Expression profiling of drug response-from genes to pathways

Understanding individual response to a drug—what determines its efficacy and tolerability—is the major bottleneck in current drug development and clinical trials. Intracellular response and metabolism, for example through cytochrome P- 450 enzymes, may either enhance or decrease the effect of different drugs, dependent on the genetic variant. Microarrays offer the potential to screen the genetic composition of the individual patient. However, experiments are “noisy” and must be accompanied by solid and robust data analysis. Furthermore, recent research aims at the combination of highthroughput data with methods of mathematical modeling, enabling problem-oriented assistance in the drug discovery process. This article will discuss state-of-the-art DNA array technology platforms and the basic elements of data analysis and bioinformatics research in drug discovery. Enhancing single-gene analysis, we will present a new method for interpreting gene expression changes in the context of entire pathways. Furthermore, we will introduce the concept of systems biology as a new paradigm for drug development and highlight our recent research—the development of a modeling and simulation platform for biomedical applications. We discuss the potentials of systems biology for modeling the drug response of the individual patient

Bioinformatics

The analysis of gene regulatory networks (GRNs) is a central goal of bioinformatics highly accelerated by the advent of new experimental techniques, such as RNA interference. A battery of reverse engineering methods has been developed in recent years to reconstruct the underlying GRNs from these and other experimental data. However, the performance of the individual methods is poorly understood and validation of algorithmic performances is still missing to a large extent. To enable such systematic validation, we have developed the web application GeNGe (GEne Network GEnerator), a controlled framework for the automatic generation of GRNs. The theoretical model for a GRN is a non-linear differential equation system. Networks can be user-defined or constructed in a modular way with the option to introduce global and local network perturbations. Resulting data can be used, e.g. as benchmark data for evaluating GRN reconstruction methods or for predicting effects of perturbations as theoretical counterparts of biological experiment

Beam Performance and Luminosity Limitations in the High-Energy Storage Ring (HESR)

The High-Energy Storage Ring (HESR) of the future International Facility for Antiproton and Ion Research (FAIR) at GSI in Darmstadt is planned as an antiproton synchrotron and storage ring in the momentum range from 1.5 to 15 GeV/c. An important feature of this new facility is the combination of phase space cooled beams with dense internal targets (e.g. pellet targets), resulting in demanding beam parameter of two operation modes: high luminosity mode with peak luminosities up to 2*10^32 cm-2 s-1, and high resolution mode with a momentum spread down to 10^-5, respectively. To reach these beam parameters very powerful phase space cooling is needed, utilizing high-energy electron cooling and high-bandwidth stochastic cooling. The effect of beam-target scattering and intra-beam interaction is investigated in order to study beam equilibria and beam losses for the two different operation modes.Comment: 8 pages, based on a talk presented at COULOMB'05, Accepted for publication by Nuclear Instruments and Methods in Physics Research Section A: Accelerators, Spectrometers, Detectors and Associated Equipmen

Analysis of Oct4-dependent transcriptional networks regulating self-renewal and pluripotency in human embryonic stem cells

The POU domain transcription factor OCT4 is a key regulator of pluripotency in the early mammalian embryo and is highly expressed in the inner cell mass of the blastocyst. Consistent with its essential role in maintaining pluripotency, Oct4 expression is rapidly downregulated during formation of the trophoblast lineage. To enhance our understanding of the molecular basis of this differentiation event in humans, we used a functional genomics approach involving RNA interference-mediated suppression of OCT4 function in a human ESC line and analysis of the resulting transcriptional profiles to identify OCT4-dependent genes in human cells. We detected altered expression of >1,000 genes, including targets regulated directly by OCT4 either positively (NANOG, SOX2, REX1, LEFTB, LEFTA/EBAF DPPA4, THY1, and TDGF1) or negatively (CDX2, EOMES, BMP4, TBX18, Brachyury [T], DKK1, HLX1, GATA6, ID2, and DLX5), as well as targets for the OCT4-associated stem cell regulators SOX2 and NANOG. Our data set includes regulators of ACTIVIN, BMP, fibroblast growth factor, and WNT signaling. These pathways are implicated in regulating human ESC differentiation and therefore further validate the results of our analysis. In addition, we identified a number of differentially expressed genes that are involved in epigenetics, chromatin remodeling, apoptosis, and metabolism that may point to underlying molecular mechanisms that regulate pluripotency and trophoblast differentiation in humans. Significant concordance between this data set and previous comparisons between inner cell mass and trophectoderm in human embryos indicates that the study of human ESC differentiation in vitro represents a useful model of early embryonic differentiation in humans

