Ribonucleic Acid Sequencing Research Articles

NAT10 promotes vascular remodelling via mRNA ac4C acetylation.

Vascular smooth muscle cell (VSMC) phenotype switching is a pathological hallmark in various cardiovascular diseases. N4-acetylcytidine (ac4C) catalyzed by N-acetyltransferase 10 (NAT10) is well conserved in the enzymatic modification of ribonucleic acid (RNA). NAT10-mediated ac4C acetylation is involved in various physiological and pathological processes, including cardiac remodelling. However, the biological functions and underlying regulatory mechanisms of mRNA ac4C modifications in vascular diseases remain elusive. By combining in-vitro and in-vivo vascular injury models, NAT10 was identified as a crucial protein involved in the promotion of post-injury neointima formation, as well as VSMC phenotype switching. The potential mechanisms of NAT10 in the vascular neointima formation were clarified by RNA sequence (RNA-seq), acetylated mRNA immunoprecipitation sequence (acRIP-seq), and RNA binding protein immunoprecipitation sequence (RIP-seq). NAT10 and ac4C modifications were upregulated in injured human and rodent arteries. Deletion of NAT10 in VSMCs effectively reduced post-injury neointima formation and VSMC phenotype switching. Further RNA-seq, RIP-seq, and acRIP-seq revealed that NAT10, by its ac4C modification, directly interacts with genes, including integrin-β1 (ITGB1) and collagen type I alpha 2 chain (Col1a2) mRNAs. Taking ITGB1 as one example, it showed that NAT10-mediated ac4C consequently increased ITGB1 mRNA stability and its downstream focal adhesion kinase (FAK) signaling, directly influencing the proliferation of VSMCs and vascular remodelling. The regulation of NAT10 on the VSMC phenotype is of translational significance because the administration of Remodelin, a NAT10 inhibitor, effectively prevents neointima formation by suppressing VSMC proliferation and downregulating ITGB1 expression and deactivating its FAK signaling. This study reveals that NAT10 promotes vascular remodelling via mRNA ac4C acetylation, which may be a promising therapeutic target against vascular remodelling.

Physiological and transcriptomic analysis reveals the coating of microcapsules embedded with bacteria can enhance wheat salt tolerance

Salt stress is one of the most important abiotic stress factors limiting crop production. Therefore, improving the stress resistance of seeds is very important for crop growth. Our previous studies have shown that using microcapsules encapsulating bacteria (Pontibacter actiniarum DSM 19842) as seed coating for wheat can alleviate salt stress. In this study, the genes and pathways involved in the response of wheat to salt stress were researched further. The results showed that compared with the control, the coating can improve osmotic stress and decrease oxidative damage by increasing the content of proline (29.1%), the activity of superoxide dismutase (SOD) (94.2%), peroxidase (POD) (45.7%) and catalase (CAT) (3.3%), reducing the content of hydrogen peroxide (H2O2) (39.8%) and malondialdehyde (MDA) (45.9%). In addition, ribonucleic acid (RNA) sequencing data showed that 7628 differentially expressed genes (DEGs) were identified, and 4426 DEGs up-regulated, 3202 down-regulated in the coated treatment. Many DEGs related to antioxidant enzymes were up-regulated, indicating that coating can promote the expression of antioxidant enzyme-related genes and alleviate oxidative damage under salt stress. The differential gene expression analysis demonstrated up-regulation of 27 genes and down-regulation of 20 genes. Transcription factor families, mostly belonging to bHLH, MYB, B3, NAC, and WRKY. Overall, this seed coating can promote the development of sustainable agriculture in saline soil.

Seasonal Variability of Human Enteric Viruses Discovered in Food Production Mussels (Mytilus galloprovincialis) Farmed in the Central Adriatic Sea (Italy).

