Single-cell Ribo-seq reveals cell cycle-dependent translational pausing

The role of polypeptides encoded by ncRNAs in cancer

It was previously thought that ncRNA could not encode polypeptides, but recent reports have challenged this notion. As research into ncRNA progresses, it is increasingly clear that it serves roles beyond traditional mechanisms, playing significant regulatory roles in various diseases, notably cancer, which is responsible for 70% of human deaths. Numerous studies have highlighted the diverse regulatory mechanisms of ncRNA that are pivotal in cancer initiation and progression. The role of ncRNA-encoded polypeptides in cancer regulation has gained prominence. This article explores the newly identified regulatory functions of these polypeptides in three types of ncRNA-lncRNA, pri-miRNA, and circRNA. These polypeptides can interact with proteins, influence signaling pathways, enhance miRNA stability, and regulate cancer progression, malignancy, resistance, and other clinical challenges. Furthermore, we discuss the evolutionary significance of these polypeptides in the transition from RNA to protein, examining their emergence and conservation throughout evolution.

RPFdb v3.0: an enhanced repository for ribosome profiling data and related content

RPFdb (http://www.rpfdb.org or http://sysbio.gzzoc.com/rpfdb/) is a comprehensive repository dedicated to hosting ribosome profiling (Ribo-seq) data and related content. Herein, we present RPFdb v3.0, a significant update featuring expanded data content and improved functionality. Key enhancements include (i) increased data coverage, now encompassing 5018 Ribo-seq datasets and 2343 matched RNA-seq datasets from 496 studies across 34 species; (ii) implementation of translation efficiency, combining Ribo-seq and RNA-seq data to provide gene-specific translation efficiency; (iii) addition of pausing score, facilitating the identification of condition-specific triplet amino acid motifs with enhanced ribosome enrichment; (iv) refinement of open reading frame (ORF) annotation, leveraging RibORF v2.0 for more sensitive detection of actively translated ORFs; (v) introduction of a resource hub, curating advances in translatome sequencing techniques and data analytics tools to support a panoramic overview of the field; and (vi) redesigned web interface, providing intuitive navigation with dedicated pages for streamlined data retrieval, comparison and visualization. These enhancements make RPFdb a more powerful and user-friendly resource for researchers in the field of translatomics. The database is freely accessible and regularly updated to ensure its continued relevance to the scientific community.

Multi-Omic Approaches in Cancer-Related Micropeptide Identification

Despite the advances in modern cancer therapy, malignant diseases are still a leading cause of morbidity and mortality worldwide. Conventional treatment methods frequently lead to side effects and drug resistance in patients, highlighting the need for novel therapeutic approaches. Recent findings have identified the existence of non-canonical micropeptides, an additional layer of the proteome complexity, also called the microproteome. These small peptides are a promising class of therapeutic agents with the potential to address the limitations of current cancer treatments. The microproteome is encoded by regions of the genome historically annotated as non-coding, and its existence has been revealed thanks to recent advances in proteomic and bioinformatic technology, which dramatically improved the understanding of proteome complexity. Micropeptides have been shown to be biologically active in several cancer types, indicating their therapeutic role. Furthermore, they are characterized by low toxicity and high target specificity, demonstrating their potential for the development of better tolerated drugs. In this review, we survey the current landscape of known micropeptides with a role in cancer progression or treatment, discuss their potential as anticancer agents, and describe the methodological challenges facing the proteome field of research.

The crosstalk between metabolism and translation

Metabolism and mRNA translation represent critical steps involved in modulating gene expression and cellular physiology. Being the most energy-consuming process in the cell, mRNA translation is strictly linked to cellular metabolism and in synchrony with it. Indeed, several mRNAs for metabolic pathways are regulated at the translational level, resulting in translation being a coordinator of metabolism. On the other hand, there is a growing appreciation for how metabolism impacts several aspects of RNA biology. For example, metabolic pathways and metabolites directly control the selectivity and efficiency of the translational machinery, as well as post-transcriptional modifications of RNA to fine-tune protein synthesis. Consistently, alterations in the intricate interplay between translational control and cellular metabolism have emerged as a critical axis underlying human diseases. A better understanding of such events will foresee innovative therapeutic strategies in human disease states.

Current limitations in predicting mRNA translation with deep learning models

BACKGROUND

The design of nucleotide sequences with defined properties is a long-standing problem in bioengineering. An important application is protein expression, be it in the context of research or the production of mRNA vaccines. The rate of protein synthesis depends on the 5' untranslated region (5'UTR) of the mRNAs, and recently, deep learning models were proposed to predict the translation output of mRNAs from the 5'UTR sequence. At the same time, large data sets of endogenous and reporter mRNA translation have become available.

RESULTS

In this study, we use complementary data obtained in two different cell types to assess the accuracy and generality of currently available models for predicting translational output. We find that while performing well on the data sets on which they were trained, deep learning models do not generalize well to other data sets, in particular of endogenous mRNAs, which differ in many properties from reporter constructs.

CONCLUSIONS

These differences limit the ability of deep learning models to uncover mechanisms of translation control and to predict the impact of genetic variation. We suggest directions that combine high-throughput measurements and machine learning to unravel mechanisms of translation control and improve construct design.

Unraveling paraquat-induced toxicity on mouse neural stem cells: Dose-response metabolomics insights and identification of sensitive biomarkers for risk assessment

Exposure to pesticide could contribute to neurodevelopmental and neurodegenerative disorders. Notably, research suggests that prenatal or early postnatal exposure to paraquat (PQ), an herbicide, might trigger neurodevelopmental toxicity in neural stem cells (NSCs) via oxidative stress. However, the molecular mechanisms of PQ-induced perturbations in NSCs, particularly at the metabolite level, are not fully understood. Using a dose-response metabolomics approach, we examined metabolic changes in murine NSCs exposed to different PQ doses (0, 10, 20, 40 μM) for 24h. At 20 μM, PQ treatment led to significant metabolic alterations, highlighting unique toxic mechanisms. Metabolic perturbations, mainly affecting amino acid metabolism pathways (e.g., phenylalanine, tyrosine, arginine, tryptophan, and pyrimidine metabolism), were associated with oxidative stress, mitochondrial dysfunction, and cell cycle dysregulation. Dose-response models were used to identify potential biomarkers (e.g., Putrescine, L-arginine, ornithine, L-histidine, N-acetyl-L-phenylalanine, thymidine) reflecting early damage from low-dose PQ exposure. These biomarkers could be used as points of departure (PoD) for characterizing PQ exposure hazard in risk assessment. Our study offers insights into mechanisms and risk assessment related to PQ-induced neurotoxicity in NSCs.

