4,457 research outputs found

    Mining Host-Pathogen Interactions

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    A Computational Framework for Host-Pathogen Protein-Protein Interactions

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    Infectious diseases cause millions of illnesses and deaths every year, and raise great health concerns world widely. How to monitor and cure the infectious diseases has become a prevalent and intractable problem. Since the host-pathogen interactions are considered as the key infection processes at the molecular level for infectious diseases, there have been a large amount of researches focusing on the host-pathogen interactions towards the understanding of infection mechanisms and the development of novel therapeutic solutions. For years, the continuously development of technologies in biology has benefitted the wet lab-based experiments, such as small-scale biochemical, biophysical and genetic experiments and large-scale methods (for example yeast-two-hybrid analysis and cryogenic electron microscopy approach). As a result of past decades of efforts, there has been an exploded accumulation of biological data, which includes multi omics data, for example, the genomics data and proteomics data. Thus, an initiative review of omics data has been conducted in Chapter 2, which has exclusively demonstrated the recent update of ‘omics’ study, particularly focusing on proteomics and genomics. With the high-throughput technologies, the increasing amount of ‘omics’ data, including genomics and proteomics, has even further boosted. An upsurge of interest for data analytics in bioinformatics comes as no surprise to the researchers from a variety of disciplines. Specifically, the astonishing rate at which genomics and proteomics data are generated leads the researchers into the realm of ‘Big Data’ research. Chapter 2 is thus developed to providing an update of the omics background and the state-of-the-art developments in the omics area, with a focus on genomics data, from the perspective of big data analytics..

    A combined approach for comparative exoproteome analysis of Corynebacterium pseudotuberculosis

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    Background: Bacterial exported proteins represent key components of the host-pathogen interplay. Hence, we sought to implement a combined approach for characterizing the entire exoproteome of the pathogenic bacterium Corynebacterium pseudotuberculosis, the etiological agent of caseous lymphadenitis (CLA) in sheep and goats. Results: An optimized protocol of three-phase partitioning (TPP) was used to obtain the C. pseudotuberculosis exoproteins, and a newly introduced method of data-independent MS acquisition (LC-MSE) was employed for protein identification and label-free quantification. Additionally, the recently developed tool SurfG+ was used for in silico prediction of sub-cellular localization of the identified proteins. In total, 93 different extracellular proteins of C. pseudotuberculosis were identified with high confidence by this strategy; 44 proteins were commonly identified in two different strains, isolated from distinct hosts, then composing a core C. pseudotuberculosis exoproteome. Analysis with the SurfG+ tool showed that more than 75% (70/93) of the identified proteins could be predicted as containing signals for active exportation. Moreover, evidence could be found for probable non-classical export of most of the remaining proteins. Conclusions: Comparative analyses of the exoproteomes of two C. pseudotuberculosis strains, in addition to comparison with other experimentally determined corynebacterial exoproteomes, were helpful to gain novel insights into the contribution of the exported proteins in the virulence of this bacterium. The results presented here compose the most comprehensive coverage of the exoproteome of a corynebacterial species so far

    A Perspective on CRN Proteins in the Genomics Age:Evolution, Classification, Delivery and Function Revisited

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    Plant associated microbes rely on secreted virulence factors (effectors) to modulate host immunity and ensure progressive infection. Amongst the secreted protein repertoires defined and studied in pathogens to date, the CRNs (for CRinkling and Necrosis) have emerged as one of only a few highly conserved protein families, spread across several kingdoms. CRN proteins were first identified in plant pathogenic oomycetes where they were found to be modular factors that are secreted and translocated inside host cells by means of a conserved N-terminal domain. Subsequent localization and functional studies have led to the view that CRN C-termini execute their presumed effector function in the host nucleus, targeting processes required for immunity. These findings have led to great interest in this large protein family and driven the identification of additional CRN-like proteins in other organisms. The identification of CRN proteins and subsequent functional studies have markedly increased the number of candidate CRN protein sequences, expanded the range of phenotypes tentatively associated with function and revealed some of their molecular functions toward virulence. The increased number of characterized CRNs also has presented a set of challenges that may impede significant progress in the future. Here, we summarize our current understanding of the CRNs and re-assess some basic assumptions regarding this protein family. We will discuss the latest findings on CRN biology and highlight exciting new hypotheses that have emanated from the field. Finally, we will discuss new approaches to study CRN functions that would lead to a better understanding of CRN effector biology as well as the processes that lead to host susceptibility and immunity

    Worldwide Research on Plant Defense against Biotic Stresses as Improvement for Sustainable Agriculture

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    Agriculture is the basis for food production on a global scale. Sustainable agriculture tries to improve or maintain the quality of food without compromising the environment. As sessile organisms, plants cannot avoid adverse environmental conditions and contact with other living organisms. The damage caused to plants by other living organisms such as parasites and pathogens (virus, bacteria, fungi, nematodes or insects) brings about what is known as biotic stress. Plants are constantly exposed to biotic stress, which causes changes in plant metabolism involving physiological damages that lead to a reduction of their productivity. To fight biotic stress, plants have developed sophisticated defense mechanisms. Thus, understanding plant defense mechanisms might prevent important crop and economic losses. In this article, a bibliometric analysis of biotic stress is carried out. Different aspects of the publications are analyzed, such as publication type, research field, journal type, countries and their institutions, as well as the keyword occurrence frequency, and finally special attention is paid to the plant studied by the leading countries and institutions. As expected, journals selected by authors to publish their relevant findings are plant-specific journals. However, it should be noted that the fourth position, in terms of the number of publications per journal, is occupied by BMC Genomics journal. Such a journal considers mainly articles on genomics, which indicates the involvement of genetic factors in the control of biotic stress. Analysis of the keywords used in publications about biotic stress shows the great interest in the biotic–abiotic stress interaction, in the gene expression regulation in plants as well as phytohormones in the current research. In short, the great effort made by the scientific community in the biotic and abiotic stresses field with the aim to understand, regulate and control plant damages caused by biotic stress agents will help in the development of sustainable agriculture

