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Featured researches published by Marko Petek.


Journal of Experimental Botany | 2014

Salicylic acid is an indispensable component of the Ny-1 resistance-gene-mediated response against Potato virus Y infection in potato

Špela Baebler; Kamil Witek; Marko Petek; Katja Stare; M. Tušek-Žnidarič; Maruša Pompe-Novak; Jenny Renaut; Katarzyna Szajko; Danuta Strzelczyk-Żyta; Waldemar Marczewski; K. Morgiewicz; Kristina Gruden; Jacek Hennig

The purpose of the study was to investigate the role of salicylic acid (SA) signalling in Ny-1-mediated hypersensitive resistance (HR) of potato (Solanum tuberosum L.) to Potato virus Y (PVY). The responses of the Ny-1 allele in the Rywal potato cultivar and transgenic NahG-Rywal potato plants that do not accumulate SA were characterized at the cytological, biochemical, transcriptome, and proteome levels. Analysis of noninoculated and inoculated leaves revealed that HR lesions started to develop from 3 d post inoculation and completely restricted the virus spread. At the cytological level, features of programmed cell death in combination with reactive oxygen species burst were observed. In response to PVY infection, SA was synthesized de novo. The lack of SA accumulation in the NahG plants led to the disease phenotype due to unrestricted viral spreading. Grafting experiments show that SA has a critical role in the inhibition of PVY spreading in parenchymal tissue, but not in vascular veins. The whole transcriptome analysis confirmed the central role of SA in orchestrating Ny-1-mediated responses and showed that the absence of SA leads to significant changes at the transcriptome level, including a delay in activation of expression of genes known to participate in defence responses. Moreover, perturbations in the expression of hormonal signalling genes were detected, shown as a switch from SA to jasmonic acid/ethylene signalling. Viral multiplication in the NahG plants was accompanied by downregulation of photosynthesis genes and activation of multiple energy-producing pathways.


BMC Bioinformatics | 2011

SegMine workflows for semantic microarray data analysis in Orange4WS.

Vid Podpečan; Nada Lavrač; Igor Mozetič; Petra Kralj Novak; Igor Trajkovski; Laura Langohr; Kimmo Kulovesi; Hannu Toivonen; Marko Petek; Helena Motaln; Kristina Gruden

BackgroundIn experimental data analysis, bioinformatics researchers increasingly rely on tools that enable the composition and reuse of scientific workflows. The utility of current bioinformatics workflow environments can be significantly increased by offering advanced data mining services as workflow components. Such services can support, for instance, knowledge discovery from diverse distributed data and knowledge sources (such as GO, KEGG, PubMed, and experimental databases). Specifically, cutting-edge data analysis approaches, such as semantic data mining, link discovery, and visualization, have not yet been made available to researchers investigating complex biological datasets.ResultsWe present a new methodology, SegMine, for semantic analysis of microarray data by exploiting general biological knowledge, and a new workflow environment, Orange4WS, with integrated support for web services in which the SegMine methodology is implemented. The SegMine methodology consists of two main steps. First, the semantic subgroup discovery algorithm is used to construct elaborate rules that identify enriched gene sets. Then, a link discovery service is used for the creation and visualization of new biological hypotheses. The utility of SegMine, implemented as a set of workflows in Orange4WS, is demonstrated in two microarray data analysis applications. In the analysis of senescence in human stem cells, the use of SegMine resulted in three novel research hypotheses that could improve understanding of the underlying mechanisms of senescence and identification of candidate marker genes.ConclusionsCompared to the available data analysis systems, SegMine offers improved hypothesis generation and data interpretation for bioinformatics in an easy-to-use integrated workflow environment.


