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Registro completo
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Biblioteca (s) : |
INIA La Estanzuela. |
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Fecha : |
12/07/2022 |
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Actualizado : |
30/11/2022 |
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Tipo de producción científica : |
Artículos en Revistas Indexadas Internacionales |
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Autor : |
LOZANO, J.; FERNÁNDEZ-CIGANDA, S.; GONZÁLEZ REVELLO, A.; HIRIGOYEN, D.; MARTÍNEZ, M.; SCORZA, C.; ZUNINO, P. |
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Afiliación : |
JOAQUIN LOZANO, Department of Microbiology, Instituto de Investigaciones Biológicas Clemente Estable, Montevideo, Uruguay.; SOFÍA FERNÁNDEZ-CIGANDA, INIA (Instituto Nacional de Investigación Agropecuaria), Uruguay./ Department of Microbiology, Instituto de Investigaciones Biológicas Clemente Estable, Montevideo, Uruguay.; ÁLVARO GONZÁLEZ REVELLO, Department of Food Science and Technology, Facultad de Veterinaria, UdelaR, Montevideo, Uruguay.; DARÍO JAVIER HIRIGOYEN TREVIN, INIA (Instituto Nacional de Investigación Agropecuaria), Uruguay; MARCELA MARTÍNEZ, Analytical Platform, Instituto de Investigaciones Biológicas Clemente Estable, Montevideo, Uruguay.; CECILIA SCORZA, Department of Experimental Neuropharmacology, Instituto de Investigaciones Biológicas Clemente Estable, Montevideo, Uruguay.; PABLO ZUNINO, Department of Microbiology, Instituto de Investigaciones Biológicas Clemente Estable, Montevideo, Uruguay. |
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Título : |
Probiotic potential of GABA-producing lactobacilli isolated from Uruguayan artisanal cheese starter cultures. |
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Fecha de publicación : |
2022 |
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Fuente / Imprenta : |
Journal of Microbiology, 2022, volume 133, issue 3, pages 1610-1619. doi: https://doi.org/10.1111/jam.15664 |
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ISSN : |
1364-5072 |
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DOI : |
10.1111/jam.15664 |
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Idioma : |
Inglés |
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Notas : |
Article history: Received 18 March 2022; Revised 5 May 2022; Accepted 6 June 2022; Published online September 2022. -- Corresponding author: Zunino, P.; Department of Microbiology, Instituto de Investigaciones Biológicas Clemente Estable, Montevideo, Uruguay; email:pzunino@iibce.edu.uy -- |
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Contenido : |
Abstract: Aims: In this study, we sought to identify and characterize a collection of 101 lactobacilli strains isolated from natural whey starters used in Uruguayan artisan cheese production, based on their capacity to produce gamma-aminobutyric acid (GABA) and their probiotic potential. Methods and Results: The probiotic potential was assessed using low pH and bile salt resistance assays; bacterial adhesion to intestinal mucus was also evaluated. Selected strains were then identified by 16S sequencing, and their GABA-producing potential was confirmed and quantified using a UHPLC-MS system. Twenty-five strains were identified and characterized as GABA-producing lactobacilli belonging to the phylogenetical groups Lactiplantibacillus (n =19) and Lacticaseibacillus (n =6). Fifteen strains of the Lactiplantibacillus group showed a significantly higher GABA production than the rest. They showed the predicted ability to survive the passage through the gastrointestinal tract, according to the in vitro assays. Conclusions: A set of promising candidate strains was identified as potential probiotics with action on the gut-brain axis. Further studies are needed to assess their possible effects on behaviour using in vivo assay. Significance and Impact of the Study: This study shows the potential of strains isolated from local natural whey starters as probiotics and for biotechnological use in functional GABA-enriched foods formulation. © 2022 Society for Applied Microbiology. |
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Palabras claves : |
Fermented foods; Gut-brain axis; Lactic acid bacteria; Lactiplantibacilus; PLATAFORMA DE INVESTIGACIÓN EN SALUD ANIMAL; PLATAFORMA DE SALUD ANIMAL; Probiotics. |
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Asunto categoría : |
L10 Genética y mejoramiento animal |
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Marc : |
LEADER 02779naa a2200313 a 4500
001 1063420
005 2022-11-30
008 2022 bl uuuu u00u1 u #d
022 $a1364-5072
024 7 $a10.1111/jam.15664$2DOI
100 1 $aLOZANO, J.
