Skip navigation

DSpace

機構典藏 DSpace 系統致力於保存各式數位資料(如:文字、圖片、PDF)並使其易於取用。

點此認識 DSpace
DSpace logo
English
中文
  • 瀏覽論文
    • 校院系所
    • 出版年
    • 作者
    • 標題
    • 關鍵字
    • 指導教授
  • 搜尋 TDR
  • 授權 Q&A
    • 我的頁面
    • 接受 E-mail 通知
    • 編輯個人資料
  1. NTU Theses and Dissertations Repository
  2. 醫學院
  3. 國際三校農業生技與健康醫療碩士學位學程
請用此 Handle URI 來引用此文件: http://tdr.lib.ntu.edu.tw/jspui/handle/123456789/99364
完整後設資料紀錄
DC 欄位值語言
dc.contributor.advisor丁詩同zh_TW
dc.contributor.advisorShih-Torng Dingen
dc.contributor.author邱于珍zh_TW
dc.contributor.authorYu-Chen Chiuen
dc.date.accessioned2025-09-09T16:09:57Z-
dc.date.available2025-09-10-
dc.date.copyright2025-09-09-
dc.date.issued2025-
dc.date.submitted2025-08-04-
dc.identifier.citation1. Szoke, Z., Fauszt, P., Mikolas, M., David, P., Szilagyi-Tolnai, E., Pesti-Asboth, G., Homoki, J.R., Kovacs-Forgacs, I., Gal, F., Stundl, L., et al. (2025). Comprehensive analysis of antimicrobial resistance dynamics among broiler and duck intensive production systems. Sci Rep 15, 4673. 10.1038/s41598-025-89432-z.
2. World Health Organization (2023). Antimicrobial resistance. https://www.who.int/news-room/fact-sheets/detail/antimicrobial-resistance.
3. Salam, M.A., Al-Amin, M.Y., Salam, M.T., Pawar, J.S., Akhter, N., Rabaan, A.A., and Alqumber, M.A.A. (2023). Antimicrobial Resistance: A Growing Serious Threat for Global Public Health. Healthcare (Basel) 11. 10.3390/healthcare11131946.
4. World Health Organization (2024). One Health priority research agenda for antimicrobial resistance in the WHO European Region. WHO/EURO:2024-9510-49282-73655.
5. Zhang, T., Nickerson, R., Zhang, W., Peng, X., Shang, Y., Zhou, Y., Luo, Q., Wen, G., and Cheng, Z. (2024). The impacts of animal agriculture on One Health-Bacterial zoonosis, antimicrobial resistance, and beyond. One Health 18, 100748. 10.1016/j.onehlt.2024.100748.
6. Larsson, D.G.J., and Flach, C.F. (2022). Antibiotic resistance in the environment. Nat Rev Microbiol 20, 257-269. 10.1038/s41579-021-00649-x.
7. Andersson, D.I., Balaban, N.Q., Baquero, F., Courvalin, P., Glaser, P., Gophna, U., Kishony, R., Molin, S., and Tønjum, T. (2020). Antibiotic resistance: turning evolutionary principles into clinical reality. FEMS Microbiol Rev 44, 171-188. 10.1093/femsre/fuaa001.
8. Castañeda-Barba, S., Top, E.M., and Stalder, T. (2024). Plasmids, a molecular cornerstone of antimicrobial resistance in the One Health era. Nat Rev Microbiol 22, 18-32. 10.1038/s41579-023-00926-x.
9. Kuo, S.C., Huang, W.C., Wang, H.Y., Shiau, Y.R., Cheng, M.F., and Lauderdale, T.L. (2016). Colistin resistance gene mcr-1 in Escherichia coli isolates from humans and retail meats, Taiwan. J Antimicrob Chemother 71, 2327-2329. 10.1093/jac/dkw122.
10. Kuo, S.-C., and Lauderdale, T.-L. (2017). Plasmid-Mediated Colistin Resistance. Infection Control Journal 27, 29-33. 10.6526/ICJ.2017.104.
11. Rhouma, M., Madec, J.Y., and Laxminarayan, R. (2023). Colistin: from the shadows to a One Health approach for addressing antimicrobial resistance. Int J Antimicrob Agents 61, 106713. 10.1016/j.ijantimicag.2023.106713.
12. Oyenuga, N., Cobo-Díaz, J.F., Alvarez-Ordóñez, A., and Alexa, E.A. (2024). Overview of Antimicrobial Resistant ESKAPEE Pathogens in Food Sources and Their Implications from a One Health Perspective. Microorganisms 12. 10.3390/microorganisms12102084.
