Genetic Engineering of Induced Pluripotent Stem Cells and Reprogramming to Motor Neurons to Elucidate Selective Motor Neuron Death in Amyotrophic Lateral Sclerosis

Amyotrophic lateral sclerosis (ALS) is a progressive motor neuron disease, fatal within 1 to 5 years after onset of symptoms. About 3 out of 100’000 persons are diagnosed with ALS and there is still no cure available [1, 2]. 95% of all cases occur sporadically and the aetiology remains largely unknown [XXXX]. However, up to now 16 genes were identified to play a role in the development of familial ALS. One of these genes is FUS that encodes for the protein fused in sarcoma/translocated in liposarcoma (FUS/TLS). Mutations in this gene are responsible for some cases of sporadic as well as of inherited ALS [3]. FUS belongs to the family of heterogeneous nuclear ribonucleoproteins and is predicted to be involved in several cellular functions like transcription regulation [4], RNA splicing [5, 6], mRNA transport in neurons [7] and microRNA processing [8]. Aberrant accumulation of mutated FUS has been found in the cytoplasm of motor neurons from ALS patients [9]. The mislocalization of FUS is based on a mutation in the nuclear localization signal of FUS [10]. However, it is still unclear if the cytoplasmic localization of FUS leads to a toxic gain of cytoplasmic function and/or a loss of nuclear function that might be crucial in the course of ALS. The goal of this project is to characterize the impact of ALS-associated FUS mutations on in vitro differentiated motor neurons. To this end, we edit the genome of induced pluripotent stem cells (iPSC) using transcription activator-like effector nucleases (TALENs) [11,12] to create three isogenic cell lines, each carrying an ALS-associated FUS mutation (G156E, R244C and P525L). These iPSC’s will then be differentiated to motor neurons according to a recently establishe protocol (Ref Wichterle) and serve to study alterations in the transcriptome, proteome and metabolome upon the expression of ALS-associated FUS. With this approach, we hope to unravel the molecular mechanism leading to FUS-associated ALS and to provide new insight into the emerging connection between misregulation of RNA metabolism and neurodegeneration, a connection that is currently implied in a variety of additional neurological diseases, including spinocerebellar ataxia 2 (SCA-2), spinal muscular atrophy (SMA), fragile X syndrome, and myotonic dystrophy.

Genetic Engineering of Induced Pluripotent Stem Cells and Reprogramming to Motor Neurons to Elucidate Selective Motor Neuron Death in Amyotrophic Lateral Sclerosis

Amyotrophic lateral sclerosis (ALS) is a progressive motor neuron disease, fatal within 1 to 5 years after onset of symptoms. About 3 out of 100’000 persons are diagnosed with ALS and there is still no cure available [1, 2]. 95% of all cases occur sporadically and the aetiology remains largely unknown [3]. However, up to now 16 genes were identified to play a role in the development of familial ALS. One of these genes is FUS that encodes for the protein fused in sarcoma (FUS). Mutations in this gene are responsible for some cases of sporadic as well as of inherited ALS [4]. FUS belongs to the family of heterogeneous nuclear ribonucleoproteins and is predicted to be involved in several cellular functions like transcription regulation, RNA splicing, mRNA transport in neurons and microRNA processing [5] Aberrant accumulation of mutated FUS has been found in the cytoplasm of motor neurons from ALS patients [6]. The mislocalization of FUS is based on a mutation in the nuclear localization signal of FUS [7]. However, it is still unclear if the cytoplasmic localization of FUS leads to a toxic gain of cytoplasmic function and/or a loss of nuclear function that might be crucial in the course of ALS. The goal of this project is to characterize the impact of ALS-associated FUS mutations on in vitro differentiated motor neurons. To this end, we edit the genome of induced pluripotent stem cells (iPSC) using transcription activator-like effector nucleases (TALENs) [8,9] to create three isogenic cell lines, each carrying an ALS-associated FUS mutation (G156E, R244C and P525L). These iPSC’s will then be differentiated to motor neurons according to a recently established protocol [10] and serve to study alterations in the transcriptome, proteome and metabolome upon the expression of ALS-associated FUS. With this approach, we hope to unravel the molecular mechanism leading to FUS-associated ALS and to provide new insight into the emerging connection between misregulation of RNA metabolism and neurodegeneration, a connection that is currently implied in a variety of additional neurological diseases, including spinocerebellar ataxia 2 (SCA-2), spinal muscular atrophy (SMA), fragile X syndrome, and myotonic dystrophy. [1] Cleveland, D.W. et al. (2001) Nat Rev Neurosci 2(11): 806-819 [2] Sathasivam, S. (2010) Singapore Med J 51(5): 367-372 [3] Schymick, J.C. et al. (2007) Hum Mol Genet Vol 16: 233-242 [4] Pratt, A.J. et al. (2012). Degener Neurol Neuromuscul Dis 2012(2): 1-14 [5] Lagier-Tourenne, C. Hum Mol Genet, 2010. 19(R1): p. R46-64 [6] Mochizuki, Y. et al. (2012) J Neurol Sci 323(1-2): 85-92 [7] Dormann, D. et al. (2010) EMBO J 29(16): 2841-2857 [8] Hockemeyer, D. et al. (2011) Nat Biotech 29(8): 731-734 [9] Joung, J.K. and J.D. Sander (2013) Nat Rev Mol Cell Biol 14(1): 49-55 [10]Amoroso, M.W. et al. (2013) J Neurosci 33(2): 574-586.

