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3. Addressing global ruminant agricultural challenges through understanding the rumen microbiome: Past, present, and future

Author

European Commission, Ministerio de Economía y Competitividad (España), Biotechnology and Biological Sciences Research Council (UK), Huws, Sharon A., Creevey, C. J., Oyama, L. B., Mizrahi, I., Denman, Stuart E., Popova, M., Muñoz-Tamayo, R., Forano, E., Waters, S. M., Hess, M., Tapio, I., Smidt, H., Krizsan, S. J., Yáñez Ruiz, David R., Belanche, A., Guan, L., Gruninger, R. J., McAllister, T. A., Newbold, C. Jamie, Roehe, R., Dewhurst, R. J., Snelling, T. J., Watson, M., Suen, G., Hart, E. H., Kingston-Smith, Alison H., Scollan, N. D., Do Prado, R. M., Pilau, E. J., Mantovani, H. C., Attwood, G. T., Edwards, J. E., McEwan, Neil R., Morrisson, S., Mayorga, O. L., Elliott, C., Morgavi, Diego P., European Commission, Ministerio de Economía y Competitividad (España), Biotechnology and Biological Sciences Research Council (UK), Huws, Sharon A., Creevey, C. J., Oyama, L. B., Mizrahi, I., Denman, Stuart E., Popova, M., Muñoz-Tamayo, R., Forano, E., Waters, S. M., Hess, M., Tapio, I., Smidt, H., Krizsan, S. J., Yáñez Ruiz, David R., Belanche, A., Guan, L., Gruninger, R. J., McAllister, T. A., Newbold, C. Jamie, Roehe, R., Dewhurst, R. J., Snelling, T. J., Watson, M., Suen, G., Hart, E. H., Kingston-Smith, Alison H., Scollan, N. D., Do Prado, R. M., Pilau, E. J., Mantovani, H. C., Attwood, G. T., Edwards, J. E., McEwan, Neil R., Morrisson, S., Mayorga, O. L., Elliott, C., and Morgavi, Diego P.

Abstract

The rumen is a complex ecosystem composed of anaerobic bacteria, protozoa, fungi, methanogenic archaea and phages. These microbes interact closely to breakdown plant material that cannot be digested by humans, whilst providing metabolic energy to the host and, in the case of archaea, producing methane. Consequently, ruminants produce meat and milk, which are rich in high-quality protein, vitamins and minerals, and therefore contribute to food security. As the world population is predicted to reach approximately 9.7 billion by 2050, an increase in ruminant production to satisfy global protein demand is necessary, despite limited land availability, and whilst ensuring environmental impact is minimized. Although challenging, these goals can be met, but depend on our understanding of the rumen microbiome. Attempts to manipulate the rumen microbiome to benefit global agricultural challenges have been ongoing for decades with limited success, mostly due to the lack of a detailed understanding of this microbiome and our limited ability to culture most of these microbes outside the rumen. The potential to manipulate the rumen microbiome and meet global livestock challenges through animal breeding and introduction of dietary interventions during early life have recently emerged as promising new technologies. Our inability to phenotype ruminants in a high-throughput manner has also hampered progress, although the recent increase in >omic> data may allow further development of mathematical models and rumen microbial gene biomarkers as proxies. Advances in computational tools, high-throughput sequencing technologies and cultivation-independent >omics> approaches continue to revolutionize our understanding of the rumen microbiome. This will ultimately provide the knowledge framework needed to solve current and future ruminant livestock challenges.

Published
2018

4. Rumen microbial community composition varies with diet and host, but a core microbiome is found across a wide geographical range

