Predicting cellular adaptation proteins dependent on eIF2α regulation under stress conditions: Physiological and...

Understanding the intricate mechanisms governing gene expression regulation is crucial for deciphering neuronal responses to cellular stress at both the physiological (i.e., synaptogenesis) and pathophysiological (i.e., neurodegenerative diseases) levels. These rapid adaptive changes depend on the translation of specific proteins with specialized 5' untranslated regions (5'UTRs), triggered by the phosphorylation of eukaryotic initiation factor 2 alpha (eIF2α), while normal cellular translation remains largely inhibited. This study aims to provide a useful tool to identify mRNAs susceptible to regulation by p-eIF2α. We compiled a database of 5'UTRs using Ensembl canonical transcripts from the GRCh38.p14 genome build. Ensembl IDs were used to extract coding sequences and cDNA via the REST API, and 5'UTR regions were identified. We applied translation efficiency-based filters to existing databases of p-eIF2α-dependent translation to obtain reliable training and testing datasets. A multiple logistic regression (MLR) model-using 5'UTR length, GC content, upstream open reading frames (uORFs), and the features of Atf4 as a reference-predicted scores for p-eIF2α-driven translation. Gene Ontology (GO) enrichment analysis identified significant biological processes, molecular functions, and cellular components involved. An interactome analysis using STRING-db highlighted pathways related to synaptoplasticity (physiological stress) and Alzheimer's disease (pathophysiological stress). In vitro luciferase assays validated SLC30A4 as a novel p-eIF2α-regulated transcript, uncovering the role of eIF2α regulation in zinc homeostasis and neurodegeneration. These findings underscore the importance of translational control mechanisms in memory formation and disease pathogenesis, contributing to the identification of potential therapeutic targets to mitigate pathological outcomes.