| |
|
|
|
Registro completo
|
|
Biblioteca (s) : |
INIA Treinta y Tres. |
|
Fecha : |
04/09/2019 |
|
Actualizado : |
16/03/2021 |
|
Tipo de producción científica : |
Artículos en Revistas Indexadas Internacionales |
|
Autor : |
ROVIRA, P.J.; MCALLISTER, T.; LAKIN, S.M.; COOK, S.R.; DOSTER, E.; NOYES, N. R.; WEINROTH, M.D.; YANG, X.; PARKER, J. K.; BOUCHER, C.; BOOKER, C. W.; WOENER, D. R.; BELK, K. E.; MORLEY, P. S. |
|
Afiliación : |
PABLO JUAN ROVIRA SANZ, INIA (Instituto Nacional de Investigación Agropecuaria), Uruguay. Department of Animal Sciences, College of Agricultural Sciences, Colorado State University, USA.; TIM MCALLISTER, Lethbridge Research and Development Centre, Agriculture and Agri-Food Canada.; STEVEN M. LAKIN, Department of Microbiology, Immunology and Pathology, College of Veterinary Medicine and Biomedical Sciences, Colorado State University, USA.; SHAUN R. COOK, Alberta Agricultural and forestry, Lethbridge, Canada.; ENRIQUE DOSTER, Department of Microbiology, Immunology and Pathology, College of Veterinary Medicine and Biomedical Sciences, Colorado State University, USA.; NOELLE R. NOYES, Veterinary Population Medicine Department, University of Minnesota, USA.; MAGGIE D. WEINROTH, Department of Animal Sciences, College of Agricultural Sciences, Colorado State University, USA.; XIANG YANG, Department of Animal Science, University of California, Davis, USA.; JENNIFER K. PARKER, Deparment of Molecular Biosciences, University of Florida, Gainesville, FL, USA.; CHRISTINA BOUCHER, Deparment of Computer and Information Science and Engineering, University of Florida, Gainessville, FL, USA.; CALVIN W. BOOKER, Feedlot Health Management Services, Okotoks, AB, Canada.; DALE R. WOEMER, Deparment of Animal and Food Sciences, College of Agricultural Sciences & Natural Resources, Texas University, TX, USA.; KEITH E. BELK, Department of Animal Sciences, College of Agricultural Sciences, Colorado State University, USA.; PAUL S. MORLEY, VERO, Veterinary Education, Research , and Outreach Program, Texas A&M University and West Texas A&M University, Canyon, TX, USA. |
|
Título : |
Characterization of the microbial resistome in conventional and "raised without antibiotics" beef and dairy production systems. |
|
Fecha de publicación : |
2019 |
|
Fuente / Imprenta : |
Frontier in Microbiology, September 2019. v. 10, article 1980, 11 p. OPEN ACCESS. |
|
DOI : |
10.3389/fmicb.2019.01980 |
|
Idioma : |
Inglés |
|
Notas : |
Received 18 March 2019 // Accepted 12 August 2019 // Published 4 September 2019. |
|
Contenido : |
Metagenomic investigations have the potential to provide unprecedented insights into microbial ecologies, such as those relating to antimicrobial resistance (AMR). We characterized the microbial resistome in livestock operations raising cattle conventionally (CONV) or without antibiotic exposures (RWA) using shotgun metagenomics. Samples of feces, wastewater from catchment basins, and soil where wastewater was applied were collected from CONV and RWA feedlot and dairy farms. After DNA extraction and sequencing, shotgun metagenomic reads were aligned to reference databases for identification of bacteria (Kraken) and antibiotic resistance genes (ARGs) accessions (MEGARes). Differences in microbial resistomes were found across farms with different production practices (CONV vs. RWA), types of cattle (beef vs. dairy), and types of sample (feces vs. wastewater vs. soil). Feces had the greatest number of ARGs per sample (mean = 118 and 79 in CONV and RWA, respectively), with tetracycline efflux pumps, macrolide phosphotransferases, and aminoglycoside nucleotidyltransferases mechanisms of resistance more abundant in CONV than in RWA feces. Tetracycline and macrolide-lincosamide-streptogramin classes of resistance were more abundant in feedlot cattle than in dairy cow feces, whereas the b-lactam class was more abundant in dairy cow feces. Lack of congruence between ARGs and microbial communities (procrustes analysis) suggested that other factors (e.g., location of farms, cattle source, management practices, diet, horizontal ARGs transfer, and co-selection of resistance), in addition to antimicrobial use, could have impacted resistome profiles. For that reason, we could not establish a cause-effect relationship between antimicrobial use and AMR, although ARGs in feces and effluents were associated with drug classes used to treat animals according to farms' records (tetracyclines and macrolides in feedlots, b-lactams in dairies), whereas ARGs in soil were dominated by multidrug resistance.
