In Tokyo, they developed a map showing the gradual development of E resistance. coli to an antibiotic which will be very helpful in controlling the bacteria.
Antibiotic resistance, the name given to the phenomenon whereby the bacteria that cause infections evolve so that they are no longer affected by the action of antibiotics, is a global problem. New research from the University of Tokyo has mapped the evolution and natural selection process of Escherichia coli (E. coli) bacteria in the laboratory. These maps, called “Fitness landscapes”, help to better understand the gradual development and resistance characteristics of E. coli to eight different drugs, including antibiotics. The researchers hope their findings and methods will be useful for predicting and controlling E. coli and other bacteria in the future.
There are several types of food poisoning, but a common cause is the growth of bacteria such as E. coli. Most cases of poisoning with this bacteria, although unpleasant, can be managed at home with rest and rehydration. However, in some cases, life-threatening infections can arise. If so, antibiotic medications can be a powerful and effective treatment. If, however, antibiotics are no longer effective, we will again be at risk of serious illnesses due to common pathologies and injuries, even small ones. “Developing methods that can predict and control bacterial evolution is critical to detecting and suppressing the emergence of resistant bacteria. “We have therefore developed an innovative method to predict the evolution of drug resistance using data obtained from laboratory experiments,” said researcher Junichiro Iwasawa.
The researchers used a method called adaptive laboratory evolution to “review the tape” of E. coli evolutionresistant. The method allowed researchers to study the evolution of bacterial strains with specific observable characteristics (called phenotypes) in the laboratory. “While conventional evolution experiments in the laboratory are labor intensive, we mitigated the problem by using an automated culture system previously developed in our laboratory. This allowed us to acquire sufficient data on the phenotypic changes related to the evolution of drug resistance,” explained Iwasawa. “By analyzing the acquired data, using a machine learning method, we were able to outline the fitness landscape underlying the evolution of E. coli drug resistance .”
Fitness landscapes look like 3D topo maps. The mountains and valleys on the map show the gradual development of resistance of E. coli to tetracycline , a common antibiotic used to treat a wide variety of infections. The bacteria found on top of the ‘mountains’ (in red) are in the best ‘fitness’ and most likely to resist the effects of the antibiotic. Iwasawa explained, “The fitness scenario coordinates represent internal states of the organism, such as gene mutation patterns (genotypes) or drug resistance profiles (phenotypes), etc. The fitness landscape thus describes the relationshipbetween the internal states of the organism and the corresponding levels of fitness.
The research team believes that the evolution of antibiotic resistance mapped in this study and the methods developed in the process will be useful for predicting and controlling not only E. coli, but also other forms of microbial evolution. The researchers hope this will lead to future studies that may find ways to suppress drug-resistant bacteria and contribute to the development of microbes useful for bioengineering and agriculture.