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Tseten T, Sanjorjo RA, Son JW, Baik KS, Berdos JI, Kim SH, Yoon SH, Kang MK, Kwon M, Lee SS, Kim SW. Reduction of enteric methane emission using methanotroph-based probiotics in Hanwoo steers. Anim Microbiome 2025; 7:19. [PMID: 39987198 PMCID: PMC11846464 DOI: 10.1186/s42523-025-00385-0] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 11/27/2024] [Accepted: 02/18/2025] [Indexed: 02/24/2025] Open
Abstract
BACKGROUND Methane emission from enteric rumen fermentation is a main source of greenhouse gas (GHG) emission and a major concern for global warming. RESULTS In this study, we isolated methanotroph-methylotroph consortium NC52PC from the rumen after a series of sub-culture and repetitive streaking on an agar plate and polycarbonate membrane filter. The NC52PC comprises methanotroph species (Methylocystis sp.) and methylotroph species (Methylobacterium sp.), forming a consortium capable of growing solely on methane as a carbon source. Their morphology, growth, and genome sequence were characterized. We assessed its effectiveness in mitigating methane emissions through both in vitro and in vivo experiments. During the in vitro trial, the introduction of NC52PC (at a concentration of 5.1 × 107 CFUs/ml) demonstrated a reduction in methane production exceeding 40% and 50% after 12 and 24 h, respectively. Also, NC52PC did not significantly alter other aspects of the in vitro rumen fermentation parameters such as pH, total gas production, and digestibility. Further investigation involved testing NC52PC as a dietary supplement in 12 young Hanwoo steers over three 30-day test periods. The steers received a diet comprising 70.8% concentrate and 29.2% bluegrass on a dry matter basis, with variations including 3 × 107 CFUs/ml of NC52PC (LOW) and 3 × 108 CFUs/ml (HIGH) of NC52PC, and without NC52PC as a control (CON). Steers administered with HIGH and LOW concentrations of NC52PC exhibited reduced enteric methane emission (g/day) by 14.4% and 12.0%, respectively. CONCLUSION Feeding methanotroph-methylotroph consortium NC52PC significantly reduced methane emissions in Korean beef cattle without any adverse effects on animal health. These findings suggest that this probiotic could serve as a promising feed additive to effectively mitigate methane emissions from ruminants. However, further research is needed to evaluate the long-term effects of NC52PC on animal health, and on meat and milk quality.
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Affiliation(s)
- Tenzin Tseten
- Anti-Aging Bio Cell Factory Regional Leading Research Center, Gyeongsang National University, Jinju, 52828, Republic of Korea
- Division of Applied Life Science (BK21 Four), Gyeongsang National University, Jinju, 52828, Republic of Korea
| | - Rey Anthony Sanjorjo
- Anti-Aging Bio Cell Factory Regional Leading Research Center, Gyeongsang National University, Jinju, 52828, Republic of Korea
- Division of Applied Life Science (BK21 Four), Gyeongsang National University, Jinju, 52828, Republic of Korea
| | - Jong-Wook Son
- Anti-Aging Bio Cell Factory Regional Leading Research Center, Gyeongsang National University, Jinju, 52828, Republic of Korea
- Division of Applied Life Science (BK21 Four), Gyeongsang National University, Jinju, 52828, Republic of Korea
| | - Keun Sik Baik
- Ruminant Nutrition and Anaerobe Laboratory, Department of Animal Science and Technology, Sunchon National University, 413 Jungangro, Suncheon, Jeonnam, 57922, Republic of Korea
| | - Janine I Berdos
- Ruminant Nutrition and Anaerobe Laboratory, Department of Animal Science and Technology, Sunchon National University, 413 Jungangro, Suncheon, Jeonnam, 57922, Republic of Korea
- Department of Animal Science, College of Agriculture and Forestry, Tarlac Agricultural University, Camiling, Tarlac, 2306, Philippines
| | - Seon-Ho Kim
- Ruminant Nutrition and Anaerobe Laboratory, Department of Animal Science and Technology, Sunchon National University, 413 Jungangro, Suncheon, Jeonnam, 57922, Republic of Korea
| | - Sang-Hwal Yoon
- Anti-Aging Bio Cell Factory Regional Leading Research Center, Gyeongsang National University, Jinju, 52828, Republic of Korea
| | - Min-Kyoung Kang
- Anti-Aging Bio Cell Factory Regional Leading Research Center, Gyeongsang National University, Jinju, 52828, Republic of Korea
| | - Moonhyuk Kwon
- Anti-Aging Bio Cell Factory Regional Leading Research Center, Gyeongsang National University, Jinju, 52828, Republic of Korea
- Division of Applied Life Science (BK21 Four), Gyeongsang National University, Jinju, 52828, Republic of Korea
- Research Institute of Molecular Alchemy, Gyeongsang National University, Jinju, 52828, Republic of Korea
| | - Sang-Suk Lee
- Ruminant Nutrition and Anaerobe Laboratory, Department of Animal Science and Technology, Sunchon National University, 413 Jungangro, Suncheon, Jeonnam, 57922, Republic of Korea.
| | - Seon-Won Kim
- Anti-Aging Bio Cell Factory Regional Leading Research Center, Gyeongsang National University, Jinju, 52828, Republic of Korea.
- Division of Applied Life Science (BK21 Four), Gyeongsang National University, Jinju, 52828, Republic of Korea.
- Plant Molecular Biology & Biotechnology Research Center, Gyeongsang National University, Jinju, 52828, Republic of Korea.
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Belanche A, Bannink A, Dijkstra J, Durmic Z, Garcia F, Santos FG, Huws S, Jeyanathan J, Lund P, Mackie RI, McAllister TA, Morgavi DP, Muetzel S, Pitta DW, Yáñez-Ruiz DR, Ungerfeld EM. Feed additives for methane mitigation: A guideline to uncover the mode of action of antimethanogenic feed additives for ruminants. J Dairy Sci 2025; 108:375-394. [PMID: 39725503 DOI: 10.3168/jds.2024-25046] [Citation(s) in RCA: 2] [Impact Index Per Article: 2.0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 04/15/2024] [Accepted: 08/27/2024] [Indexed: 12/28/2024]
Abstract
This publication aims to provide guidelines of the knowledge required and the potential research to be conducted in order to understand the mode of action of antimethanogenic feed additives (AMFA). In the first part of the paper, we classify AMFA into 4 categories according to their mode of action: (1) lowering dihydrogen (H2) production; (2) inhibiting methanogens; (3) promoting alternative H2-incorporating pathways; and (4) oxidizing methane (CH4). The second part of the paper presents questions that guide the research to identify the mode of action of an AMFA on the rumen CH4 production from 5 different perspectives: (1) microbiology; (2) cell and molecular biochemistry; (3) microbial ecology; (4) animal metabolism; and (5) cross-cutting aspects. Recommendations are provided to address various research questions within each perspective, along with examples of how aspects of the mode of action of AMFA have been elucidated before. In summary, this paper offers timely and comprehensive guidelines to better understand and reveal the mode of action of current and emerging AMFA.
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Affiliation(s)
- Alejandro Belanche
- Departamento de Producción Animal y Ciencia de los Alimentos, Universidad de Zaragoza, 50013 Zaragoza, Spain.
| | - André Bannink
- Wageningen Livestock Research, Wageningen University & Research, 6700 AH Wageningen, the Netherlands
| | - Jan Dijkstra
- Animal Nutrition Group, Wageningen University & Research, 6700 AH Wageningen, the Netherlands
| | - Zoey Durmic
- The University of Western Australia, Crawley, WA 6009, Australia
| | - Florencia Garcia
- Universidad Nacional de Córdoba, Facultad de Ciencias Agropecuarias, 5000 Córdoba, Argentina
| | - Fernanda G Santos
- School of Biological Sciences, Institute for Global Food Security, Queen's University Belfast, Belfast BT9 5DL, United Kingdom
| | - Sharon Huws
- School of Biological Sciences, Institute for Global Food Security, Queen's University Belfast, Belfast BT9 5DL, United Kingdom
| | - Jeyamalar Jeyanathan
- Laboratory for Animal Nutrition and Animal Product Quality, Department of Animal Sciences and Aquatic Ecology, Faculty of Bioscience Engineering, Ghent University, 9000 Ghent, Belgium
| | - Peter Lund
- Department of Animal and Veterinary Sciences, AU Viborg - Research Centre Foulum, Aarhus University, 8830 Tjele, Denmark
| | - Roderick I Mackie
- Department of Animal Sciences, University of Illinois at Urbana-Champaign, Urbana, IL 61801
| | - Tim A McAllister
- Agriculture and Agri-Food Canada, Lethbridge, AB T1J 4B1, Canada
| | - Diego P Morgavi
- Université Clermont Auvergne, INRAE, VetAgro Sup, UMR Herbivores, F-63122 Saint-Genes-Champanelle, France
| | | | - Dipti W Pitta
- School of Veterinary Medicine, New Bolton Center, University of Pennsylvania, Kennett Square, PA 19384
| | | | - Emilio M Ungerfeld
- Instituto de Investigaciones Agropecuarias - Centro Regional de Investigación Carillanca, 4880000 Vilcún, La Araucanía, Chile.
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Bao J, Wang L, Li S, Guo J, Ma P, Huang X, Guo G, Zhang H, Wang Y. Screening and Functional Prediction of Rumen Microbiota Associated with Methane Emissions in Dairy Cows. Animals (Basel) 2024; 14:3195. [PMID: 39595248 PMCID: PMC11591143 DOI: 10.3390/ani14223195] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 10/04/2024] [Revised: 11/01/2024] [Accepted: 11/06/2024] [Indexed: 11/28/2024] Open
Abstract
Agricultural activities are a significant contributor to global greenhouse gas emissions, accounting for 14.5% of total anthropogenic emissions. Specifically, greenhouse gas emissions from beef cattle and dairy cattle constitute 35% and 30% of total global livestock emissions, respectively. This study focuses on dairy cattle, exploring the complex relationships between rumen microbiota and methane emission. The methane emissions of 968 lactating Holstein cows were measured using a laser methane detector (LMD, Shanghai Hesai Technology Co., Ltd., Shanghai, China). Among the measured cows, 107 individuals were further selected into high (HME) and low methane-emitting (LME) groups, including 50 cows in the HME group and 57 in the LME group. This study analyzed differences in rumen microbiota and microbial functions between cows with varying levels of methane emissions. The results showed significant differences in the Simpson and Pielou indices of rumen bacterial communities between the HME and LME groups. Beta diversity analysis revealed significant differences in microbial community structure between the two groups. It was found that the abundance of Bacteroidales and Prevotellaceae in the rumen of cows in the HME group cows was significantly higher than that of cows in the LME group (LDA > 3, p < 0.05). Additionally, bacterial functions related to biosynthesis and carbohydrate metabolism were more active in the HME group. This study revealed distinct differences in the rumen bacterial communities between HME and LME cow in Chinese Holstein cattle, and identified specific bacteria and their functional differences in the HME group. The microbial characteristics and metabolic pathways provide new insights for developing strategies to reduce methane emissions, supporting the sustainable development of the dairy industry.
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Affiliation(s)
- Jiatai Bao
- Laboratory of Animal Genetics, Breeding and Reproduction, Ministry of Agriculture of China, National Engineering Laboratory of Animal Breeding, State Key Laboratory of Animal Biotech Breeding, College of Animal Science and Technology, China Agricultural University, Beijing 100193, China; (J.B.); (L.W.); (S.L.); (J.G.)
- College of Animal Science, Xinjiang Agricultural University, Urumqi 830052, China; (P.M.); (X.H.)
| | - Lei Wang
- Laboratory of Animal Genetics, Breeding and Reproduction, Ministry of Agriculture of China, National Engineering Laboratory of Animal Breeding, State Key Laboratory of Animal Biotech Breeding, College of Animal Science and Technology, China Agricultural University, Beijing 100193, China; (J.B.); (L.W.); (S.L.); (J.G.)
| | - Shanshan Li
- Laboratory of Animal Genetics, Breeding and Reproduction, Ministry of Agriculture of China, National Engineering Laboratory of Animal Breeding, State Key Laboratory of Animal Biotech Breeding, College of Animal Science and Technology, China Agricultural University, Beijing 100193, China; (J.B.); (L.W.); (S.L.); (J.G.)
| | - Jiahe Guo
- Laboratory of Animal Genetics, Breeding and Reproduction, Ministry of Agriculture of China, National Engineering Laboratory of Animal Breeding, State Key Laboratory of Animal Biotech Breeding, College of Animal Science and Technology, China Agricultural University, Beijing 100193, China; (J.B.); (L.W.); (S.L.); (J.G.)
| | - Pan Ma
- College of Animal Science, Xinjiang Agricultural University, Urumqi 830052, China; (P.M.); (X.H.)
| | - Xixia Huang
- College of Animal Science, Xinjiang Agricultural University, Urumqi 830052, China; (P.M.); (X.H.)
| | - Gang Guo
- Beijing Sunlon Livestock Development Company Limited, Beijing 100029, China;
| | - Hailiang Zhang
- Laboratory of Animal Genetics, Breeding and Reproduction, Ministry of Agriculture of China, National Engineering Laboratory of Animal Breeding, State Key Laboratory of Animal Biotech Breeding, College of Animal Science and Technology, China Agricultural University, Beijing 100193, China; (J.B.); (L.W.); (S.L.); (J.G.)
| | - Yachun Wang
- Laboratory of Animal Genetics, Breeding and Reproduction, Ministry of Agriculture of China, National Engineering Laboratory of Animal Breeding, State Key Laboratory of Animal Biotech Breeding, College of Animal Science and Technology, China Agricultural University, Beijing 100193, China; (J.B.); (L.W.); (S.L.); (J.G.)
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Marcos CN, Carro MD, Gutiérrez-Rivas M, Atxaerandio R, Goiri I, García-Rodríguez A, González-Recio O. Ruminal microbiome changes across lactation in primiparous Holstein cows with varying methane intensity: Heritability assessment. J Dairy Sci 2024; 107:7064-7078. [PMID: 38788852 DOI: 10.3168/jds.2023-24552] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 12/15/2023] [Accepted: 04/02/2024] [Indexed: 05/26/2024]
Abstract
Methane is a potent greenhouse gas produced during the ruminal fermentation and is associated with a loss of feed energy. Therefore, efforts to reduce methane emissions have been ongoing in the last decades. Methane production is highly influenced by factors such as the ruminal microbiome and host genetics. Previous studies have proposed to use the ruminal microbiome to reduce long-term methane emissions, as ruminal microbiome composition is a moderately heritable trait and genetic improvement accumulates over time. Lactation stage is another important factor that might influence methane production, but potential associations with the ruminal microbiome have not been evaluated previously. This study sought to examine the changes in ruminal microbiome over the lactation period of primiparous Holstein cows differing in methane intensity (MI) and estimate the heritability of the abundance of relevant microorganisms. Ruminal content samples from 349 primiparous Holstein cows with 14 to 378 DIM were collected from May 2018 to June 2019. Methane intensity of each cow was calculated as methane concentration/milk yield. Up to 64 taxonomic features (TF) from 20 phyla had a significant differential abundance between cows with low and high MI early in lactation, 16 TF during mid lactation, and none late in lactation. Taxonomical features within the Firmicutes, Proteobacteria, Melainabacteria, Cyanobacteria, Bacteroidetes, and Actinobacteria phyla were associated with low MI, whereas eukaryotic TF and those within the Euryarchaeota, Verrucomicrobia, Kiritimatiellaeota, and Lentisphaerae phyla were associated with high MI. Out of the 60 TF that were found to be differentially abundant between early and late lactation in cows with low MI, 56 TF were also significant when cows with low and high MI were compared in the first third of the lactation. In general, microbes associated with low MI were more abundant early in lactation (e.g., Acidaminococcus, Aeromonas, and Weimeria genera) and showed low to moderate heritabilities (0.03 to 0.33). These results suggest some potential to modulate the rumen microbiome composition through selective breeding for lower MI. Differences in the ruminal microbiome of cows with extreme MI levels likely result from variations in the ruminal physiology of these cows and were more noticeable early in lactation, probably due to important interactions between the host phenotype and environmental factors associated with that period. Our results suggest that the ruminal microbiome evaluated early in lactation may be more precise for MI difference, and hence, this should be considered to optimize sampling periods to establish a reference population in genomic selection scenarios.
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Affiliation(s)
- C N Marcos
- Departamento de Producción Agraria, ETSIAAB, Universidad Politécnica de Madrid, Ciudad Universitaria, 28040 Madrid, Spain; Departamento de Mejora Genética Animal, Instituto Nacional de Investigación y Tecnología Agraria y Alimentaria-CSIC, 28040 Madrid, Spain.
| | - M D Carro
- Departamento de Producción Agraria, ETSIAAB, Universidad Politécnica de Madrid, Ciudad Universitaria, 28040 Madrid, Spain
| | - M Gutiérrez-Rivas
- Departamento de Mejora Genética Animal, Instituto Nacional de Investigación y Tecnología Agraria y Alimentaria-CSIC, 28040 Madrid, Spain
| | - R Atxaerandio
- NEIKER-Instituto Vasco de Investigación y Desarrollo Agrario, Basque Research and Technology Alliance (BRTA), Campus Agroalimentario de Arkaute s/n, 01192 Arkaute, Spain
| | - I Goiri
- NEIKER-Instituto Vasco de Investigación y Desarrollo Agrario, Basque Research and Technology Alliance (BRTA), Campus Agroalimentario de Arkaute s/n, 01192 Arkaute, Spain
| | - A García-Rodríguez
- NEIKER-Instituto Vasco de Investigación y Desarrollo Agrario, Basque Research and Technology Alliance (BRTA), Campus Agroalimentario de Arkaute s/n, 01192 Arkaute, Spain
| | - O González-Recio
- Departamento de Mejora Genética Animal, Instituto Nacional de Investigación y Tecnología Agraria y Alimentaria-CSIC, 28040 Madrid, Spain.