PLOS ONE | 2016

Primary Metabolism, Phenylpropanoids and Antioxidant Pathways Are Regulated in Potato as a Response to Potato virus Y Infection

Polona Kogovšek; Maruša Pompe-Novak; Marko Petek; Lena Fragner; Wolfram Weckwerth; Kristina Gruden

Potato production is one of the most important agricultural sectors, and it is challenged by various detrimental factors, including virus infections. To control losses in potato production, knowledge about the virus—plant interactions is crucial. Here, we investigated the molecular processes in potato plants as a result of Potato virus Y (PVY) infection, the most economically important potato viral pathogen. We performed an integrative study that links changes in the metabolome and gene expression in potato leaves inoculated with the mild PVYN and aggressive PVYNTN isolates, for different times through disease development. At the beginning of infection (1 day post-inoculation), virus-infected plants showed an initial decrease in the concentrations of metabolites connected to sugar and amino-acid metabolism, the TCA cycle, the GABA shunt, ROS scavangers, and phenylpropanoids, relative to the control plants. A pronounced increase in those metabolites was detected at the start of the strong viral multiplication in infected leaves. The alterations in these metabolic pathways were also seen at the gene expression level, as analysed by quantitative PCR. In addition, the systemic response in the metabolome to PVY infection was analysed. Systemic leaves showed a less-pronounced response with fewer metabolites altered, while phenylpropanoid-associated metabolites were strongly accumulated. There was a more rapid onset of accumulation of ROS scavengers in leaves inoculated with PVYN than those inoculated with PVYNTN. This appears to be related to the lower damage observed for leaves of potato infected with the milder PVYN strain, and at least partially explains the differences between the phenotypes observed.


PLOS ONE | 2012

Signalling Network Construction for Modelling Plant Defence Response

Dragana Miljkovic; Tjaša Stare; Igor Mozetič; Vid Podpečan; Marko Petek; Kamil Witek; Marina Dermastia; Nada Lavrač; Kristina Gruden

Plant defence signalling response against various pathogens, including viruses, is a complex phenomenon. In resistant interaction a plant cell perceives the pathogen signal, transduces it within the cell and performs a reprogramming of the cell metabolism leading to the pathogen replication arrest. This work focuses on signalling pathways crucial for the plant defence response, i.e., the salicylic acid, jasmonic acid and ethylene signal transduction pathways, in the Arabidopsis thaliana model plant. The initial signalling network topology was constructed manually by defining the representation formalism, encoding the information from public databases and literature, and composing a pathway diagram. The manually constructed network structure consists of 175 components and 387 reactions. In order to complement the network topology with possibly missing relations, a new approach to automated information extraction from biological literature was developed. This approach, named Bio3graph, allows for automated extraction of biological relations from the literature, resulting in a set of (component1, reaction, component2) triplets and composing a graph structure which can be visualised, compared to the manually constructed topology and examined by the experts. Using a plant defence response vocabulary of components and reaction types, Bio3graph was applied to a set of 9,586 relevant full text articles, resulting in 137 newly detected reactions between the components. Finally, the manually constructed topology and the new reactions were merged to form a network structure consisting of 175 components and 524 reactions. The resulting pathway diagram of plant defence signalling represents a valuable source for further computational modelling and interpretation of omics data. The developed Bio3graph approach, implemented as an executable language processing and graph visualisation workflow, is publically available at http://ropot.ijs.si/bio3graph/and can be utilised for modelling other biological systems, given that an adequate vocabulary is provided.


BMC Microbiology | 2010

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

Marko Petek; Špela Baebler; Drago Kuzman; Ana Rotter; Zdravko Podlesek; Kristina Gruden; Maja Ravnikar; Uroš Urleb

BackgroundStaphylococcus aureus 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.ResultsS. aureus ATCC 29213 cells were treated with sub-MIC concentrations of fosfomycin and harvested at 10, 20 and 40 minutes after treatment. S. aureus 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.ConclusionsSeveral 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.


Molecular Ecology | 2014

Potato virus Y infection hinders potato defence response and renders plants more vulnerable to Colorado potato beetle attack

Marko Petek; Ana Rotter; Polona Kogovšek; Špela Baebler; Axel Mithöfer; Kristina Gruden

