词： In-silico strain engineering Network flow Graph mining constraint-based modeling

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Escher-FBA: a web application for interactive flux balance analysis

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BMC SYSTEMS BIOLOGY 2018年第1期12卷 84-84页

作者： Rowe, Elliot Palsson, Bernhard O. King, Zachary A. Univ Calif San Diego Dept Bioengn La Jolla CA 92093 USA Univ Calif San Diego Bioinformat & Syst Biol Program La Jolla CA 92093 USA Univ Calif San Diego Dept Pediat La Jolla CA 92093 USA Tech Univ Denmark Novo Nordisk Fdn Ctr Biosustainabil Bldg 220 DK-2800 Lyngby Denmark

Background: Flux balance analysis (FBA) is a widely-used method for analyzing metabolic networks. However, most existing tools that implement FBA require downloading software and writing code. Furthermore, FBA generates predictions for metabolic networks with thousands of components, so meaningful changes in FBA solutions can be difficult to identify. These challenges make it difficult for beginners to learn how FBA works. Results: To meet this need, we present Escher-FBA, a web application for interactive FBA simulations within a pathway visualization. Escher-FBA allows users to set flux bounds, knock out reactions, change objective functions, upload metabolic models, and generate high-quality figures without downloading software or writing code. We provide detailed instructions on how to use Escher-FBA to replicate several FBA simulations that generate real scientific hypotheses. Conclusions: We designed Escher-FBA to be as intuitive as possible so that users can quickly and easily understand the core concepts of FBA. The web application can be accessed at https://***/escher-fba.

关键词： constraint-based modeling Flux balance analysis Escher Visualization Metabolism Web application

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Data calibration for statistical-based assessment in constraint-based tutors

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KNOWLEDGE-based SYSTEMS 2016年 97卷 11-23页

作者： Galvez, Jaime Guzman, Eduardo Conejo, Ricardo Mitrovic, Antonija Mathews, Moffat Univ Malaga Dept Lenguajes & Ciencias Comp ETSI Informat Bulevar Louis Pasteur35Campus Teatinos E-29071 Malaga Spain Univ Canterbury Dept Comp Sci & Software Engn Private Bag 4800 Christchurch 8140 New Zealand

Intelligent Tutoring Systems (ITSs) are one of a wide range of learning environments, where the main activity is problem solving. One of the most successful approaches for implementing ITSs is constraint based modeling (CBM). constraint-based tutors have been successfully used as drill-and-practice environments for learning. More recently CBM tutors have been complemented with a model derived from the field of Psychometrics. The goal of this synergy is to provide CBM tutors with a data-driven and sound mechanism of assessment, which mainly consists in applying the principles of Item Response Theory (IRT). The result of this synergy is, therefore, a formal approach that allows carrying out assessments of performance on problem solving tasks. Several previous studies were conducted proving the validity and utility of this combined approach with small groups of students, in short periods of time and using systems designed specifically for assessment purposes. In this paper, the approach has been extended and adapted to deal with a large set of students who used an ITS over a long period of time. The main research questions addressed in this paper are: (1) Which IRT models are more suitable to be used in a constrained-based tutor? (2) Can data collected from the ITS be used as a source for calibrating the constraints characteristic curves? (3) Which is the best strategy to assemble data for calibration? To answer these questions, we have analyzed three years of data from SQL-Tutor. (C) 2016 Elsevier B.V. All rights reserved.

关键词： Learning analytics Assessment constraint-based modeling Intelligent Tutoring Systems Item Response Theory

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Development of a Framework for Metabolic Pathway Analysis-Driven Strain Optimization Methods

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INTERDISCIPLINARY SCIENCES-COMPUTATIONAL LIFE SCIENCES 2017年第1期9卷 46-55页

作者： Vieira, Vitor Maia, Paulo Rocha, Isabel Rocha, Miguel Univ Minho Ctr Biol Engn Campus Gualtar P-4710057 Braga Portugal SilicoLife Lda Rua Canastreiro 15 P-4715387 Braga Portugal

Genome-scale metabolic models (GSMMs) have become important assets for rational design of compound overproduction using microbial cell factories. Most computational strain optimization methods (CSOM) using GSMMs, while useful in metabolic engineering, rely on the definition of questionable cell objectives, leading to some bias. Metabolic pathway analysis approaches do not require an objective function. Though their use brings immediate advantages, it has mostly been restricted to small scale models due to computational demands. Additionally, their complex parameterization and lack of intuitive tools pose an important challenge towards making these widely available to the community. Recently, MCSEnumerator has extended the scale of these methods, namely regarding enumeration of minimal cut sets, now able to handle GSMMs. This work proposes a tool implementing this method as a Java library and a plugin within the OptFlux metabolic engineering platform providing a friendly user interface. A standard enumeration problem and pipeline applicable to GSMMs is proposed, making use by the community simpler. To highlight the potential of these approaches, we devised a case study for overproduction of succinate, providing a phenotype analysis of a selected strategy and comparing robustness with a selected solution from a bi-level CSOM.