13. Xu, C., Kong, L., Gao, H., Cheng, X., and Wang, X. (2022). A Review of Current Bacterial Resistance to Antibiotics in Food Animals. Front Microbiol 13, 822689. 10.3389/fmicb.2022.822689.
14. World Health Organization, Food and Agriculture Organization of the United Nations, United Nations Environment Programme, and World Organisation for Animal Health (2023). A one health priority research agenda for antimicrobial resistance. CC BY-NC-SA 3.0 IGO.
15. Ritchie, H., and Spooner, F. (2024). Large amounts of antibiotics are used in livestock, but several countries have shown this doesn’t have to be the case. https://ourworldindata.org/antibiotics-livestock.
16. Van Boeckel, T.P., Brower, C., Gilbert, M., Grenfell, B.T., Levin, S.A., Robinson, T.P., Teillant, A., and Laxminarayan, R. (2015). Global trends in antimicrobial use in food animals. Proc Natl Acad Sci U S A 112, 5649-5654. 10.1073/pnas.1503141112.
17. Tang, K.L., Caffrey, N.P., Nóbrega, D.B., Cork, S.C., Ronksley, P.E., Barkema, H.W., Polachek, A.J., Ganshorn, H., Sharma, N., Kellner, J.D., and Ghali, W.A. (2017). Restricting the use of antibiotics in food-producing animals and its associations with antibiotic resistance in food-producing animals and human beings: a systematic review and meta-analysis. Lancet Planet Health 1, e316-e327. 10.1016/s2542-5196(17)30141-9.
18. Van Boeckel, T.P., Glennon, E.E., Chen, D., Gilbert, M., Robinson, T.P., Grenfell, B.T., Levin, S.A., Bonhoeffer, S., and Laxminarayan, R. (2017). Reducing antimicrobial use in food animals. Science 357, 1350-1352. 10.1126/science.aao1495.
19. Birgand, G., Castro-Sánchez, E., Hansen, S., Gastmeier, P., Lucet, J.C., Ferlie, E., Holmes, A., and Ahmad, R. (2018). Comparison of governance approaches for the control of antimicrobial resistance: Analysis of three European countries. Antimicrob Resist Infect Control 7, 28. 10.1186/s13756-018-0321-5.
20. Bengtsson-Palme, J., Abramova, A., Berendonk, T.U., Coelho, L.P., Forslund, S.K., Gschwind, R., Heikinheimo, A., Jarquín-Díaz, V.H., Khan, A.A., Klümper, U., et al. (2023). Towards monitoring of antimicrobial resistance in the environment: For what reasons, how to implement it, and what are the data needs? Environ Int 178, 108089. 10.1016/j.envint.2023.108089.
21. EU-JAMRAI. Surveillance. https://eu-jamrai.eu/surveillance/#.
22. Hendriksen, R.S., Munk, P., Njage, P., van Bunnik, B., McNally, L., Lukjancenko, O., Röder, T., Nieuwenhuijse, D., Pedersen, S.K., Kjeldgaard, J., et al. (2019). Global monitoring of antimicrobial resistance based on metagenomics analyses of urban sewage. Nat Commun 10, 1124. 10.1038/s41467-019-08853-3.
23. Berglund, F., Österlund, T., Boulund, F., Marathe, N.P., Larsson, D.G.J., and Kristiansson, E. (2019). Identification and reconstruction of novel antibiotic resistance genes from metagenomes. Microbiome 7, 52. 10.1186/s40168-019-0670-1.
24. Liu, Z., Klümper, U., Liu, Y., Yang, Y., Wei, Q., Lin, J.G., Gu, J.D., and Li, M. (2019). Metagenomic and metatranscriptomic analyses reveal activity and hosts of antibiotic resistance genes in activated sludge. Environ Int 129, 208-220. 10.1016/j.envint.2019.05.036.
25. Gschwind, R., Ugarcina Perovic, S., Weiss, M., Petitjean, M., Lao, J., Coelho, L.P., and Ruppé, E. (2023). ResFinderFG v2.0: a database of antibiotic resistance genes obtained by functional metagenomics. Nucleic Acids Res 51, W493-w500. 10.1093/nar/gkad384.
26. Corona, F., and Martinez, J.L. (2013). Phenotypic Resistance to Antibiotics. Antibiotics (Basel) 2, 237-255. 10.3390/antibiotics2020237.
27. Manaia, C.M. (2017). Assessing the Risk of Antibiotic Resistance Transmission from the Environment to Humans: Non-Direct Proportionality between Abundance and Risk. Trends Microbiol 25, 173-181. 10.1016/j.tim.2016.11.014.
