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Metagenomics Insights Into the Microbial Diversity and Microbiome Network Analysis on the Heterogeneity of Influent to Effluent Water

Sanitizing the water sources of local communities is important to control the spread of microbial resistance genes, especially those for water-borne illnesses. The activities of antibiotic resistance gene (ARG)-host pathogens pose a threat to public health, and it has been estimated that the infecti...

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Autores principales: Azli, Bahiyah, Razak, Mohd Nasharudin, Omar, Abdul Rahman, Mohd Zain, Nor Azimah, Abdul Razak, Fatimah, Nurulfiza, I.
Formato: Online Artículo Texto
Lenguaje:English
Publicado: Frontiers Media S.A. 2022
Materias:
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC9048743/
https://www.ncbi.nlm.nih.gov/pubmed/35495647
http://dx.doi.org/10.3389/fmicb.2022.779196
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author Azli, Bahiyah
Razak, Mohd Nasharudin
Omar, Abdul Rahman
Mohd Zain, Nor Azimah
Abdul Razak, Fatimah
Nurulfiza, I.
author_facet Azli, Bahiyah
Razak, Mohd Nasharudin
Omar, Abdul Rahman
Mohd Zain, Nor Azimah
Abdul Razak, Fatimah
Nurulfiza, I.
author_sort Azli, Bahiyah
collection PubMed
description Sanitizing the water sources of local communities is important to control the spread of microbial resistance genes, especially those for water-borne illnesses. The activities of antibiotic resistance gene (ARG)-host pathogens pose a threat to public health, and it has been estimated that the infection will lead up to 10 million deaths globally by the year 2050. Hence, in this study, we aim to analyze the efficiency of our municipal wastewater treatment plant (WWTP) process in producing pathogen-free water by investigating the microbial composition between influent and effluent water sites. Shotgun metagenomics sequencing using the Illumina platform was performed on the influent and effluent samples of six different WWTP sites located in Johore, Malaysia. After raw data pre-processing, the non-redundant contigs library was then aligned against BLASTP for taxonomy profiling and the Comprehensive Antibiotic Resistance Database for ARG annotation. Interestingly, the alpha-diversity result reported that effluent site samples showed higher abundance and diverse heterogeneity compared to the influent site. The principal component analysis (PCA) and non-metric multidimensional scaling (NMDS) plots also suggested that effluent sites showed high variation in the genetic material due to loosely clustered sample plots, as compared to the tightly clustered influent samples. This study has successfully identified the top three abundant phyla in influent—Proteobacteria, Firmicutes, and Bacteroidetes—and effluent—Proteobacteria, Actinobacteria, and Bacteroidetes—water. Despite the overlap within the top three abundant phyla in influent and effluent sites (Proteobacteria and Bacteroidetes), the ARG composition heat map and drug class phenotype plot bar exhibits a general trend of a downward shift, showing the efficiency of WWTP in reducing opportunistic pathogens. Overall, it was demonstrated that our municipal WWTP efficiently eliminated pathogenic microbes from the influent water before its total discharge to the environment, though not with the total elimination of microorganisms. This metagenomics study allowed for an examination of our water source and showed the potential interaction of species and ARGs residing in the influent and effluent environment. Both microbial profile structure and co-occurrence network analysis provide integrated understanding regarding the diversity of microorganisms and interactions for future advanced water sanitation treatments.
