Identification of key genes and molecular mechanisms of chronic urticaria based on bioinformatics.

Chronic urticaria (CU) is characterized by persistent skin hives, redness, and itching, enhanced by immune dysregulation and inflammation. Our main objective is identifying key genes and molecular mechanisms of chronic urticaria based on bioinformatics. We used the Gene Expression Omnibus (GEO) database and retrieved two GEO datasets, GSE57178 and GSE72540. The raw data were extracted, pre-processed, and analyzed using the GEO2R tool to identify the differentially expressed genes (DEGs). The samples were divided into two groups: healthy samples and CU samples. We defined cut-off values of log2 fold change ≥1 and p < .05. Analyses were performed in the Kyoto Encyclopaedia of Genes and Genomes (KEGG), the Database for Annotation, Visualization and Integrated Discovery (DAVID), Metascape, Search Tool for the Retrieval of Interacting Genes/Proteins (STRING) and CIBERSOFT databases. We obtained 1613 differentially expressed genes. There were 114 overlapping genes in both datasets, out of which 102 genes were up-regulated while 12 were down-regulated. The biological processes included activation of myeloid leukocytes, response to inflammations, and response to organic substances. Moreover, the KEGG pathways of CU were enriched in the Nuclear Factor-Kappa B (NF-kB) signaling pathway, Tumor Necrosis Factor (TNF) signaling pathway, and Janus kinase/signal transducers and activators of transcription (JAK-STAT) signaling pathway. We identified 27 hub genes that were implicated in the pathogenesis of CU, such as interleukin-6 (IL-6), Prostaglandin-endoperoxide synthase 2 (PTGS2), and intercellular adhesion molecule-1 (ICAM1). The complex interplay between immune responses, inflammatory pathways, cytokine networks, and specific genes enhances CU. Understanding these mechanisms paves the way for potential interventions to mitigate symptoms and improve the quality of life of CU patients.

Integrative multi-omics analysis reveals the crucial biological pathways involved in the adaptive response to NaCl stress in peanut seedlings.

Plant growth is restricted by salt stress, which is a significant abiotic factor, particularly during the seedling stage. The aim of this study was to investigate the mechanisms underlying peanut adaptation to salt stress by transcriptomic and metabolomic analysis during the seedling stage. In this study, phenotypic variations of FH23 and NH5, two peanut varieties with contrasting tolerance to salt, changed obviously, with the strongest differences observed at 24 h. FH23 leaves wilted and the membrane system was seriously damaged. A total of 1470 metabolites were identified, with flavonoids being the most common (21.22%). Multi-omics analyses demonstrated that flavonoid biosynthesis (ko00941), isoflavones biosynthesis (ko00943), and plant hormone signal transduction (ko04075) were key metabolic pathways. The comparison of metabolites in isoflavone biosynthesis pathways of peanut varieties with different salt tolerant levels demonstrated that the accumulation of naringenin and formononetin may be the key metabolite leading to their different tolerance. Using our transcriptomic data, we identified three possible reasons for the difference in salt tolerance between the two varieties: (1) differential expression of LOC112715558 (HIDH) and LOC112709716 (HCT), (2) differential expression of LOC112719763 (PYR/PYL) and LOC112764051 (ABF) in the abscisic acid (ABA) signal transduction pathway, then (3) differential expression of genes encoding JAZ proteins (LOC112696383 and LOC112790545). Key metabolites and candidate genes related to improving the salt tolerance in peanuts were screened to promote the study of the responses of peanuts to NaCl stress and guide their genetic improvement.

Multiple toxins and a protease contribute to the aphid-killing ability of Pseudomonas fluorescens PpR24.

Aphids are globally important pests causing damage to a broad range of crops. Due to insecticide resistance, there is an urgent need to develop alternative control strategies. In our previous work, we found Pseudomonas fluorescens PpR24 can orally infect and kill the insecticide-resistant green-peach aphid (Myzus persicae). However, the genetic basis of the insecticidal capability of PpR24 remains unclear. Genome sequencing of PpR24 confirmed the presence of various insecticidal toxins such as Tc (toxin complexes), Rhs (rearrangement hotspot) elements, and other insect-killing proteases. Upon aphids infection with PpR24, RNA-Seq analysis revealed 193 aphid genes were differentially expressed with down-regulation of 16 detoxification genes. In addition, 1325 PpR24 genes (542 were upregulated and 783 downregulated) were subject to differential expression, including genes responsible for secondary metabolite biosynthesis, the iron-restriction response, oxidative stress resistance, and virulence factors. Single and double deletion of candidate virulence genes encoding a secreted protease (AprX) and four toxin components (two TcA-like; one TcB-like; one TcC-like insecticidal toxins) showed that all five genes contribute significantly to aphid killing, particularly AprX. This comprehensive host-pathogen transcriptomic analysis provides novel insight into the molecular basis of bacteria-mediated aphid mortality and the potential of PpR24 as an effective biocontrol agent.

