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At least 919 records · Page 51

PNNL DataHub Project: Omics Lethal Human Viruses Project Profiling of the Host Interferon-Stimulated Response to Virus Infection, Processed Experimental Dataset Catalog

Human Interferon (IFN) alpha, beta, and gamma participate in the body's natural immune response to lethal virus infection and disease.The NIAID Modeling Host Responses to Understand Severe Human Virus Infections Research Program project (2013 - 2018) aimed to develop an improved comprehensive understanding of the host response to a suite of viruses causing lethal infections leveraging a systems biology approach. The NIAID Modeling Host Responses to Understand Severe Human Virus Infections Research Program project (2013-2018) aimed to develop an improved comprehensive understanding of the host response to a suite of viruses causing lethal infections leveraging a systems biology approach. Herein, PNNL sub-projects provide a never before released comprehensive infectious disease collection of primary and secondary transformation multi-Omics data profiling a series of priority pathogen primary experimental studies for enhanced open-access to viral Omics datasets and project lifecycle metadata. Secondary host-associated viral dataset downloads contain one or more statistically processed (normalization data transformation) quantitative dataset collections resulting in qualitative expression analyses of primary host-pathogen experimental study designs. Transcriptomics (T) dataset downloads each have a direct relationship to a primary sample submission corresponding to a specific Human Interferon (IFN), interferon alpha (IFNα), interferon beta (IFNβ), and/or interferon gamma (IFNγ) stimulated response to an experimental virus infection treatment study. Host sample types include cerebellum ["CB", BTO:0000232], cortical neurons ["CN", BTO:0004102], cortex ["CT", BTO:0000233], dendritic cells ["DC", BTO:0002042], granule cell neurons ["GCN", BTO:0003393], lymph node ["LN", BTO:0000784], and serum ["SE", BTO:0001239] from mouse (Mus musculus) tissue collections.

59 BASIC BIOLOGICAL SCIENCES↗

PNNL DataHub Project: Omics Lethal Human Viruses Project Profiling of the Host Response to West Nile Virus Infection, Processed Experimental Dataset Catalog

West Nile virus (WNV) is classified as a Category B priority pathogen (mosquito-borne Flavivirus) by the National Institute of Allergy and Infectious Diseases (NIAID), and are known to cause severe infections in humans where lethal host-associated mechanisms are not clearly defined. The NIAID Modeling Host Responses to Understand Severe Human Virus Infections Research Program project (2013 - 2018) aimed to develop an improved comprehensive understanding of the host response to a suite of viruses causing lethal infections leveraging a systems biology approach. The NIAID Modeling Host Responses to Understand Severe Human Virus Infections Research Program project (2013-2018) aimed to develop an improved comprehensive understanding of the host response to a suite of viruses causing lethal infections leveraging a systems biology approach. Herein, PNNL sub-projects provide a never before released comprehensive infectious disease collection of primary and secondary transformation multi-Omics data profiling a series of priority pathogen primary experimental studies for enhanced open-access to viral Omics datasets and project lifecycle metadata. Secondary host-pathogen viral dataset downloads contain one or more statistically processed (normalization data transformation) quantitative dataset collections resulting in qualitative expression analyses of primary host-pathogen experimental study designs. Leveraging unique high-resolution Omics capabilities for proteomics (P), metabolomics (M), lipidomics (L), and transcriptomics (T) dataset downloads each have a direct relationship to a primary sample submission corresponding a specific West Nile virus [NCBITAXON:11082] (WNV-NY99 382) experimental infection study. Host sample types include cerebellum ["CB", BTO:0000232], cortical neurons ["CN", BTO:0004102], cortex ["CT", BTO:0000233], dendritic cells ["DC", BTO:0002042], granule cell neurons ["GCN", BTO:0003393], lymph node ["LN", BTO:0000784], and serum ["SE", BTO:0001239] from mouse (Mus musculus) tissue collections.

