RpfG is a paradigm for a class of widespread bacterial two-component regulators with a CheY-like receiver domain attached to a histidine-aspartic acid-glycine-tyrosine-proline (HD-GYP) cyclic di-GMP phosphodiesterase domain. In the plant pathogen Xanthomonas campestris pv. campestris (Xcc), a two-component system comprising RpfG and the complex sensor kinase RpfC is implicated in sensing and responding to the diffusible signaling factor (DSF), which is essential for cell-cell signaling. RpfF is involved in synthesizing DSF, and mutations of rpfF, rpfG, or rpfC lead to a coordinate reduction in the synthesis of virulence factors such as extracellular enzymes, biofilm structure, and motility. Using yeast two-hybrid analysis and fluorescence resonance energy transfer experiments in Xcc, we show that the physical interaction of RpfG with two proteins with diguanylate cyclase (GGDEF) domains controls a subset of RpfG-regulated virulence functions. RpfG interactions were abolished by alanine substitutions of the three residues of the conserved GYP motif in the HD-GYP domain. Changing the GYP motif or deletion of the two GGDEF-domain proteins reduced Xcc motility but not the synthesis of extracellular enzymes or biofilm formation. RpfG-GGDEF interactions are dynamic and depend on DSF signaling...
Because GABA(A) receptors containing alpha 2 subunits are highly represented in areas of the brain, such as nucleus accumbens (NAcc), frontal cortex, and amygdala, regions intimately involved in signaling motivation and reward, we hypothesized that manipulations of this receptor subtype would influence processing of rewards. Voltage-clamp recordings from NAcc medium spiny neurons of mice with alpha 2 gene deletion showed reduced synaptic GABA(A) receptor-mediated responses. Behaviorally, the deletion abolished cocaine`s ability to potentiate behaviors conditioned to rewards (conditioned reinforcement), and to support behavioral sensitization. In mice with a point mutation in the benzodiazepine binding pocket of alpha 2-GABA(A) receptors (alpha 2H101R), GABAergic neurotransmission in medium spiny neurons was identical to that of WT (i.e., the mutation was silent), but importantly, receptor function was now facilitated by the atypical benzodiazepine Ro 15-4513 (ethyl 8-amido-5,6-dihydro-5-methyl-6-oxo-4H-imidazo [1,5-a] [1,4] benzodiazepine-3-carboxylate). In alpha 2H101R, but not WT mice, Ro 15-4513 administered directly into the NAcc-stimulated locomotor activity, and when given systemically and repeatedly, induced behavioral sensitization. These data indicate that activation of alpha 2-GABA(A) receptors (most likely in NAcc) is both necessary and sufficient for behavioral sensitization. Consistent with a role of these receptors in addiction...
Thousands of genes have recently been sequenced in organisms ranging from Escherichia coli to human. For the majority of these genes, however, available sequence does not define a biological role. Efficient functional characterization of these genes requires strategies for scaling genetic analyses to the whole genome level. Plasmid-based library selections are an established approach to the functional analysis of uncharacterized genes and can help elucidate biological function by identifying, for example, physical interactors for a gene and genetic enhancers and suppressors of mutant phenotypes. The application of these selections to every gene in a eukaryotic genome, however, is generally limited by the need to manipulate and sequence hundreds of DNA plasmids. We present an alternative approach in which identification of nucleic acids is accomplished by direct hybridization to high-density oligonucleotide arrays. Based on the complete sequence of Saccharomyces cerevisiae, high-density arrays containing oligonucleotides complementary to every gene in the yeast genome have been designed and synthesized. Two-hybrid protein–protein interaction screens were carried out for S. cerevisiae genes implicated in mRNA splicing and microtubule assembly. Hybridization of labeled DNA derived from positive clones is sufficient to characterize the results of a screen in a single experiment...