Author

Henderson, G., Cox, F., Ganesh, S., Jonker, A., Young, W., Janssen, P. H., Abecia, Leticia, Angarita, E., Aravena, P., Arenas, G. N., Ariza, C., Kelly, W. J., Guan, L. L., Miri, V. H., Hernandez-Sanabria, E., Gomez, A. X. I., Isah, O. A., Ishaq, S., Kim, S.-H., Klieve, A., Kobayashi, Y., Parra, D., Koike, S., Kopecny, J., Kristensen, T. N., O'Neill, B., Krizsan, S. J., LaChance, H., Lachman, M., Lamberson, W. R., Lambie, S., Lassen, J., Muñoz, C., Leahy, S. C., Lee, S. S., Leiber, F., Lewis, E., Ospina, S., Lin, B., Lira, R., Lund, P., Macipe, E., Mamuad, L. L., Murovec, B., Mantovani, H. C., Marcoppido, G. A., Márquez, C., Martin, C., Martínez-Fernández, Gonzalo, Ouwerkerk, D., Martínez, M. E., Mayorga, O. L., McAllister, T. A., McSweeney, C., Newbold, C. Jamie, Mestre, L., Minnee, E., Mitsumori, M., Mizrahi, I., Molina, I., Muenger, A., Nsereko, V., O'Donovan, M., Okunade, S., Pereira, L. G. R., Pinares-Patino, C., Pope, P. B., Bannink, A., Poulsen, M., Rodehutscord, M., Rodriguez, T., Attwood, G. T., Saito, K., Sales, F., Sauer, C., Shingfield, K. J., Shoji, N., Simunek, J., Zambrano, R., Stojanović -Radić, Z., Stres, B., Sun, X., Swartz, J., Ávila, J. M., Tan, Z. L., Tapio, I., Taxis, T. M., Tomkins, N., Ungerfeld, E., Zeitz, J., Valizadeh, R., Van Adrichem, P., van Hamme, J., Van Hoven, W., Waghorn, G., Avila-Stagno, J., Wallace, R. J., Wang, M., Waters, S. M., Keogh, K., Zhou, M., Witzig, M., Wright, A.-D. G., Yamano, H., Yan, T., Yáñez Ruiz, David R., Yeoman, C. J., Zhou, H. W., Zou, C. X., Zunino, P., Barahona, R., Batistotti, M., Bertelsen, M. F., Jami, E., Brown-Kav, A., Carvajal, A. M., Cersosimo, L., Chaves, A. V., Church, J., Clipson, N., Cobos-Peralta, M. A., Cookson, A. L., Cravero, S., Carballo, O. C., Jelincic, J., Crosley, K., Cruz, Gustavo, Cucchi, M. C., De La Barra, R., De Menezes, A. B., Detmann, E., Dieho, K., Dijkstra, J., Dos Reis, W. L. S., Dugan, M. E. R., Kantanen, J., Ebrahimi, S. H., Eythórsdóttir, E., Fon, F. N., Fraga, M., Franco, F., Friedeman, C., Fukuma, N., Gagić , D., Gangnat, I., Grilli, D. J., European Commission, and De Menezes, AB

Subjects
DNA, Bacterial, Rumen, animal structures, Animal Nutrition, Microorganism, Article, 03 medical and health sciences, Species Specificity, Ruminant, Butyrivibrio, Animals, DNA Barcoding, Taxonomic, Life Science, Microbiome, Phylogeny, 030304 developmental biology, 2. Zero hunger, 0303 health sciences, Multidisciplinary, Bacteria, Geography, biology, 030306 microbiology, Host (biology), Ecology, Genetic Variation, Ruminants, Sequence Analysis, DNA, DNA, Protozoan, 15. Life on land, biology.organism_classification, Archaea, Diervoeding, Diet, Gastrointestinal Microbiome, DNA, Archaeal, Microbial population biology, 13. Climate action, Host-Pathogen Interactions, WIAS, Erratum
Abstract

© 2015 Macmillan Publishers Limited. Ruminant livestock are important sources of human food and global greenhouse gas emissions. Feed degradation and methane formation by ruminants rely on metabolic interactions between rumen microbes and affect ruminant productivity. Rumen and camelid foregut microbial community composition was determined in 742 samples from 32 animal species and 35 countries, to estimate if this was influenced by diet, host species, or geography. Similar bacteria and archaea dominated in nearly all samples, while protozoal communities were more variable. The dominant bacteria are poorly characterised, but the methanogenic archaea are better known and highly conserved across the world. This universality and limited diversity could make it possible to mitigate methane emissions by developing strategies that target the few dominant methanogens. Differences in microbial community compositions were predominantly attributable to diet, with the host being less influential. There were few strong co-occurrence patterns between microbes, suggesting that major metabolic interactions are non-selective rather than specific., We thank Ron Ronimus, Paul Newton, and Christina Moon for reading and commenting on the manuscript. We thank all who provided assistance that allowed Global Rumen Census collaborators to supply samples and metadata (Supplemental Text 1). AgResearch was funded by the New Zealand Government as part of its support for the Global Research Alliance on Agricultural Greenhouse Gases. The following funding sources allowed Global Rumen Census collaborators to supply samples and metadata, listed with the primary contact(s) for each funding source: Agencia Nacional de Investigación e Innovación, Martín Fraga; Alberta Livestock and Meat Agency, Canada, Tim A. McAllister; Area de Ciencia y Técnica, Universidad Juan A Maza (Resolución Proy. N° 508/2012), Diego Javier Grilli; Canada British Columbia Ranching Task Force Funding Initiative, John Church; CNPq, Hilário Cuquetto Mantovani, Luiz Gustavo Ribeiro Pereira; FAPEMIG, Hilário Cuquetto Mantovani; FAPEMIG, PECUS RumenGases, Luiz Gustavo Ribeiro Pereira; Cooperative Research Program for Agriculture Science & Technology Development (project number PJ010906), Rural Development Administration, Republic of Korea, Sang-Suk Lee; Dutch Dairy Board & Product Board Animal Feed, André Bannink, Kasper Dieho, Jan Dijkstra; Ferdowsi University of Mashhad, Vahideh Heidarian Miri; Finnish Ministry of Agriculture and Forestry, Ilma Tapio; Instituto Nacional de Tecnología Agropecuaria, Argentina (Project PNBIO1431044), Silvio Cravero, María Cerón Cucchi; Irish Department of Agriculture, Fisheries and Food, Alexandre B. De Menezes; Meat & Livestock Australia; and Department of Agriculture, Fisheries & Forestry (Australian Government), Chris McSweeney; Ministerio de Agricultura y desarrollo sostenible (Colombia), Olga Lucía Mayorga; Montana Agricultural Experiment Station project (MONB00113), Carl Yeoman; Multistate project W-3177 Enhancing the competitiveness of US beef (MONB00195), Carl Yeoman; NSW Stud Merino Breeders’ Association, Alexandre Vieira Chaves; Queensland Enteric Methane Hub, Diane Ouwerkerk; RuminOmics, Jan Kopecny, Ilma Tapio; Rural and Environment Science and Analytical Services Division (RESAS) of the Scottish Government and the Technology Strategy Board, UK, R. John Wallace; Science Foundation Ireland (09/RFP/GEN2447), Sinead Waters; Secretaría de Agricultura, Ganadería, Desarrollo Rural, Pesca y Alimentación, Mario A. Cobos-Peralta; Slovenian Research Agency (project number J1-6732 and P4-0097), Blaz Stres; Strategic Priority Research Program, Climate Change: Carbon Budget and Relevant Issues (Grant No.XDA05020700), ZhiLiang Tan; The European Research Commission Starting Grant Fellowship (336355—MicroDE), Phil B. Pope; The Independent Danish Research Council (project number 4002-00036), Torsten Nygaard Kristensen; and The Independent Danish Research Council (Technology and Production, project number 11-105913), Jan Lassen. These funders had no role in study design, data collection and analysis, decision to publish, or preparation of the manuscript.

