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5. Rumen Bacteria

Author

Zhou, M., Chen, Y., Guan, L. L., Puniya, Anil Kumar, editor, Singh, Rameshwar, editor, and Kamra, Devki Nandan, editor

Published
2015
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9. Rumen microbiota and its relation to fermentation in lactose-fed calves

Author

Koike, S., Ueno, M., Miura, H., Saegusa, A., Inouchi, K., Inabu, Y., Sugino, T., Guan, L. L., Oba, M., Kobayashi, Y., Koike, S., Ueno, M., Miura, H., Saegusa, A., Inouchi, K., Inabu, Y., Sugino, T., Guan, L. L., Oba, M., and Kobayashi, Y.

Abstract

In our previous studies, we revealed the effect of lactose inclusion in calf starters on the growth performance and gut development of calves. We conducted the present study as a follow-up study to identify the shift in rumen microbiota and its relation to rumen fermentation when calves are fed a lactose-containing starter. Thirty Holstein bull calves were divided into 2 calf starter treatment groups: texturized calf starter (i.e., control; n = 15) or calf starter in which starch was replaced with lactose at 10% (i.e., LAC10; n = 15) on a dry matter basis. All calves were fed their respective treatment calf starter ad libitum from d 7, and kleingrass hay from d 35. Rumen digesta were collected on d 80 (i.e., 3 wk after weaning) and used to analyze rumen microbiota and fermentation products. There was no apparent effect of lactose feeding on the alpha-diversity and overall composition of rumen microbiota. Amplicon sequencing and real-time PCR quantification of the 16S rRNA gene confirmed that the abundance of butyrate producing bacteria (i.e., Butyrivibrio group and Megasphaera elsdenii) did not differ between the control and LAC10 groups. Conversely, the relative abundance of Mitsuokella spp., which produce lactate, succinate, and acetate, was significantly higher in the rumen of calves that were fed lactose, whereas the lactate concentration did not differ between the control and LAC10 groups. These findings suggest that the lactate production can be elevated by an increase of Mitsuokella spp. and then converted into butyrate, not propionate, since the proportion of propionate was lower in lactose-fed calves. In addition, we observed a higher abundance of Coriobacteriaceae and Pseudoramibacter-Eubacterium in the LAC10 group. Both these bacterial taxa include acetate-producing bacteria, and a positive correlation between the acetate-to-propionate ratio and the abundance of Pseudoramibacter-Eubacterium was observed. Therefore, the higher abundance of Coriobacteriacea

Published
2021

10. Rumen microbiota and its relation to fermentation in lactose-fed calves

Author

1000090431353, Koike, S., Ueno, M., Miura, H., Saegusa, A., Inouchi, K., Inabu, Y., Sugino, T., Guan, L. L., Oba, M., Kobayashi, Y., 1000090431353, Koike, S., Ueno, M., Miura, H., Saegusa, A., Inouchi, K., Inabu, Y., Sugino, T., Guan, L. L., Oba, M., and Kobayashi, Y.

Abstract

In our previous studies, we revealed the effect of lactose inclusion in calf starters on the growth performance and gut development of calves. We conducted the present study as a follow-up study to identify the shift in rumen microbiota and its relation to rumen fermentation when calves are fed a lactose-containing starter. Thirty Holstein bull calves were divided into 2 calf starter treatment groups: texturized calf starter (i.e., control; n = 15) or calf starter in which starch was replaced with lactose at 10% (i.e., LAC10; n = 15) on a dry matter basis. All calves were fed their respective treatment calf starter ad libitum from d 7, and kleingrass hay from d 35. Rumen digesta were collected on d 80 (i.e., 3 wk after weaning) and used to analyze rumen microbiota and fermentation products. There was no apparent effect of lactose feeding on the alpha-diversity and overall composition of rumen microbiota. Amplicon sequencing and real-time PCR quantification of the 16S rRNA gene confirmed that the abundance of butyrate producing bacteria (i.e., Butyrivibrio group and Megasphaera elsdenii) did not differ between the control and LAC10 groups. Conversely, the relative abundance of Mitsuokella spp., which produce lactate, succinate, and acetate, was significantly higher in the rumen of calves that were fed lactose, whereas the lactate concentration did not differ between the control and LAC10 groups. These findings suggest that the lactate production can be elevated by an increase of Mitsuokella spp. and then converted into butyrate, not propionate, since the proportion of propionate was lower in lactose-fed calves. In addition, we observed a higher abundance of Coriobacteriaceae and Pseudoramibacter-Eubacterium in the LAC10 group. Both these bacterial taxa include acetate-producing bacteria, and a positive correlation between the acetate-to-propionate ratio and the abundance of Pseudoramibacter-Eubacterium was observed. Therefore, the higher abundance of Coriobacteriacea

Published
2021

11. Metagenomic analysis revealed the individualized shift in ileal microbiome of neonatal calves in response to delaying the first colostrum feeding

Author

Song, Y., Li, F., Fischer-Tlustos, A. J., Neves, A. L.A., He, Z., Steele, M. A., Guan, L. L., Song, Y., Li, F., Fischer-Tlustos, A. J., Neves, A. L.A., He, Z., Steele, M. A., and Guan, L. L.

