Single-cell RNA sequencing highlights the roles of C1QB and NKG7 in the pancreatic islet immune microenvironment in type 1 diabetes mellitus

A systematic review of single-cell RNA sequencing applications and innovations

Bulk RNA sequencing is one type of RNA sequencing technique, as well as targeted RNA sequencing and whole transcriptome sequencing. It provides valuable insights into gene expression in specific cell populations or regions. However, these methods often miss the diversity of cells within complex tissues. This restriction is overcome by single-cell RNA sequencing, which records gene expression at the single-cell level. It offers a detailed picture of the diversity of cells. It is essential to study glucose homeostasis. It offers thorough explanations of cellular variation. Networks and Governance Dynamics The use of scRNA-seq in islet cells is reviewed in this study, along with sample preparation, sequencing, and computational analysis. It highlights advances in understanding cell types. Gene activity and cell interactions. Along with the challenges and limitations of scRNA-seq, this review highlights the importance of scRNA-seq in understanding complex biological processes and diseases. It is an essential resource for future research and method development in this field, which will help to build personalized treatment.

RNA-based diagnostic innovations: A new frontier in diabetes diagnosis and management

Background/Objective: Diabetes mellitus (DM) remains a major global health challenge due to its chronic nature and associated complications. Traditional diagnostic approaches, though effective, often lack the sensitivity required for early-stage detection. Recent advancements in molecular biology have identified RNA molecules, particularly non-coding RNAs such as microRNAs (miRNAs), long non-coding RNAs (lncRNAs), and circular RNAs (circRNAs), as promising biomarkers for diabetes. This review aims to explore the role of RNA-based biomarkers in the diagnosis, prognosis, and management of diabetes, highlighting their potential to revolutionize diabetes care.Method: A comprehensive literature review was conducted using electronic databases including PubMed, Scopus, and Web of Science. Articles published up to 2024 were screened and analyzed to extract relevant findings related to RNA-based diagnostics in diabetes. Emphasis was placed on studies demonstrating clinical utility, mechanistic insights, and translational potential of RNA molecules.Results: Numerous RNA species, particularly miRNAs such as miR-375, miR-29, and lncRNAs like H19 and MEG3, exhibit altered expression patterns in diabetic patients. These molecules are involved in key regulatory pathways of glucose metabolism, insulin resistance, and β-cell function. Circulating RNAs are detectable in various biofluids, enabling non-invasive diagnostic approaches. Emerging technologies, including RNA sequencing and liquid biopsy platforms, have enhanced the sensitivity and specificity of RNA detection, fostering the development of novel diagnostic tools and personalized therapeutic strategies.Conclusion: RNA-based biomarkers hold significant promise in advancing early detection, risk stratification, and therapeutic monitoring in diabetes care. Despite current challenges such as standardization and clinical validation, the integration of RNA diagnostics into routine clinical practice could transform diabetes management, paving the way for precision medicine approaches. Further research and multi-center trials are essential to validate these biomarkers and facilitate their regulatory approval and clinical implementation.

A molecular mechanism for bright color variation in parrots

Parrots produce stunning plumage colors through unique pigments called psittacofulvins. However, the mechanism underlying their ability to generate a spectrum of vibrant yellows, reds, and greens remains enigmatic. We uncover a unifying chemical basis for a wide range of parrot plumage colors, which result from the selective deposition of red aldehyde- and yellow carboxyl-containing psittacofulvin molecules in developing feathers. Through genetic mapping, biochemical assays, and single-cell genomics, we identified a critical player in this process, the aldehyde dehydrogenase ALDH3A2, which oxidizes aldehyde psittacofulvins into carboxyl forms in late-differentiating keratinocytes during feather development. The simplicity of the underlying molecular mechanism, in which a single enzyme influences the balance of red and yellow pigments, offers an explanation for the exceptional evolutionary lability of parrot coloration.

