Network reconstruction using knock-out and over-expression data

This paper outlines necessary and sufficient conditions for network reconstruction of linear, time-invariant systems using data from either knock-out or over-expression experiments. These structural system perturbations, which are common in biological experiments, can be formulated as unknown system inputs, allowing the network topology and dynamics to be found. We assume that only partial state measurements are available and propose an algorithm that can reconstruct the network at the level of the measured states using either time-series or steady-state data. A simulated example illustrates how the algorithm successfully reconstructs a network from data. © 2013 EUCA.

Cell types, network homeostasis, and pathological compensation from a biologically plausible ion channel expression model.

How do neurons develop, control, and maintain their electrical signaling properties in spite of ongoing protein turnover and perturbations to activity? From generic assumptions about the molecular biology underlying channel expression, we derive a simple model and show how it encodes an "activity set point" in single neurons. The model generates diverse self-regulating cell types and relates correlations in conductance expression observed in vivo to underlying channel expression rates. Synaptic as well as intrinsic conductances can be regulated to make a self-assembling central pattern generator network; thus, network-level homeostasis can emerge from cell-autonomous regulation rules. Finally, we demonstrate that the outcome of homeostatic regulation depends on the complement of ion channels expressed in cells: in some cases, loss of specific ion channels can be compensated; in others, the homeostatic mechanism itself causes pathological loss of function.

A novel 3D network coordination polymer consisting of paddlewheel Co-3 clusters connected by PO4 and 4-pyridinecarboxylate

The synthesis, structural characterization and preliminary magnetic studies of a novel coordination polymer with paddlewheel Co-3 clusters are reported firstly. In the polymer, Co-3 clusters are covalently linked through PO4 tetrahedra and 4-pyridinecarboxylate (4-pya) ligands into interpenetrated three-dimensional network.

Enhanced surface attachment of protein-type targeting ligands to poly(lactide-co-glycolide) nanoparticles using variable expression of polymeric acid functionality

The density of reactive carboxyl groups on the surface of poly(lactide-co-glycolide) (PLGA) nanoparticles (NP) was modulated using a combination of high-molecular weight (MW) encapped and low MW non-encapped PLGA. Carboxyl groups were activated using carbodiimide chemistry and conjugated to bovine serum albumin and a model polyclonal antibody. Activation of carboxyl,groups in solution-phase PLGA prior to NP formation was compared with a postformation activation of peripheral carboxyl groups on intact NP. Activation before or after NP formation did not influence conjugation efficiency to NP prepared using 100% of the low-MW PLGA. The effect of steric stabilization using poly(vinyl alcohol) reduced conjugation of a polyclonal antibody from 62 mu g/(mg NP) to 32 mu g/(mg NP), but enhanced particulate stability. Increasing the amount of a high-MW PLGA also reduced Conjugation, with the activation post-formation still superior to the preformation approach. Drug release studies showed that high proportions of high-MW PLGA in the NP produced a longer sustained release profile of a model drug (celecoxib). It can be concluded that activating intact PLGA NP is superior to activating component parts prior to NP formation. Also, high MW PLGA could be used to prolong drug release, but at the expense of conjugation efficiency on to the NP surface. (C) 2008 Wiley Periodicals, Inc. J Biomed Mater Res 87A: 873-884, 2008

Investigation of swelling and network parameters of poly (ethylene glycol)-crosslinked poly (methyl vinyl ether-co-maleic acid) hydrogels

he influence of poly(ethylene glycol) (PEG) plasticiser content and molecular weight on the physicochemical properties of films cast from aqueous blends of poly(methyl vinyl ether-co-maleic acid) was investigated using thermal analysis, swelling studies, scanning electron microscopy (SEM) and attenuated total reflectance (ATR)-Fourier transform infrared (FTIR) spectroscopy. FTIR spectroscopy revealed a shift of the CO peak from 1708 to 1731 cm-1, indicating that an esterification reaction had occurred upon heating, thus producing crosslinked films. Higher molecular weight PEGs (10,000 and 1000 Da, respectively), having greater chain length, producing hydrogel networks with lower crosslink densities and higher average molecular weight between two consecutive crosslinks. Accordingly, such materials exhibited higher swelling rates. Hydrogels crosslinked with a low molecular weight PEG (PEG 200) showed rigid networks with high crosslink densities and, therefore, lower swelling rates. Polymer:plasticizer ratio alteration did not yield any discernable patterns, regardless of the method of analysis. The polymer–water interaction parameter (?) increased with increases in the crosslink density. SEM studies showed that porosity of the crosslinked films increased with increasing PEG MW, confirming what had been observed with swelling studies and thermal analysis, that the crosslink density must be decreased as the Mw of the crosslinker is increased. Hydrogels containing PMVE/MA/PEG 10,000 could be used for rapid delivery of drug, due to their low crosslink density. Moderately crosslinked PMVE/MA/PEG 1000 hydrogels or highly crosslinked PMVE/MA/PEG 200 systems could then be used in controlling the drug delivery rates. We are currently evaluating these systems, both alone and in combination, for use in sustained release drug delivery devices.

