Synapse molecular complexity and the plasticity behaviour problem

Simulated complexes formed from a set of postsynaptic proteins suggest a localised effect of a hypomorphic Shank mutation

BACKGROUND

The postsynaptic density is an elaborate protein network beneath the postsynaptic membrane involved in the molecular processes underlying learning and memory. The postsynaptic density is built up from the same major proteins but its exact composition and organization differs between synapses. Mutations perturbing protein: protein interactions generally occurring in this network might lead to effects specific for cell types or processes, the understanding of which can be especially challenging.

RESULTS

In this work we use systems biology-based modeling of protein complex distributions in a simplified set of major postsynaptic proteins to investigate the effect of a hypomorphic Shank mutation perturbing a single well-defined interaction. We use data sets with widely variable abundances of the constituent proteins. Our results suggest that the effect of the mutation is heavily dependent on the overall availability of all the protein components of the whole network and no trivial correspondence between the expression level of the directly affected proteins and overall complex distribution can be observed.

CONCLUSIONS

Our results stress the importance of context-dependent interpretation of mutations. Even the weakening of a generally occurring protein: protein interaction might have well-defined effects, and these can not easily be predicted based only on the abundance of the proteins directly affected. Our results provide insight on how cell-specific effects can be exerted by a mutation perturbing a generally occurring interaction even when the wider interaction network is largely similar.

In vivo overexpression of synaptogyrin-3 promotes striatal synaptic dopamine uptake in LRRK2R1441G mutant mouse model of Parkinson's disease

BACKGROUND

Leucine-rich repeat kinase 2 (LRRK2) mutation is a common genetic risk factor of Parkinson's disease (PD). Presynaptic dysfunction is an early pathogenic event associated with dopamine (DA) dysregulation in striatum of the brain. DA uptake activity of DA uptake transporter (DAT) affects synaptic plasticity and motor and non-motor behavior. Synaptogyrin-3 (SYNGR3) is part of the synaptogyrin family, especially abundant in brain. Previous in vitro studies demonstrated interaction between SYNGR3 and DAT. Reduced SYNGR3 expression was observed in human PD brains with unclear reasons.

METHODS

Here, we further explored whether inducing SYNGR3 expression can influence (i) cellular DA uptake using differentiated human SH-SY5Y neuronal cells, (ii) striatal synaptosomal DA uptake in a mutant LRRK2^R1441G  knockin mouse model of PD, and (iii) innate rodent behavior using the marble burying test.

RESULTS

Young LRRK2 mutant mice exhibited significantly lower SYNGR3 levels in striatum compared to age-matched wild-type (WT) controls, resembling level in aged WT mice. SYNGR3 is spatially co-localized with DAT at striatal presynaptic terminals, visualized by immuno-gold transmission electron microscopy and immunohistochemistry. Their protein-protein interaction was confirmed by co-immunoprecipitation. Transient overexpression of SYNGR3 in differentiated SH-SY5Y cells increased cellular DA uptake activity without affecting total DAT levels. Inducing SYNGR3 overexpression by adeno-associated virus-7 (AAV7) injection in vivo into striatum increased ex vivo synaptosomal DA uptake in LRRK2 mutant mice and improved their innate marble burying behavior.

CONCLUSION

Brain SYNGR3 expression may be an important determinant to striatal DA homeostasis and synaptic function. Our preliminary behavioral test showed improved innate behavior after SYNGR3 overexpression in LRRK2 mutant mice, advocating further studies to determine the influence of SYNGR3 in the pathophysiology of DA neurons in PD.

Artifacts and levels of abstraction

The purpose of this article is to show how the comparison or analogy with artifacts (i.e., systems engineered by humans) is foundational for the idea that complex neuro-cognitive systems are amenable to explanation at distinct levels, which is a central simplifying strategy for modeling the brain. The most salient source of analogy is of course the digital computer, but I will discuss how some more general comparisons with the processes of design and engineering also play a significant role. I will show how the analogies, and the subsequent notion of a distinct computational level, have engendered common ideas about how safely to abstract away from the complexity of concrete neural systems, yielding explanations of how neural processes give rise to cognitive functions. I also raise worries about the limitations of these explanations, due to neglected differences between the human-made devices and biological organs.

