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Thompson, M. P.

Publications and source records attributed to Thompson, M. P..

3 recordsLinked to original sources

Protein-Like Polymer for Inhibition of Tau Fibril Propagation in Human-Derived Models of Neurodegeneration

The misfolding, aggregation, and spread of tau protein fibrils underlie tauopathies, a diverse class of neurodegenerative diseases for which effective treatments remain elusive. Among these are corticobasal dementia (CBD) and progressive supranuclear palsy (PSP), canonical examples of 4-repeat (4R) tauopathies characterized by tau isoforms exclusively with four microtubule-binding repeat domains. We target this 4R tau isoform-specific mechanism by focusing on misfolded taus distinctive stem-loop-stem structural motif formed by the junction of the 4R-defining alternatively spliced exon and the adjacent constitutive exon. A synthetic peptide based on this stem-loop-stem sequence can induce aggregation and spread in an isoform-specific manner. Here, we develop a protein-like polymer (PLP) in which multiple copies of this synthetic peptide form a brush-like structure capable of preventing tau aggregation by binding and capping fibril ends in vitro, in human brain organoids, and in cellular models with an EC50 of 105 {+/-} 14 nM. PLPs demonstrate robust activity against fibrils derived from CBD and PSP patient brains and a PS19 mouse tauopathy model. Previous tau-targeted treatments have primarily focused on broad tau clearance, aggregation inhibition, or microtubule stabilization, often lacking isoform specificity and precision. In contrast, this approach targets the 4R tau isoforms unique structural motif, offering a tailored therapeutic intervention for diseases like CBD and PSP. Supported by prior studies showing blood-brain barrier penetrance and safety profiles, this tau-binding PLP offers a promising translational path toward clinical applications in tauopathy treatment.

neuroscience↗

Self-Assembly of Tunable Intrinsically DisorderedPeptide Amphiphiles

Intrinsically disordered peptide amphiphiles (IDPAs) present a novel class of synthetic conjugates that consist of short hydrophilic polypeptides anchored to hydrocarbon chains. These hybrid polymer-lipid block constructs spontaneously self-assemble into dispersed nanoscopic aggregates or ordered mesophases in aqueous solution due to hydrophobic interactions. Yet, the possible sequence variations and their influence on the self-assembly structures is vast and have hardly been explored. Here, we measure the nanoscopic self-assembled structures of four IDPA systems that differ by their amino acid sequence. We show that permutations in the charge pattern along the sequence remarkably alter the headgroup conformation and consequently alters the pH-triggered phase transitions between spherical, cylindrical micelles and hexagonal condensed phases. We demonstrate that even a single amino acid mutation is sufficient to tune structural transitions in the condensed IDPA mesophases, while peptide conformations remain unfolded and disordered. Furthermore, alteration of the peptide sequence can render IDPAs to become susceptible to enzymatic cleavage and induces enzymatically activated phase transitions. These results hold great potential for embedding multiple functionalities into lipid nanoparticle delivery systems by incorporating IDPAs with desired properties.

biophysics↗

A Computational Solution To Improve Biomarker Reproducibility During Long-term Projects

Biomarkers are fundamental to basic and clinical research outcomes by reporting host responses and providing insight into disease pathophysiology. Measuring biomarkers with research-use ELISA kits is universal, yet lack of kit standardization and unexpected lot-to-lot variability presents analytic challenges for long-term projects. During an ongoing two-year project measuring plasma biomarkers in cancer patients, control concentrations for one biomarker (PF) decreased significantly after changes in ELISA kit lots. A comprehensive operations review pointed to standard curve shifts with the new kits, an analytic variable that jeopardized data already collected on hundreds of patient samples. After excluding other reasonable contributors to data variability, a computational solution was developed to provide a uniform platform for data analysis across multiple ELISA kit lots. The solution (ELISAtools) was developed within open-access R software in which variability between kits is treated as a batch effect. A defined best-fit Reference standard curve is modelled, a unique Shift factor \"S\" is calculated for every standard curve and data adjusted accordingly. The averaged S factors for PF ELISA kit lots #1-5 ranged from -0.086 to 0.735, and reduced control inter-assay variability from 62.4% to <9%, within quality control limits. S factors calculated for four other biomarkers provided a quantitative metric to monitor ELISAs over the 10 month study period for quality control purposes. Reproducible biomarker measurements are essential, particularly for long-term projects with valuable patient samples. Use of research-use ELISA kits is ubiquitous and judicious use of this computational solution maximizes biomarker reproducibility.

pathology↗