ResearchPad - Cellular and Molecular Neuroscience https://www.researchpad.co Default RSS Feed en-us © 2020 Newgen KnowledgeWorks <![CDATA[Network inference reveals novel connections in pathways regulating growth and defense in the yeast salt response]]> https://www.researchpad.co/product?articleinfo=5afd46d0463d7e6ee57105d0

Cells respond to stressful conditions by coordinating a complex, multi-faceted response that spans many levels of physiology. Much of the response is coordinated by changes in protein phosphorylation. Although the regulators of transcriptome changes during stress are well characterized in Saccharomyces cerevisiae, the upstream regulatory network controlling protein phosphorylation is less well dissected. Here, we developed a computational approach to infer the signaling network that regulates phosphorylation changes in response to salt stress. We developed an approach to link predicted regulators to groups of likely co-regulated phospho-peptides responding to stress, thereby creating new edges in a background protein interaction network. We then use integer linear programming (ILP) to integrate wild type and mutant phospho-proteomic data and predict the network controlling stress-activated phospho-proteomic changes. The network we inferred predicted new regulatory connections between stress-activated and growth-regulating pathways and suggested mechanisms coordinating metabolism, cell-cycle progression, and growth during stress. We confirmed several network predictions with co-immunoprecipitations coupled with mass-spectrometry protein identification and mutant phospho-proteomic analysis. Results show that the cAMP-phosphodiesterase Pde2 physically interacts with many stress-regulated transcription factors targeted by PKA, and that reduced phosphorylation of those factors during stress requires the Rck2 kinase that we show physically interacts with Pde2. Together, our work shows how a high-quality computational network model can facilitate discovery of new pathway interactions during osmotic stress.

]]>
<![CDATA[Switchable slow cellular conductances determine robustness and tunability of network states]]> https://www.researchpad.co/product?articleinfo=5ae95a42463d7e06f246c06c

Neuronal information processing is regulated by fast and localized fluctuations of brain states. Brain states reliably switch between distinct spatiotemporal signatures at a network scale even though they are composed of heterogeneous and variable rhythms at a cellular scale. We investigated the mechanisms of this network control in a conductance-based population model that reliably switches between active and oscillatory mean-fields. Robust control of the mean-field properties relies critically on a switchable negative intrinsic conductance at the cellular level. This conductance endows circuits with a shared cellular positive feedback that can switch population rhythms on and off at a cellular resolution. The switch is largely independent from other intrinsic neuronal properties, network size and synaptic connectivity. It is therefore compatible with the temporal variability and spatial heterogeneity induced by slower regulatory functions such as neuromodulation, synaptic plasticity and homeostasis. Strikingly, the required cellular mechanism is available in all cell types that possess T-type calcium channels but unavailable in computational models that neglect the slow kinetics of their activation.

]]>
<![CDATA[Computational mechanisms underlying cortical responses to the affordance properties of visual scenes]]> https://www.researchpad.co/product?articleinfo=5ae95a44463d7e06f246c06d

Biologically inspired deep convolutional neural networks (CNNs), trained for computer vision tasks, have been found to predict cortical responses with remarkable accuracy. However, the internal operations of these models remain poorly understood, and the factors that account for their success are unknown. Here we develop a set of techniques for using CNNs to gain insights into the computational mechanisms underlying cortical responses. We focused on responses in the occipital place area (OPA), a scene-selective region of dorsal occipitoparietal cortex. In a previous study, we showed that fMRI activation patterns in the OPA contain information about the navigational affordances of scenes; that is, information about where one can and cannot move within the immediate environment. We hypothesized that this affordance information could be extracted using a set of purely feedforward computations. To test this idea, we examined a deep CNN with a feedforward architecture that had been previously trained for scene classification. We found that responses in the CNN to scene images were highly predictive of fMRI responses in the OPA. Moreover the CNN accounted for the portion of OPA variance relating to the navigational affordances of scenes. The CNN could thus serve as an image-computable candidate model of affordance-related responses in the OPA. We then ran a series of in silico experiments on this model to gain insights into its internal operations. These analyses showed that the computation of affordance-related features relied heavily on visual information at high-spatial frequencies and cardinal orientations, both of which have previously been identified as low-level stimulus preferences of scene-selective visual cortex. These computations also exhibited a strong preference for information in the lower visual field, which is consistent with known retinotopic biases in the OPA. Visualizations of feature selectivity within the CNN suggested that affordance-based responses encoded features that define the layout of the spatial environment, such as boundary-defining junctions and large extended surfaces. Together, these results map the sensory functions of the OPA onto a fully quantitative model that provides insights into its visual computations. More broadly, they advance integrative techniques for understanding visual cortex across multiple level of analysis: from the identification of cortical sensory functions to the modeling of their underlying algorithms.