Published
2015
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5. Rumen microbial community composition varies with diet and host, but a core microbiome is found across a wide geographical range

Author

European Commission, Henderson, G., Cox, F., Ganesh, S., Jonker, A., Young, W., Janssen, P. H., Abecia, Leticia, Angarita, E., Aravena, P., Arenas, G. N., Ariza, C., Zhou, M., Witzig, M., Wright, A.-D. G., Yamano, H., Yan, T., Yáñez Ruiz, David R., Yeoman, C. J., Zhou, H. W., Zou, C. X., Zunino, P., Kelly, W. J., Barahona, R., Batistotti, M., Bertelsen, M. F., Jami, E., Brown-Kav, A., Carvajal, A. M., Cersosimo, L., Chaves, A. V., Church, J., Clipson, N., Guan, L. L., Cobos-Peralta, M. A., Cookson, A. L., Cravero, S., Carballo, O. C., Jelincic, J., Crosley, K., Cruz, Gustavo, Cucchi, M. C., De La Barra, R., De Menezes, A. B., Miri, V. H., Detmann, E., Dieho, K., Dijkstra, J., Dos Reis, W. L. S., Dugan, M. E. R., Kantanen, J., Ebrahimi, S. H., Eythórsdóttir, E., Fon, F. N., Fraga, M., Hernandez-Sanabria, E., Franco, F., Friedeman, C., Fukuma, N., Gagić , D., Gangnat, I., Grilli, D. J., Gomez, A. X. I., Isah, O. A., Ishaq, S., Kim, S.-H., Klieve, A., Kobayashi, Y., Parra, D., Koike, S., Kopecny, J., Kristensen, T. N., O'Neill, B., Krizsan, S. J., LaChance, H., Lachman, M., Lamberson, W. R., Lambie, S., Lassen, J., Muñoz, C., Leahy, S. C., Lee, S. S., Leiber, F., Lewis, E., Ospina, S., Lin, B., Lira, R., Lund, P., Macipe, E., Mamuad, L. L., Murovec, B., Mantovani, H. C., Marcoppido, G. A., Márquez, C., Martín, C., Martínez-Fernández, Gonzalo, Ouwerkerk, D., Martínez, M. E., Mayorga, O. L., McAllister, T. A., McSweeney, C., Newbold, C. Jamie, Mestre, L., Minnee, E., Mitsumori, M., Mizrahi, I., Molina, I., Muenger, A., Nsereko, V., O'Donovan, M., Okunade, S., Pereira, L. G. R., Pinares-Patino, C., Pope, P. B., Bannink, A., Poulsen, M., Rodehutscord, M., Rodríguez, T., Attwood, G. T., Saito, K., Sales, F., Sauer, C., Shingfield, K. J., Shoji, N., Simunek, J., Zambrano, R., Stojanović -Radić, Z., Stres, B., Sun, X., Swartz, J., Ávila, J. M., Tan, Z. L., Tapio, I., Taxis, T. M., Tomkins, N., Ungerfeld, E., Zeitz, J., Valizadeh, R., Van Adrichem, P., van Hamme, J., Van Hoven, W., Waghorn, G., Avila-Stagno, J., Wallace, R. J., Wang, M., Waters, S. M., Keogh, K., European Commission, Henderson, G., Cox, F., Ganesh, S., Jonker, A., Young, W., Janssen, P. H., Abecia, Leticia, Angarita, E., Aravena, P., Arenas, G. N., Ariza, C., Zhou, M., Witzig, M., Wright, A.-D. G., Yamano, H., Yan, T., Yáñez Ruiz, David R., Yeoman, C. J., Zhou, H. W., Zou, C. X., Zunino, P., Kelly, W. J., Barahona, R., Batistotti, M., Bertelsen, M. F., Jami, E., Brown-Kav, A., Carvajal, A. M., Cersosimo, L., Chaves, A. V., Church, J., Clipson, N., Guan, L. L., Cobos-Peralta, M. A., Cookson, A. L., Cravero, S., Carballo, O. C., Jelincic, J., Crosley, K., Cruz, Gustavo, Cucchi, M. C., De La Barra, R., De Menezes, A. B., Miri, V. H., Detmann, E., Dieho, K., Dijkstra, J., Dos Reis, W. L. S., Dugan, M. E. R., Kantanen, J., Ebrahimi, S. H., Eythórsdóttir, E., Fon, F. N., Fraga, M., Hernandez-Sanabria, E., Franco, F., Friedeman, C., Fukuma, N., Gagić , D., Gangnat, I., Grilli, D. J., Gomez, A. X. I., Isah, O. A., Ishaq, S., Kim, S.-H., Klieve, A., Kobayashi, Y., Parra, D., Koike, S., Kopecny, J., Kristensen, T. N., O'Neill, B., Krizsan, S. J., LaChance, H., Lachman, M., Lamberson, W. R., Lambie, S., Lassen, J., Muñoz, C., Leahy, S. C., Lee, S. S., Leiber, F., Lewis, E., Ospina, S., Lin, B., Lira, R., Lund, P., Macipe, E., Mamuad, L. L., Murovec, B., Mantovani, H. C., Marcoppido, G. A., Márquez, C., Martín, C., Martínez-Fernández, Gonzalo, Ouwerkerk, D., Martínez, M. E., Mayorga, O. L., McAllister, T. A., McSweeney, C., Newbold, C. Jamie, Mestre, L., Minnee, E., Mitsumori, M., Mizrahi, I., Molina, I., Muenger, A., Nsereko, V., O'Donovan, M., Okunade, S., Pereira, L. G. R., Pinares-Patino, C., Pope, P. B., Bannink, A., Poulsen, M., Rodehutscord, M., Rodríguez, T., Attwood, G. T., Saito, K., Sales, F., Sauer, C., Shingfield, K. J., Shoji, N., Simunek, J., Zambrano, R., Stojanović -Radić, Z., Stres, B., Sun, X., Swartz, J., Ávila, J. M., Tan, Z. L., Tapio, I., Taxis, T. M., Tomkins, N., Ungerfeld, E., Zeitz, J., Valizadeh, R., Van Adrichem, P., van Hamme, J., Van Hoven, W., Waghorn, G., Avila-Stagno, J., Wallace, R. J., Wang, M., Waters, S. M., and Keogh, K.