28. Kahlmeter, G., and Turnidge, J. (2022). How to: ECOFFs-the why, the how, and the don'ts of EUCAST epidemiological cutoff values. Clin Microbiol Infect 28, 952-954. 10.1016/j.cmi.2022.02.024.
29. Mulchandani, R., Wang, Y., Gilbert, M., and Van Boeckel, T.P. (2023). Global trends in antimicrobial use in food-producing animals: 2020 to 2030. PLOS Glob Public Health 3, e0001305. 10.1371/journal.pgph.0001305.
30. Van Boeckel, T.P., Pires, J., Silvester, R., Zhao, C., Song, J., Criscuolo, N.G., Gilbert, M., Bonhoeffer, S., and Laxminarayan, R. (2019). Global trends in antimicrobial resistance in animals in low- and middle-income countries. Science 365. 10.1126/science.aaw1944.
31. Kasimanickam, V., Kasimanickam, M., and Kasimanickam, R. (2021). Antibiotics Use in Food Animal Production: Escalation of Antimicrobial Resistance: Where Are We Now in Combating AMR? Med Sci (Basel) 9. 10.3390/medsci9010014.
32. Simjee, S., and Ippolito, G. (2022). European regulations on prevention use of antimicrobials from january 2022. Braz J Vet Med 44, e000822. 10.29374/2527-2179.bjvm000822.
33. Ministry of Agriculture, Forestry and Fisheries, Japan (2025). 飼料及び飼料添加物の成分規格等に関する省令.
34. Ministry of Agriculture, Taiwan (2025). 動物用藥品使用準則.
35. Food and Agricultural Materials Inspection Center, Japan (2024). List of Feed Additives. http://www.famic.go.jp/ffis/feed/sub3_feedadditives_en.html.
36. The European Parliament and the Council of the European Union (2022). Regulation (EU) 2019/6 of the European Parliament and of the Council on veterinary medicinal products and repealing Directive 2001/82/EC.
37. Castanon, J.I. (2007). History of the use of antibiotic as growth promoters in European poultry feeds. Poult Sci 86, 2466-2471. 10.3382/ps.2007-00249.
38. The European Commission (2022). Commission Implementing Regulation (EU) 2022/1255 of 19 July 2022 designating antimicrobials or groups of antimicrobials reserved for treatment of certain infections in humans, in accordance with Regulation (EU) 2019/6 of the European Parliament and of the Council.
39. Ministry of Agriculture, Forestry and Fisheries, Japan (2014). 農林水産省令第7号.
40. Ministry of Agriculture, Forestry and Fisheries, Japan (2017). 農林水産省令第71号.
41. Ministry of Agriculture, Forestry and Fisheries, Japan (2018). 農林水産省令第83号.
42. Ministry of Agriculture, Forestry and Fisheries, Japan (2019). 農林水産省令第38号.
43. Ministry of Agriculture, Forestry and Fisheries, Japan (2019). 農林水産省令第37号.
44. Ministry of Agriculture, Taiwan (2014). 農防字第1031472328號.
45. Ministry of Agriculture, Taiwan (2015). 農防字第1041473480號.
46. Ministry of Agriculture, Taiwan (2016). 農防字第1051472565號.
47. Ministry of Agriculture, Taiwan (2022). 農防字第1111470620號.
48. Ministry of Agriculture, Taiwan (2023). 農防字第1121470886號.
49. Agency for Food, Environmental and Occupational Health & Safety, France (2025). Index des Médicaments vétérinaires autorisés en France. https://www.ircp.anmv.anses.fr.
50. National Veterinary Assay Laboratory, Japan (2025). 動物用医薬品等データベース. https://www.vm.nval.go.jp.
51. Animal and Plant Health Inspection Agency, Taiwan (2025). 動物用藥品許可證查詢. https://amdrug2.aphia.gov.tw/license-query.
52. Global Antibiotic Research & Development Partnership (2025). AntibioticDB. https://antibioticdb.com.
53. Agency for Food, Environmental and Occupational Health & Safety, France (2023). Sales of Veterinary Medicinal Products Containing Antimicrobials in France in 2022.
54. Hosoi, Y., Matsuda, M., Kawanishi, M., Harada, S., Kumakawa, M., Sekiguchi, H., Asai, T., and Sekiya, T. (2024). Antimicrobial Use in the Animal Sector in Japan from 2011 to 2022. Antibiotics (Basel) 13. 10.3390/antibiotics13121204.
