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PubMed2007

Transcriptome classification of HCC is related to gene alterations and to new therapeutic targets.

UNLABELLED: Hepatocellular carcinomas (HCCs) are a heterogeneous group of tumors that differ in risk factors and genetic alterations. We further investigated transcriptome-genotype-phenotype correlations in HCC. Global transcriptome analyses were performed on 57 HCCs and 3 hepatocellular adenomas and validated by quantitative RT-PCR using 63 additional HCCs. We determined loss of heterozygosity, gene mutations, promoter methylation of CDH1 and CDKN2A, and HBV DNA copy number for each tumor. Unsupervised transcriptome analysis identified 6 robust subgroups of HCC (G1-G6) associated with clinical and genetic characteristics. G1 tumors were associated with low copy number of HBV and overexpression of genes expressed in fetal liver and controlled by parental imprinting. G2 included HCCs infected with a high copy number of HBV and mutations in PIK3CA and TP53. In these first groups, we detected specific activation of the AKT pathway. G3 tumors were typified by mutation of TP53 and overexpression of genes controlling the cell cycle. G4 was a heterogeneous subgroup of tumors including TCF1-mutated hepatocellular adenomas and carcinomas. G5 and G6 were strongly related to beta-catenin mutations that lead to Wnt pathway activation; in particular, G6 tumors were characterized by satellite nodules, higher activation of the Wnt pathway, and E-cadherin underexpression. CONCLUSION: These results have furthered our understanding of the genetic diversity of human HCC and have provided specific identifiers for classifying tumors. In addition, our classification has potential therapeutic implications because 50% of the tumors were related to WNT or AKT pathway activation, which potentially could be targeted by specific inhibiting therapies.

Adenoma↗

PubMed2006

Insights into human CD34+ hematopoietic stem/progenitor cells through a systematically proteomic survey coupled with transcriptome.

Hematopoietic stem cells are capable of self-renewal and differentiation into different hematopoietic lineages. To gain a comprehensive understanding of hematopoietic stem/progenitor cells, a systematic proteomic survey of human CD34+ cells collected from human umbilical cord blood was performed, in which the proteins were separated by 1- and 2-DE, as well as by nano-LC, and subsequently identified by MS. A total of 370 distinct proteins identified from those cells provided new insights into the potential of the stem/progenitor cells because the nerve, gonad, and eye-associated proteins were reliably identified. Interestingly, the transcripts of 133 (35.9%) identified proteins were not found by the prevalent transcriptome approaches, although several selected transcripts could be detected by RT-PCR. Moreover, the heterogeneity of 33 proteins identified from 2-DE was attributable primarily to post-translational processes rather than to alternative splicing at transcriptional level. Furthermore, the biosyntheses of 15 proteins identified in this study appears not to be completely interrupted in spite of the fact that corresponding antisense RNAs were found in the existing transcriptome data. The integrated proteomic and transcriptomic analyses employed here provided a unique view of the human stem/progenitor cells.

Antigens, CD34↗

PubMed2006

The iron-regulated transcriptome and proteome of Neisseria meningitidis serogroup C.

Restricting bacterial growth by iron-chelating proteins that reduce iron availability in mucosal secretions and body fluids belongs to basic mechanisms of innate immunity. Most pathogens and commensals thus developed gene regulons responding to iron concentration and encoding iron acquisition systems and genes involved in host colonization and virulence. Here, we analyzed the steady-state composition of the iron-regulated proteome and transcriptome of an invasive serogroup C clinical isolate of Neisseria meningitidis. The proteome of meningococci grown under iron-depleted and iron-replete conditions was analyzed by 2-DE and proteins exhibiting significantly altered expression were identified by MALDI-TOF MS analysis. In parallel, total RNA was isolated from the same cultures and iron-regulated genes were identified using whole-genome DNA microarrays. The proteome and the transcriptome were found to overlap by only 19 iron-regulated genes/proteins, with 111 genes/proteins being significantly up-regulated in iron-replete cultures and 130 genes/proteins being up-regulated during iron starvation, respectively. Comparisons with published transcriptomic data for N. meningitidis serogroup B, moreover, indicate that expression of up to 20% of all meningococcal genes can be subject to regulation in function of iron availability.

