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Altered eIF4A1 activity promotes translation of highly structured, eIF4A1-dependent oncogene mRNAs at root of oncogenic translational programmes. It remains unclear how these mRNAs recruit and activate eIF4A1 unwinding specifically to facilitate their preferential translation. Here, we show that single-stranded RNA sequence motifs specifically activate eIF4A1 unwinding allowing local RNA structural rearrangement and translation of eIF4A1-dependent mRNAs in cells. Our data demonstrate that eIF4A1-dependent mRNAs contain AG-rich motifs within their 5'UTR which specifically activate eIF4A1 unwinding of local RNA structure to facilitate translation. This mode of eIF4A1 regulation is used by mRNAs encoding components of mTORC-signalling and cell cycle progression, and renders these mRNAs particularly sensitive to eIF4A1-inhibition. Mechanistically, we show that binding of eIF4A1 to AG-rich sequences leads to multimerization of eIF4A1 with eIF4A1 subunits performing distinct enzymatic activities. Our structural data suggest that RNA-binding of multimeric eIF4A1 induces conformational changes in the RNA resulting in an optimal positioning of eIF4A1 proximal to the RNA duplex enabling efficient unwinding. Our data proposes a model in which AG-motifs in the 5'UTR of eIF4A1-dependent mRNAs specifically activate eIF4A1, enabling assembly of the helicase-competent multimeric eIF4A1 complex, and positioning these complexes proximal to stable localised RNA structure allowing ribosomal subunit scanning., (© The Author(s) 2023. Published by Oxford University Press on behalf of Nucleic Acids Research.)

Minimal absent words (MAWs) are minimal-length oligomers absent from a genome or proteome. Although some artificially synthesized MAWs have deleterious effects, there is still a lack of a strategy for the classification of non-occurring sequences as potentially malicious or benign. In this work, by using Markovian models with multiple-testing correction, we reveal significant absent oligomers, which are statistically expected to exist. This suggests that their absence is due to negative selection. We survey genomes and proteomes covering the diversity of life and find thousands of significant absent sequences. Common significant MAWs are often mono- or dinucleotide tracts, or palindromic. Significant viral MAWs are often restriction sites and may indicate unknown restriction motifs. Surprisingly, significant mammal genome MAWs are often present, but rare, in other mammals, suggesting that they are suppressed but not completely forbidden. Significant human MAWs are frequently present in prokaryotes, suggesting immune function, but rarely present in human viruses, indicating viral mimicry of the host. More than one-fourth of human proteins are one substitution away from containing a significant MAW, with the majority of replacements being predicted harmful. We provide a web-based, interactive database of significant MAWs across genomes and proteomes., (© The Author(s) 2021. Published by Oxford University Press on behalf of Nucleic Acids Research.)

Understanding protein dynamics is crucial in order to elucidate protein function and interactions. Advances in modern microscopy facilitate the exploration of the mobility of fluorescently tagged proteins within living cells. Fluorescence recovery after photobleaching (FRAP) is an increasingly popular functional live-cell imaging technique which enables the study of the dynamic properties of proteins at a single-cell level. As an increasing number of labs generate FRAP datasets, there is a need for fast, interactive and user-friendly applications that analyze the resulting data. Here we present easyFRAP-web, a web application that simplifies the qualitative and quantitative analysis of FRAP datasets. EasyFRAP-web permits quick analysis of FRAP datasets through an intuitive web interface with interconnected analysis steps (experimental data assessment, different types of normalization and estimation of curve-derived quantitative parameters). In addition, easyFRAP-web provides dynamic and interactive data visualization and data and figure export for further analysis after every step. We test easyFRAP-web by analyzing FRAP datasets capturing the mobility of the cell cycle regulator Cdt2 in the presence and absence of DNA damage in cultured cells. We show that easyFRAP-web yields results consistent with previous studies and highlights cell-to-cell heterogeneity in the estimated kinetic parameters. EasyFRAP-web is platform-independent and is freely accessible at: https://easyfrap.vmnet.upatras.gr/.