Differential proteomic and genomic profiling of mouse striatal cell model of Huntington's disease and control; probable implications to the disease biology

Huntington's disease (HD) is an autosomal dominant disorder of central nervous system caused by expansion of CAG repeats in exon1 of the huntingtin gene (Htt). Among various dysfunctions originated from the mutation in Htt gene, transcriptional deregulation has been considered to be one of the most important abnormalities. Large numbers of investigations identified altered expressions of genes in brains of HD patients and many models of HD. In this study we employed 2D SDS-PAGE/MALDI-MS coupled with 2D-DIGE and real-time PCR experiments of an array of genes focused to HD pathway to determine altered protein and gene expressions in STHdh(Q111)/Hdh(Q111) cells, a cell model of HD and compared with STHdh(Q7)/Hdh(Q7) cells, its wild type counterpart. We annotated 76 proteins from these cells and observed differential expressions of 31 proteins (by 2D-DIGE) involved in processes like unfolded protein binding, negative regulation of neuron apoptosis, response to superoxides etc. Our PCR array experiments identified altered expressions of 47 genes. Altogether significant alteration of 77 genes/proteins could be identified in this HD cell line with potential relevance to HD biology. Biological significance: In this study we intended to find out differential proteomic and genomic profiles in HD condition. We used the STHdh cells, a cellular model for HD and control. These are mouse striatal neuronal cell lines harboring 7 and 111 knock -in CAG repeats in their two alleles. The 111Q containing cell line (STHdh(Q111)/Hdh(Q111)) mimics diseased condition, whereas the 7Q containing ones (STHdh(Q7)/Hdh(Q7)), serves as the proper control cell line. Proteomic experiments were performed earlier to obtain differential expressions of proteins in R6/2 mice models, Hdh(Q) knock -in mice and in plasma and CSF from HD patients. However, no earlier report on proteomic alterations in these two HD cell lines and control was available in literature. It was, therefore, an important objective to find out differential expressions of proteins in these two cell lines. In this study, we annotated 76 proteins from STHdh(Q7)/Hdh(Q7) and STHdh(Q111)/Hdh(Q111) cells using 2D-gel/mass spectrometry. Next, by performing 2D-DIGE, we observed differential expressions of 31 proteins (16 upregulated and 15 downregulated) between these two cell lines. We also performed customized qRT-PCR array focused to HD pathway and found differential expressions of 47 genes (8 gene exptessions increased and 39 genes were decreased significantly). A total of 77 genes/proteins (Htt downregulated in both the studies) were found to be significantly altered from both the experimental paradigms. We validated the differential expressions of Vim, Hypk, Ran, Dstn, Hspa5 and Sod2 either by qRT-PCR or Western blot analysis or both. Out of these 77, similar trends in alteration of 19 out of 31 and 38 out of 47 proteins/genes were reported in earlier studies. Thus our study confirmed earlier observations on differential gene/protein expressions in HD and are really useful. Additionally, we observed differential expression of some novel genes/proteins. One of this was Hypk, a Htt-interacting chaperone protein with the ability to solubilize mHtt aggregated structures in cell lines. We propose that downregulation of Hypk in STHdh-Qm (Q111)/Hdh(Q111) has a causal effect towards HD pathogenesis. Thus the novel findings from our study need further research and might be helpful to understand the molecular mechanism behind HD pathogenesis. (C) 2015 Elsevier B.V. All rights reserved.

Transgenic Drosophila model to study apolipoprotein E4-induced neurodegeneration

The epsilon 4 isoform of apolipoprotein E (ApoE4) that is involved in neuron-glial lipid metabolism has been demonstrated as the main genetic risk factor in late-onset of Alzheimer's disease. However, the mechanism underlying ApoE4-mediated neurodegeneration remains unclear. We created a transgenic model of neurodegenerative disorder by expressing epsilon 3 and epsilon 4 isoforms of human ApoE in the Drosophila melanogaster. The genetic models exhibited progressive neurodegeneration, shortened lifespan and memory impairment. Genetic interaction studies between amyloid precursor protein and ApoE in axon pathology of the disease revealed that over expression of hApoE in Appl-expressing neurons of Drosophila brain causes neurodegeneration. Moreover, acute oxidative damage in the hApoE transgenic flies triggered a neuroprotective response of hApoE3 while chronic induction of oxidative damage accelerated the rate of neurodegeneration. This Drosophila model may facilitate analysis of the molecular and cellular events implicated in hApoE4 neurotoxicity. (C) 2015 Elsevier B.V. All rights reserved.

