Journal articles: 'Translation regulatory network' – Grafiati (2024)

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An intricate regulatory network controls the expression of Salmonella virulence genes. The transcriptional regulator HilD plays a central role in this network by controlling the expression of tens of genes mainly required for intestinal colonization. Accordingly, the expression/activity of HilD is highly regulated by multiple factors, such as the SirA/BarA two-component system and the Hcp-like protein HilE. SirA/BarA positively regulates translation of hilD mRNA through a regulatory cascade involving the small RNAs CsrB and CsrC, and the RNA-binding protein CsrA, whereas HilE inhibits HilD activity by protein-protein interaction. In this study, we show that SirA/BarA also positively regulates translation of hilE mRNA through the same mentioned regulatory cascade. Thus, our results reveal a paradoxical regulation exerted by SirA/BarA-Csr on HilD, which involves simultaneous opposite effects, direct positive control and indirect negative control through HilE. This kind of regulation is called an incoherent type-1 feedforward loop (I1-FFL), which is a motif present in certain regulatory networks and represents a complex biological problem to decipher. Interestingly, our results, together with those from a previous study, indicate that HilE, the repressor component of the I1-FFL reported here (I1-FFLSirA/BarA-HilE-HilD), is required to reduce the growth cost imposed by the expression of the genes regulated by HilD. Moreover, we and others found that HilE is necessary for successful intestinal colonization by Salmonella. Thus, these findings support that I1-FFLSirA/BarA-HilE-HilD cooperates to control the precise amount and activity of HilD, for an appropriate balance between the growth cost and the virulence benefit generated by the expression of the genes induced by this regulator. I1-FFLSirA/BarA-HilE-HilD represents a complex regulatory I1-FFL that involves multiple regulators acting at distinct levels of gene expression, as well as showing different connections to the rest of the regulatory network governing Salmonella virulence.

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Gene regulatory networks represent the interactions among genes regulating the activation of specific cell functionalities and they have been successfully modeled using threshold Boolean networks. In this paper we propose a systematic translation of threshold Boolean networks into reaction systems. Our translation produces a non redundant set of rules with a minimal number of objects. This translation allows us to simulate the behavior of a Boolean network simply by executing the (closed) reaction system we obtain. This can be very useful for investigating the role of different genes simply by “playing” with the rules. We developed a tool able to systematically translate a threshold Boolean network into a reaction system. We use our tool to translate two well known Boolean networks modelling biological systems: the yeast-cell cycle and the SOS response in Escherichia coli. The resulting reaction systems can be used for investigating dynamic causalities among genes.

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Cells are equipped with a diverse network of signaling and regulatory proteins that function as cell cycle regulators and checkpoint proteins to ensure the proper progression of cell division. A key regulator of cell division is polo-like kinase 1 (PLK1), a member of the serine/threonine kinase family that plays an important role in regulating the mitotic and meiotic cell cycle. The phosphorylation of specific substrates mediated by PLK1 controls nuclear envelope breakdown (NEBD), centrosome maturation, proper spindle assembly, chromosome segregation, and cytokinesis. In mammalian oogenesis, PLK1 is essential for resuming meiosis before ovulation and for establishing the meiotic spindle. Among other potential roles, PLK1 regulates the localized translation of spindle-enriched mRNAs by phosphorylating and thereby inhibiting the translational repressor 4E-BP1, a downstream target of the mTOR (mammalian target of rapamycin) pathway. In this review, we summarize the functions of PLK1 in mitosis, meiosis, and cytokinesis and focus on the role of PLK1 in regulating mRNA translation. However, knowledge of the role of PLK1 in the regulation of meiosis remains limited.

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We have been able to observe the dynamic interactions between a specific messenger RNA (mRNA) and its protein product in vivo by studying the synthesis and assembly of peripherin intermediate filaments (IFs). The results show that peripherin mRNA-containing particles (messenger ribonucleoproteins [mRNPs]) move mainly along microtubules (MT). These mRNPs are translationally silent, initiating translation when they cease moving. Many peripherin mRNPs contain multiple mRNAs, possibly amplifying the total amount of protein synthesized within these “translation factories.” This mRNA clustering is dependent on MT, regulatory sequences within the RNA and the nascent protein. Peripherin is cotranslationally assembled into insoluble, nonfilamentous particles that are precursors to the long IF that form extensive cytoskeletal networks. The results show that the motility and targeting of peripherin mRNPs, their translational control, and the assembly of an IF cytoskeletal system are linked together in a process we have termed dynamic cotranslation.

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The control of translation in the course of gene expression regulation plays a crucial role in plants’ cellular events and, particularly, in responses to environmental factors. The paradox of the great variance between levels of mRNAs and their protein products in eukaryotic cells, including plants, requires thorough investigation of the regulatory mechanisms of translation. A wide and amazingly complex network of mechanisms decoding the plant genome into proteome challenges researchers to design new methods for genome-wide analysis of translational control, develop computational algorithms detecting regulatory mRNA contexts, and to establish rules underlying differential translation. The aims of this review are to (i) describe the experimental approaches for investigation of differential translation in plants on a genome-wide scale; (ii) summarize the current data on computational algorithms for detection of specific structure–function features and key determinants in plant mRNAs and their correlation with translation efficiency; (iii) highlight the methods for experimental verification of existed and theoretically predicted features within plant mRNAs important for their differential translation; and finally (iv) to discuss the perspectives of discovering the specific structural features of plant mRNA that mediate differential translation control by the combination of computational and experimental approaches.