59 BASIC BIOLOGICAL SCIENCES↗

Neonatal Zika virus infection causes transient perineuronal net degradation

Perineuronal nets (PNNs) form a specialized extracellular matrix that predominantly surrounds parvalbumin (PV)-expressing GABAergic inhibitory interneurons and help regulate neuronal activity. Their formation early in the postnatal period is regulated by neuronal signaling and glial activation raising concerns that part of the long-term effects ascribed to perinatal viral infections could be mediated by altered PNN formation. Previously, we developed a model of neonatal Zika virus (ZIKV) infection where mice have lifelong neurological sequelae that includes motor disfunction and reduced anxiety coupled with a persistent low-grade expression in proinflammatory markers despite resolving the acute infection. Here, we demonstrate that ZIKV infection to P1 neonatal mice results in a reduction of PNN formation during the acute disease with significant reduction in Wisteria floribunda agglutinin (WFA) staining at the peak of infection [15 days post infection (dpi)] that persisted after the symptoms resolved (30 dpi). At 60 dpi, when there is residual inflammation in the CNS, the number of WFA + cells and the level of WFA staining as well as levels of aggrecan and brevican in the brains of convalescent mice were not different from those in uninfected controls, however, there was increased frequency of PNNs with an immature phenotype. Over time the impact of the perinatal infection became less evident and there were no clear differences in PNN morphology between the groups at 1 year post infection. Of note, the reduction in PNNs during acute ZIKV infection was not associated with decreased mRNA levels of aggrecan or brevican, but increased levels of degraded aggrecan and brevican indicating increased PNN degradation. These changes were associated with increased expression of matrix metalloproteinase 12 (MMP12) and MMP19, but not MMP9, a disintegrin and metalloproteinase with thrombospondin motifs 4 (ADAMTS4) or ADAMTS5. Together our findings indicate that infection at the time of PNN development interferes with PNN formation, but the nets can reform once the infection and inflammation subside.

60 APPLIED LIFE SCIENCES↗

Role of the site of synaptic competition and the balance of learning forces for Hebbian encoding of probabilistic Markov sequences

The majority of distinct sensory and motor events occur as temporally ordered sequences with rich probabilistic structure. Sequences can be characterized by the probability of transitioning from the current state to upcoming states (forward probability), as well as the probability of having transitioned to the current state from previous states (backward probability). Despite the prevalence of probabilistic sequencing of both sensory and motor events, the Hebbian mechanisms that mold synapses to reflect the statistics of experienced probabilistic sequences are not well understood. Here, we show through analytic calculations and numerical simulations that Hebbian plasticity (correlation, covariance, and STDP) with pre-synaptic competition can develop synaptic weights equal to the conditional forward transition probabilities present in the input sequence. In contrast, post-synaptic competition can develop synaptic weights proportional to the conditional backward probabilities of the same input sequence. We demonstrate that to stably reflect the conditional probability of a neuron’s inputs and outputs, local Hebbian plasticity requires balance between competitive learning forces that promote synaptic differentiation and homogenizing learning forces that promote synaptic stabilization. The balance between these forces dictates a prior over the distribution of learned synaptic weights, strongly influencing both the rate at which structure emerges and the entropy of the final distribution of synaptic weights. Together, these results demonstrate a simple correspondence between the biophysical organization of neurons, the site of synaptic competition, and the temporal flow of information encoded in synaptic weights by Hebbian plasticity while highlighting the utility of balancing learning forces to accurately encode probability distributions, and prior expectations over such probability distributions.

59 BASIC BIOLOGICAL SCIENCES↗

Learned adaptive properties for mitigation of weight perturbations in embedded spiking networks

Recent years have seen an increased importance of neural network inference in edge-based scenarios, which impose size and power constraints requiring novel computing devices. These same edge scenarios may require operating over long periods of time, or exposure to extreme environments, resulting in a drift of neural network weights that cause degraded performance. In searching for ways to develop neural network approaches that perform robustly under these conditions, we propose a biologically-inspired mechanism for the dynamic adaptation of within-neuron parameters that is guided by a global context signal carrying information about perturbations and variability in incoming stimuli. Specifically, we demonstrate that adaptive voltage thresholds or neuronal time constants, when informed by a global context signal, can enable network-level mechanisms to recover from perturbed synaptic weights. Consistent with prior literature, the context-modulated approach is effective for recurrent, but not feedforward networks, by modulating network level dynamics. We demonstrate this approach successfully recovers performance in image classification tasks and spatiotemporal tracking tasks under idealized and Gaussian noise as well as for realistic perturbations from a memristive device when exposed to ionizing radiation. Finally, we discuss how this approach enables the design of robust and energy-efficient neuromorphic systems that perform well, even in resource-constrained scenarios with extreme environments such as edge processing.

