Interaction of Fibroblast Growth Factor-2 (FGF-2) with Free Gangliosides: Biochemical Characterization and Biological Consequences in Endothelial Cell Cultures

Exogenous gangliosides affect the angiogenic activity of fibroblast growth factor-2 (FGF-2), but their mechanism of action has not been elucidated. Here, a possible direct interaction of sialo-glycolipids with FGF-2 has been investigated. Size exclusion chromatography demonstrates that native, but not heat-denatured, 125I-FGF-2 binds to micelles formed by gangliosides GT1b, GD1b, or GM1. Also, gangliosides protect native FGF-2 from trypsin digestion at micromolar concentrations, the order of relative potency being GT1b > GD1b > GM1 = GM2 = sulfatide > GM3 = galactosyl-ceramide, whereas asialo-GM1, neuraminic acid, and N-acetylneuramin-lactose were ineffective. Scatchard plot analysis of the binding data of fluorochrome-labeled GM1 to immobilized FGF-2 indicates that FGF–2/GM1 interaction occurs with a Kd equal to 6 μM. This interaction is inhibited by the sialic acid-binding peptide mastoparan and by the synthetic fragments FGF-2(112–129) and, to a lesser extent, FGF-2(130–155), whereas peptides FGF-2(10–33), FGF-2(39–59), FGF-2(86–96), and the basic peptide HIV-1 Tat(41–60) were ineffective. These data identify the COOH terminus of FGF-2 as a putative ganglioside-binding region. Exogenous gangliosides inhibit the binding of 125I-FGF-2 to high-affinity tyrosine-kinase FGF-receptors (FGFRs) of endothelial GM 7373 cells at micromolar concentrations. The order of relative potency was GT1b > GD1b > GM1 > sulfatide a = sialo-GM1. Accordingly, GT1b,GD1b, GM1, and GM2, but not GM3 and asialo-GM1, prevent the binding of 125I-FGF-2 to a soluble, recombinant form of extracellular FGFR-1. Conversely, the soluble receptor and free heparin inhibit the interaction of fluorochrome-labeled GM1 to immobilized FGF-2. In agreement with their FGFR antagonist activity, free gangliosides inhibit the mitogenic activity exerted by FGF-2 on endothelial cells in the same range of concentrations. Also in this case, GT1b was the most effective among the gangliosides tested while asialo-GM1, neuraminic acid, N-acetylneuramin-lactose, galactosyl-ceramide, and sulfatide were ineffective. In conclusion, the data demonstrate the capacity of exogenous gangliosides to interact with FGF-2. This interaction involves the COOH terminus of the FGF-2 molecule and depends on the structure of the oligosaccharide chain and on the presence of sialic acid residue(s) in the ganglioside molecule. Exogenous gangliosides act as FGF-2 antagonists when added to endothelial cell cultures. Since gangliosides are extensively shed by tumor cells and reach elevated levels in the serum of tumor-bearing patients, our data suggest that exogenous gangliosides may affect endothelial cell function by a direct interaction with FGF-2, thus modulating tumor neovascularization.

αvβ3 Integrin Mediates the Cell-adhesive Capacity and Biological Activity of Basic Fibroblast Growth Factor (FGF-2) in Cultured Endothelial Cells

Fibroblast growth factor-2 (FGF-2) immobilized on non-tissue culture plastic promotes adhesion and spreading of bovine and human endothelial cells that are inhibited by anti-FGF-2 antibody. Heat-inactivated FGF-2 retains its cell-adhesive activity despite its incapacity to bind to tyrosine-kinase FGF receptors or to cell-surface heparan sulfate proteoglycans. Recombinant glutathione-S-transferase-FGF-2 chimeras and synthetic FGF-2 fragments identify two cell-adhesive domains in FGF-2 corresponding to amino acid sequences 38–61 and 82–101. Both regions are distinct from the FGF-receptor-binding domain of FGF-2 and contain a DGR sequence that is the inverse of the RGD cell-recognition sequence. Calcium deprivation, RGD-containing eptapeptides, soluble vitronectin (VN), but not fibronectin (FN), inhibit cell adhesion to FGF-2. Conversely, soluble FGF-2 prevents cell adhesion to VN but not FN, thus implicating VN receptor in the cell-adhesive activity of FGF-2. Accordingly, monoclonal and polyclonal anti-αvβ3 antibodies prevent cell adhesion to FGF-2. Also, purified human αvβ3 binds to immobilized FGF-2 in a cation-dependent manner, and this interaction is competed by soluble VN but not by soluble FN. Finally, anti-αvβ3 monoclonal and polyclonal antibodies specifically inhibit mitogenesis and urokinase-type plasminogen activator (uPA) up-regulation induced by free FGF-2 in endothelial cells adherent to tissue culture plastic. These data demonstrate that FGF-2 interacts with αvβ3 integrin and that this interaction mediates the capacity of the angiogenic growth factor to induce cell adhesion, mitogenesis, and uPA up-regulation in endothelial cells.