55. Ministry of Agriculture and Food, France (2024). Écoantibio 3 : réduire les risques d’antibiorésistance et promouvoir le bon usage des antimicrobiens en médecine vétérinaire (plan national 2023-2028). https://agriculture.gouv.fr/le-plan-ecoantibio-3-2023-2028.
56. Zhao, C., Wang, Y., Mulchandani, R., and Van Boeckel, T.P. (2024). Global surveillance of antimicrobial resistance in food animals using priority drugs maps. Nat Commun 15, 763. 10.1038/s41467-024-45111-7.
57. Emes, D., Naylor, N., Waage, J., and Knight, G. (2022). Quantifying the Relationship between Antibiotic Use in Food-Producing Animals and Antibiotic Resistance in Humans. Antibiotics (Basel) 11. 10.3390/antibiotics11010066.
58. Durazzi, F., Pezzani, M.D., Arieti, F., Simonetti, O., Canziani, L.M., Carrara, E., Barbato, L., Onorati, F., Remondini, D., and Tacconelli, E. (2023). Modelling antimicrobial resistance transmission to guide personalized antimicrobial stewardship interventions and infection control policies in healthcare setting: a pilot study. Sci Rep 13, 15803. 10.1038/s41598-023-42511-5.
59. Statistics and Forecasting Department of the Ministry of Agriculture and Food, France (2023). Statistical Book 2022.
60. Japan, P.S.o.O.S.o. (2024). 畜産統計調査.
61. Ministry of Agriculture, Taiwan. (2022). 畜牧類農情統計調查結果(含產值)(110年).
62. Central Intelligence Agency, U.S. (2025). The World Factbook. https://www.cia.gov/the-world-factbook/.
63. Munk, P., Brinch, C., Møller, F.D., Petersen, T.N., Hendriksen, R.S., Seyfarth, A.M., Kjeldgaard, J.S., Svendsen, C.A., van Bunnik, B., Berglund, F., et al. (2022). Genomic analysis of sewage from 101 countries reveals global landscape of antimicrobial resistance. Nat Commun 13, 7251. 10.1038/s41467-022-34312-7.
64. Martiny, H.M., Pyrounakis, N., Petersen, T.N., Lukjančenko, O., Aarestrup, F.M., Clausen, P., and Munk, P. (2024). ARGprofiler-a pipeline for large-scale analysis of antimicrobial resistance genes and their flanking regions in metagenomic datasets. Bioinformatics 40. 10.1093/bioinformatics/btae086.
65. Martiny, H.-M., Pyrounakis, N., Lukjančenko, O., Petersen, T.N., Aarestrup, F.M., Clausen, P.T.L.C., and Munk, P. (2024). PanRes - Collection of antimicrobial resistance genes. 10.5281/zenodo.8055115.
66. Ruscheweyh, H.J., Milanese, A., Paoli, L., Karcher, N., Clayssen, Q., Keller, M.I., Wirbel, J., Bork, P., Mende, D.R., Zeller, G., and Sunagawa, S. (2022). Cultivation-independent genomes greatly expand taxonomic-profiling capabilities of mOTUs across various environments. Microbiome 10, 212. 10.1186/s40168-022-01410-z.
67. Robinson, M.D., McCarthy, D.J., and Smyth, G.K. (2010). edgeR: a Bioconductor package for differential expression analysis of digital gene expression data. Bioinformatics 26, 139-140. 10.1093/bioinformatics/btp616.
68. van Lingen, H.J., Suarez-Diez, M., and Saccenti, E. (2024). Normalization of gene counts affects principal components-based exploratory analysis of RNA-sequencing data. Biochim Biophys Acta Gene Regul Mech 1867, 195058. 10.1016/j.bbagrm.2024.195058.
69. Pérez-Cobas, A.E., Gomez-Valero, L., and Buchrieser, C. (2020). Metagenomic approaches in microbial ecology: an update on whole-genome and marker gene sequencing analyses. Microb Genom 6. 10.1099/mgen.0.000409.
70. Wang, B., Sun, F., and Luan, Y. (2024). Comparison of the effectiveness of different normalization methods for metagenomic cross-study phenotype prediction under heterogeneity. Sci Rep 14, 7024. 10.1038/s41598-024-57670-2.
71. Daruka, L., Czikkely, M.S., Szili, P., Farkas, Z., Balogh, D., Grézal, G., Maharramov, E., Vu, T.H., Sipos, L., Juhász, S., et al. (2025). ESKAPE pathogens rapidly develop resistance against antibiotics in development in vitro. Nat Microbiol 10, 313-331. 10.1038/s41564-024-01891-8.
