Couple of days ago I’ve come across a recent paper in Nature with quite an eyebrow-raising title “A trans-synaptic nanocolumn aligns neurotransmitter release to receptors“. The title made me think as if the authors have observed hitherto unknown structures in the synaptic cleft. That would be quite a sensation! But then this sentence comes in the abstract:
These presynaptic RIM nanoclusters closely align with concentrated postsynaptic receptors and scaffolding proteins4, 5, 6, suggesting the existence of a trans-synaptic molecular ‘nanocolumn’.
Now it looked like they propose some kind of neuroscience equivalent of dark matter. You know, something that nobody knows what it is, but that certainly must be there, otherwise there’s no explanation to what we see. Continue reading “Skepticism about synaptic nanocolumns”
Epigenetics is an exciting but a weird area. It’s well recognized that messing with chromatin and chemical modifications of nucleic acids has profound consequences at the cellular and organism levels. But for me the mechanistic rationale for targeting epigenome pharmacologically was always somewhere close to throwing a monkey wrench into the clockworks and watching what will happen. It seems (not surprisingly) that in fact the effects are more predictable. Continue reading “Epigenetic ant reprogramming”
When during my undergraduate years I learned that lithium carbonate treats depression and bipolar disorder, my first thought was “there’s something bizarre here”.
The most well-known observational studies suggested that even low levels of Li+ ions in drinking water reduce suicide incidence. However, there’s a lot of critics of these studies pointing out trivial ‘correlation = causation’ fallacy and poor study design for drawing serious conclusions.
New study demonstrates the effect of Li+ in induced stem cells. Well, the actual goal for the paper was to establish a relevant cellular model for bipolar disorder (BD). For that authors took fibroblasts from two sets of patients, Li-responsive (LR) and Li-non-responsive (LN) ones, as well as healthy controls. They differentiated the fibroblasts into dentate gyrus (DG) hyppocampal neurons and studied possible genetic sources of BD. The biggest change was detected in mitochondrial genes expression, which correlated with observed hyperactivity of BD iNeurons.
A real gem is the clinical relevance experiment. Authors tested the effect of LiCl on LR- and LN-derived BD iNeurons. As it turned out, Li+ indeed worked only in cells from LR patients but not in LN group. The effect was confirmed by electrophysiology and Ca2+ imaging. Further look into genetics showed change in expression of 560 genes in LR iNeurons, compared to 40 in LN. Of those 560, 84 were rescued BD genes, including those regulating mitochondria transport, protein kinase A (PKA)/protein kinase C (PKC) signaling and action potential.
Hopefully, further studies of the newly established iPSC model will provide new insights into genetics of BD and contribute to the development of more effective drugs. And these are badly needed, taking into account severe side effects of chronic lithium treatment. For sure, more rigorous genotyping of patients is needed but at least the model already substantially narrowed down the candidate genes.
It is useful sometimes to raise your head from the ground and to have a look on the opposite site of a scientific field. Conceptually, most of the research in general is done via two approaches: top-down and bottom-up. In memory research, while some scientist are trying to identify the right receptor or gene and manipulate it with molecular preciseness (bottom-up), the others put electrodes into different brain areas and fire the entire groups of neurons (top-down).
Naturally, both approaches have their pros and cons. The greatest question in going bottom-up is “will the mechanism work on the next level of complexity?” When you go from the top, however, you will always be left with a question “How in the world did it work?”
A recent overview in Nature prompted me to look at the websites of groups doing that kind of research. There’s certainly lots of mathematical modeling and pattern recognition involved, which can lead to quite remarkable results in reverse-engeneering of neural circuitry. At the same time, reading the publication titles left me with a perception of how little we know even about such seemingly trivial circuits as CA1-CA3 in the hippocampus, which is known from 60-es or 70-es to be crucial for the memory formation. This kind of argument poses a big question mark behind the Human Brain Project. Will the neuron-by-neuron reverse-engineering of the brain help us with understanding its function? Probably not, unless someone digs from the opposite side.