Mycobacterial infections remain a significant cause of morbidity and mortality worldwide. Due to limitations of the currently available model systems, there are still comparably large gaps in the knowledge about the pathogenesis of these chronic inflammatory diseases in particular with regard to the human host. Therefore, we aimed to characterize the initial phase of mycobacterial infections utilizing a human ex vivo lung tissue culture model designated STST (Short-Term Stimulation of Tissues).

ABSTRACT Antibiotic-resistant tuberculosis poses a global threat, causing the deaths of hundreds of thousands of people annually. While whole-genome sequencing (WGS), with its unprecedented level of detail, promises to play an increasingly important role in diagnosis, data analysis is a daunting challenge. Here, we present a simple-to-use web service (free for academic use at http://phyresse.org ). Delineating both lineage and resistance, it provides state-of-the-art methodology to life scientists and physicians untrained in bioinformatics. It combines elaborate data processing and quality control, as befits human diagnostics, with a treasure trove of validated resistance data collected from well-characterized samples in-house and worldwide.

Micro-organisms sense the availability of nutrients in their environment to control cellular behaviour and the expression of transporters and enzymes that are required for the utilization of these nutrients. In the pathogenic yeast Candida albicans, the preferred nitrogen source ammonium suppresses the switch from yeast to filamentous growth in response to certain stimuli, and it also represses the secretion of proteases, which are required for the utilization of proteins as an alternative nitrogen source. To investigate whether C. albicans senses the availability of ammonium in the extracellular environment or if ammonium uptake into the cell is required to regulate morphogenesis and gene expression, we compared the behaviour of wild-type cells and ammonium uptake-deficient mutants in the presence and absence of extracellular ammonium. Arginine-induced filamentous growth was suppressed by ammonium in the wild-type, but not in mutants lacking the ammonium permeases Mep1 and Mep2. Similarly, ammonium suppressed protease secretion and extracellular protein degradation in the wild-type, but not in mutants lacking the ammonium transporters. By comparing the gene expression profiles of C. albicans grown in the presence of low or high ammonium concentrations, we identified a set of genes whose expression is controlled by nitrogen availability. The repression of genes involved in the utilization of alternative nitrogen sources, which occurred under ammonium-replete conditions in the wild-type, was abrogated in mep1Δ mep2Δ mutants. These results demonstrate that C. albicans does not respond to the presence of sufficient amounts of the preferred nitrogen source ammonium by sensing its availability in the environment. Instead, ammonium has to be taken up into the cell to control morphogenesis, protease secretion and gene expression.

PURPOSE:In this study, plasma samples from a multicentric case-control study on lymphoma were analyzed for the identification of proteins useful for diagnosis.EXPERIMENTAL DESIGN:The protein content in the plasma of 100 patients suffering from the three most common B-cell lymphomas and 100 control samples was studied with antibody microarrays composed of 810 antibodies that target cancer-associated proteins. Sample pools were screened for an identification of marker proteins. Then, the samples were analyzed individually to validate the usability of these markers.RESULTS:More than 200 proteins with disease-associated abundance changes were found. The evaluation on individual patients confirmed some molecules as robust informative markers while others were inadequate for this purpose. In addition, the analysis revealed distinct subgroups for each of the three investigated B-cell lymphoma subtypes. With this information, we delineated a classifier that discriminates the different lymphoma entities.CONCLUSIONS AND CLINICAL RELEVANCE:Variations in plasma protein abundance permit discrimination between different patient groups. After validation on a larger study cohort, the findings could have diagnostic as well as differential diagnostic potential. Beside this, methodological aspects were critically evaluated, such as the value of sample pooling for the identification of biomarkers that are useful for a diagnosis on individual patients.

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.

Antibody microarrays are a multiplexing technique for the analyses of hundreds of different analytes in parallel from small sample volumes of few microlitres only. With sensitivities in the picomolar to femtomolar range, they are gaining importance in proteomic analyses. These sensitivities can be obtained for complex protein samples without any pre-fractionation or signal amplification. Also, no expensive or elaborate protein depletion steps are needed. As with custom DNA-microarrays, the implementation of a dual-colour assay adds to assay robustness and reproducibility and was therefore a focus of our technical implementation. In order to perform antibody microarray experiments for large sets of samples and analytes in a robust manner, it was essential to optimise the experimental layout, the protein extraction, labelling and incubation as well as data processing steps. Here, we present our current protocol, which is used for the simultaneous analysis of the abundance of more than 800 proteins in plasma, urine, and tissue samples.

