Constraint-Based Model of Shewanella oneidensis MR-1 Metabolism: A Tool for Data Analysis and Hypothesis Generation

Shewanellae are gram-negative facultatively anaerobic metal-reducing bacteria commonly found in chemically (i.e., redox) stratified environments. Occupying such niches requires the ability to rapidly acclimate to changes in electron donor/acceptor type and availability; hence, the ability to compete and thrive in such environments must ultimately be reflected in the organization and utilization of electron transfer networks, as well as central and peripheral carbon metabolism. To understand how Shewanella oneidensis MR-1 utilizes its resources, the metabolic network was reconstructed. The resulting network consists of 774 reactions, 783 genes, and 634 unique metabolites and contains biosynthesis pathways for all cell constituents. Using constraint-based modeling, we investigated aerobic growth of S. oneidensis MR-1 on numerous carbon sources. To achieve this, we (i) used experimental data to formulate a biomass equation and estimate cellular ATP requirements, (ii) developed an approach to identify cycles (such as futile cycles and circulations), (iii) classified how reaction usage affects cellular growth, (iv) predicted cellular biomass yields on different carbon sources and compared model predictions to experimental measurements, and (v) used experimental results to refine metabolic fluxes for growth on lactate. The results revealed that aerobic lactate-grown cells of S. oneidensis MR-1 used less efficient enzymes to couple electron transport to proton motive force generation, and possibly operated at least one futile cycle involving malic enzymes. Several examples are provided whereby model predictions were validated by experimental data, in particular the role of serine hydroxymethyltransferase and glycine cleavage system in the metabolism of one-carbon units, and growth on different sources of carbon and energy. This work illustrates how integration of computational and experimental efforts facilitates the understanding of microbial metabolism at a systems level.     

Characterization of Metabolism in the Fe(III)-Reducing Organism Geobacter sulfurreducens by Constraint-Based Modeling

Geobacter sulfurreducens is a well-studied representative of the Geobacteraceae, which play a critical role in organic matter oxidation coupled to Fe(III) reduction, bioremediation of groundwater contaminated with organics or metals, and electricity production from waste organic matter. In order to investigate G. sulfurreducens central metabolism and electron transport, a metabolic model which integrated genome-based predictions with available genetic and physiological data was developed via the constraint-based modeling approach. Evaluation of the rates of proton production and consumption in the extracellular and cytoplasmic compartments revealed that energy conservation with extracellular electron acceptors, such as Fe(III), was limited relative to that associated with intracellular acceptors. This limitation was attributed to lack of cytoplasmic proton consumption during reduction of extracellular electron acceptors. Model-based analysis of the metabolic cost of producing an extracellular electron shuttle to promote electron transfer to insoluble Fe(III) oxides demonstrated why Geobacter species, which do not produce shuttles, have an energetic advantage over shuttle-producing Fe(III) reducers in subsurface environments. In silico analysis also revealed that the metabolic network of G. sulfurreducens could synthesize amino acids more efficiently than that of Escherichia coli due to the presence of a pyruvate-ferredoxin oxidoreductase, which catalyzes synthesis of pyruvate from acetate and carbon dioxide in a single step. In silico phenotypic analysis of deletion mutants demonstrated the capability of the model to explore the flexibility of G. sulfurreducens central metabolism and correctly predict mutant phenotypes. These results demonstrate that iterative modeling coupled with experimentation can accelerate the understanding of the physiology of poorly studied but environmentally relevant organisms and may help optimize their practical applications.     

Dynamic Model for Characterizing Contractile Behaviors and Mechanical Properties of a Cardiomyocyte

Studies on the contractile dynamics of heart cells have attracted broad attention for the development of both heart disease therapies and cardiomyocyte-actuated micro-robotics. In this study, a linear dynamic model of a single cardiomyocyte cell was proposed at the subcellular scale to characterize the contractile behaviors of heart cells, with system parameters representing the mechanical properties of the subcellular components of living cardiomyocytes. The system parameters of the dynamic model were identified with the cellular beating pattern measured by a scanning ion conductance microscope. The experiments were implemented with cardiomyocytes in one control group and two experimental groups with the drugs cytochalasin-D or nocodazole, to identify the system parameters of the model based on scanning ion conductance microscope measurements, measurement of the cellular Young’s modulus with atomic force microscopy indentation, measurement of cellular contraction forces using the micro-pillar technique, and immunofluorescence staining and imaging of the cytoskeleton. The proposed mathematical model was both indirectly and qualitatively verified by the variation in cytoskeleton, beating amplitude, and contractility of cardiomyocytes among the control and the experimental groups, as well as directly and quantitatively validated by the simulation and the significant consistency of 90.5% in the comparison between the ratios of the Young’s modulus and the equivalent comprehensive cellular elasticities of cells in the experimental groups to those in the control group. Apart from mechanical properties (mass, elasticity, and viscosity) of subcellular structures, other properties of cardiomyocytes have also been studied, such as the properties of the relative action potential pattern and cellular beating frequency. This work has potential implications for research on cytobiology, drug screening, mechanisms of the heart, and cardiomyocyte-based bio-syncretic robotics.     

