Bioprospection of Basidiomycetes and molecular phylogenetic analysis using internal transcribed spacer (ITS) and 5.8S rRNA gene sequence

Sundari, T Mowna; Anand, Asha; Jenifer, Packiaraj; Shenbagarathai, R.

doi:10.1038/s41598-018-29046-w

Cited by 18 publications

(13 citation statements)

References 54 publications

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“…In Tamilnadu, hundreds of macrofungi basidiocarps were found during the rainy season. Around that thirty of these strains were discovered using the internal transcribed spacer (ITS) and 5.8S rRNA gene sequence markers (29) that have been gathered from NCBI (National Center for Biotechnology Information. The sequences that were used for the research are listed below.…”

Section: Data Collectionmentioning

confidence: 99%

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Cluster Predictive Model Using Affinity Propagation Algorithm to Group Mushroom 5.8s rRNA Sequences

Sudhasini¹,

Ashadevi²

2022

IJST

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Background:The main emphasis of the article is biological information on a distinct species of mushroom (Phylum Basidiomycota) data collection of 5.8s rRNA sequences. Macrofungi from the phylum Basidiomycota are predominantly used as therapeutic mushrooms in several countries. During the rainy season, hundreds of macrofungal basidiocarps were discovered in Tamilnadu. The internal transcribed spacer (ITS) and 5.8S rRNA gene sequence markers, which have been collected from NCBI, were used to isolate at least thirty of these strains that fall under the Basidiomycota kingdom (suborders of Polyporales, Hymenochataeles, and Russuales), which have the therapeutic properties of the Basidiomycota kingdom. Objectives: This article's main objective is to organise the sequences according to similarity utilising multiple sequence alignment and an algorithmic perspective. Methods: In this paper, we use 30 × 30 pairwise similarity matrix data of these thirty 5.8s rRNA mushroom sequences obtained using the clustal omega tool to develop an affinity propagation approach. As a continuation of earlier work, this will be evaluated against k-means, hierarchical clustering based on the ideal cluster, and time and space complexity. Findings: The affinity propagation algorithm typically discourages providing the initial number of clusters; therefore, the optimal number of cluster values and grouping of clustered results obtained from the affinity propagation algorithm are also the same as the results obtained from the previous existing research work using the kmeans, hierarchical agglomerative clustering algorithm. Novelty: The overall suggested technique involves applying the cluster validation metrics Silhouette score, Calinski-Harabasz Index, and Davies-Bouldin Index methodologies to find the ideal number of clusters. The CD-hit Clustering tool does not offer these metrics, and the Cluster Omega tool does not support this kind of extension work. This follow-up work assists bioinformatics researchers in obtaining favourable results by utilising the existing software prior to working in wet laboratories; rather than wasting a lot of chemical resources, this result https://www.indjst.org/ 2129

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Section: Data Collectionmentioning

confidence: 99%

“…Mushroom 5.8s rRNA (under the division Basidiomycota) sequences Data Set collected from NCBI database(29) Identity…”

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confidence: 99%

Cluster Predictive Model Using Affinity Propagation Algorithm to Group Mushroom 5.8s rRNA Sequences

Sudhasini¹,

Ashadevi²

2022

IJST

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“…Ganodermataceae species (Polyporales) are medicinal mushrooms that have been used in traditional medicine in China and other Asian countries for approximately 2000 years. 12–14…”

Section: Introductionmentioning

confidence: 99%

Integrating in Silico and In Vitro Studies to Screen Anti-Staphylococcus aureus Activity From Vietnamese Ganoderma multiplicatum and Ganoderma sinense

Nguyen

et al. 2023

Natural Product Communications

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Background: Staphylococcus aureus is a nosocomial pathogen responsible for many serious infectious diseases in humans. Finding the anti- S. aureus agents is a time-consuming and costly process. Recently, computational methods have provided a better understanding of the interactions between herbal medicine drug targets to help clinical practitioners rationally design herbal formulae. Methods: In this study, molecular docking simulation was applied to screen a list of natural secondary metabolites from Ganoderma sp. on the protein target S. aureus sortase A. Molecular dynamics models were used to assess the stability of protein–ligand complexes during the first 100 ns. To validate the computational results, 2 Ganoderma species, G. multiplicatum VNKKK1901 and G. sinense VNKKK1902, were tested for antibacterial activity against S. aureus using the disk diffusion method. Results: The results showed that, among the selected compounds, ganosinensin B and ganosinoside A generated the highest binding energy on S. aureus sortase A, and demonstrated strong and stable binding capacity to proteins. In addition, the extracts of G. sinense VNKKK1902 and G. multiplicatum VNKKK1901 were bactericidal, with minimum bactericidal concentration (MBC)/minimum inhibitory concentration (MIC) ratios of 2. Conclusion: Our findings provide the first scientific report on the antibacterial activity of Ganoderma sp., which contain 2 promising compounds, ganosinensin B and ganosinoside A, as potential hits for developing novel drugs capable of supporting treatment of S. aureus infection.

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“…In forest ecosystems, biological diversity is caused by the vital activity of many organisms, including macromycetes [14,15,16]. They are widespread in nature and are a permanent component of biogeocenoses [17,18].…”

Section: Introductionmentioning

confidence: 99%

The Mycobiota Oak Forests of the Ural River Valley Within the West Kazakhstan Region

Abiev

SARSENOVA

Darbayeva

2022

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The study and conservation of biodiversity is one of the global problems of modern biology, since currently in many regions of the planet there is a decrease in the species composition of various organisms, including fungi. The obtained data make a significant contribution to the knowledge of the diversity of macromycetes of oak forests in the middle reaches of the Ural River, information about which is still insufficient and fragmented on the territory of Kazakhstan.The article presents data on the biodiversity of mycobiota of the oak forests of the Ural River valley, growing not only in the floodplain of the river, but also in beams, that is, the ravine forests flowing into the central floodplain. We have registered 31 species belonging to 23 genera, 17 families and five orders. The leading families are Polyporaceae, Boletaceae, Russulaceae, Amanitaceae. As a result of our research, it has been found that the mycological composition in ravine oak forests is richer than in floodplain oak forests. The richness of the species composition of macromycetes appears to have been influenced by well-defined associations in ravine oak forests (22 associations), represented by forest boreal tree-shrub species absent in floodplain oak forests, as well as favorable microclimatic conditions, relief, soil cover and various ecotopes that are not observed in floodplain oak forests (16 associations).Ecological-trophic analysis showed the predominance of mycorrhizal (45.1%) and xylotrophs (41.9%) over humus saprotrophs (12.9%). The considered taxonomic composition of macromycetes of the studied area is collected, identified and presented for the first time for this region.

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Bioprospection of Basidiomycetes and molecular phylogenetic analysis using internal transcribed spacer (ITS) and 5.8S rRNA gene sequence

Cited by 18 publications

References 54 publications

Cluster Predictive Model Using Affinity Propagation Algorithm to Group Mushroom 5.8s rRNA Sequences

Cluster Predictive Model Using Affinity Propagation Algorithm to Group Mushroom 5.8s rRNA Sequences

Integrating in Silico and In Vitro Studies to Screen Anti-Staphylococcus aureus Activity From Vietnamese Ganoderma multiplicatum and Ganoderma sinense

The Mycobiota Oak Forests of the Ural River Valley Within the West Kazakhstan Region

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