Computing the Local Field Potential (LFP) from Integrate-and-Fire Network Models

Leaky integrate-and-fire (LIF) network models are commonly used to study how the spiking dynamics of neural networks changes with stimuli, tasks or dynamic network states. However, neurophysiological studies in vivo often rather measure the mass activity of neuronal microcircuits with the local field potential (LFP). Given that LFPs are generated by spatially separated currents across the neuronal membrane, they cannot be computed directly from quantities defined in models of point-like LIF neurons. Here, we explore the best approximation for predicting the LFP based on standard output from point-neuron LIF networks. To search for this best “LFP proxy”, we compared LFP predictions from candidate proxies based on LIF network output (e.g, firing rates, membrane potentials, synaptic currents) with “ground-truth” LFP obtained when the LIF network synaptic input currents were injected into an analogous three-dimensional (3D) network model of multi-compartmental neurons with realistic morphology, spatial distributions of somata and synapses. We found that a specific fixed linear combination of the LIF synaptic currents provided an accurate LFP proxy, accounting for most of the variance of the LFP time course observed in the 3D network for all recording locations. This proxy performed well over a broad set of conditions, including substantial variations of the neuronal morphologies. Our results provide a simple formula for estimating the time course of the LFP from LIF network simulations in cases where a single pyramidal population dominates the LFP generation, and thereby facilitate quantitative comparison between computational models and experimental LFP recordings in vivo.     

eMatchSite: Sequence Order-Independent Structure Alignments of Ligand Binding Pockets in Protein Models

Detecting similarities between ligand binding sites in the absence of global homology between target proteins has been recognized as one of the critical components of modern drug discovery. Local binding site alignments can be constructed using sequence order-independent techniques, however, to achieve a high accuracy, many current algorithms for binding site comparison require high-quality experimental protein structures, preferably in the bound conformational state. This, in turn, complicates proteome scale applications, where only various quality structure models are available for the majority of gene products. To improve the state-of-the-art, we developed eMatchSite, a new method for constructing sequence order-independent alignments of ligand binding sites in protein models. Large-scale benchmarking calculations using adenine-binding pockets in crystal structures demonstrate that eMatchSite generates accurate alignments for almost three times more protein pairs than SOIPPA. More importantly, eMatchSite offers a high tolerance to structural distortions in ligand binding regions in protein models. For example, the percentage of correctly aligned pairs of adenine-binding sites in weakly homologous protein models is only 4–9% lower than those aligned using crystal structures. This represents a significant improvement over other algorithms, e.g. the performance of eMatchSite in recognizing similar binding sites is 6% and 13% higher than that of SiteEngine using high- and moderate-quality protein models, respectively. Constructing biologically correct alignments using predicted ligand binding sites in protein models opens up the possibility to investigate drug-protein interaction networks for complete proteomes with prospective systems-level applications in polypharmacology and rational drug repositioning. eMatchSite is freely available to the academic community as a web-server and a stand-alone software distribution at http://www.brylinski.org/ematchsite.

This is a PLOS Computational Biology Software Article

     

Use of operative temperature and standard operative temperature models in thermal biology

Operative temperature (T_e) and standard operative temperature (T_es) models have been used to address ecological questions about the thermal biology of ectotherms and endotherms for over 25 years. This review focuses on the accuracy and use of T_e and T_es models in ecological and physiological studies. The utility of T_e and T_es models lie in the fact that they take a multivariate problem involving inputs of air temperature, ground temperature, solar radiation, and wind speed and map them into a single thermal metric on a spatial scale appropriate for the animal. The most reliable T_e models are copper casts that mimic the morphology and absorptivity of an animal. Simplified T_e models such as cylinders and spheres have been shown to produce errors in T_e as large as 12 °C under certain conditions and should only be used after careful calibration against a live animal. The accuracy of heated T_es models has been addressed in much less detail then that of T_e models. When calibrated and used under conditions of low solar radiation, heated taxidermic mounts and simplified T_es models produce errors in net heat production on the order of 5% or less. In order to provide reliable data, all types of models must be calibrated over an ecologically realistic range of environmental conditions experienced by the animal. This advice has been largely ignored in the literature, where 61% of the of studies examined failed to properly calibrate the models prior to use. Additionally, studies using these models tend to lack experimental rigor, using only one or two models to make measurements on 1 or 2 days of the active season. When used correctly, T_e and T_es models can be powerful tools for integrating the thermal environment experienced by an animal into a single metric that can address questions regarding the ecology, physiology, and behavior of endotherms and ectotherms. However, until investigators make the effort to use these models in a scientifically valid manner with proper calibration and experimental design their value to thermal biologists will be limited.     