Characterizing Urban Household Waste Generation and Metabolism Considering Community Stratification in a Rapid Urbanizing Area of China

The relationship between social stratification and municipal solid waste generation remains uncertain under current rapid urbanization. Based on a multi-object spatial sampling technique, we selected 191 households in a rapidly urbanizing area of Xiamen, China. The selected communities were classified into three types: work-unit, transitional, and commercial communities in the context of housing policy reform in China. Field survey data were used to characterize household waste generation patterns considering community stratification. Our results revealed a disparity in waste generation profiles among different households. The three community types differed with respect to family income, living area, religious affiliation, and homeowner occupation. Income, family structure, and lifestyle caused significant differences in waste generation among work-unit, transitional, and commercial communities, respectively. Urban waste generation patterns are expected to evolve due to accelerating urbanization and associated community transition. A multi-scale integrated analysis of societal and ecosystem metabolism approach was applied to waste metabolism linking it to particular socioeconomic conditions that influence material flows and their evolution. Waste metabolism, both pace and density, was highest for family structure driven patterns, followed by lifestyle and income driven. The results will guide community-specific management policies in rapidly urbanizing areas.     

Enrichment of a dioxin-dehalogenating Dehalococcoides species in two-liquid phase cultures

Enrichment cultures capable of reductively dechlorinating 1,2,4-trichlorodibenzo-p-dioxin (1,2,4-TrCDD) were shown to dechlorinate 1,2,3-trichlorobenzene (1,2,3-TrCB) to 1,3-dichlorobenzene. To test if this activity can be used to enrich for dioxin-dechlorinating bacteria, a two-liquid phase cultivation with 200 mM 1,2,3-TrCB dissolved in hexadecane was established. During the dechlorination of 1,2,3-TrCB, the number of 1,2,4-TrCDD-dechlorinating bacteria increased by four orders of magnitude, eventually accounting for 11% of the total cell number. Characterization of the bacterial communities of the initial dioxin-dechlorinating culture and of the trichlorobenzene enrichments by restriction fragment length polymorphism (RFLP) analysis of cloned 16S rRNA genes revealed a proportional increase of nine different sequence types, one representing a Dehalococcoides strain. Inhibition of methanogens further enhanced the rate of chlorobenzene dehalogenation and also resulted in a rapid dechlorination of 1,2,3,4-tetrachlorodibenzo-p-dioxin that was applied via a hexadecane phase. The further enrichment was monitored by terminal RFLP, quantitative real-time PCR and microscopy, and aimed at the reduction of the accompanying non-dehalogenating populations by using different combinations of electron donors and the application of antibiotics. Hydrogen as the sole electron donor proved to be less efficient due to the co-enrichment of acetogens. The novel Dehalococcoides strain DCMB5 was enriched up to 50% by the cultivation with organic acids, hydrogen and vancomycin, and was finally purified by conventional isolation techniques.     

Dynamics of Parameters Characterizing the Energy Metabolism of the Rat Cerebral Cortex At Late Stages of Ontogeny

Parameters that characterize the energy metabolism of the brain—the field potential and temperature of the cerebral cortex—were studied in rats of different ages. The results showed that, at late ontogenetic stages, these nonspecific parameters of energy metabolism undergo multiphasic changes which are qualitatively similar in both hemispheres. The interhemispheric temperature and electrophysiological gradients are maintained throughout individual development, which is regarded as a factor accounting for asymmetry in the aging of the cerebral hemispheres. The problem of age-related changes in energy expenditures for the maintenance of these interhemispheric gradients is discussed. It is suggested that the multiphasic dynamics of the parameters studied are associated with changes in the type of control over metabolic processes and cerebral functions providing for the maintenance of homeostasis in different periods of life.     

Characterizing activity-dependent processes with a piecewise exponential model

The response of some biological processes is dependent on the frequency of stimulation. With first-order processes, the response is driven exponentially to an equilibrium determined by the value of the driving function. When the stimulus or driving function is viewed as switching between constant values the resulting response is piecewise exponential. With periodic excitation, the time course of a point fixed in time relative to the initiation time of each stimulus is shown to be exponential with a rate and steady state that are linearly dependent on the rates and equilibria associated with each component exponential. This linearity can be exploited and leads to a simple estimation procedure for the apparent state-dependent rates.     