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Sato Y, Shioya H, Uda Y, Asano H, Nagao Y, Kuno H, Yoshizawa F. Effects of two types of Coccomyxa sp. KJ on in vitro ruminal fermentation, methane production, and the rumen microbiota. PLoS One 2024; 19:e0308646. [PMID: 39173024 PMCID: PMC11341058 DOI: 10.1371/journal.pone.0308646] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 05/08/2024] [Accepted: 07/26/2024] [Indexed: 08/24/2024] Open
Abstract
Coccomyxa sp. KJ is a unicellular green microalga that accumulates abundant lipids when cultured under nitrogen-deficient conditions (KJ1) and high nitrogen levels when cultured under nitrogen-sufficient conditions (KJ2). Considering the different characteristics between KJ1 and KJ2, they are expected to have different effects on rumen fermentation. This study aimed to determine the effects of KJ1 and KJ2 on in vitro ruminal fermentation, digestibility, CH4 production, and the ruminal microbiome as corn silage substrate condition. Five treatments were evaluated: substrate only (CON) and CON + 0.5% dry matter (DM) KJ1 (KJ1_L), 1.0% DM KJ1 (KJ1_H), 0.5% DM KJ2 (KJ2_L), and 1.0% DM KJ2 (KJ2_H). DM degradability-adjusted CH4 production was inhibited by 48.4 and 40.8% in KJ2_L and KJ2_H, respectively, compared with CON. The proportion of propionate was higher in the KJ1 treatments than the CON treatment and showed further increases in the KJ2 treatments. The abundances of Megasphaera, Succiniclasticum, Selenomonas, and Ruminobacter, which are related to propionate production, were higher in KJ2_H than in CON. The results suggested that the rumen microbiome was modified by the addition of 0.5-1.0% DM KJ1 and KJ2, resulting in increased propionate and reduced CH4 production. In particular, the KJ2 treatments inhibited ruminal CH4 production more than the KJ1 treatments. These findings provide important information for inhibiting ruminal CH4 emissions, which is essential for increasing animal productivity and sustaining livestock production under future population growth.
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Affiliation(s)
- Yoshiaki Sato
- Department of Agrobiology and Bioresources, School of Agriculture, Utsunomiya University, Tochigi, Japan
| | - Honoka Shioya
- Department of Agrobiology and Bioresources, School of Agriculture, Utsunomiya University, Tochigi, Japan
| | - Yuma Uda
- University Farm, School of Agriculture, Utsunomiya University, Tochigi, Japan
| | - Hiroshi Asano
- University Farm, School of Agriculture, Utsunomiya University, Tochigi, Japan
| | - Yoshikazu Nagao
- University Farm, School of Agriculture, Utsunomiya University, Tochigi, Japan
| | | | - Fumiaki Yoshizawa
- Department of Agrobiology and Bioresources, School of Agriculture, Utsunomiya University, Tochigi, Japan
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Shinkai T, Takizawa S, Enishi O, Higuchi K, Ohmori H, Mitsumori M. Characteristics of rumen microbiota and Prevotella isolates found in high propionate and low methane-producing dairy cows. Front Microbiol 2024; 15:1404991. [PMID: 38887715 PMCID: PMC11180796 DOI: 10.3389/fmicb.2024.1404991] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 03/22/2024] [Accepted: 05/21/2024] [Indexed: 06/20/2024] Open
Abstract
Ruminal methane production is the main sink for metabolic hydrogen generated during rumen fermentation, and is a major contributor to greenhouse gas (GHG) emission. Individual ruminants exhibit varying methane production efficiency; therefore, understanding the microbial characteristics of low-methane-emitting animals could offer opportunities for mitigating enteric methane. Here, we investigated the association between rumen fermentation and rumen microbiota, focusing on methane production, and elucidated the physiological characteristics of bacteria found in low methane-producing cows. Thirteen Holstein cows in the late lactation stage were fed a corn silage-based total mixed ration (TMR), and feed digestion, milk production, rumen fermentation products, methane production, and rumen microbial composition were examined. Cows were classified into two ruminal fermentation groups using Principal component analysis: low and high methane-producing cows (36.9 vs. 43.2 L/DMI digested) with different ruminal short chain fatty acid ratio [(C2+C4)/C3] (3.54 vs. 5.03) and dry matter (DM) digestibility (67.7% vs. 65.3%). However, there were no significant differences in dry matter intake (DMI) and milk production between both groups. Additionally, there were differences in the abundance of OTUs assigned to uncultured Prevotella sp., Succinivibrio, and other 12 bacterial phylotypes between both groups. Specifically, a previously uncultured novel Prevotella sp. with lactate-producing phenotype was detected, with higher abundance in low methane-producing cows. These findings provide evidence that Prevotella may be associated with low methane and high propionate production. However, further research is required to improve the understanding of microbial relationships and metabolic processes involved in the mitigation of enteric methane.
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Affiliation(s)
- Takumi Shinkai
- Division of Dairy Cattle Feeding and Breeding Research, Institute of Livestock and Grassland Science, National Agriculture and Food Research Organization, Tsukuba, Ibaraki, Japan
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Qi W, Xue MY, Jia MH, Zhang S, Yan Q, Sun HZ. - Invited Review - Understanding the functionality of the rumen microbiota: searching for better opportunities for rumen microbial manipulation. Anim Biosci 2024; 37:370-384. [PMID: 38186256 PMCID: PMC10838668 DOI: 10.5713/ab.23.0308] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 08/17/2023] [Accepted: 11/03/2023] [Indexed: 01/09/2024] Open
Abstract
Rumen microbiota play a central role in the digestive process of ruminants. Their remarkable ability to break down complex plant fibers and proteins, converting them into essential organic compounds that provide animals with energy and nutrition. Research on rumen microbiota not only contributes to improving animal production performance and enhancing feed utilization efficiency but also holds the potential to reduce methane emissions and environmental impact. Nevertheless, studies on rumen microbiota face numerous challenges, including complexity, difficulties in cultivation, and obstacles in functional analysis. This review provides an overview of microbial species involved in the degradation of macromolecules, the fermentation processes, and methane production in the rumen, all based on cultivation methods. Additionally, the review introduces the applications, advantages, and limitations of emerging omics technologies such as metagenomics, metatranscriptomics, metaproteomics, and metabolomics, in investigating the functionality of rumen microbiota. Finally, the article offers a forward-looking perspective on the new horizons and technologies in the field of rumen microbiota functional research. These emerging technologies, with continuous refinement and mutual complementation, have deepened our understanding of rumen microbiota functionality, thereby enabling effective manipulation of the rumen microbial community.
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Affiliation(s)
- Wenlingli Qi
- Key Laboratory of Dairy Cow Genetic Improvement and Milk Quality Research of Zhejiang Province, College of Animal Sciences, Zhejiang University, Hangzhou 310058, China
| | - Ming-Yuan Xue
- Key Laboratory of Dairy Cow Genetic Improvement and Milk Quality Research of Zhejiang Province, College of Animal Sciences, Zhejiang University, Hangzhou 310058, China
| | - Ming-Hui Jia
- Key Laboratory of Dairy Cow Genetic Improvement and Milk Quality Research of Zhejiang Province, College of Animal Sciences, Zhejiang University, Hangzhou 310058, China
| | - Shuxian Zhang
- CAS Key Laboratory of Agro-Ecological Processes in Subtropical Region, Hunan Provincial Key Laboratory of Animal Nutritional Physiology and Metabolic Process, Institute of Subtropical Agriculture, Chinese Academy of Sciences, Changsha 410125, China
| | - Qiongxian Yan
- CAS Key Laboratory of Agro-Ecological Processes in Subtropical Region, Hunan Provincial Key Laboratory of Animal Nutritional Physiology and Metabolic Process, Institute of Subtropical Agriculture, Chinese Academy of Sciences, Changsha 410125, China
| | - Hui-Zeng Sun
- Key Laboratory of Dairy Cow Genetic Improvement and Milk Quality Research of Zhejiang Province, College of Animal Sciences, Zhejiang University, Hangzhou 310058, China
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Rabee AE, Mohamed M Ghandour M, Sallam A, Elwakeel EA, Mohammed RS, Sabra EA, Abdel-Wahed AM, Mourad DM, Hamed AA, Hafez OR. Rumen fermentation and microbiota in Shami goats fed on condensed tannins or herbal mixture. BMC Vet Res 2024; 20:35. [PMID: 38297287 PMCID: PMC10829277 DOI: 10.1186/s12917-024-03887-2] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 09/18/2023] [Accepted: 01/17/2024] [Indexed: 02/02/2024] Open
Abstract
BACKGROUND Phytochemical compounds can modify the rumen microbiome and improve rumen fermentation. This study evaluated the impact of supplementation with tannin and an herbal mixture containing ginger (Zingiber officinale), garlic (Allium sativum), Artemisia (Artemisia vulgaris), and turmeric (Curcuma longa) on the rumen fermentation and microbiota, and histology of rumen tissue of goats. Eighteen Shami male goats were divided into three groups (n = 6): non-supplemented animals fed the basal diet (C, control); animals fed basal diet and supplemented with condensed tannin (T); and animals fed basal diet and supplemented with herbal mixture (HM). Each animal received a basal diet composed of Alfalfa hay and a concentrate feed mixture. RESULTS Group HM revealed higher (P < 0.05) rumen pH, total volatile fatty acids (VFA), acetic, propionic, isobutyric, butyric, isovaleric, and valeric. Principal Co-ordinate analysis (PCoA) showed that rumen microbial communities in the control group and supplemented groups were distinct. The supplementation increased (P < 0.05) the relative abundances of phylum Bacteroidota and Proteobacteria and declined (P < 0.05) Firmicutes and Fibrobacterota. Additionally, the dominant genus Prevotella and Rikenellaceae RC9 gut group were increased (P < 0.05) and the family Ruminococcaceae was declined (P < 0.05) due to the supplementation. The supplementation decreased (P < 0.05) the archaeal genus Methanobrevibacter and increased (P < 0.05) Candidatus Methanomethylophilus. Tannin supplementation in T group shortened the rumen papillae. CONCLUSIONS The results revealed that the herbal mixture might be used to alter the rumen microbiota to improve rumen fermentation.
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Affiliation(s)
- Alaa Emara Rabee
- Animal and Poultry Nutrition Department, Desert Research Center, Ministry of Agriculture and Land Reclamation, Cairo, Egypt.
| | - Moustafa Mohamed M Ghandour
- Animal and Poultry Nutrition Department, Desert Research Center, Ministry of Agriculture and Land Reclamation, Cairo, Egypt
| | - Ahmed Sallam
- Animal and Poultry Breeding Department, Desert Research Center, Cairo, Egypt
| | - Eman A Elwakeel
- Department of Animal and Fish production, Faculty of Agriculture, Alexandria University, Alexandria, Egypt
| | - Rasha S Mohammed
- Animal and Poultry Health Department, Desert Research Center, Ministry of Agriculture and Land Reclamation, Cairo, Egypt
| | - Ebrahim A Sabra
- Genetic Engineering and Biotechnology Research Institute, University of Sadat City, Sadat City, Egypt
| | - Adel M Abdel-Wahed
- Animal and Poultry Nutrition Department, Desert Research Center, Ministry of Agriculture and Land Reclamation, Cairo, Egypt
| | - Disouky Mohamed Mourad
- Animal and Poultry Health Department, Desert Research Center, Ministry of Agriculture and Land Reclamation, Cairo, Egypt
| | - Amal Amin Hamed
- Botany and Microbiology Department, Faculty of science, Cairo University, Cairo, Egypt
| | - Osama Raef Hafez
- Animal and Poultry Nutrition Department, Desert Research Center, Ministry of Agriculture and Land Reclamation, Cairo, Egypt
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Wang W, Dong Y, Guo W, Zhang X, Degen AA, Bi S, Ding L, Chen X, Long R. Linkages between rumen microbiome, host, and environment in yaks, and their implications for understanding animal production and management. Front Microbiol 2024; 15:1301258. [PMID: 38348184 PMCID: PMC10860762 DOI: 10.3389/fmicb.2024.1301258] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 09/24/2023] [Accepted: 01/03/2024] [Indexed: 02/15/2024] Open
Abstract
Livestock on the Qinghai-Tibetan Plateau is of great importance for the livelihood of the local inhabitants and the ecosystem of the plateau. The natural, harsh environment has shaped the adaptations of local livestock while providing them with requisite eco-services. Over time, unique genes and metabolic mechanisms (nitrogen and energy) have evolved which enabled the yaks to adapt morphologically and physiologically to the Qinghai-Tibetan Plateau. The rumen microbiota has also co-evolved with the host and contributed to the host's adaptation to the environment. Understanding the complex linkages between the rumen microbiota, the host, and the environment is essential to optimizing the rumen function to meet the growing demands for animal products while minimizing the environmental impact of ruminant production. However, little is known about the mechanisms of host-rumen microbiome-environment linkages and how they ultimately benefit the animal in adapting to the environment. In this review, we pieced together the yak's adaptation to the Qinghai-Tibetan Plateau ecosystem by summarizing the natural selection and nutritional features of yaks and integrating the key aspects of its rumen microbiome with the host metabolic efficiency and homeostasis. We found that this homeostasis results in higher feed digestibility, higher rumen microbial protein production, higher short-chain fatty acid (SCFA) concentrations, and lower methane emissions in yaks when compared with other low-altitude ruminants. The rumen microbiome forms a multi-synergistic relationship among the rumen microbiota services, their communities, genes, and enzymes. The rumen microbial proteins and SCFAs act as precursors that directly impact the milk composition or adipose accumulation, improving the milk or meat quality, resulting in a higher protein and fat content in yak milk and a higher percentage of protein and abundant fatty acids in yak meat when compared to dairy cow or cattle. The hierarchical interactions between the climate, forage, rumen microorganisms, and host genes have reshaped the animal's survival and performance. In this review, an integrating and interactive understanding of the host-rumen microbiome environment was established. The understanding of these concepts is valuable for agriculture and our environment. It also contributes to a better understanding of microbial ecology and evolution in anaerobic ecosystems and the host-environment linkages to improve animal production.
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Affiliation(s)
- Weiwei Wang
- Laboratory of Animal Genetics, Breeding and Reproduction in the Plateau Mountainous Region, Ministry of Education, College of Animal Science, Guizhou University, Guiyang, Guizhou, China
- State Key Laboratory of Grassland Agro-Ecosystems, College of Ecology, Lanzhou University, Lanzhou, China
| | - Yuntao Dong
- Laboratory of Animal Genetics, Breeding and Reproduction in the Plateau Mountainous Region, Ministry of Education, College of Animal Science, Guizhou University, Guiyang, Guizhou, China
| | - Wei Guo
- Laboratory of Animal Genetics, Breeding and Reproduction in the Plateau Mountainous Region, Ministry of Education, College of Animal Science, Guizhou University, Guiyang, Guizhou, China
- State Key Laboratory of Grassland Agro-Ecosystems, College of Ecology, Lanzhou University, Lanzhou, China
| | - Xiao Zhang
- Tianjin Key Laboratory of Conservation and Utilization of Animal Diversity, College of Life Sciences, Tianjin Normal University, Tianjin, China
| | - A. Allan Degen
- Desert Animal Adaptations and Husbandry, Wyler Department of Dryland Agriculture, Blaustein Institutes for Desert Research, Ben-Gurion University of the Negev, Beer Sheva, Israel
| | - Sisi Bi
- State Key Laboratory of Grassland Agro-Ecosystems, College of Ecology, Lanzhou University, Lanzhou, China
| | - Luming Ding
- State Key Laboratory of Grassland Agro-Ecosystems, College of Ecology, Lanzhou University, Lanzhou, China
| | - Xiang Chen
- Laboratory of Animal Genetics, Breeding and Reproduction in the Plateau Mountainous Region, Ministry of Education, College of Animal Science, Guizhou University, Guiyang, Guizhou, China
| | - Ruijun Long
- State Key Laboratory of Grassland Agro-Ecosystems, College of Ecology, Lanzhou University, Lanzhou, China
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Diaz GR, Gaire TN, Ferm P, Case L, Caixeta LS, Goldsmith TJ, Armstrong J, Noyes NR. Effect of castration timing and weaning strategy on the taxonomic and functional profile of ruminal bacteria and archaea of beef calves. Anim Microbiome 2023; 5:61. [PMID: 38041127 PMCID: PMC10691087 DOI: 10.1186/s42523-023-00284-2] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 07/20/2023] [Accepted: 11/28/2023] [Indexed: 12/03/2023] Open
Abstract
BACKGROUND Beef cattle experience several management challenges across their lifecycle. Castration and weaning, two major interventions in the early life of beef cattle, can have a substantial impact on animal performance. Despite the key role of the rumen microbiome on productive traits of beef cattle, the effect of castration timing and weaning strategy on this microbial community has not been formally described. We assessed the effect of four castration time windows (at birth, turnout, pre-weaning and weaning) and two weaning strategies (fence-line and truck transportation) on the rumen microbiome in a randomized controlled study with 32 male calves across 3 collection days (i.e., time points). Ruminal fluid samples were submitted to shotgun metagenomic sequencing and changes in the taxonomic (microbiota) and functional profile (metagenome) of the rumen microbiome were described. RESULTS Using a comprehensive yet stringent taxonomic classification approach, we identified 10,238 unique taxa classified under 40 bacterial and 7 archaeal phyla across all samples. Castration timing had a limited long-term impact on the rumen microbiota and was not associated with changes in alpha and beta diversity. The interaction of collection day and weaning strategy was associated with changes in the rumen microbiota, which experienced a significant decrease in alpha diversity and shifts in beta diversity within 48 h post-weaning, especially in calves abruptly weaned by truck transportation. Calves weaned using a fence-line weaning strategy had lower relative abundance of Bacteroides, Lachnospira, Fibrobacter and Ruminococcus genera compared to calves weaned by truck transportation. Some genes involved in the hydrogenotrophic methanogenesis pathway (fwdB and fwdF) had higher relative abundance in fence-line-weaned calves post-weaning. The antimicrobial resistance gene tetW consistently represented more than 50% of the resistome across time, weaning and castration groups, without significant changes in relative abundance. CONCLUSIONS Within the context of this study, castration timing had limited long-term effects on the rumen microbiota, while weaning strategy had short-term effects on the rumen microbiota and methane-associated metagenome, but not on the rumen resistome.
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Affiliation(s)
- Gerardo R Diaz
- Department of Veterinary Population Medicine, College of Veterinary Medicine, University of Minnesota, St. Paul, MN, 55108, USA
| | - Tara N Gaire
- Department of Veterinary Population Medicine, College of Veterinary Medicine, University of Minnesota, St. Paul, MN, 55108, USA
| | - Peter Ferm
- Department of Veterinary Population Medicine, College of Veterinary Medicine, University of Minnesota, St. Paul, MN, 55108, USA
| | - Lacey Case
- North Central Research and Outreach Center, Department of Animal Science, University of Minnesota, St. Paul, MN, 55108, USA
| | - Luciano S Caixeta
- Department of Veterinary Population Medicine, College of Veterinary Medicine, University of Minnesota, St. Paul, MN, 55108, USA
| | - Timothy J Goldsmith
- Department of Veterinary Population Medicine, College of Veterinary Medicine, University of Minnesota, St. Paul, MN, 55108, USA
| | - Joe Armstrong
- Agricultural and Natural Resource Systems, University of Minnesota Extension, University of Minnesota, St. Paul, MN, 55108, USA
| | - Noelle R Noyes
- Department of Veterinary Population Medicine, College of Veterinary Medicine, University of Minnesota, St. Paul, MN, 55108, USA.
