Search PubMed⌕ Search

PubMed · 10509708

A biochemical blueprint for long-term memory.

Abstract

The greatest barrier to the long-term storage of information in a biological system is the inevitability of molecular turnover. In this review, we discuss the features required of any chemical mechanism capable of overcoming this obstacle, positing that a specific type of "mnemogenic", or memory-forming, chemical reaction is the basis of the engram. We describe how molecules as diverse as protein kinases, prions, and transcription factors can participate in mnemogenic reactions, and outline a blueprint for memory that postulates mnemogenic reactions at the synapse and in the nucleus and considers the constraints imposed by requirements for high fidelity and the ability to forget. This sort of a priori analysis may facilitate directed experimental approaches to understanding the mechanisms of lifelong memory.

Explore related subjects

Keep this discovery

Explore connections, maps & timelines

BibTeXRIS

E D Roberson, J D Sweatt. A biochemical blueprint for long-term memory.. https://pubmed.ncbi.nlm.nih.gov/10509708/

Cite the original work for its findings. Save a collection to share your selection of sources.

KEEP EXPLORING

Related citations

Molecular differences between young and mature stria vascularis from organotypic explants and transcriptomics.

The stria vascularis (SV) is an essential component of the inner ear that regulates the ionic environment required for hearing. SV degeneration disrupts cochlear homeostasis, leading to irreversible hearing loss, yet a comprehensive understanding of the SV, and consequently therapeutic availability for SV degeneration, is lacking. We developed a whole-tissue explant model from neonatal and mature mice to create a platform for advancing SV research. We validated our model by demonstrating that the proliferative behavior of the SV in vitro mimics SV in vivo. We also provided evidence for pharmacological experimentation by investigating the role of Wnt/β-catenin signaling in SV proliferation. Finally, we performed single-cell RNA sequencing from in vivo neonatal and mature mouse SV and surrounding tissue and revealed key genes and pathways that may play a role in SV proliferation and maintenance. Together, our results contribute new insights into investigating biological solutions for SV-associated hearing loss.

Biochemistry↗

Manipulation of cell-sized phospholipid-coated microdroplets and their use as biochemical microreactors.

Cell-sized water droplets coated by a phospholipid layer mimicking the inner surface of living cells were manipulated by laser tweezers and used as biochemical microreactors. The cell-sized phospholipid-coated microdroplets (CPMDs) consisted of a water droplet in mineral oil with a diameter of 1-100 microm and coated by 1,2-dioleoyl-sn-glycero-3-phosphoethanolamine. We monitored the time development of biochemical reactions in a single CPMD obtained after the controlled fusion of two CPMDs containing a substrate and an enzyme, respectively. We present results on two enzymatic reactions: calcein production in the presence of esterase and green fluorescence protein expression.

Biochemistry↗

Classical versus stochastic kinetics modeling of biochemical reaction systems.

We study fundamental relationships between classical and stochastic chemical kinetics for general biochemical systems with elementary reactions. Analytical and numerical investigations show that intrinsic fluctuations may qualitatively and quantitatively affect both transient and stationary system behavior. Thus, we provide a theoretical understanding of the role that intrinsic fluctuations may play in inducing biochemical function. The mean concentration dynamics are governed by differential equations that are similar to the ones of classical chemical kinetics, expressed in terms of the stoichiometry matrix and time-dependent fluxes. However, each flux is decomposed into a macroscopic term, which accounts for the effect of mean reactant concentrations on the rate of product synthesis, and a mesoscopic term, which accounts for the effect of statistical correlations among interacting reactions. We demonstrate that the ability of a model to account for phenomena induced by intrinsic fluctuations may be seriously compromised if we do not include the mesoscopic fluxes. Unfortunately, computation of fluxes and mean concentration dynamics requires intensive Monte Carlo simulation. To circumvent the computational expense, we employ a moment closure scheme, which leads to differential equations that can be solved by standard numerical techniques to obtain more accurate approximations of fluxes and mean concentration dynamics than the ones obtained with the classical approach.

Biochemistry↗