Nanostructural Diversity of Synapses in the Mammalian Spinal Cord

This work for funded by the Biotechnology and Biological Sciences Research Council (BBSRC; BB/M021793/1), RS MacDonald Charitable Trust, Motor Neurone Disease (MND) Association UK (Miles/Apr18/863-791), the Engineering and Physical Sciences Research Council (EPSRC; EP/P030017/1), Welcome Trust (202932/Z/16/Z), European Research Council (ERC; 695568) and the Simons Initiative for the Developing Brain.Functionally distinct synapses exhibit diverse and complex organisation at molecular and nanoscale levels. Synaptic diversity may be dependent on developmental stage, anatomical locus and the neural circuit within which synapses reside. Furthermore, astrocytes, which align with pre and post-synaptic structures to form “tripartite synapses”, can modulate neural circuits and impact on synaptic organisation. In this study, we aimed to determine which factors impact the diversity of excitatory synapses throughout the lumbar spinal cord. We used PSD95-eGFP mice, to visualise excitatory postsynaptic densities (PSDs) using high-resolution and super-resolution microscopy. We reveal a detailed and quantitative map of the features of excitatory synapses in the lumbar spinal cord, detailing synaptic diversity that is dependent on developmental stage, anatomical region and whether associated with VGLUT1 or VGLUT2 terminals. We report that PSDs are nanostructurally distinct between spinal laminae and across age groups. PSDs receiving VGLUT1 inputs also show enhanced nanostructural complexity compared with those receiving VGLUT2 inputs, suggesting pathway-specific diversity. Finally, we show that PSDs exhibit greater nanostructural complexity when part of tripartite synapses, and we provide evidence that astrocytic activation enhances PSD95 expression. Taken together, these results provide novel insights into the regulation and diversification of synapses across functionally distinct spinal regions and advance our general understanding of the ‘rules’ governing synaptic nanostructural organisation.Publisher PDFPeer reviewe

Neuron-glial Interactions

Although lagging behind classical computational neuroscience, theoretical and computational approaches are beginning to emerge to characterize different aspects of neuron-glial interactions. This chapter aims to provide essential knowledge on neuron-glial interactions in the mammalian brain, leveraging on computational studies that focus on structure (anatomy) and function (physiology) of such interactions in the healthy brain. Although our understanding of the need of neuron-glial interactions in the brain is still at its infancy, being mostly based on predictions that await for experimental validation, simple general modeling arguments borrowed from control theory are introduced to support the importance of including such interactions in traditional neuron-based modeling paradigms.Junior Leader Fellowship Program by “la Caixa” Banking Foundation (LCF/BQ/LI18/11630006

Neuron-Glial Interactions

Although lagging behind classical computational neuroscience, theoretical and computational approaches are beginning to emerge to characterize different aspects of neuron-glial interactions. This chapter aims to provide essential knowledge on neuron-glial interactions in the mammalian brain, leveraging on computational studies that focus on structure (anatomy) and function (physiology) of such interactions in the healthy brain. Although our understanding of the need of neuron-glial interactions in the brain is still at its infancy, being mostly based on predictions that await for experimental validation, simple general modeling arguments borrowed from control theory are introduced to support the importance of including such interactions in traditional neuron-based modeling paradigms.Comment: 43 pages, 2 figures, 1 table. Accepted for publication in the "Encyclopedia of Computational Neuroscience," D. Jaeger and R. Jung eds., Springer-Verlag New York, 2020 (2nd edition

Uso de Arcillas Especiales para Depuración de Aguas Residuales

Para evaluar la eficacia de las arcillas especiales para la remoción de metales pesados de aguas residuales, se muestrearon y caracterizaron varios tipos de arcillas y las aguas de tres efluentes residuales industriales. Los componentes mayoritarios de las arcillas fueron: sepiolita: montmorillonita (76%); bentonita magnésica: vermiculita (74,4%); bentonita alumínica: esmectita (69,1%) y paligorskita (80%). Las aguas residuales se hicieron circular a través de lechos de cada una de las arcillas; manteniendo un tiempo de contacto de tres horas. Se analizó el contenido de metales pesados disueltos en las aguas antes y después de pasar a través de cada lecho. La sepiolita y la bentonita magnésica son eficaces para reducir la concentración de metales pesados en aguas residuales industriales. Se concluye que la adsorción depende del pH, del contenido de metales y del contenido de sólidos en suspensión en las agua

Activity-dependent switch of gabaergic inhibition into glutamatergic excitation in astrocyte-neuron networks

Interneurons are critical for proper neural network function and can activate Ca2 signaling in astrocytes. However, the impact of the interneuron-astrocyte signaling into neuronal network operation remains unknown. Using the simplest hippocampal Astrocyte-Neuron network, i.e., GABAergic interneuron, pyramidal neuron, single CA3-CA1 glutamatergic synapse, and astrocytes, we found that interneuron-astrocyte signaling dynamically affected excitatory neurotransmission in an activity- and time-dependent manner, and determined the sign (inhibition vs potentiation) of the GABA-mediated effects. While synaptic inhibition was mediated by GABAA receptors, potentiation involved astrocyte GABAB receptors, astrocytic glutamate release, and presynaptic metabotropic glutamate receptors. Using conditional astrocyte-specific GABAB receptor (Gabbr1) knockout mice, we confirmed the glial source of the interneuron-induced potentiation, and demonstrated the involvement of astrocytes in hippocampal theta and gamma oscillations in vivo. Therefore, astrocytes decode interneuron activity and transform inhibitory into excitatory signals, contributing to the emergence of novel network properties resulting from the interneuron-astrocyte interplay.Peer Reviewe