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11
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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? Vet Sci 2023; 10:679. [PMID: 38133230 PMCID: PMC10747152 DOI: 10.3390/vetsci10120679] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 10/06/2023] [Revised: 11/20/2023] [Accepted: 11/22/2023] [Indexed: 12/23/2023] Open
Abstract
Rumen microbial protein synthesis (MPS) provides at least half of the amino acids for the synthesis of milk and meat protein in ruminants. As such, it is fundamental to global food protein security. Estimating microbial protein is central to diet formulation, maximising nitrogen (N)-use efficiency and reducing N losses to the environment. Whilst factors influencing MPS are well established in vitro, techniques for in vivo estimates, including older techniques with cannulated animals and the more recent technique based on urinary purine derivative (UPD) excretion, are subject to large experimental errors. Consequently, models of MPS used in protein rationing are imprecise, resulting in wasted feed protein and unnecessary N losses to the environment. Newer 'omics' techniques are used to characterise microbial communities, their genes and resultant proteins and metabolites. An analysis of microbial communities and genes has recently been used successfully to model complex rumen-related traits, including feed conversion efficiency and methane emissions. Since microbial proteins are more directly related to microbial genes, we expect a strong relationship between rumen metataxonomics/metagenomics and MPS. The main aims of this review are to gauge the understanding of factors affecting MPS, including the use of the UPD technique, and explore whether omics-focused studies could improve the predictability of MPS, with a focus on beef cattle.
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Affiliation(s)
- Joana Lima
- SRUC Dairy Research and Innovation Centre, Barony Campus, Dumfries DG1 3NE, UK; (J.L.); (W.I.)
| | - Winfred Ingabire
- SRUC Dairy Research and Innovation Centre, Barony Campus, Dumfries DG1 3NE, UK; (J.L.); (W.I.)
| | | | - Richard James Dewhurst
- SRUC Dairy Research and Innovation Centre, Barony Campus, Dumfries DG1 3NE, UK; (J.L.); (W.I.)
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12
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Aryee G, Luecke SM, Dahlen CR, Swanson KC, Amat S. Holistic View and Novel Perspective on Ruminal and Extra-Gastrointestinal Methanogens in Cattle. Microorganisms 2023; 11:2746. [PMID: 38004757 PMCID: PMC10673468 DOI: 10.3390/microorganisms11112746] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 10/23/2023] [Revised: 11/08/2023] [Accepted: 11/09/2023] [Indexed: 11/26/2023] Open
Abstract
Despite the extensive research conducted on ruminal methanogens and anti-methanogenic intervention strategies over the last 50 years, most of the currently researched enteric methane (CH4) abatement approaches have shown limited efficacy. This is largely because of the complex nature of animal production and the ruminal environment, host genetic variability of CH4 production, and an incomplete understanding of the role of the ruminal microbiome in enteric CH4 emissions. Recent sequencing-based studies suggest the presence of methanogenic archaea in extra-gastrointestinal tract tissues, including respiratory and reproductive tracts of cattle. While these sequencing data require further verification via culture-dependent methods, the consistent identification of methanogens with relatively greater frequency in the airway and urogenital tract of cattle, as well as increasing appreciation of the microbiome-gut-organ axis together highlight the potential interactions between ruminal and extra-gastrointestinal methanogenic communities. Thus, a traditional singular focus on ruminal methanogens may not be sufficient, and a holistic approach which takes into consideration of the transfer of methanogens between ruminal, extra-gastrointestinal, and environmental microbial communities is of necessity to develop more efficient and long-term ruminal CH4 mitigation strategies. In the present review, we provide a holistic survey of the methanogenic archaea present in different anatomical sites of cattle and discuss potential seeding sources of the ruminal methanogens.
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Affiliation(s)
- Godson Aryee
- Department of Microbiological Sciences, North Dakota State University, Fargo, ND 58108, USA; (G.A.); (S.M.L.)
| | - Sarah M. Luecke
- Department of Microbiological Sciences, North Dakota State University, Fargo, ND 58108, USA; (G.A.); (S.M.L.)
| | - Carl R. Dahlen
- Department of Animal Sciences, and Center for Nutrition and Pregnancy, North Dakota State University, Fargo, ND 58102, USA; (C.R.D.); (K.C.S.)
| | - Kendall C. Swanson
- Department of Animal Sciences, and Center for Nutrition and Pregnancy, North Dakota State University, Fargo, ND 58102, USA; (C.R.D.); (K.C.S.)
| | - Samat Amat
- Department of Microbiological Sciences, North Dakota State University, Fargo, ND 58108, USA; (G.A.); (S.M.L.)
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13
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Khairunisa BH, Heryakusuma C, Ike K, Mukhopadhyay B, Susanti D. Evolving understanding of rumen methanogen ecophysiology. Front Microbiol 2023; 14:1296008. [PMID: 38029083 PMCID: PMC10658910 DOI: 10.3389/fmicb.2023.1296008] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 09/17/2023] [Accepted: 10/12/2023] [Indexed: 12/01/2023] Open
Abstract
Production of methane by methanogenic archaea, or methanogens, in the rumen of ruminants is a thermodynamic necessity for microbial conversion of feed to volatile fatty acids, which are essential nutrients for the animals. On the other hand, methane is a greenhouse gas and its production causes energy loss for the animal. Accordingly, there are ongoing efforts toward developing effective strategies for mitigating methane emissions from ruminant livestock that require a detailed understanding of the diversity and ecophysiology of rumen methanogens. Rumen methanogens evolved from free-living autotrophic ancestors through genome streamlining involving gene loss and acquisition. The process yielded an oligotrophic lifestyle, and metabolically efficient and ecologically adapted descendants. This specialization poses serious challenges to the efforts of obtaining axenic cultures of rumen methanogens, and consequently, the information on their physiological properties remains in most part inferred from those of their non-rumen representatives. This review presents the current knowledge of rumen methanogens and their metabolic contributions to enteric methane production. It also identifies the respective critical gaps that need to be filled for aiding the efforts to mitigate methane emission from livestock operations and at the same time increasing the productivity in this critical agriculture sector.
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Affiliation(s)
| | - Christian Heryakusuma
- Genetics, Bioinformatics, and Computational Biology, Virginia Tech, Blacksburg, VA, United States
- Department of Biochemistry, Virginia Tech, Blacksburg, VA, United States
| | - Kelechi Ike
- Department of Biology, North Carolina Agricultural and Technical State University, Greensboro, NC, United States
| | - Biswarup Mukhopadhyay
- Genetics, Bioinformatics, and Computational Biology, Virginia Tech, Blacksburg, VA, United States
- Department of Biochemistry, Virginia Tech, Blacksburg, VA, United States
- Virginia Tech Carilion School of Medicine, Virginia Tech, Blacksburg, VA, United States
| | - Dwi Susanti
- Microbial Discovery Research, BiomEdit, Greenfield, IN, United States
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14
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Malheiros JM, Correia BSB, Ceribeli C, Bruscadin JJ, Diniz WJS, Banerjee P, da Silva Vieira D, Cardoso TF, Andrade BGN, Petrini J, Cardoso DR, Colnago LA, Bogusz Junior S, Mourão GB, Coutinho LL, Palhares JCP, de Medeiros SR, Berndt A, de Almeida Regitano LC. Ruminal and feces metabolites associated with feed efficiency, water intake and methane emission in Nelore bulls. Sci Rep 2023; 13:18001. [PMID: 37865691 PMCID: PMC10590413 DOI: 10.1038/s41598-023-45330-w] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 05/02/2023] [Accepted: 10/18/2023] [Indexed: 10/23/2023] Open
Abstract
The objectives of this study were twofold: (1) to identify potential differences in the ruminal and fecal metabolite profiles of Nelore bulls under different nutritional interventions; and (2) to identify metabolites associated with cattle sustainability related-traits. We used different nutritional interventions in the feedlot: conventional (Conv; n = 26), and by-product (ByPr, n = 26). Thirty-eight ruminal fluid and 27 fecal metabolites were significantly different (P < 0.05) between the ByPr and Conv groups. Individual dry matter intake (DMI), residual feed intake (RFI), observed water intake (OWI), predicted water intake (WI), and residual water intake (RWI) phenotypes were lower (P < 0.05) in the Conv group, while the ByPr group exhibited lower methane emission (ME) (P < 0.05). Ruminal fluid dimethylamine was significantly associated (P < 0.05) with DMI, RFI, FE (feed efficiency), OWI and WI. Aspartate was associated (P < 0.05) with DMI, RFI, FE and WI. Fecal C22:1n9 was significantly associated with OWI and RWI (P < 0.05). Fatty acid C14:0 and hypoxanthine were significantly associated with DMI and RFI (P < 0.05). The results demonstrated that different nutritional interventions alter ruminal and fecal metabolites and provided new insights into the relationship of these metabolites with feed efficiency and water intake traits in Nelore bulls.
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Affiliation(s)
| | | | - Caroline Ceribeli
- Institute of Chemistry, University of São Paulo/USP, São Carlos, São Paulo, Brazil
- Department of Food Science, University of Copenhagen, Copenhagen, Denmark
| | | | - Wellison J S Diniz
- Departament of Animal Sciences, Auburn University, Auburn, AL, 36849, USA
| | - Priyanka Banerjee
- Departament of Animal Sciences, Auburn University, Auburn, AL, 36849, USA
| | | | | | - Bruno Gabriel Nascimento Andrade
- Embrapa Southeast Livestock, São Carlos, São Paulo, Brazil
- Computer Science Department, Munster Technological University, MTU/ADAPT, Cork, Ireland
| | - Juliana Petrini
- Department of Animal Science, University of São Paulo/ESALQ, Piracicaba, São Paulo, Brazil
| | | | | | | | - Gerson Barreto Mourão
- Department of Animal Science, University of São Paulo/ESALQ, Piracicaba, São Paulo, Brazil
| | - Luiz Lehmann Coutinho
- Department of Animal Science, University of São Paulo/ESALQ, Piracicaba, São Paulo, Brazil
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15
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Torres Manno MA, Gizzi FO, Martín M, Espariz M, Magni C, Blancato VS. Metagenomic approach to infer rumen microbiome derived traits of cattle. World J Microbiol Biotechnol 2023; 39:250. [PMID: 37439894 DOI: 10.1007/s11274-023-03694-1] [Citation(s) in RCA: 3] [Impact Index Per Article: 1.5] [Reference Citation Analysis] [Abstract] [Key Words] [Grants] [Journal Information] [Subscribe] [Scholar Register] [Received: 06/14/2023] [Accepted: 07/04/2023] [Indexed: 07/14/2023]
Abstract
Ruminants enable the conversion of indigestible plant material into animal consumables, including dairy products, meat, and valuable fibers. Microbiome research is gaining popularity in livestock species because it aids in the knowledge of illnesses and efficiency processes in animals. In this study, we use WGS metagenomic data to thoroughly characterize the ruminal ecosystem of cows to infer positive and negative livestock traits determined by the microbiome. The rumen of cows from Argentina were described by combining different gene biomarkers, pathways composition and taxonomic information. Taxonomic characterization indicated that the two major phyla were Bacteroidetes and Firmicutes; in third place, Proteobacteria was highly represented followed by Actinobacteria; Prevotella, and Bacteroides were the most abundant genera. Functional profiling of carbohydrate-active enzymes indicated that members of the Glycoside Hydrolase (GH) class accounted for 52.2 to 55.6% of the total CAZymes detected, among them the most abundant were the oligosaccharide degrading enzymes. The diversity of GH families found suggested efficient hydrolysis of complex biomass. Genes of multidrug, macrolides, polymyxins, beta-lactams, rifamycins, tetracyclines, and bacitracin resistance were found below 0.12% of relative abundance. Furthermore, the clustering analysis of genera and genes that correlated to methane emissions or feed efficiency, suggested that the cows analysed could be regarded as low methane emitters and clustered with high feed efficiency reference animals. Finally, the combination of bioinformatic analyses used in this study can be applied to assess cattle traits difficult to measure and guide enhanced nutrition and breeding methods.
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Affiliation(s)
- Mariano A Torres Manno
- Laboratorio de Fisiología y Genética de Bacterias Lácticas, Instituto de Biología Molecular y Celular de Rosario (IBR), Concejo Nacional de Investigaciones Científicas y Tecnológicas (CONICET), Universidad Nacional de Rosario (UNR), Suipacha 531, 2000, Rosario, Argentina
| | - Fernán O Gizzi
- Laboratorio de Fisiología y Genética de Bacterias Lácticas, Instituto de Biología Molecular y Celular de Rosario (IBR), Concejo Nacional de Investigaciones Científicas y Tecnológicas (CONICET), Universidad Nacional de Rosario (UNR), Suipacha 531, 2000, Rosario, Argentina
| | - Mariana Martín
- Centro de Estudios Fotosintéticos y Bioquímicos (CEFOBI), Concejo Nacional de Investigaciones Científicas y Tecnológicas (CONICET) - UNR, Rosario, Argentina
| | - Martín Espariz
- Laboratorio de Fisiología y Genética de Bacterias Lácticas, Instituto de Biología Molecular y Celular de Rosario (IBR), Concejo Nacional de Investigaciones Científicas y Tecnológicas (CONICET), Universidad Nacional de Rosario (UNR), Suipacha 531, 2000, Rosario, Argentina
- Laboratorio de Biotecnología e Inocuidad de los Alimentos, Facultad de Ciencias Bioquímicas y Farmacéuticas (FBioyF) - Municipalidad de Granadero Baigorria, Universidad Nacional de Rosario (UNR), Rosario, Argentina
| | - Christian Magni
- Laboratorio de Fisiología y Genética de Bacterias Lácticas, Instituto de Biología Molecular y Celular de Rosario (IBR), Concejo Nacional de Investigaciones Científicas y Tecnológicas (CONICET), Universidad Nacional de Rosario (UNR), Suipacha 531, 2000, Rosario, Argentina
- Laboratorio de Biotecnología e Inocuidad de los Alimentos, Facultad de Ciencias Bioquímicas y Farmacéuticas (FBioyF) - Municipalidad de Granadero Baigorria, Universidad Nacional de Rosario (UNR), Rosario, Argentina
- Biotecnología de los Alimentos, LCTA, FBioyF-UNR, Suipacha 590, Rosario, Argentina
| | - Víctor S Blancato
- Laboratorio de Fisiología y Genética de Bacterias Lácticas, Instituto de Biología Molecular y Celular de Rosario (IBR), Concejo Nacional de Investigaciones Científicas y Tecnológicas (CONICET), Universidad Nacional de Rosario (UNR), Suipacha 531, 2000, Rosario, Argentina.
- Laboratorio de Biotecnología e Inocuidad de los Alimentos, Facultad de Ciencias Bioquímicas y Farmacéuticas (FBioyF) - Municipalidad de Granadero Baigorria, Universidad Nacional de Rosario (UNR), Rosario, Argentina.
- Biotecnología de los Alimentos, LCTA, FBioyF-UNR, Suipacha 590, Rosario, Argentina.
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16
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Choi Y, Lee SJ, Kim HS, Eom JS, Jo SU, Guan LL, Seo J, Park T, Lee Y, Lee SS, Lee SS. Oral administration of Pinus koraiensis cone essential oil reduces rumen methane emission by altering the rumen microbial composition and functions in Korean native goat ( Capra hircus coreanae). Front Vet Sci 2023; 10:1168237. [PMID: 37275608 PMCID: PMC10234127 DOI: 10.3389/fvets.2023.1168237] [Citation(s) in RCA: 1] [Impact Index Per Article: 0.5] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 02/17/2023] [Accepted: 04/21/2023] [Indexed: 06/07/2023] Open
Abstract
This study aimed to investigate Pinus koraiensis cone essential oil (PEO) as a methane (CH4) inhibitor and determine its impact on the taxonomic and functional characteristics of the rumen microbiota in goats. A total of 10 growing Korean native goats (Capra hircus coreanae, 29.9 ± 1.58 kg, male) were assigned to different dietary treatments: control (CON; basal diet without additive) and PEO (basal diet +1 g/d of PEO) by a 2 × 2 crossover design. Methane measurements were conducted every 4 consecutive days for 17-20 days using a laser CH4 detector. Samples of rumen fluid and feces were collected during each experimental period to evaluate the biological effects and dry matter (DM) digestibility after PEO oral administration. The rumen microbiota was analyzed via 16S rRNA gene amplicon sequencing. The PEO oral administration resulted in reduced CH4 emission (eructation CH4/body weight0.75, p = 0.079) without affecting DM intake; however, it lowered the total volatile fatty acids (p = 0.041), molar proportion of propionate (p = 0.075), and ammonia nitrogen (p = 0.087) in the rumen. Blood metabolites (i.e., albumin, alanine transaminase/serum glutamic pyruvate transaminase, creatinine, and triglyceride) were significantly affected (p < 0.05) by PEO oral administration. The absolute fungal abundance (p = 0.009) was reduced by PEO oral administration, whereas ciliate protozoa, total bacteria, and methanogen abundance were not affected. The composition of rumen prokaryotic microbiota was altered by PEO oral administration with lower evenness (p = 0.054) observed for the PEO group than the CON group. Moreover, PICRUSt2 analysis revealed that the metabolic pathways of prokaryotic bacteria, such as pyruvate metabolism, were enriched in the PEO group. We also identified the Rikenellaceae RC9 gut group as the taxa potentially contributing to the enriched KEGG modules for histidine biosynthesis and pyruvate oxidation in the rumen of the PEO group using the FishTaco analysis. The entire co-occurrence networks showed that more nodes and edges were detected in the PEO group. Overall, these findings provide an understanding of how PEO oral administration affects CH4 emission and rumen prokaryotic microbiota composition and function. This study may help develop potential manipulation strategies to find new essential oils to mitigate enteric CH4 emissions from ruminants.