DDX20 is required for cell-cycle reentry of prospermatogonia and establishment of spermatogonial stem cell pool during testicular development in mice

RNA-binding proteins (RBPs), as key regulators of mRNA fate, are abundantly expressed in the testis. However, RBPs associated with human male infertility remain largely unknown. Through bioinformatic analyses, we identified 62 such RBPs, including an evolutionarily conserved RBP, DEAD-box helicase 20 (DDX20). Male germ-cell-specific inactivation of Ddx20 at E15.5 caused T1-propsermatogonia (T1-ProSG) to fail to reenter cell cycle during the first week of testicular development in mice. Consequently, neither the foundational spermatogonial stem cell (SSC) pool nor progenitor spermatogonia were ever formed in the knockout testes. Mechanistically, DDX20 functions to control the translation of its target mRNAs, many of which encode cell-cycle-related regulators, by interacting with key components of the translational machinery in prospermatogonia. Our data demonstrate a previously unreported function of DDX20 as a translational regulator of critical cell-cycle-related genes, which is essential for cell-cycle reentry of T1-ProSG and formation of the SSC pool.

On the evolutionary developmental biology of the cell

Organisms are complex assemblages of cells, cells that produce light, shoot harpoons, and secrete glue. Therefore, identifying the mechanisms that generate novelty at the level of the individual cell is essential for understanding how multicellular life evolves. For decades, the field of evolutionary developmental biology (Evo-Devo) has been developing a framework for connecting genetic variation that arises during embryonic development to the emergence of diverse adult forms. With increasing access to new single cell 'omics technologies and an array of techniques for manipulating gene expression, we can now extend these inquiries inward to the level of the individual cell. In this opinion, I argue that applying an Evo-Devo framework to single cells makes it possible to explore the natural history of cells, where this was once only possible at the organismal level.

Threonine fuels glioblastoma through YRDC-mediated codon-biased translational reprogramming

Cancers commonly reprogram translation and metabolism, but little is known about how these two features coordinate in cancer stem cells. Here we show that glioblastoma stem cells (GSCs) display elevated protein translation. To dissect underlying mechanisms, we performed a CRISPR screen and identified YRDC as the top essential transfer RNA (tRNA) modification enzyme in GSCs. YRDC catalyzes the formation of N6-threonylcarbamoyladenosine (t6A) on ANN-decoding tRNA species (A denotes adenosine, and N denotes any nucleotide). Targeting YRDC reduced t6A formation, suppressed global translation and inhibited tumor growth both in vitro and in vivo. Threonine is an essential substrate of YRDC. Threonine accumulated in GSCs, which facilitated t6A formation through YRDC and shifted the proteome to support mitosis-related genes with ANN codon bias. Dietary threonine restriction (TR) reduced tumor t6A formation, slowed xenograft growth and augmented anti-tumor efficacy of chemotherapy and anti-mitotic therapy, providing a molecular basis for a dietary intervention in cancer treatment.

The Advancement and Application of the Single-Cell Transcriptome in Biological and Medical Research

Single-cell RNA sequencing technology (scRNA-seq) has been steadily developing since its inception in 2009. Unlike bulk RNA-seq, scRNA-seq identifies the heterogeneity of tissue cells and reveals gene expression changes in individual cells at the microscopic level. Here, we review the development of scRNA-seq, which has gone through iterations of reverse transcription, in vitro transcription, smart-seq, drop-seq, 10 × Genomics, and spatial single-cell transcriptome technologies. The technology of 10 × Genomics has been widely applied in medicine and biology, producing rich research results. Furthermore, this review presents a summary of the analytical process for single-cell transcriptome data and its integration with other omics analyses, including genomes, epigenomes, proteomes, and metabolomics. The single-cell transcriptome has a wide range of applications in biology and medicine. This review analyzes the applications of scRNA-seq in cancer, stem cell research, developmental biology, microbiology, and other fields. In essence, scRNA-seq provides a means of elucidating gene expression patterns in single cells, thereby offering a valuable tool for scientific research. Nevertheless, the current single-cell transcriptome technology is still imperfect, and this review identifies its shortcomings and anticipates future developments. The objective of this review is to facilitate a deeper comprehension of scRNA-seq technology and its applications in biological and medical research, as well as to identify avenues for its future development in alignment with practical needs.

Exploiting the metabolic vulnerability of circulating tumour cells

Metastasis has a major part in the severity of disease and lethality of cancer. Circulating tumour cells (CTCs) represent a reservoir of metastatic precursors in circulation, most of which cannot survive due to hostile conditions in the bloodstream. Surviving cells colonise a secondary site based on a combination of physical, metabolic, and oxidative stress protection states required for that environment. Recent advances in CTC isolation methods and high-resolution 'omics technologies are revealing specific metabolic pathways that support this selection of CTCs. In this review, we discuss recent advances in our understanding of CTC biology and discoveries of adaptations in metabolic pathways during their selection. Understanding these traits and delineating mechanisms by which they confer acquired resistance or vulnerability in CTCs is crucial for developing successful prognostic and therapeutic strategies in cancer.

Next generation sequencing technologies to address aberrant mRNA translation in cancer

In this review, we explore the transformative impact of next generation sequencing technologies in the realm of translatomics (the study of how translational machinery acts on a genome-wide scale). Despite the expectation of a direct correlation between mRNA and protein content, the complex regulatory mechanisms that affect this relationship remark the limitations of standard RNA-seq approaches. Then, the review characterizes crucial techniques such as polysome profiling, ribo-seq, trap-seq, proximity-specific ribosome profiling, rnc-seq, tcp-seq, qti-seq and scRibo-seq. All these methods are summarized within the context of cancer research, shedding light on their applications in deciphering aberrant translation in cancer cells. In addition, we encompass databases and bioinformatic tools essential for researchers that want to address translatome analysis in the context of cancer biology.

