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PubMed2006

Microarray analysis of IFN-gamma response genes in astrocytes.

IFN-gamma (IFN-gamma) has been shown to activate astrocytes to acquire immune functions. In this study the effect of IFN-gamma on murine astrocytes was investigated via microarray analysis. The activating effect of IFN-gamma on the astrocyte transcriptome showed predominance toward pathways involved in adaptive immunity, initiation of the immune response and innate immunity. Previously unknown astrocytic genes expressed included members of the p47 GTPases and guanine nucleotide binding protein (GBP) families. Down-regulatory effects of IFN-gamma stimulation were confined to pathways involved in growth regulation, cell differentiation and cell adhesion. This data supports the notion that astrocytes are an important immunocompetant cell in the brain and indicate that astrocytes may have a significant role in various infectious diseases such as Toxoplasmic Encephalitis and neurological diseases with an immunological component such as Alzheimer's and autoimmune disorders.

Animals↗

PubMed2005

Development of anonymous cDNA microarrays to study changes to the Senecio floral transcriptome during hybrid speciation.

Interspecific hybridization is an important process through which abrupt speciation can occur. In recent years, genetic changes associated with hybrid speciation have been identified through a variety of techniques, including AFLP/SSR mapping, GISH/FISH and cDNA-AFLP differential display. However, progress in using microarray technology to analyse whole genome/transcriptome changes associated with hybrid speciation has been limited due to the lack of extensive sequence data for many hybrid species and the difficulties in extrapolating results from commercially available microarrays for model species onto nonmodel hybrid taxa. Increasingly therefore researchers studying nonmodel systems are turning to the development of 'anonymous' cDNA microarrays, where the time and cost of producing microarrays is reduced by printing unsequenced cDNA clones, and sequencing only those clones that display interesting expression patterns. Here we describe the creation, testing and preliminary use of anonymous cDNA microarrays to study changes in floral transcriptome associated with allopolyploid speciation in the genus Senecio. We report a comparison of gene expression between the allohexaploid hybrid, Senecio cambrensis, its parental taxa Senecio squalidus (diploid) and Senecio vulgaris (tetraploid), and the intermediate triploid (sterile) hybrid Senecioxbaxteri. Anonymous microarray analysis revealed dramatic differences in floral gene expression between these four taxa and demonstrates the power of this technique for studies of the genetic impact of hybridization in nonmodel flowering plants.

Base Sequence↗

PubMed2005

Synaptic and genomic responses to JNK and AP-1 signaling in Drosophila neurons.

BACKGROUND: The transcription factor AP-1 positively controls synaptic plasticity at the Drosophila neuromuscular junction. Although in motor neurons, JNK has been shown to activate AP-1, a positive regulator of growth and strength at the larval NMJ, the consequences of JNK activation are poorly studied. In addition, the downstream transcriptional targets of JNK and AP-1 signaling in the Drosophila nervous system have yet to be identified. Here, we further investigated the role of JNK signaling at this model synapse employing an activated form of JNK-kinase; and using Serial Analysis of Gene Expression and oligonucleotide microarrays, searched for candidate early targets of JNK or AP-1 dependent transcription in neurons. RESULTS: Temporally-controlled JNK induction in postembryonic motor neurons triggers synaptic growth at the NMJ indicating a role in developmental plasticity rather than synaptogenesis. An unexpected observation that JNK activation also causes a reduction in transmitter release is inconsistent with JNK functioning solely through AP-1 and suggests an additional, yet-unidentified pathway for JNK signaling in motor neurons. SAGE profiling of mRNA expression helps define the neural transcriptome in Drosophila. Though many putative AP-1 and JNK target genes arose from the genomic screens, few were confirmed in subsequent validation experiments. One potentially important neuronal AP-1 target discovered, CG6044, was previously implicated in olfactory associative memory. In addition, 5 mRNAs regulated by RU486, a steroid used to trigger conditional gene expression were identified. CONCLUSION: This study demonstrates a novel role for JNK signaling at the larval neuromuscular junction and provides a quantitative profile of gene transcription in Drosophila neurons. While identifying potential JNK/AP-1 targets it reveals the limitations of genome-wide analyses using complex tissues like the whole brain.