72. Maeda, T., and Furusawa, C. (2024). Laboratory Evolution of Antimicrobial Resistance in Bacteria to Develop Rational Treatment Strategies. Antibiotics (Basel) 13. 10.3390/antibiotics13010094.
73. De Oliveira, D.M.P., Forde, B.M., Kidd, T.J., Harris, P.N.A., Schembri, M.A., Beatson, S.A., Paterson, D.L., and Walker, M.J. (2020). Antimicrobial Resistance in ESKAPE Pathogens. Clin Microbiol Rev 33. 10.1128/cmr.00181-19.
74. Kritsotakis, E.I., Lagoutari, D., Michailellis, E., Georgakakis, I., and Gikas, A. (2022). Burden of multidrug and extensively drug-resistant ESKAPEE pathogens in a secondary hospital care setting in Greece. Epidemiol Infect 150, e170. 10.1017/s0950268822001492.
75. Breijyeh, Z., Jubeh, B., and Karaman, R. (2020). Resistance of Gram-Negative Bacteria to Current Antibacterial Agents and Approaches to Resolve It. Molecules 25. 10.3390/molecules25061340.
76. Elshobary, M.E., Badawy, N.K., Ashraf, Y., Zatioun, A.A., Masriya, H.H., Ammar, M.M., Mohamed, N.A., Mourad, S., and Assy, A.M. (2025). Combating Antibiotic Resistance: Mechanisms, Multidrug-Resistant Pathogens, and Novel Therapeutic Approaches: An Updated Review. Pharmaceuticals (Basel) 18. 10.3390/ph18030402.
77. Elshamy, A.A., Aboshanab, K.M., Yassien, M.A., and Hassouna, N.A. (2020). Prevalence of plasmid-mediated resistance genes among multidrug-resistant uropathogens in Egypt. Afr Health Sci 20, 190-198. 10.4314/ahs.v20i1.24.
78. Bennett, P.M. (2008). Plasmid encoded antibiotic resistance: acquisition and transfer of antibiotic resistance genes in bacteria. Br J Pharmacol 153 Suppl 1, S347-357. 10.1038/sj.bjp.0707607.
79. Molano, L.G., Hirsch, P., Hannig, M., Müller, R., and Keller, A. (2025). The PLSDB 2025 update: enhanced annotations and improved functionality for comprehensive plasmid research. Nucleic Acids Res 53, D189-d196. 10.1093/nar/gkae1095.
80. Alcock, B.P., Huynh, W., Chalil, R., Smith, K.W., Raphenya, A.R., Wlodarski, M.A., Edalatmand, A., Petkau, A., Syed, S.A., Tsang, K.K., et al. (2023). CARD 2023: expanded curation, support for machine learning, and resistome prediction at the Comprehensive Antibiotic Resistance Database. Nucleic Acids Res 51, D690-d699. 10.1093/nar/gkac920.
81. Yusuf, I., Skiebe, E., and Wilharm, G. (2023). Evaluation of CHROMagar Acinetobacter and MacConkey media for the recovery of Acinetobacter baumannii from soil samples. Lett Appl Microbiol 76. 10.1093/lambio/ovac051.
82. Sigma-Aldrich (2018). 50875 GSP Agar (Pseudomonas Aeromonas Selective Agar acc. to Kielwein, Glutamate Starch Phenol Red Agar).
83. Prasad, M., Shetty, S.K., Nair, B.G., Pal, S., and Madhavan, A. (2022). A novel and improved selective media for the isolation and enumeration of Klebsiella species. Appl Microbiol Biotechnol 106, 8273-8284. 10.1007/s00253-022-12270-w.
84. Jung, B., and Hoilat, G.J. (2025). MacConkey Medium. In StatPearls, (StatPearls Publishing Copyright © 2025, StatPearls Publishing LLC.).
85. Rozwandowicz, M., Brouwer, M.S.M., Fischer, J., Wagenaar, J.A., Gonzalez-Zorn, B., Guerra, B., Mevius, D.J., and Hordijk, J. (2018). Plasmids carrying antimicrobial resistance genes in Enterobacteriaceae. J Antimicrob Chemother 73, 1121-1137. 10.1093/jac/dkx488.
86. Wyres, K.L., and Holt, K.E. (2018). Klebsiella pneumoniae as a key trafficker of drug resistance genes from environmental to clinically important bacteria. Curr Opin Microbiol 45, 131-139. 10.1016/j.mib.2018.04.004.
