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B O Palsson

Publications and source records attributed to B O Palsson.

At least 19 recordsLinked to original sources
PubMed2006

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.

Amino Acids↗
PubMed2004

Properties of metabolic networks: structure versus function.

Biological data from high-throughput technologies describing the network components (genes, proteins, metabolites) and their associated interactions have driven the reconstruction and study of structural (topological) properties of large-scale biological networks. In this article, we address the relation of the functional and structural properties by using extensively experimentally validated genome-scale metabolic network models to compute observable functional states of a microorganism and compare the "structure versus function" attributes of metabolic networks. It is observed that, functionally speaking, the essentiality of reactions in a node is not correlated with node connectivity as structural analyses of other biological networks have suggested. These findings are illustrated with the analysis of the genome-scale biochemical networks of three species with distinct modes of metabolism. These results also suggest fundamental differences among different biological networks arising out of their representation and functional constraints.

Algorithms↗
PubMed2003

Quantitative analysis of Escherichia coli metabolic phenotypes within the context of phenotypic phase planes.

In silico models of Escherichia coli metabolism have been developed to predict metabolic behavior and propose experimentally testable hypotheses. However, a thorough assessment of the metabolic phenotype requires well-designed experimentation and reproducible experimental techniques. A method for the quantitative analysis of E. coli metabolism in vivo within the framework of in silico phenotypic phase plane analysis is presented. Using this approach, we have quantitatively studied E. coli metabolism in various environmental conditions and nutritional media. Our experimental methodology, in combination with steady-state metabolic models, can be used to study biological properties and evaluate the metabolic capabilities of microbes.

Aerobiosis↗
PubMed2001

Metabolic modeling of microbial strains in silico.

The large volume of genome-scale data that is being produced and made available in databases on the World Wide Web is demanding the development of integrated mathematical models of cellular processes. The analysis of reconstructed metabolic networks as systems leads to the development of an in silico or computer representation of collections of cellular metabolic constituents, their interactions and their integrated function as a whole. The use of quantitative analysis methods to generate testable hypotheses and drive experimentation at a whole-genome level signals the advent of a systemic modeling approach to cellular and molecular biology.

Genome↗
PubMed2001

In silico predictions of Escherichia coli metabolic capabilities are consistent with experimental data.

A significant goal in the post-genome era is to relate the annotated genome sequence to the physiological functions of a cell. Working from the annotated genome sequence, as well as biochemical and physiological information, it is possible to reconstruct complete metabolic networks. Furthermore, computational methods have been developed to interpret and predict the optimal performance of a metabolic network under a range of growth conditions. We have tested the hypothesis that Escherichia coli uses its metabolism to grow at a maximal rate using the E. coli MG1655 metabolic reconstruction. Based on this hypothesis, we formulated experiments that describe the quantitative relationship between a primary carbon source (acetate or succinate) uptake rate, oxygen uptake rate, and maximal cellular growth rate. We found that the experimental data were consistent with the stated hypothesis, namely that the E. coli metabolic network is optimized to maximize growth under the experimental conditions considered. This study thus demonstrates how the combination of in silico and experimental biology can be used to obtain a quantitative genotype-phenotype relationship for metabolism in bacterial cells.

Acetates↗
PubMed2001

Dynamic simulation of the human red blood cell metabolic network.

We have developed a Mathematica application package to perform dynamic simulations of the red blood cell (RBC) metabolic network. The package relies on, and integrates, many years of mathematical modeling and biochemical work on red blood cell metabolism. The extensive data regarding the red blood cell metabolic network and the previous kinetic analysis of all the individual components makes the human RBC an ideal 'model' system for mathematical metabolic models. The Mathematica package can be used to understand the dynamics and regulatory characteristics of the red blood cell.

Computer Simulation↗
PubMed2001

Flux-balance analysis of mitochondrial energy metabolism: consequences of systemic stoichiometric constraints.

Mitochondrial metabolism is a critical component in the functioning and maintenance of cellular organs. The stoichiometry of biochemical reaction networks imposes constraints on mitochondrial function. A modeling framework, flux-balance analysis (FBA), was used to characterize the optimal flux distributions for maximal ATP production in the mitochondrion. The model predicted the expected ATP yields for glucose, lactate, and palmitate. Genetic defects that affect mitochondrial functions have been implicated in several human diseases. FBA can characterize the metabolic behavior due to genetic deletions at the metabolic level, and the effect of mutations in the tricarboxylic acid (TCA) cycle on mitochondrial ATP production was simulated. The mitochondrial ATP production is severely affected by TCA-cycle mutations. In addition, the model predicts the secretion of TCA-cycle intermediates, which is observed in clinical studies of mitochondriopathies such as those associated with fumarase deficiency. The model provides a systemic perspective to characterize the effect of stoichiometric constraints and specific metabolic fluxes on mitochondrial function.

