Engineered tissues can be used to understand fundamental features of biology, develop organotypic in vitro model systems, and as engineered tissue constructs for replacing damaged tissue in vivo. However, a key limitation is an inability to test the wide range of parameters that might impact the engineered tissue in a high-throughput manner and in an environment that mimics the three-dimensional (3D) native architecture. We developed a microfabricated platform to generate arrays of microtissues embedded within 3D micropatterned matrices. Microcantilevers simultaneously constrain microtissue formation and report forces generated by the microtissues in real time, opening the possibility to use high-throughput, low-volume screening for studies on engineered tissues. Thanks to the micrometer scale of the microtissues, this platform is also suitable for high-throughput monitoring of drug-induced effect on architecture and contractility in engineered tissues. Moreover, independent variations of the mechanical stiffness of the cantilevers and collagen matrix allow the measurement and manipulation of the mechanics of the microtissues. Thus, our approach will likely provide valuable opportunities to elucidate how biomechanical, electrical, biochemical, and genetic/epigenetic cues modulate the formation and maturation of 3D engineered tissues. In this chapter, we describe the microfabrication, preparation, and experimental use of such microfabricated tissue gauges.

Fluorescence microscopy, a key driver for progress in the life sciences, faces limitations due to the microscope’s optics, fluorophore chemistry, and photon exposure limits, necessitating trade-offs in imaging speed, resolution, and depth. Here, we introduce MicroSplit, a computational multiplexing technique based on deep learning that allows multiple cellular structures to be imaged in a single fluorescent channel and then unmixed computationally, allowing faster imaging and reduced photon exposure. We show that MicroSplit efficiently separates up to four superimposed noisy structures into distinct denoised fluorescent image channels. Furthermore, using Variational Splitting Encoder-Decoder (VSE) networks, our approach can sample diverse predictions from a trained posterior of solutions. The diversity of these samples scales with the uncertainty in a given input, allowing us to estimate the true prediction errors by computing the variability between posterior samples. We demonstrate the robustness of MicroSplit across various datasets and noise levels and show its utility to image more, image faster, and improve downstream analysis. We provide MicroSplit along with all associated training and evaluation datasets as open resources, enabling life scientists to benefit from the potential of computational multiplexing and accelerate the pace of scientific discovery.

We present a method for microtubule tracking in electron microscopy volumes. Our method first identifies a sparse set of voxels that likely belong to microtubules. Similar to prior work, we then enumerate potential edges between these voxels, which we represent in a candidate graph. Tracks of microtubules are found by selecting nodes and edges in the candidate graph by solving a constrained optimization problem incorporating biological priors on microtubule structure. For this, we present a novel integer linear programming formulation, which results in speed-ups of three orders of magnitude and an increase of 53% in accuracy compared to prior art (evaluated on three 1 . 2 × 4 × 4µm volumes of Drosophila neural tissue). We also propose a scheme to solve the optimization problem in a block-wise fashion, which allows distributed tracking and is necessary to process very large electron microscopy volumes. Finally, we release a benchmark dataset for microtubule tracking, here used for training, testing and validation, consisting of eight 30 x 1000 x 1000 voxel blocks (1 . 2 × 4 × 4µm) of densely annotated microtubules in the CREMI data set (https://github.com/nilsec/micron).

Tethered midbody remnants dancing across apical microvilli, encountering the centrosome, and beckoning forth a cilium-who would have guessed this is how polarized epithelial cells coordinate the end of mitosis and the beginning of ciliogenesis? New evidence from Bernabé-Rubio et al. (2016. J. Cell Biol http://dx.doi.org/10.1083/jcb.201601020) supports this emerging model.

Although nervous system sexual dimorphisms are known in many species, relatively little is understood about the molecular mechanisms generating these dimorphisms. Recent findings in Drosophila provide the tools for dissecting how neurogenesis and neuronal differentiation are modulated by the Drosophila sex-determination regulatory genes to produce nervous system sexual dimorphisms. Here we report studies aimed at illuminating the basis of the sexual dimorphic axonal projection patterns of foreleg gustatory receptor neurons (GRNs): only in males do GRN axons project across the midline of the ventral nerve cord. We show that the sex determination genes fruitless (fru) and doublesex (dsx) both contribute to establishing this sexual dimorphism. Male-specific Fru (Fru(M)) acts in foreleg GRNs to promote midline crossing by their axons, whereas midline crossing is repressed in females by female-specific Dsx (Dsx(F)). In addition, midline crossing by these neurons might be promoted in males by male-specific Dsx (Dsx(M)). Finally, we (1) demonstrate that the roundabout (robo) paralogs also regulate midline crossing by these neurons, and (2) provide evidence that Fru(M) exerts its effect on midline crossing by directly or indirectly regulating Robo signaling.

