How pioneer factors interface with chromatin to promote accessibility for transcription control is poorly understood in vivo. Here, we directly visualize chromatin association by the prototypical GAGA pioneer factor (GAF) in live Drosophila hemocytes. Single-particle tracking reveals that most GAF is chromatin bound, with a stable-binding fraction showing nucleosome-like confinement residing on chromatin for more than 2 min, far longer than the dynamic range of most transcription factors. These kinetic properties require the full complement of GAF's DNA-binding, multimerization and intrinsically disordered domains, and are autonomous from recruited chromatin remodelers NURF and PBAP, whose activities primarily benefit GAF's neighbors such as Heat Shock Factor. Evaluation of GAF kinetics together with its endogenous abundance indicates that, despite on-off dynamics, GAF constitutively and fully occupies major chromatin targets, thereby providing a temporal mechanism that sustains open chromatin for transcriptional responses to homeostatic, environmental and developmental signals.

In this work, we find that CD8 T cells expressing inhibitory killer cell immunoglobulin-like receptors (KIRs) are the human equivalent of Ly49CD8 regulatory T cells in mice and are increased in the blood and inflamed tissues of patients with a variety of autoimmune diseases. Moreover, these CD8 T cells efficiently eliminated pathogenic gliadin-specific CD4 T cells from the leukocytes of celiac disease patients in vitro. We also find elevated levels of KIRCD8 T cells, but not CD4 regulatory T cells, in COVID-19 patients, correlating with disease severity and vasculitis. Selective ablation of Ly49CD8 T cells in virus-infected mice led to autoimmunity after infection. Our results indicate that in both species, these regulatory CD8 T cells act specifically to suppress pathogenic T cells in autoimmune and infectious diseases.

Previously, we developed a novel model for anxiety during motivated behavior by training rats to perform a task where actions executed to obtain a reward were probabilistically punished and observed that after learning, neuronal activity in the ventral tegmental area (VTA) and dorsomedial prefrontal cortex (dmPFC) represent the relationship between action and punishment risk (Park & Moghaddam, 2017). Here we used male and female rats to expand on the previous work by focusing on neural changes in the dmPFC and VTA that were associated with the learning of probabilistic punishment, and anxiolytic treatment with diazepam after learning. We find that adaptive neural responses of dmPFC and VTA during the learning of anxiogenic contingencies are independent from the punisher experience and occur primarily during the peri-action and reward period. Our results also identify peri-action ramping of VTA neural calcium activity, and VTA-dmPFC correlated activity, as potential markers for the anxiolytic properties of diazepam.

Manifold attractors are a key framework for understanding how continuous variables, such as position or head direction, are encoded in the brain. In this framework, the variable is represented along a continuum of persistent neuronal states which forms a manifold attactor. Neural networks with symmetric synaptic connectivity that can implement manifold attractors have become the dominant model in this framework. In addition to a symmetric connectome, these networks imply homogeneity of individual-neuron tuning curves and symmetry of the representational space; these features are largely inconsistent with neurobiological data. Here, we developed a theory for computations based on manifold attractors in trained neural networks and show how these manifolds can cope with diverse neuronal responses, imperfections in the geometry of the manifold and a high level of synaptic heterogeneity. In such heterogeneous trained networks, a continuous representational space emerges from a small set of stimuli used for training. Furthermore, we find that the network response to external inputs depends on the geometry of the representation and on the level of synaptic heterogeneity in an analytically tractable and interpretable way. Finally, we show that a too complex geometry of the neuronal representation impairs the attractiveness of the manifold and may lead to its destabilization. Our framework reveals that continuous features can be represented in the recurrent dynamics of heterogeneous networks without assuming unrealistic symmetry. It suggests that the representational space of putative manifold attractors in the brain dictates the dynamics in their vicinity.

Interplay between models and experimental data advances discovery and understanding in biology, particularly when models generate predictions that allow well-designed experiments to distinguish between alternative mechanisms. To illustrate how this feedback between models and experiments can lead to key insights into biological mechanisms, we explore three examples from cellular slime mold chemotaxis. These examples include studies that identified chemotaxis as the primary mechanism behind slime mold aggregation, discovered that cells likely measure chemoattractant gradients by sensing concentration differences across cell length, and tested the role of cell-associated chemoattractant degradation in shaping chemotactic fields. Although each study used a different model class appropriate to their hypotheses - qualitative, mathematical, or simulation-based - these examples all highlight the utility of modeling to formalize assumptions and generate testable predictions. A central element of this framework is the iterative use of models and experiments, specifically: matching experimental designs to the models, revising models based on mismatches with experimental data, and validating critical model assumptions and predictions with experiments. We advocate for continued use of this interplay between models and experiments to advance biological discovery.

During their lifetime, animals must adapt their behavior to survive in changing environments. This ability requires the nervous system to adjust through dynamic expression of neurotransmitters and receptors but also through growth, spatial reorganization and connectivity while integrating external stimuli. For instance, despite having a fixed neuronal cell lineage, the nematode Caenorhabditis elegans’ nervous system remains plastic throughout its development. Here, we focus on a specific example of nervous system plasticity, the C. elegans dauer exit decision. Under unfavorable conditions, larvae will enter the non-feeding and non-reproductive dauer stage and adapt their behavior to cope with a new environment. Upon improved conditions, this stress resistant developmental stage is actively reversed to resume reproductive development. However, how different environmental stimuli regulate the exit decision mechanism and thereby drive the larva’s behavioral change is unknown. To fill this gap, we developed a new open hardware method for long-term imaging (12h) of C. elegans larvae. We identified dauer-specific behavioral motifs and characterized the behavioral trajectory of dauer exit in different environments to identify key decision points. Combining long-term behavioral imaging with transcriptomics, we find that bacterial ingestion triggers a change in neuropeptide gene expression to establish post-dauer behavior. Taken together, we show how a developing nervous system can robustly integrate environmental changes, activate a developmental switch and adapt the organism’s behavior to a new environment.

