microRNAs Mediated Regulation of the Ribosomal Proteins and its Consequences on the Global Translation of Proteins

Discovery of novel microRNA mimic repressors of ribosome biogenesis

While microRNAs and other non-coding RNAs are the next frontier of novel regulators of mammalian ribosome biogenesis (RB), a systematic exploration of microRNA-mediated RB regulation has not yet been undertaken. We carried out a high-content screen in MCF10A cells for changes in nucleolar number using a library of 2603 mature human microRNA mimics. Following a secondary screen for nucleolar rRNA biogenesis inhibition, we identified 72 novel microRNA negative regulators of RB after stringent hit calling. Hits included 27 well-conserved microRNAs present in MirGeneDB, and were enriched for mRNA targets encoding proteins with nucleolar localization or functions in cell cycle regulation. Rigorous selection and validation of a subset of 15 microRNA hits unexpectedly revealed that most of them caused dysregulated pre-rRNA processing, elucidating a novel role for microRNAs in RB regulation. Almost all hits impaired global protein synthesis and upregulated CDKN1A (p21) levels, while causing diverse effects on RNA Polymerase 1 (RNAP1) transcription and TP53 protein levels. We provide evidence that the MIR-28 siblings, hsa-miR-28-5p and hsa-miR-708-5p, potently target the ribosomal protein mRNA RPS28 via tandem primate-specific 3' UTR binding sites, causing a severe pre-18S pre-rRNA processing defect. Our work illuminates novel microRNA attenuators of RB, forging a promising new path for microRNA mimic chemotherapeutics.

MIWE: detecting the critical states of complex biological systems by the mutual information weighted entropy

Complex biological systems often undergo sudden qualitative changes during their dynamic evolution. These critical transitions are typically characterized by a catastrophic progression of the system. Identifying the critical point is critical to uncovering the underlying mechanisms of complex biological systems. However, the system may exhibit minimal changes in its state until the critical point is reached, and in the face of high throughput and strong noise data, traditional biomarkers may not be effective in distinguishing the critical state. In this study, we propose a novel approach, mutual information weighted entropy (MIWE), which uses mutual information between genes to build networks and identifies critical states by quantifying molecular dynamic differences at each stage through weighted differential entropy. The method is applied to one numerical simulation dataset and four real datasets, including bulk and single-cell expression datasets. The critical states of the system can be recognized and the robustness of MIWE method is verified by numerical simulation under the influence of different noises. Moreover, we identify two key transcription factors (TFs), CREB1 and CREB3, that regulate downstream signaling genes to coordinate cell fate commitment. The dark genes in the single-cell expression datasets are mined to reveal the potential pathway regulation mechanism.

Uterine secretome: What do the proteins say about maternal-fetal communication in buffaloes?

The aim was to compare the UF proteomics of pregnant and non-pregnant buffalo during early pregnancy. Forty-four females were submitted to hormonal estrus synchronization and randomly divided into two groups: pregnant (n = 30) and non-pregnant (n = 14). The pregnant group was artificially inseminated and divided into a further two groups: P12 (n = 15) and P18 (n = 15). Conceptus and uterine fluid samples were collected during slaughter at, respectively, 12 and 18 days after insemination. Of all the inseminated females, only eight animals in each group were pregnant, which reduced the sample of the groups to P12 (n = 8) and P18 (n = 8). The non-pregnant group was also re-divided into two groups at the end of synchronization: NP12 (n = 7) and NP18 (n = 7). The UF samples were processed for proteomic analysis. The results were submitted to multivariate and univariate analysis. A total of 1068 proteins were found in the uterine fluid in both groups. Our results describe proteins involved in the conceptus elongation and maternal recognition of pregnancy, and their action was associated with cell growth, endometrial remodeling, and modulation of immune and antioxidant protection, mechanisms necessary for embryonic maintenance in the uterine environment. SIGNIFICANCE: Uterine fluid is a substance synthesized and secreted by the endometrium that plays essential roles during pregnancy in ruminants, contributing significantly to embryonic development. Understanding the functions that the proteins present in the UF perform during early pregnancy, a period marked by embryonic implantation, and maternal recognition of pregnancy is of fundamental importance to understanding the mechanisms necessary for the maintenance of pregnancy. The present study characterized and compared the UF proteome at the beginning of pregnancy in pregnant and non-pregnant buffaloes to correlate the functions of the proteins and the stage of development of the conceptus and unravel their processes in maternal recognition of pregnancy. The proteins found were involved in cell growth and endometrial remodeling, in addition to acting in the immunological protection of the conceptus and performing antioxidant actions necessary for establishing a pregnancy.

