Life and Work of Stress Granules and Processing Bodies: New Insights into Their Formation and Function.

The dynamic formation of stress granules (SGs), processing bodies (PBs), and related RNA organelles regulates diverse cellular processes, including the coordination of functionally connected messengers, the translational regulation at the synapse, and the control of viruses and retrotransposons. Recent studies have shown that pyruvate kinase and other enzymes localize in SGs and PBs, where they become protected from stress insults. These observations may have implications for enzyme regulation and metabolic control exerted by RNA-based organelles. The formation of these cellular bodies is governed by liquid-liquid phase separation (LLPS) processes, and it needs to be strictly controlled to prevent pathogenic aggregation. The intracellular concentration of key metabolites, such as ATP and sterol derivatives, may influence protein solubility, thus affecting the dynamics of liquid organelles. LLPS in vitro depends on the thermal diffusion of macromolecules, which is limited inside cells, where the condensation and dissolution of membrane-less organelles are helped by energy-driven processes. The active transport by the retrograde motor dynein helps SG assembly, whereas the anterograde motor kinesin mediates SG dissolution; a tug of war between these two molecular motors allows transient SG formation. There is evidence that the efficiency of dynein-mediated transport increases with the number of motor molecules associated with the cargo. The dynein-dependent transport may be influenced by cargo size as larger cargos can load a larger number of motors. We propose a model based on this emergent property of dynein motors, which would be collectively stronger during SG condensation and weaker during SG breakdown, thus allowing kinesin-mediated dispersion.

Sudestada1, a Drosophila ribosomal prolyl-hydroxylase required for mRNA translation, cell homeostasis, and organ growth.

Genome sequences predict the presence of many 2-oxoglutarate (2OG)-dependent oxygenases of unknown biochemical and biological functions in Drosophila. Ribosomal protein hydroxylation is emerging as an important 2OG oxygenase catalyzed pathway, but its biological functions are unclear. We report investigations on the function of Sudestada1 (Sud1), a Drosophila ribosomal oxygenase. As with its human and yeast homologs, OGFOD1 and Tpa1p, respectively, we identified Sud1 to catalyze prolyl-hydroxylation of the small ribosomal subunit protein RPS23. Like OGFOD1, Sud1 catalyzes a single prolyl-hydroxylation of RPS23 in contrast to yeast Tpa1p, where Pro-64 dihydroxylation is observed. RNAi-mediated Sud1 knockdown hinders normal growth in different Drosophila tissues. Growth impairment originates from both reduction of cell size and diminution of the number of cells and correlates with impaired translation efficiency and activation of the unfolded protein response in the endoplasmic reticulum. This is accompanied by phosphorylation of eIF2α and concomitant formation of stress granules, as well as promotion of autophagy and apoptosis. These observations, together with those on enzyme homologs described in the companion articles, reveal conserved biochemical and biological roles for a widely distributed ribosomal oxygenase.

7SK methylation by METTL3 promotes transcriptional activity.

A fundamental feature of cell signaling is the conversion of extracellular signals into adaptive transcriptional responses. The role of RNA modifications in this process is poorly understood. The small nuclear RNA 7SK prevents transcriptional elongation by sequestering the cyclin dependent kinase 9/cyclin T1 (CDK9/CCNT1) positive transcription elongation factor (P-TEFb) complex. We found that epidermal growth factor signaling induces phosphorylation of the enzyme methyltransferase 3 (METTL3), leading to METTL3-mediated methylation of 7SK. 7SK methylation enhanced its binding to heterogeneous nuclear ribonucleoproteins, causing the release of the HEXIM1 P-TEFb complex subunit1 (HEXIM1)/P-TEFb complex and inducing transcriptional elongation. Our findings establish the mechanism underlying 7SK activation and uncover a previously unknown function for the m6A modification in converting growth factor signaling events into a regulatory transcriptional response via an RNA methylation-dependent switch.

BUHO: a MATLAB script for the study of stress granules and processing bodies by high-throughput image analysis.

The spontaneous and reversible formation of foci and filaments that contain proteins involved in different metabolic processes is common in both the nucleus and the cytoplasm. Stress granules (SGs) and processing bodies (PBs) belong to a novel family of cellular structures collectively known as mRNA silencing foci that harbour repressed mRNAs and their associated proteins. SGs and PBs are highly dynamic and they form upon stress and dissolve thus releasing the repressed mRNAs according to changes in cell physiology. In addition, aggregates containing abnormal proteins are frequent in neurodegenerative disorders. In spite of the growing relevance of these supramolecular aggregates to diverse cellular functions a reliable automated tool for their systematic analysis is lacking. Here we report a MATLAB Script termed BUHO for the high-throughput image analysis of cellular foci. We used BUHO to assess the number, size and distribution of distinct objects with minimal deviation from manually obtained parameters. BUHO successfully addressed the induction of both SGs and PBs in mammalian and insect cells exposed to different stress stimuli. We also used BUHO to assess the dynamics of specific mRNA-silencing foci termed Smaug 1 foci (S-foci) in primary neurons upon synaptic stimulation. Finally, we used BUHO to analyze the role of candidate genes on SG formation in an RNAi-based experiment. We found that FAK56D, GCN2 and PP1 govern SG formation. The role of PP1 is conserved in mammalian cells as judged by the effect of the PP1 inhibitor salubrinal, and involves dephosphorylation of the translation factor eIF2α. All these experiments were analyzed manually and by BUHO and the results differed in less than 5% of the average value. The automated analysis by this user-friendly method will allow high-throughput image processing in short times by providing a robust, flexible and reliable alternative to the laborious and sometimes unfeasible visual scrutiny.