Multiplex analysis of sphingolipids using amine-reactive tags (iTRAQ)

Ceramides play a crucial role in divergent signaling events, including differentiation, senescence, proliferation, and apoptosis. Ceramides are a minor lipid component in terms of content; thus, highly sensitive detection is required for accurate quantification. The recently developed isobaric tags for relative and absolute quantitation (iTRAQ) method enables a precise comparison of both protein and aminophospholipids. However, iTRAQ tagging had not been applied to the determination of sphingolipids. Here we report a method for the simultaneous measurement of multiple ceramide and monohexosylceramide samples using iTRAQ tags. Samples were hydrolyzed with sphingolipid ceramide N-deacylase (SCDase) to expose the free amino group of the sphingolipids, to which the N-hydroxysuccinimide group of iTRAQ reagent was conjugated. The reaction was performed in the presence of a cleavable detergent, 3-[3-(1,1-bisalkyloxyethyl)pyridine-1-yl]propane-1-sulfonate (PPS) to both improve the hydrolysis and ensure the accuracy of the mass spectrometry analysis performed after iTRAQ labeling. This method was successfully applied to the profiling of ceramides and monohexosylceramides in sphingomyelinase-treated Madin Darby canine kidney (MDCK) cells and apoptotic Jurkat cells.     

Analysis of allelic differential expression in the human genome using allele-specific serial analysis of gene expression tags

Recent reports have demonstrated that a significant proportion of human genes display allelic differential expression (ADE). ADE is associated with phenotypic variability and may contribute to complex genetic diseases. Here, we present a computational analysis of ADE using allele-specific serial analysis of gene expression (SAGE) tags representing 1295 human genes. We identified 472 genes for which unequal representation (>3-fold) of allele-specific SAGE tags was observed in at least one SAGE library, suggesting the occurrence of ADE. For 235 out of these 472 genes, the difference in the expression level between both allele-specific SAGE tags was statistically significant (p < 0.05). Eleven candidate genes were then subjected to experimental validation and ADE was confirmed for 8 out of these 11 genes. Our results suggest that at least 25% of the human genes display ADE and that allele-specific SAGE tags can be efficiently used for the identification of such genes.     

Approaches to the analysis of gene expression using mRNA: a technical overview

Messenger RNA is the blueprint for all proteins expressed within living systems. Therefore, the study of mRNA expression within normal and diseased tissues is central to our understanding of biological systems. However, blueprints, in themselves, perform no function unless they are used to produce the material for which they code. Spurious results may frequently result from poorly designed or inappropriate studies. This review seeks to highlight both the pitfalls and the promise of various approaches to the analysis of mRNA in different systems and to place these studies in the wider context of research approaches aimed at understanding the function of living systems. The various techniques for the analysis of mRNA are discussed, with particular reference to their potential uses and problems and relevant examples are cited from the literature. It is hoped that this overview of the uses of analytical approaches will allow both the novice researcher and the more experienced scientist to better structure research approaches.     

Automation of gene assignments to metabolic pathways using high-throughput expression data

Background  

Accurate assignment of genes to pathways is essential in order to understand the functional role of genes and to map the existing pathways in a given genome. Existing algorithms predict pathways by extrapolating experimental data in one organism to other organisms for which this data is not available. However, current systems classify all genes that belong to a specific EC family to all the pathways that contain the corresponding enzymatic reaction, and thus introduce ambiguity.     

Screening for ligands using a generic and high-throughput light-scattering-based assay

Rapid identification of small molecules that interact with protein targets using a generic screening method greatly facilitates the development of therapeutic agents. The authors describe a novel method for performing homogeneous biophysical assays in a high-throughput format. The use of light scattering as a method to evaluate protein stability during thermal denaturation in a 384-well format yields a robust assay with a low frequency of false positives. This novel method leads to the identification of interacting small molecules without the addition of extraneous fluorescent probes. The analysis and interpretation of data is rapid, with sensitivity for protein stability comparable to differential scanning calorimetry. The authors propose potential uses in drug discovery, structural genomics, and functional genomics as a method to evaluate small-molecule interactions, identify natural cofactors that stabilize target proteins, and identify natural substrates and products for previously uncharacterized protein targets.     

