An increasing amount of expressed sequence tag (EST) and genomic data, predominantly for the cnidarians Acropora , Hydra and Nematostella , reveals that cnidarians have a high genomic complexity, despite being one of the morphologically simplest multicellular animals. Considering the diversity of cnidarians, we performed an EST project on the hydroid Hydractinia echinata , to contribute towards a broader coverage of this phylum. After random sequencing of almost 9000 clones, EST characterization revealed a broad diversity in gene content. Corroborating observations in other cnidarians, Hydractinia sequences exhibited a higher sequence similarity to vertebrates than to ecdysozoan invertebrates. A significant number of sequences were hitherto undescribed in metazoans, suggesting that these may be either cnidarian innovations or ancient genes lost in the bilaterian genomes analysed so far. However, we cannot rule out some degree of contamination from commensal bacteria. The identification of unique Hydractinia sequences emphasizes that the acquired genomic information generated so far is not large enough to be representative of the highly diverse cnidarian phylum. Finally, a database was created to store all the acquired information ( http://www.mchips.org/hydractinia_echinata.html ).
Plants respond to pathogen attack by deploying several defense reactions. Some rely on the activation of preformed components, whereas others depend on changes in transcriptional activity. Using cDNA arrays comprising 13,000 unique expressed sequence tags, changes in the transcriptome ofArabidopsis thaliana were monitored after attempted infection with the bacterial plant pathogen Pseudomonas syringae pv. tomato carrying the avirulence geneavrRpt2. Sampling at four time points during the first 24 h after infiltration revealed significant changes in the steady state transcript levels of ∼650 genes within 10 min and a massive shift in gene expression patterns by 7 h involving ∼2,000 genes representing many cellular processes. This shift from housekeeping to defense metabolism results from changes in regulatory and signaling circuits and from an increased demand for energy and biosynthetic capacity in plants fighting off a pathogenic attack. Concentrating our detailed analysis on the genes encoding enzymes in glycolysis, the Krebs cycle, the pentose phosphate pathway, the biosynthesis of aromatic amino acids, phenylpropanoids, and ethylene, we observed interesting differential regulation patterns. Furthermore, our data showed potentially important changes in areas of metabolism, such as the glyoxylate metabolism, hitherto not suspected to be components of plant defense.
Abstract Motivation: Cross-species meta-analyses of microarray data usually require prior affiliation of genes based on orthology information that often relies on sequence similarity. Results: We present an algorithm merging microarray datasets on the basis of co-expression alone, without any requirement for orthology information to affiliate genes. Combining existing methods such as co-inertia analysis, back-transformation, Hungarian matching and majority voting in an iterative non-greedy hill-climbing approach, it affiliates arrays and genes at the same time, maximizing the co-structure between the datasets. To introduce the method, we demonstrate its performance on two closely and two distantly related datasets of different experimental context and produced on different platforms. Each pair stems from two different species. The resulting cross-species dynamic Bayesian gene networks improve on the networks inferred from each dataset alone by yielding more significant network motifs, as well as more of the interactions already recorded in KEGG and other databases. Also, it is shown that our algorithm converges on the optimal number of nodes for network inference. Being readily extendable to more than two datasets, it provides the opportunity to infer extensive gene regulatory networks. Availability and Implementation: Source code (MATLAB and R) freely available for download at http://www.mchips.org/supplements/moghaddasi_source.tgz Contact: kurt@tum.de Supplementary information: Supplementary data are available at Bioinformatics online.
