Estimating Microbial Protein Synthesis in the Rumen—Can ‘Omics’ Methods Provide New Insights into a Long-Standing Question?
Abstract
:Simple Summary
Abstract
1. Introduction
2. Energy Supply Limiting Microbial Protein Synthesis
3. Protein Supply Limiting Microbial Protein Synthesis
4. Methodological Problems
5. Analysis of Factors Affecting Urinary Purine Derivative Excretion
5.1. Methods
5.2. Results
6. Microbiome Approaches to Predict Rumen-Related Traits
7. Conclusions
Author Contributions
Funding
Institutional Review Board Statement
Informed Consent Statement
Data Availability Statement
Conflicts of Interest
References
- United Nations, Department of Economic and Social Affairs, Population Division. World Population Prospects: The 2017 Revision—Key Findings and Advance Tables; United Nations: New York, NY, USA, 2017. [Google Scholar]
- Godfray, H.C.J.; Beddington, J.R.; Crute, I.R.; Haddad, L.; Lawrence, D.; Muir, J.F.; Pretty, J.; Robinson, S.; Thomas, S.M.; Toulmin, C. Food Security: The Challenge of Feeding 9 Billion People. Science 2010, 327, 813–818. [Google Scholar] [CrossRef]
- Storm, E.; Orskov, E.R. The Nutritive Value of Rumen Micro-Organisms in Ruminants. 1. Large-Scale Isolation and Chemical Composition of Rumen Micro-Organisms. Br. J. Nutr. 1983, 50, 463–470. [Google Scholar] [CrossRef]
- Virtanen, A.I. Milk Production of Cows on Protein-Free Feed. Science 1966, 153, 1603–1614. [Google Scholar] [CrossRef]
- Krol, D.J.; Carolan, R.; Minet, E.; McGeough, K.L.; Watson, C.J.; Forrestal, P.J.; Lanigan, G.J.; Richards, K.G. Improving and Disaggregating N2O Emission Factors for Ruminant Excreta on Temperate Pasture Soils. Sci. Total Environ. 2016, 568, 327–338. [Google Scholar] [CrossRef]
- Pathak, A.K. Various Factors Affecting Microbial Protein Synthesis in the Rumen. Vet. World 2008, 1, 186–189. [Google Scholar]
- Dewhurst, R.J.; Davies, D.R.; Merry, R.J. Microbial Protein Supply from the Rumen. Anim. Feed Sci. Technol. 2000, 85, 1–21. [Google Scholar] [CrossRef]
- Liu, J.; Zhang, M.; Xue, C.; Zhu, W.; Mao, S. Characterization and Comparison of the Temporal Dynamics of Ruminal Bacterial Microbiota Colonizing Rice Straw and Alfalfa Hay within Ruminants. J. Dairy Sci. 2016, 99, 9668–9681. [Google Scholar] [CrossRef] [PubMed]
- Mayorga, O.L.; Kingston-Smith, A.H.; Kim, E.J.; Allison, G.G.; Wilkinson, T.J.; Hegarty, M.J.; Theodorou, M.K.; Newbold, C.J.; Huws, S.A. Temporal Metagenomic and Metabolomic Characterization of Fresh Perennial Ryegrass Degradation by Rumen Bacteria. Front. Microbiol. 2016, 7, 1854. [Google Scholar] [CrossRef] [PubMed]
- Jin, W.; Wang, Y.; Li, Y.; Cheng, Y.; Zhu, W. Temporal Changes of the Bacterial Community Colonizing Wheat Straw in the Cow Rumen. Anaerobe 2018, 50, 1–8. [Google Scholar] [CrossRef]
- Huws, S.A.; Edwards, J.E.; Creevey, C.J.; Rees Stevens, P.; Lin, W.; Girdwood, S.E.; Pachebat, J.A.; Kingston-Smith, A.H. Temporal Dynamics of the Metabolically Active Rumen Bacteria Colonizing Fresh Perennial Ryegrass. FEMS Microbiol. Ecol. 2016, 92, fiv137. [Google Scholar] [CrossRef] [PubMed]
- Piao, H.; Lachman, M.; Malfatti, S.; Sczyrba, A.; Knierim, B.; Auer, M.; Tringe, S.G.; Mackie, R.I.; Yeoman, C.J.; Hess, M. Temporal Dynamics of Fibrolytic and Methanogenic Rumen Microorganisms during in Situ Incubation of Switchgrass Determined by 16S rRNA Gene Profiling. Front. Microbiol. 2014, 5, 307. [Google Scholar] [CrossRef]
- Edwards, J.E.; Huws, S.A.; Kim, E.J.; Kingston-Smith, A.H. Characterization of the Dynamics of Initial Bacterial Colonization of Nonconserved Forage in the Bovine Rumen. FEMS Microbiol. Ecol. 2007, 62, 323–335. [Google Scholar] [CrossRef] [PubMed]
- Firkins, J.L. Maximizing Microbial Protein Synthesis in the Rumen. J. Nutr. 1996, 126, 1347S–1354S. [Google Scholar] [CrossRef] [PubMed]
- Pirt, S.J.; Hinshelwood, C.N. The Maintenance Energy of Bacteria in Growing Cultures. Proc. R. Soc. Lond. B Biol. Sci. 1997, 163, 224–231. [Google Scholar] [CrossRef]