87. Lam, M.M.C., and Hamidian, M. (2024). Examining the role of Acinetobacter baumannii plasmid types in disseminating antimicrobial resistance. NPJ Antimicrob Resist 2, 1. 10.1038/s44259-023-00019-y.
88. Cazares, A., Moore, M.P., Hall, J.P.J., Wright, L.L., Grimes, M., Emond-Rhéault, J.G., Pongchaikul, P., Santanirand, P., Levesque, R.C., Fothergill, J.L., and Winstanley, C. (2020). A megaplasmid family driving dissemination of multidrug resistance in Pseudomonas. Nat Commun 11, 1370. 10.1038/s41467-020-15081-7.
89. Letunic, I., and Bork, P. (2024). Interactive Tree of Life (iTOL) v6: recent updates to the phylogenetic tree display and annotation tool. Nucleic Acids Res 52, W78-w82. 10.1093/nar/gkae268.
90. European Committee on Antimicrobial Susceptibility Testing. (2025). Data from the EUCAST MIC distribution website. https://www.eucast.org.
91. Zalewska, M., Błażejewska, A., Czapko, A., and Popowska, M. (2021). Antibiotics and Antibiotic Resistance Genes in Animal Manure - Consequences of Its Application in Agriculture. Front Microbiol 12, 610656. 10.3389/fmicb.2021.610656.
92. Wang, F.H., Qiao, M., Chen, Z., Su, J.Q., and Zhu, Y.G. (2015). Antibiotic resistance genes in manure-amended soil and vegetables at harvest. J Hazard Mater 299, 215-221. 10.1016/j.jhazmat.2015.05.028.
93. Șchiopu, P., Toc, D.A., Colosi, I.A., Costache, C., Ruospo, G., Berar, G., Gălbău Ș, G., Ghilea, A.C., Botan, A., Pană, A.G., et al. (2023). An Overview of the Factors Involved in Biofilm Production by the Enterococcus Genus. Int J Mol Sci 24. 10.3390/ijms241411577.
94. Hunashal, Y., Kumar, G.S., Choy, M.S., D'Andréa É, D., Da Silva Santiago, A., Schoenle, M.V., Desbonnet, C., Arthur, M., Rice, L.B., Page, R., and Peti, W. (2023). Molecular basis of β-lactam antibiotic resistance of ESKAPE bacterium E. faecium Penicillin Binding Protein PBP5. Nat Commun 14, 4268. 10.1038/s41467-023-39966-5.
95. Alexander, J.A.N., Worrall, L.J., Hu, J., Vuckovic, M., Satishkumar, N., Poon, R., Sobhanifar, S., Rosell, F.I., Jenkins, J., Chiang, D., et al. (2023). Structural basis of broad-spectrum β-lactam resistance in Staphylococcus aureus. Nature 613, 375-382. 10.1038/s41586-022-05583-3.
96. Peng, Q., Tang, X., Dong, W., Sun, N., and Yuan, W. (2022). A Review of Biofilm Formation of Staphylococcus aureus and Its Regulation Mechanism. Antibiotics (Basel) 12. 10.3390/antibiotics12010012.
97. Sharp, S.E., and Searcy, C. (2006). Comparison of mannitol salt agar and blood agar plates for identification and susceptibility testing of Staphylococcus aureus in specimens from cystic fibrosis patients. J Clin Microbiol 44, 4545-4546. 10.1128/jcm.01129-06.
98. Russo, A., Tarantino, U., d'Ettorre, G., Della Rocca, C., Ceccarelli, G., Gasbarra, E., Venditti, M., and Iundusi, R. (2021). First report of spondylodiscitis caused by Bacillus circulans in an immunocompetent patient: Clinical case and review of the literature. IDCases 23, e01058. 10.1016/j.idcr.2021.e01058.
99. Ministry of Health and Welfare, Taiwan (2024). 國家級防疫一體抗生素抗藥性管理行動計畫.
100. Li, L.G., Yin, X., and Zhang, T. (2018). Tracking antibiotic resistance gene pollution from different sources using machine-learning classification. Microbiome 6, 93. 10.1186/s40168-018-0480-x.
101. Partridge, S.R., Kwong, S.M., Firth, N., and Jensen, S.O. (2018). Mobile Genetic Elements Associated with Antimicrobial Resistance. Clin Microbiol Rev 31. 10.1128/cmr.00088-17.
102. Loos, D., Filho, A., Dutilh, B.E., Barber, A.E., and Panagiotou, G. (2024). A global survey of host, aquatic, and soil microbiomes reveals shared abundance and genomic features between bacterial and fungal generalists. Cell Rep 43, 114046. 10.1016/j.celrep.2024.114046.
