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At least 1,153 records · Page 64Linked to original sources
PubMed2005

Transcriptome profiling of adult zebrafish at the late stage of chronic tuberculosis due to Mycobacterium marinum infection.

The Mycobacterium marinum-zebrafish infection model was used in this study for analysis of a host transcriptome response to mycobacterium infection at the organismal level. RNA isolated from adult zebrafish that showed typical signs of fish tuberculosis due to a chronic progressive infection with M. marinum was compared with RNA from healthy fish in microarray analyses. Spotted oligonucleotide sets (designed by Sigma-Compugen and MWG) and Affymetrix GeneChips were used, in total comprising 45,465 zebrafish transcript annotations. Based on a detailed comparative analysis and quantitative reverse transcriptase-PCR analysis, we present a validated reference set of 159 genes whose regulation is strongly affected by mycobacterial infection in the three types of microarrays analyzed. Furthermore, we analyzed the separate datasets of the microarrays with special emphasis on the expression profiles of immune-related genes. Upregulated genes include many known components of the inflammatory response and several genes that have previously been implicated in the response to mycobacterial infections in cell cultures of other organisms. Different marker genes of the myeloid lineage that have been characterized in zebrafish also showed increased expression. Furthermore, the zebrafish homologs of many signal transduction genes with relationship to the immune response were induced by M. marinum infection. Future functional analysis of these genes may contribute to understanding the mechanisms of mycobacterial pathogenesis. Since a large group of genes linked to immune responses did not show altered expression in the infected animals, these results suggest specific responses in mycobacterium-induced disease.

Animals↗
PubMed2005

Metabolome analysis: the potential of in vivo labeling with stable isotopes for metabolite profiling.

Metabolome analysis technologies are still in early development because, unlike genome, transcriptome and proteome analyses, metabolome analysis has to deal with a highly diverse range of biomolecules. Combinations of different analytical platforms are therefore required for comprehensive metabolomic studies. Each of these platforms covers only part of the metabolome. To establish multiparallel technologies, thorough standardization of each measured metabolite is required. Standardization is best achieved by addition of a specific stable isotope-labeled compound, a mass isotopomer, for each metabolite. This suggestion, at first glance, seems unrealistic because of cost and time constraints. A possible solution to this problem is discussed in this article. Saturation in vivo labeling with stable isotopes enables the biosynthesis of differentially mass-labeled metabolite mixtures, which can be exploited for highly standardized metabolite profiling by mass isotopomer ratios.

Biochemistry↗
PubMed2026

Full-length single-cell spatial transcriptomics reveals spatial and cell-type-specific transcript isoforms in the primate brain.

The primate brain exhibits complex RNA alternative splicing heterogeneity crucial for functional complexity, yet systematic spatial isoform characterization has been lacking. We developed Fullscope-seq, a full-length single-molecule large field-of-view spatial transcriptomics sequencing method at single-cell resolution, based on programmed concatenation cDNA for multiple long-read sequencing platforms. Applying Fullscope-seq to the macaque brain, we uncovered thousands of genes exhibiting differential transcript usage (DTU) across cortical layers, cell types and brain regions. Fullscope-seq resolved hundreds of major isoform switches across distinct brain regions and identified DTUs between superficial and deep cortical layers. Cortical layer-specific DTUs showed cell-composition dependence, whereas regional DTUs were regulated according to both cellular composition and spatial contexts. These isoform variations showed substantial enrichment for neuropsychiatric disorder-associated genes and were conserved across platforms and species. Our study establishes a scalable framework for spatial isoform analysis and provides a resource for understanding transcriptomic diversity in complex tissues.

Animals↗
PubMed2026

Integrative Multi-Omics Analysis of Stem Growth Habit Divergence in Wild Soybean (Glycine soja).

Stem architecture is a major determinant of lodging resistance, biomass accumulation, and harvest efficiency in soybean. However, the molecular features associated with contrasting stem growth habits in wild soybean remain incompletely characterised. Here, we performed an integrated transcriptomic, metabolomic, and epigenomic analysis of stem growth-habit divergence in wild soybean, comparing the wild-type accession ZYD7068 with contrasting vining and erect mutant lines derived from carbon-ion beam mutagenesis. Pairwise transcriptomic comparisons identified between 20 311 and 28 705 differentially expressed genes per contrast, with a core set of 2672 genes consistently altered across the comparisons. Functional enrichment, gene set variation analysis, and gene set enrichment analysis converged on xylem and phloem pattern formation as a prominent molecular pathway associated with growth-habit divergence. Random forest analysis identified BBR-BPC and ARF transcription factor families as major molecular discriminators, while metabolomic profiling revealed distinct metabolic profiles involving amino-acid-derived and lipid-associated metabolites. Whole-genome bisulfite sequencing revealed context-specific DNA methylation differences, including substantial variation in CHG methylation among erect mutant lines. Integrated network and in silico perturbation analyses prioritised four candidate genes associated with vascular development for future functional validation. Together, these results provide a multi-layer molecular resource for investigating stem growth-habit divergence in G. soja and establish testable candidate pathways and genes for subsequent functional studies and soybean improvement.

glycine soja↗
PubMed2026

Spatial analysis reveals the evolving organization of IDH-mutant glioma.