- Isaacson, H.R.; Hinds, F.C.; Bryant, M.P.; Owens, F.N. Efficiency of Energy Utilization by Mixed Rumen Bacteria in Continuous Culture. J. Dairy Sci. 1975, 58, 1645–1659. [Google Scholar] [CrossRef]
- Agricultural Research and Food Council Technical Committee on Responses to Nutrients. Report No. 9. Nutritive Requirements of Ruminant Animals: Protein. In Nutrition Abstracts and Reviews (Series B); Oxford University Press: Oxford, UK, 1992; Volume 62, pp. 787–835. [Google Scholar]
- National Academies of Sciences, Engineering, and Medicine. Nutrient Requirements of Beef Cattle, 8th ed.; The National Academies Press: Washington, DC, USA, 2016. [Google Scholar]
- Agricultural Research Council. The Nutrient Requirements of Ruminant Livestock; CAB: Farnham Royal, UK, 1980. [Google Scholar]
- Agricultural Research Council. The Nutrient Requirements of Ruminant Livestock. Supplement 1; CAB: Farnham Royal, UK, 1984. [Google Scholar]
- Galyean, M.L.; Tedeschi, L.O. Predicting Microbial Protein Synthesis in Beef Cattle: Relationship to Intakes of Total Digestible Nutrients and Crude Protein. J. Anim. Sci. 2014, 92, 5099–5111. [Google Scholar] [CrossRef] [PubMed]
- Thomas, C. Feed into Milk: A New Applied Feeding System for Dairy Cows: An Advisory Manual; Nottingham University Press: Nottingham, UK, 2004; ISBN 978-1-904761-26-6. [Google Scholar]
- Archimède, H.; Sauvant, D.; Schmidely, P. Quantitative Review of Ruminal and Total Tract Digestion of Mixed Diet Organic Matter and Carbohydrates. Reprod. Nutr. Dev. 1997, 37, 173–189. [Google Scholar] [CrossRef] [PubMed]
- Clark, J.H.; Klusmeyer, T.H.; Cameron, M.R. Microbial Protein Synthesis and Flows of Nitrogen Fractions to the Duodenum of Dairy Cows. J. Dairy Sci. 1992, 75, 2304–2323. [Google Scholar] [CrossRef]
- Ushida, K.; Kayouli, C.; De Smet, S.; Jouany, J.P. Effect of Defaunation on Protein and Fibre Digestion in Sheep Fed on Ammonia-Treated Straw-Based Diets with or without Maize. Br. J. Nutr. 1990, 64, 765–775. [Google Scholar] [CrossRef]
- Newbold, C.J. The Need for Nitrogen. Br. J. Nutr. 1999, 82, 81–82. [Google Scholar] [CrossRef]
- Brito, A.F.; Broderick, G.A. Effects of Different Protein Supplements on Milk Production and Nutrient Utilization in Lactating Dairy Cows. J. Dairy Sci. 2007, 90, 1816–1827. [Google Scholar] [CrossRef]
- Verite, R.; Journet, M.; Jarrige, R. A New System for the Protein Feeding of Ruminants: The PDI System. Livest. Prod. Sci. 1979, 6, 349–367. [Google Scholar] [CrossRef]
- Offer, N.W.; Axford, R.F.; Evans, R.A. The Effect of Dietary Energy Source in Nitrogen Metabolism in the Rumen of Sheep. Br. J. Nutr. 1978, 40, 35–44. [Google Scholar] [CrossRef]
- McAllan, A.B.; Smith, R.H. Degradation of Nucleic Acids in the Rumen. Br. J. Nutr. 1973, 29, 331–345. [Google Scholar] [CrossRef]
- Zinn, R.A.; Owens, F.N. Influence of Roughage Level and Feed Intake Level on Digestive Function. Okla. Agric. Exp. Stn. Misc. Publ. 1980, 107, 150–155. [Google Scholar]
- Djouvinov, D.S.; Todorov, N.A. Influence of Dry Matter Intake and Passage Rate on Microbial Protein Synthesis in the Rumen of Sheep and Its Estimation by Cannulation and a Non-Invasive Method. Anim. Feed Sci. Technol. 1994, 48, 289–304. [Google Scholar] [CrossRef]
- Chen, X.B.; Hovell, F.D.D.; Ørskov, E.R.; Brown, D.S. Excretion of Purine Derivatives by Ruminants: Effect of Exogenous Nucleic Acid Supply on Purine Derivative Excretion by Sheep. Br. J. Nutr. 1990, 63, 131–142. [Google Scholar] [CrossRef] [PubMed]
- Chen, X.B.; Gomes, M.J. Estimation of Microbial Protein Supply to Sheep and Cattle Based on Urinary Excretion of Purine Derivatives—An Overview of Technical Details. 1995. Available online: https://www.researchgate.net/profile/M-Gomes-2/publication/265323654_Estimation_of_Microbial_Protein_Supply_to_Sheep_and_Cattle_Based_on_Urinary_Excretion_of_Purine_Derivatives_-_An_Overview_of_Technical_Details/links/557579bc08aeb6d8c0195f72/Estimation-of-Microbial-Protein-Supply-to-Sheep-and-Cattle-Based-on-Urinary-Excretion-of-Purine-Derivatives-An-Overview-of-Technical-Details.pdf (accessed on 5 October 2023).
