Methylation Of Ribonucleic Acid Research Articles

METTL3-mediated HPV vaccine enhances the effect of anti PD-1 immunotherapy to alleviate the development of cutaneous squamous cell carcinoma

BackgroundCutaneous squamous cell carcinoma (cSCC) develops from epithelial keratinocytes by dysregulation of self-renewal and differentiation. Recent studies have found that the size and number of cSCC tumors gradually decrease or even disappear after HPV vaccination. However, the role of the HPV vaccine in the cSCC mechanism is poorly understood. ObjectiveThe aim of this study is to investigate the effect and mechanism of the HPV vaccine in cSCC. MethodsImmunofluorescence was used to study the immune infiltrating cells in the tumor tissues of patients with cSCC. The effects of the HPV vaccine on cSCC cells and tissues were studied by Cell Culture, Real-time PCR, Western Blot, Cytotoxicity Assay, Enzyme-linked Immunosorbent Assay, m6A Blotting, CCK-8 Assay, m6A Ribonucleic acid Methylation Quantification and tumor transplantation. ResultsThe HPV vaccine enhanced the toxic effect of CD8+T cells on cSCC cells and promoted the secretion of multiple cytokines by CD8+T cells. In addition, HPV vaccines can increase tumor sensitivity to anti-PD-1 therapy by downregulating METTL3 in tumor tissue, with the combination of HPV vaccine and PD-1 monoclonal antibodies producing enhanced immune cell infiltration compared to PD-1 blockade alone. Study limitationsIt is important to note the limitations of this study, including the small sample size, the construction of the mouse model, and the choice of HPV vaccine and PD-1 monoclonal antibody, which may limit the generalization of our findings to a wider population. ConclusionsIt is hoped that this research will contribute to a deeper understanding of the role of the HPV vaccine in the treatment of cSCC. HPV vaccine is expected to become an important approach to alleviate the development of cSCC.

Non-SMC condensin I complex subunit D2 (NCAPD2) reveals its prognostic and immunologic features in human cancers.

Non-SMC condensin I complex subunit D2 (NCAPD2) is overexpressed in some malignant tumors. However, there are few studies on the function of NCAPD2 in pan-cancer. We used the Cancer Genome Atlas (TCGA), Genotype-Tissue Expression (GTEx), Human Protein Atlas (HPA), and UALCAN to analyze NCAPD2 expression and promoter methylation levels in 33 tumors and normal samples. We performed immunohistochemistry (IHC) on liver cancer and corresponding normal tissues to examine NCAPD2 protein expression in LIHC. Kaplan-Meier survival and univariate regression analyses were performed to explore the pan-cancer clinical significance of NCAPD2. Moreover, correlative analysis between NCAPD2 expression and clinical characteristics, immune cell infiltration, immune checkpoints, immune regulators, tumor mutation burden (TMB), microsatellite instability (MSI), ribonucleic acid (RNA) methylation regulators, and drug sensitivity was conducted using data from TCGA. We also investigated the effects of NCAPD2 expression on immunotherapy efficacy and prognosis. Gene set enrichment analysis (GSEA) was conducted using NCAPD2. Bioinformatic analysis showed that NCAPD2 was overexpressed in most tumors and correlated with the clinical characteristics of some cancers. IHC results demonstrated that NCAPD2 protein expression was higher in LIHC than in normal liver. NCAPD2 expression was linked with T stage, clinical stage, and histologic grade in LIHC. Overexpression of NCAPD2 resulted in poor overall survival, and disease-specific survival in adrenocortical carcinoma, kidney renal papillary cell carcinoma, brain lower grade glioma, liver hepatocellular carcinoma, lung adenocarcinoma, mesothelioma, pancreatic adenocarcinoma, sarcoma, skin cutaneous melanoma, and uterine corpus endometrial carcinoma. NCAPD2 was considered an independent biomarker by Cox regression in LIHC. The time ROC curve demonstrated that the survival rate of 1-, 3-, and 5-year OS and DSS in LIHC was above 0.6. The expression of NCAPD2 was significantly correlated with immune cell infiltration, immune checkpoints, TMB, MSI, and RNA methylation regulators in several tumors. NCAPD2 had a high predictive value for immunotherapy efficiency in certain tumors. In our study, drugs sensitive to NCAPD2 protein were screened by sensitivity analysis. GSEA analysis showed that NCAPD2 mainly participated in the G2M checkpoint, mitotic spindle, and KRAS-signaling. NCAPD2 may act as a prognostic molecular marker in most cancers.