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Abstract Small-scale regulatory networks can model known biological processes; while large-scale genome-wide datasets can identify novel mechanisms. We developed a biophysical modeling framework that combines the accuracy of small-scale networks with the power of large-scale datasets. As a proof of principle, we implemented this framework on a cohort of 844 multiple myeloma (MM) patients’ (and 1092 TCGA breast cancer patients) z-normalized RNAseq data using t-Distributed Stochastic Neighbor Embedding to construct a disease-specific transcriptomic map, where genes closer to each other co-express within the cohort. Fuzzy c-means clustering is carried out to identify clusters of genes that are likely regulated by a common transcription factor (TF). We construct a gene regulatory network (GRN) for each cluster of co-expressing genes on a disease-specific transcriptomic map by identifying upstream TFs for each cluster using publicly available databases ENCODE and ChEA, and kinases that phosphorylate these TFs using PhosphoSitePlus and PhosphoPoint. An exhaustive list of TFs and kinases are reduced to a few key predictor variables using regression tree modeling for each gene in that cluster. This leads to a cascading network of kinases that phosphorylate TFs, which regulate expression of genes in a cluster. We derived a mechanistic model from first-principles to define functional relationships governing the GRN; where transcription, translation, and post-translational modifications are modeled using first-order reversible reaction kinetic equations. The patient-specific rate constants of the model are parametrized by single sample gene set enrichment analysis scores of key KEGG pathways like ribosome, protein synthesis, RNA degradation, etc. The system of differential equations, under steady-state, reduce to an algebraic equation that can predict the expression of every gene in a cluster from the expression of its upstream TFs and kinases alone, which is fitted to RNAseq data of 422 MM patients to estimate undetermined parameters. The remaining patients’ data is used to estimate the accuracy of the model using Pearson’s correlation (model predicted vs actual) coefficient, r. Out of 16,738 genes, 7,936 were predicted accurately (r>0.5), while the remaining genes were shown to have a significant overlap (hypergeometric test; p-value<1e-48 and representation factor = 7.27) with genes that have high variability in chromatin accessibility across patients. A reduced GRN with only accurately predicted genes is obtained for each cluster, followed by linking GRNs to each other through TFs and kinases that are featured in other GRNs; where betweenness centrality measures of the resulting directed graph identifies disease-specific master regulators. MYC, STAT3, CREB1, POLR2A, PLK1, and TP53 are found to be key hubs in MM network; similar analyses are being conducted for other cancers featured in TCGA. Citation Format: Praneeth Reddy Sudalagunta, Rafael Renatino Canevarolo, Mark Meads, Maria Coelho Silva, Xiaohong Zhao, Raghunandan Reddy Alugubelli, Joon-hyun Song, Erez Persi, Mehdi Damaghi, Kenneth H. Shain, Ariosto Silva. A novel gene regulatory network model identifies master regulators in cancer. [abstract]. In: Proceedings of the American Association for Cancer Research Annual Meeting 2023; Part 1 (Regular and Invited Abstracts); 2023 Apr 14-19; Orlando, FL. Philadelphia (PA): AACR; Cancer Res 2023;83(7_Suppl):Abstract nr 4313.

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RNA-binding proteins (RBPs) coordinate cell fate specification and differentiation in a variety of systems. RNA regulation is critical during oocyte development and early embryogenesis, in which RBPs control expression from maternal mRNAs encoding key cell fate determinants. The Caenorhabditis elegans Notch hom*ologue glp-1 coordinates germline progenitor cell proliferation and anterior fate specification in embryos. A network of sequence-specific RBPs is required to pattern GLP-1 translation. Here, we map the cis-regulatory elements that guide glp-1 regulation by the CCCH-type tandem zinc finger protein POS-1 and the STAR-domain protein GLD-1. Our results demonstrate that both proteins recognize the glp-1 3′ untranslated region (UTR) through adjacent, overlapping binding sites and that POS-1 binding excludes GLD-1 binding. Both factors are required to repress glp-1 translation in the embryo, suggesting that they function in parallel regulatory pathways. It is intriguing that two equivalent POS-1–binding sites are present in the glp-1 3′ UTR, but only one, which overlaps with a translational derepression element, is functional in vivo. We propose that POS-1 regulates glp-1 mRNA translation by blocking access of other RBPs to a key regulatory sequence.

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Molecular biology focuses on genes and their interactions at the transcription, regulation and protein level. Finding genes that cause certain behaviors can make therapeutic interventions more effective. Although biological tools can extract the genes and perform some analyses, without the help of computational methods, deep insight of the genetic function and its effects will not occur. On the other hand, complex systems can be modeled by networks, introducing the main data as nodes and the links in-between as the transactions occurring within the network. Gene regulatory networks are examples that are modeled and analyzed in order to gain insight of their exact functions. Since a cell's specific functionality is greatly determined by the genes it expresses, translation or the act of converting mRNA to proteins is highly regulated by the control network that directs cellular activities. This paper briefly reviews the most important computational methods for analyzing, modeling and controlling the gene regulatory networks.

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Gene network simulations are increasingly used to quantify mutual gene regulation in biological tissues. These are generally based on linear interactions between single-entity regulatory and target genes. Biological genes, by contrast, commonly have multiple, partially independent, cis-regulatory modules (CRMs) for regulator binding, and can produce variant transcription and translation products. We present a modeling framework to address some of the gene regulatory dynamics implied by this biological complexity. Spatial patterning of the hunchback (hb) gene in Drosophila development involves control by three CRMs producing two distinct mRNA transcripts. We use this example to develop a differential equations model for transcription which takes into account the cis-regulatory architecture of the gene. Potential regulatory interactions are screened by a genetic algorithms (GAs) approach and compared to biological expression data.

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The present study aimed to investigate the molecular mechanisms underlying glioblastoma multiform (GBM) and its biomarkers. The differentially expressed genes (DEGs) were diagnosed using the limma software package. The ToppGene (ToppFun) was used to perform pathway and Gene Ontology (GO) enrichment analysis of the DEGs. Protein-protein interaction (PPI) networks, extracted modules, miRNA-target genes regulatory network and TF-target genes regulatory network were used to obtain insight into the actions of DEGs. Survival analysis for DEGs was carried out. A total of 590 DEGs, including 243 up regulated and 347 down regulated genes, were diagnosed between scrambled shRNA expression and Lin7A knock down. The up-regulated genes were enriched in ribosome, mitochondrial translation termination, translation, and peptide biosynthetic process. The down-regulated genes were enriched in focal adhesion, VEGFR3 signaling in lymphatic endothelium, extracellular matrix organization, and extracellular matrix. The current study screened the genes in the PPI network, extracted modules, miRNA-target genes regulatory network, and TF-target genes regulatory network with higher degrees as hub genes, which included NPM1, CUL4A, YIPF1, SHC1, AKT1, VLDLR, RPL14, P3H2, DTNA, FAM126B, RPL34, and MYL5. Survival analysis indicated that the high expression of RPL36A and MRPL35 were predicting longer survival of GBM, while high expression of AP1S1 and AKAP12 were predicting shorter survival of GBM. High expression of RPL36A and AP1S1 were associated with pathogenesis of GBM, while low expression of ALPL was associated with pathogenesis of GBM. In conclusion, the current study diagnosed DEGs between scrambled shRNA expression and Lin7A knock down samples, which could improve our understanding of the molecular mechanisms in the progression of GBM, and these crucial as well as new diagnostic markers might be used as therapeutic targets for GBM.

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ABSTRACT The unfolded protein response (UPR) is an important regulatory network that responds to perturbations in protein homeostasis in the endoplasmic reticulum (ER). In mammalian cells, the UPR features translational and transcriptional mechanisms of gene expression aimed at restoring proteostatic control. A central feature of the UPR is phosphorylation of the α subunit of eukaryotic initiation factor-2 (eIF2) by PERK (EIF2AK3/PEK), which reduces the influx of nascent proteins into the ER by lowering global protein synthesis, coincident with preferential translation of key transcription activators of genes that function to expand the processing capacity of this secretory organelle. Upon ER stress, the apicomplexan parasite Toxoplasma gondii is known to induce phosphorylation of Toxoplasma eIF2α and lower translation initiation. To characterize the nature of the ensuing UPR in this parasite, we carried out microarray analyses to measure the changes in the transcriptome and in translational control during ER stress. We determined that a collection of transcripts linked with the secretory process are induced in response to ER stress, supporting the idea that a transcriptional induction phase of the UPR occurs in Toxoplasma. Furthermore, we determined that about 500 gene transcripts showed enhanced association with translating ribosomes during ER stress. Many of these target genes are suggested to be involved in gene expression, including JmjC5, which continues to be actively translated during ER stress. This study indicates that Toxoplasma triggers a UPR during ER stress that features both translational and transcriptional regulatory mechanisms, which is likely to be important for parasite invasion and development.