Among the different naked and quasi-enveloped viruses, the hepatitis A virus (HAV), hepatitis E virus (HEV), and norovirus genogroups I and II (NoV GI and NoV GII) are considered the main microbiological noxae involved in foodborne outbreaks. Mussels can harbor pathogens in their tissues. In addition to epidemiological attention, marine water temperature changes are considered a crucial variable influencing viral loads. This study aimed to biomolecularly screen 1775 farmed mussels (Mytilus galloprovincialis) for viral ribonucleic acid (RNA) sequence detection (belonging to the HAV, HEV, and NoV GI and GII genogroups) in three different sampling periods (spring, summer, and winter), with the mussels collected from three farms located in the Central Adriatic Sea (Italy). The results showed that 10.42% of the screened animals harbored at least one type of pathogen RNA, more specifically, 5.35% HEV, 4.51% NoV GI, and 0.56% HAV. The highest genetic equivalent (GE) amounts were majorly observed in the winter season (NoV GI 1.0 × 103 GE/g and HEV 1.0 × 102 GE/g), resulting in statistical differences when compared to summer and spring (p-value: <0.001). The original data obtained serve to bring scientific attention to the possible influence of environmental and climatic aspects on viral loads, highlighting the crucial role played by biomolecular assays as preventive medicine tools.

Transcriptomic Biomarkers Associated with Microbiological Etiology and Disease Severity in Childhood Pneumonia.

Challenges remain in discerning microbiologic etiology and disease severity in childhood pneumonia. Defining host transcriptomic profiles during illness may facilitate improved diagnostic and prognostic approaches. Using whole blood ribonucleic acid sequencing from 222 hospitalized children with radiographic pneumonia and 45 age-matched controls, we identified differentially expressed genes that best identified children according to detected microbial pathogens (viral-only vs. bacterial-only and typical vs. atypical bacterial [+/- viral co-detection]) and an ordinal measure of phenotypic severity (moderate, severe, very severe). Overall, 135 (61%) children had viral-only detections, 15 (7%) had typical bacterial (+/- viral co-detections), and 26 (12%) had atypical bacterial (+/- viral co-detections). Eleven DE genes distinguished between viral-only and bacterial-only detections. Sixteen DE genes distinguished between atypical and typical bacterial detections (+/- viral co-detections). Nineteen DE genes distinguished between levels of pneumonia severity, including four genes also identified in the viral-only vs. bacterial-only model (IGHGP, PI3, CD177, RAP1GAP1) and four genes from the typical vs atypical bacterial model (PRSS23, IFI27, OLFM4, and ABO). We identified transcriptomic biomarkers associated with microbial detections and phenotypic severity in children hospitalized with pneumonia. These DE genes are promising candidates for validation and translation into diagnostic and prognostic tools.

Multimodal Identification of Molecular Factors Linked to Severe Diabetic Foot Ulcers Using Artificial Intelligence.

Diabetic foot ulcers (DFUs) are a severe complication of diabetes mellitus (DM), which often lead to hospitalization and non-traumatic amputations in the United States. Diabetes prevalence estimates in South Texas exceed the national estimate and the number of diagnosed cases is higher among Hispanic adults compared to their non-Hispanic white counterparts. San Antonio, a predominantly Hispanic city, reports significantly higher annual rates of diabetic amputations compared to Texas. The late identification of severe foot ulcers minimizes the likelihood of reducing amputation risk. The aim of this study was to identify molecular factors related to the severity of DFUs by leveraging a multimodal approach. We first utilized electronic health records (EHRs) from two large demographic groups, encompassing thousands of patients, to identify blood tests such as cholesterol, blood sugar, and specific protein tests that are significantly associated with severe DFUs. Next, we translated the protein components from these blood tests into their ribonucleic acid (RNA) counterparts and analyzed them using public bulk and single-cell RNA sequencing datasets. Using these data, we applied a machine learning pipeline to uncover cell-type-specific and molecular factors associated with varying degrees of DFU severity. Our results showed that several blood test results, such as the Albumin/Creatinine Ratio (ACR) and cholesterol and coagulation tissue factor levels, correlated with DFU severity across key demographic groups. These tests exhibited varying degrees of significance based on demographic differences. Using bulk RNA-Sequenced (RNA-Seq) data, we found that apolipoprotein E (APOE) protein, a component of lipoproteins that are responsible for cholesterol transport and metabolism, is linked to DFU severity. Furthermore, the single-cell RNA-Seq (scRNA-seq) analysis revealed a cluster of cells identified as keratinocytes that showed overexpression of APOE in severe DFU cases. Overall, this study demonstrates how integrating extensive EHRs data with single-cell transcriptomics can refine the search for molecular markers and identify cell-type-specific and molecular factors associated with DFU severity while considering key demographic differences.

