Researchers discovered how pathogenic bacteria use secret code language for them to be resistant to antibiotics and understanding this code language can help researchers develop new antibiotics in the days to come.
Pathogenic bacteria have the ability to be hidden from the immune system and treatment as they go through an inactive state, where they are not discovered. For many years, researchers at Aarhus University have examined the molecular process that allows bacteria to hide in this way, and recent research suggests that they also utilize code language in their effort to avoid being controlled.
Palindrome Secret Code
A palindrome is a word that reads the same both forwards and backwards, such as the word “kayak.” A team of researchers from Aarhus University, Denmark, under the leadership of Associate Professor Ditlev Egeskov Brodersen, has found out that a high number of pathogenic bacteria make use of cryptic palindromes embedded in the sequence of amino acids in their proteins to decide whether the inactive state should be launched or disrupted.
The findings have been published in the journal Nucleic Acids Research, and include detailed three-dimensional structures of particular cell toxins that are triggered during treatment with antibiotics, and reveal what occurs to them when they attach to specific regions of the DNA of the bacterial cells. The toxins are normally kept in check by their partners, the so-called “anti-toxins,” and the researchers have found that the palindrome codes make the anti-toxins block two toxins simultaneously. The amino acid sequence of the codes binds like key in a lock, and the palindromic sequence is essential since the two toxins to be blocked are turned 180 degrees corresponding to each other.
And also, it appears that such codes are seen in unprecedented numbers among bacteria. In the study of over 4,000 bacterial genomes, the researchers have further shown that up to 25 percent of all known bacteria make use of such codes for resistance. Hence, the research findings denote that a better understanding of the code language of the bacteria is important in maximizing the possibilities of making new antibiotics in the future.
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