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Registro completo
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Biblioteca (s) : |
INIA Treinta y Tres. |
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Fecha : |
21/02/2014 |
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Actualizado : |
13/09/2018 |
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Tipo de producción científica : |
Artículos en Revistas Indexadas Internacionales |
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Autor : |
NOYES, N.R.; WEINROTH, M.E.; PARKER, J.K.; DEAN, C.J.; LAKIN, S.M.; RAYMOND, R.A.; ROVIRA, P.J.; DOSTER, E.; ABDO, Z.; MARTIN, J.N.; JONES, K.L.; RUIZ, J.; BOUCHER, C.A.; BELK, K.E.; MORLEY, P.S. |
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Afiliación : |
NOELLE R. NOYES; MAGGIE E. WEINROTH; JENNIFER K. PARKER; CHRIS J. DEAN; STEVEN M. LAKIN; ROBERT A. RAYMOND; PABLO JUAN ROVIRA SANZ, INIA (Instituto Nacional de Investigación Agropecuaria), Uruguay; ENRIQUE DOSTER; ZAID ABDO; JENNIFER N. MARTIN; KENNETH L. JONES; JAIME RUIZ; CHRISTINA A. BOUCHER; KEITH E. BELK; PAUL S. MORLEY. |
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Título : |
Enrichment allows identification of diverse, rate elements in metagenomic resistome-virulome sequencing. |
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Fecha de publicación : |
2017 |
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Fuente / Imprenta : |
Microbiome, 2017, 5, p. 142 |
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Páginas : |
13 p. |
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DOI : |
10.1186/s40168-017-0361-8 |
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Idioma : |
Inglés |
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Notas : |
Article History: Received: 29 May 2017, Accepted: 5 October 2017, Published: 17 October 2017 |
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Contenido : |
Background: Shotgun metagenomic sequencing is increasingly utilized as a tool to evaluate ecological-level dynamics of antimicrobial resistance and virulence, in conjunction with microbiome analysis. Interest in use of this method for environmental surveillance of antimicrobial resistance and pathogenic microorganisms is also increasing. In published metagenomic datasets, the total of all resistance- and virulence-related sequences accounts for < 1% of all sequenced DNA, leading to imitations in detection of low-abundance resistome-virulome elements. This study describes the extent and composition of the low-abundance portion of the resistome-virulome, using a bait-capture and enrichment system that incorporates unique molecular indices to count DNA molecules and correct for enrichment bias.
Results: The use of the bait-capture and enrichment system significantly increased on-target sequencing of the resistome-virulome, enabling detection of an additional 1441 gene accessions and revealing a low-abundance portion of the resistome-virulome that was more diverse and compositionally different than that detected by more traditional
metagenomic assays. The low-abundance portion of the resistome-virulome also contained resistance genes with public health importance, such as extended-spectrum betalactamases, that were not detected using traditional shotgun metagenomic sequencing. In addition, the use of the bait-capture and enrichment system enabled identification of rare resistance gene haplotypes that were used to discriminate between sample origins.
Conclusions: These results demonstrate that the rare resistome-virulome contains valuable and unique information that can be utilized for both surveillance and population genetic investigations of resistance. Access to the rare resistomevirulome using the bait-capture and enrichment system validated in this study can greatly advance our understanding of
microbiome-resistome dynamics. MenosBackground: Shotgun metagenomic sequencing is increasingly utilized as a tool to evaluate ecological-level dynamics of antimicrobial resistance and virulence, in conjunction with microbiome analysis. Interest in use of this method for environmental surveillance of antimicrobial resistance and pathogenic microorganisms is also increasing. In published metagenomic datasets, the total of all resistance- and virulence-related sequences accounts for < 1% of all sequenced DNA, leading to imitations in detection of low-abundance resistome-virulome elements. This study describes the extent and composition of the low-abundance portion of the resistome-virulome, using a bait-capture and enrichment system that incorporates unique molecular indices to count DNA molecules and correct for enrichment bias.
Results: The use of the bait-capture and enrichment system significantly increased on-target sequencing of the resistome-virulome, enabling detection of an additional 1441 gene accessions and revealing a low-abundance portion of the resistome-virulome that was more diverse and compositionally different than that detected by more traditional
metagenomic assays. The low-abundance portion of the resistome-virulome also contained resistance genes with public health importance, such as extended-spectrum betalactamases, that were not detected using traditional shotgun metagenomic sequencing. In addition, the use of the bait-capture and enrichment system enabled identification of rare resistan... Presentar Todo |
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Palabras claves : |
ANTIMICROBIAL RESISTANCE; METAGENÓMICA; MICROBIAL ECOLOGY; MOLECULAR ENRICHMENT; RARE MICROBIOME; RESISTOME. |
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Thesagro : |
ANALISIS BIOLOGICO; ECOLOGIA MICROBIANA; RESISTENCIA A AGENTES DANINOS. |
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Asunto categoría : |
U30 Métodos de investigación |
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Marc : |
LEADER 03225naa a2200433 a 4500
001 1032862
005 2018-09-13
008 2017 bl uuuu u00u1 u #d
024 7 $a10.1186/s40168-017-0361-8$2DOI
100 1 $aNOYES, N.R.
