Ribonucleic Acid Transcripts Research Articles

A Vacancy-Engineering Ferroelectric Nanomedicine for Cuproptosis/Apoptosis Co-Activated Immunotherapy.

Low efficacy of immunotherapy due to the poor immunogenicity of most tumors and their insufficient infiltration by immune cells highlights the importance of inducing immunogenic cell death and activating immune system for achieving better treatment outcomes. Herein, ferroelectric Bi2CuO4 nanoparticles with rich copper vacancies (named BCO-VCu) are rationally designed and engineered for ferroelectricity-enhanced apoptosis, cuproptosis, and the subsequently evoked immunotherapy. In this structure, the suppressed recombination of the electron-hole pairs by the vacancies and the band bending by the ferroelectric polarization lead to high catalytic activity, triggering reactive oxygen species bursts and inducing apoptosis. The cell fragments produced by apoptosis serve as antigens to activate T cells. Moreover, due to the generated charge by the ferroelectric catalysis, this nanomedicine can act as "a smart switch" to open the cell membrane, promote nanomaterial endocytosis, and shut down the Cu+ outflow pathway to evoke cuproptosis, and thus a strong immune response is triggered by the reduced content of adenosine triphosphate. Ribonucleic acid transcription tests reveal the pathways related to immune response activation. Thus, this study firstly demonstrates a feasible strategy for enhancing the efficacy of immunotherapy using single ferroelectric semiconductor-induced apoptosis and cuproptosis.

SpatialcoGCN: deconvolution and spatial information-aware simulation of spatial transcriptomics data via deep graph co-embedding.

Spatial transcriptomics (ST) data have emerged as a pivotal approach to comprehending the function and interplay of cells within intricate tissues. Nonetheless, analyses of ST data are restricted by the low spatial resolution and limited number of ribonucleic acid transcripts that can be detected with several popular ST techniques. In this study, we propose that both of the above issues can be significantly improved by introducing a deep graph co-embedding framework. First, we establish a self-supervised, co-graph convolution network-based deep learning model termed SpatialcoGCN, which leverages single-cell data to deconvolve the cell mixtures in spatial data. Evaluations of SpatialcoGCN on a series of simulated ST data and real ST datasets from human ductal carcinoma in situ, developing human heart and mouse brain suggest that SpatialcoGCN could outperform other state-of-the-art cell type deconvolution methods in estimating per-spot cell composition. Moreover, with competitive accuracy, SpatialcoGCN could also recover the spatial distribution of transcripts that are not detected by raw ST data. With a similar co-embedding framework, we further established a spatial information-aware ST data simulation method, SpatialcoGCN-Sim. SpatialcoGCN-Sim could generate simulated ST data with high similarity to real datasets. Together, our approaches provide efficient tools for studying the spatial organization of heterogeneous cells within complex tissues.

Revealing the Mutually Enhanced Mechanism of Necroptosis and Immunotherapy Induced by Defect Engineering and Piezoelectric Effect.

Owing to low immunogenicity-induced immune escape and short-term circulating immune responses, the efficiency of immunotherapy is unsatisfactory. Therefore, triggering immunogenic cell death and establishing a long-term, mutually reinforced treatment modality are urgent challenges. In this study, ultrathin CaBi2 Nb2 O9 nanosheets with tunable oxygen vacancies (abbreviated as CBNO-OV1) are prepared for synergistic necroptosis and immunotherapy. The optimized vacancy concentration significantly improves the piezoelectric effect under ultrasound irradiation, thereby considerably improving the generation of reactive oxygen species (ROS). Density functional theory shows that oxygen vacancies can improve the efficiency of electron hole separation by suppressing their recombination, thus resulting in enhanced piezocatalytic activity. Moreover, the piezoelectric effect improves the permeability of tumor cell membranes, thus resulting in Ca2+ influx. Additionally, CBNO-OV1 also releases a portion of Ca2+ , which induces necroptosis assisted by explosive ROS. Ribonucleic acid transcription tests suggest the mechanisms associated with immune response activation and necroptosis. More importantly, necroptosis can trigger a significant immune response in vivo, thus activating macrophage M1 polarization through the NF-kappa B pathway and promoting T-cell differentiation.Tumor Necrosis Factor-α differentiated from macrophages conversely promotes necroptosis, thus realizing a mutually enhanced effect. This study demonstrates the feasibility of mutually reinforced necroptosis and immunotherapy for amplifying tumor efficacy.

