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Schiltz, R. L.

Publications and source records attributed to Schiltz, R. L..

2 recordsLinked to original sources

QuantiTrack: A unified software to study protein dynamics in living cells

Linking the spatiotemporal dynamics of proteins in live cells to biological function is a fundamental challenge in biology. Single molecule tracking (SMT) has emerged as a powerful technique to investigate protein dynamics at the single molecule level. However, SMT analysis often requires expertise in biophysical modeling and programming, and integrating results from different analyses can be challenging. To address these barriers, we developed QuantiTrack: a MATLAB-based SMT analysis software with a simple graphical user interface. This provides a much-needed end-to-end solution where a user can load a movie, detect and track single molecules, and perform complementary downstream analyses within a standardized workflow. QuantiTrack includes quantitative metrics for selecting detection and tracking parameters and troubleshooting experimental design, and includes a detailed step-by-step User Guide. We used simulations to demonstrate how signal intensity, labeling density, and motion blur affect detection and tracking fidelity. Using multi-state simulations, we further benchmarked complementary methods to identify distinct mobility states from heterogeneous trajectory populations. Finally, we applied QuantiTrack to real experimental data where we address how the glucocorticoid receptor (GR), a hormone-regulated transcription factor, responds to treatment and washout of its cognate hormone. Hormone washout results in rapid (in minutes) downregulation of GR target genes to basal levels. By integrating complementary analyses within QuantiTrack, we showed that hormone washout substantially reduced the bound fraction of GR, its occupancy in the mobility state associated with GR activation, and dwell times. Together, these analyses showcase QuantiTrack as an integrated platform for extracting biologically meaningful measurements from single molecule trajectories.

biophysics↗

Single-molecule tracking reveals two low-mobility states for chromatin and transcriptional regulators within the nucleus

How transcription factors (TFs) navigate the complex nuclear environment to assemble the transcriptional machinery at specific genomic loci remains elusive. Using single-molecule tracking, coupled with machine learning, we examined the mobility of multiple transcriptional regulators. We show that H2B and ten different transcriptional regulators display two distinct low-mobility states. Our results indicate that both states represent dynamic interactions with chromatin. Ligand activation results in a dramatic increase in the proportion of steroid receptors in the lowest mobility state. Mutational analysis revealed that only chromatin interactions in the lowest mobility state require an intact DNA-binding domain as well as oligomerization domains. Importantly, these states are not spatially separated as previously believed but in fact, individual H2B and TF molecules can dynamically switch between them. Together, our results identify two unique and distinct low-mobility states of transcriptional regulators that appear to represent common pathways for transcription activation in mammalian cells.

biophysics↗