245 $aEnrichment allows identification of diverse, rate elements in metagenomic resistome-virulome sequencing.$h[electronic resource]
260 $c2017
300 $a13 p.
500 $aArticle History: Received: 29 May 2017, Accepted: 5 October 2017, Published: 17 October 2017
520 $aBackground: Shotgun metagenomic sequencing is increasingly utilized as a tool to evaluate ecological-level dynamics of antimicrobial resistance and virulence, in conjunction with microbiome analysis. Interest in use of this method for environmental surveillance of antimicrobial resistance and pathogenic microorganisms is also increasing. In published metagenomic datasets, the total of all resistance- and virulence-related sequences accounts for < 1% of all sequenced DNA, leading to imitations in detection of low-abundance resistome-virulome elements. This study describes the extent and composition of the low-abundance portion of the resistome-virulome, using a bait-capture and enrichment system that incorporates unique molecular indices to count DNA molecules and correct for enrichment bias. Results: The use of the bait-capture and enrichment system significantly increased on-target sequencing of the resistome-virulome, enabling detection of an additional 1441 gene accessions and revealing a low-abundance portion of the resistome-virulome that was more diverse and compositionally different than that detected by more traditional metagenomic assays. The low-abundance portion of the resistome-virulome also contained resistance genes with public health importance, such as extended-spectrum betalactamases, that were not detected using traditional shotgun metagenomic sequencing. In addition, the use of the bait-capture and enrichment system enabled identification of rare resistance gene haplotypes that were used to discriminate between sample origins. Conclusions: These results demonstrate that the rare resistome-virulome contains valuable and unique information that can be utilized for both surveillance and population genetic investigations of resistance. Access to the rare resistomevirulome using the bait-capture and enrichment system validated in this study can greatly advance our understanding of microbiome-resistome dynamics.
650 $aANALISIS BIOLOGICO
650 $aECOLOGIA MICROBIANA
650 $aRESISTENCIA A AGENTES DANINOS
653 $aANTIMICROBIAL RESISTANCE
653 $aMETAGENÓMICA
653 $aMICROBIAL ECOLOGY
653 $aMOLECULAR ENRICHMENT
653 $aRARE MICROBIOME
653 $aRESISTOME
700 1 $aWEINROTH, M.E.
700 1 $aPARKER, J.K.
700 1 $aDEAN, C.J.
700 1 $aLAKIN, S.M.
700 1 $aRAYMOND, R.A.
700 1 $aROVIRA, P.J.
700 1 $aDOSTER, E.
700 1 $aABDO, Z.
700 1 $aMARTIN, J.N.
700 1 $aJONES, K.L.
700 1 $aRUIZ, J.
700 1 $aBOUCHER, C.A.
700 1 $aBELK, K.E.
700 1 $aMORLEY, P.S.
773 $tMicrobiome, 2017, 5, p. 142
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Registro original : |
INIA Treinta y Tres (TT) |
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Registro completo
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Biblioteca (s) : |
INIA Treinta y Tres. |
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Fecha actual : |
17/04/2017 |
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Actualizado : |
11/10/2019 |
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Tipo de producción científica : |
Artículos en Revistas Indexadas Internacionales |
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Circulación / Nivel : |
A - A |
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Autor : |
LAKIN, S.M.; DEAN, C.; NOYES, N.R.; DETTENWANGER, A.; ROSS, A. S.; DOSTER, E.; ROVIRA, P.J.; ABDO, Z.; JONES, K.L.; RUIZ, J.; BELK, K.E.; MORLEY, P.S.; BOUCHER, C. |
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Afiliación : |
STEVEN M. LAKIN; CHRIS DEAN; NOELLE R. NOYES; ADAM DETTENWANGER; ANNE SPENCER ROSS; ENRIQUE DOSTER; PABLO JUAN ROVIRA SANZ, INIA (Instituto Nacional de Investigación Agropecuaria), Uruguay. Department of Animal Sciences, Colorado State University, USA.; ZAID ABDO; KENNETH L. JONES; JAIME RUIZ; KEITH E. BELK; PAUL S. MORLEY; CHRISTINA BOUCHER. |
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Título : |
MEGARes: an antimicrobial resistance database for high throughput sequencing. |
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Fecha de publicación : |
2017 |
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Fuente / Imprenta : |
Nucleic Acids Research, 2017 v.45 p.574-580. |
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DOI : |
10.1093/nar/gkw1009 |
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Idioma : |
Inglés |
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Notas : |
Article History: Published online 2016 Nov 24.