Adenosine Triphosphate↗
PubMed2000

Metabolic flux balance analysis and the in silico analysis of Escherichia coli K-12 gene deletions.

BACKGROUND: Genome sequencing and bioinformatics are producing detailed lists of the molecular components contained in many prokaryotic organisms. From this 'parts catalogue' of a microbial cell, in silico representations of integrated metabolic functions can be constructed and analyzed using flux balance analysis (FBA). FBA is particularly well-suited to study metabolic networks based on genomic, biochemical, and strain specific information. RESULTS: Herein, we have utilized FBA to interpret and analyze the metabolic capabilities of Escherichia coli. We have computationally mapped the metabolic capabilities of E. coli using FBA and examined the optimal utilization of the E. coli metabolic pathways as a function of environmental variables. We have used an in silico analysis to identify seven gene products of central metabolism (glycolysis, pentose phosphate pathway, TCA cycle, electron transport system) essential for aerobic growth of E. coli on glucose minimal media, and 15 gene products essential for anaerobic growth on glucose minimal media. The in silico tpi-, zwf, and pta- mutant strains were examined in more detail by mapping the capabilities of these in silico isogenic strains. CONCLUSIONS: We found that computational models of E. coli metabolism based on physicochemical constraints can be used to interpret mutant behavior. These in silica results lead to a further understanding of the complex genotype-phenotype relation.

Computational Biology↗
PubMed2000

Extension of osmolality-induced podia is observed from fluorescently labeled hematopoietic cell lines in hyperosmotic medium.

BACKGROUND: Since the description of long podia extended by hematopoietic cells and cell lines, the reliable elicitation of podia extensions is needed to study these podia systemically. In this study, hyperosmotic stress was considered as an elicitor. METHODS: Using two fluorescent membrane dyes PKH2 and PKH26, and an automated fluorescence microscopy system, morphological changes of seven human cell lines (six hematopoietic, one fibrosarcoma) at different osmolalities were monitored. Presence of surface molecules on the hyperosmolality-induced podia (osmopodia) was examined. RESULTS: In hyperosmotic medium, cells shrank rapidly, followed by osmopodia extension. Cells exhibited variable number (up to five) and length (up to longer than 100 microm) of osmopodia in about 1 h. Dead cells did not extend podia. Frequency, length, and number of podia were variable among cell lines studied. CD44 and CD45 were not present on the osmopodia, although they were present on the cell surface, showing that osmopodia characteristics differ from the podia observed previously in isotonic media. The osmopodia extension process was shown to be reversible upon repeated osmolality changes. CONCLUSIONS: Osmopodia extended by human hematopoietic cell lines display a newly observed cellular morphology and provide a tool for investigation of dynamic cellular response to environmental changes.

Antigens, CD↗
PubMed2000

Intercellular adhesion can be visualized using fluorescently labeled fibrosarcoma HT1080 cells cocultured with hematopoietic cell lines or CD34(+) enriched human mobilized peripheral blood cells.

BACKGROUND: Intercellular contacts between adjacent cells migrating over each other are important in many cellular processes. However, it has been difficult to visualize and identify dynamic intercellular adhesions between migrating cells in situ. METHODS: Two fluorescent membrane dyes, PKH2 and PKH26 for staining HT1080 and hematopoietic cells and cell lines, and an automated fluorescence microscopy system were used to monitor intercellular adhesion. RESULTS: Cellular extensions connecting two or more adjacent cells were visualized, showing the intercellular adhesion between migrating cells for minutes and up to hours. After cells adhered to each other, followed by cell migration in different directions, cellular extensions were dragged from the pivotal contact points in different focal planes. CD34(+)-enriched mobilized peripheral blood cells and six hematopoietic cell lines showed intercellular connections in cocultures with HT1080. However, the frequency of intercellular connections was variable in different cocultures. A cell density of about 3.1 x 10(4) cells/cm(2) for both cell lines in cocultures provided an adequate number of cells in each field of view, showing up to four intercellular connections per 100 total cells plated. DISCUSSION: The tools derived from this study will open new areas of investigation for understanding the mechanism of the intercellular adhesion process.

