K fragment as a polymerase chain reaction-based vector for antibiotic resistance gene hunting
Antimicrobial resistance (AMR) has emerged as an escalating health issue in the global public health arena. To evaluate and predict AMR, it is of utmost importance to identify and characterize both the known and unknown genes responsible for AMR. While known genes can be readily detected, identifying unknown genes present a challenge. In this study, we developed the plasmid K fragment (pKF) by modifying the pUC19 vector, specifically by removing the multiple cloning site and introducing a Prom-RBS sequence. pKF was used for amplification of K fragment that contains a ribosomal binding site (RBS), and promoter at both ends and plasmid origin of replication. The functionality of added Prom-RBS sequence and K fragment as a cloning vector was tested by cloning chloramphenicol resistance gene amplicon and erythromycin resistance gene from genomic DNA, respectively. The cloning experiment demonstrated the usability of this newly developed cloning method with K fragment. K fragment is an innovative vector that can be easily obtained through amplification by polymerase chain reaction and lacks antibiotic resistance markers. This novel approach is convenient to use since it allows cloning of resistance genes at all orientations and this flexibility can be maneuvered by changing restriction enzymes for primers and fragments. With these distinctive features, this vector stands out to be a versatile tool for cloning both known and unknown resistance genes, and the improved method with K fragment enables the microbiological and molecular characterization of cloned genes. K fragment can be utilized for cloning of resistance genes in bacteria originated in different environments without having to perform bacterial culture. We believe that the convenience brought by this technique could lend itself efficient in the battle against the growing AMR crisis through pre-emptive identification of resistance genes.
- World Health Organization, 2020, Central Asian and European Surveillance of Antimicrobial Resistance: Annual Report 2020 (No. WHO/EURO: 2020-3469-43228-60585). Geneva: World Health Organization. Regional Office for Europe.
- Dadgostar P, 2019, Antimicrobial resistance: Implications and costs. Infect Drug Resist, 12: 3903. https://doi.org/10.2147/IDR.S234610
- Bader MS, Loeb M, Leto D, et al., 2020, Treatment of urinary tract infections in the era of antimicrobial resistance and new antimicrobial agents. Postgrad Med, 132(3): 234–250. https://doi.org/10.1080/00325481.2019.1680052
- Davies SC, Oxlade C, 2021, Innovate to secure the future: The future of modern medicine. Future Healthc J, 8(2): e251–e256. https://doi.org/10.7861/fhj.2021-0087
- Spellberg B, Hansen GR, Kar A, et al., 2016, Antibiotic Resistance in Humans and Animals. Indonesia: NAM Perspectives.
- Patel SJ, Wellington M, Shah RM, et al., 2020, Antibiotic stewardship in food-producing animals: Challenges, progress, and opportunities. Clin Ther, 42: 1649–1658. https://doi.org/10.1016/j.clinthera.2020.07.004
- Czekalski N, Sigdel R, Birtel J, et al., 2015, Does human activity impact the natural antibiotic resistance background? Abundance of antibiotic resistance genes in 21 Swiss lakes. Environ Int, 81: 45–55. https://doi.org/10.1016/j.envint.2015.04.005
- Martinez JL, 2009, The role of natural environments in the evolution of resistance traits in pathogenic bacteria. Proc Biol Sci, 276(1667): 2521–2530. https://doi.org/10.1098/rspb.2009.0320
- Bengtsson-Palme J, Kristiansson E, Larsson DGJ, 2018, Environmental factors influencing the development and spread of antibiotic resistance. FEMS Microbiol Rev, 42(1): fux053. https://doi.org/10.1093/femsre/fux053
- Fluit AC, Visser MR, Schmitz FJ, 2001, Molecular detection of antimicrobial resistance. Clin Microbiol Rev, 14(4): 836–871. https://doi.org/10.1128/CMR.14.4.836-871.2001
- Bozdogan B, Galopin S, Gerbaud G, et al., 2003, Chromosomal aadD2 encodes an aminoglycoside nucleotidyltransferase in Bacillus clausii. Antimicrob Agents Chemother, 47(4): 1343–1346. https://doi.org/10.1128/AAC.47.4.1343-1346.2003
- Brown MG, Mitchell EH, Balkwill DL, 2010, Screening for novel antibiotic resistance genes. Methods Mol Bio, 668: 265–271. https://doi.org/10.1007/978-1-60761-823-2_18
- Mullany P, 2014, Functional metagenomics for the investigation of antibiotic resistance. Virulence, 5(3): 443–447. https://doi.org/10.4161/viru.28196
- Sambrook J, Russell DW, 2001, Molecular Cloning: A Laboratory Manual. 3rd ed. Cold Spring Harbor, NY: Cold Spring Harbor Laboratory Press. p132-150.