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Abstract SINEUPs are long non-coding RNAs (lncRNAs) that contain a SINE element, and which up-regulate the translation of target mRNA. They have been studied in a wide range of applications, as both biological and therapeutic tools, although the underpinning molecular mechanism is unclear. Here, we focused on the sub-cellular distribution of target mRNAs and SINEUP RNAs, performing co-transfection of expression vectors for these transcripts into human embryonic kidney cells (HEK293T/17), to investigate the network of translational regulation. The results showed that co-localization of target mRNAs and SINEUP RNAs in the cytoplasm was a key phenomenon. We identified PTBP1 and HNRNPK as essential RNA binding proteins. These proteins contributed to SINEUP RNA sub-cellular distribution and to assembly of translational initiation complexes, leading to enhanced target mRNA translation. These findings will promote a better understanding of the mechanisms employed by regulatory RNAs implicated in efficient protein translation.

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Unraveling molecular regulatory networks underlying disease progression is critically important for understanding disease mechanisms and identifying drug targets. The existing methods for inferring gene regulatory networks (GRNs) rely mainly on time-course gene expression data. However, most available omics data from cross-sectional studies of cancer patients often lack sufficient temporal information, leading to a key challenge for GRN inference. Through quantifying the latent progression using random walks-based manifold distance, we propose a latent-temporal progression-based Bayesian method, PROB, for inferring GRNs from the cross-sectional transcriptomic data of tumor samples. The robustness of PROB to the measurement variabilities in the data is mathematically proved and numerically verified. Performance evaluation on real data indicates that PROB outperforms other methods in both pseudotime inference and GRN inference. Applications to bladder cancer and breast cancer demonstrate that our method is effective to identify key regulators of cancer progression or drug targets. The identified ACSS1 is experimentally validated to promote epithelial-to-mesenchymal transition of bladder cancer cells, and the predicted FOXM1-targets interactions are verified and are predictive of relapse in breast cancer. Our study suggests new effective ways to clinical transcriptomic data modeling for characterizing cancer progression and facilitates the translation of regulatory network-based approaches into precision medicine.

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During neuronal circuit formation, axons progressively develop into a presynaptic compartment aided by extracellular signals. Axons display a remarkably high degree of autonomy supported in part by a local translation machinery that permits the subcellular production of proteins required for their development. Here, we review the latest findings showing that microRNAs (miRNAs) are critical regulators of this machinery, orchestrating the spatiotemporal regulation of local translation in response to cues. We first survey the current efforts toward unraveling the axonal miRNA repertoire through miRNA profiling, and we reveal the presence of a putative axonal miRNA signature. We also provide an overview of the molecular underpinnings of miRNA action. Our review of the available experimental evidence delineates two broad paradigms: cue-induced relief of miRNA-mediated inhibition, leading to bursts of protein translation, and cue-induced miRNA activation, which results in reduced protein production. Overall, this review highlights how a decade of intense investigation has led to a new appreciation of miRNAs as key elements of the local translation regulatory network controlling axon development.

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The androgen receptor (AR) is a driver of cellular differentiation and prostate cancer development. An extensive body of work has linked these normal and aberrant cellular processes to mRNA transcription; however, the extent to which AR regulates posttranscriptional gene regulation remains unknown. Here, we demonstrate that AR uses the translation machinery to shape the cellular proteome. We show that AR is a negative regulator of protein synthesis and identify an unexpected relationship between AR and the process of translation initiation in vivo. This is mediated through direct transcriptional control of the translation inhibitor 4EBP1. We demonstrate that lowering AR abundance increases the assembly of the eIF4F translation initiation complex, which drives enhanced tumor cell proliferation. Furthermore, we uncover a network of pro-proliferation mRNAs characterized by a guanine-rich cis-regulatory element that is particularly sensitive to eIF4F hyperactivity. Using both genetic and pharmacologic methods, we demonstrate that dissociation of the eIF4F complex reverses the proliferation program, resulting in decreased tumor growth and improved survival in preclinical models. Our findings reveal a druggable nexus that functionally links the processes of mRNA transcription and translation initiation in an emerging class of lethal AR-deficient prostate cancer.

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The phytohormone abscisic acid (ABA) plays crucial roles in numerous physiological processes during plant growth and abiotic stress responses. The endogenous ABA level is controlled by complex regulatory mechanisms involving biosynthesis, catabolism, transport and signal transduction pathways. This complex regulatory network may target multiple levels, including transcription, translation and post-translational regulation of genes involved in ABA responses. Most of the genes involved in ABA biosynthesis, catabolism and transport have been characterized. The local ABA concentration is critical for initiating ABA-mediated signalling during plant development and in response to environmental changes. In this chapter we discuss the mechanisms that regulate ABA biosynthesis, catabolism, transport and hom*oeostasis. We also present the findings of recent research on ABA perception by cellular receptors, and ABA signalling in response to cellular and environmental conditions.

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Using the actor-network theory (ANT), this article sought to analyze the translation process induced by the Danish regulatory agency for financial reporting to incorporate the eXtensible Business Reporting Language (XBRL) into the financial reporting practices, giving special attention to how resistance demonstrated by certain actors shapes the process of incorporating the technology into the financial reporting environment. The empirical analysis, relying on a series of semi-structured interviews conducted between November 2013 and February 2016, highlighted the strategic steps taken by the regulatory agency to deal with the emerging resistance. The analysis illustrated how the initial setting created at the early stages of the translation process develops into a socio-technical context in which the participating actors' no longer express resistance, and commit to the incorporation of XBRL. In this respect, the paper contributes to previous studies on XBRL, adds to the financial reporting literature by illustrating how resistance shapes the introduction of complex regulatory changes, and contributes to the ANT literature, especially those based on Michel Callon’s translation model.

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Abstract In green microalgae, prolonged exposure to inorganic carbon depletion requires long-term acclimation responses, involving modulated gene expression and the adjustment of photosynthetic activity to the prevailing supply of carbon dioxide. Here, we describe a microalgal regulatory cycle that adjusts the light-harvesting capacity at photosystem II (PSII) to the prevailing supply of carbon dioxide in Chlamydomonas (Chlamydomonas reinhardtii). It engages low carbon dioxide response factor (LCRF), a member of the squamosa promoter-binding protein (SBP) family of transcription factors, and the previously characterized cytosolic translation repressor nucleic acid-binding protein 1 (NAB1). LCRF combines a DNA-binding SBP domain with a conserved domain for protein–protein interaction. LCRF transcription is rapidly induced by carbon dioxide depletion. LCRF activates NAB1 transcription by specifically binding to tetranucleotide motifs present in its promoter. Accumulation of the NAB1 protein enhances translational repression of its prime target mRNA, encoding the PSII-associated major light-harvesting protein LHCBM6. The resulting truncation of the PSII antenna size helps maintaining a low excitation during carbon dioxide limitation. Analyses of low carbon dioxide acclimation in nuclear insertion mutants devoid of a functional LCRF gene confirm the essentiality of this novel transcription factor for the regulatory circuit.