Adult diffuse gliomas are composed of malignant cell states interwoven with the non-malignant brain microenvironment. Here, we combine spatial transcriptomics and spatial proteomics of isocitrate dehydrogenase (IDH)-mutant gliomas to define organizational principles across histological grades. In low-grade tumors, spatial organization is shaped by underlying brain anatomy. We identify a functional white-gray matter junction that restricts cortical invasion and is associated with marked changes in tumor composition and cellular phenotypes. This junction is preferentially traversed by oligodendrocyte progenitor (OPC)-like malignant cells, suggesting a role in tumor expansion. In contrast, tumors with intermediate histological features are largely disorganized, with few recurring interactions between cancer cell states and microenvironmental cell types. In high-grade tumors, hypoxia-associated structure emerges, resembling IDH-wild-type glioblastoma. Together, these findings reveal two independent axes of spatial organization-from anatomy-driven structure in low-grade tumors to hypoxia-driven organization in high-grade tumors-and establish a framework linking tumor grade to recurrent spatial interactions.

Isocitrate Dehydrogenase↗
PubMed2005

BRIGEP--the BRIDGE-based genome-transcriptome-proteome browser.

The growing amount of information resulting from the increasing number of publicly available genomes and experimental results thereof necessitates the development of comprehensive systems for data processing and analysis. In this paper, we describe the current state and latest developments of our BRIGEP bioinformatics software system consisting of three web-based applications: GenDB, EMMA and ProDB. These applications facilitate the processing and analysis of bacterial genome, transcriptome and proteome data and are actively used by numerous international groups. We are currently in the process of extensively interconnecting these applications. BRIGEP was developed in the Bioinformatics Resource Facility of the Center for Biotechnology at Bielefeld University and is freely available. A demo project with sample data and access to all three tools is available at https://www.cebitec.uni-bielefeld.de/groups/brf/software/brigep/. Code bundles for these and other tools developed in our group are accessible on our FTP server at ftp.cebitec.uni-bielefeld.de/pub/software/.

Bacterial Proteins↗
PubMed2006

Expression profiling of Botrytis cinerea genes identifies three patterns of up-regulation in planta and an FKBP12 protein affecting pathogenicity.

The ascomycete Botrytis cinerea is a broad-spectrum plant pathogen. Here, we describe the first macroarray transcriptomic study of the fungus in real-time infection conditions. Infection of Arabidopsis thaliana leaves by B.cinerea was monitored using macroarrays, containing 3032 genes. Variance analysis revealed that 7% of B.cinerea genes are differentially expressed during infection and allowed us to identify 27 genes significantly up-regulated in planta. Among them, two genes have already been associated with fungal pathogenicity, while eight genes have unidentified functions. The 27 genes were separated into three groups according to their expression profile. The first group showed maximal expression at the early stage following fungal penetration, the second one showed maximal expression at the outset of the colonization of plant leaves and the third group showed maximal expression when the colonization of plant leaves was completed. A gene of the last group (BcPIC5), which is homologous to FKBP12 proteins, was disrupted in order to determine its role in pathogenicity. At seven days post-inoculation, the lesions caused by the DeltaBcPIC5 mutant on bean leaves were reduced by 69% and did not further expand compared to the wild-type. These results confirm that transcriptomic analysis under infection conditions can be very valuable for the identification of fungal genes related to pathogenicity.

Arabidopsis↗
PubMed2004

Characterization of anti-inflammatory compounds using transcriptomics, proteomics, and metabolomics in combination with multivariate data analysis.

