Aminoacetone, a putative endogenous source of methylglyoxal, causes oxidative stress and death to insulin-producing RINm5f cells

Aminoacetone (AA), triose phosphates, and acetone are putative endogenous sources of potentially cytotoxic and genotoxic methylglyoxal (MG), which has been reported to be augmented in the plasma of diabetic patients. In these patients, accumulation of MG derived from aminoacetone, a threonine and glycine catabolite, is inferred from the observed concomitant endothelial overexpression of circulating semicarbazide-sensitive amine oxidases. These copper-dependent enzymes catalyze the oxidation of primary amines, such as AA and methylamine, by molecular oxygen, to the corresponding aldehydes, NH4(+) ion and H2O2. We recently reported that AA aerobic oxidation to MG also takes place immediately upon addition of catalytic amounts of copper and iron ions. Taking into account that (i) MG and H2O2 are reportedly cytotoxic to insulin-producing cell lineages such as RINm5f and that (ii) the metal-catalyzed oxidation of AA is propagated by O2(*-) radical anion, we decided to investigate the possible pro-oxidant action of AA on these cells taken here as a reliable model system for pancreatic beta-cells. Indeed, we show that AA (0.10-5.0 mM) administration to RINm5f cultures induces cell death. Ferrous (50-300 microM) and Fe(3+) ion (100 microM) addition to the cell cultures had no effect, whereas Cu(2+) (5.0-100 microM) significantly increased cell death. Supplementation of the AA- and Cu(2+)-containing culture medium with antioxidants, such as catalase (5.0 microM), superoxide dismutase (SOD, 50 U/mL), and N-acetylcysteine (NAC, 5.0 mM) led to partial protection. mRNA expression of MnSOD, CuZnSOD, glutathione peroxidase, and glutathione reductase, but not of catalase, is higher in cells treated with AA (0.50-1.0 mM) plus Cu(2+) ions (10-50 microM) relative to control cultures. This may imply higher activity of antioxidant enzymes in RINm5f AA-treated cells. In addition, we have found that AA (0.50-1.0 mM) plus Cu(2+) (100 microM) (i) increase RINm5f cytosolic calcium; (ii) promote DNA fragmentation; and (iii) increase the pro-apoptotic (Bax)/antiapoptotic (Bcl-2) ratio at the level of mRNA expression. In conclusion, although both normal and pathological concentrations of AA are probably much lower than those used here, it is tempting to propose that excess AA in diabetic patients may drive oxidative damage and eventually the death of pancreatic beta-cells.

Identification of COL6A1 as a differentially expressed gene in human astrocytomas

Diffuse infiltrating gliomas are the most common tumors of the central nervous system. Gliomas are classified by the WHO according to their histopathological and clinical characteristics into four classes: grade I (pilocytic astrocytoma), grade II (diffuse astrocytoma), grade III (anaplastic astrocytoma), and grade IV (glioblastoma multiforme). Several genes have already been correlated with astrocytomas, but many others are yet to be uncovered. By analyzing the public SAGE data from 21 patients, comprising low malignant grade astrocytomas and glioblastomas, we found COL6A1 to be differentially expressed, confirming this finding by real time RT-PCR in 66 surgical samples. To the best of our knowledge, COL6A1 has never been described in gliomas. The expression of this gene has significantly different means when normal glia is compared with low-grade astrocytomas (grades I and II) and high-grade astrocytomas (grades III and IV), with a tendency to be greater in higher grade samples, thus rendering it a powerful tumor marker.

GEDI: a user-friendly toolbox for analysis of large-scale gene expression data

BACKGROUND

Several mathematical and statistical methods have been proposed in the last few years to analyze microarray data. Most of those methods involve complicated formulas, and software implementations that require advanced computer programming skills. Researchers from other areas may experience difficulties when they attempting to use those methods in their research. Here we present an user-friendly toolbox which allows large-scale gene expression analysis to be carried out by biomedical researchers with limited programming skills.

RESULTS

Here, we introduce an user-friendly toolbox called GEDI (Gene Expression Data Interpreter), an extensible, open-source, and freely-available tool that we believe will be useful to a wide range of laboratories, and to researchers with no background in Mathematics and Computer Science, allowing them to analyze their own data by applying both classical and advanced approaches developed and recently published by Fujita et al.

