bioRxiv Science⌕ Search

Biology subjects

Kim, S.-Y.

Publications and source records attributed to Kim, S.-Y..

At least 37 records · Page 2Linked to original sources

Comparative Interactome Analysis of α-arrestin Families in Human and Drosophila

The -arrestins form a large family of evolutionally conserved modulators that control diverse signaling pathways, including both G-protein-coupled receptor-(GPCR-) mediated and non-GPCR mediated pathways, across eukaryotes. However, unlike {beta}-arrestins, only a few -arrestin targets and functions have been characterized. Here, using affinity purification and mass spectrometry, we constructed interactomes for six human and twelve Drosophila -arrestins. The resulting high-confidence interactomes comprised 307 and 467 prey proteins in human and Drosophila, respectively. A comparative analysis of these interactomes predicted not only conserved binding partners, such as motor proteins, proteases, ubiquitin ligases, RNA splicing factors, and GTPase-activating proteins, but also those specific to mammals, such as histone modifiers and the subunits of V-type ATPase. Given the manifestation of the interaction between the human -arrestin, TXNIP, and the histone-modifying enzymes, including HDAC2, we undertook a global analysis of transcription signals and chromatin structures that were affected by TXNIP knockdown. We found that TXNIP activated targets by blocking HDAC2 recruitment to targets, a result that was validated by chromatin immunoprecipitation assays. Additionally, the interactome for an uncharacterized human -arrestin ARRDC5 uncovered multiple components in the V-type ATPase, which plays a key role in bone resorption by osteoclasts. Our study presents conserved and species-specific protein-protein interaction maps for -arrestins, which provide a valuable resource for interrogating their cellular functions for both basic and clinical research.

cell biology↗

Effect of Adult Neurogenesis on Sparsely Synchronized Rhythms of The Granule Cells in The Hippocampal Dentate Gyrus

We are concerned about the main encoding granule cells (GCs) in the hippocampal dentate gyrus (DG). Young immature GCs (imGCs) appear through adult neurogenesis. In comparison to the mature GCs (mGCs) (born during development), the imGCs show high activation due to lower firing threshold. On the other hand, they receive low excitatory drive from the entorhinal cortex via perforant paths and from the hilar mossy cells with lower connection probability pc (= 20 x %) (x : synaptic connectivity fraction; 0 [≤] x [≤] 1) than the mGCs with the connection probability pc (= 20 %). Thus, the effect of low excitatory innervation (reducing activation degree) for the imGCs counteracts the effect of their high excitability. We consider a spiking neural network for the DG, incorporating both the mGCs and the imGCs. With decreasing x from 1 to 0, we investigate the effect of young adult-born imGCs on the sparsely synchronized rhythms (SSRs) of the GCs (mGCs, imGC, and whole GCs). For each x, population and individual firing behaviors in the SSRs are characterized in terms of the amplitude measure [Formula] (X = m, im, w for the mGCs, the imGCs, and the whole GCs, respectively) (representing the population synchronization degree) and the random phase-locking degree [Formula] (characterizing the regularity of individual single-cell discharges), respectively. We also note that, for 0 [≤] x [≤] 1, the mGCs and the imGCs exhibit pattern separation (i.e., a process of transforming similar input patterns into less similar output patterns) and pattern integration (making association between patterns), respectively. Quantitative relationship between SSRs and pattern separation and integration is also discussed. PACS numbers87.19.lj, 87.19.lm, 87.19.lv

neuroscience↗

Export of diverse and bioactive peptides through a type I secretion system.