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Serine/arginine-rich (SR) proteins are a type of splicing factor. They play significant roles in constitutive and alternative pre-mRNA splicing, and are involved in post-splicing activities, such as mRNA nuclear export, nonsense-mediated mRNA decay, mRNA translation, and miRNA biogenesis. In plants, SR proteins function under a complex regulatory network by protein–protein and RNA–protein interactions between SR proteins, other splicing factors, other proteins, or even RNAs. The regulatory networks of SR proteins are complex—they are regulated by the SR proteins themselves, they are phosphorylated and dephosphorylated through interactions with kinase, and they participate in signal transduction pathways, whereby signaling cascades can link the splicing machinery to the exterior environment. In a complex network, SR proteins are involved in plant growth and development, signal transduction, responses to abiotic and biotic stresses, and metabolism. Here, I review the current status of research on plant SR proteins, construct a model of SR proteins function, and ask many questions about SR proteins in plants.

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Microvascular dysfunction (MVD) has long plagued the medical field despite improvements in its prevention, diagnosis, and intervention. Microvascular lesions from MVD increase with age and further lead to impaired microcirculation, target organ dysfunction, and a mass of microvascular complications, thus contributing to a heavy medical burden and rising disability rates. An up-to-date understanding of molecular mechanisms underlying MVD will facilitate discoveries of more effective therapeutic strategies. Recent advances in epigenetics have revealed that RNA methylation, an epigenetic modification, has a pivotal role in vascular events. The N6-methylation of adenosine (m6A) modification is the most prevalent internal RNA modification in eukaryotic cells, which regulates vascular transcripts through splicing, degradation, translation, as well as translocation, thus maintaining microvascular homeostasis. Conversely, the disruption of the m6A regulatory network will lead to MVD. Herein, we provide a review discussing how m6A methylation interacts with MVD. We also focus on alterations of the m6A regulatory network under pathological conditions. Finally, we highlight the value of m6A regulators as prognostic biomarkers and novel therapeutic targets, which might be a promising addition to clinical medicine.

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Gene expression in eukaryotes depends on a web of events which are inter-related and tightly regulated. These key events can be broadly classified into post-transcriptional and post-translational processes. In general, the post-transcriptional events include pre-mRNA processing (capping, splicing, polyadenylation), RNA stability, and translation as well as chromatin modifications through regulatory RNAs (miRNA, siRNAs and long non-coding RNAs). Protein phosphorylation, ubiquitination and sumoylation are a few post-translational events. These events are constitutive as well as provoked by specific exogenous and/or endogenous stimuli. In case of the plant system, the molecular mechanisms responsible for regulating the gene expression is diverse and yet to be fully revealed. The network of post-transcriptional and post-translational events do ensure temporal and spatial suitable patterns of downstream stress-related gene expression. The current review mainly focus on a variety of molecular events which play a pivotal role in fine tuning the gene expression in eukaryotes.

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Abstract The circadian clock helps organisms to anticipate and coordinate gene regulatory responses to changes in environmental stimuli. Under growth limiting temperatures, the time of the day modulates the accumulation of polyadenylated mRNAs. In response to heat stress, plants will conserve energy and selectively translate mRNAs. How the clock and/or the time of the day regulates polyadenylated mRNAs bound by ribosomes in response to heat stress is unknown. In-depth analysis of Arabidopsis thaliana translating mRNAs found that the time of the day gates the response of approximately one-third of the circadian-regulated heat-responsive translatome. Specifically, the time of the day and heat stress interact to prioritize the pool of mRNAs in cue to be translated. For a subset of mRNAs, we observed a stronger gated response during the day, and preferentially before the peak of expression. We propose previously overlooked transcription factors (TFs) as regulatory nodes and show that the clock plays a role in the temperature response for select TFs. When the stress was removed, the redefined priorities for translation recovered within 1 h, though slower recovery was observed for abiotic stress regulators. Through hierarchical network connections between clock genes and prioritized TFs, our work provides a framework to target key nodes underlying heat stress tolerance throughout the day.

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The rapidly and constantly evolving coronavirus, SARS-CoV-2, imposes a great threat to human health causing severe lung disease and significant mortality. Cytoplasmic stress granules (SGs) exert anti-viral activities due to their involvement in translation inhibition and innate immune signaling. SARS-CoV-2 sequesters important SG nucleator proteins and impairs SG formation, thus evading the host response for efficient viral replication. However, the significance of SGs in COVID-19 infection remains elusive. In this study, we utilize a protein-protein interaction network approach to systematically dissect the crosstalk of human post-translational regulatory networks governed by SG proteins due to SARS-CoV-2 infection. We uncovered that 116 human SG proteins directly interact with SARS-CoV-2 proteins and are involved in 430 different brain disorders including COVID-19. Further, we performed gene set enrichment analysis to identify the drugs against three important key SG proteins (DYNC1H1, DCTN1, and LMNA) and also looked for potential microRNAs (miRNAs) targeting these proteins. We identified bexarotene as a potential drug molecule and miRNAs, hsa-miR-615-3p, hsa-miR-221-3p, and hsa-miR-124-3p as potential candidates for the treatment of COVID-19 and associated manifestations.

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Abstract Photosynthesis is a central determinant of plant biomass production, but its homeostasis is increasingly challenged by heat. Little is known about the sensitive regulatory principles involved in heat acclimation that underly the biogenesis and repair of chloroplast-encoded core subunits of photosynthetic complexes. Employing time-resolved ribosome and transcript profiling together with selective ribosome proteomics, we systematically deciphered these processes in chloroplasts of Chlamydomonas reinhardtii. We revealed protein biosynthesis and altered translation elongation as central processes for heat acclimation and showed that these principles are conserved between the alga and the flowering plant Nicotiana tabacum. Short-term heat exposure resulted in specific translational repression of chlorophyll a-containing core antenna proteins of photosystems I and II. Furthermore, translocation of ribosome nascent chain complexes to thylakoid membranes was affected, as reflected by the increased accumulation of stromal cpSRP54-bound ribosomes. The successful recovery of synthesizing these proteins under prolonged acclimation of nonlethal heat conditions was associated with specific changes of the co-translational protein interaction network, including increased ribosome association of chlorophyll biogenesis enzymes and acclimation factors responsible for complex assembly. We hypothesize that co-translational cofactor binding and targeting might be bottlenecks under heat but become optimized upon heat acclimation to sustain correct co-translational protein complex assembly.