BACKGROUND AND PURPOSEPancreatic cancer is one of the leading cancer-related causes of death due to high chemo-resistance and fast metastasation. Nemorosone, a polycyclic polyprenylated acylphloroglucinol, has recently been identified as a promising anticancer agent. Here, we examine its growth-inhibitory effects on pancreatic cancer cells. Based on transcription profiling, a molecular mode of action is proposed.EXPERIMENTAL APPROACHNemorosone cytotoxicity was assessed by the resazurin proliferation assay on pancreatic cancer cells and fibroblasts. Apoptosis was determined by Annexin V/propidium iodide staining as well as cytochrome c and caspase activation assays. Staining with the voltage-dependent dye JC-1 and fluorescence microscopy were used to detect effects on mitochondrial membrane potential. Total RNA was isolated from treated cell lines and subjected to microarray analysis, subsequent pathway identification and modelling. Gene expression data were validated by quantitative polymerase chain reaction and siRNA-mediated gene knock-down.KEY RESULTSNemorosone significantly inhibited cancer cell growth, induced cytochrome c release and subsequent caspase-dependent apoptosis, rapidly abolished mitochondrial membrane potential and elevated cytosolic calcium levels, while fibroblasts were largely unaffected. Expression profiling revealed 336 genes to be affected by nemorosone. A total of 75 genes were altered in all three cell lines, many of which were within the unfolded protein response (UPR) network. DNA damage inducible transcript 3 was identified as a key regulator in UPR-mediated cell death.CONCLUSIONS AND IMPLICATIONSNemorosone could be a lead compound for the development of novel anticancer drugs amplifying the already elevated UPR level in solid tumours, thus driving them into apoptosis. This study forms the basis for further investigations identifying nemorosone's direct molecular target(s).

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.

MATLAB has evolved from the command-line-based ``MATrix LABoratory” into a fullyfeatured programming environment. But is it really practical for implementing a larger software package? Also if it is intended to run on servers and if Unix is preferred as a server operation system? What if there are more problem-related statistical methods available in R? Positive answers to these and more questions are shown in example discussing the ``MultiConditional Hybridization Processing System” (M-CHiPS). Here, as well, the name is not entirely descriptive because apart from the classical microarray hybridizations it takes data from e.g. antibody array incubations as well as methylation or quantitative tandem mass spectrometry data by now. The system was implemented predominantly in MATLAB. It currently contains more than 13,000 hybridizations, incubations, gels, runs etc. comprising all common microarray transcriptomics platforms but also genomic chip data, chip-based methylation data, 2D-DIGE gels, antibody arrays (both single and dual-channel), and TMT 6-plex MS/MS data. Apart from tumor biopsies, it contains also data about model organisms, e.g. Trypansosoma brucei, Candida albicans, and Aspergillus fumigates, to date 11 organisms in total. While data stemming from e. g. Microarray and Mass Spectrometry platforms need very different preprocessing steps prior to data interpretation, the result can generally be regarded as a table with its columns representing some biological conditions, e.g. various genotypes, growth conditions or tumor stages, just to give some examples. Also, in most cases, each row roughly represents a “gene”, more precisely standing for its DNA sequence, methylation status, RNA transcript abundance, or protein level. Thus, quantitative data stemming from different platforms and representing the status of either the transcriptome, methylome or the proteome can be collected in the very same format (database structure, MATLAB variables). Also, the same set of algorithms can be applied for analysis and visualization. However, the patterns comprised by these large genes × conditions data tables cannot be understood without additional information. The behaviours of some ten thousands of genes need to be explained by Gene Ontology terms or transcription factor binding sites. And often hundreds of samples need to be related to represented genotypes, growth conditions or disease states in order to interpret these data. In addition to the signal intensities, MCHiPS records information about the protocols involved (to track down systematic errors), sample biology and clinical data. Risk parameters such as alcohol consumption and

