Neurons Controlling Aplysia Feeding Inhibit Themselves by Continuous NO Production

Neural activity can be affected by nitric oxide (NO) produced by spiking neurons. Can neural activity also be affected by NO produced in neurons in the absence of spiking?Applying an NO scavenger to quiescent Aplysia buccal ganglia initiated fictive feeding, indicating that NO production at rest inhibits feeding. The inhibition is in part via effects on neurons B31/B32, neurons initiating food consumption. Applying NO scavengers or nitric oxide synthase (NOS) blockers to B31/B32 neurons cultured in isolation caused inactive neurons to depolarize and fire, indicating that B31/B32 produce NO tonically without action potentials, and tonic NO production contributes to the B31/B32 resting potentials. Guanylyl cyclase blockers also caused depolarization and firing, indicating that the cGMP second messenger cascade, presumably activated by the tonic presence of NO, contributes to the B31/B32 resting potential. Blocking NO while voltage-clamping revealed an inward leak current, indicating that NO prevents this current from depolarizing the neuron. Blocking nitrergic transmission had no effect on a number of other cultured, isolated neurons. However, treatment with NO blockers did excite cerebral ganglion neuron C-PR, a command-like neuron initiating food-finding behavior, both in situ, and when the neuron was cultured in isolation, indicating that this neuron also inhibits itself by producing NO at rest.Self-inhibitory, tonic NO production is a novel mechanism for the modulation of neural activity. Localization of this mechanism to critical neurons in different ganglia controlling different aspects of a behavior provides a mechanism by which a humeral signal affecting background NO production, such as the NO precursor L-arginine, could control multiple aspects of the behavior

Distributed network organization underlying feeding behavior in the mollusk Lymnaea

The aim of the work reviewed here is to relate the properties of individual neurons to network organization and behavior using the feeding system of the gastropod mollusk, Lymnaea. Food ingestion in this animal involves sequences of rhythmic biting movements that are initiated by the application of a chemical food stimulus to the lips and esophagus. We investigated how individual neurons contribute to various network functions that are required for the generation of feeding behavior such as rhythm generation, initiation ('decision making'), modulation and hunger and satiety. The data support the view that feeding behavior is generated by a distributed type of network organization with individual neurons often contributing to more than one network function, sharing roles with other neurons. Multitasking in a distributed type of network would be 'economically' sensible in the Lymnaea feeding system where only about 100 neurons are available to carry out a variety of complex tasks performed by millions of neurons in the vertebrate nervous system. Having complementary and potentially alternative mechanisms for network functions would also add robustness to what is a 'noisy' network where variable firing rates and synaptic strengths are commonly encountered in electrophysiological recording experiments

Explicit Logic Circuits Discriminate Neural States

The magnitude and apparent complexity of the brain's connectivity have left explicit networks largely unexplored. As a result, the relationship between the organization of synaptic connections and how the brain processes information is poorly understood. A recently proposed retinal network that produces neural correlates of color vision is refined and extended here to a family of general logic circuits. For any combination of high and low activity in any set of neurons, one of the logic circuits can receive input from the neurons and activate a single output neuron whenever the input neurons have the given activity state. The strength of the output neuron's response is a measure of the difference between the smallest of the high inputs and the largest of the low inputs. The networks generate correlates of known psychophysical phenomena. These results follow directly from the most cost-effective architectures for specific logic circuits and the minimal cellular capabilities of excitation and inhibition. The networks function dynamically, making their operation consistent with the speed of most brain functions. The networks show that well-known psychophysical phenomena do not require extraordinarily complex brain structures, and that a single network architecture can produce apparently disparate phenomena in different sensory systems

Multipolar Reactive DPD: A Novel Tool for Spatially Resolved Systems Biology

This article reports about a novel extension of dissipative particle dynamics (DPD) that allows the study of the collective dynamics of complex chemical and structural systems in a spatially resolved manner with a combinatorially complex variety of different system constituents. We show that introducing multipolar interactions between particles leads to extended membrane structures emerging in a self-organized manner and exhibiting both the necessary mechanical stability for transport and fluidity so as to provide a two-dimensional self-organizing dynamic reaction environment for kinetic studies in the context of cell biology. We further show that the emergent dynamics of extended membrane bound objects is in accordance with scaling laws imposed by physics.Comment: submitted to CMSB 0

Neuroarchitecture of Peptidergic Systems in the Larval Ventral Ganglion of Drosophila melanogaster

