A proteomic investigation of Aspergillus carbonarius exposed to yeast volatilome or to its major component 2-phenylethanol reveals major shifts in fungal metabolism

The use of yeast-derived volatile organic compounds (VOCs) represents a promising strategy for the biological control of various plant pathogens, including mycotoxin-producing fungi. Previous studies demonstrated the efficacy of the low-fermenting yeast Candida intermedia isolate 253 in reducing growth, sporulation, and ochratoxin A biosynthesis by Aspergillus carbonarius MPVA566. This study aimed to investigate whether the inhibitory effect of the yeast volatilome is solely attributable to 2-phenylethanol, its major component, or if a synergistic effect of all volatilome components is required to achieve an effective control of the fungal growth and metabolism. Microbiological methods, HPLC measurements and a UPLC-MS/MS approach were used to investigate the metabolic profile of A. carbonarius MPVA566 at different growing conditions: standard incubation (control), exposed to C. intermedia 253 volatilome, and incubation in the presence of 2-phenylethanol. Both yeast volatilome and 2-phenylethanol succeeded in the macroscopic inhibition of the radial mycelial growth, along with a significant reduction of ochratoxin A production. Functional classification of the fungal proteome identified in the diverse growing conditions revealed a different impact of both yeast VOCs and 2-phenylethanol exposure on the fungal proteome. Yeast VOCs target an array of metabolic routes of fungal system biology, including a marked reduction in protein biosynthesis, proliferative activity, mitochondrial metabolism, and particularly in detoxification of toxic substances. Exposure to 2-phenylethanol only partially mimicked the metabolic effects observed by the whole yeast volatilome, with protein biosynthesis and proliferative activity being reduced when compared with the control samples, but still far from the VOCs-exposed condition. This study represents the first investigation on the effects of yeast-derived volatilome and 2-phenylethanol on the metabolism of a mycotoxigenic fungus by means of proteomics analysis. Chemical compounds studied or used in this article: 2-Phenylethanol (PubChem CID: 6054); ochratoxin-A (PubChem CID: 442530); sodium dodecyl sulfate (PubChem CID: 3423265); dithiothreitol (PubChem CID: 446094); phenylmethylsulfonyl fluoride (PubChem CID: 4784); iodoacetamide (PubChem CID: 3727); ammonium bicarbonate (PubChem CID: 14013); acetic acid (PubChem CID: 176); and acetonitrile (PubChem CID: 6342). - 2019 The AuthorsThis publication was made possible by NPRP grant # 8-392-4-003 from the Qatar National Research Fund (a member of Qatar Foundation). The findings achieved herein are solely the responsibility of the authors.Scopu

Parameter Identification for Laplace Equation and Approximation in Hardy Classes

We consider the inverse problem of identifying a Robin coefficient on some part of the boundary of a smooth 2D domain from overdetermined data available on the other part of the boundary, for Laplace equation in the domain. Using tools from complex analysis and analytic functions theory, we provide a constructive and convergent identification scheme for this inverse problem, together with numerical experiments

In-vitro application of a qatari burkholderia cepacia strain (QBC03) in the biocontrol of mycotoxigenic fungi and in the reduction of ochratoxin a biosynthesis by aspergillus carbonarius

Mycotoxins are secondary metabolites produced by certain filamentous fungi, causing human and animal health issues upon the ingestion of contaminated food and feed. Among the safest approaches to the control of mycotoxigenic fungi and mycotoxin detoxification is the application of microbial biocontrol agents. Burkholderia cepacia is known for producing metabolites active against a broad number of pathogenic fungi. In this study, the antifungal potential of a Qatari strain of Burkholderia cepacia (QBC03) was explored. QBC03 exhibited antifungal activity against a wide range of mycotoxigenic, as well as phytopathogenic, fungal genera and species. The QBC03 culture supernatant significantly inhibited the growth of Aspergillus carbonarius, Fusarium culmorum and Penicillium verrucosum in PDA medium, as well as A. carbonarius and P. verrucosum biomass in PDB medium. The QBC03 culture supernatant was found to dramatically reduce the synthesis of ochratoxin A (OTA) by A. carbonarius, in addition to inducing mycelia malformation. The antifungal activity of QBC03’s culture extract was retained following thermal treatment at 100 °C for 30 min. The findings of the present study advocate that QBC03 is a suitable biocontrol agent against toxigenic fungi, due to the inhibitory activity of its thermostable metabolites. View Full-TextFunding: Qatar National Research Fund (a member of Qatar Foundation) under National Priorities Research Program (NPRP) grant #NPRP8-392-4-003.Scopu

Breast cancer image classification using pattern-based Hyper Conceptual Sampling method