CONCLUSION

GEDI is an integrated user-friendly viewer that combines the state of the art SVR, DVAR and SVAR algorithms, previously developed by us. It facilitates the application of SVR, DVAR and SVAR, further than the mathematical formulas present in the corresponding publications, and allows one to better understand the results by means of available visualizations. Both running the statistical methods and visualizing the results are carried out within the graphical user interface, rendering these algorithms accessible to the broad community of researchers in Molecular Biology.

Modeling gene expression regulatory networks with the sparse vector autoregressive model

BACKGROUND

To understand the molecular mechanisms underlying important biological processes, a detailed description of the gene products networks involved is required. In order to define and understand such molecular networks, some statistical methods are proposed in the literature to estimate gene regulatory networks from time-series microarray data. However, several problems still need to be overcome. Firstly, information flow need to be inferred, in addition to the correlation between genes. Secondly, we usually try to identify large networks from a large number of genes (parameters) originating from a smaller number of microarray experiments (samples). Due to this situation, which is rather frequent in Bioinformatics, it is difficult to perform statistical tests using methods that model large gene-gene networks. In addition, most of the models are based on dimension reduction using clustering techniques, therefore, the resulting network is not a gene-gene network but a module-module network. Here, we present the Sparse Vector Autoregressive model as a solution to these problems.

RESULTS

We have applied the Sparse Vector Autoregressive model to estimate gene regulatory networks based on gene expression profiles obtained from time-series microarray experiments. Through extensive simulations, by applying the SVAR method to artificial regulatory networks, we show that SVAR can infer true positive edges even under conditions in which the number of samples is smaller than the number of genes. Moreover, it is possible to control for false positives, a significant advantage when compared to other methods described in the literature, which are based on ranks or score functions. By applying SVAR to actual HeLa cell cycle gene expression data, we were able to identify well known transcription factor targets.

CONCLUSION

The proposed SVAR method is able to model gene regulatory networks in frequent situations in which the number of samples is lower than the number of genes, making it possible to naturally infer partial Granger causalities without any a priori information. In addition, we present a statistical test to control the false discovery rate, which was not previously possible using other gene regulatory network models.

Time-varying modeling of gene expression regulatory networks using the wavelet dynamic vector autoregressive method

MOTIVATION

A variety of biological cellular processes are achieved through a variety of extracellular regulators, signal transduction, protein-protein interactions and differential gene expression. Understanding of the mechanisms underlying these processes requires detailed molecular description of the protein and gene networks involved. To better understand these molecular networks, we propose a statistical method to estimate time-varying gene regulatory networks from time series microarray data. One well known problem when inferring connectivity in gene regulatory networks is the fact that the relationships found constitute correlations that do not allow inferring causation, for which, a priori biological knowledge is required. Moreover, it is also necessary to know the time period at which this causation occurs. Here, we present the Dynamic Vector Autoregressive model as a solution to these problems.

RESULTS

We have applied the Dynamic Vector Autoregressive model to estimate time-varying gene regulatory networks based on gene expression profiles obtained from microarray experiments. The network is determined entirely based on gene expression profiles data, without any prior biological knowledge. Through construction of three gene regulatory networks (of p53, NF-kappaB and c-myc) for HeLa cells, we were able to predict the connectivity, Granger-causality and dynamics of the information flow in these networks.

SUPPLEMENTARY INFORMATION

Additional figures may be found at http://mariwork.iq.usp.br/dvar/.

Differential proteomic analysis of the anti-proliferative effect of glucocorticoid hormones in ST1 rat glioma cells