The role of sulfite reductase (SiR) in assimilatory reduction of inorganic sulfate to sulfide has long been regarded as insignificant for control of flux in this pathway. Two independent Arabidopsis thaliana T-DNA insertion lines (sir1-1 and sir1-2), each with an insertion in the promoter region of SiR, were isolated. sir1-2 seedlings had 14% SiR transcript levels compared with the wild type and were early seedling lethal. sir1-1 seedlings had 44% SiR transcript levels and were viable but strongly retarded in growth. In mature leaves of sir1-1 plants, the levels of SiR transcript, protein, and enzymatic activity ranged between 17 and 28% compared with the wild type. The 28-fold decrease of incorporation of (35)S label into Cys, glutathione, and protein in sir1-1 showed that the decreased activity of SiR generated a severe bottleneck in the assimilatory sulfate reduction pathway. Root sulfate uptake was strongly enhanced, and steady state levels of most of the sulfur-related metabolites, as well as the expression of many primary metabolism genes, were changed in leaves of sir1-1. Hexose and starch contents were decreased, while free amino acids increased. Inorganic carbon, nitrogen, and sulfur composition was also severely altered, demonstrating strong perturbations in metabolism that differed markedly from known sulfate deficiency responses. The results support that SiR is the only gene with this function in the Arabidopsis genome, that optimal activity of SiR is essential for normal growth, and that its downregulation causes severe adaptive reactions of primary and secondary metabolism.

Antibody microarrays have the potential to enable comprehensive proteomic analysis of small amounts of sample material. Here, protocols are presented for the production, quality assessment, and reproducible application of antibody microarrays in a two-color mode with an array of 1,800 features, representing 810 antibodies that were directed at 741 cancer-related proteins. In addition to measures of array quality, we implemented indicators for the accuracy and significance of dual-color detection. Dual-color measurements outperform a single-color approach concerning assay reproducibility and discriminative power. In the analysis of serum samples, depletion of high-abundance proteins did not improve technical assay quality. On the contrary, depletion introduced a strong bias in protein representation. In an initial study, we demonstrated the applicability of the protocols to proteins derived from urine samples. We identified differences between urine samples from pancreatic cancer patients and healthy subjects and between sexes. This study demonstrates that biomedically relevant data can be produced. As demonstrated by the thorough quality analysis, the dual-color antibody array approach proved to be competitive with other proteomic techniques and comparable in performance to transcriptional microarray analyses.

In recent years, antibody microarrays have developed into an important tool for proteomics. As a multiplexing technique, they facilitate the highly parallel detection of hundreds of different analytes from very small sample volumes of only a few microlitres. This is combined with high sensitivity in the picomolar to femtomolar range, which is similar to the sensitivity of ELISA, the gold standard for protein quantification. In order to obtain such sensitivities in a robust and reproducible manner for sets of several hundreds of analytes simultaneously, it is essential to optimise the experimental layout, sample handling, labelling and incubation as well as data processing steps. Here, we present our current antibody microarray protocols for multiplexed expression profiling studies, which permit the analysis of the abundance of more than 800 proteins in plasma, urine and tissue samples.

