961 resultados para MAPPING MOLECULAR NETWORKS


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Important food crops like rice are constantly exposed to various stresses that can have devastating effect on their survival and productivity. Being sessile, these highly evolved organisms have developed elaborate molecular machineries to sense a mixture of stress signals and elicit a precise response to minimize the damage. However, recent discoveries revealed that the interplay of these stress regulatory and signaling molecules is highly complex and remains largely unknown. In this work, we conducted large scale analysis of differential gene expression using advanced computational methods to dissect regulation of stress response which is at the heart of all molecular changes leading to the observed phenotypic susceptibility. One of the most important stress conditions in terms of loss of productivity is drought. We performed genomic and proteomic analysis of epigenetic and miRNA mechanisms in regulation of drought responsive genes in rice and found subsets of genes with striking properties. Overexpressed genesets included higher number of epigenetic marks, miRNA targets and transcription factors which regulate drought tolerance. On the other hand, underexpressed genesets were poor in above features but were rich in number of metabolic genes with multiple co-expression partners contributing majorly towards drought resistance. Identification and characterization of the patterns exhibited by differentially expressed genes hold key to uncover the synergistic and antagonistic components of the cross talk between stress response mechanisms. We performed meta-analysis on drought and bacterial stresses in rice and Arabidopsis, and identified hundreds of shared genes. We found high level of conservation of gene expression between these stresses. Weighted co-expression network analysis detected two tight clusters of genes made up of master transcription factors and signaling genes showing strikingly opposite expression status. To comprehensively identify the shared stress responsive genes between multiple abiotic and biotic stresses in rice, we performed meta-analyses of microarray studies from seven different abiotic and six biotic stresses separately and found more than thirteen hundred shared stress responsive genes. Various machine learning techniques utilizing these genes classified the stresses into two major classes' namely abiotic and biotic stresses and multiple classes of individual stresses with high accuracy and identified the top genes showing distinct patterns of expression. Functional enrichment and co-expression network analysis revealed the different roles of plant hormones, transcription factors in conserved and non-conserved genesets in regulation of stress response.

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BACKGROUND Low-grade gliomas (LGGs) are rare brain neoplasms, with survival spanning up to a few decades. Thus, accurate evaluations on how biomarkers impact survival among patients with LGG require long-term studies on samples prospectively collected over a long period. METHODS The 210 adult LGGs collected in our databank were screened for IDH1 and IDH2 mutations (IDHmut), MGMT gene promoter methylation (MGMTmet), 1p/19q loss of heterozygosity (1p19qloh), and nuclear TP53 immunopositivity (TP53pos). Multivariate survival analyses with multiple imputation of missing data were performed using either histopathology or molecular markers. Both models were compared using Akaike's information criterion (AIC). The molecular model was reduced by stepwise model selection to filter out the most critical predictors. A third model was generated to assess for various marker combinations. RESULTS Molecular parameters were better survival predictors than histology (ΔAIC = 12.5, P< .001). Forty-five percent of studied patients died. MGMTmet was positively associated with IDHmut (P< .001). In the molecular model with marker combinations, IDHmut/MGMTmet combined status had a favorable impact on overall survival, compared with IDHwt (hazard ratio [HR] = 0.33, P< .01), and even more so the triple combination, IDHmut/MGMTmet/1p19qloh (HR = 0.18, P< .001). Furthermore, IDHmut/MGMTmet/TP53pos triple combination was a significant risk factor for malignant transformation (HR = 2.75, P< .05). CONCLUSION By integrating networks of activated molecular glioma pathways, the model based on genotype better predicts prognosis than histology and, therefore, provides a more reliable tool for standardizing future treatment strategies.

