The genetics of PKMζ and memory maintenance.

Sci Signal

Department of Pharmacology, University of California, Davis, Davis, CA 95615, USA.

Published: November 2017

Elucidating the molecular mechanisms that maintain long-term memory is a fundamental goal of neuroscience. Accumulating evidence suggests that persistent signaling by the atypical protein kinase C (PKC) isoform protein kinase Mζ (PKMζ) might maintain synaptic long-term potentiation (LTP) and long-term memory. However, the role of PKMζ has been challenged by genetic data from PKMζ-knockout mice showing intact LTP and long-term memory. Moreover, the PKMζ inhibitor peptide ζ inhibitory peptide (ZIP) reverses LTP and erases memory in both wild-type and knockout mice. Data from four papers using additional isoform-specific genetic approaches have helped to reconcile these conflicting findings. First, a PKMζ-antisense approach showed that LTP and long-term memory in PKMζ-knockout mice are mediated through a compensatory mechanism that depends on another ZIP-sensitive atypical isoform, PKCι/λ. Second, short hairpin RNAs decreasing the amounts of individual atypical isoforms without inducing compensation disrupted memory in different temporal phases. PKCι/λ knockdown disrupted short-term memory, whereas PKMζ knockdown specifically erased long-term memory. Third, conditional PKCι/λ knockout induced compensation by rapidly activating PKMζ to preserve short-term memory. Fourth, a dominant-negative approach in the model system revealed that multiple PKCs form PKMs to sustain different types of long-term synaptic facilitation, with atypical PKM maintaining synaptic plasticity similar to LTP. Thus, under physiological conditions, PKMζ is the principal PKC isoform that maintains LTP and long-term memory. PKCι/λ can compensate for PKMζ, and because other isoforms could also maintain synaptic facilitation, there may be a hierarchy of compensatory mechanisms maintaining memory if PKMζ malfunctions.

Download full-text PDF

Source
http://www.ncbi.nlm.nih.gov/pmc/articles/PMC6171341PMC
http://dx.doi.org/10.1126/scisignal.aao2327DOI Listing

Publication Analysis

Top Keywords

long-term memory
24
ltp long-term
16
memory
12
memory pkmζ
12
long-term
8
protein kinase
8
pkc isoform
8
pkmζ
8
maintain synaptic
8
pkmζ-knockout mice
8

Similar Publications

Robust mucosal SARS-CoV-2-specific T cells effectively combat COVID-19 and establish polyfunctional resident memory in patient lungs.

Nat Immunol

January 2025

State Key Laboratory of Respiratory Disease, National Clinical Research Centre for Respiratory Disease, Guangzhou Institute of Respiratory Health, The First Affiliated Hospital of Guangzhou Medical University, Guangzhou, China.

Mucosal antigen-specific T cells are pivotal for pathogen clearance and immune modulation in respiratory infections. Dysregulated T cell responses exacerbate coronavirus disease 2019 severity, marked by cytokine storms and respiratory failure. Despite extensive description in peripheral blood, the characteristics of severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2)-specific T cells in the lungs remain elusive.

View Article and Find Full Text PDF

Olfactory testing in infants with perinatal asphyxia: enhancing encephalopathy risk stratification for future health outcomes.

Neurosci Biobehav Rev

January 2025

Department of Chemistry, Life Sciences and Environmental Sustainability, University of Parma, Viale delle Scienze 11, 43125 Parma, Italy.

Perinatal asphyxia (PA) is a leading cause of neonatal morbidity and mortality, often resulting in long-term neurodevelopmental challenges. Despite advancements in perinatal care, predicting long-term outcomes remains difficult. Early diagnosis is essential for timely interventions to reduce brain injury, with tools such as Magnetic Resonance Imaging, brain ultrasound, and emerging biomarkers playing a possible key role.

View Article and Find Full Text PDF

Re-locative guided search optimized self-sparse attention enabled deep learning decoder for quantum error correction.

Sci Rep

January 2025

Department of Mathematics, School of Advanced Sciences, VIT-AP University, Besides AP Secretariate, Amaravati, Andhra Pradesh, 522237, India.

Heavy hexagonal coding is a type of quantum error-correcting coding in which the edges and vertices of a low-degree graph are assigned auxiliary and physical qubits. While many topological code decoders have been presented, it is still difficult to construct the optimal decoder due to leakage errors and qubit collision. Therefore, this research proposes a Re-locative Guided Search optimized self-sparse attention-enabled convolutional Neural Network with Long Short-Term Memory (RlGS2-DCNTM) for performing effective error correction in quantum codes.

View Article and Find Full Text PDF

In this paper, the usage of a predictive surrogate model for the estimate of flow variables in the transient phase of coolant injection from the nose cone by combining the Long Short-Term Memory (LSTM) and Proper Orthogonal Decomposition (POD) technique. The velocity, pressure, and mass fraction of the counterflow jet is evaluated via this hybrid technique and the source of discrepancy of a predictive surrogate model with Full order model is explained in this study. The POD modes for the efficient prediction of the different flow variables are defined.

View Article and Find Full Text PDF

Importance: Cannabis use has increased globally, but its effects on brain function are not fully known, highlighting the need to better determine recent and long-term brain activation outcomes of cannabis use.

Objective: To examine the association of lifetime history of heavy cannabis use and recent cannabis use with brain activation across a range of brain functions in a large sample of young adults in the US.

Design, Setting, And Participants: This cross-sectional study used data (2017 release) from the Human Connectome Project (collected between August 2012 and 2015).

View Article and Find Full Text PDF

Want AI Summaries of new PubMed Abstracts delivered to your In-box?

Enter search terms and have AI summaries delivered each week - change queries or unsubscribe any time!