Generating anatomical variation through mutations in networks - implications for evolution

Genetic mutation leads to anatomical variation only indirectly because many proteins involved in generating anatomical structures in embryos operate cooperatively within molecular networks. These include gene-regulatory or control networks (CNs) for timing, signaling and patterning together with the process networks (PNs) for proliferation, apoptosis, differentiation and morphogenesis that they control. This paper argues that anatomical variation is achieved through a two-stage process: mutation alters the outputs of CNs and perhaps the proliferation network, and such changed outputs alter the ways that PNs construct tissues. This systems-biology approach has several implications: first, because networks contain many cooperating proteins, they amplify the effects of genetic variation so enabling mutation to generate a wider range of phenotypes than a single changed protein acting alone could. Second, this amplification helps explain how novel phenotypes can be produced relatively rapidly. Third, because even organisms with novel anatomical phenotypes derive from variants in standard networks, there is no genetic barrier to their producing viable offspring. This approach also clarifies a terminological difficulty: classical evolutionary genetics views genes in terms of phenotype heritability rather than as DNA sequences. This paper suggests that the molecular phenotype of the classical concept of a gene is often a protein network, with a mutation leading to an alteration in that network's dynamics.

Advances in huntington disease drug discovery: novel approaches to model disease phenotypes

Huntington disease is a monogenic, autosomal dominant, progressive neurodegenerative disorder caused by a trinucleotide CAG repeat expansion in exon 1 of the huntingtin (HTT) gene; age of onset of clinical symptoms inversely correlates with expanded CAG repeat length. HD leads to extensive degeneration of the basal ganglia, hypothalamic nuclei, and selected cortical areas, and a wide range of molecular mechanisms have been implicated in disease pathology in animal or cellular models expressing mutated HTT (mHTT) proteins, either full-length or amino-terminal fragments. However, HD cellular models that recapitulate the slow progression of the disease have not been available due to the toxicity of overexpressed exogenous mHTT or to limitations with using primary cells for long-term studies. Most investigations of the effects of mHTT relied on cytotoxicity or aggregation end points in heterologous systems or in primary embryonic neuroglial cultures derived from HD mouse models. More innovative approaches are currently under active investigation, including screening using electrophysiological endpoints, as well as the recent use of primary blood mononuclear cells and of human embryonic stem cells derived from a variety of HD research participants. Here we describe how these cellular systems are being used to investigate HD biology as well as to identify mechanisms with therapeutic potential.

Systems biology - the broader perspective

Systems biology has two general aims: a narrow one, which is to discover how complex networks of proteins work, and a broader one, which is to integrate the molecular and network data with the generation and function of organism phenotypes. Doing all this involves complex methodologies, but underpinning the subject are more general conceptual problems about upwards and downwards causality, complexity and information storage, and their solutions provide the constraints within which these methodologies can be used. This essay considers these general aspects and the particular role of protein networks; their functional outputs are often the processes driving phenotypic change and physiological function—networks are, in a sense, the units of systems biology much as proteins are for molecular biology. It goes on to argue that the natural language for systems-biological descriptions of biological phenomena is the mathematical graph (a set of connected facts of the general form <state 1> [process] <state 2> (e.g., <membrane-bound delta> [activates] <notch pathway>). Such graphs not only integrate events at different levels but emphasize the distributed nature of control as well as displaying a great deal of data. The implications and successes of these ideas for physiology, pharmacology, development and evolution are briefly considered. The paper concludes with some challenges for the future.