Single-Cell Sequencing: High-Resolution Analysis of Cellular Heterogeneity in Autoimmune Diseases

Autoimmune diseases (AIDs) are complex in etiology and diverse in classification but clinically show similar symptoms such as joint pain and skin problems. As a result, the diagnosis is challenging, and usually, only broad treatments can be available. Consequently, the clinical responses in patients with different types of AIDs are unsatisfactory. Therefore, it is necessary to conduct more research to figure out the pathogenesis and therapeutic targets of AIDs. This requires research technologies with strong extraction and prediction capabilities. Single-cell sequencing technology analyses the genomic, epigenomic, or transcriptomic information at the single-cell level. It can define different cell types and states in greater detail, further revealing the molecular mechanisms that drive disease progression. These advantages enable cell biology research to achieve an unprecedented resolution and scale, bringing a whole new vision to life science research. In recent years, single-cell technology especially single-cell RNA sequencing (scRNA-seq) has been widely used in various disease research. In this paper, we present the innovations and applications of single-cell sequencing in the medical field and focus on the application contributing to the differential diagnosis and precise treatment of AIDs. Despite some limitations, single-cell sequencing has a wide range of applications in AIDs. We finally present a prospect for the development of single-cell sequencing. These ideas may provide some inspiration for subsequent research.

DNA damage induces p53-independent apoptosis through ribosome stalling

In response to excessive DNA damage, human cells can activate p53 to induce apoptosis. Cells lacking p53 can still undergo apoptosis upon DNA damage, yet the responsible pathways are unknown. We observed that p53-independent apoptosis in response to DNA damage coincided with translation inhibition, which was characterized by ribosome stalling on rare leucine-encoding UUA codons and globally curtailed translation initiation. A genetic screen identified the transfer RNAse SLFN11 and the kinase GCN2 as factors required for UUA stalling and global translation inhibition, respectively. Stalled ribosomes activated a ribotoxic stress signal conveyed by the ribosome sensor ZAKα to the apoptosis machinery. These results provide an explanation for the frequent inactivation of SLFN11 in chemotherapy-unresponsive tumors and highlight ribosome stalling as a signaling event affecting cell fate in response to DNA damage.

Contributions of transcriptional noise to leukaemia evolution: KAT2A as a case-study

Transcriptional noise is proposed to participate in cell fate changes, but contributions to mammalian cell differentiation systems, including cancer, remain associative. Cancer evolution is driven by genetic variability, with modulatory or contributory participation of epigenetic variants. Accumulation of epigenetic variants enhances transcriptional noise, which can facilitate cancer cell fate transitions. Acute myeloid leukaemia (AML) is an aggressive cancer with strong epigenetic dependencies, characterized by blocked differentiation. It constitutes an attractive model to probe links between transcriptional noise and malignant cell fate regulation. Gcn5/KAT2A is a classical epigenetic transcriptional noise regulator. Its loss increases transcriptional noise and modifies cell fates in stem and AML cells. By reviewing the analysis of KAT2A-depleted pre-leukaemia and leukaemia models, I discuss that the net result of transcriptional noise is diversification of cell fates secondary to alternative transcriptional programmes. Cellular diversification can enable or hinder AML progression, respectively, by differentiation of cell types responsive to mutations, or by maladaptation of leukaemia stem cells. KAT2A-dependent noise-responsive genes participate in ribosome biogenesis and KAT2A loss destabilizes translational activity. I discuss putative contributions of perturbed translation to AML biology, and propose KAT2A loss as a model for mechanistic integration of transcriptional and translational control of noise and fate decisions. This article is part of a discussion meeting issue 'Causes and consequences of stochastic processes in development and disease'.

Translational adaptation in breast cancer metastasis and emerging therapeutic opportunities

Breast cancer's tendency to metastasize poses a critical barrier to effective treatment, making it a leading cause of mortality among women worldwide. A growing body of evidence is showing that translational adaptation is emerging as a key mechanism enabling cancer cells to thrive in the dynamic tumor microenvironment (TME). Here, we systematically summarize how breast cancer cells utilize translational adaptation to drive metastasis, highlighting the intricate regulation by specific translation machinery and mRNA attributes such as sequences and structures, along with the involvement of tRNAs and other trans-acting RNAs. We provide an overview of the latest findings and emerging concepts in this area, discussing their potential implications for therapeutic strategies in breast cancer.

Two distinct waves of transcriptome and translatome changes drive Drosophila germline stem cell differentiation

The tight control of fate transitions during stem cell differentiation is essential for proper tissue development and maintenance. However, the challenges in studying sparsely distributed adult stem cells in a systematic manner have hindered efforts to identify how the multilayered regulation of gene expression programs orchestrates stem cell differentiation in vivo. Here, we synchronised Drosophila female germline stem cell (GSC) differentiation in vivo to perform in-depth transcriptome and translatome analyses at high temporal resolution. This characterisation revealed widespread and dynamic changes in mRNA level, promoter usage, exon inclusion, and translation efficiency. Transient expression of the master regulator, Bam, drives a first wave of expression changes, primarily modifying the cell cycle program. Surprisingly, as Bam levels recede, differentiating cells return to a remarkably stem cell-like transcription and translation program, with a few crucial changes feeding into a second phase driving terminal differentiation to form the oocyte. Altogether, these findings reveal that rather than a unidirectional accumulation of changes, the in vivo differentiation of stem cells relies on distinctly regulated and developmentally sequential waves.

Translation machinery: the basis of translational control

Messenger RNA (mRNA) translation consists of initiation, elongation, termination, and ribosome recycling, carried out by the translation machinery, primarily including tRNAs, ribosomes, and translation factors (TrFs). Translational regulators transduce signals of growth and development, as well as biotic and abiotic stresses, to the translation machinery, where global or selective translational control occurs to modulate mRNA translation efficiency (TrE). As the basis of translational control, the translation machinery directly determines the quality and quantity of newly synthesized peptides and, ultimately, the cellular adaption. Thus, regulating the availability of diverse machinery components is reviewed as the central strategy of translational control. We provide classical signaling pathways (e.g., integrated stress responses) and cellular behaviors (e.g., liquid-liquid phase separation) to exemplify this strategy within different physiological contexts, particularly during host-microbe interactions. With new technologies developed, further understanding this strategy will speed up translational medicine and translational agriculture.