- Giesecke, D.; Ehrentreich, L.; Stangassinger, M.; Ahrens, F. Mammary and Renal Excretion of Purine Metabolites in Relation to Energy Intake and Milk Yield in Dairy Cows. J. Dairy Sci. 1994, 77, 2376–2381. [Google Scholar] [CrossRef]
- Polyorach, S.; Wanapat, M.; Cherdthong, A. Influence of Yeast Fermented Cassava Chip Protein (YEFECAP) and Roughage to Concentrate Ratio on Ruminal Fermentation and Microorganisms Using In Vitro Gas Production Technique. Asian-Australas. J. Anim. Sci. 2014, 27, 36–45. [Google Scholar] [CrossRef]
- Liu, L.; Zhang, W.; Yu, H.; Xu, L.; Qu, M.; Li, Y. Improved Antioxidant Activity and Rumen Fermentation in Beef Cattle under Heat Stress by Dietary Supplementation with Creatine Pyruvate. Anim. Sci. J. Nihon Chikusan Gakkaiho 2020, 91, e13486. [Google Scholar] [CrossRef]
- Cherdthong, A.; Wanapat, M.; Saenkamsorn, A.; Supapong, C.; Anantasook, N.; Gunun, P. Improving Rumen Ecology and Microbial Population by Dried Rumen Digesta in Beef Cattle. Trop. Anim. Health Prod. 2015, 47, 921–926. [Google Scholar] [CrossRef] [PubMed]
- Coneglian, S.M.; Serrano, R.D.C.; Cruz, O.T.B.; Branco, A.F. Effects of Essential Oils of Cashew and Castor on Intake, Digestibility, Ruminal Fermentation and Purine Derivatives in Beef Cattle Fed High Grain Diets. Semina Ciênc. Agrár. 2019, 40, 2057–2070. [Google Scholar] [CrossRef]
- Dias, A.O.C.; Goes, R.H.T.B.; Gandra, J.R.; Takiya, C.S.; Branco, A.F.; Jacaúna, A.G.; Oliveira, R.T.; Souza, C.J.S.; Vaz, M.S.M. Increasing Doses of Chitosan to Grazing Beef Steers: Nutrient Intake and Digestibility, Ruminal Fermentation, and Nitrogen Utilization. Anim. Feed Sci. Technol. 2017, 225, 73–80. [Google Scholar] [CrossRef]
- Ferreira, L.M.M.; Hervás, G.; Belenguer, A.; Celaya, R.; Rodrigues, M.A.M.; García, U.; Frutos, P.; Osoro, K. Comparison of Feed Intake, Digestion and Rumen Function among Domestic Ruminant Species Grazing in Upland Vegetation Communities. J. Anim. Physiol. Anim. Nutr. 2017, 101, 846–856. [Google Scholar] [CrossRef] [PubMed]
- Gionbelli, M.P.; de Campos Valadares Filho, S.; Detmann, E.; Paulino, P.V.R.; Valadares, R.F.D.; Santos, T.R.; e Silva, L.F.C.; Magalhães, F.A. Intake, Performance, Digestibility, Microbial Efficiency and Carcass Characteristics of Growing Nellore Heifers Fed Two Concentrate Levels. Rev. Bras. Zootec. 2012, 41, 1243–1252. [Google Scholar] [CrossRef]
- Hristov, A.N.; Ropp, J.K.; Grandeen, K.L.; Abedi, S.; Etter, R.P.; Melgar, A.; Foley, A.E. Effect of Carbohydrate Source on Ammonia Utilization in Lactating Dairy Cows. J. Anim. Sci. 2005, 83, 408–421. [Google Scholar] [CrossRef] [PubMed]
- Jardstedt, M.; Hessle, A.; Nørgaard, P.; Richardt, W.; Nadeau, E. Feed Intake and Urinary Excretion of Nitrogen and Purine Derivatives in Pregnant Suckler Cows Fed Alternative Roughage-Based Diets. Livest. Sci. 2017, 202, 82–88. [Google Scholar] [CrossRef]
- Koscheck, J.F.W.; Zervoudakis, J.T.; Hatamoto Zervoudakis, L.K.; da Silva Cabral, L.; de Oliveira, A.A.; Benatti, J.M.B.; de Carvalho, D.M.G.; da Silva, R.P. Total Digestible Nutrient Levels in Supplements for Finishing Steers in the Rainy Season: Nutritional Characteristics and Microbial Efficiency. Rev. Bras. Zootec. 2013, 42, 798–805. [Google Scholar] [CrossRef]
- Lin, S.X.; Wei, C.; Zhao, G.Y.; Zhang, T.T.; Yang, K. Effects of Supplementing Rare Earth Element Cerium on Rumen Fermentation, Nutrient Digestibility, Nitrogen Balance and Plasma Biochemical Parameters in Beef Cattle. J. Anim. Physiol. Anim. Nutr. 2015, 99, 1047–1055. [Google Scholar] [CrossRef]
- Wei, C.; Lin, S.; Wu, J.; Zhao, G.; Zhang, T.; Zheng, W. Supplementing Vitamin E to the Ration of Beef Cattle Increased the Utilization Efficiency of Dietary Nitrogen. Asian-Australas. J. Anim. Sci. 2016, 29, 372–377. [Google Scholar] [CrossRef]
- Liu, Q.; Wang, C.; Huang, Y.X.; Dong, K.H.; Yang, W.Z.; Zhang, S.L.; Wang, H. Effects of Isovalerate on Ruminal Fermentation, Urinary Excretion of Purine Derivatives and Digestibility in Steers. J. Anim. Physiol. Anim. Nutr. 2009, 93, 716–725. [Google Scholar] [CrossRef] [PubMed]