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Affiliation(s)
- Youyoung Choi
- Division of Applied Life Science (BK21), Gyeongsang National University, Jinju, Republic of Korea
- Institute of Agriculture and Life Science (IALS), Gyeongsang National University, Jinju, Republic of Korea
| | - Shin Ja Lee
- Institute of Agriculture and Life Science (IALS), Gyeongsang National University, Jinju, Republic of Korea
- Institute of Agriculture and Life Science and University-Centered Labs, Gyeongsang National University, Jinju, Republic of Korea
| | - Hyun Sang Kim
- Institute of Agriculture and Life Science (IALS), Gyeongsang National University, Jinju, Republic of Korea
| | - Jun Sik Eom
- Institute of Agriculture and Life Science (IALS), Gyeongsang National University, Jinju, Republic of Korea
| | - Seong Uk Jo
- Division of Applied Life Science (BK21), Gyeongsang National University, Jinju, Republic of Korea
- Institute of Agriculture and Life Science (IALS), Gyeongsang National University, Jinju, Republic of Korea
| | - Le Luo Guan
- Department of Agricultural, Food and Nutritional Science, University of Alberta, Edmonton, AB, Canada
| | - Jakyeom Seo
- Department of Animal Science, Life and Industry Convergence Research Institute, Pusan National University, Miryang, Republic of Korea
| | - Tansol Park
- Department of Animal Science and Technology, Chung-Ang University, Anseong, Republic of Korea
| | - Yookyung Lee
- Animal Nutrition and Physiology Team, National Institute of Animal Science, RDA, Jeonju, Republic of Korea
| | - Sang Suk Lee
- Ruminant Nutrition and Anaerobe Laboratory, Department of Animal Science and Technology, Sunchon National University, Sunchon, Republic of Korea
| | - Sung Sill Lee
- Division of Applied Life Science (BK21), Gyeongsang National University, Jinju, Republic of Korea
- Institute of Agriculture and Life Science (IALS), Gyeongsang National University, Jinju, Republic of Korea
- Institute of Agriculture and Life Science and University-Centered Labs, Gyeongsang National University, Jinju, Republic of Korea
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17
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Invited Review: Novel methods and perspectives for modulating the rumen microbiome through selective breeding as a means to improve complex traits: implications for methane emissions in cattle. Livest Sci 2023. [DOI: 10.1016/j.livsci.2023.105171] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 02/05/2023]
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18
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Miller GA, Auffret MD, Roehe R, Nisbet H, Martínez-Álvaro M. Different microbial genera drive methane emissions in beef cattle fed with two extreme diets. Front Microbiol 2023; 14:1102400. [PMID: 37125186 PMCID: PMC10133469 DOI: 10.3389/fmicb.2023.1102400] [Citation(s) in RCA: 1] [Impact Index Per Article: 0.5] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 11/18/2022] [Accepted: 03/29/2023] [Indexed: 05/02/2023] Open
Abstract
The ratio of forage to concentrate in cattle feeding has a major influence on the composition of the microbiota in the rumen and on the mass of methane produced. Using methane measurements and microbiota data from 26 cattle we aimed to investigate the relationships between microbial relative abundances and methane emissions, and identify potential biomarkers, in animals fed two extreme diets - a poor quality fresh cut grass diet (GRASS) or a high concentrate total mixed ration (TMR). Direct comparisons of the effects of such extreme diets on the composition of rumen microbiota have rarely been studied. Data were analyzed considering their multivariate and compositional nature. Diet had a relevant effect on methane yield of +10.6 g of methane/kg of dry matter intake for GRASS with respect to TMR, and on the centered log-ratio transformed abundance of 22 microbial genera. When predicting methane yield based on the abundance of 28 and 25 selected microbial genera in GRASS and TMR, respectively, we achieved cross-validation prediction accuracies of 66.5 ± 9% and 85 ± 8%. Only the abundance of Fibrobacter had a consistent negative association with methane yield in both diets, whereas most microbial genera were associated with methane yield in only one of the two diets. This study highlights the stark contrast in the microbiota controlling methane yield between animals fed a high concentrate diet, such as that found on intensive finishing units, and a low-quality grass forage that is often found in extensive grazing systems. This contrast must be taken into consideration when developing strategies to reduce methane emissions by manipulation of the rumen microbial composition.
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Affiliation(s)
- Gemma A. Miller
- Scotland’s Rural College (SRUC), Edinburgh, United Kingdom
- Gemma A. Miller,
| | | | - Rainer Roehe
- Scotland’s Rural College (SRUC), Edinburgh, United Kingdom
| | - Holly Nisbet
- Scotland’s Rural College (SRUC), Edinburgh, United Kingdom
| | - Marina Martínez-Álvaro
- Institute for Animal Science and Technology, Universitat Politècnica de València, Valencia, Spain
- *Correspondence: Marina Martínez-Álvaro,
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19
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de Melo HSA, Ítavo LCV, de Castro AP, Ítavo CCBF, de Araújo Caldas R, Mateus RG, Niwa MVG, de Moraes GJ, da Silva Zornitta C, Gurgel ALC, Benchaar C. Bacterial species in the ruminal content of steers fed oilseeds in the diet. Trop Anim Health Prod 2022; 54:396. [DOI: 10.1007/s11250-022-03399-x] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 04/13/2022] [Accepted: 11/09/2022] [Indexed: 11/24/2022]
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20
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Smith RH, Glendinning L, Walker AW, Watson M. Investigating the impact of database choice on the accuracy of metagenomic read classification for the rumen microbiome. Anim Microbiome 2022; 4:57. [PMID: 36401288 PMCID: PMC9673341 DOI: 10.1186/s42523-022-00207-7] [Citation(s) in RCA: 17] [Impact Index Per Article: 5.7] [Reference Citation Analysis] [Abstract] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 04/26/2022] [Accepted: 09/24/2022] [Indexed: 11/19/2022] Open
Abstract
Microbiome analysis is quickly moving towards high-throughput methods such as metagenomic sequencing. Accurate taxonomic classification of metagenomic data relies on reference sequence databases, and their associated taxonomy. However, for understudied environments such as the rumen microbiome many sequences will be derived from novel or uncultured microbes that are not present in reference databases. As a result, taxonomic classification of metagenomic data from understudied environments may be inaccurate. To assess the accuracy of taxonomic read classification, this study classified metagenomic data that had been simulated from cultured rumen microbial genomes from the Hungate collection. To assess the impact of reference databases on the accuracy of taxonomic classification, the data was classified with Kraken 2 using several reference databases. We found that the choice and composition of reference database significantly impacted on taxonomic classification results, and accuracy. In particular, NCBI RefSeq proved to be a poor choice of database. Our results indicate that inaccurate read classification is likely to be a significant problem, affecting all studies that use insufficient reference databases. We observed that adding cultured reference genomes from the rumen to the reference database greatly improved classification rate and accuracy. We also demonstrated that metagenome-assembled genomes (MAGs) have the potential to further enhance classification accuracy by representing uncultivated microbes, sequences of which would otherwise be unclassified or incorrectly classified. However, classification accuracy was strongly dependent on the taxonomic labels assigned to these MAGs. We therefore highlight the importance of accurate reference taxonomic information and suggest that, with formal taxonomic lineages, MAGs have the potential to improve classification rate and accuracy, particularly in environments such as the rumen that are understudied or contain many novel genomes.
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21
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Evaluation of the metabolomic profile through 1H-NMR spectroscopy in ewes affected by postpartum hyperketonemia. Sci Rep 2022; 12:16463. [PMID: 36183000 PMCID: PMC9526738 DOI: 10.1038/s41598-022-20371-9] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 05/18/2022] [Accepted: 09/13/2022] [Indexed: 11/21/2022] Open
Abstract
Ketosis is one of the most important health problems in dairy sheep. The aim of this study was to evaluate the metabolic alterations in hyperketonemic (HYK) ewes. Forty-six adult Sardinian ewes were enrolled between 7 ± 3 days post-partum. Blood samples were collected from the jugular vein using Venosafe tubes containing clot activator from jugular vein after clinical examination. The concentration of β-hydroxybutyrate (BHB) was determined in serum and used to divide ewes into assign ewes into: Non-HYK (serum BHB < 0.80 mmol/L) and HYK (serum BHB ≥ 0.80 mmol/L) groups. Animal data and biochemical parameters of groups were examined with one-way ANOVA, and metabolite differences were tested using a t-test. A robust principal component analysis model and a heatmap were used to highlight common trends among metabolites. Over-representation analysis was performed to investigate metabolic pathways potentially altered in connection with BHB alterations. The metabolomic analysis identified 54 metabolites with 14 different between groups. These metabolites indicate altered ruminal microbial populations and fermentations; an interruption of the tricarboxylic acid cycle; initial lack of glucogenic substrates; mobilization of body reserves; the potential alteration of electron transport chain; influence on urea synthesis; alteration of nervous system, inflammatory response, and immune cell function.
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22
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Rani V, Prasanna R, Kaushik R. Prospecting the significance of methane-utilizing bacteria in agriculture. World J Microbiol Biotechnol 2022; 38:176. [PMID: 35922575 DOI: 10.1007/s11274-022-03331-3] [Citation(s) in RCA: 1] [Impact Index Per Article: 0.3] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 04/26/2022] [Accepted: 06/08/2022] [Indexed: 11/29/2022]
Abstract
Microorganisms act as both the source and sink of methane, a potent greenhouse gas, thus making a significant contribution to the environment as an important driver of climate change. The rhizosphere and phyllosphere of plants growing in natural (mangroves) and artificial wetlands (flooded agricultural ecosystems) harbor methane-utilizing bacteria that oxidize methane at the source and reduce its net flux. For several decades, microorganisms have been used as biofertilizers to promote plant growth. However, now their role in reducing net methane flux, especially from flooded agricultural ecosystems is gaining momentum globally. Research in this context has mainly focused on taxonomic aspects related to methanotrophy among diverse bacterial genera, and environmental factors that govern methane utilization in natural and artificial wetland ecosystems. In the last few decades, concerted efforts have been made to develop multifunctional microbial inoculants that can oxidize methane and alleviate greenhouse gas emissions, as well as promote plant growth. In this context, combinations of taxonomic groups commonly found in rice paddies and those used as biofertilizers are being explored. This review deals with methanotrophy among diverse bacterial domains, factors influencing methane-utilizing ability, and explores the potential of novel methane-utilizing microbial consortia with plant growth-promoting traits in flooded ecosystems.
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Affiliation(s)
- Vijaya Rani
- ICAR-Indian Institute of Vegetable Research, Varanasi, Uttar Pradesh, India
| | - Radha Prasanna
- Division of Microbiology, ICAR-Indian Agricultural Research Institute, New Delhi, India
| | - Rajeev Kaushik
- Division of Microbiology, ICAR-Indian Agricultural Research Institute, New Delhi, India.
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23
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Rumen sampling methods bias bacterial communities observed. PLoS One 2022; 17:e0258176. [PMID: 35511785 PMCID: PMC9070869 DOI: 10.1371/journal.pone.0258176] [Citation(s) in RCA: 9] [Impact Index Per Article: 3.0] [Reference Citation Analysis] [Abstract] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 09/20/2021] [Accepted: 04/10/2022] [Indexed: 01/04/2023] Open
Abstract
The rumen is a complex ecosystem that plays a critical role in our efforts to improve feed efficiency of cattle and reduce their environmental impacts. Sequencing of the 16S rRNA gene provides a powerful tool to survey the bacterial and some archaeal. Oral stomach tubing a cow to collect a rumen sample is a rapid, cost-effective alternative to rumen cannulation for acquiring rumen samples. In this study, we determined how sampling method (oral stomach tubing vs cannulated grab sample), as well as rumen fraction type (liquid vs solid), bias the bacterial and archaeal communities observed. Liquid samples were further divided into liquid strained through cheesecloth and unstrained. Fecal samples were also collected to determine how these differed from the rumen sample types. The abundance of major archaeal communities was not different at the family level in samples acquired via rumen cannula or stomach tube. In contrast to the stable archaeal communities across sample type, the bacterial order WCHB1-41 (phylum Kiritimatiellaeota) was enriched in both liquid strained and unstrained samples as well as the family Prevotellaceae as compared to grab samples. However, these liquid samples had significantly lower abundance of Lachnospiraceae compared with grab samples. Solid samples strained of rumen liquid most closely resembled the grab samples containing both rumen liquid and solid particles obtained directly from the rumen cannula; therefore, inclusion of particulate matter is important for an accurate representation of the rumen bacteria. Stomach tube samples were the most variable and were most representative of the liquid phase. In comparison with a grab sample, stomach tube samples had significantly lower abundance of Lachnospiraceae, Fibrobacter and Treponema. Fecal samples did not reflect the community composition of the rumen, as fecal samples had significantly higher relative abundance of Ruminococcaceae and significantly lower relative abundance of Lachnospiraceae compared with grab samples.
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24
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Martínez-Álvaro M, Auffret MD, Duthie CA, Dewhurst RJ, Cleveland MA, Watson M, Roehe R. Bovine host genome acts on rumen microbiome function linked to methane emissions. Commun Biol 2022; 5:350. [PMID: 35414107 PMCID: PMC9005536 DOI: 10.1038/s42003-022-03293-0] [Citation(s) in RCA: 37] [Impact Index Per Article: 12.3] [Reference Citation Analysis] [Abstract] [MESH Headings] [Grants] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 09/17/2021] [Accepted: 03/17/2022] [Indexed: 12/28/2022] Open
Abstract
Our study provides substantial evidence that the host genome affects the comprehensive function of the microbiome in the rumen of bovines. Of 1,107/225/1,141 rumen microbial genera/metagenome assembled uncultured genomes (RUGs)/genes identified from whole metagenomics sequencing, 194/14/337 had significant host genomic effects (heritabilities ranging from 0.13 to 0.61), revealing that substantial variation of the microbiome is under host genomic control. We found 29/22/115 microbial genera/RUGs/genes host-genomically correlated (|0.59| to |0.93|) with emissions of the potent greenhouse gas methane (CH4), highlighting the strength of a common host genomic control of specific microbial processes and CH4. Only one of these microbial genes was directly involved in methanogenesis (cofG), whereas others were involved in providing substrates for archaea (e.g. bcd and pccB), important microbial interspecies communication mechanisms (ABC.PE.P), host-microbiome interaction (TSTA3) and genetic information processes (RP-L35). In our population, selection based on abundances of the 30 most informative microbial genes provided a mitigation potential of 17% of mean CH4 emissions per generation, which is higher than for selection based on measured CH4 using respiration chambers (13%), indicating the high potential of microbiome-driven breeding to cumulatively reduce CH4 emissions and mitigate climate change.
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Affiliation(s)
| | | | | | | | | | - Mick Watson
- The Roslin Institute and the Royal (Dick) School of Veterinary Studies, University of Edinburgh, Edinburgh, UK
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25
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Tamayao P, Ribeiro GO, McAllister TA, Ominski KH, Okine EK, McGeough EJ. Effects of biochar source, level of inclusion, and particle size on in vitro dry matter disappearance, total gas, and methane production and ruminal fermentation parameters in a barley silage-based diet. CANADIAN JOURNAL OF ANIMAL SCIENCE 2022. [DOI: 10.1139/cjas-2021-0007] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Track Full Text] [Subscribe] [Scholar Register] [Indexed: 11/22/2022]
Abstract
This study evaluated the effects of biochar differing in source, inclusion level, and particle size on dry matter disappearance (DMD), total gas and methane (CH4) production, and ruminal fermentation in a barley silage-based diet. The seven biochar products used were coconut (CP001 and CP014) or pine (CP002, CP015, CP016, CP023, CP024)-based. Experiment 1 (Exp. 1) evaluated these biochars at 4.5%, 13.5%, and 22.5% level of diet inclusion, whereas Experiment 2 (Exp. 2) evaluated CP002, CP016, and CP023 at 2.25% and 4.50% of the diet at <0.5, 0.5–2.0, >2.0 mm particle size. Data were analyzed using PROC MIXED in SAS as a randomized complete block design, with biochar source, inclusion level, and particle size (Exp. 2 only) as fixed effects with run and replicate as random effects. Increasing level of biochar inclusion linearly (P < 0.01) decreased DMD in Exp. 1 and did not influence DMD (P > 0.05) in Exp. 2. Total gas, CH4 (mL·g−1 DMD), and ruminal fermentation parameters were not affected by product, inclusion level, or particle size (P > 0.05). In conclusion, biochar of varying source and particle size did not mitigate CH4 production, but reduced DMD at higher inclusion levels in the barley silage-based diet.
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Affiliation(s)
- Paul Tamayao
- Department of Animal Science, University of Manitoba, Winnipeg, Manitoba, Canada, R3T 2N2
- National Centre for Livestock and the Environment, University of Manitoba, Winnipeg, Manitoba, Canada, R3T 2N2
| | - Gabriel O. Ribeiro
- Department of Animal and Poultry Science, University of Saskatchewan, 51 Campus Dr, Saskatoon, Saskatchewan, Canada, S7N 5A8
| | - Tim A. McAllister
- Lethbridge Research and Development Centre, Agriculture and Agri-Food Canada, 5403 1st Avenue South Lethbridge, Alberta, Canada, T1J 4B1
| | - Kim H. Ominski
- Department of Animal Science, University of Manitoba, Winnipeg, Manitoba, Canada, R3T 2N2
- National Centre for Livestock and the Environment, University of Manitoba, Winnipeg, Manitoba, Canada, R3T 2N2
| | - Erasmus K. Okine
- Provost and Vice President Academic, University of Lethbridge, Lethbridge, Alberta, Canada, T1K 3M4
| | - Emma J. McGeough
- Department of Animal Science, University of Manitoba, Winnipeg, Manitoba, Canada, R3T 2N2
- National Centre for Livestock and the Environment, University of Manitoba, Winnipeg, Manitoba, Canada, R3T 2N2
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26
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Perlman D, Martínez-Álvaro M, Moraïs S, Altshuler I, Hagen LH, Jami E, Roehe R, Pope PB, Mizrahi I. Concepts and Consequences of a Core Gut Microbiota for Animal Growth and Development. Annu Rev Anim Biosci 2021; 10:177-201. [PMID: 34941382 DOI: 10.1146/annurev-animal-013020-020412] [Citation(s) in RCA: 28] [Impact Index Per Article: 7.0] [Reference Citation Analysis] [Abstract] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 11/09/2022]
Abstract
Animal microbiomes are occasionally considered as an extension of host anatomy, physiology, and even their genomic architecture. Their compositions encompass variable and constant portions when examined across multiple hosts. The latter, termed the core microbiome, is viewed as more accommodated to its host environment and suggested to benefit host fitness. Nevertheless, discrepancies in its definitions, characteristics, and importance to its hosts exist across studies. We survey studies that characterize the core microbiome, detail its current definitions and available methods to identify it, and emphasize the crucial need to upgrade and standardize the methodologies among studies. We highlight ruminants as a case study and discuss the link between the core microbiome and host physiology and genetics, as well as potential factors that shape it. We conclude with main directives of action to better understand the host-core microbiome axis and acquire the necessary insights into its controlled modulation. Expected final online publication date for the Annual Review of Animal Biosciences, Volume 10 is February 2022. Please see http://www.annualreviews.org/page/journal/pubdates for revised estimates.