Abstract

© 2015 Macmillan Publishers Limited. Ruminant livestock are important sources of human food and global greenhouse gas emissions. Feed degradation and methane formation by ruminants rely on metabolic interactions between rumen microbes and affect ruminant productivity. Rumen and camelid foregut microbial community composition was determined in 742 samples from 32 animal species and 35 countries, to estimate if this was influenced by diet, host species, or geography. Similar bacteria and archaea dominated in nearly all samples, while protozoal communities were more variable. The dominant bacteria are poorly characterised, but the methanogenic archaea are better known and highly conserved across the world. This universality and limited diversity could make it possible to mitigate methane emissions by developing strategies that target the few dominant methanogens. Differences in microbial community compositions were predominantly attributable to diet, with the host being less influential. There were few strong co-occurrence patterns between microbes, suggesting that major metabolic interactions are non-selective rather than specific.

Published
2015

6. Efecto de la fuente de carbono y el tipo de inóculo sobre la producción de enzimas hidrolíticas del hongo anaeróbico ruminal Neocallimaxtis frontalis NFT 101

Author

Mayorga, O. L., López Reyes, E., Díaz, T. E., and Barahona, R.

Subjects
Enzimas, Genética y mejoramiento animal - L10, Anaerobiosis, Hongos del rumen, Transversal, Hongos, Inoculación
Abstract

El crecimiento y producción de enzimas del hongo anaeróbico Neocallimastix frontalis NFT 101, aislado del rumen de un ovino de un ecosistema tropical fue evaluado en un rango de fuentes de carbono y variando la forma de inoculación (estados mótil y vegetativo). Cuando se usó una suspensión de zoosporas (estado mótil) como inóculo, el hongo creció sobre xilosa, carboximetilcelulosa, celulosa en polvo, algodón, papel de filtro, pectina cítrica y heno de avena, pero no creció sobre arabinosa, xilano y pectina de manzana. Al inocular con fragmento de heno colonizado (estado vegetativo) hubo crecimiento en todas las fuentes de carbono con excepción de arabinosa. El complejo de enzimas hidrolíticas de este hongo incluyó endoxilanasas, endoglucanasas y exopoligalacturonasas, las que fueron liberadas principalmente al medio de cultivo, aunque se detectó actividad significativa de estas enzimas en la fracción asociada a la pared fungal, especialmente en el caso de la endoglucanasa. La principal actividad enzimática observada fue endoxilanolítica, que fue unas 100 y 1.000 veces mayor a la de endoglucanasa y exopoligalacturonasa, respectivamente. La producción de enzimas hidrolíticas fue constitutiva, pero al igual que el patrón de fermentación, la actividad fue regulada por la fuente de carbono usada en el medio de crecimiento y en menos medida por el estado de desarrollo fungal del inóculo. Dentro de las fuentes de carbono evaluadas las que presentaron un mejor balance entre la actividad enzimática y el crecimiento fungal fueron la celulosa en polvo, el heno de avena, el papel filtro y el xilano, previo proceso de adaptación.