]]>
<![CDATA[The novel 19q13 KRAB zinc-finger tumour suppressor ZNF382 is frequently methylated in oesophageal squamous cell carcinoma and antagonises Wnt/β-catenin signalling]]> https://www.researchpad.co/product?articleinfo=5b599034463d7e76cf8ed8d2

Zinc finger proteins (ZFPs) are the largest transcription factor family in mammals. About one-third of ZFPs are Krüppel-associated box domain (KRAB)-ZFPs and involved in the regulation of cell differentiation/proliferation/apoptosis and neoplastic transformation. We recently identified ZNF382 as a novel KRAB-ZFP epigenetically inactivated in multiple cancers due to frequent promoter CpG methylation. However, its epigenetic alterations, biological functions/mechanism and clinical significance in oesophageal squamous cell carcinoma (ESCC) are still unknown. Here, we demonstrate that ZNF382 expression was suppressed in ESCC due to aberrant promoter methylation, but highly expressed in normal oesophagus tissues. ZNF382 promoter methylation is correlated with ESCC differentiation levels. Restoration of ZNF382 expression in silenced ESCC cells suppressed tumour cell proliferation and metastasis through inducing cell apoptosis. Importantly, ZNF382 suppressed Wnt/β-catenin signalling and downstream target gene expression, likely through binding directly to FZD1 and DVL2 promoters. In summary, our findings demonstrate that ZNF382 functions as a bona fide tumour suppressor inhibiting ESCC pathogenesis through inhibiting the Wnt/β-catenin signalling pathway.

]]>
<![CDATA[On the role of extrinsic noise in microRNA-mediated bimodal gene expression]]> https://www.researchpad.co/product?articleinfo=5ae6147c463d7e4331d54a11

Several studies highlighted the relevance of extrinsic noise in shaping cell decision making and differentiation in molecular networks. Bimodal distributions of gene expression levels provide experimental evidence of phenotypic differentiation, where the modes of the distribution often correspond to different physiological states of the system. We theoretically address the presence of bimodal phenotypes in the context of microRNA (miRNA)-mediated regulation. MiRNAs are small noncoding RNA molecules that downregulate the expression of their target mRNAs. The nature of this interaction is titrative and induces a threshold effect: below a given target transcription rate almost no mRNAs are free and available for translation. We investigate the effect of extrinsic noise on the system by introducing a fluctuating miRNA-transcription rate. We find that the presence of extrinsic noise favours the presence of bimodal target distributions which can be observed for a wider range of parameters compared to the case with intrinsic noise only and for lower miRNA-target interaction strength. Our results suggest that combining threshold-inducing interactions with extrinsic noise provides a simple and robust mechanism for obtaining bimodal populations without requiring fine tuning. Furthermore, we characterise the protein distribution’s dependence on protein half-life.

]]>
<![CDATA[A computational model of shared fine-scale structure in the human connectome]]> https://www.researchpad.co/product?articleinfo=5ae6147b463d7e4331d54a10

Variation in cortical connectivity profiles is typically modeled as having a coarse spatial scale parcellated into interconnected brain areas. We created a high-dimensional common model of the human connectome to search for fine-scale structure that is shared across brains. Projecting individual connectivity data into this new common model connectome accounts for substantially more variance in the human connectome than do previous models. This newly discovered shared structure is closely related to fine-scale distinctions in representations of information. These results reveal a shared fine-scale structure that is a major component of the human connectome that coexists with coarse-scale, areal structure. This shared fine-scale structure was not captured in previous models and was, therefore, inaccessible to analysis and study.