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The synchronous genetic regulatory networks model includes the drive system and response system, and the drive-response system is symmetric. From a biological point of view, this model illustrates the dynamic behaviors in gene-to-protein processes, in terms of transcription and translation. This paper introduces a model of genetic regulatory networks with time delay. The fixed-time synchronization control problem of the proposed model is studied based on fixed-time stability theory and the Lyapunov method. Concretely, the authors first propose a way to switch from the given model to matrix form. Then, two types of novel controllers are designed and the corresponding sufficient conditions are investigated respectively to ensure the fixed-time synchronization goal. Moreover, the settling times of fixed-time synchronization are estimated for the addressed discontinuous controllers, which are not dependent on the initial or delayed states of the model. Finally, numerical simulations are presented and compared to illustrate the benefits of the theoretical results.

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As sessile organisms, plants have evolved complex mechanisms to rapidly respond to ever-changing ambient temperatures. Temperature response in plants is modulated by a multilayer regulatory network, including transcriptional and post-transcriptional regulations. Alternative splicing (AS) is an essential post-transcriptional regulatory mechanism. Extensive studies have confirmed its key role in plant temperature response, from adjustment to diurnal and seasonal temperature changes to response to extreme temperatures, which has been well documented by previous reviews. As a key node in the temperature response regulatory network, AS can be modulated by various upstream regulations, such as chromatin modification, transcription rate, RNA binding proteins, RNA structure and RNA modifications. Meanwhile, a number of downstream mechanisms are affected by AS, such as nonsense-mediated mRNA decay (NMD) pathway, translation efficiency and production of different protein variants. In this review, we focus on the links between splicing regulation and other mechanisms in plant temperature response. Recent advances regarding how AS is regulated and the following consequences in gene functional modulation in plant temperature response will be discussed. Substantial evidence suggests that a multilayer regulatory network integrating AS in plant temperature response has been unveiled.

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Expression noise, the variability of the amount of gene product among isogenic cells grown in identical conditions, originates from the inherent stochasticity of diffusion and binding of the molecular players involved in transcription and translation. It has been shown that expression noise is an evolvable trait and that central genes exhibit less noise than peripheral genes in gene networks. A possible explanation for this pattern is increased selective pressure on central genes since they propagate their noise to downstream targets, leading to noise amplification. To test this hypothesis, we developed a new gene regulatory network model with inheritable stochastic gene expression and simulated the evolution of gene-specific expression noise under constraint at the network level. Stabilizing selection was imposed on the expression level of all genes in the network and rounds of mutation, selection, replication and recombination were performed. We observed that local network features affect both the probability to respond to selection, and the strength of the selective pressure acting on individual genes. In particular, the reduction of gene-specific expression noise as a response to stabilizing selection on the gene expression level is higher in genes with higher centrality metrics. Furthermore, global topological structures such as network diameter, centralization and average degree affect the average expression variance and average selective pressure acting on constituent genes. Our results demonstrate that selection at the network level leads to differential selective pressure at the gene level, and local and global network characteristics are an essential component of gene-specific expression noise evolution.

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The 5’ untranslated region plays a key role in regulating mRNA translation and consequently protein abundance. Therefore, accurate modeling of 5’UTR regulatory sequences shall provide insights into translational control mechanisms and help interpret genetic variants. Recently, a model was trained on a massively parallel reporter assay to predict mean ribosome load (MRL)—a proxy for translation rate—directly from 5’UTR sequence with a high degree of accuracy. However, this model is restricted to sequence lengths investigated in the reporter assay and therefore cannot be applied to the majority of human sequences without a substantial loss of information. Here, we introduced frame pooling, a novel neural network operation that enabled the development of an MRL prediction model for 5’UTRs of any length. Our model shows state-of-the-art performance on fixed length randomized sequences, while offering better generalization performance on longer sequences and on a variety of translation-related genome-wide datasets. Variant interpretation is demonstrated on a 5’UTR variant of the gene HBB associated with beta-thalassemia. Frame pooling could find applications in other bioinformatics predictive tasks. Moreover, our model, released open source, could help pinpoint pathogenic genetic variants.

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Abstract Posttranscriptional mechanisms are now widely acknowledged to play a central role in orchestrating gene-regulatory networks in hematopoietic cell growth, differentiation, and tumorigenesis. Although much attention has focused on microRNAs as regulators of mRNA stability/translation, recent data have highlighted the role of several diverse classes of AU-rich RNA-binding protein in the regulation of mRNA decay/stabilization. AU-rich elements are found in the 3′-untranslated region of many mRNAs that encode regulators of cell growth and survival, such as cytokines and onco/tumor-suppressor proteins. These are targeted by a burgeoning number of different RNA-binding proteins. Three distinct types of AU-rich RNA binding protein (ARE poly-U–binding degradation factor-1/AUF1, Hu antigen/HuR/HuA/ELAVL1, and the tristetraprolin/ZFP36 family of proteins) are essential for normal hematopoiesis. Together with 2 further AU-rich RNA-binding proteins, nucleolin and KHSRP/KSRP, the functions of these proteins are intimately associated with pathways that are dysregulated in various hematopoietic malignancies. Significantly, all of these AU-rich RNA-binding proteins function via an interconnected network that is integrated with microRNA functions. Studies of these diverse types of RNA binding protein are providing novel insight into gene-regulatory mechanisms in hematopoiesis in addition to offering new opportunities for developing mechanism-based targeted therapeutics in leukemia and lymphoma.

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Objective: Animal models of atherosclerosis are used extensively to interrogate molecular mechanisms in serial fashion. We tested whether a novel systems biology approach to integration of preclinical data identifies novel pathways and regulators in human disease. Approach and Results: Of 716 articles published in ATVB from 1995 to 2019 using the apolipoprotein E knockout mouse to study atherosclerosis, data were extracted from 360 unique studies in which a gene was experimentally perturbed to impact plaque size or composition and analyzed using Ingenuity Pathway Analysis software. TREM1 (triggering receptor expressed on myeloid cells) signaling and LXR/RXR (liver X receptor/retinoid X receptor) activation were identified as the top atherosclerosis-associated pathways in mice (both P <1.93×10 − 4 , TREM1 implicated early and LXR/RXR in late atherogenesis). The top upstream regulatory network in mice (sc-58125, a COX2 inhibitor) linked 64.0% of the genes into a single network. The pathways and networks identified in mice were interrogated by testing for associations between the genetically predicted gene expression of each mouse pathway-identified human hom*olog with clinical atherosclerosis in a cohort of 88 660 human subjects. hom*ologous human pathways and networks were significantly enriched for gene-atherosclerosis associations (empirical P <0.01 for TREM1 and LXR/RXR pathways and COX2 network). This included 12(60.0%) TREM1 pathway genes, 15(53.6%) LXR/RXR pathway genes, and 67(49.3%) COX2 network genes. Mouse analyses predicted, and human study validated, the strong association of COX2 expression ( PTGS2 ) with increased likelihood of atherosclerosis (odds ratio, 1.68 per SD of genetically predicted gene expression; P =1.07×10 − 6 ). Conclusions: PRESCIANT (Preclinical Science Integration and Translation) leverages published preclinical investigations to identify high-confidence pathways, networks, and regulators of human disease.

