BioTapestry: a tool to visualize the dynamic properties of gene regulatory networks

Computational approaches for modeling and structural design of biological systems: A comprehensive review

The convergence of biology and computational science has ushered in a revolutionary era, revolutionizing our understanding of biological systems and providing novel solutions to global problems. The field of genetic engineering has facilitated the manipulation of genetic codes, thus providing opportunities for the advancement of innovative disease therapies and environmental enhancements. The emergence of bio-molecular simulation represents a significant advancement in this particular field, as it offers the ability to gain microscopic insights into molecular-level biological processes over extended periods. Biomolecular simulation plays a crucial role in advancing our comprehension of organismal mechanisms by establishing connections between molecular structures, interactions, and biological functions. The field of computational biology has demonstrated its significance in deciphering intricate biological enigmas through the utilization of mathematical models and algorithms. The process of decoding the human genome has resulted in the advancement of therapies for a wide range of genetic disorders, while the simulation of biological systems contributes to the identification of novel pharmaceutical compounds. The potential of biomolecular simulation and computational biology is vast and limitless. As the exploration of the underlying principles that govern living organisms progresses, the potential impact of this understanding on cancer treatment, environmental restoration, and other domains is anticipated to be transformative. This review examines the notable advancements achieved in the field of computational biology, emphasizing its potential to revolutionize the comprehension and enhancement of biological systems.

Homologous gene regulatory networks control development of apical organs and brains in Bilateria

Apical organs are relatively simple larval nervous systems. The extent to which apical organs are evolutionarily related to the more complex nervous systems of other animals remains unclear. To identify common developmental mechanisms, we analyzed the gene regulatory network (GRN) controlling the development of the apical organ in sea urchins. We characterized the developmental expression of 30 transcription factors and identified key regulatory functions for FoxQ2, Hbn, Delta/Notch signaling, and SoxC in the patterning of the apical organ and the specification of neurons. Almost the entire set of apical transcription factors is expressed in the nervous system of worms, flies, zebrafish, frogs, and mice. Furthermore, a regulatory module controlling the axial patterning of the vertebrate brain is expressed in the ectoderm of sea urchin embryos. We conclude that GRNs controlling the formation of bilaterian nervous systems share a common origin and that the apical GRN likely resembles an ancestral regulatory program.

Decoding the IGF1 signaling gene regulatory network behind alveologenesis from a mouse model of bronchopulmonary dysplasia

Lung development is precisely controlled by underlying gene regulatory networks (GRN). Disruption of genes in the network can interrupt normal development and cause diseases such as bronchopulmonary dysplasia (BPD) - a chronic lung disease in preterm infants with morbid and sometimes lethal consequences characterized by lung immaturity and reduced alveolarization. Here, we generated a transgenic mouse exhibiting a moderate severity BPD phenotype by blocking IGF1 signaling in secondary crest myofibroblasts (SCMF) at the onset of alveologenesis. Using approaches mirroring the construction of the model GRN in sea urchin's development, we constructed the IGF1 signaling network underlying alveologenesis using this mouse model that phenocopies BPD. The constructed GRN, consisting of 43 genes, provides a bird's eye view of how the genes downstream of IGF1 are regulatorily connected. The GRN also reveals a mechanistic interpretation of how the effects of IGF1 signaling are transduced within SCMF from its specification genes to its effector genes and then from SCMF to its neighboring alveolar epithelial cells with WNT5A and FGF10 signaling as the bridge. Consistently, blocking WNT5A signaling in mice phenocopies BPD as inferred by the network. A comparative study on human samples suggests that a GRN of similar components and wiring underlies human BPD. Our network view of alveologenesis is transforming our perspective to understand and treat BPD. This new perspective calls for the construction of the full signaling GRN underlying alveologenesis, upon which targeted therapies for this neonatal chronic lung disease can be viably developed.

Divergence in the ABA gene regulatory network underlies differential growth control

The phytohormone abscisic acid (ABA) is a central regulator of acclimation to environmental stress; however, its contribution to differences in stress tolerance between species is unclear. To establish a comparative framework for understanding how stress hormone signalling pathways diverge across species, we studied the growth response of four Brassicaceae species to ABA treatment and generated transcriptomic and DNA affinity purification and sequencing datasets to construct a cross-species gene regulatory network (GRN) for ABA. Comparison of genes bound directly by ABA-responsive element binding factors suggests that cis-factors are most important for determining the target loci represented in the ABA GRN of a particular species. Using this GRN, we reveal how rewiring of growth hormone subnetworks contributes to stark differences in the response to ABA in the extremophyte Schrenkiella parvula. Our study provides a model for understanding how divergence in gene regulation can lead to species-specific physiological outcomes in response to hormonal cues.

The arm of the starfish: The far-reaching applications of Patiria miniata as a model system in evolutionary, developmental, and regenerative biology

Many species of echinoderms have long been considered model research organisms in biology. Historically, much of this research has focused on the embryology of sea urchins and the use of their extensive gene regulatory networks as a tool to understand how the genome controls cell state specification and patterning. The establishment of Patiria miniata, the bat sea star, as a research organism has allowed us to expand on the concepts explored with sea urchins, viewing these genetic networks through a comparative lens, gaining great insight into the evolutionary mechanisms that shape developmental diversity. Extensive molecular tools have been developed in P. miniata, designed to explore gene expression dynamics and build gene regulatory networks. Echinoderms also have a robust set of bioinformatic and computational resources, centered around echinobase.org, an extensive database containing multiomic, developmental, and experimental resources for researchers. In addition to comparative evolutionary development, P. miniata is a promising system in its own right for studying whole body regeneration, metamorphosis and body plan development, as well as marine disease.

