Bacterial Communities in the East African Coastal Waters of the Indian Ocean

ABSTRACT Presently, very sparse information exists about the occurrences and diversity of microbes in the western Indian Ocean (WIO) relative to other areas of the ocean. In this study, high‐throughput sequencing of 16S rRNA genes and metagenomic approaches were utilised to examine microbial assemblages in Kenya and Tanzania. Results from 24 locations showed that Proteobacterial members made up the majority of the bacterial assemblages. Other dominant phyla were Bacteroidetes (9%–10%), Firmicutes (1.4%–8%), Actinobacteria (4%–6%) and Acidobacter (3.4%–3.6%). Combinations of diversity (alpha and beta) as well as Pearson correlation analyses showed that assemblages in Kenya clustered together and differed from those in Tanzania because of covariation with various environmental factors, such as temperature and salinity.

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Publication Details

Journal
African Journal of Ecology
Published
2025-04-01
DOI
https://doi.org/10.1111/aje.70046
Citations
1
Primary Topic
Microbial Community Ecology and Physiology
Type
article
Field-Weighted Citation Impact
1.72
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article

Bacterial Communities in the East African Coastal Waters of the Indian Ocean

Ola A. Olapade
1 citations
African Journal of Ecology
Microbial Community Ecology and Physiology
1.72
article

Bacterial Communities in the East African Coastal Waters of the Indian Ocean

Ola A. Olapade
article en
1 citations

Abstract

ABSTRACT Presently, very sparse information exists about the occurrences and diversity of microbes in the western Indian Ocean (WIO) relative to other areas of the ocean. In this study, high‐throughput sequencing of 16S rRNA genes and metagenomic approaches were utilised to examine microbial assemblages in Kenya and Tanzania. Results from 24 locations showed that Proteobacterial members made up the majority of the bacterial assemblages. Other dominant phyla were Bacteroidetes (9%–10%), Firmicutes (1.4%–8%), Actinobacteria (4%–6%) and Acidobacter (3.4%–3.6%). Combinations of diversity (alpha and beta) as well as Pearson correlation analyses showed that assemblages in Kenya clustered together and differed from those in Tanzania because of covariation with various environmental factors, such as temperature and salinity.

African Journal of EcologyVol. 63(3)
Albion College (US)
Openalex Percentile: Top 18%
Microbial Community Ecology and Physiology
1.72
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