We describe a general computational method for designing proteins that self-assemble to a desired symmetric architecture. Protein building blocks are docked together symmetrically to identify complementary packing arrangements, and low-energy protein-protein interfaces are then designed between the building blocks in order to drive self-assembly. We used trimeric protein building blocks to design a 24-subunit, 13-nm diameter complex with octahedral symmetry and a 12-subunit, 11-nm diameter complex with tetrahedral symmetry. The designed proteins assembled to the desired oligomeric states in solution, and the crystal structures of the complexes revealed that the resulting materials closely match the design models. The method can be used to design a wide variety of self-assembling protein nanomaterials.

A key step toward understanding a metagenomics data set is the identification of functional sequence elements within it, such as protein coding genes and structural RNAs. Relative to protein coding genes, structural RNAs are more difficult to identify because of their reduced alphabet size, lack of open reading frames, and short length. Infernal is a software package that implements "covariance models" (CMs) for RNA homology search, which harness both sequence and structural conservation when searching for RNA homologs. Thanks to the added statistical signal inherent in the secondary structure conservation of many RNA families, Infernal is more powerful than sequence-only based methods such as BLAST and profile HMMs. Together with the Rfam database of CMs, Infernal is a useful tool for identifying RNAs in metagenomics data sets.

Imaging large samples at the resolution offered by electron microscopy is typically achieved by sequentially recording overlapping tiles that are later combined to seamless mosaics. Mosaics of serial sections are aligned to reconstruct three-dimensional volumes. To achieve this, image distortions and artifacts as introduced during sample preparation or imaging need to be removed.

In this chapter, we will discuss typical sources of artifacts and distortion, and we will learn how to use the open source software TrakEM2 to correct them.

The brain is worthy of study because it is in charge of behavior. A flurry of recent technical advances in measuring and quantifying naturalistic behaviors provide an important opportunity for advancing brain science. However, the problem of understanding unrestrained behavior in the context of neural recordings and manipulations remains unsolved, and developing approaches to addressing this challenge is critical. Here we discuss considerations in computational neuroethology-the science of quantifying naturalistic behaviors for understanding the brain-and propose strategies to evaluate progress. We point to open questions that require resolution and call upon the broader systems neuroscience community to further develop and leverage measures of naturalistic, unrestrained behavior, which will enable us to more effectively probe the richness and complexity of the brain.

Electrophysiology has long been the workhorse of neuroscience, allowing scientists to record with millisecond precision the action potentials generated by neurons in vivo. Recently, calcium imaging of fluorescent indicators has emerged as a powerful alternative. This technique has its own strengths and weaknesses and unique data processing problems and interpretation confounds. Here we review the computational methods that convert raw calcium movies to estimates of single neuron spike times with minimal human supervision. By computationally addressing the weaknesses of calcium imaging, these methods hold the promise of significantly improving data quality. We also introduce a new metric to evaluate the output of these processing pipelines, which is based on the cluster isolation distance routinely used in electrophysiology.

The spatiotemporal activities of astrocyte Ca(2+) signaling in mature neuronal circuits remain unclear. We used genetically encoded Ca(2+) and glutamate indicators as well as pharmacogenetic and electrical control of neurotransmitter release to explore astrocyte activity in the hippocampal mossy fiber pathway. Our data revealed numerous localized, spontaneous Ca(2+) signals in astrocyte branches and territories, but these were not driven by neuronal activity or glutamate. Moreover, evoked astrocyte Ca(2+) signaling changed linearly with the number of mossy fiber action potentials. Under these settings, astrocyte responses were global, suppressed by neurotransmitter clearance, and mediated by glutamate and GABA. Thus, astrocyte engagement in the fully developed mossy fiber pathway was slow and territorial, contrary to that frequently proposed for astrocytes within microcircuits. We show that astrocyte Ca(2+) signaling functionally segregates large volumes of neuropil and that these transients are not suited for responding to, or regulating, single synapses in the mossy fiber pathway.

Evaluation of confidence about one's knowledge is key to the brain's ability to monitor cognition. To investigate the neural mechanism of confidence assessment, we examined a biologically realistic spiking network model and found that it reproduced salient behavioral observations and single-neuron activity data from a monkey experiment designed to study confidence about a decision under uncertainty. Interestingly, the model predicts that changes of mind can occur in a mnemonic delay when confidence is low; the probability of changes of mind increases (decreases) with task difficulty in correct (error) trials. Furthermore, a so-called "hard-easy effect" observed in humans naturally emerges, i.e., behavior shows underconfidence (underestimation of correct rate) for easy or moderately difficult tasks and overconfidence (overestimation of correct rate) for very difficult tasks. Importantly, in the model, confidence is computed using a simple neural signal in individual trials, without explicit representation of probability functions. Therefore, even a concept of metacognition can be explained by sampling a stochastic neural activity pattern.