Microcins are peptide antibiotics secreted by Gram-negative bacteria that inhibit the growth of neighboring microbes. They are exported from the cytosol to the environment in a one-step process through a specific type I secretion system (T1SS). While the rules governing export of natural or non-native substrates have been resolved for T1SSs that secrete large proteins, relatively little is known about substrate requirements for peptides exported through T1SSs that secrete microcins. Here, we investigate the prototypic microcin V T1SS from Escherichia coli and show it can export a remarkably wide range of natural and synthetic peptides. We demonstrate that secretion through this system is not affected by peptide charge or hydrophobicity and appears only constrained by peptide length. A varied range of bioactive peptides, including an antibacterial peptide, a microbial signaling factor, a protease inhibitor, and a human hormone, can all be secreted and elicit their intended biological effect. Secretion through this system is not limited to E. coli, and we demonstrate its function in additional Gram-negative species that can inhabit the gastrointestinal tract. Our findings uncover the highly promiscuous nature of peptide export thorough the microcin V T1SS, which has implications for native cargo capacity and use of Gram-negative bacteria for peptide research and delivery. ImportanceMicrocin type I secretion systems in Gram-negative bacteria transport antibacterial peptides from the cytoplasm to the extracellular environment in single step. In nature, each microcin secretion system is generally paired with a specific peptide. We know little about the export capacity of these transporters and how peptide sequence influences secretion. Here, we investigate the microcin V type I secretion system. Remarkably, our studies show this system can export diverse peptides and is only limited by peptide length. Furthermore, we demonstrate that various bioactive peptides can be secreted, and this system can be used in Gram-negative species that colonize the gastrointestinal tract. These finding expand our understanding of secretion through type I systems and their potential uses in peptide applications.

microbiology↗

Effect of Adult-Born Immature Granule Cells on Pattern Separation in The Hippocampal Dentate Gyrus

Young immature granule cells (imGCs) appear via adult neurogenesis in the hippocampal dentate gyrus (DG). In comparison to mature GCs (mGCs) (born during development), the imGCs exhibit two competing distinct properties such as high excitability and low excitatory innervation. We develop a spiking neural network for the DG, incorporating the imGCs, and investigate their effect on pattern separation (i.e., a process of transforming similar input patterns into less similar output patterns). We first consider the effect of high excitability. The imGCs become very highly active due to their low firing threshold. Then, because of high activation, strong pattern correlation occurs, which results in pattern integration (i.e., making association between events). On the other hand, the mGCs exhibit very sparse firing activity due to strongly increased feedback inhibition (caused by the high activation of the imGCs). As a result of high sparsity, the pattern separation efficacy (PSE) of the mGCs becomes very high. Thus, the whole population of GCs becomes a heterogeneous one, composed of a (major) subpopulation of mGCs (i.e., pattern separators) with very low activation degree [Formula] and a (minor) subpopulation of imGCs (i.e., pattern integrators) with very high activation degree [Formula]. In the whole heterogeneous population, the overall activation degree [Formula] of all the GCs is a little reduced in comparison to the activation degree [Formula] in the presence of only mGCs without imGCs. However, no pattern separation occurs, due to heterogeneous sparsity, in contrast to the usual intuitive thought that sparsity could improve PSE. Next, we consider the effect of low excitatory innervation for the imGCs, counteracting the effect of their high excitability. With decreasing the connection probability of excitatory inputs to the imGCs, [Formula] decreases so rapidly, and their effect becomes weaker. Then, the feedback inhibition to the mGCs is also decreased, leading to increase in [Formula] of the mGCs. Accordingly, [Formula] of the whole GCs also increases. In this case of low excitatory connectivity, the imGCs perform pattern integration. On the other hand, due to increase in [Formula], the PSE of the mGCs decreases from a high value to a limit value. In the whole population of all the GCs, when the excitatory connection probability decreases through a threshold, pattern separation starts, the overall PSE increases and approaches that of the mGCs. However, due to heterogeneity caused by the imGCs, the overall PSE becomes deteriorated, in comparison with that in the presence of only mGCs.

biophysics↗

Korea4K: whole genome sequences of 4,157 Koreans with 107 phenotypes derived from extensive health check-ups

We present 4,157 whole-genome sequences (Korea4K) coupled with 107 health check-up parameters as the largest whole genomic resource of Koreans. Korea4K provides 45,537,252 variants and encompasses most of the common and rare variants in Koreans. We identified 1,356 new geno-phenotype associations which were not found by the previous Korea1K dataset. Phenomics analyses revealed 24 genetic correlations, 1,131 pleiotropic variants, and 127 causal relationships from Mendelian randomization. Moreover, the Korea4K imputation reference panel showed a superior imputation performance to Korea1K. Collectively, Korea4K provides the most extensive genomic and phenomic data resources for discovering clinically relevant novel genome-phenome associations in Koreans.

