細菌性疾病使動物嚴重死亡並造成經濟上的損失，而現今防治與治療皆以投予抗生素為主。然而，由於其便宜又方便，因此常出現抗生素濫用的情況，不只造成藥物殘留，還會產生抗藥性。抗藥性基因可藉由細菌間互相傳遞，種類多元且複雜。本研究規劃出篩選抗藥性基因之流程,並建立細菌的抗藥性基因檢測平台。利用收集自屏東東海地區水產動物細菌分離株(72株)及哺乳類與家禽類動物之糞便分離細菌(32株)，檢測4種抗生素（amoxicillin, erythromycin, doxycycline及 florfenicol）藥物敏感性。由細菌抗藥性基因庫(CARD)尋找前述4種抗藥性基因，建立基因篩選流程、序列整理與設計評估，分析以聚合酶連鎖反應結果搭配抗生素感受性試驗資料進行檢驗效能。五組抗藥性基因(TEM-1, ermB, tetM, floR, fexA)平均敏感性上，哺乳類及禽類細菌組於不分類細菌結果約34%，數據較低，我們將細菌做革蘭氏陰性及陽性分類後，可看出革蘭氏陽性細菌敏感度上升至47％，而革蘭氏陰性菌則下降為21.2%。而水產細菌於本次實驗中，數值皆較哺乳細菌低。於哺乳類與禽類細菌中，有4個基因檢測敏感度達50%以上（革蘭氏陰性菌的floR、革蘭氏陽性菌的ermB, tetM及fexA）。而本實驗所收集的水產動物細菌經鑑定後，高於50%沒有收錄在CARD資料庫當中。在所有水產細菌檢測當中，只有革蘭氏陰性菌的floR檢測敏感度(sensitivity)超過50%。綜合上述，利用CARD的prevalence database的資料可快速獲得普及的抗藥性基因，但方法使用之對象必須符合資料庫中所收集到的221種細菌屬，且在區分革蘭氏陰陽性可提高方法之可信度。

Bacterial diseases cause severe death of animals and cause economic losses. Nowadays, prevention and treatment are mainly based on the administration of antibiotics. However, due to its cheapness and convenience, antibiotics are often abused, not only causing drug residues, but also drug resistance. Drug resistance genes can be transmitted between bacteria, and the types are diverse and complex. This research plans to screen the process of drug resistance genes, and establish a bacterial drug resistance gene detection platform. Using bacterial isolates (72 strains) collected from aquatic animals in the East China Sea area of Pingtung and isolated bacteria (32 strains) from the feces of mammals and poultry animals, the drug susceptibility of 4 antibiotics (amoxicillin, erythromycin, doxycycline and florfenicol) was tested. From the bacterial antibiotic resistance gene bank, Comprehensive Antibiotic Resistance Database (CARD) to search for the aforementioned four antibiotic resistance genes, establish a gene screening process, sequence arrangement and design evaluation. Later, the PCR results were combined with the antibiotic susceptibility test data for statistical analysis of the test efficiency. With regard to the average sensitivity of the five groups of drug resistance genes (TEM-1, ermB, tetM, floR, fexA), the results of mammalian and poultry bacteria in the unclassified bacteria group are about 34%, and the data is low. We set the bacteria as Gram-negative and positive classification, it can be seen that the sensitivity of Gram-positive bacteria has increased to 47%, while that of Gram-negative bacteria has dropped to 21.2%. In this experiment, the values of aquatic bacteria are lower than those of mammalian and poultry bacteria. In mammals and poultry bacteria, 4 genes have a sensitivity of more than 50% (floR for gram-negative bacteria, ermB, tetM and fexA for gram-positive bacteria). After the identification of the aquatic animal bacteria collected in this experiment, more than 50% were not included in the CARD database. Among all aquatic bacteria testing, only gram-negative bacteria have a floR sensitivity of more than 50%. In summary, using CARD's prevalence database data can quickly obtain popular antimicrobial resistance genes, but the method used must conform to the 221 bacterial genera collected in the database, and the distinction between gram negative and positive can improve the accuracy of analysis.

[1]黃子鳴*、鄭劭蕙、涂堅. 101 年度魚類鏈球菌藥物感受性調查. 家畜衛試所研報 2013;88:83–8.
[2]Akobeng AK. Understanding diagnostic tests 1: Sensitivity, specificity and predictive values. Acta Paediatr Int J Paediatr 2007;96:338–41.

[3]Chopra I, Roberts M. Tetracycline Antibiotics: Mode of Action, Applications, Molecular Biology, and Epidemiology of Bacterial Resistance. Microbiol Mol Biol Rev 2001;65:232–60.

[4]Clinical and Laboratory Standards Institute. Performance standards for antimicrobial disk susceptibility tests: Approved standard - Eleventh edition. vol. 32. 2012.

[5]CLSI. M45. Methods for Antimicrobial Dilution and Disk Susceptibility Testing of Infrequently Isolated or Fastidious Bacteria ; Proposed Guideline. vol. 35. 2015.