]]>
<![CDATA[MicroRNA-29b/142-5p contribute to the pathogenesis of biliary atresia by regulating the IFN-γ gene]]> https://www.researchpad.co/product?articleinfo=5b597b55463d7e5ce270da37

Biliary atresia is one of the most common liver disease in infancy. The cause and pathogenesis remain largely unknown. This study aimed to investigate the potential regulatory effect of miR-29b/142-5p on IFN-γ gene methylation. miRNAs microarray was performed on four pairs of liver and blood specimens from biliary atresia and choledochal cysts. We found the overexpression of miR-142-5p and mRNA level of DNA methyltransferase (DNMT) 1, and miR-29b and DNMT3a/DNMT3b were significantly negatively correlated in biliary atresia livers. Meanwhile, the methylation of the LINE-1, ALU and SAT2 repetitive sequences and the IFN-γ promoter was lower, but the expression of IFN-γ was upregulated. After transfected with DNMTs siRNAs, downregulation of DNMTs exerted a significant hypomethylating effect on the repetitive sequences, which led to upregulation of IFN-γ in Jurkat cells. The direct interactions between miR-29b and DNMT3a/3b, and miR-142-5p and DNMT1 were identified using luciferase reporter assays. By transfecting mimics of miR-29b/142-5p into Jurkat cells, we found overexpression of miR-29b/142-5p markedly suppressed expression of DNMTs. Furthermore, the methylation of repetitive sequences and the IFN-γ promoter region were remarkably downregulated, and with elevated IFN-γ expression. After transfecting the miRNA inhibitors, the levels of DNMTs and the methylation of the IFN-γ gene promoter region was upregulated, while levels of IFN-γ were markedly suppressed. Our study suggested that miRNA-29b/142-5p overexpression and targeted inhibition of DNMTs expression resulted in decreased overall gene methylation and overexpression of the methylation-sensitive IFN-γ gene.

]]>
<![CDATA[A computational study of astrocytic glutamate influence on post-synaptic neuronal excitability]]> https://www.researchpad.co/product?articleinfo=5ae5cb76463d7e39eef05add

The ability of astrocytes to rapidly clear synaptic glutamate and purposefully release the excitatory transmitter is critical in the functioning of synapses and neuronal circuits. Dysfunctions of these homeostatic functions have been implicated in the pathology of brain disorders such as mesial temporal lobe epilepsy. However, the reasons for these dysfunctions are not clear from experimental data and computational models have been developed to provide further understanding of the implications of glutamate clearance from the extracellular space, as a result of EAAT2 downregulation: although they only partially account for the glutamate clearance process. In this work, we develop an explicit model of the astrocytic glutamate transporters, providing a more complete description of the glutamate chemical potential across the astrocytic membrane and its contribution to glutamate transporter driving force based on thermodynamic principles and experimental data. Analysis of our model demonstrates that increased astrocytic glutamate content due to glutamine synthetase downregulation also results in increased postsynaptic quantal size due to gliotransmission. Moreover, the proposed model demonstrates that increased astrocytic glutamate could prolong the time course of glutamate in the synaptic cleft and enhances astrocyte-induced slow inward currents, causing a disruption to the clarity of synaptic signalling and the occurrence of intervals of higher frequency postsynaptic firing. Overall, our work distilled the necessity of a low astrocytic glutamate concentration for reliable synaptic transmission of information and the possible implications of enhanced glutamate levels as in epilepsy.