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Affiliation(s)
- Daphne Perlman
- Department of Life Sciences, Ben-Gurion University of the Negev and the National Institute for Biotechnology in the Negev, Be'er-Sheva, Israel;
| | - Marina Martínez-Álvaro
- Department of Agriculture, Horticulture and Engineering Sciences, SRUC (Scotland's Rural College), Edinburgh, Scotland, United Kingdom
| | - Sarah Moraïs
- Department of Life Sciences, Ben-Gurion University of the Negev and the National Institute for Biotechnology in the Negev, Be'er-Sheva, Israel;
| | - Ianina Altshuler
- Faculty of Biosciences, Norwegian University of Life Sciences, Aas, Norway;
| | - Live H Hagen
- Faculty of Chemistry, Biotechnology and Food Science, Norwegian University of Life Sciences, Aas, Norway
| | - Elie Jami
- Department of Ruminant Science, Institute of Animal Sciences, Agricultural Research Organization, Volcani Center, Rishon LeZion, Israel
| | - Rainer Roehe
- Department of Agriculture, Horticulture and Engineering Sciences, SRUC (Scotland's Rural College), Edinburgh, Scotland, United Kingdom
| | - Phillip B Pope
- Faculty of Biosciences, Norwegian University of Life Sciences, Aas, Norway; .,Faculty of Chemistry, Biotechnology and Food Science, Norwegian University of Life Sciences, Aas, Norway
| | - Itzhak Mizrahi
- Department of Life Sciences, Ben-Gurion University of the Negev and the National Institute for Biotechnology in the Negev, Be'er-Sheva, Israel;
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27
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Wang M, Wang H, Zheng H, Uhrin D, Dewhurst RJ, Roehe R. Comparison of HPLC and NMR for quantification of the main volatile fatty acids in rumen digesta. Sci Rep 2021; 11:24337. [PMID: 34934079 PMCID: PMC8692319 DOI: 10.1038/s41598-021-03553-9] [Citation(s) in RCA: 7] [Impact Index Per Article: 1.8] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 08/25/2021] [Accepted: 12/01/2021] [Indexed: 11/08/2022] Open
Abstract
Accurate quantification of volatile fatty acid (VFA) concentrations in rumen fluid are essential for research on rumen metabolism. The study comprehensively investigated the pros and cons of High-performance liquid chromatography (HPLC) and 1H Nuclear magnetic resonance (1H-NMR) analysis methods for rumen VFAs quantification. We also investigated the performance of several commonly used data pre-treatments for the two sets of data using correlation analysis, principal component analysis (PCA) and partial least squares discriminant analysis (PLS-DA). The molar proportion and reliability analysis demonstrated that the two approaches produce highly consistent VFA concentrations. In the pre-processing of NMR spectra, line broadening and shim correction may reduce estimated concentrations of metabolites. We observed differences in results using multiplet of different protons from one compound and identified "handle signals" that provided the most consistent concentrations. Different data pre-treatment strategies tested with both HPLC and NMR significantly affected the results of downstream data analysis. "Normalized by sum" pre-treatment can eliminate a large number of positive correlations between NMR-based VFA. A "Combine" strategy should be the first choice when calculating the correlation between metabolites or between samples. The PCA and PLS-DA suggest that except for "Normalize by sum", pre-treatments should be used with caution.
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Affiliation(s)
- Mengyuan Wang
- School of Computing, Ulster University, Belfast, UK
- Scotland's Rural College, Edinburgh, UK
| | - Haiying Wang
- School of Computing, Ulster University, Belfast, UK
| | - Huiru Zheng
- School of Computing, Ulster University, Belfast, UK.
| | - Dusan Uhrin
- EaStCHEM School of Chemistry, University of Edinburgh, Edinburgh, UK
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28
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Wang F, Harindintwali JD, Yuan Z, Wang M, Wang F, Li S, Yin Z, Huang L, Fu Y, Li L, Chang SX, Zhang L, Rinklebe J, Yuan Z, Zhu Q, Xiang L, Tsang DC, Xu L, Jiang X, Liu J, Wei N, Kästner M, Zou Y, Ok YS, Shen J, Peng D, Zhang W, Barceló D, Zhou Y, Bai Z, Li B, Zhang B, Wei K, Cao H, Tan Z, Zhao LB, He X, Zheng J, Bolan N, Liu X, Huang C, Dietmann S, Luo M, Sun N, Gong J, Gong Y, Brahushi F, Zhang T, Xiao C, Li X, Chen W, Jiao N, Lehmann J, Zhu YG, Jin H, Schäffer A, Tiedje JM, Chen JM. Technologies and perspectives for achieving carbon neutrality. Innovation (N Y) 2021; 2:100180. [PMID: 34877561 PMCID: PMC8633420 DOI: 10.1016/j.xinn.2021.100180] [Citation(s) in RCA: 149] [Impact Index Per Article: 37.3] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 09/20/2021] [Accepted: 10/27/2021] [Indexed: 12/17/2022] Open
Abstract
Global development has been heavily reliant on the overexploitation of natural resources since the Industrial Revolution. With the extensive use of fossil fuels, deforestation, and other forms of land-use change, anthropogenic activities have contributed to the ever-increasing concentrations of greenhouse gases (GHGs) in the atmosphere, causing global climate change. In response to the worsening global climate change, achieving carbon neutrality by 2050 is the most pressing task on the planet. To this end, it is of utmost importance and a significant challenge to reform the current production systems to reduce GHG emissions and promote the capture of CO2 from the atmosphere. Herein, we review innovative technologies that offer solutions achieving carbon (C) neutrality and sustainable development, including those for renewable energy production, food system transformation, waste valorization, C sink conservation, and C-negative manufacturing. The wealth of knowledge disseminated in this review could inspire the global community and drive the further development of innovative technologies to mitigate climate change and sustainably support human activities.
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Affiliation(s)
- Fang Wang
- CAS Key Laboratory of Soil Environment and Pollution Remediation, Institute of Soil Science, Chinese Academy of Sciences, Nanjing 210008, China
- University of Chinese Academy of Sciences, Beijing 100049, China
| | - Jean Damascene Harindintwali
- CAS Key Laboratory of Soil Environment and Pollution Remediation, Institute of Soil Science, Chinese Academy of Sciences, Nanjing 210008, China
- University of Chinese Academy of Sciences, Beijing 100049, China
| | - Zhizhang Yuan
- Dalian Institute of Chemical Physics, Chinese Academy of Sciences, Dalian 116023, China
- University of Chinese Academy of Sciences, Beijing 100049, China
| | - Min Wang
- Key Laboratory for Agro-Ecological Processes in Subtropical Region, Institute of Subtropical Agriculture, Chinese Academy of Sciences, Changsha 410125, China
- University of Chinese Academy of Sciences, Beijing 100049, China
| | - Faming Wang
- South China Botanical Garden, Chinese Academy of Sciences, Guangzhou 510650, China
- Southern Marine Science and Engineering Guangdong Laboratory (Guangzhou), Guangzhou 511458, China
- University of Chinese Academy of Sciences, Beijing 100049, China
| | - Sheng Li
- Institute of Engineering Thermophysics, Chinese Academy of Sciences, Beijing 100190, China
- University of Chinese Academy of Sciences, Beijing 100049, China
| | - Zhigang Yin
- Fujian Institute of Research on the Structure of Matter, Chinese Academy of Sciences, Fuzhou 350002, China
- University of Chinese Academy of Sciences, Beijing 100049, China
| | - Lei Huang
- International Research Center of Big Data for Sustainable Development Goals, Beijing 100094, China
- Key Laboratory of Digital Earth Science, Aerospace Information Research Institute, Chinese Academy of Sciences, Beijing 100094, China
| | - Yuhao Fu
- CAS Key Laboratory of Soil Environment and Pollution Remediation, Institute of Soil Science, Chinese Academy of Sciences, Nanjing 210008, China
- University of Chinese Academy of Sciences, Beijing 100049, China
| | - Lei Li
- State Key Laboratory of Coal Conversion, Institute of Coal Chemistry, Chinese Academy of Sciences, Taiyuan 030001, China
- University of Chinese Academy of Sciences, Beijing 100049, China
| | - Scott X. Chang
- Department of Renewable Resources, University of Alberta, Edmonton, AB T6G 2E3, Canada
| | - Linjuan Zhang
- Shanghai Institute of Applied Physics, Chinese Academy of Sciences, Shanghai 201800, China
- University of Chinese Academy of Sciences, Beijing 100049, China
| | - Jörg Rinklebe
- Department of Soil and Groundwater Management, Bergische Universität Wuppertal, Wuppertal 42285, Germany
| | - Zuoqiang Yuan
- CAS Key Laboratory of Forest Ecology and Management, Institute of Applied Ecology, Chinese Academy of Sciences, Liaoning 110016, China
- University of Chinese Academy of Sciences, Beijing 100049, China
| | - Qinggong Zhu
- Institute of Chemistry, Chinese Academy of Sciences, Beijing 100190, China
- University of Chinese Academy of Sciences, Beijing 100049, China
| | - Leilei Xiang
- CAS Key Laboratory of Soil Environment and Pollution Remediation, Institute of Soil Science, Chinese Academy of Sciences, Nanjing 210008, China
- University of Chinese Academy of Sciences, Beijing 100049, China
| | - Daniel C.W. Tsang
- Department of Civil and Environmental Engineering, Hong Kong Polytechnic University, Hong Kong, China
| | - Liang Xu
- Beijing Institute of Nanoenergy and Nanosystems, Chinese Academy of Sciences, Beijing 101400, China
- University of Chinese Academy of Sciences, Beijing 100049, China
| | - Xin Jiang
- CAS Key Laboratory of Soil Environment and Pollution Remediation, Institute of Soil Science, Chinese Academy of Sciences, Nanjing 210008, China
- University of Chinese Academy of Sciences, Beijing 100049, China
| | - Jihua Liu
- Institute of Marine Science and Technology, Shandong University, Qingdao 266273, China
| | - Ning Wei
- Institute of Rock and Soil Mechanics, Chinese Academy of Sciences, Wuhan 430000, China
- University of Chinese Academy of Sciences, Beijing 100049, China
| | - Matthias Kästner
- Department of Environmental Biotechnology, Helmholtz Centre for Environmental Research – UFZ, Leipzig 04318, Germany
| | - Yang Zou
- Shanghai Institute of Applied Physics, Chinese Academy of Sciences, Shanghai 201800, China
- University of Chinese Academy of Sciences, Beijing 100049, China
| | | | - Jianlin Shen
- Key Laboratory for Agro-Ecological Processes in Subtropical Region, Institute of Subtropical Agriculture, Chinese Academy of Sciences, Changsha 410125, China
- University of Chinese Academy of Sciences, Beijing 100049, China
| | - Dailiang Peng
- International Research Center of Big Data for Sustainable Development Goals, Beijing 100094, China
- Key Laboratory of Digital Earth Science, Aerospace Information Research Institute, Chinese Academy of Sciences, Beijing 100094, China
- University of Chinese Academy of Sciences, Beijing 100049, China
| | - Wei Zhang
- Chongqing Institute of Green and Intelligent Technology, Chinese Academy of Sciences, Chongqing 400714, China
- University of Chinese Academy of Sciences, Beijing 100049, China
| | - Damià Barceló
- Catalan Institute for Water Research ICRA-CERCA, Girona 17003, Spain
| | - Yongjin Zhou
- Dalian Institute of Chemical Physics, Chinese Academy of Sciences, Dalian 116023, China
- University of Chinese Academy of Sciences, Beijing 100049, China
| | - Zhaohai Bai
- Key Laboratory of Agricultural Water Resources, Hebei Key Laboratory of Soil Ecology, Center for Agricultural Resources Research, Institute of Genetic and Developmental Biology, Chinese Academy of Sciences, Shijiazhuang 050021, China
- University of Chinese Academy of Sciences, Beijing 100049, China
| | - Boqiang Li
- CAS Key Laboratory of Plant Resources, Institute of Botany, Chinese Academy of Sciences, Beijing 100093, China
- University of Chinese Academy of Sciences, Beijing 100049, China
| | - Bin Zhang
- State Key Laboratory of Coal Conversion, Institute of Coal Chemistry, Chinese Academy of Sciences, Taiyuan 030001, China
- University of Chinese Academy of Sciences, Beijing 100049, China
| | - Ke Wei
- The Institute of Atmospheric Physics, Chinese Academy of Sciences, Beijing 100029, China
- University of Chinese Academy of Sciences, Beijing 100049, China
| | - Hujun Cao
- Dalian Institute of Chemical Physics, Chinese Academy of Sciences, Dalian 116023, China
- University of Chinese Academy of Sciences, Beijing 100049, China
| | - Zhiliang Tan
- Key Laboratory for Agro-Ecological Processes in Subtropical Region, Institute of Subtropical Agriculture, Chinese Academy of Sciences, Changsha 410125, China
- University of Chinese Academy of Sciences, Beijing 100049, China
| | - Liu-bin Zhao
- Department of Chemistry, School of Chemistry and Chemical Engineering, Southwest University, Chongqing, 400715, China
| | - Xiao He
- Institute of High Energy Physics, Chinese Academy of Sciences, Beijing 100049, China
- University of Chinese Academy of Sciences, Beijing 100049, China
| | - Jinxing Zheng
- Institute of Plasma Physics, Chinese Academy of Sciences, Anhui 230031, China
- University of Chinese Academy of Sciences, Beijing 100049, China
| | - Nanthi Bolan
- School of Agriculture and Environment, Institute of Agriculture, University of Western Australia, Crawley 6009, Australia
| | - Xiaohong Liu
- Chongqing Institute of Green and Intelligent Technology, Chinese Academy of Sciences, Chongqing 400714, China
- University of Chinese Academy of Sciences, Beijing 100049, China
| | - Changping Huang
- Key Laboratory of Digital Earth Science, Aerospace Information Research Institute, Chinese Academy of Sciences, Beijing 100094, China
- University of Chinese Academy of Sciences, Beijing 100049, China
| | - Sabine Dietmann
- Institute for Informatics (I), Washington University, St. Louis, MO 63110-1010, USA
| | - Ming Luo
- South China Botanical Garden, Chinese Academy of Sciences, Guangzhou 510650, China
- University of Chinese Academy of Sciences, Beijing 100049, China
| | - Nannan Sun
- Shanghai Advanced Research Institute, Chinese Academy of Sciences, Shanghai 201210, China
- University of Chinese Academy of Sciences, Beijing 100049, China
| | - Jirui Gong
- Key Laboratory of Surface Processes and Resource Ecology, Faculty of Geographical Science, Beijing Normal University, Beijing 100875, China
| | - Yulie Gong
- CAS Key Laboratory of Renewable Energy, Guangzhou Institute of Energy Conversion, Chinese Academy of Sciences, Guangzhou 510640, China
- University of Chinese Academy of Sciences, Beijing 100049, China
| | - Ferdi Brahushi
- Department of Agro-environment and Ecology, Agricultural University of Tirana, Tirana 1029, Albania
| | - Tangtang Zhang
- Key Laboratory of Land Surface Process and Climate Change in Cold and Arid Regions, Chinese Academy of Sciences, Lanzhou 730000, China
| | - Cunde Xiao
- Key Laboratory of Surface Processes and Resource Ecology, Faculty of Geographical Science, Beijing Normal University, Beijing 100875, China
| | - Xianfeng Li
- Key Laboratory for Agro-Ecological Processes in Subtropical Region, Institute of Subtropical Agriculture, Chinese Academy of Sciences, Changsha 410125, China
- University of Chinese Academy of Sciences, Beijing 100049, China
| | - Wenfu Chen
- Shenyang Agricultural University, Shenyang 110866, China
| | - Nianzhi Jiao
- Joint Laboratory for Ocean Research and Education at Dalhousie University, Shandong University and Xiamen University, Halifax, NS, B3H 4R2, Canada, Qingdao 266237, China, and, Xiamen 361005, China
- Institute of Marine Microbes and Ecospheres, Xiamen University, Xiamen 361101, China
- State Key Laboratory of Marine Environmental Science and College of Ocean and Earth Sciences, Fujian Key Laboratory of Marine Carbon Sequestration, Xiamen University, Xiamen 361005, China
| | - Johannes Lehmann
- School of Integrative Plant Science, Section of Soil and Crop Sciences, Cornell University, Ithaca, NY 14853, USA
- Institute for Advanced Studies, Technical University Munich, Garching 85748, Germany
| | - Yong-Guan Zhu
- Key Lab of Urban Environment and Health, Institute of Urban Environment, Chinese Academy of Sciences, 1799 Jimei Road, Xiamen, 361021, China
- State Key Laboratory of Urban and Regional Ecology, Research Center for Eco-Environmental Sciences, Chinese Academy of Sciences, Beijing, 100085, China
- University of Chinese Academy of Sciences, Beijing 100049, China
| | - Hongguang Jin
- International Research Center of Big Data for Sustainable Development Goals, Beijing 100094, China
- University of Chinese Academy of Sciences, Beijing 100049, China
| | - Andreas Schäffer
- Institute for Environmental Research, RWTH Aachen University, Aachen 52074, Germany
| | - James M. Tiedje
- Center for Microbial Ecology, Department of Plant, Soil and Microbial Sciences, Michigan State University, East Lansing, MI 48824, USA
| | - Jing M. Chen
- Department of Geography and Planning, University of Toronto, Ontario, Canada, M5S 3G3
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Reisinger A, Clark H, Cowie AL, Emmet-Booth J, Gonzalez Fischer C, Herrero M, Howden M, Leahy S. How necessary and feasible are reductions of methane emissions from livestock to support stringent temperature goals? PHILOSOPHICAL TRANSACTIONS. SERIES A, MATHEMATICAL, PHYSICAL, AND ENGINEERING SCIENCES 2021; 379:20200452. [PMID: 34565223 PMCID: PMC8480228 DOI: 10.1098/rsta.2020.0452] [Citation(s) in RCA: 25] [Impact Index Per Article: 6.3] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Subscribe] [Scholar Register] [Accepted: 06/02/2021] [Indexed: 05/05/2023]
Abstract
Agriculture is the largest single source of global anthropogenic methane (CH4) emissions, with ruminants the dominant contributor. Livestock CH4 emissions are projected to grow another 30% by 2050 under current policies, yet few countries have set targets or are implementing policies to reduce emissions in absolute terms. The reason for this limited ambition may be linked not only to the underpinning role of livestock for nutrition and livelihoods in many countries but also diverging perspectives on the importance of mitigating these emissions, given the short atmospheric lifetime of CH4. Here, we show that in mitigation pathways that limit warming to 1.5°C, which include cost-effective reductions from all emission sources, the contribution of future livestock CH4 emissions to global warming in 2050 is about one-third of that from future net carbon dioxide emissions. Future livestock CH4 emissions, therefore, significantly constrain the remaining carbon budget and the ability to meet stringent temperature limits. We review options to address livestock CH4 emissions through more efficient production, technological advances and demand-side changes, and their interactions with land-based carbon sequestration. We conclude that bringing livestock into mainstream mitigation policies, while recognizing their unique social, cultural and economic roles, would make an important contribution towards reaching the temperature goal of the Paris Agreement and is vital for a limit of 1.5°C. This article is part of a discussion meeting issue 'Rising methane: is warming feeding warming? (part 1)'.