Single-cell RNA sequencing of the Strongylocentrotus purpuratus larva reveals the blueprint of major cell types and nervous system of a non-chordate deuterostome

Identifying the molecular fingerprint of organismal cell types is key for understanding their function and evolution. Here, we use single-cell RNA sequencing (scRNA-seq) to survey the cell types of the sea urchin early pluteus larva, representing an important developmental transition from non-feeding to feeding larva. We identify 21 distinct cell clusters, representing cells of the digestive, skeletal, immune, and nervous systems. Further subclustering of these reveal a highly detailed portrait of cell diversity across the larva, including the identification of neuronal cell types. We then validate important gene regulatory networks driving sea urchin development and reveal new domains of activity within the larval body. Focusing on neurons that co-express Pdx-1 and Brn1/2/4, we identify an unprecedented number of genes shared by this population of neurons in sea urchin and vertebrate endocrine pancreatic cells. Using differential expression results from Pdx-1 knockdown experiments, we show that Pdx1 is necessary for the acquisition of the neuronal identity of these cells. We hypothesize that a network similar to the one orchestrated by Pdx1 in the sea urchin neurons was active in an ancestral cell type and then inherited by neuronal and pancreatic developmental lineages in sea urchins and vertebrates.

Biomolecule and Bioentity Interaction Databases in Systems Biology: A Comprehensive Review

Technological advances in high-throughput techniques have resulted in tremendous growth of complex biological datasets providing evidence regarding various biomolecular interactions. To cope with this data flood, computational approaches, web services, and databases have been implemented to deal with issues such as data integration, visualization, exploration, organization, scalability, and complexity. Nevertheless, as the number of such sets increases, it is becoming more and more difficult for an end user to know what the scope and focus of each repository is and how redundant the information between them is. Several repositories have a more general scope, while others focus on specialized aspects, such as specific organisms or biological systems. Unfortunately, many of these databases are self-contained or poorly documented and maintained. For a clearer view, in this article we provide a comprehensive categorization, comparison and evaluation of such repositories for different bioentity interaction types. We discuss most of the publicly available services based on their content, sources of information, data representation methods, user-friendliness, scope and interconnectivity, and we comment on their strengths and weaknesses. We aim for this review to reach a broad readership varying from biomedical beginners to experts and serve as a reference article in the field of Network Biology.

Familiarity Breeds Strategy: In Silico Untangling of the Molecular Complexity on Course of Autoimmune Liver Disease-to-Hepatocellular Carcinoma Transition Predicts Novel Transcriptional Signatures

Autoimmune liver diseases (AILD) often lead to transformation of the liver tissues into hepatocellular carcinoma (HCC). Considering the drawbacks of surgical procedures in such cases, need of successful non-invasive therapeutic strategies and treatment modalities for AILD-associated-HCC still exists. Due to the lack of clear, sufficient knowledge about factors mediating AILD-to-HCC transition, an in silico approach was adopted to delineate the underlying molecular deterministic factors. Parallel enrichment analyses on two different public microarray datasets (GSE159676 and GSE62232) pinpointed the core transcriptional regulators as key players. Correlation between the expression kinetics of these transcriptional modules in AILD and HCC was found to be positive primarily with the advancement of hepatic fibrosis. Most of the regulatory interactions were operative during early (F0-F1) and intermediate fibrotic stages (F2-F3), while the extent of activity in the regulatory network considerably diminished at late stage of fibrosis/cirrhosis (F4). Additionally, most of the transcriptional targets with higher degrees of connectivity in the regulatory network (namely DCAF11, PKM2, DGAT2 and BCAT1) may be considered as potential candidates for biomarkers or clinical targets compared to their low-connectivity counterparts. In summary, this study uncovers new possibilities in the designing of novel prognostic and therapeutic regimen for autoimmunity-associated malignancy of liver in a disease progression-dependent fashion.

Tools for time-course simulation in systems biology: a brief overview

Dynamic modeling of biological systems is essential for understanding all properties of a given organism as it allows us to look not only at the static picture of an organism but also at its behavior under various conditions. With the increasing amount of experimental data, the number of tools that enable dynamic analysis also grows. However, various tools are based on different approaches, use different types of data and offer different functions for analyses; so it can be difficult to choose the most suitable tool for a selected type of model. Here, we bring a brief overview containing descriptions of 50 tools for the reconstruction of biological models, their time-course simulation and dynamic analysis. We examined each tool using test data and divided them based on the qualitative and quantitative nature of the mathematical apparatus they use.

A generalizable data-driven multicellular model of pancreatic ductal adenocarcinoma

BACKGROUND

Mechanistic models, when combined with pertinent data, can improve our knowledge regarding important molecular and cellular mechanisms found in cancer. These models make the prediction of tissue-level response to drug treatment possible, which can lead to new therapies and improved patient outcomes. Here we present a data-driven multiscale modeling framework to study molecular interactions between cancer, stromal, and immune cells found in the tumor microenvironment. We also develop methods to use molecular data available in The Cancer Genome Atlas to generate sample-specific models of cancer.

RESULTS

By combining published models of different cells relevant to pancreatic ductal adenocarcinoma (PDAC), we built an agent-based model of the multicellular pancreatic tumor microenvironment, formally describing cell type-specific molecular interactions and cytokine-mediated cell-cell communications. We used an ensemble-based modeling approach to systematically explore how variations in the tumor microenvironment affect the viability of cancer cells. The results suggest that the autocrine loop involving EGF signaling is a key interaction modulator between pancreatic cancer and stellate cells. EGF is also found to be associated with previously described subtypes of PDAC. Moreover, the model allows a systematic exploration of the effect of possible therapeutic perturbations; our simulations suggest that reducing bFGF secretion by stellate cells will have, on average, a positive impact on cancer apoptosis.

