Proteomic analysis of Porphyromonas gingivalis exposed to nicotine and cotinine

Cogo K, de Andrade A, Labate CA, Bergamaschi CC, Berto LA, Franco GCN, Goncalves RB, Groppo FC. Proteomic analysis of Porphyromonas gingivalis exposed to nicotine and cotinine. J Periodont Res 2012; 47: 766775. (c) 2012 John Wiley & Sons A/S Background and Objective: Smokers are more predisposed than nonsmokers to infection with Porphyromonas gingivalis, one of the most important pathogens involved in the onset and development of periodontitis. It has also been observed that tobacco, and tobacco derivatives such as nicotine and cotinine, can induce modifications to P. gingivalis virulence. However, the effect of the major compounds derived from cigarettes on expression of protein by P.gingivalis is poorly understood. Therefore, this study aimed to evaluate and compare the effects of nicotine and cotinine on the P.gingivalis proteomic profile. Material and Methods: Total proteins of P gingivalis exposed to nicotine and cotinine were extracted and separated by two-dimensional electrophoresis. Proteins differentially expressed were successfully identified through liquid chromatography-mass spectrometry and primary sequence databases using MASCOT search engine, and gene ontology was carried out using DAVID tools. Results: Of the approximately 410 protein spots that were reproducibly detected on each gel, 23 were differentially expressed in at least one of the treatments. A particular increase was seen in proteins involved in metabolism, virulence and acquisition of peptides, protein synthesis and folding, transcription and oxidative stress. Few proteins showed significant decreases in expression; those that did are involved in cell envelope biosynthesis and proteolysis and also in metabolism. Conclusion: Our results characterized the changes in the proteome of P.gingivalis following exposure to nicotine and cotinine, suggesting that these substances may modulate, with minor changes, protein expression. The present study is, in part, a step toward understanding the potential smokepathogen interaction that may occur in smokers with periodontitis.

Pilot survey of expressed sequence tags (ESTs) from the asexual blood stages of Plasmodium vivax in human patients

Abstract Background Plasmodium vivax is the most widely distributed human malaria, responsible for 70–80 million clinical cases each year and large socio-economical burdens for countries such as Brazil where it is the most prevalent species. Unfortunately, due to the impossibility of growing this parasite in continuous in vitro culture, research on P. vivax remains largely neglected. Methods A pilot survey of expressed sequence tags (ESTs) from the asexual blood stages of P. vivax was performed. To do so, 1,184 clones from a cDNA library constructed with parasites obtained from 10 different human patients in the Brazilian Amazon were sequenced. Sequences were automatedly processed to remove contaminants and low quality reads. A total of 806 sequences with an average length of 586 bp met such criteria and their clustering revealed 666 distinct events. The consensus sequence of each cluster and the unique sequences of the singlets were used in similarity searches against different databases that included P. vivax, Plasmodium falciparum, Plasmodium yoelii, Plasmodium knowlesi, Apicomplexa and the GenBank non-redundant database. An E-value of <10-30 was used to define a significant database match. ESTs were manually assigned a gene ontology (GO) terminology Results A total of 769 ESTs could be assigned a putative identity based upon sequence similarity to known proteins in GenBank. Moreover, 292 ESTs were annotated and a GO terminology was assigned to 164 of them. Conclusion These are the first ESTs reported for P. vivax and, as such, they represent a valuable resource to assist in the annotation of the P. vivax genome currently being sequenced. Moreover, since the GC-content of the P. vivax genome is strikingly different from that of P. falciparum, these ESTs will help in the validation of gene predictions for P. vivax and to create a gene index of this malaria parasite.

Genome mapping and expression analyses of human intronic noncoding RNAs reveal tissue-specific patterns and enrichment in genes related to regulation of transcription

Abstract Background RNAs transcribed from intronic regions of genes are involved in a number of processes related to post-transcriptional control of gene expression. However, the complement of human genes in which introns are transcribed, and the number of intronic transcriptional units and their tissue expression patterns are not known. Results A survey of mRNA and EST public databases revealed more than 55,000 totally intronic noncoding (TIN) RNAs transcribed from the introns of 74% of all unique RefSeq genes. Guided by this information, we designed an oligoarray platform containing sense and antisense probes for each of 7,135 randomly selected TIN transcripts plus the corresponding protein-coding genes. We identified exonic and intronic tissue-specific expression signatures for human liver, prostate and kidney. The most highly expressed antisense TIN RNAs were transcribed from introns of protein-coding genes significantly enriched (p = 0.002 to 0.022) in the 'Regulation of transcription' Gene Ontology category. RNA polymerase II inhibition resulted in increased expression of a fraction of intronic RNAs in cell cultures, suggesting that other RNA polymerases may be involved in their biosynthesis. Members of a subset of intronic and protein-coding signatures transcribed from the same genomic loci have correlated expression patterns, suggesting that intronic RNAs regulate the abundance or the pattern of exon usage in protein-coding messages. Conclusion We have identified diverse intronic RNA expression patterns, pointing to distinct regulatory roles. This gene-oriented approach, using a combined intron-exon oligoarray, should permit further comparative analysis of intronic transcription under various physiological and pathological conditions, thus advancing current knowledge about the biological functions of these noncoding RNAs.