]]>
<![CDATA[Allostery in the dengue virus NS3 helicase: Insights into the NTPase cycle from molecular simulations]]> https://www.researchpad.co/product?articleinfo=5ae5cb77463d7e39eef05ade

The C-terminus domain of non-structural 3 (NS3) protein of the Flaviviridae viruses (e.g. HCV, dengue, West Nile, Zika) is a nucleotide triphosphatase (NTPase) -dependent superfamily 2 (SF2) helicase that unwinds double-stranded RNA while translocating along the nucleic polymer. Due to these functions, NS3 is an important target for antiviral development yet the biophysics of this enzyme are poorly understood. Microsecond-long molecular dynamic simulations of the dengue NS3 helicase domain are reported from which allosteric effects of RNA and NTPase substrates are observed. The presence of a bound single-stranded RNA catalytically enhances the phosphate hydrolysis reaction by affecting the dynamics and positioning of waters within the hydrolysis active site. Coupled with results from the simulations, electronic structure calculations of the reaction are used to quantify this enhancement to be a 150-fold increase, in qualitative agreement with the experimental enhancement factor of 10–100. Additionally, protein-RNA interactions exhibit NTPase substrate-induced allostery, where the presence of a nucleotide (e.g. ATP or ADP) structurally perturbs residues in direct contact with the phosphodiester backbone of the RNA. Residue-residue network analyses highlight pathways of short ranged interactions that connect the two active sites. These analyses identify motif V as a highly connected region of protein structure through which energy released from either active site is hypothesized to move, thereby inducing the observed allosteric effects. These results lay the foundation for the design of novel allosteric inhibitors of NS3.

]]>
<![CDATA[Backbone Brackets and Arginine Tweezers delineate Class I and Class II aminoacyl tRNA synthetases]]> https://www.researchpad.co/product?articleinfo=5ae5cb79463d7e39eef05adf

The origin of the machinery that realizes protein biosynthesis in all organisms is still unclear. One key component of this machinery are aminoacyl tRNA synthetases (aaRS), which ligate tRNAs to amino acids while consuming ATP. Sequence analyses revealed that these enzymes can be divided into two complementary classes. Both classes differ significantly on a sequence and structural level, feature different reaction mechanisms, and occur in diverse oligomerization states. The one unifying aspect of both classes is their function of binding ATP. We identified Backbone Brackets and Arginine Tweezers as most compact ATP binding motifs characteristic for each Class. Geometric analysis shows a structural rearrangement of the Backbone Brackets upon ATP binding, indicating a general mechanism of all Class I structures. Regarding the origin of aaRS, the Rodin-Ohno hypothesis states that the peculiar nature of the two aaRS classes is the result of their primordial forms, called Protozymes, being encoded on opposite strands of the same gene. Backbone Brackets and Arginine Tweezers were traced back to the proposed Protozymes and their more efficient successors, the Urzymes. Both structural motifs can be observed as pairs of residues in contemporary structures and it seems that the time of their addition, indicated by their placement in the ancient aaRS, coincides with the evolutionary trace of Proto- and Urzymes.

]]>
<![CDATA[Multiscale modelization in a small virus: Mechanism of proton channeling and its role in triggering capsid disassembly]]> https://www.researchpad.co/product?articleinfo=5ae5cb7a463d7e39eef05ae0

In this work, we assess a previously advanced hypothesis that predicts the existence of ion channels in the capsid of small and non-enveloped icosahedral viruses. With this purpose we examine Triatoma Virus (TrV) as a case study. This virus has a stable capsid under highly acidic conditions but disassembles and releases the genome in alkaline environments. Our calculations range from a subtle sub-atomic proton interchange to the dismantling of a large-scale system representing several million of atoms. Our results provide structure-based explanations for the three roles played by the capsid to enable genome release. First, we observe, for the first time, the formation of a hydrophobic gate in the cavity along the five-fold axis of the wild-type virus capsid, which can be disrupted by an ion located in the pore. Second, the channel enables protons to permeate the capsid through a unidirectional Grotthuss-like mechanism, which is the most likely process through which the capsid senses pH. Finally, assuming that the proton leak promotes a charge imbalance in the interior of the capsid, we model an internal pressure that forces shell cracking using coarse-grained simulations. Although qualitatively, this last step could represent the mechanism of capsid opening that allows RNA release. All of our calculations are in agreement with current experimental data obtained using TrV and describe a cascade of events that could explain the destabilization and disassembly of similar icosahedral viruses.