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Affiliation(s)
| | - Harry Clark
- New Zealand Agricultural Greenhouse Gas Research Centre (NZAGRC), Palmerston North, New Zealand
| | - Annette L. Cowie
- New South Wales Department of Primary Industries/University of New England, Armidale, Australia
| | - Jeremy Emmet-Booth
- New Zealand Agricultural Greenhouse Gas Research Centre (NZAGRC), Palmerston North, New Zealand
| | - Carlos Gonzalez Fischer
- New Zealand Agricultural Greenhouse Gas Research Centre (NZAGRC), Palmerston North, New Zealand
| | - Mario Herrero
- Department of Global Development, College of Agriculture and Life Sciences, and Cornell Atkinson Centre for Sustainability, Cornell University, Ithaca, USA
| | - Mark Howden
- Australian National University, Canberra, Australia
| | - Sinead Leahy
- New Zealand Agricultural Greenhouse Gas Research Centre (NZAGRC), Palmerston North, New Zealand
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30
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Smith PE, Waters SM, Kenny DA, Kirwan SF, Conroy S, Kelly AK. Effect of divergence in residual methane emissions on feed intake and efficiency, growth and carcass performance, and indices of rumen fermentation and methane emissions in finishing beef cattle. J Anim Sci 2021; 99:6379086. [PMID: 34598276 PMCID: PMC8598385 DOI: 10.1093/jas/skab275] [Citation(s) in RCA: 3] [Impact Index Per Article: 0.8] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 08/07/2021] [Accepted: 09/29/2021] [Indexed: 12/31/2022] Open
Abstract
Residual expressions of enteric emissions favor a more equitable identification of an animal's methanogenic potential compared with traditional measures of enteric emissions. The objective of this study was to investigate the effect of divergently ranking beef cattle for residual methane emissions (RME) on animal productivity, enteric emissions, and rumen fermentation. Dry matter intake (DMI), growth, feed efficiency, carcass output, and enteric emissions (GreenFeed emissions monitoring system) were recorded on 294 crossbred beef cattle (steers = 135 and heifers = 159; mean age 441 d (SD = 49); initial body weight (BW) of 476 kg (SD = 67)) at the Irish national beef cattle performance test center. Animals were offered a total mixed ration (77% concentrate and 23% forage; 12.6 MJ ME/kg of DM and 12% CP) ad libitum with emissions estimated for 21 d over a mean feed intake measurement period of 91 d. Animals had a mean daily methane emissions (DME) of 229.18 g/d (SD = 45.96), methane yield (MY) of 22.07 g/kg of DMI (SD = 4.06), methane intensity (MI) 0.70 g/kg of carcass weight (SD = 0.15), and RME 0.00 g/d (SD = 0.34). RME was computed as the residuals from a multiple regression model regressing DME on DMI and BW (R2 = 0.45). Animals were ranked into three groups namely high RME (>0.5 SD above the mean), medium RME (±0.5 SD above/below the mean), and low RME (>0.5 SD below the mean). Low RME animals produced 17.6% and 30.4% less (P < 0.05) DME compared with medium and high RME animals, respectively. A ~30% reduction in MY and MI was detected in low versus high RME animals. Positive correlations were apparent among all methane traits with RME most highly associated with (r = 0.86) DME. MY and MI were correlated (P < 0.05) with DMI, growth, feed efficiency, and carcass output. High RME had lower (P < 0.05) ruminal propionate compared with low RME animals and increased (P < 0.05) butyrate compared with medium and low RME animals. Propionate was negatively associated (P < 0.05) with all methane traits. Greater acetate:propionate ratio was associated with higher RME (r = 0.18; P < 0.05). Under the ad libitum feeding regime deployed here, RME was the best predictor of DME and only methane trait independent of animal productivity. Ranking animals on RME presents the opportunity to exploit interanimal variation in enteric emissions as well as providing a more equitable index of the methanogenic potential of an animal on which to investigate the underlying biological regulatory mechanisms.
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Affiliation(s)
- Paul E Smith
- Teagasc, Animal and Bioscience Research Department, Animal and Grassland Research and Innovation Centre, Grange, Dunsany, County Meath, Ireland.,UCD School of Agriculture and Food Science, University College Dublin, Belfield, Dublin 4, Ireland
| | - Sinead M Waters
- Teagasc, Animal and Bioscience Research Department, Animal and Grassland Research and Innovation Centre, Grange, Dunsany, County Meath, Ireland
| | - David A Kenny
- Teagasc, Animal and Bioscience Research Department, Animal and Grassland Research and Innovation Centre, Grange, Dunsany, County Meath, Ireland
| | - Stuart F Kirwan
- Teagasc, Animal and Bioscience Research Department, Animal and Grassland Research and Innovation Centre, Grange, Dunsany, County Meath, Ireland
| | - Stephen Conroy
- Irish Cattle Breeding Federation, G€N€ IR€LAND Progeny Test Centre, Tully, Kildare Town, County Kildare, Ireland
| | - Alan K Kelly
- UCD School of Agriculture and Food Science, University College Dublin, Belfield, Dublin 4, Ireland
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31
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Tamayao P, Ribeiro GO, McAllister TA, Ominski KH, Saleem AM, Yang HE, Okine EK, McGeough EJ. Effect of pine-based biochars with differing physiochemical properties on methane production, ruminal fermentation, and rumen microbiota in an artificial rumen (RUSITEC) fed barley silage. CANADIAN JOURNAL OF ANIMAL SCIENCE 2021. [DOI: 10.1139/cjas-2020-0129] [Citation(s) in RCA: 1] [Impact Index Per Article: 0.3] [Reference Citation Analysis] [Abstract] [Track Full Text] [Subscribe] [Scholar Register] [Indexed: 12/14/2022]
Abstract
This study investigated the effects of three pine-based biochar products on nutrient disappearance, total gas and methane (CH4) production, rumen fermentation, microbial protein synthesis, and rumen microbiota in a rumen simulation technique (RUSITEC) fed a barley-silage-based total mixed ration (TMR). Treatments consisted of 10 g TMR supplemented with no biochar (control) and three different biochars (CP016, CP024, and CP028) included at 20 g·kg−1 DM. Treatments were assigned to 16 fermenters (n = 4 per treatment) in two RUSITEC units in a randomized block design for a 17 d experimental period. Data were analyzed using MIXED procedure in SAS, with treatment and day of sampling as fixed effects and RUSITEC unit and fermenters as random effects. Biochar did not affect nutrient disappearance (P > 0.05), nor total gas or CH4, irrespective of unit of expression. The volatile fatty acid, NH3-N, total protozoa, and microbial protein synthesis were not affected by biochar inclusion (P > 0.05). Alpha and beta diversity and rumen microbiota families were not affected by biochar inclusion (P > 0.05). In conclusion, biochar did not reduce CH4 emissions nor affect nutrient disappearance, rumen fermentation, microbial protein synthesis, or rumen microbiota in the RUSITEC.
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Affiliation(s)
- Paul Tamayao
- Department of Animal Science, University of Manitoba, Winnipeg, MB R3T 2N2, Canada
- National Centre for Livestock and the Environment, University of Manitoba, Winnipeg, MB R3T 2N2, Canada
| | - Gabriel O. Ribeiro
- Department of Animal and Poultry Science, University of Saskatchewan, 51 Campus Drive, Saskatoon, SK S7N 5A8, Canada
| | - Tim A. McAllister
- Lethbridge Research and Development Centre, Agriculture and Agri-Food Canada, 5403 1st Avenue South, Lethbridge, AB T1J 4B1, Canada
| | - Kim H. Ominski
- Department of Animal Science, University of Manitoba, Winnipeg, MB R3T 2N2, Canada
- National Centre for Livestock and the Environment, University of Manitoba, Winnipeg, MB R3T 2N2, Canada
| | - Atef M. Saleem
- Animal and Poultry Production Department, Faculty of Agriculture, South Valley University, Qena 83523, Egypt
| | - Hee Eun Yang
- Lethbridge Research and Development Centre, Agriculture and Agri-Food Canada, 5403 1st Avenue South, Lethbridge, AB T1J 4B1, Canada
| | - Erasmus K. Okine
- Office of the Provost and Vice-President Academic, University of Lethbridge, Lethbridge, AB T1K 3M4, Canada
| | - Emma J. McGeough
- Department of Animal Science, University of Manitoba, Winnipeg, MB R3T 2N2, Canada
- National Centre for Livestock and the Environment, University of Manitoba, Winnipeg, MB R3T 2N2, Canada
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Bharanidharan R, Lee CH, Thirugnanasambantham K, Ibidhi R, Woo YW, Lee HG, Kim JG, Kim KH. Feeding Systems and Host Breeds Influence Ruminal Fermentation, Methane Production, Microbial Diversity and Metagenomic Gene Abundance. Front Microbiol 2021; 12:701081. [PMID: 34354694 PMCID: PMC8329423 DOI: 10.3389/fmicb.2021.701081] [Citation(s) in RCA: 14] [Impact Index Per Article: 3.5] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 04/27/2021] [Accepted: 06/28/2021] [Indexed: 12/12/2022] Open
Abstract
Our previous research revealed the advantages of separate feeding (SF) systems compared to total mixed ration (TMR) in terms of ruminal methane (CH4) production. The purpose of this experiment was to confirm the advantage of SF as a nutritional strategy for CH4 mitigation, and to determine the effects of different feeding systems (TMR and SF) on the rumen microbiome and associated metagenome of two different breeds and on CH4 emissions. We randomly allocated four Holstein (305 ± 29 kg) and four Hanwoo steers (292 ± 24 kg) to two groups; the steers were fed a commercial concentrate with tall fescue (75:25) as TMR or SF, in a crossover design (two successive 22-day periods). Neither feeding systems nor cattle breeds had an effect on the total tract digestibility of nutrients. The TMR feeding system and Hanwoo steers generated significantly more CH4 (P < 0.05) and had a higher yield [g/d and g/kg dry matter intake (DMI)] compared to the SF system and Holstein steers. A larger rumen acetate:propionate ratio was observed for the TMR than the SF diet (P < 0.05), and for Hanwoo than Holstein steers (P < 0.001), clearly reflecting a shift in the ruminal H2 sink toward CH4 production. The linear discriminant analysis (LDA) effect size (LEfSe) revealed a greater abundance (α < 0.05 and LDA > 2.0) of operational taxonomic units (OTUs) related to methanogenesis for Hanwoo steers compared to Holstein steers. Kendall’s correlation analysis revealed wide variation of microbial co-occurrence patterns between feeding systems, indicating differential H2 thermodynamics in the rumen. A metagenome analysis of rumen microbes revealed the presence of 430 differentially expressed genes, among which 17 and 27 genes exhibited positive and negative associations with CH4 production, respectively (P < 0.001). A strong interaction between feeding system and breed was observed for microbial and metagenomic abundance. Overall, these results suggest that the TMR feeding system produces more CH4, and that Hanwoo cattle are higher CH4 emitters than SF diet and Holstein cattle, respectively. Interestingly, host-associated microbial interactions differed within each breed depending on the feeding system, which indicated that breed-specific feeding systems should be taken into account for farm management.
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Affiliation(s)
- Rajaraman Bharanidharan
- Department of Agricultural Biotechnology, College of Agriculture and Life Sciences, Seoul National University, Seoul, South Korea
| | - Chang Hyun Lee
- Cargill Agri Purina Inc., Technology Application Center, Pyeongchang, South Korea
| | - Krishnaraj Thirugnanasambantham
- Department of Ecofriendly Livestock Science, Institute of Green Bio Science and Technology, Seoul National University, Pyeongchang, South Korea.,Pondicherry Centre for Biological Science and Educational Trust, Tamil Nadu, India
| | - Ridha Ibidhi
- Department of Ecofriendly Livestock Science, Institute of Green Bio Science and Technology, Seoul National University, Pyeongchang, South Korea
| | | | - Hong-Gu Lee
- Department of Animal Science and Technology, SangHa Life Science College, Konkuk University, Seoul, South Korea
| | - Jong Geun Kim
- Department of Ecofriendly Livestock Science, Institute of Green Bio Science and Technology, Seoul National University, Pyeongchang, South Korea.,Department of International Agricultural Technology, Graduate School of International Agricultural Technology, Seoul National University, Pyeongchang, South Korea
| | - Kyoung Hoon Kim
- Department of Ecofriendly Livestock Science, Institute of Green Bio Science and Technology, Seoul National University, Pyeongchang, South Korea.,Department of International Agricultural Technology, Graduate School of International Agricultural Technology, Seoul National University, Pyeongchang, South Korea
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Accessing Dietary Effects on the Rumen Microbiome: Different Sequencing Methods Tell Different Stories. Vet Sci 2021; 8:vetsci8070138. [PMID: 34357930 PMCID: PMC8310016 DOI: 10.3390/vetsci8070138] [Citation(s) in RCA: 1] [Impact Index Per Article: 0.3] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 06/08/2021] [Revised: 07/02/2021] [Accepted: 07/14/2021] [Indexed: 12/29/2022] Open
Abstract
The current study employed both amplicon and shotgun sequencing to examine and compare the rumen microbiome in Angus bulls fed with either a backgrounding diet (BCK) or finishing diet (HG), to assess if both methods produce comparable results. Rumen digesta samples from 16 bulls were subjected for microbial profiling. Distinctive microbial profiles were revealed by the two methods, indicating that choice of sequencing approach may be a critical facet in studies of the rumen microbiome. Shotgun-sequencing identified the presence of 303 bacterial genera and 171 archaeal species, several of which exhibited differential abundance. Amplicon-sequencing identified 48 bacterial genera, 4 archaeal species, and 9 protozoal species. Among them, 20 bacterial genera and 5 protozoal species were differentially abundant between the two diets. Overall, amplicon-sequencing showed a more drastic diet-derived effect on the ruminal microbial profile compared to shotgun-sequencing. While both methods detected dietary differences at various taxonomic levels, few consistent patterns were evident. Opposite results were seen for the phyla Firmicutes and Bacteroidetes, and the genus Selenomonas. This study showcases the importance of sequencing platform choice and suggests a need for integrative methods that allow robust comparisons of microbial data drawn from various omic approaches, allowing for comprehensive comparisons across studies.
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34
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Bailoni L, Carraro L, Cardin M, Cardazzo B. Active Rumen Bacterial and Protozoal Communities Revealed by RNA-Based Amplicon Sequencing on Dairy Cows Fed Different Diets at Three Physiological Stages. Microorganisms 2021; 9:754. [PMID: 33918504 PMCID: PMC8066057 DOI: 10.3390/microorganisms9040754] [Citation(s) in RCA: 5] [Impact Index Per Article: 1.3] [Reference Citation Analysis] [Abstract] [Key Words] [Grants] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 02/24/2021] [Revised: 03/29/2021] [Accepted: 04/01/2021] [Indexed: 12/12/2022] Open
Abstract
Seven Italian Simmental cows were monitored during three different physiological stages, namely late lactation (LL), dry period (DP), and postpartum (PP), to evaluate modifications in their metabolically-active rumen bacterial and protozoal communities using the RNA-based amplicon sequencing method. The bacterial community was dominated by seven phyla: Proteobacteria, Bacteroidetes, Firmicutes, Spirochaetes, Fibrobacteres, Verrucomicrobia, and Tenericutes. The relative abundance of the phylum Proteobacteria decreased from 47.60 to 28.15% from LL to DP and then increased to 33.24% in PP. An opposite pattern in LL, DP, and PP stages was observed for phyla Verrucomicrobia (from 0.96 to 4.30 to 1.69%), Elusimicrobia (from 0.32 to 2.84 to 0.25%), and SR1 (from 0.50 to 2.08 to 0.79%). The relative abundance of families Succinivibrionaceae and Prevotellaceae decreased in the DP, while Ruminococcaceae increased. Bacterial genera Prevotella and Treponema were least abundant in the DP as compared to LL and PP, while Ruminobacter and Succinimonas were most abundant in the DP. The rumen eukaryotic community was dominated by protozoal phylum Ciliophora, which showed a significant decrease in relative abundance from 97.6 to 93.9 to 92.6 in LL, DP, and PP, respectively. In conclusion, the physiological stage-dependent dietary changes resulted in a clear shift in metabolically-active rumen microbial communities.
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Affiliation(s)
- Lucia Bailoni
- Department of Comparative Biomedicine and Food Science (BCA), University of Padova, Viale dell’Universitá 16, 35020 Legnaro, PD, Italy; (L.C.); (M.C.); (B.C.)
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35
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Metagenomic analysis of the cow, sheep, reindeer and red deer rumen. Sci Rep 2021; 11:1990. [PMID: 33479378 PMCID: PMC7820578 DOI: 10.1038/s41598-021-81668-9] [Citation(s) in RCA: 31] [Impact Index Per Article: 7.8] [Reference Citation Analysis] [Abstract] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 09/21/2020] [Accepted: 12/15/2020] [Indexed: 12/12/2022] Open
Abstract
The rumen microbiota comprises a community of microorganisms which specialise in the degradation of complex carbohydrates from plant-based feed. These microbes play a highly important role in ruminant nutrition and could also act as sources of industrially useful enzymes. In this study, we performed a metagenomic analysis of samples taken from the ruminal contents of cow (Bos Taurus), sheep (Ovis aries), reindeer (Rangifer tarandus) and red deer (Cervus elaphus). We constructed 391 metagenome-assembled genomes originating from 16 microbial phyla. We compared our genomes to other publically available microbial genomes and found that they contained 279 novel species. We also found significant differences between the microbiota of different ruminant species in terms of the abundance of microbial taxonomies, carbohydrate-active enzyme genes and KEGG orthologs. We present a dataset of rumen-derived genomes which in combination with other publicly-available rumen genomes can be used as a reference dataset in future metagenomic studies.