Recently, mutations in the Met tyrosine kinase receptor have been identified in both hereditary and sporadic forms of papillary renal carcinoma. We have introduced the corresponding mutations into the met cDNA and examined the effect of each mutation in biochemical and biological assays. We find that the Met mutants exhibit increased levels of tyrosine phosphorylation and enhanced kinase activity toward an exogenous substrate when compared with wild-type Met. Moreover, NIH 3T3 cells expressing mutant Met molecules form foci in vitro and are tumorigenic in nude mice. Enzymatic and biological differences were evident among the various mutants examined, and the somatic mutations were generally more active than those of germ-line origin. A strong correlation between the enzymatic and biological activity of the mutants was observed, indicating that tumorigenesis by Met is quantitatively related to its level of activation. These results demonstrate that the Met mutants originally identified in human papillary renal carcinoma are oncogenic and thus are likely to play a determinant role in this disease, and these results raise the possibility that activating Met mutations also may contribute to other human malignancies.
Transthyretin (TTR) tetramer dissociation and misfolding facilitate
assembly into amyloid fibrils that putatively cause senile systemic
amyloidosis and familial amyloid polyneuropathy. We have previously
discovered more than 50 small molecules that bind to and stabilize
tetrameric TTR, inhibiting amyloid fibril formation in
vitro. A method is presented here to evaluate the binding
selectivity of these inhibitors to TTR in human plasma, a complex
biological fluid composed of more than 60 proteins and numerous small
molecules. Our immunoprecipitation approach isolates TTR and bound
small molecules from a biological fluid such as plasma, and quantifies
the amount of small molecules bound to the protein by HPLC analysis.
This approach demonstrates that only a small subset of the inhibitors
that saturate the TTR binding sites in vitro do so in
plasma. These selective inhibitors can now be tested in animal models
of TTR amyloid disease to probe the validity of the amyloid hypothesis.
This method could be easily extended to evaluate small molecule binding
selectivity to any protein in a given biological fluid without the
necessity of determining or guessing which other protein components may
be competitors. This is a central issue to understanding the
A crystal structure of the anaerobic Ni-Fe-S carbon monoxide dehydrogenase (CODH) from Rhodospirillum rubrum has been determined to 2.8-Å resolution. The CODH family, for which the R. rubrum enzyme is the prototype, catalyzes the biological oxidation of CO at an unusual Ni-Fe-S cluster called the C-cluster. The Ni-Fe-S C-cluster contains a mononuclear site and a four-metal cubane. Surprisingly, anomalous dispersion data suggest that the mononuclear site contains Fe and not Ni, and the four-metal cubane has the form [NiFe3S4] and not [Fe4S4]. The mononuclear site and the four-metal cluster are bridged by means of Cys531 and one of the sulfides of the cube. CODH is organized as a dimer with a previously unidentified [Fe4S4] cluster bridging the two subunits. Each monomer is comprised of three domains: a helical domain at the N terminus, an α/β (Rossmann-like) domain in the middle, and an α/β (Rossmann-like) domain at the C terminus. The helical domain contributes ligands to the bridging [Fe4S4] cluster and another [Fe4S4] cluster, the B-cluster, which is involved in electron transfer. The two Rossmann domains contribute ligands to the active site C-cluster. This x-ray structure provides insight into the mechanism of biological CO oxidation and has broader significance for the roles of Ni and Fe in biological systems.
The design of polymers and oligomers that mimic the complex
structures and remarkable biological properties of proteins is an
important endeavor with both fundamental and practical implications.
Recently, a number of nonnatural peptides with designed sequences have
been elaborated to provide biologically active structures; in
particular, facially amphiphilic peptides built from β-amino acids
have been shown to mimic both the structures as well as the biological
function of natural antimicrobial peptides such as magainins and
cecropins. However, these natural peptides as well as their
β-peptide analogues are expensive to prepare and difficult to produce
on a large scale, limiting their potential use to certain
pharmaceutical applications. We therefore have designed a series of
facially amphiphilic arylamide polymers that capture the physical and
biological properties of this class of antimicrobial peptides, but are
easy to prepare from inexpensive monomers. The design process was aided
by molecular calculations with density functional
theory-computed torsional potentials. This new class of
amphiphilic polymers may be applied in situations where inexpensive
antimicrobial agents are required.