The discovery of new anti-inflammatory drugs is often based on an interaction with a specific target, although other pathways often play a primary or secondary role. Anti-inflammatory drugs can be categorized into classes, based on their mechanism of action. In this article we investigate the possibility to characterize novel anti-inflammatory compounds by three holistic methods. For this purpose, we make use of macrophage-like U937 cells which are stimulated with LPS in the absence or presence of an anti-inflammatory compound. Using micro-arrays, 2-D gel electrophoresis and a LC-MS method for lipids the effects on the transcriptome, proteome and metabolome of the exposed cells is investigated. The expression patterns are subsequently analyzed using in-house developed pattern recognition tools. Using the methods described above, we have examined the effects of six anti-inflammatory compounds. Our results demonstrate that different classes of anti-inflammatory compounds show distinct and characteristic mRNA, protein, and lipid expression patterns, which can be used to categorise known molecules and to discover and classify new leads. The potential of our approach is illustrated by the analysis of several beta (2)-adrenergic agonists (beta2-agonists). In addition to their primary pharmacological target, beta2-agonists posses certain anti-inflammatory properties. We were able to show that zilpaterol, a poorly characterized beta2-agonist, gives rise to an almost identical expression pattern as the beta2-agonists clenbuterol and salbutamol. Furthermore we have identified specific mRNA, protein and lipid markers for the anti-inflammatory compounds investigated in this study.

Adrenergic beta-2 Receptor Agonists↗
PubMed2025

GSK3B inhibition partially reverses brain ethanol-induced transcriptomic changes in C57BL/6J mice: Expression network co-analysis with human genome-wide association studies.

Alcohol use disorder (AUD) is a chronic behavioral disease with greater than 50% of its risk due to complex genetic contributions. Existing pharmacological and behavioral treatments for AUD are minimally effective and underutilized. Animal model behavioral genetics and human genome-wide association studies have begun to identify individual genes contributing to the progressive compulsive consumption of ethanol that occurs with AUD, promising possible new therapeutic targets. Our laboratory has previously identified Gsk3b as a central member in a network of ethanol-responsive genes in mouse prefrontal cortex, which altered ethanol consumption with genetic manipulation and was also significantly associated with risk for alcohol dependence in human genome-wide association studies. Here we perform detailed brain RNA sequencing transcriptomic studies to characterize a highly specific and clinically available GSK3B pharmacological inhibitor, tideglusib, as a possible therapeutic for clinical trials on treatment of AUD. A model of chronic intermittent ethanol consumption was used to study gene expression changes in prefrontal cortex and nucleus accumbens in the presence or absence of tideglusib treatment. Multivariate analysis of differentially expressed genes showed that tideglusib largely reversed ethanol- induced expression changes for two prominent clusters of genes in both prefrontal cortex and nucleus accumbens. Bioinformatic analysis showed these genes to have prominent roles in neuronal functioning and synaptic activity. Additionally, mouse brain differential gene expression data was analyzed together with human protein-protein interaction and genome-wide association studies on AUD to derive networks responding to tideglusib and relevant to human genetic risk for alcohol dependence. These studies identified discrete networks significantly enriched with genes provisionally associated with AUD, and provide key information on central hubs of such networks. Together these studies document tideglusib as a major modulator of chronic ethanol consumption-evoked brain gene expression signatures, and identify possible new targets for therapeutic modulation of AUD.

Journal Article↗
PubMed2022

Species-specific transcriptomic changes upon respiratory syncytial virus infection in cotton rats.

The cotton rat (Sigmodon) is the gold standard pre-clinical small animal model for respiratory viral pathogens, especially for respiratory syncytial virus (RSV). However, without a reference genome or a published transcriptome, studies requiring gene expression analysis in cotton rats are severely limited. The aims of this study were to generate a comprehensive transcriptome from multiple tissues of two species of cotton rats that are commonly used as animal models (Sigmodon fulviventer and Sigmodon hispidus), and to compare and contrast gene expression changes and immune responses to RSV infection between the two species. Transcriptomes were assembled from lung, spleen, kidney, heart, and intestines for each species with a contig N50 > 1600. Annotation of contigs generated nearly 120,000 gene annotations for each species. The transcriptomes of S. fulviventer and S. hispidus were then used to assess immune response to RSV infection. We identified 238 unique genes that are significantly differentially expressed, including several genes implicated in RSV infection (e.g., Mx2, I27L2, LY6E, Viperin, Keratin 6A, ISG15, CXCL10, CXCL11, IRF9) as well as novel genes that have not previously described in RSV research (LG3BP, SYWC, ABEC1, IIGP1, CREB1). This study presents two comprehensive transcriptome references as resources for future gene expression analysis studies in the cotton rat model, as well as provides gene sequences for mechanistic characterization of molecular pathways. Overall, our results provide generalizable insights into the effect of host genetics on host-virus interactions, as well as identify new host therapeutic targets for RSV treatment and prevention.

Animals↗
PubMed2005

Gene expression profiling in hypothalamus of immobilization-stressed mouse using cDNA microarray.