eThread: A Highly Optimized Machine Learning-Based Approach to Meta-Threading and the Modeling of Protein Tertiary Structures

Template-based modeling that employs various meta-threading techniques is currently the most accurate, and consequently the most commonly used, approach for protein structure prediction. Despite the evident progress in this field, accurate structure models cannot be constructed for a significant fraction of gene products, thus the development of new algorithms is required. Here, we describe the development, optimization and large-scale benchmarking of eThread, a highly accurate meta-threading procedure for the identification of structural templates and the construction of corresponding target-to-template alignments. eThread integrates ten state-of-the-art threading/fold recognition algorithms in a local environment and extensively uses various machine learning techniques to carry out fully automated template-based protein structure modeling. Tertiary structure prediction employs two protocols based on widely used modeling algorithms: Modeller and TASSER-Lite. As a part of eThread, we also developed eContact, which is a Bayesian classifier for the prediction of inter-residue contacts and eRank, which effectively ranks generated multiple protein models and provides reliable confidence estimates as structure quality assessment. Excluding closely related templates from the modeling process, eThread generates models, which are correct at the fold level, for >80% of the targets; 40–50% of the constructed models are of a very high quality, which would be considered accurate at the family level. Furthermore, in large-scale benchmarking, we compare the performance of eThread to several alternative methods commonly used in protein structure prediction. Finally, we estimate the upper bound for this type of approach and discuss the directions towards further improvements.     

Biases in Demographic Modeling Affect Our Understanding of Recent Divergence

Testing among competing demographic models of divergence has become an important component of evolutionary research in model and non-model organisms. However, the effect of unaccounted demographic events on model choice and parameter estimation remains largely unexplored. Using extensive simulations, we demonstrate that under realistic divergence scenarios, failure to account for population size (N_e) changes in daughter and ancestral populations leads to strong biases in divergence time estimates as well as model choice. We illustrate these issues reconstructing the recent demographic history of North Sea and Baltic Sea turbots (Scophthalmus maximus) by testing 16 isolation with migration (IM) and 16 secondary contact (SC) scenarios, modeling changes in N_e as well as the effects of linked selection and barrier loci. Failure to account for changes in N_e resulted in selecting SC models with long periods of strict isolation and divergence times preceding the formation of the Baltic Sea. In contrast, models accounting for N_e changes suggest recent (<6 kya) divergence with constant gene flow. We further show how interpreting genomic landscapes of differentiation can help discerning among competing models. For example, in the turbot data, islands of differentiation show signatures of recent selective sweeps, rather than old divergence resisting secondary introgression. The results have broad implications for the study of population divergence by highlighting the potential effects of unmodeled changes in N_e on demographic inference. Tested models should aim at representing realistic divergence scenarios for the target taxa, and extreme caution should always be exercised when interpreting results of demographic modeling.     

The Suppression of Maternal–Fetal Leukemia Inhibitory Factor Signal Relay Pathway by Maternal Immune Activation Impairs Brain Development in Mice