CONCLUSIONS

The developed framework allows model-driven hypotheses to be generated regarding therapeutically relevant PDAC states with potential molecular and cellular drivers indicating specific intervention strategies.

A Guide to Conquer the Biological Network Era Using Graph Theory

Networks are one of the most common ways to represent biological systems as complex sets of binary interactions or relations between different bioentities. In this article, we discuss the basic graph theory concepts and the various graph types, as well as the available data structures for storing and reading graphs. In addition, we describe several network properties and we highlight some of the widely used network topological features. We briefly mention the network patterns, motifs and models, and we further comment on the types of biological and biomedical networks along with their corresponding computer- and human-readable file formats. Finally, we discuss a variety of algorithms and metrics for network analyses regarding graph drawing, clustering, visualization, link prediction, perturbation, and network alignment as well as the current state-of-the-art tools. We expect this review to reach a very broad spectrum of readers varying from experts to beginners while encouraging them to enhance the field further.

How Does the Regulatory Genome Work?

The regulatory genome controls genome activity throughout the life of an organism. This requires that complex information processing functions are encoded in, and operated by, the regulatory genome. Although much remains to be learned about how the regulatory genome works, we here discuss two cases where regulatory functions have been experimentally dissected in great detail and at the systems level, and formalized by computational logic models. Both examples derive from the sea urchin embryo, but assess two distinct organizational levels of genomic information processing. The first example shows how the regulatory system of a single gene, endo16, executes logic operations through individual transcription factor binding sites and cis-regulatory modules that control the expression of this gene. The second example shows information processing at the gene regulatory network (GRN) level. The GRN controlling development of the sea urchin endomesoderm has been experimentally explored at an almost complete level. A Boolean logic model of this GRN suggests that the modular logic functions encoded at the single-gene level show compositionality and suffice to account for integrated function at the network level. We discuss these examples both from a biological-experimental point of view and from a computer science-informational point of view, as both illuminate principles of how the regulatory genome works.

Developmental effector gene regulation: Multiplexed strategies for functional analysis

The staggering complexity of the genome controls for developmental processes is revealed through massively parallel cis-regulatory analysis using new methods of perturbation and readout. The choice of combinations of these new methods is tailored to the system, question and resources at hand. Our focus is on issues that include the necessity or sufficiency of given cis-regulatory modules, cis-regulatory function in the normal spatial genomic context, and easily accessible high throughput and multiplexed analysis methods. In the sea urchin embryonic model, recombineered BACs offer new opportunities for consecutive modes of cis-regulatory analyses that answer these requirements, as we here demonstrate on a diverse suite of previously unstudied sea urchin effector genes expressed in skeletogenic cells. Positively active cis-regulatory modules were located in single Nanostring experiments per BAC containing the gene of interest, by application of our previously reported "barcode" tag vectors of which> 100 can be analyzed at one time. Computational analysis of DNA sequences that drive expression, based on the known skeletogenic regulatory state, then permitted effective identification of functional target site clusters. Deletion of these sub-regions from the parent BACs revealed module necessity, as simultaneous tests of the same regions in short constructs revealed sufficiency. Predicted functional inputs were then confirmed by site mutations, all generated and tested in multiplex formats. There emerged the simple conclusion that each effector gene utilizes a small subset of inputs from the skeletogenic GRN. These inputs may function to only adjust expression levels or in some cases necessary for expression. Since we know the GRN architecture upstream of the effector genes, we could then conceptually isolate and compare the wiring of the effector gene driver sub-circuits and identify the inputs whose removal abolish expression.

Using ATAC-seq and RNA-seq to increase resolution in GRN connectivity

Echinoderms have some of the most complete reconstructed developmental gene regulatory networks (GRN) of any embryo, accounting for the formation of most embryo tissues and organs. Yet, many nodes (genes and regulators) and their regulatory interactions are still to be uncovered. Traditionally, knockdown/knockout experiments are performed to determine regulator-gene interactions, which are individually validated by cis-regulatory analysis. Differential RNA-seq, combined with perturbation analysis, allows for genome-wide reconstruction of a GRN around given regulators; however, this level of resolution cannot determine direct interactions. ChiP-chip or ChIP-seq is better equipped for determining, genome-wide, whether binding of a given transcription factor (TF) to cis-regulatory elements occurs. Antibodies for the TFs of interest must be available, and if not, this presents a limiting factor. ATAC-seq identifies regions of open chromatin, that are typically trimethylated at H3K4, H3K36 and H3K79 (Kouzarides, 2007), for a given time point, condition, or tissue. This technology combined with RNA-seq and perturbation analysis provides high resolution of the possible functional interactions occurring during development. Additionally, ATAC-seq is less expensive than ChIP-seq, requires less starting material, and provides a global view of regulatory regions. This chapter provides detailed steps to identify potential regulatory relationships between the nodes of a GRN, given a well assembled genome, annotated with gene models, and ATAC-seq data combined with RNA-seq and knockdown experiments.

Conserved regulatory state expression controlled by divergent developmental gene regulatory networks in echinoids

Evolution of the animal body plan is driven by changes in developmental gene regulatory networks (GRNs), but how networks change to control novel developmental phenotypes remains, in most cases, unresolved. Here, we address GRN evolution by comparing the endomesoderm GRN in two echinoid sea urchins, Strongylocentrotus purpuratus and Eucidaris tribuloides, with at least 268 million years of independent evolution. We first analyzed the expression of twelve transcription factors and signaling molecules of the S. purpuratus GRN in E. tribuloides embryos, showing that orthologous regulatory genes are expressed in corresponding endomesodermal cell fates in the two species. However, perturbation of regulatory genes revealed that important regulatory circuits of the S. purpuratus GRN are significantly different in E. tribuloides For example, mesodermal Delta/Notch signaling controls exclusion of alternative cell fates in E. tribuloides but controls mesoderm induction and activation of a positive feedback circuit in S. purpuratus These results indicate that the architecture of the sea urchin endomesoderm GRN evolved by extensive gain and loss of regulatory interactions between a conserved set of regulatory factors that control endomesodermal cell fate specification.