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36
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Wang M, Wang H, Zheng H, Dewhurst RJ, Roehe R. A heat diffusion multilayer network approach for the identification of functional biomarkers in rumen methane emissions. Methods 2020; 192:57-66. [PMID: 33068740 DOI: 10.1016/j.ymeth.2020.09.014] [Citation(s) in RCA: 4] [Impact Index Per Article: 0.8] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Journal Information] [Subscribe] [Scholar Register] [Received: 06/26/2020] [Revised: 09/15/2020] [Accepted: 09/16/2020] [Indexed: 02/06/2023] Open
Abstract
A better understanding of rumen microbial interactions is crucial for the study of rumen metabolism and methane emissions. Metagenomics-based methods can explore the relationship between microbial genes and metabolites to clarify the effect of microbial function on the host phenotype. This study investigated the rumen microbial mechanisms of methane metabolism in cattle by combining metagenomic data and network-based methods. Based on the relative abundance of 1461 rumen microbial genes and the main volatile fatty acids (VFAs), a multilayer heterogeneous network was constructed, and the functional modules associated with metabolite-microbial genes were obtained by heat diffusion algorithm. The PLS model by integrating data from VFAs and microbial genes explained 72.98% variation of methane emissions. Compared with single-layer networks, more previously reported biomarkers of methane prediction can be captured by the multilayer network. More biomarkers with the rank of top 20 topological centralities were from the PLS models of diffusion subsets. The heat diffusion algorithm is different from the strategy used by the microbial metabolic system to understand methane phenotype. It inferred 24 novel biomarkers that were preferentially affected by changes in specific VFAs. Results showed that the heat diffusion multilayer network approach improved the understanding of the microbial patterns of VFAs affecting methane emissions which represented by the functional microbial genes.
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Affiliation(s)
- Mengyuan Wang
- School of Computing, Ulster University, United Kingdom
| | - Haiying Wang
- School of Computing, Ulster University, United Kingdom
| | - Huiru Zheng
- School of Computing, Ulster University, United Kingdom.
| | | | - Rainer Roehe
- Scotland's Rural College, Edinburgh, United Kingdom
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37
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Wilkinson T, Korir D, Ogugo M, Stewart RD, Watson M, Paxton E, Goopy J, Robert C. 1200 high-quality metagenome-assembled genomes from the rumen of African cattle and their relevance in the context of sub-optimal feeding. Genome Biol 2020; 21:229. [PMID: 32883364 PMCID: PMC7469290 DOI: 10.1186/s13059-020-02144-7] [Citation(s) in RCA: 42] [Impact Index Per Article: 8.4] [Reference Citation Analysis] [Abstract] [MESH Headings] [Grants] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 12/20/2018] [Accepted: 08/16/2020] [Indexed: 12/20/2022] Open
Abstract
BACKGROUND The Boran (Bos indicus), indigenous Zebu cattle breed from sub-Saharan Africa, is remarkably well adapted to harsh tropical environments. Due to financial constraints and low-quality forage, African livestock are rarely fed at 100% maintenance energy requirements (MER) and the effect of sub-optimal restricted feeding on the rumen microbiome of African Zebu cattle remains largely unexplored. We collected 24 rumen fluid samples from six Boran cattle fed at sub-optimal and optimal MER levels and characterised their rumen microbial composition by performing shotgun metagenomics and de novo assembly of metagenome-assembled genomes (MAGs). These MAGs were used as reference database to investigate the effect of diet restriction on the composition and functional potential of the rumen microbiome of African cattle. RESULTS We report 1200 newly discovered MAGs from the rumen of Boran cattle. A total of 850 were dereplicated, and their uniqueness confirmed with pairwise comparisons (based on Mash distances) between African MAGs and other publicly available genomes from the rumen. A genome-centric investigation into sub-optimal diets highlighted a statistically significant effect on rumen microbial abundance profiles and a previously unobserved relationship between whole microbiome shifts in functional potential and taxon-level associations in metabolic pathways. CONCLUSIONS This study is the first to identify 1200 high-quality African rumen-specific MAGs and provides further insight into the rumen function in harsh environments with food scarcity. The genomic information from the rumen microbiome of an indigenous African cattle breed sheds light on the microbiome contribution to rumen functionality and constitutes a vital resource in addressing food security in developing countries.
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Affiliation(s)
- Toby Wilkinson
- The Roslin Institute and R(D)SVS, University of Edinburgh, Easter Bush, Roslin, EH25 9RG, UK
| | - Daniel Korir
- International Livestock Research Institute (ILRI), P.O. Box 30709, Nairobi, 00100, Kenya
| | - Moses Ogugo
- International Livestock Research Institute (ILRI), P.O. Box 30709, Nairobi, 00100, Kenya
| | - Robert D Stewart
- The Roslin Institute and R(D)SVS, University of Edinburgh, Easter Bush, Roslin, EH25 9RG, UK
| | - Mick Watson
- The Roslin Institute and R(D)SVS, University of Edinburgh, Easter Bush, Roslin, EH25 9RG, UK
| | - Edith Paxton
- The Roslin Institute and R(D)SVS, University of Edinburgh, Easter Bush, Roslin, EH25 9RG, UK
| | - John Goopy
- International Livestock Research Institute (ILRI), P.O. Box 30709, Nairobi, 00100, Kenya
| | - Christelle Robert
- The Roslin Institute and R(D)SVS, University of Edinburgh, Easter Bush, Roslin, EH25 9RG, UK.
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38
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Wang M, Wang H, Zheng H, Dewhurst R, Roehe R. A Knowledge-Driven Network-Based Analytical Framework for the Identification of Rumen Metabolites. IEEE Trans Nanobioscience 2020; 19:518-526. [DOI: 10.1109/tnb.2020.2991577] [Citation(s) in RCA: 1] [Impact Index Per Article: 0.2] [Reference Citation Analysis] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 11/08/2022]
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39
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Auffret MD, Stewart RD, Dewhurst RJ, Duthie CA, 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. [PMID: 32582125 PMCID: PMC7292206 DOI: 10.3389/fmicb.2020.01229] [Citation(s) in RCA: 30] [Impact Index Per Article: 6.0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 01/17/2020] [Accepted: 05/14/2020] [Indexed: 12/15/2022] Open
Abstract
In this study, Bos Taurus cattle offered one high concentrate diet (92% concentrate-8% straw) during two independent trials allowed us to classify 72 animals comprising of two cattle breeds as "Low" or "High" feed efficiency groups. Digesta samples were taken from individual beef cattle at the abattoir. After metagenomic sequencing, the rumen microbiome composition and genes were determined. Applying a targeted approach based on current biological evidence, 27 genes associated with host-microbiome interaction activities were selected. Partial least square analysis enabled the identification of the most significant genes and genera of feed efficiency (VIP > 0.8) across years of the trial and breeds when comparing all potential genes or genera together. As a result, limited number of genes explained about 40% of the variability in both feed efficiency indicators. Combining information from rumen metagenome-assembled genomes and partial least square analysis results, microbial genera carrying these genes were determined and indicated that a limited number of important genera impacting on feed efficiency. In addition, potential mechanisms explaining significant difference between Low and High feed efficiency animals were analyzed considering, based on the literature, their gastrointestinal location of action. High feed efficiency animals were associated with microbial species including several Eubacterium having the genetic capacity to form biofilm or releasing metabolites like butyrate or propionate known to provide a greater contribution to cattle energy requirements compared to acetate. Populations associated with fucose sensing or hemolysin production, both mechanisms specifically described in the lower gut by activating the immune system to compete with pathogenic colonizers, were also identified to affect feed efficiency using rumen microbiome information. Microbial mechanisms associated with low feed efficiency animals involved potential pathogens within Proteobacteria and Spirochaetales, releasing less energetic substrates (e.g., acetate) or producing sialic acid to avoid the host immune system. Therefore, this study focusing on genes known to be involved in host-microbiome interaction improved the identification of rumen microbial genetic capacities and potential mechanisms significantly impacting on feed efficiency in beef cattle fed high concentrate diet.
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Affiliation(s)
| | - Robert D. Stewart
- Division of Genetics and Genomics, The Roslin Institute and R(D)SVS, University of Edinburgh, Edinburgh, United Kingdom
| | | | | | - Mick Watson
- Division of Genetics and Genomics, The Roslin Institute and R(D)SVS, University of Edinburgh, Edinburgh, United Kingdom
- Edinburgh Genomics, The Roslin Institute and R(D)SVS, University of Edinburgh, Edinburgh, United Kingdom
| | - Rainer Roehe
- Scotland’s Rural College (SRUC), Edinburgh, United Kingdom
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Bayesian modeling reveals host genetics associated with rumen microbiota jointly influence methane emission in dairy cows. ISME JOURNAL 2020; 14:2019-2033. [PMID: 32366970 PMCID: PMC7368015 DOI: 10.1038/s41396-020-0663-x] [Citation(s) in RCA: 46] [Impact Index Per Article: 9.2] [Reference Citation Analysis] [Abstract] [Track Full Text] [Download PDF] [Figures] [Subscribe] [Scholar Register] [Received: 05/07/2019] [Revised: 03/25/2020] [Accepted: 04/15/2020] [Indexed: 12/11/2022]
Abstract
Reducing methane emissions from livestock production is of great importance for the sustainable management of the Earth’s environment. Rumen microbiota play an important role in producing biogenic methane. However, knowledge of how host genetics influences variation in ruminal microbiota and their joint effects on methane emission is limited. We analyzed data from 750 dairy cows, using a Bayesian model to simultaneously assess the impact of host genetics and microbiota on host methane emission. We estimated that host genetics and microbiota explained 24% and 7%, respectively, of variation in host methane levels. In this Bayesian model, one bacterial genus explained up to 1.6% of the total microbiota variance. Further analysis was performed by a mixed linear model to estimate variance explained by host genomics in abundances of microbial genera and operational taxonomic units (OTU). Highest estimates were observed for a bacterial OTU with 33%, for an archaeal OTU with 26%, and for a microbial genus with 41% heritability. However, after multiple testing correction for the number of genera and OTUs modeled, none of the effects remained significant. We also used a mixed linear model to test effects of individual host genetic markers on microbial genera and OTUs. In this analysis, genetic markers inside host genes ABS4 and DNAJC10 were found associated with microbiota composition. We show that a Bayesian model can be utilized to model complex structure and relationship between microbiota simultaneously and their interaction with host genetics on methane emission. The host genome explains a significant fraction of between-individual variation in microbial abundance. Individual microbial taxonomic groups each only explain a small amount of variation in methane emissions. The identification of genes and genetic markers suggests that it is possible to design strategies for breeding cows with desired microbiota composition associated with phenotypes.
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Review: Fifty years of research on rumen methanogenesis: lessons learned and future challenges for mitigation. Animal 2020; 14:s2-s16. [PMID: 32024560 DOI: 10.1017/s1751731119003100] [Citation(s) in RCA: 218] [Impact Index Per Article: 43.6] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 01/01/2023] Open
Abstract
Meat and milk from ruminants provide an important source of protein and other nutrients for human consumption. Although ruminants have a unique advantage of being able to consume forages and graze lands not suitable for arable cropping, 2% to 12% of the gross energy consumed is converted to enteric CH4 during ruminal digestion, which contributes approximately 6% of global anthropogenic greenhouse gas emissions. Thus, ruminant producers need to find cost-effective ways to reduce emissions while meeting consumer demand for food. This paper provides a critical review of the substantial amount of ruminant CH4-related research published in past decades, highlighting hydrogen flow in the rumen, the microbiome associated with methanogenesis, current and future prospects for CH4 mitigation and insights into future challenges for science, governments, farmers and associated industries. Methane emission intensity, measured as emissions per unit of meat and milk, has continuously declined over the past decades due to improvements in production efficiency and animal performance, and this trend is expected to continue. However, continued decline in emission intensity will likely be insufficient to offset the rising emissions from increasing demand for animal protein. Thus, decreases in both emission intensity (g CH4/animal product) and absolute emissions (g CH4/day) are needed if the ruminant industries continue to grow. Providing producers with cost-effective options for decreasing CH4 emissions is therefore imperative, yet few cost-effective approaches are currently available. Future abatement may be achieved through animal genetics, vaccine development, early life programming, diet formulation, use of alternative hydrogen sinks, chemical inhibitors and fermentation modifiers. Individually, these strategies are expected to have moderate effects (<20% decrease), with the exception of the experimental inhibitor 3-nitrooxypropanol for which decreases in CH4 have consistently been greater (20% to 40% decrease). Therefore, it will be necessary to combine strategies to attain the sizable reduction in CH4 needed, but further research is required to determine whether combining anti-methanogenic strategies will have consistent additive effects. It is also not clear whether a decrease in CH4 production leads to consistent improved animal performance, information that will be necessary for adoption by producers. Major constraints for decreasing global enteric CH4 emissions from ruminants are continued expansion of the industry, the cost of mitigation, the difficulty of applying mitigation strategies to grazing ruminants, the inconsistent effects on animal performance and the paucity of information on animal health, reproduction, product quality, cost-benefit, safety and consumer acceptance.
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Martínez-Álvaro M, Auffret MD, Stewart RD, Dewhurst RJ, Duthie CA, Rooke JA, Wallace RJ, Shih B, Freeman TC, Watson M, Roehe R. 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. [PMID: 32362882 PMCID: PMC7181398 DOI: 10.3389/fmicb.2020.00659] [Citation(s) in RCA: 45] [Impact Index Per Article: 9.0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 10/22/2019] [Accepted: 03/23/2020] [Indexed: 11/13/2022] Open
Abstract
A network analysis including relative abundances of all ruminal microbial genera (archaea, bacteria, fungi, and protists) and their genes was performed to improve our understanding of how the interactions within the ruminal microbiome affects methane emissions (CH4). Metagenomics and CH4 data were available from 63 bovines of a two-breed rotational cross, offered two basal diets. Co-abundance network analysis revealed 10 clusters of functional niches. The most abundant hydrogenotrophic Methanobacteriales with key microbial genes involved in methanogenesis occupied a different functional niche (i.e., "methanogenesis" cluster) than methylotrophic Methanomassiliicoccales (Candidatus Methanomethylophylus) and acetogens (Blautia). Fungi and protists clustered together and other plant fiber degraders like Fibrobacter occupied a seperate cluster. A Partial Least Squares analysis approach to predict CH4 variation in each cluster showed the methanogenesis cluster had the best prediction ability (57.3%). However, the most important explanatory variables in this cluster were genes involved in complex carbohydrate degradation, metabolism of sugars and amino acids and Candidatus Azobacteroides carrying nitrogen fixation genes, but not methanogenic archaea and their genes. The cluster containing Fibrobacter, isolated from other microorganisms, was positively associated with CH4 and explained 49.8% of its variability, showing fermentative advantages compared to other bacteria and fungi in providing substrates (e.g., formate) for methanogenesis. In other clusters, genes with enhancing effect on CH4 were related to lactate and butyrate (Butyrivibrio and Pseudobutyrivibrio) production and simple amino acids metabolism. In comparison, ruminal genes negatively related to CH4 were involved in carbohydrate degradation via lactate and succinate and synthesis of more complex amino acids by γ-Proteobacteria. When analyzing low- and high-methane emitters data in separate networks, competition between methanogens in the methanogenesis cluster was uncovered by a broader diversity of methanogens involved in the three methanogenesis pathways and larger interactions within and between communities in low compared to high emitters. Generally, our results suggest that differences in CH4 are mainly explained by other microbial communities and their activities rather than being only methanogens-driven. Our study provides insight into the interactions of the rumen microbial communities and their genes by uncovering functional niches affecting CH4, which will benefit the development of efficient CH4 mitigation strategies.
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Affiliation(s)
- Marina Martínez-Álvaro
- Scotland’s Rural College, Edinburgh, United Kingdom
- Institute for Animal Science and Technology, Polytechnic University of Valencia, Valencia, Spain
| | | | - Robert D. Stewart
- Edinburgh Genomics, The Roslin Institute and R(D)SVS, The University of Edinburgh, Edinburgh, United Kingdom
| | | | | | | | - R. John Wallace
- The Rowett Institute, University of Aberdeen, Aberdeen, United Kingdom
| | - Barbara Shih
- Division of Genetics and Genomics, The Roslin Institute and R(D)SVS, The University of Edinburgh, Edinburgh, United Kingdom
| | - Tom C. Freeman
- Division of Genetics and Genomics, The Roslin Institute and R(D)SVS, The University of Edinburgh, Edinburgh, United Kingdom
| | - Mick Watson
- Edinburgh Genomics, The Roslin Institute and R(D)SVS, The University of Edinburgh, Edinburgh, United Kingdom
- Division of Genetics and Genomics, The Roslin Institute and R(D)SVS, The University of Edinburgh, Edinburgh, United Kingdom
| | - Rainer Roehe
- Scotland’s Rural College, Edinburgh, United Kingdom
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Bica R, Palarea-Albaladejo J, Kew W, Uhrin D, Pacheco D, Macrae A, Dewhurst RJ. Nuclear Magnetic Resonance to Detect Rumen Metabolites Associated with Enteric Methane Emissions from Beef Cattle. Sci Rep 2020; 10:5578. [PMID: 32221381 PMCID: PMC7101347 DOI: 10.1038/s41598-020-62485-y] [Citation(s) in RCA: 9] [Impact Index Per Article: 1.8] [Reference Citation Analysis] [Abstract] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 11/28/2019] [Accepted: 03/13/2020] [Indexed: 11/10/2022] Open
Abstract
This study presents the application of metabolomics to evaluate changes in the rumen metabolites of beef cattle fed with three different diet types: forage-rich, mixed and concentrate-rich. Rumen fluid samples were analysed by 1H-NMR spectroscopy and the resulting spectra were used to characterise and compare metabolomic profiles between diet types and assess the potential for NMR metabolite signals to be used as proxies of methane emissions (CH4 in g/kg DMI). The dataset available consisted of 128 measurements taken from 4 experiments with CH4 measurements taken in respiration chambers. Predictive modelling of CH4 was conducted by partial least squares (PLS) regression, fitting calibration models either using metabolite signals only as predictors or using metabolite signals as well as other diet and animal covariates (DMI, ME, weight, BW0.75, DMI/BW0.75). Cross-validated R2 were 0.57 and 0.70 for the two models respectively. The cattle offered the concentrate-rich diet showed increases in alanine, valerate, propionate, glucose, tyrosine, proline and isoleucine. Lower methane yield was associated with the concentrate-rich diet (p < 0.001). The results provided new insight into the relationship between rumen metabolites, CH4 production and diets, as well as showing that metabolites alone have an acceptable association with the variation in CH4 production from beef cattle.