]]>
<![CDATA[Origins of scale invariance in vocalization sequences and speech]]> https://www.researchpad.co/product?articleinfo=5ae5cb75463d7e39eef05adc

To communicate effectively animals need to detect temporal vocalization cues that vary over several orders of magnitude in their amplitude and frequency content. This large range of temporal cues is evident in the power-law scale-invariant relationship between the power of temporal fluctuations in sounds and the sound modulation frequency (f). Though various forms of scale invariance have been described for natural sounds, the origins and implications of scale invariant phenomenon remain unknown. Using animal vocalization sequences, including continuous human speech, and a stochastic model of temporal amplitude fluctuations we demonstrate that temporal acoustic edges are the primary acoustic cue accounting for the scale invariant phenomenon. The modulation spectrum of vocalization sequences and the model both exhibit a dual regime lowpass structure with a flat region at low modulation frequencies and scale invariant 1/f2 trend for high modulation frequencies. Moreover, we find a time-frequency tradeoff between the average vocalization duration of each vocalization sequence and the cutoff frequency beyond which scale invariant behavior is observed. These results indicate that temporal edges are universal features responsible for scale invariance in vocalized sounds. This is significant since temporal acoustic edges are salient perceptually and the auditory system could exploit such statistical regularities to minimize redundancies and generate compact neural representations of vocalized sounds.

]]>
<![CDATA[MiR-422a regulates cellular metabolism and malignancy by targeting pyruvate dehydrogenase kinase 2 in gastric cancer]]> https://www.researchpad.co/product?articleinfo=5b595796463d7e5b5d3ed198

Increasing evidence indicates that dysregulation of microRNAs (miRNAs) plays a crucial role in human malignancies. Here, we showed that microRNA-422a (miR-422a) expression was dramatically downregulated in gastric cancer (GC) samples and cell lines compared with normal controls, and that its expression level was inversely related to tumor size and depth of infiltration. Functional studies revealed that the overexpression of miR-422a in GC tumor cells suppressed cell proliferation and migration, and drove a metabolic shift from aerobic glycolysis to oxidative phosphorylation. Mechanistic analysis suggested that miR-422a repressed pyruvate dehydrogenase kinase 2 (PDK2) to restore activity of the pyruvate dehydrogenase (PDH), the gatekeeping enzyme that catalyzes the decarboxylation of pyruvate to produce acetyl-CoA. Importantly, we further demonstrated that the mir-422a–PDK2 axis also influenced another metabolic pathway, de novo lipogenesis in cancer cells, and that it subsequently affected reactive oxygen species (ROS) and RB phosphorylation levels, ultimately resulting in cell cycle arrest in G1 phase. Our findings show that the miR-422a–PDK2 axis is an important mediator in metabolic reprogramming and a promising therapeutic target for antitumor treatment.

]]>
<![CDATA[Biobeam—Multiplexed wave-optical simulations of light-sheet microscopy]]> https://www.researchpad.co/product?articleinfo=5ae5a51f463d7e33ca31f532

Sample-induced image-degradation remains an intricate wave-optical problem in light-sheet microscopy. Here we present biobeam, an open-source software package that enables simulation of operational light-sheet microscopes by combining data from 105–106 multiplexed and GPU-accelerated point-spread-function calculations. The wave-optical nature of these simulations leads to the faithful reproduction of spatially varying aberrations, diffraction artifacts, geometric image distortions, adaptive optics, and emergent wave-optical phenomena, and renders image-formation in light-sheet microscopy computationally tractable.

]]>
<![CDATA[An open source tool for automatic spatiotemporal assessment of calcium transients and local ‘signal-close-to-noise’ activity in calcium imaging data]]> https://www.researchpad.co/product?articleinfo=5ae424dd463d7e02f65f0ba8