Su, Andrew I.; Cooke, Michael P.; Ching, Keith A.; Hakak, Yaron; Walker, John R.; Wiltshire, Tim; Orth, Anthony P.; Vega, Raquel G.; Sapinoso, Lisa M.; Moqrich, Aziz; Patapoutian, Ardem; Hampton, Garret M.; Schultz, Peter G.; Hogenesch, John B.
Fonte: The National Academy of SciencesPublicador: The National Academy of Sciences
High-throughput gene expression profiling has become an important tool for investigating transcriptional activity in a variety of biological samples. To date, the vast majority of these experiments have focused on specific biological processes and perturbations. Here, we have generated and analyzed gene expression from a set of samples spanning a broad range of biological conditions. Specifically, we profiled gene expression from 91 human and mouse samples across a diverse array of tissues, organs, and cell lines. Because these samples predominantly come from the normal physiological state in the human and mouse, this dataset represents a preliminary, but substantial, description of the normal mammalian transcriptome. We have used this dataset to illustrate methods of mining these data, and to reveal insights into molecular and physiological gene function, mechanisms of transcriptional regulation, disease etiology, and comparative genomics. Finally, to allow the scientific community to use this resource, we have built a free and publicly accessible website (http://expression.gnf.org) that integrates data visualization and curation of current gene annotations.
The opposing transcriptional activities of the basic-helix–loop–helix-leucine zipper proteins Myc and Mad, taken together with information related to their expression patterns and biological effects, have led to a model of the Myc/Max/Mad network in which Myc and Mad proteins function as antagonists. This antagonism is presumed to operate at the level of genes targeted by these complexes, where Myc:Max activates and Mad:Max represses expression of the same set of genes. However, a detailed analysis of the DNA-binding preferences for Mad proteins has not been performed. Furthermore, the model does not address the findings that Myc:Max indirectly represses transcription of several regulatory genes. To examine these issues relating to DNA-binding specificity and biological responses, we have determined the DNA-binding preferences of Mad1 by using selection and amplification of randomized oligonucleotides and demonstrated that its intrinsic specificity is identical with that of c-Myc. We have also used a chimeric Myc protein, containing a substitution of the entire Mad basic-helix–loop–helix-leucine zipper motif, and shown that it can reproduce the growth-promoting activities of Myc, but not its apoptotic function. Our results suggest that Myc and Mad...
Current methods for the functional analysis of microarray gene expression data make the implicit assumption that genes with similar expression profiles have similar functions in cells. However, among genes involved in the same biological pathway, not all gene pairs show high expression similarity. Here, we propose that transitive expression similarity among genes can be used as an important attribute to link genes of the same biological pathway. Based on large-scale yeast microarray expression data, we use the shortest-path analysis to identify transitive genes between two given genes from the same biological process. We find that not only functionally related genes with correlated expression profiles are identified but also those without. In the latter case, we compare our method to hierarchical clustering, and show that our method can reveal functional relationships among genes in a more precise manner. Finally, we show that our method can be used to reliably predict the function of unknown genes from known genes lying on the same shortest path. We assigned functions for 146 yeast genes that are considered as unknown by the Saccharomyces Genome Database and by the Yeast Proteome Database. These genes constitute around 5% of the unknown yeast ORFome.
Heart failure (HF) is the end result of progressive and diverse biological adaptations within the diseased myocardium. We used cDNA microarrays and quantitative PCR to examine the transcriptomes of 38 left ventricles from failing and nonfailing human myocardium. After identification of a pool of putative HF-responsive candidate genes by microarrays on seven nonfailing and eight failing hearts, we used quantitative PCR and a general linear statistical model in a larger sample set (n = 34) to validate and examine the role of contributing biological variables (age and sex). We find that most HF-candidate genes (transcription factors, Cebpb, Npat; signaling molecules, Map2k3, Map4k5; extracellular matrix proteins, Lum, Cola1; and metabolic enzymes, Mars) demonstrated significant changes in gene expression; however, the majority of differences among samples depended on variables such as sex and age, and not on HF alone. Some HF-responsive gene products also demonstrated highly significant changes in expression as a function of age and/or sex, but independent of HF (Ngp1, Cd163, and Npat). These results emphasize the need to account for biological variables (HF, sex and age interactions) to elucidate genomic correlates that trigger molecular pathways responsible for the progression of HF syndromes.