Glucocorticoid hormones (GCs) exert a potent anti-proliferative activity on several cell types. The classic molecular mechanism of GCs involves modulation of the activity of the glucocorticoids receptor, a transcriptional regulator. However, the anti-proliferative effect of GCs may also involve modulation of processes such as translation, subcellular localization and post-translational modifications, which are not reflected at the mRNA level. To investigate these potential effects of GCs, we employed the proteomic approach (two-dimensional electrophoresis and mass spectrometry) and the ST1 cells, obtained from the C6 rat glioma cell line, as a model. GC treatment leads ST1 cells to a complete transformed-to-normal phenotypic reversion and loss of their tumorigenic potential. By comparing sets of 2D nuclear protein profiles of ST1 cells treated (or not) with hydrocortisone (Hy), 13 polypeptides displaying >or=two-fold difference in abundance upon Hy treatment were found. Five of these polypeptides were identified by peptide mass fingerprinting, including Annexin 2 (ANX2), hnRNP A3 and Ubiquitin. Evidence obtained by Western blot analysis indicates that ANX2 is present in the nucleus and has its subcellular localization modulated by GC-treatment of ST1 cells. Our findings indicate complementary mechanisms contributing to the regulation of gene expression associated with ST1 cells' response to GCs.

Androgen responsive intronic non-coding RNAs

BACKGROUND

Transcription of large numbers of non-coding RNAs originating from intronic regions of human genes has been recently reported, but mechanisms governing their biosynthesis and biological functions are largely unknown. In this work, we evaluated the existence of a common mechanism of transcription regulation shared by protein-coding mRNAs and intronic RNAs by measuring the effect of androgen on the transcriptional profile of a prostate cancer cell line.

RESULTS

Using a custom-built cDNA microarray enriched in intronic transcribed sequences, we found 39 intronic non-coding RNAs for which levels were significantly regulated by androgen exposure. Orientation-specific reverse transcription-PCR indicated that 10 of the 13 were transcribed in the antisense direction. These transcripts are long (0.5-5 kb), unspliced and apparently do not code for proteins. Interestingly, we found that the relative levels of androgen-regulated intronic transcripts could be correlated with the levels of the corresponding protein-coding gene (asGAS6 and asDNAJC3) or with the alternative usage of exons (asKDELR2 and asITGA6) in the corresponding protein-coding transcripts. Binding of the androgen receptor to a putative regulatory region upstream from asMYO5A, an androgen-regulated antisense intronic transcript, was confirmed by chromatin immunoprecipitation.

CONCLUSION

Altogether, these results indicate that at least a fraction of naturally transcribed intronic non-coding RNAs may be regulated by common physiological signals such as hormones, and further corroborate the notion that the intronic complement of the transcriptome play functional roles in the human gene-expression program.

Prolactin-induced changes in protein expression in human pancreatic islets

Ex vivo islet cell culture prior to transplantation appears as an attractive alternative for treatment of type 1 diabetes. Previous results from our laboratory have demonstrated beneficial effects of human prolactin (rhPRL) treatment on human islet primary cultures. In order to probe into the molecular events involved in the intracellular action of rhPRL in these cells, we set out to identify proteins with altered expression levels upon rhPRL cell treatment, using two-dimensional (2D) gel electrophoresis and mass spectrometry (MS). An average of 300 different protein spots were detected, 14 of which were modified upon rhPRL treatment (p<0.01), of which 12 were successfully identified using MS and grouped according to their biological functions. In conclusion, our study provides, for the first time, information about proteins that could be critically involved in PRL's action on human pancreatic islets, and facilitate identification of new and specific targets involved in islet cell function and proliferation.

Beneficial effects of prolactin and laminin on human pancreatic islet-cell cultures

The problem of pancreas donor shortage could be addressed through in vitro islet-cell proliferation prior to transplantation into diabetic patients. Therefore, we set out to evaluate the effects of prolactin (rhPRL) and laminin on primary cultures of human pancreatic islets. Our results showed that rhPRL induced an increase in islet-cell number and in cumulative insulin secretion (p<0.01). However, glucose-induced insulin secretion was enhanced only in the presence of both laminin and rhPRL. In addition, we describe, for the first time in human islets, the PRL-induced activation of JAK2, and signal transducer and activator of transcription (STAT) 1, 3 and 5. Our results demonstrate a significant beneficial effect of rhPRL and laminin on human islets and support widely held notion that the closer physiological stimuli and environment of beta cells are mimicked, the better are the results in cell proliferation and secretory function, both essential for successful islet transplantation.

