Carlas Smith

In vivo single-particle imaging of nuclear mRNA export in budding yeast demonstrates an essential role for Mex67p

Single-particle imaging in budding yeast demonstrates that mRNP export is fast (∼200 ms) and that mRNPs are retained at NPCs and undergo retrograde transport in a mex67-5 mutant, proving an essential role for Mex67p in directional mRNP transport.

Nuclear accessibility of β-actin mRNA is measured by 3D single-molecule real-time tracking

Multifocus microscopy combined with precise registration between fluorescently labeled mRNA, nuclear pore complexes, and chromatin reveals that β-actin mRNAs freely access the entire nucleus and most are within 0.5 µm of a nuclear pore.

Probability-based particle detection that enables threshold-free and robust in vivo single-molecule tracking

Any single-molecule study starts with finding those single-molecule signals in recorded images. Currently, parameters such as filter and thresholds are user set, and errors are unknown and not observed or controlled. A framework is presented in which expert knowledge and parameter tweaking are replaced with a probability-based hypothesis test.

Iterative learning control of a membrane deformable mirror for optimal wavefront correction

We present an iterative learning control (ILC) algorithm for controlling the shape of a membrane deformable mirror (DM). We furthermore give a physical interpretation of the design parameters of the ILC algorithm. On the basis of this insight, we derive a simple tuning procedure for the ILC algorithm that, in practice, guarantees stable and fast convergence of the membrane to the desired shape. In order to demonstrate the performance of the algorithm, we have built an experimental setup that consists of a commercial membrane DM, a wavefront sensor, and a real-time controller. The experimental results show that, by using the ILC algorithm, we are able to achieve a relatively small error between the real and desired shape of the DM while at the same time we are able to control the saturation of the actuators. Moreover, we show that the ILC algorithm outperforms other control algorithms available in the literature.

Iterative linear focal-plane wavefront correction

We propose an efficient approximation to the nonlinear phase diversity (PD) method for wavefront reconstruction and correction from intensity measurements with potential of being used in real-time applications. The new iterative linear phase diversity (ILPD) method assumes that the residual phase aberration is small and makes use of a first-order Taylor expansion of the point spread function (PSF), which allows for arbitrary (large) diversities in order to optimize the phase retrieval. For static disturbances, at each step, the residual phase aberration is estimated based on one defocused image by solving a linear least squares problem, and compensated for with a deformable mirror. Due to the fact that the linear approximation does not have to be updated with each correction step, the computational complexity of the method is reduced to that of a matrix-vector multiplication. The convergence of the ILPD correction steps has been investigated and numerically verified. The comparative study that we make demonstrates the improved performance in computational time with no decrease in accuracy with respect to existing methods that also linearize the PSF.

Simultaneous measurement of emission color and 3D position of single molecules

We show that the position of single molecules in all three spatial dimensions can be estimated alongside its emission color by diffractive optics based design of the Point Spread Function (PSF). The phase in a plane conjugate to the aperture stop of the objective lens is modified by a diffractive structure that splits the spot on the camera into closely spaced diffraction orders. The distance between and the size of these sub-spots are a measure of the emission color. Estimation of the axial position is enabled by imprinting aberrations such as astigmatism and defocus onto the orders. The overall spot shape is fitted with a fully vectorial PSF model. Proof-of-principle experiments on quantum dots indicate that a spectral precision of 10 to 20 nm, an axial localization precision of 25 to 50 nm, and a lateral localization precision of 10 to 30 nm can be achieved over a 1 μm range of axial positions for on average 800 signal photons and 17 background photons/pixel. The method appears to be rather sensitive to PSF model errors such as aberrations, giving in particular rise to biases in the fitted wavelength of up to 15 nm.

Single molecule fluorescence in situ hybridisation for quantitating post-transcriptional regulation in Drosophila brains.

Highlights • Simple and rapid smFISH protocol suitable for medium throughput.• Sensitive mRNA detection deep in whole-mount larval and adult Drosophila brains.• Multiplexed detection of RNA in combination with antibody staining.• Quantitation of primary transcription and post-transcriptional mRNA levels.• Reliable cell type markers in a whole-mount brain complementary to antibody markers.

Real-time wavefront reconstruction from intensity measurements

We propose an efficient approximation to the nonlinear phase diversity method for wavefront reconstruction from intensity measurements. The new method, iterative linear phase diversity (ILPD), assumes that the residual phase aberration is small and makes use of a first order Taylor expansion of the point spread function (PSF) performed for an arbitrary (large) diversity in order to optimize the phase retrieval. For static aberrations, ILPD makes use of two images collected at each iteration of the algorithm. In each step, the residual phase aberrations are estimated by solving a linear least squares problem, followed by the use of a deformable mirror to correct for the aberrations. A further contribution of the paper is the extension of the static ILPD to the case of dynamic wavefront reconstruction for which a computationally efficient H2 controller is presented.

Integration of Parallel Opposing Memories Underlies Memory Extinction

Summary Accurately predicting an outcome requires that animals learn supporting and conflicting evidence from sequential experience. In mammals and invertebrates, learned fear responses can be suppressed by experiencing predictive cues without punishment, a process called memory extinction. Here, we show that extinction of aversive memories in Drosophila requires specific dopaminergic neurons, which indicate that omission of punishment is remembered as a positive experience. Functional imaging revealed co-existence of intracellular calcium traces in different places in the mushroom body output neuron network for both the original aversive memory and a new appetitive extinction memory. Light and ultrastructural anatomy are consistent with parallel competing memories being combined within mushroom body output neurons that direct avoidance. Indeed, extinction-evoked plasticity in a pair of these neurons neutralizes the potentiated odor response imposed in the network by aversive learning. Therefore, flies track the accuracy of learned expectations by accumulating and integrating memories of conflicting events.

Fast phase diversity wavefront sensing using object independent metrics

Phase-diversity methods allow to estimate both the wavefront disturbance as well as the object that is being imaged and that is extended in space. Hence, in principle, phase-diversity methods can be used for wavefront sensing as well, without the need to spill part of the observed light to wavefront sensing with a dedicated wavefront sensor. However, the use of phase-diversity in real-time applications is prevented by its high computational complexity, determined by the number of parameters quantifying the wavefront and the object. To reduce the computational complexity, metrics have been proposed that are independent of the object, that allow to only estimate the wavefront, but still yield a nonlinear inverse problem. To further reduce the computational complexity of the wavefront estimation methods we consider linear approximations of these metrics, that allow to update the estimate of the wavefront by solving a linear least squares problem. We study the estimation error w.r.t. the presence of noise and the spectral content of the extended object, and compare metrics presented in literature.