genomics↗

MECP2pedia: A Comprehensive Transcriptome Portal for MECP2 Disease Research

Mutations in MeCP2 result in a crippling neurological disease, but we lack a lucid picture of MeCP2s molecular role. Focusing on individual transcriptomic studies yields inconsistent differentially expressed genes. We have aggregated and homogeneously processed modern public MeCP2 transcriptome data, which we present in a web portal. With this big data, we discovered a commonly perturbed core set of genes that transcends the limitations of any individual study. We then found distinct consistently up and downregulated subsets within these genes. We observe enrichment for this mouse core in other species MeCP2 models and see overlap between this core and ASD models. Analysis of signal to noise finds that many studies lack enough biological replicates. By integrating and examining transcriptomic data at scale, we have generated a valuable resource and insight on MeCP2 function.

bioinformatics↗

ModelMatcher: A scientist-centric online platform to facilitate collaborations between stakeholders of rare and undiagnosed disease research

Next-generation sequencing is a prevalent diagnostic tool for undiagnosed diseases, and has played a significant role in rare disease gene discovery. While this technology resolves some cases, others are given a list of possibly damaging genetic variants necessitating functional studies. Productive collaborations between scientists, clinicians, and patients can help resolve such medical mysteries, and provide insights into in vivo function of human genes. Furthermore, facilitating interactions between scientists and research funders, including non-profit organizations or commercial entities, can dramatically reduce the time to translate discoveries from bench to bedside. Several systems designed to connect clinicians and researchers with a shared gene of interest have been successful. However, these platforms exclude some stakeholders based on their role or geography. Here we describe ModelMatcher, a global online matchmaking tool designed to facilitate cross-disciplinary collaborations, especially between scientists and other stakeholders of rare and undiagnosed disease research. ModelMatcher is integrated into the Rare Diseases Models and Mechanisms Network and Matchmaker Exchange, allowing users to identify potential collaborators in other registries. This living database decreases the time from when a scientist or clinician is making discoveries regarding their genes of interest, to when they identify collaborators and sponsors to facilitate translational and therapeutic research.

genetics↗

Disynaptic Effect of Hilar Cells on Pattern Separation in A Spiking Neural Network of Hippocampal Dentate Gyrus

We investigate the disynaptic effect of the hilar cells on pattern separation in a spiking neural network of the hippocampal dentate gyrus (DG). The principal granule cells (GCs) in the DG perform pattern separation, transforming similar input patterns into less-similar output patterns. In our DG network, the hilus consists of excitatory mossy cells (MCs) and inhibitory HIPP (hilar perforant path-associated) cells. Here, we consider the disynaptic effects of the MCs and the HIPP cells on the GCs, mediated by the inhibitory basket cells (BCs) in the granular layer; MC [->] BC [->] GC and HIPP [->] BC [->] GC. Disynaptic inhibition from the MCs tends to decrease the firing activity of the GCs. On the other hand, the HIPP cells disinhibit the intermediate BCs, which leads to increasing the activity of the GCs. By changing the synaptic strength K(BC,X) [from the presynaptic X (= MC or HIPP) to the postsynaptic BC] from the default value K(BC,X)*, we study the change in the pattern separation degree [S]d. When decreasing K(BC,MC) or independently increasing K(BC,HIPP) from their default values, [S]d is found to decrease (i.e., pattern separation is reduced). On the other hand, as K(BC,MC) is increased or independently K(BC,HIPP) is decreased from their default values, pattern separation becomes enhanced (i.e., [S]d increases). In this way, the disynaptic effects of the MCs and the HIPP cells on the pattern separation are opposite ones. Thus, when simultaneously varying both K(BC,MC) and K(BC,HIPP), as a result of balance between the two competing disynaptic effects of the MCs and the HIPP cells, [S]d forms a bell-shaped curve with an optimal maximum at their default values. Moreover, we also investigate population and individual behaviors of the sparsely synchronized rhythm of the GCs, and find that the amplitude measure [M]a (representing population synchronization degree) and the random-phase-locking degree [L]d (denoting individual activity degree) are strongly correlated with the pattern separation degree [S]d. Consequently, the larger the synchronization and the random phase-locking degrees of the sparsely synchronized rhythm is, the more the pattern separation becomes enhanced.

neuroscience↗

Population and Individual Firing Behaviors in Sparsely Synchronized Rhythms in The Hippocampal Dentate Gyrus