EJ-ras oncogene transfection of endothelial cells upregulates the expression of syndecan-4 and downregulates heparan sulfate sulfotransferases and epimerase

The EC rabbit endothelial cell line was transfected with the EJ-ras oncogene (EJ-ras EC). EJ-ras EC cells display over expression of the Ras oncogene, morphological changes and deregulation of the cell cycle, becoming more densely populated and serum-independent. In addition, EJ-ras-transfectant cells show higher levels of the syndecan-4 mRNA. In addition to the increase in the core protein, a parallel increase in the glycosylation of the syndecan-4 protein, a proteoglycan that bears heparan sulfate chains, also occurs. This increase is observed both for the heparan sulfate proteoglycan synthesized by the cells and for that secreted to the culture medium. This enhancement in heparan sulfate synthesis was observed through metabolic labeling of the cells, immunoprecipitation of syndecan-4 and heparitinases treatment. Furthermore, the EJ-ras-transfectant cells do not exhibit decreased synthesis of heparan sulfate during the G(1)-S phase transition, as observed for the parental cell line. Also, heparan sulfate synthesis is not stimulated by PMA as displayed by parental endothelial cells. Significant structural changes of heparan sulfate, such as decreased O-sulfation, were observed in the EJ-ras-transfected cells. Decreases in the mRNA levels of some enzymes (glucuronosyl C-5 epimerase, iduronosyl-2-O-sulfotransferase, glucosaminyl-6-O-sulfotransferase-1 and N-deacetylase/N-sulfotransferase-1), involved in the biosynthetic pathway of heparan sulfate, were also observed. The results suggest that overexpression of the EJ-ras oncogene alters the cell cycle, through signal transduction cascades, upregulates the expression of syndecan-4, and downregulates enzymes involved in the heparan sulfate biosynthesis related to chain modification, leading to the structural changes of the heparan sulfate syndecan-4 proteoglycan in endothelial cells.

Progestin-induced caveolin-1 expression mediates breast cancer cell proliferation

Progestin regulation of gene expression was assessed in the progestin-dependent murine tumor line C4HD which requires MPA, a synthetic progestin, for in vivo growth and expresses high levels of progesterone receptor (PR). By using suppressive subtractive hybridization, caveolin-1 was identified as a gene whose expression was increased with in vivo MPA treatment. By Northern and Western blot analysis, we further confirmed that caveolin-1 mRNA and protein expression increased in MPA-treated tumors as compared with untreated tumors. When primary cultures of C4HD cells were treated in vitro with MPA, caveolin-1 levels also increased, effect that was abolished by pre-treatment with progestin antagonist RU486. In addition, MPA promoted strong caveolin-1 promoter transcriptional activation both in mouse and human breast cancer cells. We also showed that MPA regulation of caveolin-1 expression involved in activation of two signaling pathways: MAPK and PI-3K. Short-term MPA treatment of C4HD cells led to tyrosine phosphorylation of caveolin-1 protein, where Src was the kinase involved. Additionally, we showed that MPA-induced association of caveolin-1 and PR, which was detected by coimmunoprecipitation and by confocal microscopy. Finally, we proved that MPA-induced proliferation of C4HD cells was inhibited by suppression of caveolin-1 expression with antisense oligodeoxynucleotides to caveolin-1 mRNA. Furthermore, we observed that inhibition of caveolin-1 expression abrogated PR capacity to induced luciferase activity from a progesterone response element-driven reporter plasmid. Comprehensively, our results demonstrated for the first time that caveolin-1 expression is upregulated by progestin in breast cancer. We also demonstrated that caveolin-1 is a downstream effector of MPA that is partially responsible for the stimulation of growth of breast cancer cells.

Gene expression profiles underlying alternative caste phenotypes in a highly eusocial bee, Melipona quadrifasciata

To evaluate caste-biased gene expression in Melipona quadrifasciata, a stingless bee, we generated 1278 ESTs using Representational Difference Analysis. Most annotated sequences were similar to honey bee genes of unknown function. Only few queen-biased sequences had their putative function assigned by sequence comparison, contrasting with the worker-biased ESTs. The expression of six annotated genes connected to caste specificity was validated by real time PCR. Interestingly, queens that were developmentally induced by treatment with a juvenile hormone analogue displayed an expression profile clearly different from natural queens for this set of genes. In summary, this study represents an important first step in applying a comparative genomic approach to queen/worker polyphenism in the bee.