Expression profiles and gene set enrichment analysis of the transcriptomes from the cancer tissue, white adipose tissue and paracancer tissue with colorectal cancer.

Background: Colorectal cancer (CRC) is one of the most common cancers worldwide and is related to diet and obesity. Currently, crosstalk between lipid metabolism and CRC has been reported; however, the specific mechanism is not yet understood. In this study, we screened differentially expressed long non-coding RNAs (lncRNAs) and mRNAs from primary cancer, paracancer, and white adipose tissue of CRC patients. We screened and analyzed the genes differentially expressed between primary and paracancer tissue and between paracancer and white adipose tissue but not between primary and white adipose tissue. According to the results of the biological analysis, we speculated a lncRNA (MIR503HG) that may be involved in the crosstalk between CRC and lipid metabolism through exosome delivery. Methods: We screened differentially expressed long non-coding RNAs (lncRNAs) and mRNAs from primary cancer, paracancer, and white adipose tissue of CRC patients. We screened and analyzed the genes differentially expressed between primary and paracancer tissue and between paracancer and white adipose tissue but not between primary and white adipose tissue. Results: We speculated a lncRNA (MIR503HG) that may be involved in the crosstalk between CRC and lipid metabolism through exosome delivery. Conclusions: In this study, the findings raise the possibility of crosstalk between lipid metabolism and CRC through the exosomal delivery of lncRNAs.

Transcriptomic changes in the microsporidia proliferation and host responses in congenitally infected embryos and larvae.

Congenital infection caused by vertical transmission of microsporidia N. bombycis can result in severe economic losses in the silkworm-rearing industry. Whole-transcriptome analyses have revealed non-coding RNAs and their regulatory networks in N. bombycis infected embryos and larvae. However, transcriptomic changes in the microsporidia proliferation and host responses in congenitally infected embryos and larvae remains unclear. Here, we simultaneously compared the transcriptomes of N. bombycis and its host B. mori embryos of 5-day and larvae of 1-, 5- and 10-day during congenital infection. For the transcriptome of N. bombycis, a comparison of parasite expression patterns between congenital-infected embryos and larva showed most genes related to parasite central carbon metabolism were down-regulated in larvae during infection, whereas the majority of genes involved in parasite proliferation and growth were up-regulated. Interestingly, a large number of distinct or shared differentially expressed genes (DEGs) were revealed by the Venn diagram and heat map, many of them were connected to infection related factors such as Ricin B lectin, spore wall protein, polar tube protein, and polysaccharide deacetylase. For the transcriptome of B. mori infected with N. bombycis, beyond numerous DEGs related to DNA replication and repair, mRNA surveillance pathway, RNA transport, protein biosynthesis, and proteolysis, with the progression of infection, a large number of DEGs related to immune and infection pathways, including phagocytosis, apoptosis, TNF, Toll-like receptor, NF-kappa B, Fc epsilon RI, and some diseases, were successively identified. In contrast, most genes associated with the insulin signaling pathway, 2-oxacarboxylic acid metabolism, amino acid biosynthesis, and lipid metabolisms were up-regulated in larvae compared to those in embryos. Furthermore, dozens of distinct and three shared DEGs that were involved in the epigenetic regulations, such as polycomb, histone-lysine-specific demethylases, and histone-lysine-N-methyltransferases, were identified via the Venn diagram and heat maps. Notably, many DEGs of host and parasite associated with lipid-related metabolisms were verified by RT-qPCR. Taken together, simultaneous transcriptomic analyses of both host and parasite genes lead to a better understanding of changes in the microsporidia proliferation and host responses in embryos and larvae in N. bombycis congenital infection.

A compendium of multi-omics data illuminating host responses to lethal human virus infections.

Human infections caused by viral pathogens trigger a complex gamut of host responses that limit disease, resolve infection, generate immunity, and contribute to severe disease or death. Here, we present experimental methods and multi-omics data capture approaches representing the global host response to infection generated from 45 individual experiments involving human viruses from the Orthomyxoviridae, Filoviridae, Flaviviridae, and Coronaviridae families. Analogous experimental designs were implemented across human or mouse host model systems, longitudinal samples were collected over defined time courses, and global multi-omics data (transcriptomics, proteomics, metabolomics, and lipidomics) were acquired by microarray, RNA sequencing, or mass spectrometry analyses. For comparison, we have included transcriptomics datasets from cells treated with type I and type II human interferon. Raw multi-omics data and metadata were deposited in public repositories, and we provide a central location linking the raw data with experimental metadata and ready-to-use, quality-controlled, statistically processed multi-omics datasets not previously available in any public repository. This compendium of infection-induced host response data for reuse will be useful for those endeavouring to understand viral disease pathophysiology and network biology.