Deferoxamine↗

PubMed2006

Myc target transcriptomes.

The c-Myc oncogenic transcription factor plays a central role in many human cancers through the regulation of gene expression. Although the molecular mechanisms by which c-Myc and its obligate partner, Max, regulate gene expression are becoming better defined, genes or transcriptomes that c-Myc regulate are just emerging from a variety of different experimental approaches. Studies of individual c-Myc target genes and their functional implications are now complemented by large surveys of c-Myc target genes through the use of subtraction cloning, DNA microarray analysis, serial analysis of gene expression (SAGE), chromatin immunoprecipitation, and genome marking methods. To fully appreciate the differences between physiological c-Myc function in normal cells and deregulated c-Myc function in tumors, the challenge now is to determine how the authenticated transcriptomes effect the various phenotypes induced by c-Myc and to define how c-Myc transcriptomes are altered by the Mad family of proteins.

Animals↗

PubMed2006

Global transcriptome response of recombinant Escherichia coli to heat-shock and dual heat-shock recombinant protein induction.

Recombinant Escherichia coli cultures are used to manufacture numerous therapeutic proteins and industrial enzymes, where many of these processes use elevated temperatures to induce recombinant protein production. The heat-shock response in wild-type E. coli has been well studied. In this study, the transcriptome profiles of recombinant E. coli subjected to a heat-shock and to a dual heat-shock recombinant protein induction were examined. Most classical heat-shock protein genes were identified as regulated in both conditions. The major transcriptome differences between the recombinant and reported wild-type cultures were heavily populated by hypothetical and putative genes, which indicates recombinant cultures utilize many unique genes to respond to a heat-shock. Comparison of the dual stressed culture data with literature recombinant protein induced culture data revealed numerous differences. The dual stressed response encompassed three major response patterns: induced-like, in-between, and greater than either individual stress response. Also, there were no genes that only responded to the dual stress. The most interesting difference between the dual stressed and induced cultures was the amino acid-tRNA gene levels. The amino acid-tRNA genes were elevated for the dual cultures compared to the induced cultures. Since, tRNAs facilitate protein synthesis via translation, this observed increase in amino acid-tRNA transcriptome levels, in concert with elevated heat-shock chaperones, might account for improved productivities often observed for thermo-inducible systems. Most importantly, the response of the recombinant cultures to a heat-shock was more profound than wild-type cultures, and further, the response to recombinant protein induction was not a simple additive response of the individual stresses.

Cell Culture Techniques↗

PubMed2006

The transcriptome of the uterine cervix before and after spontaneous term parturition.

OBJECTIVE: This study was designed to identify genes differentially expressed in the human uterine cervix after spontaneous term labor. STUDY DESIGN: The transcriptome of cervical tissue was characterized using Affymetrix HG-U133 plus 2 microarrays. Samples were collected from patients at term not in labor (n = 7) and after spontaneous labor (n = 9). Microarray statistical analysis included robust multiarray average, reduction of invariant probes, and permutation analysis for differential expression. Real-time quantitative reverse transcriptase-polymerase chain reaction assays of selected genes were performed on a new set of samples from term patients without labor (n = 10) and patients after spontaneous labor (n = 9). RESULTS: (1) The cervical transcriptome of term patients without labor was dramatically different from that of patients who underwent labor; (2) unique genes (n = 1192) were differentially expressed in the cervical tissue from patients after spontaneous labor, compared with that of the term patients without labor (false discovery rate less than 0.05, absolute fold change greater than 2); (3) Gene Ontology analysis indicated that multiple "Biological Process" categories were enriched, including "response to biotic stimulus," "apoptosis," "epidermis development," and "steroid metabolism"; (4) of major interest, genes involved in neutrophil chemotaxis were dramatically up-regulated in specimens from women after spontaneous labor; (5) real-time quantitative reverse transcriptase-polymerase chain reaction confirmed the increased expression of interleukin-8, interleukin-6, and vascular endothelial growth factor in patients after spontaneous labor; and (6) Toll-like receptor-3 and Toll-like receptor-5 showed decreased gene expression in patients after spontaneous labor. This was confirmed by real-time quantitative reverse transcriptase-polymerase chain reaction. CONCLUSION: (1) Cervical dilatation in term labor is associated with a stereotypic gene expression pattern determined by microarray, which is characterized by overexpression of genes involved in neutrophil chemotaxis, apoptosis, extracellular matrix regulation, and steroid metabolism; (2) Toll-like receptor-3 and Toll-like receptor-5 are differentially regulated during spontaneous parturition at term; and (3) this study provides an unbiased and comprehensive description of the changes in the cervical transcriptome before and after spontaneous term labor.

