Author response: Native KCC2 interactome reveals PACSIN1 as a critical regulator of synaptic inhibition
Bibliographic record
Abstract
Neurons in the brain talk to each other by releasing chemicals called neurotransmitters. These neurotransmitters can either increase ('excite') or decrease ('inhibit') the activity of other neurons. Inhibitory neurotransmission uses the chemical GABA as a neurotransmitter. When a neuron releases GABA it is like applying the brake in your car – you can slow down subtly to stay under the speed limit, or stomp on it to avoid an accident. The brain needs to carefully control the amount of inhibition so that the animal can learn and produce complex behaviours. For GABA to inhibit the activity of a neuron, the neuron must maintain a low amount of chloride ions inside. A transporter protein called KCC2 shuttles chloride out of cells; if this transporter fails to work, chloride builds up in the neuron and prevents inhibition so that GABA neurotransmission switches from inhibitory to excitatory. This breakdown of GABA inhibition is a hallmark of abnormal brain activity during conditions such as epilepsy, pain and some forms of autism. Despite the fact that neurons need KCC2 for inhibition in the brain, we do not know much about how this transporter works. Since the activity of a protein is determined in part by the other proteins it interacts with, it is therefore important to identify all the proteins that interact with KCC2 – termed the KCC2 interactome. To discover these protein interactions, Mahadevan et al. performed a technique called liquid chromatography-mass spectrometry on KCC2 protein isolated from mouse brains. This revealed that there are 181 proteins in the KCC2 interactome. Of these proteins, the most abundant was a protein called PACSIN1, which helps to pull proteins out of the membrane that surrounds each neuron. To investigate how the interaction between PACSIN1 and KCC2 regulates the activity of this transporter, Mahadevan et al. performed fluorescence imaging of neurons and recorded their electrical activity. This revealed that PACSIN1 restricts the expression of KCC2, meaning that the more PACSIN there is in the neuron, the less KCC2 will be present. The KCC2 interactome provides a database of proteins that can be targeted to increase the activity of KCC2. This could allow new treatments to be developed for brain disorders in which the inhibition of neurons is reduced.
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How this classification was reachedexpand
Full frame machine prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. The Gemma side is a direct model label for every work in the frame, read from the title-only record. The Codex side is a classifier learned from the 10,348 direct Codex labels and calibrated to design-weighted sample rates; fields without enough sample support carry no Codex call. Candidate is the union of the two sides; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels.
Distilled classifier scores by category (both heads)
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.001 | 0.002 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.002 | 0.001 |
| Scholarly communication | 0.002 | 0.002 |
| Open science | 0.001 | 0.002 |
| Research integrity | 0.003 | 0.003 |
| Insufficient payload (model declined to judge) | 0.244 | 0.105 |
Machine scores (provisional)
The two teacher heads of the student model, read on this work. A score orders the frame for review; it never asserts a category, and the validation status ships verbatim with every row.
Baseline scores from an immature model (maturity gate not passed, 7 training rounds). Scores rank; they never assert a category.
score_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from itClassification
machine, unvalidatedMachine predicted; a candidate call from one source (direct Gemma or distilled Codex), not a consensus.
How this classification was reached, model by model and score by score, is at the end of the page under "How this classification was reached".