Nuno Rosa

Computational prediction of the human-microbial oral interactome

BackgroundThe oral cavity is a complex ecosystem where human chemical compounds coexist with a particular microbiota. However, shifts in the normal composition of this microbiota may result in the onset of oral ailments, such as periodontitis and dental caries. In addition, it is known that the microbial colonization of the oral cavity is mediated by protein-protein interactions (PPIs) between the host and microorganisms. Nevertheless, this kind of PPIs is still largely undisclosed. To elucidate these interactions, we have created a computational prediction method that allows us to obtain a first model of the Human-Microbial oral interactome.ResultsWe collected high-quality experimental PPIs from five major human databases. The obtained PPIs were used to create our positive dataset and, indirectly, our negative dataset. The positive and negative datasets were merged and used for training and validation of a naïve Bayes classifier. For the final prediction model, we used an ensemble methodology combining five distinct PPI prediction techniques, namely: literature mining, primary protein sequences, orthologous profiles, biological process similarity, and domain interactions. Performance evaluation of our method revealed an area under the ROC-curve (AUC) value greater than 0.926, supporting our primary hypothesis, as no single set of features reached an AUC greater than 0.877. After subjecting our dataset to the prediction model, the classified result was filtered for very high confidence PPIs (probability ≥ 1-10−7), leading to a set of 46,579 PPIs to be further explored.ConclusionsWe believe this dataset holds not only important pathways involved in the onset of infectious oral diseases, but also potential drug-targets and biomarkers. The dataset used for training and validation, the predictions obtained and the network final network are available at http://bioinformatics.ua.pt/software/oralint.

OralCard: A bioinformatic tool for the study of oral proteome

OBJECTIVES The molecular complexity of the human oral cavity can only be clarified through identification of components that participate within it. However current proteomic techniques produce high volumes of information that are dispersed over several online databases. Collecting all of this data and using an integrative approach capable of identifying unknown associations is still an unsolved problem. This is the main motivation for this work. RESULTS We present the online bioinformatic tool OralCard, which comprises results from 55 manually curated articles reflecting the oral molecular ecosystem (OralPhysiOme). It comprises experimental information available from the oral proteome both of human (OralOme) and microbial origin (MicroOralOme) structured in protein, disease and organism. CONCLUSIONS This tool is a key resource for researchers to understand the molecular foundations implicated in biology and disease mechanisms of the oral cavity. The usefulness of this tool is illustrated with the analysis of the oral proteome associated with diabetes melitus type 2. OralCard is available at http://bioinformatics.ua.pt/oralcard.

CanisOme — The protein signatures of Canis lupus familiaris diseases

UNLABELLED Although the applications of Proteomics in Human Biomedicine have been explored for some time now, in animal and veterinary research, the potential of this resource has just started to be explored, especially when companion animal health is considered. In the last years, knowledge on the Canis lupus familiaris proteome has been accumulating in the literature and a resource compiling all this information and critically reviewing it was lacking. This article presents such a resource for the first time. CanisOme is a database of all proteins identified in Canis lupus familiaris tissues, either in health or in disease, annotated with information on the proteins present on the sample and on the donors. This database reunites information on 549 proteins, associated with 63 dog diseases and 33 dog breeds. Examples of how this information may be used to produce new hypothesis on disease mechanisms is presented both through the functional analysis of the proteins quantified in canine cutaneous mast cell tumors and through the study of the interactome of C. lupus familiaris and Leishmania infantum. Therefore, the usefulness of CanisOme for researchers looking for protein biomarkers in dogs and interested in a comprehensive analysis of disease mechanisms is demonstrated. BIOLOGICAL SIGNIFICANCE This paper presents CanisOme, a database of proteomic studies with relevant protein annotation, allowing the enlightenment of disease mechanisms and the discovery of novel disease biomarkers for C. lupus familiaris. This knowledge is important not only for the improvement of animal health but also for the use of dogs as models for human health studies.

The landscape of protein biomarkers proposed for periodontal disease: markers with functional meaning.

Periodontal disease (PD) is characterized by a deregulated inflammatory response which fails to resolve, activating bone resorption. The identification of the proteomes associated with PD has fuelled biomarker proposals; nevertheless, many questions remain. Biomarker selection should favour molecules representing an event which occurs throughout the disease progress. The analysis of proteome results and the information available for each protein, including its functional role, was accomplished using the OralOme database. The integrated analysis of this information ascertains if the suggested proteins reflect the cell and/or molecular mechanisms underlying the different forms of periodontal disease. The evaluation of the proteins present/absent or with very different concentrations in the proteome of each disease state was used for the identification of the mechanisms shared by different PD variants or specific to such state. The information presented is relevant for the adequate design of biomarker panels for PD. Furthermore, it will open new perspectives and help envisage future studies targeted to unveil the functional role of specific proteins and help clarify the deregulation process in the PD inflammatory response.