Bagging statistical network inference from large-scale gene expression data.

Modern biology and medicine aim at hunting molecular and cellular causes of biological functions and diseases. Gene regulatory networks (GRN) inferred from gene expression data are considered an important aid for this research by providing a map of molecular interactions. Hence, GRNs have the potential enabling and enhancing basic as well as applied research in the life sciences. In this paper, we introduce a new method called BC3NET for inferring causal gene regulatory networks from large-scale gene expression data. BC3NET is an ensemble method that is based on bagging the C3NET algorithm, which means it corresponds to a Bayesian approach with noninformative priors. In this study we demonstrate for a variety of simulated and biological gene expression data from S. cerevisiae that BC3NET is an important enhancement over other inference methods that is capable of capturing biochemical interactions from transcription regulation and protein-protein interaction sensibly. An implementation of BC3NET is freely available as an R package from the CRAN repository. © 2012 de Matos Simoes, Emmert-Streib.

Genome-wide analysis of p63 binding sites identifies AP-2 factors as co-regulators of epidermal differentiation

The p63 transcription factor (TP63) is critical in development, growth and differentiation of stratifying epithelia. This is highlighted by the severity of congenital abnormalities caused by TP63 mutations in humans, the dramatic phenotypes in knockout mice and de-regulation of TP63 expression in neoplasia altering the tumour suppressive roles of the TP53 family. In order to define the normal role played by TP63 and provide the basis for better understanding how this network is perturbed in disease, we used chromatin immunoprecipitation combined with massively parallel sequencing (ChIP-seq) to identify >7500 high-confidence TP63-binding regions across the entire genome, in primary human neonatal foreskin keratinocytes (HFKs). Using integrative strategies, we demonstrate that only a subset of these sites are bound by TP53 in response to DNA damage. We identify a role for TP63 in transcriptional regulation of multiple genes genetically linked to cleft palate and identify AP-2alpha (TFAP2A) as a co-regulator of a subset of these genes. We further demonstrate that AP-2gamma (TFAP2C) can bind a subset of these regions and that acute depletion of either TFAP2A or TFAP2C alone is sufficient to reduce terminal differentiation of organotypic epidermal skin equivalents, indicating overlapping physiological functions with TP63.

Investigation of swelling and network parameters of poly(ethylene glycol)-crosslinked poly(methyl vinyl ether-co-maleic acid) hydrogels

The influence of poly(ethylene glycol) (PEG) plasticiser content and molecular weight on the physicochemical properties of films cast from aqueous blends of poly(methyl vinyl ether-co-maleic acid) was investigated using thermal analysis, swelling studies, scanning electron microscopy (SEM) and attenuated total reflectance (ATR)-Fourier transform infrared (FTIR) spectroscopy. FTIR spectroscopy revealed a shift of the C{double bond, long}O peak from 1708 to 1731 cm, indicating that an esterification reaction had occurred upon heating, thus producing crosslinked films. Higher molecular weight PEGs (10,000 and 1000 Da, respectively), having greater chain length, producing hydrogel networks with lower crosslink densities and higher average molecular weight between two consecutive crosslinks. Accordingly, such materials exhibited higher swelling rates. Hydrogels crosslinked with a low molecular weight PEG (PEG 200) showed rigid networks with high crosslink densities and, therefore, lower swelling rates. Polymer:plasticizer ratio alteration did not yield any discernable patterns, regardless of the method of analysis. The polymer-water interaction parameter (?) increased with increases in the crosslink density. SEM studies showed that porosity of the crosslinked films increased with increasing PEG MW, confirming what had been observed with swelling studies and thermal analysis, that the crosslink density must be decreased as the M of the crosslinker is increased. Hydrogels containing PMVE/MA/PEG 10,000 could be used for rapid delivery of drug, due to their low crosslink density. Moderately crosslinked PMVE/MA/PEG 1000 hydrogels or highly crosslinked PMVE/MA/PEG 200 systems could then be used in controlling the drug delivery rates. We are currently evaluating these systems, both alone and in combination, for use in sustained release drug delivery devices. © 2008 Elsevier Ltd. All rights reserved.

