Gene Updater: a web tool that autocorrects and updates for Excel misidentified gene names

Molybdenum's Role as an Essential Element in Enzymes Catabolizing Redox Reactions: A Review

Molybdenum (Mo) is an essential element for human life, acting as a cofactor in various enzymes crucial for metabolic homeostasis. This review provides a comprehensive insight into the latest advances in research on molybdenum-containing enzymes and their clinical significance. One of these enzymes is xanthine oxidase (XO), which plays a pivotal role in purine catabolism, generating reactive oxygen species (ROS) capable of inducing oxidative stress and subsequent organ dysfunction. Elevated XO activity is associated with liver pathologies such as non-alcoholic fatty liver disease (NAFLD) and hepatocellular carcinoma (HCC). Aldehyde oxidases (AOs) are also molybdenum-containing enzymes that, similar to XO, participate in drug metabolism, with notable roles in the oxidation of various substrates. However, beneath its apparent efficacy, AOs' inhibition may impact drug effectiveness and contribute to liver damage induced by hepatotoxins. Another notable molybdenum-enzyme is sulfite oxidase (SOX), which catalyzes the conversion of sulfite to sulfate, crucial for the degradation of sulfur-containing amino acids. Recent research highlights SOX's potential as a diagnostic marker for HCC, offering promising sensitivity and specificity in distinguishing cancerous lesions. The newest member of molybdenum-containing enzymes is mitochondrial amidoxime-reducing component (mARC), involved in drug metabolism and detoxification reactions. Emerging evidence suggests its involvement in liver pathologies such as HCC and NAFLD, indicating its potential as a therapeutic target. Overall, understanding the roles of molybdenum-containing enzymes in human physiology and disease pathology is essential for advancing diagnostic and therapeutic strategies for various health conditions, particularly those related to liver dysfunction. Further research into the molecular mechanisms underlying these enzymes' functions could lead to novel treatments and improved patient outcomes.

Placental expression quantitative trait loci in an East Asian population

Expression quantitative trait loci (eQTL) analysis measures the contribution of genetic variation in gene expression on complex traits. Although this methodology has been used to examine gene regulation in numerous human tissues, eQTL research in solid tissues is relatively lacking. We conducted eQTL analysis on placentas collected from an East Asian population in an effort to identify gene regulatory mechanisms in this tissue. Placentas (n = 102) were collected at the time of cesarean delivery. mRNA was extracted, sequenced with NGS, and compared with matched maternal and fetal DNA arrays performed using maternal and neonatal cord blood. Linear regression modeling was performed using tensorQTL. Fine-mapping along with epigenomic annotation was used to select putative functional variants. We identified 2,703 coding genes that contained at least one eQTL with statistical significance (false discovery rate <0.05). After fine-mapping, we found 108 previously unreported eQTL variants with posterior inclusion probability >0.1. Of these, 19% were located in genomic regions with evidence from public placental epigenome suggesting that they may be functionally relevant. For example, variant rs28379289 located in the placenta-specific regulatory region changes the binding affinity of transcription factor leading to higher expression of LGALS3, which is known to affect placental function. This study expands the knowledge base of regulatory elements within the human placenta and identifies 108 previously unreported placenta eQTL signals, which are listed in our publicly available GMI eQTL database. Further studies are needed to identify and characterize genetic regulatory mechanisms that affect placental function in normal pregnancy and placenta-related diseases.

The History of mARC

The mitochondrial amidoxime-reducing component (mARC) is the most recently discovered molybdoenzyme in humans after sulfite oxidase, xanthine oxidase and aldehyde oxidase. Here, the timeline of mARC's discovery is briefly described. The story begins with investigations into N-oxidation of pharmaceutical drugs and model compounds. Many compounds are N-oxidized extensively in vitro, but it turned out that a previously unknown enzyme catalyzes the retroreduction of the N-oxygenated products in vivo. After many years, the molybdoenzyme mARC could finally be isolated and identified in 2006. mARC is an important drug-metabolizing enzyme and N-reduction by mARC has been exploited very successfully for prodrug strategies, that allow oral administration of otherwise poorly bioavailable therapeutic drugs. Recently, it was demonstrated that mARC is a key factor in lipid metabolism and likely involved in the pathogenesis of non-alcoholic fatty liver disease (NAFLD). The exact link between mARC and lipid metabolism is not yet fully understood. Regardless, many now consider mARC a potential drug target for the prevention or treatment of liver diseases. This article focusses on discoveries related to mammalian mARC enzymes. mARC homologues have been studied in algae, plants and bacteria. These will not be discussed extensively here.

STAGEs: A web-based tool that integrates data visualization and pathway enrichment analysis for gene expression studies

Gene expression profiling has helped tremendously in the understanding of biological processes and diseases. However, interpreting processed data to gain insights into biological mechanisms remain challenging, especially to the non-bioinformaticians, as many of these data visualization and pathway analysis tools require extensive data formatting. To circumvent these challenges, we developed STAGEs (Static and Temporal Analysis of Gene Expression studies) that provides an interactive visualisation of omics analysis outputs. Users can directly upload data created from Excel spreadsheets and use STAGEs to render volcano plots, differentially expressed genes stacked bar charts, pathway enrichment analysis by Enrichr and Gene Set Enrichment Analysis (GSEA) against established pathway databases or customized gene sets, clustergrams and correlation matrices. Moreover, STAGEs takes care of Excel gene to date misconversions, ensuring that every gene is considered for pathway analysis. Output data tables and graphs can be exported, and users can easily customize individual graphs using widgets such as sliders, drop-down menus, text boxes and radio buttons. Collectively, STAGEs is an integrative platform for data analysis, data visualisation and pathway analysis, and is freely available at https://kuanrongchan-stages-stages-vpgh46.streamlitapp.com/ . In addition, developers can customise or modify the web tool locally based on our existing codes, which is publicly available at https://github.com/kuanrongchan/STAGES .