Recent studies on Drosophila melanogaster and other insects have revealed important insights into the functions and evolution of neuropeptide signaling. In contrast, in- and output connections of insect peptidergic circuits are largely unexplored. Existing morphological descriptions typically do not determine the exact spatial location of peptidergic axonal pathways and arborizations within the neuropil, and do not identify peptidergic in- and output compartments. Such information is however fundamental to screen for possible peptidergic network connections, a prerequisite to understand how the CNS controls the activity of peptidergic neurons at the synaptic level. We provide a precise 3D morphological description of peptidergic neurons in the thoracic and abdominal neuromeres of the Drosophila larva based on fasciclin-2 (Fas2) immunopositive tracts as landmarks. Comparing the Fas2 “coordinates” of projections of sensory or other neurons with those of peptidergic neurons, it is possible to identify candidate in- and output connections of specific peptidergic systems. These connections can subsequently be more rigorously tested. By immunolabeling and GAL4-directed expression of marker proteins, we analyzed the projections and compartmentalization of neurons expressing 12 different peptide genes, encoding approximately 75% of the neuropeptides chemically identified within the Drosophila CNS. Results are assembled into standardized plates which provide a guide to identify candidate afferent or target neurons with overlapping projections. In general, we found that putative dendritic compartments of peptidergic neurons are concentrated around the median Fas2 tracts and the terminal plexus. Putative peptide release sites in the ventral nerve cord were also more laterally situated. Our results suggest that i) peptidergic neurons in the Drosophila ventral nerve cord have separated in- and output compartments in specific areas, and ii) volume transmission is a prevailing way of peptidergic communication within the CNS. The data can further be useful to identify colocalized transmitters and receptors, and develop peptidergic neurons as new landmarks

Sequencing and de novo assembly of 150 genomes from Denmark as a population reference

Hundreds of thousands of human genomes are now being sequenced to characterize genetic variation and use this information to augment association mapping studies of complex disorders and other phenotypic traits. Genetic variation is identified mainly by mapping short reads to the reference genome or by performing local assembly. However, these approaches are biased against discovery of structural variants and variation in the more complex parts of the genome. Hence, large-scale de novo assembly is needed. Here we show that it is possible to construct excellent de novo assemblies from high-coverage sequencing with mate-pair libraries extending up to 20 kilobases. We report de novo assemblies of 150 individuals (50 trios) from the GenomeDenmark project. The quality of these assemblies is similar to those obtained using the more expensive long-read technology. We use the assemblies to identify a rich set of structural variants including many novel insertions and demonstrate how this variant catalogue enables further deciphering of known association mapping signals. We leverage the assemblies to provide 100 completely resolved major histocompatibility complex haplotypes and to resolve major parts of the Y chromosome. Our study provides a regional reference genome that we expect will improve the power of future association mapping studies and hence pave the way for precision medicine initiatives, which now are being launched in many countries including Denmark

Aging and disease-relevant gene products in the neuronal transcriptome of the great pond snail (Lymnaea stagnalis): a potential model of aging, age-related memory loss, and neurodegenerative diseases

Modelling of human aging, age-related memory loss, and neurodegenerative diseases has developed into a progressive area in invertebrate neuroscience. Gold standard molluscan neuroscience models such as the sea hare (Aplysia californica) and the great pond snail (Lymnaea stagnalis) have proven to be attractive alternatives for studying these processes. Until now, A. californica has been the workhorse due to the enormous set of publicly available transcriptome and genome data. However, with growing sequence data, L. stagnalis has started to catch up with A. californica in this respect. To contribute to this and inspire researchers to use molluscan species for modelling normal biological aging and/or neurodegenerative diseases, we sequenced the whole transcriptome of the central nervous system of L. stagnalis and screened for the evolutionary conserved homolog sequences involved in aging and neurodegenerative/other diseases. Several relevant molecules were identified, including for example gelsolin, presenilin, huntingtin, Parkinson disease protein 7/Protein deglycase DJ-1, and amyloid precursor protein, thus providing a stable genetic background for L. stagnalis in this field. Our study supports the notion that molluscan species are highly suitable for studying molecular, cellular, and circuit mechanisms of the mentioned neurophysiological and neuropathological processes

Ubiquitous molecular substrates for associative learning and activity-dependent neuronal facilitation.

Recent evidence suggests that many of the molecular cascades and substrates that contribute to learning-related forms of neuronal plasticity may be conserved across ostensibly disparate model systems. Notably, the facilitation of neuronal excitability and synaptic transmission that contribute to associative learning in Aplysia and Hermissenda, as well as associative LTP in hippocampal CA1 cells, all require (or are enhanced by) the convergence of a transient elevation in intracellular Ca2+ with transmitter binding to metabotropic cell-surface receptors. This temporal convergence of Ca2+ and G-protein-stimulated second-messenger cascades synergistically stimulates several classes of serine/threonine protein kinases, which in turn modulate receptor function or cell excitability through the phosphorylation of ion channels. We present a summary of the biophysical and molecular constituents of neuronal and synaptic facilitation in each of these three model systems. Although specific components of the underlying molecular cascades differ across these three systems, fundamental aspects of these cascades are widely conserved, leading to the conclusion that the conceptual semblance of these superficially disparate systems is far greater than is generally acknowledged. We suggest that the elucidation of mechanistic similarities between different systems will ultimately fulfill the goal of the model systems approach, that is, the description of critical and ubiquitous features of neuronal and synaptic events that contribute to memory induction