Deciphering the molecular nexus between Omicron infection and acute kidney injury: a bioinformatics approach

Background

The ongoing global health crisis of COVID-19, and particularly the challenges posed by recurrent infections of the Omicron variant, have significantly strained healthcare systems worldwide. There is a growing body of evidence indicating an increased susceptibility to Omicron infection in patients suffering from Acute Kidney Injury (AKI). However, the intricate molecular interplay between AKI and Omicron variant of COVID-19 remains largely enigmatic.

Methods

This study employed a comprehensive analysis of human RNA sequencing (RNA-seq) and microarray datasets to identify differentially expressed genes (DEGs) associated with Omicron infection in the context of AKI. We engaged in functional enrichment assessments, an examination of Protein-Protein Interaction (PPI) networks, and advanced network analysis to elucidate the cellular signaling pathways involved, identify critical hub genes, and determine the relevant controlling transcription factors and microRNAs. Additionally, we explored protein-drug interactions to highlight potential pharmacological interventions.

Results

Our investigation revealed significant DEGs and cellular signaling pathways implicated in both Omicron infection and AKI. We identified pivotal hub genes, including EIF2AK2, PLSCR1, GBP1, TNFSF10, C1QB, and BST2, and their associated regulatory transcription factors and microRNAs. Notably, in the murine AKI model, there was a marked reduction in EIF2AK2 expression, in contrast to significant elevations in PLSCR1, C1QB, and BST2. EIF2AK2 exhibited an inverse relationship with the primary AKI mediator, Kim-1, whereas PLSCR1 and C1QB demonstrated strong positive correlations with it. Moreover, we identified potential therapeutic agents such as Suloctidil, Apocarotenal, 3'-Azido-3'-deoxythymidine, among others. Our findings also highlighted a correlation between the identified hub genes and diseases like myocardial ischemia, schizophrenia, and liver cirrhosis. To further validate the credibility of our data, we employed an independent validation dataset to verify the hub genes. Notably, the expression patterns of PLSCR1, GBP1, BST2, and C1QB were consistent with our research findings, reaffirming the reliability of our results.

Conclusion

Our bioinformatics analysis has provided initial insights into the shared genetic landscape between Omicron COVID-19 infections and AKI, identifying potential therapeutic targets and drugs. This preliminary investigation lays the foundation for further research, with the hope of contributing to the development of innovative treatment strategies for these complex medical conditions.

Effect of supplementing lysins and methionine to low-protein diets on growth performance, hepatic antioxidant capacity, immune status, and glycolytic activity of tibetan sheep

Reducing the levels of dietary protein is an effective nutritional approach in lowering feed cost and nitrogen emissions in ruminants. The purpose of this study was to evaluate the effects of dietary Lys/Met ratio in a low protein diet (10%, dry matter basis) on the growth performance and hepatic function (antioxidant capacity, immune status, and glycolytic activity) in Tibetan lambs. Ninety two-month-old rams with an average weight of 15.37 ± 0.92 kg were randomly assigned to LP-L (dietary Lys/Met = 1:1), LP-M (dietary Lys/Met = 2:1) and LP-H (dietary Lys/Met = 3:1) treatments. The trial was conducted over 100 d, including 10 d of adaption to the diets. Hepatic phenotypes, antioxidant capacity, immune status, glycolytic activity and gene expression profiling was detected after the conclusion of the feeding trials. The results showed that the body weight was higher in the LP-L group when compared to those on the LP-M group (P < 0.05). In addition, the activities of the catalase (CAT) and glutathione peroxidase (GSH-Px) in the LP-L group were significantly increased compared with the LP-M group (P < 0.05), while the malondialdehyde (MDA) levels in LP-H group were significantly decreased (P < 0.05). Compared with LP-H group, both hepatic glycogen (P < 0.01) and lactate dehydrogenase (LDH) (P < 0.05) were significantly elevated in LP-L group. For the LP-L group, the hepatocytes were arranged radially with the central vein in the center, and hepatic plates exhibited tight arrangement. Transcriptome analysis identified 29, 179, and 129 differentially expressed genes (DEGs) between the LP-M vs. LP-L, LP-H vs. LP-M, and LP-H vs. LP-L groups, respectively (Q-values < 0.05 and |log2Fold Change| > 1). Gene Ontology (GO) and correlation analyses showed that in the LP-L group, core genes (C1QA and JUNB) enriched in oxidoreductase activity were positively correlated with antioxidant indicators, while the MYO9A core gene enriched in the immune response was positively associated with immune indicators, and core genes enriched in molecular function (PDK3 and PDP2) were positively correlated with glycolysis indicators. In summary, low-protein diet with a low Lys/Met ratio (1:1) could reduce the hepatic oxidative stress and improve the glycolytic activity by regulating the expression of related genes of Tibetan sheep.