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In this paper, we present the Cellular Dynamic Simulator (CDS) for simulating diffusion and chemical reactions within crowded molecular environments. CDS is based on a novel event driven algorithm specifically designed for precise calculation of the timing of collisions, reactions and other events for each individual molecule in the environment. Generic mesh based compartments allow the creation / importation of very simple or detailed cellular structures that exist in a 3D environment. Multiple levels of compartments and static obstacles can be used to create a dense environment to mimic cellular boundaries and the intracellular space. The CDS algorithm takes into account volume exclusion and molecular crowding that may impact signaling cascades in small sub-cellular compartments such as dendritic spines. With the CDS, we can simulate simple enzyme reactions; aggregation, channel transport, as well as highly complicated chemical reaction networks of both freely diffusing and membrane bound multi-protein complexes. Components of the CDS are generally defined such that the simulator can be applied to a wide range of environments in terms of scale and level of detail. Through an initialization GUI, a simple simulation environment can be created and populated within minutes yet is powerful enough to design complex 3D cellular architecture. The initialization tool allows visual confirmation of the environment construction prior to execution by the simulator. This paper describes the CDS algorithm, design implementation, and provides an overview of the types of features available and the utility of those features are highlighted in demonstrations.

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Aminoacyl-tRNA synthetases (RSs) are responsible for the essential connection of amino acids with trinucleotide sequences of tRNA's. The RS family constitutes two structurally dissimilar groups of proteins, class I and class II. Methionyl-tRNA synthetase (MetRS) and isoleucyl-tRNA synthetase (IleRS), both members of class I, were the focus of this work. Both enzymes are zinc-containing proteins; show a high degree of amino acid specificity; and edit activated noncognate amino acids, thereby ensuring the fidelity of the genetic code. The goals of this work were to further delineate the molecular basis of catalysis and discrimination in these enzymes by mapping active site geometries using high-resolution nuclear magnetic resonance spectroscopy (NMR).^ Internuclear distances obtained from transferred nuclear Overhauser effects were used to define the conformations of Mg($\alpha$,$\beta$-methylene)ATP bound to E. coli MetRS and E. coli IleRS in multiple complexes. Identical conformations were found for the bound ATP. Thus, the predicted structural homology between IleRS and MetRS is supported by consensus enzyme-bound nucleotide conformations. The conformation of the bound nucleotide is not sensitive to occupation of the amino acid site of MetRS or IleRS. Therefore, conformational changes known to occur in the synthetases upon ligand binding appear not to alter the bound conformation of the adenosine portion of the nucleotide. Nuclear Overhauser effects on the substrate amino acid L-selenomethionine were also used to evaluate the enzyme-bound conformation of the cognate amino acid. The amino acid assumes a conformation which is consistent with a proposed editing mechanism.^ The E. coli MetRS was shown to catalyze amino acid $\alpha$-proton exchange in the presence of deuterium oxide of all cognate amino acids. It is proposed that the enzyme-bound zinc coordinates the $\alpha$-carboxylate of the amino acid, rendering the $\alpha$-proton more acidic. An enzymic base is responsible for exchange of the $\alpha$-proton. This proposal suggests that the enzyme-bound zinc may have a role in amino acid discrimination in MetRS. However, the role of this exchange reaction in catalysis remains unknown. ^

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Human x rodent somatic cell hybrids have played an important role in human genetics research. They have been especially useful for assigning genes to chromosomes and isolating DNA markers from specific regions of the human genome.^ By employing a combination of somatic cell genetic, recombinant DNA, and cytogenetic techniques, human DNA excision repair gene ERCC4 was mapped regionally to human 16p13.13-13.2, even though the gene has not been cloned. Human x Chinese hamster ovary (CHO) cell hybrids selected for human ERCC4 activity and containing 16p13.1-p13.3 as the only human genetic material were identified. These hybrids were used to order DNA markers located in 16p13.1-p13.3. New DNA markers physically close to ERCC4 were isolated from such hybrids. Using amplified human DNA from the hybrids as probe in fluorescent in situ hybridization, the short arm breakpoint in the chromosome 16 inversion associated with acute myelomonocytic leukemia (AMML) was found to be physically close to the ERCC4 gene. The physical mapping and eventually, the cloning of the ERCC4 gene, will benefit the understanding of the DNA repair system and the study of other important biomedical problems such as tumorigenesis.^ To facilitate the cloning of ERCC4 gene and, in general, the cloning of genes from any defined regions of the human genome, a method was developed for the direct isolation of human transcribed genes ffom somatic cell hybrids. cDNA was prepared from human x rodent hybrid by using consensus 5$\sp\prime$ splice site sequences as primers. These primers were designed to select immature, unspliced messenger RNA (still retaining species specific repeat sequences) as templates. Screening of a derived cDNA library for human repeat sequences resulted in the isolation of human clones at the anticipated frequency with characteristics expected of exons of transcribed human genes. The usefulness of the splice site specific primers was analyzed and the cDNA synthesis conditions with these primers were optimized. The procedure was shown to be sensitive enough to clone weakly expressed genes. Studying the expression of the represented genes with the isolated clones was shown to be feasible. Such regional specific human gene fragments will be very valuable for many human genetic studies such as the search of inherited disease genes and the construction of a cDNA map of the human genome. ^