Published
2005

9. Frequency spectrum of enthalpy fluctuations associated with macromolecular transitions.

Author

Mayorga, O L, van Osdol, W W, Lacomba, J L, and Freire, E

Abstract

A multifrequency calorimeter has been designed to measure the amplitude and time regime of the enthalpic fluctuations associated with structural or conformational transitions in biological macromolecular systems. The heat capacity function at constant pressure is directly proportional to the magnitude of the enthalpic fluctuations in a system. Biological macromolecules undergo thermally induced transitions of different kinds. Within the transition region, these systems exhibit relatively large enthalpy fluctuations that give rise to the characteristic peaks observed by conventional differential scanning calorimetry. The multifrequency calorimeter developed in this laboratory has been designed to measure the frequency spectrum of the enthalpy fluctuations, thus allowing us to estimate thermodynamic parameters as well as relaxation times. This information is obtained from the attenuation in the amplitude or phase-angle shift of the response of the system to a periodic temperature oscillation. This instrument has been used to study the gel-liquid crystalline transition of phosphatidylcholine bilayers. The frequency-temperature response surface for large dimyristoyl phosphatidylcholine vesicles has been measured in the frequency range 0.04-1 Hz. The data are consistent with two enthalpic relaxation processes with time constants on the order of 3.8 s and 80 ms at the midpoint of the main gel-liquid crystalline transition.

Published
1988
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10. Addressing global ruminant agricultural challenges through understanding the rumen microbiome: past, present and future.

Author

Huws, S. A. (Sharon A.), Creevey, C. J. (Christopher J.), Oyama, L. B. (Linda B.), Mizrahi, I. (Itzhak), Denman, S. E. (Stuart E.), Popova, M. (Milka), Muñoz-Tamayo, R. (Rafael), Forano, E. (Evelyne), Waters, S. M. (Sinead M.), Hess, M. (Matthias), Tapio, I. (Ilma), Smidt, H. (Hauke), Krizsan, S. J. (Sophie J.), Yáñez-Ruiz, D. R. (David R.), Belanche, A. (Alejandro), Guan, L. (Leluo), Gruninger, R. J. (Robert J.), McAllister, T. A. (Tim A.), Newbold, C. J. (C. Jamie), Roehe, R. (Rainer), Dewhurst, R. J. (Richard J.), Snelling, T. J. (Tim J.), Watson, M. (Mick), Suen, G. (Garret), Hart, E. H. (Elizabeth H.), Kingston-Smith, A. H. (Alison H.), Scollan, N. D. (Nigel D.), do Prado, R. M. (Rodolpho M.), Pilau, E. J. (Eduardo J.), Mantovani, H. C. (Hilario C.), Attwood, G. T. (Graeme T.), Edwards, J. E. (Joan E.), McEwan, N. R. (Neil R.), Morrisson, S. (Steven), Mayorga, O. L. (Olga L.), Elliott, C. (Christopher), Morgavi, D. P. (Diego P.), Huws, S. A. (Sharon A.), Creevey, C. J. (Christopher J.), Oyama, L. B. (Linda B.), Mizrahi, I. (Itzhak), Denman, S. E. (Stuart E.), Popova, M. (Milka), Muñoz-Tamayo, R. (Rafael), Forano, E. (Evelyne), Waters, S. M. (Sinead M.), Hess, M. (Matthias), Tapio, I. (Ilma), Smidt, H. (Hauke), Krizsan, S. J. (Sophie J.), Yáñez-Ruiz, D. R. (David R.), Belanche, A. (Alejandro), Guan, L. (Leluo), Gruninger, R. J. (Robert J.), McAllister, T. A. (Tim A.), Newbold, C. J. (C. Jamie), Roehe, R. (Rainer), Dewhurst, R. J. (Richard J.), Snelling, T. J. (Tim J.), Watson, M. (Mick), Suen, G. (Garret), Hart, E. H. (Elizabeth H.), Kingston-Smith, A. H. (Alison H.), Scollan, N. D. (Nigel D.), do Prado, R. M. (Rodolpho M.), Pilau, E. J. (Eduardo J.), Mantovani, H. C. (Hilario C.), Attwood, G. T. (Graeme T.), Edwards, J. E. (Joan E.), McEwan, N. R. (Neil R.), Morrisson, S. (Steven), Mayorga, O. L. (Olga L.), Elliott, C. (Christopher), and Morgavi, D. P. (Diego P.)

