Curr Opin Chem Biol

Technological innovations and novel applications have greatly advanced the field of protein microarrays. Over the past two years, different types of protein microarrays have been used for serum profiling, protein abundance determinations, and identification of proteins that bind DNA or small compounds. However, considerable development is still required to ensure common quality standards and to establish large content repertoires. Here, we summarize applications available to date and discuss recent technological achievements and efforts on standardization

Differential binding studies applying functional protein microarrays and surface plasmon resonance

A variety of different in vivo and in vitro technologies provide comprehensive insights in protein-protein interaction networks. Here we demonstrate a novel approach to analyze, verify and quantify putative interactions between two members of the S100 protein family and 80 recombinant proteins derived from a proteome-wide protein expression library. Surface plasmon resonance (SPR) using Biacore technology and functional protein microarrays were used as two independent methods to study protein-protein interactions. With this combined approach we were able to detect nine calcium-dependent interactions between Arg-Gly-Ser-(RGS)-His6 tagged proteins derived from the library and GST-tagged S100B and S100A6, respectively. For the protein microarray affinity-purified proteins from the expression library were spotted onto modified glass slides and probed with the S100 proteins. SPR experiments were performed in the same setup and in a vice-versa approach reversing analytes and ligands to determine distinct association and dissociation patterns of each positive interaction. Besides already known interaction partners, several novel binders were found independently with both detection methods, albeit analogous immobilization strategies had to be applied in both assays

Primary differentiation in the human blastocyst : comparative molecular portraits of inner cell mass and trophectoderm cells

The primary differentiation event during mammalian development occurs at the blastocyst stage and leads to the delineation of the inner cell mass (ICM) and the trophectoderm (TE). We provide the first global mRNA expression data from immunosurgically dissected ICM cells, TE cells, and intact human blastocysts. Using a cDNA microarray composed of 15,529 cDNAs from known and novel genes, we identify marker transcripts specific to the ICM (e.g., OCT4/POU5F1, NANOG, HMGB1, and DPPA5) and TE (e.g., CDX2, ATP1B3, SFN, and IPL), in addition to novel ICM- and TE-specific expressed sequence tags. The expression patterns suggest that the emergence of pluripotent ICM and TE cell lineages from the morula is controlled by metabolic and signaling pathways, which include inter alia, WNT, mitogen-activated protein kinase, transforming growth factor-beta, NOTCH, integrin-mediated cell adhesion, phosphatidylinositol 3-kinase, and apoptosis. These data enhance our understanding of the first step in human cellular differentiation and, hence, the derivation of both embryonic stem cells and trophoblastic stem cells from these lineages

Observation of hard scattering in photoproduction events with a large rapidity gap at HERA

Events with a large rapidity gap and total transverse energy greater than 5 GeV have been observed in quasi-real photoproduction at HERA with the ZEUS detector. The distribution of these events as a function of the $\gamma p$ centre of mass energy is consistent with diffractive scattering. For total transverse energies above 12 GeV, the hadronic final states show predominantly a two-jet structure with each jet having a transverse energy greater than 4 GeV. For the two-jet events, little energy flow is found outside the jets. This observation is consistent with the hard scattering of a quasi-real photon with a colourless object in the proton.Comment: 19 pages, latex, 4 figures appended as uuencoded fil

Ecological networks: Pursuing the shortest path, however narrow and crooked

International audienceRepresenting data as networks cuts across all sub-disciplines in ecology and evolutionary biology. Besides providing a compact representation of the interconnections between agents, network analysis allows the identification of especially important nodes, according to various metrics that often rely on the calculation of the shortest paths connecting any two nodes. While the interpretation of a shortest paths is straightforward in binary, unweighted networks, whenever weights are reported, the calculation could yield unexpected results. We analyzed 129 studies of ecological networks published in the last decade that use shortest paths, and discovered a methodological inaccuracy related to the edge weights used to calculate shortest paths (and related centrality measures), particularly in interaction networks. Specifically, 49% of the studies do not report sufficient information on the calculation to allow their replication, and 61% of the studies on weighted networks may contain errors in how shortest paths are calculated. Using toy models and empirical ecological data, we show how to transform the data prior to calculation and illustrate the pitfalls that need to be avoided. We conclude by proposing a five-point checklist to foster best-practices in the calculation and reporting of centrality measures in ecology and evolution studies. The last two decades have witnessed an exponential increase in the use of graph analysis in ecological and conservation studies (see refs. 1,2 for recent introductions to network theory in ecology and evolution). Networks (graphs) represent agents as nodes linked by edges representing pairwise relationships. For instance, a food web can be represented as a network of species (nodes) and their feeding relationships (edges) 3. Similarly, the spatial dynamics of a metapopulation can be analyzed by connecting the patches of suitable habitat (nodes) with edges measuring dispersal between patches 4. Data might either simply report the presence/absence of an edge (binary, unweighted networks), or provide a strength for each edge (weighted networks). In turn, these weights can represent a variety of ecologically-relevant quantities, depending on the system being described. For instance, edge weights can quantify interaction frequency (e.g., visitation networks 5), interaction strength (e.g., per-capita effect of one species on the growth rate of another 3), carbon-flow between trophic levels 6 , genetic similarity 7 , niche overlap (e.g., number of shared resources between two species 8), affinity 9 , dispersal probabilities (e.g., the rate at which individuals of a population move between patches 10), cost of dispersal between patches (e.g., resistance 11), etc. Despite such large variety of ecological network representations, a common task is the identification of nodes of high importance, such as keystone species in a food web, patches acting as stepping stones in a dispersal network , or genes with pleiotropic effects. The identification of important nodes is typically accomplished through centrality measures 5,12. Many centrality measures has been proposed, each probing complementary aspects of node-to-node relationships 13. For instance, Closeness centrality 14,15 highlights nodes that are "near" to all othe

Observation of direct processes in photoproduction at HERA

Jets in photoproduction events have been studied with the ZEUS detector for gammap centre-of-mass energies ranging from 130 to 2 50 GeV. The inclusive jet distributions give evidence for the dominance of resolved photon interactions. In the di-jet sample the direct processes are for the first time clearly isolated. Di-jet cross sections for the resolved and direct processes are given in a restricted kinematic range

Measurement of Charged and Neutral Current e-p Deep Inelastic Scattering Cross Sections at High Q2

Deep inelastic e-p scattering has been studied in both the charged current (CC) and neutral current (NC) reactions at momentum transfers squared Q(2) above 400 GeV2 using the ZEUS detector at the HERA ep collider. The CC and NC total cross sections, the NC to CC cross section ratio, and the differential cross sections d sigma/dQ(2) are presented. From the Q(2) dependence of the CC cross section, the mass term in the CC propagator is determined to be M(W) = 76 +/- 16 +/- 13 GeV