We present STIM, an imaging-based computational framework focused on visualizing and aligning high-throughput spatial sequencing datasets. STIM is built on the powerful, scalable ImgLib2 and BigDataViewer (BDV) image data frameworks and thus enables novel development or transfer of existing computer vision techniques to the sequencing domain characterized by datasets with irregular measurement-spacing and arbitrary spatial resolution, such as spatial transcriptomics data generated by multiplexed targeted hybridization or spatial sequencing technologies. We illustrate STIM’s capabilities by representing, interactively visualizing, 3D rendering, automatically registering and segmenting publicly available spatial sequencing data from 13 serial sections of mouse brain tissue, and from 19 sections of a human metastatic lymph node.Competing Interest StatementThis work is part of a larger patent application in which the authors are among the inventors. The patent application was submitted through the Technology Transfer Office of the Max-Delbrueck Center (MDC), with the MDC being the patent applicant.

The use of fluorescent sensors for functional imaging has revolutionized the study of organellar Ca2+ signaling. However, understanding the dynamic interplay between intracellular Ca2+ sinks and sources requires bright, photostable and multiplexed measurements in each signaling compartment of interest to dissect the origins and destinations of Ca2+ fluxes. We introduce a new toolkit of chemigenetic indicators based on HaloCaMP, optimized to report Ca2+ dynamics in the endoplasmic reticulum (ER) and mitochondria of mammalian cells and neurons. Both ER-HaloCaMP and Mito-HaloCaMP present high brightness and responsiveness, and the use of different HaloTag ligands enables tunable red and far-red emission when quantifying organelle Ca2+ dynamics, expanding significantly multiplexing capacities of Ca2+ signaling. The improved brightness of ER-HaloCaMP using either red or far-red HaloTag ligands enabled measuring ER Ca2+ fluxes in axons of neurons, in which the ER is formed by a tiny tubule of 30-60 nanometers of diameter that impeded measurements with previous red ER Ca2+ sensors. When measuring ER Ca2+ fluxes in activated neuronal dendritic spines of cultured neurons, ER-HaloCaMP presented increased photostability compared to the gold-standard ER Ca2+ sensor in the field, ER-GCaMP6-210, while presenting the same responsiveness. On the other hand, Mito-HaloCaMP presented higher responsiveness than current red sensors, and enabled the first measurements of mitochondrial Ca2+ signaling in far-red in cell lines and primary neurons. As a proof-of-concept, we used 3-plex multiplexing to quantify interorganellar Ca2+ signaling. We show that effective transfer of Ca2+ from the ER to mitochondria depends on the ER releasing a critical amount of Ca2+. When this threshold is not met, the mobilized Ca2+ is diverted to the cytosol instead. Our new toolkit provides an expanded palette of bright, photostable and responsive organellar Ca2+ sensors, which will facilitate future studies of intracellular Ca2+ signaling.

Background

Reducing fibrous aggregates of protein tau is a possible strategy for halting progression of Alzheimer’s disease (AD). Previously we found that in vitro the D-peptide D-TLKIVWC fragments tau fibrils from AD brains (AD-tau) into benign segments, whereas its six-residue analog D-TLKIVW cannot. However, the underlying fragmentation mechanism remains unknown, preventing the further development of this type of drug candidate for AD.

Method

To understand the necessity of the cysteine residue of D-TLKIVWC in fragmenting AD-tau, we designed a series of peptides of sequence D-TLKIVWX varying only at the seventh residue, X. To better understand the fragmentation process of AD-tau, we conducted a time-course dot blot and EM experiment. We determined the structures of D-TLKIVWX amyloid-like fibrils by atomic force microscopy and cryo-electron microscopy. We studied the complexes of D-TLKIVWX (X = I, S, R) with AD-tau by cryo-electron microscopy and confirmed the binding site between D-TLKIVWX and Tau through NMR.

Result

These D-TLKIVWX candidates showed various efficacies in fragmenting AD-tau in vitro, in which X = Ile was the best performer. From electron microscopy, we discovered that D-TLKIVWX peptides form amyloid-like fibrils themselves, and from atomic force microscopy we learned that these fibrils have a right-handed helical twist, in contrast to the left-handed helical twist of AD-tau. From cryo-EM we learned that D-TLKIVWX protofilaments bind to tau fibrils of opposing twist.

Conclusion

We find that the amyloid-like, fibril-forming property of D-TLKIVWX contributes to the fragmentation of AD-tau fibrils. We propose the strain-relief mechanism of fragmentation and believe the fragmentation of AD-tau fibrils is driven by the release of torsion in D-TLKIVWX protofilaments.