Use of FISH-FLOW as a Method for the Identification and Quantification of Bacterial Populations.

The gastrointestinal tract (GIT) harbors the largest group of microbiotas among the microbial communities of the human host. The resident organisms typical of a healthy gut are well adapted to the gastrointestinal environment while alteration of these populations can trigger disorders that may affect the health and well-being of the host. Various investigations have applied different tools to study bacterial communities in the gut and their correlation with gastrointestinal disorders such as inflammatory bowel disease (IBD), obesity, and diabetes. This study proposes fluorescent in situ hybridization, combined with flow cytometry (FISH-FLOW), as an alternative approach for phylum level identification of Firmicutes, Bacteroidetes, Actinobacteria, and Proteobacteria and quantification of target bacteria from the GIT based on analysis of fecal samples, where results are validated by quantitative polymerase chain reaction (qPCR) and 16S ribosomal ribonucleic acid (16s rRNA) sequencing. The results obtained via FISH-FLOW experimental approach show high specificity for the developed probes for hybridization with the target bacteria. The study, therefore, suggests the FISH-FLOW as a reliable method for studying bacterial communities in the gut with results correlating well with those of metagenomic investigations of the same fecal samples.

Elucidating the Mechanism of Large-Diameter Titanium Dioxide Nanotubes in Protecting Osteoblasts Under Oxidative Stress Environment: The Role of Fibronectin and Albumin Adsorption.

Large-diameter titanium dioxide nanotubes (TNTs) have shown promise in preserving osteoblast function under oxidative stress (OS) in vitro. However, their ability to enhance osteogenesis in vivo under OS conditions and the underlying mechanisms remain unclear. This study aimed to evaluate the osteogenic potential of 110 nm TNTs (TNT110) compared to 30 nm TNTs (TNT30) in an aging rat model exhibiting OS, and to investigate the mechanisms involved. Surface properties of TNTs were characterized, and in vitro and in vivo experiments were conducted to assess their osteoinductive effects under OS. Transcriptomic, proteomic analyses, and Western blotting were performed to investigate the protective mechanisms of TNT110 on osteoblasts. Protein adsorption studies focused on the roles of fibronectin (FN) and albumin (BSA) in modulating osteoblast behavior on TNT110. In both in vitro and in vivo experiments, TNT110 significantly improved new bone formation and supported osteoblast survival under OS conditions. Subsequent ribonucleic acid sequencing results indicated that TNT110 tended to attenuate inflammatory responses and reactive oxygen species (ROS) expression while promoting endoplasmic reticulum (ER) stress and extracellular matrix receptor interactions, all of which are crucial for osteoblast survival and functionality. Further confirmation indicated that the cellular behavior changes of osteoblasts in the TNT110 group could only occur in the presence of serum. Moreover, proteomic analysis under OS conditions revealed the pivotal roles of FN and BSA in augmenting TNT110's resistance to OS. Surface pretreatment of TNT110 with FN/BSA alone could beneficially influence the early adhesion, spreading, ER activity, and ROS expression of osteoblasts, a trend not observed with TNT30. TNT110 effectively protects osteoblast function in the OS microenvironment by modulating protein adsorption, with FN and BSA synergistically enhancing osteogenesis. These findings suggest TNT110's potential for use in implants for elderly patients.