Abstract

The aim of this study was to explore the effect of colostrum feeding time on the ileal microbiome of neonatal calves. In this study, 22 male Holstein calves were randomly assigned to different colostrum feeding time treatments: after birth (at 45 min, n = 7); at 6 h after birth (n = 8); and at 12 h after birth (TRT12h; n = 7). At 51 h after birth, calves were killed and ileum digesta was collected for microbiome analysis using shotgun metagenomic sequencing. Bacteria, archaea, eukaryotes, and viruses were identified from the ileum microbiome. For the bacteriome, Firmicutes and Proteobacteria were the predominant phyla, and Escherichia, Streptococcus, Lactobacillus were the 3 most abundant genera. For the archaeal community, Euryarchaeota and Crenarchaeota were the 2 major phyla, and Methanosarcina, Methanobrevibacter, and Methanocorpusculum were the 3 most abundant genera. In total, 116 Kyoto Encyclopedia of Genes and Genomes (KEGG) pathways were identified from the ileal microbiome, with “biosynthesis of vancomycin group antibiotics,” “biosynthesis of ansamycins,” “valine, leucine, and isoleucine biosynthesis,” “ribosome,” and “D-alanine metabolism” as the top 5 functions. When the ileal microbiomes were compared among the 3 treatments, the relative abundance of Enterococcus was higher in TRT12h calves, suggesting that calves may have a higher abundance of opportunistic pathogens when the feeding of colostrum is delayed for 12 h. Moreover, among all KEGG pathways, the enriched “taurine and hypotaurine metabolism” (KO00430) pathway was identified in the ileal microbiome of TRT12h calves; however, future studies are needed to understand the effect on the host. Additionally, 2 distinct ileal microbial profiles were identified across all samples, indicating that that host factors may play a significant role in driving varied microbiome changes in response to colostrum feeding time. Whether such microbiome shifts affect long-term gut function and calf performance war

Published
2021

16. Taxonomic and functional assessment using metatranscriptomics reveals the effect of Angus cattle on rumen microbial signatures.

Author

Neves, A. L. A., Chen, Y., Lê Cao, K.-A., Mandal, S., Sharpton, T. J., McAllister, T., and Guan, L. L.

Abstract

A greater understanding of the rumen microbiota and its function may help find new strategies to improve feed efficiency in cattle. This study aimed to investigate whether the cattle breed affects specific ruminal taxonomic microbial groups and functions associated with feed conversion ratio (FCR), using two genetically related Angus breeds as a model. Total RNA was extracted from 24 rumen content samples collected from purebred Black and Red Angus bulls fed the same forage diet and then subjected to metatranscriptomic analysis. Multivariate discriminant analysis (sparse partial least square discriminant analysis (sPLS-DA)) and analysis of composition of microbiomes were conducted to identify microbial signatures characterizing Black and Red Angus cattle. Our analyses revealed relationships among bacterial signatures, host breeds and FCR. Although Black and Red Angus are genetically similar, sPLS-DA detected 25 bacterial species and 10 functions that differentiated the rumen microbial signatures between those two breeds. In Black Angus, we identified bacterial taxa Chitinophaga pinensis , Clostridium stercorarium and microbial functions with large and small subunits ribosomal proteins L16 and S7 exhibiting a higher abundance in the rumen microbiome. In Red Angus, nonetheless, we identified the poorly characterized bacterial taxon Oscillibacter valericigenes with a higher abundance and pathways related to carbohydrate metabolism. Analysis of composition of microbiomes revealed that C. pinensis and C. stercorarium exhibited a higher abundance in Black Angus compared to Red Angus associated with FCR, suggesting that these bacterial species may play a key role in the feed conversion efficiency of forage-fed bulls. This study highlights how the discovery of signatures of bacterial taxa and their functions can be used to harness the full potential of the rumen microbiome in Angus cattle. [ABSTRACT FROM AUTHOR]

Published
2020
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23. 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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33. 1427 Effects of feeding steers extruded flaxseed and hay together (total mixed ration) or sequentially (non-total mixed ration) on animal performance and erythrocyte vaccenic, rumenic, and α-linolenic acid content

Author

Vahmani, P., primary, Rolland, D. C., additional, McAllister, T. A., additional, Block, H. C., additional, Proctor, S. D., additional, Guan, L. L., additional, Prieto, N., additional, Aalhus, J. L., additional, and Dugan, M. E. R., additional