We investigate population and individual firing behaviors in sparsely synchronized rhythms (SSRs) in a spiking neural network of the hippocampal dentate gyrus (DG). The main encoding granule cells (GCs) are grouped into lamellar clusters. In each GC cluster, there is one inhibitory (I) basket cell (BC) along with excitatory (E) GCs, and they form the E-I loop. Winner-take-all competition, leading to sparse activation of the GCs, occurs in each GC cluster. Such sparsity has been thought to enhance pattern separation performed in the DG. During the winner-take-all competition, SSRs are found to appear in each population of the GCs and the BCs through interaction of excitation of the GCs with inhibition of the BCs. Sparsely synchronized spiking stripes appear successively with the population frequency fp (= 13 Hz) in the raster plots of spikes. We also note that excitatory hilar mossy cells (MCs) control the firing activity of the GC-BC loop by providing excitation to both the GCs and the BCs. SSR also appears in the population of MCs via interaction with the GCs (i.e., GC-MC loop). Population behaviors in the SSRs are quantitatively characterized in terms of the synchronization measures. In addition, we investigate individual firing activity of GCs, BCs, and MCs in the SSRs. Individual GCs exhibit random spike skipping, leading to a multi-peaked inter-spike-interval histogram, which is well characterized in terms of the random phase-locking degree. In this case, population-averaged mean-firing-rate [Formula] is less than the population frequency fp. On the other hand, both BCs and MCs show "intrastripe" burstings within stripes, together with "interstripe" random spike skipping. Thus, the population-averaged [Formula] (X = MC and BC) is larger than fp, in contrast to the case of the GCs. MC loss may occur during epileptogenesis. With decreasing the fraction of the MCs, changes in the population and individual firings in the SSRs are also studied. Finally, quantitative association between the population/individual firing behaviors in the SSRs and the winner-take-all competition is discussed.

biophysics↗

Dynamical Origin for Winner-Take-All Competition in A Biological Network of The Hippocampal Dentate Gyrus

We consider a biological network of the hippocampal dentate gyrus (DG). The DG is a pre-processor for pattern separation which facilitates pattern storage and retrieval in the CA3 area of the hippocampus. The main encoding cells in the DG are the granule cells (GCs) which receive the input from the entorhinal cortex (EC) and send their output to the CA3. We note that the activation degree of GCs is so low (~ 5%). This sparsity has been thought to enhance the pattern separation. We investigate the dynamical origin for winner-take-all (WTA) competition which leads to sparse activation of the GCs. The whole GCs are grouped into lamellar clusters. In each GC cluster, there is one inhibitory (I) basket cell (BC) along with excitatory (E) GCs. There are three kinds of external inputs into the GCs; the direct excitatory EC input, the indirect inhibitory EC input, mediated by the HIPP (hilar perforant path-associated) cells, and the excitatory input from the hilar mossy cells (MCs). The firing activities of the GCs are determined via competition between the external E and I inputs. The E-I conductance ratio [Formula] (given by the time average of the external E to I conductances) may represents well the degree of such external E-I input competition. It is thus found that GCs become active when their [Formula] is larger than a threshold [Formula], and then the mean firing rates of the active GCs are strongly correlated with [Formula]. In each GC cluster, the feedback inhibition of the BC may select the winner GCs. GCs with larger [Formula] than the threshold [Formula] survive, and they become winners; all the other GCs with smaller [Formula] become silent. In this way, WTA competition occurs via competition between the firing activity of the GCs and the feedback inhibition from the BC in each GC cluster. In this case, the hilar MCs are also found to play an essential role of enhancing the WTA competition in each GC cluster by exciting both the GCs and the BC. PACS numbers: 87.19.lj, 87.19.lm, 87.19.lv

neuroscience↗

Effect of Diverse Temporal Recoding of Granule Cells on Pavlovian Eyeblink Conditioning in The Cerebellum