103. Food Safety Commission, Japan (2011). 動物用医薬品・飼料添加物評価書: アビラマイシン.
104. Dos Santos, D.F., Istvan, P., Quirino, B.F., and Kruger, R.H. (2017). Functional Metagenomics as a Tool for Identification of New Antibiotic Resistance Genes from Natural Environments. Microb Ecol 73, 479-491. 10.1007/s00248-016-0866-x.
105. MacFadden, D.R., McGough, S.F., Fisman, D., Santillana, M., and Brownstein, J.S. (2018). Antibiotic Resistance Increases with Local Temperature. Nat Clim Chang 8, 510-514. 10.1038/s41558-018-0161-6.
106. Rodrigues da Costa, M., and Diana, A. (2022). A Systematic Review on the Link between Animal Welfare and Antimicrobial Use in Captive Animals. Animals (Basel) 12. 10.3390/ani12081025.
-
dc.identifier.urihttp://tdr.lib.ntu.edu.tw/jspui/handle/123456789/99364-
dc.description.abstract抗生素抗藥性(AMR)為影響防疫一體(One Health)架構之重要議題。本報告視產食動物之抗生素使用為人為因素,以全面的觀點探討其傳播抗生素抗藥性之可能性。研究方法包括分析法國、日本及台灣之產食動物抗生素使用習慣及實地樣本之抗藥性分析。結果顯示相較於日本及台灣,法國具有較強力度之法規及較少之抗生素使用。相似趨勢亦發現於廢水宏基因體定序分析,與日本及台灣之集群相比,法國樣本之集群表現出較為獨立之趨勢。依據前述之研究結果,同時擁有β-內醯胺類抗生素及多黏菌素抗性之抗藥性基因被提議作為追溯產食動物抗藥性來源之指標基因。抗生素敏感性試驗更進一步的被用於探討產食動物相關樣品分離出之菌株抗藥性機制。自法國肉牛農場採集之動物及環境樣本篩選分離出之革蘭氏陰性菌菌株用於探討以質體為媒介之抗藥性傳播,而自日本蔬菜農場採集之含產食動物糞便肥料樣本篩選分離出之革蘭氏陽性菌菌株則被用於探討其可能之β-內醯胺類抗生素抗藥性。ESKAPEE病原體所屬之菌屬在抗藥性傳播中可能扮演的生態棲位也同時於本研究中探討。產食動物抗生素使用及抗生素抗藥性之間存在由多樣因子構成之關聯,現今之相關研究因而有所侷限,多元之研究方法因此被建議使用以彌補研究之不足。本報告提議以功能性宏基因體定序分析作為填補現今產食動物抗生素抗藥性研究缺口之方法,從而連接防疫一體及全球意識,提升抗生素抗藥性監測效能。整體而言,本研究提供關於產食動物抗生素抗藥性的全面見解,旨在守護所有生物與環境的健康與福祉,並為未來抗生素抗藥性提供可能之研究方向。zh_TW
dc.description.abstractAntimicrobial resistance (AMR) is a serious concern that affects the One Health sectors. This report examines antibiotic use in food-producing animals as an anthropogenic factor, identifying its potential contribution to resistance spread by analyzing antibiotic use patterns and real-life sample resistance profiling in France, Japan, and Taiwan to provide a comprehensive perspective. The results indicated stricter policies and lower levels of antibiotic use in France compared to Japan and Taiwan. Similar trends were discovered in the wastewater metagenomic analyses, with samples from France forming more distinct clusters than the other two countries. Genes resistant to both beta-lactam and polymyxin are proposed as potential markers to track animal-originated sources. Phenotypic profiling was further performed to explore strain-specific, animal-originated resistance mechanisms by identifying plasmid-mediated resistance in Gram-negative isolates from France and possible beta-lactam resistance in Gram-positive isolates from Japan, alongside the consideration of possible ecological roles played by ESKAPEE-associated genera in resistance dissemination. The relationship between food-producing animal antibiotic practices and AMR is shaped by complex factors, which pose limitations for current studies. A multi-method approach is therefore recommended to complement existing constraints. Functional metagenomics is proposed as a potential solution to address current gaps in food-producing animals’ AMR research to bridge One Health and global efforts toward improved AMR surveillance. Overall, this study provides insights about AMR related to food-producing animals with the aim of protecting the health and welfare of all living beings, and offers possible directions for future AMR research.en