In the field, plants are challenged by more than one biotic stressor at the same time. In this study, the molecular interactions between potato (Solanum tuberosum L.), Colorado potato beetle (Leptinotarsa decemlineata Say; CPB) and Potato virus YNTN (PVYNTN) were investigated through analyses of gene expression in the potato leaves and the gut of the CPB larvae, and of the release of potato volatile compounds. CPB larval growth was enhanced when reared on secondary PVYNTN‐infected plants, which was linked to decreased accumulation of transcripts associated with the antinutritional properties of potato. In PVYNTN‐infected plants, ethylene signalling pathway induction and induction of auxin response transcription factors were attenuated, while no differences were observed in jasmonic acid (JA) signalling pathway. Similarly to rearing on virus‐infected plants, CPB larvae gained more weight when reared on plants silenced in JA receptor gene (coi1). Although herbivore‐induced defence mechanism is regulated predominantly by JA, response in coi1‐silenced plants only partially corresponded to the one observed in PVYNTN‐infected plants, confirming the role of other plant hormones in modulating this response. The release of β‐barbatene and benzyl alcohol was different in healthy and PVYNTN‐infected plants before CPB larvae infestation, implicating the importance of PVYNTN infection in plant communication with its environment. This was reflected in gene expression profiles of neighbouring plants showing different degree of defence response. This study thus contributes to our understanding of plant responses in agro‐ecosystems.


Journal of Agricultural and Food Chemistry | 2013

Inhibition of the growth of colorado potato beetle larvae by macrocypins, protease inhibitors from the parasol mushroom.

Ida Šmid; Kristina Gruden; Meti Buh Gašparič; Katarina Koruza; Marko Petek; Jure Pohleven; Jože Brzin; Janko Kos; Jana Žel; Jerica Sabotič

Proteins from higher fungi have attracted interest because of their exceptional characteristics. Macrocypins, cysteine protease inhibitors from the parasol mushroom Macrolepiota procera , were evaluated for their adverse effects and their mode of action on the major potato pest Colorado potato beetle (CPB, Leptinotarsa decemlineata Say). They were shown to reduce larval growth when expressed in potato or when their recombinant analogues were added to the diet. Macrocypins target a specific set of digestive cysteine proteases, intestains. Additionally, protein-protein interaction analysis revealed potential targets among other digestive enzymes and proteins related to development and primary metabolism. No effect of dietary macrocypins on gene expression of known adaptation-related digestive enzymes was observed in CPB guts. Macrocypins are the first fungal protease inhibitors to be reported as having a negative effect on growth and development of CPB larvae and could also be evaluated as control agents for other pests.


Microbial Cell Factories | 2013

SACE_5599, a putative regulatory protein, is involved in morphological differentiation and erythromycin production in Saccharopolyspora erythraea

Benjamin Kirm; Vasilka Magdevska; Miha Tome; Marinka Horvat; Katarina Karničar; Marko Petek; Robert Vidmar; Špela Baebler; Polona Jamnik; Štefan Fujs; Jaka Horvat; Marko Fonović; Boris Turk; Kristina Gruden; Hrvoje Petković; Gregor Kosec

BackgroundErythromycin is a medically important antibiotic, biosynthesized by the actinomycete Saccharopolyspora erythraea. Genes encoding erythromycin biosynthesis are organized in a gene cluster, spanning over 60 kbp of DNA. Most often, gene clusters encoding biosynthesis of secondary metabolites contain regulatory genes. In contrast, the erythromycin gene cluster does not contain regulatory genes and regulation of its biosynthesis has therefore remained poorly understood, which has for a long time limited genetic engineering approaches for erythromycin yield improvement.ResultsWe used a comparative proteomic approach to screen for potential regulatory proteins involved in erythromycin biosynthesis. We have identified a putative regulatory protein SACE_5599 which shows significantly higher levels of expression in an erythromycin high-producing strain, compared to the wild type S. erythraea strain. SACE_5599 is a member of an uncharacterized family of putative regulatory genes, located in several actinomycete biosynthetic gene clusters. Importantly, increased expression of SACE_5599 was observed in the complex fermentation medium and at controlled bioprocess conditions, simulating a high-yield industrial fermentation process in the bioreactor. Inactivation of SACE_5599 in the high-producing strain significantly reduced erythromycin yield, in addition to drastically decreasing sporulation intensity of the SACE_5599-inactivated strains when cultivated on ABSM4 agar medium. In contrast, constitutive overexpression of SACE_5599 in the wild type NRRL23338 strain resulted in an increase of erythromycin yield by 32%. Similar yield increase was also observed when we overexpressed the bldD gene, a previously identified regulator of erythromycin biosynthesis, thereby for the first time revealing its potential for improving erythromycin biosynthesis.ConclusionsSACE_5599 is the second putative regulatory gene to be identified in S. erythraea which has positive influence on erythromycin yield. Like bldD, SACE_5599 is involved in morphological development of S. erythraea, suggesting a very close relationship between secondary metabolite biosynthesis and morphological differentiation in this organism. While the mode of action of SACE_5599 remains to be elucidated, the manipulation of this gene clearly shows potential for improvement of erythromycin production in S. erythraea in industrial setting. We have also demonstrated the applicability of the comparative proteomics approach for identifying new regulatory elements involved in biosynthesis of secondary metabolites in industrial conditions.


