Cognition encompasses a range of higher-order mental processes, such as attention, working memory, and model-based decision-making. These processes are thought to involve the dynamic interaction of multiple central brain regions. A mechanistic understanding of such computations requires not only monitoring and manipulating specific neural populations during behavior, but also knowing the connectivity of the underlying circuitry. These goals are experimentally challenging in mammals, but are feasible in numerically simpler insect brains. In Drosophila melanogaster in particular, genetic tools enable precisely targeted physiology and optogenetics in actively behaving animals. In this article we discuss how these advantages are increasingly being leveraged to study abstract neural representations and sensorimotor computations that may be relevant for cognition in both insects and mammals.

Cortical neurons exhibit temporally irregular spiking patterns and heterogeneous firing rates. These features arise in model circuits operating in a 'fluctuation-driven regime', in which fluctuations in membrane potentials emerge from the network dynamics. However, it is still debated whether the cortex operates in such a regime. We evaluated the fluctuation-driven hypothesis by analyzing spiking and sub-threshold membrane potentials of neurons in the frontal cortex of mice performing a decision-making task. We showed that while standard fluctuation-driven models successfully account for spiking statistics, they fall short in capturing the heterogeneity in sub-threshold activity. This limitation is an inevitable outcome of bombarding single-compartment neurons with a large number of pre-synaptic inputs, thereby clamping the voltage of all neurons to more or less the same average voltage. To address this, we effectively incorporated dendritic morphology into the standard models. Inclusion of dendritic morphology in the neuronal models increased neuronal selectivity and reduced error trials, suggesting a functional role for dendrites during decision-making. Our work suggests that, during decision-making, cortical neurons in high-order cortical areas operate in a fluctuation-driven regime.

The atomic structure of the infectious, protease-resistant, β-sheet-rich and fibrillar mammalian prion remains unknown. Through the cryo-EM method MicroED, we reveal the sub-ångström-resolution structure of a protofibril formed by a wild-type segment from the β2-α2 loop of the bank vole prion protein. The structure of this protofibril reveals a stabilizing network of hydrogen bonds that link polar zippers within a sheet, producing motifs we have named 'polar clasps'.

Protein kinase A (PKA) plays multiple roles in neurons. The localization and specificity of PKA are largely controlled by A-kinase anchoring proteins (AKAPs). However, the dynamics of PKA in neurons and the roles of specific AKAPs are poorly understood. We imaged the distribution of type II PKA in hippocampal and cortical layer 2/3 pyramidal neurons in vitro and in vivo. PKA was concentrated in dendritic shafts compared to the soma, axons, and dendritic spines. This spatial distribution was imposed by the microtubule-binding protein MAP2, indicating that MAP2 is the dominant AKAP in neurons. Following cAMP elevation, catalytic subunits dissociated from the MAP2-tethered regulatory subunits and rapidly became enriched in nearby spines. The spatial gradient of type II PKA between dendritic shafts and spines was critical for the regulation of synaptic strength and long-term potentiation. Therefore, the localization and activity-dependent translocation of type II PKA are important determinants of PKA function.

Fluorescence light microscopy allows multicolor visualization of cellular components with high specificity, but its utility has until recently been constrained by the intrinsic limit of spatial resolution. We applied three-dimensional structured illumination microscopy (3D-SIM) to circumvent this limit and to study the mammalian nucleus. By simultaneously imaging chromatin, nuclear lamina, and the nuclear pore complex (NPC), we observed several features that escape detection by conventional microscopy. We could resolve single NPCs that colocalized with channels in the lamin network and peripheral heterochromatin. We could differentially localize distinct NPC components and detect double-layered invaginations of the nuclear envelope in prophase as previously seen only by electron microscopy. Multicolor 3D-SIM opens new and facile possibilities to analyze subcellular structures beyond the diffraction limit of the emitted light.