We recently identified ten novel SLE susceptibility loci in Asians and uncovered several additional suggestive loci requiring further validation. This study aimed to replicate five of these suggestive loci in a Han Chinese cohort from Hong Kong, followed by meta-analysis (11,656 cases and 23,968 controls) on previously reported Asian and European populations, and to perform bioinformatic analyses on all 82 reported SLE loci to identify shared regulatory signatures. We performed a battery of analyses for these five loci, as well as joint analyses on all 82 SLE loci. All five loci passed genome-wide significance: MYNN (rs10936599, Pmeta = 1.92 × 10-13, OR = 1.14), ATG16L2 (rs11235604, Pmeta = 8.87 × 10 -12, OR = 0.78), CCL22 (rs223881, Pmeta = 5.87 × 10-16, OR = 0.87), ANKS1A (rs2762340, Pmeta = 4.93 × 10-15, OR = 0.87) and RNASEH2C (rs1308020, Pmeta = 2.96 × 10-19, OR = 0.84) and co-located with annotated gene regulatory elements. The novel loci share genetic signatures with other reported SLE loci, including effects on gene expression, transcription factor binding, and epigenetic characteristics. Most (56%) of the correlated (r2 > 0.8) SNPs from the 82 SLE loci were implicated in differential expression (9.81 × 10-198 < P < 5 × 10-3) of cis-genes. Transcription factor binding sites for p53, MEF2A and E2F1 were significantly (P < 0.05) over-represented in SLE loci, consistent with apoptosis playing a critical role in SLE. Enrichment analysis revealed common pathways, gene ontology, protein domains, and cell type-specific expression. In summary, we provide evidence of five novel SLE susceptibility loci. Integrated bioinformatics using all 82 loci revealed that SLE susceptibility loci share many gene regulatory features, suggestive of conserved mechanisms of SLE etiopathogenesis.

The nanoscale connectomics community has recently generated automated and semi-automated "wiring diagrams" of brain subregions from terabytes and petabytes of dense 3D neuroimagery. This process involves many challenging and imperfect technical steps, including dense 3D image segmentation, anisotropic nonrigid image alignment and coregistration, and pixel classification of each neuron and their individual synaptic connections. As data volumes continue to grow in size, and connectome generation becomes increasingly commonplace, it is important that the scientific community is able to rapidly assess the quality and accuracy of a connectome product to promote dataset analysis and reuse. In this work, we share our scalable toolkit for assessing the quality of a connectome reconstruction via targeted inquiry and large-scale graph analysis, and to provide insights into how such connectome proofreading processes may be improved and optimized in the future. We illustrate the applications and ecosystem on a recent reference dataset.Clinical relevance- Large-scale electron microscopy (EM) data offers a novel opportunity to characterize etiologies and neurological diseases and conditions at an unprecedented scale. EM is useful for low-level analyses such as biopsies; this increased scale offers new possibilities for research into areas such as neural networks if certain bottlenecks and problems are overcome.

HIV-1 envelope spike [Env; trimeric (gp160)3, cleaved to (gp120/gp41)3] induces membrane fusion, leading to viral entry. It is also the viral component targeted by neutralizing antibodies. Vaccine development requires production, in quantities suitable for clinical studies, of a recombinant form that resembles functional Env. HIV-1 gp140 trimers - the uncleaved ectodomains of (gp160)3 - from a few selected viral isolates adopt a compact conformation with many antigenic properties of native Env spikes. One is currently being evaluated in a clinical trial. We report here low-resolution (20Å) cryoEM (electron cryomicroscopy) structures of this gp140 trimer, which adopts two principal conformations, one closed and the other slightly open. The former is indistinguishable at this resolution from those adopted by a stabilized, cleaved trimer (SOSIP) or by a membrane-bound Env trimer with truncated cytoplasmic tail (EnvΔCT). The latter conformation is closer to a partially open Env trimer than to the fully open conformation induced by CD4. These results show that a stable, uncleaved HIV-1 gp140 trimer has a compact structure close to that of native Env.IMPORTANCE Development of any HIV vaccine with a protein component (either prime or boost) requires production of a recombinant form to mimic the trimeric, functional HIV-1 envelope spike, in quantities suitable for clinical studies. Our understanding of the envelope structure has depended in part on a cleaved, soluble trimer, known as SOSIP.664, stabilized by several modifications including an engineered disulfide. This construct, difficult to produce in large quantities, has yet to induce better antibody responses than other envelope-based immunogens, even in animal models. The uncleaved ectodomain of the envelope protein, called gp140, has also been made as a soluble form to mimic the native Env present on the virion surface. Most HIV-1 gp140 preparations are not stable, however, and of inhomogeneous conformation. The results presented here show that gp140 preparations from suitable isolates can adopt a compact, native-like structure, supporting its use as a vaccine candidate.