From canonical to modified nucleotides: balancing translation and metabolism

A role for a Trypanosoma brucei cytosine RNA methyltransferase homolog in ribosomal RNA processing

In Trypanosoma brucei, gene expression is primarily regulated posttranscriptionally making RNA metabolism critical. T. brucei has an epitranscriptome containing modified RNA bases. Yet, the identity of the enzymes catalyzing modified RNA base addition and the functions of the enzymes and modifications remain unclear. Homology searches indicate the presence of numerous T. brucei cytosine RNA methyltransferase homologs. One such homolog, TbNop2 was studied in detail. TbNop2 contains the six highly conserved motifs found in cytosine RNA methyltransferases and is evolutionarily related to the Nop2 protein family required for rRNA modification and processing. RNAi experiments targeting TbNop2 resulted in reduced levels of TbNop2 RNA and protein, and a cessation of parasite growth. Next generation sequencing of bisulfite-treated RNA (BS-seq) detected the presence of two methylation sites in the large rRNA; yet TbNop2 RNAi did not result in a significant reduction of methylation. However, TbNop2 RNAi resulted in the retention of 28S internal transcribed spacer RNAs, indicating a role for TbNop2 in rRNA processing.

Prognostic value of comprehensive typing based on m6A and gene cluster in TNBC

BACKGROUND

Triple-negative breast cancer (TNBC) is resistant to targeted therapy with HER2 monoclonal antibodies and endocrine therapy, because it lacks the estrogen receptor (ER), progesterone receptor (PR), and human epidermal growth factor receptor 2 (HER2). TNBC is a subtype of breast cancer with the worst prognosis and the highest mortality rate compared to other subtypes. N6-methyladenosine (m6A) modification is significant in cancer and metastasis, because it can alter gene expression and function at numerous levels, such as RNA splicing, stability, translocation, and translation. There are limited investigations into the connection between TNBC and m6A.

MATERIALS AND METHODS

Breast cancer-related data were retrieved from the Cancer Genome Atlas (TCGA) database, and 116 triple-negative breast cancer cases were identified from the data. The GSE31519 data set, which included 68 cases of TNBC, was obtained from the Gene Expression Omnibus (GEO) database. Survival analysis was used to determine the prognosis of distinct m6A types based on their m6A group, gene group, and m6A score. To investigate the potential mechanism, GO and KEGG analyses were performed on the differentially expressed genes.

RESULTS

The expression of m6A-related genes and their impact on prognosis in TNBC patients were studied. According to the findings, m6A was crucial in determining the prognosis of TNBC patients, and the major m6A-linked genes in this process were YTHDF2, RBM15B, IGFBP3, and WTAP. YTHDF2, RBM15B and IGFBP3 are associated with poor prognosis, while WTAP is associated with good prognosis. By cluster analysis, the gene cluster and the m6A cluster were beneficial in predicting the prognosis of TNBC patients. The m6A score based on m6A and gene clusters was more effective in predicting the prognosis of TNBC patients. Furthermore, the tumor microenvironment may play an important role in the process of m6A, influencing TNBC prognosis.

CONCLUSIONS

N6-adenylic acid methylation (m6A) was important in altering the prognosis of TNBC patients, and the key m6A-associated genes in this process were YTHDF2, RBM15B, IGFBP3, and WTAP. Furthermore, the comprehensive typing based on m6A and gene clusters was useful in predicting TNBC patients' prognosis, showing potential as valuable evaluating tools for TNBC.

Prognostic value of comprehensive typing based on m6A and gene cluster.. [DOI: 10.21203/rs.3.rs-1922311/v1] [Citation(s) in RCA: 0] [Impact Index Per Article: 0]