Despite substantial and growing knowledge about its biology, pancreatic cancer is constantly evading new treatment strategies due to its chemoresistant nature. Thus, the aim of many oncologists is to identify and evaluate drugs with novel mechanisms of action to overcome resistance. Nemorosone, a polyisoprenylated benzophenone isolated from the flower resin of Clusia rosea, showed extraordinary cytotoxic and antitumoral activity on a panel of cancer cell lines. To assess its potential in more detail for the treatment of pancreatic cancer, the effects of nemorosone on three pancreatic cancer cell lines known to be very chemoresistant were analyzed by cytotoxicity/apoptosis assays as well as gene expression profiling. cDNA microarray data of 3500 genes were analyzed to identify pathways and molecular networks affected by treatment with nemorosone in order to shed light on its molecular mechanism of action. Results were validated using quantitative RT-PCR, RNAi-mediated gene silencing and immunofluorescence. After 72 h of incubation, nemorosone showed a remarkable IC50 of 5 µM on all pancreatic cancer cell lines in comparison to 40 µM on normal fibroblasts. Nemorosone induced cell cycle arrest and apoptosis in a dose- and time-dependent manner. Interestingly, apoptosis rate was dependent on the degree of differentiation of the cell line, with MIA-PaCa-2 (undifferentiated cell line) exhibiting the highest rate of apoptosis and almost no signs of apoptosis in normal fibroblasts. Gene expression analysis after treatment revealed a strong induction of the cell cycle regulator p21 and, consequently, massive down-regulation of many genes associated with the cell cycle and DNA synthesis. The induction of the stress-response protein GADD153 as well as anti-oxidative proteins and many down-stream targets of ATF4 suggests the involvement of the endoplasmic reticulum stress response. It is concluded that these events trigger the intrinsic pathway of apoptosis which results in the fast loss of mitochondrial membrane potential as measured by voltage-dependent staining with JC-1. RNAi-mediated knock-down of GADD153 resulted in a significant reduction of apoptosis rate in MIA-PaCa-2 cells. Furthermore, it is hypothesized that the rapid depolarization of the mitochondrial membrane in cancer cells is also due to ion fluxes from the endoplasmic reticulum to mitochondria, leading to the disturbance of ER homeostasis and, finally, apoptosis. Thus, considering its high efficacy on undifferentiated cells and lower cytotoxicity on normal cells, nemorosone is a potential drug candidate for the treatment of advanced pancreatic cancer which is the fifth most common cancer-related cause of death in the western world. Note: This abstract was not presented at the AACR 101st Annual Meeting 2010 because the presenter was unable to attend. Citation Format: {Authors}. {Abstract title} [abstract]. In: Proceedings of the 101st Annual Meeting of the American Association for Cancer Research; 2010 Apr 17-21; Washington, DC. Philadelphia (PA): AACR; Cancer Res 2010;70(8 Suppl):Abstract nr 3572.

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.

Pancreatic cancer is one of the most aggressive human malignancies, with an extremely poor prognosis. The paucity of curative therapies has translated into an overall 5-year survival rate of less than 5%, underscoring a desperate need for new therapeutic options. Artesunate (ART), clinically used as anti-malarial agent, has recently revealed remarkable anti-tumor activity. However, the mechanisms underlying those activities in pancreatic cancer are not yet known. Here we evaluated the anti-tumor activity of Artesunate and the possible underlying mechanisms in pancreatic cancer. MiaPaCa-2 (poorly differentiated) and BxPC-3 (moderately differentiated) pancreatic cancer cell lines were treated with Artesunate and the effect was monitored by a tetrazolium-based assay (MTS) for evaluating cell viability and by flow cytometry and caspase 3/7 activation for apoptosis evaluation. In addition cDNA arrays were used to identify differentially expressed genes. The microarray data were then validated by RT-PCR and Western blotting. Moreover, pathways associated with these expression changes were identified using the Ingenuity Pathway Analysis. The expression analysis identified a common set of genes that were regulated by Artesunate in pancreatic cancer. Our results provide the first in vitro evidence for the therapeutic utility of Artesunate in pancreatic cancer. Moreover, we identified Artesunate as a novel topoisomerase IIalpha inhibitor that inhibits pancreatic cancer growth through modulation of multiple signaling pathways. The present analysis is a starting point for the generation of hypotheses on candidate genes and for a more detailed dissection of the functional role of individual genes for the activity of Artesunate in tumor cells.

Transcript profiling by microarray analysis offers a great opportunity to reveal unknown effects in a comprehensive context. To be able to interpret the data, some basic issues in experimental setting and design including type and number of replications have to be considered and are discussed in this work. In order to facilitate and automate data interpretation, the experimental data were projected and clustered by Correspondence Analysis, subsequently associated with gene ontology (GO) terms for functional classification.We applied the technology to investigate copper metabolism in the human pathogen Candida albicans. The presented dataset gives an example of how different fluorescent labeling, biological and technical replicas and data analysis strategies for microarray experiments may influence the final outcome of the results. (C) 2009 by WILEY-VCH Verlag GmbH & Co. KGaA, Weinheim.

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).