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Rubella virus (RV) typically causes a mild childhood illness, but complications can result from both viral and immune-mediated pathogenesis. RV can persist in the presence of neutralizing antibodies, suggesting that cell-mediated immune responses may be necessary for viral clearance. However, the molecular determinants recognized by RV-specific T-cells have not been identified. Using recombinant proteins which express the entire RV structural open reading frame in proliferation assays with lymphocytes of RV-immune individuals, domains which elicit major histocompatibility complex class II-restricted helper T-cells were identified. Synthetic peptides representing these domains were used to define specific epitopes. Two immunodominant domains were mapped to the capsid protein sequence C$\sb1$-C$\sb{29}$ and the E1 glycoprotein sequence E1$\sb{202}$-E1$\sb{283}.$ RV-specific MHC class I-restricted cytotoxic T lymphocytes (CTLs) were identified using a chromium-release assay with infected fibroblasts as target cells. An infectious Sindbis virus vector expressing each of the RV structural proteins identified the capsid, E2 and E1 proteins as targets of CTLs. Specific CTL epitopes were mapped within the previously identified immunodominant domains. This study identified domains of the RV structural proteins that may be beneficial for development of a synthetic vaccine, and provides normative data on RV-specific T-cell responses that should enhance our ability to understand RV persistence and associated complications. ^

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Tumor-specific loss of constitutional heterozygosity by deletion, mitotic recombination or nondisjunction is a common mechanism for tumor suppressor allele inactivation. When loss of heterozygosity is the result of mitotic recombination, or a segmental deletion event, only a portion of the chromosome is lost. This information can be used to map the location of new tumor suppressor genes. In osteosarcoma, the highest frequencies of loss of heterozygosity have been reported for chromosomes 3q, 13q, 17p. On chromosomes 13q and 17p, allelic losses are associated with loss of function at the retinoblastoma susceptibility locus (RB1) and the p53 locus, respectively. Chromosome 3q is also of particular interest because the high percent of loss of heterozygosity (62%-75%) suggests the presence of another tumor suppressor important for osteosarcoma tumorigenesis. To localize this putative tumor suppressor gene, we used polymorphic markers on chromosome 3q to find the smallest common region of allele loss. This putative tumor suppressor was localized to a 700 kb region on chromosome 3q26.2 between the polymorphic loci D3S1282 and D3S1246. ^

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D1S1, an anonymous human DNA clone originally called (lamda)Ch4-H3 or (lamda)H3, was the first single copy mapped to a human chromosome (1p36) by in situ hybridization. The chromosomal assignment has been confirmed in other laboratories by repeating the in situ hybridization but not by another method. In the present study, hybridization to a panel of hamster-human somatic cell hybrids revealed copies of D1S1 on both chromosomes 1 and 3. Subcloning D1S1 showed that the D1S1 clone itself is from chromosome 3, and the sequence detected by in situ hybridization is at least two copies of part of the chromosome 3 copy. This finding demonstrates the importance of verifying gene mapping with two methods and questions the accuracy of in situ hybridization mapping.^ Non-human mammals have only one copy of D1S1, and the non-human primate D1S1 map closely resembles the human chromosome 3 copy. Thus, the human chromosome 1 copies appear to be part of a very recent duplication that occurred after the divergence between humans and the other great apes.^ A moderately informative HindIII D1S1 RFLP was mapped to chromosome 3. This marker and 12 protein markers were applied to a linkage study of autosomal dominant retinitis pigmentosa (ADRP). None of the markers proved linkage, but adding the three families examined to previously published data raises the ADRP:Rh lod score to 1.92 at (THETA) = 0.30. ^

