Quantitative Analysis of Genetic and Neuronal Multi-Perturbation Experiments

Perturbation studies, in which functional performance is measured after deletion, mutation, or lesion of elements of a biological system, have been traditionally employed in many fields in biology. The vast majority of these studies have been qualitative and have employed single perturbations, often resulting in little phenotypic effect. Recently, newly emerging experimental techniques have allowed researchers to carry out concomitant multi-perturbations and to uncover the causal functional contributions of system elements. This study presents a rigorous and quantitative multi-perturbation analysis of gene knockout and neuronal ablation experiments. In both cases, a quantification of the elements' contributions, and new insights and predictions, are provided. Multi-perturbation analysis has a potentially wide range of applications and is gradually becoming an essential tool in biology

Mammalian Brain As a Network of Networks

Acknowledgements AZ, SG and AL acknowledge support from the Russian Science Foundation (16-12-00077). Authors thank T. Kuznetsova for Fig. 6.Peer reviewedPublisher PD

The pharmacological perturbation of brain zinc impairs BDNF-related signaling and the cognitive performances of young mice.

Zinc (Zn2+) is a pleiotropic modulator of the neuronal and brain activity. The disruption of intraneuronal Zn2+ levels triggers neurotoxic processes and affects neuronal functioning. In this study, we investigated how the pharmacological modulation of brain Zn2+ affects synaptic plasticity and cognition in wild-type mice. To manipulate brain Zn2+ levels, we employed the Zn2+ (and copper) chelator 5-chloro-7-iodo-8-hydroxyquinoline (clioquinol, CQ). CQ was administered for two weeks to 2.5-month-old (m.o.) mice, and effects studied on BDNF-related signaling, metalloproteinase activity as well as learning and memory performances. CQ treatment was found to negatively affect short- and long-term memory performances. The CQ-driven perturbation of brain Zn2+ was found to reduce levels of BDNF, synaptic plasticity-related proteins and dendritic spine density in vivo. Our study highlights the importance of choosing "when", "where", and "how much" in the modulation of brain Zn2+ levels. Our findings confirm the importance of targeting Zn2+ as a therapeutic approach against neurodegenerative conditions but, at the same time, underscore the potential drawbacks of reducing brain Zn2+ availability upon the early stages of development

Lithium alters expression of RNAs in a type-specific manner in differentiated human neuroblastoma neuronal cultures, including specific genes involved in Alzheimer's disease.

Lithium (Li) is a medication long-used to treat bipolar disorder. It is currently under investigation for multiple nervous system disorders, including Alzheimer's disease (AD). While perturbation of RNA levels by Li has been previously reported, its effects on the whole transcriptome has been given little attention. We, therefore, sought to determine comprehensive effects of Li treatment on RNA levels. We cultured and differentiated human neuroblastoma (SK-N-SH) cells to neuronal cells with all-trans retinoic acid (ATRA). We exposed cultures for one week to lithium chloride or distilled water, extracted total RNA, depleted ribosomal RNA and performed whole-transcriptome RT-sequencing. We analyzed results by RNA length and type. We further analyzed expression and protein interaction networks between selected Li-altered protein-coding RNAs and common AD-associated gene products. Lithium changed expression of RNAs in both non-specific (inverse to sequence length) and specific (according to RNA type) fashions. The non-coding small nucleolar RNAs (snoRNAs) were subject to the greatest length-adjusted Li influence. When RNA length effects were taken into account, microRNAs as a group were significantly less likely to have had levels altered by Li treatment. Notably, several Li-influenced protein-coding RNAs were co-expressed or produced proteins that interacted with several common AD-associated genes and proteins. Lithium's modification of RNA levels depends on both RNA length and type. Li activity on snoRNA levels may pertain to bipolar disorders while Li modification of protein coding RNAs may be relevant to AD

Optogenetic perturbations reveal the dynamics of an oculomotor integrator

Many neural systems can store short-term information in persistently firing neurons. Such persistent activity is believed to be maintained by recurrent feedback among neurons. This hypothesis has been fleshed out in detail for the oculomotor integrator (OI) for which the so-called “line attractor” network model can explain a large set of observations. Here we show that there is a plethora of such models, distinguished by the relative strength of recurrent excitation and inhibition. In each model, the firing rates of the neurons relax toward the persistent activity states. The dynamics of relaxation can be quite different, however, and depend on the levels of recurrent excitation and inhibition. To identify the correct model, we directly measure these relaxation dynamics by performing optogenetic perturbations in the OI of zebrafish expressing halorhodopsin or channelrhodopsin. We show that instantaneous, inhibitory stimulations of the OI lead to persistent, centripetal eye position changes ipsilateral to the stimulation. Excitatory stimulations similarly cause centripetal eye position changes, yet only contralateral to the stimulation. These results show that the dynamics of the OI are organized around a central attractor state—the null position of the eyes—which stabilizes the system against random perturbations. Our results pose new constraints on the circuit connectivity of the system and provide new insights into the mechanisms underlying persistent activity

The ASD Living Biology: from cell proliferation to clinical phenotype.