Published
2016
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38. P6034 Associations between cis-expression quantitative trait loci markers and host response to Porcine reproductive and respiratory syndrome virus infection

Author

Bao, H., primary, Kommadath, A., additional, Choi, I., additional, Lunney, J. K., additional, Reecy, J. M., additional, Fritz-Waters, E., additional, Eisley, C. J., additional, Tuggle, C. K., additional, Koltes, J. E., additional, Rowland, R. R. R., additional, Dekkers, J. C. M., additional, Guan, L. L., additional, Stothard, P., additional, and Plastow, G., additional

Published
2016
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39. 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

40. Review: Biological determinants of between-animal variation in feed efficiency of growing beef cattle.

Author

Cantalapiedra-Hijar, G., Abo-Ismail, M., Carstens, G. E., Guan, L. L., Hegarty, R., Kenny, D. A., McGee, M., Plastow, G., Relling, A., Ortigues-Marty, I., Cassar-Malek, Isabelle, Baumont, René, Bannink, Andre, Teixeira, Izabelle, Mayberry, Dianne, and Kyriazakis, Ilias

Abstract

Animal's feed efficiency in growing cattle (i.e. the animal ability to reach a market or adult BW with the least amount of feed intake), is a key factor in the beef cattle industry. Feeding systems have made huge progress to understand dietary factors influencing the average animal feed efficiency. However, there exists a considerable amount of animal-to-animal variation around the average feed efficiency observed in beef cattle reared in similar conditions, which is still far from being understood. This review aims to identify biological determinants and molecular pathways involved in the between-animal variation in feed efficiency with particular reference to growing beef cattle phenotyped for residual feed intake (RFI). Moreover, the review attempts to distinguish true potential determinants from those revealed through simple associations or indirectly linked to RFI through their association with feed intake. Most representative and studied biological processes which seem to be connected to feed efficiency were reviewed, such as feeding behaviour, digestion and methane production, rumen microbiome structure and functioning, energy metabolism at the whole body and cellular levels, protein turnover, hormone regulation and body composition. In addition, an overall molecular network analysis was conducted for unravelling networks and their linked functions involved in between-animal variation in feed efficiency. The results from this review suggest that feeding and digestive-related mechanisms could be associated with RFI mainly because they co-vary with feed intake. Although much more research is warranted, especially with high-forage diets, the role of feeding and digestive related mechanisms as true determinants of animal variability in feed efficiency could be minor. Concerning the metabolic-related mechanisms, despite the scarcity of studies using reference methods it seems that feed efficient animals have a significantly lower energy metabolic rate independent of the associated intake reduction. This lower heat production in feed efficient animals may result from a decreased protein turnover and a higher efficiency of ATP production in mitochondria, both mechanisms also identified in the molecular network analysis. In contrast, hormones and body composition could not be conclusively related to animal-to-animal variation in feed efficiency. The analysis of potential biological networks underlying RFI variations highlighted other significant pathways such as lipid metabolism and immunity and stress response. Finally, emerging knowledge suggests that metabolic functions underlying genetic variation in feed efficiency could be associated with other important traits in animal production. This emphasizes the relevance of understanding the biological basis of relevant animal traits to better define future balanced breeding programmes. [ABSTRACT FROM AUTHOR]

Published
2018
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43. Associations of rumen parameters with feed efficiency and sampling routine in beef cattle.

Author

Lam, S., Munro, J. C., Zhou, M., Guan, L. L., Schenkel, F. S., Steele, M. A., Miller, S. P., and Montanholi, Y. R.