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Hypusine modification of eukaryotic initiation factor 5A (eIF-5A) represents a unique and highly specific post-translational modification with regulatory functions in cancer, diabetes, and infectious diseases. However, the specific cellular pathways that are influenced by the hypusine modification remain largely unknown. To globally characterize eIF-5A and hypusine-dependent pathways, we used an approach that combines large-scale bioreactor cell culture with tandem affinity purification and mass spectrometry: “bioreactor-TAP-MS/MS.” By applying this approach systematically to all four components of the hypusine modification system (eIF-5A1, eIF-5A2, DHS, and DOHH), we identified 248 interacting proteins as components of the cellular hypusine network, with diverse functions including regulation of translation, mRNA processing, DNA replication, and cell cycle regulation. Network analysis of this data set enabled us to provide a comprehensive overview of the protein-protein interaction landscape of the hypusine modification system. In addition, we validated the interaction of eIF-5A with some of the newly identified associated proteins in more detail. Our analysis has revealed numerous novel interactions, and thus provides a valuable resource for understanding how this crucial homeostatic signaling pathway affects different cellular functions.

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Limited nutrient availability is a cause of intrauterine growth restriction (IUGR), a condition that has important implications for the well being of the offspring. Using the established IUGR model of maternal fasting in the rat, we investigated mechanisms that control gene expression and mRNA translation in late-gestation fetal liver. Maternal fasting for 48 h during the last one-third of gestation was associated with a 10–15% reduction in fetal body weight and a disproportionate one-third reduction in total fetal liver protein. The fetal liver transcriptome showed only subtle changes consistent with reduced cell proliferation and enhanced differentiation in IUGR. Effects on the transcriptome could not be attributed to specific transcription factors. We purified translating polysomes to profile the population of mRNAs undergoing active translation. Microarray analysis of the fetal liver translatome indicated a global reduction of translation. The only targeted effect was enhanced translation of mitochondrial ribosomal proteins in IUGR, consistent with enhanced mitochondrial biogenesis. There was no evidence for attenuated signaling through the mammalian target of rapamycin (mTOR). Western blot analysis showed no changes in fetal liver mTOR signaling. However, eukaryotic initiation factor 2α (eIF2α) phosphorylation was increased in livers from IUGR fetuses, consistent with a role in global translation control. Our data indicate that IUGR-associated changes in hepatic gene expression and mRNA translation likely involve a network of complex regulatory mechanisms, some of which are novel and distinct from those that mediate the response of the liver to nutrient restriction in the adult rat.

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Module networks model gene regulatory relationship and LemonTree is one of its popular implementations. This work reports a comprehensive performance characterization, proposes optimal parameter settings, patches the algorithm, and expands application to the human gut-intestinal metagenome for potential application in translational medicine.

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Protein binding to the non-coding regions of mRNAs is relatively well characterized and its functionality has been described in many examples. New results obtained by high-throughput methods indicate that binding to the coding sequence (CDS) by RNA-binding proteins is also quite common, but the functions thereof are more obscure. As described in this review, CDS binding has a role in the regulation of mRNA stability, but it has also a more intriguing role in the regulation of translational efficiency. Global approaches, which suggest the significance of CDS binding along with specific examples of CDS-binding RBPs and their modes of action, are outlined here, pointing to the existence of a relatively less-known regulatory network controlling mRNA stability and translation on yet another level.

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Abstract In photosynthesizing chloroplasts, rapidly changing energy input, intermediate generation of strong reductants as well as oxidants and multiple participating physicochemical processes and pathways, call for efficient regulation. Coupling redox information to protein function via thiol modifications offers a powerful mechanism to activate, down-regulate and coordinate interdependent processes. Efficient thiol switching of target proteins involves the thiol-disulfide redox regulatory network, which is highly elaborated in chloroplasts. This review addresses the features of this network. Its conditional function depends on specificity of reduction and oxidation reactions and pathways, thiol redox buffering, but also formation of heterogeneous milieus by microdomains, metabolite gradients and macromolecular assemblies. One major player is glutathione. Its synthesis and function is under feedback redox control. The number of thiol-controlled processes and involved thiol switched proteins is steadily increasing, e.g., in tetrapyrrole biosynthesis, plastid transcription and plastid translation. Thus chloroplasts utilize an intricate and versatile redox regulatory network for intraorganellar and retrograde communication.

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Background. Epithelial splicing regulatory protein 1 (ESRP1) has been described as an RNA-binding protein involved in cancer development. However, the expression and regulatory network of ESRP1 in cutaneous malignant melanoma (CMM) remain unclear. Methods. From the sequencing data of 103 CMM samples in The Cancer Genome Atlas database, the expression level of ESRP1 and its correlation with the clinicopathological characteristics were analyzed using the Oncomine 4.5, Gene Expression Profiling Interactive Analysis (GEPIA), and UALCAN tools, while LinkedOmics was used to identify differential gene expression with ESRP1 and to analyze Gene Ontology (GO) and Kyoto Encyclopedia of Genes and Genomes (KEGG) pathways. Gene enrichment analysis examined target networks of kinases, miRNAs, and transcription factors. Finally, TIMER was used to analyze the relationship between ESRP1 and tumor immune cell infiltration. Results. We found that ESRP1 was lowly expressed in CMM tissues, and a low level of ESRP1 expression correlated with better overall survival. Expression of this gene was linked to functional networks involving the condensed chromosomes, epidermal development, and translation initiation. Functional network analysis suggested that ESRP1 regulated ribosome metabolism, drug metabolism, and chemical carcinogenesis via pathways involving several cancer-related kinases, miRNAs, and transcription factors. Furthermore, our results suggested that ESRP1 played an important role in regulating tumor-associated macrophage polarization, dendritic cell infiltration, Treg cells, and T cell exhaustion. Conclusion. Our study demonstrates ESRP1 expression, prognostic value, and potential regulatory networks in CMM, thereby shedding light on the clinical significance of ESRP1, and provides a novel biomarker for determining prognosis and immune infiltration in CMM.

