16S rRNA Amplicon Sequencing for Epidemiological Surveys of Bacteria in Wildlife

ABSTRACT The human impact on natural habitats is increasing the complexity of human-wildlife interactions and leading to the emergence of infectious diseases worldwide. Highly successful synanthropic wildlife species, such as rodents, will undoubtedly play an increasingly important role in transmitt...

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Autores principales:	Maxime Galan, Maria Razzauti, Emilie Bard, Maria Bernard, Carine Brouat, Nathalie Charbonnel, Alexandre Dehne-Garcia, Anne Loiseau, Caroline Tatard, Lucie Tamisier, Muriel Vayssier-Taussat, Helene Vignes, Jean-François Cosson
Formato:	article
Lenguaje:	EN
Publicado:	American Society for Microbiology 2016
Materias:	bacteria emerging infectious diseases high-throughput sequencing metabarcoding molecular epidemiology next-generation sequencing Microbiology QR1-502
Acceso en línea:	https://doaj.org/article/866cb509d1a548e4b0a4f938e98aa3a4
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spelling	oai:doaj.org-article:866cb509d1a548e4b0a4f938e98aa3a42021-12-02T18:39:33Z16S rRNA Amplicon Sequencing for Epidemiological Surveys of Bacteria in Wildlife10.1128/mSystems.00032-162379-5077https://doaj.org/article/866cb509d1a548e4b0a4f938e98aa3a42016-08-01T00:00:00Zhttps://journals.asm.org/doi/10.1128/mSystems.00032-16https://doaj.org/toc/2379-5077ABSTRACT The human impact on natural habitats is increasing the complexity of human-wildlife interactions and leading to the emergence of infectious diseases worldwide. Highly successful synanthropic wildlife species, such as rodents, will undoubtedly play an increasingly important role in transmitting zoonotic diseases. We investigated the potential for recent developments in 16S rRNA amplicon sequencing to facilitate the multiplexing of the large numbers of samples needed to improve our understanding of the risk of zoonotic disease transmission posed by urban rodents in West Africa. In addition to listing pathogenic bacteria in wild populations, as in other high-throughput sequencing (HTS) studies, our approach can estimate essential parameters for studies of zoonotic risk, such as prevalence and patterns of coinfection within individual hosts. However, the estimation of these parameters requires cleaning of the raw data to mitigate the biases generated by HTS methods. We present here an extensive review of these biases and of their consequences, and we propose a comprehensive trimming strategy for managing these biases. We demonstrated the application of this strategy using 711 commensal rodents, including 208 Mus musculusdomesticus, 189 Rattus rattus, 93 Mastomys natalensis, and 221 Mastomys erythroleucus, collected from 24 villages in Senegal. Seven major genera of pathogenic bacteria were detected in their spleens: Borrelia, Bartonella, Mycoplasma, Ehrlichia, Rickettsia, Streptobacillus, and Orientia. Mycoplasma, Ehrlichia, Rickettsia, Streptobacillus, and Orientia have never before been detected in West African rodents. Bacterial prevalence ranged from 0% to 90% of individuals per site, depending on the bacterial taxon, rodent species, and site considered, and 26% of rodents displayed coinfection. The 16S rRNA amplicon sequencing strategy presented here has the advantage over other molecular surveillance tools of dealing with a large spectrum of bacterial pathogens without requiring assumptions about their presence in the samples. This approach is therefore particularly suitable to continuous pathogen surveillance in the context of disease-monitoring programs. IMPORTANCE Several recent public health crises have shown that the surveillance of zoonotic agents in wildlife is important to prevent pandemic risks. High-throughput sequencing (HTS) technologies are potentially useful for this surveillance, but rigorous experimental processes are required for the use of these effective tools in such epidemiological contexts. In particular, HTS introduces biases into the raw data set that might lead to incorrect interpretations. We describe here a procedure for cleaning data before estimating reliable biological parameters, such as positivity, prevalence, and coinfection, using 16S rRNA amplicon sequencing on an Illumina MiSeq platform. This procedure, applied to 711 rodents collected in West Africa, detected several zoonotic bacterial species, including some at high prevalence, despite their never before having been reported for West Africa. In the future, this approach could be adapted for the monitoring of other microbes such as protists, fungi, and even viruses.Maxime GalanMaria RazzautiEmilie BardMaria BernardCarine BrouatNathalie CharbonnelAlexandre Dehne-GarciaAnne LoiseauCaroline TatardLucie TamisierMuriel Vayssier-TaussatHelene VignesJean-François CossonAmerican Society for Microbiologyarticlebacteriaemerging infectious diseaseshigh-throughput sequencingmetabarcodingmolecular epidemiologynext-generation sequencingMicrobiologyQR1-502ENmSystems, Vol 1, Iss 4 (2016)
institution	DOAJ
collection	DOAJ
language	EN