Development and validation of an m6A RNA methylation regulator-based signature for the prediction of prognosis and immunotherapy in cutaneous melanoma.

Development and validation of an m6A RNA methylation regulator-based signature for the prediction of prognosis and immunotherapy in cutaneous melanoma.

M6A RNA Methylation Decreases Atherosclerotic Vulnerable Plaque Through Inducing T Cells.

Knockdown of fat mass and obesity-associated gene (FTO) can induce N6-methyladenosine (m6A) ribonucleic acid (RNA) methylation. The objective of this study was to explore the effect of m 6A RNA methylation on atherosclerotic vulnerable plaque by FTO knockdown. A total of 50 New Zealand white rabbits were randomly divided into pure high-fat group, sham operation group, vulnerable plaque group, empty load group, and FTO knockdown group (10 rabbits/group). Flow cytometry showed that helper T (Th) cells in the FTO knockdown group accounted for a significantly higher proportion of lymphocytes than in the vulnerable plaque group and empty load group (P<0.05). Th cells were screened by cell flow. The level of m6A RNA methylation in the FTO knockdown group was significantly higher than in the vulnerable plaque group and empty load group (P<0.05). The levels of total cholesterol, triglyceride, and low-density lipoprotein C were higher at the 12th week than at the 1st week, but the high-density lipoprotein C level was lower at the 12th week than at the 1st week. At the 12th week, the interleukin-7 level was significantly lower in the adeno-associated virus-9 (AVV9)-FTO short hairpin RNA group than in the control and AVV9-green fluorescent protein groups (P<0.001). After successfully establishing a vascular parkinsonism rabbit model, m6A RNA methylation can decrease Th cells and vulnerable atherosclerotic plaques.

Molecular Characterization and Clinical Characteristics of m5C-Based RNA Methylation in Spinal Cord Injury: Validated by qPCR.

Aberrant patterns of 5-methylcytosine (m5C)-based ribonucleic acid (RNA) methylation have critical roles in various human diseases, but their importance in spinal cord injury (SCI) is largely unknown. We explore the expression patterns and potential roles of m5C-based regulators of RNA modification after SCI. We analyzed 16 m5C-based regulators of RNA modification in tissues with SCI and normal rats from the Gene Expression Omnibus database. We constructed a "gene signature" of m5C-based regulators of RNA modification to predict the prognosis of SCI using least absolute shrinkage and selection operator regression and random-forest strategy. We found that the m5C-related genes, deoxyribonucleic acid (DNA) methyltransferase1 (Dnmt1), methyl-CpG binding domain protein 2 (Mbd2), ubiquitin-like with PHD and ring finger domains 1 (Uhrf1), uracil-N-glycosylase (Ung), and zinc finger and BTB(brica-brac, tramtrack, and broad) domain containing 38 (Zbtb38) had high expression, and zinc finger and BTB domain containing 4 (Zbtb4) had low expression in SCI. Analysis of the correlation between the gene sets of m5C-based regulators of RNA modification and immune-cell infiltration and immune response revealed Dnmt1, DNA methyltransferases 3A (Dnmt3a), Mbd2, and Ung to be positive regulators of the immune microenvironment, and Zbtb4 may negatively regulate the immune environment. Then, two molecular subtypes were identified based on 16 m5C-regulated genes. Functional-enrichment analysis of differentially expressed genes between different patterns of m5C-based modification was undertaken. Through the creation of a protein-protein interaction network, we screened 11 hub genes. We demonstrated their importance between SCI group and sham group using real-time reverse transcription-quantitative polymerase chain reaction in rat model. Expression of hub genes did not correlate with mitophagy but was positively correlated with endoplasmic reticulum stress (ERS), which suggested that there may be differences in ERS between different patterns of m5C-based modification. This present study explored and discovered the close link between m5C regulators-related genes and SCI. We also hope our findings may contribute to further mechanistic and therapeutic research on the role of key m5C regulators after SCI.