Marinesco-Sjögren syndrome protein SIL1 regulates motor neuron subtype-selective ER stress in ALS.

Mechanisms underlying motor neuron subtype-selective endoplasmic reticulum (ER) stress and associated axonal pathology in amyotrophic lateral sclerosis (ALS) remain unclear. Here we show that the molecular environment of the ER between motor neuron subtypes is distinct, with characteristic signatures. We identify cochaperone SIL1, mutated in Marinesco-Sjögren syndrome (MSS), as being robustly expressed in disease-resistant slow motor neurons but not in ER stress-prone fast-fatigable motor neurons. In a mouse model of MSS, we demonstrate impaired ER homeostasis in motor neurons in response to loss of SIL1 function. Loss of a single functional Sil1 allele in an ALS mouse model (SOD1-G93A) enhanced ER stress and exacerbated ALS pathology. In SOD1-G93A mice, SIL1 levels were progressively and selectively reduced in vulnerable fast-fatigable motor neurons. Mechanistically, reduction in SIL1 levels was associated with lowered excitability of fast-fatigable motor neurons, further influencing expression of specific ER chaperones. Adeno-associated virus-mediated delivery of SIL1 to familial ALS motor neurons restored ER homeostasis, delayed muscle denervation and prolonged survival.

Random Sampling with Interspike-Intervals of the Exponential Integrate and Fire Neuron: A Computational Interpretation of UP-States

Oscillations between high and low values of the membrane potential (UP and DOWN states respectively) are an ubiquitous feature of cortical neurons during slow wave sleep and anesthesia. Nevertheless, a surprisingly small number of quantitative studies have been conducted only that deal with this phenomenon’s implications for computation. Here we present a novel theory that explains on a detailed mathematical level the computational benefits of UP states. The theory is based on random sampling by means of interspike intervals (ISIs) of the exponential integrate and fire (EIF) model neuron, such that each spike is considered a sample, whose analog value corresponds to the spike’s preceding ISI. As we show, the EIF’s exponential sodium current, that kicks in when balancing a noisy membrane potential around values close to the firing threshold, leads to a particularly simple, approximative relationship between the neuron’s ISI distribution and input current. Approximation quality depends on the frequency spectrum of the current and is improved upon increasing the voltage baseline towards threshold. Thus, the conceptually simpler leaky integrate and fire neuron that is missing such an additional current boost performs consistently worse than the EIF and does not improve when voltage baseline is increased. For the EIF in contrast, the presented mechanism is particularly effective in the high-conductance regime, which is a hallmark feature of UP-states. Our theoretical results are confirmed by accompanying simulations, which were conducted for input currents of varying spectral composition. Moreover, we provide analytical estimations of the range of ISI distributions the EIF neuron can sample from at a given approximation level. Such samples may be considered by any algorithmic procedure that is based on random sampling, such as Markov Chain Monte Carlo or message-passing methods. Finally, we explain how spike-based random sampling relates to existing computational theories about UP states during slow wave sleep and present possible extensions of the model in the context of spike-frequency adaptation.