Methods for the experimental and computational analysis of gene regulatory networks in sea urchins

The discovery of gene regulatory networks (GRNs) has opened a gate to access the genomic mechanisms controlling development. GRNs are systems of transcriptional regulatory circuits that control the differential specification of cell fates during development by regulating gene expression. The experimental analysis of GRNs involves a collection of methods, each revealing aspects of the overall control process. This review provides an overview of experimental and computational methods that have been successfully applied for solving developmental GRNs in the sea urchin embryo. The key in this approach is to obtain experimental evidence for functional interactions between transcription factors and regulatory DNA. In the second part of this review, a more generally applicable strategy is discussed that shows a path from experimental evidence to annotation of regulatory linkages to the generation of GRN models.

Ectomesoderm and epithelial-mesenchymal transition-related genes in spiralian development

BACKGROUND

Spiralians (e.g., annelids, molluscs, and flatworms) possess two sources of mesoderm. One is from endodermal precursors (endomesoderm), which is considered to be the ancestral source in metazoans. The second is from ectoderm (ectomesoderm) and may represent a novel cell type in the Spiralia. In the mollusc Crepidula fornicata, ectomesoderm is derived from micromere daughters within the A and B cell quadrants. Their progeny lie along the anterolateral edges of the blastopore. There they undergo epithelial-mesenchymal transition (EMT), become rounded and undergo delamination/ingression. Subsequently, they assume the mesenchymal phenotype, and migrate beneath the surface ectoderm to differentiate various cell types, including muscles and pigment cells.

RESULTS

We examined expression of several genes whose homologs are known to regulate Type 1 EMT in other metazoans. Most of these genes were expressed within spiralian ectomesoderm during EMT.

CONCLUSIONS

We propose that spiralian ectomesoderm, which exhibits analogous cellular behaviors to other populations of mesenchymal cells, may be controlled by the same genes that drive EMT in other metazoans. Perhaps these genes comprise a conserved metazoan EMT gene regulatory network (GRN). This study represents the first step in elucidating the GRN controlling the development of a novel spiralian cell type (ectomesoderm). Developmental Dynamics 247:1097-1120, 2018. © 2018 Wiley Periodicals, Inc.

Regulatory states in the developmental control of gene expression

A growing body of evidence shows that gene expression in multicellular organisms is controlled by the combinatorial function of multiple transcription factors. This indicates that not the individual transcription factors or signaling molecules, but the combination of expressed regulatory molecules, the regulatory state, should be viewed as the functional unit in gene regulation. Here, I discuss the concept of the regulatory state and its proposed role in the genome-wide control of gene expression. Recent analyses of regulatory gene expression in sea urchin embryos have been instrumental for solving the genomic control of cell fate specification in this system. Some of the approaches that were used to determine the expression of regulatory states during sea urchin embryogenesis are reviewed. Significant developmental changes in regulatory state expression leading to the distinct specification of cell fates are regulated by gene regulatory network circuits. How these regulatory state transitions are encoded in the genome is illuminated using the sea urchin endoderm-mesoderms cell fate decision circuit as an example. These observations highlight the importance of considering developmental gene regulation, and the function of individual transcription factors, in the context of regulatory states.

Omics approaches to study gene regulatory networks for development in echinoderms

Gene regulatory networks (GRNs) describe the interactions for a developmental process at a given time and space. Historically, perturbation experiments represent one of the key methods for analyzing and reconstructing a GRN, and the GRN governing early development in the sea urchin embryo stands as one of the more deeply dissected so far. As technology progresses, so do the methods used to address different biological questions. Next-generation sequencing (NGS) has become a standard experimental technique for genome and transcriptome sequencing and studies of protein-DNA interactions and DNA accessibility. While several efforts have been made toward the integration of different omics approaches for the study of the regulatory genome in many animals, in a few cases, these are applied with the purpose of reconstructing and experimentally testing developmental GRNs. Here, we review emerging approaches integrating multiple NGS technologies for the prediction and validation of gene interactions within echinoderm GRNs. These approaches can be applied to both 'model' and 'non-model' organisms. Although a number of issues still need to be addressed, advances in NGS applications, such as assay for transposase-accessible chromatin sequencing, combined with the availability of embryos belonging to different species, all separated by various evolutionary distances and accessible to experimental regulatory biology, place echinoderms in an unprecedented position for the reconstruction and evolutionary comparison of developmental GRNs. We conclude that sequencing technologies and integrated omics approaches allow the examination of GRNs on a genome-wide scale only if biological perturbation and cis-regulatory analyses are experimentally accessible, as in the case of echinoderm embryos.

Dynamic changes in Sox2 spatio-temporal expression promote the second cell fate decision through Fgf4/Fgfr2 signaling in preimplantation mouse embryos

Oct4 and Sox2 regulate the expression of target genes such as Nanog, Fgf4, and Utf1, by binding to their respective regulatory motifs. Their functional cooperation is reflected in their ability to heterodimerize on adjacent cis regulatory motifs, the composite Sox/Oct motif. Given that Oct4 and Sox2 regulate many developmental genes, a quantitative analysis of their synergistic action on different Sox/Oct motifs would yield valuable insights into the mechanisms of early embryonic development. In the present study, we measured binding affinities of Oct4 and Sox2 to different Sox/Oct motifs using fluorescence correlation spectroscopy. We found that the synergistic binding interaction is driven mainly by the level of Sox2 in the case of the Fgf4 Sox/Oct motif. Taking into account Sox2 expression levels fluctuate more than Oct4, our finding provides an explanation on how Sox2 controls the segregation of the epiblast and primitive endoderm populations within the inner cell mass of the developing rodent blastocyst.

