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...

Ausführliche Beschreibung

Gespeichert in:
Bibliographische Detailangaben
Veröffentlicht in:Environmental research 2023-08, Vol.231 (Pt 1), p.116040-116040, Article 116040
Hauptverfasser: Carneiro, João, Pascoal, Francisco, Semedo, Miguel, Pratas, Diogo, Tomasino, Maria Paola, Rego, Adriana, Carvalho, Maria de Fátima, Mucha, Ana Paula, Magalhães, Catarina
Format: Artikel
Sprache:eng
Schlagworte:
Online-Zugang:Volltext
Tags: Tag hinzufügen
Keine Tags, Fügen Sie den ersten Tag hinzu!
container_end_page 116040
container_issue Pt 1
container_start_page 116040
container_title Environmental research
container_volume 231
creator Carneiro, João
Pascoal, Francisco
Semedo, Miguel
Pratas, Diogo
Tomasino, Maria Paola
Rego, Adriana
Carvalho, Maria de Fátima
Mucha, Ana Paula
Magalhães, Catarina
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. •Metatranscriptomic tool to detect potential pathogens in wastewater.•Cross validation of metatranscriptomic workflows improves detection accuracy.•FALCON-meta detects potential human viral and bacterial pathogens.•Metatranscriptomic tool can be introduced in wastewater monitoring.
doi_str_mv 10.1016/j.envres.2023.116040
format Article
fullrecord <record><control><sourceid>proquest_pubme</sourceid><recordid>TN_cdi_pubmedcentral_primary_oai_pubmedcentral_nih_gov_10172761</recordid><sourceformat>XML</sourceformat><sourcesystem>PC</sourcesystem><els_id>S0013935123008320</els_id><sourcerecordid>2811215665</sourcerecordid><originalsourceid>FETCH-LOGICAL-c490t-bb4c13eee0525ac762d535e6ee7ce3a17c1041fba745f8ef688b253af6f344e03</originalsourceid><addsrcrecordid>eNp9kUFr3DAQhUVJaTZp_0EJPubijcayZO-lpYQ2CaT00p7FWDve1bKWHEnekH8fLU5Dc-lJDPrem-E9xj4DXwIHdbVbkjsEisuKV2IJoHjN37EF8JUq-UqKE7bgHES5EhJO2VmMuzyCFPwDOxUNSC7aZsHufuI4WrcpttOArhgxbf2GXCysKx4xJnrERKGY4pHBYqCEKaCLJtgx-cGaIuuDR7P9yN73uI_06eU9Z39-fP99fVve_7q5u_52X5p6xVPZdbUBQURcVhJNo6q1FJIUUWNIIDQGeA19h00t-5Z61bZdJQX2qhd1TVycs6-z7zh1A60NuXzQXo_BDhietEer3_44u9Ubf9A5taZqFGSHyxeH4B8mikkPNhra79GRn6KuWoAKpFIyo_WMmuBjDNS_7gF-NFR6p-ca9LEGPdeQZRf_3vgq-pt7Br7MAOWkDpaCjsaSM7S2gUzSa2__v-EZIzGdOQ</addsrcrecordid><sourcetype>Open Access Repository</sourcetype><iscdi>true</iscdi><recordtype>article</recordtype><pqid>2811215665</pqid></control><display><type>article</type><title>Mapping human pathogens in wastewater using a metatranscriptomic approach</title><source>MEDLINE</source><source>Access via ScienceDirect (Elsevier)</source><creator>Carneiro, João ; Pascoal, Francisco ; Semedo, Miguel ; Pratas, Diogo ; Tomasino, Maria Paola ; Rego, Adriana ; Carvalho, Maria de Fátima ; Mucha, Ana Paula ; Magalhães, Catarina</creator><creatorcontrib>Carneiro, João ; Pascoal, Francisco ; Semedo, Miguel ; Pratas, Diogo ; Tomasino, Maria Paola ; Rego, Adriana ; Carvalho, Maria de Fátima ; Mucha, Ana Paula ; Magalhães, Catarina</creatorcontrib><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. •Metatranscriptomic tool to detect potential pathogens in wastewater.•Cross validation of metatranscriptomic workflows improves detection accuracy.