Dynamic regulation and key roles of ribonucleic acid methylation.

Ribonucleic acid (RNA) methylation is the most abundant modification in biological systems, accounting for 60% of all RNA modifications, and affects multiple aspects of RNA (including mRNAs, tRNAs, rRNAs, microRNAs, and long non-coding RNAs). Dysregulation of RNA methylation causes many developmental diseases through various mechanisms mediated by N 6-methyladenosine (m6A), 5-methylcytosine (m5C), N 1-methyladenosine (m1A), 5-hydroxymethylcytosine (hm5C), and pseudouridine (Ψ). The emerging tools of RNA methylation can be used as diagnostic, preventive, and therapeutic markers. Here, we review the accumulated discoveries to date regarding the biological function and dynamic regulation of RNA methylation/modification, as well as the most popularly used techniques applied for profiling RNA epitranscriptome, to provide new ideas for growth and development.

Construction and validation of a m6A RNA methylation and ferroptosis-related prognostic model for pancreatic cancer by integrated bioinformatics analysis.

Both N6-methyladenosine (m6A) ribonucleic acid (RNA) methylation and ferroptosis regulators are demonstrated to have significant effects on the malignant clinicopathological characteristics of pancreatic adenocarcinoma (PAAD) patients. However, the currently available clinical indexes are not sufficient to predict precise prognostic outcomes pf PAAD patients accurately. This study aims to examine the clinicopathologic features of m6A RNA methylation and ferroptosis regulators in predicting the outcomes of different types of cancer. As the foundation for this research, the differentially expressed genes (DEGs) between PAAD tissues and adjacent normal tissues were first identified. Next, dimensional reduction analysis (DCA) based on m6A RNA methylation regulators and ferroptosis regulators were performed and DEGs between good/poor prognosis PAAD patient clusters were identified. DEGs were then screened by Cox analysis, and finally a risk signature was established by least absolute shrinkage and selection operator (LASSO) analyses. The prediction model based on risk score was further evaluated by a validation set from Gene Expression Omnibus (GEO) database. In total, 4 m6A RNA methylation regulator genes and 29 ferroptosis regulator genes were found to have close causal relationships with the prognosis of PAAD, and a risk score with 3 m6A methylation regulators (i.e., IGF2BP2, IGF2BP3, and METTL16) and 4 ferroptosis regulators (i.e., ENPP2, ATP6V1G2, ITGB4, and PROM2) was constructed and showed to be highly involved in PAAD progression and could serve as effective markers for prognosis with AUC value equaled 0.753 in training set and 0.803 in validation set. The combined prediction model, composed of seven regulators of m6A methylation and ferroptosis, in this study more effectively reflects the progression and prognosis of PAAD than previous single genome or epigenetic analysis. Our study provides a broader perspective for the subsequent establishment of prognostic models and the patients may benefit from more precision management.

A brief review of machine learning methods for RNA methylation sites prediction.

Thanks to the tremendous advancement of deep sequencing and large-scale profiling, epitranscriptomics has become a rapidly growing field. As one of the most important parts of epitranscriptomics, ribonucleic acid (RNA) methylation has been focused on for years for its fundamental role in regulating the many aspects of RNA function. Thanks to the big data generated in sequencing, machine learning methods have been developed for efficiently identifying methylation sites. In this review, we comprehensively explore machine learning based approaches for predicting 10 types of methylation of RNA, which include m6A, m5C, m7G, 5hmC, m1A, m5U, m6Am, and so on. Firstly, we reviewed three main aspects of machine learning which are data, features and learning algorithms. Then, we summarized all the methods that have been used to predict the 10 types of methylation. Furthermore, the emergent methods which were designed to predict multiple types of methylation were also reviewed. Finally, we discussed the future perspectives for RNA methylation sites prediction.

