Single-particle tracking (SPT) has become an important method to bridge biochemistry and cell biology since it allows direct observation of protein binding and diffusion dynamics in live cells. However, accurately inferring information from SPT studies is challenging due to biases in both data analysis and experimental design. To address analysis bias, we introduce 'Spot-On', an intuitive web-interface. Spot-On implements a kinetic modeling framework that accounts for known biases, including molecules moving out-of-focus, and robustly infers diffusion constants and subpopulations from pooled single-molecule trajectories. To minimize inherent experimental biases, we implement and validate stroboscopic photo-activation SPT (spaSPT), which minimizes motion-blur bias and tracking errors. We validate Spot-On using experimentally realistic simulations and show that Spot-On outperforms other methods. We then apply Spot-On to spaSPT data from live mammalian cells spanning a wide range of nuclear dynamics and demonstrate that Spot-On consistently and robustly infers subpopulation fractions and diffusion constants.

Light-mediated chemical reactions are powerful methods for manipulating and interrogating biological systems. Photosensitizers, compounds that generate reactive oxygen species upon excitation with light, can be utilized for numerous biological experiments, but the repertoire of bioavailable photosensitizers is limited. Here, we describe the synthesis, characterization, and utility of two photosensitizers based upon the widely used rhodamine scaffold and demonstrate their efficacy for chromophore-assisted light inactivation, cell ablation in culture and in vivo, and photopolymerization of diaminobenzidine for electron microscopy. These chemical tools will facilitate a broad range of applications spanning from targeted destruction of proteins to high-resolution imaging.

The worldwide coronavirus disease 2019 pandemic has had devastating effects on health, healthcare infrastructure, social structure, and economics. One of the limiting factors in containing the spread of this virus has been the lack of widespread availability of fast, inexpensive, and reliable methods for testing of individuals. Frequent screening for infected and often asymptomatic people is a cornerstone of pandemic management plans. Here, we introduce 2 pH-sensitive "LAMPshade" dyes as novel readouts in an isothermal Reverse Transcriptase Loop-mediated isothermal AMPlification amplification assay for severe acute respiratory syndrome coronavirus 2 RNA. The resulting JaneliaLAMP assay is robust, simple, inexpensive, and has low technical requirements, and we describe its use and performance in direct testing of contrived and clinical samples without RNA extraction.

To image the accessible genome at nanometer scale in situ, we developed three-dimensional assay for transposase-accessible chromatin-photoactivated localization microscopy (3D ATAC-PALM) that integrates an assay for transposase-accessible chromatin with visualization, PALM super-resolution imaging and lattice light-sheet microscopy. Multiplexed with oligopaint DNA-fluorescence in situ hybridization (FISH), RNA-FISH and protein fluorescence, 3D ATAC-PALM connected microscopy and genomic data, revealing spatially segregated accessible chromatin domains (ACDs) that enclose active chromatin and transcribed genes. Using these methods to analyze genetically perturbed cells, we demonstrated that genome architectural protein CTCF prevents excessive clustering of accessible chromatin and decompacts ACDs. These results highlight 3D ATAC-PALM as a useful tool to probe the structure and organizing mechanism of the genome.

Serotonin plays a central role in cognition and is the target of most pharmaceuticals for psychiatric disorders. Existing drugs have limited efficacy; creation of improved versions will require better understanding of serotonergic circuitry, which has been hampered by our inability to monitor serotonin release and transport with high spatial and temporal resolution. We developed and applied a binding-pocket redesign strategy, guided by machine learning, to create a high-performance, soluble, fluorescent serotonin sensor (iSeroSnFR), enabling optical detection of millisecond-scale serotonin transients. We demonstrate that iSeroSnFR can be used to detect serotonin release in freely behaving mice during fear conditioning, social interaction, and sleep/wake transitions. We also developed a robust assay of serotonin transporter function and modulation by drugs. We expect that both machine-learning-guided binding-pocket redesign and iSeroSnFR will have broad utility for the development of other sensors and in vitro and in vivo serotonin detection, respectively.