•FALCON-meta detects potential human viral and bacterial pathogens.•Metatranscriptomic tool can be introduced in wastewater monitoring.</description><identifier>ISSN: 0013-9351</identifier><identifier>EISSN: 1096-0953</identifier><identifier>DOI: 10.1016/j.envres.2023.116040</identifier><identifier>PMID: 37150387</identifier><language>eng</language><publisher>Netherlands: Elsevier Inc</publisher><subject>Bacteria - genetics ; COVID-19 ; Human pathogens ; Humans ; Metatranscriptomics ; Pandemics ; Public health ; Viruses - genetics ; Wastewater</subject><ispartof>Environmental research, 2023-08, Vol.231 (Pt 1), p.116040-116040, Article 116040</ispartof><rights>2023 The Authors</rights><rights>Copyright © 2023 The Authors. Published by Elsevier Inc. All rights reserved.</rights><rights>2023 The Authors 2023</rights><lds50>peer_reviewed</lds50><oa>free_for_read</oa><woscitedreferencessubscribed>false</woscitedreferencessubscribed><citedby>FETCH-LOGICAL-c490t-bb4c13eee0525ac762d535e6ee7ce3a17c1041fba745f8ef688b253af6f344e03</citedby><cites>FETCH-LOGICAL-c490t-bb4c13eee0525ac762d535e6ee7ce3a17c1041fba745f8ef688b253af6f344e03</cites><orcidid>0000-0003-2263-2212 ; 0000-0001-9647-1197 ; 0000-0002-7181-0540</orcidid></display><links><openurl>$$Topenurl_article</openurl><openurlfulltext>$$Topenurlfull_article</openurlfulltext><thumbnail>$$Tsyndetics_thumb_exl</thumbnail><linktohtml>$$Uhttps://dx.doi.org/10.1016/j.envres.2023.116040$$EHTML$$P50$$Gelsevier$$Hfree_for_read</linktohtml><link.rule.ids>230,314,780,784,885,3550,27924,27925,45995</link.rule.ids><backlink>$$Uhttps://www.ncbi.nlm.nih.gov/pubmed/37150387$$D View this record in MEDLINE/PubMed$$Hfree_for_read</backlink></links><search><creatorcontrib>Carneiro, João</creatorcontrib><creatorcontrib>Pascoal, Francisco</creatorcontrib><creatorcontrib>Semedo, Miguel</creatorcontrib><creatorcontrib>Pratas, Diogo</creatorcontrib><creatorcontrib>Tomasino, Maria Paola</creatorcontrib><creatorcontrib>Rego, Adriana</creatorcontrib><creatorcontrib>Carvalho, Maria de Fátima</creatorcontrib><creatorcontrib>Mucha, Ana Paula</creatorcontrib><creatorcontrib>Magalhães, Catarina</creatorcontrib><title>Mapping human pathogens in wastewater using a metatranscriptomic approach</title><title>Environmental research</title><addtitle>Environ Res</addtitle><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. •Metatranscriptomic tool to detect potential pathogens in wastewater.•Cross validation of metatranscriptomic workflows improves detection accuracy.•FALCON-meta detects potential human viral and bacterial pathogens.•Metatranscriptomic tool can be introduced in wastewater monitoring.