Complex regulation of Gephyrin splicing is a determinant of inhibitory postsynaptic diversity

Gephyrin (GPHN) regulates the clustering of postsynaptic components at inhibitory synapses and is involved in pathophysiology of neuropsychiatric disorders. Here, we uncover an extensive diversity of GPHN transcripts that are tightly controlled by splicing during mouse and human brain development. Proteomic analysis reveals at least a hundred isoforms of GPHN incorporated at inhibitory Glycine and gamma-aminobutyric acid A receptors containing synapses. They exhibit different localization and postsynaptic clustering properties, and altering the expression level of one isoform is sufficient to affect the number, size, and density of inhibitory synapses in cerebellar Purkinje cells. Furthermore, we discovered that splicing defects reported in neuropsychiatric disorders are carried by multiple alternative GPHN transcripts, demonstrating the need for a thorough analysis of the GPHN transcriptome in patients. Overall, we show that alternative splicing of GPHN is an important genetic variation to consider in neurological diseases and a determinant of the diversity of postsynaptic inhibitory synapses.

The protein gephyrin is involved in organizing synapses. Here, the authors show how different transcripts of gephyrin form and regulate inhibitory synapses.

Geometric framework to predict structure from function in neural networks

Neural computation in biological and artificial networks relies on the nonlinear summation of many inputs. The structural connectivity matrix of synaptic weights between neurons is a critical determinant of overall network function, but quantitative links between neural network structure and function are complex and subtle. For example, many networks can give rise to similar functional responses, and the same network can function differently depending on context. Whether certain patterns of synaptic connectivity are required to generate specific network-level computations is largely unknown. Here we introduce a geometric framework for identifying synaptic connections required by steady-state responses in recurrent networks of threshold-linear neurons. Assuming that the number of specified response patterns does not exceed the number of input synapses, we analytically calculate the solution space of all feedforward and recurrent connectivity matrices that can generate the specified responses from the network inputs. A generalization accounting for noise further reveals that the solution space geometry can undergo topological transitions as the allowed error increases, which could provide insight into both neuroscience and machine learning. We ultimately use this geometric characterization to derive certainty conditions guaranteeing a nonzero synapse between neurons. Our theoretical framework could thus be applied to neural activity data to make rigorous anatomical predictions that follow generally from the model architecture.

Towards the Idea of Molecular Brains

How can single cells without nervous systems perform complex behaviours such as habituation, associative learning and decision making, which are considered the hallmark of animals with a brain? Are there molecular systems that underlie cognitive properties equivalent to those of the brain? This review follows the development of the idea of molecular brains from Darwin’s “root brain hypothesis”, through bacterial chemotaxis, to the recent discovery of neuron-like r-protein networks in the ribosome. By combining a structural biology view with a Bayesian brain approach, this review explores the evolutionary labyrinth of information processing systems across scales. Ribosomal protein networks open a window into what were probably the earliest signalling systems to emerge before the radiation of the three kingdoms. While ribosomal networks are characterised by long-lasting interactions between their protein nodes, cell signalling networks are essentially based on transient interactions. As a corollary, while signals propagated in persistent networks may be ephemeral, networks whose interactions are transient constrain signals diffusing into the cytoplasm to be durable in time, such as post-translational modifications of proteins or second messenger synthesis. The duration and nature of the signals, in turn, implies different mechanisms for the integration of multiple signals and decision making. Evolution then reinvented networks with persistent interactions with the development of nervous systems in metazoans. Ribosomal protein networks and simple nervous systems display architectural and functional analogies whose comparison could suggest scale invariance in information processing. At the molecular level, the significant complexification of eukaryotic ribosomal protein networks is associated with a burst in the acquisition of new conserved aromatic amino acids. Knowing that aromatic residues play a critical role in allosteric receptors and channels, this observation suggests a general role of π systems and their interactions with charged amino acids in multiple signal integration and information processing. We think that these findings may provide the molecular basis for designing future computers with organic processors.

