Aggressive social interactions are used to compete for limited resources and are regulated by complex sensory cues and the organism's internal state. While both sexes exhibit aggression, its neuronal underpinnings are understudied in females. Here, we identify a population of sexually dimorphic aIPg neurons in the adult central brain whose optogenetic activation increased, and genetic inactivation reduced, female aggression. Analysis of GAL4 lines identified in an unbiased screen for increased female chasing behavior revealed the involvement of another sexually dimorphic neuron, pC1d, and implicated aIPg and pC1d neurons as core nodes regulating female aggression. Connectomic analysis demonstrated that aIPg neurons and pC1d are interconnected and suggest that aIPg neurons may exert part of their effect by gating the flow of visual information to descending neurons. Our work reveals important regulatory components of the neuronal circuitry that underlies female aggressive social interactions and provides tools for their manipulation.

Piloerection (goosebumps) requires concerted actions of the hair follicle, the arrector pili muscle (APM), and the sympathetic nerve, providing a model to study interactions across epithelium, mesenchyme, and nerves. Here, we show that APMs and sympathetic nerves form a dual-component niche to modulate hair follicle stem cell (HFSC) activity. Sympathetic nerves form synapse-like structures with HFSCs and regulate HFSCs through norepinephrine, whereas APMs maintain sympathetic innervation to HFSCs. Without norepinephrine signaling, HFSCs enter deep quiescence by down-regulating the cell cycle and metabolism while up-regulating quiescence regulators Foxp1 and Fgf18. During development, HFSC progeny secretes Sonic Hedgehog (SHH) to direct the formation of this APM-sympathetic nerve niche, which in turn controls hair follicle regeneration in adults. Our results reveal a reciprocal interdependence between a regenerative tissue and its niche at different stages and demonstrate sympathetic nerves can modulate stem cells through synapse-like connections and neurotransmitters to couple tissue production with demands.

Cells alter their mechanical properties in response to their local microenvironment; this plays a role in determining cell function and can even influence stem cell fate. Here, we identify a robust and unified relationship between cell stiffness and cell volume. As a cell spreads on a substrate, its volume decreases, while its stiffness concomitantly increases. We find that both cortical and cytoplasmic cell stiffness scale with volume for numerous perturbations, including varying substrate stiffness, cell spread area, and external osmotic pressure. The reduction of cell volume is a result of water efflux, which leads to a corresponding increase in intracellular molecular crowding. Furthermore, we find that changes in cell volume, and hence stiffness, alter stem-cell differentiation, regardless of the method by which these are induced. These observations reveal a surprising, previously unidentified relationship between cell stiffness and cell volume that strongly influences cell biology.

The utility of small molecules to probe or perturb biological systems is limited by the lack of cell-specificity. "Masking" the activity of small molecules using a general chemical modification and "unmasking" it only within target cells overcomes this limitation. To this end, we have developed a selective enzyme-substrate pair consisting of engineered variants of E. coli nitroreductase (NTR) and a 2-nitro- N-methylimidazolyl (NM) masking group. To discover and optimize this NTR-NM system, we synthesized a series of fluorogenic substrates containing different nitroaromatic masking groups, confirmed their stability in cells, and identified the best substrate for NTR. We then engineered the enzyme for improved activity in mammalian cells, ultimately yielding an enzyme variant (enhanced NTR, or eNTR) that possesses up to 100-fold increased activity over wild-type NTR. These improved NTR enzymes combined with the optimal NM masking group enable rapid, selective unmasking of dyes, indicators, and drugs to genetically defined populations of cells.

Dendritic cells (DCs) are specialized sentinel and APCs coordinating innate and adaptive immunity. Through proteins on their cell surface, DCs sense changes in the environment, internalize pathogens, present processed Ags, and communicate with other immune cells. By combining chemical labeling and quantitative mass spectrometry, we systematically profiled and compared the cell-surface proteomes of human primary conventional DCs (cDCs) in their resting and activated states. TLR activation by a lipopeptide globally reshaped the cell-surface proteome of cDCs, with >100 proteins upregulated or downregulated. By simultaneously elevating positive regulators and reducing inhibitory signals across multiple protein families, the remodeling creates a cell-surface milieu promoting immune responses. Still, cDCs maintain the stimulatory-to-inhibitory balance by leveraging a distinct set of inhibitory molecules. This analysis thus uncovers the molecular complexity and plasticity of the cDC cell surface and provides a roadmap for understanding cDC activation and signaling.