Adolescent↗

PubMed2004

The difficult interpretation of transcriptome data: the case of the GATC regulatory network.

Genomic analyses on part of Escherichia coli's chromosome had suggested the existence of a GATC regulated network. This has recently been confirmed through a transcriptome analysis. Two hypotheses about the molecular control mechanism have been proposed-(i) the GATC network regulation is caused by the presence of GATC clusters within the coding sequences; the regulation is the direct consequence of the clusters' hemi-methylation and therefore their elevated melting temperature, (ii) the regulation is caused by the presence of GATCs in the non-coding 500 bp upstream regions of the affected genes; it is the consequence of an interaction with a regulatory protein like Fnr or CAP. An analysis of the transcriptome data has not allowed us to decide between the two hypotheses. We have therefore taken a classic genomic approach, analyzing the statistical distribution of GATC along the chromosome, using a realistic model of the chromosome as theoretical reference. We observe no particular distribution of GATC in the non-coding upstream regions; however, we confirm the presence of GATC clusters within the genes. In order to verify that the particular distribution observed in E. coli is not a statistical artefact, but has a physiological role, we have carried out the same analysis on Salmonella, making the hypothesis that the genes containing a GATC clusters should be largely the same in the two bacteria. This has been indeed observed, showing that the genes containing a GATC cluster are part of a regulation network. The present is a case study, which demonstrates that the analysis of transcriptome data does not always permit to identify the primary cause of a phenomenon observed; on the other hand, a classic genomic approach linked with a comparative study of related genomes may allow this identification.

Computational Biology↗

PubMed2006

The heterogeneity of human mesenchymal stem cell preparations--evidence from simultaneous analysis of proteomes and transcriptomes.

OBJECTIVE: Mesenchymal stem cells (MSC) raise high hopes in clinical applications. However, the lack of common standards and a precise definition of MSC preparations remains a major obstacle in research and application of MSC. Whereas surface antigen markers have failed to precisely define this population, a combination of proteomic data and microarray data provides a new dimension for the definition of MSC preparations. METHODS: In our continuing effort to characterize MSC, we have analyzed the differential transcriptome and proteome expression profiles of MSC preparations isolated from human bone marrow under two different expansion media (BM-MSC-M1 and BM-MSC-M2). RESULTS: In proteomics, 136 protein spots were unambiguously identified by MALDI-TOF-MS and corresponding cDNA spots were selected on our "Human Transcriptome cDNA Microarray." Combination of datasets revealed a correlation in differential gene expression and protein expression of BM-MSC-M1 vs BM-MSC-M2. Genes involved in metabolism were more highly expressed in BM-MSC-M1, whereas genes involved in development, morphogenesis, extracellular matrix, and differentiation were more highly expressed in BM-MSC-M2. Interchanging culture conditions for 8 days revealed that differential expression was retained in several genes whereas it was altered in others. CONCLUSION: Our results have provided evidence that homogeneous BM-MSC preparations can reproducibly be isolated under standardized conditions, whereas culture conditions exert a prominent impact on transcriptome, proteome, and cellular organization of BM-MSC.

Cell Culture Techniques↗

PubMed2005

Genomic technologies and the interrogation of the transcriptome.