Discovery of novel microRNA mimic repressors of ribosome biogenesis

While microRNAs and other non-coding RNAs are the next frontier of novel regulators of mammalian ribosome biogenesis (RB), a systematic exploration of microRNA-mediated RB regulation has not yet been undertaken. We carried out a high-content screen in MCF10A cells for changes in nucleolar number using a library of 2,603 mature human microRNA mimics. Following a secondary screen for nucleolar rRNA biogenesis inhibition, we identified 72 novel microRNA negative regulators of RB after stringent hit calling. Hits included 27 well-conserved microRNAs present in MirGeneDB, and were enriched for mRNA targets encoding proteins with nucleolar localization or functions in cell cycle regulation. Rigorous selection and validation of a subset of 15 microRNA hits unexpectedly revealed that most of them caused dysregulated pre-rRNA processing, elucidating a novel role for microRNAs in RB regulation. Almost all hits impaired global protein synthesis and upregulated CDKN1A ( p21 ) levels, while causing diverse effects on RNA Polymerase 1 (RNAP1) transcription and TP53 protein levels. We discovered that the MIR-28 siblings, hsa-miR-28-5p and hsa-miR-708-5p, directly and potently target the ribosomal protein mRNA RPS28 via tandem primate-specific 3' UTR binding sites, causing a severe pre-18S pre-rRNA processing defect. Our work illuminates novel microRNA attenuators of RB, forging a promising new path for microRNA mimic chemotherapeutics.

A new machine learning based computational framework identifies therapeutic targets and unveils influential genes in pancreatic islet cells

Pancreatic islets comprise a group of cells that produce hormones regulating blood glucose levels. Particularly, the alpha and beta islet cells produce glucagon and insulin to stabilize blood glucose. When beta islet cells are dysfunctional, insulin is not secreted, inducing a glucose metabolic disorder. Identifying effective therapeutic targets against the disease is a complicated task and is not yet conclusive. To close the wide gap between understanding the molecular mechanism of pancreatic islet cells and providing effective therapeutic targets, we present a computational framework to identify potential therapeutic targets against pancreatic disorders. First, we downloaded three transcriptome expression profiling datasets pertaining to pancreatic islet cells (GSE87375, GSE79457, GSE110154) from the Gene Expression Omnibus database. For each dataset, we extracted expression profiles for two cell types. We then provided these expression profiles along with the cell types to our proposed constrained optimization problem of a support vector machine and to other existing methods, selecting important genes from the expression profiles. Finally, we performed (1) an evaluation from a classification perspective which showed the superiority of our methods against the baseline; and (2) an enrichment analysis which indicated that our methods achieved better outcomes. Results for the three datasets included 44 unique genes and 10 unique transcription factors (SP1, HDAC1, EGR1, E2F1, AR, STAT6, RELA, SP3, NFKB1, and ESR1) which are reportedly related to pancreatic islet functions, diseases, and therapeutic targets.

The roles and mechanisms of the lncRNA-miRNA axis in the progression of esophageal cancer: a narrative review

BACKGROUND AND OBJECTIVE

Esophageal cancer is one of the most common malignant digestive tract tumors. Despite various treatment methods, the prognosis of patients remains unsatisfactory, largely due to an insufficient understanding of the mechanisms involved in the pathogenesis and progression of esophageal cancer. More than 98% of the nucleotide sequences in the human genome do not encode proteins, and their transcription products are noncoding RNAs (ncRNAs), mainly long noncoding RNAs (lncRNAs) and microRNAs (miRNAs). Experiments have shown that lncRNAs and miRNAs play crucial roles in the occurrence and progression of various human malignancies. These ncRNAs influence the progression of esophageal cancer through an intricate regulatory network. We herein summarized the roles and mechanisms of the lncRNA-miRNA axis in esophageal cancer cell proliferation, apoptosis, epithelial-mesenchymal transition (EMT), invasion and metastasis, drug resistance, radiotherapy resistance, and angiogenesis. This review provides a rationale for anticancer therapy that targets the lncRNA-miRNA axis in esophageal cancer.

METHODS

Related articles published in the PubMed database between 05/30/2008 to 09/10/2022 were identified using the following terms: "lncRNA AND miRNA AND esophageal cancer", "lncRNA AND miRNA AND cell proliferation", "lncRNA AND miRNA AND apoptosis", "lncRNA AND miRNA AND EMT", "lncRNA AND miRNA AND invasion and metastasis", "lncRNA AND miRNA AND drug resistance", and "lncRNA AND miRNA AND radiotherapy resistance". Published articles written in English available to readers were considered.

KEY CONTENT AND FINDINGS

We summarized the roles of the lncRNA-miRNA axis in the progression of esophageal cancer, including cell proliferation, apoptosis, EMT, invasion and metastasis, drug resistance, radio resistance, and other progressions, and determined that the lncRNA-miRNA axis may serve as a potential clinical treatment target for esophageal cancer.

CONCLUSIONS

The lncRNA-miRNA axis is closely related to the progression of esophageal cancer and may act as a potential biological target for the clinical treatment of patients with esophageal cancer.