The Effect of Ferritin Level and Gene Expression of β-globin Promoter with β-thalassemia Patients in Al-Qadisiyah Governorate, Iraq

Abstract BACKGROUND: The genetic condition β-thalassemia causes a deficit in the β-globin chain. Goblins are produced under the supervision of at least nine different genes. Thalassemia can be distinguished from other disorders by changes in these genes, which can lead to issues with hemoglobin synthesis. A typical side effect of thalassemia syndromes is iron overload, which raises the risk of mortality and can cause organ damage. Blood ferritin levels as well as total iron of body reserves have a positive correlation when there is no inflammation. OBJECTIVE: The purpose of this study was to assess the ferritin level of an Iraqi patient and the relationship between β-thalassemia and gene expression of β-globin. MATERIALS AND METHODS: A case–control study included 60 samples with mean age (17.76 ± 0.88; 28 males and 32 females) which had been collected from patients who were diagnosed with β-thalassemia and 60 samples with mean age (22.7 ± 0.75; 29 males, 31 females) which were collected from apparently healthy individuals as a control group (CG). The procedure’s outcome is monitored using polymerase chain reaction and the Fluorecare instrument. RESULTS: Ferritin levels in thalassemia patients were higher than in CG patients. The β-globin expression in the thalassemia group was significantly lower than in the CG. The discovery of two essential sequences thymine-adenine-thymine-adenine and cytosine-adenine-thymine-adenine in the β-gene promoter that are crucial in the start of transcription can account for this downregulation. Changes made to these sequences decreased the affinity of transcription factors, which in turn restricted the transcription of the messenger ribonucleic acid. Examples of these transcription factors are erythroid Kruppel-like factor and specificity protein 1. CONCLUSION: Ferritin can be a useful indicator of severe iron overload. The results showed that the level of expression of β-globin was dramatically downregulated within the thalassemia group as compared with the CG future prospective of this study.

Association of Key Genes IFIT1 and IFIT3 with Immune Infiltration in Systemic Lupus Erythematosus

Systemic lupus erythematosus is a diffuse connective tissue disease mediated by autoimmunity and characterized by immune inflammation. The purpose of this study is to explore candidate key genes and immune cell infiltration involved in the pathogenesis of systemic lupus erythematosus. Intersection genes derived from differentially expressed genes between systemic lupus erythematosus patients and healthy individuals are identified by weighted gene co-expression network analysis of module genes were aimed for gene ontology functional enrichment analysis and Kyoto encyclopedia of genes and genomes pathway enrichment analysis. The key candidate genes interferon induced protein with tetratricopeptide repeats 1 and interferon induced protein with tetratricopeptide repeats 3 were searched through the protein-protein interaction network. The cell-type identification by estimating relative subsets of ribonucleic acid transcripts arithmetic tool assessed the abundance of immune cells in samples from systemic lupus erythematosus patients. Enzymelinked immunosorbent assay confirmed the differential expression of candidate genes in serum samples from systemic lupus erythematosus patients and healthy controls. This study found that interferon induced protein with tetratricopeptide repeats 1 and interferon induced protein with tetratricopeptide repeats 3 may devote to the pathogenesis and development of systemic lupus erythematosus and can be used as prediction target genes of systemic lupus erythematosus. In addition, neutrophils and plasma cells were infiltrated more in systemic lupus erythematosus patients with high expression of interferon induced protein with tetratricopeptide repeats 1 and interferon induced protein with tetratricopeptide repeats 3. Interferon induced protein with tetratricopeptide repeats 1 and interferon induced protein with tetratricopeptide repeats 3 are important predictors for the diagnosis and treatment of systemic lupus erythematosus.

Circulating messenger RNA variants as a potential biomarker for surveillance of hepatocellular carcinoma.