CITEViz: interactively classify cell populations in CITE-Seq via a flow cytometry-like gating workflow using R-Shiny.

BACKGROUND: The rapid advancement of new genomic sequencing technology has enabled the development of multi-omic single-cell sequencing assays. These assays profile multiple modalities in the same cell and can often yield new insights not revealed with a single modality. For example, Cellular Indexing of Transcriptomes and Epitopes by Sequencing (CITE-Seq) simultaneously profiles the RNA transcriptome and the surface protein expression. The surface protein markers in CITE-Seq can be used to identify cell populations similar to the iterative filtration process in flow cytometry, also called "gating", and is an essential step for downstream analyses and data interpretation. While several packages allow users to interactively gate cells, they often do not process multi-omic sequencing datasets and may require writing redundant code to specify gate boundaries. To streamline the gating process, we developed CITEViz which allows users to interactively gate cells in Seurat-processed CITE-Seq data. CITEViz can also visualize basic quality control (QC) metrics allowing for a rapid and holistic evaluation of CITE-Seq data. RESULTS: We applied CITEViz to a peripheral blood mononuclear cell CITE-Seq dataset and gated for several major blood cell populations (CD14 monocytes, CD4 T cells, CD8 T cells, NK cells, B cells, and platelets) using canonical surface protein markers. The visualization features of CITEViz were used to investigate cellular heterogeneity in CD14 and CD16-expressing monocytes and to detect differential numbers of detected antibodies per patient donor. These results highlight the utility of CITEViz to enable the robust classification of single cell populations. CONCLUSIONS: CITEViz is an R-Shiny app that standardizes the gating workflow in CITE-Seq data for efficient classification of cell populations. Its secondary function is to generate basic feature plots and QC figures specific to multi-omic data. The user interface and internal workflow of CITEViz uniquely work together to produce an organized workflow and sensible data structures for easy data retrieval. This package leverages the strengths of biologists and computational scientists to assess and analyze multi-omic single-cell datasets. In conclusion, CITEViz streamlines the flow cytometry gating workflow in CITE-Seq data to help facilitate novel hypothesis generation.

Combined sensory, volatilome and transcriptome analyses identify a limonene terpene synthase as a major contributor to the characteristic aroma of a Coffea arabica L. specialty coffee.

BACKGROUND: The fruity aromatic bouquet of coffee has attracted recent interest to differentiate high value market produce as specialty coffee. Although the volatile compounds present in green and roasted coffee beans have been extensively described, no study has yet linked varietal molecular differences to the greater abundance of specific substances and support the aroma specificity of specialty coffees. RESULTS: This study compared four Arabica genotypes including one, Geisha Especial, suggested to generate specialty coffee. Formal sensory evaluations of coffee beverages stressed the importance of coffee genotype in aroma perception and that Geisha Especial-made coffee stood out by having fine fruity, and floral, aromas and a more balanced acidity. Comparative SPME-GC-MS analyses of green and roasted bean volatile compounds indicated that those of Geisha Especial differed by having greater amounts of limonene and 3-methylbutanoic acid in agreement with the coffee cup aroma perception. A search for gene ontology differences of ripening beans transcriptomes of the four varieties revealed that they differed by metabolic processes linked to terpene biosynthesis due to the greater gene expression of prenyl-pyrophosphate biosynthetic genes and terpene synthases. Only one terpene synthase (CaTPS10-like) had an expression pattern that paralleled limonene loss during the final stage of berry ripening and limonene content in the studied four varieties beans. Its functional expression in tobacco leaves confirmed its functioning as a limonene synthase. CONCLUSIONS: Taken together, these data indicate that coffee variety genotypic specificities may influence ripe berry chemotype and final coffee aroma unicity. For the specialty coffee variety Geisha Especial, greater expression of terpene biosynthetic genes including CaTPS10-like, a limonene synthase, resulted in the greater abundance of limonene in green beans, roasted beans and a unique citrus note of the coffee drink.

Transcriptomic profiling of an evolved Yarrowia lipolytica strain: tackling hexanoic acid fermentation to increase lipid production from short-chain fatty acids.

