Expansion microscopy (ExM) enables nanoscale fluorescence imaging on standard microscopes, but its combination with single-molecule localization microscopy (SMLM) remains challenging due to the incompatibility of expanded hydrogels with photoswitching buffers. Here, we introduce a single-step expansion microscopy approach that enables SMLM using spontaneously blinking dyes in 6–14× expanded samples, without re-embedding or buffer exchange. Using this approach, we achieve nanometer-scale spatial resolution by resolving the organization of the nuclear pore complex and the molecular structure of recombinant homotrimeric proliferating cell nuclear antigen.

Once secretory proteins have been targeted to the endoplasmic reticulum (ER) lumen, the proteins typically remain partitioned from the cytosol. If the secretory proteins misfold, they can be unfolded and retrotranslocated into the cytosol for destruction by the proteasome by ER-associated protein Degradation (ERAD). Here, we report that correctly folded and targeted luminal ER fluorescent protein reporters accumulate in the cytosol during acute misfolded secretory protein stress in yeast. Photoactivation fluorescence microscopy experiments reveal that luminal reporters already localized to the ER relocalize to the cytosol, even in the absence of essential ERAD machinery. We named this process "ER reflux." Reflux appears to be regulated in a size-dependent manner for reporters. Interestingly, prior heat shock stress also prevents ER stress-induced reflux. Together, our findings establish a new ER stress-regulated pathway for relocalization of small luminal secretory proteins into the cytosol, distinct from the ERAD and pre-emptive quality control pathways. Importantly, our results highlight the value of fully characterizing the cell biology of reporters and describe a simple modification to maintain luminal ER reporters in the ER during acute ER stress. This article is protected by copyright. All rights reserved.

Accumulating evidence indicates that biological aging can be accelerated by environmental exposures, collectively called the 'exposome'. The skin, as the largest and most exposed organ, can be viewed as a 'window' for the deep exploration of the exposome and its effects on systemic aging. The complex interplay across hallmarks of aging in the skin and systemic biological aging suggests that physiological processes associated with skin aging influence, and are influenced by, systemic hallmarks of aging. This bidirectional relationship provides potential avenues for the prevention of accelerated biological aging and the identification of therapeutic targets. We provide a review of the interactions between skin exposure, aging hallmarks in the skin and associated systemic changes, and their implications in treatment and disease. We also discuss key questions that need to be addressed to maintain skin and overall health, highlighting the need for the development of precise biomarkers and advanced skin models.

BACKGROUND: Logos are commonly used in molecular biology to provide a compact graphical representation of the conservation pattern of a set of sequences. They render the information contained in sequence alignments or profile hidden Markov models by drawing a stack of letters for each position, where the height of the stack corresponds to the conservation at that position, and the height of each letter within a stack depends on the frequency of that letter at that position. RESULTS: We present a new tool and web server, called Skylign, which provides a unified framework for creating logos for both sequence alignments and profile hidden Markov models. In addition to static image files, Skylign creates a novel interactive logo plot for inclusion in web pages. These interactive logos enable scrolling, zooming, and inspection of underlying values. Skylign can avoid sampling bias in sequence alignments by down-weighting redundant sequences and by combining observed counts with informed priors. It also simplifies the representation of gap parameters, and can optionally scale letter heights based on alternate calculations of the conservation of a position. CONCLUSION: Skylign is available as a website, a scriptable web service with a RESTful interface, and as a software package for download. Skylign’s interactive logos are easily incorporated into a web page with just a few lines of HTML markup. Skylign may be found at http://skylign.org.