Effects of Shaofu Zhuyu decoction on intestinal flora and fibrosis in a mouse model of endometriosis

Shaofu Zhuyu decoction has been widely used to treat gynecological diseases; however, its mechanism of action in endometriosis remains unclear. We analyzed Shaofu Zhuyu decoction’s chemical composition using ultra-high performance liquid chromatography-mass spectrometry. In an endometriosis mouse model, ectopic lesions weight measurements and hematoxylin and eosin staining were used to assess the therapeutic efficacy of Shaofu Zhuyu decoction. Effects on intestinal microflora were analyzed using 16S ribosomal ribonucleic acid sequencing, and impacts on focal fibrosis were analyzed using Masson’s trichrome staining. Moreover, fibrosis- and metabolism-related proteins were assessed using immunohistochemistry and enzyme-linked immunosorbent assay. The study identified 157 chemical constituents within Shaofu Zhuyu decoction. Shaofu Zhuyu decoction treatment in mice with endometriosis resulted in a reduction in ectopic lesions weight (P<0.05) and delayed disease progression. Moreover, it improved the diversity and abundance of intestinal flora, and decreased the expression of Lachnospiraceae (P<0.05), Rikenellaceae (P<0.01), Ruminococcaceae (P<0.01), Lachnoclostridium (P<0.05), and unclassified_f__Ruminococcaceae (P<0.05). Kyoto Encyclopedia of Genes and Genomes analysis revealed enrichment in carbohydrate, amino acid, and lipid metabolism pathways. Masson’s trichrome staining revealed that compared to the untreated group, the Shaofu Zhuyu decoction group exhibited significantly reduced collagen deposition areas (P<0.001), lower TGF-β1 (P<0.001), COL1A1 (P<0.05), and α-SMA (P<0.01) expression in ectopic lesions, along with increased serum adiponectin (P<0.05), decreased serum leptin (P<0.05), TGF-β1 (P<0.001), and CTGF (P<0.05). Shaofu Zhuyu decoction regulates the intestinal flora of mice with endometriosis while also reducing fibrosis at the lesion site. These findings highlight novel mechanisms for its efficacy in alleviating endometriosis.

ScDFN: enhancing single-cell RNA-seq clustering with deep fusion networks.

Single-cell ribonucleic acid sequencing (scRNA-seq) technology can be used to perform high-resolution analysis of the transcriptomes of individual cells. Therefore, its application has gained popularity for accurately analyzing the ever-increasing content of heterogeneous single-cell datasets. Central to interpreting scRNA-seq data is the clustering of cells to decipher transcriptomic diversity and infer cell behavior patterns. However, its complexity necessitates the application of advanced methodologies capable of resolving the inherent heterogeneity and limited gene expression characteristics of single-cell data. Herein, we introduce a novel deep learning-based algorithm for single-cell clustering, designated scDFN, which can significantly enhance the clustering of scRNA-seq data through a fusion network strategy. The scDFN algorithm applies a dual mechanism involving an autoencoder to extract attribute information and an improved graph autoencoder to capture topological nuances, integrated via a cross-network information fusion mechanism complemented by a triple self-supervision strategy. This fusion is optimized through a holistic consideration of four distinct loss functions. A comparative analysis with five leading scRNA-seq clustering methodologies across multiple datasets revealed the superiority of scDFN, as determined by better the Normalized Mutual Information (NMI) and the Adjusted Rand Index (ARI) metrics. Additionally, scDFN demonstrated robust multi-cluster dataset performance and exceptional resilience to batch effects. Ablation studies highlighted the key roles of the autoencoder and the improved graph autoencoder components, along with the critical contribution of the four joint loss functions to the overall efficacy of the algorithm. Through these advancements, scDFN set a new benchmark in single-cell clustering and can be used as an effective tool for the nuanced analysis of single-cell transcriptomics.

A Statistical Methodology for Evaluating Asymmetry after Normalization with Application to Genomic Data

This study evaluates the symmetry of data distributions after normalization, focusing on various statistical tests, including a few explored test named Rp. We apply normalization techniques, such as variance stabilizing transformations, to ribonucleic acid sequencing data with varying sample sizes to assess their effectiveness in achieving symmetric data distributions. Our findings reveal that while normalization generally induces symmetry, some samples retain asymmetric distributions, challenging the conventional assumption of post-normalization symmetry. The Rp test, in particular, shows superior performance when there are variations in sample size and data distribution, making it a preferred tool for assessing symmetry when applied to genomic data. This finding underscores the importance of validating symmetry assumptions during data normalization, especially in genomic data, as overlooked asymmetries can lead to potential inaccuracies in downstream analyses. We analyze postmortem lateral temporal lobe samples to explore normal aging and Alzheimer’s disease, highlighting the critical role of symmetry testing in the accurate interpretation of genomic data.