</description><subject>Bacteria - genetics</subject><subject>COVID-19</subject><subject>Human pathogens</subject><subject>Humans</subject><subject>Metatranscriptomics</subject><subject>Pandemics</subject><subject>Public health</subject><subject>Viruses - genetics</subject><subject>Wastewater</subject><issn>0013-9351</issn><issn>1096-0953</issn><fulltext>true</fulltext><rsrctype>article</rsrctype><creationdate>2023</creationdate><recordtype>article</recordtype><sourceid>EIF</sourceid><recordid>eNp9kUFr3DAQhUVJaTZp_0EJPubijcayZO-lpYQ2CaT00p7FWDve1bKWHEnekH8fLU5Dc-lJDPrem-E9xj4DXwIHdbVbkjsEisuKV2IJoHjN37EF8JUq-UqKE7bgHES5EhJO2VmMuzyCFPwDOxUNSC7aZsHufuI4WrcpttOArhgxbf2GXCysKx4xJnrERKGY4pHBYqCEKaCLJtgx-cGaIuuDR7P9yN73uI_06eU9Z39-fP99fVve_7q5u_52X5p6xVPZdbUBQURcVhJNo6q1FJIUUWNIIDQGeA19h00t-5Z61bZdJQX2qhd1TVycs6-z7zh1A60NuXzQXo_BDhietEer3_44u9Ubf9A5taZqFGSHyxeH4B8mikkPNhra79GRn6KuWoAKpFIyo_WMmuBjDNS_7gF-NFR6p-ca9LEGPdeQZRf_3vgq-pt7Br7MAOWkDpaCjsaSM7S2gUzSa2__v-EZIzGdOQ</recordid><startdate>20230815</startdate><enddate>20230815</enddate><creator>Carneiro, João</creator><creator>Pascoal, Francisco</creator><creator>Semedo, Miguel</creator><creator>Pratas, Diogo</creator><creator>Tomasino, Maria Paola</creator><creator>Rego, Adriana</creator><creator>Carvalho, Maria de Fátima</creator><creator>Mucha, Ana Paula</creator><creator>Magalhães, Catarina</creator><general>Elsevier Inc</general><general>The Authors. Published by Elsevier Inc</general><scope>6I.</scope><scope>AAFTH</scope><scope>CGR</scope><scope>CUY</scope><scope>CVF</scope><scope>ECM</scope><scope>EIF</scope><scope>NPM</scope><scope>AAYXX</scope><scope>CITATION</scope><scope>7X8</scope><scope>5PM</scope><orcidid>https://orcid.org/0000-0003-2263-2212</orcidid><orcidid>https://orcid.org/0000-0001-9647-1197</orcidid><orcidid>https://orcid.org/0000-0002-7181-0540</orcidid></search><sort><creationdate>20230815</creationdate><title>Mapping human pathogens in wastewater using a metatranscriptomic approach</title><author>Carneiro, João ; Pascoal, Francisco ; Semedo, Miguel ; Pratas, Diogo ; Tomasino, Maria Paola ; Rego, Adriana ; Carvalho, Maria de Fátima ; Mucha, Ana Paula ; Magalhães, Catarina</author></sort><facets><frbrtype>5</frbrtype><frbrgroupid>cdi_FETCH-LOGICAL-c490t-bb4c13eee0525ac762d535e6ee7ce3a17c1041fba745f8ef688b253af6f344e03</frbrgroupid><rsrctype>articles</rsrctype><prefilter>articles</prefilter><language>eng</language><creationdate>2023</creationdate><topic>Bacteria - genetics</topic><topic>COVID-19</topic><topic>Human pathogens</topic><topic>Humans</topic><topic>Metatranscriptomics</topic><topic>Pandemics</topic><topic>Public health</topic><topic>Viruses - genetics</topic><topic>Wastewater</topic><toplevel>peer_reviewed</toplevel><toplevel>online_resources</toplevel><creatorcontrib>Carneiro, João</creatorcontrib><creatorcontrib>Pascoal, Francisco</creatorcontrib><creatorcontrib>Semedo, Miguel</creatorcontrib><creatorcontrib>Pratas, Diogo</creatorcontrib><creatorcontrib>Tomasino, Maria Paola</creatorcontrib><creatorcontrib>Rego, Adriana</creatorcontrib><creatorcontrib>Carvalho, Maria de Fátima</creatorcontrib><creatorcontrib>Mucha, Ana Paula</creatorcontrib><creatorcontrib>Magalhães, Catarina</creatorcontrib><collection>ScienceDirect Open Access Titles</collection><collection>Elsevier:ScienceDirect:Open Access</collection><collection>Medline</collection><collection>MEDLINE</collection><collection>MEDLINE (Ovid)</collection><collection>MEDLINE</collection><collection>MEDLINE</collection><collection>PubMed</collection><collection>CrossRef</collection><collection>MEDLINE - Academic</collection><collection>PubMed Central (Full Participant titles)</collection><jtitle>Environmental research</jtitle></facets><delivery><delcategory>Remote Search Resource</delcategory><fulltext>fulltext</fulltext></delivery><addata><au>Carneiro, João</au><au>Pascoal, Francisco</au><au>Semedo, Miguel</au><au>Pratas, Diogo</au><au>Tomasino, Maria Paola</au><au>Rego, Adriana</au><au>Carvalho, Maria de Fátima</au><au>Mucha, Ana Paula</au><au>Magalhães, Catarina</au><format>journal</format><genre>article</genre><ristype>JOUR</ristype><atitle>Mapping human pathogens in wastewater using a metatranscriptomic approach</atitle><jtitle>Environmental research</jtitle><addtitle>Environ Res</addtitle><date>2023-08-15</date><risdate>2023</risdate><volume>231</volume><issue>Pt 1</issue><spage>116040</spage><epage>116040</epage><pages>116040-116040</pages><artnum>116040</artnum><issn>0013-9351</issn><eissn>1096-0953</eissn><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. •Metatranscriptomic tool to detect potential pathogens in wastewater.•Cross validation of metatranscriptomic workflows improves detection accuracy.•FALCON-meta detects potential human viral and bacterial pathogens.•Metatranscriptomic tool can be introduced in wastewater monitoring.</abstract><cop>Netherlands</cop><pub>Elsevier Inc</pub><pmid>37150387</pmid><doi>10.1016/j.envres.2023.116040</doi><tpages>1</tpages><orcidid>https://orcid.org/0000-0003-2263-2212</orcidid><orcidid>https://orcid.org/0000-0001-9647-1197</orcidid><orcidid>https://orcid.org/0000-0002-7181-0540</orcidid><oa>free_for_read</oa></addata></record>
fulltext fulltext
identifier ISSN: 0013-9351
ispartof Environmental research, 2023-08, Vol.231 (Pt 1), p.116040-116040, Article 116040
issn 0013-9351
1096-0953
language eng
recordid cdi_pubmedcentral_primary_oai_pubmedcentral_nih_gov_10172761
source MEDLINE; Access via ScienceDirect (Elsevier)
subjects Bacteria - genetics
COVID-19
Human pathogens
Humans
Metatranscriptomics
Pandemics
Public health
Viruses - genetics
Wastewater
title Mapping human pathogens in wastewater using a metatranscriptomic approach
url https://sfx.bib-bvb.de/sfx_tum?ctx_ver=Z39.88-2004&ctx_enc=info:ofi/enc:UTF-8&ctx_tim=2024-12-20T19%3A06%3A24IST&url_ver=Z39.88-2004&url_ctx_fmt=infofi/fmt:kev:mtx:ctx&rfr_id=info:sid/primo.exlibrisgroup.com:primo3-Article-proquest_pubme&rft_val_fmt=info:ofi/fmt:kev:mtx:journal&rft.genre=article&rft.atitle=Mapping%20human%20pathogens%20in%20wastewater%20using%20a%20metatranscriptomic%20approach&rft.jtitle=Environmental%20research&rft.au=Carneiro,%20Jo%C3%A3o&rft.date=2023-08-15&rft.volume=231&rft.issue=Pt%201&rft.spage=116040&rft.epage=116040&rft.pages=116040-116040&rft.artnum=116040&rft.issn=0013-9351&rft.eissn=1096-0953&rft_id=info:doi/10.1016/j.envres.2023.116040&rft_dat=%3Cproquest_pubme%3E2811215665%3C/proquest_pubme%3E%3Curl%3E%3C/url%3E&disable_directlink=true&sfx.directlink=off&sfx.report_link=0&rft_id=info:oai/&rft_pqid=2811215665&rft_id=info:pmid/37150387&rft_els_id=S0013935123008320&rfr_iscdi=true