context modulation↗

Two VHH Antibodies Neutralize Botulinum Neurotoxin E1 by Blocking Its Membrane Translocation in Host Cells

Botulinum neurotoxin serotype E (BoNT/E) is one of the major causes of human botulism, which is a life-threatening disease caused by flaccid paralysis of muscles. After receptor-mediated toxin internalization into motor neurons, the translocation domain (HN) of BoNT/E transforms into a protein channel upon vesicle acidification in endosomes and delivers its protease domain (LC) across membrane to enter the neuronal cytosol. It is believed that the rapid onset of BoNT/E intoxication compared to other BoNT serotypes is related to its swift internalization and translocation. We recently identified two neutralizing single-domain camelid antibodies (VHHs) against BoNT/E1 termed JLE-E5 and JLE-E9. Here, we report the crystal structures of these two VHHs bound to the LCHN domain of BoNT/E1. The structures reveal that these VHHs recognize two distinct epitopes that are partially overlapping with the putative transmembrane regions on HN, and therefore could physically block membrane association of BoNT/E1. This is confirmed by our in vitro studies, which show that these VHHs inhibit the structural change of BoNT/E1 at acidic pH and interfere with BoNT/E1 association with lipid vesicles. Therefore, these two VHHs neutralize BoNT/E1 by preventing the transmembrane delivery of LC. Furthermore, structure-based sequence analyses show that the 3-dimensional epitopes of these two VHHs are largely conserved across many BoNT/E subtypes, suggesting a broad-spectrum protection against the BoNT/E family. In summary, this work improves our understanding of the membrane translocation mechanism of BoNT/E and paves the way for developing VHHs as diagnostics or therapeutics for the treatment of BoNT/E intoxication.

60 APPLIED LIFE SCIENCES↗

Altered microRNA expression in animal models of Huntington’s disease and potential therapeutic strategies

A review of recent animal models of Huntington’s disease showed many microRNAs had altered expression levels in the striatum and cerebral cortex, and which were mostly downregulated. Among the altered microRNAs were miR-9/9*, miR-29b, miR-124a, miR-132, miR-128, miR-139, miR-122, miR-138, miR-23b, miR-135b, miR-181 (all downregulated) and miR-448 (upregulated), and similar changes had been previously found in Huntington’s disease patients. In the animal cell studies, the altered microRNAs included miR-9, miR-9*, miR-135b, miR-222 (all downregulated) and miR-214 (upregulated). In the animal models, overexpression of miR-155 and miR-196a caused a decrease in mutant huntingtin mRNA and protein level, lowered the mutant huntingtin aggregates in striatum and cortex, and improved performance in behavioral tests. Improved performance in behavioral tests also occurred with overexpression of miR-132 and miR-124. In the animal cell models, overexpression of miR-22 increased the viability of rat primary cortical and striatal neurons infected with mutant huntingtin and decreased huntingtin -enriched foci of ≥ 2 µm. Also, overexpression of miR-22 enhanced the survival of rat primary striatal neurons treated with 3-nitropropionic acid. Exogenous expression of miR-214, miR-146a, miR-150, and miR-125b decreased endogenous expression of huntingtin mRNA and protein in Hdh Q111 /Hdh Q111 cells. Further studies with animal models of Huntington’s disease are warranted to validate these findings and identify specific microRNAs whose overexpression inhibits the production of mutant huntingtin protein and other harmful processes and may provide a more effective means of treating Huntington’s disease in patients and slowing its progression.

59 BASIC BIOLOGICAL SCIENCES↗

Drosophila Nanos acts as a molecular clamp that modulates the RNA-binding and repression activities of Pumilio

Collaboration among the multitude of RNA-binding proteins (RBPs) is ubiquitous, yet our understanding of these key regulatory complexes has been limited to single RBPs. We investigated combinatorial translational regulation by Drosophila Pumilio (Pum) and Nanos (Nos), which control development, fertility, and neuronal functions. Our results show how the specificity of one RBP (Pum) is modulated by cooperative RNA recognition with a second RBP (Nos) to synergistically repress mRNAs. Crystal structures of Nos-Pum-RNA complexes reveal that Nos embraces Pum and RNA, contributes sequence-specific contacts, and increases Pum RNA-binding affinity. Nos shifts the recognition sequence and promotes repression complex formation on mRNAs that are not stably bound by Pum alone, explaining the preponderance of sub-optimal Pum sites regulated in vivo . Our results illuminate the molecular mechanism of a regulatory switch controlling crucial gene expression programs, and provide a framework for understanding how the partnering of RBPs evokes changes in binding specificity that underlie regulatory network dynamics.