Transgenic Drosophila model to study apolipoprotein E4-induced neurodegeneration

The epsilon 4 isoform of apolipoprotein E (ApoE4) that is involved in neuron-glial lipid metabolism has been demonstrated as the main genetic risk factor in late-onset of Alzheimer's disease. However, the mechanism underlying ApoE4-mediated neurodegeneration remains unclear. We created a transgenic model of neurodegenerative disorder by expressing epsilon 3 and epsilon 4 isoforms of human ApoE in the Drosophila melanogaster. The genetic models exhibited progressive neurodegeneration, shortened lifespan and memory impairment. Genetic interaction studies between amyloid precursor protein and ApoE in axon pathology of the disease revealed that over expression of hApoE in Appl-expressing neurons of Drosophila brain causes neurodegeneration. Moreover, acute oxidative damage in the hApoE transgenic flies triggered a neuroprotective response of hApoE3 while chronic induction of oxidative damage accelerated the rate of neurodegeneration. This Drosophila model may facilitate analysis of the molecular and cellular events implicated in hApoE4 neurotoxicity. (C) 2015 Elsevier B.V. All rights reserved.

Patterning and detailed study of human hNT astrocytes on parylene-C/silicon dioxide substrates to the single cell level.

It is estimated that the adult human brain contains 100 billion neurons with 5-10 times as many astrocytes. Although it has been generally considered that the astrocyte is a simple supportive cell to the neuron, recent research has revealed new functionality of the astrocyte in the form of information transfer to neurons of the brain. In our previous work we developed a protocol to pattern the hNT neuron (derived from the human teratocarcinoma cell line (hNT)) on parylene-C/SiO(2) substrates. In this work, we report how we have managed to pattern hNT astrocytes, on parylene-C/SiO(2) substrates to single cell resolution. This article disseminates the nanofabrication and cell culturing steps necessary for the patterning of such cells. In addition, it reports the necessary strip lengths and strip width dimensions of parylene-C that encourage high degrees of cellular coverage and single cell isolation for this cell type. The significance in patterning the hNT astrocyte on silicon chip is that it will help enable single cell and network studies into the undiscovered functionality of this interesting cell, thus, contributing to closer pathological studies of the human brain.

Early Functional Deficit and Microglial Disturbances in a Mouse Model of Amyotrophic Lateral Sclerosis

11 p.

Metabolic efficiency with fast spiking in the squid axon

Fundamentally, action potentials in the squid axon are consequence of the entrance of sodium ions during the depolarization of the rising phase of the spike mediated by the outflow of potassium ions during the hyperpolarization of the falling phase. Perfect metabolic efficiency with a minimum charge needed for the change in voltage during the action potential would confine sodium entry to the rising phase and potassium efflux to the falling phase. However, because sodium channels remain open to a significant extent during the falling phase, a certain overlap of inward and outward currents is observed. In this work we investigate the impact of ion overlap on the number of the adenosine triphosphate (ATP) molecules and energy cost required per action potential as a function of the temperature in a Hodgkin–Huxley model. Based on a recent approach to computing the energy cost of neuronal action potential generation not based on ion counting, we show that increased firing frequencies induced by higher temperatures imply more efficient use of sodium entry, and then a decrease in the metabolic energy cost required to restore the concentration gradients after an action potential. Also, we determine values of sodium conductance at which the hydrolysis efficiency presents a clear minimum.

Role of G protein coupled inwardly rectifier K+ channels (GIRK) on the neurobiology depression

353 págs.

GABA release by hippocampal astrocytes

10 p.