We consider the Pavlovian eyeblink conditioning (EBC) via repeated presentation of paired conditioned stimulus (tone) and unconditioned stimulus (airpuff). The influence of various temporal recoding of granule cells on the EBC is investigated in a cerebellar network where the connection probability pc from Golgi to granule cells is changed. In an optimal case of [Formula], individual granule cells show various well- and ill-matched firing patterns relative to the unconditioned stimulus. Then, these variously-recoded signals are fed into the Purkinje cells (PCs) through parallel-fibers (PFs), and the instructor climbing-fiber (CF) signals from the inferior olive depress them effectively. In the case of well-matched PF-PC synapses, their synaptic weights are strongly depressed through strong long-term depression (LTD). On the other hand, practically no LTD occurs for the ill-matched PF-PC synapses. This type of "effective" depression at the PF-PC synapses coordinates firings of PCs effectively, which then make effective inhibitory coordination on cerebellar nucleus neuron [which elicits conditioned response (CR; eyeblink)]. When the learning trial passes a threshold, acquisition of CR begins. In this case, the timing degree [T]d of CR becomes good due to presence of the ill-matched firing group which plays a role of protection barrier for the timing. With further increase in the trial, strength [S] of CR (corresponding to the amplitude of eyelid closure) increases due to strong LTD in the well-matched firing group, while its timing degree [T]d decreases. In this way, the well- and the ill-matched firing groups play their own roles for the strength and the timing of CR, respectively. Thus, with increasing the learning trial, the (overall) learning efficiency degree [L]e (taking into consideration both timing and strength of CR) for the CR is increased, and eventually it becomes saturated. By changing pc from [Formula], we also investigate the influence of various temporal recoding on the EBC. It is thus found that, the more various in temporal recoding, the more effective in learning for the Pavlovian EBC.

neuroscience↗

Stage-specific muscle wasting mechanisms in a novel cancer cachexia mouse model for ovarian granulosa cell tumor

Cachexia is a progressive muscle wasting syndrome that increases mortality risk in cancer patients, while there are still no effective treatment due to the complexity of syndrome and the lack of preclinical models. We identified a transgenic mice model with ovarian granulosa cell tumors mimic the progression of cachexia seen in humans, including drastic weight loss, skeletal muscle wasting and increased serum cachexia biomarker activin A and GDF15. Hypercatabolism was detected in skeletal muscle, having upregulation of E3 ligases Atrogin-1 and Murf-1. Our cachexia model exhibited stage-specific muscle wasting mechanisms. At precachexia stage, elevation of activin A activates p38 MAPK. Inhibition of activin A with Follistatin reversed weight loss at precachexia stage. At cachexia stage, energy stress in skeletal muscle activates AMPK and leads to upregulation of FoxO3. Our results indicate this novel preclinical cancer cachexia model is exploitable for studying pathophysiological mechanisms and testing therapeutic agents of cachexia.

cancer biology↗

Effect of Diverse Recoding of Granule Cells on Optokinetic Response in A Cerebellar Ring Network with Synaptic Plasticity

We consider a cerebellar ring network for the optokinetic response (OKR), and investigate the effect of diverse recoding of granule (GR) cells on OKR by varybing the connection probability pc from Golgi to GR cells. For an optimal value of [Formula], individual GR cells exhibit diverse spiking patterns which are in-phase, anti-phase, or complex out-of-phase with respect to their population-averaged firing activity. Then, these diversely-recoded signals via parallel fibers (PFs) from GR cells are effectively depressed by the error-teaching signals via climbing fibers from the inferior olive which are also in-phase ones. Synaptic weights at in-phase PF-Purkinje cell (PC) synapses of active GR cells are strongly depressed via strong long-term depression (LTD), while those at anti-phase and complex out-of-phase PF-PC synapses are weakly depressed through weak LTD. This kind of "effective" depression (i.e., strong/weak LTD) at the PF-PC synapses causes a big modulation in firings of PCs, which then exert effective inhibitory coordination on the vestibular nucleus (VN) neuron (which evokes OKR). For the firing of the VN neuron, the learning gain degree [L]g, corresponding to the modulation gain ratio, increases with increasing the learning cycle, and it saturates at about the 300th cycle. By varying pc from [Formula], we find that a plot of saturated learning gain degree [Formula] versus pc forms a bell-shaped curve with a peak at [Formula] (where the diversity degree in spiking patterns of GR cells is also maximum). Consequently, the more diverse in recoding of GR cells, the more effective in motor learning for the OKR adaptation.

neuroscience↗

Feasibility of real-time in vivo 89Zr-DFO-labeled CAR T-cell trafficking using PET imaging

