Blue Brain Seminar - Variability and co-variations in ion channel expression and in electrophysiological properties in neurons
Event details
| Date | 22.07.2021 |
| Hour | 15:00 |
| Speaker | Jean-Marc Goaillard |
| Category | Conferences - Seminars |
Virtual Event
The next seminar in the series in Neural Computation, will be on ‘Variability and co-variations in ion channel expression and in electrophysiological properties in neurons’. The seminar will be given by Jean-Marc Goaillard, Inserm CRCN, Group Leader
‘Systems Approaches to Neuronal Excitability’ group, Institut de Neurosciences de la Timone, Marseille, France.
Abstract
About Jean-Marc Goaillard
“After a PhD thesis where I used patch-clamp combined with cAMP imaging to investigate the modulation of ion channels by second messengers, I moved to the stomatogastric nervous system to try and decipher the mechanisms underlying the robustness of neural networks. During this post-doctoral work, we showed that neurons of the same type can generate virtually identical waveforms of activity while simultaneously displaying a high degree of variability in expression for the ion channels underlying this activity pattern. We also demonstrated that ion channel expression levels are not only variable but also co-vary, such that specific modules of co-expression characterize each neuronal type (Schulz et al., Nat. Neurosci. 2006; PNAS, 2007; Goaillard et al., Nat. Neurosci. 2009). I then started my lab in Marseille, transposing these questions into the more complex mammalian nervous system. Specifically, we started investigating how midbrain dopaminergic neurons generate their typical "pacemaking" pattern of activity, and how the variations in this pattern relate to variations in the expression levels or biophysical properties of ion channels (Amendola et al., J. Neurosci. 2012; Dufour et al., eLife 2014; Tapia et al., Sci. Rep. 2018; Moubarak et al., J. Neurosci. 2019). In particular, we developed a multi-disciplinary line of work involving patch-clamp recordings, computational modeling, single-neuron transcriptomics and advanced multivariate analyses, based on the belief that neuronal activity can only be understood if precise biophysical mechanisms are combined with -omics and database approaches to hopefully achieve a systems-level understanding of this fundametal process.”
Find out more - https://www.unis-neuro.com/26-membre-goaillard-jean-marc.html
The next seminar in the series in Neural Computation, will be on ‘Variability and co-variations in ion channel expression and in electrophysiological properties in neurons’. The seminar will be given by Jean-Marc Goaillard, Inserm CRCN, Group Leader
‘Systems Approaches to Neuronal Excitability’ group, Institut de Neurosciences de la Timone, Marseille, France.
Abstract
In spite of the considerable biophysical knowledge available about ion channel types and properties, we still have a poor understanding of how a specific neuronal type invariably achieves its characteristic electrical phenotype and maintains it in spite of all the insults the neuron faces during its long lifespan.
This lack of understanding seems to be essentially due to the fact that i) any neuronal type relies on a large number of different ion channel subtypes to generate its characteristic electrical phenotype, ii) the respective expression levels of these ion channels are critical in defining their impact, and iii), the functional impact of these ion channels is also influenced by the morphology of the neuron.
Over the past six years, we have tried to develop systems-level approaches to understand how midbrain dopaminergic neurons invariably generate a stable electrical phenotype when recorded in vitro (pacemaking activity, broad action potential, etc...). In particular, we used a combination of single-neuron transcriptomics, electrophysiological recordings, and advanced multivariate mathematical analysis to try to understand how quantitative changes in ion channel expression levels may explain variations in the electrical phenotype (or stability thereof).
As described in other systems, we found that ion channel expression levels are highly variable from neuron to neuron, even in this well-identified neuronal population. We also found that electrophysiological properties displayed significant variations from neuron to neuron. More interestingly, we found that both ion channel expression levels and specific electrophysiological properties co-varied, highlighting the presence of invariant high-dimensional relationships. We believe that these co-variations play an essential role in achieving a given electrophysiological phenotype and maintaining it over time in the face of perturbations.
This lack of understanding seems to be essentially due to the fact that i) any neuronal type relies on a large number of different ion channel subtypes to generate its characteristic electrical phenotype, ii) the respective expression levels of these ion channels are critical in defining their impact, and iii), the functional impact of these ion channels is also influenced by the morphology of the neuron.
Over the past six years, we have tried to develop systems-level approaches to understand how midbrain dopaminergic neurons invariably generate a stable electrical phenotype when recorded in vitro (pacemaking activity, broad action potential, etc...). In particular, we used a combination of single-neuron transcriptomics, electrophysiological recordings, and advanced multivariate mathematical analysis to try to understand how quantitative changes in ion channel expression levels may explain variations in the electrical phenotype (or stability thereof).
As described in other systems, we found that ion channel expression levels are highly variable from neuron to neuron, even in this well-identified neuronal population. We also found that electrophysiological properties displayed significant variations from neuron to neuron. More interestingly, we found that both ion channel expression levels and specific electrophysiological properties co-varied, highlighting the presence of invariant high-dimensional relationships. We believe that these co-variations play an essential role in achieving a given electrophysiological phenotype and maintaining it over time in the face of perturbations.
About Jean-Marc Goaillard
“After a PhD thesis where I used patch-clamp combined with cAMP imaging to investigate the modulation of ion channels by second messengers, I moved to the stomatogastric nervous system to try and decipher the mechanisms underlying the robustness of neural networks. During this post-doctoral work, we showed that neurons of the same type can generate virtually identical waveforms of activity while simultaneously displaying a high degree of variability in expression for the ion channels underlying this activity pattern. We also demonstrated that ion channel expression levels are not only variable but also co-vary, such that specific modules of co-expression characterize each neuronal type (Schulz et al., Nat. Neurosci. 2006; PNAS, 2007; Goaillard et al., Nat. Neurosci. 2009). I then started my lab in Marseille, transposing these questions into the more complex mammalian nervous system. Specifically, we started investigating how midbrain dopaminergic neurons generate their typical "pacemaking" pattern of activity, and how the variations in this pattern relate to variations in the expression levels or biophysical properties of ion channels (Amendola et al., J. Neurosci. 2012; Dufour et al., eLife 2014; Tapia et al., Sci. Rep. 2018; Moubarak et al., J. Neurosci. 2019). In particular, we developed a multi-disciplinary line of work involving patch-clamp recordings, computational modeling, single-neuron transcriptomics and advanced multivariate analyses, based on the belief that neuronal activity can only be understood if precise biophysical mechanisms are combined with -omics and database approaches to hopefully achieve a systems-level understanding of this fundametal process.”
Find out more - https://www.unis-neuro.com/26-membre-goaillard-jean-marc.html
Links
Practical information
- General public
- Registration required