The ERATO Systems Biology Workbench: Enabling Interaction and Exchange Between Software Tools for Computational Biology

Researchers in computational biology today make use of a large number of different software packages for modeling, analysis, and data manipulation and visualization. In this paper, we describe the ERATO Systems Biology Workbench (SBW), a software framework that allows these heterogeneous application components--written in diverse programming languages and running on different platforms--to communicate and use each others' data and algorithmic capabilities. Our goal is to create a simple, open-source software infrastructure which is effective, easy to implement and easy to understand. SBW uses a broker-based architecture and enables applications (potentially running on separate, distributed computers) to communicate via a simple network protocol. The interfaces to the system are encapsulated in client-side libraries that we provide for different programming languages. We describe the SBW architecture and the current set of modules, as well as alternative implementation technologies

How to Build Transcriptional Network Models of Mammalian Pattern Formation

Genetic regulatory networks of sequence specific transcription factors underlie pattern formation in multicellular organisms. Deciphering and representing the mammalian networks is a central problem in development, neurobiology, and regenerative medicine. Transcriptional networks specify intermingled embryonic cell populations during pattern formation in the vertebrate neural tube. Each embryonic population gives rise to a distinct type of adult neuron. The homeodomain transcription factor Lbx1 is expressed in five such populations and loss of Lbx1 leads to distinct respecifications in each of the five populations. allele, respectively. Microarrays were used to show that expression levels of 8% of all transcription factor genes were altered in the respecified pool. These transcription factor genes constitute 20–30% of the active nodes of the transcriptional network that governs neural tube patterning. Half of the 141 regulated nodes were located in the top 150 clusters of ultraconserved non-coding regions. Generally, Lbx1 repressed genes that have expression patterns outside of the Lbx1-expressing domain and activated genes that have expression patterns inside the Lbx1-expressing domain.nalysis, and think that it will be generally useful in discovering and assigning network interactions to specific populations. We discuss how ANCEA, coupled with population partitioning analysis, can greatly facilitate the systematic dissection of transcriptional networks that underlie mammalian patterning

Studying the functional conservation of cis-regulatory modules and their transcriptional output

<p>Abstract</p> <p>Background</p> <p><it>Cis</it>-regulatory modules (CRMs) are distinct, genomic regions surrounding the target gene that can independently activate the promoter to drive transcription. The activation of a CRM is controlled by the binding of a certain combination of transcription factors (TFs). It would be of great benefit if the transcriptional output mediated by a specific CRM could be predicted. Of equal benefit would be identifying <it>in silico </it>a specific CRM as the driver of the expression in a specific tissue or situation. We extend a recently developed biochemical modeling approach to manage both prediction tasks. Given a set of TFs, their protein concentrations, and the positions and binding strengths of each of the TFs in a putative CRM, the model predicts the transcriptional output of the gene. Our approach predicts the location of the regulating CRM by using predicted TF binding sites in regions near the gene as input to the model and searching for the region that yields a predicted transcription rate most closely matching the known rate.</p> <p>Results</p> <p>Here we show the ability of the model on the example of one of the CRMs regulating the <it>eve </it>gene, MSE2. A model trained on the MSE2 in <it>D. melanogaster </it>was applied to the surrounding sequence of the <it>eve </it>gene in seven other <it>Drosophila </it>species. The model successfully predicts the correct MSE2 location and output in six out of eight <it>Drosophila </it>species we examine.</p> <p>Conclusion</p> <p>The model is able to generalize from <it>D. melanogaster </it>to other <it>Drosophila </it>species and accurately predicts the location and transcriptional output of MSE2 in those species. However, we also show that the current model is not specific enough to function as a genome-wide CRM scanner, because it incorrectly predicts other genomic regions to be MSE2s.</p

The Innate Immune Database (IIDB)