BACKGROUND: Short-chain fatty acids (SCFAs) are cost-effective carbon sources for an affordable production of lipids. Hexanoic acid, the acid with the longest carbon chain in the SCFAs pool, is produced in anaerobic fermentation of organic residues and its use is very challenging, even inhibiting oleaginous yeasts growth. RESULTS: In this investigation, an adaptive laboratory evolution (ALE) was performed to improve Yarrowia lipolytica ACA DC 50109 tolerance to high hexanoic acid concentrations. Following ALE, the transcriptomic analysis revealed several genetic adaptations that improved the assimilation of this carbon source in the evolved strain compared to the wild type (WT). Indeed, the evolved strain presented a high expression of the up-regulated gene YALI0 E16016g, which codes for FAT1 and is related to lipid droplets formation and responsible for mobilizing long-chain acids within the cell. Strikingly, acetic acid and other carbohydrate transporters were over-expressed in the WT strain. CONCLUSIONS: A more tolerant yeast strain able to attain higher lipid content under the presence of high concentrations of hexanoic acid has been obtained. Results provided novel information regarding the assimilation of hexanoic acid in yeasts.

Race-specific coregulatory and transcriptomic profiles associated with DNA methylation and androgen receptor in prostate cancer.

BACKGROUND: Prostate cancer is a significant health concern, particularly among African American (AA) men who exhibit higher incidence and mortality compared to European American (EA) men. Understanding the molecular mechanisms underlying these disparities is imperative for enhancing clinical management and achieving better outcomes. METHODS: Employing a multi-omics approach, we analyzed prostate cancer in both AA and EA men. Using Illumina methylation arrays and RNA sequencing, we investigated DNA methylation and gene expression in tumor and non-tumor prostate tissues. Additionally, Boolean analysis was utilized to unravel complex networks contributing to racial disparities in prostate cancer. RESULTS: When comparing tumor and adjacent non-tumor prostate tissues, we found that DNA hypermethylated regions are enriched for PRC2/H3K27me3 pathways and EZH2/SUZ12 cofactors. Olfactory/ribosomal pathways and distinct cofactors, including CTCF and KMT2A, were enriched in DNA hypomethylated regions in prostate tumors from AA men. We identified race-specific inverse associations of DNA methylation with expression of several androgen receptor (AR) associated genes, including the GATA family of transcription factors and TRIM63. This suggests that race-specific dysregulation of the AR signaling pathway exists in prostate cancer. To investigate the effect of AR inhibition on race-specific gene expression changes, we generated in-silico patient-specific prostate cancer Boolean networks. Our simulations revealed prolonged AR inhibition causes significant dysregulation of TGF-ß, IDH1, and cell cycle pathways specifically in AA prostate cancer. We further quantified global gene expression changes, which revealed differential expression of genes related to microtubules, immune function, and TMPRSS2-fusion pathways, specifically in prostate tumors of AA men. Enrichment of these pathways significantly correlated with an altered risk of disease progression in a race-specific manner. CONCLUSIONS: Our study reveals unique signaling networks underlying prostate cancer biology in AA and EA men, offering potential insights for clinical management strategies tailored to specific racial groups. Targeting AR and associated pathways could be particularly beneficial in addressing the disparities observed in prostate cancer outcomes in the context of AA and EA men. Further investigation into these identified pathways may lead to the development of personalized therapeutic approaches to improve outcomes for prostate cancer patients across different racial backgrounds.

Transcriptomic responses of rabbits to infections by precocious line and wild-type Eimeria media: revealing molecular signatures and pathway differences in liver and duodenum during the peak and terminal phases of oocyst production.

Eimeria media is a principal pathogen responsible for rabbit coccidiosis, targeting the rabbit's intestinal epithelial cells. This parasitism damages the intestinal mucosal barrier, initiating a systemic immune and inflammatory response that jeopardizes the sustainable growth of rabbit farming. To understand the implications of infection on the host's immune and metabolic responses, we employed RNA-Seq to analyze RNA from the liver and duodenum tissues of post-infected rabbits infected with both the precocious line and wild-type strain of E.media. Comprehensive transcriptomic analysis revealed that the two parasites exhibit divergent transcriptomic imprints on host tissues. While the precocious line predominantly modulates immune-centric pathways with significant differential gene enrichment, wild-type strain favors pathways that affect metabolism. In addition, our study pinpointed a set of genes that undergo significant modifications in response to these effects. These revelations grant a fresh avenue to probe deeper into the symbiotic intricacies of the E.media and its rabbit host.

