Gentamicin and related aminoglycoside antibiotics enter the hair cells of the inner ear through the same channels that detect sound, then get trapped inside and kill the cells, causing permanent hearing loss in an estimated 20–50% of patients who receive them. These antibiotics are among the most effective weapons against life-threatening hospital infections, and their use is increasing because few alternatives exist. The problem is that no strategy currently prevents the collateral damage to hearing. This research aims to change that. The team has already identified how the drugs enter hair cells and trigger cell death. They now want to understand the precise route by which the drugs reach the mitochondria inside the cells, and to characterise a newly discovered repair process that allows hair cells to recover from early damage if drug exposure is brief. The central goal is to develop compounds that compete with aminoglycosides for entry into hair cells, blocking the damage before it starts. If successful, this work could lead to a co-administered drug that prevents deafness in seriously ill patients who need these antibiotics. The research is fundamental cell biology, but with a direct translational aim: turning a mechanistic understanding of drug entry and cellular repair into a practical otoprotective strategy.
View original technical description
Our sense of hearing depends on the correct functioning of hair cells, the cells in the inner ear that convert motion into electrical signals that the brain interprets as sound. The aminoglycoside antibiotics, of which gentamicin is the most widely used, are administered to seriously ill patients in hospital that are at risk from life-threatening infections, in order to try to eradicate the bacteria causing those infections. These antibiotics have the unfortunate side effect of causing hearing loss in an estimated 20-50% of patients. Because of their high efficacy compared to other antibiotics and broad anti-bacterial spectrum the use of these antibiotics is however on the increase and likely to continue. It would therefore be very beneficial to try and develop strategies for preventing the hearing loss caused by these drugs. In our recent research we have identified how aminoglycoside antibiotics enter hair cells in the inner ear, eventually killing them and thus leading to deafness. First, they enter the hair cells via their mechano-electrical transducer channels - these are situated on top of the bundles of 'hairs' or stereocilia on the hair cells, and these channels open and close as sound waves move the stereocilia. Once inside the hair cells, they remain trapped and cannot get out. Then they enter the energy producing machinery in the cell, the mitochondria, by a currently unknown route. We will investigate whether entry is via ion channels in the inner membrane of the mitochondria. After the aminoglycosides have entered them, these mitochondria release proteins (pro-apoptotic factors) that ultimately kill the cells. Before the hair cells are killed though, we found that they form bleb-like membrane protrusions on their surface, on and around the hair bundles. We will investigate whether this is a direct effect of the aminoglycosides or whether this depends on the aminoglycosides first entering the mitochondria. We also found that the hair cells can recover from these membrane 'blebs', provided the exposure to the aminoglycosides is sufficiently short. This indicates the presence of a damage-repair process in the hair cells, which we wish to investigate with a view to making it more effective. One of the main aims of our research is to develop compounds that can compete with the aminoglycoside antibiotics for entry into the hair cells, and that may therefore prevent hair-cell damage and death. If any of these compounds are found to be clinically safe, we hope this may eventually lead to the development of drugs that, when co-administered with aminoglycoside antibiotics, prevent deafness in patients.
Plain English summaries and category classifications on this site are generated by AI and may not perfectly reflect the original research.
Is something wrong? Let us know