Background Triple-negative breast cancer (TNBC) is resistant to targeted therapy with HER2 monoclonal antibodies and endocrine therapy because it lacks the estrogen receptor (ER), progesterone receptor (PR), and human epidermal growth factor receptor 2 (HER2). TNBC is a subtype of breast cancer with the worst prognosis and the highest mortality rate compared to other subtypes. N6-methyladenosine (m6A) modification is significant in cancer and metastasis because it can alter gene expression and function at numerous levels, such as RNA splicing, stability, translocation, and translation. There has been limited investigation into the connection between TNBC and m6A. Materials and Methods Breast cancer-related data were retrieved from the Cancer Genome Atlas (TCGA) database, and 116 triple-negative breast cancer cases were identified from the data. The GSE31519 dataset, which included 68 cases of TNBC, was obtained from the Gene Expression Omnibus (GEO) database. Survival analysis was used to determine the prognosis of distinct m6A types based on their m6A group, gene group, and m6A score. To investigate the potential mechanism, GO and KEGG analyses were performed on the differentially expressed genes. Results The expression of m6A-related genes and their impact on prognosis in TNBC patients were studied. According to the findings, m6A was crucial in determining the prognosis of TNBC patients, and the major m6A-linked genes in this process were YTHDF2, RBM15B, IGFBP3, and WTAP. By cluster analysis, the gene cluster and the m6A cluster were beneficial in predicting the prognosis of TNBC patients. The m6A score based on m6A and gene clusters was more effective in predicting the prognosis of TNBC patients. Furthermore, the tumor microenvironment may play an important role in the process of m6A, influencing TNBC prognosis. Conclusion N6-adenylic acid methylation (m6A) was important in altering the prognosis of TNBC patients, and the key m6A-associated genes in this process were YTHDF2, RBM15B, IGFBP3, and WTAP. Furthermore, the comprehensive typing based on m6A and gene clusters was useful in predicting TNBC patients' prognosis, showing potential as a meaningful evaluating tools for TNBC.

Role of SSD1 in Phenotypic Variation of Saccharomyces cerevisiae Strains Lacking DEG1-Dependent Pseudouridylation

Yeast phenotypes associated with the lack of wobble uridine (U₃₄) modifications in tRNA were shown to be modulated by an allelic variation of SSD1, a gene encoding an mRNA-binding protein. We demonstrate that phenotypes caused by the loss of Deg1-dependent tRNA pseudouridylation are similarly affected by SSD1 allelic status. Temperature sensitivity and protein aggregation are elevated in deg1 mutants and further increased in the presence of the ssd1-d allele, which encodes a truncated form of Ssd1. In addition, chronological lifespan is reduced in a deg1 ssd1-d mutant, and the negative genetic interactions of the U₃₄ modifier genes ELP3 and URM1 with DEG1 are aggravated by ssd1-d. A loss of function mutation in SSD1, ELP3, and DEG1 induces pleiotropic and overlapping phenotypes, including sensitivity against target of rapamycin (TOR) inhibitor drug and cell wall stress by calcofluor white. Additivity in ssd1 deg1 double mutant phenotypes suggests independent roles of Ssd1 and tRNA modifications in TOR signaling and cell wall integrity. However, other tRNA modification defects cause growth and drug sensitivity phenotypes, which are not further intensified in tandem with ssd1-d. Thus, we observed a modification-specific rather than general effect of SSD1 status on phenotypic variation in tRNA modification mutants. Our results highlight how the cellular consequences of tRNA modification loss can be influenced by protein targeting specific mRNAs.

Locating chemical modifications in RNA sequences through ribonucleases and LC-MS based analysis

Knowledge of the structural information is essential for understanding the functional details of modified RNA. Cellular non-coding RNA such as rRNA, tRNA and even viral RNAs contain a number of post-transcriptional modifications with varied degree of diversity and density. In this chapter, we discuss the use of a combination of biochemical and analytical tools such as ribonucleases and liquid chromatography coupled with mass spectrometry approaches for characterization of modified RNA. We present the protocols and alternate strategies for obtaining confident modified sequence information to facilitate the understanding of function.

RNA immunoprecipitation to identify in vivo targets of RNA editing and modifying enzymes

The past decade has seen an exponential increase in the identification of individual nucleobases that undergo base conversion and/or modification in transcriptomes. While the enzymes that catalyze these types of changes have been identified, the global interactome of these modifiers is still largely unknown. Furthermore, in some instances, redundancy among a family of enzymes leads to an inability to pinpoint the protein responsible for modifying a given transcript merely from high-throughput sequencing data. This chapter focuses on a method for global identification of transcripts recognized by an RNA modification/editing enzyme via capture of the RNAs that are bound in vivo, a method referred as RNA immunoprecipitation (RIP). We provide a guide of the major issues to consider when designing a RIP experiment, a detailed experimental protocol as well as troubleshooting advice. The RIP protocol presented here can be readily applied to any organism or cell line of interest as well as both RNA modification enzymes and RNA-binding proteins (RBPs) that regulate RNA modification levels. As mentioned at the end of the protocol, the RIP assay can be coupled to high-throughput sequencing to globally identify bound targets. For more quantitative investigations, such as how binding of an RNA modification enzyme/regulator to a given target changes during development/in specific tissues or assessing how the presence or absence of RNA modification affects transcript recognition by a particular RBP (irrespective of a role for the RBP in modulating modification levels); the RIP assay should be coupled to quantitative real-time PCR (qRT-PCR).