mRNA- and factor-driven dynamic variability controls eIF4F-cap recognition for translation initiation.

mRNA 5' cap recognition by eIF4F is a key element of eukaryotic translational control. Kinetic differences in eIF4F-mRNA interactions have long been proposed to mediate translation-efficiency differences between mRNAs, and recent transcriptome-wide studies have revealed significant heterogeneity in eIF4F engagement with differentially-translated mRNAs. However, detailed kinetic information exists only for eIF4F interactions with short model RNAs. We developed and applied single-molecule fluorescence approaches to directly observe real-time Saccharomyces cerevisiae eIF4F subunit interactions with full-length polyadenylated mRNAs. We found that eIF4E-mRNA association rates linearly anticorrelate with mRNA length. eIF4G-mRNA interaction accelerates eIF4E-mRNA association in proportion to mRNA length, as does an eIF4F-independent activity of eIF4A, though cap-proximal secondary structure still plays an important role in defining the final association rates. eIF4F-mRNA interactions remained dominated by effects of eIF4G, but were modulated to different extents for different mRNAs by the presence of eIF4A and ATP. We also found that eIF4A-catalyzed ATP hydrolysis ejects eIF4E, and likely eIF4E•eIF4G from the mRNA after initial eIF4F•mRNA complex formation, suggesting a mechanism to prepare the mRNA 5' end for ribosome recruitment. Our results support a role for mRNA-specific, factor-driven eIF4F association rates in kinetically controlling translation.

DNMT1 reads heterochromatic H4K20me3 to reinforce LINE-1 DNA methylation.

DNA methylation and trimethylated histone H4 Lysine 20 (H4K20me3) constitute two important heterochromatin-enriched marks that frequently cooperate in silencing repetitive elements of the mammalian genome. However, it remains elusive how these two chromatin modifications crosstalk. Here, we report that DNA methyltransferase 1 (DNMT1) specifically 'recognizes' H4K20me3 via its first bromo-adjacent-homology domain (DNMT1BAH1). Engagement of DNMT1BAH1-H4K20me3 ensures heterochromatin targeting of DNMT1 and DNA methylation at LINE-1 retrotransposons, and cooperates with the previously reported readout of histone H3 tail modifications (i.e., H3K9me3 and H3 ubiquitylation) by the RFTS domain to allosterically regulate DNMT1's activity. Interplay between RFTS and BAH1 domains of DNMT1 profoundly impacts DNA methylation at both global and focal levels and genomic resistance to radiation-induced damage. Together, our study establishes a direct link between H4K20me3 and DNA methylation, providing a mechanism in which multivalent recognition of repressive histone modifications by DNMT1 ensures appropriate DNA methylation patterning and genomic stability.

Heterogeneous Dynamics of Protein-RNA Interactions across Transcriptome-Derived Messenger RNA Populations.

Dynamic RNA-protein interactions underpin numerous molecular control mechanisms in biology. However, relatively little is known about the kinetic landscape of protein interactions with full-length RNAs. The extent to which interaction kinetics vary for the same RNA element across the transcriptome and the molecular determinants of variability therefore remain poorly defined. Moreover, it is unclear how one protein-RNA interaction might be transduced by RNA to kinetically impact a second. We report a parallelized, real-time single-molecule fluorescence assay for protein interaction kinetics on eukaryotic mRNA populations obtained from cells. We observed ∼100-fold heterogeneity for interactions of the translation initiation factor eIF4E with the universal mRNA 5' cap structure, dominated by steric effects on barrier-height variability for association. We also found that an RNA helicase, eIF4A, independently accelerated eIF4E-cap association. These data support a kinetic mechanism for how mRNA can determine the sensitivity of its translation to reduction in cellular eIF4E concentrations. They also support the view that global RNA structure significantly modulates protein-RNA interaction dynamics and can facilitate real-time communication between protein interactions at distinct sites.

Emerging Clinical Technology: Application of Machine Learning to Chronic Pain Assessments Based on Emotional Body Maps.

Depression and anxiety co-occur with chronic pain, and all three are thought to be caused by dysregulation of shared brain systems related to emotional processing associated with body sensations. Understanding the connection between emotional states, pain, and bodily sensations may help understand chronic pain conditions. We developed a mobile platform for measuring pain, emotions, and associated bodily feelings in chronic pain patients in their daily life conditions. Sixty-five chronic back pain patients reported the intensity of their pain, 11 emotional states, and the corresponding body locations. These variables were used to predict pain 2 weeks later. Applying machine learning, we developed two predictive models of future pain, emphasizing interpretability. One model excluded pain-related features as predictors of future pain, and the other included pain-related predictors. The best predictors of future pain were interactive effects of (a) body maps of fatigue with negative affect and (b) positive affect with past pain. Our findings emphasize the contribution of emotions, especially emotional experience felt in the body, to understanding chronic pain above and beyond the mere tracking of pain levels. The results may contribute to the generation of a novel artificial intelligence framework to help in the development of better diagnostic and therapeutic approaches to chronic pain.

Direct readout of heterochromatic H3K9me3 regulates DNMT1-mediated maintenance DNA methylation.

In mammals, repressive histone modifications such as trimethylation of histone H3 Lys9 (H3K9me3), frequently coexist with DNA methylation, producing a more stable and silenced chromatin state. However, it remains elusive how these epigenetic modifications crosstalk. Here, through structural and biochemical characterizations, we identified the replication foci targeting sequence (RFTS) domain of maintenance DNA methyltransferase DNMT1, a module known to bind the ubiquitylated H3 (H3Ub), as a specific reader for H3K9me3/H3Ub, with the recognition mode distinct from the typical trimethyl-lysine reader. Disruption of the interaction between RFTS and the H3K9me3Ub affects the localization of DNMT1 in stem cells and profoundly impairs the global DNA methylation and genomic stability. Together, this study reveals a previously unappreciated pathway through which H3K9me3 directly reinforces DNMT1-mediated maintenance DNA methylation.