The growing channel count of silicon probes has substantially increased the number of neurons recorded in electrophysiology (ephys) experiments, rendering traditional manual spike sorting impractical. Instead, modern ephys recordings are processed with automated methods that use waveform template matching to isolate putative single neurons. While scalable, automated methods are subject to assumptions that often fail to account for biophysical changes in action potential waveforms, leading to systematic errors. Consequently, manual curation of these errors, which is both time-consuming and lacks reproducibility, remains necessary. To improve efficiency and reproducibility in the spike-sorting pipeline, we introduce here the Spike-sorting Lapse Amelioration System (SLAy), an algorithm that automatically merges oversplit spike clusters. SLAy employs two novel metrics: (1) a waveform similarity metric that uses a neural network to obtain spatially informed, time-shift invariant low-dimensional waveform representations, and (2) a cross-correlogram significance metric based on the earth-movers distance between the observed and null cross-correlograms. We demonstrate that SLAy achieves 85% agreement with human curators across a diverse set of animal models, brain regions, and probe geometries. To illustrate the impact of spike sorting errors on downstream analyses, we develop a new burst-detection algorithm and show that SLAy fixes spike sorting errors that preclude the accurate detection of bursts in neural data. SLAy leverages GPU parallelization and multithreading for computational efficiency, and is compatible with Phy and NeuroData Without Borders, making it a practical and flexible solution for large-scale ephys data analysis.

Prolonged wakefulness leads to persistent, deep recovery sleep (RS). However, the neuronal circuits that mediate this process remain elusive. From a circuit screen in mice, we identified a group of thalamic nucleus reuniens (RE) neurons activated during sleep deprivation (SD) and required for sleep homeostasis. Optogenetic activation of RE neurons leads to an unusual phenotype: presleep behaviors (grooming and nest organizing) followed by prolonged, intense sleep that resembles RS. Inhibiting RE activity during SD impairs subsequent RS, which suggests that these neurons signal sleep need. RE neurons act upstream of sleep-promoting zona incerta cells, and SD triggers plasticity of this circuit to strengthen their connectivity. These findings reveal a circuit mechanism by which sleep need transforms the functional coupling of a sleep circuit to promote persistent, deep sleep.

Glycans are one of the fundamental biopolymers encountered in living systems. Compared to polynucleotide and polypeptide biosynthesis, polysaccharide biosynthesis is a uniquely combinatorial process to which interdependent enzymes with seemingly broad specificities contribute. The resulting intracellular cell surface, and secreted glycans play key roles in health and disease, from embryogenesis to cancer progression. The study and modulation of glycans in cell and organismal biology is aided by small molecule inhibitors of the enzymes involved in glycan biosynthesis. In this review, we survey the arsenal of currently available inhibitors, focusing on agents which have been independently validated in diverse systems. We highlight the utility of these inhibitors and drawbacks to their use, emphasizing the need for innovation for basic research as well as for therapeutic applications.

Pixel and superpixel classifiers have become essential tools for EM segmentation algorithms. Training these classifiers remains a major bottleneck primarily due to the requirement of completely annotating the dataset which is tedious, error-prone and costly. In this paper, we propose an interactive learning scheme for the superpixel classifier for EM segmentation. Our algorithm is "active semi-supervised" because it requests the labels of a small number of examples from user and applies label propagation technique to generate these queries. Using only a small set (<20%) of all datapoints, the proposed algorithm consistently generates a classifier almost as accurate as that estimated from a complete groundtruth. We provide segmentation results on multiple datasets to show the strength of these classifiers.

Pixel and superpixel classifiers have become essential tools for EM segmentation algorithms. Training these classifiers remains a major bottleneck primarily due to the requirement of completely annotating the dataset which is tedious, error-prone and costly. In this paper, we propose an interactive learning scheme for the superpixel classifier for EM segmentation. Our algorithm is 'active semi-supervised' because it requests the labels of a small number of examples from user and applies label propagation technique to generate these queries. Using only a small set (< 20%) of all datapoints, the proposed algorithm consistently generates a classifier almost as accurate as that estimated from a complete groundtruth. We provide segmentation results on multiple datasets to show the strength of these classifiers.

Animals rely on visual motion for navigating the world, and research in flies has clarified how neural circuits extract information from moving visual scenes. However, the major pathways connecting these patterns of optic flow to behavior remain poorly understood. Using a high-throughput quantitative assay of visually guided behaviors and genetic neuronal silencing, we discovered a region in Drosophila’s protocerebrum critical for visual motion following. We used neuronal silencing, calcium imaging, and optogenetics to identify a single cell type, LPC1, that innervates this region, detects translational optic flow, and plays a key role in regulating forward walking. Moreover, the population of LPC1s can estimate the travelling direction, such as when gaze direction diverges from body heading. By linking specific cell types and their visual computations to specific behaviors, our findings establish a foundation for understanding how the nervous system uses vision to guide navigation.