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Determination of biodiversity of Coprinus comatus using genotyping and metabolic profiling tools

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Pawlik A., Malinowska A., Siwulski M., Frąc M., Rogalski J., Janusz G.
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2015
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vol. 62
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issue 4
683-689
EN
Coprinus comatus strains (CCMs) originating from Poland were identified using ITS region sequencing. Based on the sequences obtained, the genetic relationship between the CCM strains was determined and a clear separation of all strains into two main clusters was obtained. The Coprinus strains were also genetically characterized for the first time by the AFLP technique. The analysis showed that the CCMs separated into four main clusters and a high complication of a UPGMA-based dendrogram was achieved. C. comatus strains included in the analysis displayed an AFLP profile similarity level in the range from 44 to 66%. The highest similarity coefficient, 0.490, was found between CCM12 and CCM13, and the lowest (0.202) between the CCM2 and CCM5 isolates. Biolog FF MicroPlates were applied to obtain data on utilization of 95 carbon sources and mycelial growth. The analysis allowed comparison of the functional diversity of the CCM strains and revealed a broad variability within the analyzed Coprinus species based on substrate utilization profiles. Significant differences (2-48) have been shown in the substrate richness values. The Biolog experiments proved to be a good profiling technology for studying the diversity in shaggy manes due to metabolic differences and demonstrated that all the strains might be considered individually. It is evident that the strain metabolic grouping does not correlate with the grouping based on the ITS sequences and AFLP profiles, however, some similarities may be observed.
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Bacterial species identification

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Kshikhundo R., Itumhelo S.
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The traditional methods of bacterial identification are based on observation of either the morphology of single cells or colony characteristics. However, the adoption of newer and automated methods offers advantage in terms of rapid and reliable identification of bacterial species. The review provides a comprehensive appreciation of new and improved technologies such fatty acid profiling, sequence analysis of the 16S rRNA gene, matrix-assisted laser desorption/ionization time-of-flight (MALDI-TOF), metabolic finger profiling using BIOLOG, ribotyping, together with the computational tools employed for querying the databases that are associated with these identification tools and high throughput genomic sequencing in bacterial identification. It is evident that with the increase in the adoption of new technologies, bacterial identification is becoming easier.
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