Recent studies in rodents suggest that maternal immune activation (MIA) by viral infection is associated with schizophrenia and autism in offspring. Although maternal IL-6 is though t to be a possible mediator relating MIA induced these neuropsychiatric disorders, the mechanism remains to be elucidated. Previously, we reported that the maternal leukemia inhibitory factor (LIF)–placental ACTH–fetal LIF signaling relay pathway (maternal–fetal LIF signal relay) promotes neurogenesis of fetal cerebrum in rats. Here we report that the maternal–fetal LIF signal relay in mice is suppressed by injection of polyriboinosinic-polyribocytidylic acid into dams, which induces MIA at 12.5 days post-coitum. Maternal IL-6 levels and gene expression of placental suppressor of cytokine signaling 3 (Socs3) increased according to the severity of MIA and gene expression of placental Socs3 correlated with maternal IL-6 levels. Furthermore, we show that MIA causes reduction of LIF level in the fetal cerebrospinal fluid, resulting in the decreased neurogenesis in the cerebrum. These findings suggest that maternal IL-6 interferes the maternal–fetal LIF signal relay by inducing SOCS3 in the placenta and leads to decreased neurogenesis.     

Using induced pluripotent stem cell neuronal models to study neurodegenerative diseases

Current application of human induced pluripotent stem cells (hiPSCs) technology in patient-specific models of neurodegenerative disorders recapitulate some of key phenotypes of diseases, representing disease-specific cellular modeling and providing a unique platform for therapeutics development. We review recent efforts toward advancing hiPSCs-derived neuronal cell types and highlight their potential use for the development of more complex in vitro models of neurodegenerative diseases by focusing on Alzheimer's disease, Parkinson's disease, Huntington's disease and Amyotrophic lateral sclerosis. We present evidence from previous works on the important phenotypic changes of various neuronal types in these neurological diseases. We also summarize efforts on conducting low- and high-throughput screening experiments with hiPSCs toward developing potential therapeutics for treatment of neurodegenerative diseases. Lastly, we discuss the limitations of hiPSCs culture system in studying neurodegenerative diseases and alternative strategies to overcome these hurdles.     

Molecular-docking-guided design and synthesis of new IAA-tacrine hybrids as multifunctional AChE/BChE inhibitors

A series of new indole-3-acetic acid (IAA)-tacrine hybrids as dual acetylcholinesterase (AChE)/butyrylcholinesterase (BChE) inhibitors were designed and prepared based on the molecular docking mode of AChE with an IAA derivative (1a), a moderate AChE inhibitor identified by screening our compound library for anti-Alzheimer’s disease (AD) drug leads. The enzyme assay results revealed that some hybrids, e.g. 5d and 5e, displayed potent dual in vitro inhibitory activities against AChE/BChE with IC₅₀ values in low nanomolar range. Molecular modeling studies in tandem with kinetic analysis suggest that these hybrids target both catalytic active site and peripheral anionic site of cholinesterase (ChE). Molecular dynamic simulations and Molecular Mechanics/Poisson-Boltzmann Surface Area (MM-PBSA) calculations indicate that 5e has more potent binding affinity than hit 1a, which may explain the stronger inhibitory effect of 5e on AChE. Furthermore, their predicted pharmacokinetic properties and in vitro influences on mouse brain neural network electrical activity were discussed. Taken together, compound 5e can be highlighted as a lead compound worthy of further optimization for designing new anti-AD drugs.     

Glial cell line-derived neurotrophic factor alters the growth characteristics and genomic imprinting of mouse multipotent adult germline stem cells

This study evaluated the essentiality of glial cell line-derived neurotrophic factor (GDNF) for in vitro culture of established mouse multipotent adult germline stem (maGS) cell lines by culturing them in the presence of GDNF, leukemia inhibitory factor (LIF) or both. We show that, in the absence of LIF, GDNF slows the proliferation of maGS cells and result in smaller sized colonies without any change in distribution of cells to different cell-cycle stages, expression of pluripotency genes and in vitro differentiation potential. Furthermore, in the absence of LIF, GDNF increased the expression of male germ-line genes and repopulated the empty seminiferous tubule of W/W^v mutant mouse without the formation of teratoma. GDNF also altered the genomic imprinting of Igf2, Peg1, and H19 genes but had no effect on DNA methylation of Oct4, Nanog and Stra8 genes. However, these effects of GDNF were masked in the presence of LIF. GDNF also did not interfere with the multipotency of maGS cells if they are cultured in the presence of LIF. In conclusion, our results suggest that, in the absence of LIF, GDNF alters the growth characteristics of maGS cells and partially impart them some of the germline stem (GS) cell-like characteristics.     

