Spatial Proteomics Reveals Differences in the Cellular Architecture of Antibody-Producing CHO and Plasma Cell-Derived Cells.

Most of the recombinant biotherapeutics employed today to combat severe illnesses, for example, various types of cancer or autoimmune diseases, are produced by Chinese hamster ovary (CHO) cells. To meet the growing demand of these pharmaceuticals, CHO cells are under constant development in order to enhance their stability and productivity. The last decades saw a shift from empirical cell line optimization toward rational cell engineering using a growing number of large omics datasets to alter cell physiology on various levels. Especially proteomics workflows reached new levels in proteome coverage and data quality because of advances in high-resolution mass spectrometry instrumentation. One type of workflow concentrates on spatial proteomics by usage of subcellular fractionation of organelles with subsequent shotgun mass spectrometry proteomics and machine learning algorithms to determine the subcellular localization of large portions of the cellular proteome at a certain time point. Here, we present the first subcellular spatial proteome of a CHO-K1 cell line producing high titers of recombinant antibody in comparison to the spatial proteome of an antibody-producing plasma cell-derived myeloma cell line. Both cell lines show colocalization of immunoglobulin G chains with chaperones and proteins associated in protein glycosylation within the endoplasmic reticulum compartment. However, we report differences in the localization of proteins associated to vesicle-mediated transport, transcription, and translation, which may affect antibody production in both cell lines. Furthermore, pairing subcellular localization data with protein expression data revealed elevated protein masses for organelles in the secretory pathway in plasma cell-derived MPC-11 (Merwin plasma cell tumor-11) cells. Our study highlights the potential of subcellular spatial proteomics combined with protein expression as potent workflow to identify characteristics of highly efficient recombinant protein-expressing cell lines. Data are available via ProteomeXchange with identifier PXD029115.

SBML Level 3 package: Render, Version 1, Release 1.

Many software tools provide facilities for depicting reaction network diagrams in a visual form. Two aspects of such a visual diagram can be distinguished: the layout (i.e.: the positioning and connections) of the elements in the diagram, and the graphical form of the elements (for example, the glyphs used for symbols, the properties of the lines connecting them, and so on). This document describes the SBML Level 3 Render package that complements the SBML Level 3 Layout package and provides a means of capturing the precise rendering of the elements in a diagram. The SBML Level 3 Render package provides a flexible approach to rendering that is independent of both the underlying SBML model and the Layout information. There can be one block of render information that applies to all layouts or an additional block for each layout. Many of the elements used in the current render specification are based on corresponding elements from the SVG specification. This allows us to easily convert a combination of layout information and render information into a SVG drawing.

The Systems Biology Markup Language (SBML) Level 3 Package: Layout, Version 1 Core.

Many software tools provide facilities for depicting reaction network diagrams in a visual form. Two aspects of such a visual diagram can be distinguished: the layout (i.e.: the positioning and connections) of the elements in the diagram, and the graphical form of the elements (for example, the glyphs used for symbols, the properties of the lines connecting them, and so on). For software tools that also read and write models in SBML (Systems Biology Markup Language) format, a common need is to store the network diagram together with the SBML representation of the model. This in turn raises the question of how to encode the layout and the rendering of these diagrams. The SBML Level 3 Version 1 Core specification does not provide a mechanism for explicitly encoding diagrams, but it does provide a mechanism for SBML packages to extend the Core specification and add additional syntactical constructs. The Layout package for SBML Level 3 adds the necessary features to SBML so that diagram layouts can be encoded in SBML files, and a companion package called SBML Rendering specifies how the graphical rendering of elements can be encoded. The SBML Layout package is based on the principle that reaction network diagrams should be described as representations of entities such as species and reactions (with direct links to the underlying SBML elements), and not as arbitrary drawings or graphs; for this reason, existing languages for the description of vector drawings (such as SVG) or general graphs (such as GraphML) cannot be used.