Animals↗

PubMed2006

Adaptation of Bacillus subtilis to growth at low temperature: a combined transcriptomic and proteomic appraisal.

The soil bacterium Bacillus subtilis frequently encounters a reduction in temperature in its natural habitats. Here, a combined transcriptomic and proteomic approach has been used to analyse the adaptational responses of B. subtilis to low temperature. Propagation of B. subtilis in minimal medium at 15 degrees C triggered the induction of 279 genes and the repression of 301 genes in comparison to cells grown at 37 degrees C. The analysis thus revealed profound adjustments in the overall gene expression profile in chill-adapted cells. Important transcriptional changes in low-temperature-grown cells comprise the induction of the SigB-controlled general stress regulon, the induction of parts of the early sporulation regulons (SigF, SigE and SigG) and the induction of a regulatory circuit (RapA/PhrA and Opp) that is involved in the fine-tuning of the phosphorylation status of the Spo0A response regulator. The analysis of chill-stress-repressed genes revealed reductions in major catabolic (glycolysis, oxidative phosphorylation, ATP synthesis) and anabolic routes (biosynthesis of purines, pyrimidines, haem and fatty acids) that likely reflect the slower growth rates at low temperature. Low-temperature repression of part of the SigW regulon and of many genes with predicted functions in chemotaxis and motility was also noted. The proteome analysis of chill-adapted cells indicates a major contribution of post-transcriptional regulation phenomena in adaptation to low temperature. Comparative analysis of the previously reported transcriptional responses of cold-shocked B. subtilis cells with this data revealed that cold shock and growth in the cold constitute physiologically distinct phases of the adaptation of B. subtilis to low temperature.

Adaptation, Physiological↗

PubMed2026

Comparative genomics reveals genotype-phenotype concordance and cryptic resistomes in clinical Pseudomonas aeruginosa.

BACKGROUND: Pseudomonas aeruginosa (P. aeruginosa) is a major pathogen because of its adaptability. It shows rapid evolution of multidrug resistance (MDR). Phenotype-based diagnostics often fail to detect silent resistance determinants and early adaptive changes. This study integrates phenotypic profiling with whole-genome sequencing (WGS) to examine resistance architecture in clinical isolates from eastern India. METHODS: From 1295 culture-positive P. aeruginosa specimens collected at a tertiary care hospital in eastern India. Using predefined criteria, representative MDR and non-MDR isolates were selected, including distinct resistance phenotypes, specimen-source diversity, and hospital and community-acquired settings; multivariate analysis of resistance profiles illustrated phenotypic diversity. Antimicrobial susceptibility assessed using VITEK-2 and Kirby-Bauer disk diffusion, species identity confirmed by 16 S rRNA sequencing, and genomic analysis processed through a reference-guided workflow. Antimicrobial Resistance (AMR) determinants were identified through CARD, and phylogenetic tree constructed from 454 publicly available P. aeruginosa genomes. RESULTS: MDR exhibited greater sequence divergence relative to PA14 (~ 69,000 variants) than the non-MDR isolate (~ 58,700 variants), with > 92% coverage at ≥ 30X depth. Strong genotype-phenotype concordance observed in MDR isolates across five antibiotic classes, associated with β-lactamase variants (PDC-67, OXA-396) and regulatory adaptations (ArmR, cprS). The non-MDR isolate harboured gyrA (T83I) resistance-associated mutations, PDC-1, and OXA-847 without phenotypic expression, indicating silent resistome. Phylogenetically, MDR isolates clustered tightly within the phylogeny, while the non-MDR isolate formed a distinct lineage. CONCLUSION: Observed genomic differences align with adaptation under antimicrobial selection, though confirmation requires larger collections. The non-MDR isolate retained a silent resistome. Findings highlight limitations of phenotype-only diagnostics, support genomic data integration, and emphasize transcriptomics for hidden resistance expression and regulatory dynamics.