[6]CLSI. Performance Standards for Antimicrobial Susceptibility Testing; Twenty-Seventh Informational Supplement. CLSI Document M100-S27. 2017.

[7]Dahl LG, Joensen KG, Østerlund MT, Kiil K, Nielsen EM. Prediction of antimicrobial resistance in clinical Campylobacter jejuni isolates from whole-genome sequencing data. Eur J Clin Microbiol Infect Dis 2021;40:673–82.

[8]Descheemaeker P, Chapelle S, Lammens C, Hauchecorne M, Wijdooghe M, Vandamme P, et al. Macrolide resistance and erythromycin resistance determinants among Belgian Streptococcus pyogenes and Streptococcus pneumoniae isolates. J Antimicrob Chemother 2000;45:167–73.

[9]Eady EA, Ross JI, Tipper JL, Walters CE, Cove JH, Noble WC. Distribution of genes encoding erythromycin ribosomal methylases and an erythromycin efflux pump in epidemiologically distinct groups of staphylococci. J Antimicrob Chemother 1993;31:211–7.

[10] Feßler A, Scott C, Kadlec K, Ehricht R, Monecke S, Schwarz S. Characterization of methicillin-resistant Staphylococcus aureus ST398 from cases of bovine mastitis. J Antimicrob Chemother 2010;65:619–25.

[11] Fiebelkorn KR, Crawford SA, McElmeel ML, Jorgensen JH. Practical disk diffusion method for detection of inducible clindamycin resistance in Staphylococcus aureus and coagulase-negative staphylococci. J Clin Microbiol 2003;41:4740–4.

[12] Frank JA, Reich CI, Sharma S, Weisbaum JS, Wilson BA, Olsen GJ. Critical evaluation of two primers commonly used for amplification of bacterial 16S rRNA genes. Appl Environ Microbiol 2008;74:2461–70.

[13] Alcock BP, Raphenya AR, Lau TTY, Tsang KK, Bouchard M, Edalatmand A, et al. CARD 2020: Antibiotic resistome surveillance with the comprehensive antibiotic resistance database. Nucleic Acids Res 2020;48:D517–25.

[14] Heuer H, Krsek M, Baker P, Smalla K, Wellington EMH. Analysis of actinomycete communities by specific amplification of genes encoding 16S rRNA and gel-electrophoretic separation in denaturing gradients. Appl Environ Microbiol 1997;63:3233–41.

[15] Hong B, Ba Y, Niu L, Lou F, Zhang Z, Liu H, et al. A comprehensive research on antibiotic resistance genes in microbiota of aquatic animals. Front Microbiol 2018;9:1–10.

[16] Hyatt D, Chen GL, LoCascio PF, Land ML, Larimer FW, Hauser LJ. Prodigal: Prokaryotic gene recognition and translation initiation site identification. BMC Bioinformatics 2010;11.

[17] Jang HM, Kim YB, Choi S, Lee Y, Shin SG, Unno T, et al. Prevalence of antibiotic resistance genes from effluent of coastal aquaculture, South Korea. Environ Pollut 2018;233:1049–57.
[18] Jiang HX, Tang D, Liu YH, Zhang XH, Zeng ZL, Xu L, et al. Prevalence and characteristics of β-lactamase and plasmid-mediated quinolone resistance genes in Escherichia coli isolated from farmed fish in China. J Antimicrob Chemother 2012;67:2350–3.

[19] Johnson M, Zaretskaya I, Raytselis Y, Merezhuk Y, McGinnis S, Madden TL. NCBI BLAST: a better web interface. Nucleic Acids Res 2008;36:5–9.

[20] Jorgensen JH, Ferraro MJ. Antimicrobial susceptibility testing: A review of general principles and contemporary practices. Clin Infect Dis 2009;49:1749–55.

[21] Kai S, Matsuo Y, Nakagawa S, Kryukov K, Matsukawa S, Tanaka H, et al. Rapid bacterial identification by direct PCR amplification of 16S rRNA genes using the MinIONTM nanopore sequencer. FEBS Open Bio 2019;9:548–57.

[22] Kuo HC, Lauderdale TL, Lo DY, Chen CL, Chen PC, Liang SY, et al. An association of genotypes and antimicrobial resistance patterns among Salmonella isolates from pigs and humans in Taiwan. PLoS One 2014;9.

[23] Langille MGI, Hsiao WWL, Brinkman FSL. Detecting genomic islands using bioinformatics approaches. Nat Rev Microbiol 2010;8:373–82.

[24] Balouiri M, Sadiki M, Ibnsouda SK. Methods for in vitro evaluating antimicrobial activity: A review. J Pharm Anal 2016;6:71–9.

[25] Liu B, Pop M. ARDB - Antibiotic resistance genes database. Nucleic Acids Res 2009;37:443–7.

[26] McArthur AG, Wright GD. Bioinformatics of antimicrobial resistance in the age of molecular epidemiology. Curr Opin Microbiol 2015;27:45–50.

[27] Patel J. 16S rRNA gene sequencing for bacterial pathogen identification in the clinical laboratory. Mol Diagnosis 2001;6:313–21.