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Eukaryotic gene expression is controlled at multiple levels, including gene transcription and protein translation initiation. One molecule with key roles in both regulatory mechanisms is methyl CpG binding protein 2 (MeCP2). MECP2 gain- and loss-of-function mutations lead to Rett Syndrome and MECP2 Duplication Syndrome, respectively. To study MECP2 gain-of-function, we generated stably transduced human brain cells using lentiviral vectors for both MECP2E1 and MECP2E2 isoforms. Stable overexpression was confirmed by Western blot and immunofluorescence. We assessed the impact of MeCP2E1-E2 gain-of-function on the MeCP2 homeostasis regulatory network (MECP2E1/E2-BDNF/BDNF-miR-132), mTOR-AKT signaling, ribosome biogenesis, markers of chromatin structure, and protein translation initiation. We observed that combined co-transduction of MeCP2 isoforms led to protein degradation of MeCP2E1. Proteosome inhibition by MG132 treatment recovered MeCP2E1 protein within an hour, suggesting its induced degradation through the proteosome pathway. No significant change was detected for translation initiation factors as a result of MeCP2E1, MeCP2E2, or combined overexpression of both isoforms. In contrast, analysis of human Rett Syndrome brains tissues compared with controls indicated impaired protein translation initiation, suggesting that such mechanisms may have differential sensitivity to MECP2 gain- and loss-of-function. Collectively, our results provide further insight towards the dose-dependent functional role of MeCP2 isoforms in the human brain.

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The 80S cytoplasmic ribosome is responsible for translating the transcriptome into the proteome. Demand for ribosome production depends on growth rate, and both the ribosomal RNA (rRNA) and ribosomal protein (RP) components must respond coordinately and rapidly to positive and negative growth stimuli to prevent deleterious effects of excess or insufficient subunits. The 81 RPs of the Arabidopsis 80S ribosome are encoded by multigene families that often exhibit overlapping patterns of transcript accumulation; however, only one isoform of each RP family (with the exception of a small number of acidic RPs) assembles into a single ribosome. Here we dissected the regulatory regions (RRs) of both members of the RPL23a family (RPL23aA and RPL23aB) to identify salient cis-acting elements involved in transcriptional, posttranscriptional, and translational regulation of expression. Full length and truncated RRs of RPL23a paralogs were cloned upstream of a GUS reporter gene and expressed in Arabidopsis transgenic plants. High level expression in mitotically active tissues, driven by RPL23aA and RPL23aB RRs, required TATA-box, telo-box, and site II motif elements. First and second introns were found to play a minor role in posttranscriptional regulation of paralogs, and conserved transcript features (e.g., UTR base composition) may be involved in enhancing translational efficiency. Overall, our results indicate that RPL23a expression is governed by a complex network of multiple regulatory layers.

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Abstract Currently, predictive translation tuning of regulatory elements to the desired output of transcription factor (TF)-based biosensors remains a challenge. The gene expression of a biosensor system must exhibit appropriate translation intensity, which is controlled by the ribosome-binding site (RBS), to achieve fine-tuning of its dynamic range (i.e. fold change in gene expression between the presence and absence of inducer) by adjusting the translation level of the TF and reporter. However, existing TF-based biosensors generally suffer from unpredictable dynamic range. Here, we elucidated the connections and partial mechanisms between RBS, translation level, protein folding and dynamic range, and presented a design platform that predictably tuned the dynamic range of biosensors based on deep learning of large datasets cross-RBSs (cRBSs). In doing so, a library containing 7053 designed cRBSs was divided into five sub-libraries through fluorescence-activated cell sorting to establish a classification model based on convolutional neural network in deep learning. Finally, the present work exhibited a powerful platform to enable predictable translation tuning of RBS to the dynamic range of biosensors.

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Despite regulatory approval of several immune-based treatments for cancer in the past decade, a number of barriers remain to be addressed in order to fully harness the therapeutic potential of the immune system and provide benefits for patients with cancer. As part of the Cancer Moonshot initiative, the Immuno-Oncology Translational Network (IOTN) was established to accelerate the translation of basic discoveries to improve immunotherapy outcomes across the spectrum of adult cancers and to develop immune-based approaches that prevent cancers before they occur. The IOTN currently consists of 32 academic institutions in the USA. By leveraging cutting-edge preclinical research in immunotherapy and immunoprevention, open data and resource sharing, and fostering highly collaborative team science across the immuno-oncology ecosystem, the IOTN is designed to accelerate the generation of novel mechanism-driven immune-based cancer prevention and therapies, and the development of safe and effective personalized immuno-oncology approaches.

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Viruses feature an evolutionary shaped minimal genome that is obligately dependent on the cellular transcription and translation machinery for propagation. To suppress host cell immune responses and ensure efficient replication, viruses employ numerous tactics to favor viral gene expression and protein synthesis. This necessitates a carefully balanced network of virus- and host-encoded components, of which the RNA-based regulatory mechanisms have emerged as particularly interesting albeit insufficiently studied, especially in unicellular organisms such as archaea, bacteria, and yeasts. Here, recent advances that further our understanding of RNA-based translation regulation, mainly through post-transcriptional chemical modification of ribonucleosides, codon usage, and (virus-encoded) transfer RNAs, will be discussed in the context of viral infection.

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Biological networks have evolved through adaptation in uncertain environments. Of the different possible design paradigms, some may offer functional advantages over others. These designs can be quantified by the structure of the network resulting from molecular interactions and the parameter values. One may, therefore, like to identify the design motif present in the evolved network that makes it preferable over other alternatives. In this work, we focus on the regulatory networks characterized by serially arranged processes, which are regulated by multiple feedback loops. Specifically, we consider the tryptophan system present in Escherichia coli , which may be conceptualized as three processes in series, namely transcription, translation and tryptophan synthesis. The multiple feedback loop motif results from three distinct negative feedback loops, namely genetic repression, mRNA attenuation and enzyme inhibition. A framework is introduced to identify the key design components of this network responsible for its physiological performance. We demonstrate that the multiple feedback loop motif, as seen in the tryptophan system, enables robust performance to variations in system parameters while maintaining a rapid response to achieve homeostasis. Superior performance, if arising from a design principle, is intrinsic and, therefore, inherent to any similarly designed system, either natural or engineered. An experimental engineering implementation of the multiple feedback loop design on a two-tank system supports the generality of the robust attributes offered by the design.

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<abstract><p>In this paper, based on a p53 gene regulatory network regulated by Programmed Cell Death 5(PDCD5), a time delay in transcription and translation of Mdm2 gene expression is introduced into the network, the effects of the time delay on oscillation dynamics of p53 are investigated through stability and bifurcation analyses. The local stability of the positive equilibrium in the network is proved through analyzing the characteristic values of the corresponding linearized systems, which give the conditions on undergoing Hopf bifurcation without and with time delay, respectively. The theoretical results are verified through numerical simulations of time series, characteristic values and potential landscapes. Furthermore, combined effect of time delay and several typical parameters in the network on oscillation dynamics of p53 are explored through two-parameter bifurcation diagrams. The results show p53 reaches a lower stable steady state under smaller PDCD5 level, the production rates of p53 and Mdm2 while reaches a higher stable steady state under these larger ones. But the case is the opposite for the degradation rate of p53. Specially, p53 oscillates at a smaller Mdm2 degradation rate, but a larger one makes p53 reach a low stable steady state. Besides, moderate time delay can make the steady state switch from stable to unstable and induce p53 oscillation for moderate value of these parameters. Theses results reveal that time delay has a significant impact on p53 oscillation and may provide a useful insight into developing anti-cancer therapy.</p></abstract>

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Abstract RNA binding proteins (RBPs) frequently regulate the expression of other RBPs in mammalian cells. Such cross-regulation has been proposed to be important to control networks of coordinated gene expression; however, much remains to be understood about how such networks of cross-regulation are established and what the functional consequence is of coordinated or reciprocal expression of RBPs. Here we demonstrate that the RBPs CELF2 and hnRNP C regulate the expression of each other, such that depletion of one results in reduced expression of the other. Specifically, we show that loss of hnRNP C reduces the transcription of CELF2 mRNA, while loss of CELF2 results in decreased efficiency of hnRNP C translation. We further demonstrate that this reciprocal regulation serves to fine tune the splicing patterns of many downstream target genes. Together, this work reveals new activities of hnRNP C and CELF2, provides insight into a previously unrecognized gene regulatory network, and demonstrates how cross-regulation of RBPs functions to shape the cellular transcriptome.