Potential Impact of N6-Methyladenosine RNA Methylation on Vision Function and the Pathological Processes of Ocular Diseases: New Discoveries and Future Perspectives

N6-methyladenosine (m6A) methylation/modification plays a critical role in various biological processes through post-transcriptional ribonucleic acid (RNA) modification, which involves RNA processing, nuclear export, translation and decay. Functionally, m6A modification may be involved in ocular cell growth and differentiation, stem cell identity, development, haemostasis and innate versus adaptive immunity. Aberrations in m6A methylation may mediate numerous pathological conditions in the eye, including microorganism infection, inflammation, autoimmune disease, senescence, degeneration, epithelial-mesenchymal transition, fibrosis, angiogenesis, tumorigenesis and complex eye diseases. In this review, we have discussed the relevance of m6A modification to precision medicine, stem cell directional differentiation, biomarkers of eye diseases and m6A methylation activators and inhibitors. In addition, we summarised the challenges and future research directions in the field related to visual function and eye diseases.

Wavelength-resolved photoelectrochemical biosensor triggered by cascade signal amplification reactions for RNA methylation analysis on a single interface

Among ribonucleic acid (RNA) methylation modifications, those of m6A and m5C are the two most abundant forms, and the bias of m6A and m5C modification levels plays an essential role in many biological processes. Therefore, constructing a mechanism that can simultaneously analyze the two modifications would be potentially very significant. Herein, we propose a wavelength-resolved photoelectrochemical (PEC) biosensor based on cascade signal amplification reactions for m6A-RNA and m5C-RNA analysis on a single interface. First, a target sequence was transformed with antibody-functionalized magnetic beads to obtain the initial sequences, triggering the 3D DNA nanomachine to transform and amplify targets by generating many output sequences. Subsequently, the output sequences were combined with rolling-circle-amplification (RCA) primer scaffolds, and then a DNA origami structure was formed based on RCA. A DNA origami could immobilize many photoelectrochemical mediators to amplify photocurrent responses. As expected, the proposed PEC biosensor exhibited excellent analytical performances for both m6A-RNA and m5C-RNA. The detection limits were as low as 1.96 fM and 7.37 pM, respectively. The successful fabrication of the PEC biosensor opened new possibilities for epigenetic research and the diagnosis and treatment of methylation-related diseases.

Modification of STIM2 by m6A RNA methylation inhibits metastasis of cholangiocarcinoma.

BackgroundN6-methyladenosine (m6A) is the most frequent internal methylation of eukaryotic RNA (ribonucleic acid) transcripts and plays an important function in RNA processing. The current research aimed to investigate the role of m6A-STIM2 axis in cholangiocarcinoma (CCA) progression.MethodsThe expression of STIM2 (Stromal Interaction Molecule 2) in CCA was measured using quantitative polymerase chain reaction (PCR) and immunohistochemistry (IHC). STIM2 was examined in vivo for its effects on the malignant phenotypes of CCA cells. The m6A modification of STIM2 was assessed through MeRIP (methylated RNA Immunoprecipitation)-PCR.ResultsBased on the GEPIA (Gene Expression Profiling Interactive Analysis) 2 database findings, a low STIM2 mRNA (messenger RNA) level was related to a poor prognosis in individuals with CCA. Quantitative PCR and IHC assays indicated decreased protein satin in CCA tissues and were associated with extrahepatic metastasis. Vianude mice tail vein injection model indicated that increased STIM2 levels suppressed CCA cell metastasis in vivo, while KRT8 (keratin 8) was detected as the direct downstream target of STIM2-mediated CCA cell metastasis in vivo. Meanwhile, based on SRAMP database and MeRIP assays indicated that m6A alteration resulted in abnormal STIM2 expression in CCA via METTL14 and YTHDC2.ConclusionsOur findings revealed the epi-transcriptomic dysregulation in CCA and metastasis by proposing a complicated STIM2-KRT8 regulatory paradigm based on m6A alteration.

Identification of an eight-m6A RNA methylation regulator prognostic signature of uterine corpus endometrial carcinoma based on bioinformatics analysis.

