👤 Valentina Davì

Single Particle Tracking (SPT) is a powerful technique for elucidating the dynamic behaviours of macromolecules within live cells. However, SPT's application to subcellular environments is hampered by the error-proneness of tracking at high particle velocities and densities and the lack of tools to assess trajectory reliability. Here, we introduce FidlTrack, a methodology that benchmarks and improves SPT fidelity. It contains three modules: a parameter optimiser that uses synthetic ground truth SPT data to determine the fidelity-maximising experimental and tracking settings; Structure-aware tracking, that exploits the information provided by organelle structures to constrain particle tracking algorithms; And a tracking quality evaluator that detects, quantifies and removes error-prone ambiguous track segments. Together these tools allow the rational design of SPT experiments, resolving the motion in tight and convoluted organelles, and provide up to 2-fold enrichment in accurate data. We showcase FidlTrack's utility for reliably tracking proteins in the cytosol, mitochondria and endoplasmic reticulum (ER). Further, we demonstrate its efficacy by analysing ER protein dynamics at exit sites, resolving BACE1 amyloidogenic cleavage of the amyloid precursor protein and characterising the spatiotemporal binding dynamics of an ER-targeted intrabody. FidlTrack is provided as a universal open-access platform that can be incorporated into any SPT pipeline. Show less

Hypertrophic cardiomyopathy (HCM) is mainly associated with myosin, heavy chain 7 (MYH7) and myosin binding protein C, cardiac (MYBPC3) mutations. In order to better explain the clinical and genetic heterogeneity in HCM patients, in this study, we implemented a target-next generation sequencing (NGS) assay. An Ion AmpliSeq™ Custom Panel for the enrichment of 19 genes, of which 9 of these did not encode thick/intermediate and thin myofilament (TTm) proteins and, among them, 3 responsible of HCM phenocopy, was created. Ninety-two DNA samples were analyzed by the Ion Personal Genome Machine: 73 DNA samples (training set), previously genotyped in some of the genes by Sanger sequencing, were used to optimize the NGS strategy, whereas 19 DNA samples (discovery set) allowed the evaluation of NGS performance. In the training set, we identified 72 out of 73 expected mutations and 15 additional mutations: the molecular diagnosis was achieved in one patient with a previously wild-type status and the pre-excitation syndrome was explained in another. In the discovery set, we identified 20 mutations, 5 of which were in genes encoding non-TTm proteins, increasing the diagnostic yield by approximately 20%: a single mutation in genes encoding non-TTm proteins was identified in 2 out of 3 borderline HCM patients, whereas co-occuring mutations in genes encoding TTm and galactosidase alpha (GLA) altered proteins were characterized in a male with HCM and multiorgan dysfunction. Our combined targeted NGS-Sanger sequencing-based strategy allowed the molecular diagnosis of HCM with greater efficiency than using the conventional (Sanger) sequencing alone. Mutant alleles encoding non-TTm proteins may aid in the complete understanding of the genetic and phenotypic heterogeneity of HCM: co-occuring mutations of genes encoding TTm and non-TTm proteins could explain the wide variability of the HCM phenotype, whereas mutations in genes encoding only the non-TTm proteins are identifiable in patients with a milder HCM status. Show less