Autoimmune CD8+ T cells in type 1 diabetes: from single-cell RNA sequencing to T-cell receptor redirection

Type 1 diabetes (T1D) is an organ-specific autoimmune disease caused by pancreatic β cell destruction and mediated primarily by autoreactive CD8+ T cells. It has been shown that only a small number of stem cell-like β cell-specific CD8+ T cells are needed to convert normal mice into T1D mice; thus, it is likely that T1D can be cured or significantly improved by modulating or altering self-reactive CD8+ T cells. However, stem cell-type, effector and exhausted CD8+ T cells play intricate and important roles in T1D. The highly diverse T-cell receptors (TCRs) also make precise and stable targeted therapy more difficult. Therefore, this review will investigate the mechanisms of autoimmune CD8+ T cells and TCRs in T1D, as well as the related single-cell RNA sequencing (ScRNA-Seq), CRISPR/Cas9, chimeric antigen receptor T-cell (CAR-T) and T-cell receptor-gene engineered T cells (TCR-T), for a detailed and clear overview. This review highlights that targeting CD8+ T cells and their TCRs may be a potential strategy for predicting or treating T1D.

Identification of Age-Related Characteristic Genes Involved in Severe COVID-19 Infection Among Elderly Patients Using Machine Learning and Immune Cell Infiltration Analysis

Elderly patients infected with severe acute respiratory syndrome coronavirus 2 are at higher risk of severe clinical manifestation, extended hospitalization, and increased mortality. Those patients are more likely to experience persistent symptoms and exacerbate the condition of basic diseases with long COVID-19 syndrome. However, the molecular mechanisms underlying severe COVID-19 in the elderly patients remain unclear. Our study aims to investigate the function of the interaction between disease-characteristic genes and immune cell infiltration in patients with severe COVID-19 infection. COVID-19 datasets (GSE164805 and GSE180594) and aging dataset (GSE69832) were obtained from the Gene Expression Omnibus database. The combined different expression genes (DEGs) were subjected to Gene Ontology (GO) functional enrichment analysis, Kyoto Encyclopedia of Genes and Genomes (KEGG) pathway and Diseases Ontology functional enrichment analysis, Gene Set Enrichment Analysis, machine learning, and immune cell infiltration analysis. GO and KEGG enrichment analyses revealed that the eight DEGs (IL23A, PTGER4, PLCB1, IL1B, CXCR1, C1QB, MX2, ALOX12) were mainly involved in inflammatory mediator regulation of TRP channels, coronavirus disease-COVID-19, and cytokine activity signaling pathways. Three-degree algorithm (LASSO, SVM-RFE, KNN) and correlation analysis showed that the five DEGs up-regulated the immune cells of macrophages M0/M1, memory B cells, gamma delta T cell, dendritic cell resting, and master cell resisting. Our study identified five hallmark genes that can serve as disease-characteristic genes and target immune cells infiltrated in severe COVID-19 patients among the elderly population, which may contribute to the study of pathogenesis and the evaluation of diagnosis and prognosis in aging patients infected with severe COVID-19.