Application of polyphasic approach for identification of epiphytic fungi isolated from wheat grains
In this study, epiphytic fungi were isolated from wheat seeds (Triticum aestivum L) and a polyphasic approach for their identification was applied. The initial morphological characterisation was done on selected twenty-tree strains and continued with their identification based on the carbon utilisat...
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          | Published in | Agricultural Sciences Vol. 15; no. 36; pp. 83 - 94 | 
|---|---|
| Main Authors | , , | 
| Format | Journal Article | 
| Language | English | 
| Published | 
          
        27.04.2023
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| Online Access | Get full text | 
| ISSN | 1313-6577 2367-5772 2367-5772  | 
| DOI | 10.22620/agrisci.2023.36.008 | 
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| Abstract | In this study, epiphytic fungi were isolated from wheat seeds (Triticum aestivum L) and a polyphasic approach for their identification was applied. The initial morphological characterisation was done on selected twenty-tree strains and continued with their identification based on the carbon utilisation pattern according to the Biolog OmniLog system protocol (Hayward, CA, USA). Throughout the isolated strains, the Biolog data indicated predominance of the genera Aspergillus, Penicillium and Fusarium. The carbon utilisation pattern of five strains assigned them to several different from aforementioned genera and due to their scarcity they were not included in the current study. The indicated by the Biolog genus designation of the strains was used as a guideline for the further molecular identification of seventeen strains from the predominant genera. Molecular identification was based on a polymerase chain reaction (PCR) with universal primers, which targeted the internal transcribed spacer (ITS) region of rDNA gene. The PCR fragments were sequenced and after applying a BLAST algorithm, a high percentage of similarity was found for eleven strains. At the species level, the Biolog and molecular technique showed a discrepancy in the identification of two strains. The procedure of identification was unsuccessful for six strains either due to insufficient quantity of the PCR product or the lack of sufficient similarity of the fragments to the GenBank database. Current study showed that the unbiased identification of epiphytic fungi requires a polyphasic approach, which applies morphological, physiological and molecular techniques. | 
    
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| AbstractList | In this study, epiphytic fungi were isolated from wheat seeds (Triticum aestivum L) and a polyphasic approach for their identification was applied. The initial morphological characterisation was done on selected twenty-tree strains and continued with their identification based on the carbon utilisation pattern according to the Biolog OmniLog system protocol (Hayward, CA, USA). Throughout the isolated strains, the Biolog data indicated predominance of the genera Aspergillus, Penicillium and Fusarium. The carbon utilisation pattern of five strains assigned them to several different from aforementioned genera and due to their scarcity they were not included in the current study. The indicated by the Biolog genus designation of the strains was used as a guideline for the further molecular identification of seventeen strains from the predominant genera. Molecular identification was based on a polymerase chain reaction (PCR) with universal primers, which targeted the internal transcribed spacer (ITS) region of rDNA gene. The PCR fragments were sequenced and after applying a BLAST algorithm, a high percentage of similarity was found for eleven strains. At the species level, the Biolog and molecular technique showed a discrepancy in the identification of two strains. The procedure of identification was unsuccessful for six strains either due to insufficient quantity of the PCR product or the lack of sufficient similarity of the fragments to the GenBank database. Current study showed that the unbiased identification of epiphytic fungi requires a polyphasic approach, which applies morphological, physiological and molecular techniques. | 
    
| Author | Kartalska, Yordanka Dimitrova, Katya Emin, Nevin  | 
    
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