Applied Science Private University

Volume Volume 18, 2024 · Issue 1 · Open Access · Double-blind Peer-review

Hypothesis

Molecular diagnosis using metagenomic technology on wastewater from the Danville Valley in the city of Mosul, Iraq

1 Department of Environmental Sciences, College of Environmental Sciences, University of Mosul, Mosul, Iraq.

2 Department of Biology, College of Science, University of Mosul, Mosul, Iraq.

* Corresponding author: Ramadhan A. M. Al-Hadedi ([email protected])

Published: 30 Dec 2024

Abstract

Background: The wastewater of the Danville Valley is one of the most polluted valleys in the city, as it consists of sewage and industrial wastewater, in addition to excreta from fodder residues and animal waste, along with rainwater and agricultural waste.

Objective: This study aims to perform molecular diagnosis of Danville Valley waste to determine the types of bacteria present in sewage wastewater in the city of Mosul.

Methods: The PCR results were sent to Zymo Research Europe in Freiburg, Germany, in order to analyze the entire genetic material in the sample using metagenomic technology. Special primers were used to amplify the (V3-V4) region of the complete 16S rRNA gene.

Results: The analysis of the wastewater sample from the study area revealed varying percentages of bacterial levels. The phylum (Proteobacteria) was the dominant bacterial phylum in the wastewater at a rate of 82.9%. The class (Epsilonproteobacteria) and the order (Campylobacterales) both recorded rates of 42.7%, while the family (Campylobacteraceae) recorded a rate of 41.1%. The dominant bacterial genus was (Arcobacter) at 39.9%.

Conclusion: The phylum (Proteobacteria) is the dominant bacterial phylum in the wastewater of the study area at a rate of 82.9%. The class (Epsilonproteobacteria) recorded a rate of 42.7%, the order (Campylobacterales) at 42.7%, and the family (Campylobacteraceae) at 41.1%. The dominant bacterial genus was (Arcobacter) at 39.9%.

KeywordsWater pollutionDanfeli ValleyTigris Rivermetagenomicsmolecular diagnosis

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