Computational framework to support integration of biomolecular and clinical data within a translational approach

Background The use of the knowledge produced by sciences to promote human health is the main goal of translational medicine. To make it feasible we need computational methods to handle the large amount of information that arises from bench to bedside and to deal with its heterogeneity. A computational challenge that must be faced is to promote the integration of clinical, socio-demographic and biological data. In this effort, ontologies play an essential role as a powerful artifact for knowledge representation. Chado is a modular ontology-oriented database model that gained popularity due to its robustness and flexibility as a generic platform to store biological data; however it lacks supporting representation of clinical and socio-demographic information. Results We have implemented an extension of Chado – the Clinical Module - to allow the representation of this kind of information. Our approach consists of a framework for data integration through the use of a common reference ontology. The design of this framework has four levels: data level, to store the data; semantic level, to integrate and standardize the data by the use of ontologies; application level, to manage clinical databases, ontologies and data integration process; and web interface level, to allow interaction between the user and the system. The clinical module was built based on the Entity-Attribute-Value (EAV) model. We also proposed a methodology to migrate data from legacy clinical databases to the integrative framework. A Chado instance was initialized using a relational database management system. The Clinical Module was implemented and the framework was loaded using data from a factual clinical research database. Clinical and demographic data as well as biomaterial data were obtained from patients with tumors of head and neck. We implemented the IPTrans tool that is a complete environment for data migration, which comprises: the construction of a model to describe the legacy clinical data, based on an ontology; the Extraction, Transformation and Load (ETL) process to extract the data from the source clinical database and load it in the Clinical Module of Chado; the development of a web tool and a Bridge Layer to adapt the web tool to Chado, as well as other applications. Conclusions Open-source computational solutions currently available for translational science does not have a model to represent biomolecular information and also are not integrated with the existing bioinformatics tools. On the other hand, existing genomic data models do not represent clinical patient data. A framework was developed to support translational research by integrating biomolecular information coming from different “omics” technologies with patient’s clinical and socio-demographic data. This framework should present some features: flexibility, compression and robustness. The experiments accomplished from a use case demonstrated that the proposed system meets requirements of flexibility and robustness, leading to the desired integration. The Clinical Module can be accessed in http://dcm.ffclrp.usp.br/caib/pg=iptrans webcite.

Genes involved in thoracic exoskeleton formation during the pupal-to-adult molt in a social insect model, Apis mellifera

Background: The insect exoskeleton provides shape, waterproofing, and locomotion via attached somatic muscles. The exoskeleton is renewed during molting, a process regulated by ecdysteroid hormones. The holometabolous pupa transforms into an adult during the imaginal molt, when the epidermis synthe3sizes the definitive exoskeleton that then differentiates progressively. An important issue in insect development concerns how the exoskeletal regions are constructed to provide their morphological, physiological and mechanical functions. We used whole-genome oligonucleotide microarrays to screen for genes involved in exoskeletal formation in the honeybee thoracic dorsum. Our analysis included three sampling times during the pupal-to-adult molt, i.e., before, during and after the ecdysteroid-induced apolysis that triggers synthesis of the adult exoskeleton. Results: Gene ontology annotation based on orthologous relationships with Drosophila melanogaster genes placed the honeybee differentially expressed genes (DEGs) into distinct categories of Biological Process and Molecular Function, depending on developmental time, revealing the functional elements required for adult exoskeleton formation. Of the 1,253 unique DEGs, 547 were upregulated in the thoracic dorsum after apolysis, suggesting induction by the ecdysteroid pulse. The upregulated gene set included 20 of the 47 cuticular protein (CP) genes that were previously identified in the honeybee genome, and three novel putative CP genes that do not belong to a known CP family. In situ hybridization showed that two of the novel genes were abundantly expressed in the epidermis during adult exoskeleton formation, strongly implicating them as genuine CP genes. Conserved sequence motifs identified the CP genes as members of the CPR, Tweedle, Apidermin, CPF, CPLCP1 and Analogous-to-Peritrophins families. Furthermore, 28 of the 36 muscle-related DEGs were upregulated during the de novo formation of striated fibers attached to the exoskeleton. A search for cis-regulatory motifs in the 5′-untranslated region of the DEGs revealed potential binding sites for known transcription factors. Construction of a regulatory network showed that various upregulated CP- and muscle-related genes (15 and 21 genes, respectively) share common elements, suggesting co-regulation during thoracic exoskeleton formation. Conclusions: These findings help reveal molecular aspects of rigid thoracic exoskeleton formation during the ecdysteroid-coordinated pupal-to-adult molt in the honeybee.