topic	bacteria emerging infectious diseases high-throughput sequencing metabarcoding molecular epidemiology next-generation sequencing Microbiology QR1-502
spellingShingle	bacteria emerging infectious diseases high-throughput sequencing metabarcoding molecular epidemiology next-generation sequencing Microbiology QR1-502 Maxime Galan Maria Razzauti Emilie Bard Maria Bernard Carine Brouat Nathalie Charbonnel Alexandre Dehne-Garcia Anne Loiseau Caroline Tatard Lucie Tamisier Muriel Vayssier-Taussat Helene Vignes Jean-François Cosson 16S rRNA Amplicon Sequencing for Epidemiological Surveys of Bacteria in Wildlife
description	ABSTRACT The human impact on natural habitats is increasing the complexity of human-wildlife interactions and leading to the emergence of infectious diseases worldwide. Highly successful synanthropic wildlife species, such as rodents, will undoubtedly play an increasingly important role in transmitting zoonotic diseases. We investigated the potential for recent developments in 16S rRNA amplicon sequencing to facilitate the multiplexing of the large numbers of samples needed to improve our understanding of the risk of zoonotic disease transmission posed by urban rodents in West Africa. In addition to listing pathogenic bacteria in wild populations, as in other high-throughput sequencing (HTS) studies, our approach can estimate essential parameters for studies of zoonotic risk, such as prevalence and patterns of coinfection within individual hosts. However, the estimation of these parameters requires cleaning of the raw data to mitigate the biases generated by HTS methods. We present here an extensive review of these biases and of their consequences, and we propose a comprehensive trimming strategy for managing these biases. We demonstrated the application of this strategy using 711 commensal rodents, including 208 Mus musculusdomesticus, 189 Rattus rattus, 93 Mastomys natalensis, and 221 Mastomys erythroleucus, collected from 24 villages in Senegal. Seven major genera of pathogenic bacteria were detected in their spleens: Borrelia, Bartonella, Mycoplasma, Ehrlichia, Rickettsia, Streptobacillus, and Orientia. Mycoplasma, Ehrlichia, Rickettsia, Streptobacillus, and Orientia have never before been detected in West African rodents. Bacterial prevalence ranged from 0% to 90% of individuals per site, depending on the bacterial taxon, rodent species, and site considered, and 26% of rodents displayed coinfection. The 16S rRNA amplicon sequencing strategy presented here has the advantage over other molecular surveillance tools of dealing with a large spectrum of bacterial pathogens without requiring assumptions about their presence in the samples. This approach is therefore particularly suitable to continuous pathogen surveillance in the context of disease-monitoring programs. IMPORTANCE Several recent public health crises have shown that the surveillance of zoonotic agents in wildlife is important to prevent pandemic risks. High-throughput sequencing (HTS) technologies are potentially useful for this surveillance, but rigorous experimental processes are required for the use of these effective tools in such epidemiological contexts. In particular, HTS introduces biases into the raw data set that might lead to incorrect interpretations. We describe here a procedure for cleaning data before estimating reliable biological parameters, such as positivity, prevalence, and coinfection, using 16S rRNA amplicon sequencing on an Illumina MiSeq platform. This procedure, applied to 711 rodents collected in West Africa, detected several zoonotic bacterial species, including some at high prevalence, despite their never before having been reported for West Africa. In the future, this approach could be adapted for the monitoring of other microbes such as protists, fungi, and even viruses.
format	article
author	Maxime Galan Maria Razzauti Emilie Bard Maria Bernard Carine Brouat Nathalie Charbonnel Alexandre Dehne-Garcia Anne Loiseau Caroline Tatard Lucie Tamisier Muriel Vayssier-Taussat Helene Vignes Jean-François Cosson
author_facet	Maxime Galan Maria Razzauti Emilie Bard Maria Bernard Carine Brouat Nathalie Charbonnel Alexandre Dehne-Garcia Anne Loiseau Caroline Tatard Lucie Tamisier Muriel Vayssier-Taussat Helene Vignes Jean-François Cosson
author_sort	Maxime Galan
title	16S rRNA Amplicon Sequencing for Epidemiological Surveys of Bacteria in Wildlife
title_short	16S rRNA Amplicon Sequencing for Epidemiological Surveys of Bacteria in Wildlife
title_full	16S rRNA Amplicon Sequencing for Epidemiological Surveys of Bacteria in Wildlife
title_fullStr	16S rRNA Amplicon Sequencing for Epidemiological Surveys of Bacteria in Wildlife
title_full_unstemmed	16S rRNA Amplicon Sequencing for Epidemiological Surveys of Bacteria in Wildlife
title_sort	16s rrna amplicon sequencing for epidemiological surveys of bacteria in wildlife
publisher	American Society for Microbiology
publishDate	2016
url	https://doaj.org/article/866cb509d1a548e4b0a4f938e98aa3a4
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16S rRNA Amplicon Sequencing for Epidemiological Surveys of Bacteria in Wildlife

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