A functional SNP in the promoter region of TCOF1 is associated with reduced gene expression and YY1 DNA-protein interaction

Treacher Collins syndrome (TCS) is an autosomal dominant craniofacial malformation caused by null mutations in the TCOF1 gene. High inter and intra familial clinical variability, ranging from mild malar hypoplasia to perinatal death due to airway collapse is observed, but, to date, no genotype-phenotype correlation has been reported. Considering haploinsufficiency as the molecular mechanism underlying the disease, we have hypothesized that mutations in the promoter region of the gene, which has never been previously characterized, in trans with a pathogenic mutation, could modulate the phenotype. Therefore, the aims of the present study were to determine the TCOF1 gene's core promoter and to identify mutations in this region that could contribute to the phenotypic variation observed in this syndrome. We have delimitated the minimal promoter to a region of less than 150 bp, with 63% of identity among 5 different species. We screened 1.2 kbp of the TCOF1 5' flanking sequence in the DNA obtained from 21 patients and 51 controls and identified four new single nucleotide polymorphisms (SNPs), one of which (-346C>T), was proved to be functional, as it decreased the promoter activity by 38%. Electrophoretic mobility shift assay (EMSA) analysis demonstrated that the -346T allele impairs DNA-binding to the YY1 transcription factor. This promoter variant represents a candidate allele to explain the clinical variability in patients bearing TCS.

The GATO gene annotation tool for research laboratories

Large-scale genome projects have generated a rapidly increasing number of DNA sequences. Therefore, development of computational methods to rapidly analyze these sequences is essential for progress in genomic research. Here we present an automatic annotation system for preliminary analysis of DNA sequences. The gene annotation tool (GATO) is a Bioinformatics pipeline designed to facilitate routine functional annotation and easy access to annotated genes. It was designed in view of the frequent need of genomic researchers to access data pertaining to a common set of genes. In the GATO system, annotation is generated by querying some of the Web-accessible resources and the information is stored in a local database, which keeps a record of all previous annotation results. GATO may be accessed from everywhere through the internet or may be run locally if a large number of sequences are going to be annotated. It is implemented in PHP and Perl and may be run on any suitable Web server. Usually, installation and application of annotation systems require experience and are time consuming, but GATO is simple and practical, allowing anyone with basic skills in informatics to access it without any special training. GATO can be downloaded at [http://mariwork.iq.usp.br/gato/]. Minimum computer free space required is 2 MB.

Characterization of human collagen XVIII promoter 2: interaction of Sp1, Sp3 and YY1 with the regulatory region and a SNP that increases transcription in hepatocytes

Different levels of Collagen XVIII expression have been associated with several pathological processes such as cancer, liver fibrosis, diabetic retinopathy and Alzheimer's disease. Understanding the transcriptional regulation of Collagen XVIII might elucidate some pathways related to the progression of these diseases. The promoter 2 of COL18A1 gene is poorly understood and is responsible for the transcription of this gene in several adult tissues such as liver, eyes and brain. This study focused upon characterization of cis-regulatory elements interacting with human COL18A1 promoter 2 and identification of SNPs in this region in different ethnic groups. Our results show that there are five conserved regions (I to V) between human and mouse promoter 2 and that the human COL18A1 core promoter is located between nucleotides -186 and -21. Sp1 and Sp3 bind to conserved regions I and V, while Sp3 and YY1 interact with region II. We have verified that the SNP at position -700 (T>G) is embedded in two common haplotypes, which have different frequencies between European and African descendents. The allele -700G increases transcription and binding for a still unknown transcription factor. SNP -700 affects Sp3 and YY1 interaction with this region, even though it is not part of these transcription factors' predicted binding sites. Therefore, our results show for the first time that Sp3 and YY1 interact with human COL18A1 promoter 2, and that nucleotide -700 is part of a binding motif for a still unknown TF that is involved in the expression of this gene in hepatocytes. In addition, we also confirm the involvement of Sp1 in the regulation of this gene.