A European focus on proteomics

A report on the First International Symposium of the Austrian Proteomics Platform, Seefeld, Austria, 26-29 January 2004

A Method to Polarize Stored Antiprotons to a High Degree

Polarized antiprotons can be produced in a storage ring by spin--dependent interaction in a purely electron--polarized hydrogen gas target. The polarizing process is based on spin transfer from the polarized electrons of the target atoms to the orbiting antiprotons. After spin filtering for about two beam lifetimes at energies $T\approx 40-170$ MeV using a dedicated large acceptance ring, the antiproton beam polarization would reach $P=0.2-0.4$. Polarized antiprotons would open new and unique research opportunities for spin--physics experiments in $\bar{p}p$ interactions

Creation and application of immortalized bait libraries for targeted enrichment and next-generation sequencing

Since the introduction of next-generation sequencing, several techniques have been developed to selectively enrich and sequence specific parts of the genome at high coverage. These techniques include enzymatic methods employing molecular inversion probes, PCR based approaches, hybrid capture, and in-solution capture. In-solution capture employs RNA probes transcribed from a pool of DNA template oligos designed to match regions of interest to specifically bind and enrich genomic DNA fragments. This method is highly efficient, especially if genomic target regions are large in size or quantity. Diverse in-solution capture kits are available, but are costly when large sample numbers need to be analyzed. Here we present a cost-effective strategy for the design of custom DNA libraries, their transcription into RNA libraries, and application for in-solution capture. We show the efficacy by comparing the method to a commercial kit and further demonstrate that emulsion PCR can be used for bias free amplification and virtual immortalization of DNA template libraries

IT Future of Medicine: from molecular analysis to clinical diagnosis and improved treatment

The IT Future of Medicine (ITFoM, http://www.itfom.eu/) initiative will produce computational models of individuals to enable the prediction of their future health risks, progression of diseases and selection and efficacy of treatments while minimising side effects. To be able to move our health care system to treat patients as individuals rather than as members of larger, divergent groups, the ITFoM initiative, proposes to integrate molecular, physiological and anatomical data of every person in 'virtual patient' models. The establishment of such 'virtual patient' models is now possible due to the enormous progress in analytical techniques, particularly in the '-omics' technology areas and in imaging, as well as in sensor technologies, but also due to the immense developments in the ICT field. As one of six Future and Emerging Technologies (FET) Flagship Pilot Projects funded by the European Commission, ITFoM with more than 150 academic and industrial partners from 34 countries, will foster the development in functional genomics and computer technologies to generate 'virtual patient' models to make them available for clinical application. The increase in the capacity of next generation sequencing systems will enable the high-throughput analysis of a large number of individuals generating huge amounts of genome, epigenome and transcriptome data, but making it feasible to apply deep sequencing in the clinic to characterise not only the patient's genome, but also individual samples, for example, from tumours. The genome profile will be integrated with proteome and metabolome information generated via new powerful chromatography, mass spectrometry and nuclear magnetic resonance techniques. The individualised model will not only enable the analysis of the current situation, but will allow the prediction of the response of the patient to different therapy options or intolerance for certain drugs

FGF inhibition directs BMP4-mediated differentiation of human embryonic stem cells to syncytiotrophoblast

Bone morphogenetic protein (BMP) signaling is known to support differentiation of human embryonic stem cells (hESCs) into mesoderm and extraembryonic lineages, whereas other signaling pathways can largely influence this lineage specification. Here, we set out to reinvestigate the influence of ACTIVIN/NODAL and fibroblast growth factor (FGF) pathways on the lineage choices made by hESCs during BMP4-driven differentiation. We show that BMP activation, coupled with inhibition of both ACTIVIN/NODAL and FGF signaling, induces differentiation of hESCs, specifically to betahCG hormone-secreting multinucleated syncytiotrophoblast and does not support induction of embryonic and extraembryonic lineages, extravillous trophoblast, and primitive endoderm. It has been previously reported that FGF2 can switch BMP4-induced hESC differentiation outcome to mesendoderm. Here, we show that FGF inhibition alone, or in combination with either ACTIVIN/NODAL inhibition or BMP activation, supports hESC differentiation to hCG-secreting syncytiotrophoblast. We show that the inhibition of the FGF pathway acts as a key in directing BMP4-mediated hESC differentiation to syncytiotrophoblast