Apoptosis and Oxidative Stress in Human Intestinal Epithelial Caco-2 Cells Caused by Marine Phycotoxin Azaspiracid-2.

When humans consume seafood contaminated by lipophilic polyether phycotoxins, such as azaspiracids (AZAs), the toxins are mainly leached and absorbed in the small intestine, potentially causing intestinal damage. In this study, human intestinal epithelial Caco-2 cells were used to investigate the adverse effects of azaspiracid-2 (AZA-2) on human intestinal epithelial cells. Cell viability, apoptosis, oxidative damage and mitochondrial ultrastructure were investigated, and ribonucleic acid sequence (RNA-seq) analysis was applied to explore the potential mechanisms of AZA-2 toxicity to Caco-2 cells. Results showed that AZA-2 significantly reduced the proliferation of Caco-2 cells in a concentration-dependent response, and the 48 h EC50 of AZA-2 was 12.65 nmol L-1. AZA-2 can induce apoptosis in Caco-2 cells in a dose-dependent manner. Visible mitochondrial swelling, cristae disintegration, membrane rupture and autophagy were observed in Caco-2 cells exposed to AZA-2. Reactive oxygen species (ROS) and malondialdehyde (MDA) content were significantly increased in Caco-2 cells after 48 h of exposure to 1 and 10 nmol L-1 of AZA-2. Transcriptome analysis showed that KEGG pathways related to cellular oxidative damage and lipid metabolism were affected, mainly including mitophagy, oxidative phosphorylation, cholesterol metabolism, vitamin digestion and absorption, bile secretion and the peroxisome proliferator-activated receptor signaling pathway. The cytotoxic effects of AZA-2 on Caco-2 cells may be associated with ROS-mediated autophagy and apoptosis in mitochondrial cells. Results of this study improve understanding of the cytotoxicity and molecular mechanisms of AZA-2 on Caco-2 cells, which is significant for protecting human health.

Phosphoribosyl pyrophosphate amidotransferase: Novel biomarker and therapeutic target for nasopharyngeal carcinoma.

Cancer cells show a dynamic metabolic landscape, requiring a sufficient supply of nucleotides to proliferate. They are highly dependent on de novo purine biosynthetic pathways for their nucleotide requirements. Phosphoribosyl pyrophosphate amidotransferase (PPAT), catalyzing the first step of de novo purine biosynthesis, is highly expressed in various cancers. We observed an increased expression of PPAT in nasopharyngeal carcinoma (NPC). Moreover, our ribonucleic acid sequencing analysis showed high PPAT expression in Epstein-Barr virus-positive NPC, which was supported by invitro analysis. Through a gene knockdown study, we showed that the suppression of PPAT expression reduced the proliferation and invasion of NPC cells. We also demonstrated the regulation of PPAT by glutamine, a cosubstrate for PPAT. A glutamine antagonist, 6-diazo-5-oxo-L-norleucine, blocked glutamine-mediated induction of PPAT and reduced NPC cell proliferation. Immunohistochemical analysis of PPAT in NPC tissues revealed increased expression of PPAT with disease progression, which was significantly associated with poor prognosis. In summary, this study highlighted the biological function of PPAT in NPC, establishing its potential as a novel prognostic biomarker for aggressive NPC and a promising therapeutic target.

Therapeutic delivery of CCL2 modulates immune response and restores host-microbe homeostasis.