Union of Geometric Constraint-Based Simulations with Molecular Dynamics for Protein Structure Prediction

Although proteins are a fundamental unit in biology, the mechanism by which proteins fold into their native state is not well understood. In this work, we explore the assembly of secondary structure units via geometric constraint-based simulations and the effect of refinement of assembled structures using reservoir replica exchange molecular dynamics. Our approach uses two crucial features of these methods: i), geometric simulations speed up the search for nativelike topologies as there are no energy barriers to overcome; and ii), molecular dynamics identifies the low free energy structures and further refines these structures toward the actual native conformation. We use eight α-, β-, and α/β-proteins to test our method. The geometric simulations of our test set result in an average RMSD from native of 3.7 Å and this further reduces to 2.7 Å after refinement. We also explore the question of robustness of assembly for inaccurate (shifted and shortened) secondary structure. We find that the RMSD from native is highly dependent on the accuracy of secondary structure input, and even slightly shifting the location of secondary structure along the amino acid sequence can lead to a rapid decrease in RMSD to native due to incorrect packing.     

Depot-Specific Changes in Fat Metabolism with Aging in a Type 2 Diabetic Animal Model

Visceral fat accretion is a hallmark of aging and is associated with aging-induced metabolic dysfunction. PPARγ agonist was reported to improve insulin sensitivity by redistributing fat from visceral fat to subcutaneous fat. The purpose of this study was to investigate the underlying mechanisms by which aging affects adipose tissue remodeling in a type 2 diabetic animal model and through which PPARγ activation modulates aging-related fat tissue distribution. At the ages of 21, 31 and 43 weeks, OLETF rats as an animal model of type 2 diabetes were evaluated for aging-related effects on adipose tissue metabolism in subcutaneous and visceral fat depots. During aging, the ratio of visceral fat weight to subcutaneous fat weight (V/S ratio) increased. Aging significantly increased the mRNA expression of genes involved in lipogenesis such as lipoprotein lipase, fatty acid binding protein aP2, lipin 1, and diacylglycerol acyltransferase 1, which were more prominent in visceral fat than subcutaneous fat. The mRNA expression of adipose triglyceride lipase, which is involved in basal lipolysis and fatty acid recycling, was also increased, more in visceral fat compared to subcutaneous fat during aging. The mRNA levels of the genes associated with lipid oxidation were increased, whereas the mRNA levels of genes associated with energy expenditure showed no significant change during aging. PPARγ agonist treatment in OLETF rats resulted in fat redistribution with a decreasing V/S ratio and improved glucose intolerance. The genes involved in lipogenesis decreased in visceral fat of the PPARγ agonist-treated rats. During aging, fat distribution was changed by stimulating lipid uptake and esterification in visceral fat rather than subcutaneous fat, and by altering the lipid oxidation.     

A Model of Leaf Carbon Metabolism

A model relating the levels of some carbon metabolites in theleaves of C₃ plant species to the light and carbon dioxide environmentof the leaf is constructed, and provides a basis for quantitativeinvestigation of the diurnal variations in the carbon metabolitelevels. The model also predicts relationships between the respiratoryactivity of the leaf during the night and the preceding photosyntheticactivity of the leaf.     

A Dynamical Model of Lipoprotein Metabolism

We present a dynamical model of lipoprotein metabolism derived by combining a cascading process in the blood stream and cellular level regulatory dynamics. We analyse the existence and stability of equilibria and show that this low-dimensional, nonlinear model exhibits bistability between a low and a high cholesterol state. A sensitivity analysis indicates that the intracellular concentration of cholesterol is robust to parametric variations while the plasma cholesterol can vary widely. We show how the dynamical response to time-dependent inputs can be used to diagnose the state of the system. We also establish the connection between parameters in the system and medical and genetic conditions.     

