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Systems biology has experienced dramatic growth in the number, size, and complexity of computational models. To reproduce simulation results and reuse models, researchers must exchange unambiguous model descriptions. We review the latest edition of the Systems Biology Markup Language (SBML), a format designed for this purpose. A community of modelers and software authors developed SBML Level 3 over the past decade. Its modular form consists of a core suited to representing reaction-based models and packages that extend the core with features suited to other model types including constraint-based models, reaction-diffusion models, logical network models, and rule-based models. The format leverages two decades of SBML and a rich software ecosystem that transformed how systems biologists build and interact with models. More recently, the rise of multiscale models of whole cells and organs, and new data sources such as single-cell measurements and live imaging, has precipitated new ways of integrating data with models. We provide our perspectives on the challenges presented by these developments and how SBML Level 3 provides the foundation needed to support this evolution.

We present the molecular landscape of pediatric acute myeloid leukemia (AML) and characterize nearly 1,000 participants in Children's Oncology Group (COG) AML trials. The COG-National Cancer Institute (NCI) TARGET AML initiative assessed cases by whole-genome, targeted DNA, mRNA and microRNA sequencing and CpG methylation profiling. Validated DNA variants corresponded to diverse, infrequent mutations, with fewer than 40 genes mutated in [greater than] 2% of cases. In contrast, somatic structural variants, including new gene fusions and focal deletions of MBNL1, ZEB2 and ELF1, were disproportionately prevalent in young individuals as compared to adults. Conversely, mutations in DNMT3A and TP53, which were common in adults, were conspicuously absent from virtually all pediatric cases. New mutations in GATA2, FLT3 and CBL and recurrent mutations in MYC-ITD, NRAS, KRAS and WT1 were frequent in pediatric AML. Deletions, mutations and promoter DNA hypermethylation convergently impacted Wnt signaling, Polycomb repression, innate immune cell interactions and a cluster of zinc finger-encoding genes associated with KMT2A rearrangements. These results highlight the need for and facilitate the development of age-tailored targeted therapies for the treatment of pediatric AML., Author(s): Hamid Bolouri (corresponding author) [1]; Jason E Farrar [2]; Timothy Triche, Jr [3]; Rhonda E Ries [4]; Emilia L Lim [5]; Todd A Alonzo [6, 7]; Yussanne Ma [5]; [...]

BACKGROUND. Despite a rapidly growing body of literature on coronavirus disease 2019 (COVID-19), our understanding of the immune correlates of disease severity, course, and outcome remains poor. METHODS. Using mass cytometry, we assessed the immune landscape in longitudinal whole-blood specimens from 59 patients presenting with acute COVID-19 and classified based on maximal disease severity. Hospitalized patients negative for SARS-CoV-2 were used as controls. RESULTS. We found that the immune landscape in COVID-19 formed 3 dominant clusters, which correlated with disease severity. Longitudinal analysis identified a pattern of productive innate and adaptive immune responses in individuals who had a moderate disease course, whereas those with severe disease had features suggestive of a protracted and dysregulated immune response. Further, we identified coordinate immune alterations accompanying clinical improvement and decline that were also seen in patients who received IL-6 pathway blockade. CONCLUSION. The hospitalized COVID-19 negative cohort allowed us to identify immune alterations that were shared between severe COVID-19 and other critically ill patients. Collectively, our findings indicate that selection of immune interventions should be based in part on disease presentation and early disease trajectory due to the profound differences in the immune response in those with mild to moderate disease and those with the most severe disease. FUNDING. Benaroya Family Foundation, the Leonard and Norma Klorfine Foundation, Glenn and Mary Lynn Mounger, and the National Institutes of Health., Introduction The coronavirus disease 2019 (COVID-19) pandemic has brought a worldwide focus not only on the severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2), but also on how immunity to the [...]

Tumor heterogeneity may reduce the efficacy of molecularly guided systemic therapy for cancers that have metastasized. To determine whether the genomic alterations in a single metastasis provide a reasonable assessment of the major oncogenic drivers of other dispersed metastases in an individual, we analyzed multiple tumors from men with disseminated prostate cancer through whole-exome sequencing, array comparative genomic hybridization (CGH) and RNA transcript profiling, and we compared the genomic diversity within and between individuals. In contrast to the substantial heterogeneity between men, there was limited diversity among metastases within an individual. The number of somatic mutations, the burden of genomic copy number alterations and aberrations in known oncogenic drivers were all highly concordant, as were metrics of androgen receptor (AR) activity and cell cycle activity. AR activity was inversely associated with cell proliferation, whereas the expression of Fanconi anemia (FA)-complex genes was correlated with elevated cell cycle progression, expression of the E2F transcription factor 1 (E2F1) and loss of retinoblastoma 1 (RB1). Men with somatic aberrations in FA-complex genes or in ATM serine/threonine kinase (ATM) exhibited significantly longer treatment-response durations to carboplatin than did men without defects in genes encoding DNA-repair proteins. Collectively, these data indicate that although exceptions exist, evaluating a single metastasis provides a reasonable assessment of the major oncogenic driver alterations that are present in disseminated tumors within an individual, and thus may be useful for selecting treatments on the basis of predicted molecular vulnerabilities., Personalized approaches for cancer treatment rely on the premise that defined molecular alterations in tumors will confer susceptibility to specific therapeutics, and that malignancies without the alteration will not respond [...]

