70 research outputs found

    Network modeling unravels mechanisms of crosstalk between ethylene and salicylate signaling in potato

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    To develop novel crop breeding strategies, it is crucial to understand the mechanisms underlying the interaction between plants and their pathogens. Network modeling represents a powerful tool that can unravel properties of complex biological systems. In this study, we aimed to use network modeling to better understand immune signaling in potato (Solanum tuberosum). For this, we first built on a reliable Arabidopsis (Arabidopsis thaliana) immune signaling model, extending it with the information from diverse publicly available resources. Next, we translated the resulting prior knowledge network (20,012 nodes and 70,091 connections) to potato and superimposed it with an ensemble network inferred from time-resolved transcriptomics data for potato. We used different network modeling approaches to generate specific hypotheses of potato immune signaling mechanisms. An interesting finding was the identification of a string of molecular events illuminating the ethylene pathway modulation of the salicylic acid pathway through Nonexpressor of PR Genesi gene expression. Functional validations confirmed this modulation, thus supporting the potential of our integrative network modeling approach for unraveling molecular mechanisms in complex systems. In addition, this approach can ultimately result in improved breeding strategies for potato and other sensitive crops

    Adaptation of the MapMan ontology to biotic stress responses: application in solanaceous species

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    <p>Abstract</p> <p>Background</p> <p>The results of transcriptome microarray analysis are usually presented as a list of differentially expressed genes. As these lists can be long, it is hard to interpret the desired experimental treatment effect on the physiology of analysed tissue, e.g. via selected metabolic or other pathways. For some organisms, gene ontologies and data visualization software have been implemented to overcome this problem, whereas for others, software adaptation is yet to be done.</p> <p>Results</p> <p>We present the classification of tentative potato contigs from the potato gene index (StGI) available from Dana-Farber Cancer Institute (DFCI) into the MapMan ontology to enable the application of the MapMan family of tools to potato microarrays. Special attention has been focused on mapping genes that could not be annotated based on similarity to Arabidopsis genes alone, thus possibly representing genes unique for potato. 97 such genes were classified into functional BINs (i.e. functional classes) after manual annotation. A new pathway, focusing on biotic stress responses, has been added and can be used for all other organisms for which mappings have been done. The BIN representation on the potato 10 k cDNA microarray, in comparison with all putative potato gene sequences, has been tested. The functionality of the prepared potato mapping was validated with experimental data on plant response to viral infection. In total 43,408 unigenes were mapped into 35 corresponding BINs.</p> <p>Conclusion</p> <p>The potato mappings can be used to visualize up-to-date, publicly available, expressed sequence tags (ESTs) and other sequences from GenBank, in combination with metabolic pathways. Further expert work on potato annotations will be needed with the ongoing EST and genome sequencing of potato. The current MapMan application for potato is directly applicable for analysis of data obtained on potato 10 k cDNA microarray by TIGR (The Institute for Genomic Research) but can also be used by researchers working on other potato gene sets. The potato mapping file and the stress mapping diagram are available from the MapMan website <abbrgrp><abbr bid="B1">1</abbr></abbrgrp>.</p

    Potentially toxic planktic and benthic Cyanobacteria in Slovenian freshwater bodies: detection by quantitative PCR

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    Due to increased frequency of cyanobacterial blooms and emerging evidence of cyanotoxicity in biofilm, reliable methods for early cyanotoxin threat detection are of major importance for protection of human, animal and environmental health. To complement the current methods of risk assessment, this study aimed to evaluate selected qPCR assays for detection of potentially toxic cyanobacteria in environmental samples. In the course of one year, 25 plankton and 23 biofilm samples were collected from 15 water bodies in Slovenia. Three different analyses were performed and compared to each other; qPCR targeting mcyE, cyrJ and sxtA genes involved in cyanotoxin production, LC-MS/MS quantifying microcystin, cylindrospermopsin and saxitoxin concentration, and microscopic analyses identifying potentially toxic cyanobacterial taxa. qPCR analyses detected potentially toxic Microcystis in 10 lake plankton samples, and potentially toxic Planktothrix cells in 12 lake plankton and one lake biofilm sample. A positive correlation was observed between numbers of mcyE gene copies and microcystin concentrations. Potential cylindrospermopsin- and saxitoxin-producers were detected in three and seven lake biofilm samples, respectively. The study demonstrated a potential for cyanotoxin production that was left undetected by traditional methods in both plankton and biofilm samples. Thus, the qPCR method could be useful in regular monitoring of water bodies to improve risk assessment and enable timely measures

    Revealing fosfomycin primary effect on Staphylococcus aureus transcriptome: modulation of cell envelope biosynthesis and phosphoenolpyruvate induced starvation