SalivaPRINT Toolkit – Protein profile evaluation and phenotype stratification

The value of the molecular information obtained from saliva is dependent on the use of in vitro and in silico techniques. The main proteins of saliva when separated by capillary electrophoresis enable the establishment of individual profiles with characteristic patterns reflecting each individual phenotype. Different physiological or pathological conditions may be identified by specific protein profiles. The association of each profile to the particular protein composition provides clues as to which biological processes are compromised in each situation. Patient stratification according to different phenotypes often within a particular disease spectrum is especially important for the management of individuals carrying multiple diseases and requiring personalized interventions. In this work we present the SalivaPRINT Toolkit, which enables the analysis of protein profile patterns and patient phenotyping. Additionally, the SalivaPRINT Toolkit allows the identification of molecular weight ranges altered in a particular condition and therefore potentially involved in the underlying dysregulated mechanisms. This tutorial introduces the use of the SalivaPRINT Toolkit command line interface (https://github.com/salivatec/SalivaPRINT) as an independent tool for electrophoretic protein profile evaluation. It provides a detailed overview of its functionalities, illustrated by the application to the analysis of profiles obtained from a healthy population versus a population affected with inflammatory conditions. BIOLOGICAL SIGNIFICANCE We present SalivaPRINT, which serves as a patient characterization tool to identify molecular weights related with particular conditions and, from there, find proteins, which may be involved in the underlying dysregulated cellular mechanisms. The proposed analysis strategy has the potential to boost personalized diagnosis. To our knowledge this is the first independent tool for electrophoretic protein profile evaluation and is crucial when a large number of complex electrophoretic profiles needs to be compared and classified.

Selected Cardoon (Cynara cardunculus L.) Genotypes Suitable for PDO Cheeses in Mediterranean Regions

Cardoon flower extract is a traditional and exclusive rennet used for some PDO cheeses in several Mediterranean regions, due to its extremely high concentration in cardosins. In this preliminary study, six individual cardoon genotypes (1M – 6M) were selected because they revealed a wide and consistent diversity of total and specific cardosin concentrations in flowers. During three growing seasons, the stability of 12 biochemical characteristics of flower extracts and 26 plant morphological descriptors was confirmed. Surprisingly, the cardosin profiles of each genotype, based on four main groups A0, A1, A and B, were stable during the annual flower harvesting period and over all three years using ion‐exchange chromatography and native‐PAGE electrophoresis. This knowledge will allow an improvement in the quality and standardization of cardosin profiles from cardoon flowers used for cheese production and other innovative applications. The results obtained are promising for the development of a plant breeding program based on biochemical and morphological characteristics in order to obtain the most adapted plant architecture for combined purposes related to specific cardosins composition, flower and plant biomass production, and ease of harvesting.

New Targets for Zika Virus Determined by Human-Viral Interactomic: A Bioinformatics Approach

Identifying ZIKV factors interfering with human host pathways represents a major challenge in understanding ZIKV tropism and pathogenesis. The integration of proteomic, gene expression and Protein-Protein Interactions (PPIs) established between ZIKV and human host proteins predicted by the OralInt algorithm identified 1898 interactions with medium or high score (≥0.7). Targets implicated in vesicular traffic and docking were identified. New receptors involved in endocytosis pathways as ZIKV entry targets, using both clathrin-dependent (17 receptors) and independent (10 receptors) pathways, are described. New targets used by the ZIKV to undermine the hosts antiviral immune response are proposed based on predicted interactions established between the virus and host cell receptors and/or proteins with an effector or signaling role in the immune response such as IFN receptors and TLR. Complement and cytokines are proposed as extracellular potential interacting partners of the secreted form of NS1 ZIKV protein. Altogether, in this article, 18 new human targets for structural and nonstructural ZIKV proteins are proposed. These results are of great relevance for the understanding of viral pathogenesis and consequently the development of preventive (vaccines) and therapeutic targets for ZIKV infection management.

Data Integration Solution for Organ-Specific Studies: An Application for Oral Biology

The human oral cavity is a complex ecosystem where multiple interactions occur and whose comprehension is critical in understanding several disease mechanisms. In order to comprehend the composition of the oral cavity at a molecular level, it is necessary to compile and integrate the biological information resulting from specific techniques, especially from proteomic studies of saliva. The objective of this work was to compile and curate a specific group of proteins related to the oral cavity, providing a tool to conduct further studies of the salivary proteome. In this paper we present a platform that integrates in a single endpoint all available information for proteins associated with the oral cavity. The proposed tool allows researchers in biomedical sciences to explore microorganisms, proteins and diseases, constituting a unique tool to analyse meaningful interactions for oral health.