Abstract

The rumen is a complex ecosystem composed of anaerobic bacteria, protozoa, fungi, methanogenic archaea and phages. These microbes interact closely to breakdown plant material that cannot be digested by humans, whilst providing metabolic energy to the host and, in the case of archaea, producing methane. Consequently, ruminants produce meat and milk, which are rich in high-quality protein, vitamins and minerals, and therefore contribute to food security. As the world population is predicted to reach approximately 9.7 billion by 2050, an increase in ruminant production to satisfy global protein demand is necessary, despite limited land availability, and whilst ensuring environmental impact is minimized. Although challenging, these goals can be met, but depend on our understanding of the rumen microbiome. Attempts to manipulate the rumen microbiome to benefit global agricultural challenges have been ongoing for decades with limited success, mostly due to the lack of a detailed understanding of this microbiome and our limited ability to culture most of these microbes outside the rumen. The potential to manipulate the rumen microbiome and meet global livestock challenges through animal breeding and introduction of dietary interventions during early life have recently emerged as promising new technologies. Our inability to phenotype ruminants in a high-throughput manner has also hampered progress, although the recent increase in "omic" data may allow further development of mathematical models and rumen microbial gene biomarkers as proxies. Advances in computational tools, high-throughput sequencing technologies and cultivation-independent "omics" approaches continue to revolutionize our understanding of the rumen microbiome. This will ultimately provide the knowledge framework needed to solve current and future ruminant livestock challenges.

11. Addressing global ruminant agricultural challenges through understanding the rumen microbiome: past, present and future.

Author

Huws, S. A. (Sharon A.), Creevey, C. J. (Christopher J.), Oyama, L. B. (Linda B.), Mizrahi, I. (Itzhak), Denman, S. E. (Stuart E.), Popova, M. (Milka), Forano, E. (Evelyne), Waters, S. M. (Sinead M.), Hess, M. (Matthias), Tapio, I. (Ilma), Smidt, H. (Hauke), Krizsan, S. J. (Sophie J.), Belanche, A. (Alejandro), Guan, L. (Leluo), Gruninger, R. J. (Robert J.), McAllister, T. A. (Tim A.), Newbold, C. J. (C. Jamie), Roehe, R. (Rainer), Dewhurst, R. J. (Richard J.), Snelling, T. J. (Tim J.), Watson, M. (Mick), Suen, G. (Garret), Hart, E. H. (Elizabeth H.), Kingston-Smith, A. H. (Alison H.), Scollan, N. D. (Nigel D.), do Prado, R. M. (Rodolpho M.), Pilau, E. J. (Eduardo J.), Mantovani, H. C. (Hilario C.), Attwood, G. T. (Graeme T.), Edwards, J. E. (Joan E.), McEwan, N. R. (Neil R.), Morrisson, S. (Steven), Mayorga, O. L. (Olga L.), Elliott, C. (Christopher), Morgavi, D. P. (Diego P.), Huws, S. A. (Sharon A.), Creevey, C. J. (Christopher J.), Oyama, L. B. (Linda B.), Mizrahi, I. (Itzhak), Denman, S. E. (Stuart E.), Popova, M. (Milka), Forano, E. (Evelyne), Waters, S. M. (Sinead M.), Hess, M. (Matthias), Tapio, I. (Ilma), Smidt, H. (Hauke), Krizsan, S. J. (Sophie J.), Belanche, A. (Alejandro), Guan, L. (Leluo), Gruninger, R. J. (Robert J.), McAllister, T. A. (Tim A.), Newbold, C. J. (C. Jamie), Roehe, R. (Rainer), Dewhurst, R. J. (Richard J.), Snelling, T. J. (Tim J.), Watson, M. (Mick), Suen, G. (Garret), Hart, E. H. (Elizabeth H.), Kingston-Smith, A. H. (Alison H.), Scollan, N. D. (Nigel D.), do Prado, R. M. (Rodolpho M.), Pilau, E. J. (Eduardo J.), Mantovani, H. C. (Hilario C.), Attwood, G. T. (Graeme T.), Edwards, J. E. (Joan E.), McEwan, N. R. (Neil R.), Morrisson, S. (Steven), Mayorga, O. L. (Olga L.), Elliott, C. (Christopher), and Morgavi, D. P. (Diego P.)