245 $aProbiotic potential of GABA-producing lactobacilli isolated from Uruguayan artisanal cheese starter cultures.$h[electronic resource]
260 $c2022
500 $aArticle history: Received 18 March 2022; Revised 5 May 2022; Accepted 6 June 2022; Published online September 2022. -- Corresponding author: Zunino, P.; Department of Microbiology, Instituto de Investigaciones Biológicas Clemente Estable, Montevideo, Uruguay; email:pzunino@iibce.edu.uy --
520 $aAbstract: Aims: In this study, we sought to identify and characterize a collection of 101 lactobacilli strains isolated from natural whey starters used in Uruguayan artisan cheese production, based on their capacity to produce gamma-aminobutyric acid (GABA) and their probiotic potential. Methods and Results: The probiotic potential was assessed using low pH and bile salt resistance assays; bacterial adhesion to intestinal mucus was also evaluated. Selected strains were then identified by 16S sequencing, and their GABA-producing potential was confirmed and quantified using a UHPLC-MS system. Twenty-five strains were identified and characterized as GABA-producing lactobacilli belonging to the phylogenetical groups Lactiplantibacillus (n =19) and Lacticaseibacillus (n =6). Fifteen strains of the Lactiplantibacillus group showed a significantly higher GABA production than the rest. They showed the predicted ability to survive the passage through the gastrointestinal tract, according to the in vitro assays. Conclusions: A set of promising candidate strains was identified as potential probiotics with action on the gut-brain axis. Further studies are needed to assess their possible effects on behaviour using in vivo assay. Significance and Impact of the Study: This study shows the potential of strains isolated from local natural whey starters as probiotics and for biotechnological use in functional GABA-enriched foods formulation. © 2022 Society for Applied Microbiology.
653 $aFermented foods
653 $aGut-brain axis
653 $aLactic acid bacteria
653 $aLactiplantibacilus
653 $aPLATAFORMA DE INVESTIGACIÓN EN SALUD ANIMAL
653 $aPLATAFORMA DE SALUD ANIMAL
653 $aProbiotics
700 1 $aFERNÁNDEZ-CIGANDA, S.
700 1 $aGONZÁLEZ REVELLO, A.
700 1 $aHIRIGOYEN, D.
700 1 $aMARTÍNEZ, M.
700 1 $aSCORZA, C.
700 1 $aZUNINO, P.
773 $tJournal of Microbiology, 2022, volume 133, issue 3, pages 1610-1619. doi: https://doi.org/10.1111/jam.15664
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| Acceso al texto completo restringido a Biblioteca INIA La Estanzuela. Por información adicional contacte bib_le@inia.org.uy. |
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Registro completo
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Biblioteca (s) : |
INIA La Estanzuela. |
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Fecha actual : |
12/12/2017 |
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Actualizado : |
12/12/2017 |
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Tipo de producción científica : |
Trabajos en Congresos/Conferencias |
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Autor : |
LADO, B.; BATTENFIELD, S.; SILVA, P.; QUINCKE, M.; GUZMAN, C.; SINGH, R.P.; DREISIGACKER, S.; PEÑA, J.; FRITZ, A.; POLAND, J.; GUTIERREZ, L. |
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Afiliación : |
BETTINA LADO, Facultad de Agronomía, Universidad de la República, Montevideo, Uruguay.; SARAH BATTENFIELD, AgriPro Wheat, Syngenta, 11783 Ascher Rd. Junction City, KS, 66441, USA.; MARIA PAULA SILVA VILLELLA, INIA (Instituto Nacional de Investigación Agropecuaria), Uruguay; MARTIN CONRADO QUINCKE WALDEN, INIA (Instituto Nacional de Investigación Agropecuaria), Uruguay; CARLOS GUZMAN, CIMMYT, El Batan, Mexico, Mexico.; RAVI P. SINGH, CIMMYT, El Batan, Mexico, Mexico.; SUSANNE DREISIGACKER, CIMMYT, El Batan, Mexico, Mexico.; JAVIER PEÑA, CIMMYT, El Batan, Mexico, Mexico.; ALLAN FRITZ, Wheat Genetics Resource Center, Department of Plant Pathology, 1712 Claflin Rd., Kansas State University, Manhattan, KS 66506, USA; .; JESSE POLAND, Wheat Genetics Resource Center, Department of Plant Pathology, 1712 Claflin Rd., Kansas State University, Manhattan, KS 66506, USA.; LUCIA GUTIERREZ, Department of Agronomy, University of Wisconsin, 1575 Linden Dr., Madison, WI 53706, USA. |
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Título : |
Comparing strategies to select crosses using genomic prediction in two wheat breeding programs. |
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Fecha de publicación : |
2017 |
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Fuente / Imprenta : |
In: International Wheat Genetics Symposium, 12, Tulln, Austria; April 23-28, 2017; BOKU: University of Natural Resources and Life Sciences, Vienna, Austria. |
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Páginas : |
p.88-90. |
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Idioma : |
Español |
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Contenido : |
Key message: Evaluation of crosses prediction methods with and without accounting for progeny variance. Mid-parent values was a much larger factor determining genetic gain than increasing the progeny variance of a cross.