Transcriptional profiling of Saccharomyces cerevisiae exposed to propolis

Abstract Background Propolis is a natural product of plant resins collected by honeybees (Apis mellifera) from various plant sources. Our previous studies indicated that propolis sensitivity is dependent on the mitochondrial function and that vacuolar acidification and autophagy are important for yeast cell death caused by propolis. Here, we extended our understanding of propolis-mediated cell death in the yeast Saccharomyces cerevisiae by applying systems biology tools to analyze the transcriptional profiling of cells exposed to propolis. Methods We have used transcriptional profiling of S. cerevisiae exposed to propolis. We validated our findings by using real-time PCR of selected genes. Systems biology tools (physical protein-protein interaction [PPPI] network) were applied to analyse the propolis-induced transcriptional bevavior, aiming to identify which pathways are modulated by propolis in S. cerevisiae and potentially influencing cell death. Results We were able to observe 1,339 genes modulated in at least one time point when compared to the reference time (propolis untreated samples) (t-test, p-value 0.01). Enrichment analysis performed by Gene Ontology (GO) Term finder tool showed enrichment for several biological categories among the genes up-regulated in the microarray hybridization such as transport and transmembrane transport and response to stress. Real-time RT-PCR analysis of selected genes showed by our microarray hybridization approach was capable of providing information about S. cerevisiae gene expression modulation with a considerably high level of confidence. Finally, a physical protein-protein (PPPI) network design and global topological analysis stressed the importance of these pathways in response of S. cerevisiae to propolis and were correlated with the transcriptional data obtained thorough the microarray analysis. Conclusions In summary, our data indicate that propolis is largely affecting several pathways in the eukaryotic cell. However, the most prominent pathways are related to oxidative stress, mitochondrial electron transport chain, vacuolar acidification, regulation of macroautophagy associated with protein target to vacuole, cellular response to starvation, and negative regulation of transcription from RNA polymerase II promoter. Our work emphasizes again the importance of S. cerevisiae as a model system to understand at molecular level the mechanism whereby propolis causes cell death in this organism at the concentration herein tested. Our study is the first one that investigates systematically by using functional genomics how propolis influences and modulates the mRNA abundance of an organism and may stimulate further work on the propolis-mediated cell death mechanisms in fungi.

Relacionismo substancial: a ontologia do comportamento à luz do behaviorismo radical

Sob a influência do pragmatismo e contextualismo pepperiano, analistas do comportamento extraíram do behaviorismo radical qualquer posição ontológica. Como resultado, há a defesa de um relacionismo radical no qual a única propriedade relevante para a existência do comportamento é a própria relação que o define. O objetivo deste ensaio é avaliar a pertinência dessa posição. Três questões guiram esse trabalho: (1) Por que a substância não é importante para o behaviorismo radical?; (2) Por que a substância é importante para o behaviorismo radical?; e (3) Qual seria, de fato, o posicionamento ontológico mais condizente com o behaviorismo radical? Argumenta-se que o relacionismo radical não reflete com acurácia a ontologia behaviorista radical e sugere-se que o relacionismo substancial seja a posição mais coerente.

New insights in osteogenic differentiation revealed by mass spectrometric assessment of phosphorylated substrates in murine skin mesenchymal cells

Abstract Background Bone fractures and loss represent significant costs for the public health system and often affect the patients quality of life, therefore, understanding the molecular basis for bone regeneration is essential. Cytokines, such as IL-6, IL-10 and TNFα, secreted by inflammatory cells at the lesion site, at the very beginning of the repair process, act as chemotactic factors for mesenchymal stem cells, which proliferate and differentiate into osteoblasts through the autocrine and paracrine action of bone morphogenetic proteins (BMPs), mainly BMP-2. Although it is known that BMP-2 binds to ActRI/BMPR and activates the SMAD 1/5/8 downstream effectors, little is known about the intracellular mechanisms participating in osteoblastic differentiation. We assessed differences in the phosphorylation status of different cellular proteins upon BMP-2 osteogenic induction of isolated murine skin mesenchymal stem cells using Triplex Stable Isotope Dimethyl Labeling coupled with LC/MS. Results From 150 μg of starting material, 2,264 proteins were identified and quantified at five different time points, 235 of which are differentially phosphorylated. Kinase motif analysis showed that several substrates display phosphorylation sites for Casein Kinase, p38, CDK and JNK. Gene ontology analysis showed an increase in biological processes related with signaling and differentiation at early time points after BMP2 induction. Moreover, proteins involved in cytoskeleton rearrangement, Wnt and Ras pathways were found to be differentially phosphorylated during all timepoints studied. Conclusions Taken together, these data, allow new insights on the intracellular substrates which are phosphorylated early on during differentiation to BMP2-driven osteoblastic differentiation of skin-derived mesenchymal stem cells.