Liver derived messenger ribonucleic acid (mRNA) transcripts were reported to be elevated in the circulation of hepatocellular carcinoma (HCC) patients. We now report the detection of high-risk mRNA variants exclusively in the circulation of HCC patients. Numerous genomic alleles such as single nucleotide polymorphisms (SNPs), nucleotide insertions and deletions (called Indels), splicing variants in many genes, have been associated with elevated risk of cancer. Our findings potentially offer a novel non-invasive platform for HCC surveillance and early detection. RNAseq analysis was carried out in the plasma of 14 individuals with a diagnosis of HCC, 8 with LC and no HCC, and 6 with no liver disease diagnosis. RNA from 6 matching tumors and 5 circulating extracellular vesicle (EV) samples from 14 of those with HCC was also analyzed. Specimens from two cholangiocarcinoma (CCA) patients were also included in our study. HCC specific SNPs and Indels referred as "variants" were identified using GATK HaplotypeCaller and annotated by SnpEff to filter out high risk variants. The variant calling on all RNA samples enabled the detection of 5.2 million SNPs, 0.91 million insertions and 0.81 million deletions. RNAseq analyses in tumors, normal liver tissue, plasma, and plasma derived EVs led to the detection of 5480 high-risk tumor specific mRNA variants in the circulation of HCC patients. These variants are concurrently detected in tumors and plasma samples or tumors and EVs from HCC patients, but none of these were detected in normal liver, plasma of LC patients or normal healthy individuals. Our results demonstrate selective detection of concordant high-risk HCC-specific mRNA variants in free plasma, plasma derived EVs and tumors of HCC patients. The variants comprise of splicing, frameshift, fusion and single nucleotide alterations and correspond to cancer and tumor metabolism pathways. Detection of these high-risk variants in matching specimens from same subjects with an enrichment in circulating EVs is remarkable. Validation of these HCC selective ctmRNA variants in larger patient cohorts is likely to identify a predictive set of ctmRNA with high diagnostic performance and thus offer a novel non-invasive serology-based biomarker for HCC.

Abstract 13172: Systematic Dissection, Preservation, and Multiomics in Whole Human and Bovine Hearts

Introduction: We developed a rigorous, systematic protocol for the dissection and preservation of human hearts for biobanking to advance our understanding of cardiovascular diseases (CVDs). Existing cardiac biobanks consist largely of biopsy tissue in select diseases and are insufficient for correlating whole organ phenotype with clinical data. Methods: We demonstrate optimal conditions for multiomics interrogation (ribonucleic acid (RNA) sequencing, untargeted metabolomics) in hearts by evaluating the effect of technical variables (storage solution, temperature) and simulated postmortem interval (PMI) on RNA and metabolite stability. We used bovine (N=3) and human (N=2) hearts fixed in PAXgene or snap-frozen with liquid nitrogen. Results: Using a paired Wald test, only two of the genes assessed were differentially expressed between left ventricular samples from bovine hearts stored in PAXgene at 0 and 12 hours PMI (FDR q < 0.05). We obtained similar findings in human left ventricular samples, suggesting stability of RNA transcripts at PMIs up to 12 hours. Different library preparation methods (mRNA poly-A capture vs. rRNA depletion) resulted in similar quality metrics with both library preparations achieving >95% of reads properly aligning to the reference genomes across all PMIs for bovine and human hearts. PMI had no effect on RNA Integrity Number or quantity of RNA recovered at the time points evaluated. Of the metabolites identified (855 total) using untargeted metabolomics of human left ventricular tissue, 503 metabolites remained stable across PMIs (0, 4, 8, 12 hours). Most metabolic pathways retained several stable metabolites. Conclusions: Our data demonstrate a technically rigorous, feasible and reproducible protocol that will enhance cardiac biobanking practices and facilitate novel insights into human CVD through the use of multiomics in postmortem human cardiac tissue.