[28] Patterson AJ, Colangeli R, Spigaglia P, Scott KP. Distribution of specific tetracycline and erythromycin resistance genes in environmental samples assessed by macroarray detection. Environ Microbiol 2007;9:703–15.

[29] Piotrowska M, Popowska M. The prevalence of antibiotic resistance genes among Aeromonas species in aquatic environments. Ann Microbiol 2014;64:921–34.

[30] Piotrowska M, Rzeczycka M, Ostrowski R, Popowska M. Diversity of antibiotic resistance among bacteria isolated from sediments and water of carp farms located in a Polish nature reserve. Polish J Environ Stud 2017;26:239–52.

[31] Preena PG, Swaminathan TR, Rejish Kumar VJ, Bright Singh IS. Unravelling the menace: detection of antimicrobial resistance in aquaculture. Lett Appl Microbiol 2020;71:26–38.

[32] Roberts MC. Acquired tetracycline and/or macrolide-lincosamides-streptogramin resistance in anaerobes. Anaerobe 2003;9:63–9.

[33] Salverda MLM, de Visser JAGM, Barlow M. Natural evolution of TEM-1 β-lactamase: Experimental reconstruction and clinical relevance. FEMS Microbiol Rev 2010;34:1015–36.

[34] Brown SS, Chen YW, Wang M, Clipson A, Ochoa E, Du MQ. PrimerPooler: Automated primer pooling to prepare library for targeted sequencing. Biol Methods Protoc 2017;2:1–10.

[35] Sandle T. Antibiotics and preservatives. Pharm Microbiol 2016:171–83.

[36] Sapkota A, Sapkota AR, Kucharski M, Burke J, McKenzie S, Walker P, et al. Aquaculture practices and potential human health risks: Current knowledge and future priorities. Environ Int 2008;34:1215–26.

[37] Shen Z, Qu W, Wang W, Lu Y, Wu Y, Li Z, et al. MPprimer: A program for reliable multiplex PCR primer design. BMC Bioinformatics 2010;11.

[38] Sousa M, Torres C, Barros J, Somalo S, Igrejas G, Poeta P. Gilthead seabream (Sparus aurata) as carriers of SHV-12 and TEM-52 extended-spectrum beta-lactamases-containing Escherichia coli isolates. Foodborne Pathog Dis 2011;8:1139–41.
[39] Stackebrandt E, Goebel BM. Taxonomic note: A place for DNA-DNA reassociation and 16S rRNA sequence analysis in the present species definition in bacteriology. Int J Syst Bacteriol 1994;44:846–9.

[40] Suzuki S, Hoa PTP. Distribution of quinolones, sulfonamides, tetracyclines in aquatic environment and antibiotic resistance in Indochina. Front Microbiol 2012;3:1–8.

[41] Terrance Walker G, Quan J, Higgins SG, Toraskar N, Chang W, Saeed A, et al. Predicting antibiotic resistance in gram-negative bacilli from resistance genes. Antimicrob Agents Chemother 2019;63:1–9.

[42] TRUSSELL PC, BAIRD EA. A rapid method for the assay of penicillin. Can J Res 1947;25:5–8.

[43] Untergasser A, Cutcutache I, Koressaar T, Ye J, Faircloth BC, Remm M, et al. Primer3-new capabilities and interfaces. Nucleic Acids Res 2012;40:1–12.

[44] Vignesh R, Karthikeyan B, Periyasamy N, Devanathan K. Antibiotics in Aquaculture: An Overview. South Asian J Exp Biol 2011;1:114-120–120.

[45] Buchfink B, Xie C, Huson DH. Fast and sensitive protein alignment using DIAMOND. Nat Methods 2014;12:59–60.

[46] Watts JEM, Schreier HJ, Lanska L, Hale MS. The rising tide of antimicrobial resistance in aquaculture: Sources, sinks and solutions. Mar Drugs 2017;15:1–16.

[47] World Organisation of Animal Health. Laboratory Methodologies for Bacterial Antimicrobial Susceptibility Testing. OIE Terr Man 2012:1–11.

[48] Ye J, Coulouris G, Zaretskaya I, Cutcutache I, Rozen S, Madden TL. Primer-BLAST: A tool to design target-specific primers for polymerase chain reaction. BMC Bioinformatics 2012;13.

[49] Zhang XX, Zhang T, Fang HHP. Antibiotic resistance genes in water environment. Appl Microbiol Biotechnol 2009;82:397–414.
[50] Burdett V. tRNA modification activity is necessary for Tet(M)-mediated tetracycline resistance. J Bacteriol 1993;175:7209–15.

[51] C Reygaert W. An overview of the antimicrobial resistance mechanisms of bacteria. AIMS Microbiol 2018;4:482–501.

[52] Cabello FC. Heavy use of prophylactic antibiotics in aquaculture: A growing problem for human and animal health and for the environment. Environ Microbiol 2006;8:1137–44.

[53] Camacho C, Coulouris G, Avagyan V, Ma N, Papadopoulos J, Bealer K, et al. BLAST+: Architecture and applications. BMC Bioinformatics 2009;10:1–9.