dc.description.provenanceSubmitted by admin ntu (admin@lib.ntu.edu.tw) on 2025-09-09T16:09:57Z
No. of bitstreams: 0
en
dc.description.provenanceMade available in DSpace on 2025-09-09T16:09:57Z (GMT). No. of bitstreams: 0en
dc.description.tableofcontentsAcknowledgement i
摘要 ii
Abstract iii
Nomenclature iv
Chapter 1 Introduction 1
1.1. Global Threat of Antimicrobial Resistance (AMR) 1
1.2. One Health Framework and AMR Dissemination 1
1.3. Concern of AMR in Food-Producing Animals 2
1.4. Surveillance of AMR 3
1.5. Case Selection: France, Japan, and Taiwan 4
1.6. Study Objective and Scope 5
Chapter 2 Food-Producing Animal Antibiotic Use in France, Japan, and Taiwan 6
2.1. Policies Regarding Antibiotics in Animal Feed 6
2.2. Authorized Antibiotic Products 9
2.3. Food-Producing Animal Antibiotic Sales 12
2.4. Quantifying the Impact of Antibiotic Use on AMR 15
Chapter 3 Metagenomic Profiling of the Resistome in Wastewater from France, Japan, and Taiwan 19
3.1. Comparative Resistome Structure Based on ARG Abundance 20
3.2. Potential Signatures of Food-Producing Animal Contribution to the Wastewater Resistome 22
3.3. Prevalence of ESKAPEE Pathogen-Associated Genera 24
Chapter 4 Phenotypic Characterization of Antibiotic Resistance in Animal-Associated Bacteria 27
4.1. Resistance in Gram-Negative Bacteria from France 28
4.2. Resistance in Gram-Positive Bacteria from Japan 39
Chapter 5 Conclusion and Discussion 41
5.1. Human: Decision Maker for Anthropogenic Factors 41
5.2. Environment: Wastewater Samples as Surveillance Model 42
5.3. Animal: Phenotypic Profiling of Originated Strains 45
5.4. Solution: Functional Metagenomics as One Health Gap-Filler 47
5.5. Conclusion 50
References 51
Appendix 58
-
dc.language.isoen-
dc.subject抗生素抗藥性zh_TW
dc.subject防疫一體zh_TW
dc.subject產食動物zh_TW
dc.subject人為因素zh_TW
dc.subject宏基因體zh_TW
dc.subject抗生素敏感性試驗zh_TW
dc.subjectFood-Producing Animalsen
dc.subjectOne Healthen
dc.subjectAntibiotic Susceptibility Testingen
dc.subjectAntimicrobial Resistance (AMR)en
dc.subjectAnthropogenic Factorsen
dc.subjectMetagenomicsen
dc.title產食動物抗生素抗藥性:法國、日本及台灣之防疫一體分析zh_TW
dc.titleAntibiotic Resistance in Food-Producing Animals: A One Health Analysis Across France, Japan, and Taiwanen
dc.typeThesis-
dc.date.schoolyear113-2-
dc.description.degree碩士-
dc.contributor.oralexamcommitteeChristophe Dagot;王如邦zh_TW
dc.contributor.oralexamcommitteeChristophe Dagot;Reuben Wangen
dc.subject.keyword抗生素抗藥性,防疫一體,產食動物,人為因素,宏基因體,抗生素敏感性試驗,zh_TW
dc.subject.keywordAntimicrobial Resistance (AMR),One Health,Food-Producing Animals,Anthropogenic Factors,Metagenomics,Antibiotic Susceptibility Testing,en
dc.relation.page77-
dc.identifier.doi10.6342/NTU202503336-
dc.rights.note同意授權(全球公開)-
dc.date.accepted2025-08-05-
dc.contributor.author-college醫學院-
dc.contributor.author-dept國際三校農業生技與健康醫療碩士學位學程-
dc.date.embargo-lift2025-09-10-
顯示於系所單位:國際三校農業生技與健康醫療碩士學位學程

文件中的檔案:
檔案 大小格式 
ntu-113-2.pdf20.1 MBAdobe PDF檢視/開啟
顯示文件簡單紀錄


系統中的文件,除了特別指名其著作權條款之外,均受到著作權保護,並且保留所有的權利。

社群連結
聯絡資訊
10617臺北市大安區羅斯福路四段1號
No.1 Sec.4, Roosevelt Rd., Taipei, Taiwan, R.O.C. 106
Tel: (02)33662353
Email: ntuetds@ntu.edu.tw
意見箱
相關連結
館藏目錄
國內圖書館整合查詢 MetaCat
臺大學術典藏 NTU Scholars
臺大圖書館數位典藏館
本站聲明
© NTU Library All Rights Reserved