Identification of Novel Toxins Using Machine Learning
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Identification of Novel Toxins Using Machine Learning


New study reveals how bacteria use a special system, like a tiny syringe, to inject toxins into other organisms. This is important because it helps us understand how bacteria interact with hosts and likely with each other. Using artificial intelligence, the researchers identified over 2,000 possible toxins, likely injected by the syringe, some of which could be potentially used as new antimicrobials. By combining AI and microbiology these findings could lead to new ways to treat infections and create new biotechnological tools.

Microscopic Syringes and AI: Scientists Uncover New Bacterial Weapons
In a novel study, featured on the cover of August 2024 volume of Molecular Systems Biology journal, researchers have unveiled new secrets about a fascinating bacterial weapon system that acts like a microscopic syringe. Led by Dr. Asaf Levy from the Hebrew University and collaborators from the Hebrew University and from the University of Illinois Urbana-Champaine, the team has made significant strides in understanding the extracellular contractile injection system (eCIS), a unique mechanism used by bacteria and archaea to inject toxins into other organisms.

Cracking the Bacterial Code with Artificial Intelligence
The eCIS is a 100-nanometer long weapon that evolved from viruses that previously attacked microbes (phages). During evolution these viruses lost their ability to infect microbes and turned into syringes that inject toxins into different organisms, such as insects. Previously, the Levy group identified eCIS as a weapon carried by more than 1,000 microbial species. Interestingly, these microbes rarely attack humans, and the eCIS role in Nature remains mostly unknown. (Geller et al. 2021). However, we know that it loads and injects protein toxins.

The specific proteins injected by eCIS and their functions have long remained a mystery. Before the study we knew about ~20 toxins that eCIS can load and inject. To solve this biological puzzle, the research team developed an innovative machine learning tool that combines genetic and biochemical data of different genes and proteins to accurately identify these elusive toxins. The project resulted in identification of over 2,000 potential toxin proteins.

"Our discovery not only sheds light on how microbes interact with their hosts and maybe with each other, but also demonstrates the power of machine learning in uncovering new gene functions," explains Dr. Levy. "This could open up new avenues for developing antimicrobial treatments or novel biotechnological tools."

New Toxins with Enzymatic Activities against Different Molecules
Using AI technology, the researchers analyzed 950 microbial genomes and identified an impressive 2,194 potential toxins. Among these, four new toxins (named EAT14-17) were experimentally validated by demonstrating that they can inhibit growth of bacteria or yeast cells. Remarkably, one of these toxins, EAT14, was found to inhibit cell signaling in human cells, showcasing its potential impact on human health. The group showed that the new toxins likely act as enzymes that damage the target cells by targeting proteins, DNA or a molecule that is critical to energy metabolism. Moreover, the group was able to decipher the protein sequence code that allow loading of toxins into the eCIS syringe. Recently, it was demonstrated that eCIS can be used as a programmable syringe that can be engineered for injection into various cell types, including brain cells (Krietz et al. 2023). The new findings from the current paper leverage this ability by providing thousands of toxins that are naturally injected by eCIS and the code that facilitates their loading into the eCIS syringe. The code can be transferred into other proteins of interest.

From Microscopic Battles to Medical Breakthroughs
The study's findings could have far-reaching applications in medicine, agriculture, and biotechnology. The newly identified toxins might be used to develop new antibiotics or pesticides, efficient enzyme for different industries, or to engineer microbes that can target specific pathogens. This research highlights the incredible potential of combining biology with artificial intelligence to solve complex problems that could ultimately benefit human health.

"We're essentially deciphering the weapons that bacteria evolved and keep evolving to compete over resources in Nature" adds Dr. Levy. “Microbes are creative inventors and it is fulfilling to be part of a group that discovers these amazing and surprising inventions”.

The study was led by two talented students: Aleks Danov and Inbal Pollin from the department of Plant Pathology and Microbiology, the Institute of Environmental Sciences, and was performed in collaboration with Prof. Tommy Kaplan (School of Computer Science and Engineering) and Dr. Philippos A Papathanos (Department of Entomology) from the Hebrew University of Jerusalem in collaboration with Prof. Brenda A Wilson from University of Illinois Urbana Champaign. The study was funded by the Israeli Science Foundation, Israeli Ministry of Innovation, Science and Technology, Volkswagen Foundation, and a joint seed grant between the two universities.
The research paper titled “Identification of novel toxins associated with the extracellular contractile injection system using machine learning” is now available in Molecular Systems Biology and can be accessed at https://doi.org/10.1038/s44320-024-00053-6

Researchers:
Aleks Danov1, Inbal Pollin1, Eric Moon2, Mengfei Ho2, Brenda A Wilson2, Philippos A Papathanos3, Tommy Kaplan4,5 and Asaf Levy1

Institutions:
1) Department of Plant Pathology and Microbiology, Institute of Environmental Sciences, The Robert H. Smith Faculty of Agriculture, Food & Environment, The Hebrew University of Jerusalem
2) Department of Microbiology, University of Illinois
3) Department of Entomology, Institute of Environmental Sciences, The Robert H. Smith Faculty of Agriculture, Food & Environment, The Hebrew University of Jerusalem
4) School of Computer Science and Engineering, The Hebrew University of Jerusalem
5) Department of Developmental Biology and Cancer Research, Faculty of Medicine, The Hebrew University of Jerusalem
Regions: Middle East, Israel
Keywords: Health, Environmental health, Medical, Applied science, Artificial Intelligence, Science, Life Sciences, Environment - science

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