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Zhang J, Jiang Q, Du Z, Geng Y, Hu Y, Tong Q, Song Y, Zhang HY, Yan X, Feng Z. Knowledge graph-derived feed efficiency analysis via pig gut microbiota. Sci Rep 2024; 14:13939. [PMID: 38886444 PMCID: PMC11182767 DOI: 10.1038/s41598-024-64835-6] [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: 12/29/2023] [Accepted: 06/13/2024] [Indexed: 06/20/2024] Open
Abstract
Feed efficiency (FE) is essential for pig production, has been reported to be partially explained by gut microbiota. Despite an extensive body of research literature to this topic, studies regarding the regulation of feed efficiency by gut microbiota remain fragmented and mostly confined to disorganized or semi-structured unrestricted texts. Meanwhile, structured databases for microbiota analysis are available, yet they often lack a comprehensive understanding of the associated biological processes. Therefore, we have devised an approach to construct a comprehensive knowledge graph by combining unstructured textual intelligence with structured database information and applied it to investigate the relationship between pig gut microbes and FE. Firstly, we created the pgmReading knowledge base and the domain ontology of pig gut microbiota by annotating, extracting, and integrating semantic information from 157 scientific publications. Secondly, we created the pgmPubtator by utilizing PubTator to expand the semantic information related to microbiota. Thirdly, we created the pgmDatabase by mapping and combining the ADDAGMA, gutMGene, and KEGG databases based on the ontology. These three knowledge bases were integrated to form the Pig Gut Microbial Knowledge Graph (PGMKG). Additionally, we created five biological query cases to validate the performance of PGMKG. These cases not only allow us to identify microbes with the most significant impact on FE but also provide insights into the metabolites produced by these microbes and the associated metabolic pathways. This study introduces PGMKG, mapping key microbes in pig feed efficiency and guiding microbiota-targeted optimization.
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Affiliation(s)
- Junmei Zhang
- National Key Laboratory of Agricultural Microbiology, College of Informatics, College of Animal Sciences and Technology, College of Veterinary Medicine, Huazhong Agricultural University, Wuhan, 430070, China
| | - Qin Jiang
- National Key Laboratory of Agricultural Microbiology, College of Informatics, College of Animal Sciences and Technology, College of Veterinary Medicine, Huazhong Agricultural University, Wuhan, 430070, China
- Yazhouwan National Laboratory (YNL), Sanya, 572025, China
| | - Zhihong Du
- National Key Laboratory of Agricultural Microbiology, College of Informatics, College of Animal Sciences and Technology, College of Veterinary Medicine, Huazhong Agricultural University, Wuhan, 430070, China
| | - Yilin Geng
- National Key Laboratory of Agricultural Microbiology, College of Informatics, College of Animal Sciences and Technology, College of Veterinary Medicine, Huazhong Agricultural University, Wuhan, 430070, China
| | - Yuren Hu
- National Key Laboratory of Agricultural Microbiology, College of Informatics, College of Animal Sciences and Technology, College of Veterinary Medicine, Huazhong Agricultural University, Wuhan, 430070, China
| | - Qichang Tong
- National Key Laboratory of Agricultural Microbiology, College of Informatics, College of Animal Sciences and Technology, College of Veterinary Medicine, Huazhong Agricultural University, Wuhan, 430070, China
| | - Yunfeng Song
- National Key Laboratory of Agricultural Microbiology, College of Informatics, College of Animal Sciences and Technology, College of Veterinary Medicine, Huazhong Agricultural University, Wuhan, 430070, China
| | - Hong-Yu Zhang
- National Key Laboratory of Agricultural Microbiology, College of Informatics, College of Animal Sciences and Technology, College of Veterinary Medicine, Huazhong Agricultural University, Wuhan, 430070, China
| | - Xianghua Yan
- National Key Laboratory of Agricultural Microbiology, College of Informatics, College of Animal Sciences and Technology, College of Veterinary Medicine, Huazhong Agricultural University, Wuhan, 430070, China
| | - Zaiwen Feng
- National Key Laboratory of Agricultural Microbiology, College of Informatics, College of Animal Sciences and Technology, College of Veterinary Medicine, Huazhong Agricultural University, Wuhan, 430070, China.
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Lu C, Zhang Y, Qin Y, Zhou J, Wang Y, Su X, Han J. Tuna Dark Muscle Feeding Improved the Meat Quality of Holland Mini-Piglets and Modulated the Gut Microbiota. Foods 2024; 13:1577. [PMID: 38790877 PMCID: PMC11121099 DOI: 10.3390/foods13101577] [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: 04/18/2024] [Revised: 05/13/2024] [Accepted: 05/14/2024] [Indexed: 05/26/2024] Open
Abstract
Pork is one of the most widely produced and consumed meats in the world, and it is also an important source of animal protein. The continuous rise in feed prices has forced the pig industry to consider adding cost-effective alternative feed to pig diets. In this study, we aimed to explore the beneficial effects of tuna dark muscle as a nutritional supplement on the growth performance, serum lipids and antioxidant levels of Holland mini-piglets, as well as on the odor and volatile substances of pork and the gut microbiota. Two-month-old male mini-piglets (n = 24) were fed a control diet or supplemented with either 2% (LD) or 4% (HD) tuna dark muscle for 8 weeks. The use of tuna dark muscle at low and high dosages significantly increased the average daily weight gain, but it showed no significant effect on organ indices or blood lipids. In addition, dark muscle treatment significantly increased the antioxidant capacity, characterized by increased SOD and GSH-Px activities, and it decreased the content of MDA in serum. Moreover, tuna dark muscle feeding shifted the odor of rib muscle and tendon meat away from that of the control group, while similar odor patterns were observed in the longissimus dorsi muscle. Among these volatile substances, hexanal, nonanal, and heptanal increased in response to dietary tuna dark muscle and were regarded as indispensable contributors to the feeding. Furthermore, dietary tuna dark muscle modulated the gut microbiota of the piglets, increasing the abundance of beneficial bacteria such as butyric acid-producing bacteria, and reduced the abundance of harmful bacteria. The feeding strategy reported in this study not only reduces the production costs of pork but also utilizes tuna processing by-products in an environmentally friendly way.
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Affiliation(s)
- Chenyang Lu
- School of Food Science and Biotechnology, Zhejiang Gongshang University, 18 Xuezheng Road, Hangzhou 310018, China
- School of Marine Science, Ningbo University, 169 Qixing South Road, Ningbo 315832, China
| | - Yuanming Zhang
- School of Marine Science, Ningbo University, 169 Qixing South Road, Ningbo 315832, China
| | - Yang Qin
- School of Marine Science, Ningbo University, 169 Qixing South Road, Ningbo 315832, China
| | - Jun Zhou
- School of Marine Science, Ningbo University, 169 Qixing South Road, Ningbo 315832, China
| | - Yanbo Wang
- School of Food Science and Biotechnology, Zhejiang Gongshang University, 18 Xuezheng Road, Hangzhou 310018, China
| | - Xiurong Su
- School of Marine Science, Ningbo University, 169 Qixing South Road, Ningbo 315832, China
| | - Jiaojiao Han
- School of Marine Science, Ningbo University, 169 Qixing South Road, Ningbo 315832, China
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