Weidmann, Chase A.↗

Antiparallel protocadherin homodimers use distinct affinity- and specificity-mediating regions in cadherin repeats 1-4

Protocadherins (Pcdhs) are cell adhesion and signaling proteins used by neurons to develop and maintain neuronal networks, relying on trans homophilic interactions between their extracellular cadherin (EC) repeat domains. We present the structure of the antiparallel EC1-4 homodimer of human PcdhγB3, a member of the γ subfamily of clustered Pcdhs. Structure and sequence comparisons of α, β, and γ clustered Pcdh isoforms illustrate that subfamilies encode specificity in distinct ways through diversification of loop region structure and composition in EC2 and EC3, which contains isoform-specific conservation of primarily polar residues. In contrast, the EC1/EC4 interface comprises hydrophobic interactions that provide non-selective dimerization affinity. Using sequence coevolution analysis, we found evidence for a similar antiparallel EC1-4 interaction in non-clustered Pcdh families. We thus deduce that the EC1-4 antiparallel homodimer is a general interaction strategy that evolved before the divergence of these distinct protocadherin families.

59 BASIC BIOLOGICAL SCIENCES↗

Molecular basis of sidekick-mediated cell-cell adhesion and specificity

Sidekick (Sdk) 1 and 2 are related immunoglobulin superfamily cell adhesion proteins required for appropriate synaptic connections between specific subtypes of retinal neurons. Sdks mediate cell-cell adhesion with homophilic specificity that underlies their neuronal targeting function. Here we report crystal structures of Sdk1 and Sdk2 ectodomain regions, revealing similar homodimers mediated by the four N-terminal immunoglobulin domains (Ig1–4), arranged in a horseshoe conformation. These Ig1–4 horseshoes interact in a novel back-to-back orientation in both homodimers through Ig1:Ig2, Ig1:Ig1 and Ig3:Ig4 interactions. Structure-guided mutagenesis results show that this canonical dimer is required for both Sdk-mediated cell aggregation (via trans interactions) and Sdk clustering in isolated cells (via cis interactions). Sdk1/Sdk2 recognition specificity is encoded across Ig1–4, with Ig1–2 conferring the majority of binding affinity and differential specificity. We suggest that competition between cis and trans interactions provides a novel mechanism to sharpen the specificity of cell-cell interactions.

36 MATERIALS SCIENCE↗

Correlation of hippocampal theta rhythm with changes in cutaneous temperature

A possible role for the hippocampus in alerting an animal to changes in cutaneous temperature was examined. Following local warming or cooling of the ears of unanesthetized, loosely restrained rabbits, theta waves (4-7 Hz EEG waves) were recorded from electrodes straddling the hippocampus. The onset of the hippocampal theta rhythm was correlated with changes in cutaneous temperature, an observation consistent with studies indicating that the theta rhythm is a nonspecific response evoked by stimulation of several sensory modalities. Additional data from cats and rabbits were correlated with specific neurons within the hippocampus, namely pyramidal cells. Post stimulus time histograms obtained by excitation of the dorsal fornix were interpreted in terms of excitatory and inhibitory inputs to pyramidal cells. Thus, the theta rhythm, which appears to be evoked by changes in cutaneous temperature, can be related to a specific type of hippocampal neuron which is in turn connected with other areas of the brain involved in temperature regulation.

Horowitz, J. M.↗

Responses to preoptic temperature manipulation in the awake and hibernating marmot

Responses of normothermic and hibernating marmots to manipulations of the preoptic-hypothalamic temperature (T-PO) were experimentally investigated. An exponential increase in open-loop gain (OLG) occurred with decreases in temperature; it is concluded that this response can be explained by recruitment of cold-sensitive neurons brought about by low-temperature inactivation of inhibitory neurons. Marmots not only seek out the hibernating state, but also utilize all the thermoregulatory means they possess to remain in it for a given period of time.