- Liu, Q.; Wang, C.; Yang, W.Z.; Dong, Q.; Dong, K.H.; Huang, Y.X.; Yang, X.M.; He, D.C. Effects of Malic Acid on Rumen Fermentation, Urinary Excretion of Purine Derivatives and Feed Digestibility in Steers. Animal 2009, 3, 32–39. [Google Scholar] [CrossRef]
- Liu, Q.; Wang, C.; Huang, Y.X.; Dong, K.H.; Yang, W.Z.; Wang, H. Effects of Lanthanum on Rumen Fermentation, Urinary Excretion of Purine Derivatives and Digestibility in Steers. Anim. Feed Sci. Technol. 2008, 142, 121–132. [Google Scholar] [CrossRef]
- Liu, Q.; Huang, Y.-X.; Wang, C.; Zhou, Y.; Wang, H. Effect of Selenium Methionine on Rumen Fermentation and Purine Derivatives in Simmental Steer. Chin. J. Eco-Agric. 2009, 17, 110–114. [Google Scholar] [CrossRef]
- Magalhaes, F.A.; de Campos Valadares Filho, S.; de Castro Menezes, G.C.; Pies Gionbelli, M.; Zanetti, D.; Grossi Machado, M.; dos Santos Pina, D.; Komura, K. Intake and Performance of Feedlot Cattle Fed Diets Based on High and Low Brix Sugar Cane with or without Calcium Oxide and Corn Silage. Rev. Bras. Zootec. 2012, 41, 6. [Google Scholar] [CrossRef]
- Pacheco, R.D.L.; Souza, J.M.; Marino, C.T.; Bastos, J.P.S.T.; Martins, C.L.; Rodrigues, P.H.M.; Arrigoni, M.D.B.; Millen, D.D. Ruminal Fermentation Pattern of Acidosis-Induced Cows Fed Either Monensin or Polyclonal Antibodies Preparation against Several Ruminal Bacteria. Front. Vet. Sci. 2023, 10, 1090107. [Google Scholar] [CrossRef]
- Polyorach, S.; Wanapat, M.; Wachirapakorn, C.; Navanukroaw, C.; Wanapat, S.; Nontaso, N. Supplementation of Yeast Fermented Liquid (YFL) and Coconut Oil on Rumen Fermentation Characteristics, N-Balance and Urinary Purine Derivatives in Beef Cattle. J. Anim. Vet. Adv. 2011, 10, 2084–2089. [Google Scholar] [CrossRef]
- Silva Júnior, J.M.; Rennó, L.N.; Valadares Filho, S.C.; Paulino, M.F.; Detmann, E.; Menezes, G.C.C.; Martins, T.S.; Paula, R.M.; Rodrigues, J.P.P.; Marcondes, M.I. Evaluation of Collection Days and Times to Estimate Urinary Excretion of Purine Derivatives and Nitrogen Compounds in Grazing Nellore Cattle. Livest. Sci. 2018, 217, 85–91. [Google Scholar] [CrossRef]
- Da Silva Júnior, J.M.; Rodrigues, J.P.P.; de Campos Valadares Filho, S.; Detmann, E.; Paulino, M.F.; Rennó, L.N. Estimating Purine Derivatives and Nitrogen Compound Excretion Using Total Urine Collection or Spot Urine Samples in Grazing Heifers. J. Anim. Physiol. Anim. Nutr. 2021, 105, 861–873. [Google Scholar] [CrossRef]
- Solanas, E.; Castrillo, C.; Fondevila, M.; Ruiz Narváez, Q.O.; Guada, J.A. Effects of Cereals and/or Protein Supplement Extrusion on Diet Utilisation and Performance of Intensively Reared Cattle. Livest. Sci. 2008, 117, 203–214. [Google Scholar] [CrossRef]
- Vieira de Barros, L.V.; Paulino, M.F.; Valadares Filho, S.C.; Detmann, E.; Silva, F.G.; Valente, E.E.L.; Lopes, S.A.; Martins, L.S. Replacement of Soybean Meal by Cottonseed Meal 38% in Multiple Supplements for Grazing Beef Heifers. Rev. Bras. Zootec. 2011, 40, 852–859. [Google Scholar] [CrossRef]
- Wang, C.; Liu, Q.; Meng, J.; Yang, W.Z.; Yang, X.M.; He, D.C.; Dong, K.H.; Huang, Y.X. Effects of Citric Acid Supplementation on Rumen Fermentation, Urinary Excretion of Purine Derivatives and Feed Digestibility in Steers. J. Sci. Food Agric. 2009, 89, 2302–2307. [Google Scholar] [CrossRef]
- Wang, C.; Liu, Q.; Guo, G.; Huo, W.J.; Ma, L.; Zhang, Y.L.; Pei, C.X.; Zhang, S.L.; Wang, H. Effects of Rumen-Protected Folic Acid on Ruminal Fermentation, Microbial Enzyme Activity, Cellulolytic Bacteria and Urinary Excretion of Purine Derivatives in Growing Beef Steers. Anim. Feed Sci. Technol. 2016, 221, 185–194. [Google Scholar] [CrossRef]
- Zhao, X.H.; Zhou, S.; Bao, L.B.; Song, X.Z.; Ouyang, K.H.; Xu, L.J.; Pan, K.; Liu, C.J.; Qu, M.R. Response of Rumen Bacterial Diversity and Fermentation Parameters in Beef Cattle to Diets Containing Supplemental Daidzein. Ital. J. Anim. Sci. 2018, 17, 643–649. [Google Scholar] [CrossRef]