SRG-vote: Predicting miRNA-gene relationships via embedding and LSTM ensemble

AbstractTargeted therapy for one for a set of genes has made it possible to apply precision medicine for different patients due to the existence of tumor heterogeneity. However, how to regulate those genes are still problematic. One of the natural regulators of genes is microRNAs. Thus, a better understanding of the miRNA-gene interaction mechanism might contribute to future diagnosis, prevention, and cancer therapy. The interactions between microRNA and genes play an essential role in molecular genetics. The in-vivo experiments validating the relationships between them are time-consuming, money-costly, and labor-intensive. With the development of high-throughput technology, we dealt with tons of biological data. However, extracting features from tremendous raw data and making a mathematical model is still a challenging topic. Machine learning and deep learning algorithms have become powerful tools in dealing with biological data. Inspired by this, in this paper, we propose a model that combines features/embedding extraction methods, deep learning algorithms, and a voting system. We leverage doc2vec to generate sequential embedding from molecular sequences. The role2vec, GCN, and GMM for geometrical embedding were generated from the complex network from similarity and pair-wise datasets. For the deep learning algorithms, we leveraged LSTM and Bi-LSTM according to different embedding and features. Finally, we adopted a voting system to balance results from different data sources. The results have shown that our voting system could achieve a higher AUC than the existing benchmark. The case studies demonstrate that our model could reveal potential relationships between miRNAs and genes. The source code, features, and predictive results can be downloaded at https://github.com/Xshelton/SRG-vote.

Modulating the bicoid gradient in space and time

Background

The formation of the Bicoid (Bcd) gradient in the early Drosophila is one of the most fascinating observations in biology and serves as a paradigm for gradient formation, yet its mechanism is still not fully understood. Two distinct models were proposed in the past, the SDD and the ARTS model.

Results

We define novel cis- and trans-acting factors that are indispensable for gradient formation. The first one is the poly A tail length of the bcd mRNA where we demonstrate that it changes not only in time, but also in space. We show that posterior bcd mRNAs possess a longer poly tail than anterior ones and this elongation is likely mediated by wispy (wisp), a poly A polymerase. Consequently, modulating the activity of Wisp results in changes of the Bcd gradient, in controlling downstream targets such as the gap and pair-rule genes, and also in influencing the cuticular pattern. Attempts to modulate the Bcd gradient by subjecting the egg to an extra nuclear cycle, i.e. a 15^th nuclear cycle by means of the maternal haploid (mh) mutation showed no effect, neither on the appearance of the gradient nor on the control of downstream target. This suggests that the segmental anlagen are determined during the first 14 nuclear cycles. Finally, we identify the Cyclin B (CycB) gene as a trans-acting factor that modulates the movement of Bcd such that Bcd movement is allowed to move through the interior of the egg.

Conclusions

Our analysis demonstrates that Bcd gradient formation is far more complex than previously thought requiring a revision of the models of how the gradient is formed.

Application of miRNA-seq in neuropsychiatry: A methodological perspective

MiRNAs are emerging as key molecules to study neuropsychiatric diseases. However, despite the large number of methodologies and software for miRNA-seq analyses, there is little supporting literature for researchers in this area. This review focuses on evaluating how miRNA-seq has been used to study neuropsychiatric diseases to date, analyzing both the main findings discovered and the bioinformatics workflows and tools used from a methodological perspective. The objective of this review is two-fold: first, to evaluate current miRNA-seq procedures used in neuropsychiatry; and second, to offer comprehensive information that can serve as a guide to new researchers in bioinformatics. After conducting a systematic search (from 2016 to June 30, 2020) of articles using miRNA-seq in neuropsychiatry, we have seen that it has already been used for different types of studies in three main categories: diagnosis, prognosis, and mechanism. We carefully analyzed the bioinformatics workflows of each study, observing a high degree of variability with respect to the tools and methods used and several methodological complexities that are identified and discussed in this review.

Mutant p53 Mediates Sensitivity to Cancer Treatment Agents in Oesophageal Adenocarcinoma Associated with MicroRNA and SLC7A11 Expression

TP53 gene mutations occur in 70% of oesophageal adenocarcinomas (OACs). Given the central role of p53 in controlling cellular response to therapy we investigated the role of mutant (mut-) p53 and SLC7A11 in a CRISPR-mediated JH-EsoAd1 TP53 knockout model. Response to 2 Gy irradiation, cisplatin, 5-FU, 4-hydroxytamoxifen, and endoxifen was assessed, followed by a TaqMan OpenArray qPCR screening for differences in miRNA expression. Knockout of mut-p53 resulted in increased chemo- and radioresistance (2 Gy survival fraction: 38% vs. 56%, p < 0.0001) and in altered miRNA expression levels. Target mRNA pathways analyses indicated several potential mechanisms of treatment resistance. SLC7A11 knockdown restored radiosensitivity (2 Gy SF: 46% vs. 73%; p = 0.0239), possibly via enhanced sensitivity to oxidative stress. Pathway analysis of the mRNA targets of differentially expressed miRNAs indicated potential involvement in several pathways associated with apoptosis, ribosomes, and p53 signaling pathways. The data suggest that mut-p53 in JH-EsoAd1, despite being classified as non-functional, has some function related to radio- and chemoresistance. The results also highlight the important role of SLC7A11 in cancer metabolism and redox balance and the influence of p53 on these processes. Inhibition of the SLC7A11-glutathione axis may represent a promising approach to overcome resistance associated with mut-p53.