Analysis of changes in antibiotic resistance in the human body using an in vitro digestion model incorporating human gut microbiota
Seung Yun Lee,
Da Young Lee,
Hea Jin Kang,
Seung Hyeon Yun,
Ermie Jr. Mariano,
Juhyun Lee,
Jong Hyuk Kim,
Sun Jin Hur
Affiliations
Seung Yun Lee
Division of Applied Life Science (BK21 Four), Gyeongsang National University, Jinju, 52725, South Korea; Institute of Agriculture & Life Science, Gyeongsang National University, Jinju, 52725, South Korea
Da Young Lee
Department of Animal Science and Technology, Chung-Ang University, Anseong, 17546, South Korea
Hea Jin Kang
Department of Animal Science and Technology, Chung-Ang University, Anseong, 17546, South Korea
Seung Hyeon Yun
Department of Animal Science and Technology, Chung-Ang University, Anseong, 17546, South Korea
Ermie Jr. Mariano
Department of Animal Science and Technology, Chung-Ang University, Anseong, 17546, South Korea
Juhyun Lee
Department of Animal Science and Technology, Chung-Ang University, Anseong, 17546, South Korea
Jong Hyuk Kim
Department of Animal Science, Chungbuk National University, Cheongju, 28644, South Korea
Sun Jin Hur
Department of Animal Science and Technology, Chung-Ang University, Anseong, 17546, South Korea; Corresponding author.
Residual antibiotics may affect human health by increasing challenges related to infection treatment due to antibiotic resistance development. Hence, determining whether residual antibiotics in the body can lead to antibiotic resistance is important. We developed a model to predict possible antibiotic resistance caused by residual antibiotics by simulating human digestion in vitro. Increased antibiotic resistance was found to be dependent on the digestion process. Ethical prediction of antibiotic resistance using fewer animals and no humans was possible by simulating the internal environment. Thus, preliminary studies to monitor antibiotic resistance that can affect human health may be safely conducted using this model.