Pan-cellular organelles and suborganelles-from common functions to cellular diversity?

Cell diversification is at the base of increasing multicellular organism complexity in phylogeny achieved during ontogeny. However, there are also functions common to all cells, such as cell division, cell migration, translation, endocytosis, exocytosis, etc. Here we revisit the organelles involved in such common functions, reviewing recent evidence of unexpected differences of proteins at these organelles. For instance, centrosomes or mitochondria differ significantly in their protein composition in different, sometimes closely related, cell types. This has relevance for development and disease. Particularly striking is the high amount and diversity of RNA-binding proteins at these and other organelles, which brings us to review the evidence for RNA at different organelles and suborganelles. We include a discussion about (sub)organelles involved in translation, such as the nucleolus and ribosomes, for which unexpected cell type-specific diversity has also been reported. We propose here that the heterogeneity of these organelles and compartments represents a novel mechanism for regulating cell diversity. One reason is that protein functions can be multiplied by their different contributions in distinct organelles, as also exemplified by proteins with moonlighting function. The specialized organelles still perform pan-cellular functions but in a cell type-specific mode, as discussed here for centrosomes, mitochondria, vesicles, and other organelles. These can serve as regulatory hubs for the storage and transport of specific and functionally important regulators. In this way, they can control cell differentiation, plasticity, and survival. We further include examples highlighting the relevance for disease and propose to examine organelles in many more cell types for their possible differences with functional relevance.

Riboformer: a deep learning framework for predicting context-dependent translation dynamics

Translation elongation is essential for maintaining cellular proteostasis, and alterations in the translational landscape are associated with a range of diseases. Ribosome profiling allows detailed measurements of translation at the genome scale. However, it remains unclear how to disentangle biological variations from technical artifacts in these data and identify sequence determinants of translation dysregulation. Here we present Riboformer, a deep learning-based framework for modeling context-dependent changes in translation dynamics. Riboformer leverages the transformer architecture to accurately predict ribosome densities at codon resolution. When trained on an unbiased dataset, Riboformer corrects experimental artifacts in previously unseen datasets, which reveals subtle differences in synonymous codon translation and uncovers a bottleneck in translation elongation. Further, we show that Riboformer can be combined with in silico mutagenesis to identify sequence motifs that contribute to ribosome stalling across various biological contexts, including aging and viral infection. Our tool offers a context-aware and interpretable approach for standardizing ribosome profiling datasets and elucidating the regulatory basis of translation kinetics.

Natural uORF variation in plants

Taking advantage of natural variation promotes our understanding of phenotypic diversity and trait evolution, ultimately accelerating plant breeding, in which the identification of causal variations is critical. To date, sequence variations in the coding region and transcription level polymorphisms caused by variations in the promoter have been prioritized. An upstream open reading frame (uORF) in the 5' untranslated region (5' UTR) regulates gene expression at the post-transcription or translation level. In recent years, studies have demonstrated that natural uORF variations shape phenotypic diversity. This opinion article highlights recent researches and speculates on future directions for natural uORF variation in plants.

Ribosome inactivation regulates translation elongation in neurons

Cellular plasticity is crucial for adapting to ever-changing stimuli. As a result, cells consistently reshape their translatome, and, consequently, their proteome. The control of translational activity has been thoroughly examined at the stage of translation initiation. However, the regulation of ribosome speed in cells is widely unknown. In this study, we utilized a timed ribosome runoff approach, along with proteomics and transmission electron microscopy, to investigate global translation kinetics in cells. We found that ribosome speeds vary among various cell types, such as astrocytes, induced pluripotent human stem cells, human neural stem cells, and human and rat neurons. Of all cell types studied, mature cortical neurons exhibit the highest rate of translation. This finding is particularly remarkable because mature cortical neurons express the eukaryotic elongation factor 2 (eEF2) at lower levels than other cell types. Neurons solve this conundrum by inactivating a fraction of their ribosomes. As a result, the increase in eEF2 levels leads to a reduction of inactive ribosomes and an enhancement of active ones. Processes that alter the demand for active ribosomes, like neuronal excitation, cause increased inactivation of redundant ribosomes in an eEF2-dependent manner. Our data suggest a novel regulatory mechanism in which neurons dynamically inactivate ribosomes to facilitate translational remodeling. These findings have important implications for developmental brain disorders characterized by, among other things, aberrant translation.

Representing and extracting knowledge from single-cell data

Single-cell analysis is currently one of the most high-resolution techniques to study biology. The large complex datasets that have been generated have spurred numerous developments in computational biology, in particular the use of advanced statistics and machine learning. This review attempts to explain the deeper theoretical concepts that underpin current state-of-the-art analysis methods. Single-cell analysis is covered from cell, through instruments, to current and upcoming models. The aim of this review is to spread concepts which are not yet in common use, especially from topology and generative processes, and how new statistical models can be developed to capture more of biology. This opens epistemological questions regarding our ontology and models, and some pointers will be given to how natural language processing (NLP) may help overcome our cognitive limitations for understanding single-cell data.

Advances and opportunities in methods to study protein translation - A review

It is generally believed that the regulation of gene expression involves protein translation occurring before RNA transcription. Therefore, it is crucial to investigate protein translation and its regulation. Recent advancements in biological sciences, particularly in the field of omics, have revolutionized protein translation research. These studies not only help characterize changes in protein translation during specific biological or pathological processes but also have significant implications in disease prevention and treatment. In this review, we summarize the latest methods in ribosome-based translation omics. We specifically focus on the application of fluorescence imaging technology and omics technology in studying overall protein translation. Additionally, we analyze the advantages, disadvantages, and application of these experimental methods, aiming to provide valuable insights and references to researchers studying translation.