South, F. E.↗

Effects of high-LET particles /A-40/ on the brain of Drosophila melanogaster

To investigate the effects of galactic heavy particles on nervous tissue, Drosophila melanogaster flies were exposed to A-40 from the Super-HILAC accelerator at the Lawrence Berkeley Laboratory. The energy of the particles reaching the Drosophila neurons was 4.8 MeV/nucleon, and the fluence ranged from 60,000 to 80 million particles/sq cm. Thirty-five days after irradiation at the higher fluences, extensive tissue fragmentation and cysts were found. At fluences as low as one hit/two cell bodies (about 5 million) and one hit/90 cell bodies (about 90,000 particles/sq cm or 21 rad average dose) swelling of neuronal cytoplasm and focally fragmented membranes were noted; at fluences ranging from one hit/six to one hit/135 cell bodies, there was frequently a marked increase in glial lamellae around nerve-cell processes, which often had degenerative features. These findings support the view that single hits by heavy particles may injure nervous tissue.

Miquel, J.↗

Introduction to a system for implementing neural net connections on SIMD architectures

Neural networks have attracted much interest recently, and using parallel architectures to simulate neural networks is a natural and necessary application. The SIMD model of parallel computation is chosen, because systems of this type can be built with large numbers of processing elements. However, such systems are not naturally suited to generalized communication. A method is proposed that allows an implementation of neural network connections on massively parallel SIMD architectures. The key to this system is an algorithm permitting the formation of arbitrary connections between the neurons. A feature is the ability to add new connections quickly. It also has error recovery ability and is robust over a variety of network topologies. Simulations of the general connection system, and its implementation on the Connection Machine, indicate that the time and space requirements are proportional to the product of the average number of connections per neuron and the diameter of the interconnection network.

Tomboulian, Sherryl↗

Studies with spike initiators - Linearization by noise allows continuous signal modulation in neural networks

It is shown that noise can be an important element in the translation of neuronal generator potentials (summed inputs) to neuronal spike trains (outputs), creating or expanding a range of amplitudes over which the spike rate is proportional to the generator potential amplitude. Noise converts the basically nonlinear operation of a spike initiator into a nearly linear modulation process. This linearization effect of noise is examined in a simple intuitive model of a static threshold and in a more realistic computer simulation of spike initiator based on the Hodgkin-Huxley (HH) model. The results are qualitatively similar; in each case larger noise amplitude results in a larger range of nearly linear modulation. The computer simulation of the HH model with noise shows linear and nonlinear features that were earlier observed in spike data obtained from the VIIIth nerve of the bullfrog. This suggests that these features can be explained in terms of spike initiator properties, and it also suggests that the HH model may be useful for representing basic spike initiator properties in vertebrates.

Yu, Xiaolong↗

Programmable synaptic chip for electronic neural networks

A binary synaptic matrix chip has been developed for electronic neural networks. The matrix chip contains a programmable 32X32 array of 'long channel' NMOSFET binary connection elements implemented in a 3-micron bulk CMOS process. Since the neurons are kept off-chip, the synaptic chip serves as a 'cascadable' building block for a multi-chip synaptic network as large as 512X512 in size. As an alternative to the programmable NMOSFET (long channel) connection elements, tailored thin film resistors are deposited, in series with FET switches, on some CMOS test chips, to obtain the weak synaptic connections. Although deposition and patterning of the resistors require additional processing steps, they promise substantial savings in silicon area. The performance of synaptic chip in a 32-neuron breadboard system in an associative memory test application is discussed.

Moopenn, A.↗

Introduction to a system for implementing neural net connections on SIMD architectures

Neural networks have attracted much interest recently, and using parallel architectures to simulate neural networks is a natural and necessary application. The SIMD model of parallel computation is chosen, because systems of this type can be built with large numbers of processing elements. However, such systems are not naturally suited to generalized elements. A method is proposed that allows an implementation of neural network connections on massively parallel SIMD architectures. The key to this system is an algorithm permitting the formation of arbitrary connections between the neurons. A feature is the ability to add new connections quickly. It also has error recovery ability and is robust over a variety of network topologies. Simulations of the general connection system, and its implementation on the Connection Machine, indicate that the time and space requirements are proportional to the product of the average number of connections per neuron and the diameter of the interconnection network.

Tomboulian, Sherryl↗

Optoelectronic Integrated Circuits For Neural Networks

Many threshold devices placed on single substrate. Integrated circuits containing optoelectronic threshold elements developed for use as planar arrays of artificial neurons in research on neural-network computers. Mounted with volume holograms recorded in photorefractive crystals serving as dense arrays of variable interconnections between neurons.

Psaltis, D.↗