A Systems Biology Study on NFκB Signaling in Primary Mouse Hepatocytes.

The cytokine tumor necrosis factor-alpha (TNFα) is one of the key factors during the priming phase of liver regeneration as well as in hepatocarcinogenesis. TNFα activates the nuclear factor κ-light-chain-enhancer of activated B cells (NFκB) signaling pathway and contributes to the conversion of quiescent hepatocytes to activated hepatocytes that are able to proliferate in response to growth factor stimulation. Different mathematical models have been previously established for TNFα/NFκB signaling in the context of tumor cells. Combining these mathematical models with time-resolved measurements of expression and phosphorylation of TNFα/NFκB pathway constituents in primary mouse hepatocytes revealed that an additional phosphorylation step of the NFκB isoform p65 has to be considered in the mathematical model in order to sufficiently describe the dynamics of pathway activation in the primary cells. Also, we addressed the role of basal protein turnover by experimentally measuring the degradation rate of pivotal players in the absence of TNFα and including this information in the model. To elucidate the impact of variations in the protein degradation rates on TNFα/NFκB signaling on the overall dynamic behavior we used global sensitivity analysis that accounts for parameter uncertainties and showed that degradation and translation of p65 had a major impact on the amplitude and the integral of p65 phosphorylation. Finally, our mathematical model of TNFα/NFκB signaling was able to predict the time-course of the complex formation of p65 and of the inhibitor of NFκB (IκB) in primary mouse hepatocytes, which was experimentally verified. Hence, we here present a mathematical model for TNFα/NFκB signaling in primary mouse hepatocytes that provides an important basis to quantitatively disentangle the complex interplay of multiple factors in liver regeneration and tumorigenesis.

The Systems Biology Graphical Notation.

Circuit diagrams and Unified Modeling Language diagrams are just two examples of standard visual languages that help accelerate work by promoting regularity, removing ambiguity and enabling software tool support for communication of complex information. Ironically, despite having one of the highest ratios of graphical to textual information, biology still lacks standard graphical notations. The recent deluge of biological knowledge makes addressing this deficit a pressing concern. Toward this goal, we present the Systems Biology Graphical Notation (SBGN), a visual language developed by a community of biochemists, modelers and computer scientists. SBGN consists of three complementary languages: process diagram, entity relationship diagram and activity flow diagram. Together they enable scientists to represent networks of biochemical interactions in a standard, unambiguous way. We believe that SBGN will foster efficient and accurate representation, visualization, storage, exchange and reuse of information on all kinds of biological knowledge, from gene regulation, to metabolism, to cellular signaling.

Computational modeling of biochemical networks using COPASI.

Computational modeling and simulation of biochemical networks is at the core of systems biology and this includes many types of analyses that can aid understanding of how these systems work. COPASI is a generic software package for modeling and simulation of biochemical networks which provides many of these analyses in convenient ways that do not require the user to program or to have deep knowledge of the numerical algorithms. Here we provide a description of how these modeling techniques can be applied to biochemical models using COPASI. The focus is both on practical aspects of software usage as well as on the utility of these analyses in aiding biological understanding. Practical examples are described for steady-state and time-course simulations, stoichiometric analyses, parameter scanning, sensitivity analysis (including metabolic control analysis), global optimization, parameter estimation, and stochastic simulation. The examples used are all published models that are available in the BioModels database in SBML format.

SYCAMORE--a systems biology computational analysis and modeling research environment.

UNLABELLED: SYCAMORE is a browser-based application that facilitates construction, simulation and analysis of kinetic models in systems biology. Thus, it allows e.g. database supported modelling, basic model checking and the estimation of unknown kinetic parameters based on protein structures. In addition, it offers some guidance in order to allow non-expert users to perform basic computational modelling tasks. AVAILABILITY: SYCAMORE is freely available for academic use at http://sycamore.eml.org. Commercial users may acquire a license. CONTACT: ursula.kummer@bioquant.uni-heidelberg.de.