    Ontology-based Brucella vaccine literature indexing and systematic analysis of gene-vaccine association network

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    <p>Abstract</p> <p>Background</p> <p>Vaccine literature indexing is poorly performed in PubMed due to limited hierarchy of Medical Subject Headings (MeSH) annotation in the vaccine field. Vaccine Ontology (VO) is a community-based biomedical ontology that represents various vaccines and their relations. SciMiner is an in-house literature mining system that supports literature indexing and gene name tagging. We hypothesize that application of VO in SciMiner will aid vaccine literature indexing and mining of vaccine-gene interaction networks. As a test case, we have examined vaccines for <it>Brucella</it>, the causative agent of brucellosis in humans and animals.</p> <p>Results</p> <p>The VO-based SciMiner (VO-SciMiner) was developed to incorporate a total of 67 <it>Brucella </it>vaccine terms. A set of rules for term expansion of VO terms were learned from training data, consisting of 90 biomedical articles related to <it>Brucella </it>vaccine terms. VO-SciMiner demonstrated high recall (91%) and precision (99%) from testing a separate set of 100 manually selected biomedical articles. VO-SciMiner indexing exhibited superior performance in retrieving <it>Brucella </it>vaccine-related papers over that obtained with MeSH-based PubMed literature search. For example, a VO-SciMiner search of "live attenuated <it>Brucella </it>vaccine" returned 922 hits as of April 20, 2011, while a PubMed search of the same query resulted in only 74 hits. Using the abstracts of 14,947 <it>Brucella</it>-related papers, VO-SciMiner identified 140 <it>Brucella </it>genes associated with <it>Brucella </it>vaccines. These genes included known protective antigens, virulence factors, and genes closely related to <it>Brucella </it>vaccines. These VO-interacting <it>Brucella </it>genes were significantly over-represented in biological functional categories, including metabolite transport and metabolism, replication and repair, cell wall biogenesis, intracellular trafficking and secretion, posttranslational modification, and chaperones. Furthermore, a comprehensive interaction network of <it>Brucella </it>vaccines and genes were identified. The asserted and inferred VO hierarchies provide semantic support for inferring novel knowledge of association of vaccines and genes from the retrieved data. New hypotheses were generated based on this analysis approach.</p> <p>Conclusion</p> <p>VO-SciMiner can be used to improve the efficiency for PubMed searching in the vaccine domain.</p

    Bioinformatics analysis of Brucella vaccines and vaccine targets using VIOLIN

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    Abstract Background Brucella spp. are Gram-negative, facultative intracellular bacteria that cause brucellosis, one of the commonest zoonotic diseases found worldwide in humans and a variety of animal species. While several animal vaccines are available, there is no effective and safe vaccine for prevention of brucellosis in humans. VIOLIN (http://www.violinet.org) is a web-based vaccine database and analysis system that curates, stores, and analyzes published data of commercialized vaccines, and vaccines in clinical trials or in research. VIOLIN contains information for 454 vaccines or vaccine candidates for 73 pathogens. VIOLIN also contains many bioinformatics tools for vaccine data analysis, data integration, and vaccine target prediction. To demonstrate the applicability of VIOLIN for vaccine research, VIOLIN was used for bioinformatics analysis of existing Brucella vaccines and prediction of new Brucella vaccine targets. Results VIOLIN contains many literature mining programs (e.g., Vaxmesh) that provide in-depth analysis of Brucella vaccine literature. As a result of manual literature curation, VIOLIN contains information for 38 Brucella vaccines or vaccine candidates, 14 protective Brucella antigens, and 68 host response studies to Brucella vaccines from 97 peer-reviewed articles. These Brucella vaccines are classified in the Vaccine Ontology (VO) system and used for different ontological applications. The web-based VIOLIN vaccine target prediction program Vaxign was used to predict new Brucella vaccine targets. Vaxign identified 14 outer membrane proteins that are conserved in six virulent strains from B. abortus, B. melitensis, and B. suis that are pathogenic in humans. Of the 14 membrane proteins, two proteins (Omp2b and Omp31-1) are not present in B. ovis, a Brucella species that is not pathogenic in humans. Brucella vaccine data stored in VIOLIN were compared and analyzed using the VIOLIN query system. Conclusions Bioinformatics curation and ontological representation of Brucella vaccines promotes classification and analysis of existing Brucella vaccines and vaccine candidates. Computational prediction of Brucella vaccine targets provides more candidates for rational vaccine development. The use of VIOLIN provides a general approach that can be applied for analyses of vaccines against other pathogens and infection diseases.http://deepblue.lib.umich.edu/bitstream/2027.42/78263/1/1745-7580-6-S1-S5.xmlhttp://deepblue.lib.umich.edu/bitstream/2027.42/78263/2/1745-7580-6-S1-S5.pdfPeer Reviewe
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