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spelling pubmed-90487432022-04-29 Metagenomics Insights Into the Microbial Diversity and Microbiome Network Analysis on the Heterogeneity of Influent to Effluent Water Azli, Bahiyah Razak, Mohd Nasharudin Omar, Abdul Rahman Mohd Zain, Nor Azimah Abdul Razak, Fatimah Nurulfiza, I. Front Microbiol Microbiology Sanitizing the water sources of local communities is important to control the spread of microbial resistance genes, especially those for water-borne illnesses. The activities of antibiotic resistance gene (ARG)-host pathogens pose a threat to public health, and it has been estimated that the infection will lead up to 10 million deaths globally by the year 2050. Hence, in this study, we aim to analyze the efficiency of our municipal wastewater treatment plant (WWTP) process in producing pathogen-free water by investigating the microbial composition between influent and effluent water sites. Shotgun metagenomics sequencing using the Illumina platform was performed on the influent and effluent samples of six different WWTP sites located in Johore, Malaysia. After raw data pre-processing, the non-redundant contigs library was then aligned against BLASTP for taxonomy profiling and the Comprehensive Antibiotic Resistance Database for ARG annotation. Interestingly, the alpha-diversity result reported that effluent site samples showed higher abundance and diverse heterogeneity compared to the influent site. The principal component analysis (PCA) and non-metric multidimensional scaling (NMDS) plots also suggested that effluent sites showed high variation in the genetic material due to loosely clustered sample plots, as compared to the tightly clustered influent samples. This study has successfully identified the top three abundant phyla in influent—Proteobacteria, Firmicutes, and Bacteroidetes—and effluent—Proteobacteria, Actinobacteria, and Bacteroidetes—water. Despite the overlap within the top three abundant phyla in influent and effluent sites (Proteobacteria and Bacteroidetes), the ARG composition heat map and drug class phenotype plot bar exhibits a general trend of a downward shift, showing the efficiency of WWTP in reducing opportunistic pathogens. Overall, it was demonstrated that our municipal WWTP efficiently eliminated pathogenic microbes from the influent water before its total discharge to the environment, though not with the total elimination of microorganisms. This metagenomics study allowed for an examination of our water source and showed the potential interaction of species and ARGs residing in the influent and effluent environment. Both microbial profile structure and co-occurrence network analysis provide integrated understanding regarding the diversity of microorganisms and interactions for future advanced water sanitation treatments. Frontiers Media S.A. 2022-04-14 /pmc/articles/PMC9048743/ /pubmed/35495647 http://dx.doi.org/10.3389/fmicb.2022.779196 Text en Copyright © 2022 Azli, Razak, Omar, Mohd Zain, Abdul Razak and Nurulfiza. https://creativecommons.org/licenses/by/4.0/This is an open-access article distributed under the terms of the Creative Commons Attribution License (CC BY). The use, distribution or reproduction in other forums is permitted, provided the original author(s) and the copyright owner(s) are credited and that the original publication in this journal is cited, in accordance with accepted academic practice. No use, distribution or reproduction is permitted which does not comply with these terms.
spellingShingle Microbiology
Azli, Bahiyah
Razak, Mohd Nasharudin
Omar, Abdul Rahman
Mohd Zain, Nor Azimah
Abdul Razak, Fatimah
Nurulfiza, I.
Metagenomics Insights Into the Microbial Diversity and Microbiome Network Analysis on the Heterogeneity of Influent to Effluent Water
title Metagenomics Insights Into the Microbial Diversity and Microbiome Network Analysis on the Heterogeneity of Influent to Effluent Water
title_full Metagenomics Insights Into the Microbial Diversity and Microbiome Network Analysis on the Heterogeneity of Influent to Effluent Water
title_fullStr Metagenomics Insights Into the Microbial Diversity and Microbiome Network Analysis on the Heterogeneity of Influent to Effluent Water
title_full_unstemmed Metagenomics Insights Into the Microbial Diversity and Microbiome Network Analysis on the Heterogeneity of Influent to Effluent Water
title_short Metagenomics Insights Into the Microbial Diversity and Microbiome Network Analysis on the Heterogeneity of Influent to Effluent Water
title_sort metagenomics insights into the microbial diversity and microbiome network analysis on the heterogeneity of influent to effluent water
topic Microbiology
url https://www.ncbi.nlm.nih.gov/pmc/articles/PMC9048743/
https://www.ncbi.nlm.nih.gov/pubmed/35495647
http://dx.doi.org/10.3389/fmicb.2022.779196
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