Hippocampal activity represents many behaviorally important variables, including context, an animal's location within a given environmental context, time, and reward. Using longitudinal calcium imaging in mice, multiple large virtual environments, and differing reward contingencies, we derived a unified probabilistic model of CA1 representations centered on a single feature-the field propensity. Each cell's propensity governs how many place fields it has per unit space, predicts its reward-related activity, and is preserved across distinct environments and over months. Propensity is broadly distributed-with many low, and some very high, propensity cells-and thus strongly shapes hippocampal representations. This results in a range of spatial codes, from sparse to dense. Propensity varied ∼10-fold between adjacent cells in salt-and-pepper fashion, indicating substantial functional differences within a presumed cell type. Intracellular recordings linked propensity to cell excitability. The stability of each cell's propensity across conditions suggests this fundamental property has anatomical, transcriptional, and/or developmental origins.

Acetyl esterases from carbohydrate esterase family 7 exhibit unusual substrate specificity. These proteins catalyze the cleavage of disparate acetate esters with high efficiency, but are unreactive to larger acyl groups. The structural basis for this distinct selectivity profile is unknown. Here, we investigate a thermostable acetyl esterase (TM0077) from Thermotoga maritima using evolutionary relationships, structural information, fluorescent kinetic measurements, and site directed mutagenesis. We measured the kinetic and structural determinants for this specificity using a diverse series of small molecule enzyme substrates, including novel fluorogenic esters. These experiments identified two hydrophobic plasticity residues (Pro228, and Ile276) surrounding the nucleophilic serine that impart this specificity of TM0077 for small, straight-chain esters. Substitution of these residues with alanine imparts broader specificity to TM0077 for the hydrolysis of longer and bulkier esters. Our results suggest the specificity of acetyl esterases have been finely tuned by evolution to catalyze the removal of acetate groups from diverse substrates, but can be modified by focused amino acid substitutions to yield enzymes capable of cleaving larger ester functionalities.

Approximately one-third of global CO fixation occurs in a phase-separated algal organelle called the pyrenoid. The existing data suggest that the pyrenoid forms by the phase separation of the CO-fixing enzyme Rubisco with a linker protein; however, the molecular interactions underlying this phase separation remain unknown. Here we present the structural basis of the interactions between Rubisco and its intrinsically disordered linker protein Essential Pyrenoid Component 1 (EPYC1) in the model alga Chlamydomonas reinhardtii. We find that EPYC1 consists of five evenly spaced Rubisco-binding regions that share sequence similarity. Single-particle cryo-electron microscopy of these regions in complex with Rubisco indicates that each Rubisco holoenzyme has eight binding sites for EPYC1, one on each Rubisco small subunit. Interface mutations disrupt binding, phase separation and pyrenoid formation. Cryo-electron tomography supports a model in which EPYC1 and Rubisco form a codependent multivalent network of specific low-affinity bonds, giving the matrix liquid-like properties. Our results advance the structural and functional understanding of the phase separation underlying the pyrenoid, an organelle that plays a fundamental role in the global carbon cycle.

Approximately one-third of global CO fixation occurs in a phase-separated algal organelle called the pyrenoid. The existing data suggest that the pyrenoid forms by the phase separation of the CO-fixing enzyme Rubisco with a linker protein; however, the molecular interactions underlying this phase separation remain unknown. Here we present the structural basis of the interactions between Rubisco and its intrinsically disordered linker protein Essential Pyrenoid Component 1 (EPYC1) in the model alga Chlamydomonas reinhardtii. We find that EPYC1 consists of five evenly spaced Rubisco-binding regions that share sequence similarity. Single-particle cryo-electron microscopy of these regions in complex with Rubisco indicates that each Rubisco holoenzyme has eight binding sites for EPYC1, one on each Rubisco small subunit. Interface mutations disrupt binding, phase separation and pyrenoid formation. Cryo-electron tomography supports a model in which EPYC1 and Rubisco form a codependent multivalent network of specific low-affinity bonds, giving the matrix liquid-like properties. Our results advance the structural and functional understanding of the phase separation underlying the pyrenoid, an organelle that plays a fundamental role in the global carbon cycle.

In this paper, we provide a historical account of the contribution of a single line of research to our current understanding of the structure of cis-regulatory regions and the genetic basis for morphological evolution. We revisit the experiments that shed light on the evolution of larval cuticular patterns within the genus Drosophila and the evolution and structure of the shavenbaby gene. We describe the experiments that led to the discovery that multiple genetic changes in the cis-regulatory region of shavenbaby caused the loss of dorsal cuticular hairs (quaternary trichomes) in first instar larvae of Drosophila sechellia. We also discuss the experiments that showed that the convergent loss of quaternary trichomes in D. sechellia and Drosophila ezoana was generated by parallel genetic changes in orthologous enhancers of shavenbaby. We discuss the observation that multiple shavenbaby enhancers drive overlapping patterns of expression in the embryo and that these apparently redundant enhancers ensure robust shavenbaby expression and trichome morphogenesis under stressful conditions. All together, these data, collected over 13 years, provide a fundamental case study in the fields of gene regulation and morphological evolution, and highlight the importance of prolonged, detailed studies of single genes.