Local and spontaneous calcium signals play important roles in neurons and neuronal networks. Spontaneous or cell-autonomous calcium signals may be difficult to assess because they appear in an unpredictable spatiotemporal pattern and in very small neuronal loci of axons or dendrites. We developed an open source bioinformatics tool for an unbiased assessment of calcium signals in x,y-t imaging series. The tool bases its algorithm on a continuous wavelet transform-guided peak detection to identify calcium signal candidates. The highly sensitive calcium event definition is based on identification of peaks in 1D data through analysis of a 2D wavelet transform surface. For spatial analysis, the tool uses a grid to separate the x,y-image field in independently analyzed grid windows. A document containing a graphical summary of the data is automatically created and displays the loci of activity for a wide range of signal intensities. Furthermore, the number of activity events is summed up to create an estimated total activity value, which can be used to compare different experimental situations, such as calcium activity before or after an experimental treatment. All traces and data of active loci become documented. The tool can also compute the signal variance in a sliding window to visualize activity-dependent signal fluctuations. We applied the calcium signal detector to monitor activity states of cultured mouse neurons. Our data show that both the total activity value and the variance area created by a sliding window can distinguish experimental manipulations of neuronal activity states. Notably, the tool is powerful enough to compute local calcium events and ‘signal-close-to-noise’ activity in small loci of distal neurites of neurons, which remain during pharmacological blockade of neuronal activity with inhibitors such as tetrodotoxin, to block action potential firing, or inhibitors of ionotropic glutamate receptors. The tool can also offer information about local homeostatic calcium activity events in neurites.

]]>
<![CDATA[Fluctuating Finite Element Analysis (FFEA): A continuum mechanics software tool for mesoscale simulation of biomolecules]]> https://www.researchpad.co/product?articleinfo=5abf47e7463d7e0ff1646e8b

Fluctuating Finite Element Analysis (FFEA) is a software package designed to perform continuum mechanics simulations of proteins and other globular macromolecules. It combines conventional finite element methods with stochastic thermal noise, and is appropriate for simulations of large proteins and protein complexes at the mesoscale (length-scales in the range of 5 nm to 1 μm), where there is currently a paucity of modelling tools. It requires 3D volumetric information as input, which can be low resolution structural information such as cryo-electron tomography (cryo-ET) maps or much higher resolution atomistic co-ordinates from which volumetric information can be extracted. In this article we introduce our open source software package for performing FFEA simulations which we have released under a GPLv3 license. The software package includes a C ++ implementation of FFEA, together with tools to assist the user to set up the system from Electron Microscopy Data Bank (EMDB) or Protein Data Bank (PDB) data files. We also provide a PyMOL plugin to perform basic visualisation and additional Python tools for the analysis of FFEA simulation trajectories. This manuscript provides a basic background to the FFEA method, describing the implementation of the core mechanical model and how intermolecular interactions and the solvent environment are included within this framework. We provide prospective FFEA users with a practical overview of how to set up an FFEA simulation with reference to our publicly available online tutorials and manuals that accompany this first release of the package.

]]>
<![CDATA[Population dynamics of engineered underdominance and killer-rescue gene drives in the control of disease vectors]]> https://www.researchpad.co/product?articleinfo=5abf47e4463d7e0ff1646e88

A number of different genetics-based vector control methods have been proposed. Two approaches currently under development in Aedes aegypti mosquitoes are the two-locus engineered underdominance and killer-rescue gene drive systems. Each of these is theoretically capable of increasing in frequency within a population, thus spreading associated desirable genetic traits. Thus they have gained attention for their potential to aid in the fight against various mosquito-vectored diseases. In the case of engineered underdominance, introduced transgenes are theoretically capable of persisting indefinitely (i.e. it is self-sustaining) whilst in the killer-rescue system the rescue component should initially increase in frequency (while the lethal component (killer) is common) before eventually declining (when the killer is rare) and being eliminated (i.e. it is temporally self-limiting). The population genetics of both systems have been explored using discrete generation mathematical models. The effects of various ecological factors on these two systems have also been considered using alternative modelling methodologies. Here we formulate and analyse new mathematical models combining the population dynamics and population genetics of these two classes of gene drive that incorporate ecological factors not previously studied and are simple enough to allow the effects of each to be disentangled. In particular, we focus on the potential effects that may be obtained as a result of differing ecological factors such as strengths of larval competition; numbers of breeding sites; and the relative fitness of transgenic mosquitoes compared with their wild-type counterparts. We also extend our models to consider population dynamics in two demes in order to explore the effects of dispersal between neighbouring populations on the outcome of UD and KR gene drive systems.

