Quanyu Zhao

Optimizing the formation of in vitro sponge primmorphs from the Chinese sponge Stylotella agminata (Ridley).

The establishment and optimization of in vitro primmorph formation from a Chinese sponge, Stylotella agminata (Ridley), collected from the South China Sea, were investigated. Our aims were to identify the key factors affecting primmorph formation in this species and to optimize the technique for developing an in vitro primmorph culture system. The size of dissociated cells from S. agminata is relatively small, in the range between 5 and 10 microm. Round-shaped primmorphs of less than 100 microm were formed 3 days after transferring the dissociated cells into seawater containing Ca(2+) and Mg(2+). The effect of various cell dissociation conditions, inoculum cell density, concentration of antibiotics, pH, and temperature was further investigated upon the formation of primmorphs. The time required for primmorph formation, primmorph size distribution, and the proliferating capability were microscopically documented. Healthy sponge S. agminata, inoculum cell density and culture temperature play a critical role for the successful formation of primmorphs and that the microbial contamination will have to be controlled.

Integration of enzyme activities into metabolic flux distributions by elementary mode analysis

BackgroundIn systems biology, network-based pathway analysis facilitates understanding or designing metabolic systems and enables prediction of metabolic flux distributions. Network-based flux analysis requires considering not only pathway architectures but also the proteome or transcriptome to predict flux distributions, because recombinant microbes significantly change the distribution of gene expressions. The current problem is how to integrate such heterogeneous data to build a network-based model.ResultsTo link enzyme activity data to flux distributions of metabolic networks, we have proposed Enzyme Control Flux (ECF), a novel model that integrates enzyme activity into elementary mode analysis (EMA). ECF presents the power-law formula describing how changes in enzyme activities between wild-type and a mutant are related to changes in the elementary mode coefficients (EMCs). To validate the feasibility of ECF, we integrated enzyme activity data into the EMCs of Escherichia coli and Bacillus subtilis wild-type. The ECF model effectively uses an enzyme activity profile to estimate the flux distribution of the mutants and the increase in the number of incorporated enzyme activities decreases the model error of ECF.ConclusionThe ECF model is a non-mechanistic and static model to link an enzyme activity profile to a metabolic flux distribution by introducing the power-law formula into EMA, suggesting that the change in an enzyme profile rather reflects the change in the flux distribution. The ECF model is highly applicable to the central metabolism in knockout mutants of E. coli and B. subtilis.

Maximum entropy decomposition of flux distribution at steady state to elementary modes

Enzyme Control Flux (ECF) is a method of correlating enzyme activity and flux distribution. The advantage of ECF is that the measurement integrates proteome data with metabolic flux analysis through Elementary Modes (EMs). But there are a few methods of effectively determining the Elementary Mode Coefficient (EMC) in cases where no objective biological function is available. Therefore, we proposed a new algorithm implementing the maximum entropy principle (MEP) as an objective function for estimating the EMC. To demonstrate the feasibility of using the MEP in this way, we compared it with Linear Programming and Quadratic Programming for modeling the metabolic networks of Chinese Hamster Ovary, Escherichia coli, and Saccharomyces cerevisiae cells. The use of the MEP presents the most plausible distribution of EMCs in the absence of any biological hypotheses describing the physiological state of cells, thereby enhancing the prediction accuracy of the flux distribution in various mutants.

Extended CADLIVE: a novel graphical notation for design of biochemical network maps and computational pathway analysis

Biochemical network maps are helpful for understanding the mechanism of how a collection of biochemical reactions generate particular functions within a cell. We developed a new and computationally feasible notation that enables drawing a wide resolution map from the domain-level reactions to phenomenological events and implemented it as the extended GUI network constructor of CADLIVE (Computer-Aided Design of LIVing systEms). The new notation presents ‘Domain expansion’ for proteins and RNAs, ‘Virtual reaction and nodes’ that are responsible for illustrating domain-based interaction and ‘InnerLink’ that links real complex nodes to virtual nodes to illustrate the exact components of the real complex. A modular box is also presented that packs related reactions as a module or a subnetwork, which gives CADLIVE a capability to draw biochemical maps in a hierarchical modular architecture. Furthermore, we developed a pathway search module for virtual knockout mutants as a built-in application of CADLIVE. This module analyzes gene function in the same way as molecular genetics, which simulates a change in mutant phenotypes or confirms the validity of the network map. The extended CADLIVE with the newly proposed notation is demonstrated to be feasible for computational simulation and analysis.

Biopotentials of marine sponges from China oceans: past and future

An extensive literature survey of over 17 Journals was carried out on Chinese sponges and their natural products in the period from 1980 to 2001. This review is thus intended to provide the first thorough overview of research on marine sponges from China Ocean territories. Information is provided about the rather-limited taxonomic study of Chinese marine sponges, with an analysis on their distribution and diversity. Research findings on the natural products and their bioactivity screening from Chinese sponges are summarized. The weaknesses, gaps and problems in the past R&D program of Chinese sponges are identified, which point to the future opportunities in exploiting these huge untapped sponge resources. The report is expected to serve as an entry point for understanding Chinese sponges and for furthering R&D on their bioactive compounds for new drug development.