To link to full-text access for this article, visit this link: http://dx.doi.org/10.1016/j.ydbio.2009.06.007 Byline: Hamid Bolouri, Eric H. Davidson Keywords: Community effect; Intradomain signaling; Sea urchin embryo; nodal gene regulation Abstract: The 'Community Effect' denotes intra-territorial signaling amongst cells which constitute a particular tissue or embryonic progenitor field. The cells of the territory express the same transcriptional regulatory state, and the intra-territorial signaling is essential to maintenance of this specific regulatory state. The structure of the underlying gene regulatory network (GRN) subcircuitry explains the genomically wired mechanism by which community effect signaling is linked to the continuing transcriptional generation of the territorial regulatory state. A clear example is afforded by the oral ectoderm GRN of the sea urchin embryo where cis-regulatory evidence, experimental embryology, and network analysis combine to provide a complete picture. We review this example and consider less well known but similar cases in other developing systems where the same subcircuit GRN topology is present. To resolve mechanistic issues that arise in considering how community effect signaling could operate to produce its observed effects, we construct and analyze the behavior of a quantitative model of community effect signaling in the sea urchin embryo oral ectoderm. Community effect network topology could constitute part of the genomic regulatory code that defines transcriptional function in multicellular tissues composed of cells in contact, and hence may have arisen as a metazoan developmental strategy. Author Affiliation: Division of Biology, California Institute of Technology, Pasadena, CA 91125, USA Article History: Received 18 March 2009; Revised 20 May 2009; Accepted 5 June 2009 Article Note: (footnote) [star] This article was accepted in 2009 to celebrate the 50th anniversary of Developmental Biology.

Endoderm and mesoderm specification are the most fundamental pattern formation events in embryonic development. This process starts with blimp1 and wnt8 gene expression at the vegetal pole when the embryonic transcription begins.

Author(s): Mark Gilchrist [1]; Vesteinn Thorsson [1]; Bin Li [1]; Alistair G. Rust [1]; Martin Korb [1]; Kathleen Kennedy [1]; Tsonwin Hai [2]; Hamid Bolouri [1]; Alan Aderem (corresponding author) [...]

Different experimental technologies measure different aspects of a system and to differing depth and breadth. High-throughput assays have inherently high false-positive and false-negative rates. Moreover, each technology includes systematic biases of a different nature. These differences make network reconstruction from multiple data sets difficult and error-prone. Additionally, because of the rapid rate of progress in biotechnology, there is usually no curated exemplar data set from which one might estimate data integration parameters. To address these concerns, we have developed data integration methods that can handle multiple data sets differing in statistical power, type, size, and network coverage without requiring a curated training data set. Our methodology is general in purpose and may be applied to integrate data from any existing and future technologies. Here we outline our methods and then demonstrate their performance by applying them to simulated data sets. The results show that these methods select truepositive data elements much more accurately than classical approaches. In an accompanying companion paper, we demonstrate the applicability of our approach to biological data. We have integrated our methodology into a free open source software package named POINTILLIST. Fisher's method | mixture distribution models

To link to full-text access for this article, visit this link: http://dx.doi.org/10.1016/j.ydbio.2005.04.023 Byline: William J.R. Longabaugh (a), Eric H. Davidson (b), Hamid Bolouri (a)(b) Abstract: Developmental genetic regulatory networks (GRNs) have unique architectural characteristics. They are typically large-scale, multi-layered, and organized in a nested, modular hierarchy of regulatory network kernels, function-specific building blocks, and structural gene batteries. They are also inherently multicellular and involve changing topological relationships among a growing number of cells. Reconstruction of developmental GRNs requires unique computational tools that support the above representational requirements. In addition, we argue that DNA-centered network modeling, separate descriptions of network organization and network behavior, and support for network documentation and annotation are essential requirements for computational modeling of developmental GRNs. Based on these observations, we have developed a freely available, platform-independent, open source software package (BioTapestry) which supports both the process of model construction and also model visualization, analysis, documentation, and dissemination. We provide an overview of the main features of BioTapestry. The BioTapestry software and additional documents are available from http://www.biotapestry.org. We recommend BioTapestry as the substrate for further co-development for and by the developmental biology community. Author Affiliation: (a) Institute for Systems Biology, Seattle, WA 98103-8904, USA (b) Division of Biology, California Institute of Technology, Pasadena, CA 91125, USA