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Current models of embryological development focus on intracellular processes such as gene expression and protein networks, rather than on the complex relationship between subcellular processes and the collective cellular organization these processes support. We have explored this collective behavior in the context of neocortical development, by modeling the expansion of a small number of progenitor cells into a laminated cortex with layer and cell type specific projections. The developmental process is steered by a formal language analogous to genomic instructions, and takes place in a physically realistic three-dimensional environment. A common genome inserted into individual cells control their individual behaviors, and thereby gives rise to collective developmental sequences in a biologically plausible manner. The simulation begins with a single progenitor cell containing the artificial genome. This progenitor then gives rise through a lineage of offspring to distinct populations of neuronal precursors that migrate to form the cortical laminae. The precursors differentiate by extending dendrites and axons, which reproduce the experimentally determined branching patterns of a number of different neuronal cell types observed in the cat visual cortex. This result is the first comprehensive demonstration of the principles of self-construction whereby the cortical architecture develops. In addition, our model makes several testable predictions concerning cell migration and branching mechanisms.

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BACKGROUND Interferon-α (IFN-α) treatment suppresses HIV-1 viremia and reduces the size of the HIV-1 latent reservoir. Therefore, investigation of the molecular and immunologic effects of IFN-α may provide insights that contribute to the development of novel prophylactic, therapeutic and curative strategies for HIV-1 infection. In this study, we hypothesized that microRNAs (miRNAs) contribute to the IFN-α-mediated suppression of HIV-1. To inform the development of novel miRNA-based antiretroviral strategies, we investigated the effects of exogenous IFN-α treatment on global miRNA expression profile, HIV-1 viremia, and potential regulatory networks between miRNAs and cell-intrinsic anti-HIV-1 host factors in vivo. METHODS Global miRNA expression was examined in longitudinal PBMC samples obtained from seven HIV/HCV-coinfected, antiretroviral therapy-naïve individuals before, during, and after pegylated interferon-α/ribavirin therapy (IFN-α/RBV). We implemented novel hybrid computational-empirical approaches to characterize regulatory networks between miRNAs and anti-HIV-1 host restriction factors. RESULTS miR-422a was the only miRNA significantly modulated by IFN-α/RBV in vivo (p<0.0001, paired t test; FDR<0.037). Our interactome mapping revealed extensive regulatory involvement of miR-422a in p53-dependent apoptotic and pyroptotic pathways. Based on sequence homology and inverse expression relationships, 29 unique miRNAs may regulate anti-HIV-1 restriction factor expression in vivo. CONCLUSIONS The specific reduction of miR-422a is associated with exogenous IFN-α treatment, and likely contributes to the IFN-α suppression of HIV-1 through the enhancement of anti-HIV-1 restriction factor expression and regulation of genes involved in programmed cell death. Moreover, our regulatory network analysis presents additional candidate miRNAs that may be targeted to enhance anti-HIV-1 restriction factor expression in vivo.