Decoding leukemia at the single-cell level: clonal architecture, classification, microenvironment, and drug resistance

Leukemias are refractory hematological malignancies, characterized by marked intrinsic heterogeneity which poses significant obstacles to effective treatment. However, traditional bulk sequencing techniques have not been able to effectively unravel the heterogeneity among individual tumor cells. With the emergence of single-cell sequencing technology, it has bestowed upon us an unprecedented resolution to comprehend the mechanisms underlying leukemogenesis and drug resistance across various levels, including the genome, epigenome, transcriptome and proteome. Here, we provide an overview of the currently prevalent single-cell sequencing technologies and a detailed summary of single-cell studies conducted on leukemia, with a specific focus on four key aspects: (1) leukemia's clonal architecture, (2) frameworks to determine leukemia subtypes, (3) tumor microenvironment (TME) and (4) the drug-resistant mechanisms of leukemia. This review provides a comprehensive summary of current single-cell studies on leukemia and highlights the markers and mechanisms that show promising clinical implications for the diagnosis and treatment of leukemia.

Ribosome profiling: a powerful tool in oncological research

Neoplastic cells need to adapt their gene expression pattern to survive in an ever-changing or unfavorable tumor microenvironment. Protein synthesis (or mRNA translation), an essential part of gene expression, is dysregulated in cancer. The emergence of distinct translatomic technologies has revolutionized oncological studies to elucidate translational regulatory mechanisms. Ribosome profiling can provide adequate information on diverse aspects of translation by aiding in quantitatively analyzing the intensity of translating ribosome-protected fragments. Here, we review the primary currently used translatomics techniques and highlight their advantages and disadvantages as tools for translatomics studies. Subsequently, we clarified the areas in which ribosome profiling could be applied to better understand translational control. Finally, we summarized the latest advances in cancer studies using ribosome profiling to highlight the extensive application of this powerful and promising translatomic tool.

RNA-binding protein Nocte regulates Drosophila development by promoting translation reinitiation on mRNAs with long upstream open reading frames

RNA-binding proteins (RBPs) with intrinsically disordered regions (IDRs) are linked to multiple human disorders, but their mechanisms of action remain unclear. Here, we report that one such protein, Nocte, is essential for Drosophila eye development by regulating a critical gene expression cascade at translational level. Knockout of nocte in flies leads to lethality, and its eye-specific depletion impairs eye size and morphology. Nocte preferentially enhances translation of mRNAs with long upstream open reading frames (uORFs). One of the key Nocte targets, glass mRNA, encodes a transcription factor critical for differentiation of photoreceptor neurons and accessory cells, and re-expression of Glass largely rescued the eye defects caused by Nocte depletion. Mechanistically, Nocte counteracts long uORF-mediated translational suppression by promoting translation reinitiation downstream of the uORF. Nocte interacts with translation factors eIF3 and Rack1 through its BAT2 domain, and a Nocte mutant lacking this domain fails to promote translation of glass mRNA. Notably, de novo mutations of human orthologs of Nocte have been detected in schizophrenia patients. Our data suggest that Nocte family of proteins can promote translation reinitiation to overcome long uORFs-mediated translational suppression, and disruption of this function can lead to developmental defects and neurological disorders.

Translatomics to explore dynamic differences in immunocytes in the tumor microenvironment

Protein is an essential component of all living organisms and is primarily responsible for life activities; furthermore, its synthesis depends on a highly complex and accurate translation system. For proteins, the regulation at the translation level exceeds the sum of that during transcription, mRNA degradation, and protein degradation. Therefore, it is necessary to study regulation at the translation level. Imbalance in the translation process may change the cellular landscape, which not only leads to the occurrence, maintenance, progression, invasion, and metastasis of cancer but also affects the function of immune cells and changes the tumor microenvironment. Detailed analysis of transcriptional and protein atlases is needed to better understand how gene translation occurs. However, a more rigorous direct correlation between mRNA and protein levels is needed, which somewhat limits further studies. Translatomics is a technique for capturing and sequencing ribosome-related mRNAs that can effectively identify translation changes caused by ribosome stagnation and local translation abnormalities during cancer occurrence to further understand the changes in the translation landscape of cancer cells themselves and immune cells in the tumor microenvironment, which can provide new strategies and directions for tumor treatment.

NAT10 Is Involved in Cardiac Remodeling Through ac4C-Mediated Transcriptomic Regulation

BACKGROUND

Heart failure, characterized by cardiac remodeling, is associated with abnormal epigenetic processes and aberrant gene expression. Here, we aimed to elucidate the effects and mechanisms of NAT10 (N-acetyltransferase 10)-mediated N4-acetylcytidine (ac4C) acetylation during cardiac remodeling.

METHODS

NAT10 and ac4C expression were detected in both human and mouse subjects with cardiac remodeling through multiple assays. Subsequently, acetylated RNA immunoprecipitation and sequencing, thiol-linked alkylation for the metabolic sequencing of RNA (SLAM-seq), and ribosome sequencing (Ribo-seq) were employed to elucidate the role of ac4C-modified posttranscriptional regulation in cardiac remodeling. Additionally, functional experiments involving the overexpression or knockdown of NAT10 were conducted in mice models challenged with Ang II (angiotensin II) and transverse aortic constriction.

RESULTS

NAT10 expression and RNA ac4C levels were increased in in vitro and in vivo cardiac remodeling models, as well as in patients with cardiac hypertrophy. Silencing and inhibiting NAT10 attenuated Ang II-induced cardiomyocyte hypertrophy and cardiofibroblast activation. Next-generation sequencing revealed ac4C changes in both mice and humans with cardiac hypertrophy were associated with changes in global mRNA abundance, stability, and translation efficiency. Mechanistically, NAT10 could enhance the stability and translation efficiency of CD47 and ROCK2 transcripts by upregulating their mRNA ac4C modification, thereby resulting in an increase in their protein expression during cardiac remodeling. Furthermore, the administration of Remodelin, a NAT10 inhibitor, has been shown to prevent cardiac functional impairments in mice subjected to transverse aortic constriction by suppressing cardiac fibrosis, hypertrophy, and inflammatory responses, while also regulating the expression levels of CD47 and ROCK2 (Rho associated coiled-coil containing protein kinase 2).

CONCLUSIONS

Therefore, our data suggest that modulating epitranscriptomic processes, such as ac4C acetylation through NAT10, may be a promising therapeutic target against cardiac remodeling.