<p>Abstract</p> <p>Background</p> <p>As part of a National Institute of Allergy and Infectious Diseases funded collaborative project, we have performed over 150 microarray experiments measuring the response of C57/BL6 mouse bone marrow macrophages to toll-like receptor stimuli. These microarray expression profiles are available freely from our project web site <url>http://www.innateImmunity-systemsbiology.org</url>. Here, we report the development of a database of computationally predicted transcription factor binding sites and related genomic features for a set of over 2000 murine immune genes of interest. Our database, which includes microarray co-expression clusters and a host of web-based query, analysis and visualization facilities, is available freely via the internet. It provides a broad resource to the research community, and a stepping stone towards the delineation of the network of transcriptional regulatory interactions underlying the integrated response of macrophages to pathogens.</p> <p>Description</p> <p>We constructed a database indexed on genes and annotations of the immediate surrounding genomic regions. To facilitate both gene-specific and systems biology oriented research, our database provides the means to analyze individual genes or an entire genomic locus. Although our focus to-date has been on mammalian toll-like receptor signaling pathways, our database structure is not limited to this subject, and is intended to be broadly applicable to immunology. By focusing on selected immune-active genes, we were able to perform computationally intensive expression and sequence analyses that would currently be prohibitive if applied to the entire genome. Using six complementary computational algorithms and methodologies, we identified transcription factor binding sites based on the Position Weight Matrices available in TRANSFAC. For one example transcription factor (ATF3) for which experimental data is available, over 50% of our predicted binding sites coincide with genome-wide chromatin immnuopreciptation (ChIP-chip) results. Our database can be interrogated via a web interface. Genomic annotations and binding site predictions can be automatically viewed with a customized version of the Argo genome browser.</p> <p>Conclusion</p> <p>We present the Innate Immune Database (IIDB) as a community resource for immunologists interested in gene regulatory systems underlying innate responses to pathogens. The database website can be freely accessed at <url>http://db.systemsbiology.net/IIDB</url>.</p

A De Novo Mouse Model of C11orf95-RELA Fusion-Driven Ependymoma Identifies Driver Functions in Addition to NF-κB.

The majority of supratentorial ependymomas (ST-ependymomas) have few mutations but frequently display chromothripsis of chromosome 11q that generates a fusion between C11orf95 and RELA (RELAFUS). Neural stem cells transduced with RELAFUSex vivo form ependymomas when implanted in the brain. These tumors display enhanced NF-κB signaling, suggesting that this aberrant signal is the principal mechanism of oncogenesis. However, it is not known whether RELAFUS is sufficient to drive de novo ependymoma tumorigenesis in the brain and, if so, whether these tumors also arise from neural stem cells. We show that RELAFUS drives ST-ependymoma formation from periventricular neural stem cells in mice and that RELAFUS-induced tumorigenesis is likely dependent on a series of cell signaling pathways in addition to NF-κB

The Drosophila Gap Gene Network Is Composed of Two Parallel Toggle Switches

Drosophila “gap” genes provide the first response to maternal gradients in the early fly embryo. Gap genes are expressed in a series of broad bands across the embryo during first hours of development. The gene network controlling the gap gene expression patterns includes inputs from maternal gradients and mutual repression between the gap genes themselves. In this study we propose a modular design for the gap gene network, involving two relatively independent network domains. The core of each network domain includes a toggle switch corresponding to a pair of mutually repressive gap genes, operated in space by maternal inputs. The toggle switches present in the gap network are evocative of the phage lambda switch, but they are operated positionally (in space) by the maternal gradients, so the synthesis rates for the competing components change along the embryo anterior-posterior axis. Dynamic model, constructed based on the proposed principle, with elements of fractional site occupancy, required 5–7 parameters to fit quantitative spatial expression data for gap gradients. The identified model solutions (parameter combinations) reproduced major dynamic features of the gap gradient system and explained gap expression in a variety of segmentation mutants

Sequential Logic Model Deciphers Dynamic Transcriptional Control of Gene Expressions

