Analysis of differential gene expression is crucial for the study of cell fate and behavior during embryonic development. However, automated methods for the sensitive detection and quantification of RNAs at cellular resolution in embryos are lacking. With the advent of single-molecule fluorescence in situ hybridization (smFISH), gene expression can be analyzed at single-molecule resolution. However, the limited availability of protocols for smFISH in embryos and the lack of efficient image analysis pipelines have hampered quantification at the (sub)cellular level in complex samples such as tissues and embryos. Here, we present a protocol for smFISH on zebrafish embryo sections in combination with an image analysis pipeline for automated transcript detection and cell segmentation. We use this strategy to quantify gene expression differences between different cell types and identify differences in subcellular transcript localization between genes. The combination of our smFISH protocol and custom-made, freely available, analysis pipeline will enable researchers to fully exploit the benefits of quantitative transcript analysis at cellular and subcellular resolution in tissues and embryos.

This protocol describes a method to obtain spatially resolved proteomic maps of specific compartments within living mammalian cells. An engineered peroxidase, APEX2, is genetically targeted to a cellular region of interest. Upon the addition of hydrogen peroxide for 1 min to cells preloaded with a biotin-phenol substrate, APEX2 generates biotin-phenoxyl radicals that covalently tag proximal endogenous proteins. Cells are then lysed, and biotinylated proteins are enriched with streptavidin beads and identified by mass spectrometry. We describe the generation of an appropriate APEX2 fusion construct, proteomic sample preparation, and mass spectrometric data acquisition and analysis. A two-state stable isotope labeling by amino acids in cell culture (SILAC) protocol is used for proteomic mapping of membrane-enclosed cellular compartments from which APEX2-generated biotin-phenoxyl radicals cannot escape. For mapping of open cellular regions, we instead use a 'ratiometric' three-state SILAC protocol for high spatial specificity. Isotopic labeling of proteins takes 5–7 cell doublings. Generation of the biotinylated proteomic sample takes 1 d, acquiring the mass spectrometric data takes 2–5 d and analysis of the data to obtain the final proteomic list takes 1 week.

Many animals use visual signals to estimate motion. Canonical models suppose that animals estimate motion by cross-correlating pairs of spatiotemporally separated visual signals, but recent experiments indicate that humans and flies perceive motion from higher-order correlations that signify motion in natural environments. Here we show how biologically plausible processing motifs in neural circuits could be tuned to extract this information. We emphasize how known aspects of Drosophila's visual circuitry could embody this tuning and predict fly behavior. We find that segregating motion signals into ON/OFF channels can enhance estimation accuracy by accounting for natural light/dark asymmetries. Furthermore, a diversity of inputs to motion detecting neurons can provide access to more complex higher-order correlations. Collectively, these results illustrate how non-canonical computations improve motion estimation with naturalistic inputs. This argues that the complexity of the fly's motion computations, implemented in its elaborate circuits, represents a valuable feature of its visual motion estimator.

Members of the ArsR/SmtB family of transcriptional repressors, such as CadC, regulate the intracellular levels of heavy metals like Cd(II), Hg(II), and Pb(II). These metal sensing proteins bind their target metals with high specificity and affinity, however, a lack of structural information about these proteins makes defining the coordination sphere of the target metal difficult. Lingering questions as to the identity of Cd(II) coordination in CadC are addressed via protein design techniques. Two designed peptides with tetrathiolate metal binding sites were prepared and characterized, revealing fast exchange between CdS3O and CdS4 coordination spheres. Correlation of (111m)Cd PAC spectroscopy and (113)Cd NMR spectroscopy suggests that Cd(II) coordinated to CadC is in fast exchange between CdS3O and CdS4 forms, which may provide a mechanism for rapid sensing of heavy metal contaminants by this regulatory protein.

Alzheimer's disease (AD) is a fatal neurodegenerative disorder in humans and the main cause of dementia in aging societies. The disease is characterized by the aberrant formation of β-amyloid (Aβ) peptide oligomers and fibrils. These structures may damage the brain and give rise to cerebral amyloid angiopathy, neuronal dysfunction, and cellular toxicity. Although the connection between AD and Aβ fibrillation is extensively documented, much is still unknown about the formation of these Aβ aggregates and their structures at the molecular level. Here, we combined electron cryomicroscopy, 3D reconstruction, and integrative structural modeling methods to determine the molecular architecture of a fibril formed by Aβ(1-42), a particularly pathogenic variant of Aβ peptide. Our model reveals that the individual layers of the Aβ fibril are formed by peptide dimers with face-to-face packing. The two peptides forming the dimer possess identical tilde-shaped conformations and interact with each other by packing of their hydrophobic C-terminal β-strands. The peptide C termini are located close to the main fibril axis, where they produce a hydrophobic core and are surrounded by the structurally more flexible and charged segments of the peptide N termini. The observed molecular architecture is compatible with the general chemical properties of Aβ peptide and provides a structural basis for various biological observations that illuminate the molecular underpinnings of AD. Moreover, the structure provides direct evidence for a steric zipper within a fibril formed by full-length Aβ peptide.