Influence of a pore-forming agent on swelling, network parameters, and permeability of poly(ethylene glycol)-crosslinked poly(methyl vinyl ether-co-maleic acid) hydrogels:Application in transdermal delivery systems

We characterized hydrogels, prepared from aqueous blends of poly(methyl vinyl ether-co-maleic acid) (PMVE/MA) and poly(ethylene glycol) (PEG 10,000 Daltons) containing a pore-forming agent (sodium bicarbonate, NaHCO ). Increase in NaHCO content increased the equilibrium water content (EWC) and average molecular weight between crosslinks (M ) of hydrogels. For example, the %EWC was 731, 860, 1109, and 7536% and the M was 8.26, 31.64, 30.04, and 3010.00 × 10 g/mol for hydrogels prepared from aqueous blends containing 0, 1, 2, and 5% w/w of NaHCO , respectively. Increase in NaHCO content also resulted in increased permeation of insulin. After 24 h, percentage permeation was 0.94, 3.68, and 25.71% across hydrogel membranes prepared from aqueous blends containing 0, 2, and 5% w/w of NaHCO , respectively. Hydrogels containing the pore-forming agent were fabricated into microneedles (MNs) for transdermal drug delivery applications by integrating the MNs with insulin-loaded patches. It was observed that the mean amount of insulin permeating across neonatal porcine skin in vitro was 20.62% and 52.48% from hydrogel MNs prepared from aqueous blends containing 0 and 5% w/w of NaHCO . We believe that these pore-forming hydrogels are likely to prove extremely useful for applications in transdermal drug delivery of biomolecules. © 2012 Wiley Periodicals, Inc.

Urothelial cancer gene regulatory networks inferred from large-scale RNAseq, Bead and Oligo gene expression data

BACKGROUND: Urothelial pathogenesis is a complex process driven by an underlying network of interconnected genes. The identification of novel genomic target regions and gene targets that drive urothelial carcinogenesis is crucial in order to improve our current limited understanding of urothelial cancer (UC) on the molecular level. The inference of genome-wide gene regulatory networks (GRN) from large-scale gene expression data provides a promising approach for a detailed investigation of the underlying network structure associated to urothelial carcinogenesis.

METHODS: In our study we inferred and compared three GRNs by the application of the BC3Net inference algorithm to large-scale transitional cell carcinoma gene expression data sets from Illumina RNAseq (179 samples), Illumina Bead arrays (165 samples) and Affymetrix Oligo microarrays (188 samples). We investigated the structural and functional properties of GRNs for the identification of molecular targets associated to urothelial cancer.

RESULTS: We found that the urothelial cancer (UC) GRNs show a significant enrichment of subnetworks that are associated with known cancer hallmarks including cell cycle, immune response, signaling, differentiation and translation. Interestingly, the most prominent subnetworks of co-located genes were found on chromosome regions 5q31.3 (RNAseq), 8q24.3 (Oligo) and 1q23.3 (Bead), which all represent known genomic regions frequently deregulated or aberated in urothelial cancer and other cancer types. Furthermore, the identified hub genes of the individual GRNs, e.g., HID1/DMC1 (tumor development), RNF17/TDRD4 (cancer antigen) and CYP4A11 (angiogenesis/ metastasis) are known cancer associated markers. The GRNs were highly dataset specific on the interaction level between individual genes, but showed large similarities on the biological function level represented by subnetworks. Remarkably, the RNAseq UC GRN showed twice the proportion of significant functional subnetworks. Based on our analysis of inferential and experimental networks the Bead UC GRN showed the lowest performance compared to the RNAseq and Oligo UC GRNs.

CONCLUSION: To our knowledge, this is the first study investigating genome-scale UC GRNs. RNAseq based gene expression data is the data platform of choice for a GRN inference. Our study offers new avenues for the identification of novel putative diagnostic targets for subsequent studies in bladder tumors.

HES6 drives a critical AR transcriptional programme to induce castration-resistant prostate cancer through activation of an E2F1-mediated cell cycle network

Castrate-resistant prostate cancer (CRPC) is poorly characterized and heterogeneous and while the androgen receptor (AR) is of singular importance, other factors such as c-Myc and the E2F family also play a role in later stage disease. HES6 is a transcription co-factor associated with stem cell characteristics in neural tissue. Here we show that HES6 is up-regulated in aggressive human prostate cancer and drives castration-resistant tumour growth in the absence of ligand binding by enhancing the transcriptional activity of the AR, which is preferentially directed to a regulatory network enriched for transcription factors such as E2F1. In the clinical setting, we have uncovered a HES6-associated signature that predicts poor outcome in prostate cancer, which can be pharmacologically targeted by inhibition of PLK1 with restoration of sensitivity to castration. We have therefore shown for the first time the critical role of HES6 in the development of CRPC and identified its potential in patient-specific therapeutic strategies.