University of São Paulo: Analysis of gut microbiota suggests that antibiotics in livestock intensify bacterial resistance

A study developed at the Institute of Mathematical and Computer Sciences (ICMC) at USP in São Carlos used Artificial Intelligence and machine learning to analyze the genetic composition of the intestinal flora of people with different types of diet, including current and pre-existing data. industrial. The results point to a greater amount of bacteria with antibiotic resistance genes in meat consumers from industrial and intensive farming, that is, produced on a large scale and for commercial purposes. This was verified both for those who adopt an omnivorous (varied) and ketogenic (with limited carbohydrates and higher consumption of protein and fat). The research raises the alarm for the use of antibiotics in livestock as a factor for the emergence of superbugs, which can resist treatment even with the use of a large amount and variety of antibiotics.

Jonas Coelho Kasmanas, PhD student at ICMC and Leipzig University and author of the research, received an award from the Helmholtz Association of German Research, the largest scientific organization in Germany, for his thesis Analysis and Classification of Human Microbiomes: detection of bioindicators and optimization through machine learning , which was supported by Cepid-CeMEAI and is available here .

The study was dedicated to analyzing the influence of food on the so-called intestinal microbiome, formed by the set of microorganisms present there and the environment in which they are inserted – in this case, the digestive tract. “The human intestinal microbiome is very rich, and it directly influences our health”, explains Kasmanas to Jornal da USP , mentioning the existence of studies that associate psychiatric problems and certain types of cancer with this microbiome.

Molecular biology data is naturally very complex and the analysis of a single genome is quite complicated. “It is even more challenging to study a microbiome, which is made up of multiple genomes from different viruses and bacteria, each with its own genetic material. To give you an idea, we have more bacterial genes in our bodies than human genes”, comments the researcher. To overcome this difficulty, the study used Artificial Intelligence and machine learning to store and process the information from the hundreds of samples analyzed.

The research sought to investigate the presence or absence of specific genes to differentiate the microbiome of the researched individuals. Another objective was to evaluate the possibility of manipulating this structure to optimize people’s health, with therapeutic and diagnostic potential.

“We hypothesized that modern diets that include meat and commercial agriculture could potentially be linked to greater exposure to bacteria that have been subjected to antibiotics,” explains Kasmanas. This would also be related to the imbalance of the gut microbiome and the presence of antibiotic-resistant microorganisms, such as superbugs.

The main source of data used in the study were public repositories, which are sample banks available around the world. After collection, sample information was standardized and selected according to criteria such as age, health conditions, country of origin and the diet adopted by the patient, such as omnivorous, vegetarian, vegan or ketogenic.

Fossilized human feces samples were also selected to integrate the research, to enable the comparison between contemporary and pre-industrial food.

After the reconstruction of the microbiomes with machine learning algorithms and data analysis, the bacteria present in the samples were identified from their genes and cataloged according to drug resistance.

The comparison between the samples showed that people who ate meat, such as omnivores, who consume all types of food, and ketogenics, who ingest little amount of carbohydrates and a lot of fat, had a greater amount of bacteria with microbial resistance genes when compared to adepts. of plant-based diets. Similarity was also found between the genes of the fossilized and vegetarian samples, which points to a potential approximation between these diets.

“The Superbugs Pandemic”: Ways to Avoid a Greater Disaster
Bacteria that have mutated and are resistant to available antibiotics end up thriving and multiplying, whereas new antibiotics are not developed at the same rate.

According to the expert, the results of the study are preliminary, but it is possible to find important conclusions to reassess food production, such as the relationship between the consumption of meat of industrial origin and the greater tendency to resistance of microorganisms. “Knowing these data, it is necessary to rethink the way we do farming and the indiscriminate use of antibiotics in animals for consumption and pesticides in agriculture”, he comments.

Kasmanas reinforces that microbial resistance is already a relevant public health issue. Superbugs, which evolve to circumvent the mechanism of action of conventional antibiotics, cause thousands of deaths worldwide – and the trend is that this number will increase more and more in the coming years.

A study published in the journal The Lancet indicated that 1.2 million people died as a result of superbugs in 2019 and, if no action is taken, the world projection for 2050 is 10 million deaths per year, surpassing cancer, AIDS. and malaria . Some experts refer to the phenomenon as the “ superbug pandemic ” .

“It is a serious problem that needs to be addressed as such. If there is an indicator that exposure to current diets based on industrial production accentuates the danger, it is urgent to redesign the way of food production and make the population aware of the excessive and inappropriate use of antibiotics, whether in agriculture or for personal treatment”, he says.

Computer science and microbiology need to be improved to allow for more adequate data analysis in metagenome matters. Kasmanas hopes that the research will encourage more scientists to study the topic and, above all, that new studies will be carried out with even larger databases to reinforce the conclusions. “We need to increase the scale of analysis to take concrete action on this issue.”

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