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MOSCOW, April 5. /TASS /.Researchers from the Scientific Research Institute of Physical-Chemical Medicine, MIPT (Moscow Institute of Physics and Technology), M&S Decisions company and the Yandex research department have built a computer model of the interaction between different bacteria, and between bacteria and the gut wall. This has led them to explain how antibiotic-resistant microbes develop and spread, MIPT said on Tuesday.
"In our study, we used a simple modelling method - Agent Based Modelling (ABM) - to recreate the processes involving bacteria that take place in the gut and explain some interesting effects when resistivity occurs," said Dmitry Alexeyev, deputy head of MIPT’s Laboratory of Systems Biology and the corresponding author of the study.
Russian scientists built a model of the interaction between two types of bacteria and the intestine and they determined what happens when antibiotics are taken that kill a large number of microorganisms. They were interested in a number of important issues - firstly, the speed at which the number of bacteria was restored after antibiotic therapy. Secondly, the scientists were interested in finding what proportion of bacteria was not affected by antibiotics, and thirdly the model described in detail the process of feedback between bacteria and the intestinal wall, which produces and absorbs certain substances affecting the number of bacteria and their "state of health".
Schematic representation of different Feedbacks’ mechanismsMIPT press office
Using the model, the researchers were able to prove that even after antibiotic therapy there may be more bacteria that are sensitive to the effects of the antibiotic drug than those that are resistant to it. This conclusion may seem contradictory, but it is in fact true: the resistance to antibiotics comes at a price to the microorganisms. By altering their biochemical properties or using up resources on additional chemical reactions, bacteria inevitably lose out on efficiency: they consume "food" slower, divide slower and therefore it is certainly not the case that these microbes will be able to drive out ordinary microorganisms. The fact that we now have increasing numbers of antibiotic-resistant strains is important both from a scientific, as well as a medical point of view.
The model also enabled the scientists to observe the location of strains in the gut and how their position changes after various substances are produced by the intestinal wall or bacteria. The visualization of the model showed that the spatial structure is a key factor that helps bacteria to survive and adapt to the changing conditions of their environment. The researchers believe that further studies in this area will be useful to understand the fundamental causes of the emergence of antibiotic-resistant bacteria, and to develop drugs targeted at pathogens.
According to one of the authors of the study - the Head of MIPT’s Department of Discrete Mathematics and Head of the Department of Theoretical and Applied Research at Yandex, Andrei Raigorodsky, mathematicians became involved because the task required, among other things, an expert opinion in graph theory, which was actively used as part of the project. "Mathematicians are interested in applying their methods to problems in biology and medicine. My research department at MIPT and Yandex are actively using "complex networks" that are found everywhere in our environment and society: social networks, and the Internet itself, networks in economics, and networks in biology too. I am pleased that our collaboration has resulted in an interesting and informative publication, and I look forward to the topic being developed further."
The human intestine contains trillions of different bacteria, which together are called the microbiota. Bacteria protect us from harmful microorganisms, produce digestive enzymes, and help the immune system to function normally. Many diseases, such as obesity, Crohn’s disease, colon cancer, and other inflammatory processes are associated with a change in the gut microbiota.
Research was published in PLOS One