Upon inflammation, leukocytes rapidly transmigrate across the endothelium to enter the inflamed tissue. Evidence accumulates that leukocytes use preferred exit sites, though it is not yet clear how these hotspots in the endothelium are defined and how they are recognized by the leukocyte. Using lattice light sheet microscopy, we discovered that leukocytes prefer endothelial membrane protrusions at cell junctions for transmigration. Phenotypically, these junctional membrane protrusions are present in an asymmetric manner, meaning that one endothelial cell shows the protrusion and the adjacent one does not. Consequently, leukocytes cross the junction by migrating underneath the protruding endothelial cell. These protrusions depend on Rac1 activity and by using a photo-activatable Rac1 probe, we could artificially generate local exit-sites for leukocytes. Overall, we have discovered a new mechanism that uses local induced junctional membrane protrusions to facilitate/steer the leukocyte escape/exit from inflamed vessel walls.

Upon inflammation, leukocytes rapidly transmigrate across the endothelium to enter the inflamed tissue. Evidence accumulates that leukocytes use preferred exit sites, though it is not yet clear how these hotspots in the endothelium are defined and how they are recognized by the leukocyte. Using lattice light sheet microscopy, we discovered that leukocytes prefer endothelial membrane protrusions at cell junctions for transmigration. Phenotypically, these junctional membrane protrusions are present in an asymmetric manner, meaning that one endothelial cell shows the protrusion and the adjacent one does not. Consequently, leukocytes cross the junction by migrating underneath the protruding endothelial cell. These protrusions depend on Rac1 activity and by using a photo-activatable Rac1 probe, we could artificially generate local exit-sites for leukocytes. Overall, we have discovered a new mechanism that uses local induced junctional membrane protrusions to facilitate/steer the leukocyte escape/exit from inflamed vessel walls.

We consider an energy functional that arises in micromagnetic and liquid crystal theory on thin films. In particular, our energy comprises a non-convex term that models anti-symmetric exchange as well as an anisotropy term. We devise an algorithm for energy minimization in the continuous case and show weak convergence of a subsequence towards a solution of the corresponding Euler--Lagrange equation. Furthermore, an algorithm for numerical energy minimization is presented. We show empirically that this numerical algorithm converges to the correct solutions for a benchmark problem without the need for user-supplied parameters, and present a rigorous convergence analysis for important special cases.

The development and maintenance of tissues requires collective cell movement, during which neighbouring cells coordinate the polarity of their migration machineries. Here, we ask how polarity signals are transmitted from one cell to another across symmetrical cadherin junctions, during collective migration. We demonstrate that collectively migrating endothelial cells have polarized VE-cadherin-rich membrane protrusions, ‘cadherin fingers’, which leading cells extend from their rear and follower cells engulf at their front, thereby generating opposite membrane curvatures and asymmetric recruitment of curvature-sensing proteins. In follower cells, engulfment of cadherin fingers occurs along with the formation of a lamellipodia-like zone with low actomyosin contractility, and requires VE-cadherin/catenin complexes and Arp2/3-driven actin polymerization. Lateral accumulation of cadherin fingers in follower cells precedes turning, and increased actomyosin contractility can initiate cadherin finger extension as well as engulfment by a neighbouring cell, to promote follower behaviour. We propose that cadherin fingers serve as guidance cues that direct collective cell migration.

Focused Ion Beam Scanning Electron Microscopy (FIB-SEM) can automatically generate 3D images with superior z-axis resolution, yielding data that needs minimal image registration and related post-processing. Obstacles blocking wider adoption of FIB-SEM include slow imaging speed and lack of long-term system stability, which caps the maximum possible acquisition volume. Here we present techniques that accelerate image acquisition while greatly improving FIB-SEM reliability, allowing the system to operate for months and generating continuously imaged volumes > 10(6) µm(3). These volumes are large enough for connectomics, where the excellent z resolution can help in tracing of small neuronal processes and accelerate the tedious and time-consuming human proofreading effort. Even higher resolution can be achieved on smaller volumes. We present example data sets from mammalian neural tissue, Drosophila brain, and Chlamydomonas reinhardtii to illustrate the power of this novel high-resolution technique to address questions in both connectomics and cell biology.

Gene targeting is an incredibly valuable technique. Sometimes however, it can also be extremely challenging for various intrinsic reasons (e.g. low target accessibility or nature/extent of gene modification). To bypass these barriers, we designed a transgene-based system in Drosophila that increases the number of independent gene targeting events while at the same time enriching for correctly targeted progeny. Unfortunately, with particularly challenging gene targeting experiments, our original design yielded numerous false positives. Here we deliver a much-improved technique named Enhanced Golic+ (E-Golic+). E-Golic+ incorporates genetic modifications to tighten lethality-based selection while simultaneously boosting efficiency. With E-Golic+, we easily achieve previously unattainable gene targeting. Additionally, we built an E-Golic+ based, high-efficiency genetic pipeline for transgene swapping. We demonstrate its utility by transforming GAL4 enhancer-trap lines into tissue-specific Cas9-expressing lines. Given the superior efficiency, specificity and scalability, E-Golic+ promises to expedite development of additional sophisticated genetic/genomic tools in .

