Bacteria are becoming a promising delivery system for treating human diseases. Here, we have engineered the genome-reduced human lung pathogen, Mycoplasma pneumoniae to create a bacterial chassis that could be used to treat bacterial infections. This bacterium does not recombine, has an unique genetic code that prevents gene transfer to other bacteria and does not have a cell wall so it can be used in combination with other antibiotics. We have developed a new system to allow genome engineering of this bacterium which could be used with other bacteria with poor homologous recombination. After removal of pathogenic factors, we have shown that the chassis is attenuated in a mammary gland mice model and in mice lungs. We have then developed synthetic promoters, to ensure high levels of expression, and we have identified endogenous peptide signal sequence that when fused to heterologous proteins results in efficient secretion. We have introduced antibiofilm and bactericidal enzymes in the chassis and we have shown that our chassis could effectively dissolve S. aureus biofilms formed in catheters in vitro, ex vivo and in vivo as well as eliminate the S. aureus infection. We have also shown that the engineered chassis can be used to prevent P. aeruginosa colonization of mice lungs. Quite important our engineered bacteria can be used in combination with antibiotics affecting cell wall formation in gram positive and negative bacteria. Also, we have shown that the engineered chassis can dissolve biofilms made by P. aeruginosa in endotracheal tube (ETT) of intubated patients that were at the intensive care units suffering ventilator associated pneumonia (VAP). Based on these results a company termed Pulmobiotics (https://www.pulmobio.com/) has been founded.
Dr. Luis Serrano Pubul’s group is aiming at a quantitative understanding of biological systems to an extent that one is able to predict systemic features and with the hope to rational design and modify their behaviour. This applies to any system comprising biological components that is more than the mere sum of its components, or, in other words, the addition of the individual components results in systemic properties that could not be predicted by considering the components individually. By achieving this objective they are aiming at new global understanding and treatment of human diseases in which the target will not be a single molecule but a network. For this purpose in their group they develop on one hand new software and theoretical approximations to understand complex systems and on the other they do experiments to validate our predictions.
For details of his research and recent publication, please visit HERE
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