Primate-specific retrotransposons and the evolution of circadian networks in the human brain

The circadian rhythm of the human brain is attuned to sleep-wake cycles that entail global alterations in neuronal excitability. This periodicity involves a highly coordinated regulation of gene expression. A growing number of studies are documenting a fascinating connection between primate-specific retrotransposons (Alu elements) and key epigenetic regulatory processes in the primate brain. Collectively, these studies indicate that Alu elements embedded in the human neuronal genome mediate post-transcriptional processes that unite human-specific neuroepigenetic landscapes and circadian rhythm. Here, we review evidence linking Alu retrotransposon-mediated posttranscriptional pathways to circadian gene expression. We hypothesize that Alu retrotransposons participate in the organization of circadian brain function through multidimensional neuroepigenetic pathways. We anticipate that these pathways are closely tied to the evolution of human cognition and their perturbation contributes to the manifestation of human-specific neurological diseases. Finally, we address current challenges and accompanying opportunities in studying primate- and human-specific transposable elements.

Environmental Enrichment Enhances Cav 2.1 Channel-Mediated Presynaptic Plasticity in Hypoxic-Ischemic Encephalopathy

Hypoxic–ischemic encephalopathy (HIE) is a devastating neonatal brain condition caused by lack of oxygen and limited blood flow. Environmental enrichment (EE) is a classic paradigm with a complex stimulation of physical, cognitive, and social components. EE can exert neuroplasticity and neuroprotective effects in immature brains. However, the exact mechanism of EE on the chronic condition of HIE remains unclear. HIE was induced by a permanent ligation of the right carotid artery, followed by an 8% O₂ hypoxic condition for 1 h. At 6 weeks of age, HIE mice were randomly assigned to either standard cages or EE cages. In the behavioral assessments, EE mice showed significantly improved motor performances in rotarod tests, ladder walking tests, and hanging wire tests, compared with HIE control mice. EE mice also significantly enhanced cognitive performances in Y-maze tests. Particularly, EE mice showed a significant increase in Ca_v 2.1 (P/Q type) and presynaptic proteins by molecular assessments, and a significant increase of Ca_v 2.1 in histological assessments of the cerebral cortex and hippocampus. These results indicate that EE can upregulate the expression of the Ca_v 2.1 channel and presynaptic proteins related to the synaptic vesicle cycle and neurotransmitter release, which may be responsible for motor and cognitive improvements in HIE.

The Synapse Diversity Dilemma: Molecular Heterogeneity Confounds Studies of Synapse Function

Recent studies have shown an unexpectedly high degree of synapse diversity arising from molecular and morphological differences among individual synapses. Diverse synapse types are spatially distributed within individual dendrites, between different neurons, and across and between brain regions, producing the synaptome architecture of the brain. The spatial organization of synapse heterogeneity is important because the physiological activation of heterogeneous excitatory synapses produces a non-uniform spatial output of synaptic potentials, which confounds the interpretation of measurements obtained from population-averaging electrodes, optrodes and biochemical methods that lack single-synapse resolution. Population-averaging measurements cannot distinguish between changes in the composition of populations of synapses and changing synaptic physiology. Here we consider the implications of synapse diversity and its organization into synaptome architecture for studies of synapse physiology, plasticity, development and behavior, and for the interpretation of phenotypes arising from pharmacological and genetic perturbations. We conclude that prevailing models based on population-averaging measurements need reconsideration and that single-synapse resolution physiological recording methods are required to confirm or refute the major synaptic models of behavior.