Pseudomonas aeruginosa↗

PubMed2006

Integrated analysis of transcriptomic and proteomic data of Desulfovibrio vulgaris: zero-inflated Poisson regression models to predict abundance of undetected proteins.

MOTIVATION: Integrated analysis of global scale transcriptomic and proteomic data can provide important insights into the metabolic mechanisms underlying complex biological systems. However, because the relationship between protein abundance and mRNA expression level is complicated by many cellular and physical processes, sophisticated statistical models need to be developed to capture their relationship. RESULTS: In this study, we describe a novel data-driven statistical model to integrate whole-genome microarray and proteomic data collected from Desulfovibrio vulgaris grown under three different conditions. Based on the Poisson distribution pattern of proteomic data and the fact that a large number of proteins were undetected (excess zeros), zero-inflated Poisson (ZIP)-based models were proposed to define the correlation pattern between mRNA and protein abundance. In addition, by assuming that there is a probability mass at zero representing unexpressed genes and expressed proteins that were undetected owing to technical limitations, a Potential ZIP model was established. Two significant improvements introduced by this approach are (1) the predicted protein abundance level values for experimentally detected proteins are corrected by considering their mRNA levels and (2) protein abundance values can be predicted for undetected proteins (in the case of this study, approximately 83% of the proteins in the D.vulgaris genome) for better biological interpretation. We demonstrated the use of these statistical models by comparatively analyzing proteomic and microarray results from D.vulgaris grown on lactate-based versus formate-based media. These models correctly predicted increased expression of Ech hydrogenase and decreased expression of Coo hydrogenase for D.vulgaris grown on formate.

Adenosine Triphosphate↗

PubMed2003

Microarray analyses of Xylella fastidiosa provide evidence of coordinated transcription control of laterally transferred elements.

Genetically distinct strains of the plant bacterium Xylella fastidiosa (Xf) are responsible for a variety of plant diseases, accounting for severe economic damage throughout the world. Using as a reference the genome of Xf 9a5c strain, associated with citrus variegated chlorosis (CVC), we developed a microarray-based comparison involving 12 Xf isolates, providing a thorough assessment of the variation in genomic composition across the group. Our results demonstrate that Xf displays one of the largest flexible gene pools characterized to date, with several horizontally acquired elements, such as prophages, plasmids, and genomic islands (GIs), which contribute up to 18% of the final genome. Transcriptome analysis of bacteria grown under different conditions shows that most of these elements are transcriptionally active, and their expression can be influenced in a coordinated manner by environmental stimuli. Finally, evaluation of the genetic composition of these laterally transferred elements identified differences that may help to explain the adaptability of Xf strains to infect such a wide range of plant species.

Chromosome Mapping↗

PubMed2006

ppGalNAc-T13: a new molecular marker of bone marrow involvement in neuroblastoma.

BACKGROUND: To identify new molecular markers of bone marrow dissemination in human neuroblastoma (NB), we studied the transcriptome profiles of malignant neuroblasts established from the human MYCN-amplified IGR-N-91 model. METHODS: This experimental model includes human neuroblastoma cells derived from a subcutaneous stage 4 disease, myocardium (Myoc) and bone marrow (BM) metastatic cells. RESULTS: Gene expression profiles obtained with Agilent oligo microarrays revealed a set of 107 differentially expressed genes in the metastatic neuroblasts. This set included up-regulated genes involved in chemoresistance, cell motility, neuronal structure/signaling, and the recently characterized GALNT13 gene encoding a glycosyltransferase that initiates mucin-type O-glycosylation. Because the glycosylation process is involved in the progression of primary tumor to metastatic disease, we investigated whether the most strongly up-regulated gene, GALNT13, might be a marker of bone marrow involvement in stage 4 NB patients. Importantly, in the BM of healthy adults no GALNT13 transcript was detected with analysis by quantitative (n = 3) and nested reverse transcription-PCR (n = 4) assays. In contrast, GALNT13 transcripts were detected in 23/23 cytologically involved BM samples obtained at diagnosis of stage 4 NB patients and in 5/27 cytologically noninvolved BM samples obtained from patients with stage 1-4 and 4S and treated stage 4 NB. The quantitative measurements of tyrosine hydroxylase (TH), ganglioside D2 synthase, dopa decarboxylase, and GALNT13 transcript values were compared in the same NB patients, and the results showed that GALNT13 expression was most highly correlated to poor clinical outcome at diagnosis. CONCLUSION: We propose ppGalNAc-T13 as a new informative marker for the molecular diagnosis of BM involvement and the follow-up of minimal residual disease in NB patients.