Systematic dissection, preservation, and multiomics in whole human and bovine hearts

ObjectivesWe sought to develop a rigorous, systematic protocol for the dissection and preservation of human hearts for biobanking that expands previous success in postmortem transcriptomics to multiomics from paired tissue. BackgroundExisting cardiac biobanks consist largely of biopsy tissue or explanted hearts in select diseases and are insufficient for correlating whole organ phenotype with clinical data. MethodsWe demonstrate optimal conditions for multiomics interrogation (ribonucleic acid (RNA) sequencing, untargeted metabolomics) in hearts by evaluating the effect of technical variables (storage solution, temperature) and simulated postmortem interval (PMI) on RNA and metabolite stability. We used bovine (n=3) and human (n=2) hearts fixed in PAXgene or snap-frozen with liquid nitrogen. ResultsUsing a paired Wald test, only two of the genes assessed were differentially expressed between left ventricular samples from bovine hearts stored in PAXgene at 0 and 12 hours PMI (FDR q<0.05). We obtained similar findings in human left ventricular samples, suggesting stability of RNA transcripts at PMIs up to 12 hours. Different library preparation methods (mRNA poly-A capture vs. rRNA depletion) resulted in similar quality metrics with both library preparations achieving >95% of reads properly aligning to the reference genomes across all PMIs for bovine and human hearts. PMI had no effect on RNA Integrity Number or quantity of RNA recovered at the time points evaluated. Of the metabolites identified (855 total) using untargeted metabolomics of human left ventricular tissue, 503 metabolites remained stable across PMIs (0, 4, 8, 12 hours). Most metabolic pathways retained several stable metabolites. ConclusionsOur data demonstrate a technically rigorous, reproducible protocol that will enhance cardiac biobanking practices and facilitate novel insights into human CVD. Condensed abstractCardiovascular disease (CVD) is the leading cause of mortality worldwide. Current biobanking practices insufficiently capture both the diverse array of phenotypes present in CVDs and the spatial heterogeneity across cardiac tissue sites. We have developed a rigorous and systematic protocol for the dissection and preservation of human cardiac biospecimens to enhance the availability of whole organ tissue for multiple applications. When combined with longitudinal clinical phenotyping, our protocol will enable multiomics in hearts to deepen our understanding of CVDs.

Mutational and transcriptional alterations and clinicopathological factors predict the prognosis of stage I hepatocellular carcinoma

BackgroundThe prognosis of hepatocellular carcinoma (HCC) has been extensively studied. However, the impact on prognosis of stage I HCC has not been well studied at clincopathological, mutational and transcriptional levels.MethodsHere we first characterized the influencing factors of prognosis of stage I HCC patients by downloading and analyzing the whole-exome somatic mutation data, messenger ribonucleic acid (mRNA) transcription data, along with demographic and clinical information of 163 stage I HCC patients from the TCGA database. The relationship between the influencing factors and HCC prognosis was studied in detail, and a prediction Nomogram model was established. Figures and tables were plotted using the R software.ResultsTP53, CTNNB1, TTN, MUC16 and ALB were the top mutated genes in stage I HCC. A series of co-mutations and mutually exclusive mutations were identified. Twenty-nine genes with significant stratification on prognosis were identified, including highly mutated LRP1B, ARID1A and PTPRQ. Patients with wild type (WT) genes unanimously exhibited significantly better overall survival rate than those with mutants. Patients with the top 10% tumor mutational burden (TMB) exhibited significantly worse prognosis than the rest 90%. Further characterization of transcriptional profile revealed that membrane functions, cell skeleton proteins, ion channels, receptor function and cell cycle were comprehensively altered in stage I HCC. Univariate and multivariate analyses were performed at clinicopathological, mutational and transcriptional levels. The combined analysis revealed sex, race, TMB, neoplasm histologic grade, Child–Pugh grade, MMRN1, OXT and COX6A2 transcription as independent risk factors. These factors were used to establish a Nomogram model to predict the prognosis of individual HCC patients.ConclusionsThe influencing factors of prognosis of stage I HCC have been characterized for the first time at clinicopathological, mutational and transcriptional levels. A Nomogram model has been established to predict the prognosis. Further validation is needed to confirm the effectiveness and reliability of the model.

Effect of dietary inclusion of camelina or chia oil on fatty acid digestibility, histology, blood biochemistry and molecular biomarkers in juvenile gilthead sea bream (Sparus aurata, L.)