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Resting-state functional connectivity (FC) fMRI (rs-fcMRI) offers an appealing approach to mapping the brain's intrinsic functional organization. Blood oxygen level dependent (BOLD) and arterial spin labeling (ASL) are the two main rs-fcMRI approaches to assess alterations in brain networks associated with individual differences, behavior and psychopathology. While the BOLD signal is stronger with a higher temporal resolution, ASL provides quantitative, direct measures of the physiology and metabolism of specific networks. This study systematically investigated the similarity and reliability of resting brain networks (RBNs) in BOLD and ASL. A 2×2×2 factorial design was employed where each subject underwent repeated BOLD and ASL rs-fcMRI scans on two occasions on two MRI scanners respectively. Both independent and joint FC analyses revealed common RBNs in ASL and BOLD rs-fcMRI with a moderate to high level of spatial overlap, verified by Dice Similarity Coefficients. Test-retest analyses indicated more reliable spatial network patterns in BOLD (average modal Intraclass Correlation Coefficients: 0.905±0.033 between-sessions; 0.885±0.052 between-scanners) than ASL (0.545±0.048; 0.575±0.059). Nevertheless, ASL provided highly reproducible (0.955±0.021; 0.970±0.011) network-specific CBF measurements. Moreover, we observed positive correlations between regional CBF and FC in core areas of all RBNs indicating a relationship between network connectivity and its baseline metabolism. Taken together, the combination of ASL and BOLD rs-fcMRI provides a powerful tool for characterizing the spatiotemporal and quantitative properties of RBNs. These findings pave the way for future BOLD and ASL rs-fcMRI studies in clinical populations that are carried out across time and scanners.

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The urban transition almost always involves wrenching social adjustment as small agricultural communities are forced to adjust rapidly to industrial ways of life. Large-scale in-migration of young people, usually from poor regions, creates enormous demand and expectations for community and social services. One immediate problem planners face in approaching this challenge is how to define, differentiate, and map what is rural, urban, and transitional (i.e., peri-urban). This project established an urban classification for Vietnam by using national census and remote sensing data to identify and map the smallest administrative units for which data are collected as rural, peri-urban, urban, or urban core. We used both natural and human factors in the quantitative model: income from agriculture, land under agriculture and forests, houses with modern sanitation, and the Normalized Difference Vegetation Index. Model results suggest that in 2006, 71% of Vietnam's 10,891 communes were rural, 18% peri-urban, 3% urban, and 4% urban core. Of the communes our model classified as peri-urban, 61% were classified by the Vietnamese government as rural. More than 7% of Vietnam's land area can be classified as peri-urban and approximately 13% of its population (more than 11 million people) lives in peri-urban areas. We identified and mapped three types of peri-urban places: communes in the periphery of large towns and cities; communes along highways; and communes associated with provincial administration or home to industrial, energy, or natural resources projects (e.g., mining). We validated this classification based on ground observations, analyses of multi-temporal night-time lights data, and an examination of road networks. The model provides a method for rapidly assessing the rural–urban nature of places to assist planners in identifying rural areas undergoing rapid change with accompanying needs for investments in building, sanitation, road infrastructure, and government institutions.

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The brain is a complex neural network with a hierarchical organization and the mapping of its elements and connections is an important step towards the understanding of its function. Recent developments in diffusion-weighted imaging have provided the opportunity to reconstruct the whole-brain structural network in-vivo at a large scale level and to study the brain structural substrate in a framework that is close to the current understanding of brain function. However, methods to construct the connectome are still under development and they should be carefully evaluated. To this end, the first two studies included in my thesis aimed at improving the analytical tools specific to the methodology of brain structural networks. The first of these papers assessed the repeatability of the most common global and local network metrics used in literature to characterize the connectome, while in the second paper the validity of further metrics based on the concept of communicability was evaluated. Communicability is a broader measure of connectivity which accounts also for parallel and indirect connections. These additional paths may be important for reorganizational mechanisms in the presence of lesions as well as to enhance integration in the network. These studies showed good to excellent repeatability of global network metrics when the same methodological pipeline was applied, but more variability was detected when considering local network metrics or when using different thresholding strategies. In addition, communicability metrics have been found to add some insight into the integration properties of the network by detecting subsets of nodes that were highly interconnected or vulnerable to lesions. The other two studies used methods based on diffusion-weighted imaging to obtain knowledge concerning the relationship between functional and structural connectivity and about the etiology of schizophrenia. The third study integrated functional oscillations measured using electroencephalography (EEG) and functional magnetic resonance imaging (fMRI) as well as diffusion-weighted imaging data. The multimodal approach that was applied revealed a positive relationship between individual fluctuations of the EEG alpha-frequency and diffusion properties of specific connections of two resting-state networks. Finally, in the fourth study diffusion-weighted imaging was used to probe for a relationship between the underlying white matter tissue structure and season of birth in schizophrenia patients. The results are in line with the neurodevelopmental hypothesis of early pathological mechanisms as the origin of schizophrenia. The different analytical approaches selected in these studies also provide arguments for discussion of the current limitations in the analysis of brain structural networks. To sum up, the first studies presented in this thesis illustrated the potential of brain structural network analysis to provide useful information on features of brain functional segregation and integration using reliable network metrics. In the other two studies alternative approaches were presented. The common discussion of the four studies enabled us to highlight the benefits and possibilities for the analysis of the connectome as well as some current limitations.

