Adult stem cells are responsible for life-long tissue maintenance. They reside in and interact with specialized tissue microenvironments (niches). Using murine hair follicle as a model, we show that when junctional perturbations in the niche disrupt barrier function, adjacent stem cells dramatically change their transcriptome independent of bacterial invasion and become capable of directly signaling to and recruiting immune cells. Additionally, these stem cells elevate cell cycle transcripts which reduce their quiescence threshold, enabling them to selectively proliferate within this microenvironment of immune distress cues. However, rather than mobilizing to fuel new tissue regeneration, these ectopically proliferative stem cells remain within their niche to contain the breach. Together, our findings expose a potential communication relay system that operates from the niche to the stem cells to the immune system and back. The repurposing of proliferation by these stem cells patch the breached barrier, stoke the immune response and restore niche integrity.

Seven neuropeptides are expressed within the Drosophila brain circadian network. Our previous mRNA profiling suggested that Allatostatin-C (AstC) is an eighth neuropeptide and specifically expressed in dorsal clock neurons (DN1s). Our results here show that AstC is, indeed, expressed in DN1s, where it oscillates. AstC is also expressed in two less well-characterized circadian neuronal clusters, the DN3s and lateral-posterior neurons (LPNs). Behavioral experiments indicate that clock-neuron-derived AstC is required to mediate evening locomotor activity under short (winter-like) and long (summer-like) photoperiods. The AstC-Receptor 2 (AstC-R2) is expressed in LNds, the clock neurons that drive evening locomotor activity, and AstC-R2 is required in these neurons to modulate the same short photoperiod evening phenotype. Ex vivo calcium imaging indicates that AstC directly inhibits a single LNd. The results suggest that a novel AstC/AstC-R2 signaling pathway, from dorsal circadian neurons to an LNd, regulates the evening phase in Drosophila.

Granule cells (GCs) in the cerebellar cortex are important for sparse encoding of afferent sensorimotor information. Modeling studies show that GCs can perform their function most effectively when they have four dendrites. Indeed, mature GCs have four short dendrites on average, each terminating in a claw-like ending that receives both excitatory and inhibitory inputs. Immature GCs, however, have significantly more dendrites-all without claws. How these redundant dendrites are refined during development is largely unclear. Here, we used in vivo time-lapse imaging and immunohistochemistry to study developmental refinement of GC dendritic arbors and its relation to synapse formation. We found that while the formation of dendritic claws stabilized the dendrites, the selection of surviving dendrites was made before claw formation, and longer immature dendrites had a significantly higher chance of survival than shorter dendrites. Using immunohistochemistry, we show that glutamatergic and GABAergic synapses are transiently formed on immature GC dendrites, and the number of GABAergic, but not glutamatergic, synapses correlates with the length of immature dendrites. Together, these results suggest a potential role of transient GABAergic synapses on dendritic selection and show that preselected dendrites are stabilized by the formation of dendritic claws-the site of mature synapses.

A fundamental goal of systems neuroscience is to understand how neural activity gives rise to natural behavior. In order to achieve this goal, we must first build comprehensive models that offer quantitative descriptions of behavior. We develop a new class of probabilistic models to tackle this challenge in the study of larval zebrafish, an important model organism for neuroscience. Larval zebrafish locomote via sequences of punctate swim bouts--brief flicks of the tail--which are naturally modeled as a marked point process. However, these sequences of swim bouts belie a set of discrete and continuous internal states, latent variables that are not captured by standard point process models. We incorporate these variables as latent marks of a point process and explore various models for their dynamics. To infer the latent variables and fit the parameters of this model, we develop an amortized variational inference algorithm that targets the collapsed posterior distribution, analytically marginalizing out the discrete latent variables. With a dataset of over 120,000 swim bouts, we show that our models reveal interpretable discrete classes of swim bouts and continuous internal states like hunger that modulate their dynamics. These models are a major step toward understanding the natural behavioral program of the larval zebrafish and, ultimately, its neural underpinnings.

Whole-brain imaging allows for comprehensive functional mapping of distributed neural pathways, but neuronal perturbation experiments are usually limited to targeting predefined regions or genetically identifiable cell types. To complement whole-brain measures of activity with brain-wide manipulations for testing causal interactions, we introduce a system that uses measuredactivity patterns to guide optical perturbations of any subset of neurons in the same fictively behaving larval zebrafish. First, a light-sheet microscope collects whole-brain data that are rapidly analyzed by a distributed computing system to generate functional brain maps. On the basis of these maps, the experimenter can then optically ablate neurons and image activity changes across the brain. We applied this method to characterize contributions of behaviorally tuned populations to the optomotor response. We extended the system to optogenetically stimulate arbitrary subsets of neurons during whole-brain imaging. These open-source methods enable delineating the contributions of neurons to brain-wide circuit dynamics and behavior in individual animals.