Characterization of the "resistance potential" of animal-derived and environmental samples is the first step toward incorporating metagenomic approaches into AMR surveillance in agricultural systems. Further research is needed to assess the publichealth risk associated with different microbial resistomes. MenosMetagenomic investigations have the potential to provide unprecedented insights into microbial ecologies, such as those relating to antimicrobial resistance (AMR). We characterized the microbial resistome in livestock operations raising cattle conventionally (CONV) or without antibiotic exposures (RWA) using shotgun metagenomics. Samples of feces, wastewater from catchment basins, and soil where wastewater was applied were collected from CONV and RWA feedlot and dairy farms. After DNA extraction and sequencing, shotgun metagenomic reads were aligned to reference databases for identification of bacteria (Kraken) and antibiotic resistance genes (ARGs) accessions (MEGARes). Differences in microbial resistomes were found across farms with different production practices (CONV vs. RWA), types of cattle (beef vs. dairy), and types of sample (feces vs. wastewater vs. soil). Feces had the greatest number of ARGs per sample (mean = 118 and 79 in CONV and RWA, respectively), with tetracycline efflux pumps, macrolide phosphotransferases, and aminoglycoside nucleotidyltransferases mechanisms of resistance more abundant in CONV than in RWA feces. Tetracycline and macrolide-lincosamide-streptogramin classes of resistance were more abundant in feedlot cattle than in dairy cow feces, whereas the b-lactam class was more abundant in dairy cow feces. Lack of congruence between ARGs and microbial communities (procrustes analysis) suggested that other factors (e.g., location of farms, cattle sour... Presentar Todo |
|
Palabras claves : |
ANTIBIOTIC RESISTANCE; CATTLE; CATTLE BEEF; DAIRY CATTLE; METAGENOMICA; METAGENOMICS; MICROBIOMA; MICROBIOME; RESISTENCIA A ANTIBIÓTICOS; RESISTOME. |
|
Thesagro : |
BOVINOS; BOVINOS DE CARNE; GANADO LECHERO. |
|
Asunto categoría : |
-- |
|
URL : |
http://www.ainfo.inia.uy/digital/bitstream/item/13237/1/Rovira-Front-microb-2019.pdf
|
|
Marc : |
LEADER 03681naa a2200457 a 4500
001 1060137
005 2021-03-16
008 2019 bl uuuu u00u1 u #d
024 7 $a10.3389/fmicb.2019.01980$2DOI
100 1 $aROVIRA, P.J.
245 $aCharacterization of the microbial resistome in conventional and "raised without antibiotics" beef and dairy production systems.$h[electronic resource]
260 $c2019
500 $aReceived 18 March 2019 // Accepted 12 August 2019 // Published 4 September 2019.
520 $aMetagenomic investigations have the potential to provide unprecedented insights into microbial ecologies, such as those relating to antimicrobial resistance (AMR). We characterized the microbial resistome in livestock operations raising cattle conventionally (CONV) or without antibiotic exposures (RWA) using shotgun metagenomics. Samples of feces, wastewater from catchment basins, and soil where wastewater was applied were collected from CONV and RWA feedlot and dairy farms. After DNA extraction and sequencing, shotgun metagenomic reads were aligned to reference databases for identification of bacteria (Kraken) and antibiotic resistance genes (ARGs) accessions (MEGARes). Differences in microbial resistomes were found across farms with different production practices (CONV vs. RWA), types of cattle (beef vs. dairy), and types of sample (feces vs. wastewater vs. soil). Feces had the greatest number of ARGs per sample (mean = 118 and 79 in CONV and RWA, respectively), with tetracycline efflux pumps, macrolide phosphotransferases, and aminoglycoside nucleotidyltransferases mechanisms of resistance more abundant in CONV than in RWA feces. Tetracycline and macrolide-lincosamide-streptogramin classes of resistance were more abundant in feedlot cattle than in dairy cow feces, whereas the b-lactam class was more abundant in dairy cow feces. Lack of congruence between ARGs and microbial communities (procrustes analysis) suggested that other factors (e.g., location of farms, cattle source, management practices, diet, horizontal ARGs transfer, and co-selection of resistance), in addition to antimicrobial use, could have impacted resistome profiles. For that reason, we could not establish a cause-effect relationship between antimicrobial use and AMR, although ARGs in feces and effluents were associated with drug classes used to treat animals according to farms' records (tetracyclines and macrolides in feedlots, b-lactams in dairies), whereas ARGs in soil were dominated by multidrug resistance. Characterization of the "resistance potential" of animal-derived and environmental samples is the first step toward incorporating metagenomic approaches into AMR surveillance in agricultural systems. Further research is needed to assess the publichealth risk associated with different microbial resistomes.