Sensitivity to inhibition by β-chemokines correlates with biological phenotypes of primary HIV-1 isolates

Primary HIV-1 isolates were evaluated for their sensitivity to inhibition by β-chemokines RANTES (regulated upon activation, normal T-cell expressed and secreted), macrophage inflammatory protein 1α (MIP-1α), and MIP-1β. Virus isolates of both nonsyncytium-inducing (NSI) and syncytium-inducing (SI) biological phenotypes recovered from patients at various stages of HIV-1 infection were assessed, and the results indicated that only the isolates with the NSI phenotype were substantially inhibited by the β-chemokines. More important to note, these data demonstrate that resistance to inhibition by β-chemokines RANTES, MIP-1α, and MIP-1β is not restricted to T cell line-adapted SI isolates but is also a consistent property among primary SI isolates. Analysis of isolates obtained sequentially from infected individuals in whom viruses shifted from NSI to SI phenotype during clinical progression exhibited a parallel loss of sensitivity to β-chemokines. Loss of virus sensitivity to inhibition by β-chemokines RANTES, MIP-1α, and MIP-1β was furthermore associated with changes in the third variable (V3) region amino acid residues previously described to correlate with a shift of virus phenotype from NSI to SI. Of interest, an intermediate V3 genotype correlated with a partial inhibition by the β-chemokines. In addition, we also identified viruses sensitive to RANTES, MIP-1α, and MIP-1β of NSI phenotype that were isolated from individuals with AIDS manifestations, indicating that loss of sensitivity to β-chemokine inhibition and shift in viral phenotype are not necessarily prerequisites for the pathogenesis of HIV-1 infection.

Paleoproterozoic snowball Earth: Extreme climatic and geochemical global change and its biological consequences

Geological, geophysical, and geochemical data support a theory that Earth experienced several intervals of intense, global glaciation (“snowball Earth” conditions) during Precambrian time. This snowball model predicts that postglacial, greenhouse-induced warming would lead to the deposition of banded iron formations and cap carbonates. Although global glaciation would have drastically curtailed biological productivity, melting of the oceanic ice would also have induced a cyanobacterial bloom, leading to an oxygen spike in the euphotic zone and to the oxidative precipitation of iron and manganese. A Paleoproterozoic snowball Earth at 2.4 Giga-annum before present (Ga) immediately precedes the Kalahari Manganese Field in southern Africa, suggesting that this rapid and massive change in global climate was responsible for its deposition. As large quantities of O2 are needed to precipitate this Mn, photosystem II and oxygen radical protection mechanisms must have evolved before 2.4 Ga. This geochemical event may have triggered a compensatory evolutionary branching in the Fe/Mn superoxide dismutase enzyme, providing a Paleoproterozoic calibration point for studies of molecular evolution.

Knowledge-based analysis of microarray gene expression data by using support vector machines

We introduce a method of functionally classifying genes by using gene expression data from DNA microarray hybridization experiments. The method is based on the theory of support vector machines (SVMs). SVMs are considered a supervised computer learning method because they exploit prior knowledge of gene function to identify unknown genes of similar function from expression data. SVMs avoid several problems associated with unsupervised clustering methods, such as hierarchical clustering and self-organizing maps. SVMs have many mathematical features that make them attractive for gene expression analysis, including their flexibility in choosing a similarity function, sparseness of solution when dealing with large data sets, the ability to handle large feature spaces, and the ability to identify outliers. We test several SVMs that use different similarity metrics, as well as some other supervised learning methods, and find that the SVMs best identify sets of genes with a common function using expression data. Finally, we use SVMs to predict functional roles for uncharacterized yeast ORFs based on their expression data.