Many chronic inflammatory diseases are attributed to disturbances in host-microbe interactions, which drive immune-mediated tissue damage. Depending on the anatomic setting, a chronic inflammatory disease can exert unique local and systemic influences, which provide an exceptional opportunity for understanding disease mechanism and testing therapeutic interventions. The oral cavity is an easily accessible environment that allows for protective interventions aiming at modulating the immune response to control disease processes driven by a breakdown of host-microbe homeostasis. Periodontal disease (PD) is a prevalent condition in which quantitative and qualitative changes of the oral microbiota (dysbiosis) trigger nonresolving chronic inflammation, progressive bone loss, and ultimately tooth loss. Here, we demonstrate the therapeutic benefit of local sustained delivery of the myeloid-recruiting chemokine (C-C motif) ligand 2 (CCL2) in murine ligature-induced PD using clinically relevant models as a preventive, interventional, or reparative therapy. Local delivery of CCL2 into the periodontium inhibited bone loss and accelerated bone gain that could be ascribed to reduced osteoclasts numbers. CCL2 treatment up-regulated M2-macrophage and downregulated proinflammatory and pro-osteoclastic markers. Furthermore, single-cell ribonucleic acid (RNA) sequencing indicated that CCL2 therapy reversed disease-associated transcriptomic profiles of murine gingival macrophages via inhibiting the triggering receptor expressed on myeloid cells-1 (TREM-1) signaling in classically activated macrophages and inducing protein kinase A (PKA) signaling in infiltrating macrophages. Finally, 16S ribosomal ribonucleic acid (rRNA) sequencing showed mitigation of microbial dysbiosis in the periodontium that correlated with a reduction in microbial load in CCL2-treated mice. This study reveals a novel protective effect of CCL2 local delivery in PD as a model for chronic inflammatory diseases caused by a disturbance in host-microbe homeostasis.

Exploring the transcriptomic and metabolomic profiles of adipose tissues: Insights and implications for fat grafting

BackgroundExpanding on our prior research on murine fat grafts' metabolic shift, this study delves deeper into the metabolic profiles of human adipose tissues, specifically the superficial subcutaneous adipose tissue (SSAT) and deep subcutaneous adipose tissue (DSAT). MethodsUtilizing RNA-sequencing, metabolome, and metabolic flux analyses, we examined SSAT and DSAT samples obtained during deep inferior epigastric perforator flap breast reconstructions. Transcript data underwent unsupervised hierarchical clustering and Gene set enrichment analysis. Metabolomics involved analyzing samples for cationic and anionic metabolites via Capillary Electrophoresis Time-of-Flight Mass Spectrometry (CE-TOFMS), followed by principal component analysis (PCA) and heat map generation. Additionally, primary adipocytes from SSAT and DSAT were assessed using the Seahorse® extracellular flux analyzer. ResultsPCA and heat map analyses highlighted distinct transcriptome and metabolome differences between SSAT and DSAT. SSAT predominantly upregulated genes linked to adipogenesis (false discovery rate [FDR] q < 0.0001), oxidative phosphorylation (FDR q < 0.0001), fatty acid metabolism (FDR q <0.0001), and glycolysis (FDR q = 0.001). In contrast, DSAT showed a significant upregulation in inflammatory response genes (FDR q <0.05). Metabolite analysis revealed an abundance of glycolytic metabolites in SSAT, whereas DSAT was rich in metabolites associated with fatty acid metabolism and oxidative phosphorylation. Cellular flux analysis further confirmed SSAT's elevated glycolysis and spare oxidative phosphorylation capacities. ConclusionOur results highlight the metabolic uniqueness of SSAT and DSAT in humans, with SSAT exhibiting superior metabolic flexibility. The implications of these metabolic differences, especially in fat grafting procedures, necessitate further research and exploration in future studies. Data availabilityThe ribonucleic acid sequencing data were deposited in the Gene Expression Omnibus database (GSE216803). https://www.ncbi.nlm.nih.gov/geo/query/acc.cgi?acc=GSE216803 (GEO token: qnsngiuqplqdpaf).