ViSiBooL-visualization and simulation of Boolean networks with temporal constraints

Summary

Mathematical models and their simulation are increasingly used to gain insights into cellular pathways and regulatory networks. Dynamics of regulatory factors can be modeled using Boolean networks (BNs), among others. Text-based representations of models are precise descriptions, but hard to understand and interpret. ViSiBooL aims at providing a graphical way of modeling and simulating networks. By providing visualizations of static and dynamic network properties simultaneously, it is possible to directly observe the effects of changes in the network structure on the behavior. In order to address the challenges of clear design and a user-friendly graphical user interface (GUI), ViSiBooL implements visual representations of BNs. Additionally temporal extensions of the BNs for the modeling of regulatory time delays are incorporated. The GUI of ViSiBooL allows to model, organize, simulate and visualize BNs as well as corresponding simulation results such as attractors. Attractor searches are performed in parallel to the modeling process. Hence, changes in the network behavior are visualized at the same time.

Availability and Implementation

ViSiBooL (Java 8) is freely available at http://sysbio.uni-ulm.de/?Software:ViSiBooL .

Contact

hans.kestler@uni-ulm.de.

Thyroid Hormones Accelerate Initiation of Skeletogenesis via MAPK (ERK1/2) in Larval Sea Urchins (Strongylocentrotus purpuratus)

Thyroid hormones are important regulators of development and metabolism in animals. Their function via genomic and non-genomic actions is well-established in vertebrate species but remains largely elusive among invertebrates. Previous work suggests that thyroid hormones, principally 3,5,3',5'-Tetraiodo-L-thyronine (T4), regulate development to metamorphosis in sea urchins. Here we show that thyroid hormones, including T4, 3,5,3'-triiodo-l-thyronine (T3), and 3,5-Diiodothyronine (T2) accelerate initiation of skeletogenesis in sea urchin gastrulae and pluteus larvae of the sea urchin Strongylocentrotus purpuratus, as measured by skeletal spicule formation. Fluorescently conjugated hormones show T4 binding to primary mesenchyme cells in sea urchin gastrulae. Furthermore, our investigation of TH mediated skeletogenesis shows that Ets1, a transcription factor controlling initiation of skeletogenesis, is a target of activated (phosphorylated) mitogen-activated protein kinase [MAPK; extracellular signal-regulated kinase 1/2 (ERK1/2)]. As well, we show that PD98059, an inhibitor of ERK1/2 MAPK signaling, prevents the T4 mediated acceleration of skeletogenesis and upregulation of Ets1. In contrast, SB203580, an inhibitor of p38 MAPK signaling, did not inhibit the effect of T4. Immunohistochemistry revealed that T4 causes phosphorylation of ERK1/2 in presumptive primary mesenchyme cells and the basal membrane of epithelial cells in the gastrula. Pre-incubation of sea urchin gastrulae with RGD peptide, a competitive inhibitor of TH binding to integrins, inhibited the effect of T4 on skeletogenesis. Together, these experiments provide evidence that T4 acts via a MAPK- (ERK1/2) mediated integrin membrane receptor to accelerate skeletogenesis in sea urchin mesenchyme cells. These findings shed light, for the first time, on a putative non-genomic pathway of TH action in a non-chordate deuterostome and help elucidate the evolutionary history of TH signaling in animals.

Activation of a T-box-Otx2-Gsc gene network independent of TBP and TBP-related factors

Embryonic development relies on activating and repressing regulatory influences that are faithfully integrated at the core promoter of individual genes. In vertebrates, the basal machinery recognizing the core promoter includes TATA-binding protein (TBP) and two TBP-related factors. In Xenopus embryos, the three TBP family factors are all essential for development and are required for expression of distinct subsets of genes. Here, we report on a non-canonical TBP family-insensitive (TFI) mechanism of transcription initiation that involves mesoderm and organizer gene expression. Using TBP family single- and triple-knockdown experiments, α-amanitin treatment, transcriptome profiling and chromatin immunoprecipitation, we found that TFI gene expression cannot be explained by functional redundancy, is supported by active transcription and shows normal recruitment of the initiating form of RNA polymerase II to the promoter. Strikingly, recruitment of Gcn5 (also known as Kat2a), a co-activator that has been implicated in transcription initiation, to TFI gene promoters is increased upon depletion of TBP family factors. TFI genes are part of a densely connected TBP family-insensitive T-box-Otx2-Gsc interaction network. The results indicate that this network of genes bound by Vegt, Eomes, Otx2 and Gsc utilizes a novel, flexible and non-canonical mechanism of transcription that does not require TBP or TBP-related factors.

Highlighted article: A network of embryonic genes, many of which are expressed in the mesoderm and the organiser, can initiate transcription through a non-canonical mechanism.

Photoreceptor cell fate specification in vertebrates

Photoreceptors--the light-sensitive cells in the vertebrate retina--have been extremely well-characterized with regards to their biochemistry, cell biology and physiology. They therefore provide an excellent model for exploring the factors and mechanisms that drive neural progenitors into a differentiated cell fate in the nervous system. As a result, great progress in understanding the transcriptional network that controls photoreceptor specification and differentiation has been made over the last 20 years. This progress has also enabled the production of photoreceptors from pluripotent stem cells, thereby aiding the development of regenerative medical approaches to eye disease. In this Review, we outline the signaling and transcription factors that drive vertebrate photoreceptor development and discuss how these function together in gene regulatory networks to control photoreceptor cell fate specification.