- Zhou, J.W.; Zhong, C.L.; Liu, H.; Degen, A.A.; Titgemeyer, E.C.; Ding, L.M.; Shang, Z.H.; Guo, X.S.; Qiu, Q.; Li, Z.P.; et al. Comparison of Nitrogen Utilization and Urea Kinetics between Yaks (Bos grunniens) and Indigenous Cattle (Bos taurus). J. Anim. Sci. 2017, 95, 4600–4612. [Google Scholar] [CrossRef] [PubMed]
- Yang, K.; Wei, C.; Zhao, G.; Xu, Z.; Lin, S. Dietary Supplementation of Tannic Acid Modulates Nitrogen Excretion Pattern and Urinary Nitrogenous Constituents of Beef Cattle. Livest. Sci. 2016, 191, 148–152. [Google Scholar] [CrossRef]
- Wang, C.; Liu, Q.; Pei, C.X.; Li, H.Y.; Wang, Y.X.; Wang, H.; Bai, Y.S.; Shi, Z.G.; Liu, X.N.; Li, P. Effects of 2-Methylbutyrate on Rumen Fermentation, Ruminal Enzyme Activities, Urinary Excretion of Purine Derivatives and Feed Digestibility in Steers. Livest. Sci. 2012, 145, 160–166. [Google Scholar] [CrossRef]
- Wang, C.; Liu, Q.; Huo, W.J.; Yang, W.Z.; Dong, K.H.; Huang, Y.X.; Guo, G. Effects of Glycerol on Rumen Fermentation, Urinary Excretion of Purine Derivatives and Feed Digestibility in Steers. Livest. Sci. 2009, 121, 15–20. [Google Scholar] [CrossRef]
- Wanapat, M.; Totakul, P.; Viennasay, B.; Matra, M. Sunnhemp (Crotalaria juncea, L.) Silage Can Enrich Rumen Fermentation Process, Microbial Protein Synthesis, and Nitrogen Utilization Efficiency in Beef Cattle Crossbreds. Trop. Anim. Health Prod. 2021, 53, 187. [Google Scholar] [CrossRef]
- Norrapoke, T.; Pongjongmit, T.; Polyorach, S. Cassava Pulp Can Be Nutritionally Improved by Yeast and Various Crude Protein Levels Fed to Cattle. Anim. Prod. Sci. 2022, 62, 333–341. [Google Scholar] [CrossRef]
- Cherdthong, A.; Khonkhaeng, B.; Foiklang, S.; Wanapat, M.; Gunun, N.; Gunun, P.; Chanjula, P.; Polyorach, S. Effects of Supplementation of Piper Sarmentosum Leaf Powder on Feed Efficiency, Rumen Ecology and Rumen Protozoal Concentration in Thai Native Beef Cattle. Animals 2019, 9, 130. [Google Scholar] [CrossRef]
- Wanapat, M.; Kang, S.; Hankla, N.; Phesatcha, K. Effect of Rice Straw Treatment on Feed Intake, Rumen Fermentation and Milk Production in Lactating Dairy Cows. Afr J Agric Res 2013, 8, 1677–1687. [Google Scholar] [CrossRef]
- R Core Team. R: A Language and Environment for Statistical Computing; R Foundation for Statistical Computing: Vienna, Austria, 2022; Available online: https://www.R-project.org/ (accessed on 1 October 2023).
- Schauberger, P.; Walker, A. Openxlsx: Read, Write and Edit Xlsx Files. 2022. Available online: https://CRAN.R-project.org/package=openxlsx (accessed on 1 October 2023).
- Hegarty, R.S. Genotype Differences and Their Impact on Digestive Tract Function of Ruminants: A Review. Aust. J. Exp. Agric. 2004, 44, 459–467. [Google Scholar] [CrossRef]
- Prates, L.L.; Valadares, R.F.D.; Valadares Filho, S.C.; Detmann, E.; Santos, S.A.; Braga, J.M.S.; Pellizzoni, S.G.; Barbosa, K.S. Endogenous Fraction and Urinary Recovery of Purine Derivatives in Nellore and Holstein Heifers with Abomasal Purine Infusion. Livest. Sci. 2012, 150, 179–186. [Google Scholar] [CrossRef]
- Gandra, J.R.; Freitas, J.E.; Barletta, R.V.; Filho, M.M.; Gimenes, L.U.; Vilela, F.G.; Baruselli, P.S.; Rennó, F.P. Productive Performance, Nutrient Digestion and Metabolism of Holstein (Bos taurus) and Nellore (Bos taurus indicus) Cattle and Mediterranean Buffaloes (Bubalis bubalis) Fed with Corn-Silage Based Diets. Livest. Sci. 2011, 140, 283–291. [Google Scholar] [CrossRef]
- Zhu, W.; Liu, T.; Deng, J.; Wei, C.C.; Zhang, Z.J.; Wang, D.M.; Chen, X.Y. Microbiome-Metabolomics Analysis of the Effects of Decreasing Dietary Crude Protein Content on Goat Rumen Mictobiota and Metabolites. Anim. Biosci. 2022, 35, 1535–1544. [Google Scholar] [CrossRef] [PubMed]
- Guan, L.L.; Basarab, J.; Moore, S. Linkage of Microbial Ecology to Phenotype: Correlation of Rumen Microbial Ecology to Cattle’s Feed Efficiency. FEMS Microbiol. Lett. 2008, 288, 85–91. [Google Scholar] [CrossRef]
- Wallace, R.J.; Rooke, J.A.; McKain, N.; Duthie, C.-A.; Hyslop, J.J.; Ross, D.W.; Waterhouse, A.; Watson, M.; Roehe, R. The Rumen Microbial Metagenome Associated with High Methane Production in Cattle. BMC Genomics 2015, 16, 839. [Google Scholar] [CrossRef]