Differentiation of the SH-SY5Y Human Neuroblastoma Cell Line

Having appropriate in vivo and in vitro systems that provide translational models for human disease is an integral aspect of research in neurobiology and the neurosciences. Traditional in vitro experimental models used in neurobiology include primary neuronal cultures from rats and mice, neuroblastoma cell lines including rat B35 and mouse Neuro-2A cells, rat PC12 cells, and short-term slice cultures. While many researchers rely on these models, they lack a human component and observed experimental effects could be exclusive to the respective species and may not occur identically in humans. Additionally, although these cells are neurons, they may have unstable karyotypes, making their use problematic for studies of gene expression and reproducible studies of cell signaling. It is therefore important to develop more consistent models of human neurological disease. The following procedure describes an easy-to-follow, reproducible method to obtain homogenous and viable human neuronal cultures, by differentiating the chromosomally stable human neuroblastoma cell line, SH-SY5Y. This method integrates several previously described methods^1-4 and is based on sequential removal of serum from media. The timeline includes gradual serum-starvation, with introduction of extracellular matrix proteins and neurotrophic factors. This allows neurons to differentiate, while epithelial cells are selected against, resulting in a homogeneous neuronal culture. Representative results demonstrate the successful differentiation of SH-SY5Y neuroblastoma cells from an initial epithelial-like cell phenotype into a more expansive and branched neuronal phenotype. This protocol offers a reliable way to generate homogeneous populations of neuronal cultures that can be used for subsequent biochemical and molecular analyses, which provides researchers with a more accurate translational model of human infection and disease.     

eRepo-ORP: Exploring the Opportunity Space to Combat Orphan Diseases with Existing Drugs

About 7000 rare, or orphan, diseases affect more than 350 million people worldwide. Although these conditions collectively pose significant health care problems, drug companies seldom develop drugs for orphan diseases due to extremely limited individual markets. Consequently, developing new treatments for often life-threatening orphan diseases is primarily contingent on financial incentives from governments, special research grants, and private philanthropy. Computer-aided drug repositioning is a cheaper and faster alternative to traditional drug discovery offering a promising venue for orphan drug research. Here, we present eRepo-ORP, a comprehensive resource constructed by a large-scale repositioning of existing drugs to orphan diseases with a collection of structural bioinformatics tools, including eThread, eFindSite, and eMatchSite. Specifically, a systematic exploration of 320,856 possible links between known drugs in DrugBank and orphan proteins obtained from Orphanet reveals as many as 18,145 candidates for repurposing. In order to illustrate how potential therapeutics for rare diseases can be identified with eRepo-ORP, we discuss the repositioning of a kinase inhibitor for Ras-associated autoimmune leukoproliferative disease. The eRepo-ORP data set is available through the Open Science Framework at https://osf.io/qdjup/.     

Heat Shock Alters the Expression of Schizophrenia and Autism Candidate Genes in an Induced Pluripotent Stem Cell Model of the Human Telencephalon

Schizophrenia (SZ) and autism spectrum disorders (ASD) are highly heritable neuropsychiatric disorders, although environmental factors, such as maternal immune activation (MIA), play a role as well. Cytokines mediate the effects of MIA on neurogenesis and behavior in animal models. However, MIA stimulators can also induce a febrile reaction, which could have independent effects on neurogenesis through heat shock (HS)-regulated cellular stress pathways. However, this has not been well-studied. To help understand the role of fever in MIA, we used a recently described model of human brain development in which induced pluripotent stem cells (iPSCs) differentiate into 3-dimensional neuronal aggregates that resemble a first trimester telencephalon. RNA-seq was carried out on aggregates that were heat shocked at 39°C for 24 hours, along with their control partners maintained at 37°C. 186 genes showed significant differences in expression following HS (p<0.05), including known HS-inducible genes, as expected, as well as those coding for NGFR and a number of SZ and ASD candidates, including SMARCA2, DPP10, ARNT2, AHI1 and ZNF804A. The degree to which the expression of these genes decrease or increase during HS is similar to that found in copy loss and copy gain copy number variants (CNVs), although the effects of HS are likely to be transient. The dramatic effect on the expression of some SZ and ASD genes places HS, and perhaps other cellular stressors, into a common conceptual framework with disease-causing genetic variants. The findings also suggest that some candidate genes that are assumed to have a relatively limited impact on SZ and ASD pathogenesis based on a small number of positive genetic findings, such as SMARCA2 and ARNT2, may in fact have a much more substantial role in these disorders - as targets of common environmental stressors.     