To investigate the effects of repeated immobilization-stress challenge on HPA axis, genomic transcriptome in the hypothalamus of immobilization-stressed mouse was analyzed by using cDNA microarray. With the 1.5-fold cutoff of arbitrary criteria, the expression levels of 108 genes out of 6016 genes were significantly modulated in the hypothalamus by the stress. Energy metabolism-, lipid metabolism-, and apoptosis- and signal transduction-related genes were activated while DNA repair-, protein biosynthesis-, and structure integrity-related genes were down-regulated in the hypothalamus. Eighteen genes among them were selected for RT-PCR analysis to confirm the change of their expression levels on agarose gels. Besides, dozens of novel genes, which have not been previously reported, were screened to be modulated by the immobilization stress through the transcriptome analysis. These genes are related to apoptosis, tumor-suppression, DNA-binding and protein folding, and thus may be used as potential targets for the development of therapeutics of chronic stress or depressant.

Animals↗
PubMed2003

Transcriptome profiling of a Saccharomyces cerevisiae mutant with a constitutively activated Ras/cAMP pathway.

Often changes in gene expression levels have been considered significant only when above/below some arbitrarily chosen threshold. We investigated the effect of applying a purely statistical approach to microarray analysis and demonstrated that small changes in gene expression have biological significance. Whole genome microarray analysis of a pde2Delta mutant, constructed in the Saccharomyces cerevisiae reference strain FY23, revealed altered expression of approximately 11% of protein encoding genes. The mutant, characterized by constitutive activation of the Ras/cAMP pathway, has increased sensitivity to stress, reduced ability to assimilate nonfermentable carbon sources, and some cell wall integrity defects. Applying the Munich Information Centre for Protein Sequences (MIPS) functional categories revealed increased expression of genes related to ribosome biogenesis and downregulation of genes in the cell rescue, defense, cell death and aging category, suggesting a decreased response to stress conditions. A reduced level of gene expression in the unfolded protein response pathway (UPR) was observed. Cell wall genes whose expression was affected by this mutation were also identified. Several of the cAMP-responsive orphan genes, upon further investigation, revealed cell wall functions; others had previously unidentified phenotypes assigned to them. This investigation provides a statistical global transcriptome analysis of the cellular response to constitutive activation of the Ras/cAMP pathway.

Cell Wall↗
PubMed2004

Pitfalls of quantitative real-time reverse-transcription polymerase chain reaction.

Polymerase chain reaction (PCR)-based assays can target either DNA (the genome) or RNA (the transcriptome). Targeting the genome generates robust data that are informative and, most importantly, generally applicable. This is because the information contained within the genome is context-independent; i.e., generally, every normal cell contains the same DNA sequence--the same mutations and polymorphisms. The transcriptome, on the other hand, is context-dependent; i.e., the mRNA complement and level varies with physiology, pathology, or development. This makes the information contained within the transcriptome intrinsically flexible and variable. If this variability is combined with the technical limitations inherent in any reverse-transcription (RT)-PCR assay, it can be difficult to achieve not just a technically accurate but a biologically relevant result. Template quality, operator variability, the RT step itself, and subjectivity in data analysis and reporting are just a few technical aspects that make real-time RT-PCR appear to be a fragile assay that makes accurate data interpretation difficult. There can be little doubt that in the future, transcriptome-based analysis will become a routine technique. However, for the time being it remains a research tool, and it is important to recognize the considerable pitfalls associated with transcriptome analysis, with the successful application of RTPCR depending on careful experimental design, application, and validation.

Animals↗
PubMed2006

Identification and analysis of genes expressed in the adult filarial parasitic nematode Dirofilaria immitis.

The heartworm Dirofilaria immitis is a filarial parasitic nematode infecting dogs and other mammals worldwide causing fatal complications. Here, we present the first large-scale survey of the adult heartworm transcriptome by generation and analysis of 4005 expressed sequence tags, identifying about 1800 genes and expanding the available sequence information for the parasite significantly. Brugia malayi genomic data offered the most valuable information to interpret heartworm genes, with about 70% of D. immitis genes showing significant similarities to the assembly. Comparative genomic analyses revealed both genes common to metazoans or nematodes and genes specific to filarial parasites that may relate to parasitism. Characterization of abundant transcripts suggested important roles for genes involved in energy generation and antioxidant defense in adults. In particular, we proposed that adult heartworm likely adopted an anaerobic electron transfer-based energy generation system distinct from the aerobic pathway utilized by its mammalian host, making it a promising target in developing next generation macrofilaricides and other treatments. Our survey provided novel insights into the D. immitis transcriptome and laid a foundation for further comparative studies on biology, parasitism and evolution within the phylum Nematoda.