Gene translation depends on accurate decoding of mRNA, the structural mechanism of which remains poorly understood. Ribosomes decode mRNA codons by selecting cognate aminoacyl-tRNAs delivered by elongation factor Tu (EF-Tu). Here we present high-resolution structural ensembles of ribosomes with cognate or near-cognate aminoacyl-tRNAs delivered by EF-Tu. Both cognate and near-cognate tRNA anticodons explore the aminoacyl-tRNA-binding site (A site) of an open 30S subunit, while inactive EF-Tu is separated from the 50S subunit. A transient conformation of decoding-centre nucleotide G530 stabilizes the cognate codon-anticodon helix, initiating step-wise 'latching' of the decoding centre. The resulting closure of the 30S subunit docks EF-Tu at the sarcin-ricin loop of the 50S subunit, activating EF-Tu for GTP hydrolysis and enabling accommodation of the aminoacyl-tRNA. By contrast, near-cognate complexes fail to induce the G530 latch, thus favouring open 30S pre-accommodation intermediates with inactive EF-Tu. This work reveals long-sought structural differences between the pre-accommodation of cognate and near-cognate tRNAs that elucidate the mechanism of accurate decoding.

Internal ribosome entry sites (IRESs) mediate cap-independent translation of viral mRNAs. Using electron cryo-microscopy of a single specimen, we present five ribosome structures formed with the Taura syndrome virus IRES and translocase eEF2•GTP bound with sordarin. The structures suggest a trajectory of IRES translocation, required for translation initiation, and provide an unprecedented view of eEF2 dynamics. The IRES rearranges from extended to bent to extended conformations. This inchworm-like movement is coupled with ribosomal inter-subunit rotation and 40S head swivel. eEF2, attached to the 60S subunit, slides along the rotating 40S subunit to enter the A site. Its diphthamide-bearing tip at domain IV separates the tRNA-mRNA-like pseudoknot I (PKI) of the IRES from the decoding center. This unlocks 40S domains, facilitating head swivel and biasing IRES translocation via hitherto-elusive intermediates with PKI captured between the A and P sites. The structures suggest missing links in our understanding of tRNA translocation.

Foraging animals often sample options that yield rewards with different probabilities. In such scenarios, many animals exhibit “matching”, whereby they allocate their choices such that the fraction of rewarded samples is equal across options. While matching can be optimal in environments with diminishing returns, this condition alone is not sufficient to determine optimality. Moreover, diminishing returns arise when resources deplete and replenish over time, but their form depends on the temporal structure and statistics of replenishment. Here, we investigate how these environmental properties influence whether matching is optimal. We consider an agent that samples options at fixed rates and derive the resulting reward probabilities across different types of environments. This allows us to analytically determine conditions under which the optimal policy exhibits matching. When all options share the same replenishment dynamics, matching emerges as optimal across a wide range of environments. However, when dynamics differ across options, optimal policies can deviate from matching. In such cases, the rank-ordering of observed reward probabilities depends only on the qualitative nature of the replenishment process, and not on the specific replenishment rates. As a result, the optimal policy can exhibit under- or over-matching depending on which options are more rewarding. We use this result to identify environments where performance differs substantially between matching and optimality. Finally, we show that fluctuations in replenishment rates—representing environmental stochasticity or internal uncertainty—can amplify deviations from matching. These findings deepen our understanding of the relationship between environmental variability and behavioral optimality, and provide testable predictions across diverse settings.

To interpret the sensory environment, the brain combines ambiguous sensory measurements with knowledge that reflects context-specific prior experience. But environmental contexts can change abruptly and unpredictably, resulting in uncertainty about the current context. Here we address two questions: how should context-specific prior knowledge optimally guide the interpretation of sensory stimuli in changing environments, and do human decision-making strategies resemble this optimum? We probe these questions with a task in which subjects report the orientation of ambiguous visual stimuli that were drawn from three dynamically switching distributions, representing different environmental contexts. We derive predictions for an ideal Bayesian observer that leverages knowledge about the statistical structure of the task to maximize decision accuracy, including knowledge about the dynamics of the environment. We show that its decisions are biased by the dynamically changing task context. The magnitude of this decision bias depends on the observer's continually evolving belief about the current context. The model therefore not only predicts that decision bias will grow as the context is indicated more reliably, but also as the stability of the environment increases, and as the number of trials since the last context switch grows. Analysis of human choice data validates all three predictions, suggesting that the brain leverages knowledge of the statistical structure of environmental change when interpreting ambiguous sensory signals.