Binding between DIP and Dpr neuronal recognition proteins has been proposed to regulate synaptic connections between lamina and medulla neurons in the Drosophila visual system. Each lamina neuron was previously shown to express many Dprs. Here, we demonstrate, by contrast, that their synaptic partners typically express one or two DIPs, with binding specificities matched to the lamina neuron-expressed Dprs. A deeper understanding of the molecular logic of DIP/Dpr interaction requires quantitative studies on the properties of these proteins. We thus generated a quantitative affinity-based DIP/Dpr interactome for all DIP/Dpr protein family members. This revealed a broad range of affinities and identified homophilic binding for some DIPs and some Dprs. These data, along with full-length ectodomain DIP/Dpr and DIP/DIP crystal structures, led to the identification of molecular determinants of DIP/Dpr specificity. This structural knowledge, along with a comprehensive set of quantitative binding affinities, provides new tools for functional studies in vivo.

Single-particle electron cryo-microscopy and computational image classification can be used to analyze structural variability in macromolecules and their assemblies. In some cases, a particle may contain different regions that each display a range of distinct conformations. We have developed strategies, implemented within the Frealign and cisTEM image processing packages, to focus classify on specific regions of a particle and detect potential covariance. The strategies are based on masking the region of interest using either a 2-D mask applied to reference projections and particle images, or a 3-D mask applied to the 3-D volume. We show that focused classification approaches can be used to study structural covariance, a concept that is likely to gain more importance as datasets grow in size, allowing the distinction of more structural states and smaller differences between states. Finally, we apply the approaches to an experimental dataset containing the HIV-1 Transactivation Response (TAR) element RNA fused into the large bacterial ribosomal subunit to deconvolve structural mobility within localized regions of interest, and to a dataset containing assembly intermediates of the large subunit to measure structural covariance.

Macroscale fluorescence imaging is increasingly used to observe biological samples. However, it may suffer from spectral interferences that originate from ambient light or autofluorescence of the sample or its support. In this manuscript, we built a simple and inexpensive fluorescence macroscope, which has been used to evaluate the performance of Speed OPIOM (Out of Phase Imaging after Optical Modulation), which is a reference-free dynamic contrast protocol, to selectively image reversibly photoswitchable fluorophores as labels against detrimental autofluorescence and ambient light. By tuning the intensity and radial frequency of the modulated illumination to the Speed OPIOM resonance and adopting a phase-sensitive detection scheme that ensures noise rejection, we enhanced the sensitivity and the signal-to-noise ratio for fluorescence detection in blot assays by factors of 50 and 10, respectively, over direct fluorescence observation under constant illumination. Then, we overcame the strong autofluorescence of growth media that are currently used in microbiology and realized multiplexed fluorescence observation of colonies of spectrally similar fluorescent bacteria with a unique configuration of excitation and emission wavelengths. Finally, we easily discriminated fluorescent labels from the autofluorescent and reflective background in labeled leaves, even under the interference of incident light at intensities that are comparable to sunlight. The proposed approach is expected to find multiple applications, from biological assays to outdoor observations, in fluorescence macroimaging.

A complex nervous system requires precise numbers of various neuronal types produced with exquisite spatiotemporal control. This striking diversity is generated by a limited number of neural stem cells (NSC), where spatial and temporal patterning intersect. Drosophila is a genetically tractable model system that has significant advantages for studying stem cell biology and neuronal fate specification. Here we review the latest findings in the rich literature of temporal patterning of neuronal identity in the Drosophila central nervous system. Rapidly changing consecutive transcription factors expressed in NSCs specify short series of neurons with considerable differences. More slowly progressing changes are orchestrated by NSC intrinsic temporal factor gradients which integrate extrinsic signals to coordinate nervous system and organismal development.

PURPOSE: To develop switchable and tunable labels with high contrast ratio for MRI using magnetocaloric materials that have sharp first-order magnetic phase transitions at physiological temperatures and typical MRI magnetic field strengths.

METHODS: A prototypical magnetocaloric material iron-rhodium (FeRh) was prepared by melt mixing, high-temperature annealing, and ice-water quenching. Temperature- and magnetic field-dependent magnetization measurements of wire-cut FeRh samples were performed on a vibrating sample magnetometer. Temperature-dependent MRI of FeRh samples was performed on a 4.7T MRI.

RESULTS: Temperature-dependent MRI clearly demonstrated image contrast changes due to the sharp magnetic state transition of the FeRh samples in the MRI magnetic field (4.7T) and at a physiologically relevant temperature (~37°C).

CONCLUSION: A magnetocaloric material, FeRh, was demonstrated to act as a high contrast ratio switchable MRI contrast agent due to its sharp first-order magnetic phase transition in the DC magnetic field of MRI and at physiologically relevant temperatures. A wide range of magnetocaloric materials are available that can be tuned by materials science techniques to optimize their response under MRI-appropriate conditions and be controllably switched in situ with temperature, magnetic field, or a combination of both.