Tag Archives: Cellular intelligence

Cellular intelligence, epigenetics, internal memory, learning, Synaptic Plasticity , , , , , ,

Epigenetics and memory

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Epigenetic modification is a powerful mechanism for the induction, the expression and persistence of long-term memory.

For long-term memory, we need to consider diverse cellular processes. These occur in neurons from different brain regions (in particular hippocampus, cortex, amygdala) during memory consolidation and recall. For instance, long-term changes in kinase expression in the proteome, changes in receptor subunit composition and localization at synaptic/dendritic membranes, epigenetic modifications of chromatin such as DNA methylation and histone methylation in the nucleus, and the posttranslational modifications of histones, including phosphorylation and acetylation, all these play a role. Histone acetylation is of particular interest because a number of known medications exist, which function as histone deacetylase inhibitors (HDACs), i.e. have a potential to increase DNA transcription and memory (more on this in a later post).

Epigenetic changes are important because they define the internal conditions for plasticity for the individual neuron. They underlie for instance, kinase or phosphatase-mediated (de)activations of enzymatic proteins and therefore influence the probability of membrane proteins to become altered by synaptic activation.

Among epigenetic changes, DNA methylation typically acts to alter, often to repress, DNA transcription at cytosine, or CpG islands in vertebrates. DNA methylation is mediated by enzymes such as Tet3, which catalyses an important step in the demethylation of DNA. In dentate gyrus of live rats, it was shown that the expression of Tet3 is greatly increased by LTP – synaptically induced memorization – , suggesting that certain DNA stretches were demethylated [5], and presumably activated. During induction of LTP by high frequency electrical stimulation, DNA methylation is changed specifically for certain genes known for their role in neural plasticity [1]. The expression of neural plasticity genes is widely correlated with the methylation status of the corresponding DNA .

So there is interesting evidence for filtering the induction of plasticity via the epigenetic landscape and modifiers of gene expression, such as HDACs. Substances which act as histone deacetylase inhibitors (HDACs) increase histone acetylation. An interesting result from research on fear suggests that HDACs increase some DNA transcription, and enhance specifically fear extinction memories [2], [3],[4]. 

Cellular intelligence, General, Signal Transduction, Systems Biology , , , ,

Antagonistic regulation for cellular intelligence

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Cellular intelligence refers to information processing in single cells, i.e. genetic regulation, protein signaling and metabolic processing, all tightly integrated with each other. The goal is to uncover general ‘rules of life’ wrt e.g. the transmission of information, homeostatic and multistable regulation, learning and memory (habituation, sensitization etc.). These principles extend from unicellular organisms like bacteria to specialized cells, which are parts of a multicellular organism.

A prominent example is the ubiquitous role of feedback cycles in cellular information processing. These are often nested, or connected to a central hub, as a set of negative feedback cycles, sometimes interspersed with positive feedback cycles as well. Starting from Norbert Wiener’s work on cybernetics, we have gained a deeper understanding of this regulatory motif, and the complex modules that can be built from a multitude of these cycles by modeling as well as mathematical analysis.

Another motif that is similar in significance and ubiquity is antagonistic interaction. A prototypical antagonistic interaction consists of a signal, two pathways, one negative, one positive, and a target. The signal connects to the target by both pathways. No further parts are required.

On the face of it, this interaction seems redundant. When you connect a signal to a target by a positive and a negative connection, the amount of change is a sum of both connections, and for this, one connection should be sufficient. But this motif is actually very widespread and powerful, and there are two main aspects to this:

A. Gearshifting, scale-invariance or digitalization of input: for an input signal that can occur at different strengths, the antagonistic transmission allows to shift the signal to a lower level/gear with a limited bandwidth compared to the input range. This can also be described as scale-invariance or standardization of the input, or in the extreme case, digitalization of an analog input signal.

B. Fast onset-slow offset response curves: in this case the double transmission lines are used with a time delay. The positive interaction is fast, the negative interaction is slow. Therefore there is a fast peak response with a slower relaxation time– useful in many biological contexts, where fast reaction times are crucial.

Negative feedback cycles which can achieve similar effects by acting on the signal itself: the positive signal is counteracted by a negative input which reduces the input signal. The result is again a fast peak response followed by a downregulation to an equilibrium value. The advantage for antagonistic interactions is that the original signal is left intact, which is useful. because the same signal may act on other targets unchanged. In a feedback cycle the signal itself is consumed by the feedback interaction. The characteristic shape of the signal, fast peak response with a slower downregulation, may therefore arise from different structures.

The type of modules that can be built from both antagonistic interactions and feedback have not been explored systematically. However, one example is morphogenetic patterning, often referred to as ‘Turing patterns’, which relies on a positive feedback cycle by an activator, plus antagonistic interactions (activator/inhibitor) with a time delay for the inhibitor.

 turing_pattern