Energy and information in Hodgkin-Huxley neurons

[EN]The generation of spikes by neurons is energetically a costly process and the evaluation of the metabolic energy required to maintain the signaling activity of neurons a challenge of practical interest. Neuron models are frequently used to represent the dynamics of real neurons but hardly ever to evaluate the electrochemical energy required to maintain that dynamics. This paper discusses the interpretation of a Hodgkin-Huxley circuit as an energy model for real biological neurons and uses it to evaluate the consumption of metabolic energy in the transmission of information between neurons coupled by electrical synapses, i.e., gap junctions. We show that for a single postsynaptic neuron maximum energy efficiency, measured in bits of mutual information per molecule of adenosine triphosphate (ATP) consumed, requires maximum energy consumption. For groups of parallel postsynaptic neurons we determine values of the synaptic conductance at which the energy efficiency of the transmission presents clear maxima at relatively very low values of metabolic energy consumption. Contrary to what could be expected, the best performance occurs at a low energy cost.

Psychobiophysics of transcranial magnetic stimulation

Transcranial magnetic stimulation (TMS) is a technique that stimulates the brain using a magnetic coil placed on the scalp. Since it is applicable to humans non-invasively, directly interfering with neural electrical activity, it is potentially a good tool to study the direct relationship between perceptual experience and neural activity. However, it has been difficult to produce a clear perceptible phenomenon with TMS of sensory areas, especially using a single magnetic pulse. Also, the biophysical mechanisms of magnetic stimulation of single neurons have been poorly understood.

In the psychophysical part of this thesis, perceptual phenomena induced by TMS of the human visual cortex are demonstrated as results of the interactions with visual inputs. We first introduce a method to create a hole, or a scotoma, in a flashed, large-field visual pattern using single-pulse TMS. Spatial aspects of the interactions are explored using the distortion effect of the scotoma depending on the visual pattern, which can be luminance-defined or illusory. Its similarity to the distortion of afterimages is also discussed. Temporal interactions are demonstrated in the filling-in of the scotoma with temporally adjacent visual features, as well as in the effective suppression of transient visual features. Also, paired-pulse TMS is shown to lead to different brightness modulations in transient and sustained visual stimuli.

In the biophysical part, we first develop a biophysical theory to simulate the effect of magnetic stimulation on arbitrary neuronal structure. Computer simulations are performed on cortical neuron models with realistic structure and channels, combined with the current injection that simulates magnetic stimulation. The simulation results account for general and basic characteristics of the macroscopic effects of TMS including our psychophysical findings, such as a long inhibitory effect, dependence on the background activity, and dependence on the direction of the induced electric field.

The perceptual effects and the cortical neuron model presented here provide foundations for the study of the relationship between perception and neural activity. Further insights would be obtained from extension of our model to neuronal networks and psychophysical studies based on predictions of the biophysical model.

Latent variable models for neural data analysis

The brain is perhaps the most complex system to have ever been subjected to rigorous scientific investigation. The scale is staggering: over 10^11 neurons, each making an average of 10^3 synapses, with computation occurring on scales ranging from a single dendritic spine, to an entire cortical area. Slowly, we are beginning to acquire experimental tools that can gather the massive amounts of data needed to characterize this system. However, to understand and interpret these data will also require substantial strides in inferential and statistical techniques. This dissertation attempts to meet this need, extending and applying the modern tools of latent variable modeling to problems in neural data analysis.

It is divided into two parts. The first begins with an exposition of the general techniques of latent variable modeling. A new, extremely general, optimization algorithm is proposed - called Relaxation Expectation Maximization (REM) - that may be used to learn the optimal parameter values of arbitrary latent variable models. This algorithm appears to alleviate the common problem of convergence to local, sub-optimal, likelihood maxima. REM leads to a natural framework for model size selection; in combination with standard model selection techniques the quality of fits may be further improved, while the appropriate model size is automatically and efficiently determined. Next, a new latent variable model, the mixture of sparse hidden Markov models, is introduced, and approximate inference and learning algorithms are derived for it. This model is applied in the second part of the thesis.

The second part brings the technology of part I to bear on two important problems in experimental neuroscience. The first is known as spike sorting; this is the problem of separating the spikes from different neurons embedded within an extracellular recording. The dissertation offers the first thorough statistical analysis of this problem, which then yields the first powerful probabilistic solution. The second problem addressed is that of characterizing the distribution of spike trains recorded from the same neuron under identical experimental conditions. A latent variable model is proposed. Inference and learning in this model leads to new principled algorithms for smoothing and clustering of spike data.