Autism spectrum disorder (ASD) has captured the attention of scientists, clinicians and the lay public because of its uncertain origins and striking and unexplained clinical heterogeneity. Here we review genetic, genomic, cellular, postmortem, animal model, and cell model evidence that shows ASD begins in the womb. This evidence leads to a new theory that ASD is a multistage, progressive disorder of brain development, spanning nearly all of prenatal life. ASD can begin as early as the 1st and 2nd trimester with disruption of cell proliferation and differentiation. It continues with disruption of neural migration, laminar disorganization, altered neuron maturation and neurite outgrowth, disruption of synaptogenesis and reduced neural network functioning. Among the most commonly reported high-confidence ASD (hcASD) genes, 94% express during prenatal life and affect these fetal processes in neocortex, amygdala, hippocampus, striatum and cerebellum. A majority of hcASD genes are pleiotropic, and affect proliferation/differentiation and/or synapse development. Proliferation and subsequent fetal stages can also be disrupted by maternal immune activation in the 1st trimester. Commonly implicated pathways, PI3K/AKT and RAS/ERK, are also pleiotropic and affect multiple fetal processes from proliferation through synapse and neural functional development. In different ASD individuals, variation in how and when these pleiotropic pathways are dysregulated, will lead to different, even opposing effects, producing prenatal as well as later neural and clinical heterogeneity. Thus, the pathogenesis of ASD is not set at one point in time and does not reside in one process, but rather is a cascade of prenatal pathogenic processes in the vast majority of ASD toddlers. Despite this new knowledge and theory that ASD biology begins in the womb, current research methods have not provided individualized information: What are the fetal processes and early-age molecular and cellular differences that underlie ASD in each individual child? Without such individualized knowledge, rapid advances in biological-based diagnostic, prognostic, and precision medicine treatments cannot occur. Missing, therefore, is what we call ASD Living Biology. This is a conceptual and paradigm shift towards a focus on the abnormal prenatal processes underlying ASD within each living individual. The concept emphasizes the specific need for foundational knowledge of a living child's development from abnormal prenatal beginnings to early clinical stages. The ASD Living Biology paradigm seeks this knowledge by linking genetic and in vitro prenatal molecular, cellular and neural measurements with in vivo post-natal molecular, neural and clinical presentation and progression in each ASD child. We review the first such study, which confirms the multistage fetal nature of ASD and provides the first in vitro fetal-stage explanation for in vivo early brain overgrowth. Within-child ASD Living Biology is a novel research concept we coin here that advocates the integration of in vitro prenatal and in vivo early post-natal information to generate individualized and group-level explanations, clinically useful prognoses, and precision medicine approaches that are truly beneficial for the individual infant and toddler with ASD

Onecut-dependent Nkx6.2 transcription factor expression is required for proper formation and activity of spinal locomotor circuits.

In the developing spinal cord, Onecut transcription factors control the diversification of motor neurons into distinct neuronal subsets by ensuring the maintenance of Isl1 expression during differentiation. However, other genes downstream of the Onecut proteins and involved in motor neuron diversification have remained unidentified. In the present study, we generated conditional mutant embryos carrying specific inactivation of Onecut genes in the developing motor neurons, performed RNA-sequencing to identify factors downstream of Onecut proteins in this neuron population, and employed additional transgenic mouse models to assess the role of one specific Onecut-downstream target, the transcription factor Nkx6.2. Nkx6.2 expression was up-regulated in Onecut-deficient motor neurons, but strongly downregulated in Onecut-deficient V2a interneurons, indicating an opposite regulation of Nkx6.2 by Onecut factors in distinct spinal neuron populations. Nkx6.2-null embryos, neonates and adult mice exhibited alterations of locomotor pattern and spinal locomotor network activity, likely resulting from defective survival of a subset of limb-innervating motor neurons and abnormal migration of V2a interneurons. Taken together, our results indicate that Nkx6.2 regulates the development of spinal neuronal populations and the formation of the spinal locomotor circuits downstream of the Onecut transcription factors

Gene Expression of Caenorhabditis elegans Neurons Carries Information on Their Synaptic Connectivity

The claim that genetic properties of neurons significantly influence their synaptic network structure is a common notion in neuroscience. The nematode Caenorhabditis elegans provides an exciting opportunity to approach this question in a large-scale quantitative manner. Its synaptic connectivity network has been identified, and, combined with cellular studies, we currently have characteristic connectivity and gene expression signatures for most of its neurons. By using two complementary analysis assays we show that the expression signature of a neuron carries significant information about its synaptic connectivity signature, and identify a list of putative genes predicting neural connectivity. The current study rigorously quantifies the relation between gene expression and synaptic connectivity signatures in the C. elegans nervous system and identifies subsets of neurons where this relation is highly marked. The results presented and the genes identified provide a promising starting point for further, more detailed computational and experimental investigations

NeuroFlow: A General Purpose Spiking Neural Network Simulation Platform using Customizable Processors

© 2016 Cheung, Schultz and Luk.NeuroFlow is a scalable spiking neural network simulation platform for off-the-shelf high performance computing systems using customizable hardware processors such as Field-Programmable Gate Arrays (FPGAs). Unlike multi-core processors and application-specific integrated circuits, the processor architecture of NeuroFlow can be redesigned and reconfigured to suit a particular simulation to deliver optimized performance, such as the degree of parallelism to employ. The compilation process supports using PyNN, a simulator-independent neural network description language, to configure the processor. NeuroFlow supports a number of commonly used current or conductance based neuronal models such as integrate-and-fire and Izhikevich models, and the spike-timing-dependent plasticity (STDP) rule for learning. A 6-FPGA system can simulate a network of up to ~600,000 neurons and can achieve a real-time performance of 400,000 neurons. Using one FPGA, NeuroFlow delivers a speedup of up to 33.6 times the speed of an 8-core processor, or 2.83 times the speed of GPU-based platforms. With high flexibility and throughput, NeuroFlow provides a viable environment for large-scale neural network simulation