Using MitER for 3D analysis of mitochondrial morphology and ER contacts.

We have developed an open-source workflow that allows for quantitative single-cell analysis of organelle morphology, distribution, and inter-organelle contacts with an emphasis on the analysis of mitochondria and mitochondria-endoplasmic reticulum (mito-ER) contact sites. As the importance of inter-organelle contacts becomes more widely recognized, there is a concomitant increase in demand for tools to analyze subcellular architecture. Here, we describe a workflow we call MitER (pronounced "mightier"), which allows for automated calculation of organelle morphology, distribution, and inter-organelle contacts from 3D renderings by employing the animation software Blender. We then use MitER to quantify the variations in the mito-ER networks of Saccharomyces cerevisiae, revealing significantly more mito-ER contacts within respiring cells compared to fermenting cells. We then demonstrate how this workflow can be applied to mammalian systems and used to monitor mitochondrial dynamics and inter-organelle contact in time-lapse studies.

High-throughput feedback-enabled optogenetic stimulation and spectroscopy in microwell plates.

The ability to perform sophisticated, high-throughput optogenetic experiments has been greatly enhanced by recent open-source illumination devices that allow independent programming of light patterns in single wells of microwell plates. However, there is currently a lack of instrumentation to monitor such experiments in real time, necessitating repeated transfers of the samples to stand-alone analytical instruments, thus limiting the types of experiments that could be performed. Here we address this gap with the development of the optoPlateReader (oPR), an open-source, solid-state, compact device that allows automated optogenetic stimulation and spectroscopy in each well of a 96-well plate. The oPR integrates an optoPlate illumination module with a module called the optoReader, an array of 96 photodiodes and LEDs that allows 96 parallel light measurements. The oPR was optimized for stimulation with blue light and for measurements of optical density and fluorescence. After calibration of all device components, we used the oPR to measure growth and to induce and measure fluorescent protein expression in E. coli. We further demonstrated how the optical read/write capabilities of the oPR permit computer-in-the-loop feedback control, where the current state of the sample can be used to adjust the optical stimulation parameters of the sample according to pre-defined feedback algorithms. The oPR will thus help realize an untapped potential for optogenetic experiments by enabling automated reading, writing, and feedback in microwell plates through open-source hardware that is accessible, customizable, and inexpensive.

Initializing LSTM internal states via manifold learning.

We present an approach, based on learning an intrinsic data manifold, for the initialization of the internal state values of long short-term memory (LSTM) recurrent neural networks, ensuring consistency with the initial observed input data. Exploiting the generalized synchronization concept, we argue that the converged, "mature" internal states constitute a function on this learned manifold. The dimension of this manifold then dictates the length of observed input time series data required for consistent initialization. We illustrate our approach through a partially observed chemical model system, where initializing the internal LSTM states in this fashion yields visibly improved performance. Finally, we show that learning this data manifold enables the transformation of partially observed dynamics into fully observed ones, facilitating alternative identification paths for nonlinear dynamical systems.