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    <p>Abstract</p> <p>Background</p> <p><it>Staphylococcus aureus </it>is a highly adaptable human pathogen and there is a constant search for effective antibiotics. Fosfomycin is a potent irreversible inhibitor of MurA, an enolpyruvyl transferase that uses phosphoenolpyruvate as substrate. The goal of this study was to identify the pathways and processes primarily affected by fosfomycin at the genome-wide transcriptome level to aid development of new drugs.</p> <p>Results</p> <p><it>S. aureus </it>ATCC 29213 cells were treated with sub-MIC concentrations of fosfomycin and harvested at 10, 20 and 40 minutes after treatment. <it>S. aureus </it>GeneChip statistical data analysis was complemented by gene set enrichment analysis. A visualization tool for mapping gene expression data into biological pathways was developed in order to identify the metabolic processes affected by fosfomycin. We have shown that the number of significantly differentially expressed genes in treated cultures increased with time and with increasing fosfomycin concentration. The target pathway - peptidoglycan biosynthesis - was upregulated following fosfomycin treatment. Modulation of transport processes, cofactor biosynthesis, energy metabolism and nucleic acid biosynthesis was also observed.</p> <p>Conclusions</p> <p>Several pathways and genes downregulated by fosfomycin have been identified, in contrast to previously described cell wall active antibiotics, and was explained by starvation response induced by phosphoenolpyruvate accumulation. Transcriptomic profiling, in combination with meta-analysis, has been shown to be a valuable tool in determining bacterial response to a specific antibiotic.</p

    The need for standardisation in life science research - an approach to excellence and trust

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    Today, academic researchers benefit from the changes driven by digital technologies and the enormous growth of knowledge and data, on globalisation, enlargement of the scientific community, and the linkage between different scientific communities and the society. To fully benefit from this development, however, information needs to be shared openly and transparently. Digitalisation plays a major role here because it permeates all areas of business, science and society and is one of the key drivers for innovation and international cooperation. To address the resulting opportunities, the EU promotes the development and use of collaborative ways to produce and share knowledge and data as early as possible in the research process, but also to appropriately secure results with the European strategy for Open Science (OS). It is now widely recognised that making research results more accessible to all societal actors contributes to more effective and efficient science; it also serves as a boost for innovation in the public and private sectors. However for research data to be findable, accessible, interoperable and reusable the use of standards is essential. At the metadata level, considerable efforts in standardisation have already been made (e.g. Data Management Plan and FAIR Principle etc.), whereas in context with the raw data these fundamental efforts are still fragmented and in some cases completely missing. The CHARME consortium, funded by the European Cooperation in Science and Technology (COST) Agency, has identified needs and gaps in the field of standardisation in the life sciences and also discussed potential hurdles for implementation of standards in current practice. Here, the authors suggest four measures in response to current challenges to ensure a high quality of life science research data and their re-usability for research and innovation

    Oxytetracycline hyper-production through targeted genome reduction of Streptomyces rimosus

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    Most biosynthetic gene clusters (BGC) encoding the synthesis of important microbial secondary metabolites, such as antibiotics, are either silent or poorly expressed; therefore, to ensure a strong pipeline of novel antibiotics, there is a need to develop rapid and efficient strain development approaches. This study uses comparative genome analysis to instruct rational strain improvement, using Streptomyces rimosus, the producer of the important antibiotic oxytetracycline (OTC) as a model system. Sequencing of the genomes of two industrial strains M4018 and R6-500, developed independently from a common ancestor, identified large DNA rearrangements located at the chromosome end. We evaluated the effect of these genome deletions on the parental S. rimosus Type Strain (ATCC 10970) genome where introduction of a 145 kb deletion close to the OTC BGC in the Type Strain resulted in massive OTC overproduction, achieving titers that were equivalent to M4018 and R6-500. Transcriptome data supported the hypothesis that the reason for such an increase in OTC biosynthesis was due to enhanced transcription of the OTC BGC and not due to enhanced substrate supply. We also observed changes in the expression of other cryptic BGCs; some metabolites, undetectable in ATCC 10970, were now produced at high titers. This study demonstrated for the first time that the main force behind BGC overexpression is genome rearrangement. This new approach demonstrates great potential to activate cryptic gene clusters of yet unexplored natural products of medical and industrial value

    Dynamics of Responses in Compatible Potato - Potato virus Y Interaction Are Modulated by Salicylic Acid

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    To investigate the dynamics of the potato – Potato virus Y (PVY) compatible interaction in relation to salicylic acid - controlled pathways we performed experiments using non-transgenic potato cv. Désirée, transgenic NahG-Désirée, cv. Igor and PVYNTN, the most aggressive strain of PVY. The importance of salicylic acid in viral multiplication and symptom development was confirmed by pronounced symptom development in NahG-Désirée, depleted in salicylic acid, and reversion of the effect after spraying with 2,6-dichloroisonicotinic acid (a salicylic acid - analogue). We have employed quantitative PCR for monitoring virus multiplication, as well as plant responses through expression of selected marker genes of photosynthetic activity, carbohydrate metabolism and the defence response. Viral multiplication was the slowest in inoculated potato of cv. Désirée, the only asymptomatic genotype in the study. The intensity of defence-related gene expression was much stronger in both sensitive genotypes (NahG-Désirée and cv. Igor) at the site of inoculation than in asymptomatic plants (cv. Désirée). Photosynthesis and carbohydrate metabolism gene expression differed between the symptomatic and asymptomatic phenotypes. The differential gene expression pattern of the two sensitive genotypes indicates that the outcome of the interaction does not rely simply on one regulatory component, but similar phenotypical features can result from distinct responses at the molecular level
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