NetworkPainter: dynamic intracellular pathway animation in Cytobank

BACKGROUND

High-throughput technologies such as flow and mass cytometry have the potential to illuminate cellular networks. However, analyzing the data produced by these technologies is challenging. Visualization is needed to help researchers explore this data.

RESULTS

We developed a web-based software program, NetworkPainter, to enable researchers to analyze dynamic cytometry data in the context of pathway diagrams. NetworkPainter provides researchers a graphical interface to draw and "paint" pathway diagrams with experimental data, producing animated diagrams which display the activity of each network node at each time point.

CONCLUSION

NetworkPainter enables researchers to more fully explore multi-parameter, dynamical cytometry data.

Systems biology approaches to defining transcription regulatory networks in halophilic archaea

To survive complex and changing environmental conditions, microorganisms use gene regulatory networks (GRNs) composed of interacting regulatory transcription factors (TFs) to control the timing and magnitude of gene expression. Genome-wide datasets; such as transcriptomics and protein-DNA interactions; and experiments such as high throughput growth curves; facilitate the construction of GRNs and provide insight into TF interactions occurring under stress. Systems biology approaches integrate these datasets into models of GRN architecture as well as statistical and/or dynamical models to understand the function of networks occurring in cells. Previously, these types of studies have focused on traditional model organisms (e.g. Escherichia coli, yeast). However, recent advances in archaeal genetics and other tools have enabled a systems approach to understanding GRNs in these relatively less studied archaeal model organisms. In this report, we outline a systems biology workflow for generating and integrating data focusing on the TF regulator. We discuss experimental design, outline the process of data collection, and provide the tools required to produce high confidence regulons for the TFs of interest. We provide a case study as an example of this workflow, describing the construction of a GRN centered on multi-TF coordinate control of gene expression governing the oxidative stress response in the hypersaline-adapted archaeon Halobacterium salinarum.

HES5 silencing is an early and recurrent change in prostate tumourigenesis

Prostate cancer is the most common cancer in men, resulting in over 10 000 deaths/year in the UK. Sequencing and copy number analysis of primary tumours has revealed heterogeneity within tumours and an absence of recurrent founder mutations, consistent with non-genetic disease initiating events. Using methylation profiling in a series of multi-focal prostate tumours, we identify promoter methylation of the transcription factor HES5 as an early event in prostate tumourigenesis. We confirm that this epigenetic alteration occurs in 86-97% of cases in two independent prostate cancer cohorts (n=49 and n=39 tumour-normal pairs). Treatment of prostate cancer cells with the demethylating agent 5-aza-2'-deoxycytidine increased HES5 expression and downregulated its transcriptional target HES6, consistent with functional silencing of the HES5 gene in prostate cancer. Finally, we identify and test a transcriptional module involving the AR, ERG, HES1 and HES6 and propose a model for the impact of HES5 silencing on tumourigenesis as a starting point for future functional studies.

Dose-dependent nuclear β-catenin response segregates endomesoderm along the sea star primary axis

In many invertebrates, the nuclearization of β-catenin at one pole of the embryo initiates endomesoderm specification. An intriguing possibility is that a gradient of nuclear β-catenin (nβ-catenin), similar to that operating in vertebrate neural tube patterning, functions to distinguish cell fates in invertebrates. To test this hypothesis, we determined the function of nβ-catenin during the early development of the sea star, which undergoes a basal deuterostomal mode of embryogenesis. We show that low levels of nβ-catenin activity initiate bra, which is expressed in the future posterior endoderm-fated territory; intermediate levels are required for expression of foxa and gata4/5/6, which are later restricted to the endoderm; and activation of ets1 and erg in the mesoderm-fated territory requires the highest nβ-catenin activity. Transcription factors acting downstream of high nβ-catenin segregate the endoderm/mesoderm boundary, which is further reinforced by Delta/Notch signaling. Significantly, therefore, in sea stars, endomesoderm segregation arises through transcriptional responses to levels of nβ-catenin activity. Here, we describe the first empirical evidence of a dose-dependent response to a dynamic spatiotemporal nβ-catenin activity that patterns cell fates along the primary axis in an invertebrate.

Geometric control of ciliated band regulatory states in the sea urchin embryo

The trapezoidal ciliated band (CB) of the postgastrular sea urchin embryo surrounds the oral ectoderm, separating it from adjacent embryonic territories. Once differentiated, the CB is composed of densely arranged cells bearing long cilia that endow the larva with locomotion and feeding capability. The spatial pattern from which the CB will arise is first evidenced during pregastrular stages by expression of the pioneer gene onecut. Immediately after gastrulation, the CB consists of four separate regulatory state domains, each of which expresses a unique set of transcription factors: (1) the oral apical CB, located within the apical neurogenic field; (2) the animal lateral CB, which bilaterally separates the oral from aboral ectoderm; (3) the vegetal lateral CB, which bilaterally serves as signaling centers; and (4) the vegetal oral CB, which delineates the boundary with the underlying endoderm. Remarkably, almost all of the regulatory genes specifically expressed within these domains are downregulated by interference with SoxB1 expression, implying their common activation by this factor. Here, we show how the boundaries of the CB subdomains are established, and thus ascertain the design principle by which the geometry of this unique and complex regulatory state pattern is genomically controlled. Each of these boundaries, on either side of the CB, is defined by spatially confined transcriptional repressors, the products of regulatory genes operating across the border of each subdomain. In total this requires deployment of about ten different repressors, which we identify in this work, thus exemplifying the complexity of information required for spatial regulatory organization during embryogenesis.

