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Mapping human pathogens in wastewater using a metatranscriptomic approach
The monitoring of cities’ wastewaters for the detection of potentially pathogenic viruses and bacteria has been considered a priority during the COVID-19 pandemic to monitor public health in urban environments. The methodological approaches frequently used for this purpose include deoxyribonucleic a...
Autores principales: | , , , , , , , , |
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Formato: | Online Artículo Texto |
Lenguaje: | English |
Publicado: |
The Authors. Published by Elsevier Inc.
2023
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Materias: | |
Acceso en línea: | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC10172761/ https://www.ncbi.nlm.nih.gov/pubmed/37150387 http://dx.doi.org/10.1016/j.envres.2023.116040 |
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author | Carneiro, João Pascoal, Francisco Semedo, Miguel Pratas, Diogo Tomasino, Maria Paola Rego, Adriana Carvalho, Maria de Fátima Mucha, Ana Paula Magalhães, Catarina |
author_facet | Carneiro, João Pascoal, Francisco Semedo, Miguel Pratas, Diogo Tomasino, Maria Paola Rego, Adriana Carvalho, Maria de Fátima Mucha, Ana Paula Magalhães, Catarina |
author_sort | Carneiro, João |
collection | PubMed |
description | The monitoring of cities’ wastewaters for the detection of potentially pathogenic viruses and bacteria has been considered a priority during the COVID-19 pandemic to monitor public health in urban environments. The methodological approaches frequently used for this purpose include deoxyribonucleic acid (DNA)/Ribonucleic acid (RNA) isolation followed by quantitative polymerase chain reaction (qPCR) and reverse transcription (RT)‒qPCR targeting pathogenic genes. More recently, the application of metatranscriptomic has opened opportunities to develop broad pathogenic monitoring workflows covering the entire pathogenic community within the sample. Nevertheless, the high amount of data generated in the process requires an appropriate analysis to detect the pathogenic community from the entire dataset. Here, an implementation of a bioinformatic workflow was developed to produce a map of the detected pathogenic bacteria and viruses in wastewater samples by analysing metatranscriptomic data. The main objectives of this work was the development of a computational methodology that can accurately detect both human pathogenic virus and bacteria in wastewater samples. This workflow can be easily reproducible with open-source software and uses efficient computational resources. The results showed that the used algorithms can predict potential human pathogens presence in the tested samples and that active forms of both bacteria and virus can be identified. By comparing the computational method implemented in this study to other state-of-the-art workflows, the implementation analysis was faster, while providing higher accuracy and sensitivity. Considering these results, the processes and methods to monitor wastewater for potential human pathogens can become faster and more accurate. The proposed workflow is available at https://github.com/waterpt/watermonitor and can be implemented in currently wastewater monitoring programs to ascertain the presence of potential human pathogenic species. |
format | Online Article Text |
id | pubmed-10172761 |
institution | National Center for Biotechnology Information |
language | English |
publishDate | 2023 |
publisher | The Authors. Published by Elsevier Inc. |
record_format | MEDLINE/PubMed |
spelling | pubmed-101727612023-05-11 Mapping human pathogens in wastewater using a metatranscriptomic approach Carneiro, João Pascoal, Francisco Semedo, Miguel Pratas, Diogo Tomasino, Maria Paola Rego, Adriana Carvalho, Maria de Fátima Mucha, Ana Paula Magalhães, Catarina Environ Res Article The monitoring of cities’ wastewaters for the detection of potentially pathogenic viruses and bacteria has been considered a priority during the COVID-19 pandemic to monitor public health in urban environments. The methodological approaches frequently used for this purpose include deoxyribonucleic acid (DNA)/Ribonucleic acid (RNA) isolation followed by quantitative polymerase chain reaction (qPCR) and reverse transcription (RT)‒qPCR targeting pathogenic genes. More recently, the application of metatranscriptomic has opened opportunities to develop broad pathogenic monitoring workflows covering the entire pathogenic community within the sample. Nevertheless, the high amount of data generated in the process requires an appropriate analysis to detect the pathogenic community from the entire dataset. Here, an implementation of a bioinformatic workflow was developed to produce a map of the detected pathogenic bacteria and viruses in wastewater samples by analysing metatranscriptomic data. The main objectives of this work was the development of a computational methodology that can accurately detect both human pathogenic virus and bacteria in wastewater samples. This workflow can be easily reproducible with open-source software and uses efficient computational resources. The results showed that the used algorithms can predict potential human pathogens presence in the tested samples and that active forms of both bacteria and virus can be identified. By comparing the computational method implemented in this study to other state-of-the-art workflows, the implementation analysis was faster, while providing higher accuracy and sensitivity. Considering these results, the processes and methods to monitor wastewater for potential human pathogens can become faster and more accurate. The proposed workflow is available at https://github.com/waterpt/watermonitor and can be implemented in currently wastewater monitoring programs to ascertain the presence of potential human pathogenic species. The Authors. Published by Elsevier Inc. 2023-08-15 2023-05-05 /pmc/articles/PMC10172761/ /pubmed/37150387 http://dx.doi.org/10.1016/j.envres.2023.116040 Text en © 2023 The Authors Since January 2020 Elsevier has created a COVID-19 resource centre with free information in English and Mandarin on the novel coronavirus COVID-19. The COVID-19 resource centre is hosted on Elsevier Connect, the company's public news and information website. Elsevier hereby grants permission to make all its COVID-19-related research that is available on the COVID-19 resource centre - including this research content - immediately available in PubMed Central and other publicly funded repositories, such as the WHO COVID database with rights for unrestricted research re-use and analyses in any form or by any means with acknowledgement of the original source. These permissions are granted for free by Elsevier for as long as the COVID-19 resource centre remains active. |
spellingShingle | Article Carneiro, João Pascoal, Francisco Semedo, Miguel Pratas, Diogo Tomasino, Maria Paola Rego, Adriana Carvalho, Maria de Fátima Mucha, Ana Paula Magalhães, Catarina Mapping human pathogens in wastewater using a metatranscriptomic approach |
title | Mapping human pathogens in wastewater using a metatranscriptomic approach |
title_full | Mapping human pathogens in wastewater using a metatranscriptomic approach |
title_fullStr | Mapping human pathogens in wastewater using a metatranscriptomic approach |
title_full_unstemmed | Mapping human pathogens in wastewater using a metatranscriptomic approach |
title_short | Mapping human pathogens in wastewater using a metatranscriptomic approach |
title_sort | mapping human pathogens in wastewater using a metatranscriptomic approach |
topic | Article |
url | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC10172761/ https://www.ncbi.nlm.nih.gov/pubmed/37150387 http://dx.doi.org/10.1016/j.envres.2023.116040 |
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