Animals↗
PubMed2006

Hypoxia modifies the transcriptome of primary human monocytes: modulation of novel immune-related genes and identification of CC-chemokine ligand 20 as a new hypoxia-inducible gene.

Peripheral blood monocytes migrate to and accumulate in hypoxic areas of inflammatory and tumor lesions. To characterize the molecular bases underlying monocyte functions within a hypoxic microenvironment, we investigated the transcriptional profile induced by hypoxia in primary human monocytes using high-density oligonucleotide microarrays. Profound changes in the gene expression pattern were detected following 16 h exposure to 1% O(2), with 536 and 677 sequences showing at least a 1.5-fold increase and decrease, respectively. Validation of this analysis was provided by quantitative RT-PCR confirmation of expression differences of selected genes. Among modulated genes, 74 were known hypoxia-responsive genes, whereas the majority were new genes whose responsiveness to hypoxia had not been previously described. The hypoxic transcriptome was characterized by the modulation of a significant cluster of genes with immunological relevance. These included scavenger receptors (CD163, STAB1, C1qR1, MSR1, MARCO, TLR7), immunoregulatory, costimulatory, and adhesion molecules (CD32, CD64, CD69, CD89, CMRF-35H, ITGB5, LAIR1, LIR9), chemokines/cytokines and receptors (CCL23, CCL15, CCL8, CCR1, CCR2, RDC1, IL-23A, IL-6ST). Furthermore, we provided conclusive evidence of hypoxic induction of CCL20, a chemoattractant for immature dendritic cells, activated/memory T lymphocytes, and naive B cells. CCL20 mRNA up-regulation was paralleled by increased protein expression and secretion. This study represents the first transcriptome analysis of hypoxic primary human monocytes, which provides novel insights into monocyte functional behavior within ischemic/hypoxic tissues. CCL20 up-regulation by hypoxia may constitute an important mechanism to promote recruitment of specific leukocyte subsets at pathological sites and may have implications for the pathogenesis of chronic inflammatory diseases.

Cell Hypoxia↗
PubMed2025

Cardiovascular Complications Are Increased in Inflammatory Bowel Disease: A Path Toward Achievement of a Personalized Risk Estimation.

Background/Objectives: The global burden of inflammatory bowel diseases (IBDs) continues to rise, with up to 50% of patients experiencing extraintestinal manifestations. Cardiovascular diseases (CVDs) are of particular concern, ranking as the second leading cause of mortality in this population. Despite a comparatively lower prevalence of traditional cardiovascular (CV) risk factors, the persistent inflammatory milieu and immune dysregulation inherent to IBD may contribute to heightened CVD risk. In this study, following a review of the current literature, an ongoing prospective trial designed to clarify CV risk profiles in IBD patients is detailed. Methods: A cohort of patients with IBD is being enrolled for comprehensive baseline evaluation of CV risk factors, lifestyle metrics, and disease characteristics. The incidence of major adverse cardiovascular events (MACEs) will be tracked and contrasted with a gender- and age-matched non-IBD cohort over a 2-year follow-up period. In cases of MACE occurrence, a multi-omics analysis-including genomic, proteomic, transcriptomic, and microbiome profiling-will be performed, along with a parallel evaluation in matched IBD controls without MACE. An artificial intelligence (AI) framework will support the analysis of this complex dataset. Results: To date, over 150 patients with IBD have been enrolled, and detailed phenotypic data and biological samples have been collected. Conclusions: We aim to introduce an IBD-specific correction factor for existing CV risk scores upon study completion. This is particularly relevant for individuals under 40 years of age, who are often inadequately assessed by current risk stratification models.

Crohn’s disease↗
PubMed2003

Transcriptome-based determination of multiple transcription regulator activities in Escherichia coli by using network component analysis.

Cells adjust gene expression profiles in response to environmental and physiological changes through a series of signal transduction pathways. Upon activation or deactivation, the terminal regulators bind to or dissociate from DNA, respectively, and modulate transcriptional activities on particular promoters. Traditionally, individual reporter genes have been used to detect the activity of the transcription factors. This approach works well for simple, non-overlapping transcription pathways. For complex transcriptional networks, more sophisticated tools are required to deconvolute the contribution of each regulator. Here, we demonstrate the utility of network component analysis in determining multiple transcription factor activities based on transcriptome profiles and available connectivity information regarding network connectivity. We used Escherichia coli carbon source transition from glucose to acetate as a model system. Key results from this analysis were either consistent with physiology or verified by using independent measurements.

Cyclic AMP↗