Serial analysis of gene expression: rapid RT-PCR analysis of unknown SAGE tags.

In a pilot study on SAGE on Reed-Sternberg cells we have sequenced 1055 tags representing 701 genes. Screening of the GenBank database resulted in the identification of a corresponding gene or EST for 490 of them. For 211 of the tags no homology could be detected. A major problem of the serial analysis of gene expression (SAGE) approach is how to further analyse the unknown tags. We have developed an RT-PCR-based method, rapid analysis of unknown SAGE tags (RAST-PCR), to analyse the expression of the corresponding genes. This approach can be used as a screening method to investigate whether or not the gene is differentially expressed between several cell types of interest.     

Generation of 919 expressed sequence tags from immature flower buds and gene expression analysis using expressed sequence tags in the model plant Lotus japonicus

Lotus japonicus has received increased attention as a potential model legume plant. In order to study gene expression in reproductive organs and to identify genes that play a crucial function in sexual reproduction, we constructed a cDNA library from immature flower buds containing anthers at the stage of developing tapetum cells in L. japonicus, and characterized 919 expressed sequence tags (ESTs) randomly selected from a cDNA library of the immature flower buds. The 919 ESTs analyzed were clustered into 821 non-redundant EST groups. As a result of a database search, 436 groups (53%) out of the 821 groups showed sequence similarity to genes registered in the public database. Out of these 436 groups, 109 groups showed similarity to genes encoding hypothetical proteins whose function had not yet been estimated. Three hundred eighty five groups (47%) showed no significant homology to known sequences and were classified as novel sequences. A comparison of 821 non-redundant EST sequences and EST sequences derived from the whole plant L. japonicus revealed that 474 EST sequences derived from immature flower buds were not found in the EST sequences of the whole plant. In order to confirm the expression pattern of potential reproductive-organ specific EST clones, nine clones, which were not matched to ESTs derived from the whole plant, were selected, and RT-PCR analysis was performed on these clones. As a result of RT-PCR, we found two novel anther specific clones. One clone was homologous to a gene encoding human cleft lip and palate associated transmembrane protein (CLPTM1) like protein, and the other clone did not show a significant similarity to any genes deposited in the public database. These results indicate that ESTs analyzed here represent a valuable resource for finding reproductive-organ specific genes in Lotus japonicus.     

Identifying glucagon-like peptide-1 mimetics using a novel functional reporter gene high-throughput screening assay

Glucagon-like peptide-1 (GLP-1) stimulates insulin and inhibits glucagon secretion and therefore could potentially be used to treat diabetes type II. However, its therapeutic use is limited by its short half-life in vivo, due mainly to enzymatic degradation by dipeptidyl peptidase IV (DPP-IV). Developing GLP-1 analogs with greater bioactivity is therefore an important step toward using them therapeutically. Accordingly, we aimed to identify GLP-1 mimetic peptides by creating a high-throughput screening (HTS) assay of a phage displayed (PhD) peptide library. This assay was functionally based using the GLP-1 receptor (GLP-1R) gene. Rat GLP-1R cDNA was transfected into CHO/enhanced green fluorescent protein (EGFP) cells by lipofection. The resulting stable, recombinant cell line functionally expressed the GLP-1R and a cAMP-responsive EGFP reporter gene, to monitor receptor activation, and was used to screen a PhD dodecapeptide library. After four rounds of selection, 10 positive clones were selected based on functional evaluation and sequenced. Three sequences were obtained, corresponding to three different domains of GLP-1 (Group 1: 22-34; Group 2: 18-29; and Group 3: 6-17). The Group 3 peptide had the highest bioactivity, was synthesized, and designated KS-12. Importantly, KS-12 activated GLP-1R in vitro and reduced blood glucose levels in a dose-dependent manner when administered to Chinese Kunming mice. Although KS-12 was not as effective as GLP-1, it was significantly resistant to DPP-IV both in vitro and in vivo. Thus, this study provides a novel way to screen DPP-IV resistant agonist peptides of GLP-1 from a PhD peptide library using the functional reporter gene HTS assay.     

