Fighting superbugs with mathematical models

Some infectious bacteria have developed resistance to antibiotics. Mathematical models could help design alternative treatments to overcome them.

Antibiotic resistance is considered one of the main threats to global public health, food security (animal health and agriculture) and development.

Antibiotics are substances that serve as drugs to prevent and treat infections caused by bacteria. Their job is to kill or stop the growth of bacteria; the current problem is that they are no longer effective, which jeopardizes the progress of modern medicine.

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In 2019 alone, about 4.9 million deaths associated with antimicrobial resistance and 1.27 million direct deaths were counted worldwide.

By 2050 it was estimated to rise to 10 million per year, “but it could be many more because the current COVID-19 pandemic aggravated the problem,” stated Dr. María Jiménez Martínez, an academic at the UNAM School of Medicine.

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What is antibiotic resistance?

When bacteria evade the mechanisms of action of antibiotics, they are considered to have achieved resistance. When this happens, the resistant bacteria continue to cause infection. When they resist several types of antibiotics, they are considered “superbugs” because they are multidrug resistant.

Every year, 480,000 people develop multidrug-resistant tuberculosis.

Multidrug resistance is particularly serious when the patient is hospitalized, in critical condition or in danger of death because they are unable to stop the infection that can compromise the entire system and vital organs.

“Just as there are different types of antibiotics, the mechanisms of resistance are also diverse. For example, there are several organisms that secrete enzymes to degrade the antibiotic; another way are flow pumps, which are proteins that actively transport antibiotic molecules from inside the cell to the outside, decreasing the internal concentration of the antibiotic; there can also be changes in the permeability of the membrane that make the antiobiotic no longer able to enter the cell, among others”, says Dr. Ayari Fuentes, who studied the sequential strategies of antibiotic use in the evolution of resistance during her postdoctoral studies at the Department of Biosciences of the University of Exeter, England.

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Basic science and bacteria

A major challenge in the problem of antibiotic resistance is that no new ones are being generated and the ones we have are no longer fully serving.

“Knowledge is being generated to understand more about the combinations between antibiotics, which ones are good and which ones are harmful in order to be able to design better treatments. It is not that from all this basic science there is an immediate leap to the clinic, but finally all the technology requires the basis and the design that is done in basic science,” the researcher clarifies.

The United Nations Educational, Scientific and Cultural Organization proposed 2022 as the International Year of Basic Sciences for Sustainable Development, in which it seeks to highlight the links of the contributions of basic sciences with the scope of the Sustainable Development Goals (SDGs) adopted in 2015 by UN member countries.

Among the challenges is ensuring Health and well-being (SDG 3). It is believed that it will depend on the knowledge of fundamental biology with the preservation and study of Life on Earth (SDG 15).

Precisely, one of the great concerns of antibiotic resistance is the ability of bacteria to survive treatments and spread resistance genes to other generations and even transmit them to other organisms horizontally, with adverse effects on pharmacology and health.

Mathematics to understand biology

Dr. Ayari Fuentes studied Physics at the Faculty of Sciences of the UNAM, did doctoral studies at the Department of Mathematics at Imperial College London and the Department of Biology at the University of Bath postulating mathematical models of cooperative behavior in populations of microbes.

The focus of the Systems Biology and Synthetic Biology Laboratory at UNAM’s Genomic Sciences Center is to combine mathematical models, experimental evolution and microfluidic techniques to study the effect of bacteria and antibiotics on different time scales and environments.

“Mathematics is a perfect abstraction to try to test hypotheses of things that are essential in processes, without having to include all the inherent complexity of biology, of the bacteria themselves. Often, mathematical models inform us of trends, where it could go or where the answer is, for things we want to do in experimental practice.”

Theoretical models to the rescue

The biomathematics specialist explains that there is mathematical theory that has already been developed, for example, that based on population genetics models that predict bacterial growth, and now theoretical and experimental models are also being built in which bacteria are analyzed in different contexts in the presence of antibiotics.

“With theoretical models we can apply hypotheses that might be difficult in experimental models, for example turning off certain genes, or doing thousands of repetitions of an experiment, and see if this influences antibiotic resistance.”

Understanding the dynamics of bacterial populations could help design better antibiotic treatments or other ways to defeat the bacteria that cause the infections and diseases we are so concerned about in health preservation.