The present study evaluated fatty acid digestibility, histology, blood biochemistry and gene expression in the gut of juvenile gilthead sea bream, Sparus aurata (initial mean weight, 60.4 ± 4.9 g) fed with iso-proteic (48%) and iso-lipidic (20.7%) diets in which fish oil was partially (60%) or totally (100%) replaced with either camelina or chia oil. Each of the experimental diets was fed to triplicate groups of fish stocked at 10 fish/tank in 150 L tanks for 90 days. Although inclusion of camelina or chia oil altered dietary fatty acid (FA) profile, major differences in digestibility in the individual FAs were not observed. Total replacement of fish oil with camelina or chia oil did not have any effect on blood glucose levels, whereas cholesterol and triglyceride levels were reduced. Results of messenger ribonucleic acid (mRNA) transcription showed elevated levels in the expression of the elongases and desaturases in gilthead seabream fed with diets devoid of fish oil. Fish fed with camelina or chia oil based diets had increased expression in lipolytic and lipogenic genes, resulting in accumulation of lipid droplets in the gut of fish. Histological examination revealed no pathological disorders in the guts of the fish.

Correlation of receptor density and mRNA expression patterns in the human cerebral cortex

Changes in distribution of associated molecular targets have been reported across several neuropsychiatric disorders. However, the high-resolution topology of most proteins is unknown and simultaneous in vivo measurement in multi-receptor systems is complicated. To account for the missing proteomic information, messenger ribonucleic acid (mRNA) transcripts are typically used as a surrogate. Nonetheless, post-transcriptional and post-translational processes might cause the discrepancy between the final distribution of proteins and gene expression patterns. Therefore, this study aims to investigate ex vivo links between mRNA expression and corresponding receptor density in the human cerebral cortex.To this end, autoradiography data on the density of 15 different receptors in 38 brain regions were correlated with the expression patterns of 50 associated genes derived from microarray data (mA), RNA sequencing data (RNA-Seq) provided by the Allen Human Brain Atlas and predicted mRNA expression patterns (pred-mRNA). Spearman's rank correlation was used to evaluate the possible links between proteomic data and mRNA expression patterns.Correlations between mRNA and protein density varied greatly between targets: Positive associations were found for e.g. the serotonin 1A (pred-mRNA: rs = 0.708; mA: rs = 0.601) or kainate receptor (pred-mRNA: rs = 0.655; mA: rs = 0.601; RNA-Seq: rs = 0.575) as well as a few negative associations e.g. γ-Aminobutyric acid (GABA) A receptor subunit α3 (pred-mRNA: rs = -0.638; mA: rs = -0.619) or subunit α5 (pred-mRNA: rs = -0.565; mA: rs = -0.563), while most of the other investigated target receptors showed low correlations.The high variability in the correspondence of mRNA expression and receptor spatial distribution warrants caution when inferring the topology of molecular targets in the brain from transcriptome data. This not only highlights the longstanding value of molecular imaging but also indicates a need for comprehensive proteomic studies.

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.

Research Progress on the Omics of Methamphetamine Toxic Damage and Addiction.

The mechanism of methamphetamine toxicity and addiction is the key research direction of forensic toxicology, and the development of omics technology provides a new platform for further study of this direction. METH toxic damage and addiction are reflected differently in genes, ribonucleic acid (RNA) transcription, protein and metabolism. This article summarizes the achievements and shortcomings of multi-omics technologies such as genome, transcriptome, metabolome and proteome in the study of METH damage and addiction, and discusses the strategies and advantages of multi-omics combined analysis in the study of METH toxic damage and addiction mechanism, in order to provide more useful reference information for forensic toxicology of METH.

Developments in Smart Multi-Function Gait Assistive Devices for the Prevention and Treatment of Knee Osteoarthritis—A Literature Review

Knee osteoarthritis (OA) is a degenerative condition that critically affects locomotor ability and quality of life and, the condition is particularly prevalent in the senior population. The current review presents a gait biomechanics conceptual framework for designing active knee orthoses to prevent and remediate knee OA. Constant excessive loading diminishes knee joint articular cartilage and, therefore, measures to reduce kinetic stresses due to the fact of adduction moments and joint compression are an essential target for OA prevention. A powered orthosis enables torque generation to support knee joint motions and machine-learning-driven “smart systems” can optimise the magnitude and timing of joint actuator forces. Although further research is required, recent findings raise the possibility of exoskeleton-supported, non-surgical OA interventions, increasing the treatment options for this prevalent, painful and seriously debilitating disease. Combined with advances in regenerative medicine, such as stem cell implantation and manipulation of messenger ribonucleic acid (m-RNA) transcription, active knee orthoses can be designed to incorporate electro-magnetic stimulators to promote articular cartilage resynthesis.