Response of multiple simultaneously recorded macaque area LIP neurons in a memory saccade task

Cells in the lateral intraparietal cortex (LIP) of rhesus macaques respond vigorously and in spatially-tuned fashion to briefly memorized visual stimuli. Responses to stimulus presentation, memory maintenance, and task completion are seen, in varying combination from neuron to neuron. To help elucidate this functional segmentation a new system for simultaneous recording from multiple neighboring neurons was developed. The two parts of this dissertation discuss the technical achievements and scientific discoveries, respectively.

Technology. Simultanous recordings from multiple neighboring neurons were made with four-wire bundle electrodes, or tetrodes, which were adapted to the awake behaving primate preparation. Signals from these electrodes were partitionable into a background process with a 1/f-like spectrum and foreground spiking activity spanning 300-6000 Hz. Continuous voltage recordings were sorted into spike trains using a state-of-the-art clustering algorithm, producing a mean of 3 cells per site. The algorithm classified 96% of spikes correctly when tetrode recordings were confirmed with simultaneous intracellular signals. Recording locations were verified with a new technique that creates electrolytic lesions visible in magnetic resonance imaging, eliminating the need for histological processing. In anticipation of future multi-tetrode work, the chronic chamber microdrive, a device for long-term tetrode delivery, was developed.

Science. Simultaneously recorded neighboring LIP neurons were found to have similar preferred targets in the memory saccade paradigm, but dissimilar peristimulus time histograms, PSTH). A majority of neighboring cell pairs had a difference in preferred directions of under 45° while the trial time of maximal response showed a broader distribution, suggesting homogeneity of tuning with het erogeneity of function. A continuum of response characteristics was present, rather than a set of specific response types; however, a mapping experiment suggests this may be because a given cell's PSTH changes shape as well as amplitude through the response field. Spike train autocovariance was tuned over target and changed through trial epoch, suggesting different mechanisms during memory versus background periods. Mean frequency-domain spike-to-spike coherence was concentrated below 50 Hz with a significant maximum of 0.08; mean time-domain coherence had a narrow peak in the range ±10 ms with a significant maximum of 0.03. Time-domain coherence was found to be untuned for short lags (10 ms), but significantly tuned at larger lags (50 ms).

The central nervous control of walking in the locust, Schistocerca Americana

Rhythmic motor behaviors in all animals appear to be under the control of "central pattern generator" circuits, neural circuits which can produce output patterns appropriate for behavior even when isolated from their normal peripheral inputs. Insects have been a useful model system in which to study the control of legged terrestrial locomotion. Much is known about walking in insects at the behavioral level, but to date there has been no clear demonstration that a central pattern generator for walking exists. The focus of this thesis is to explore the central neural basis for locomotion in the locust, Schistocerca americana.

Rhythmic motor patterns could be evoked in leg motor neurons of isolated thoracic ganglia of locusts by the muscarinic agonist pilocarpine. These motor patterns would be appropriate for the movement of single legs during walking. Rhythmic patterns could be evoked in all three thoracic ganglia, but the segmental rhythms differed in their sensitivities to pilocarpine, their frequencies, and the phase relationships of motor neuron antagonists. These different patterns could be generated by a simple adaptable model circuit, which was both simulated and implemented in VLSI hardware. The intersegmental coordination of leg motor rhythms was then examined in preparations of isolated chains of thoracic ganglia. Correlations between motor patterns in different thoracic ganglia indicated that central coupling between segmental pattern generators is likely to contribute to the coordination of the legs during walking.

The work described here clearly demonstrates that segmental pattern generators for walking exist in insects. The pattern generators produce motor outputs which are likely to contribute to the coordination of the joints of a limb, as well as the coordination of different limbs. These studies lay the groundwork for further studies to determine the relative contributions of central and sensory neural mechanisms to terrestrial walking.

Modelagem do potencial elétrico através da membrana do neurônio ganglionar e células de neuroblastoma: efeitos das cargas superficiais.

