Inferences of gut bacterial diversity from next-generation sequencing of 16S rDNA in deep sea blind ray - Benthobatis moresbyi

Abstract. Geraldi A, Tay CC, Ni’matuzahroh, Fatimah, Hanafi WNW. 2021. Unraveling the bacterial diversity of Cangar Hot Spring, Indonesia by Next Generation Sequencing of 16S rRNA gene. Biodiversitas 22: 4060-4066. This study is the first attempt at using the Next Generation Sequencing (NGS) method with 16S rRNA to understand the bacterial community structure in an Indonesian hot spring. This study aims to unravel the bacterial diversity of the Cangar Hot Spring as one of the most explored natural hot springs in East Java, Indonesia. We found Proteobacteria and Bacteroidetes as the two most abundant phyla. We discovered the first occurrence of genera Cloacibacterium and Methylobacillus in the hot spring ecosystem, which was the most dominant genera at Cangar Hot Spring. We also found several potential bacteria for bioindustry and bioremediation, such as Acinetobacter junii and Pseudomonas alcaligenes. Besides that, we also observed opportunistic pathogens from genera Comamonas and Vogesella. This study result will provide valuable information for further bioprospecting of bacteria with commercial potential and the development of health and safety measures in the Cangar Hot Spring, among others. Hopefully, this report would encourage the use of NGS technology for studying other hot springs in Indonesia.

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Spatial Modelling of Bacterial Diversity over the Selected Regions in Bangladesh by Next-Generation Sequencing: Role of Water Temperature

Applied Sciences ◽

10.3390/app10072537 ◽

2020 ◽

Vol 10 (7) ◽

pp. 2537

Author(s):

Nabila Akter ◽

Md Wahiduzzaman ◽

Alea Yeasmin ◽

Kazi Saiful Islam ◽

Jing-Jia Luo

Keyword(s):

Next Generation Sequencing ◽

Water Temperature ◽

Bacterial Diversity ◽

Bay Of Bengal ◽

Spatial Model ◽

Spatial Modelling ◽

Next Generation ◽

Chain Reactions ◽

Generation Sequencing

In this study, a spatial model has been developed to investigate the role of water temperature to the distribution of bacteria over the selected regions in the Bay of Bengal, located in the southern region of Bangladesh using next-generation sequencing. Bacterial concentration, quantitative polymerase chain reactions, and sequencing were performed on water samples and identified Acidobacteria, Actinobacteria, Bacteroidetes, Chlorobi, Chloroflexi, Cyanobacteria, Firmicutes, Nitrospirae, Planctomycetes, Proteobacteria, and Verrucomicrobia. The spatial model tessellated the parts of the Bay of Bengal with hexagons and analyzed the relationship between the distribution of bacteria and water temperature. A geographically weighted regression was used to observe whether water temperature contributed strongly or weakly to the distribution of bacteria. The residuals were examined to assess the model’s fitness. The spatial model has the potential to predict the bacterial diversity in the selected regions of Bangladesh.

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