RIVET: comprehensive graphic user interface for analysis and exploration of genome-wide translatomics data

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.

Ribosomal RNA 2'-O-methylation dynamics impact cell fate decisions

Translational regulation impacts both pluripotency maintenance and cell differentiation. To what degree the ribosome exerts control over this process remains unanswered. Accumulating evidence has demonstrated heterogeneity in ribosome composition in various organisms. 2'-O-methylation (2'-O-me) of rRNA represents an important source of heterogeneity, where site-specific alteration of methylation levels can modulate translation. Here, we examine changes in rRNA 2'-O-me during mouse brain development and tri-lineage differentiation of human embryonic stem cells (hESCs). We find distinct alterations between brain regions, as well as clear dynamics during cortex development and germ layer differentiation. We identify a methylation site impacting neuronal differentiation. Modulation of its methylation levels affects ribosome association of the fragile X mental retardation protein (FMRP) and is accompanied by an altered translation of WNT pathway-related mRNAs. Together, these data identify ribosome heterogeneity through rRNA 2'-O-me during early development and differentiation and suggest a direct role for ribosomes in regulating translation during cell fate acquisition.

Breast cancer cell mesenchymal transition and metastasis directed by DAP5/eIF3d-mediated selective mRNA translation

Cancer cell plasticity enables cell survival in harsh physiological environments and fate transitions such as the epithelial-to-mesenchymal transition (EMT) that underlies invasion and metastasis. Using genome-wide transcriptomic and translatomic studies, an alternate mechanism of cap-dependent mRNA translation by the DAP5/eIF3d complex is shown to be essential for metastasis, EMT, and tumor directed angiogenesis. DAP5/eIF3d carries out selective translation of mRNAs encoding EMT transcription factors and regulators, cell migration integrins, metalloproteinases, and cell survival and angiogenesis factors. DAP5 is overexpressed in metastatic human breast cancers associated with poor metastasis-free survival. In human and murine breast cancer animal models, DAP5 is not required for primary tumor growth but is essential for EMT, cell migration, invasion, metastasis, angiogenesis, and resistance to anoikis. Thus, cancer cell mRNA translation involves two cap-dependent mRNA translation mechanisms, eIF4E/mTORC1 and DAP5/eIF3d. These findings highlight a surprising level of plasticity in mRNA translation during cancer progression and metastasis.

H/ACA snRNP-dependent ribosome biogenesis regulates translation of polyglutamine proteins

Stem cells in many systems, including Drosophila germline stem cells (GSCs), increase ribosome biogenesis and translation during terminal differentiation. Here, we show that the H/ACA small nuclear ribonucleoprotein (snRNP) complex that promotes pseudouridylation of ribosomal RNA (rRNA) and ribosome biogenesis is required for oocyte specification. Reducing ribosome levels during differentiation decreased the translation of a subset of messenger RNAs that are enriched for CAG trinucleotide repeats and encode polyglutamine-containing proteins, including differentiation factors such as RNA-binding Fox protein 1. Moreover, ribosomes were enriched at CAG repeats within transcripts during oogenesis. Increasing target of rapamycin (TOR) activity to elevate ribosome levels in H/ACA snRNP complex-depleted germlines suppressed the GSC differentiation defects, whereas germlines treated with the TOR inhibitor rapamycin had reduced levels of polyglutamine-containing proteins. Thus, ribosome biogenesis and ribosome levels can control stem cell differentiation via selective translation of CAG repeat-containing transcripts.