We report a novel connection between the phosphatidylinositol (PI) metabolic pathway and the DNA replication and damage checkpoint pathway discovered from an unbiased chemical genomics screen. Substrates and products of PI kinases are important signaling molecules that affect a wide range of biological processes. The full collection of yeast deletion strains was screened to identify genes that confer altered sensitivity to the natural product wortmannin, a PI kinase inhibitor. These experiments have allowed us to explore metabolomic and proteomic implications of PI synthesis and turnover. This study also uncovers other biological processes affected by wortmannin treatment, including proteasome-mediated degradation and chromatin remodeling. Bioinformatic analyses were used to reveal the relative distances among cellular processes affected by wortmannin and protein–protein interactions in the wortmannin-sensitive proteomic subnetwork. These results illustrate the great utility of using a whole-genome approach in annotating the biological effects of small molecules and have clear implications for pharmacogenomics. Furthermore, our discovery points to a route to overcoming genome instability, a result of defective DNA damage signaling/repair and a hallmark of cancer.
Genomic sequencing is no longer a novelty, but gene function annotation
remains a key challenge in modern biology. A variety of functional genomics
experimental techniques are available, from classic methods such as affinity
precipitation to advanced high-throughput techniques such as gene expression
microarrays. In the future, more disparate methods will be developed, further
increasing the need for integrated computational analysis of data generated by
these studies. We address this problem with magic (Multisource
Association of Genes by Integration of Clusters), a general framework that
uses formal Bayesian reasoning to integrate heterogeneous types of
high-throughput biological data (such as large-scale two-hybrid screens and
multiple microarray analyses) for accurate gene function prediction. The
system formally incorporates expert knowledge about relative accuracies of
data sources to combine them within a normative framework. magic
provides a belief level with its output that allows the user to vary the
stringency of predictions. We applied magic to Saccharomyces
cerevisiae genetic and physical interactions, microarray, and
transcription factor binding sites data and assessed the biological relevance
of gene groupings using Gene Ontology annotations produced by the
Saccaromyces Genome Database. We found that by creating functional
groupings based on heterogeneous data types...
With recent interest in seeking new biologically inspired device-fabrication methods in nanotechnology, a new biological approach was examined to fabricate Cu nanotubes by using sequenced histidine-rich peptide nanotubes as templates. The sequenced histidine-rich peptide molecules were assembled as nanotubes, and the biological recognition of the specific sequence toward Cu lead to efficient Cu coating on the nanotubes. Cu nanocrystals were uniformly coated on the histidine-incorporated nanotubes with high packing density. In addition, the diameter of Cu nanocrystal was controlled between 10 and 30 nm on the nanotube by controlling the conformation of histidine-rich peptide by means of pH changes. Those nanotubes showed significant change in electronic structure by varying the nanocrystal diameter; therefore, this system may be developed to a conductivity-tunable building block for microelectronics and biological sensors. This simple biomineralization method can be applied to fabricate various metallic and semiconductor nanotubes with peptides whose sequences are known to mineralize specific ions.
The advent of high-throughput biology has catalyzed a remarkable improvement in our ability to identify new genes. A large fraction of newly discovered genes have an unknown functional role, particularly when they are specific to a particular lineage or organism. These genes, currently labeled “hypothetical,” might support important biological cell functions and could potentially serve as targets for medical, diagnostic, or pharmacogenomic studies. An important challenge to the scientific community is to associate these newly predicted genes with a biological function that can be validated by experimental screens. In the absence of sequence or structural homology to known genes, we must rely on advanced biotechnological methods, such as DNA chips and protein–protein interaction screens as well as computational techniques to assign putative functions to these genes. In this article, we propose an effective methodology for combining biological evidence obtained in several high-throughput experimental screens and integrating this evidence in a way that provides consistent functional assignments to hypothetical genes. We use the visualization method of propagation diagrams to illustrate the flow of functional evidence that supports the functional assignments produced by the algorithm. Our results contain a number of predictions and furnish strong evidence that integration of functional information is indeed a promising direction for improving the accuracy and robustness of functional genomics.
