One of the limitations on imaging fluorescent proteins within living cells is that they are usually present in small numbers and need to be detected over a large background. We have developed the means to isolate specific fluorescence signals from background by using lock-in detection of the modulated fluorescence of a class of optical probe termed ''optical switches.'' This optical lock-in detection (OLID) approach involves modulating the fluorescence emission of the probe through deterministic, optical control of its fluorescent and nonfluorescent states, and subsequently applying a lock-in detection method to isolate the modulated signal of interest from nonmodulated background signals. Cross-correlation analysis provides a measure of correlation between the total fluorescence emission within single pixels of an image detected over several cycles of optical switching and a reference waveform detected within the same image over the same switching cycles. This approach to imaging provides a means to selectively detect the emission from optical switch probes among a larger population of conventional fluorescent probes and is compatible with conventional microscopes. OLID using nitrospirobenzopyran-based probes and the genetically encoded Dronpa fluorescent protein are shown to generate high-contrast images of specific structures and proteins in labeled cells in cultured and explanted neurons and in live Xenopus embryos and zebrafish larvae.high-contrast ͉ optical switches ͉ "ac"-imaging ͉ fluorescence microscopy U nderstanding the molecular basis for the regulation of complex biological processes such as cell motility and proliferation requires analysis of the distribution and dynamics of protein interactions within living cells in culture and in intact tissue (1). Tremendous advances have been made toward the development of new optical probes (2, 3) and imaging techniques that are capable of detecting proteins down to the level of single molecules (4-11). However, in living cells, such detection is compromised by autofluorescence, which can amount to several thousand equivalents of fluorescein per cell (12), as well as by light scattering (13). A major challenge in live-cell imaging, therefore, is to develop classes of probes and imaging techniques that are capable of resolving fluorescence signals from synthetic probes or genetically encoded fluorescent proteins in living cells and tissue against large background signals that may vary in time and space.A simple and highly-effective approach for isolating a specific fluorescence signal from a large background is to reversibly modulate the fluorescence intensity of only a probe of interest that is bound to a specific protein by applying a uniform, rapid and specific perturbation (e.g., a change in temperature (14), pressure (15), or voltage (16) to which that probe is uniquely attuned. The modulated fluorescence can be isolated from other steady sources of background fluorescence by lock-in detection, making it possible to specifically extract the probe fluoresc...

High-throughput single-cell RNA-Seq (scRNA-Seq) methods can efficiently generate expression profiles for thousands of cells, and promise to enable the comprehensive molecular characterization of all cell types and states present in heterogeneous tissues. However, compared to bulk RNA-Seq, single-cell expression profiles are extremely noisy and only capture a fraction of transcripts present in the cell. Here, we propose an algorithm to smooth scRNA-Seq data, with the goal of significantly improving the signal-tonoise ratio of each profile, while largely preserving biological expression heterogeneity. The algorithm is based on the observation that across protocols, the technical noise exhibited by UMI-filtered scRNA-Seq data closely follows Poisson statistics. Smoothing is performed by first identifying the nearest neighbors of each cell in a step-wise fashion, based on variance-stabilized and partially smoothed expression profiles, and then aggregating their transcript counts. On data from human pancreatic islet tissue and peripheral blood mononuclear cells, we show that smoothing greatly facilitates the identification of clusters of cells and co-expressed genes. Using simulated datasets that closely mimic real expression data, we show that our algorithm drastically improves upon the accuracy of other smoothing methods. Our work implies that there exists a quantitative relationship between the number of cells profiled and the potential accuracy with which individual cell types or states can be characterized, and helps unlock the full potential of scRNA-Seq to elucidate molecular processes in healthy and disease tissues. Reference implementations of our algorithm can be found at https://github.com/yanailab/knn-smoothing.

The Förster resonance energy transfer (FRET) technique is widely used for studying protein interactions within live cells. The effectiveness and sensitivity of determining FRET, however, can be reduced by photobleaching, cross talk, autofluorescence, and unlabeled, endogenous proteins. We present a FRET imaging method using an optical switch probe, Nitrobenzospiropyran (NitroBIPS), which substantially improves the sensitivity of detection to <1% FRET efficiency. Through orthogonal optical control of the colorful merocyanine and colorless spiro states of the NitroBIPS acceptor, donor fluorescence can be measured both in the absence and presence of FRET in the same FRET pair in the same cell. A SNAP-tag approach is used to generate a green fluorescent protein-alkylguaninetransferase fusion protein (GFP-AGT) that is labeled with benzylguanine-NitroBIPS. In vivo imaging studies on this green fluorescent protein-alkylguaninetransferase (GFP-AGT) (NitroBIPS) complex, employing optical lock-in detection of FRET, allow unambiguous resolution of FRET efficiencies below 1%, equivalent to a few percent of donor-tagged proteins in complexes with acceptor-tagged proteins.

This study characterizes the interactions between kabiramide C (KabC) and related macrolides and actin and establishes the mechanisms that underlie their inhibition of actin filament dynamics and cytotoxicity. The G-actin-KabC complex is formed through a twostep binding reaction and is extremely stable and long-lived. Competition-binding studies show that KabC binds to the same site on G-actin as Gelsolin domain 1 and CapG. KabC also binds to protomers within F-actin and results in the severing and capping of the (؉) end; these studies suggest that free KabC and related macrolides act as biomimetics of Gelsolin. The G-actin-KabC complex binds to the (؉) end of a growing filament, where it functions as a novel, unregulated, (؉)-end capper and is largely responsible for the inhibition of motility and cytokinesis in Ϸ10 -100 nM KabC-treated cells. KabC and related macrolides are useful probes to study the regulation of the actin filament (؉) end and may lead to new therapies to treat diseases of the actin cytoskeleton.