Translational regulation of TFH cell differentiation and autoimmune pathogenesis

Little is known regarding T cell translational regulation. We demonstrate that T follicular helper (TFH) cells use a previously unknown mechanism of selective messenger RNA (mRNA) translation for their differentiation, role in B cell maturation, and in autoimmune pathogenesis. We show that TFH cells have much higher levels of translation factor eIF4E than non-TFH CD4+ T cells, which is essential for translation of TFH cell fate-specification mRNAs. Genome-wide translation studies indicate that modest down-regulation of eIF4E activity by a small-molecule inhibitor or short hairpin RN impairs TFH cell development and function. In mice, down-regulation of eIF4E activity specifically reduces TFH cells among T helper subtypes, germinal centers, B cell recruitment, and antibody production. In experimental autoimmune encephalomyelitis, eIF4E activity down-regulation blocks TFH cell participation in disease pathogenesis while promoting rapid remission and spinal cord remyelination. TFH cell development and its role in autoimmune pathogenesis involve selective mRNA translation that is highly druggable.

An eIF3d-dependent switch regulates HCMV replication by remodeling the infected cell translation landscape to mimic chronic ER stress

Regulated loading of eIF3-bound 40S ribosomes on capped mRNA is generally dependent upon the translation initiation factor eIF4E; however, mRNA translation often proceeds during physiological stress, such as virus infection, when eIF4E availability and activity are limiting. It remains poorly understood how translation of virus and host mRNAs are regulated during infection stress. While initially sensitive to mTOR inhibition, which limits eIF4E-dependent translation, we show that protein synthesis in human cytomegalovirus (HCMV)-infected cells unexpectedly becomes progressively reliant upon eIF3d. Targeting eIF3d selectively inhibits HCMV replication, reduces polyribosome abundance, and interferes with expression of essential virus genes and a host gene expression signature indicative of chronic ER stress that fosters HCMV reproduction. This reveals a strategy whereby cellular eIF3d-dependent protein production is hijacked to exploit virus-induced ER stress. Moreover, it establishes how switching between eIF4E and eIF3d-responsive cap-dependent translation can differentially tune virus and host gene expression in infected cells.

Instead of eIF4E-regulated ribosome loading, Thompson et al. show capped mRNA translation in HCMV-infected cells becomes reliant upon eIF3d. Depleting eIF3d inhibits HCMV replication, reduces polyribosomes, and restricts virus late gene and host chronic ER stress-induced gene expression. Thus, switching to eIF3d-responsive translation tunes gene expression to support virus replication.

Regulation of translation by site-specific ribosomal RNA methylation

Ribosomes are complex ribozymes that interpret genetic information by translating messenger RNA (mRNA) into proteins. Natural variation in ribosome composition has been documented in several organisms and can arise from several different sources. A key question is whether specific control over ribosome heterogeneity represents a mechanism by which translation can be regulated. We used RiboMeth-seq to demonstrate that differential 2'-O-methylation of ribosomal RNA (rRNA) represents a considerable source of ribosome heterogeneity in human cells, and that modification levels at distinct sites can change dynamically in response to upstream signaling pathways, such as MYC oncogene expression. Ablation of one prominent methylation resulted in altered translation of select mRNAs and corresponding changes in cellular phenotypes. Thus, differential rRNA 2'-O-methylation can give rise to ribosomes with specialized function. This suggests a broader mechanism where the specific regulation of rRNA modification patterns fine tunes translation.

Targeting eIF4F translation initiation complex with SBI-756 sensitises B lymphoma cells to venetoclax

BACKGROUND

The BCL2 inhibitor venetoclax has shown efficacy in several hematologic malignancies, with the greatest response rates in indolent blood cancers such as chronic lymphocytic leukaemia. There is a lower response rate to venetoclax monotherapy in diffuse large B-cell lymphoma (DLBCL).

METHODS

We tested inhibitors of cap-dependent mRNA translation for the ability to sensitise DLBCL and mantle cell lymphoma (MCL) cells to apoptosis by venetoclax. We compared the mTOR kinase inhibitor (TOR-KI) MLN0128 with SBI-756, a compound targeting eukaryotic translation initiation factor 4G1 (eIF4G1), a scaffolding protein in the eIF4F complex.