Antigens, CD34↗
PubMed2000

The Escherichia coli MG1655 in silico metabolic genotype: its definition, characteristics, and capabilities.

The Escherichia coli MG1655 genome has been completely sequenced. The annotated sequence, biochemical information, and other information were used to reconstruct the E. coli metabolic map. The stoichiometric coefficients for each metabolic enzyme in the E. coli metabolic map were assembled to construct a genome-specific stoichiometric matrix. The E. coli stoichiometric matrix was used to define the system's characteristics and the capabilities of E. coli metabolism. The effects of gene deletions in the central metabolic pathways on the ability of the in silico metabolic network to support growth were assessed, and the in silico predictions were compared with experimental observations. It was shown that based on stoichiometric and capacity constraints the in silico analysis was able to qualitatively predict the growth potential of mutant strains in 86% of the cases examined. Herein, it is demonstrated that the synthesis of in silico metabolic genotypes based on genomic, biochemical, and strain-specific information is possible, and that systems analysis methods are available to analyze and interpret the metabolic phenotype.

Bacterial Proteins↗
PubMed2000

Theory for the systemic definition of metabolic pathways and their use in interpreting metabolic function from a pathway-oriented perspective.

Cellular metabolism is most often described and interpreted in terms of the biochemical reactions that make up the metabolic network. Genomics is providing near complete information regarding the genes/gene products participating in cellular metabolism for a growing number of organisms. As the true functional units of metabolic systems are its pathways, the time has arrived to define metabolic pathways in the context of whole-cell metabolism for the analysis of the structural design and capabilities of the metabolic network. In this study, we present the theoretical foundations for the identification of the unique set of systemically independent biochemical pathways, termed extreme pathways, based on system stochiometry and limited thermodynamics. These pathways represent the edges of the steady-state flux cone derived from convex analysis, and they can be used to represent any flux distribution achievable by the metabolic network. An algorithm is presented to determine the set of extreme pathways for a system of any complexity and a classification scheme is introduced for the characterization of these pathways. The property of systemic independence is discussed along with its implications for issues related to metabolic regulation and the evolution of cellular metabolic networks. The underlying pathway structure that is determined from the set of extreme pathways now provides us with the ability to analyse, interpret, and perhaps predict metabolic function from a pathway-based perspective in addition to the traditional reaction-based perspective. The algorithm and classification scheme developed can be used to describe the pathway structure in annotated genomes to explore the capabilities of an organism.

Algorithms↗
PubMed2000

Assessment of the metabolic capabilities of Haemophilus influenzae Rd through a genome-scale pathway analysis.

The annotated full DNA sequence is becoming available for a growing number of organisms. This information along with additional biochemical and strain-specific data can be used to define metabolic genotypes and reconstruct cellular metabolic networks. The first free-living organism for which the entire genomic sequence was established was Haemophilus influenzae. Its metabolic network is reconstructed herein and contains 461 reactions operating on 367 intracellular and 84 extracellular metabolites. With the metabolic reaction network established, it becomes necessary to determine its underlying pathway structure as defined by the set of extreme pathways. The H. influenzae metabolic network was subdivided into six subsystems and the extreme pathways determined for each subsystem based on stoichiometric, thermodynamic, and systems-specific constraints. Positive linear combinations of these pathways can be taken to determine the extreme pathways for the complete system. Since these pathways span the capabilities of the full system, they could be used to address a number of important physiological questions. First, they were used to reconcile and curate the sequence annotation by identifying reactions whose function was not supported in any of the extreme pathways. Second, they were used to predict gene products that should be co-regulated and perhaps co-expressed. Third, they were used to determine the composition of the minimal substrate requirements needed to support the production of 51 required metabolic products such as amino acids, nucleotides, phospholipids, etc. Fourth, sets of critical gene deletions from core metabolism were determined in the presence of the minimal substrate conditions and in more complete conditions reflecting the environmental niche of H. influenzae in the human host. In the former case, 11 genes were determined to be critical while six remained critical under the latter conditions. This study represents an important milestone in theoretical biology, namely the establishment of the first extreme pathway structure of a whole genome.

Genome, Bacterial↗
PubMed1999

Key adhesion molecules are present on long podia extended by hematopoietic cells.