A Brief Review for Identifying Prokaryotic Promoters Based on Computational Biology

As a key region of deoxyribonucleic acid (DNA), prokaryotic promoter contains the conserved sequence required for specific binding of ribonucleic acid (RNA) polymerase and transcription initiation, and plays an important role in transcription regulation. However, due to the limitations of experimental methods that are long experimental period and high cost, the identification of prokaryotic promoter sequences remains a major challenge. With the development of computer technology, dozens of prokaryotic promoter identification methods based on computational biology have emerged, which show a high degree of diversity in terms of data quality, dataset size, extracted features, feature selection techniques, classification algorithms and evaluation strategies. Thus, there is an urgent need to systematically compare and summarize these methods so as to improve and further develop prokaryotic promoter recognition techniques.

Nucleic Acid Tests for Clinical Translation.

Nucleic acids, including deoxyribonucleic acid (DNA) and ribonucleic acid (RNA), are natural biopolymers composed of nucleotides that store, transmit, and express genetic information. Overexpressed or underexpressed as well as mutated nucleic acids have been implicated in many diseases. Therefore, nucleic acid tests (NATs) are extremely important. Inspired by intracellular DNA replication and RNA transcription, in vitro NATs have been extensively developed to improve the detection specificity, sensitivity, and simplicity. The principles of NATs can be in general classified into three categories: nucleic acid hybridization, thermal-cycle or isothermal amplification, and signal amplification. Driven by pressing needs in clinical diagnosis and prevention of infectious diseases, NATs have evolved to be a rapidly advancing field. During the past ten years, an explosive increase of research interest in both basic research and clinical translation has been witnessed. In this review, we aim to provide comprehensive coverage of the progress to analyze nucleic acids, use nucleic acids as recognition probes, construct detection devices based on nucleic acids, and utilize nucleic acids in clinical diagnosis and other important fields. We also discuss the new frontiers in the field and the challenges to be addressed.

The Emerging Role of microRNA in Periodontitis: Pathophysiology, Clinical Potential and Future Molecular Perspectives.

During the last few decades, it has been established that messenger ribonucleic acid (mRNA) transcription does not inevitably lead to protein translation, but there are numerous processes involved in post-transcriptional regulation, which is a continuously developing field of research. MicroRNAs (miRNAs) are a group of small non-coding RNAs, which negatively regulate protein expression and are implicated in several physiological and pathological mechanisms. Aberrant expression of miRNAs triggers dysregulation of multiple cellular processes involved in innate and adaptive immune responses. For many years, it was thought that miRNAs acted only within the cell in which they were synthesised, but, recently, they have been found outside cells bound to lipids and proteins, or enclosed in extracellular vesicles, namely exosomes. They can circulate throughout the body, transferring information between cells and altering gene expression in the recipient cells, as they can fuse with and be internalised by the recipient cells. Numerous studies on miRNAs have been conducted in order to identify possible biomarkers that can be used in the diagnosis of periodontal disease. However, as therapeutic agents, single miRNAs can target several genes and influence multiple regulatory networks. The aim of this review was to examine the molecular role of miRNAs and exosomes in the pathophysiology of periodontal disease and to evaluate possible clinical and future implications for a personalised therapeutical approach.

RNA sequencing and proteomic profiling reveal different alterations by dietary methylmercury in the hippocampal transcriptome and proteome in BALB/c mice.