Abstract

Characterizing ruminal parameters in the context of sampling routine and feed efficiency is fundamental to understand the efficiency of feed utilization in the bovine. Therefore, we evaluated microbial and volatile fatty acid (VFA) profiles, rumen papillae epithelial and stratum corneum thickness and rumen pH (RpH) and temperature (RT) in feedlot cattle. In all, 48 cattle (32 steers plus 16 bulls), fed a high moisture corn and haylage-based ration, underwent a productive performance test to determine residual feed intake (RFI) using feed intake, growth, BW and composition traits. Rumen fluid was collected, then RpH and RT logger were inserted 5.5±1 days before slaughter. At slaughter, the logger was recovered and rumen fluid and rumen tissue were sampled. The relative daily time spent in specific RpH and RT ranges were determined. Polynomial regression analysis was used to characterize RpH and RT circadian patterns. Animals were divided into efficient and inefficient groups based on RFI to compare productive performance and ruminal parameters. Efficient animals consumed 1.8 kg/day less dry matter than inefficient cattle (P⩽0.05) while achieving the same productive performance (P⩾0.10). Ruminal bacteria population was higher (P⩽0.05) (7.6×1011v. 4.3×1011 copy number of 16S rRNA gene/ml rumen fluid) and methanogen population was lower (P⩽0.05) (2.3×109v. 4.9×109 copy number of 16S rRNA gene/ml rumen fluid) in efficient compared with inefficient cattle at slaughter with no differences (P⩾0.10) between samples collected on-farm. No differences (P⩾0.10) in rumen fluid VFA were also observed between feed efficiency groups either on-farm or at slaughter. However, increased (P⩽0.05) acetate, and decreased (P⩽0.05) propionate, butyrate, valerate and caproate concentrations were observed at slaughter compared with on-farm. Efficient had increased (P⩽0.05) rumen epithelium thickness (136 v. 126 µm) compared with inefficient cattle. Efficient animals also spent 318% and 93.2% more time (P⩽0.05) in acidotic (4.14% v. 1.30%) (pH⩽5.6) and optimal (5.6v. 4.42%) RpH range compared with inefficient cattle. The circadian patterns revealed lower (P⩽0.05) RpH and no differences (P⩾0.10) in RT pre-, during, and post-prandial periods in efficient compared with inefficient cattle. In essence, superior feed efficiency in cattle seems linked to rumen features consistent with improved efficiency of feed utilization. Microbial abundance, rumen epithelial histomorphology, and RpH, may serve as indicators for feed efficiency in cattle. The divergences of assessments made on-farm and at slaughter should be considered in the development of proxies for feed efficiency. [ABSTRACT FROM AUTHOR]

Published
2018
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45. Obesity, Metabolic Syndrome, and Adipocytes

Author

Dodson, M. V., Mir, P. S., Hausman, G. J., Guan, L. L., Du, Min, Jiang, Z., Fernyhough, M. E., and Bergen, W. G.

Subjects
Article Subject
Abstract

Obesity and metabolic syndromes are examples whereby excess energy consumption and energy flux disruptions are causative agents of increased fatness. Because other, as yet elucidated, cellular factors may be involved and because potential treatments of these metabolic problems involve systemic agents that are not adipose depot-specific in their actions, should we be thinking of adipose depot-specific (cellular) treatments for these problems? For sure, whether treating obesity or metabolic syndrome, the characteristics of all adipose depot-specific adipocytes and stromal vascular cells should be considered. The focus of this paper is to begin to align metabolic dysfunctions with specific characteristics of adipocytes.

Published
2011
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50. Shifts in Host Mucosal Innate Immune Function Are Associated with Ruminal Microbial Succession in Supplemental Feeding and Grazing Goats at Different Ages.

Author

Jinzhen Jiao, Chuanshe Zhou, Guan, L. L., McSweeney, Shaoxun Tang, Min Wang, and Zhiliang Tan

Subjects
ANIMAL nutrition, GASTROINTESTINAL mucosa, MICROBIAL diversity
Abstract

Gastrointestinal microbiota may play an important role in regulating host mucosal innate immune function. This study was conducted to test the hypothesis that age (non-rumination, transition and rumination) and feeding type [Supplemental feeding (S) vs. Grazing (G)] could alter ruminal microbial diversity and maturation of host mucosal innate immune system in goat kids. MiSeq sequencing was applied to investigate ruminal microbial composition and diversity, and RT-PCR was used to test expression of immune-related genes in ruminal mucosa. Results showed that higher (P < 0.05) relative abundances of Prevotella, Butyrivibrio, Pseudobutyrivibrio, Methanobrevibacter.gottschalkii, Neocallimastix, Anoplodinium-Diplodinium, and Polyplastron, and lower relative abundance of Methanosphaera (P D 0.042) were detected in the rumen of S kids when compared to those in G kids. The expression of genes encoding TLRs, IL1α, IL1β and TICAM2 was downregulated (P < 0.01), while expression of genes encoding tight junction proteins was up-regulated (P < 0.05) in the ruminal mucosa of S kids when compared to that in G kids. Moreover, irrespective of feeding type, relative abundances of ruminal Prevotella, Fibrobacter, Ruminococcus, Butyrivibrio, Methanobrevibacter, Neocallimastix, and Entodinium increased with age. The expression of most genes encoding TLRs and cytokines increased (P < 0.05) from day 0 to 7, while expression of genes encoding tight junction proteins declined with age (P < 0.05). This study revealed that the composition of each microbial domain changed as animals grew, and these changes might be associated with variations in host mucosal innate immune function. Moreover, supplementing goat kids with concentrate could modulate ruminal microbial composition, enhance barrier function and decrease local inflammation. The findings provide useful information in interpreting microbiota and host interactions, and developing nutritional strategies to improve the productivity and health of rumen during early life. [ABSTRACT FROM AUTHOR]

Published
2017
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