Cloning and characterization of the human and rabbit NUDEL-oligopeptidase promoters and their negative regulation

NUDEL-oligopeptidase is a cytosolic cysteine peptidase, active towards oligopeptides and involved in the conversion and inactivation of a number of bioactive peptides. This protein interacts with neuronal proteins and is essential for brain development and cortical organization during embryogenesis. In this study, 5'-flanking sequences of the human and rabbit NUDEL-oligopeptidase gene were cloned into the pGL3 reporter gene vector and the promoter activity of the full-length fragment and deletions series was measured in transient transfection assays using two different cell lines, namely, C6 rat glioma and NH15 human neuroblastoma. Overall, a very similar pattern of promoter activity was obtained for both rabbit and human NUDEL-oligopeptidase promoter sequences, and their respective serial deletion constructs upon transient transfection into these cell lines. The only exception was for the longest rabbit upstream sequence that displayed about 1.8-fold higher luciferase expression upon transfection into NH15 neuronal cells than that observed upon transfection into C6 glioma cells. On the other hand, no significant difference was observed for the human longest sequence. These results are in good agreement with the expression pattern of NUDEL-oligopeptidase in human and rabbit tissues.

Bone morphogenetic proteins: from structure to clinical use

Bone morphogenetic proteins (BMPs) are multi-functional growth factors belonging to the transforming growth factor ss superfamily. Family members are expressed during limb development, endochondral ossification, early fracture, and cartilage repair. The activity of BMPs was first identified in the 1960s but the proteins responsible for bone induction were unknown until the purification and cloning of human BMPs in the 1980s. To date, about 15 BMP family members have been identified and characterized. The signal triggered by BMPs is transduced through serine/threonine kinase receptors, type I and II subtypes. Three type I receptors have been shown to bind BMP ligands, namely: type IA and IB BMP receptors and type IA activin receptors. BMPs seem to be involved in the regulation of cell proliferation, survival, differentiation and apoptosis, but their hallmark is their ability to induce bone, cartilage, ligament, and tendon formation at both heterotopic and orthotopic sites. This suggests that, in the future, they may play a major role in the treatment of bone diseases. Several animal studies have illustrated the potential of BMPs to enhance spinal fusion, repair critical-size defects, accelerate union, and heal articular cartilage lesions. Difficulties in producing and purifying BMPs from bone tissue have prompted the attempts made by several laboratories, including ours, to express these proteins in the recombinant form in heterologous systems. This review focuses on BMP structure, molecular mechanisms of action and significance and potential applications in medical, dental and veterinary practice for the treatment of cartilage and bone-related diseases.

Identification of novel differentially expressed genes in human astrocytomas by cDNA representational difference analysis

Diffuse infiltrating gliomas are the most common tumors of the central nervous system (CNS), naturally progressing from a lower-grade to a higher-grade malignancy. Several genetic alterations have been correlated with astrocytic tumors; however, a number of as yet unknown genes may also be involved. Therefore, we set out to search for genes that are differentially expressed in anaplastic astrocytoma and normal CNS tissue by applying a PCR-based subtractive hybridization approach, namely, representational difference analysis (RDA). The results of DNA sequencing of a sample (96 cDNA clones) from the subtracted library allowed the identification of 18 different genes, some of which were represented by several cDNA clones, coding for the Np95, LMO1, FCGBP, DSCAM, and taxilin proteins. Quantitative real-time PCR analysis for five of these genes was performed using samples of astrocytic tumors of different grades, confirming their higher expression when compared to non-tumoral CNS tissue. Identification of differentially expressed genes present in gliomas but not in normal CNS tissue is important not only to better understand the molecular basis of these cancers, but also to generate diagnostic DNA chips, which may be useful in future therapeutic intervention.

ADAM23 methylation and expression analysis in brain tumors

The ADAMs comprises a family of cell surface proteins with putative roles in cell-cell and/or cell-matrix interactions and in protease activities. In this work, we have examined the expression level and the methylation status of the 5' upstream region of the adhesion molecule ADAM23 in two brain tumor cell lines (A172 and T98G) as well as in three primary brain tumors (one grade II astrocytoma and two meningiomas) and 15 glioblastoma xenografts. Using bisulfite sequencing we verified that the percentage of methylated dinucleotides is higher in T98G when compared to A172 and that methylation significantly correlates with ADAM23 mRNA and protein expression. However, we were unable to detect methylation and down-regulation of the ADAM23 gene in brain tumors. Together, these results indicate that ADAM23 down-regulation by methylation in brain tumors is a rare event and it may help explain why brain tumor metastases are rarely found elsewhere in the body.