Deciphering cutaneous melanoma prognosis through LDL metabolism: Single-cell transcriptomics analysis via 101 machine learning algorithms.

Cutaneous melanoma poses a formidable challenge within the field of oncology, marked by its aggressive nature and capacity for metastasis. Despite extensive research uncovering numerous genetic and molecular contributors to cutaneous melanoma development, there remains a critical knowledge gap concerning the role of lipids, notably low-density lipoprotein (LDL), in this lethal skin cancer. This article endeavours to bridge this knowledge gap by delving into the intricate interplay between LDL metabolism and cutaneous melanoma, shedding light on how lipids influence tumour progression, immune responses and potential therapeutic avenues. Genes associated with LDL metabolism were extracted from the GSEA database. We acquired and analysed single-cell sequencing data (GSE215120) and bulk-RNA sequencing data, including the TCGA data set, GSE19234, GSE22153 and GSE65904. Our analysis unveiled the heterogeneity of LDL across various cell types at the single-cell sequencing level. Additionally, we constructed an LDL-related signature (LRS) using machine learning algorithms, incorporating differentially expressed genes and highly correlated genes. The LRS serves as a valuable tool for assessing the prognosis, immunity and mutation status of patients with cutaneous melanoma. Furthermore, we conducted experiments on A375 and WM-115 cells to validate the function of PPP2R1A, a pivotal gene within the LRS. Our comprehensive approach, combining advanced bioinformatics analyses with an extensive review of current literature, presents compelling evidence regarding the significance of LDL within the cutaneous melanoma microenvironment.

Gene expression analyses of GH/IGF axis in triploid crucian carp with growth heterosis.

Hybridization and polyploid breeding are the main approaches used to obtain new aquaculture varieties. Allotriploid crucian carp (3n) with rapid growth performance was generated by mating red crucian carp (RCC) with allotetraploids (4n). Fish growth is controlled by the growth hormone (GH)/insulin-like growth factor (IGF) axis. In the present study, we examined the expression characteristics of GH/IGF axis genes in hybrids F1, 4n, 3n, RCC and common carp (CC). The results showed that GHRa, GHRb, IGF1, IGF2, and IGF-1Ra were highly expressed in 3n compared with RCC and CC, whereas IGF3 was undetectable in the liver in RCC, CC and 3n. GHRa and GHRb had low expression in the 4n group. In hybrid F1, GHRa expression was low, whereas GHRb was highly expressed compared to the levels in RCC and CC. Moreover, in hybrid F1, the expression of IGF3 was higher, and the expression of IGF1 and IGF2 was lower than that in the RCC and CC, whereas the expression of IGF-1Ra was similar to that in RCC and CC. For the IGFBP genes, IGFBP1 had higher expression in 3n compared than that in RCC and CC, while other IGFBP genes were not high expressed in 3n. Among the genes detected in this study, 11 genes were nonadditively expressed in 3n, with 5 genes in the transgressive upregulation model. We proposed that the 11 nonadditive expression of GH/IGF axis genes is related to growth heterosis in 3n. This evidence provides new insights into hybridization and polyploid breeding from the perspective of hormone regulation.

Identification of Potential Crucial Biomarkers in STEMI Through Integrated Bioinformatic Analysis. / Identificação de Potenciais Biomarcadores Cruciais em IAMCSST por Meio de Análise Bioinformática Integrada.

BACKGROUND: ST-segment elevation myocardial infarction (STEMI) is one of the leading causes of fatal cardiovascular diseases, which have been the prime cause of mortality worldwide. Diagnosis in the early phase would benefit clinical intervention and prognosis, but the exploration of the biomarkers of STEMI is still lacking. OBJECTIVES: In this study, we conducted a bioinformatics analysis to identify potential crucial biomarkers in the progress of STEMI. METHODS: We obtained GSE59867 for STEMI and stable coronary artery disease (SCAD) patients. Differentially expressed genes (DEGs) were screened with the threshold of |log2fold change| > 0.5 and p <0.05. Based on these genes, we conducted enrichment analysis to explore the potential relevance between genes and to screen hub genes. Subsequently, hub genes were analyzed to detect related miRNAs and DAVID to detect transcription factors for further analysis. Finally, GSE62646 was utilized to assess DEGs specificity, with genes demonstrating AUC results exceeding 75%, indicating their potential as candidate biomarkers. RESULTS: 133 DEGs between SCAD and STEMI were obtained. Then, the PPI network of DEGs was constructed using String and Cytoscape, and further analysis determined hub genes and 6 molecular complexes. Functional enrichment analysis of the DEGs suggests that pathways related to inflammation, metabolism, and immunity play a pivotal role in the progression from SCAD to STEMI. Besides, related-miRNAs were predicted, has-miR-124, has-miR-130a/b, and has-miR-301a/b regulated the expression of the largest number of genes. Meanwhile, Transcription factors analysis indicate that EVI1, AML1, GATA1, and PPARG are the most enriched gene. Finally, ROC curves demonstrate that MS4A3, KLRC4, KLRD1, AQP9, and CD14 exhibit both high sensitivity and specificity in predicting STEMI. CONCLUSIONS: This study revealed that immunity, metabolism, and inflammation are involved in the development of STEMI derived from SCAD, and 6 genes, including MS4A3, KLRC4, KLRD1, AQP9, CD14, and CCR1, could be employed as candidate biomarkers to STEMI.