Recent findings implicate alternate core promoter recognition complexes in regulating cellular differentiation. Here we report a spatial segregation of the alternative core factor TAF3, but not canonical TFIID subunits, away from the nuclear periphery, where the key myogenic gene MyoD is preferentially localized in myoblasts. This segregation is correlated with the differential occupancy of TAF3 versus TFIID at the MyoD promoter. Loss of this segregation by modulating either the intranuclear location of the MyoD gene or TAF3 protein leads to altered TAF3 occupancy at the MyoD promoter. Intriguingly, in differentiated myotubes, the MyoD gene is repositioned to the nuclear interior, where TAF3 resides. The specific high-affinity recognition of H3K4Me3 by the TAF3 PHD (plant homeodomain) finger appears to be required for the sequestration of TAF3 to the nuclear interior. We suggest that intranuclear sequestration of core transcription components and their target genes provides an additional mechanism for promoter selectivity during differentiation.

Commentary: Jie Yao in Bob Tijan’s lab used a combination of confocal microscopy and dual label PALM in thin sections cut from resin-embedded cells to show that certain core transcription components and their target genes are spatially segregated in myoblasts, but not in differentiated myotubes, suggesting that such spatial segregation may play a role in guiding cellular differentiation.

In the past few years, three-dimensional (3D) subtomogram alignment has become an important tool in cryo-electron tomography (CET). This technique allows one to produce higher resolution images of structures which can not be reconstructed using single-particle methods. Building on previous work, we present a new dissimilarity measure between subtomograms that works well for the noisy images that often occur in CET images. A technique that is more robust to noise provides the ability to analyze macromolecules in thicker samples such as whole cells or lower the defocus in thinner samples to push the first zero of the Contrast Transfer Function (CTF). Our method, Threshold Constrained Cross-Correlation (TCCC), uses statistics of the noise to automatically select only a small percentage of the Fourier coefficients to compute the cross-correlation, which has two main advantages: first, it reduces the influence of the noise by looking at only those peaks dominated by signal; and second, it avoids the missing wedge normalization problem since we consider the same number of coefficients for all possible pairs of subtomograms. We present results with synthetic and real data to compare our approach with other existing methods under different SNR and missing wedge conditions, and show that TCCC improves alignment results for datasets with SNR<0.1. We have made our source code freely available for the community.

Papillomaviruses, members of a group of dsDNA viruses associated with epithelial growths and tumors, have compact capsids assembled from 72 pentamers of the protein L1. We have determined the structure of bovine papillomavirus by electron cryomicrosopy (cryoEM), at approximately 3.6 A resolution. The density map, obtained from single-particle analysis of approximately 4,000 particle images, shows the trace of the L1 polypeptide chain and reveals how the N- and C-terminal "arms" of a subunit (extensions from its beta-jelly-roll core) associate with a neighboring pentamer. Critical contacts come from the C-terminal arm, which loops out from the core of the subunit, forms contacts (including a disulfide) with two subunits in a neighboring pentamer, and reinserts into the pentamer from which it emanates. This trace corrects one feature of an earlier model. We discuss implications of the structure for virion assembly and for pathways of infectious viral entry. We suggest that it should be possible to obtain image reconstructions of comparable resolution from cryoEM images of asymmetric particles. From the work on papillomavirus described here, we estimate that such a reconstruction will require about 1.5 million images to achieve the same number of averaged asymmetric units; structural variability will increase this number substantially.

A new and conceptually simple data structure, called a suffix array, for on-line string searches is introduced in this paper. Constructing and querying suffix arrays is reduced to a sort and search paradigm that employs novel algorithms. The main advantage of suffix arrays over suffix trees is that, in practice, they use three to five times less space. From a complexity standpoint, suffix arrays permit on-line string searches of the type, ‘‘Is W a substring of A?’’ to be answered in time O(P + log N), where P is the length of W and N is the length of A, which is competitive with (and in some cases slightly better than) suffix trees. The only drawback is that in those instances where the underlying alphabet is finite and small, suffix trees can be constructed in O(N) time in the worst case, versus O(N log N) time for suffix arrays.

However, we give an augmented algorithm that, regardless of the alphabet size, constructs suffix arrays in O(N) expected time, albeit with lesser space efficiency. We believe that suffix arrays will prove to be better in practice than suffix trees for many applications.