Adolescent↗

PubMed2003

[Identification of differentially expressed genes of acute hypoxia-treated HepG2 cells and hypoxia-acclimatized HepG2 cells].

To provide necessary information for further understanding of molecular mechanism of hypoxia acclimatization, the differentially expressed genes of HepG2 cells exposed to normoxia, acute hypoxia-treated cells which were exposed to 1% oxygen for 48 h, and hypoxia-acclimatized HepG2 cells which were cultured for 6 circles of alternate low oxygen (1% oxygen for 24 h) and normal oxygen (21% oxygen for 24 h), were identified respectively by combining the suppression subtractive hybridization (SSH) and cDNA microarray. Thirty-seven genes were expressed differentially in cells exposed to 1% oxygen for 48 h compared with those in cells exposed to normoxia. The expression of all these 37 genes was down-regulated, including the genes participating in cell cycle, cell response to stimulus, and cell signal transduction, and cell cytoskeleton formation, the genes associated with transcription and cell metabolism, 4 expressed sequence tags (ESTs), and 12 genes of which the functions are not known. There is a novel gene sequence, which has not been found in existing databases. There were only 6 genes differentially expressed in the hypoxia-acclimatized cells compared with cells exposed to normoxia, including two mitochondrion genes, metalloprotease-1 gene, ferritin gene, thymosin beta-4 and TPT1 genes. The expressions of mitochondrion ND4, ferritin, thymosin beta-4 and TPT1 were up-regulated, while the expressions of mitochondrion ND1 gene and metalloproease-1 gene were down-regulated. Cell tolerance to hypoxia increased after the cells were hypoxia-acclimatized. The different gene expression patterns of the acute hypoxia-treated cells and the hypoxia-acclimatized cells may be related to the increased tolerance of the cells to hypoxia.

Adaptation, Physiological↗

PubMed2003

Assessment of SAGE in transcript identification.

An essential step in Serial Analysis of Gene Expression (SAGE) is tag mapping, which refers to the unambiguous determination of the gene represented by a SAGE tag. Current resources for tag mapping are incomplete, and thus do not allow assessment of the efficacy of SAGE in transcript identification. A method of tag mapping is described here and applied to the Drosophila melanogaster and Caenorhabditis elegans genomes, which permits detailed SAGE assessment and provides tag-mapping resources that were unavailable previously for these organisms. In our method, a conceptual transcriptome is constructed using genomic sequence and annotation by extending predicted coding regions to include UTRs on the basis of EST and cDNA alignments, UTR length distributions, and polyadenylation signals. Analysis of extracted tags suggests that, using the standard SAGE procedure, expression of 8% of D. melanogaster and 15% of C. elegans genes cannot be detected unambiguously by SAGE due to shared sequence or lack of NlaIII-anchoring enzyme sites. Both increasing tag length by 2-3 bp and using Sau3A instead of NlaIII as the anchoring enzyme increases potential for transcript detection. This work identifies and quantifies genes not amenable to SAGE analysis, in addition to providing tag-to-gene mappings for two model organisms.

Animals↗

PubMed2004

A non-EST-based method for exon-skipping prediction.

