Home Products Machine Learning Uncovers New Ways to Kill Bacteria With Non-Antibiotic Drugs : ScienceAlert

Machine Learning Uncovers New Ways to Kill Bacteria With Non-Antibiotic Drugs : ScienceAlert

by Universalwellnesssystems

Human history has changed forever discovery of antibiotics Infectious diseases such as pneumonia, tuberculosis, and sepsis were widespread and deadly until penicillin made them treatable.

Surgical procedures that once carried a high risk of infection have become safer and more routine. Antibiotics marked a moment of scientific triumph that transformed medical practice and saved countless lives.

But antibiotics come with their own caveats. Overuse can cause bacteria to develop resistance to these drugs. The World Health Organization estimates that these superbugs are responsible. 1.27 million people died worldwide The threat increased in 2019 and is likely to increase the threat to global public health in the coming years.

New discoveries are helping scientists address this challenge in innovative ways. According to research, almost a quarter Some drugs that are not usually prescribed as antibiotics, such as those used to treat cancer, diabetes, and depression, can kill bacteria at the doses typically prescribed to people.

Understanding the mechanisms underlying how certain drugs become toxic to bacteria can have far-reaching implications for medicine. If non-antibiotics target bacteria differently than standard antibiotics, they could provide clues for the development of new antibiotics.

However, if non-antibiotics kill bacteria in a similar way to known antibiotics, long-term use of antibiotics, such as in the treatment of chronic diseases, can inadvertently promote antibiotic resistance.

among us Recently published researchMy colleagues and I have developed a new machine learning method that not only helps us identify how non-antibiotics kill bacteria, but also finds new bacterial targets for antibiotics.

Mycobacterium tuberculosis is one of many microbial species that have developed resistance to multiple antibiotics. (NIAID/Flickr, (CC BY)

A new way to kill germs

Many scientists and doctors around the world are working on the problem of drug resistance. including me and my colleagues mitchell institute At Masachan University of Medicine. We use bacterial genetics to study which mutations make bacteria more resistant or sensitive to drugs.

When my team and I learned that non-antibiotics have a wide range of antibacterial effects, we became obsessed with the challenge it posed: figuring out how these drugs kill bacteria. I did.

To answer this question, I studied how this might be done using genetic screening techniques recently developed by colleagues. Anticancer drugs target bacteria. This method identifies which specific genes and cellular processes change when bacteria mutate. By monitoring how these changes affect bacterial survival, researchers can deduce the mechanisms these drugs use to kill bacteria.

I have collected and analyzed nearly 2 million cases of toxicity between 200 drugs and thousands of mutant bacteria. Using the machine learning algorithm I developed, Infer similarities between different drugsThey grouped drugs into networks based on how they affected the mutant bacteria.

My map shows the known antibiotics tightly grouped By a known class of killing mechanisms. For example, all antibiotics that target the cell wall (the thick protective layer that surrounds bacterial cells) were grouped together and well separated from antibiotics that interfere with bacterial DNA replication.

Interestingly, when non-antibiotics were added to the analysis, they formed a separate hub from antibiotics. This shows that non-antibiotics and antibiotics kill bacterial cells differently. Although these groupings do not reveal how each drug specifically kills antibiotics, they do indicate that clustered drugs are likely to act in similar ways. .

The final piece of the puzzle – whether we can find new drug targets within bacteria to kill them – came from the work of my colleagues. carmen lee.

She grew hundreds of generations of bacteria exposed to a variety of non-antibiotics commonly prescribed to treat anxiety, parasitic infections, and cancer.

By sequencing the genomes of bacteria that have evolved to adapt to the presence of these drugs, they were able to pinpoint specific bacterial proteins. Triclabendazole – Medications used to treat parasitic infections – aimed at killing bacteria. Importantly, current antibiotics typically do not target this protein.

Additionally, they discovered that triclabendazole and two other non-antibiotics that use a similar mechanism also target the same protein. This demonstrated the power of my drug similarity map to identify drugs with similar lethal mechanisms, even if that mechanism was not yet known.

Supporting antibiotic discovery

Our findings present many opportunities for researchers to study how non-antibiotic drugs work differently than standard antibiotics. Our method of mapping and testing drugs also has the potential to address critical bottlenecks in antibiotic development.

The search for new antibiotics usually requires the commitment of considerable resources. Screen thousands of chemicals It’s about killing germs and understanding how they work. Most of these chemicals have been found to work similarly to existing antibiotics and are being discarded.

Our research shows that combining genetic screening and machine learning can help researchers discover chemical needles in the haystack that can kill bacteria in a way never used before. Masu.

There are many different ways to kill bacteria that we have not yet taken advantage of, and there is still a path forward for us to take to combat the threat of bacterial infections and antibiotic resistance.conversation

mariana noto guillenPhD Systems Biology Candidate, Masachan University of Medical Sciences

This article is republished from conversation Under Creative Commons License.read Original work.

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