COPASI--a COmplex PAthway SImulator.

MOTIVATION: Simulation and modeling is becoming a standard approach to understand complex biochemical processes. Therefore, there is a big need for software tools that allow access to diverse simulation and modeling methods as well as support for the usage of these methods. RESULTS: Here, we present COPASI, a platform-independent and user-friendly biochemical simulator that offers several unique features. We discuss numerical issues with these features; in particular, the criteria to switch between stochastic and deterministic simulation methods, hybrid deterministic-stochastic methods, and the importance of random number generator numerical resolution in stochastic simulation. AVAILABILITY: The complete software is available in binary (executable) for MS Windows, OS X, Linux (Intel) and Sun Solaris (SPARC), as well as the full source code under an open source license from http://www.copasi.org.

A model diagram layout extension for SBML.

MOTIVATION: Since the knowledge about processes in living cells is increasing, modelling and simulation techniques are used to get new insights into these complex processes. During the last few years, the SBML file format has gained in popularity and support as a means of exchanging model data between the different modelling and simulation tools. In addition to specifying the model as a set of equations, many modern modelling tools allow the user to create and to interact with the model in the form of a reaction graph. Unfortunately, the SBML file format does not provide for the storage of this graph data along with the mathematical description of the model. RESULTS: Therefore, we developed an extension to the SBML file format that makes it possible to store such layout information which describes position and size of objects in the graphical representation. AVAILABILITY: The complete specification can be found on (http://projects.villa-bosch.de/bcb/sbml/ (SBML Layout Extension documentation, 2005). Additionally, a complete implementation exists as part of libSBML (2006, http://www.sbml.org/software/libsbml/).

CombAlign: a protein sequence comparison algorithm considering recombinations.

The basic linear treatment of sequence comparisons limits the ability of contemporary sequence alignment algorithms to detect non-order-conserving recombinations. Here, we introduce the algorithm combAlign which addresses the assessment of pairwise sequence similarity on non-order-conserving recombinations on a large scale. Emphasizing a two-level approach, combAlign first detects locally well conserved subsequences in a target and a source sequence. Subsequently, the relative placement of alignments is mapped to a graph. Concatenating local alignments to reassemble the target sequence to the fullest extent, the maximum scoring path through the graph denotes the best attainable combAlignment. Parameters influencing this process can be set to meet the user's specific demands. combAlign is applied to examples demonstrating the possibility to reflect evolutionary kinship of proteins even if their domains and motifs are strongly rearranged.

Comparison of the dynamics of substrate access channels in three cytochrome P450s reveals different opening mechanisms and a novel functional role for a buried arginine.

Understanding the mechanism and specificity of substrate binding in the cytochrome P450 (P450) superfamily is an important step toward explaining its key role in drug metabolism, toxicity, xenobiotic degradation, and several biosynthetic pathways. Here we investigate the ligand exit pathways and mechanisms of P450cam (CYP101), P450BM-3 (CYP102), and P450eryF (CYP107A1) by using random expulsion molecular dynamics and classical molecular dynamics simulations. Although several different pathways are found for each protein, one pathway is common to all three. The mechanism of ligand exit along this pathway is, however, quite different in the three different proteins. For P450cam, small backbone conformational changes, in combination with aromatic side chain rotation, allow for the passage of the rather rigid, compact, and hydrophobic substrate, camphor. In P450BM-3, larger transient backbone changes are observed on ligand exit. R47, situated at the entrance to the channel, appears important in guiding negatively charged fatty acid substrates in and out of the active site. In P450eryF, an isolated buried arginine, R185, stabilized by four hydrogen bonds to backbone carbonyl oxygen atoms, is located in the exit channel and is identified as having a particularly unusual functionality, dynamically gating channel opening. The results for these three P450s suggest that the channel opening mechanisms are adjusted to the physico-chemical properties of the substrate and can kinetically modulate protein-substrate specificity.