It is estimated that between 35% and 74% of all human genes can undergo alternative splicing. Currently, the most efficient methods for large-scale detection of alternative splicing use expressed sequence tags (ESTs) or microarray analysis. As these methods merely sample the transcriptome, splice variants that do not appear in deeply sampled tissues have a low probability of being detected. We present a new method by which we can predict that an internal exon is skipped (namely whether it is a cassette-exon) merely based on its naked genomic sequence and on the sequence of its mouse ortholog. No other data, such as ESTs, are required for the prediction. Using our method, which was experimentally validated, we detected hundreds of novel splice variants that were not detectable using ESTs. We show that a substantial fraction of the splice variants in the human genome could not be identified through current human EST or cDNA data.

Alternative Splicing↗

PubMed2005

A computational study of off-target effects of RNA interference.

RNA interference (RNAi) is an intracellular mechanism for post-transcriptional gene silencing that is frequently used to study gene function. RNAi is initiated by short interfering RNA (siRNA) of approximately 21 nt in length, either generated from the double-stranded RNA (dsRNA) by using the enzyme Dicer or introduced experimentally. Following association with an RNAi silencing complex, siRNA targets mRNA transcripts that have sequence identity for destruction. A phenotype resulting from this knockdown of expression may inform about the function of the targeted gene. However, 'off-target effects' compromise the specificity of RNAi if sequence identity between siRNA and random mRNA transcripts causes RNAi to knockdown expression of non-targeted genes. The complete off-target effects must be investigated systematically on each gene in a genome by adjusting a group of parameters, which is too expensive to conduct experimentally and motivates a study in silico. This computational study examined the potential for off-target effects of RNAi, employing the genome and transcriptome sequence data of Homo sapiens, Caenorhabditis elegans and Schizosaccharomyces pombe. The chance for RNAi off-target effects proved considerable, ranging from 5 to 80% for each of the organisms, when using as parameter the exact identity between any possible siRNA sequences (arbitrary length ranging from 17 to 28 nt) derived from a dsRNA (range 100-400 nt) representing the coding sequences of target genes and all other siRNAs within the genome. Remarkably, high-sequence specificity and low probability for off-target reactivity were optimally balanced for siRNA of 21 nt, the length observed mostly in vivo. The chance for off-target RNAi increased (although not always significantly) with greater length of the initial dsRNA sequence, inclusion into the analysis of available untranslated region sequences and allowing for mismatches between siRNA and target sequences. siRNA sequences from within 100 nt of the 5' termini of coding sequences had low chances for off-target reactivity. This may be owing to coding constraints for signal peptide-encoding regions of genes relative to regions that encode for mature proteins. Off-target distribution varied along the chromosomes of C.elegans, apparently owing to the use of more unique sequences in gene-dense regions. Finally, biological and thermodynamical descriptors of effective siRNA reduced the number of potential siRNAs compared with those identified by sequence identity alone, but off-target RNAi remained likely, with an off-target error rate of approximately 10%. These results also suggest a direction for future in vivo studies that could both help in calibrating true off-target rates in living organisms and also in contributing evidence toward the debate of whether siRNA efficacy is correlated with, or independent of, the target molecule. In summary, off-target effects present a real but not prohibitive concern that should be considered for RNAi experiments.

Animals↗

PubMed2004

Gene expression profiling of human cancers.

DNA microarrays allow us to visualize simultaneously the expression of potentially all genes within a cell population or tissue sample-revealing the "transcriptome." The analysis of this type of data is commonly called "gene expression profiling" (GEP) because it provides a comprehensive picture of the pattern of gene expression in a particular biological sample. For this reason microarrays are revolutionizing life sciences research and are leading to the development of novel and powerful methods for investigating cancer biology, classifying cancers, and predicting clinical outcome of cancers. Several recent high-profile reports have revealed how clustering of GEP data can clearly identify clinically (and prognostically) important subtypes of cancer among patients considered by established clinicopathological criteria to have similar tumors. Accurate "prognostic signatures" can be obtained from GEP data, which represent relatively small numbers of genes. These signatures can be valuable in directing appropriate treatment and in predicting clinical outcome, and they generally outperform other systems based on clinical and histological criteria. In this paper the basic principles of DNA microarray technology and the different types of microarray platforms available will be introduced, and the power of the technique will be illustrated by reviewing some recent GEP studies on selected cancers, including a preliminary analysis of hepatocellular carcinoma from our Palermo laboratory. GEP is likely to be adopted in the future as a key decision-making tool in the clinical arena. However, several issues relating to data analysis, reproducibility, cross-comparability, validation, and cost need to be resolved before the technology can be adopted broadly in this context.