650 $aBOVINOS
650 $aBOVINOS DE CARNE
650 $aGANADO LECHERO
653 $aANTIBIOTIC RESISTANCE
653 $aCATTLE
653 $aCATTLE BEEF
653 $aDAIRY CATTLE
653 $aMETAGENOMICA
653 $aMETAGENOMICS
653 $aMICROBIOMA
653 $aMICROBIOME
653 $aRESISTENCIA A ANTIBIÓTICOS
653 $aRESISTOME
700 1 $aMCALLISTER, T.
700 1 $aLAKIN, S.M.
700 1 $aCOOK, S.R.
700 1 $aDOSTER, E.
700 1 $aNOYES, N. R.
700 1 $aWEINROTH, M.D.
700 1 $aYANG, X.
700 1 $aPARKER, J. K.
700 1 $aBOUCHER, C.
700 1 $aBOOKER, C. W.
700 1 $aWOENER, D. R.
700 1 $aBELK, K. E.
700 1 $aMORLEY, P. S.
773 $tFrontier in Microbiology, September 2019.$gv. 10, article 1980, 11 p. OPEN ACCESS.
Descargar
Esconder MarcPresentar Marc Completo |
|
Registro original : |
INIA Treinta y Tres (TT) |
|
|
Biblioteca
|
Identificación
|
Origen
|
Tipo / Formato
|
Clasificación
|
Cutter
|
Registro
|
Volumen
|
Estado
|
Volver
|
|
|
|
Registro completo
|
|
Biblioteca (s) : |
INIA Tacuarembó. |
|
Fecha actual : |
23/09/2016 |
|
Actualizado : |
23/09/2016 |
|
Tipo de producción científica : |
Abstracts/Resúmenes |
|
Autor : |
BASILE, P.; FORMOSO, D.; TISCORNIA, G.; BLUMETTO, O. |
|
Afiliación : |
PATRICIA CECILIA BASILE LORENZO, Universidad de la República (UdelaR)/ Centro Universitario Regional Tacuarembó; DANIEL FORMOSO CUNHA, INIA (Instituto Nacional de Investigación Agropecuaria), Uruguay; GUADALUPE TISCORNIA TOSAR, INIA (Instituto Nacional de Investigación Agropecuaria), Uruguay; OSCAR RICARDO BLUMETTO VELAZCO, INIA (Instituto Nacional de Investigación Agropecuaria), Uruguay. |
|
Título : |
Radiation use efficiency on campos graslands with contrasting grzing methods. [Resumen de poster]. |
|
Fecha de publicación : |
2016 |
|
Fuente / Imprenta : |
ln: Encuentro de Investigadores de la Región Noreste: Cerro Largo-Rivera-Tacuarembó, 1., 12 de agosto de 2016, Campus Interinstitucional de Tacuarembó, Tacuarembó. Libro de Resúmenes. Tacuarembó: UDELAR; INIA, 2016. |
|
Páginas : |
p. 64 |
|
Idioma : |
Inglés |
|
Contenido : |
Introduction: In Uruguay, the Basaltic region has de highest proportion of natural grasslands of the country. In this pastures, livestock management is the main reason of degradation of natural grasslands. Today, it's possible to estimate ANPP (Aboveground Net Primary Production) using remote sensing techniques. The RUE (Radiation Use Efficiency) is the effectiveness with which fPAR (fraction of Photosyntethically Active Radiation absorbed by plants) is transformed in ANPP and is known to vary according to temperature, precipitation and species composition. Objectives; The aims of this work were: a) to calibrate RUE and b) study the temporal variability
of RUE for two contrasting grazing methods. Materials & Methods: The study was conducted on five livestock farms located in the Basaltic region. In each site, two contrasting pastures with different historical grazing management (controlled vs continuous stocking rate) were selected. Data was collected between september 2013 and february 2015. RUE coefficient was estimated following Monteith equation: RUE= ANPP / APAR and APAR= fPAR x PAR. ANPP was estimated using the technique of regrowth in three exclusion cages. Biomass was cut at 1cm in boxes 20 x 50cm with shears every 45-50 days and was dried in forced air oven at 60 ° C. fPAR
was obtained as a function of ENVI images from MODIS sensor (US Geological Survey) and PAR was estimated from agro-climatic stations of INIA. RUE data were analyzed with a oneway ANOVA and the means were compared with T test for paired samples. Results: Between grazing methods, RUE average values were statistically different (p <0.05), with controlled management reporting values above 44%. When analysing seasonal variation between grazing methods, there were no statistical differences in RUE values. Seasonal variation of RUE for each grazing methods separately, was significantly different within seasons (p <0.05). Conclusions: The RUE values obtained could be used in the estimation of a more accurately ANPP in natural grasslands of this region. MenosIntroduction: In Uruguay, the Basaltic region has de highest proportion of natural grasslands of the country. In this pastures, livestock management is the main reason of degradation of natural grasslands. Today, it's possible to estimate ANPP (Aboveground Net Primary Production) using remote sensing techniques. The RUE (Radiation Use Efficiency) is the effectiveness with which fPAR (fraction of Photosyntethically Active Radiation absorbed by plants) is transformed in ANPP and is known to vary according to temperature, precipitation and species composition. Objectives; The aims of this work were: a) to calibrate RUE and b) study the temporal variability