Repeat administration of human umbilical cord mesenchymal stem cells improves left ventricular diastolic function in mice with heart failure with preserved ejection fraction

Currently, no therapy is proven to effectively improve heart failure with preserved ejection fraction (HFpEF). Although stem cell therapy has demonstrated promising results in treating ischemic heart disease, the effectiveness of treating HFpEF with human umbilical cord mesenchymal stem cells (hucMSCs) remains unclear. To answer this question, we administered hucMSCs intravenously (i.v.), either once or repetitively, in a mouse model of HFpEF induced by a high-fat diet and NG-nitroarginine methyl ester hydrochloride. hucMSC treatment improved left ventricular diastolic dysfunction, reduced heart weight and pulmonary edema, and attenuated cardiac modeling (inflammation, interstitial fibrosis, and hypertrophy) in HFpEF mice. Repeat hucMSC administration had better outcomes than a single injection. In vitro, hucMSC culture supernatants reduced maladaptive remodeling in neonatal-rat cardiomyocytes. Ribonucleic acid sequencing and protein level analysis of left ventricle (LV) tissues suggested that hucMSCs activated the protein kinase B (Akt)/forkhead box protein O1 (FoxO1) signaling pathway to treat HFpEF. Inhibition of this pathway reversed the efficacy of hucMSC treatment. In conclusion, these findings indicated that hucMSCs could be a viable therapeutic option for HFpEF.

PMart Web Application: Marketplace for Interactive Analysis of Panomics Data.

PMart is a web-based tool for reproducible quality control, exploratory data analysis, statistical analysis, and interactive visualization of 'omics data, based on the functionality of the pmartR R package. The newly improved user interface supports more 'omics data types, additional statistical capabilities, and enhanced options for creating downloadable graphics. PMart supports the analysis of label-free and isobaric-labeled (e.g., TMT, iTRAQ) proteomics, nuclear magnetic resonance (NMR) and mass-spectrometry (MS)-based metabolomics, MS-based lipidomics, and ribonucleic acid sequencing (RNA-seq) transcriptomics data. At the end of a PMart session, a report is available that summarizes the processing steps performed and includes the pmartR R package functions used to execute the data processing. In addition, built-in safeguards in the backend code prevent users from utilizing methods that are inappropriate based on omics data type. PMart is a user-friendly interface for conducting exploratory data analysis and statistical comparisons of omics data without programming.

Erythrocyte Very Long-Chain Saturated Fatty Acids, Gut Microbiota-Bile Acid Axis, and Incident Coronary Artery Disease in Adults: A Prospective Cohort Study

BackgroundPrior research has highlighted inverse associations between concentrations of circulating very long-chain saturated fatty acids (VLCSFAs) and coronary artery disease (CAD). However, the intricate links involving VLCSFAs, gut microbiota, and bile acids remain underexplored. ObjectivesThis study examined the association of erythrocyte VLCSFAs with CHD incidence, focusing on the mediating role of gut microbiota and fecal bile acids. MethodsThis 10-y prospective study included 2383 participants without CHD at baseline. Erythrocyte VLCSFAs [arachidic acid (C20:0), behenic acid (C22:0), and lignoceric acid (C24:0)] were measured using gas chromatography at baseline, and 274 CHD incidents were documented in triennial follow-ups. Gut microbiota in 1744 participants and fecal bile acid metabolites in 945 participants were analyzed using 16S ribosomal ribonucleic acid sequencing and ultra-performance liquid chromatography-tandem mass spectrometry at middle-term. ResultsThe multivariable-adjusted hazard ratios (95% confidence interval) for CHD incidence in highest compared with lowest quartiles were 0.87 (0.61, 1.25) for C20:0, 0.63 (0.42, 0.96) for C22:0, 0.59 (0.41, 0.85) for C24:0, and 0.57 (0.39, 0.83) for total VLCSFAs. Participants with higher total VLCSFA concentrations exhibited increased abundances of Holdemanella, Coriobacteriales Incertae Sedis spp., Ruminococcaceae UCG-005 and UCG-010, and Lachnospiraceae ND3007 group. These 5 genera generated overlapping differential microbial scores (ODMSs) that accounted for 11.52% of the total VLCSFAs-CHD association (Pmediation = 0.018). Bile acids tauro_α_ and tauro_β_muricholic acid were inversely associated with ODMS and positively associated with incident CHD. Opposite associations were found for glycolithocholic acid and glycodeoxycholic acid. Mediation analyses indicated that glycolithocholic acid, glycodeoxycholic acid, and tauro_α_ and tauro_β_muricholic acid explained 56.40%, 35.19%, and 26.17% of the ODMS-CHD association, respectively (Pmediation = 0.002, 0.008, and 0.020). ConclusionsElevated erythrocyte VLCSFAs are inversely associated with CHD risk in the Chinese population, with gut microbiota and fecal bile acid profiles potentially mediating this association. The identified microbiota and bile acid metabolites may serve as potential intervention targets in future studies.This trial was registered at www.clinicaltrials.gov as NCT03179657.