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Using molecular building blocks to self-assemble lattices supporting long-range magnetic order is currently an active area of solid-state chemistry. Consequently, it is the realm of supramolecular chemistry that synthetic chemists are turning to in order to develop techniques for the synthesis of structurally well-defined supramolecular materials. In recent years we have investigated the versatility and usefulness of two classes of molecular building blocks, namely, tris-oxalato transition-metal (M. Pilkington and S. Decurtins, in “Magnetoscience—From Molecules to Materials,” Wiley–VCH, 2000), and octacyanometalate complexes (Pilkington and Decurtins, Chimia 54, 593 (2001)), for applications in the field of molecule-based magnets. Anionic, tris-chelated oxalato building blocks are able to build up two-dimensional honeycomb-layered structural motifs as well as three-dimensional decagon frameworks. The discrimination between the crystallization of the two- or three-dimensional structures relies on the choice of the templating counterions (Decurtins, Chimia 52, 539 (1998); Decurtins et al. Mol. Cryst. Liq. Cryst. 273, 167 (1995); New J. Chem. 117 (1998)). These structural types display a range of ferro, ferri, and antiferromagnetic properties (Pilkington and Decurtins, in “Magnetoscience—From Molecules to Materials”). Octacyanometalate building blocks self-assemble to afford two new classes of cyano-bridged compounds namely, molecular clusters and extended three dimensional networks (J. Larionova et al., Angew. Chem. Int. Ed. 39, 1605 (2000); Pilkington et al., in preparation). The molecular cluster with a MnII9MoV6 core has the highest ground state spin value, S=51/2, reported to-date (Larionova et al., Angew. Chem. Int. Ed. 39, 1605 (2000)). In the high-temperature regime, the magnetic properties are characterized by ferromagnetic intracluster coupling. In the magnetic range below 44 K, the magnetic cluster signature is lost as possibly a bulk behavior starts to emerge. The three-dimensional networks exhibit both paramagnetic and ferromagnetic behavior, since the magnetic properties of these materials directly reflect the electronic configuration of the metal ion incorporated into the octacyanometalate building blocks (Pilkington et al., in preparation). For both the oxalate- and cyanide-bridged materials, we are able to manipulate the magnetic properties of the supramolecular assemblies by tuning the electronic configurations of the metal ions incorporated into the appropriate molecular building blocks (Pilkington and Decurtins, in “Magnetoscience—From Molecules to Materials,” Chimia 54, 593 (2000)).

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Different cytokines are secreted in response to specific microbial molecules referred to as pathogen associated molecular patterns (PAMPs). Interleukin 6 (IL6) and interleukin 10 (IL10), both secreted by macrophages and lymphocytes, play a central role in the immunological response. In this work we obtained the genomic structure and complete DNA sequence of the porcine IL6 and IL10 genes and identified polymorphisms in the genomic sequences of these genes on a panel of ten different pig breeds. Comparative intra- and interbreed sequence analysis revealed a total of eight polymorphisms in the porcine IL6 gene and 21 in the porcine IL10 gene, which include single nucleotide polymorphisms (SNPs) and insertion deletion polymorphisms (indels). Additionally, the chromosomal localization of the IL10 gene was determined by FISH and RH mapping.