FUNDAMENTO: O infarto do miocárdio com elevação do segmento ST (IAMCSST) é uma das principais causas de doenças cardiovasculares fatais, que têm sido a principal causa de mortalidade em todo o mundo. O diagnóstico na fase inicial beneficiaria a intervenção clínica e o prognóstico, mas ainda falta a exploração dos biomarcadores do IAMCSST. OBJETIVOS: Neste estudo, conduzimos uma análise bioinformática para identificar potenciais biomarcadores cruciais no progresso do IAMCSST. MÉTODOS: Obtivemos GSE59867 para pacientes com IAMCSST e doença arterial coronariana estável (DACE). Genes diferencialmente expressos (GDEs) foram selecionados com o limiar de |log2fold change| > 0,5 e p < 0,05. Com base nesses genes, conduzimos análises de enriquecimento para explorar a relevância potencial entre genes e para rastrear genes centrais. Posteriormente, os genes centrais foram analisados para detectar miRNAs relacionados e DAVID para detectar fatores de transcrição para análise posterior. Finalmente, o GSE62646 foi utilizado para avaliar a especificidade dos GDEs, com genes demonstrando resultados de AUC superiores a 75%, indicando seu potencial como candidatos a biomarcadores. Posteriormente, os genes centrais foram analisados para detectar miRNAs relacionados e DAVID para detectar fatores de transcrição para análise posterior. Finalmente, o GSE62646 foi utilizado para avaliar a especificidade dos GDEs, com genes demonstrando resultados de AUC superiores a 75%, indicando seu potencial como candidatos a biomarcadores. RESULTADOS: 133 GDEs entre DACE e IAMCSST foram obtidos. Em seguida, a rede PPI de GDEs foi construída usando String e Cytoscape, e análises posteriores determinaram genes centrais e 6 complexos moleculares. A análise de enriquecimento funcional dos GDEs sugere que as vias relacionadas à inflamação, metabolismo e imunidade desempenham um papel fundamental na progressão de DACE para IAMCSST. Além disso, foram previstos miRNAs relacionados, has-miR-124, has-miR-130a/b e has-miR-301a/b regularam a expressão do maior número de genes. Enquanto isso, a análise dos fatores de transcrição indica que EVI1, AML1, GATA1 e PPARG são os genes mais enriquecidos. Finalmente, as curvas ROC demonstram que MS4A3, KLRC4, KLRD1, AQP9 e CD14 exibem alta sensibilidade e especificidade na previsão de IAMCSST. CONCLUSÕES: Este estudo revelou que imunidade, metabolismo e inflamação estão envolvidos no desenvolvimento de IAMCSST derivado de DACE, e 6 genes, incluindo MS4A3, KLRC4, KLRD1, AQP9, CD14 e CCR1, poderiam ser empregados como candidatos a biomarcadores para IAMCSST.

An integrated metagenomic, metabolomic and transcriptomic survey of Populus across genotypes and environments.

Bridging molecular information to ecosystem-level processes would provide the capacity to understand system vulnerability and, potentially, a means for assessing ecosystem health. Here, we present an integrated dataset containing environmental and metagenomic information from plant-associated microbial communities, plant transcriptomics, plant and soil metabolomics, and soil chemistry and activity characterization measurements derived from the model tree species Populus trichocarpa. Soil, rhizosphere, root endosphere, and leaf samples were collected from 27 different P. trichocarpa genotypes grown in two different environments leading to an integrated dataset of 318 metagenomes, 98 plant transcriptomes, and 314 metabolomic profiles that are supported by diverse soil measurements. This expansive dataset will provide insights into causal linkages that relate genomic features and molecular level events to system-level properties and their environmental influences.

Transcriptomic analysis of Anopheles gambiae from Benin reveals overexpression of salivary and cuticular proteins associated with cross-resistance to pyrethroids and organophosphates.