Exploring the potential of omics technologies in medicinal plant research: A review in Colombia

This review presents advances in the implementation of high-throughput sequencing and its application to the knowledge of medicinal plants. We conducted a bibliographic search of papers published in PubMed, Science Direct, Google Scholar, Scopus, and Web of Science databases and analyzed the obtained data using VOSviewer (version 1.6.19). Given that medicinal plants are a source of specialized metabolites with immense therapeutic values and important pharmacological properties, plant researchers around the world have turned their attention toward them and have begun to examine them widely. Recent advances in sequencing technologies have reduced cost and time demands and accelerated medicinal plant research. Such research leverages full genome sequencing, as well as RNA (ribonucleic acid) sequencing and the analysis of the transcriptome, to identify molecular markers of species and functional genes that control key biological traits, as well as to understand the biosynthetic pathways of bioactive metabolites and regulatory mechanisms of environmental responses. As such, the omics (e.g., transcriptomics, metabolomics, proteomics, and genomics, among others) have been widely applied within the study of medicinal plants, although their usage in Colombia is still few and, in some areas, scarce.

Unveiling G-protein coupled receptors as potential targets for ovarian cancer nanomedicines: from RNA sequencing data analysis to in vitro validation

Genetic heterogeneity in ovarian cancer indicates the need for personalised treatment approaches. Currently, very few G-protein coupled receptors (GPCRs) have been investigated for active targeting with nanomedicines such as antibody-conjugated drugs and drug-loaded nanoparticles, highlighting a neglected potential to develop personalised treatment. To address the genetic heterogeneity of ovarian cancer, a future personalised approach could include the identification of unique GPCRs expressed in cancer biopsies, matched with personalised GPCR-targeted nanomedicines, for the delivery of lethal drugs to tumour tissue before, during and after surgery. Here we report on the systematic analysis of public ribonucleic acid-sequencing (RNA-seq) gene expression data, which led to prioritisation of 13 GPCRs as candidates with frequent overexpression in ovarian cancer tissues. Subsequently, primary ovarian cancer cells derived from ascites and ovarian cancer cell lines were used to confirm frequent gene expression for the selected GPCRs. However, the expression levels showed high variability within our selection of samples, therefore, supporting and emphasising the need for the future development of case-to-case personalised targeting approaches.

Detecting microsatellite instability by length comparison of microsatellites in the 3' untranslated region with RNA-seq.

Microsatellite instability (MSI), a phenomenon caused by deoxyribonucleic acid (DNA) mismatch repair system deficiencies, is an important biomarker in cancer research and clinical diagnostics. MSI detection often involves next-generation sequencing data, with many studies focusing on DNA. Here, we introduce a novel approach by measuring microsatellite lengths directly from ribonucleic acid sequencing (RNA-seq) data and comparing its distribution to detect MSI. Our findings reveal distinct instability patterns between MSI-high (MSI-H) and microsatellite stable samples, indicating the efficacy of RNA-based MSI detection. Additionally, microsatellites in the 3'-untranslated regions showed the greatest predictive value for MSI detection. Notably, this efficacy extends to detecting MSI-H samples even in tumors not commonly associated with MSI. Our approach highlights the utility of RNA-seq data in MSI detection, facilitating more precise diagnostics through the integration of various biological data.