scholarly journals Optimization of Medium Components for the Production of Antagonistic Lytic Enzymes Against Phytopathogenic Fungi and Their Biocontrol Potential

2014 ◽  
Vol 47 (4) ◽  
pp. 299-305
Author(s):  
Yong Seong Lee ◽  
Saophuong Neung ◽  
Yun Suk Park ◽  
Kil Yong Kim
Keyword(s):  
Phytopathogenic Fungi ◽  
Lytic Enzymes ◽  
Medium Components ◽  
Biocontrol Potential

scholarly journals THE COMPOST, A SOURCE OF PLANT BENEFICIAL BACTERIA WITH BIOCONTROL POTENTIAL

2021 ◽  
Vol 10 (20) ◽  
pp. 32-38
Author(s):  
Oana-Alina Boiu-Sicuia ◽  
Vasilica Stan ◽  
Călina Petruța Cornea
Keyword(s):  
Plant Protection ◽  
Bacterial Load ◽  
Pathogenic Fungi ◽  
Phytopathogenic Fungi ◽  
Microbial Load ◽  
Bacterial Strains ◽  
Beneficial Bacteria ◽  
Lytic Enzymes ◽  
Common Activity ◽  
Biocontrol Potential

Recycling the sewage sludge from treatment plants is a common activity. The resulting compost is usually rich in plant nutrients and beneficial microorganisms. However, compost properties greatly differ depending on the nature of the fermented biomass and fermentation processes. The aim of this study was to analyze the microbial load of three different composts, in order to detect new bacterial strains with plant protection properties. Isolated bacteria were microbiologically characterized and evaluated for their potential to reduce soil-borne phytopathogenic fungi. Results showed a microbial load of approximately 106 CFU/g of compost. In the analyzed samples it was revealed that as bacterial load increases, the fungal amount decreases. Analyzing some newly isolated bacteria obtained from these composts, a good biocontrol potential against soil-borne pathogenic fungi was revealed. Some of the isolated bacterial strains revealed antifungal activity against Rhizoctonia solani and Sclerotinia sclerotiorum. These bacteria showed good colonization capacity and lytic enzymes production, correlated to antimicrobial activity. These compost-originated bacteria reveal high potential in pathogens inhibition. Therefore, the analyzed composts are recommended not only as soil fertility improvers, but also as potential suppressors of soil-borne pathogens. Results revealed these composts as source of plant beneficial bacteria with biological control potential.

scholarly journals Mycoparasitic antagonism of a Trichoderma harzianum strain isolated from banana plants in Oaxaca, Mexico

Biotecnia ◽  
2021 ◽  
Vol 23 (1) ◽  
pp. 127-134
Author(s):  
Ana Claudia Sánchez-Espinosa ◽  
José Luis Villarruel-Ordaz ◽  
Luis David Maldonado Bonilla
Keyword(s):  
Biological Control ◽  
Developing Countries ◽  
Trichoderma Harzianum ◽  
Phytopathogenic Fungi ◽  
The Novel ◽  
Panama Disease ◽  
Banana Production ◽  
Biocontrol Potential ◽  
Identification And Characterization

Bananas are important crops in developing countries with tropical climate. In Mexico, the banana production has increased, and it must be guaranteed. The Panama disease, caused by the fungus Fusarium oxysporum f.sp. cubense threatens the current banana production, for what is necessary to implement methods to protect this crop. Fungi from genus Trichoderma are natural residents of the rhizosphere. This genus comprises mycoparasite species used to control diseases caused by phytopathogenic fungi, and also benefit plant development. In this report, we present data of the identification and characterization of the novel strain Trichoderma harzianum M110 that displays antagonism and biocontrol potential in laboratory conditions. Exploration of the rhizosphere and the endophytic microbial communities might help to identify microbes adapted to banana plants that can be incorporated in organic biological control formulations that ensure production of Fusarium-free plants and healthy fruits with export quality.

scholarly journals Chitinolytic Bacillus subtilis Ege-B-1.19 as a biocontrol agent against mycotoxigenic and phytopathogenic fungi

2018 ◽  
Vol 44 (3) ◽  
pp. 323-331
Author(s):  
Ozlem Oztopuz ◽  
Nermin Sarigul ◽  
Fakhra Liaqat ◽  
Ro-Dong Park ◽  
Rengin Eltem
Keyword(s):  
Molecular Weight ◽  
Bacillus Subtilis ◽  
Biocontrol Agent ◽  
Pathogenic Fungi ◽  
Phytopathogenic Fungi ◽  
Aspergillus Ochraceus ◽  
Lytic Enzyme ◽  
Rrna Gene ◽  
Lytic Enzymes ◽  
16S Rrna Gene Analysis

