Machine learning and laboratory experiments have given scientists insights into the different languages bacteria use to communicate. By understanding how bacteria interact and under what circumstances their communication is disrupted, researchers can solve problems related to drug-resistant bacteria and advance biocomputing technologies.
In an earlier project, the researchers found that disrupting bacterial communication is an effective way to combat multidrug-resistant bacteria. The team's research shows that interfering with bacterial communication by blocking these molecules can reduce inflammation and make bacteria more vulnerable to antibiotics.
Deciphering the language of bacteria: a new frontier
Now, researchers have taken a closer look at the bacteria's communication language. They used a combination of machine learning and wet lab experiments to study all approximately 170 known bacterial languages. Through their analysis, the researchers learned about the similarities and differences between bacterial languages, which can be used to both destroy harmful bacteria and build useful "bacterial logic circuits."
The first step was to conduct a machine learning analysis to group bacterial languages based on their molecular structure. The analysis showed that the languages in these groups were more similar to each other than to the languages in other groups. This is equivalent to human languages: English, French, and Dutch, for example, belong to one category of languages, while Arabic and Hebrew belong to another.
Bacteria understood and misunderstood: key findings
Next, the research team experimentally demonstrated that the bacteria can understand the relevant language to a certain extent. "We performed a 'bacterial language check' and found that bacteria that speak very similar languages can understand each other, just as the Dutch can understand some German. We also tested communication between bacteria that speak very different languages and found that they couldn't understand each other at all - just like a conversation between Finnish, Dutch and Arabic speakers wouldn't go anywhere," said Christopher Jonkergouw, a doctoral student who led the study.
Using these tools, the researchers demonstrated that we can accurately estimate the connections between bacterial languages and predict whether they can be understood. The findings are valuable for further refining the research team's new treatments, but also have implications for biotechnology - bacterial languages could be used to coordinate tasks between groups in bacterial communities and even be used in bacterial microprocessors.
References: "Exploration of Chemical Diversity in Prokaryotic Intercellular Quantitative Sensing Signaling Systems" co-authored by Christopher Jonkergouw, Pihla Savola, Ekaterina Osmekhina, Joerivan Strien, Piotr Batys and Markus B. Linder, October 25, 2023, "Angewandte Chemie International Edition".
DOI:10.1002/anie.202314469
Compiled source: ScitechDaily