Identification and complete sequencing of novel human transcripts through the use of mouse orthologs and testis cDNA sequences

The correct identification of all human genes, and their derived transcripts, has not yet been achieved, and it remains one of the major aims of the worldwide genomics community. Computational programs suggest the existence of 30,000 to 40,000 human genes. However, definitive gene identification can only be achieved by experimental approaches. We used two distinct methodologies, one based on the alignment of mouse orthologous sequences to the human genome, and another based on the construction of a high-quality human testis cDNA library, in an attempt to identify new human transcripts within the human genome sequence. We generated 47 complete human transcript sequences, comprising 27 unannotated and 20 annotated sequences. Eight of these transcripts are variants of previously known genes. These transcripts were characterized according to size, number of exons, and chromosomal localization, and a search for protein domains was undertaken based on their putative open reading frames. In silico expression analysis suggests that some of these transcripts are expressed at low levels and in a restricted set of tissues.

Antisense intronic non-coding RNA levels correlate to the degree of tumor differentiation in prostate cancer

A large fraction of transcripts are expressed antisense to introns of known genes in the human genome. Here we show the construction and use of a cDNA microarray platform enriched in intronic transcripts to assess their biological relevance in pathological conditions. To validate the approach, prostate cancer was used as a model, and 27 patient tumor samples with Gleason scores ranging from 5 to 10 were analyzed. We find that a considerably higher fraction (6.6%, [23/346]) of intronic transcripts are significantly correlated (P< or =0.001) to the degree of prostate tumor differentiation (Gleason score) when compared to transcripts from unannotated genomic regions (1%, [6/539]) or from exons of known genes (2%, [27/1369]). Among the top twelve transcripts most correlated to tumor differentiation, six are antisense intronic messages as shown by orientation-specific RT-PCR or Northern blot analysis with strand-specific riboprobe. Orientation-specific real-time RT-PCR with six tumor samples, confirmed the correlation (P=0.024) between the low/high degrees of tumor differentiation and antisense intronic RASSF1 transcript levels. The need to use intron arrays to reveal the transcriptome profile of antisense intronic RNA in cancer has clearly emerged.

Amyloidogenicity and cytotoxicity of recombinant mature human islet amyloid polypeptide (rhIAPP)

Pancreatic amyloid plaques formed by the pancreatic islet amyloid polypeptide (IAPP) are present in more than 95% of type II diabetes mellitus patients, and their abundance correlates with the severity of the disease. IAPP is currently considered the most amyloidogenic peptide known, but the molecular bases of its aggregation are still incompletely understood. Detailed characterization of the mechanisms of amyloid formation requires large quantities of pure material. Thus, availability of recombinant IAPP in sufficient amounts for such studies constitutes an important step toward elucidation of the mechanisms of amyloidogenicity. Here, we report, for the first time, the successful expression, purification and characterization of the amyloidogenicity and cytotoxicity of recombinant human mature IAPP. This approach is likely to be useful for the production of other amyloidogenic peptides or proteins that are difficult to obtain by chemical synthesis.

A transcript finishing initiative for closing gaps in the human transcriptome

We report the results of a transcript finishing initiative, undertaken for the purpose of identifying and characterizing novel human transcripts, in which RT-PCR was used to bridge gaps between paired EST clusters, mapped against the genomic sequence. Each pair of EST clusters selected for experimental validation was designated a transcript finishing unit (TFU). A total of 489 TFUs were selected for validation, and an overall efficiency of 43.1% was achieved. We generated a total of 59,975 bp of transcribed sequences organized into 432 exons, contributing to the definition of the structure of 211 human transcripts. The structure of several transcripts reported here was confirmed during the course of this project, through the generation of their corresponding full-length cDNA sequences. Nevertheless, for 21% of the validated TFUs, a full-length cDNA sequence is not yet available in public databases, and the structure of 69.2% of these TFUs was not correctly predicted by computer programs. The TF strategy provides a significant contribution to the definition of the complete catalog of human genes and transcripts, because it appears to be particularly useful for identification of low abundance transcripts expressed in a restricted set of tissues as well as for the delineation of gene boundaries and alternatively spliced isoforms.