Hypergraph models of biological networks to identify genes critical to pathogenic viral response

Background: Representing biological networks as graphs is a powerful approach to reveal underlying patterns, signatures, and critical components from high-throughput biomolecular data. However, graphs do not natively capture the multi-way relationships present among genes and proteins in biological systems. Hypergraphs are generalizations of graphs that naturally model multi-way relationships and have shown promise in modeling systems such as protein complexes and metabolic reactions. In this paper we seek to understand how hypergraphs can more faithfully identify, and potentially predict, important genes based on complex relationships inferred from genomic expression data sets. Results: We compiled a novel data set of transcriptional host response to pathogenic viral infections and formulated relationships between genes as a hypergraph where hyperedges represent significantly perturbed genes, and vertices represent individual biological samples with specific experimental conditions. We find that hypergraph betweenness centrality is a superior method for identification of genes important to viral response when compared with graph centrality. Conclusions: Our results demonstrate the utility of using hypergraphs to represent complex biological systems and highlight central important responses in common to a variety of highly pathogenic viruses

A theory of how active behavior stabilises neural activity: neural gain modulation by closed-loop environmental feedback

During active behaviours like running, swimming, whisking or sniffing, motor actions shape sensory input and sensory percepts guide future motor commands. Ongoing cycles of sensory and motor processing constitute a closed-loop feedback system which is central to motor control and, it has been argued, for perceptual processes. This closed-loop feedback is mediated by brainwide neural circuits but how the presence of feedback signals impacts on the dynamics and function of neurons is not well understood. Here we present a simple theory suggesting that closed-loop feedback between the brain/body/environment can modulate neural gain and, consequently, change endogenous neural fluctuations and responses to sensory input. We support this theory with modeling and data analysis in two vertebrate systems. First, in a model of rodent whisking we show that negative feedback mediated by whisking vibrissa can suppress coherent neural fluctuations and neural responses to sensory input in the barrel cortex. We argue this suppression provides an appealing account of a brain state transition (a marked change in global brain activity) coincident with the onset of whisking in rodents. Moreover, this mechanism suggests a novel signal detection mechanism that selectively accentuates active, rather than passive, whisker touch signals. This mechanism is consistent with a predictive coding strategy that is sensitive to the consequences of motor actions rather than the difference between the predicted and actual sensory input. We further support the theory by re-analysing previously published two-photon data recorded in zebrafish larvae performing closed-loop optomotor behaviour in a virtual swim simulator. We show, as predicted by this theory, that the degree to which each cell contributes in linking sensory and motor signals well explains how much its neural fluctuations are suppressed by closed-loop optomotor behaviour. More generally we argue that our results demonstrate the dependence of neural fluctuations, across the brain, on closed-loop brain/body/environment interactions strongly supporting the idea that brain function cannot be fully understood through open-loop approaches alone

A Systematic Study of Mid-Infrared Emission from Core-Collapse Supernovae with Spirits

The American Astronomical Society. All rights reserved.We present a systematic study of mid-infrared emission from 141 nearby supernovae (SNe) observed with Spitzer/IRAC as part of the ongoing SPIRITS survey. We detect 8 Type Ia and 36 core-collapse SNe. All Type Ia/Ibc SNe become undetectable within three years of explosion, whereas 22 ± 11% of Type II SNe continue to be detected. Five Type II SNe are detected even two decades after discovery (SN 1974E, 1979C, 1980K, 1986J, and 1993J). Warm dust luminosity, temperature, and a lower limit on mass are obtained by fitting the two IRAC bands, assuming an optically thin dust shell. We derive warm dust masses between 10-6 and 10-2 M o and dust color temperatures between 200 and 1280 K. This observed warm dust could be pre-existing or newly created, but in either case represents a lower limit to the dust mass because cooler dust may be present. We present three case studies of extreme SNe. SN 2011ja (II-P) was over-luminous ([4.5] = -15.6 mag) at 900 days post explosion with increasing hot dust mass, suggesting either an episode of dust formation or intensifying circumstellar material (CSM) interactions heating up pre-existing dust. SN 2014bi (II-P) showed a factor of 10 decrease in dust mass over one month, suggesting either dust destruction or reduced dust heating. The IR luminosity of SN 2014C (Ib) stayed constant over 800 days, possibly due to strong CSM interaction with an H-rich shell, which is rare among stripped-envelope SNe. The observations suggest that this CSM shell originated from an LBV-like eruption roughly 100 years pre-explosion. The observed diversity demonstrates the power of mid-IR observations of a large sample of SNe. © 2017

A tale of two stories: astrocyte regulation of synaptic depression and facilitation

Short-term presynaptic plasticity designates variations of the amplitude of synaptic information transfer whereby the amount of neurotransmitter released upon presynaptic stimulation changes over seconds as a function of the neuronal firing activity. While a consensus has emerged that changes of the synapse strength are crucial to neuronal computations, their modes of expression in vivo remain unclear. Recent experimental studies have reported that glial cells, particularly astrocytes in the hippocampus, are able to modulate short-term plasticity but the underlying mechanism is poorly understood. Here, we investigate the characteristics of short-term plasticity modulation by astrocytes using a biophysically realistic computational model. Mean-field analysis of the model unravels that astrocytes may mediate counterintuitive effects. Depending on the expressed presynaptic signaling pathways, astrocytes may globally inhibit or potentiate the synapse: the amount of released neurotransmitter in the presence of the astrocyte is transiently smaller or larger than in its absence. But this global effect usually coexists with the opposite local effect on paired pulses: with release-decreasing astrocytes most paired pulses become facilitated, while paired-pulse depression becomes prominent under release-increasing astrocytes. Moreover, we show that the frequency of astrocytic intracellular Ca2+ oscillations controls the effects of the astrocyte on short-term synaptic plasticity. Our model explains several experimental observations yet unsolved, and uncovers astrocytic gliotransmission as a possible transient switch between short-term paired-pulse depression and facilitation. This possibility has deep implications on the processing of neuronal spikes and resulting information transfer at synapses.Comment: 93 pages, manuscript+supplementary text, 10 main figures, 11 supplementary figures, 1 tabl

Observation of Charge-Dependent Azimuthal Correlations in p-Pb Collisions and Its Implication for the Search for the Chiral Magnetic Effect

Peer reviewe

Search for narrow resonances in dilepton mass spectra in proton-proton collisions at root s=13 TeV and combination with 8 TeV data

Peer reviewe