Semantic integration of gene expression analysis tools and data sources using software connectors

Abstract Background The study and analysis of gene expression measurements is the primary focus of functional genomics. Once expression data is available, biologists are faced with the task of extracting (new) knowledge associated to the underlying biological phenomenon. Most often, in order to perform this task, biologists execute a number of analysis activities on the available gene expression dataset rather than a single analysis activity. The integration of heteregeneous tools and data sources to create an integrated analysis environment represents a challenging and error-prone task. Semantic integration enables the assignment of unambiguous meanings to data shared among different applications in an integrated environment, allowing the exchange of data in a semantically consistent and meaningful way. This work aims at developing an ontology-based methodology for the semantic integration of gene expression analysis tools and data sources. The proposed methodology relies on software connectors to support not only the access to heterogeneous data sources but also the definition of transformation rules on exchanged data. Results We have studied the different challenges involved in the integration of computer systems and the role software connectors play in this task. We have also studied a number of gene expression technologies, analysis tools and related ontologies in order to devise basic integration scenarios and propose a reference ontology for the gene expression domain. Then, we have defined a number of activities and associated guidelines to prescribe how the development of connectors should be carried out. Finally, we have applied the proposed methodology in the construction of three different integration scenarios involving the use of different tools for the analysis of different types of gene expression data. Conclusions The proposed methodology facilitates the development of connectors capable of semantically integrating different gene expression analysis tools and data sources. The methodology can be used in the development of connectors supporting both simple and nontrivial processing requirements, thus assuring accurate data exchange and information interpretation from exchanged data.

Expression analysis and in silico characterization of intronic long noncoding RNAs in renal cell carcinoma: emerging functional associations

Abstract Background Intronic and intergenic long noncoding RNAs (lncRNAs) are emerging gene expression regulators. The molecular pathogenesis of renal cell carcinoma (RCC) is still poorly understood, and in particular, limited studies are available for intronic lncRNAs expressed in RCC Methods Microarray experiments were performed with custom-designed arrays enriched with probes for lncRNAs mapping to intronic genomic regions. Samples from 18 primary RCC tumors and 11 nontumor adjacent matched tissues were analyzed. Meta-analyses were performed with microarray expression data from three additional human tissues (normal liver, prostate tumor and kidney nontumor samples), and with large-scale public data for epigenetic regulatory marks and for evolutionarily conserved sequences. Results A signature of 29 intronic lncRNAs differentially expressed between RCC and nontumor samples was obtained (false discovery rate (FDR) <5%). A signature of 26 intronic lncRNAs significantly correlated with the RCC five-year patient survival outcome was identified (FDR <5%, p-value ≤0.01). We identified 4303 intronic antisense lncRNAs expressed in RCC, of which 22% were significantly (p <0.05) cis correlated with the expression of the mRNA in the same locus across RCC and three other human tissues. Gene Ontology (GO) analysis of those loci pointed to 'regulation of biological processes’ as the main enriched category. A module map analysis of the protein-coding genes significantly (p <0.05) trans correlated with the 20% most abundant lncRNAs, identified 51 enriched GO terms (p <0.05). We determined that 60% of the expressed lncRNAs are evolutionarily conserved. At the genomic loci containing the intronic RCC-expressed lncRNAs, a strong association (p <0.001) was found between their transcription start sites and genomic marks such as CpG islands, RNA Pol II binding and histones methylation and acetylation. Conclusion Intronic antisense lncRNAs are widely expressed in RCC tumors. Some of them are significantly altered in RCC in comparison with nontumor samples. The majority of these lncRNAs is evolutionarily conserved and possibly modulated by epigenetic modifications. Our data suggest that these RCC lncRNAs may contribute to the complex network of regulatory RNAs playing a role in renal cell malignant transformation.

Link prediction using a probabilistic description logic

Due to the growing interest in social networks, link prediction has received significant attention. Link prediction is mostly based on graph-based features, with some recent approaches focusing on domain semantics. We propose algorithms for link prediction that use a probabilistic ontology to enhance the analysis of the domain and the unavoidable uncertainty in the task (the ontology is specified in the probabilistic description logic crALC). The scalability of the approach is investigated, through a combination of semantic assumptions and graph-based features. We evaluate empirically our proposal, and compare it with standard solutions in the literature.