- Roehe, R.; Dewhurst, R.J.; Duthie, C.-A.; Rooke, J.A.; McKain, N.; Ross, D.W.; Hyslop, J.J.; Waterhouse, A.; Freeman, T.C.; Watson, M.; et al. Bovine Host Genetic Variation Influences Rumen Microbial Methane Production with Best Selection Criterion for Low Methane Emitting and Efficiently Feed Converting Hosts Based on Metagenomic Gene Abundance. PLoS Genet. 2016, 12, e1005846. [Google Scholar] [CrossRef]
- Auffret, M.D.; Stewart, R.; Dewhurst, R.J.; Duthie, C.-A.; Rooke, J.A.; Wallace, R.J.; Freeman, T.C.; Snelling, T.J.; Watson, M.; Roehe, R. Identification, Comparison, and Validation of Robust Rumen Microbial Biomarkers for Methane Emissions Using Diverse Bos taurus Breeds and Basal Diets. Front. Microbiol. 2018, 8, 2642. [Google Scholar] [CrossRef]
- Wang, H.; Zheng, H.; Browne, F.; Roehe, R.; Dewhurst, R.J.; Engel, F.; Hemmje, M.; Lu, X.; Walsh, P. Integrated Metagenomic Analysis of the Rumen Microbiome of Cattle Reveals Key Biological Mechanisms Associated with Methane Traits. Methods 2017, 124, 108–119. [Google Scholar] [CrossRef] [PubMed]
- Auffret, M.D.; Stewart, R.D.; Dewhurst, R.J.; Duthie, C.-A.; Watson, M.; Roehe, R. Identification of Microbial Genetic Capacities and Potential Mechanisms Within the Rumen Microbiome Explaining Differences in Beef Cattle Feed Efficiency. Front. Microbiol. 2020, 11, 1229. [Google Scholar] [CrossRef]
- Lima, J.; Auffret, M.D.; Stewart, R.D.; Dewhurst, R.J.; Duthie, C.-A.; Snelling, T.J.; Walker, A.W.; Freeman, T.C.; Watson, M.; Roehe, R. Identification of Rumen Microbial Genes Involved in Pathways Linked to Appetite, Growth, and Feed Conversion Efficiency in Cattle. Front. Genet. 2019, 10, 701. [Google Scholar] [CrossRef] [PubMed]
- Martínez-Álvaro, M.; Auffret, M.D.; Stewart, R.D.; Dewhurst, R.J.; Duthie, C.-A.; Rooke, J.A.; Wallace, R.J.; Shih, B.; Freeman, T.C.; Watson, M.; et al. Identification of Complex Rumen Microbiome Interaction Within Diverse Functional Niches as Mechanisms Affecting the Variation of Methane Emissions in Bovine. Front. Microbiol. 2020, 11, 659. [Google Scholar] [CrossRef] [PubMed]
- Martínez-Álvaro, M.; Auffret, M.D.; Duthie, C.-A.; Dewhurst, R.J.; Cleveland, M.A.; Watson, M.; Roehe, R. Bovine Host Genome Acts on Rumen Microbiome Function Linked to Methane Emissions. Commun. Biol. 2022, 5, 350. [Google Scholar] [CrossRef] [PubMed]
- Martínez-Álvaro, M.; Mattock, J.; Auffret, M.; Weng, Z.; Duthie, C.-A.; Dewhurst, R.J.; Cleveland, M.A.; Watson, M.; Roehe, R. Microbiome-Driven Breeding Strategy Potentially Improves Beef Fatty Acid Profile Benefiting Human Health and Reduces Methane Emissions. Microbiome 2022, 10, 166. [Google Scholar] [CrossRef] [PubMed]
- Danielsson, R.; Dicksved, J.; Sun, L.; Gonda, H.; Müller, B.; Schnürer, A.; Bertilsson, J. Methane Production in Dairy Cows Correlates with Rumen Methanogenic and Bacterial Community Structure. Front. Microbiol. 2017, 8, 226. [Google Scholar] [CrossRef]
- Gebreyesus, G.; Difford, G.F.; Buitenhuis, B.; Lassen, J.; Noel, S.J.; Højberg, O.; Plichta, D.R.; Zhu, Z.; Poulsen, N.A.; Sundekilde, U.K.; et al. Predictive Ability of Host Genetics and Rumen Microbiome for Subclinical Ketosis. J. Dairy Sci. 2020, 103, 4557–4569. [Google Scholar] [CrossRef]
- Buitenhuis, B.; Lassen, J.; Noel, S.J.; Plichta, D.R.; Sørensen, P.; Difford, G.F.; Poulsen, N.A. Impact of the Rumen Microbiome on Milk Fatty Acid Composition of Holstein Cattle. Genet. Sel. Evol. 2019, 51, 23. [Google Scholar] [CrossRef] [PubMed]
- Xue, M.-Y.; Sun, H.-Z.; Wu, X.-H.; Liu, J.-X.; Guan, L.L. Multi-Omics Reveals That the Rumen Microbiome and Its Metabolome Together with the Host Metabolome Contribute to Individualized Dairy Cow Performance. Microbiome 2020, 8, 64. [Google Scholar] [CrossRef]
- Arambel, M.J.; Bartley, E.E.; Dufva, G.S.; Nagaraja, T.G.; Dayton, A.D. Effect of Diet on Amino and Nucleic Acids of Rumen Bacteria and Protozoa. J. Dairy Sci. 1982, 65, 2095–2101. [Google Scholar] [CrossRef] [PubMed]