Genetic modification of flux for flux prediction of mutants

MOTIVATION Gene deletion and overexpression are critical technologies for designing or improving the metabolic flux distribution of microbes. Some algorithms including flux balance analysis (FBA) and minimization of metabolic adjustment (MOMA) predict a flux distribution from a stoichiometric matrix in the mutants in which some metabolic genes are deleted or non-functional, but there are few algorithms that predict how a broad range of genetic modifications, such as over- and underexpression of metabolic genes, alters the phenotypes of the mutants at the metabolic flux level. RESULTS To overcome such existing limitations, we develop a novel algorithm that predicts the flux distribution of the mutants with a broad range of genetic modification, based on elementary mode analysis. It is denoted as genetic modification of flux (GMF), which couples two algorithms that we have developed: modified control effective flux (mCEF) and enzyme control flux (ECF). mCEF is proposed based on CEF to estimate the gene expression patterns in genetically modified mutants in terms of specific biological functions. GMF is demonstrated to predict the flux distribution of not only gene deletion mutants, but also the mutants with underexpressed and overexpressed genes in Escherichia coli and Corynebacterium glutamicum. This achieves breakthrough in the a priori flux prediction of a broad range of genetically modified mutants. SUPPLEMENTARY INFORMATION Supplementary file and programs are available at Bioinformatics online or http://www.cadlive.jp.

Formulation of a basal medium for primary cell culture of the marine sponge Hymeniacidon perleve.

Marine sponge cell culture is a potential route for the sustainable production of sponge‐derived bioproducts. Development of a basal culture medium is a prerequisite for the attachment, spreading, and growth of sponge cells in vitro. With the limited knowledge available on nutrient requirements for sponge cells, a series of statistical experimental designs has been employed to screen and optimize the critical nutrient components including inorganic salts (ferric ion, zinc ion, silicate, and NaCl), amino acids (glycine, glutamine, and aspartic acid), sugars (glucose, sorbitol, and sodium pyruvate), vitamin C, and mammalian cell medium (DMEM and RPMI 1640) using MTT assay in 96‐well plates. The marine sponge Hymeniacidon perleve was used as a model system. Plackett‐Burman design was used for the initial screening, which identified the significant factors of ferric ion, NaCl, and vitamin C. These three factors were selected for further optimization by Uniform Design and Response Surface Methodology (RSM), respectively. A basal medium was finally established, which supported an over 100% increase in viability of sponge cells.

Use of maximum entropy principle with Lagrange multipliers extends the feasibility of elementary mode analysis

Elementary mode (EM) analysis is potentially effective in integrating transcriptome or proteome data into metabolic network analyses and in exploring the mechanism of how phenotypic or metabolic flux distribution is changed with respect to environmental and genetic perturbations. The EM coefficients (EMCs) indicate the quantitative contribution of their associated EMs and can be estimated by maximizing Shannons entropy as a general objective function in our previous study, but the use of EMCs is still restricted to a relatively small-scale networks. We propose a fast and universal method that optimizes hundreds of thousands of EMCs under the constraint of the Maximum entropy principle (MEP). Lagrange multipliers (LMs) are applied to maximize the Shannons entropy-based objective function, analytically solving each EMC as the function of LMs. Consequently, the number of such search variables, the EMC number, is dramatically reduced to the reaction number. To demonstrate the feasibility of the MEP with Lagrange multipliers (MEPLM), it is coupled with enzyme control flux (ECF) to predict the flux distributions of Escherichia coli and Saccharomycescerevisiae for different conditions (gene deletion, adaptive evolution, temperature, and dilution rate) and to provide a quantitative understanding of how metabolic or physiological states are changed in response to these genetic or environmental perturbations at the elementary mode level. It is shown that the ECF-based method is a feasible framework for the prediction of metabolic flux distribution by integrating enzyme activity data into EMs to genetic and environmental perturbations.

Attachment of marine sponge cells of Hymeniacidon perleve on microcarriers

Toward the development of an in vitro cultivation of marine sponge cells for sustainable production of bioactive metabolites, the attachment characteristics of marine sponge cells of Hymeniacidon perleve on three types of microcarriers, Hillex, Cytodex 3, and glass beads, were studied. Mixed cell population and enriched cell fractions of specific cell types by Ficoll gradient centrifugation (6%/8%/15%/20%) were also assessed. Cell attachment ratio (defined as the ratio of cells attached on microcarrier to the total number of cells in the culture) on glass beads is much higher than that on Cytodex 3 and Hillex for both mixed cell population and cell fraction at Ficoll 15–20% interface. The highest attachment ratio of 41% was obtained for the cell fraction at Ficoll 15–20% interface on glass beads, which was significantly higher than that of a mixed cell population (18%). The attachment kinetics on glass beads indicated that the attachment was completed within 1 h. Cell attachment ratio decreases with increase in cell‐to‐microcarrier ratio (3–30 cells/bead) and pH (7.6–9.0). The addition of serum and BSA (bovine serum albumin) reduced the cell attachment on glass beads.

Estimation of Intracellular Flux Distribution under Underdetermined and Uncertain Conditions by Maximum Entropy Principle

Abstract In silico simulation is much more powerful and reliable than before for the bioprocess analysis and optimization in the fields of metabolic engineering and systems biology. The intracellular flux distribution could be estimated by Metabolic Flux Analysis (MFA) and Elementary Mode Analysis (EMA). It is always difficult to obtain an accurate flux distribution due to the insufficiencies, the measurement errors of the experimental data and the redundancy of EMs. An algorithm has been proposed to determine the Elementary Mode Coefficients (EMCs) by the maximum entropy principle (MEP). The intracellular flux distribution is calculated from the extracellular fluxes under underdetermined and uncertain conditions. To demonstrate the feasibility of this algorithm, it is used to estimate of the intracellular flux distribution for hybridoma, Escherichia coli and Bacillus subtilis. The MEP algorithm avoids any physiological hypotheses for the cellular states. It is reliable and feasible for the estimation of the intracellular flux distribution compared with other objective functions.