The field of connectomics has recently produced neuron wiring diagrams from relatively large brain regions from multiple animals. Most of these neural reconstructions were computed from isotropic (e.g., FIBSEM) or near isotropic (e.g., SBEM) data. In spite of the remarkable progress on algorithms in recent years, automatic dense reconstruction from anisotropic data remains a challenge for the connectomics community. One significant hurdle in the segmentation of anisotropic data is the difficulty in generating a suitable initial over-segmentation. In this study, we present a segmentation method for anisotropic EM data that agglomerates a 3D over-segmentation computed from the 3D affinity prediction. A 3D U-net is trained to predict 3D affinities by the MALIS approach. Experiments on multiple datasets demonstrates the strength and robustness of the proposed method for anisotropic EM segmentation.

Full reconstruction of neuron morphology is of fundamental interest for the analysis and understanding of their functioning. We have developed a novel method capable of automatically tracing neurons in three-dimensional microscopy data. In contrast to template-based methods, the proposed approach makes no assumptions about the shape or appearance of neurite structure. Instead, an efficient seeding approach is applied to capture complex neuronal structures and the tracing problem is solved by computing the optimal reconstruction with a weighted graph. The optimality is determined by the cost function designed for the path between each pair of seeds and by topological constraints defining the component interrelations and completeness. In addition, an automated neuron comparison method is introduced for performance evaluation and structure analysis. The proposed algorithm is computationally efficient and has been validated using different types of microscopy data sets including Drosophila’s projection neurons and fly neurons with presynaptic sites. In all cases, the approach yielded promising results.

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.

Many different types of functional non-coding RNAs participate in a wide range of important cellular functions but the large majority of these RNAs are not routinely annotated in published genomes. Several programs have been developed for identifying RNAs, including specific tools tailored to a particular RNA family as well as more general ones designed to work for any family. Many of these tools utilize covariance models (CMs), statistical models of the conserved sequence, and structure of an RNA family. In this chapter, as an illustrative example, the Infernal software package and CMs from the Rfam database are used to identify RNAs in the genome of the archaeon Methanobrevibacter ruminantium, uncovering some additional RNAs not present in the genome’s initial annotation. Analysis of the results and comparison with family-specific methods demonstrate some important strengths and weaknesses of this general approach.

Reconstructing neuronal circuits at the level of synapses is a central problem in neuroscience and becoming a focus of the emerging field of connectomics. To date, electron microscopy (EM) is the most proven technique for identifying and quantifying synaptic connections. As advances in EM make acquiring larger datasets possible, subsequent manual synapse identification ({\em i.e.}, proofreading) for deciphering a connectome becomes a major time bottleneck. Here we introduce a large-scale, high-throughput, and semi-automated methodology to efficiently identify synapses. We successfully applied our methodology to the Drosophila medulla optic lobe, annotating many more synapses than previous connectome efforts. Our approaches are extensible and will make the often complicated process of synapse identification accessible to a wider-community of potential proofreaders.

The anterolateral motor cortex (ALM) and ventromedial (VM) thalamus are functionally linked to support persistent activity during motor planning. We analyzed the underlying synaptic interconnections using optogenetics and electrophysiology in mice (♀/♂). In cortex, thalamocortical (TC) axons from VM excited VM-projecting pyramidal-tract (PT) neurons in layer 5B of ALM. These axons also strongly excited layer 2/3 neurons (which strongly excite PT neurons, as previously shown) but not VM-projecting corticothalamic (CT) neurons in layer 6. The strongest connections in the VM→PT circuit were localized to apical-tuft dendrites of PT neurons, in layer 1. These tuft inputs were selectively augmented after blocking hyperpolarization-activated cyclic nucleotide-gated (HCN) channels. In thalamus, axons from ALM PT neurons excited ALM-projecting VM neurons, located medially in VM. These axons provided weak input to neurons in mediodorsal nucleus, and little or no input either to neurons in the GABAergic reticular thalamic nucleus or to neurons in VM projecting to primary motor cortex (M1). Conversely, M1 PT axons excited M1- but not ALM-projecting VM neurons. Our findings indicate, first, a set of cell-type-specific connections forming an excitatory thalamo-cortico-thalamic (T-C-T) loop for ALM↔VM communication and a circuit-level substrate for supporting reverberant activity in this system. Second, a key feature of this loop is the prominent involvement of layer 1 synapses onto apical dendrites, a subcellular compartment with distinct signaling properties, including HCN-mediated gain control. Third, the segregation of the ALM↔VM loop from M1-related circuits of VM adds cellular-level support for the concept of parallel pathway organization in the motor system.Anterolateral motor cortex (ALM), a higher-order motor area in the mouse, and ventromedial thalamus (VM) are anatomically and functionally linked, but their synaptic interconnections at the cellular level are unknown. Our results show that ALM pyramidal tract neurons monosynaptically excite ALM-projecting thalamocortical neurons in a medial subdivision of VM, and vice versa. The thalamo-cortico-thalamic loop formed by these recurrent connections constitutes a circuit-level substrate for supporting reverberant activity in this system.

The brain's ability to rapidly transition between sleep, quiet wakefulness, and states of high vigilance is remarkable. Cerebral norepinephrine (NE) plays a key role in promoting wakefulness, but how does the brain avoid neuronal hyperexcitability upon arousal? Here, we show that NE exposure results in the generation of free fatty acids (FFAs) within the plasma membrane from both astrocytes and neurons. In turn, FFAs dampen excitability by differentially modulating the activity of astrocytic and neuronal Na, K, ATPase. Direct application of FFA to the occipital cortex in awake, behaving mice dampened visual-evoked potential (VEP). Conversely, blocking FFA production via local application of a lipase inhibitor heightened VEP and triggered seizure-like activity. These results suggest that FFA release is a crucial step in NE signaling that safeguards against hyperexcitability. Targeting lipid-signaling pathways may offer a novel therapeutic approach for seizure prevention.

Although purification of biotinylated molecules is highly efficient, identifying specific sites of biotinylation remains challenging. We show that anti-biotin antibodies enable unprecedented enrichment of biotinylated peptides from complex peptide mixtures. Live-cell proximity labeling using APEX peroxidase followed by anti-biotin enrichment and mass spectrometry yielded over 1,600 biotinylation sites on hundreds of proteins, an increase of more than 30-fold in the number of biotinylation sites identified compared to streptavidin-based enrichment of proteins.

Molecular adaptations are believed to contribute to the mechanism of action of antipsychotic drugs (APDs). We attempted to establish common gene regulation patterns induced by chronic treatment with APDs.