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Pawelek, K.

Publications and source records attributed to Pawelek, K..

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Assessment of the effects of transthyretin peptide inhibitors in Drosophila models of neuropathic ATTR

Transthyretin amyloidosis (ATTR) is a fatal disease caused by the systemic aggregation and deposition of transthyretin (TTR), a blood transporter that is mainly produced in the liver. TTR deposits are made of elongated amyloid fibrils that interfere with normal tissue function leading to organ failure. The current standard care for hereditary neuropathic ATTR is liver transplantation or stabilization of the native form of TTR by tafamidis. In our previous work, we explored an additional strategy to halt protein aggregation by capping pre-existing TTR fibrils with structure-based designed peptide inhibitors. Our best peptide inhibitor TabFH2 has shown to be effective at inhibiting not only TTR aggregation but also amyloid seeding driven by fibrils extracted from ATTR patients. Here we evaluate the effects of peptide inhibitors in two Drosophila models of neuropathic ATTR and compared their efficacy with diflunisal, a protein stabilizer currently used off-label for the treatment of ATTR. Our peptide inhibitor TabFH2 was found the most effective treatment, which resulted in motor improvement and the reduction of TTR deposition. Our in vivo study shows that inhibiting TTR deposition by peptide inhibitors may represent a therapeutic strategy for halting the progression of ATTR.\n\nSIGNIFICANCE STATEMENTFamilial Amyloid Polyneuropathy (FAP) is a hereditary condition caused by the deposition of transthyretin (TTR) in nerves. Marked by progressive deficit and disability, FAP has no cure and limited therapeutic options. The replacement of the production source of mutant TTR by liver transplantation and the stabilization of native TTR by compounds, current lines of treatment, often fail to halt disease progression. Previously, we discovered that two segments of TTR drive amyloid deposition, and designed structure-based peptide inhibitors. Here we evaluate these peptide inhibitors in FAP models of Drosophila. The most efficient inhibitor resulted in an improvement of locomotor abilities and a reduction of TTR deposition. This study points to peptide inhibitors as a potential therapeutic strategy for FAP.

neuroscience

Exploring the impact of inoculum dose on host immunity and morbidity to inform model-based vaccine design

BackgroundVaccination is an effective method to protect against infectious diseases. An important consideration in any vaccine formulation is the inoculum dose, i.e., amount of antigen or live attenuated pathogen that is used. Higher levels generally lead to better stimulation of the immune response but might cause more severe side effects and allow for less population coverage in the presence of vaccine shortages. Determining the optimal amount of inoculum dose is an important component of rational vaccine design. A combination of mathematical models with experimental data can help determine the impact of the inoculum dose.\n\nMethodsWe designed mathematical models and fit them to data from influenza A virus (IAV) infection of mice and human parainfluenza virus (HPIV) of cotton rats at different inoculum doses. We used the model to predict the level of immune protection and morbidity for different inoculum doses and to explore what an optimal inoculum dose might be.\n\nResultsWe show how a framework that combines mathematical models with experimental data can be used to study the impact of inoculum dose on important outcomes such as immune protection and morbidity. We find that the impact of inoculum dose on immune protection and morbidity depends on the pathogen and both protection and morbidity do not always increase with increasing inoculum dose. An intermediate inoculum dose can provide the best balance between immune protection and morbidity, though this depends on the specific weighting of protection and morbidity.\n\nConclusionsOnce vaccine design goals are specified with required levels of protection and acceptable levels of morbidity, our proposed framework which combines data and models can help in the rational design of vaccines and determination of the optimal amount of inoculum.

systems biology