Functional genomics refers to the study of whole genomes and the function of its constituent parts to explain biological processes. Though these investigations may involve whole proteome analysis, the primary focus is on the transcriptome and how it is regulated. Recent advances in technologies that can interrogate cellular transcripts on a genome-wide scale seek the complete disclosure of the transcriptome over time-intervals and across many different cellular states. This massively complex data when viewed as a whole can provide surprisingly precise assessment of cellular conditions. Moreover, these data can define hierarchies of importance and have shown us new transcriptional elements. Herein, we describe the technologies and the experimental strategies to study the transcriptome that would be pertinent to cancer and ageing research.

Animals↗

PubMed2005

Correlation of proteomic and transcriptomic profiles of Staphylococcus aureus during the post-exponential phase of growth.

A combined proteomic and transcriptomic analysis of Staphylococcus aureus strain N315 was performed to study a sequenced strain at the system level. Total protein and membrane protein extracts were prepared and analyzed using various proteomic workflows including: 2-DE, SDS-PAGE combined with microcapillary LC-MALDI-MS/MS, and multidimensional liquid chromatography. The presence of a protein was then correlated with its respective transcript level from S. aureus cells grown under the same conditions. Gene-expression data revealed that 97% of the 2'596 ORFs were detected during the post-exponential phase. At the protein level, 23% of these ORFs (591 proteins) were identified. Correlation of the two datasets revealed that 42% of the identified proteins (248 proteins) were amongst the top 25% of genes with highest mRNA signal intensities, and 69% of the identified proteins (406 proteins) were amongst the top 50% with the highest mRNA signal intensities. The fact that the remaining 31% of proteins were not strongly expressed at the RNA level indicates either that some low-abundance proteins were identified or that some transcripts or proteins showed extended half-lives. The most abundant classes identified with the combined proteomic and transcriptomic approach involved energy production, translational activities and nucleotide transport, reflecting an active metabolism. The simultaneous large-scale analysis of transcriptomes and proteomes enables a global and holistic view of the S. aureus biology, allowing the parallel study of multiple active events in an organism.

Bacterial Proteins↗

PubMed2006

Correlation of transcriptome profile with electrical activity in temporal lobe epilepsy.

The biology underlying epileptic brain activity in humans is not well understood and likely depends on changes in gene expression. We performed a microarray transcriptome profiling of 12 anterolateral temporal cortical samples originating from five individuals who suffered with temporal lobe epilepsy for at least 10 years. Prior to partial lobectomy, intraoperative electrocorticography was performed on the cortical surface of each patient. These recordings showed characteristic differences in frequency and amplitude that were defined as "spiking" (abnormal) or "non-spiking" (normal). Between the transcriptome of the two sample groups, transferrin (TF) was the most differentially expressed gene. Furthermore, gene expression profiling also revealed a downregulation of multiple GABA system-related genes (GABRA5, GABRB3, ABAT) in the spiking samples and an upregulation of oligodendrocyte and lipid metabolism transcripts (MOG, CA2, CNP, SCD, PLP1, FA2H, ABCA2). In addition, several transcripts related to the classical MAPK cascade showed expression level alterations between the spiking and non-spiking samples (G3BP2, MAPK1, PRKAR1A, and MAP4K4). Out of 12 genes chosen for verification by RT qPCR, 9 showed significant expression changes in the microarray-predicted direction. Furthermore, the microarray and qPCR data were highly correlated (r = 0.98; P < 0.001). We conclude that abnormal electrical brain activity in the spiking samples is strongly correlated with gene expression changes and we speculate that some of the observed transcriptome changes may be directly involved in the induction or prevention of the ictal events seen in epilepsy.

Action Potentials↗

PubMed2006

Elements of the granular gland peptidome and transcriptome persist in air-dried skin of the South American orange-legged leaf frog, Phyllomedusa hypocondrialis.