BMC Bioinformatics | 2017

quantGenius: implementation of a decision support system for qPCR-based gene quantification

Špela Baebler; Miha Svalina; Marko Petek; Katja Stare; Ana Rotter; Maruša Pompe-Novak; Kristina Gruden

BackgroundQuantitative molecular biology remains a challenge for researchers due to inconsistent approaches for control of errors in the final results. Due to several factors that can influence the final result, quantitative analysis and interpretation of qPCR data are still not trivial. Together with the development of high-throughput qPCR platforms, there is a need for a tool allowing for robust, reliable and fast nucleic acid quantification.ResultsWe have developed “quantGenius” (http://quantgenius.nib.si), an open-access web application for a reliable qPCR-based quantification of nucleic acids. The quantGenius workflow interactively guides the user through data import, quality control (QC) and calculation steps. The input is machine- and chemistry–independent. Quantification is performed using the standard curve approach, with normalization to one or several reference genes. The special feature of the application is the implementation of user-guided QC-based decision support system, based on qPCR standards, that takes into account pipetting errors, assay amplification efficiencies, limits of detection and quantification of the assays as well as the control of PCR inhibition in individual samples. The intermediate calculations and final results are exportable in a data matrix suitable for further statistical analysis or visualization. We additionally compare the most important features of quantGenius with similar advanced software tools and illustrate the importance of proper QC system in the analysis of qPCR data in two use cases.ConclusionsTo our knowledge, quantGenius is the only qPCR data analysis tool that integrates QC-based decision support and will help scientists to obtain reliable results which are the basis for biologically meaningful data interpretation.


Microbial Cell Factories | 2016

Integrated omics approaches provide strategies for rapid erythromycin yield increase in Saccharopolyspora erythraea

Katarina Karničar; Igor Drobnak; Marko Petek; Vasilka Magdevska; Jaka Horvat; Robert Vidmar; Špela Baebler; Ana Rotter; Polona Jamnik; Štefan Fujs; Boris Turk; Marko Fonović; Kristina Gruden; Gregor Kosec; Hrvoje Petković

BackgroundOmics approaches have significantly increased our understanding of biological systems. However, they have had limited success in explaining the dramatically increased productivity of commercially important natural products by industrial high-producing strains, such as the erythromycin-producing actinomycete Saccharopolyspora erythraea. Further yield increase is of great importance but requires a better understanding of the underlying physiological processes.ResultsTo reveal the mechanisms related to erythromycin yield increase, we have undertaken an integrated study of the genomic, transcriptomic, and proteomic differences between the wild type strain NRRL2338 (WT) and the industrial high-producing strain ABE1441 (HP) of S. erythraea at multiple time points of a simulated industrial bioprocess. 165 observed mutations lead to differences in gene expression profiles and protein abundance between the two strains, which were most prominent in the initial stages of erythromycin production. Enzymes involved in erythromycin biosynthesis, metabolism of branched chain amino acids and proteolysis were most strongly upregulated in the HP strain. Interestingly, genes related to TCA cycle and DNA-repair were downregulated. Additionally, comprehensive data analysis uncovered significant correlations in expression profiles of the erythromycin-biosynthetic genes, other biosynthetic gene clusters and previously unidentified putative regulatory genes. Based on this information, we demonstrated that overexpression of several genes involved in amino acid metabolism can contribute to increased yield of erythromycin, confirming the validity of our systems biology approach.ConclusionsOur comprehensive omics approach, carried out in industrially relevant conditions, enabled the identification of key pathways affecting erythromycin yield and suggests strategies for rapid increase in the production of secondary metabolites in industrial environment.

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Igor Mozetič

Austrian Research Institute for Artificial Intelligence

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Nada Lavrač

University of Nova Gorica

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Ana Rotter

RWTH Aachen University

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