BACKGROUND: Insecticide resistance (IR) is one of the major threats to malaria vector control programs in endemic countries. However, the mechanisms underlying IR are poorly understood. Thus, investigating gene expression patterns related to IR can offer important insights into the molecular basis of IR in mosquitoes. In this study, RNA-Seq was used to characterize gene expression in Anopheles gambiae surviving exposure to pyrethroids (deltamethrin, alphacypermethrin) and an organophosphate (pirimiphos-methyl). RESULTS: Larvae of An. gambiae s.s. collected from Bassila and Djougou in Benin were reared to adulthood and phenotyped for IR using a modified CDC intensity bottle bioassay. The results showed that mosquitoes from Djougou were more resistant to pyrethroids (5X deltamethrin: 51.7% mortality; 2X alphacypermethrin: 47.4%) than Bassila (1X deltamethrin: 70.7%; 1X alphacypermethrin: 77.7%), while the latter were more resistant to pirimiphos-methyl (1.5X: 48.3% in Bassila and 1X: 21.5% in Djougou). RNA-seq was then conducted on resistant mosquitoes, non-exposed mosquitoes from the same locations and the laboratory-susceptible An. gambiae s.s. Kisumu strain. The results showed overexpression of detoxification genes, including cytochrome P450s (CYP12F2, CYP12F3, CYP4H15, CYP4H17, CYP6Z3, CYP9K1, CYP4G16, and CYP4D17), carboxylesterase genes (COEJHE5E, COE22933) and glutathione S-transferases (GSTE2 and GSTMS3) in all three resistant mosquito groups analyzed. Genes encoding cuticular proteins (CPR130, CPR10, CPR15, CPR16, CPR127, CPAP3-C, CPAP3-B, and CPR76) were also overexpressed in all the resistant groups, indicating their potential role in cross resistance in An. gambiae. Salivary gland protein genes related to 'salivary cysteine-rich peptide' and 'salivary secreted mucin 3' were also over-expressed and shared across all resistant groups. CONCLUSION: Our results suggest that in addition to metabolic enzymes, cuticular and salivary gland proteins could play an important role in cross-resistance to multiple classes of insecticides in Benin. These genes warrant further investigation to validate their functional role in An. gambiae resistance to insecticides.

Lack of Laminar Shear Stress Facilitates the Endothelial Uptake of Very Small Superparamagnetic Iron Oxide Nanoparticles by Modulating the Endothelial Surface Layer.

Purpose: To study whether the absence of laminar shear stress (LSS) enables the uptake of very small superparamagnetic iron oxide nanoparticles (VSOP) in endothelial cells by altering the composition, size, and barrier function of the endothelial surface layer (ESL). Methods and Results: A quantitative particle exclusion assay with living human umbilical endothelial cells using spinning disc confocal microscopy revealed that the dimension of the ESL was reduced in cells cultivated in the absence of LSS. By combining gene expression analysis, flow cytometry, high pressure freezing/freeze substitution immuno-transmission electron microscopy, and confocal laser scanning microscopy, we investigated changes in ESL composition. We found that increased expression of the hyaluronan receptor CD44 by absence of shear stress did not affect the uptake rate of VSOPs. We identified collagen as a previously neglected component of ESL that contributes to its barrier function. Experiments with inhibitor halofuginone and small interfering RNA (siRNA) demonstrated that suppression of collagen expression facilitates VSOP uptake in endothelial cells grown under LSS. Conclusion: The absence of laminar shear stress disturbs the barrier function of the ESL, facilitating membrane accessibility and endocytic uptake of VSOP. Collagen, a previously neglected component of ESL, contributes to its barrier function.

Integrated Full-Length Transcriptomics and Metabolomics Reveal Glycosyltransferase Involved in the Biosynthesis of Flavonol Glycosides in Laportea bulbifera.

Many species of the Urticaceae family are important cultivated fiber plants that are known for their economic and industrial values. However, their secondary metabolite profiles and associated biosynthetic mechanisms have not been well-studied. Using Laportea bulbifera as a model, we conducted widely targeted metabolomics, which revealed 523 secondary metabolites, including a unique accumulation of flavonol glycosides in bulblet. Through full-length transcriptomic and RNA-seq analyses, the related genes in the flavonoid biosynthesis pathway were identified. Finally, weighted gene correlation network analysis and functional characterization revealed four LbUGTs, including LbUGT78AE1, LbUGT72CT1, LbUGT71BX1, and LbUGT71BX2, can catalyze the glycosylation of flavonol aglycones (kaempferol, myricetin, gossypetin, and quercetagetin) using UDP-Gal and UDP-Glu as the sugar donors. LbUGT78AE1 and LbUGT72CT1 showed substrate promiscuity, whereas LbUGT71BX1 and LbUGT71BX2 exhibited different substrate and sugar donor selectivity. These results provide a genetic resource for studying Laportea in the Urticaceae family, as well as key enzymes responsible for the metabolism of valuable flavonoid glycosides.