A regulatory hierarchy controls the dynamic transcriptional response to extreme oxidative stress in archaea

Networks of interacting transcription factors are central to the regulation of cellular responses to abiotic stress. Although the architecture of many such networks has been mapped, their dynamic function remains unclear. Here we address this challenge in archaea, microorganisms possessing transcription factors that resemble those of both eukaryotes and bacteria. Using genome-wide DNA binding location analysis integrated with gene expression and cell physiological data, we demonstrate that a bacterial-type transcription factor (TF), called RosR, and five TFIIB proteins, homologs of eukaryotic TFs, combinatorially regulate over 100 target genes important for the response to extremely high levels of peroxide. These genes include 20 other transcription factors and oxidative damage repair genes. RosR promoter occupancy is surprisingly dynamic, with the pattern of target gene expression during the transition from rapid growth to stress correlating strongly with the pattern of dynamic binding. We conclude that a hierarchical regulatory network orchestrated by TFs of hybrid lineage enables dynamic response and survival under extreme stress in archaea. This raises questions regarding the evolutionary trajectory of gene networks in response to stress.

Complex circuits of genes rather than a single gene underlie many important processes such as disease, development, and cellular damage repair. Although the wiring of many of these circuits has been mapped, how circuits operate in real time to carry out their functions is poorly understood. Here we address these questions by investigating the function of a gene circuit that responds to reactive oxygen species damage in archaea, microorganisms that represent the third domain of life. Members of this domain of life are excellent models for investigating the function and evolution of gene circuits. Components of archaeal regulatory machinery driving gene circuits resemble those of both bacteria and eukaryotes. Here we demonstrate that regulatory proteins of hybrid ancestry collaborate to control the expression of over 100 genes whose products repair cellular damage. Among these are other regulatory proteins, setting up a stepwise hierarchical circuit that controls damage repair. Regulation is dynamic, with gene targets showing immediate response to damage and restoring normal cellular functions soon thereafter. This study demonstrates how strong environmental forces such as stress may have shaped the wiring and dynamic function of gene circuits, raising important questions regarding how circuits originated over evolutionary time.

Genome scale modeling in systems biology: algorithms and resources

In recent years, in silico studies and trial simulations have complemented experimental procedures. A model is a description of a system, and a system is any collection of interrelated objects; an object, moreover, is some elemental unit upon which observations can be made but whose internal structure either does not exist or is ignored. Therefore, any network analysis approach is critical for successful quantitative modeling of biological systems. This review highlights some of most popular and important modeling algorithms, tools, and emerging standards for representing, simulating and analyzing cellular networks in five sections. Also, we try to show these concepts by means of simple example and proper images and graphs. Overall, systems biology aims for a holistic description and understanding of biological processes by an integration of analytical experimental approaches along with synthetic computational models. In fact, biological networks have been developed as a platform for integrating information from high to low-throughput experiments for the analysis of biological systems. We provide an overview of all processes used in modeling and simulating biological networks in such a way that they can become easily understandable for researchers with both biological and mathematical backgrounds. Consequently, given the complexity of generated experimental data and cellular networks, it is no surprise that researchers have turned to computer simulation and the development of more theory-based approaches to augment and assist in the development of a fully quantitative understanding of cellular dynamics.

Modeling genomic regulatory networks with big data

High-throughput sequencing, large-scale data generation projects, and web-based cloud computing are changing how computational biology is performed, who performs it, and what biological insights it can deliver. I review here the latest developments in available data, methods, and software, focusing on the modeling and analysis of the gene regulatory interactions in cells. Three key findings are: (i) although sophisticated computational resources are increasingly available to bench biologists, tailored ongoing education is necessary to avoid the erroneous use of these resources. (ii) Current models of the regulation of gene expression are far too simplistic and need updating. (iii) Integrative computational analysis of large-scale datasets is becoming a fundamental component of molecular biology. I discuss current and near-term opportunities and challenges related to these three points.

General approach for in vivo recovery of cell type-specific effector gene sets

Differentially expressed, cell type-specific effector gene sets hold the key to multiple important problems in biology, from theoretical aspects of developmental gene regulatory networks (GRNs) to various practical applications. Although individual cell types of interest have been recovered by various methods and analyzed, systematic recovery of multiple cell type-specific gene sets from whole developing organisms has remained problematic. Here we describe a general methodology using the sea urchin embryo, a material of choice because of the large-scale GRNs already solved for this model system. This method utilizes the regulatory states expressed by given cells of the embryo to define cell type and includes a fluorescence activated cell sorting (FACS) procedure that results in no perturbation of transcript representation. We have extensively validated the method by spatial and qualitative analyses of the transcriptome expressed in isolated embryonic skeletogenic cells and as a consequence, generated a prototypical cell type-specific transcriptome database.

A time delay gene circuit is required for palp formation in the ascidian embryo

The ascidian larval brain and palps (a putative rudimentary placode) are specified by two transcription factor genes, ZicL and FoxC, respectively. FGF9/16/20 induces ZicL expression soon after the bi-potential ancestral cells divide into the brain and palp precursors at the early gastrula stage. FGF9/16/20 begins to be expressed at the 16-cell stage, and induces several target genes, including Otx, before the gastrula stage. Here, we show that ZicL expression in the brain lineage is transcriptionally repressed by Hes-a and two Blimp-1-like zinc finger proteins, BZ1 and BZ2, in the bi-potential ancestral cells. ZicL is precociously expressed in the bi-potential cells in embryos in which these repressors are knocked down. This precocious ZicL expression produces extra brain cells at the expense of palp cells. The expression of BZ1 and BZ2 is turned off by a negative auto-feedback loop. This auto-repression acts as a delay circuit that prevents ZicL from being expressed precociously before the brain and palp fates split, thereby making room within the neural plate for the palps to be specified. Addition of the BZ1/2 delay timer circuit to the gene regulatory network responsible for brain formation might represent a key event in the acquisition of the primitive palps/placodes in an ancestral animal.