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This paper explores the emerging role of Big Data in environmental governance. We focus on the case of salmon aquaculture management from 2011 to 2017 in Macquarie Harbour, Australia, and compare this with the foundational case that inspired the development of the concept of ‘translation’ in actor-network theory, that of scallop domestication in St Brieuc Bay, France, in the 1970s. A key difference is the salience of environmental data in the contemporary case. Recent dramatic events in the environmental governance of Macquarie Harbour have been driven by increasing spatial and temporal resolution of environmental monitoring, including real-time data collection from sensors mounted on the fish themselves. The resulting environmental data now takes centre stage in increasingly heated debates over how the harbour should be managed: overturning long-held assumptions about environmental interactions, inducing changes in regulatory practices and institutions, fracturing historical alliances and shaping the on-going legitimacy of the industry. Environmental Big Data is now a key actor within the networks that constitute and enact environmental governance. Given its new and unpredictable agency, control over access to data is likely to become critical in future power struggles over environmental resources and their governance.

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Cellular senescence is a complex process characterized by irreversible cell cycle arrest. Senescent cells accumulate with age, promoting disease development, yet the absence of specific markers hampers the development of selective anti-senescence drugs. The integrated stress response (ISR), an evolutionarily highly conserved signaling network activated in response to stress, globally downregulates protein translation while initiating the translation of specific protein sets including transcription factors. We propose that ISR signaling plays a central role in controlling senescence, given that senescence is considered a form of cellular stress. Exploring the intricate relationship between the ISR pathway and cellular senescence, we emphasize its potential as a regulatory mechanism in senescence and cellular metabolism. The ISR emerges as a master regulator of cellular metabolism during stress, activating autophagy and the mitochondrial unfolded protein response, crucial for maintaining mitochondrial quality and efficiency. Our review comprehensively examines ISR molecular mechanisms, focusing on ATF4-interacting partners, ISR modulators, and their impact on senescence-related conditions. By shedding light on the intricate relationship between ISR and cellular senescence, we aim to inspire future research directions and advance the development of targeted anti-senescence therapies based on ISR modulation.

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This commentary integrates historical and modern findings that underpin our understanding of the cell-specific functions of the Tribbles (TRIB) proteins that bear on tumorigenesis. We touch on the initial discovery of roles played by mammalian TRIB proteins in a diverse range of cell-types and pathologies, for example, TRIB1 in regulatory T-cells, TRIB2 in acute myeloid leukaemia and TRIB3 in gliomas; the origins and diversity of TRIB1 transcripts; microRNA-mediated (miRNA) regulation of TRIB1 transcript decay and translation; the substantial conformational changes that ensue on binding of TRIB1 to the transcription factor C/EBPα; and the unique pocket formed by TRIB1 to sequester its C-terminal motif bearing a binding site for the E3 ubiquitin ligase COP1. Unashamedly, the narrative is relayed through the perspective of the Tribbles Research and Innovation Network, and its establishment, progress and future ambitions: the growth of TRIB and COP1 research to hasten discovery of their cell-specific contributions to health and obesity-related cancers.

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Since oxygenic photosynthesis evolved in the common ancestor of cyanobacteria during the Archean, a range of sensing and response strategies evolved to allow efficient acclimation to the fluctuating light conditions experienced in the diverse environments they inhabit. However, how these regulatory mechanisms are assimilated at the molecular level to coordinate individual gene expression is still being elucidated. Here, we demonstrate that integration of a series of three distinct light signals generate an unexpectedly complex network regulating expression of the sole DEAD-box RNA helicase, CrhR, encoded in Synechocystis sp. PCC 6803. The mechanisms function at the transcriptional, translational and post-translation levels, fine-tuning CrhR abundance to permit rapid acclimation to fluctuating light and temperature regimes. CrhR abundance is enhanced 15-fold by low temperature stress. We initially confirmed that the primary mechanism controlling crhR transcript accumulation at 20 °C requires a light quantity-driven reduction of the redox poise in the vicinity of the plastoquinone pool. Once transcribed, a specific light quality cue, a red light signal, was required for crhR translation, far-red reversal of which indicates a phytochrome-mediated mechanism. Examination of CrhR repression at 30 °C revealed that a redox- and light quality-independent light signal was required to initiate CrhR degradation. The crucial role of light was further revealed by the observation that dark conditions superseded the light signals required to initiate each of these regulatory processes. The findings reveal an unexpected complexity of light-dark sensing and signaling that regulate expression of an individual gene in cyanobacteria, an integrated mechanism of environmental perception not previously reported.

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Background and Aims. Histone deacetylase 1 (HDAC1) codes a protein that is a component of the histone deacetylase complex. The abnormal expression of HDAC1 is strongly correlated with cell proliferation, differentiation, transcription, and translation. Through continuous screening of genes associated with changes in lung adenocarcinoma (LUAD), gene networks are formed to explore tumor pathogenesis and new therapeutic targets. Methods. We evaluated HDAC1 gene survival analysis and its expression of LUAD using relevant websites and databases (TCGA and GEO databases). Through data mining, we determined the frequency and type of HDAC1 mutation, obtained the relevant heat map of the gene interaction network, completed the analysis of gene ontology and function enrichment, and understood the pharmaceutic of HDAC1. Results. We found that HDAC1 expression was associated with the prognosis of patients with LUAD. In gene expression analysis, HDAC1 was highly expressed in LUAD, and the HDAC1 interaction gene network (MARCKSL, eIF3I) was closely related to cellular gene expression. Functional network analysis shows that the expression of HDAC1 is related to the monitoring point of the G1-S phase of the cell cycle and the activation of the Notch signaling pathway (CSL transcription factor), which is involved in the process of cell proliferation and differentiation and gene expression associated with new therapeutic targets. Conclusion. Our data revealed the expression and potential regulatory factors of HDAC1 in LUAD of data mining, which laid a foundation for the study of the occurrence, development, and treatment of HDAC1 in LUAD.