O objetivo do presente trabalho é comparar, do ponto de vista elétrico, a membrana do neurônio ganglionar com a da célula de neuroblastoma, analisando os efeitos das cargas fixas sobre o potencial elétrico nas superfícies da bicamada lipídica e também sobre o comportamento do perfil de potencial através da membrana, considerando as condiçõesfísico-químicas do estado de repouso e do estado de potencial de ação. As condições para a ocorrência dos referidos estados foram baseadas em valores numéricos de parâmetros elétricos e químicos, característicos dessas células, obtidos na literatura. O neurônio ganglionar exemplifica um neurônio sadio, e a célula de neuroblastoma, que é uma célula tumoral, exemplifica um neurônio patológico, alterado por esta condição. O neuroblastoma é um tumor que se origina das células da crista neural (neuroblastos), que é uma estrutura embrionária que dá origem a muitas partes do sistema nervoso, podendo surgir em diversos locais do organismo, desde a região do crânio até a área mais inferior da coluna. O modelo adotado para simular a membrana de neurônio inclui: (a) as distribuições espaciais de cargas elétricas fixas no glicocálix e na rede de proteínas citoplasmáticas; (b) as distribuições de cargas na solução eletrolítica dos meios externo e interno; e (c) as cargas superficiais da bicamada lipídica. Os resultados que obtivemos mostraram que, nos estados de repouso e de ação, os potenciais superficiais da bicamada interno (ÁSbc) e externo (ÁSgb) da célula de neuroblastoma não sofrem alteração mensurável, quando a densidade de carga na superfície interna (QSbc) torna-se 50 vezes mais negativa, tanto para uma densidade de carga na superfície externa da bicamada nula (QSgb = 0), como para um valor de QSgb 6= 0. Porém, no estado de repouso, uma leve queda em ÁSbc do neur^onio ganglionar pode ser observada com este nível de variação de carga, sendo que ÁSgb do neurônio ganglionar é mais negativo quando QSgb = 1=1100 e/A2. No estado de ação, para QSgb = 0, o aumento da negatividade de QSbc não provoca alteração detectável de ÁSbc e ÁSgb para os dois neurônios. Quando consideramos QSgb = 1=1100 e/A2, ÁSgb do neurônio ganglionar se torna mais negativo, não se observando variações detectáveis nos potenciais superficiais da célula de neuroblastoma. Tanto no repouso quanto no estado de ação, ÁSgb das duas células não sofre variação sensível com o aumento da negatividade da carga fixa distribuída espacialmente no citoplasma. Já a ÁSbc sofre uma queda gradativa nos dois tipos celulares; porém, no estado de ação, esta queda é mais rápida. Descobrimos diferenças importantes nos perfis de potencial das duas células, especialmente na região do glicocálix.

The Physiology and Computation of Pyramidal Neurons

A variety of neural signals have been measured as correlates to consciousness. In particular, late current sinks in layer 1, distributed activity across the cortex, and feedback processing have all been implicated. What are the physiological underpinnings of these signals? What computational role do they play in the brain? Why do they correlate to consciousness? This thesis begins to answer these questions by focusing on the pyramidal neuron. As the primary communicator of long-range feedforward and feedback signals in the cortex, the pyramidal neuron is set up to play an important role in establishing distributed representations. Additionally, the dendritic extent, reaching layer 1, is well situated to receive feedback inputs and contribute to current sinks in the upper layers. An investigation of pyramidal neuron physiology is therefore necessary to understand how the brain creates, and potentially uses, the neural correlates of consciousness. An important part of this thesis will be in establishing the computational role that dendritic physiology plays. In order to do this, a combined experimental and modeling approach is used.

This thesis beings with single-cell experiments in layer 5 and layer 2/3 pyramidal neurons. In both cases, dendritic nonlinearities are characterized and found to be integral regulators of neural output. Particular attention is paid to calcium spikes and NMDA spikes, which both exist in the apical dendrites, considerable distances from the spike initiation zone. These experiments are then used to create detailed multicompartmental models. These models are used to test hypothesis regarding spatial distribution of membrane channels, to quantify the effects of certain experimental manipulations, and to establish the computational properties of the single cell. We find that the pyramidal neuron physiology can carry out a coincidence detection mechanism. Further abstraction of these models reveals potential mechanisms for spike time control, frequency modulation, and tuning. Finally, a set of experiments are carried out to establish the effect of long-range feedback inputs onto the pyramidal neuron. A final discussion then explores a potential way in which the physiology of pyramidal neurons can establish distributed representations, and contribute to consciousness.