A food web consists of nodes, each consisting of one or more species. The role of each node as predator or prey determines the trophic relations that weave the web. Much effort in trophic food web research is given to understand the connectivity structure, or the nature and degree of dependence among nodes. Social network analysis (SNA) techniques—quantitative methods commonly used in the social sciences to understand network relational structure—have been used for this purpose, although postanalysis effort or biological theory is still required to determine what natural factors contribute to the feeding behavior. Thus, a conventional SNA alone provides limited insight into trophic structure. Here we show that by using novel statistical modeling methodologies to express network links as the random response of within- and internode characteristics (predictors), we gain a much deeper understanding of food web structure and its contributing factors through a unified statistical SNA. We do so for eight empirical food webs: Phylogeny is shown to have nontrivial influence on trophic relations in many webs, and for each web trophic clustering based on feeding activity and on feeding preference can differ substantially. These and other conclusions about network features are purely empirical...
Childhood maltreatment is likely to influence fundamental biological processes and engrave long-lasting epigenetic marks, leading to adverse health outcomes in adulthood. We aimed to elucidate the impact of different early environment on disease-related genome-wide gene expression and DNA methylation in peripheral blood cells in patients with posttraumatic stress disorder (PTSD). Compared with the same trauma-exposed controls (n = 108), gene-expression profiles of PTSD patients with similar clinical symptoms and matched adult trauma exposure but different childhood adverse events (n = 32 and 29) were almost completely nonoverlapping (98%). These differences on the level of individual transcripts were paralleled by the enrichment of several distinct biological networks between the groups. Moreover, these gene-expression changes were accompanied and likely mediated by changes in DNA methylation in the same loci to a much larger proportion in the childhood abuse (69%) vs. the non-child abuse-only group (34%). This study is unique in providing genome-wide evidence of distinct biological modifications in PTSD in the presence or absence of exposure to childhood abuse. The findings that nonoverlapping biological pathways seem to be affected in the two PTSD groups and that changes in DNA methylation appear to have a much greater impact in the childhood-abuse group might reflect differences in the pathophysiology of PTSD...
Mental disorders are increasingly understood biologically. We tested the effects of biological explanations among mental health clinicians, specifically examining their empathy toward patients. Conventional wisdom suggests that biological explanations reduce perceived blameworthiness against those with mental disorders, which could increase empathy. Yet, conceptualizing mental disorders biologically can cast patients as physiologically different from “normal” people and as governed by genetic or neurochemical abnormalities instead of their own human agency, which can engender negative social attitudes and dehumanization. This suggests that biological explanations might actually decrease empathy. Indeed, we find that biological explanations significantly reduce clinicians’ empathy. This is alarming because clinicians’ empathy is important for the therapeutic alliance between mental health providers and patients and significantly predicts positive clinical outcomes.
The meeting “Conceptual Assessment in the Biological Sciences” was held March 3–4, 2007, in Boulder, Colorado. Sponsored by the National Science Foundation and hosted by University of Colorado, Boulder's Biology Concept Inventory Team, the meeting drew together 21 participants from 13 institutions, all of whom had received National Science Foundation funding for biology education. Topics of interest included Introductory Biology, Genetics, Evolution, Ecology, and the Nature of Science. The goal of the meeting was to organize and leverage current efforts to develop concept inventories for each of these topics. These diagnostic tools are inspired by the success of the Force Concept Inventory, developed by the community of physics educators to identify student misconceptions about Newtonian mechanics. By working together, participants hope to lessen the risk that groups might develop competing rather than complementary inventories.
The dual-use dilemma arises in the context of research in the biological and other sciences as a consequence of the fact that one and the same piece of scientific research sometimes has the potential to be used for bad as well as good purposes. It is an e