Major splice variants and multiple polyadenylation site utilization in mRNAs encoding human translation initiation factors eIF4E1 and eIF4E3 regulate the translational regulators?

Integrative identification of hub genes in development of atrial fibrillation related stroke

BACKGROUND

As the most common arrhythmia, atrial fibrillation (AF) is associated with a significantly increased risk of stroke, which causes high disability and mortality. To date, the underlying mechanism of stroke occurring after AF remains unclear. Herein, we studied hub genes and regulatory pathways involved in AF and secondary stroke and aimed to reveal biomarkers and therapeutic targets of AF-related stroke.

METHODS

The GSE79768 and GSE58294 datasets were used to analyze AF- and stroke-related differentially expressed genes (DEGs) to obtain a DEG1 dataset. Weighted correlation network analysis (WGCNA) was used to identify modules associated with AF-related stroke in GSE66724 (DEG2). DEG1 and DEG2 were merged, and hub genes were identified based on protein-protein interaction networks. Gene Ontology terms were used to analyze the enriched pathways. The GSE129409 and GSE70887 were applied to construct a circRNA-miRNA-mRNA network in AF-related stroke. Hub genes were verified in patients using quantitative real-time polymerase chain reaction (qRT-PCR).

RESULTS

We identified 3,132 DEGs in blood samples and 253 DEGs in left atrial specimens. Co-expressed hub genes of EIF4E3, ZNF595, ZNF700, MATR3, ACKR4, ANXA3, SEPSECS-AS1, and RNF166 were significantly associated with AF-related stroke. The hsa_circ_0018657/hsa-miR-198/EIF4E3 pathway was explored as the regulating axis in AF-related stroke. The qRT-PCR results were consistent with the bioinformatic analysis.

CONCLUSIONS

Hub genes EIF4E3, ZNF595, ZNF700, MATR3, ACKR4, ANXA3, SEPSECS-AS1, and RNF166 have potential as novel biomarkers and therapeutic targets in AF-related stroke. The hsa_circ_0018657/hsa-miR-198/EIF4E3 axis could play an important role regulating the development of AF-related stroke.

eIF4E3 forms an active eIF4F complex during stresses (eIF4FS) targeting mTOR and re-programs the translatome

The eIF4E are a family of initiation factors that bind the mRNA 5′ cap, regulating the proteome and the cellular phenotype. eIF4E1 mediates global translation and its activity is controlled via the PI3K/AKT/mTOR pathway. mTOR down-regulation results in eIF4E1 sequestration into an inactive complex with the 4E binding proteins (4EBPs). The second member, eIF4E2, regulates the translatome during hypoxia. However, the exact function of the third member, eIF4E3, has remained elusive. We have dissected its function using a range of techniques. Starting from the observation that it does not interact with 4EBP1, we demonstrate that eIF4E3 recruitment into an eIF4F complex occurs when Torin1 inhibits the mTOR pathway. Ribo-seq studies demonstrate that this complex (eIF4F^S) is translationally active during stress and that it selects specific mRNA populations based on 5′ TL (UTR) length. The interactome reveals that it associates with cellular proteins beyond the cognate initiation factors, suggesting that it may have ‘moon-lighting’ functions. Finally, we provide evidence that cellular metabolism is altered in an eIF4E3 KO background but only upon Torin1 treatment. We propose that eIF4E3 acts as a second branch of the integrated stress response, re-programming the translatome to promote ‘stress resistance’ and adaptation.

Multifaceted control of mRNA translation machinery in cancer

The mRNA translation machinery is tightly regulated through several, at times overlapping, mechanisms that modulate its efficiency and accuracy. Due to their fast rate of growth and metabolism, cancer cells require an excessive amount of mRNA translation and protein synthesis. However, unfavorable conditions, such as hypoxia, amino acid starvation, and oxidative stress, which are abundant in cancer, as well as many anti-cancer treatments inhibit mRNA translation. Cancer cells adapt to the various internal and environmental stresses by employing specialised transcript-specific translation to survive and gain a proliferative advantage. We will highlight the major signaling pathways and mechanisms of translation that regulate the global or mRNA-specific translation in response to the intra- or extra-cellular signals and stresses that are key components in the process of tumourigenesis.

Poly(A)-DG: A deep-learning-based domain generalization method to identify cross-species Poly(A) signal without prior knowledge from target species

In eukaryotes, polyadenylation (poly(A)) is an essential process during mRNA maturation. Identifying the cis-determinants of poly(A) signal (PAS) on the DNA sequence is the key to understand the mechanism of translation regulation and mRNA metabolism. Although machine learning methods were widely used in computationally identifying PAS, the need for tremendous amounts of annotation data hinder applications of existing methods in species without experimental data on PAS. Therefore, cross-species PAS identification, which enables the possibility to predict PAS from untrained species, naturally becomes a promising direction. In our works, we propose a novel deep learning method named Poly(A)-DG for cross-species PAS identification. Poly(A)-DG consists of a Convolution Neural Network-Multilayer Perceptron (CNN-MLP) network and a domain generalization technique. It learns PAS patterns from the training species and identifies PAS in target species without re-training. To test our method, we use four species and build cross-species training sets with two of them and evaluate the performance of the remaining ones. Moreover, we test our method against insufficient data and imbalanced data issues and demonstrate that Poly(A)-DG not only outperforms state-of-the-art methods but also maintains relatively high accuracy when it comes to a smaller or imbalanced training set.

Signal Transduction in Ribosome Biogenesis: A Recipe to Avoid Disaster

Energetically speaking, ribosome biogenesis is by far the most costly process of the cell and, therefore, must be highly regulated in order to avoid unnecessary energy expenditure. Not only must ribosomal RNA (rRNA) synthesis, ribosomal protein (RP) transcription, translation, and nuclear import, as well as ribosome assembly, be tightly controlled, these events must be coordinated with other cellular events, such as cell division and differentiation. In addition, ribosome biogenesis must respond rapidly to environmental cues mediated by internal and cell surface receptors, or stress (oxidative stress, DNA damage, amino acid depletion, etc.). This review examines some of the well-studied pathways known to control ribosome biogenesis (PI3K-AKT-mTOR, RB-p53, MYC) and how they may interact with some of the less well studied pathways (eIF2α kinase and RNA editing/splicing) in higher eukaryotes to regulate ribosome biogenesis, assembly, and protein translation in a dynamic manner.