Rat leukocyte inhibitory factor (LIF): Similarities to human LIF and generation by cells from rats with collagen-induced arthritis

Rat lymph node cells (LNC) produce a mediator which exhibits functional and physicochemical similarities to human leukocyte inhibitory factor (LIF). Measurement of LIF can be used to quantify cellular sensitivity in rats to foreign protein antigens or to a heterologous antigen in vitro. Concanavalin A-induced rat LIF has a molecular weight of 100,000-60,000 daltons and retains activity after heating to 56 °C for 30 min. Rat LIF is not synthesized in the presence of puromycin and appears to be a protein, since it is inactivated by treatment with chymotrypsin. Moreover, the activity of rat LIF is susceptible to the serine esterase inhibitor, diisopropylphosphofluoridate, but it is resistant to neuraminidase treatment. Finally, rat LIF preferentially inhibits the migration of rat and human polymorphonuclear leukocytes but not that of rat or guinea pig peritoneal exudate cells enriched for macrophages. Except for the more dispersed size of rat LIF, these properties are analogous to those described for human LIF. LIF activity is generated, in an antigen-specific manner, by LNC sensitized to ovalbumin or purified protein derivative of tuberculin when cultured with the antigen used for sensitization. LNC from rats rendered arthritic by prior intradermal (id) injection of native chick type II collagen in incomplete Freund's adjuvant produce LIF in response to this heterologous antigen. These studies delineate a new assay for cellular sensitivity in rats and provide additional evidence that cellular reactivity to type II collagen is present in this animal model of arthritis.     

Anti-enteroviral activity of new MDL-860 analogues: Synthesis,in vitro/in vivo studies and QSAR analysis

A series of 60 nitrobenzonitrile analogues of the anti-viral agent MDL-860 were synthesized (50 of which are new) and evaluated for their activity against three types of enteroviruses (coxsackievirus B1, coxsackievirus B3 and poliovirus 1). Among them, six diaryl ethers (20e, 27e, 28e, 29e, 33e and 35e) demonstrated high in vitro activity (SI > 50) towards at least one of the tested viruses and very low cytotoxicity against human cells. Compound 27e possesses the broadest spectrum of activity towards all tested viruses in the same way as MDL-860 does. The most active derivatives (27e, 29e and 35e) against coxsackievirus B1 were tested in vivo in newborn mice experimentally infected with 20 MLD₅₀ of coxsackievirus B1. Compound 29e showed promising in vivo activity (protection index 26% and 4 days lengthening of mean survival time). QSAR analysis of the substituent effects on the in vitro cytotoxicity (CC₅₀) and anti-viral activity of the nitrobenzonitrile derivatives was carried out and adequate QSAR models for the anti-viral activity of the compounds against poliovirus 1 and coxsackievirus B1 were constructed.     

Effect of Percent Relative Humidity,Moisture Content,and Compression Force on Light-Induced Fluorescence (LIF) Response as a Process Analytical Tool

The effect of percent relative humidity (16–84% RH), moisture content (4.2–6.5% w/w MC), and compression force (4.9–44.1 kN CF) on the light-induced fluorescence (LIF) response of 10% w/w active pharmaceutical ingredient (API) compacts is reported. The fluorescent response was evaluated using two separate central composite designs of experiments. The effect of % RH and CF on the LIF signal was highly significant with an adjusted R ² ?=?0.9436 and p?<?0.0001. Percent relative humidity (p?=?0.0022), CF (p?<?0.0001), and % RH² (p?=?0.0237) were statistically significant factors affecting the LIF response. The effects of MC and CF on LIF response were also statistically significant with a p value <0.0001 and adjusted R ² value of 0.9874. The LIF response was highly impacted by MC (p?<?0.0001), CF (p?<?0.0001), and MC² (p?=?0022). At 10% w/w API, increased % RH, MC, and CF led to a nonlinear decrease in LIF response. The derived quadratic model equations explained more than 94% of the data. Awareness of these effects on LIF response is critical when implementing LIF as a process analytical tool.     