Abstract Background Biological control of pathogenic fungi is a possible alternate to the chemical control, which is harmful to humans and environment. Soil-borne Bacillus strains can be potential biocontrol agents and a source of lytic enzymes. Aim This study aimed to examine biocontrol potential and lytic enzyme activities of a soil isolate Bacillus subtilis Ege-B-1.19. Materials and methods Strain was identified by biochemical and 16S rRNA gene analysis and its biocontrol activity was investigated against Aspergillus niger EGE-K-213, Aspergillus foetidus EGE-K-211, Aspergillus ochraceus EGE-K-217, Fusarium solani KCTC6328, Rhizoctonia solani KACC40111 and Colletotrichum gloeosporioides KACC40689. Chitinase, chitosanase, N-acetyl-β-hexosaminidase and protease activities of B. subtilis Ege-B-1.19 were also determined. Chitosanase was purified using Sephadex G-150 column and its molecular weight was determined by SDS-PAGE. Chitooligosaccharides production using chitosanase was carried out and analysed by TLC and HPLC. Results Results depicted that B. subtilis Ege-B-1.19 has shown inhibitory effects against all the test fungi. Chitinase, chitosanase, N-acetyl-β-hexosaminidase and protease activities were determined as 2.7 U mL−1, 7.2 U mL−1, 6.2 U mL−1 and 12.2 U mL−1, respectively. Molecular weight of purified chitosanase was 44 kDa. Chitosanase hydrolysed chitosan to glucosamine (GlcN), dimers (GlcN)2 and trimers (GlcN)3. Conclusion Bacillus subtilis Ege-B-1.19 can be anticipated as useful biocontrol agent and its chitosanase can be utilized for enzymatic synthesis of chitooligosaccharides.

scholarly journals Transcriptional Reprogramming of the Mycoparasitic Fungus Ampelomyces quisqualis During the Powdery Mildew Host-Induced Germination

2015 ◽  
Vol 105 (2) ◽  
pp. 199-209 ◽  
Author(s):  
Stefanos Siozios ◽  
Lorenzo Tosi ◽  
Alberto Ferrarini ◽  
Alessandro Ferrari ◽  
Paola Tononi ◽  
...  
Keyword(s):  
Powdery Mildew ◽  
Phytopathogenic Fungi ◽  
Diverse Range ◽  
Transcriptional Reprogramming ◽  
Ampelomyces Quisqualis ◽  
Genome Wide ◽  
Mycoparasitic Fungus ◽  
Biocontrol Potential ◽  
Related Proteins ◽  
Upregulated Genes

Ampelomyces quisqualis is a mycoparasite of a diverse range of phytopathogenic fungi associated with the powdery mildew disease. Among them are several Erysiphaceae species with great economic impact on high-value crops such as grape. Due to its ability to parasitize and prevent the spread of powdery mildews, A. quisqualis has received considerable attention for its biocontrol potential. However, and in sharp contrast to the extensively studied biocontrol species belonging to the genus Trichoderma, little is known about the biology of A. quisqualis at the molecular and genetic levels. We present the first genome-wide transcription profiling in A. quisqualis during host-induced germination. A total of 1,536 putative genes showed significant changes in transcription during the germination of A. quisqualis. This finding denotes an extensive transcriptional reprogramming of A. quisqualis induced by the presence of the host. Several upregulated genes were predicted to encode for putative mycoparasitism-related proteins such as secreted proteases, virulence factors, and proteins related to toxin biosynthesis. Our data provide the most comprehensive sequence resource currently available for A. quisqualis in addition to offering valuable insights into the biology of A. quisqualis and its mycoparasitic lifestyle. Eventually, this may improve the biocontrol capacity of this mycoparasite.

scholarly journals Lytic Enzymes of Aspergillus piperis as a Tool for Attacking Some Phytopathogenic Fungi In vitro with Special Reference to its Cytotoxicity