Methylmercury (MeHg) is a highly neurotoxic form of mercury (Hg) present in seafood. Here, we recorded and compared proteomic and transcriptomic changes in hippocampus of male BALB/c mice exposed to two doses of MeHg. Mice were fed diets spiked with 0.28 mg MeHg kg–1, 5 mg MeHg kg–1, or an unspiked control diet for 77 days. Total mercury content was significantly (P < 0.05) increased in brain tissue of both MeHg-exposed groups (18 ± 2 mg Hg kg–1 and 0.56 ± 0.06 mg Hg kg–1). Hippocampal protein and ribonucleic acid (RNA) expression levels were significantly altered both in tissues from mice receiving a low dose MeHg (20 proteins/294 RNA transcripts) and a high dose MeHg (61 proteins/876 RNA transcripts). The majority but not all the differentially expressed features in hippocampus were dose dependent. The combined use of transcriptomic and proteomic profiling data provided insight on the influence of MeHg on neurotoxicity, energy metabolism, and oxidative stress through several regulated features and pathways, including RXR function and superoxide radical degradation.

A broad introduction to RNA-Seq

RNA-Seq, named as an abbreviation of "RNA sequencing" and sometimes spelled RNA-seq, RNAseq, or RNASeq, uses next-generation sequencing (NGS) to reveal the presence and quantity of ribonucleic acid (RNA) in a biological sample at a given moment.[1][2] RNA-Seq is used to analyze the continuously changing cellular transcriptome (Figure 1). Specifically, RNA-Seq facilitates the ability to look at alternative gene spliced transcripts, post-transcriptional modifications, gene fusion, mutations/single nucleotide polymorphisms (SNPs) and changes in gene expression over time, or differences in gene expression in different groups or treatments.[3] In addition to messenger RNA (mRNA) transcripts, RNA-Seq can look at different populations of RNA to include total RNA, small RNA, such as microRNA (miRNA), transfer RNA (tRNA), and ribosomal profiling.[4] RNA-Seq can also be used to determine exon/intron boundaries and verify or amend previously annotated 5' and 3' gene boundaries. Recent advances in RNA-Seq include single cell sequencing, in situ sequencing of fixed tissue, and native RNA molecule sequencing with single-molecule real-time sequencing.[5] Prior to RNA-Seq, gene expression studies were done with hybridization-based microarrays. Issues with microarrays include cross-hybridization artifacts, poor quantification of lowly and highly expressed genes, and needing to know the sequence a priori.[6] Because of these technical issues, transcriptomics transitioned to sequencing-based methods. These progressed from Sanger sequencing of Expressed Sequence Tag libraries, to chemical tag-based methods (e.g., serial analysis of gene expression), and finally to the current technology, next-gen sequencing of complementary DNA ( cDNA), notably RNA-Seq.

An evaluation of the molecular mode of action of trans-resveratrol in the Porphyromonas gingivalis lipopolysaccharide challenged neuronal cell model

Porphyromonas gingivalis triggers a range of innate immune responses in the host that may contribute to the development of periodontitis and dementing diseases including Alzheimer’s disease (AD). This study aimed to assess the mode of action of trans-resveratrol in modulating the P. gingivalis lipopolysaccharide (PgLPS) induced metabolic inflammation in a neuronal cell model. Confluent IMR-32 neuroblastoma cells were treated with trans-resveratrol from Polygonum cuspidatum in the presence or absence of PgLPS. The abundance of messenger ribo-nucleic acid (mRNA) transcripts of a panel of 92 genes was quantitatively assessed through targeted transcriptome profiling technique and the biochemical pathways affected were identified through Ingenuity Pathway Analysis. Gene expression analysis revealed that trans-resveratrol down-regulated the mRNA of multiple gene markers including growth factors, transcription factors, kinases, trans-membrane receptors, cytokines and enzymes that were otherwise activated by PgLPS treatment of IMR-32 neuroblastoma cells. Pathway analysis demonstrated that the cellular oxidative stress caused by the activation of phosphoinositide-3-kinase/Akt1 (PI3K/Akt1) pathway that leads to the production of reactive oxygen species (ROS), chronic inflammatory response induced by the activation of nuclear factor kappa-light-chain-enhancer of activated B cells (NF-kB) pathway and nutrient utilization pathways were favourably modulated by trans-resveratrol in the PgLPS challenged IMR-32 cells. This study demonstrates the potential of trans-resveratrol as a bioactive compound with multiple modes of intracellular action further supporting its therapeutic application in neuroinflammatory diseases.