Human brain organoid model of maternal immune activation identifies radial glia cells as selectively vulnerable

Maternal immune activation (MIA) during critical windows of gestation is correlated with long-term neurodevelopmental deficits in the offspring, including increased risk for autism spectrum disorder (ASD) in humans. Interleukin 6 (IL-6) derived from the gestational parent is one of the major molecular mediators by which MIA alters the developing brain. In this study, we establish a human three-dimensional (3D) in vitro model of MIA by treating induced pluripotent stem cell-derived dorsal forebrain organoids with a constitutively active form of IL-6, Hyper-IL-6. We validate our model by showing that dorsal forebrain organoids express the molecular machinery necessary for responding to Hyper-IL-6 and activate STAT signaling upon Hyper-IL-6 treatment. RNA sequencing analysis reveals the upregulation of major histocompatibility complex class I (MHCI) genes in response to Hyper-IL-6 exposure, which have been implicated with ASD. We find a small increase in the proportion of radial glia cells after Hyper-IL-6 treatment through immunohistochemistry and single-cell RNA-sequencing. We further show that radial glia cells are the cell type with the highest number of differentially expressed genes, and Hyper-IL-6 treatment leads to the downregulation of genes related to protein translation in line with a mouse model of MIA. Additionally, we identify differentially expressed genes not found in mouse models of MIA, which might drive species-specific responses to MIA. Finally, we show abnormal cortical layering as a long-term consequence of Hyper-IL-6 treatment. In summary, we establish a human 3D model of MIA, which can be used to study the cellular and molecular mechanisms underlying the increased risk for developing disorders such as ASD.

Recent advances and future prospects in direct cardiac reprogramming

Cardiovascular disease remains a leading cause of death worldwide despite important advances in modern medical and surgical therapies. As human adult cardiomyocytes have limited regenerative ability, cardiomyocytes lost after myocardial infarction are replaced by fibrotic scar tissue, leading to cardiac dysfunction and heart failure. To replace lost cardiomyocytes, a promising approach is direct cardiac reprogramming, in which cardiac fibroblasts are transdifferentiated into induced cardiomyocyte-like cells (iCMs). Here we review cardiac reprogramming cocktails (including transcription factors, microRNAs and small molecules) that mediate iCM generation. We also highlight mechanistic studies exploring the barriers to and facilitators of this process. We then review recent progress in iCM reprogramming, with a focus on single-cell '-omics' research. Finally, we discuss obstacles to clinical application.

The role of dysregulated mRNA translation machinery in cancer pathogenesis and therapeutic value of ribosome-inactivating proteins

Dysregulated protein synthesis is a hallmark of tumors. mRNA translation reprogramming contributes to tumorigenesis, which is fueled by abnormalities in ribosome formation, tRNA abundance and modification, and translation factors. Not only malignant cells but also stromal cells within tumor microenvironment can undergo transformation toward tumorigenic phenotypes during translational reprogramming. Ribosome-inactivating proteins (RIPs) have garnered interests for their ability to selectively inhibit protein synthesis and suppress tumor growth. This review summarizes the role of dysregulated translation machinery in tumor development and explores the potential of RIPs in cancer treatment.

Streamlined and sensitive mono- and di-ribosome profiling in yeast and human cells

Ribosome profiling has unveiled diverse regulation and perturbations of translation through a transcriptome-wide survey of ribosome occupancy, read out by sequencing of ribosome-protected messenger RNA fragments. Generation of ribosome footprints and their conversion into sequencing libraries is technically demanding and sensitive to biases that distort the representation of physiological ribosome occupancy. We address these challenges by producing ribosome footprints with P1 nuclease rather than RNase I and replacing RNA ligation with ordered two-template relay, a single-tube protocol for sequencing library preparation that incorporates adaptors by reverse transcription. Our streamlined approach reduced sequence bias and enhanced enrichment of ribosome footprints relative to ribosomal RNA. Furthermore, P1 nuclease preserved distinct juxtaposed ribosome complexes informative about yeast and human ribosome fates during translation initiation, stalling and termination. Our optimized methods for mRNA footprint generation and capture provide a richer translatome profile with low input and fewer technical challenges.

Is there a localized role for translational quality control?

It is known that mRNAs and the machinery that translates them are not uniformly distributed throughout the cytoplasm. As a result, the expression of some genes is localized to particular parts of the cell and this makes it possible to carry out important activities, such as growth and signaling, in three-dimensional space. However, the functions of localized gene expression are not fully understood, and the underlying mechanisms that enable localized expression have not been determined in many cases. One consideration that could help in addressing these challenges is the role of quality control (QC) mechanisms that monitor translating ribosomes. On a global level, QC pathways are critical for detecting aberrant translation events, such as a ribosome that stalls while translating, and responding by activating stress pathways and resolving problematic ribosomes and mRNAs at the molecular level. However, it is unclear how these pathways, even when uniformly active throughout the cell, affect local translation. Importantly, some QC pathways have themselves been reported to be enriched in the proximity of particular organelles, but the extent of such localized activity remains largely unknown. Here, we describe the major QC pathways and review studies that have begun to explore their roles in localized translation. Given the limited data in this area, we also pose broad questions about the possibilities and limitations for how QC pathways could facilitate localized gene expression in the cell with the goal of offering ideas for future experimentation.

Omics Views of Mechanisms for Cell Fate Determination in Early Mammalian Development

During mammalian preimplantation development, a totipotent zygote undergoes several cell cleavages and two rounds of cell fate determination, ultimately forming a mature blastocyst. Along with compaction, the establishment of apicobasal cell polarity breaks the symmetry of an embryo and guides subsequent cell fate choice. Although the lineage segregation of the inner cell mass (ICM) and trophectoderm (TE) is the first symbol of cell differentiation, several molecules have been shown to bias the early cell fate through their inter-cellular variations at much earlier stages, including the 2- and 4-cell stages. The underlying mechanisms of early cell fate determination have long been an important research topic. In this review, we summarize the molecular events that occur during early embryogenesis, as well as the current understanding of their regulatory roles in cell fate decisions. Moreover, as powerful tools for early embryogenesis research, single-cell omics techniques have been applied to both mouse and human preimplantation embryos and have contributed to the discovery of cell fate regulators. Here, we summarize their applications in the research of preimplantation embryos, and provide new insights and perspectives on cell fate regulation.