PhenoTimer: software for the visual mapping of time-resolved phenotypic landscapes

Timing common and specific modulators of disease progression is crucial for treatment, but the understanding of the underlying complex system of interactions is limited. While attempts at elucidating this experimentally have produced enormous amounts of phenotypic data, tools that are able to visualize and analyze them are scarce and the insight obtained from the data is often unsatisfactory. Linking and visualizing processes from genes to phenotypes and back, in a temporal context, remains a challenge in systems biology. We introduce PhenoTimer, a 2D/3D visualization tool for the mapping of time-resolved phenotypic links in a genetic context. It uses a novel visualization approach for relations between morphological defects, pathways or diseases, to enable fast pattern discovery and hypothesis generation. We illustrate its capabilities of tracing dynamic motifs on cell cycle datasets that explore the phenotypic order of events upon perturbations of the system, transcriptional activity programs and their connection to disease. By using this tool we are able to fine-grain regulatory programs for individual time points of the cell cycle and better understand which patterns arise when these programs fail. We also illustrate a way to identify common mechanisms of misregulation in diseases and drug abuse.

Structure and dynamics of molecular networks: a novel paradigm of drug discovery: a comprehensive review

Despite considerable progress in genome- and proteome-based high-throughput screening methods and in rational drug design, the increase in approved drugs in the past decade did not match the increase of drug development costs. Network description and analysis not only give a systems-level understanding of drug action and disease complexity, but can also help to improve the efficiency of drug design. We give a comprehensive assessment of the analytical tools of network topology and dynamics. The state-of-the-art use of chemical similarity, protein structure, protein-protein interaction, signaling, genetic interaction and metabolic networks in the discovery of drug targets is summarized. We propose that network targeting follows two basic strategies. The "central hit strategy" selectively targets central nodes/edges of the flexible networks of infectious agents or cancer cells to kill them. The "network influence strategy" works against other diseases, where an efficient reconfiguration of rigid networks needs to be achieved by targeting the neighbors of central nodes/edges. It is shown how network techniques can help in the identification of single-target, edgetic, multi-target and allo-network drug target candidates. We review the recent boom in network methods helping hit identification, lead selection optimizing drug efficacy, as well as minimizing side-effects and drug toxicity. Successful network-based drug development strategies are shown through the examples of infections, cancer, metabolic diseases, neurodegenerative diseases and aging. Summarizing >1200 references we suggest an optimized protocol of network-aided drug development, and provide a list of systems-level hallmarks of drug quality. Finally, we highlight network-related drug development trends helping to achieve these hallmarks by a cohesive, global approach.

Visualizing time-related data in biology, a review

Time is of the essence in biology as in so much else. For example, monitoring disease progression or the timing of developmental defects is important for the processes of drug discovery and therapy trials. Furthermore, an understanding of the basic dynamics of biological phenomena that are often strictly time regulated (e.g. circadian rhythms) is needed to make accurate inferences about the evolution of biological processes. Recent advances in technologies have enabled us to measure timing effects more accurately and in more detail. This has driven related advances in visualization and analysis tools that try to effectively exploit this data. Beyond timeline plots, notable attempts at more involved temporal interpretation have been made in recent years, but awareness of the available resources is still limited within the scientific community. Here, we review some advances in biological visualization of time-driven processes and consider how they aid data analysis and interpretation.

Visual data mining of biological networks: one size does not fit all

High-throughput technologies produce massive amounts of data. However, individual methods yield data specific to the technique used and biological setup. The integration of such diverse data is necessary for the qualitative analysis of information relevant to hypotheses or discoveries. It is often useful to integrate these datasets using pathways and protein interaction networks to get a broader view of the experiment. The resulting network needs to be able to focus on either the large-scale picture or on the more detailed small-scale subsets, depending on the research question and goals. In this tutorial, we illustrate a workflow useful to integrate, analyze, and visualize data from different sources, and highlight important features of tools to support such analyses.

Initial deployment of the cardiogenic gene regulatory network in the basal chordate, Ciona intestinalis

The complex, partially redundant gene regulatory architecture underlying vertebrate heart formation has been difficult to characterize. Here, we dissect the primary cardiac gene regulatory network in the invertebrate chordate, Ciona intestinalis. The Ciona heart progenitor lineage is first specified by Fibroblast Growth Factor/Map Kinase (FGF/MapK) activation of the transcription factor Ets1/2 (Ets). Through microarray analysis of sorted heart progenitor cells, we identified the complete set of primary genes upregulated by FGF/Ets shortly after heart progenitor emergence. Combinatorial sequence analysis of these co-regulated genes generated a hypothetical regulatory code consisting of Ets binding sites associated with a specific co-motif, ATTA. Through extensive reporter analysis, we confirmed the functional importance of the ATTA co-motif in primary heart progenitor gene regulation. We then used the Ets/ATTA combination motif to successfully predict a number of additional heart progenitor gene regulatory elements, including an intronic element driving expression of the core conserved cardiac transcription factor, GATAa. This work significantly advances our understanding of the Ciona heart gene network. Furthermore, this work has begun to elucidate the precise regulatory architecture underlying the conserved, primary role of FGF/Ets in chordate heart lineage specification.