Chromosomes must be accurately partitioned to daughter cells to prevent aneuploidy, a hallmark of many tumors and birth defects. Kinetochores are the macromolecular machines that segregate chromosomes by maintaining load-bearing attachments to the dynamic tips of microtubules. Here, we present the structure of isolated budding-yeast kinetochore particles, as visualized by EM and electron tomography of negatively stained preparations. The kinetochore appears as an  126-nm particle containing a large central hub surrounded by multiple outer globular domains. In the presence of microtubules, some particles also have a ring that encircles the microtubule. Our data, showing that kinetochores bind to microtubules via multivalent attachments, lay the foundation to uncover the key mechanical and regulatory mechanisms by which kinetochores control chromosome segregation and cell division.

Understanding cortical circuits will require mapping the connections between specific populations of neurons, as well as determining the dendritic locations where the synapses occur. The dendrites of individual cortical neurons overlap with numerous types of local and long-range excitatory axons, but axodendritic overlap is not always a good predictor of actual connection strength. Here we developed an efficient channelrhodopsin-2 (ChR2)-assisted method to map the spatial distribution of synaptic inputs, defined by presynaptic ChR2 expression, within the dendritic arborizations of recorded neurons. We expressed ChR2 in two thalamic nuclei, the whisker motor cortex and local excitatory neurons and mapped their synapses with pyramidal neurons in layers 3, 5A and 5B (L3, L5A and L5B) in the mouse barrel cortex. Within the dendritic arborizations of L3 cells, individual inputs impinged onto distinct single domains. These domains were arrayed in an orderly, monotonic pattern along the apical axis: axons from more central origins targeted progressively higher regions of the apical dendrites. In L5 arborizations, different inputs targeted separate basal and apical domains. Input to L3 and L5 dendrites in L1 was related to whisker movement and position, suggesting that these signals have a role in controlling the gain of their target neurons. Our experiments reveal high specificity in the subcellular organization of excitatory circuits.

In the hippocampus, the classical pyramidal cell type of the subiculum acts as a primary output, conveying hippocampal signals to a diverse suite of downstream regions. Accumulating evidence suggests that the subiculum pyramidal cell population may actually be comprised of discrete subclasses. Here, we investigated the extent and organizational principles governing pyramidal cell heterogeneity throughout the mouse subiculum. Using single-cell RNA-seq, we find that the subiculum pyramidal cell population can be deconstructed into eight separable subclasses. These subclasses were mapped onto abutting spatial domains, ultimately producing a complex laminar and columnar organization with heterogeneity across classical dorsal-ventral, proximal-distal, and superficial-deep axes. We further show that these transcriptomically defined subclasses correspond to differential protein products and can be associated with specific projection targets. This work deconstructs the complex landscape of subiculum pyramidal cells into spatially segregated subclasses that may be observed, controlled, and interpreted in future experiments.

The tilt illusion - a bias in the perceived orientation of a center stimulus induced by an oriented surround - illustrates how context shapes visual perception. While the tilt illusion has been the subject of quantitative study for over 85 years, we still lack a comprehensive account of the phenomenon that connects its neural and behavioral characteristics. Here, we demonstrate that the tilt illusion originates from a dynamic change in neural coding precision induced by the surround context. We simultaneously obtained psychophysical and fMRI responses from human subjects while they viewed gratings in the absence and presence of an oriented surround, and extracted sensory encoding precision from their behavioral and neural data. Both measures show that in the absence of a surround, encoding reflects the natural scene statistics of orientation. However, in the presence of an oriented surround, encoding precision is significantly increased for stimuli similar to the surround orientation. This local change in encoding is sufficient to accurately predict the behavioral characteristics of the tilt illusion using a Bayesian observer model. The effect of surround modulation increases along the ventral stream, and is localized to the portion of the visual cortex with receptive fields at the center-surround boundary. The pattern of change in coding accuracy reflects the surround-conditioned orientation statistics in natural scenes, but cannot be explained by local stimulus configuration. Our results suggest that the tilt illusion naturally emerges from a dynamic coding strategy that efficiently reallocates neural coding resources based on the current stimulus context.

Animals adapt their behavior in response to informative sensory cues using multiple brain circuits. The activity of midbrain dopaminergic neurons is thought to convey a critical teaching signal: reward-prediction error. Although reward-prediction error signals are thought to be essential to learning, little is known about the dynamic changes in the activity of midbrain dopaminergic neurons as animals learn about novel sensory cues and appetitive rewards. Here we describe a large dataset of cell-attached recordings of identified dopaminergic neurons as naive mice learned a novel cue-reward association. During learning midbrain dopaminergic neuron activity results from the summation of sensory cue-related and movement initiation-related response components. These components are both a function of reward expectation yet they are dissociable. Learning produces an increasingly precise coordination of action initiation following sensory cues that results in apparent reward-prediction error correlates. Our data thus provide new insights into the circuit mechanisms that underlie a critical computation in a highly conserved learning circuit.