Identification of PPARG as key gene to link coronary atherosclerosis disease and rheumatoid arthritis via microarray data analysis.

BACKGROUND: Inflammation is the common pathogenesis of coronary atherosclerosis disease (CAD) and rheumatoid arthritis (RA). Although it is established that RA increases the risk of CAD, the underlining mechanism remained indefinite. This study seeks to explore the molecular mechanisms of RA linked CAD and identify potential target gene for early prediction of CAD in RA patients. MATERIALS AND METHODS: The study utilized five raw datasets: GSE55235, GSE55457, GSE12021 for RA patients, and GSE42148 and GSE20680 for CAD patients. Gene Set Enrichment Analysis (GSEA) was used to investigate common signaling pathways associated with RA and CAD. Then, weighted gene co-expression network analysis (WGCNA) was performed on RA and CAD training datasets to identify gene modules related to single-sample GSEA (ssGSEA) scores. Overlapping module genes and differentially expressed genes (DEGs) were considered as co-susceptible genes for both diseases. Three hub genes were screened using a protein-protein interaction (PPI) network analysis via Cytoscape plug-ins. The signaling pathways, immune infiltration, and transcription factors associated with these hub genes were analyzed to explore the underlying mechanism connecting both diseases. Immunohistochemistry and qRT-PCR were conducted to validate the expression of the key candidate gene, PPARG, in macrophages of synovial tissue and arterial walls from RA and CAD patients. RESULTS: The study found that Fc-gamma receptor-mediated endocytosis is a common signaling pathway for both RA and CAD. A total of 25 genes were screened by WGCNA and DEGs, which are involved in inflammation-related ligand-receptor interactions, cytoskeleton, and endocytosis signaling pathways. The principal component analysis(PCA) and support vector machine (SVM) and receiver-operator characteristic (ROC) analysis demonstrate that 25 DEGs can effectively distinguish RA and CAD groups from normal groups. Three hub genes TUBB2A, FKBP5, and PPARG were further identified by the Cytoscape software. Both FKBP5 and PPARG were downregulated in synovial tissue of RA and upregulated in the peripheral blood of CAD patients and differential mRNAexpreesion between normal and disease groups in both diseases were validated by qRT-PCR.Association of PPARG with monocyte was demonstrated across both training and validation datasets in CAD. PPARG expression is observed in control synovial epithelial cells and foamy macrophages of arterial walls, but was decreased in synovial epithelium of RA patients. Its expression in foamy macrophages of atherosclerotic vascular walls exhibits a positive correlation (r = 0.6276, p = 0.0002) with CD68. CONCLUSION: Our findings suggest that PPARG may serve as a potentially predictive marker for CAD in RA patients, which provides new insights into the molecular mechanism underling RA linked CAD.

Interplay of intracellular and trans-cellular DNA methylation in natural archaeal consortia.

DNA methylation serves a variety of functions across all life domains. In this study, we investigated archaeal methylomics within a tripartite xylanolytic halophilic consortium. This consortium includes Haloferax lucertense SVX82, Halorhabdus sp. SVX81, and an ectosymbiotic Candidatus Nanohalococcus occultus SVXNc, a nano-sized archaeon from the DPANN superphylum. We utilized PacBio SMRT and Illumina cDNA sequencing to analyse samples from consortia of different compositions for methylomics and transcriptomics. Endogenous cTAG methylation, typical of Haloferax, was accompanied in this strain by methylation at four other motifs, including GDGcHC methylation, which is specific to the ectosymbiont. Our analysis of the distribution of methylated and unmethylated motifs suggests that autochthonous cTAG methylation may influence gene regulation. The frequency of GRAGAaG methylation increased in highly expressed genes, while CcTTG and GTCGaGG methylation could be linked to restriction-modification (RM) activity. Generally, the RM activity might have been reduced during the evolution of this archaeon to balance the protection of cells from intruders, the reduction of DNA damage due to self-restriction in stressful environments, and the benefits of DNA exchange under extreme conditions. Our methylomics, transcriptomics and complementary electron cryotomography (cryo-ET) data suggest that the nanohaloarchaeon exports its methyltransferase to methylate the Haloferax genome, unveiling a new aspect of the interaction between the symbiont and its host.