Many animals rely on a representation of head direction for flexible, goal-directed navigation. In insects, a compass-like head direction representation is maintained in a conserved brain region called the central complex. This head direction representation is updated by self-motion information and by tethering to sensory cues in the surroundings through a plasticity mechanism. However, under natural settings, some of these sensory cues may temporarily disappear—for example, when clouds hide the sun—and prominent landmarks at different distances from the insect may move across the animal's field of view during translation, creating potential conflicts for a neural compass. We used two-photon calcium imaging in head-fixed Drosophila behaving in virtual reality to monitor the fly's compass during navigation in immersive naturalistic environments with approachable local landmarks. We found that the fly's compass remains stable even in these settings by tethering to available global cues, likely preserving the animal's ability to perform compass-driven behaviors such as maintaining a constant heading.

Hundreds of millions of structured proteins sustain life through chemical interactions and catalytic reactions1. Though dynamic, these proteins are assumed to be built upon fixed scaffolds of secondary structure, α-helices and β-sheets. Experimentally determined structures of over >58,000 non-redundant proteins support this assumption, though it has recently been challenged by ∼100 fold-switching proteins2. These “metamorphic3” proteins, though ostensibly rare, raise the question of how many uncharacterized proteins have shapeshifting–rather than fixed–secondary structures. To address this question, we developed a comparative sequence-based approach that predicts fold-switching proteins from differences in secondary structure propensity. We applied this approach to the universally conserved NusG transcription factor family of ∼15,000 proteins, one of which has a 50-residue regulatory subunit experimentally shown to switch between α-helical and β-sheet folds4. Our approach predicted that 25% of the sequences in this family undergo similar α-helix ⇌ β-sheet transitions, a frequency two orders of magnitude larger than previously observed. Our predictions evade state-of-the-art computational methods but were confirmed experimentally by circular dichroism and nuclear magnetic resonance spectroscopy for all 10 assiduously chosen dissimilar variants. These results suggest that fold switching is a pervasive mechanism of transcriptional regulation in all kingdoms of life and imply that numerous uncharacterized proteins may also switch folds.

The protein folding paradigm asserts that the three-dimensional structure of a protein is determined by its amino acid sequence. Here we show that a substantial population of proteins from the NusG superfamily of transcription factors do not adhere to this paradigm. Previous work demonstrated that one member of this superfamily has a regulatory domain that completely switches between α-helical and β-sheet folds, but the pervasiveness of this fold-switching mechanism is uncertain. To address this question, we developed a sequence-based predictor, which revealed that thousands of proteins from this superfamily switch folds. Circular dichroism and nuclear magnetic resonance spectroscopies of 10 sequence-diverse variants confirmed our predictions. By contrast, state-of-the-art methods based on the protein folding paradigm assume that related sequences adopt the same fold and thus predicted that the regulatory domains of all variants adopt only the β-sheet fold. Removal of this bias revealed that residue-residue contacts from both α-helical and β-sheet folds are conserved in a large subpopulation of fold-switching domains, poising them to assume disparate conformations. Our results suggest that fold switching is a pervasive mechanism of transcriptional regulation in all kingdoms of life and indicate that expanding the protein folding paradigm may reveal the involvement of fold-switching proteins in diverse biological processes.

The Meissner corpuscle, a mechanosensory end organ, was discovered more than 165 years ago and has since been found in the glabrous skin of all mammals, including that on human fingertips. Although prominently featured in textbooks, the function of the Meissner corpuscle is unknown. Neubarth et al. generated adult mice without Meissner corpuscles and used them to show that these corpuscles alone mediate behavioral responses to, and perception of, gentle forces (see the Perspective by Marshall and Patapoutian). Each Meissner corpuscle is innervated by two molecularly distinct, yet physiologically similar, mechanosensory neurons. These two neuronal subtypes are developmentally interdependent and their endings are intertwined within the corpuscle. Both Meissner mechanosensory neuron subtypes are homotypically tiled, ensuring uniform and complete coverage of the skin, yet their receptive fields are overlapping and offset with respect to each other. Science, this issue p. eabb2751; see also p. 1311 Light touch perception and fine sensorimotor control arise from spatially overlapping mechanoreceptors of the Meissner corpuscle. Meissner corpuscles are mechanosensory end organs that densely occupy mammalian glabrous skin. We generated mice that selectively lacked Meissner corpuscles and found them to be deficient in both perceiving the gentlest detectable forces acting on glabrous skin and fine sensorimotor control. We found that Meissner corpuscles are innervated by two mechanoreceptor subtypes that exhibit distinct responses to tactile stimuli. The anatomical receptive fields of these two mechanoreceptor subtypes homotypically tile glabrous skin in a manner that is offset with respect to one another. Electron microscopic analysis of the two Meissner afferents within the corpuscle supports a model in which the extent of lamellar cell wrappings of mechanoreceptor endings determines their force sensitivity thresholds and kinetic properties.