- Bates, D.B.; Gillett, J.A.; Barao, S.A.; Bergen, W.G. The Effect of Specific Growth Rate and Stage of Growth on Nucleic Acid-Protein Values of Pure Cultures and Mixed Ruminal Bacteria. J. Anim. Sci. 1985, 61, 713–724. [Google Scholar] [CrossRef]
- Muscarella, M.E.; Howey, X.M.; Lennon, J.T. Trait-Based Approach to Bacterial Growth Efficiency. Environ. Microbiol. 2020, 22, 3494–3504. [Google Scholar] [CrossRef] [PubMed]
- Russell, J.B.; Baldwin, R.L. Comparison of Maintenance Energy Expenditures and Growth Yields among Several Rumen Bacteria Grown on Continuous Culture. Appl. Environ. Microbiol. 1979, 37, 537–543. [Google Scholar] [CrossRef] [PubMed]
- Russell, J.B.; Cook, G.M. Energetics of Bacterial Growth: Balance of Anabolic and Catabolic Reactions. Microbiol. Rev. 1995, 59, 48–62. [Google Scholar] [CrossRef] [PubMed]
Reference | Predicted MPS |
---|---|
ARC (1980) [19] | 7.81 × ME intake (MJ/day) |
ARC (1984)—Well balanced mixed diets [20] | 8.4 × ME intake (MJ/day) |
ARC (1984)—Solely grass silage [20] | 6.25 × ME intake (MJ/day) |
ARC (1984)—Grass silage & concentrates [20] | 8.75 × ME intake (MJ/day) |
AFRC (1992) equation ǂ—Applied to maintenance level of intake [17] | 8.8 × FME intake (MJ/day) |
AFRC (1992) equation ǂ—Applied to 2× maintenance level of intake [17] | 10.0 × FME intake (MJ/day) |
AFRC (1992) equation ǂ—Applied to 3× maintenance level of intake [17] | 10.9 × FME intake (MJ/day) |
AFRC (1992) equation ǂ—Applied to 4× maintenance level of intake [17] | 11.5 × FME intake (MJ/day) |
NASEM (2016): beef cattle—Based on Galyean and Tedeschi (2014) (for dietary EE < 3.9% DM) [21] | 42.73 + 0.087 × TDN intake (g/day) |
NASEM (2016): beef cattle—Based on Galyean and Tedeschi (2014) (for dietary EE > 3:9% DM) [21] | 53.33 + 0.096 × FFTDN intake (g/day) |
UPD | CP | NDF | DMI | DMI/Weight | CP/NDF | |
---|---|---|---|---|---|---|
UPD | 0.55 * | −0.44 * | 0.16 | −0.04 | 0.56 * | |
CP | 0.36 * | −0.61 * | −0.17 | 0.03 | 0.81 * | |
NDF | −0.28 * | −0.40 * | −0.05 | −0.43 * | −0.91 * | |
DMI | 0.38 * | 0.10 | 0.06 | 0.29 | −0.18 | |
DMI/weight | 0.03 | 0.26 | −0.10 | 0.57 * | 0.22 | |
CP/NDF | 0.31 * | 0.71 * | −0.86 * | −0.03 | 0.20 |
Species | Bos taurus | Bos indicus |
---|---|---|
Explained variance (R2) | 34% | 45% |
Explanatory variables | CP/NDF + DMI + DMI/weight | CP/NDF + DMI + DMI/weight + DMIDMI/weight |
p-value | 0.00000154 | 0.00000172 |
Regression coefficients | ||
Intercept | 3.86 | 3.15 |
CP/NDF | 1.20 | 1.11 |
DMI | 0.10 | 0.22 |
DMI/weight | −32.59 | 26.88 |
DMI*DMI/weight | NA | −5.15 |
Reference | Trait (Units) | Range | Omics Technique | % of Variation Explained |
---|---|---|---|---|
[76] | RFI (kg/d) | −1.38 ± 0.14 to 1.40 ± 0.12 | PGR-DGGE | Rumen bacterial profiles clustered separately for highly and lowly efficient animals |
Metabolomics | Animals with varying RFI had different rumen VFA concentrations | |||
[77] | CH4 (g/kg DMI) | 13.43 to 25.26 | Metataxonomics | High emitters and low emitters differed due to 9 bacterial phyla, 5 bacterial genera, 1 archaeal phylum, and 2 archaeal genera |
Metagenomics | 88% (20 microbial genes + diet) | |||
[78] | CH4 (g/kg DMI) | 14.4 to 31.4 | Metagenomics | 81% (20 microbial genes) |
FCR (DMI kg/ADG kg) | 6.1 to 10.4 | Metagenomics | 86% (49 microbial genes) | |
[79] | CH4 (g/kg DMI) | 20.89 ± 0.75 | Metagenomics | 62% (37 microbial genes + diet + breed) |
Metataxonomics | 50% (56 microbial genera + diet + breed) | |||
Metagenomics + metataxonomics | 42% (37 microbiome factors including microbial genes, microbial genera, diversity indices, and A:B ratio) | |||
[80] | CH4 (g/kg DMI) | 7.64 to 30.37 | Metagenomics | Identification of 3 clusters of 237, 91, and 41 genes divergent between high and low methane emitters. Out of 91, 36 genes were in the methane metabolism pathway |
[81] | Feed efficiency (FCR, RFI) | Metagenomics | 379 microbial genera out of 1058 significantly diverged between animal groups (high efficiency vs. low efficiency) | |