IntroductionChimeric antigen receptor (CAR) T-cells have been developed recently, producing impressive outcomes in patients with hematologic malignancies. However, there is no standardized method for cell trafficking and in vivo CAR T-cell monitoring. We assessed the feasibility of real-time in vivo 89Zr-p-Isothiocyanatobenzyl-desferrioxamine (Df-Bz-NCS, DFO) labeled CAR T-cell trafficking using positron emission tomography (PET).\n\nResultsThe 89Zr-DFO radiolabeling efficiency of Jurkat/CAR and human peripheral blood mononuclear cells (hPBMC)/CAR T-cells was 70-79%, and cell radiolabeling activity was 98.1-103.6 kBq/106 cells. Cell viability after radiolabeling was >95%. Compared with unlabeled cells, cell proliferation was not significantly different during the early period after injection; however, the proliferative capacity decreased over time (p = 0.02, day 7 after labeling). IL-2 or IFN-{gamma} secretion was not significantly different between unlabeled and labeled CAR T-cells. PET/magnetic resonance images in the xenograft model showed that most of the 89Zr-DFO-labeled Jurkat/CAR T-cells were distributed in the lung (24.4% {+/-} 3.4%ID) and liver (22.9% {+/-} 5.6%ID) by 1 hour after injection. The cells gradually migrated from lung to the liver and spleen by day 1, and remained stably until day 7 (on day 7: lung 3.9% {+/-} 0.3%ID, liver 36.4% {+/-} 2.7%ID, spleen 1.4% {+/-} 0.3%ID). No significant accumulation of labeled cells was identified in tumors. A similar pattern was observed in ex vivo biodistributions on day 7 (lung 3.0% {+/-} 1.0%ID, liver 19.8% {+/-} 2.2%ID, spleen 2.3% {+/-} 1.7%ID). 89Zr-DFO-labeled hPBMC/CAR T-cells showed the similar distribution on serial PET images as Jurkat/CAR T-cells. The distribution of CAR T-cells was cross-confirmed by flow cytometry, Alu polymerase chain reaction, and immunohistochemistry.\n\nConclusionUsing PET imaging of 89Zr-DFO-labeled CAR T-cells, real time in vivo cell trafficking is feasible. It can be used to investigate cellular kinetics, initial in vivo biodistribution, and the safety profile in future CAR T-cell development.

cancer biology↗

Connecting Histopathology Imaging and Proteomics in Kidney Cancer through Machine Learning

Proteomics data encode molecular features of diagnostic value and accurately reflect key underlying biological mechanisms in cancers. Histopathology imaging is a well-established clinical approach to cancer diagnosis. The predictive relationship between large-scale proteomics and H&E-stained histopathology images remains largely uncharacterized. Here we investigate such associations through the application of machine learning, including deep neural networks, to proteomics and histology imaging datasets generated by the Clinical Proteomic Tumor Analysis Consortium (CPTAC) from clear cell renal cell carcinoma patients. We report robust correlations between a set of diagnostic proteins and predictions generated by an imaging-based classification model. Proteins significantly correlated with the histology-based predictions are significantly implicated in immune responses, extracellular matrix reorganization and metabolism. Moreover, we showed that the genes encoding these proteins also reliably recapitulate the biological associations with imaging-derived predictions based on strong gene-protein expression correlations. Our findings offer novel insights into the integrative modeling of histology and omics data through machine learning, as well as the methodological basis for new research opportunities in this and other cancer types.

systems biology↗

NRL- and CRX-guided gene network modulates photoreceptor presynapse size and positioning during retinal development