Cellular signaling involves a sequence of events from ligand binding to membrane receptors through transcription factors activation and the induction of mRNA expression. The transcriptional-regulatory system plays a pivotal role in the control of gene expression. A novel computational approach to the study of gene regulation circuits is presented here.Based on the concept of finite state machine, which provides a discrete view of gene regulation, a novel sequential logic model (SLM) is developed to decipher control mechanisms of dynamic transcriptional regulation of gene expressions. The SLM technique is also used to systematically analyze the dynamic function of transcriptional inputs, the dependency and cooperativity, such as synergy effect, among the binding sites with respect to when, how much and how fast the gene of interest is expressed. expression and additional activities of binding sites are required. Further analyses suggest detailed mechanism of R switch activity where indirect dependency occurs in between UI activity and R switch during specification to differentiation stage. is a promising step for further application of the proposed method

A positron emission tomography imaging study to confirm target engagement in the lungs of patients with idiopathic pulmonary fibrosis following a single dose of a novel inhaled αvβ6 integrin inhibitor

© 2020 The Author(s). Background: Idiopathic pulmonary fibrosis (IPF) is a chronic, progressive lung disease with poor prognosis and a significant unmet medical need. This study evaluated the safety, pharmacokinetics (PK) and target engagement in the lungs, of GSK3008348, a novel inhaled alpha-v beta-6 (αvβ6) integrin inhibitor, in participants with IPF. Methods: This was a phase 1b, randomised, double-blind (sponsor unblind) study, conducted in the UK (two clinical sites, one imaging unit) between June 2017 and July 2018 (NCT03069989). Participants with a definite or probable diagnosis of IPF received a single nebulised dose of 1000 mcg GSK3008348 or placebo (ratio 5:2) in two dosing periods. In period 1, safety and PK assessments were performed up to 24 h post-dose; in period 2, after a 7-day to 28-day washout, participants underwent a total of three positron emission tomography (PET) scans: Baseline, Day 1 (~ 30 min post-dosing) and Day 2 (~ 24 h post-dosing), using a radiolabelled αvβ6-specific ligand, [18F]FB-A20FMDV2. The primary endpoint was whole lung volume of distribution (VT), not corrected for air volume, at ~ 30 min post-dose compared with pre-dose. The study success criterion, determined using Bayesian analysis, was a posterior probability (true % reduction in VT > 0%) of ≥80%. Results: Eight participants with IPF were enrolled and seven completed the study. Adjusted posterior median reduction in uncorrected VT at ~ 30 min after GSK3008348 inhalation was 20% (95% CrI:-9 to 42%). The posterior probability that the true % reduction in VT > 0% was 93%. GSK3008348 was well tolerated with no reports of serious adverse events or clinically significant abnormalities that were attributable to study treatment. PK was successfully characterised showing rapid absorption followed by a multiphasic elimination. Conclusions: This study demonstrated engagement of the αvβ6 integrin target in the lung following nebulised dosing with GSK3008348 to participants with IPF. To the best of our knowledge this is the first time a target-specific PET radioligand has been used to assess target engagement in the lung, not least for an inhaled drug. Trial registration: Clinicaltrials.gov: NCT03069989; date of registration: 3 March 2017

Effects of iron-rich intermetallics and grain structure on semisolid tensile properties of Al-Cu 206 cast alloys near solidus temperature

The effects of iron-rich intermetallics and grain size on the semisolid tensile properties of Al-Cu 206 cast alloys near the solidus were evaluated in relation to the mush microstructure. Analyses of the stress–displacement curves showed that the damage expanded faster in the mush structure dominated by plate-like β-Fe compared to the mush structure dominated by Chinese script-like α-Fe. While there was no evidence of void formation on the β-Fe intermetallics, they blocked the interdendritic liquid channels and thus hindered liquid flow and feeding during semisolid deformation. In contrast, the interdendritic liquid flows more freely within the mush structure containing α-Fe. The tensile properties of the alloy containing α-Fe are generally higher than those containing β-Fe over the crucial liquid fraction range of ~0.6 to 2.8 pct, indicating that the latter alloy may be more susceptible to stress-related casting defects such as hot tearing. A comparison of the semisolid tensile properties of the alloy containing α-Fe with different grain sizes showed that the maximum stress and elongation of the alloy with finer grains were moderately higher for the liquid fractions of ~2.2 to 3.6 pct. The application of semisolid tensile properties for the evaluation of the hot tearing susceptibility of experimental alloys is discussed