The defensive strategy of amphibians against predator attack relies heavily on the secretion of noxious/toxic chemical cocktails from specialized skin granular glands. Bioactive peptides constitute a major component of secretions in many species and the most complex are produced by neotropical leaf frogs of the sub-family Phyllomedusinae. We recently reported that these skin secretions contain elements of both the granular gland peptidome and transcriptome and that polyadenylated mRNAs constituting the latter are protected from degradation by interactions with endogenous amphipathic peptides. This thus permits parallel amino acid sequencing of peptides and nucleic acid sequencing of cloned precursor transcripts from single lyophilized samples of secretion. Here we report that the protection afforded is sufficiently robust to permit transcriptome studies by cloning of full-length polyadenylated peptide precursor encoding mRNAs from libraries constructed using ambient temperature air-dried skin from recently deceased specimens as source material. The technique was sufficiently sensitive to permit the identification of cDNAs encoding antimicrobial peptides constituted by six different isoforms of phylloseptin and two dermaseptins. Also, for the first time, establishment of the nucleic acid and amino acid sequence of the precursor encoding the phyllomedusine frog skin bradykinin-related peptide, phyllokinin, from cloned cDNA, was achieved. These data unequivocally demonstrate that the granular gland transcriptome persists in air-dried amphibian skin--a finding that may have fundamental implications in the study of archived materials but also in the wider field of molecular biology.

Amino Acid Sequence↗

PubMed2006

Cellular transcriptomics -- the next phase of endocrine expression profiling.

Transcriptome analysis, or global gene expression profiling, has become a commonly used and valuable tool in both basic and clinical endocrine research. Novel endocrine regulators have 'surfaced' and greater consideration is now given to understanding function at the level of gene networks. Recent developments have shown that the transcriptome is considerably larger and more divergently expressed than was previously thought. Endocrine cells express a great variety of coding and noncoding RNAs in a highly cell-specific manner. If further value is to be taken from this research area, then steps towards defined cellular transcriptomics must be taken. New sampling techniques that utilize novel genetic models are a key first step.

Animals↗

PubMed2004

Analysis of mouse germ-cell transcriptome at different stages of spermatogenesis by SAGE: biological significance.

The transcriptomes of mouse type A spermatogonia (Spga), pachytene spermatocytes (Spcy), and round spermatids (Sptd) were determined by sequencing the respective SAGE (Serial Analysis of Gene Expression) libraries. A total of 444,015 tags derived from one Spga, two Spcy, and one Sptd library were analyzed, and 34,619 different species of transcripts were identified, 5279 of which were novel. Results indicated the germ-cell transcriptome comprises of more than 30,000 transcripts. Virtual subtraction showed that cell-specific transcripts constitute 12-19.5% of the transcriptome. Components of the protein biosynthetic machinery are highly expressed in Spga. In Spcy transcription factors are abundantly expressed while transcripts encoding proteins involved in chromosome remodeling and testis-specific transcripts are prominent in Sptd. The databases generated by this work provide very useful resources for cellular localization of genes in silico. They are also extremely useful as sources for identification of splice variants of genes in germ cells.

Animals↗

PubMed2006

A highly standardized, robust, and cost-effective method for genome-wide transcriptome analysis of peripheral blood applicable to large-scale clinical trials.

The use of peripheral blood mononuclear cells (PBMC) for transcriptome analysis has already been proven valuable for assessing disease-associated and drug-response-related gene signatures. While these proof-of-principle studies have been critically important, the instability of RNA within PBMC prohibits their use in large-scale multicenter trials for which samples have to be transported for a prolonged time prior to RNA isolation. Therefore, a prerequisite for transcriptome analysis of peripheral blood in clinical trials will be a standardized and valid method to stabilize the RNA profile immediately after blood withdrawal. Moreover, to be able to perform such large-scale clinical studies routinely in several hundred patients more cost-effective array technologies are required. To address these critical issues, we have combined a whole-blood RNA stabilization technology with a method to reduce globin mRNA, followed by genome-wide transcriptome analysis using a newly introduced BeadChip oligonucleotide technology. We demonstrate that the globin mRNA reduction method results in significantly improved data quality of stabilized RNA samples with low intragroup variance and a detection rate of expressed genes similar to that in PBMC. More important, even small differences in gene expression such as are observed between females and males were detected and sufficient to predict gender in whole-blood samples. We therefore propose the combination of globin mRNA reduction after whole-blood RNA stabilization with a newly introduced cost-effective BeadChip array as the preferred approach for large-scale multicenter trials, especially when establishing predictive markers for disease and treatment outcome in peripheral blood.