Unique morphologies of rod and cone photoreceptor presynaptic terminals permit the formation of synapses onto interneurons during retina development. We integrated multiple \"omics\" datasets of developing rod and S-cone-like photoreceptors and identified 719 genes that are regulated by NRL and CRX, critical transcriptional regulators of rod differentiation, as candidates for controlling presynapse morphology. In vivo knockdown of 72 candidate genes in the developing retina uncovered 26 genes that alter size and/or positioning of rod spherules in the outer plexiform layer. Co-expression of seven cDNAs with their cognate shRNAs rescued the rod presynapse phenotype. Loss of function of four genes in germline or by an AAV-mediated CRISPR/Cas9 strategy validated RNAi screen findings. A protein interaction network analysis of the 26 positive effectors revealed additional candidates in the NRL/CRX-regulated presynapse morphology-associated gene network. Follow-up knockdowns of two novel candidates support the proposed network. Our studies demonstrate a requirement of multiple components in a modular network for rod presynapse morphogenesis and provide a functional genomic framework for deciphering genetic determinants of morphological specification during development.\n\nAuthor SummaryThe relationship between neuronal morphology and function has been recognized for over 100 years. However, we still have poor understanding of genes and proteins that control morphogenesis of a specific neuron. In the current study, we address this connection between gene expression and neural morphology by identifying and knocking down a subset of expressed genes in rod photoreceptors. We ascertained a number of candidate genes controlling photoreceptor pre-synaptic terminal morphology, which is necessary for its connection with second-order neurons in the retinal circuit. Furthermore, we have curated a more plausible network of genes, either identified in our study or predicted, that are enriched for processes underlying photoreceptor morphogenesis. We suggest that our work will provide a framework for dissecting genetic basis of neuronal architecture and assist in better design of cell replacement therapies for retinal degeneration.

neuroscience↗

Effect of Interpopulation Spike-Timing-Dependent Plasticity on Synchronized Rhythms in Neuronal Networks with Inhibitory and Excitatory Populations

We consider a two-population network consisting of both inhibitory (I) interneurons and excitatory (E) pyramidal cells. This I-E neuronal network has adaptive dynamic I to E and E to I interpopulation synaptic strengths, governed by interpopulation spike-timing-dependent plasticity (STDP). In previous works without STDPs, fast sparsely synchronized rhythms, related to diverse cognitive functions, were found to appear in a range of noise intensity D for static synaptic strengths. Here, by varying D, we investigate the effect of interpopulation STDPs on fast sparsely synchronized rhythms that emerge in both the I- and the E-populations. Depending on values of D, long-term potentiation (LTP) and long-term depression (LTD) for population-averaged values of saturated interpopulation synaptic strengths are found to occur. Then, the degree of fast sparse synchronization varies due to effects of LTP and LTD. In a broad region of intermediate D, the degree of good synchronization (with higher synchronization degree) becomes decreased, while in a region of large D, the degree of bad synchronization (with lower synchronization degree) gets increased. Consequently, in each I- or E-population, the synchronization degree becomes nearly the same in a wide range of D (including both the intermediate and the large D regions). This kind of "equalization effect" is found to occur via cooperative interplay between the average occupation and pacing degrees of spikes (i.e., the average fraction of firing neurons and the average degree of phase coherence between spikes in each synchronized stripe of spikes in the raster plot of spikes) in fast sparsely synchronized rhythms. Finally, emergences of LTP and LTD of interpopulation synaptic strengths (leading to occurrence of equalization effect) are intensively investigated via a microscopic method based on the distributions of time delays between the pre- and the post-synaptic spike times. PACS numbers87.19.lw, 87.19.lm, 87.19.lc

neuroscience↗

Cluster Burst Synchronization in A Scale-Free Network of Inhibitory Bursting Neurons

We consider a scale-free network of inhibitory Hindmarsh-Rose (HR) bursting neurons, and investigate coupling-induced burst synchronization by varying the average coupling strength J0. When passing a lower threshold [Formula], a transition from desynchronization to 3-cluster burst synchronization occurs due to a constructive role of inhibition to favor the cluster burst synchronization. For this case, the whole population is segregated into 3 clusters, and HR neurons in each cluster exhibit burst synchronization. However, as J0 is increased and passes an intermediate threshold [Formula], HR neurons begin to make intermittent hoppings between the 3 clusters. Due to the intermittent intercluster hoppings, the 3 clusters are integrated into a single one. In spite of break-up of the 3 clusters, burst synchronization persists in the whole population, which is well visualized in the raster plot of burst onset times where bursting stripes (composed of burst onset times and indicating burst synchronization) appear successively. With further increase in J0, intercluster hoppings are intensified, and bursting stripes also become smeared more and more due to a destructive role of inhibition to spoil the burst synchronization. Eventually, when passing a higher threshold [Formula] a transition to desynchronization occurs via complete overlap between the bursting stripes. Finally, we also investigate the effects of stochastic noise on both 3-cluster burst synchronization and intercluster hoppings.\n\nPACS numbers: 87.19.lm, 87.19.lc

neuroscience↗