The biological clock of very premature primate infants is responsive to light

Each year more than 250,000 infants in the United States are exposed to artificial lighting in hospital nurseries with little consideration given to environmental lighting cycles. Essential in determining whether environmental lighting cycles need to be considered in hospital nurseries is identifying when the infant’s endogenous circadian clock becomes responsive to light. Using a non-human primate model of the developing human, we examined when the circadian clock, located in the hypothalamic suprachiasmatic nuclei (SCN), becomes responsive to light. Preterm infant baboons of different ages were exposed to light (5,000 lux) at night, and then changes in SCN metabolic activity and gene expression were assessed. After exposure to bright light at night, robust increases in SCN metabolic activity and gene expression were seen at ages that were equivalent to human infants at 24 weeks after conception. These data provide direct evidence that the biological clock of very premature primate infants is responsive to light.

Singular value decomposition for genome-wide expression data processing and modeling

We describe the use of singular value decomposition in transforming genome-wide expression data from genes × arrays space to reduced diagonalized “eigengenes” × “eigenarrays” space, where the eigengenes (or eigenarrays) are unique orthonormal superpositions of the genes (or arrays). Normalizing the data by filtering out the eigengenes (and eigenarrays) that are inferred to represent noise or experimental artifacts enables meaningful comparison of the expression of different genes across different arrays in different experiments. Sorting the data according to the eigengenes and eigenarrays gives a global picture of the dynamics of gene expression, in which individual genes and arrays appear to be classified into groups of similar regulation and function, or similar cellular state and biological phenotype, respectively. After normalization and sorting, the significant eigengenes and eigenarrays can be associated with observed genome-wide effects of regulators, or with measured samples, in which these regulators are overactive or underactive, respectively.

Dynamic regulation of the tryptophan operon: A modeling study and comparison with experimental data

A mathematical model for regulation of the tryptophan operon is presented. This model takes into account repression, feedback enzyme inhibition, and transcriptional attenuation. Special attention is given to model parameter estimation based on experimental data. The model's system of delay differential equations is numerically solved, and the results are compared with experimental data on the temporal evolution of enzyme activity in cultures of Escherichia coli after a nutritional shift (minimal + tryptophan medium to minimal medium). Good agreement is obtained between the numeric simulations and the experimental results for wild-type E. coli, as well as for two different mutant strains.

Dynamic modeling of gene expression data

We describe the time evolution of gene expression levels by using a time translational matrix to predict future expression levels of genes based on their expression levels at some initial time. We deduce the time translational matrix for previously published DNA microarray gene expression data sets by modeling them within a linear framework by using the characteristic modes obtained by singular value decomposition. The resulting time translation matrix provides a measure of the relationships among the modes and governs their time evolution. We show that a truncated matrix linking just a few modes is a good approximation of the full time translation matrix. This finding suggests that the number of essential connections among the genes is small.

The PDB data uniformity project

The Protein Data Bank (PDB; http://www.rcsb.org/pdb/) is the single worldwide archive of structural data of biological macromolecules. This paper describes the data uniformity project that is underway to address the inconsistency in PDB data.

PlasmoDB: An integrative database of the Plasmodium falciparum genome. Tools for accessing and analyzing finished and unfinished sequence data