of RUE for two contrasting grazing methods. Materials & Methods: The study was conducted on five livestock farms located in the Basaltic region. In each site, two contrasting pastures with different historical grazing management (controlled vs continuous stocking rate) were selected. Data was collected between september 2013 and february 2015. RUE coefficient was estimated following Monteith equation: RUE= ANPP / APAR and APAR= fPAR x PAR. ANPP was estimated using the technique of regrowth in three exclusion cages. Biomass was cut at 1cm in boxes 20 x 50cm with shears every 45-50 days and was dried in forced air oven at 60 ° C. fPAR
was obtained as a function of ENVI images from MODIS sensor (US Geological Survey) and PAR was estimated from agro-climatic stations of INIA. RUE data were analyzed with a oneway ANOVA and the mea... Presentar Todo |
|
Palabras claves : |
GRASSLAND PRODUCTIVITY; LIVESTOCK MANAGEMENT; PPNA. |
|
Thesagro : |
PASTURAS. |
|
Asunto categoría : |
P30 Ciencia del suelo y manejo del suelo |
|
URL : |
http://www.ainfo.inia.uy/digital/bitstream/item/6099/1/PAGINA-64.pdf
|
|
Marc : |
LEADER 02852naa a2200217 a 4500
001 1055722
005 2016-09-23
008 2016 bl uuuu u00u1 u #d
100 1 $aBASILE, P.
245 $aRadiation use efficiency on campos graslands with contrasting grzing methods. [Resumen de poster].$h[electronic resource]
260 $c2016
300 $ap. 64
520 $aIntroduction: In Uruguay, the Basaltic region has de highest proportion of natural grasslands of the country. In this pastures, livestock management is the main reason of degradation of natural grasslands. Today, it's possible to estimate ANPP (Aboveground Net Primary Production) using remote sensing techniques. The RUE (Radiation Use Efficiency) is the effectiveness with which fPAR (fraction of Photosyntethically Active Radiation absorbed by plants) is transformed in ANPP and is known to vary according to temperature, precipitation and species composition. Objectives; The aims of this work were: a) to calibrate RUE and b) study the temporal variability of RUE for two contrasting grazing methods. Materials & Methods: The study was conducted on five livestock farms located in the Basaltic region. In each site, two contrasting pastures with different historical grazing management (controlled vs continuous stocking rate) were selected. Data was collected between september 2013 and february 2015. RUE coefficient was estimated following Monteith equation: RUE= ANPP / APAR and APAR= fPAR x PAR. ANPP was estimated using the technique of regrowth in three exclusion cages. Biomass was cut at 1cm in boxes 20 x 50cm with shears every 45-50 days and was dried in forced air oven at 60 ° C. fPAR was obtained as a function of ENVI images from MODIS sensor (US Geological Survey) and PAR was estimated from agro-climatic stations of INIA. RUE data were analyzed with a oneway ANOVA and the means were compared with T test for paired samples. Results: Between grazing methods, RUE average values were statistically different (p <0.05), with controlled management reporting values above 44%. When analysing seasonal variation between grazing methods, there were no statistical differences in RUE values. Seasonal variation of RUE for each grazing methods separately, was significantly different within seasons (p <0.05). Conclusions: The RUE values obtained could be used in the estimation of a more accurately ANPP in natural grasslands of this region.
650 $aPASTURAS
653 $aGRASSLAND PRODUCTIVITY
653 $aLIVESTOCK MANAGEMENT
653 $aPPNA
700 1 $aFORMOSO, D.
700 1 $aTISCORNIA, G.
700 1 $aBLUMETTO, O.
773 $tln: Encuentro de Investigadores de la Región Noreste: Cerro Largo-Rivera-Tacuarembó, 1., 12 de agosto de 2016, Campus Interinstitucional de Tacuarembó, Tacuarembó. Libro de Resúmenes. Tacuarembó: UDELAR; INIA, 2016.
Descargar
Esconder MarcPresentar Marc Completo |
|
Registro original : |
INIA Tacuarembó (TBO) |
|
|
Biblioteca
|
Identificación
|
Origen
|
Tipo / Formato
|
Clasificación
|
Cutter
|
Registro
|
Volumen
|
Estado
|
Volver
|
| Expresión de búsqueda válido. Check! |
|
|