DOI: https://doi.org/10.1093/nar/gkw1009 |
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Contenido : |
Antimicrobial resistance has become an imminent concern for public health. As methods for detection and characterization of antimicrobial resistance move from targeted culture and polymerase chain reaction to high throughput metagenomics, appropriate resources for the analysis of large-scale data are required. Currently, antimicrobial resistance databases are tailored to smaller-scale, functional profiling of genes using highly descriptive annotations. Such characteristics do not facilitate the analysis of large-scale, ecological sequence datasets such as those produced with the use of metagenomics for surveillance. In order to overcome these limitations, we present MEGARes (https://megares.meglab.org), a hand-curated antimicrobial resistance database and annotation structure that provides a foundation for the development of high throughput acyclical classifiers and hierarchical statistical analysis of big data. MEGARes can be browsed as a stand-alone resource through the website or can be easily integrated into sequence analysis pipelines through download. Also via the website, we provide documentation for AmrPlusPlus, a user-friendly Galaxy pipeline for the analysis of high throughput sequencing data that is pre-packaged for use with the MEGARes database. |
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Palabras claves : |
BASE DE DATOS; BIOINFORMÁTICA; DATASETS; DRUG RESISTANCE; GENES; METAGENÓMICA; METAGENOMICS; MICROBIAL; POLYMERASE CHAIN REACTION; PUBLIC HEALTH MEDICINE; RESISTENCIA ANTIMICROBIANA; SEQUENCE ANALYSIS. |
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Asunto categoría : |
L01 Ganadería |
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URL : |
http://www.ainfo.inia.uy/digital/bitstream/item/6677/1/Rovira-arb-2017-1.pdf
https://www.ncbi.nlm.nih.gov/pmc/articles/PMC5210519/
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Marc : |
LEADER 02505naa a2200433 a 4500
001 1057051
005 2019-10-11
008 2017 bl uuuu u00u1 u #d
024 7 $a10.1093/nar/gkw1009$2DOI
100 1 $aLAKIN, S.M.
245 $aMEGARes$ban antimicrobial resistance database for high throughput sequencing.$h[electronic resource]
260 $c2017
500 $aArticle History: Published online 2016 Nov 24. DOI: https://doi.org/10.1093/nar/gkw1009
520 $aAntimicrobial resistance has become an imminent concern for public health. As methods for detection and characterization of antimicrobial resistance move from targeted culture and polymerase chain reaction to high throughput metagenomics, appropriate resources for the analysis of large-scale data are required. Currently, antimicrobial resistance databases are tailored to smaller-scale, functional profiling of genes using highly descriptive annotations. Such characteristics do not facilitate the analysis of large-scale, ecological sequence datasets such as those produced with the use of metagenomics for surveillance. In order to overcome these limitations, we present MEGARes (https://megares.meglab.org), a hand-curated antimicrobial resistance database and annotation structure that provides a foundation for the development of high throughput acyclical classifiers and hierarchical statistical analysis of big data. MEGARes can be browsed as a stand-alone resource through the website or can be easily integrated into sequence analysis pipelines through download. Also via the website, we provide documentation for AmrPlusPlus, a user-friendly Galaxy pipeline for the analysis of high throughput sequencing data that is pre-packaged for use with the MEGARes database.
653 $aBASE DE DATOS
653 $aBIOINFORMÁTICA
653 $aDATASETS
653 $aDRUG RESISTANCE
653 $aGENES
653 $aMETAGENÓMICA
653 $aMETAGENOMICS
653 $aMICROBIAL
653 $aPOLYMERASE CHAIN REACTION
653 $aPUBLIC HEALTH MEDICINE
653 $aRESISTENCIA ANTIMICROBIANA
653 $aSEQUENCE ANALYSIS
700 1 $aDEAN, C.
700 1 $aNOYES, N.R.
700 1 $aDETTENWANGER, A.
700 1 $aROSS, A. S.
700 1 $aDOSTER, E.
700 1 $aROVIRA, P.J.
700 1 $aABDO, Z.
700 1 $aJONES, K.L.
700 1 $aRUIZ, J.
700 1 $aBELK, K.E.
700 1 $aMORLEY, P.S.
700 1 $aBOUCHER, C.
773 $tNucleic Acids Research, 2017$gv.45 p.574-580.
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