关键词： constraint-based modeling Metabolic engineering Pathway analysis Minimal cut sets Strain optimization

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The Cost of Metabolic Interactions in Symbioses between Insects and Bacteria with Reduced Genomes

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MBIO 2018年第5期9卷 e01433-18页

作者： Ankrah, Nana Y. D. Chouaia, Bessem Douglas, Angela E. Cornell Univ Dept Entomol & Genet Ithaca NY 14850 USA Cornell Univ Dept Mol Biol & Genet Ithaca NY 14850 USA Univ Milan Dept Agr & Environm Sci Milan Italy

Various intracellular bacterial symbionts that provide their host with essential nutrients have much-reduced genomes, attributed largely to genomic decay and relaxed selection. To obtain quantitative estimates of the metabolic function of these bacteria, we reconstructed genome-and transcriptome-informed metabolic models of three xylem-feeding insects that bear two bacterial symbionts with complementary metabolic functions: a primary symbiont, Sulcia, that has codiversified with the insects, and a coprimary symbiont of distinct taxonomic origin and with different degrees of genome reduction in each insect species (Hodgkinia in a cicada, Baumannia in a sharpshooter, and Sodalis in a spittlebug). Our simulations reveal extensive bidirectional flux of multiple metabolites between each symbiont and the host, but near-complete metabolic segregation (i.e., near absence of metabolic cross-feeding) between the two symbionts, a likely mode of host control over symbiont metabolism. Genome reduction of the symbionts is associated with an increased number of host metabolic inputs to the symbiont and also reduced metabolic cost to the host. In particular, Sulcia and Hodgkinia with genomes of <= 0.3 Mb are calculated to recycle similar to 30 to 80% of host-derived nitrogen to essential amino acids returned to the host, while Baumannia and Sodalis with genomes of >= 0.6 Mb recycle 10 to 15% of host nitrogen. We hypothesize that genome reduction of symbionts may be driven by selection for increased host control and reduced host costs, as well as by the stochastic process of genomic decay and relaxed selection. IMPORTANCE Current understanding of many animal-microbial symbioses involving unculturable bacterial symbionts with much-reduced genomes derives almost entirely from nonquantitative inferences from genome data. To overcome this limitation, we reconstructed multipartner metabolic models that quantify both the metabolic fluxes within and between three xylem-feeding insects and

关键词： constraint-based modeling flux balance analysis nitrogen recycling symbiosis xylem-feeding insects

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The FASTCORE Family: For the Fast Reconstruction of Compact Context-Specific Metabolic Networks Models

The FASTCORE Family: For the Fast Reconstruction of Compact ...

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作者： Maria Pires Pacheco Thomas Sauter

The FASTCORE family is a family of algorithms that are mainly used to build context-specific models but can also be applied to other tasks such as gapfilling and consistency testing. The FASTCORE family has very low computational demands with running times that are several orders of magnitude lower than its main competitors. Furthermore, the models built by the FASTCORE family have a better resolution power (defined as the ability to capture metabolic variations between different tissues, cell types, or contexts) than models from other algorithms. less

关键词： Microarray Transcriptomics Python Mus musculus Homo sapiens Algorithm Metabolic modeling constraint-based modeling FBA Context-specific omics data integration

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Advances and challenges in logical modeling of cell cycle regulation: perspective for multi-scale, integrative yeast cell models

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FEMS YEAST RESEARCH 2017年第1期17卷 fow103-fow103页

作者： Barberis, Matteo Todd, Robert G. van der Zee, Lucas Univ Amsterdam Swammerdam Inst Life Sci Synthet Syst Biol & Nucl Org O 2 BldgBoelelaan 1108 NL-1081 HZ Amsterdam Netherlands Mt Mercy Univ Dept Nat & Appl Sci Cedar Rapids IA 52402 USA

The eukaryotic cell cycle is robustly designed, with interacting molecules organized within a definite topology that ensures temporal precision of its phase transitions. Its underlying dynamics are regulated by molecular switches, for which remarkable insights have been provided by genetic and molecular biology efforts. In a number of cases, this information has been made predictive, through computational models. These models have allowed for the identification of novel molecular mechanisms, later validated experimentally. Logical modeling represents one of the youngest approaches to address cell cycle regulation. We summarize the advances that this type of modeling has achieved to reproduce and predict cell cycle dynamics. Furthermore, we present the challenge that this type of modeling is now ready to tackle: its integration with intracellular networks, and its formalisms, to understand crosstalks underlying systems level properties, ultimate aim of multi-scale models. Specifically, we discuss and illustrate how such an integration may be realized, by integrating a minimal logical model of the cell cycle with a metabolic network.

关键词： cell cycle logical modeling metabolism constraint-based modeling network integration multi-scale modeling

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