Aberrant association of misfolded SOD1 with Na+/K+ATPase-α3 impairs its activity and contributes to motor neuron vulnerability in ALS.

Amyotrophic lateral sclerosis (ALS) is an adult onset progressive motor neuron disease with no cure. Transgenic mice overexpressing familial ALS associated human mutant SOD1 are a commonly used model for examining disease mechanisms. Presently, it is well accepted that alterations in motor neuron excitability and spinal circuits are pathological hallmarks of ALS, but the underlying molecular mechanisms remain unresolved. Here, we sought to understand whether the expression of mutant SOD1 protein could contribute to altering processes governing motor neuron excitability. We used the conformation specific antibody B8H10 which recognizes a misfolded state of SOD1 (misfSOD1) to longitudinally identify its interactome during early disease stage in SOD1G93A mice. This strategy identified a direct isozyme-specific association of misfSOD1 with Na+/K+ATPase-α3 leading to the premature impairment of its ATPase activity. Pharmacological inhibition of Na+/K+ATPase-α3 altered glutamate receptor 2 expression, modified cholinergic inputs and accelerated disease pathology. After mapping the site of direct association of misfSOD1 with Na+/K+ATPase-α3 onto a 10 amino acid stretch that is unique to Na+/K+ATPase-α3 but not found in the closely related Na+/K+ATPase-α1 isozyme, we generated a misfSOD1 binding deficient, but fully functional Na+/K+ATPase-α3 pump. Adeno associated virus (AAV)-mediated expression of this chimeric Na+/K+ATPase-α3 restored Na+/K+ATPase-α3 activity in the spinal cord, delayed pathological alterations and prolonged survival of SOD1G93A mice. Additionally, altered Na+/K+ATPase-α3 expression was observed in the spinal cord of individuals with sporadic and familial ALS. A fraction of sporadic ALS cases also presented B8H10 positive misfSOD1 immunoreactivity, suggesting that similar mechanism might contribute to the pathology.

Reinforcement learning in dendritic structures

The discovery of binary dendritic events such as local NMDA spikes in dendritic subbranches led to the suggestion that dendritic trees could be computationally equivalent to a 2-layer network of point neurons, with a single output unit represented by the soma, and input units represented by the dendritic branches. Although this interpretation endows a neuron with a high computational power, it is functionally not clear why nature would have preferred the dendritic solution with a single but complex neuron, as opposed to the network solution with many but simple units. We show that the dendritic solution has a distinguished advantage over the network solution when considering different learning tasks. Its key property is that the dendritic branches receive an immediate feedback from the somatic output spike, while in the corresponding network architecture the feedback would require additional backpropagating connections to the input units. Assuming a reinforcement learning scenario we formally derive a learning rule for the synaptic contacts on the individual dendritic trees which depends on the presynaptic activity, the local NMDA spikes, the somatic action potential, and a delayed reinforcement signal. We test the model for two scenarios: the learning of binary classifications and of precise spike timings. We show that the immediate feedback represented by the backpropagating action potential supplies the individual dendritic branches with enough information to efficiently adapt their synapses and to speed up the learning process.