N6-methyladenosine (m6A) methylation is proved to play a significant role in human cancers. This study aimed to explore the association between m6A ribonucleic acid (RNA) methylation regulators and uterine corpus endometrial carcinoma (UCEC), and build a prognostic signature of m6A regulators for UCEC.RNA-seq transcriptome data and clinicopathological data of UCEC were downloaded from the Cancer Genome Atlas database. We compared the expression of 23 m6A-regulators in tumor tissues and nontumor tissues. Then we classified the data into 3 clusters by consensus clustering analysis. Several regulators were picked out as the prognostic signature of patients with UCEC based on least absolute shrinkage and selection operator Cox regression analysis. Additionally, we established a predictive nomogram to calculate survival times. Finally, we used receiver operating characteristic curve, univariate Cox regression analysis, and multivariate Cox regression analysis to further verify the prognostic value of the risk signature consisting of m6A regulators.The expression of 18/23 m6A regulators was significantly different in UCEC compared with normal samples. Gene ontology functional analysis of these regulators revealed that they were mainly participated in RNA splicing, stabilization, modification, and degradation. LRPPRC, IGFBP2, KIAA1429, IGFBP3, FMR1, YTHDF1, METTL14, and YTHDF2 were selected to construct the risk signature and predictive nomogram. The results of receiver operating characteristic curve, univariate Cox regression analysis, and multivariate Cox regression analysis for the risk signature showed a good predictive performance for UCEC.The risk signature of 8-m6A regulators has potential prognostic value for patients with UCEC.

Determination of five nucleosides by LC-MS/MS and the application of the method to quantify N6 -methyladenosine level in liver messenger ribonucleic acid of an acetaminophen-induced hepatotoxicity mouse model.

Ribonucleic acid N6 -methyladenosine methylation plays an important role in a variety of biological processes and diseases. Acetaminophen-induced hepatotoxicity is one of the major challenges faced by clinicians. To date, the link between N6 -methyladenosine and acetaminophen-induced hepatotoxicity has not been studied. In this study, a simple ultra high performance liquid chromatography with tandem mass spectrometry method was developed for the simultaneous determination of five nucleosides (adenosine, uridine, cytidine, guanosine, and N6 -methyladenosine) in messenger ribonucleic acid. After enzymatic digestion of messenger ribonucleic acid, the nucleosides sample was separated on an Acquity UPLC column with gradient elution using methanol and 0.02% formic acid water, and detected by a Qtrap 4500 mass spectrometer with an electrospray ionization mode. The method was validated over the concentration ranges of 4-800ng/mL for adenosine, uridine, cytidine, and guanosine and 0.1-20ng/mL for N6 -methyladenosine. It was successfully applied to the determination of N6 -methyladenosine levels in liver messenger ribonucleic acid in an acetaminophen-induced hepatotoxicity mouse model and a control group. This study offers a method for the determination of nucleoside contents in epigenetic studies and constitutes the first step toward the investigation of ribonucleic acid methylation in acetaminophen-induced hepatotoxicity, which will facilitate the elucidation of its mechanism.

DRUM: Inference of Disease-Associated m6A RNA Methylation Sites From a Multi-Layer Heterogeneous Network.

Recent studies have revealed that the RNA N6-methyladenosine (m6A) modification plays a critical role in a variety of biological processes and associated with multiple diseases including cancers. Till this day, transcriptome-wide m6A RNA methylation sites have been identified by high-throughput sequencing technique combined with computational methods, and the information is publicly available in a few bioinformatics databases; however, the association between individual m6A sites and various diseases are still largely unknown. There are yet computational approaches developed for investigating potential association between individual m6A sites and diseases, which represents a major challenge in the epitranscriptome analysis. Thus, to infer the disease-related m6A sites, we implemented a novel multi-layer heterogeneous network-based approach, which incorporates the associations among diseases, genes and m6A RNA methylation sites from gene expression, RNA methylation and disease similarities data with the Random Walk with Restart (RWR) algorithm. To evaluate the performance of the proposed approach, a ten-fold cross validation is performed, in which our approach achieved a reasonable good performance (overall AUC: 0.827, average AUC 0.867), higher than a hypergeometric test-based approach (overall AUC: 0.7333 and average AUC: 0.723) and a random predictor (overall AUC: 0.550 and average AUC: 0.486). Additionally, we show that a number of predicted cancer-associated m6A sites are supported by existing literatures, suggesting that the proposed approach can effectively uncover the underlying epitranscriptome circuits of disease mechanisms. An online database DRUM, which stands for disease-associated ribonucleic acid methylation, was built to support the query of disease-associated RNA m6A methylation sites, and is freely available at: www.xjtlu.edu.cn/biologicalsciences/drum.