The sporophyte-to-gametophyte transition: The haploid generation comes of age

Flowering plants alternate between two multicellular generations: the diploid sporophyte and haploid gametophyte. Despite its small size, the gametophyte has significant impacts on plant genetics, evolution, and breeding. Each male pollen grain and female embryo sac is a multicellular organism with independent gene expression, a functioning metabolism, and specialized cell types. In this review, we describe recent progress in understanding the process in which the haploid genome takes over expression from its diploid parent - the sporophyte-to-gametophyte transition. The focus is on pollen, but similar concepts may also apply to the female gametophyte. Technological advances in single-cell genomics offer the opportunity to characterize haploid gene expression in unprecedented detail, positioning the field to make rapid progress.

Development of nanoRibo-seq enables study of regulated translation by cortical neuron subtypes, showing uORF translation in synaptic-axonal genes

Investigation of translation in rare cell types or subcellular contexts is challenging due to large input requirements for standard approaches. Here, we present "nanoRibo-seq" an optimized approach using 102- to 103-fold less input material than bulk approaches. nanoRibo-seq exhibits rigorous quality control features consistent with quantification of ribosome protected fragments with as few as 1,000 cells. We compare translatomes of two closely related cortical neuron subtypes, callosal projection neurons (CPN) and subcerebral projection neurons (SCPN), during their early postnatal development. We find that, while translational efficiency is highly correlated between CPN and SCPN, several dozen mRNAs are differentially translated. We further examine upstream open reading frame (uORF) translation and identify that mRNAs involved in synapse organization and axon development are highly enriched for uORF translation in both subtypes. nanoRibo-seq enables investigation of translational regulation of rare cell types in vivo and offers a flexible approach for globally quantifying translation from limited input material.

The molecular evolution of mammalian spermatogenesis

The testis is a key male reproductive organ that produces gametes through the process of spermatogenesis. Testis morphologies, sperm phenotypes, and the process of spermatogenesis evolve rapidly in mammals, presumably due to the evolutionary pressure on males to give rise to their own offspring. Here, we review studies illuminating the molecular evolution of the testis, in particular large-scale transcriptomic studies, which were based on bulk tissue samples and, more recently, individual cells. Together with various genomic and epigenomic data, these studies have unveiled the cellular source, molecular mechanisms, and evolutionary forces that underlie the rapid phenotypic evolution of the testis. They also revealed shared (ancestral) and species-specific spermatogenic gene expression programs. The insights and available data that have accumulated also provide a valuable resource for the investigation and treatment of male fertility disorders - a dramatically increasing problem in modern industrial societies.

Mapping RNA translation

A new method maps the location of thousands of translating RNAs in cells and tissues.

Spatially resolved single-cell translatomics at molecular resolution

The precise control of messenger RNA (mRNA) translation is a crucial step in posttranscriptional gene regulation of cellular physiology. However, it remains a challenge to systematically study mRNA translation at the transcriptomic scale with spatial and single-cell resolution. Here, we report the development of ribosome-bound mRNA mapping (RIBOmap), a highly multiplexed three-dimensional in situ profiling method to detect cellular translatome. RIBOmap profiling of 981 genes in HeLa cells revealed cell cycle-dependent translational control and colocalized translation of functional gene modules. We mapped 5413 genes in mouse brain tissues, yielding spatially resolved single-cell translatomic profiles for 119,173 cells and revealing cell type-specific and brain region-specific translational regulation, including translation remodeling during oligodendrocyte maturation. Our method detected widespread patterns of localized translation in neuronal and glial cells in intact brain tissue networks.

Single-cell quantification of ribosome occupancy in early mouse development

Translation regulation is critical for early mammalian embryonic development¹. However, previous studies had been restricted to bulk measurements², precluding precise determination of translation regulation including allele-specific analyses. Here, to address this challenge, we developed a novel microfluidic isotachophoresis (ITP) approach, named RIBOsome profiling via ITP (Ribo-ITP), and characterized translation in single oocytes and embryos during early mouse development. We identified differential translation efficiency as a key mechanism regulating genes involved in centrosome organization and N⁶-methyladenosine modification of RNAs. Our high-coverage measurements enabled, to our knowledge, the first analysis of allele-specific ribosome engagement in early development. These led to the discovery of stage-specific differential engagement of zygotic RNAs with ribosomes and reduced translation efficiency of transcripts exhibiting allele-biased expression. By integrating our measurements with proteomics data, we discovered that ribosome occupancy in germinal vesicle-stage oocytes is the predominant determinant of protein abundance in the zygote. The Ribo-ITP approach will enable numerous applications by providing high-coverage and high-resolution ribosome occupancy measurements from ultra-low input samples including single cells.

Microproteins: Overlooked regulators of physiology and disease

Ongoing efforts to generate a complete and accurate annotation of the genome have revealed a significant blind spot for small proteins (<100 amino acids) originating from short open reading frames (sORFs). The recent discovery of numerous sORF-encoded proteins, termed microproteins, that play diverse roles in critical cellular processes has ignited the field of microprotein biology. Large-scale efforts are currently underway to identify sORF-encoded microproteins in diverse cell-types and tissues and specialized methods and tools have been developed to aid in their discovery, validation, and functional characterization. Microproteins that have been identified thus far play important roles in fundamental processes including ion transport, oxidative phosphorylation, and stress signaling. In this review, we discuss the optimized tools available for microprotein discovery and validation, summarize the biological functions of numerous microproteins, outline the promise for developing microproteins as therapeutic targets, and look forward to the future of the field of microprotein biology.

Applications of single-cell RNA sequencing in drug discovery and development

Single-cell technologies, particularly single-cell RNA sequencing (scRNA-seq) methods, together with associated computational tools and the growing availability of public data resources, are transforming drug discovery and development. New opportunities are emerging in target identification owing to improved disease understanding through cell subtyping, and highly multiplexed functional genomics screens incorporating scRNA-seq are enhancing target credentialling and prioritization. ScRNA-seq is also aiding the selection of relevant preclinical disease models and providing new insights into drug mechanisms of action. In clinical development, scRNA-seq can inform decision-making via improved biomarker identification for patient stratification and more precise monitoring of drug response and disease progression. Here, we illustrate how scRNA-seq methods are being applied in key steps in drug discovery and development, and discuss ongoing challenges for their implementation in the pharmaceutical industry.