Reinforcement learning in dendritic structures

The discovery of binary dendritic events such as local NMDA spikes in dendritic subbranches led to the suggestion that dendritic trees could be computationally equivalent to a 2-layer network of point neurons, with a single output unit represented by the soma, and input units represented by the dendritic branches. Although this interpretation endows a neuron with a high computational power, it is functionally not clear why nature would have preferred the dendritic solution with a single but complex neuron, as opposed to the network solution with many but simple units. We show that the dendritic solution has a distinguished advantage over the network solution when considering different learning tasks. Its key property is that the dendritic branches receive an immediate feedback from the somatic output spike, while in the corresponding network architecture the feedback would require additional backpropagating connections to the input units. Assuming a reinforcement learning scenario we formally derive a learning rule for the synaptic contacts on the individual dendritic trees which depends on the presynaptic activity, the local NMDA spikes, the somatic action potential, and a delayed reinforcement signal. We test the model for two scenarios: the learning of binary classifications and of precise spike timings. We show that the immediate feedback represented by the backpropagating action potential supplies the individual dendritic branches with enough information to efficiently adapt their synapses and to speed up the learning process.

Expression and function of 5-hydroxytryptamine 4 receptors in smooth muscle preparations from the duodenum, ileum, and pelvic flexure of horses without gastrointestinal tract disease

OBJECTIVE: To evaluate the expression of the 5-hydroxytryptamine 4 (5-HT4) receptor subtype and investigate the modulating function of those receptors on contractility in intestinal tissues obtained from horses without gastrointestinal tract disease. SAMPLE POPULATION: Smooth muscle preparations from the duodenum, ileum, and pelvic flexure collected immediately after slaughter of 24 horses with no history or signs of gastrointestinal tract disease. PROCEDURES: In isometric organ baths, the contractile activities of smooth muscle preparations in response to 5-hydroxytryptamine and electric field stimulation were assessed; the effect of tegaserod alone or in combination with 5-hydroxytryptamine on contractility of intestinal specimens was also investigated. Presence and distribution of 5-HT4 receptors in intestinal tissues and localization on interstitial cells of Cajal were examined by use of an immunofluorescence technique. RESULTS: Widespread 5-HT4 receptor immunoreactivity was observed in all intestinal smooth muscle layers; 5-HT4 receptors were absent from the myenteric plexus and interstitial cells of Cajal. In electrical field-stimulated tissue preparations of duodenum and pelvic flexure, tegaserod increased the amplitude of smooth muscle contractions in a concentration-dependent manner. Preincubation with tegaserod significantly decreased the basal tone of the 5-HT-evoked contractility in small intestine specimens, compared with the effect of 5-HT alone, thereby confirming that tegaserod was acting as a partial agonist. CONCLUSIONS AND CLINICAL RELEVANCE: In horses, 5-HT4 receptors on smooth muscle cells appear to be involved in the contractile response of the intestinal tract to 5-hydroxytryptamine. Results suggest that tegaserod may be useful for treatment of reduced gastrointestinal tract motility in horses.

Are biochemical markers of neuroendocrine tumors coreleased with insulin following local calcium stimulation in patients with insulinomas?

The objective was to test whether chromogranin A (CgA), neuron-specific enolase (NSE), and pancreatic polypeptide (PP) are released from the pancreas during the selective arterial calcium stimulation and hepatic venous sampling test (ASVS) in patients with insulinomas.

A triplet spike-timing–dependent plasticity model generalizes the Bienenstock–Cooper–Munro rule to higher-order spatiotemporal correlations

Synaptic strength depresses for low and potentiates for high activation of the postsynaptic neuron. This feature is a key property of the Bienenstock–Cooper–Munro (BCM) synaptic learning rule, which has been shown to maximize the selectivity of the postsynaptic neuron, and thereby offers a possible explanation for experience-dependent cortical plasticity such as orientation selectivity. However, the BCM framework is rate-based and a significant amount of recent work has shown that synaptic plasticity also depends on the precise timing of presynaptic and postsynaptic spikes. Here we consider a triplet model of spike-timing–dependent plasticity (STDP) that depends on the interactions of three precisely timed spikes. Triplet STDP has been shown to describe plasticity experiments that the classical STDP rule, based on pairs of spikes, has failed to capture. In the case of rate-based patterns, we show a tight correspondence between the triplet STDP rule and the BCM rule. We analytically demonstrate the selectivity property of the triplet STDP rule for orthogonal inputs and perform numerical simulations for nonorthogonal inputs. Moreover, in contrast to BCM, we show that triplet STDP can also induce selectivity for input patterns consisting of higher-order spatiotemporal correlations, which exist in natural stimuli and have been measured in the brain. We show that this sensitivity to higher-order correlations can be used to develop direction and speed selectivity.