RNA methylation and diseases: experimental results, databases, Web servers and computational models.

Ribonucleic acid (RNA) methylation is a type of posttranscriptional modifications occurring in all kingdoms of life. It is strongly related to important biological process, thus making it linked to a number of human diseases. Owing to the development of high-throughput sequencing technology, plenty of achievement had been obtained in RNA methylation research recently. Meanwhile, various computational models have been developed to analyze and mining increasing RNA methylation data. In this review, we first made a brief introduction about eight types of most popular RNA methylation, the biological functions of RNA methylation, the relationship between RNA methylation and disease and five important RNA methylation-related diseases. The research of RNA methylation is based on sequencing data processing, and effective bioinformatics techniques can benefit better understanding of RNA methylation. We further introduced seven publicly available RNA methylation-related databases, and some important publicly available RNA-methylation-related Web servers and software for RNA methylation site identification, differential analysis and so on. Furthermore, we provided detailed analysis of the state-of-the-art computational models used in these Web servers and software. We also analyzed the limitations of these models and discussed the future directions of developing computational models for RNA methylation research.

N 6-methyladenosine inhibits murine erythroleukemia cell maturation by blocking methylation of RNA and memory via conversion to S-(N 6-methyl)-adenosylhomocysteine

We have shown earlier that N 6-methyladenosine (N 6mAdo) and other methylated derivatives block commitment of murine erythroleukemia (MEL) cells to terminal erythroid maturation. In this study, we further investigated the mechanism of this blockade. Treatment of MEL cells with N 6mAdo inhibited cell growth, prevented accumulation of committed cells, suppressed methylation of total cytoplasmic RNA, and erased the expression of “memory” response, an event that precedes initiation of commitment. Furthermore, N 6mAdo increased the level of S-adenosylmethionine (SAM) and S-adenosylhomocysteine (SAH) and altered the SAH SAM ratio that influences methylation of ribonucleic acid (RNA). Moreover, analysis of the intracellular extracts revealed that N 6-mAdo is converted into S-(N 6-methyl)-adenosylhomocysteine (N 6-SAH) in MEL cells, an active intermediate that affects methylation of RNA. Therefore, we conclude that N 6-mAdo prevents induction of MEL cell differentiation by affecting methylation of critical RNA transcripts involved in expression of “memory” and initiation of commitment. It is likely that this inhibition occurs via conversion of N 6mAdo into N 6-SAH.

Methylation of ribonucleic acid in a cell-free system from mouse myeloma cells.

Isolated nuclei incorporate few methyl groups into RNA when they are incubated with S-adenosyl[methyl-3H3]methionine and four ribotriphosphates. When the nuclei were supplemented with a soluble total cell protein extract, the incorporation of methyl groups into RNA was stimulated 3-6-fold. All classes of RNA were methylated. Methylation of the 2'-OH of ribose and the bases of ribosomal RNA occurred predominantly on endogenous ribosomal RNA precursors, with a minority (20%) occurring on the newly synthesized rRNA precursor. Methylation of the tRNA precursor occurred on both endogenous (40%) and newly synthesized (60%) molecules. The methylation of adenosine in hnRNA occurred predominantly on molecules transcribed in vitro and was sensitive to 1 microgram/mL alpha-amanitin. A final site of methylation was the 7 position of guanosine of the cap structure. About 10% of the RNA polymerase II transcripts were capped in vitro. Capping was blocked 90% by 1 microgram/mL alpha-amanitin and was independent of the presence of the cell protein extract.