2021 ◽  
Author(s):  
Samah Abd El-Kader El-Debaiky ◽  
Anwer S.M. El-Badry
Keyword(s):  
Cell Line ◽  
Biological Control Agent ◽  
Control Agent ◽  
Phytopathogenic Fungi ◽  
Antagonistic Activity ◽  
Lytic Enzyme ◽  
Lytic Enzymes ◽  
Wi38 Cell ◽  
Ic50 Values

The antagonistic activity of Aspergillus piperis against Fusarium oxysporum f. sp. fabae (FOF) and Sclerotinia sclerotiorum were examined and showed multiple signs of hyphal interactions. Microscopic examination of contact regions among A. piperis and each pathogen revealed distinct enzymatic lysis of pathogenic hyphal cell walls. Therefore, it is important to estimate the lytic enzyme activity of A. piperis. Extracellular lytic enzymes are important offensive forces for A. piperis as a biological control agent. Chitinase, phospholipase, and protease recorded relatively high activity from a culture age of 10 days (82.3, 42.4, and 6.2 U/ml, respectively). Enzymatic persistence was measured at room temperature, recording relatively long periods, saving 54%, 46%, and 21% of their activity, respectively. The cytotoxicity of the crude culture filtrate of A. piperis was examined in MCF7 and WI38 human cell lines. The cell viability (IC50) value of the fungal filtrate was estimated after 24 h and 48 h. The results revealed that IC50 values against the MCF7 cell line were inoperative after 24 h and were recorded 80 μg/ml after 48 h. In contrast, IC50 values against the WI38 cell line were 85.69 and 69.8 μg/ml after 24 and 48 h, respectively.

A Computational Method for the Identification of Endolysins and Autolysins

2020 ◽  
Vol 27 (4) ◽  
pp. 329-336 ◽  
Author(s):  
Lei Xu ◽  
Guangmin Liang ◽  
Baowen Chen ◽  
Xu Tan ◽  
Huaikun Xiang ◽  
...  
Keyword(s):  
Support Vector Machine ◽  
Cell Wall ◽  
Experimental Results ◽  
Computational Method ◽  
Lytic Enzyme ◽  
Support Vector ◽  
Lytic Enzymes ◽  
Data Set ◽  
Optimal Feature ◽  
Better Than

Background: Cell lytic enzyme is a kind of highly evolved protein, which can destroy the cell structure and kill the bacteria. Compared with antibiotics, cell lytic enzyme will not cause serious problem of drug resistance of pathogenic bacteria. Thus, the study of cell wall lytic enzymes aims at finding an efficient way for curing bacteria infectious. Compared with using antibiotics, the problem of drug resistance becomes more serious. Therefore, it is a good choice for curing bacterial infections by using cell lytic enzymes. Cell lytic enzyme includes endolysin and autolysin and the difference between them is the purpose of the break of cell wall. The identification of the type of cell lytic enzymes is meaningful for the study of cell wall enzymes. Objective: In this article, our motivation is to predict the type of cell lytic enzyme. Cell lytic enzyme is helpful for killing bacteria, so it is meaningful for study the type of cell lytic enzyme. However, it is time consuming to detect the type of cell lytic enzyme by experimental methods. Thus, an efficient computational method for the type of cell lytic enzyme prediction is proposed in our work. Method: We propose a computational method for the prediction of endolysin and autolysin. First, a data set containing 27 endolysins and 41 autolysins is built. Then the protein is represented by tripeptides composition. The features are selected with larger confidence degree. At last, the classifier is trained by the labeled vectors based on support vector machine. The learned classifier is used to predict the type of cell lytic enzyme. Results: Following the proposed method, the experimental results show that the overall accuracy can attain 97.06%, when 44 features are selected. Compared with Ding's method, our method improves the overall accuracy by nearly 4.5% ((97.06-92.9)/92.9%). The performance of our proposed method is stable, when the selected feature number is from 40 to 70. The overall accuracy of tripeptides optimal feature set is 94.12%, and the overall accuracy of Chou's amphiphilic PseAAC method is 76.2%. The experimental results also demonstrate that the overall accuracy is improved by nearly 18% when using the tripeptides optimal feature set. Conclusion: The paper proposed an efficient method for identifying endolysin and autolysin. In this paper, support vector machine is used to predict the type of cell lytic enzyme. The experimental results show that the overall accuracy of the proposed method is 94.12%, which is better than some existing methods. In conclusion, the selected 44 features can improve the overall accuracy for identification of the type of cell lytic enzyme. Support vector machine performs better than other classifiers when using the selected feature set on the benchmark data set.

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