Interactions between short-term and long-term plasticity: shooting for a moving target

Far from being static transmission units, synapses are highly dynamical elements that change over multiple time scales depending on the history of the neural activity of both the pre- and postsynaptic neuron. Moreover, synaptic changes on different time scales interact: long-term plasticity (LTP) can modify the properties of short-term plasticity (STP) in the same synapse. Most existing theories of synaptic plasticity focus on only one of these time scales (either STP or LTP or late-LTP) and the theoretical principles underlying their interactions are thus largely unknown. Here we develop a normative model of synaptic plasticity that combines both STP and LTP and predicts specific patterns for their interactions. Recently, it has been proposed that STP arranges for the local postsynaptic membrane potential at a synapse to behave as an optimal estimator of the presynaptic membrane potential based on the incoming spikes. Here we generalize this approach by considering an optimal estimator of a non-linear function of the membrane potential and the long-term synaptic efficacy—which itself may be subject to change on a slower time scale. We find that an increase in the long-term synaptic efficacy necessitates changes in the dynamics of STP. More precisely, for a realistic non-linear function to be estimated, our model predicts that after the induction of LTP, causing long-term synaptic efficacy to increase, a depressing synapse should become even more depressing. That is, in a protocol using trains of presynaptic stimuli, as the initial EPSP becomes stronger due to LTP, subsequent EPSPs should become weakened and this weakening should be more pronounced with LTP. This form of redistribution of synaptic efficacies agrees well with electrophysiological data on synapses connecting layer 5 pyramidal neurons.

Synaptic regulation of spike firing in interneurons of the striatum in vivo

The striatum, the major input nucleus of the basal ganglia, is numerically dominated by a single class of principal neurons, the GABAergic spiny projection neuron (SPN) that has been extensively studied both in vitro and in vivo. Much less is known about the sparsely distributed interneurons, principally the cholinergic interneuron (CIN) and the GABAergic fast-spiking interneuron (FSI). Here, we summarize results from two recent studies on these interneurons where we used in vivo intracellular recording techniques in urethane-anaesthetized rats (Schulz et al., J Neurosci 31[31], 2011; J Physiol, in press). Interneurons were identified by their characteristic responses to intracellular current steps and spike waveforms. Spontaneous spiking contained a high proportion (~45%) of short inter-spike intervals (ISI) of <30 ms in FSIs, but virtually none in CINs. Spiking patterns in CINs covered a broad spectrum ranging from regular tonic spiking to phasic activity despite very similar unimodal membrane potential distributions across neurons. In general, phasic spiking activity occurred in phase with the slow ECoG waves, whereas CINs exhibiting tonic regular spiking were little affected by afferent network activity. In contrast, FSIs exhibited transitions between Down and Up states very similar to SPNs. Compared to SPNs, the FSI Up state membrane potential was noisier and power spectra exhibited significantly larger power at frequencies in the gamma range (55-95 Hz). Cortical-evoked inputs had faster dynamics in FSIs than SPNs and the membrane potential preceding spontaneous spike discharge exhibited short and steep trajectories, suggesting that fast input components controlled spike output in FSIs. Intrinsic resonance mechanisms may have further enhanced the sensitivity of FSIs to fast oscillatory inputs. Induction of an activated ECoG state by local ejection of bicuculline into the superior colliculus, resulted in increased spike frequency in both interneuron classes without changing the overall distribution of ISIs. This manipulation also made CINs responsive to a light flashed into the contralateral eye. Typically, the response consisted of an excitation at short latency followed by a pause in spike firing, via an underlying depolarization-hyperpolarization membrane sequence. These results highlight the differential sensitivity of striatal interneurons to afferent synaptic signals and support a model where CINs modulate the striatal network in response to salient sensory bottom-up signals, while FSIs serve gating of top-down signals from the cortex during action selection and reward-related learning.