FCR | 5.11 to 11.91 | Metagenomics | 39% (8 microbial genes) | |
Metataxonomics | 60% (45 microbial genes) | |||
RFI | −1.52 to 1.58 | Metagenomics | 40% (8 microbial genes) | |
Metataxonomics | 52% (85 microbial genera) | |||
[82] | FCR | 5.16 to 11.91 | Metagenomics | 63% (20 microbial genes) |
ADG | 0.89 to 2.12 | 65% (14 microbial genes) | ||
DFI | 8.52 to 18.76 | 66% (17 microbial genes) | ||
RFI | −1.76 to 4.16 | 73% (18 microbial genes) | ||
[83] | CH4 (g/kg DMI) | 17.56 with CV of 0.13 | Metagenomics | 57% (5 microbiome features representing a methanogenic cluster) 50% and 38% (sets of 5 microbiome features representing groups of fibre-degrading microbes) |
[84] | CH4 (g/kg DMI) | Mean = 13.47 | Genomics and metagenomics | 166 microbiome features (including microbial genes, genera, and metagenome-assembled and uncultured genomes) had genetic correlations between |0.59| and |0.93| with methane emissions |
[85] | Fatty acid profiles + CH4 | NA | Genomics and metagenomics | 27.6% (1002 microbial genes) of the functional core microbiome (3631 microbial genes) has heritability from 0.20 to 0.58 372 heritable microbial genes were involved in microbial metabolic pathways associated with unsaturated fatty acids with health benefits for humans (N3), hypercholesterolemic saturated fatty acids (CLA), or both. Microbiome-driven breeding of animals for improved N3 and CLA would include 31 microbial genes. A correlated response to selection on methane emissions ranged from reductions of 4% to 9% per generation (depending on intensity of selection) |
Reference | Trait (Units) | Range | Omics Technique | % of Variation Explained |
---|---|---|---|---|
[86] | CH4 (g/d) | 282 to 408 | Metataxonomics | 26 OTUs divergent between high and low emitters |
[87] | Acetone (AC) and β-hydroxybutyric acid (BHB)—susceptibility to ketosis | MeanAC = 0.57 with CV 1.24; MeanBHB = 0.89 with CV 0.59 | Metataxonomics | 15% |
[88] | Milk protein (%) | 3.33 ± 0.35 | Metataxonomics | 8% |
Milk fat (%) | 4.00 ± 0.77 | Metataxonomics | 8% | |
Fatty acids in milk (C15:0) (%) | 1.11 ± 0.24 | Metataxonomics | 42% | |
Fatty acids in milk (C18:3 n − 3) (%) | 0.53 ± 0.09 | Metataxonomics | 31% | |
[89] | Milk protein yield (kg/d) | MeanLOW = 0.70 and meanHIGH = 1.23 | Metataxonomics | 18% |
Metagenomics | 22% | |||
Metabolomics | 30% |
Disclaimer/Publisher’s Note: The statements, opinions and data contained in all publications are solely those of the individual author(s) and contributor(s) and not of MDPI and/or the editor(s). MDPI and/or the editor(s) disclaim responsibility for any injury to people or property resulting from any ideas, methods, instructions or products referred to in the content. |
© 2023 by the authors. Licensee MDPI, Basel, Switzerland. This article is an open access article distributed under the terms and conditions of the Creative Commons Attribution (CC BY) license (https://creativecommons.org/licenses/by/4.0/).
Share and Cite
Lima, J.; Ingabire, W.; Roehe, R.; Dewhurst, R.J. Estimating Microbial Protein Synthesis in the Rumen—Can ‘Omics’ Methods Provide New Insights into a Long-Standing Question? Vet. Sci. 2023, 10, 679. https://doi.org/10.3390/vetsci10120679
Lima J, Ingabire W, Roehe R, Dewhurst RJ. Estimating Microbial Protein Synthesis in the Rumen—Can ‘Omics’ Methods Provide New Insights into a Long-Standing Question? Veterinary Sciences. 2023; 10(12):679. https://doi.org/10.3390/vetsci10120679
Chicago/Turabian StyleLima, Joana, Winfred Ingabire, Rainer Roehe, and Richard James Dewhurst. 2023. "Estimating Microbial Protein Synthesis in the Rumen—Can ‘Omics’ Methods Provide New Insights into a Long-Standing Question?" Veterinary Sciences 10, no. 12: 679. https://doi.org/10.3390/vetsci10120679
APA StyleLima, J., Ingabire, W., Roehe, R., & Dewhurst, R. J. (2023). Estimating Microbial Protein Synthesis in the Rumen—Can ‘Omics’ Methods Provide New Insights into a Long-Standing Question? Veterinary Sciences, 10(12), 679. https://doi.org/10.3390/vetsci10120679