In order to localize the neural circuits involved in generating behaviors, it is necessary to assign activity onto anatomical maps of the nervous system. Using brain registration across hundreds of larval zebrafish, we have built an expandable open-source atlas containing molecular labels and definitions of anatomical regions, the Z-Brain. Using this platform and immunohistochemical detection of phosphorylated extracellular signal–regulated kinase (ERK) as a readout of neural activity, we have developed a system to create and contextualize whole-brain maps of stimulus- and behavior-dependent neural activity. This mitogen-activated protein kinase (MAP)-mapping assay is technically simple, and data analysis is completely automated. Because MAP-mapping is performed on freely swimming fish, it is applicable to studies of nearly any stimulus or behavior. Here we demonstrate our high-throughput approach using pharmacological, visual and noxious stimuli, as well as hunting and feeding. The resultant maps outline hundreds of areas associated with behaviors.

How metazoan mechanotransduction channels sense mechanical stimuli is not well understood. The NOMPC channel in the transient receptor potential (TRP) family, a mechanotransduction channel for Drosophila touch sensation and hearing, contains 29 Ankyrin repeats (ARs) that associate with microtubules. These ARs have been postulated to act as a tether that conveys force to the channel. Here, we report that these N-terminal ARs form a cytoplasmic domain essential for NOMPC mechanogating in vitro, mechanosensitivity of touch receptor neurons in vivo, and touch-induced behaviors of Drosophila larvae. Duplicating the ARs elongates the filaments that tether NOMPC to microtubules in mechanosensory neurons. Moreover, microtubule association is required for NOMPC mechanogating. Importantly, transferring the NOMPC ARs to mechanoinsensitive voltage-gated potassium channels confers mechanosensitivity to the chimeric channels. These experiments strongly support a tether mechanism of mechanogating for the NOMPC channel, providing insights into the basis of mechanosensitivity of mechanotransduction channels.

We determined how learning modifies neural representations in primary visual cortex (V1) during acquisition of a visually guided behavioral task. We imaged the activity of the same layer 2/3 neuronal populations as mice learned to discriminate two visual patterns while running through a virtual corridor, where one pattern was rewarded. Improvements in behavioral performance were closely associated with increasingly distinguishable population-level representations of task-relevant stimuli, as a result of stabilization of existing and recruitment of new neurons selective for these stimuli. These effects correlated with the appearance of multiple task-dependent signals during learning: those that increased neuronal selectivity across the population when expert animals engaged in the task, and those reflecting anticipation or behavioral choices specifically in neuronal subsets preferring the rewarded stimulus. Therefore, learning engages diverse mechanisms that modify sensory and non-sensory representations in V1 to adjust its processing to task requirements and the behavioral relevance of visual stimuli.

The mammalian hippocampus is crucial for episodic memory formation and transiently retains information for about 3-4 weeks in adult mice and longer in humans. Although neuroscientists widely believe that neural synapses are elemental sites of information storage, there has been no direct evidence that hippocampal synapses persist for time intervals commensurate with the duration of hippocampal-dependent memory. Here we tested the prediction that the lifetimes of hippocampal synapses match the longevity of hippocampal memory. By using time-lapse two-photon microendoscopy in the CA1 hippocampal area of live mice, we monitored the turnover dynamics of the pyramidal neurons' basal dendritic spines, postsynaptic structures whose turnover dynamics are thought to reflect those of excitatory synaptic connections. Strikingly, CA1 spine turnover dynamics differed sharply from those seen previously in the neocortex. Mathematical modelling revealed that the data best matched kinetic models with a single population of spines with a mean lifetime of approximately 1-2 weeks. This implies ∼100% turnover in ∼2-3 times this interval, a near full erasure of the synaptic connectivity pattern. Although N-methyl-d-aspartate (NMDA) receptor blockade stabilizes spines in the neocortex, in CA1 it transiently increased the rate of spine loss and thus lowered spine density. These results reveal that adult neocortical and hippocampal pyramidal neurons have divergent patterns of spine regulation and quantitatively support the idea that the transience of hippocampal-dependent memory directly reflects the turnover dynamics of hippocampal synapses.

Unicellular organisms exhibit elaborate collective behaviors in response to environmental cues. These behaviors are controlled by complex biochemical networks within individual cells and coordinated through cell-to-cell communication. Describing these behaviors requires new mathematical models that can bridge scales-from biochemical networks within individual cells to spatially structured cellular populations. Here we present a family of "multiscale" models for the emergence of spiral waves in the social amoeba Dictyostelium discoideum. Our models exploit new experimental advances that allow for the direct measurement and manipulation of the small signaling molecule cyclic adenosine monophosphate (cAMP) used by Dictyostelium cells to coordinate behavior in cellular populations. Inspired by recent experiments, we model the Dictyostelium signaling network as an excitable system coupled to various preprocessing modules. We use this family of models to study spatially unstructured populations of "fixed" cells by constructing phase diagrams that relate the properties of population-level oscillations to parameters in the underlying biochemical network. We then briefly discuss an extension of our model that includes spatial structure and show how this naturally gives rise to spiral waves. Our models exhibit a wide range of novel phenomena. including a density-dependent frequency change, bistability, and dynamic death due to slow cAMP dynamics. Our modeling approach provides a powerful tool for bridging scales in modeling of Dictyostelium populations.