BACKGROUND: We recently reported that CD34(+) hematopoietic cells and the KG1a cell line extend long, thin podia. These podia can dynamically extend and retract, often adhere to the substrate, and appear to connect cells up to 300 microm apart. The surface receptors found on these podia have not been described. METHODS: By using time-lapse fluorescent microscoscopy and immunostaining techniques, we describe a method for detecting surface receptors on these podia. This includes an in situ antibody staining procedure without fixing cells. RESULTS: We demonstrate, using CD34 selected mobilized peripheral blood cells and KG1a cells, that adhesion molecules known to play important roles in blood-cell migration and adhesion are present on these podia. These include: CD11a, CD18, CD29, CD34, CD45, CD49d, CD49e, and CD62L. Additionally, CD54 and CD44 were present on the podia extended by KG1a cells, but were not detectable on the primary CD34(+) cells. The integrin CD49d localized at the base of these podia in a time-dependent manner in KG1a cells. The frequency and morphology of these long podia on three myeloid leukemia-cell lines (KG1a, MV4-11, and AML-193) and a CD34-negative T-cell line (CEM) are also compared. KG1a and CEM cell lines extend long, dynamic podia that are similar to the podia on primary CD34(+) cells in morphology and adhesion molecule expression. The AML-193 and MV4-11 cell lines, however, did not extend these long podia. CONCLUSIONS: We describe a technique that provides a method of detecting surface receptors on thin cell membrane projections. These results support the likely role of these podia in cell migration and cell-cell communication.

Antigens, CD34↗
PubMed1999

Symmetry of initial cell divisions among primitive hematopoietic progenitors is independent of ontogenic age and regulatory molecules.

We have developed a time-lapse camera system to follow the replication history and the fate of hematopoietic stem cells (HSC) at a single-cell level. Combined with single-cell culture, we correlated the early replication behavior with colony development after 14 days. The membrane dye PKH26 was used to monitor cell division. In addition to multiple, synchronous, and symmetric divisions, single-sorted CD34(+)/CD38(-) cells derived from fetal liver (FLV) also gave rise to a daughter cell that remained quiescent for up to 8 days, whereas the other daughter cell proliferated exponentially. Upon separation and replating as single cells onto medium containing a cytokine cocktail, 60.6% +/- 9.8% of the initially quiescent cells (PKH26 bright) gave rise again to colonies and 15.8% +/- 7.8% to blast colonies that could be replated. We have then determined the effects of various regulatory molecules on symmetry of initial cell divisions. After single-cell sorting, the CD34(+)/CD38(-) cells derived from FLV were exposed to flt3-ligand, thrombopoietin, stem cell factor (SCF), or medium containing a cytokine cocktail (with SCF, interleukin-3, interleukin-6, granulocyte-macrophage colony-stimulating factor, and erythropoietin). Whereas mitotic rate, colony efficiency, and asymmetric divisions could be altered using various regulatory molecules, the asymmetric division index, defined as the number of asymmetric divisions versus the number of dividing cells, was not altered significantly. This observation suggests that, although lineage commitment and cell proliferation can be skewed by extrinsic signaling, symmetry of early divisions is probably under the control of intrinsic factors.

Adult↗
PubMed1999

Phototoxicity of the fluorescent membrane dyes PKH2 and PKH26 on the human hematopoietic KG1a progenitor cell line.

BACKGROUND: The phototoxic effects of the well-known fluorescent membrane dyes PKH2 and PKH26 have been unknown, although their use in cell tracking experiments has increased dramatically. To eliminate the phototoxicity-induced alteration in cell function and morphology, it is essential to examine the suspicious phototoxicity of these dyes. METHODS: Chemical and phototoxic effects of PKH dyes on the human hematopoietic KG1a cell line were examined. To minimize phototoxicity in long-term cell tracking experiments lasting up to 18 h with a fluorescence microscope system, time-lapse monitoring with different time intervals and exposure times was introduced. RESULTS: There were no significant effects of the two PKH dyes on cell viability and growth when using dye concentrations up to 5 microM. However, when stained cells were exposed to excitation light, cell viability decreased dramatically, showing the phototoxicity of the PKH dyes. More than 60% of cells stained with 5 microM PKH26 died after 5 min of continuous light exposure. The phototoxic effect was more extensive in cells stained with higher concentrations of the dyes. CONCLUSIONS: We present guidelines for the optimal use of these dyes by using a defined hardware configuration.

Cell Division↗