Abstract

The rumen is a complex ecosystem composed of anaerobic bacteria, protozoa, fungi, methanogenic archaea and phages. These microbes interact closely to breakdown plant material that cannot be digested by humans, whilst providing metabolic energy to the host and, in the case of archaea, producing methane. Consequently, ruminants produce meat and milk, which are rich in high-quality protein, vitamins and minerals, and therefore contribute to food security. As the world population is predicted to reach approximately 9.7 billion by 2050, an increase in ruminant production to satisfy global protein demand is necessary, despite limited land availability, and whilst ensuring environmental impact is minimized. Although challenging, these goals can be met, but depend on our understanding of the rumen microbiome. Attempts to manipulate the rumen microbiome to benefit global agricultural challenges have been ongoing for decades with limited success, mostly due to the lack of a detailed understanding of this microbiome and our limited ability to culture most of these microbes outside the rumen. The potential to manipulate the rumen microbiome and meet global livestock challenges through animal breeding and introduction of dietary interventions during early life have recently emerged as promising new technologies. Our inability to phenotype ruminants in a high-throughput manner has also hampered progress, although the recent increase in "omic" data may allow further development of mathematical models and rumen microbial gene biomarkers as proxies. Advances in computational tools, high-throughput sequencing technologies and cultivation-independent "omics" approaches continue to revolutionize our understanding of the rumen microbiome. This will ultimately provide the knowledge framework needed to solve current and future ruminant livestock challenges.

13. Influence of dynamic power compensation in an isothermal titration microcalorimeter.

Author

García-Fuentes L, Barón C, and Mayorga OL

Subjects
Calibration, Cytidine Monophosphate analysis, Deoxyuracil Nucleotides chemistry, Models, Theoretical, Osmolar Concentration, Titrimetry methods, Uridine Monophosphate chemistry, Calorimetry instrumentation, Cytidine Monophosphate chemistry, Ribonuclease, Pancreatic chemistry
Abstract

A theoretical analysis in Laplace's transformed domain based on a power balance represents a suitable model for an isothermal titration calorimeter with dynamic power compensation, designed and implemented in our laboratory. A rigorous calibration of the injection system and the calorimetric response was also made. Using electrically generated heat pulses, two different time constants have been determined from the calorimetric transfer function and assigned to the physical parts of the calorimeter. The same was done for a protein-ligand interaction. The binding of 2'-CMP to ribonuclease A at low and high ionic strengths was used to check the apparatus and the results were compared with those obtained by other authors (Wiseman, T.; Williston, S.; Brandts, J.F.; Lung-Nan, L. Anal. Biochem. 1989, 179, 131-137). In this case, the analysis showed a different time constant for the heat source. Independently of the nature of the heat source, the calorimetric time constants obtained while working under compensation are always smaller than those corresponding to a noncompensated system. The improvement of the calorimetric response introduced by dynamic power compensation is thus explained in terms of the reduction of the time constants characteristic of the calorimeter. This theoretical model can be used to predict the shape of the thermogram for any given reaction of either known or supposed thermodynamic parameters. Therefore, the calorimetric study is extended to the other nucleotides, 2'-UMP and 5'-dUMP, which have not hitherto been reported in the literature.

Published
1998
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14. Structure-based thermodynamic scale of alpha-helix propensities in amino acids.

Author

Luque I, Mayorga OL, and Freire E

Subjects
Amino Acids genetics, Amino Acids metabolism, Bacterial Proteins, Leucine Zippers, Muramidase chemistry, Mutation, Peptides chemistry, Protein Conformation, Protein Folding, Regression Analysis, Ribonucleases chemistry, Thermodynamics, Amino Acids chemistry, Protein Structure, Secondary, Proteins chemistry
Abstract

A structural parameterization of the folding energetics has been used to predict the effect of single amino acid mutations at exposed locations in alpha-helices. The results have been used to derive a structure-based thermodynamic scale of alpha-helix propensities for amino acids. The structure-based thermodynamic analysis was performed for four different systems for which structural and experimental thermodynamic data are available: T4 lysozyme [Blaber et al (1994) J. Mol. Biol.235, 600-624], barnase [Horovitz et al. (1992) J.Mol.Biol.227,560-568], a synthetic leucine zipper [O'Neil & Degrado (1990) Science 250, 646-651], and a synthetic peptide [Lyu et al. (1990) Science 250, 669-673]. These studies have permitted the optimization of the set of solvent-accessible surface areas (ASA) for all amino acids in the unfolded state. It is shown that a single set of structure/thermodynamic parameters accounts well for all the experimental data sets of helix propensities. For T4 lysozyme, the average value of the absolute difference between predicted and experimental delta G values is 0.09 kcal/mol, for barnase 0.14 kcal/mol, for the synthetic coiled-coil 0.11 kcal/mol, and for the synthetic peptide 0.08 kcal/mol. In addition, this approach predicts well the overall stability of the proteins and rationalizes the differences in alpha-helix propensities between amino acids. The excellent agreement observed between predicted and experimental delta G values for all amino acids validates the use of this structural parameterization in free energy calculations for folding or binding.

Published
1996
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15. Heat and cold denaturation of beta-lactoglobulin B.

Author

Azuaga AI, Galisteo ML, Mayorga OL, Cortijo M, and Mateo PL

Subjects
Calorimetry, Differential Scanning, Circular Dichroism, Cold Temperature, Guanidine, Guanidines pharmacology, Hot Temperature, Protein Denaturation, Lactoglobulins metabolism
Abstract

The thermal denaturation of bovine beta-lactoglobulin B was investigated by high-sensitivity differential scanning microcalorimetry between pH 1.5 and 3.0 in 20 mM phosphate buffer. The process was found to be a reversible, two-state transition. Progressive addition of guanidine hydrochloride at pH 3.0 leads to the appearance of a low-temperature calorimetric endotherm, corresponding to the cold renaturation of the protein. Circular dichroism experiments have confirmed the low and high temperature denaturation processes, and have shown some structural differences between both denatured states of beta-lactoglobulin B.