Responses to Light Intensity in a Genome-Scale Model of Rice Metabolism

We describe the construction and analysis of a genome-scale metabolic model representing a developing leaf cell of rice (Oryza sativa) primarily derived from the annotations in the RiceCyc database. We used flux balance analysis to determine that the model represents a network capable of producing biomass precursors (amino acids, nucleotides, lipid, starch, cellulose, and lignin) in experimentally reported proportions, using carbon dioxide as the sole carbon source. We then repeated the analysis over a range of photon flux values to examine responses in the solutions. The resulting flux distributions show that (1) redox shuttles between the chloroplast, cytosol, and mitochondrion may play a significant role at low light levels, (2) photorespiration can act to dissipate excess energy at high light levels, and (3) the role of mitochondrial metabolism is likely to vary considerably according to the balance between energy demand and availability. It is notable that these organelle interactions, consistent with many experimental observations, arise solely as a result of the need for mass and energy balancing without any explicit assumptions concerning kinetic or other regulatory mechanisms.Rice (Oryza sativa) makes up nearly 20% of the total caloric intake for the human population as a whole; the income of more than 100 million households in developing countries depends on rice cultivation. Although rice yield has increased, though gradually more slowly, during the last four decades, the world population continues to grow, while the land and water resources for cultivation are declining, leading to a need for high-yielding, stress-tolerant, nutrient-rich rice cultivars (Nguyen and Ferrero, 2006).Researchers are trying to meet the challenges of improving production in different ways. Some of the efforts include (1) identifying the stress-tolerant rice varieties and stress-responsive genes (Xiang et al., 2007), (2) producing a “Green Super Rice” combining, in a single plant, many different favorable characteristics from the large number of available strains and cultivars, guided by molecular marker-based selection (Zhang, 2007), (3) introducing the genes of C₄ plant to change the leaf anatomy of rice and hence improving the photosynthesis (Kajala et al., 2011), and (4) producing vitamin A-enriched golden rice (Al-Babili and Beyer, 2005). In addition, current research on the genetic basis of signaling between nitrogen-fixing soil bacteria and legumes (Xie et al., 2012) has the potential to allow the engineering of nodule formation in cereal crops such as rice and wheat (Triticum aestivum).Here, we present a genome-scale model of rice metabolism and examine its responses to changing light availability. Because rice is also a model organism for other cereal crops, such as wheat, this effort should help researchers to understand the biochemistry of a photosynthetic crop plant as well as to compare it with other plants. In addition, the metabolic model of rice, which is the second metabolic model of a crop plant, can be used as a template for comparing the metabolism of different varieties of rice that are pathogen tolerant, drought tolerant, lower or higher yield, etc., and thus, it may also help in identifying characteristics of individual varieties that may assist rice biotechnologists to breed the desired rice crop.     

A gene from the mesophilic bacterium Dehalococcoides ethenogenes encodes a novel mannosylglycerate synthase

Mannosylglycerate (MG) is a common compatible solute found in thermophilic and hyperthermophilic prokaryotes. In this study we characterized a mesophilic and bifunctional mannosylglycerate synthase (MGSD) encoded in the genome of the bacterium Dehalococcoides ethenogenes. mgsD encodes two domains with extensive homology to mannosyl-3-phosphoglycerate synthase (MPGS, EC 2.4.1.217) and to mannosyl-3-phosphoglycerate phosphatase (MPGP, EC 3.1.3.70), which catalyze the consecutive synthesis and dephosphorylation of mannosyl-3-phosphoglycerate to yield MG in Pyrococcus horikoshii, Thermus thermophilus, and Rhodothermus marinus. The bifunctional MGSD was overproduced in Escherichia coli, and we confirmed the combined MPGS and MPGP activities of the recombinant enzyme. The optimum activity of the enzyme was at 50 degrees C. To examine the properties of each catalytic domain of MGSD, we expressed them separately in E. coli. The monofunctional MPGS was unstable, while the MPGP was stable and was characterized. Dehalococcoides ethenogenes cannot be grown sufficiently to identify intracellular compatible solutes, and E. coli harboring MGSD did not accumulate MG. However, Saccharomyces cerevisiae expressing mgsD accumulated MG, confirming that this gene product can synthesize this compatible solute and arguing for a role in osmotic adjustment in the natural host. We did not detect MGSD activity in cell extracts of S. cerevisiae. Here we describe the first gene and enzyme for the synthesis of MG from a mesophilic microorganism and discuss the possible evolution of this bifunctional MGSD by lateral gene transfer from thermophilic and hyperthermophilic organisms.     

Characterizing bacterial glycoproteins with LC-MS

Introduction: Though eukaryotic glycoproteins have been studied since their discovery in the 1930s, the first bacterial glycoprotein was not identified until the 1970s. As a result, their role in bacterial pathogenesis is still not well understood and they remain an understudied component of bacterial virulence. In recent years, mass spectrometry has emerged as a leading technology for the study of bacterial glycoproteins, largely due to its sensitivity and versatility.

Areas covered: Identification and comprehensive characterization of bacterial glycoproteins usually requires multiple complementary mass spectrometry approaches, including intact protein analysis, top-down analysis, and bottom-up methods used in combination with specialized liquid chromatography. This review provides an overview of liquid chromatography separation technologies, as well as current and emerging mass spectrometry approaches used specifically for bacterial glycoprotein identification and characterization.

Expert commentary: Bacterial glycoproteins may have significant clinical utility as a result of their unique structures and exposure on the surface of the cells. Better understanding of these glycoconjugates is an essential first step towards that goal. These often unique structures, and by extension the key enzymes involved in their synthesis, represent promising targets for novel antimicrobials, while unique carbohydrate structures may be used as antigens in vaccines or as biomarkers.