Repeated exposure to stressors is known to produce large-scale remodeling of neurons within the prefrontal cortex (PFC). Recent work suggests stress-related forms of structural plasticity can interact with aging to drive distinct patterns of pyramidal cell morphological changes. However, little is known about how other cellular components within PFC might be affected by these challenges. Here, we examined the effects of stress exposure and aging on medial prefrontal cortical glial subpopulations. Interestingly, we found no changes in glial morphology with stress exposure but a profound morphological change with aging. Furthermore, we found an upregulation of non-nuclear glucocorticoid receptors (GR) with aging, while nuclear levels remained largely unaffected. Both changes are selective for microglia, with no stress or aging effect found in astrocytes. Lastly, we show that the changes found within microglia inversely correlated with the density of dendritic spines on layer III pyramidal cells. These findings suggest microglia play a selective role in synaptic health within the aging brain.

Adaptive movements are critical to animal survival. To guide future actions, the brain monitors different outcomes, including achievement of movement and appetitive goals. The nature of outcome signals and their neuronal and network realization in motor cortex (M1), which commands the performance of skilled movements, is largely unknown. Using a dexterity task, calcium imaging, optogenetic perturbations, and behavioral manipulations, we studied outcome signals in murine M1. We find two populations of layer 2-3 neurons, “success”- and “failure” related neurons that develop with training and report end-result of trials. In these neurons, prolonged responses were recorded after success or failure trials, independent of reward and kinematics. In contrast, the initial state of layer-5 pyramidal tract neurons contains a memory trace of the previous trial’s outcome. Inter-trial cortical activity was needed to learn new task requirements. These M1 reflective layer-specific performance outcome signals, can support reinforcement motor learning of skilled behavior.

Spatial patterns of gene expression in the vertebrate brain are not independent, as pairs of genes can exhibit complex patterns of coexpression. Two genes may be similarly expressed in one region, but differentially expressed in other regions. These correlations have been studied quantitatively, particularly for the Allen Atlas of the adult mouse brain, but their biological meaning remains obscure. We propose a simple model of the coexpression patterns in terms of spatial distributions of underlying cell types and establish its plausibility using independently measured cell-type-specific transcriptomes. The model allows us to predict the spatial distribution of cell types in the mouse brain.

The study of synaptic specificity and plasticity in the CNS is limited by the inability to efficiently visualize synapses in identified neurons using light microscopy. Here, we describe synaptic tagging with recombination (STaR), a method for labeling endogenous presynaptic and postsynaptic proteins in a cell-type-specific fashion. We modified genomic loci encoding synaptic proteins within bacterial artificial chromosomes such that these proteins, expressed at endogenous levels and with normal spatiotemporal patterns, were labeled in an inducible fashion in specific neurons through targeted expression of site-specific recombinases. Within the Drosophila visual system, the number and distribution of synapses correlate with electron microscopy studies. Using two different recombination systems, presynaptic and postsynaptic specializations of synaptic pairs can be colabeled. STaR also allows synapses within the CNS to be studied in live animals noninvasively. In principle, STaR can be adapted to the mammalian nervous system.

Neocortical spiking dynamics control aspects of behavior, yet how these dynamics emerge during motor learning remains elusive. Activity-dependent synaptic plasticity is likely a key mechanism, as it reconfigures network architectures that govern neural dynamics. Here, we examined how the mouse premotor cortex acquires its well-characterized neural dynamics that control movement timing, specifically lick timing. To probe the role of synaptic plasticity, we have genetically manipulated proteins essential for major forms of synaptic plasticity, Ca2+/calmodulin-dependent protein kinase II (CaMKII) and Cofilin, in a region and cell-type-specific manner. Transient inactivation of CaMKII in the premotor cortex blocked learning of new lick timing without affecting the execution of learned action or ongoing spiking activity. Furthermore, among the major glutamatergic neurons in the premotor cortex, CaMKII and Cofilin activity in pyramidal tract (PT) neurons, but not intratelencephalic (IT) neurons, is necessary for learning. High-density electrophysiology in the premotor cortex uncovered that neural dynamics anticipating licks are progressively shaped during learning, which explains the change in lick timing. Such reconfiguration in behaviorally relevant dynamics is impeded by CaMKII manipulation in PT neurons. Altogether, the activity of plasticity-related proteins in PT neurons plays a central role in sculpting neocortical dynamics to learn new behavior.