Published
1992
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16. Multifrequency calorimetry of the folding/unfolding transition of cytochrome c.

Author

van Osdol WW, Mayorga OL, and Freire E

Subjects
Animals, Calorimetry instrumentation, Calorimetry methods, Horses, Models, Theoretical, Myocardium, Protein Conformation, Protein Denaturation, Cytochrome c Group chemistry
Abstract

The folding-unfolding transition of Fe(III) cytochrome c has been studied with the new technique of multifrequency calorimetry. Multifrequency calorimetry is aimed at measuring directly the dynamics of the energetic events that take place during a thermally induced transition by measuring the frequency dispersion of the heat capacity. This is done by modulating the folding/unfolding equilibrium using a variable frequency, small oscillatory temperature perturbation (approximately 0.05-0.1 degrees C) centered at the equilibrium temperature of the system. Fe(III) cytochrome c at pH 4 undergoes a fully reversible folding/unfolding transition centered at 67.7 degrees C and characterized by an enthalpy change of 81 kcal/mol and heat capacity difference between unfolded and folded states of 0.9 kcal/K*mol. By measuring the temperature dependence of the frequency dispersion of the heat capacity in the frequency range of 0.1-1 Hz it has been possible to examine the time regime of the enthalpic events associated with the transition. The multifrequency calorimetry results indicate that approximately 85% of the excess heat capacity associated with the folding/unfolding transition relaxes with a single relaxation time of 326 +/- 68 ms at the midpoint of the transition region. This is the first time that the time regime in which heat is absorbed and released during protein folding/unfolding has been measured.

Published
1991
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17. Thermodynamic characterization of interactions between ornithine transcarbamylase leader peptide and phospholipid bilayer membranes.

Author

Myers M, Mayorga OL, Emtage J, and Freire E

Subjects
Calorimetry, Differential Scanning, Kinetics, Spectrometry, Fluorescence, Structure-Activity Relationship, Thermodynamics, Lipid Bilayers, Ornithine Carbamoyltransferase metabolism, Protein Sorting Signals metabolism
Abstract

The interactions of the targeting sequence of the mitochondrial enzyme ornithine transcarbamylase with phospholipid bilayers of different molecular compositions have been studied by high-sensitivity heating and cooling differential scanning calorimetry, high-sensitivity isothermal titration calorimetry, fluorescence spectroscopy, and electron microscopy. These studies indicate that the leader peptide interacts strongly with dipalmitoylphosphatidylcholine (DPPC) bilayer membranes containing small mole percents of the anionic phospholipids dipalmitoylphosphatidylglycerol (DPPG) or brain phosphatidylserine (brain PS) but not with pure phosphatidylcholines. For the first time, the energetics of the leader peptide-membrane interaction have been measured directly by using calorimetric techniques. At 20 degrees C, the association of the peptide with the membrane is exothermic and characterized by an association constant of 2.3 X 10(6) M-1 in the case of phosphatidylglycerol-containing and 0.35 X 10(6) M-1 in the case of phosphatidylserine-containing phospholipid bilayers. In both cases, the enthalpy of association is -60 kcal/mol of peptide. Additional experiments using fluorescence techniques suggest that the peptide does not penetrate deeply into the hydrophobic core of the membrane. The addition of the leader peptide to DPPC/DPPG (5:1) or DPPC/brain PS (5:1) small sonicated vesicles results in vesicle fusion. The fusion process is dependent on peptide concentration and is maximal at the phase transition temperature of the vesicles and minimal at temperatures below the phase transition.

Published
1987
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18. An ultrasensitive electrometric system to measure membrane-bound acetylcholinesterase activity.

Author

Muñoz Delgado E, Gomez-Fernandez JC, Mayorga OL, Lozano JA, and Vidal CJ

Subjects
Animals, Electrochemistry, Hydrogen-Ion Concentration, Methods, Rabbits, Acetylcholinesterase analysis, Sarcoplasmic Reticulum enzymology
Abstract

A very sensitive method for the determination of membrane-bound acetylcholinesterase from sarcoplasmic reticulum is described. The acetic acid which is released by the enzymatic hydrolysis of acetylcholine is measured by means of an electrometric system. Diluted hydrochloric acid is used as the standard to evaluate the amount of H+ produced during the time course of the reaction. With the use of a bucking voltage device the sensitivity of the method permits one to follow changes in H+ concentration below 1 microM. Therefore the enzyme activity can be estimated using a very small amount of sarcoplasmic reticulum protein. This procedure is very simple, accurate and reproducible, and it can be applied to measure membrane-bound acetylcholinesterase where the membrane suspension makes it difficult to employ spectrophotometric techniques.

Published
1983
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