Dense-core vesicles (DCVs) are found in various types of cells, such as neurons, pancreatic β-cells, and chromaffin cells. These vesicles release transmitters, peptides, and hormones to regulate diverse functions, such as the stress response, immune response, behavior, and blood glucose levels. In traditional electron microscopy after chemical fixation, it is often reported that the dense cores occupy a portion of the vesicle towards the center and are surrounded by a clear halo. With electron microscopy following cryo-fixation in adrenal chromaffin cells, we report here that we did not observe halos, but dense cores filling up the entire vesicles suggesting that halos are likely the product of chemical fixation. More importantly, we observed that a fraction of DCVs contained 36-168 nm clear-core vesicles. A similar fraction of DCVs labeled with fluorescent false neurotransmitter FFN 511 or the dense-core matrix protein chromogranin A (CGA) were colocalized with fluorescently labeled or endogenous CD63 or ALIX, the membrane or lumen marker of ∼40-160 nm exosomes. These results suggest that DCVs contain exosomes. Since exosomes are generally thought to reside within multivesicular bodies in the cytosol and are released to the extracellular space to mediate diverse cell-to-cell communications, our findings suggest that dense-core vesicle fusion from many cell types is a new source for releasing exosomes to mediate intercellular communications. Given that dense-core vesicle fusion mediates many physiological functions, such as stress responses, immune responses, behavior regulation, and blood glucose regulation, exosome release from dense-core vesicle fusion might contribute to mediating these important functions.

The ventromedial hypothalamus (VMH) projects to the periaqueductal gray (PAG) and anterior hypothalamic nucleus (AHN), mediating freezing and escape behaviors, respectively. We investigated VMH collateral (VMH-coll) neurons, which innervate both PAG and AHN, to elucidate their role in postsynaptic processing and defensive behavior plasticity. Using all-optical voltage imaging of 22,151 postsynaptic neurons ex vivo, we found that VMH-coll neurons engage inhibitory mechanisms at both synaptic ends and can induce synaptic circuit plasticity. In vivo optogenetic activation of the VMH-coll somas induced escape behaviors. We identified an Esr1-expressing VMH-coll subpopulation with postsynaptic connectome resembling that of wild-type collaterals on the PAG side. Activation of Esr1+VMH-coll neurons evoked freezing and unexpected flattening behavior, previously not linked to the VMH. Neuropeptides such as PACAP and dynorphin modulated both Esr1+VMH-coll connectomes. In vivo κ-opioid receptor antagonism impaired Esr1+VMH-coll-mediated defensive behaviors. These findings unveiled the central role of VMH-coll pathways in innate defensive behavior plasticity.

Artificial neural networks learn faster if they are initialized well. Good initializations can generate high-dimensional macroscopic dynamics with long timescales. It is not known if biological neural networks have similar properties. Here we show that the eigenvalue spectrum and dynamical properties of large-scale neural recordings in mice (two-photon and electrophysiology) are similar to those produced by linear dynamics governed by a random symmetric matrix that is critically normalized. An exception was hippocampal area CA1: population activity in this area resembled an efficient, uncorrelated neural code, which may be optimized for information storage capacity. Global emergent activity modes persisted in simulations with sparse, clustered or spatial connectivity. We hypothesize that the spontaneous neural activity reflects a critical initialization of whole-brain neural circuits that is optimized for learning time-dependent tasks.

Optical aberrations hinder fluorescence microscopy of thick samples, reducing image signal, contrast, and resolution. Here we introduce a deep learning-based strategy for aberration compensation, improving image quality without slowing image acquisition, applying additional dose, or introducing more optics. Our method (i) introduces synthetic aberrations to images acquired on the shallow side of image stacks, making them resemble those acquired deeper into the volume and (ii) trains neural networks to reverse the effect of these aberrations. We use simulations and experiments to show that applying the trained ‘de-aberration’ networks outperforms alternative methods, providing restoration on par with adaptive optics techniques; and subsequently apply the networks to diverse datasets captured with confocal, light-sheet, multi-photon, and super-resolution microscopy. In all cases, the improved quality of the restored data facilitates qualitative image inspection and improves downstream image quantitation, including orientational analysis of blood vessels in mouse tissue and improved membrane and nuclear segmentation in C. elegans embryos.

During development, cells undergo a sequence of specification events to form functional tissues and organs. To investigate complex tissue development, it is crucial to visualize how cell lineages emerge and to be able to manipulate regulatory factors with temporal control. We recently developed TEMPO (Temporal Encoding and Manipulation in a Predefined Order), a genetic tool to label with different colors and genetically manipulate consecutive cell generations in vertebrates. TEMPO relies on CRISPR to activate a cascade of fluorescent proteins which can be imaged in vivo. Here, we explain the steps to design, generate, and express TEMPO constructs in zebrafish and mice.

Fluorescence microscopy is essential for biological research, offering high-contrast imaging of microscopic structures. However, the quality of these images is often compromised by optical aberrations and noise, particularly in low signal-to-noise ratio (SNR) conditions. While adaptive optics (AO) can correct aberrations, it requires costly hardware and slows down imaging; whereas current denoising approaches boost the SNR but leave out the aberration compensation. To address these limitations, we introduce HD2Net, a deep learning framework that enhances image quality by simultaneously denoising and suppressing the effect of aberrations without the need for additional hardware. Building on our previous work, HD2Net incorporates noise estimation and aberration removal modules, effectively restoring images degraded by noise and aberrations. Through comprehensive evaluation of synthetic phantoms and biological data, we demonstrate that HD2Net outperforms existing methods, significantly improving image resolution and contrast. This framework offers a promising solution for enhancing biological imaging, particularly in challenging aberrating and low-light conditions.