The increase in biomedical data has given rise to the need for developing data sampling techniques. With the emergence of big data and the rise of popularity of data science, sampling or reduction techniques have been assistive to significantly hasten the data analytics process. Intuitively, without sampling techniques, it would be difficult to efficiently extract useful patterns from a large dataset. However, by using sampling techniques, data analysis can effectively be performed on huge datasets, to produce a relatively small portion of data, which extracts the most representative objects from the original dataset. However, to reach effective conclusions and predictions, the samples should preserve the data behavior. In this paper, we propose a unique data sampling technique which exploits the notion of formal concept analysis. Machine learning experiments are performed on the resulting sample to evaluate quality, and the performance of our method is compared with another sampling technique proposed in the literature. The results demonstrate the effectiveness and competitiveness of the proposed approach in terms of sample size and quality, as determined by accuracy and the F1-measure. 2018This contribution was made possible by NPRP-07-794-1-145 grant from the Qatar National Research Fund (a member of Qatar foundation). The statements made herein are solely the responsibility of the authors.Scopu

The replacement of five consecutive amino acids in the cyt1a protein of bacillus thuringiensis enhances its cytotoxic activity against lung epithelial cancer cells

Cyt1A protein is a cytolytic protein encoded by the cyt gene of Bacillus thuringiensis subsp. israelensis (Bti) as part of the parasporal crystal proteins produced during the sporulation. Cyt1A protein is unique compared to the other endotoxins present in these parasporal crystals. Unlike ?-endotoxins, Cyt1A protein does not require receptors to bind to the target cell and activate the toxicity. It has the ability to affect a broad range of cell types and organisms, due to this characteristic. Cyt1A has been recognized to not only target the insect cells directly, but also recruit other endotoxins by acting as receptors. Due to these mode of actions, Cyt1A has been studied for its cytolytic activity against human cancer cell lines, although not extensively. In this study, we report a novel Cyt1A protein produced by a Bti strain QBT229 isolated from Qatar. When tested for its cytotoxicity against lung cancer cells, this local strain showed considerably higher activity compared to that of the reference Bti and other strains tested. The possible reasons for such enhanced activity were explored at the gene and protein levels. It was evidenced that five consecutive amino acid replacements in the ?8 sheet of the Cyt1A protein enhanced the cytotoxicity against the lung epithelial cancer cells. Such novel Cyt1A protein with high cytotoxicity against lung cancer cells has been characterized and reported through this study. -2018 by the authors. Licensee MDPI, Basel, Switzerland.Scopu

Investigation and Application of Bacillus licheniformis Volatile Compounds for the Biological Control of Toxigenic Aspergillus and Penicillium spp

The present study was designed to investigate the antagonistic activity of Bacillus licheniformis BL350-2 against mycotoxigenic strains of Aspergillus and Penicillium. In vitro coincubation for 5 days indicated Aspergillus westerdijkiae BA1 as the most sensitive strain, with a growth inhibition of 62%, followed by A. carbonarius MG7 (60%), Penicillium verrucosum MC12 (53%), A. niger MC05 (50%), A. flavus CM5 (49%), A. parasiticus SB01 (47%), and A. ochraceus MD1 (44%). Likewise, the majority of the tested strains on exposure to bacterial volatiles showed complete inhibition of mycotoxin synthesis. In vivo assays on maize ears resulted in 88% reduction in A. flavus CM5 growth and complete inhibition of fungal sporulation and aflatoxin accumulation. The GC-MS-based volatile profile showed 3-methyl-1-butanol as the most abundant compound. The findings of the present study advocate that B. licheniformis BL350-2 is suitable as a biocontrol agent against mycotoxigenic fungi, at least during storage of cereal grains. Copyright - 2019 American Chemical Society.This publication was made possible by NPRP grant # NPRP8- 392-4-003 from the Qatar National Research Fund (a member of Qatar Foundation). The statements made herein are solely the responsibility of the authors.Scopu

Using minimal generators for composite isolated point extraction and conceptual binary relation coverage: Application for extracting relevant textual features

In recent years, several mathematical concepts have been successfully explored in the computer science domain as a basis for finding original solutions for complex problems related to knowledge engineering, data mining, and information retrieval. Hence, relational algebra (RA) and formal concept analysis (FCA) may be considered as useful mathematical foundations that unify data and knowledge into information retrieval systems. For example, some elements in a fringe relation (related to the (RA) domain) called isolated points have been successfully used in FCA as formal concept labels or composite labels. Once associated with words in a textual document, these labels constitute relevant features of a text. This paper proposes the MinGenCoverage algorithm for covering a Formal Context (as a formal representation of a text) based on isolated labels and using these labels (or text features) for categorization, corpus structuring, and micro–macro browsing as an advanced information retrieval functionality. The main thrust of the approach introduced here relies heavily on the close connection between isolated points and minimal generators (MGs). MGs stand at the antipodes of the closures within their respective equivalence classes. By using the fact that the minimal generators are the smallest elements within an equivalence class, their detection and traversal is greatly eased and the coverage can be swiftly built. Extensive experiments provide empirical evidence for the performance of the proposed approach.NPRP Grant #06-1220-1-233 from the Qatar National Research Fund (a member of Qatar Foundation)