Carcinoma, Hepatocellular↗

PubMed2004

GadE (YhiE): a novel activator involved in the response to acid environment in Escherichia coli.

In several Gram-positive and Gram-negative bacteria glutamate decarboxylases play an important role in the maintenance of cellular homeostasis in acid environments. Here, new insight is brought to the regulation of the acid response in Escherichia coli. Overexpression of yhiE, similarly to overexpression of gadX, a known regulator of glutamate decarboxylase expression, leads to increased resistance of E. coli strains under high acid conditions, suggesting that YhiE is a regulator of gene expression in the acid response. Target genes of both YhiE (renamed GadE) and GadX were identified by a transcriptomic approach. In vitro experiments with GadE purified protein provided evidence that this regulator binds to the promoter region of these target genes. Several of them are clustered together on the chromosome and this chromosomal organization is conserved in many E. coli strains. Detailed structural (in silico) analysis of this chromosomal region suggests that the promoters of the corresponding genes are preferentially denatured. These results, along with the G+C signature of the chromosomal region, support the existence of a fitness island for acid adaptation on the E. coli chromosome.

AraC Transcription Factor↗

PubMed2006

Computational models with thermodynamic and composition features improve siRNA design.

BACKGROUND: Small interfering RNAs (siRNAs) have become an important tool in cell and molecular biology. Reliable design of siRNA molecules is essential for the needs of large functional genomics projects. RESULTS: To improve the design of efficient siRNA molecules, we performed a comparative, thermodynamic and correlation analysis on a heterogeneous set of 653 siRNAs collected from the literature. We used this training set to select siRNA features and optimize computational models. We identified 18 parameters that correlate significantly with silencing efficiency. Some of these parameters characterize only the siRNA sequence, while others involve the whole mRNA. Most importantly, we derived an siRNA position-dependent consensus, and optimized the free-energy difference of the 5' and 3' terminal dinucleotides of the siRNA antisense strand. The position-dependent consensus is based on correlation and t-test analyses of the training set, and accounts for both significantly preferred and avoided nucleotides in all sequence positions. On the training set, the two parameters' correlation with silencing efficiency was 0.5 and 0.36, respectively. Among other features, a dinucleotide content index and the frequency of potential targets for siRNA in the mRNA added predictive power to our model (R = 0.55). We showed that our model is effective for predicting the efficiency of siRNAs at different concentrations. We optimized a neural network model on our training set using three parameters characterizing the siRNA sequence, and predicted efficiencies for the test siRNA dataset recently published by Novartis. On this validation set, the correlation coefficient between predicted and observed efficiency was 0.75. Using the same model, we performed a transcriptome-wide analysis of optimal siRNA targets for 22,600 human mRNAs. CONCLUSION: We demonstrated that the properties of the siRNAs themselves are essential for efficient RNA interference. The 5' ends of antisense strands of efficient siRNAs are U-rich and possess a content similarity to the pyrimidine-rich oligonucleotides interacting with the polypurine RNA tracks that are recognized by RNase H. The advantage of our method over similar methods is the small number of parameters. As a result, our method requires a much smaller training set to produce consistent results. Other mRNA features, though expensive to compute, can slightly improve our model.

Artificial Intelligence↗

PubMed2005

Comparison of changes in fruit gene expression in tomato introgression lines provides evidence of genome-wide transcriptional changes and reveals links to mapped QTLs and described traits.