Data analysis issues for allele-specific expression using Illumina's GoldenGate assay

Background  

High-throughput measurement of allele-specific expression (ASE) is a relatively new and exciting application area for array-based technologies. In this paper, we explore several data sets which make use of Illumina's GoldenGate BeadArray technology to measure ASE. This platform exploits coding SNPs to obtain relative expression measurements for alleles at approximately 1500 positions in the genome.     

Express primer tool for high-throughput gene cloning and expression

High-throughput approaches for gene cloning and expression require the development of new nonstandard tools for molecular biologists and biochemists. We introduce a Web-based tool to design primers specifically for the generation of expression clones for both laboratory-scale and high-throughput projects. The application is designed not only to allow the user complete flexibility to specify primer design parameters but also to minimize the amount of manual intervention needed to generate a large number of primers for the simultaneous amplification of multiple target genes.     

The use of accurate mass tags for high-throughput microbial proteomics

We describe and review progress towards a global strategy that aims to extend the sensitivity, dynamic range, comprehensiveness, and throughput of proteomic measurements for microbial systems based upon the use of polypeptide accurate mass tags (AMTs) produced by global protein enzymatic digestions. The two-stage strategy exploits high accuracy mass measurements using Fourier transform ion cyclotron resonance mass spectrometry (FTICR) to validate polypeptide AMTs for a specific organism, from potential mass tags tentatively identified using tandem mass spectrometry (MS/MS), providing the basis for subsequent measurements without the need for routine MS/MS. A high-resolution capillary liquid chromatography separation combined with high sensitivity, and high-resolution accurate FTICR measurements is shown to be capable of characterizing polypeptide mixtures of more than 10(5) components, sufficient for broad protein identification using AMTs. Advantages of the approach include the high confidence of protein identification, its broad proteome coverage, and the capability for stable-isotope labeling methods for precise relative protein abundance measurements. The strategy has been initially evaluated using the microorganisms Saccharomyces cerevisiae and Deinococcus radiodurans. Additional developments, including the use of multiplexed-MS/MS capabilities and methods for dynamic range expansion of proteome measurements that promise to further extend the quality of proteomics measurements, are also described.     

Integrating high-throughput microRNA and mRNA expression data to identify risk mRNA signature for pancreatic cancer prognosis

Pancreatic cancer is a malignancy of the digestive system characterized by poor prognosis. A number of prognostic messenger RNA (mRNA) signatures have been identified by using the high-throughput expression profiles. MicroRNAs (miRNA) play a critical role in regulating multiple cellular functions. However, no such integrated analysis of miRNAs and mRNAs for studying the prognostic mechanisms of pancreatic cancer has been reported. In this study, we first identified prognostic mRNAs and miRNAs based on The Cancer Genome Atlas datasets, and then performed an enrichment analysis to explore the underlying biological mechanisms involved in pancreatic cancer prognosis at the mRNA level. Furthermore, we performed an integrated analysis of mRNAs and miRNAs to identify prognostic subpathways, which were closely associated with pancreatic cancer genes and tumor hallmarks and involved in hypoxia, oxidative phosphyorylation and xenobiotic metabolisms. Meanwhile, we performed a random walk algorithm based on global network, prognostic mRNAs and miRNAs, and identified top risk mRNAs as the prognostic signature. Finally, an independent testing set was used to confirm the predictive power of the top mRNA signature, and most of these genes involved were known oncogenes. In conclusion, we performed a series of integrated analyses by comprehensively exploring pancreatic cancer prognosis and systematically optimized the prognostic signature for clinical use.