Please use this identifier to cite or link to this item: http://hdl.handle.net/10773/37806
Title: Mapping human pathogens in wastewater using a metatranscriptomic approach
Author: Carneiro, João
Pascoal, Francisco
Semedo, Miguel
Pratas, Diogo
Tomasino, Maria Paola
Rego, Adriana
Carvalho, Maria de Fátima
Mucha, Ana Paula
Magalhães, Catarina
Keywords: Human pathogens
Wastewater
Metatranscriptomics
Public health
Issue Date: 15-Aug-2023
Publisher: Elsevier
Abstract: 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.
Peer review: yes
URI: http://hdl.handle.net/10773/37806
DOI: 10.1016/j.envres.2023.116040
ISSN: 0013-9351
Appears in Collections:DETI - Artigos
IEETA - Artigos

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