Total soluble solids content is a key determinant of tomato fruit quality for processing. Several tomato lines carrying defined introgressions from S. pennellii in a S. lycopersicum background produce fruit with elevated Brix, a refractive index measure of soluble solids. The genetic basis for this trait can be determined by fine-mapping each QTL to a single gene, but this is time-consuming and technically demanding. As an alternative, high-throughput analytical technologies can be used to provide useful information that helps characterize molecular changes in the introgression lines. This paper presents a study of transcriptomic changes in six introgression lines with increased fruit Brix. Each line also showed altered patterns of fruit carbohydrate accumulation. Transcriptomic changes in fruit at 20 d after anthesis (DAA) were assessed using a 12 000-element EST microarray and significant changes analysed by SAM (significance analysis of microarrays). Each non-overlapping introgression resulted in a unique set of transcriptomic changes with 78% of significant changes being unique to a single line. Principal components analysis allowed a clear separation of the six lines, but also revealed evidence of common changes; lines with quantitatively similar increases in Brix clustered together. A detailed examination of genes encoding enzymes of primary carbon metabolism demonstrated that few of the known introgressed alleles were altered in expression at the 20 DAA time point. However, the expression of other metabolic genes did change. Particularly striking was the co-ordinated up-regulation of enzymes of sucrose mobilization and respiration that occurred only in the two lines with the highest Brix increase. These common downstream changes suggest a similar mechanism is responsible for large Brix increases.

Carbohydrate Metabolism↗

PubMed2003

Comprehensive analysis of the mouse metabolome based on the transcriptome.

The complete set of cDNAs encoding the enzymes of known metabolic pathways has not previously been available for any mammal. Here, transcripts encoding the metabolic pathways of the mouse (mouse metabolome) were reconstructed by making use of the KEGG metabolic pathway database and gene ontology (GO) assignment to the mouse representative transcript and protein set (RTPS), which contains all available mouse transcript sequences including the FANTOM set of RIKEN mouse cDNA clones. By assigning EC numbers extracted from the molecular function ontology in GO, the known mouse transcriptome was predicted to encode enzymes with 726 unique EC numbers. Of these, 648 EC numbers were newly assigned based on the FANTOM set. The mouse metabolome confirmed by cDNA analysis includes almost all of the enzymes of well known pathways such as the tricarboxylic acid cycle and urea cycle. On the other hand, analysis of enzymes required for the tryptophan metabolism pathway revealed a lack of connectivity, indicating that cDNAs/genes encoding several key enzymes remain to be identified. The information derived from coexpression from the cDNA microarray analysis of enzymes of known function may lead to identification of the missing components of the metabolome, and will add new insights into the connectivity of the mammalian metabolic pathways.

Amino Acids↗

PubMed2024

Identification of miRNA expression profile in middle ear cholesteatoma using small RNA-sequencing.

BACKGROUND: The present study aims to identify the differential miRNA expression profile in middle ear cholesteatoma and explore their potential roles in its pathogenesis. METHODS: Cholesteatoma and matched normal retroauricular skin tissue samples were collected from patients diagnosed with acquired middle ear cholesteatoma. The miRNA expression profiling was performed using small RNA sequencing, which further validated by quantitative real-time PCR (qRT-PCR). Target genes of differentially expressed miRNAs in cholesteatoma were predicted. The interaction network of 5 most significantly differentially expressed miRNAs was visualized using Cytoscape. Further Gene Ontology (GO) and Kyoto Encyclopedia of Genes and Genome (KEGG) pathway enrichment analyses were processed to investigate the biological functions of miRNAs in cholesteatoma. RESULTS: The miRNA expression profile revealed 121 significantly differentially expressed miRNAs in cholesteatoma compared to normal skin tissues, with 56 upregulated and 65 downregulated. GO and KEGG pathway enrichment analyses suggested their significant roles in the pathogenesis of cholesteatoma. The interaction network of the the 2 most upregulated (hsa-miR-21-5p and hsa-miR-142-5p) and 3 most downregulated (hsa-miR-508-3p, hsa-miR-509-3p and hsa-miR-211-5p) miRNAs identified TGFBR2, MBNL1, and NFAT5 as potential key target genes in middle ear cholesteatoma. CONCLUSIONS: This study provides a comprehensive miRNA expression profile in middle ear cholesteatoma, which may aid in identifying therapeutic targets for its management.

Humans↗