Murine Embryonic Stem Cell Plasticity Is Regulated through Klf5 and Maintained by Metalloproteinase MMP1 and Hypoxia

Mouse embryonic stem cells (mESCs) are expanded and maintained pluripotent in vitro in the presence of leukemia inhibitory factor (LIF), an IL6 cytokine family member which displays pleiotropic functions, depending on both cell maturity and cell type. LIF withdrawal leads to heterogeneous differentiation of mESCs with a proportion of the differentiated cells apoptosising. During LIF withdrawal, cells sequentially enter a reversible and irreversible phase of differentiation during which LIF addition induces different effects. However the regulators and effectors of LIF–mediated reprogramming are poorly understood. By employing a LIF-dependent ‘plasticity’ test, that we set up, we show that Klf5, but not JunB is a key LIF effector. Furthermore PI3K signaling, required for the maintenance of mESC pluripotency, has no effect on mESC plasticity while displaying a major role in committed cells by stimulating expression of the mesodermal marker Brachyury at the expense of endoderm and neuroectoderm lineage markers. We also show that the MMP1 metalloproteinase, which can replace LIF for maintenance of pluripotency, mimics LIF in the plasticity window, but less efficiently. Finally, we demonstrate that mESCs maintain plasticity and pluripotency potentials in vitro under hypoxic/physioxic growth conditions at 3% O₂ despite lower levels of Pluri and Master gene expression in comparison to 20% O₂.     

An Ex vivo Model of an Oligodendrocyte-directed T-Cell Attack in Acute Brain Slices

Death of oligodendrocytes accompanied by destruction of neurons and axons are typical histopathological findings in cortical and subcortical grey matter lesions in inflammatory demyelinating disorders like multiple sclerosis (MS). In these disorders, mainly CD8⁺ T-cells of putative specificity for myelin- and oligodendrocyte-related antigens are found, so that neuronal apoptosis in grey matter lesions may be a collateral effect of these cells. Different types of animal models are established to study the underlying mechanisms of the mentioned pathophysiological processes. However, although they mimic some aspects of MS, it is impossible to dissect the exact mechanism and time course of ‘‘collateral’’ neuronal cell death. To address this course, here we show a protocol to study the mechanisms and time response of neuronal damage following an oligodendrocyte-directed CD8⁺ T cell attack. To target only the myelin sheath and the oligodendrocytes, in vitro activated oligodendrocyte-specific CD8⁺ T-cells are transferred into acutely isolated brain slices. After a defined incubation period, myelin and neuronal damage can be analysed in different regions of interest. Potential applications and limitations of this model will be discussed.     

Acridine-based (thio)semicarbazones and hydrazones: Synthesis,in vitro urease inhibition,molecular docking and in-silico ADME evaluation

Urease is a bacterial enzyme that is responsible for virulence of various pathogenic bacteria such as Staphylococcus aureus, Proteus mirabilis, Klebsiella pneumoniae, Ureaplasma urealyticum, Helicobacter pylori and Mycobacterium tuberculosis. Increased urease activity aids in survival and colonization of pathogenic bacteria causing several disorders especially gastric ulceration. Hence, urease inhibitors are used for treatment of such diseases. In search of new molecules with better urease inhibitory activity, herein we report a series of acridine derived (thio)semicarbazones (4a-4e, 6a-6l) that were found to be active against urease enzyme. Molecular docking studies were carried out to better comprehend the preferential mode of binding of these compounds against urease enzyme. Docking against urease from pathogenic bacterium S. pasteurii was also carried out with favorable results. In silico ADME evaluation was done to determine drug likeness of synthesized compounds.