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Affiliation(s)
- R Bica
- Scotland's Rural College, SRUC, West Mains Rd, Edinburgh, EH9 3JG, United Kingdom. .,Royal (Dick) School of Veterinary Studies and the Roslin Institute, University of Edinburgh, Easter Bush Campus, Midlothian, EH25 9RG, United Kingdom. .,AgResearch Grasslands Research Centre, Tennent Drive, 11 Dairy Farm Road, Palmerston North, 4442, New Zealand.
| | - J Palarea-Albaladejo
- Biomathematics and Statistics Scotland, JCMB, Peter Guthrie Tait Road, The King's Buildings, Edinburgh, EH9 3FD, United Kingdom
| | - W Kew
- The University of Edinburgh, EaStCHEM School of Chemistry, The King's Buildings, David Brewster Road, Edinburgh, EH9 3FJ, United Kingdom
| | - D Uhrin
- The University of Edinburgh, EaStCHEM School of Chemistry, The King's Buildings, David Brewster Road, Edinburgh, EH9 3FJ, United Kingdom
| | - D Pacheco
- AgResearch Grasslands Research Centre, Tennent Drive, 11 Dairy Farm Road, Palmerston North, 4442, New Zealand
| | - A Macrae
- Royal (Dick) School of Veterinary Studies and the Roslin Institute, University of Edinburgh, Easter Bush Campus, Midlothian, EH25 9RG, United Kingdom
| | - R J Dewhurst
- Scotland's Rural College, SRUC, West Mains Rd, Edinburgh, EH9 3JG, United Kingdom
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Ilina L, Filippova V, Yildirim E, Layshev K. Archaea in the microbial community of the reindeer rumen in the Russian Arctic. BIO WEB OF CONFERENCES 2020. [DOI: 10.1051/bioconf/20202700066] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 11/14/2022] Open
Abstract
Archaea is the least studied group of the reindeer rumen microbiocenosis. Although the functional load performed by this group of microorganisms in the rumen is large. Methane-forming archaea play a key role in the process of anaerobic decomposition of organic substances, the formation of methane. This study for the first time analyzed the composition of the archaeal part of the microbial community of the reindeer rumen using the T-RFLP method from various regions of the Russian Arctic. As a result, it was found that according to the estimates of the number of archaea by quantitative PCR in the reindeer rumen in the winter-spring period, on average, 108 genomes/g of archaea were observed in individuals of the Yamalo-Nenets Autonomous District, and 109 genomes/in animals from the Nenets Autonomous District Archean. Thus, in the winter-spring period, a lower number of archaea in the rumen was observed in the Yamalo-Nenets Autonomous District. According to the results of the T-RFLP method, 44 to 134 phylotypes were detected in the archaeal community of the reindeer rumen, the Shannon index was 2.02–3.80. The lowest content (up to 11.10 %) of methanogenic archaea of the Methanomicrobia class (including the families Methanosarcinaceae and Methanocorpusculaceae) was revealed in the Nenets Autonomous District, while their presence in individuals of the Yamalo-Nenets Autonomous District reached 36.33 %. Interestingly, in adults of the Yamalo-Nenets and Nenets Autonomous Districts, a significant decrease in the representation of methanogenic archaea of the Methanomicrobia class was noted by 1.38 (P <0.05) and 2.70 times (P <0.01), respectively, compared with young individuals (up to 2 years).
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Ramayo‐Caldas Y, Zingaretti L, Popova M, Estellé J, Bernard A, Pons N, Bellot P, Mach N, Rau A, Roume H, Perez‐Enciso M, Faverdin P, Edouard N, Ehrlich D, Morgavi DP, Renand G. Identification of rumen microbial biomarkers linked to methane emission in Holstein dairy cows. J Anim Breed Genet 2020; 137:49-59. [PMID: 31418488 PMCID: PMC6972549 DOI: 10.1111/jbg.12427] [Citation(s) in RCA: 50] [Impact Index Per Article: 10.0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 05/02/2019] [Revised: 07/12/2019] [Accepted: 07/13/2019] [Indexed: 12/29/2022]
Abstract
Mitigation of greenhouse gas emissions is relevant for reducing the environmental impact of ruminant production. In this study, the rumen microbiome from Holstein cows was characterized through a combination of 16S rRNA gene and shotgun metagenomic sequencing. Methane production (CH4 ) and dry matter intake (DMI) were individually measured over 4-6 weeks to calculate the CH4 yield (CH4 y = CH4 /DMI) per cow. We implemented a combination of clustering, multivariate and mixed model analyses to identify a set of operational taxonomic unit (OTU) jointly associated with CH4 y and the structure of ruminal microbial communities. Three ruminotype clusters (R1, R2 and R3) were identified, and R2 was associated with higher CH4 y. The taxonomic composition on R2 had lower abundance of Succinivibrionaceae and Methanosphaera, and higher abundance of Ruminococcaceae, Christensenellaceae and Lachnospiraceae. Metagenomic data confirmed the lower abundance of Succinivibrionaceae and Methanosphaera in R2 and identified genera (Fibrobacter and unclassified Bacteroidales) not highlighted by metataxonomic analysis. In addition, the functional metagenomic analysis revealed that samples classified in cluster R2 were overrepresented by genes coding for KEGG modules associated with methanogenesis, including a significant relative abundance of the methyl-coenzyme M reductase enzyme. Based on the cluster assignment, we applied a sparse partial least-squares discriminant analysis at the taxonomic and functional levels. In addition, we implemented a sPLS regression model using the phenotypic variation of CH4 y. By combining these two approaches, we identified 86 discriminant bacterial OTUs, notably including families linked to CH4 emission such as Succinivibrionaceae, Ruminococcaceae, Christensenellaceae, Lachnospiraceae and Rikenellaceae. These selected OTUs explained 24% of the CH4 y phenotypic variance, whereas the host genome contribution was ~14%. In summary, we identified rumen microbial biomarkers associated with the methane production of dairy cows; these biomarkers could be used for targeted methane-reduction selection programmes in the dairy cattle industry provided they are heritable.
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Affiliation(s)
- Yuliaxis Ramayo‐Caldas
- UMR 1313 GABIINRA, AgroParisTech, Université Paris‐SaclayJouy‐en‐JosasFrance
- Animal Breeding and Genetics ProgramIRTA Torre MarimonCaldes de MontbuiSpain
| | | | - Milka Popova
- VetAgro Sup, UMR 1213 HerbivoresINRA, Université Clermont AuvergneSaint‐Genès‐ChampanelleFrance
| | - Jordi Estellé
- UMR 1313 GABIINRA, AgroParisTech, Université Paris‐SaclayJouy‐en‐JosasFrance
| | - Aurelien Bernard
- VetAgro Sup, UMR 1213 HerbivoresINRA, Université Clermont AuvergneSaint‐Genès‐ChampanelleFrance
| | | | - Pau Bellot
- Department of Animal Genetics, CRAGUABBellaterraSpain
| | - Núria Mach
- UMR 1313 GABIINRA, AgroParisTech, Université Paris‐SaclayJouy‐en‐JosasFrance
| | - Andrea Rau
- UMR 1313 GABIINRA, AgroParisTech, Université Paris‐SaclayJouy‐en‐JosasFrance
| | - Hugo Roume
- INRA METAGENOPOLIS UnitJouy‐en‐JosasFrance
| | | | | | | | | | - Diego P. Morgavi
- VetAgro Sup, UMR 1213 HerbivoresINRA, Université Clermont AuvergneSaint‐Genès‐ChampanelleFrance
| | - Gilles Renand
- UMR 1313 GABIINRA, AgroParisTech, Université Paris‐SaclayJouy‐en‐JosasFrance
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Snelling TJ, Auffret MD, Duthie CA, Stewart RD, Watson M, Dewhurst RJ, Roehe R, Walker AW. Temporal stability of the rumen microbiota in beef cattle, and response to diet and supplements. Anim Microbiome 2019; 1:16. [PMID: 33499961 PMCID: PMC7807515 DOI: 10.1186/s42523-019-0018-y] [Citation(s) in RCA: 26] [Impact Index Per Article: 4.3] [Reference Citation Analysis] [Abstract] [Key Words] [Grants] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 07/15/2019] [Accepted: 10/28/2019] [Indexed: 12/31/2022] Open
Abstract
BACKGROUND Dietary intake is known to be a driver of microbial community dynamics in ruminants. Beef cattle go through a finishing phase that typically includes very high concentrate ratios in their feed, with consequent effects on rumen metabolism including methane production. This longitudinal study was designed to measure dynamics of the rumen microbial community in response to the introduction of high concentrate diets fed to beef cattle during the finishing period. A cohort of 50 beef steers were fed either of two basal diet formulations consisting of approximately 10:90 or 50:50 forage:concentrate ratios respectively. Nitrate and oil rich supplements were also added either individually or in combination. Digesta samples were taken at time points over ~ 200 days during the finishing period of the cattle to measure the adaptation to the basal diet and long-term stability of the rumen microbiota. RESULTS 16S rRNA gene amplicon libraries were prepared from 313 rumen digesta samples and analysed at a depth of 20,000 sequences per library. Bray Curtis dissimilarity with analysis of molecular variance (AMOVA) revealed highly significant (p < 0.001) differences in microbiota composition between cattle fed different basal diets, largely driven by reduction of fibre degrading microbial groups and increased relative abundance of an unclassified Gammaproteobacteria OTU in the high concentrate fed animals. Conversely, the forage-based diet was significantly associated with methanogenic archaea. Within basal diet groups, addition of the nitrate and combined supplements had lesser, although still significant, impacts on microbiota dissimilarity compared to pre-treatment time points and controls. Measurements of the response and stability of the microbial community over the time course of the experiment showed continuing adaptation up to 25 days in the high concentrate groups. After this time point, however, no significant variability was detected. CONCLUSIONS High concentrate diets that are typically fed to finishing beef cattle can have a significant effect on the microbial community in the rumen. Inferred metabolic activity of the different microbial communities associated with each of the respective basal diets explained differences in methane and short chain fatty acid production between cattle. Longitudinal sampling revealed that once adapted to a change in diet, the rumen microbial community remains in a relatively stable alternate state.
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Affiliation(s)
| | | | | | - Robert D. Stewart
- The Roslin Institute and R(D)SVS, University of Edinburgh, Edinburgh, EH25 9RG UK
| | - Mick Watson
- The Roslin Institute and R(D)SVS, University of Edinburgh, Edinburgh, EH25 9RG UK
| | | | | | - Alan W. Walker
- Rowett Institute, University of Aberdeen, Aberdeen, AB25 2ZD UK
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Creighbaum AJ, Ticak T, Shinde S, Wang X, Ferguson DJ. Examination of the Glycine Betaine-Dependent Methylotrophic Methanogenesis Pathway: Insights Into Anaerobic Quaternary Amine Methylotrophy. Front Microbiol 2019; 10:2572. [PMID: 31787957 PMCID: PMC6855144 DOI: 10.3389/fmicb.2019.02572] [Citation(s) in RCA: 10] [Impact Index Per Article: 1.7] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 08/09/2019] [Accepted: 10/23/2019] [Indexed: 01/23/2023] Open
Abstract
Recent studies indicate that environmentally abundant quaternary amines (QAs) are a primary source for methanogenesis, yet the catabolic enzymes are unknown. We hypothesized that the methanogenic archaeon Methanolobus vulcani B1d metabolizes glycine betaine (GB) through a corrinoid-dependent GB:coenzyme M (CoM) methyl transfer pathway. The draft genome sequence of M. vulcani B1d revealed a gene encoding a predicted non-pyrrolysine MttB homolog (MV8460) with high sequence similarity to the GB methyltransferase encoded by Desulfitobacterium hafniense Y51. MV8460 catalyzes GB-dependent methylation of free cob(I)alamin indicating it is an authentic MtgB enzyme. Proteomic analysis revealed that MV8460 and a corrinoid binding protein (MV8465) were highly abundant when M. vulcani B1d was grown on GB relative to growth on trimethylamine. The abundance of a corrinoid reductive activation enzyme (MV10335) and a methylcorrinoid:CoM methyltransferase (MV10360) were significantly higher in GB-grown B1d lysates compared to other homologs. The GB:CoM pathway was fully reconstituted in vitro using recombinant MV8460, MV8465, MV10335, and MV10360. Demonstration of the complete GB:CoM pathway expands the knowledge of direct QA-dependent methylotrophy and establishes a model to identify additional ecologically relevant anaerobic quaternary amine pathways.
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Affiliation(s)
- Adam J Creighbaum
- Department of Microbiology, Miami University, Oxford, OH, United States
| | - Tomislav Ticak
- Department of Biological Sciences, University of Idaho, Moscow, ID, United States
| | - Shrameeta Shinde
- Department of Microbiology, Miami University, Oxford, OH, United States
| | - Xin Wang
- Department of Microbiology, Miami University, Oxford, OH, United States
| | - Donald J Ferguson
- Department of Microbiology, Miami University, Oxford, OH, United States.,Department of Biological Sciences, Miami University Regionals, Hamilton, OH, United States
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Terry SA, Ribeiro GO, Gruninger RJ, Chaves AV, Beauchemin KA, Okine E, McAllister TA. A Pine Enhanced Biochar Does Not Decrease Enteric CH 4 Emissions, but Alters the Rumen Microbiota. Front Vet Sci 2019; 6:308. [PMID: 31608292 PMCID: PMC6757094 DOI: 10.3389/fvets.2019.00308] [Citation(s) in RCA: 21] [Impact Index Per Article: 3.5] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 06/22/2019] [Accepted: 08/29/2019] [Indexed: 01/17/2023] Open
Abstract
The objective of this study was to examine the effect of a pine enhanced biochar (EB) on rumen fermentation, apparent total tract digestibility, methane (CH4) emissions, and the rumen and fecal microbiome of Angus × Hereford heifers fed a barley silage-based diet. The experiment was a replicated 4 × 4 Latin square using 8 ruminally cannulated heifers (565 ± 35 kg initial BW). The basal diet contained 60% barley silage, 35% barley grain and 5% mineral supplement with EB added at 0% (control), 0.5, 1.0, or 2.0% (DM basis). Each period lasted 28 days, consisting of 14 days adaptation and 14 days of measurements. Samples for profiling of the microbiome in rumen liquid, solids and feces were collected on d 15 before feeding. Rumen samples for fermentation characterization were taken at 0, 3, 6, and 12 h post feeding. Total collection of urine and feces was conducted from days 18 to 22. Heifers were housed in open-circuit respiratory chambers on days 26-28 to estimate CH4 emissions. Ruminal pH was recorded at 1-min intervals during CH4 measurements using indwelling pH loggers. Data were analyzed with the fixed effects of dietary treatment and random effects of square, heifer within square and period. Dry matter intake was similar across treatments (P = 0.21). Ammonia N concentration and protozoa counts responded quadratically (P = 0.01) to EB in which both were decreased by EB included at 0.5 and 1.0%, compared to the control and 2.0% EB. Minimum pH was increased (P = 0.04), and variation of pH was decreased (P = 0.03) by 2.0% EB. Total tract digestibility, N balance and CH4 production were not affected (P ≥ 0.17) by EB. Enhanced biochar decreased the relative abundance of Fibrobacter (P = 0.05) and Tenericutes (P = 0.01), and increased the relative abundance of Spirochaetaes (P = 0.01), Verrucomicrobia (P = 0.02), and Elusimicrobia (P = 0.02). Results suggest that at the examined concentrations, EB was ineffective at decreasing enteric CH4 emissions, but did alter specific rumen microbiota.
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Affiliation(s)
- Stephanie A. Terry
- Lethbridge Research and Development Centre, Agriculture and Agri-Food Canada, Lethbridge, AB, Canada
- School of Life and Environmental Sciences, The University of Sydney, Sydney, NSW, Australia
| | - Gabriel O. Ribeiro
- Department of Production Animal Health, University of Calgary, Calgary, AB, Canada
| | - Robert J. Gruninger
- Lethbridge Research and Development Centre, Agriculture and Agri-Food Canada, Lethbridge, AB, Canada
| | - Alex V. Chaves
- School of Life and Environmental Sciences, The University of Sydney, Sydney, NSW, Australia
| | - Karen A. Beauchemin
- Lethbridge Research and Development Centre, Agriculture and Agri-Food Canada, Lethbridge, AB, Canada
| | - Erasmus Okine
- Department of Biological Sciences, University of Lethbridge, Lethbridge, AB, Canada
| | - Tim A. McAllister
- Lethbridge Research and Development Centre, Agriculture and Agri-Food Canada, Lethbridge, AB, Canada
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Stewart RD, Auffret MD, Warr A, Walker AW, Roehe R, Watson M. Compendium of 4,941 rumen metagenome-assembled genomes for rumen microbiome biology and enzyme discovery. Nat Biotechnol 2019; 37:953-961. [PMID: 31375809 PMCID: PMC6785717 DOI: 10.1038/s41587-019-0202-3] [Citation(s) in RCA: 317] [Impact Index Per Article: 52.8] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 11/19/2018] [Accepted: 06/27/2019] [Indexed: 12/13/2022]
Abstract
Ruminants provide essential nutrition for billions of people worldwide. The rumen is a specialized stomach that is adapted to the breakdown of plant-derived complex polysaccharides. The genomes of the rumen microbiota encode thousands of enzymes adapted to digestion of the plant matter that dominates the ruminant diet. We assembled 4,941 rumen microbial metagenome-assembled genomes (MAGs) using approximately 6.5 terabases of short- and long-read sequence data from 283 ruminant cattle. We present a genome-resolved metagenomics workflow that enabled assembly of bacterial and archaeal genomes that were at least 80% complete. Of note, we obtained three single-contig, whole-chromosome assemblies of rumen bacteria, two of which represent previously unknown rumen species, assembled from long-read data. Using our rumen genome collection we predicted and annotated a large set of rumen proteins. Our set of rumen MAGs increases the rate of mapping of rumen metagenomic sequencing reads from 15% to 50-70%. These genomic and protein resources will enable a better understanding of the structure and functions of the rumen microbiota.
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Affiliation(s)
- Robert D Stewart
- The Roslin Institute and the Royal (Dick) School of Veterinary Studies, University of Edinburgh, Easter Bush, UK
| | | | - Amanda Warr
- The Roslin Institute and the Royal (Dick) School of Veterinary Studies, University of Edinburgh, Easter Bush, UK
| | - Alan W Walker
- The Rowett Institute, University of Aberdeen, Aberdeen, UK
| | | | - Mick Watson
- The Roslin Institute and the Royal (Dick) School of Veterinary Studies, University of Edinburgh, Easter Bush, UK.
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Maggiolino A, Lorenzo J, Quiñones J, Latorre M, Blando F, Centoducati G, Dahl G, De Palo P. Effects of dietary supplementation with Pinus taeda hydrolyzed lignin on in vivo performances, in vitro nutrient apparent digestibility, and gas emission in beef steers. Anim Feed Sci Technol 2019. [DOI: 10.1016/j.anifeedsci.2019.114217] [Citation(s) in RCA: 9] [Impact Index Per Article: 1.5] [Reference Citation Analysis] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 01/15/2023]
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