On the mechanism of antibiotic resistance and fecal microbiota transplantation

Xiaxia Kang; Jie Yan; Fan Huang; Ling Yang; Xiaxia Kang; Jie Yan; Fan Huang; Ling Yang

doi:10.3934/mbe.2019354

Mathematical Biosciences and Engineering

2019, Volume 16, Issue 6: 7057-7084. doi: 10.3934/mbe.2019354

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On the mechanism of antibiotic resistance and fecal microbiota transplantation

1.
School of Mathematical Sciences, Soochow University, Suzhou 215006, P. R. China
2.
Center for Systems Biology, Soochow University, Suzhou 215006, P. R. China
3.
Mathematics Application Joint Laboratory of Soochow University and Suzhou Jiaoshi Intelligence Technology Co., Ltd, Soochow University, Suzhou 215006, P. R. China

Received: 05 June 2019 Accepted: 25 July 2019 Published: 01 August 2019

Antibiotic resistance is a growing threat to human health and is caused by mainly the overuse of antibiotics in clinical medicine. Clinically, drug resistance emerges after a series of antibiotic treatments, implying that each treatment changes the intestinal flora composition and the accumulations of these changes induce the resistance. But mathematically, this cumulative effect cannot be achieved by a general population model, because the system will return to its pre-treatment state (an isolated steady state) after each cure. Based on the fact that sensitive bacteria and resistant bacteria are similar in most respects except their reactions to antibiotics, we developed a mathematical model with a specific phase-space structure: instead of isolated points, the steady states of this system compose one-dimensional manifolds (line segments). This structure explains the fundamental mechanism of antibiotic resistance: after antibiotic treatment, the system cannot return to the pretreatment healthy steady state but rather slightly moves along the manifold to a different steady state. Each use of antibiotics can change the ratio of resistant to susceptible pathogens in the host. The change the ratio can persist and accumulate, and finally promotes the emergence of antimicrobial resistance. We also assessed key factors (such as pathogen composition, the amount and composition of beneficial bacteria, medication duration and bactericidal rates of drugs) influencing the development of drug resistance. In addition, we clarified how fecal microbiota transplantation affects the treatment of antibiotic-resistant infections. The effect is essentially a transfer towards the healthy state in the phase space. Finally, based on the mechanisms revealed by the mathematical models, we suggested some strategies to delay or prevent the emergence of drug resistance. These findings not only provide a solid theoretical basis for the treatment of antimicrobial resistance, but also inspire clues to the phenomenon of drug resistance.
- drug resistance,
- fecal microbiota transplant,
- pathogens,
- bistability,
- dynamic model
Citation: Xiaxia Kang, Jie Yan, Fan Huang, Ling Yang. On the mechanism of antibiotic resistance and fecal microbiota transplantation[J]. Mathematical Biosciences and Engineering, 2019, 16(6): 7057-7084. doi: 10.3934/mbe.2019354

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Abstract

Antibiotic resistance is a growing threat to human health and is caused by mainly the overuse of antibiotics in clinical medicine. Clinically, drug resistance emerges after a series of antibiotic treatments, implying that each treatment changes the intestinal flora composition and the accumulations of these changes induce the resistance. But mathematically, this cumulative effect cannot be achieved by a general population model, because the system will return to its pre-treatment state (an isolated steady state) after each cure. Based on the fact that sensitive bacteria and resistant bacteria are similar in most respects except their reactions to antibiotics, we developed a mathematical model with a specific phase-space structure: instead of isolated points, the steady states of this system compose one-dimensional manifolds (line segments). This structure explains the fundamental mechanism of antibiotic resistance: after antibiotic treatment, the system cannot return to the pretreatment healthy steady state but rather slightly moves along the manifold to a different steady state. Each use of antibiotics can change the ratio of resistant to susceptible pathogens in the host. The change the ratio can persist and accumulate, and finally promotes the emergence of antimicrobial resistance. We also assessed key factors (such as pathogen composition, the amount and composition of beneficial bacteria, medication duration and bactericidal rates of drugs) influencing the development of drug resistance. In addition, we clarified how fecal microbiota transplantation affects the treatment of antibiotic-resistant infections. The effect is essentially a transfer towards the healthy state in the phase space. Finally, based on the mechanisms revealed by the mathematical models, we suggested some strategies to delay or prevent the emergence of drug resistance. These findings not only provide a solid theoretical basis for the treatment of antimicrobial resistance, but also inspire clues to the phenomenon of drug resistance.

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