The ability to image neurons anywhere in the mammalian brain is a major goal of optical microscopy. Here we describe a minimally invasive microendoscopy system for studying the morphology and function of neurons at depth. Utilizing a guide cannula with an ultrathin wall, we demonstrated in vivo two-photon fluorescence imaging of deeply buried nuclei such as the striatum (2.5 mm depth), substantia nigra (4.4 mm depth) and lateral hypothalamus (5.0 mm depth) in mouse brain. We reported, for the first time, the observation of neuronal activity with subcellular resolution in the lateral hypothalamus and substantia nigra of head-fixed awake mice.

The ability to automatically segment an image into distinct regions is a critical aspect in many visual processing applications. Because inaccuracies often exist in automatic segmentation, manual segmentation is necessary in some application domains to correct mistakes, such as required in the reconstruction of neuronal processes from microscopic images. The goal of the automated segmentation tool is traditionally to produce the highest-quality segmentation, where quality is measured by the similarity to actual ground truth, so as to minimize the volume of manual correction necessary. Manual correction is generally orders-of-magnitude more time consuming than automated segmentation, often making handling large images intractable. Therefore, we propose a more relevant goal: minimizing the turn-around time of automated/manual segmentation while attaining a level of similarity with ground truth. It is not always necessary to inspect every aspect of an image to generate a useful segmentation. As such, we propose a strategy to guide manual segmentation to the most uncertain parts of segmentation. Our contributions include 1) a probabilistic measure that evaluates segmentation without ground truth and 2) a methodology that leverages these probabilistic measures to significantly reduce manual correction while maintaining segmentation quality.

An important open question in biophysics is to understand how mechanical forces shape membrane-bounded cells and their organelles. A general solution to this problem is to calculate the bending energy of an arbitrarily shaped membrane surface, which can include both lipids and cytoskeletal proteins, and minimize the energy subject to all mechanical constraints. However, the calculations are difficult to perform, especially for shapes that do not possess axial symmetry. We show that the spherical harmonics parameterization (SHP) provides an analytic description of shape that can be used to quickly and reliably calculate minimum energy shapes of both symmetric and asymmetric surfaces. Using this method, we probe the entire set of shapes predicted by the bilayer couple model, unifying work based on different computational approaches, and providing additional details of the transitions between different shape classes. In addition, we present new minimum-energy morphologies based on non-linear models of membrane skeletal elasticity that closely mimic extreme shapes of red blood cells. The SHP thus provides a versatile shape description that can be used to investigate forces that shape cells.

Mitochondria-ER membrane contact sites (MERCS) represent a fundamental ultrastructural feature underlying unique biochemistry and physiology in eukaryotic cells. The ER protein PDZD8 is required for the formation of MERCS in many cell types, however, its tethering partner on the outer mitochondrial membrane (OMM) is currently unknown. Here we identify the OMM protein FKBP8 as the tethering partner of PDZD8 using a combination of unbiased proximity proteomics, CRISPR-Cas9 endogenous protein tagging, Cryo-electron tomography, and correlative light-electron microscopy. Single molecule tracking reveals highly dynamic diffusion properties of PDZD8 along the ER membrane with significant pauses and captures at MERCS. Overexpression of FKBP8 is sufficient to narrow the ER-OMM distance, whereas independent versus combined deletions of these two proteins demonstrate their interdependence for MERCS formation. Furthermore, PDZD8 enhances mitochondrial complexity in a FKBP8-dependent manner. Our results identify a novel ER-mitochondria tethering complex that regulates mitochondrial morphology in mammalian cells.

Preprint: 10.1101/2025.02.22.639343

Healthy mitochondria are critical for reproduction. During aging, both reproductive fitness and mitochondrial homeostasis decline. Mitochondrial metabolism and dynamics are key factors in supporting mitochondrial homeostasis. However, how they are coupled to control reproductive health remains unclear. We report that mitochondrial GTP (mtGTP) metabolism acts through mitochondrial dynamics factors to regulate reproductive aging. We discovered that germline-only inactivation of GTP- but not ATP-specific succinyl-CoA synthetase (SCS) promotes reproductive longevity in Caenorhabditis elegans. We further identified an age-associated increase in mitochondrial clustering surrounding oocyte nuclei, which is attenuated by GTP-specific SCS inactivation. Germline-only induction of mitochondrial fission factors sufficiently promotes mitochondrial dispersion and reproductive longevity. Moreover, we discovered that bacterial inputs affect mtGTP levels and dynamics factors to modulate reproductive aging. These results demonstrate the significance of mtGTP metabolism in regulating oocyte mitochondrial homeostasis and reproductive longevity and identify mitochondrial fission induction as an effective strategy to improve reproductive health.