Trypanosome gene expression is regulated almost exclusively at the post-transcriptional level, with mRNA degradation playing a decisive role. When trypanosomes are transferred from the blood of a mammal to the midgut of a Tsetse fly, they transform to procyclic forms: gene expression is reprogrammed, changing the cell surface and switching the mode of energy metabolism. Within the blood, trypanosomes can pre-adapt for Tsetse transmission, becoming growth-arrested stumpy forms. We describe here the transitions in gene expression that occur during differentiation of in-vitro cultured bloodstream forms to procyclic forms.Some mRNAs showed changes within 30 min of cis-aconitate addition, whereas others responded 12-24 hours later. For the first 12 h after addition of cis-aconitate, cells accumulated at the G1 phase of the cell cycle, and showed decreases in mRNAs required for proliferation, mimicking the changes seen in stumpy forms: many mRNAs needed for ribosomal and flagellar biogenesis showed striking co-regulation. Other mRNAs encoding components of signal transduction pathways and potential regulators were specifically induced only during differentiation. Messenger RNAs encoding proteins required for individual metabolic pathways were often co-regulated.Trypanosome genes form post-transcriptional regulons in which mRNAs with functions in particular pathways, or encoding components of protein complexes, show almost identical patterns of regulation.
Isobaric tagging using reagents such as tandem mass tags (TMT) and isobaric tags for relative and absolute quantification (iTRAQ) have become popular tools for mass spectrometry based quantitative proteomics. Because the peptide quantification information is collected in tandem mass spectra, the accuracy and precision of this method largely depend on the resolution with which precursor ions can be selected for the fragmentation and the specificity of the generated reporter ion. The latter can constitute an issue if near isobaric ion signals are present in such spectra because they may distort quantification results. We propose a simple remedy for this problem by identifying reporter ions via the accurate mass differences within a single tandem mass spectrum instead of applying fixed mass error tolerances for all tandem mass spectra. Our results show that this leads to unambiguous reporter ion identification and complete removal of interfering signals. This mode of data processing is easily implemented in software and offers advantages for protein quantification based on few peptides.
Adenoviruses (Ads), especially HAdV-5, have been genetically equipped with tumor-restricted replication potential to enable applications in oncolytic cancer therapy. Such oncolytic adenoviruses have been well tolerated in cancer patients, but their anti-tumor efficacy needs to be enhanced. In this regard, it should be considered that cancer cells, dependent on their tissue of origin, can differ substantially from the normal host cells to which Ads are adapted by complex virus-host interactions. Consequently, viral replication efficiency, a key determinant of oncolytic activity, might be suboptimal in cancer cells. Therefore, we have analyzed both the replication kinetics of HAdV-5 and the virus-induced transcriptome in human bronchial epithelial cells (HBEC) in comparison to cancer cells. This is the first report on genome-wide expression profiling of Ads in their native host cells. We found that E1A expression and onset of viral genome replication are most rapid in HBEC and considerably delayed in melanoma cells. In squamous cell lung carcinoma cells, we observed intermediate HAdV-5 replication kinetics. Infectious particle production, viral spread and lytic activity of HAdV-5 were attenuated in melanoma cells versus HBEC. Expression profiling at the onset of viral genome replication revealed that HAdV-5 induced the strongest changes in the cellular transcriptome in HBEC, followed by lung cancer and melanoma cells. We identified prominent regulation of genes involved in cell cycle and DNA metabolism, replication and packaging in HBEC, which is in accord with the necessity to induce S phase for viral replication. Strikingly, in melanoma cells HAdV-5 triggered opposing regulation of said genes and, in contrast to lung cancer cells, no weak S phase induction was detected when using the E2F promoter as reporter. Our results provide a rationale for improving oncolytic adenoviruses either by adaptation of viral infection to target tumor cells or by modulating tumor cell functions to better support viral replication.
While the deciphering of basic sequence information on a genomic scale is yielding complete genomic sequences in ever-shorter intervals, experimental procedures for elucidating the cellular effects and consequences of the DNA-encoded information become critical for further analyses. In recent years, DNA microarray technology has emerged as a prime candidate for the performance of many such functional assays. Technically, array technology has come a long way since its conception some 15 years ago, initially designed as a means for large-scale mapping and sequencing.The basic arrangement, however, could be adapted readily to serve eventually as an analytical tool in a large variety of applications. On their own or in combination with other methods, microarrays open up many new avenues of functional analysis.