- Wikmark OG, Brautaset T, Agapito-Tenfen SZ, et al., 2016, Synthetic biology-biosafety and contribution to addressing societal challenges.
- Saito K, Green R, Buskirk AR, 2020, Translational initiation in E. coli occurs at the correct sites genome-wide in the absence of mRNA-rRNA base-pairing. Elife, 9: e55002. https://doi.org/10.7554/eLife.55002.
- Thompson CJ, Ward JM, Hopwood DA, 1982, Cloning of antibiotic resistance and nutritional genes in streptomycetes. J Bacteriol, 151(2): 668–677. https://doi.org/10.1128/jb.151.2.668-677.1982
- Zhou W, Wang Y, Lin J, 2012, Functional cloning and characterization of antibiotic resistance genes from the chicken gut microbiome. Appl Environ Microbiol, 78(8): 3028–3032. https://doi.org/10.1128/AEM.06920-11
- Martiny AC, Martiny JBH, Weihe C, et al., 2011, Functional metagenomics reveals previously unrecognized diversity of antibiotic resistance genes in gulls. Front microbial, 2: 238. https://doi.org/10.3389/fmicb.2011.00238
- Flórez AB, Vázquez L, Mayo B, 2017, A functional metagenomic analysis of tetracycline resistance in cheese bacteria. Front Microbiol, 8: 907. https://doi.org/10.3389/fmicb.2017.00907
- Vestö K, Huseby DL, Snygg I, et al., 2018, Muramyl endopeptidase Spr contributes to intrinsic vancomycin resistance in Salmonella enterica serovar Typhimurium. Front Microbiol, 9: 2941. https://doi.org/10.3389/fmicb.2018.02941
- Fresia P, Antelo V, Salazar C, et al., 2019, Urban metagenomics uncover antibiotic resistance reservoirs in coastal beach and sewage waters. Microbiome, 7(1): 35. https://doi.org/10.1186/s40168-019-0648-z
- Li Y, Cao W, Liang S, et al., 2020, Metagenomic characterization of bacterial community and antibiotic resistance genes in representative ready-to-eat food in southern China. Sci Rep, 10(1): 15175. https://doi.org/10.1038/s41598-020-72620-4
- Sanabria-Moreno AM, James Peter JJ, Hjerde E, et al., 2021, Shotgun-metagenomics based prediction of antibiotic resistance and virulence determinants in Staphylococcus aureus from periprosthetic tissue on blood culture bottles. Sci Rep, 11(1): 20848. https://doi.org/10.1038/s41598-021-00383-7
- Berglund F, Österlund T, Boulund F, et al., 2019, Identification and reconstruction of novel antibiotic resistance genes from metagenomes. Microbiome, 7(1): 52. https://doi.org/10.1186/s40168-019-0670-1
- Van Camp PJ, Haslam DB, Porollo A, 2020, Prediction of antimicrobial resistance in Gram-negative bacteria from whole-genome sequencing data. Front Microbiol, 11: 1013. https://doi.org/10.3389/fmicb.2020.01013
- Razavi M, Marathe NP, Gillings MR, et al., 2017, Discovery of the fourth mobile sulfonamide resistance gene. Microbiome, 5(1): 1–12. https://doi.org/10.1186/s40168-017-0379-y
- Galhano BSP, Ferrari RG, Panzenhagen P, et al., 2021, Antimicrobial resistance gene detection methods for bacteria in animal-based foods: A brief review of highlights and advantages. Microorganisms, 9(5): 923. https://doi.org/10.3390/microorganisms9050923