Functional Prediction of Biological Profile During Eutrophication in Marine Environment

Sbaoui, Yousra; Nouadi, Badreddine; Ezaouine, Abdelkarim; Salam, Mohamed Rida; Elmessal, Mariame; Bennis, Faïza; Chegdani, Fatima

doi:10.1177/11779322211063993

Cited by 1 publication

(2 citation statements)

References 75 publications

(115 reference statements)

Supporting

Mentioning

Contrasting

Order By: Relevance

“…Furthermore, the PCoA plot indicated a significant difference in beta diversity between the two coasts and the four CT studied (p < 0.05). This is in agreement with several studies that have reported vertical stratification of microbial taxa and viruses based on physicochemical changes, such as light, temperature, and nutrients [14,[23][24][25]. Considering the vertical and horizontal stratification, we characterized the taxonomic and functional richness, dissimilarity between samples (β-diversity), total cell abundance, and potential growth rates in the four CT studied.…”

Section: Discussionsupporting

confidence: 89%

“…Prediction of microbial community functions were evaluated using the R package "Tax4Fun (version: 3.10, tax4fun software, http://tax4fun.gobics.de/). The functions of the 16S rRNA marker genes were linked to orthologs (KOs) in the Kyoto Encyclopedia of Genes and Genomes (KEGG) SILVA database using the MoP-Pro approach [13,14], to determine the relative abundance of the predictive function genes for each MMM sample. The top 11 KO were then selected and plotted on bar graphs to associate relative gene abundance to CT and WS.…”

Section: Functional Profilingmentioning

confidence: 99%

See 1 more Smart Citation

Effect of Climate on Bacterial and Archaeal Diversity of Moroccan Marine Microbiota

et al. 2022

Self Cite

View full text Add to dashboard Cite

The Moroccan coast is characterized by a diversity of climate, reflecting a great richness and diversity of fauna and flora. By this, marine microbiota plays a fundamental role in many biogeochemical processes, environmental modifications, and responses to temperature changes. To date, no exploration by high-throughput techniques has been carried out on the characterization of the Moroccan marine microbiota. The objective of this work is to study the diversity and metabolic functions of MMM from the Moroccan coast (Atlantic and Mediterranean) according to the water source (WS) and the type of climate (CT) using the approach high-throughput sequencing of the 16SrRNA gene. Four water samples of twelve sampling sites from the four major climates along the Moroccan coastline were collected, and prokaryotic DNA was extracted. V4 region of 16S rRNA gene was amplified, and the product PCR was sequenced by Illumina Miseq. The β-diversity and α-diversity indices were determined to assess the species richness and evenness. The obtained results were analyzed by Mothur and R software. A total of twenty-eight Bacterial phyla and twelve Archaea were identified from the samples. Proteobacteria, Bacteroidetes, and Cyanobacteria are the three key bacterial phyla, and the Archaeal phyla identified are: Euryarchaeota, Nanoarchaeaeota, Crenarchaeota, Hydrothermarchaeota, Asgardaeota, Diapherotrites, and Thaumarchaeota in the Moroccan coastline and the four climates studied. The whole phylum are involved in marine biogeochemical cycles, and through their functions they participate in the homeostasis of the ocean in the presence of pollutants or stressful biotic and abiotic factors. In conclusion, the obtained results reported sufficient deepness of sequencing to cover the majority of Archaeal and Bacterial genera in each site. We noticed a strong difference in microbiota diversity, abundance, and taxonomy inter- and intra-climates and water source without significant differences in function. To better explore this diversity, other omic approaches can be applied such as the metagenomic shotgun, and transcriptomic approaches allowing a better characterization of the Moroccan marine microbiota and to understand the mechanisms of its adaptation and its impacts in/on the ecosystem.

show abstract

Section: Discussionsupporting

confidence: 89%

Section: Functional Profilingmentioning

confidence: 99%