RESULTS

Treatment of DLBCL and MCL cells with SBI-756 synergised with venetoclax to induce apoptosis in vitro, and enhanced venetoclax efficacy in vivo. SBI-756 prevented eIF4E-eIF4G1 association and cap-dependent translation without affecting mTOR substrate phosphorylation. In TOR-KI-resistant DLBCL cells lacking eIF4E binding protein-1, SBI-756 still sensitised to venetoclax. SBI-756 selectively reduced translation of mRNAs encoding ribosomal proteins and translation factors, leading to a reduction in protein synthesis rates in sensitive cells. When normal lymphocytes were treated with SBI-756, only B cells had reduced viability, and this correlated with reduced protein synthesis.

CONCLUSIONS

Our data highlight a novel combination for treatment of aggressive lymphomas, and establishes its efficacy and selectivity using preclinical models.

Intron retention and its impact on gene expression and protein diversity: A review and a practical guide

Intron retention (IR) occurs when a complete and unspliced intron remains in mature mRNA. An increasing body of literature has demonstrated a major role for IR in numerous biological functions, including several that impact human health and disease. Although experimental technologies used to study other forms of mRNA splicing can also be used to investigate IR, a specialized downstream computational analysis is optimal for IR discovery and analysis. Here we provide a review of IR and its biological implications, as well as a practical guide for how to detect and analyze it. Several methods, including long read third generation direct RNA sequencing, are described. We have developed an R package, FakIR, to facilitate the execution of the bioinformatic tasks recommended in this review and a tutorial on how to fit them to users aims. Additionally, we provide guidelines and experimental protocols to validate IR discovery and to evaluate the potential impact of IR on gene expression and protein output. This article is categorized under: RNA Evolution and Genomics > Computational Analyses of RNA RNA Processing > Splicing Regulation/Alternative Splicing RNA Methods > RNA Analyses in vitro and In Silico.

Shiny-DEG: A Web Application to Analyze and Visualize Differentially Expressed Genes in RNA-seq

RNA-seq analysis has become one of the most widely used methods for biological and medical experiments, aiming to identify differentially expressed genes at a large scale. However, due to lack of programming skills and statistical background, it is difficult for biologists including faculty and students to fully understand what the RNA-seq results are and how to interpret them. In recent years, even though, there are several programs or websites that assist researchers to analyze and visualize NGS results, they have several limitations. Therefore, Shiny-DEG, a web application that facilitates the exploration and visualization of differentially expressed genes from RNA-seq, was developed. It integrates multi-factor design experiments, allows users to modify the parameters interactively according to experiments purpose and all analysis results can be downloaded directly, aiming to further assisting the interpretation and explanation of the biological questions. Therefore, it serves better for biologists without programming skills. Overall, this project is of great significance to reveal the mechanism of transcriptome differences.

Computational methods for ribosome profiling data analysis

Since the introduction of the ribosome profiling technique in 2009 its popularity has greatly increased. It is widely used for the comprehensive assessment of gene expression and for studying the mechanisms of regulation at the translational level. As the number of ribosome profiling datasets being produced continues to grow, so too does the need for reliable software that can provide answers to the biological questions it can address. This review describes the computational methods and tools that have been developed to analyze ribosome profiling data at the different stages of the process. It starts with initial routine processing of raw data and follows with more specific tasks such as the identification of translated open reading frames, differential gene expression analysis, or evaluation of local or global codon decoding rates. The review pinpoints challenges associated with each step and explains the ways in which they are currently addressed. In addition it provides a comprehensive, albeit incomplete, list of publicly available software applicable to each step, which may be a beneficial starting point to those unexposed to ribosome profiling analysis. The outline of current challenges in ribosome profiling data analysis may inspire computational biologists to search for novel, potentially superior, solutions that will improve and expand the bioinformatician's toolbox for ribosome profiling data analysis. This article is characterized under: Translation > Ribosome Structure/Function RNA Evolution and Genomics > Computational Analyses of RNA Translation > Translation Mechanisms Translation > Translation Regulation.