Apicobasal RNA asymmetries regulate cell fate in the early mouse embryo

The spatial sorting of RNA transcripts is fundamental for the refinement of gene expression to distinct subcellular regions. Although, in non-mammalian early embryogenesis, differential RNA localisation presages cell fate determination, in mammals it remains unclear. Here, we uncover apical-to-basal RNA asymmetries in outer blastomeres of 16-cell stage mouse preimplantation embryos. Basally directed RNA transport is facilitated in a microtubule- and lysosome-mediated manner. Yet, despite an increased accumulation of RNA transcripts in basal regions, higher translation activity occurs at the more dispersed apical RNA foci, demonstrated by spatial heterogeneities in RNA subtypes, RNA-organelle interactions and translation events. During the transition to the 32-cell stage, the biased inheritance of RNA transcripts, coupled with differential translation capacity, regulates cell fate allocation of trophectoderm and cells destined to form the pluripotent inner cell mass. Our study identifies a paradigm for the spatiotemporal regulation of post-transcriptional gene expression governing mammalian preimplantation embryogenesis and cell fate.

Riboformer: A Deep Learning Framework for Predicting Context-Dependent Translation Dynamics

Translation elongation is essential for maintaining cellular proteostasis, and alterations in the translational landscape are associated with a range of diseases. Ribosome profiling allows detailed measurement of translation at genome scale. However, it remains unclear how to disentangle biological variations from technical artifacts and identify sequence determinant of translation dysregulation. Here we present Riboformer, a deep learning-based framework for modeling context-dependent changes in translation dynamics. Riboformer leverages the transformer architecture to accurately predict ribosome densities at codon resolution. It corrects experimental artifacts in previously unseen datasets, reveals subtle differences in synonymous codon translation and uncovers a bottleneck in protein synthesis. Further, we show that Riboformer can be combined with in silico mutagenesis analysis to identify sequence motifs that contribute to ribosome stalling across various biological contexts, including aging and viral infection. Our tool offers a context-aware and interpretable approach for standardizing ribosome profiling datasets and elucidating the regulatory basis of translation kinetics.

Aging microglia

Microglia are the tissue-resident macrophage population of the brain, specialized in supporting the CNS environment and protecting it from endogenous and exogenous insults. Nonetheless, their function declines with age, in ways that remain to be fully elucidated. Given the critical role played by microglia in neurodegenerative diseases, a better understanding of the aging microglia phenotype is an essential prerequisite in designing better preventive and therapeutic strategies. In this review, we discuss the most recent literature on microglia in aging, comparing findings in rodent models and human subjects.

Minimal upstream open reading frame of Per2 mediates phase fitness of the circadian clock to day/night physiological body temperature rhythm

Body temperature in homeothermic animals does not remain constant but displays a regular circadian fluctuation within a physiological range (e.g., 35°C-38.5°C in mice), constituting a fundamental systemic signal to harmonize circadian clock-regulated physiology. Here, we find the minimal upstream open reading frame (uORF) encoded by the 5' UTR of the mammalian core clock gene Per2 and reveal its role as a regulatory module for temperature-dependent circadian clock entrainment. A temperature shift within the physiological range does not affect transcription but instead increases translation of Per2 through its minimal uORF. Genetic ablation of the Per2 minimal uORF and inhibition of phosphoinositide-3-kinase, lying upstream of temperature-dependent Per2 protein synthesis, perturb the entrainment of cells to simulated body temperature cycles. At the organismal level, Per2 minimal uORF mutant skin shows delayed wound healing, indicating that uORF-mediated Per2 modulation is crucial for optimal tissue homeostasis. Combined with transcriptional regulation, Per2 minimal uORF-mediated translation may enhance the fitness of circadian physiology.

On the gain of entrainment in the n-dimensional ribosome flow model

The ribosome flow model (RFM) is a phenomenological model for the flow of particles along a one-dimensional chain of n sites. It has been extensively used to study ribosome flow along the mRNA molecule during translation. When the transition rates along the chain are time-varying and jointly T-periodic the RFM entrains, i.e. every trajectory of the RFM converges to a unique T-periodic solution that depends on the transition rates, but not on the initial condition. In general, entrainment to periodic excitations like the 24 h solar day or the 50 Hz frequency of the electric grid is important in numerous natural and artificial systems. An interesting question, called the gain of entrainment (GOE) in the RFM, is whether proper coordination of the periodic translation rates along the mRNA can lead to a larger average protein production rate. Analysing the GOE in the RFM is non-trivial and partial results exist only for the RFM with dimensions n = 1, 2. We use a new approach to derive several results on the GOE in the general n-dimensional RFM. Perhaps surprisingly, we rigorously characterize several cases where there is no GOE, so to maximize the average production rate in these cases, the best choice is to use constant transition rates all along the chain.

Ribosome biogenesis in disease: new players and therapeutic targets

The ribosome is a multi-unit complex that translates mRNA into protein. Ribosome biogenesis is the process that generates ribosomes and plays an essential role in cell proliferation, differentiation, apoptosis, development, and transformation. The mTORC1, Myc, and noncoding RNA signaling pathways are the primary mediators that work jointly with RNA polymerases and ribosome proteins to control ribosome biogenesis and protein synthesis. Activation of mTORC1 is required for normal fetal growth and development and tissue regeneration after birth. Myc is implicated in cancer development by enhancing RNA Pol II activity, leading to uncontrolled cancer cell growth. The deregulation of noncoding RNAs such as microRNAs, long noncoding RNAs, and circular RNAs is involved in developing blood, neurodegenerative diseases, and atherosclerosis. We review the similarities and differences between eukaryotic and bacterial ribosomes and the molecular mechanism of ribosome-targeting antibiotics and bacterial resistance. We also review the most recent findings of ribosome dysfunction in COVID-19 and other conditions and discuss the consequences of ribosome frameshifting, ribosome-stalling, and ribosome-collision. We summarize the role of ribosome biogenesis in the development of various diseases. Furthermore, we review the current clinical trials, prospective vaccines for COVID-19, and therapies targeting ribosome biogenesis in cancer, cardiovascular disease, aging, and neurodegenerative disease.