In wheat breeding programs, a critical decision is to determine crosses that have high probability to deliver progenies with higher genetics gains (Zhong & Jannink 2007, Bernardo 2014). We present an application of genomic models for predicting parental cross combinations for grain yield, grain protein, and loaf volume across two wheat-breeding programs, INIA-Uruguay and CIMMYT. We evaluated three methods for selecting the ?best? crosses based on (1) mid-parents, (2) top 10% of the progeny within a cross, and (3) maximizing mean and variance within progeny using thresholds. The last two methods were evaluated with the predicted variances obtained through progeny simulation using the PopVar (Mohammadi et al. 2015, Tiede et al. 2015) package in R software. The first two methods showed 82% of crosses in common for yield, 55% for loaf volume and 53% for grain protein, even though only the second method accounts for the variance of the progeny (Figure 1). While the expected variance of the progeny is important to increase chances of finding superior individuals from transgressive segregation, we observed that the mid-parent values of the crosses selected was a much larger factor determining genetic gain than increasing the progeny variance of a cross (Figure 2). Overall, the genomic resources and the statistical models are now available to plant breeders to predict both the performance of breeding lines per se as well as the value of progeny from any potential crosses, but further understanding on optimizing the cross combinations is needed. MenosKey message: Evaluation of crosses prediction methods with and without accounting for progeny variance. Mid-parent values was a much larger factor determining genetic gain than increasing the progeny variance of a cross.
In wheat breeding programs, a critical decision is to determine crosses that have high probability to deliver progenies with higher genetics gains (Zhong & Jannink 2007, Bernardo 2014). We present an application of genomic models for predicting parental cross combinations for grain yield, grain protein, and loaf volume across two wheat-breeding programs, INIA-Uruguay and CIMMYT. We evaluated three methods for selecting the ?best? crosses based on (1) mid-parents, (2) top 10% of the progeny within a cross, and (3) maximizing mean and variance within progeny using thresholds. The last two methods were evaluated with the predicted variances obtained through progeny simulation using the PopVar (Mohammadi et al. 2015, Tiede et al. 2015) package in R software. The first two methods showed 82% of crosses in common for yield, 55% for loaf volume and 53% for grain protein, even though only the second method accounts for the variance of the progeny (Figure 1). While the expected variance of the progeny is important to increase chances of finding superior individuals from transgressive segregation, we observed that the mid-parent values of the crosses selected was a much larger factor determining genetic gain than increasing the progeny variance of a cross (Figure 2)... Presentar Todo |
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Palabras claves : |
WHEAT BREEDING PROGRAMS; WHEAT QUALITY. |
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Thesagro : |
MEJORAMIENTO GENETICO DE PLANTAS; TRIGO. |
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Asunto categoría : |
F30 Genética vegetal y fitomejoramiento |
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Marc : |
LEADER 02689nam a2200289 a 4500
001 1057873
005 2017-12-12
008 2017 bl uuuu u01u1 u #d
100 1 $aLADO, B.
245 $aComparing strategies to select crosses using genomic prediction in two wheat breeding programs.
260 $aIn: International Wheat Genetics Symposium, 12, Tulln, Austria; April 23-28, 2017; BOKU: University of Natural Resources and Life Sciences, Vienna, Austria.$c2017
300 $ap.88-90.
520 $aKey message: Evaluation of crosses prediction methods with and without accounting for progeny variance. Mid-parent values was a much larger factor determining genetic gain than increasing the progeny variance of a cross. In wheat breeding programs, a critical decision is to determine crosses that have high probability to deliver progenies with higher genetics gains (Zhong & Jannink 2007, Bernardo 2014). We present an application of genomic models for predicting parental cross combinations for grain yield, grain protein, and loaf volume across two wheat-breeding programs, INIA-Uruguay and CIMMYT. We evaluated three methods for selecting the ?best? crosses based on (1) mid-parents, (2) top 10% of the progeny within a cross, and (3) maximizing mean and variance within progeny using thresholds. The last two methods were evaluated with the predicted variances obtained through progeny simulation using the PopVar (Mohammadi et al. 2015, Tiede et al. 2015) package in R software. The first two methods showed 82% of crosses in common for yield, 55% for loaf volume and 53% for grain protein, even though only the second method accounts for the variance of the progeny (Figure 1). While the expected variance of the progeny is important to increase chances of finding superior individuals from transgressive segregation, we observed that the mid-parent values of the crosses selected was a much larger factor determining genetic gain than increasing the progeny variance of a cross (Figure 2). Overall, the genomic resources and the statistical models are now available to plant breeders to predict both the performance of breeding lines per se as well as the value of progeny from any potential crosses, but further understanding on optimizing the cross combinations is needed.
650 $aMEJORAMIENTO GENETICO DE PLANTAS
650 $aTRIGO
653 $aWHEAT BREEDING PROGRAMS
653 $aWHEAT QUALITY
700 1 $aBATTENFIELD, S.
700 1 $aSILVA, P.
700 1 $aQUINCKE, M.
700 1 $aGUZMAN, C.
700 1 $aSINGH, R.P.
700 1 $aDREISIGACKER, S.
700 1 $aPEÑA, J.
700 1 $aFRITZ, A.
700 1 $aPOLAND, J.
700 1 $aGUTIERREZ, L.
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