Gene network analysis requires computationally based models which represent the functional architecture of regulatory interactions, and which provide directly testable predictions. The type of model that is useful is constrained by the particular features of developmentally active cis-regulatory systems. These systems function by processing diverse regulatory inputs, generating novel regulatory outputs. A computational model which explicitly accommodates this basic concept was developed earlier for the cis-regulatory system of the endo16 gene of the sea urchin. This model represents the genetically mandated logic functions that the system executes, but also shows how time-varying kinetic inputs are processed in different circumstances into particular kinetic outputs. The same basic design features can be utilized to construct models that connect the large number of cis-regulatory elements constituting developmental gene networks. The ultimate aim of the network models discussed here is to represent the regulatory relationships among the genomic control systems of the genes in the network, and to state their functional meaning. The target site sequences of the cis-regulatory elements of these genes constitute the physical basis of the network architecture. Useful models for developmental regulatory networks must represent the genetic logic by which the system operates, but must also be capable of explaining the real time dynamics of cis-regulatory response as kinetic input and output data become available. Most importantly, however, such models must display in a direct and transparent manner fundamental network design features such as intra-and intercellular feedback circuitry; the sources of parallel inputs into each cis-regulatory element; gene battery organization; and use of repressive spatial inputs in specification and boundary formation. Successful network models lead to direct tests of key architectural features by targeted cis-regulatory analysis. Key Words: gene regulatory network; model; endo16 gene; regulatory genomics.

We present the current form of a provisional DNA sequence-based regulatory gene network that explains in outline how endomesodermal specification in the sea urchin embryo is controlled. The model of the network is in a continuous process of revision and growth as new genes are added and new experimental results become available; see http://www.its.cahech.edu/~mirsky/endomeso.htm (End-mes Gene Network Update) for the latest version. The network contains over 40 genes at present, many newly uncovered in the course of this work, and most encoding DNA-binding transcriptional regulatory factors. The architecture of the network was approached initially by construction of a logic model that integrated the extensive experimental evidence now available on endomesoderm specification. The internal linkages between genes in the network have been determined functionally, by measurement of the effects of regulatory perturbations on the expression of all relevant genes in the network. Five kinds of perturbation have been applied: (1) use of morpholino antisense oligonucleotides targeted to many of the key regulatory genes in the network; (2) transformation of other regulatory factors into dominant repressors by construction of Engrailed repressor domain fusions; (3) ectopic expression of given regulatory factors, from genetic expression constructs and from injected mRNAs; (4) blockade of the [beta]-catenin/Tcf pathway by introduction of mRNA encoding the intracellular domain of cadherin; and (5) blockade of the Notch signaling pathway by introduction of mRNA encoding the extracellular domain of the Notch receptor. The network model predicts the cis-regulatory inputs that link each gene into the network. Therefore, its architecture is testable by cis-regulatory analysis. Strongylocentroms purpuratus and Lytechinus variegatus genomic BAC recombinants that include a large number of the genes in the network have been sequenced and annotated. Tests of the cis-regulatory predictions of the model are greatly facilitated by interspecific computational sequence comparison, which affords a rapid identification of likely cis-regulatory elements in advance of experimental analysis. The network specifies genomically encoded regulatory processes between early cleavage and gastrula stages. These control the specification of the micromere lineage and of the initial [veg.sub.2] endomesodermal domain; the blastula-stage separation of the central [veg.sub.2] mesodermal domain (i.e., the secondary mesenchyme progenitor field) from the peripheral [veg.sub.2] endodermal domain; the stabilization of specification state within these domains; and activation of some downstream differentiation genes. Each of the temporal--spatial phases of specification is represented in a subelement of the network model, that treats regulatory events within the relevant embryonic nuclei at particular stages. Key Words: gene network; sea urchin embryo; gene regulation.

The investigation and modeling of gene regulatory networks requires computational tools specific to the task. We present several locally developed software tools that have been used in support of our ongoing research into the embryogenesis of the sea urchin. These tools are especially well suited to iterative refinement of models through experimental and computational investigation. They include: BioArray, a macroarray spot processing program; SUGAR, a system to display and correlate large-BAC sequence analyses; SeqComp and FamilyRelations, programs for comparative sequence analysis; and NetBuilder, an environment for creating and analyzing models of gene networks. We also present an overview of the process used to build our model of the Strongylocentrotus purpuratus endomesoderm gene network. Several of the tools discussed in this paper are still in active development and some are available as open source. Key Words: sequence annotation; comparative analysis; macroarrays; gene network modeling; computational tools.