]]>
<![CDATA[A mechanistic pan-cancer pathway model informed by multi-omics data interprets stochastic cell fate responses to drugs and mitogens]]> https://www.researchpad.co/product?articleinfo=5ac47589463d7e7ba4bbc955

Most cancer cells harbor multiple drivers whose epistasis and interactions with expression context clouds drug and drug combination sensitivity prediction. We constructed a mechanistic computational model that is context-tailored by omics data to capture regulation of stochastic proliferation and death by pan-cancer driver pathways. Simulations and experiments explore how the coordinated dynamics of RAF/MEK/ERK and PI-3K/AKT kinase activities in response to synergistic mitogen or drug combinations control cell fate in a specific cellular context. In this MCF10A cell context, simulations suggest that synergistic ERK and AKT inhibitor-induced death is likely mediated by BIM rather than BAD, which is supported by prior experimental studies. AKT dynamics explain S-phase entry synergy between EGF and insulin, but simulations suggest that stochastic ERK, and not AKT, dynamics seem to drive cell-to-cell proliferation variability, which in simulations is predictable from pre-stimulus fluctuations in C-Raf/B-Raf levels. Simulations suggest MEK alteration negligibly influences transformation, consistent with clinical data. Tailoring the model to an alternate cell expression and mutation context, a glioma cell line, allows prediction of increased sensitivity of cell death to AKT inhibition. Our model mechanistically interprets context-specific landscapes between driver pathways and cell fates, providing a framework for designing more rational cancer combination therapy.

]]>
<![CDATA[Imbalanced amplification: A mechanism of amplification and suppression from local imbalance of excitation and inhibition in cortical circuits]]> https://www.researchpad.co/product?articleinfo=5abb505c463d7e06b70371f1

Understanding the relationship between external stimuli and the spiking activity of cortical populations is a central problem in neuroscience. Dense recurrent connectivity in local cortical circuits can lead to counterintuitive response properties, raising the question of whether there are simple arithmetical rules for relating circuits’ connectivity structure to their response properties. One such arithmetic is provided by the mean field theory of balanced networks, which is derived in a limit where excitatory and inhibitory synaptic currents precisely balance on average. However, balanced network theory is not applicable to some biologically relevant connectivity structures. We show that cortical circuits with such structure are susceptible to an amplification mechanism arising when excitatory-inhibitory balance is broken at the level of local subpopulations, but maintained at a global level. This amplification, which can be quantified by a linear correction to the classical mean field theory of balanced networks, explains several response properties observed in cortical recordings and provides fundamental insights into the relationship between connectivity structure and neural responses in cortical circuits.

]]>
<![CDATA[Epigenetic regulation of cell fate reprogramming in aging and disease: A predictive computational model]]> https://www.researchpad.co/product?articleinfo=5abb5059463d7e06b70371ef

Understanding the control of epigenetic regulation is key to explain and modify the aging process. Because histone-modifying enzymes are sensitive to shifts in availability of cofactors (e.g. metabolites), cellular epigenetic states may be tied to changing conditions associated with cofactor variability. The aim of this study is to analyse the relationships between cofactor fluctuations, epigenetic landscapes, and cell state transitions. Using Approximate Bayesian Computation, we generate an ensemble of epigenetic regulation (ER) systems whose heterogeneity reflects variability in cofactor pools used by histone modifiers. The heterogeneity of epigenetic metabolites, which operates as regulator of the kinetic parameters promoting/preventing histone modifications, stochastically drives phenotypic variability. The ensemble of ER configurations reveals the occurrence of distinct epi-states within the ensemble. Whereas resilient states maintain large epigenetic barriers refractory to reprogramming cellular identity, plastic states lower these barriers, and increase the sensitivity to reprogramming. Moreover, fine-tuning of cofactor levels redirects plastic epigenetic states to re-enter epigenetic resilience, and vice versa. Our ensemble model agrees with a model of metabolism-responsive loss of epigenetic resilience as a cellular aging mechanism. Our findings support the notion that cellular aging, and its reversal, might result from stochastic translation of metabolic inputs into resilient/plastic cell states via ER systems.

]]>