The Plasmodium falciparum Genome Database (http://PlasmoDB.org) integrates sequence information, automated analyses and annotation data emerging from the P.falciparum genome sequencing consortium. To date, raw sequence coverage is available for >90% of the genome, and two chromosomes have been finished and annotated. Data in PlasmoDB are organized by chromosome (1–14), and can be accessed using a variety of tools for graphical and text-based browsing or downloaded in various file formats. The GUS (Genomics Unified Schema) implementation of PlasmoDB provides a multi-species genomic relational database, incorporating data from human and mouse, as well as P.falciparum. The relational schema uses a highly structured format to accommodate diverse data sets related to genomic sequence and gene expression. Tools have been designed to facilitate complex biological queries, including many that are specific to Plasmodium parasites and malaria as a disease. Additional projects seek to integrate genomic information with the rich data sets now becoming available for RNA transcription, protein expression, metabolic pathways, genetic and physical mapping, antigenic and population diversity, and phylogenetic relationships with other apicomplexan parasites. The overall goal of PlasmoDB is to facilitate Internet- and CD-ROM-based access to both finished and unfinished sequence information by the global malaria research community.

The Molecular Biology Database Collection: an updated compilation of biological database resources

The Molecular Biology Database Collection is an online resource listing key databases of value to the biological community. This Collection is intended to bring fellow scientists’ attention to high-quality databases that are available throughout the world, rather than just be a lengthy listing of all available databases. As such, this up-to-date listing is intended to serve as the initial point from which to find specialized databases that may be of use in biological research. The databases included in this Collection provide new value to the underlying data by virtue of curation, new data connections or other innovative approaches. Short, searchable summaries of each of the databases included in the Collection are available through the Nucleic Acids Research Web site, at http://www.nar.oupjournals.org.

Estimating risks in declining populations with poor data

Census data on endangered species are often sparse, error-ridden, and confined to only a segment of the population. Estimating trends and extinction risks using this type of data presents numerous difficulties. In particular, the estimate of the variation in year-to-year transitions in population size (the “process error” caused by stochasticity in survivorship and fecundities) is confounded by the addition of high sampling error variation. In addition, the year-to-year variability in the segment of the population that is sampled may be quite different from the population variability that one is trying to estimate. The combined effect of severe sampling error and age- or stage-specific counts leads to severe biases in estimates of population-level parameters. I present an estimation method that circumvents the problem of age- or stage-specific counts and is markedly robust to severe sampling error. This method allows the estimation of environmental variation and population trends for extinction-risk analyses using corrupted census counts—a common type of data for endangered species that has hitherto been relatively unusable for these analyses.

Planetary exploration in the time of astrobiology: Protecting against biological contamination

These are intriguing times in the exploration of other solar-system bodies. Continuing discoveries about life on Earth and the return of data suggesting the presence of liquid water environments on or under the surfaces of other planets and moons have combined to suggest the significant possibility that extraterrestrial life may exist in this solar system. Similarly, not since the Viking missions of the mid-1970s has there been as great an appreciation for the potential for Earth life to contaminate other worlds. Current plans for the exploration of the solar system include constraints intended to prevent biological contamination from being spread by solar-system exploration missions.

Integrated fossil and molecular data reconstruct bat echolocation

Molecular and morphological data have important roles in illuminating evolutionary history. DNA data often yield well resolved phylogenies for living taxa, but are generally unattainable for fossils. A distinct advantage of morphology is that some types of morphological data may be collected for extinct and extant taxa. Fossils provide a unique window on evolutionary history and may preserve combinations of primitive and derived characters that are not found in extant taxa. Given their unique character complexes, fossils are critical in documenting sequences of character transformation over geologic time and may elucidate otherwise ambiguous patterns of evolution that are not revealed by molecular data alone. Here, we employ a methodological approach that allows for the integration of molecular and paleontological data in deciphering one of the most innovative features in the evolutionary history of mammals—laryngeal echolocation in bats. Molecular data alone, including an expanded data set that includes new sequences for the A2AB gene, suggest that microbats are paraphyletic but do not resolve whether laryngeal echolocation evolved independently in different microbat lineages or evolved in the common ancestor of bats and was subsequently lost in megabats. When scaffolds from molecular phylogenies are incorporated into parsimony analyses of morphological characters, including morphological characters for the Eocene taxa Icaronycteris, Archaeonycteris, Hassianycteris, and Palaeochiropteryx, the resulting trees suggest that laryngeal echolocation evolved in the common ancestor of fossil and extant bats and was subsequently lost in megabats. Molecular dating suggests that crown-group bats last shared a common ancestor 52 to 54 million years ago.