The rise of methicillin-resistant Staphylococcus aureus (MRSA) infections has gained concern throughout the world over the past decades. Alternative therapeutic agents to antibiotics are rapidly growing to impede the proliferation of MRSA-caused infections. Lately, synthetic biology techniques have developed whole-cell biosensors by designing gene circuitry capable of sensing quorum-sensing (QS) molecules of pathogens and triggering expression of an antimicrobial moiety that kills MRSA and therefore prevents its further proliferation. Here, an E. coli was engineered in silico to act as a whole-cell biosensor that senses QS molecules from MRSA and triggers the expression of a bacteriocin that kills MRSA. To achi... More
The rise of methicillin-resistant Staphylococcus aureus (MRSA) infections has gained concern throughout the world over the past decades. Alternative therapeutic agents to antibiotics are rapidly growing to impede the proliferation of MRSA-caused infections. Lately, synthetic biology techniques have developed whole-cell biosensors by designing gene circuitry capable of sensing quorum-sensing (QS) molecules of pathogens and triggering expression of an antimicrobial moiety that kills MRSA and therefore prevents its further proliferation. Here, an E. coli was engineered in silico to act as a whole-cell biosensor that senses QS molecules from MRSA and triggers the expression of a bacteriocin that kills MRSA. To achieve this functionality, biosensor and bacteriocin modules were constructed and assembled into a vector. Both modules were codon-optimized to increase the yield production of the recombinant proteins. We then demonstrate in silico that the construction of a dual biosensor-killer plasmid, which holds two genetical modules known as biosensor and bacteriocin modules, enables the recombinant host to sense QS molecules from MRSA. Our designed whole-cell biosensor demonstrates in silico its ability to produce and secrete the bacteriocin as a function of the external concentration of autoinducer peptide from MRSA. These in silico results unravel the possibility of designing antimicrobial smarter therapeutics against resistant pathogens.