Blood Cells↗

PubMed2005

True and false discovery in DNA microarray experiments: transcriptome changes in the hippocampus of presenilin 1 mutant mice.

In transcriptome profiling experiments using DNA microarrays, it is critical to maximize putatively true data discovery while keeping the false discovery rate at acceptable levels. Using previously published and verified transcriptome datasets of mice with genetically altered PS1 physiology, we present a simple, robust, and system-specific assessment of type I and type II errors in two independent microarray experimental series. We provide evidence to suggest that for maximizing true discovery and minimizing false discovery, statistical criteria alone are inferior to statistical significance plus magnitude of change criteria. Furthermore, we found that, regardless of the exact criteria used for determining differential expression, different data extraction protocols give rise to different discovery and false discovery rates. In addition, a large proportion of expression differences were both dataset and analytical approach dependent. The data assessment methods presented and discussed in this manuscript can be easily carried out on any microarray dataset using basic spreadsheet functions as the only tool needed. Finally, we provide an in-depth analysis of the hippocampal transcriptome of DeltaE9 hPS1 transgenic mice and mice with a conditional ablation of the PS1 gene.

Animals↗

PubMed2005

Group A Streptococcus transcriptome dynamics during growth in human blood reveals bacterial adaptive and survival strategies.

The molecular basis for bacterial responses to host signals during natural infections is poorly understood. The gram-positive bacterial pathogen group A Streptococcus (GAS) causes human mucosal, skin, and life-threatening systemic infections. During the transition from a throat or skin infection to an invasive infection, GAS must adapt to changing environments and host factors. To better understand how GAS adapts, we used transcript profiling and functional analysis to investigate the transcriptome of a wild-type serotype M1 GAS strain in human blood. Global changes in GAS gene expression occur rapidly in response to human blood exposure. Increased transcription was observed for many genes that likely enhance bacterial survival, including those encoding superantigens and host-evasion proteins regulated by a multiple gene activator called Mga. GAS also coordinately expressed genes involved in proteolysis, transport, and catabolism of oligopeptides to obtain amino acids in this protein-rich host environment. Comparison of the transcriptome of the wild-type strain to that of an isogenic deletion mutant (DeltacovR) mutated in the two-component regulatory system designated CovR-CovS reinforced the hypothesis that CovR-CovS has an important role linking key biosynthetic, catabolic, and virulence functions during transcriptome restructuring. Taken together, the data provide crucial insights into strategies used by pathogenic bacteria for thwarting host defenses and surviving in human blood.

DNA, Complementary↗

PubMed2001

Discovering altered genomic expression patterns in heart: transcriptome determination by serial analysis of gene expression.

The development of cardiovascular diseases such as heart failure involve functional changes that are beneficial short-term, but may be fatal long-term. Current therapeutic approaches are tailored to limit progression of a disease and to maintain quality of life. At a molecular level, these disease processes involve quantitative and qualitative changes in gene expression. Although some changes in mRNA abundance may not have direct protein correlates, analysis of all the mRNAs present in a cell population (the cells transcriptome) has become a focal point of genomic research. The aim is to provide information about the dynamics of total genome expression in response to environmental changes and point to candidate genes responsible for the cascade of events that result in a disease state. One way of performing these analyses utilizes the technique of Serial Analysis of Gene Expression (SAGE). This method evaluates thousands of expressed transcripts both quantitatively and qualitatively in a single assay. In the first of two reviews on transcriptome analysis, we describe the current state of genomic research for determination of the transcriptome by Serial Analysis of Gene Expression, present the first limited SAGE analysis of rodent heart gene expression, and discuss how results generated with this approach can be applied to the study and treatment of cardiovascular diseases.

Cardiovascular Diseases↗