Nucleic acids and alkylating agents: Carbon-13 magnetic resonance studies of the methylation of ribonucleic acid with methyl methanesulfonate

Direct examination of the interaction of ribonucleic acid with the alkylating agent, methyl methanesulfonate, by carbon-13 magnetic resonance spectroscopy has demonstrated the potential usefulness of this new spectroscopic method in studying the interaction between nucleic acids and biologically active agents. By comparison with the model compounds isolated from the reactions of mononucleotides with methyl methanesulfonate, five methylated products, 7-methylguanosine (49.7%), 1-methyladenosine (21.2%), 3-methyl cytosine (12.7%), 1-methylguanosine (7.5%), and methyl phosphate (8.9%, tentative) have been identified in the alkylated RNA from the reaction without buffer, whose pH is maintained using a pH stat; three methylated products, 7-methylguanosine (61.1%), 1-methyladenosine (20.5%), and 3-methylcytosine (18.4%) have been identified from the reaction in phosphate buffer. These quantitative differences may account for the failure of previous structure-activity correlations. The limits of the biological interpretation of the present and previous chemical results are discussed.

Ribonucleic acid synthesis in normal and immune macrophages after antigenic stimulus

Macrophage ribonucleic acid (RNA) synthesis is an important metabolic process intimately related to the function of these cells. Mouse peritoneal macrophage RNA was extracted with phenol in the presence of bentonite and electrophoresed on composite agarose-polyacrylamide gels. The pulse-chase technique was used to follow the precursor relationships in macrophage ribosomal RNA (rRNA) maturation. The rRNA species at 18S and 28S appeared at 15 and 45 min, respectively, after RNA synthesis was halted. Their appearance corresponded closely to decreases in the rRNA precursors at 45S, 36S, and 34S. Studies of RNA methylation aided in confirming the identity of these ribosomal species. Unmethylated RNA species appeared as messenger RNA between 5S and 15S, and at about 55S probably represented heterodisperse nuclear RNA. When normal macrophages were incubated with heat-killed Salmonella enteritidis, an acceleration in the maturation of RNA was observed. The accelerated maturation was indicated by the earlier appearance of 28S rRNA and the more rapid development of an equilibrium state, where further labeling did not change the RNA profile. In macrophage RNA from mice immunized with S. enteritidis, rRNA species appeared rapidly but did not accumulate to the same extent as observed for normal macrophages. Precursor rRNA and other RNA species developed as usual, suggesting specific degradation of mature rRNA. Such rRNA wastage could indicate a mechanism controlling ribosome assembly in the non-proliferating activated macrophage. The pattern of RNA synthesis in immune macrophages was essentially unchanged by the presence of heat-killed S. enteritidis in vitro.

Effects of estradiol on uterine ribonucleic acid metabolism. Assessment of transfer ribonucleic acid methylation.

Immature rats treated with estradiol for selected periods of time demonstrated both increased methylation of uterine transfer ribonucleic acid (tRNA) and methylase activities. Whereas the former parameter was assessed by incubating whole uteri with [methyl-14C]methionine and measuring the incorporation of isotope into the tRNA, methylase activity was obtained by measuring the rate of incorporation of methyl groups from S-adenosyl[methyl-14C]methionine into heterologous tRNA (Escherichia coli B) in the presence of uterine cytosol preparations (100,000g supernatants). Although increased methylation of tRNA during the estrogen response was demonstrated, additional studies indicated that these results were largely attributable to an increased rate of synthesis of tRNA rather than gross changes in either the type or amount of methylated constituents present. Evidence in this regard included the inability of estrogen treatment of alter significantly the (a) resulting patterns of methyl-14C-methylated constituents of uterine tRNA, (b) the extent ot which [2-14C]guanine residues, incorporated into tRNA, become methylated, (c) the extent of methylation of precursor tRNA in the absence of tRNA synthesis, and (d) the types of methylase activities expressed in vitro.