Driving developmental and evolutionary change: A systems biology view

Embryonic development is underpinned by ∼50 core processes that drive morphogenesis, growth, patterning and differentiation, and each is the functional output of a complex molecular network. Processes are thus the natural and parsimonious link between genotype and phenotype and the obvious focus for any discussion of biological change. Here, the implications of this approach are explored. One is that many features of developmental change can be modeled as mathematical graphs, or sets of connected triplets of the general form <noun><verb><noun>. In these, the verbs (edges) are the outputs of the processes that drive change and the nouns (nodes) are the time-dependent states of biological entities (from molecules to tissues). Such graphs help unpick the multi-level complexity of developmental phenomena and may help suggest new experiments. Another comes from analyzing the effect of mutation that lead to tinkering with the dynamic properties of these processes and to congenital abnormalities; if these changes are both inherited and advantageous, they become evolutionary modifications. In this context, protein networks often represents what classical evolutionary genetics sees as genes, and the realization that traits reflect the output processes of complex networks, particularly for growth, patterning and pigmentation, rather than anything simpler clarifies some problems that the evolutionary synthesis of the 1950s has found hard to solve. In the wider context, most processes are used many times in development and cooperate to produce tissue modules (bones, branching duct systems, muscles etc.). Their underlying generative networks can thus be thought of as genomic modules or subroutines.

A new ontology (structured hierarchy) of human developmental anatomy for the first 7 weeks (Carnegie stages 1-20)

This paper describes a new ontology of human developmental anatomy covering the first 49 days [Carnegie stages (CS)1-20], primarily structured around the parts of organ systems and their development. The ontology includes more than 2000 anatomical entities (AEs) that range from the whole embryo, through organ systems and organ parts down to simple or leaf tissues (groups of cells with the same morphological phenotype), as well as features such as cavities. Each AE has assigned to it a set of facts of the form <AE><relationship><parent>, with the relationships including starts_at and ends_at (CSs), part_of (there can be several parents) and is_a (this gives the type of tissue, from an organ system down to one of ~ 80 simple tissues predominantly composed of a single cell kind, which is also specified). Leaf tissues also have a develops_from link to its parent tissue. The ontology includes ~14 000 such facts, which are mainly from the literature and an earlier ontology of human developmental anatomy (EHDAA, now withdrawn). The relationships enable these facts to be integrated into a single, complex hierarchy (or mathematical graph) that was made and can be viewed in the OBO-Edit browser (oboedit.org). Each AE has an EHDAA2 ID that may be useful in an informatics context, while the ontology as a whole can be used for organizing databases of human development. It is also a knowledge resource: a user can trace the lineage of any tissue back to the egg, study the changes in cell phenotype that occur as a tissue develops, and use the structure to add further (e.g. molecular) information. The ontology may be downloaded from www.obofoundry.org. Queries and corrections should be sent to j.bard@ed.ac.uk.

A systems biology representation of developmental anatomy

The formation of any tissue involves differentiation, cell dynamics and interactions with adjacent tissues. This paper suggests that the complexity of the system as a whole can be represented as a mathematical graph, that is, a set of connected triples of the general form [term] [term]. Computationally, such graphs are widely used for modeling data; visually, they form hierarchies and networks. For morphogenesis, the triples are of the general structure , where nouns cover tissues, molecules and networks and verbs describe processes such as moves, differentiates, grows and apoptoses. The paper considers the general formalism of graphs, where graphs are already used in biology, and how developmental anatomy may be described using this format. Representing morphogenesis as a visual graph is complicated as the formalism has to incorporate tissue types, molecular signals, networks, dynamic processes and some aspects, at least, of tissue geometry. The formation of a capillary sprout is chosen as an example of how this complexity can be represented graphically, with colour used to distinguish tissues and molecules. There are three key benefits, beyond its compactness, in using the graph formalism of morphogenesis to complement experimentation. First, it emphasizes the distributed nature of causality in morphogenesis. Secondly, producing all the triples for the visual graph requires explicit formalization of each aspect of the process, and this, in turn, often exposes gaps in knowledge and so suggests new experiments. Thirdly, once the graph has been formalized, triples can be annotated with associated information or IDs (e.g. cell types, publications, gene-expression data) that link to external online resources that may be regularly updated. Such annotations allow the graph to be viewed as a self-maintaining review. The graph approach sees dynamic processes as the drivers of developmental momentum and, because the same processes are used many times during development, it seems appropriate to view them as modules and their underlying networks as genomic subroutines.

Finding and sharing: new approaches to registries of databases and services for the biomedical sciences

The recent explosion of biological data and the concomitant proliferation of distributed databases make it challenging for biologists and bioinformaticians to discover the best data resources for their needs, and the most efficient way to access and use them. Despite a rapid acceleration in uptake of syntactic and semantic standards for interoperability, it is still difficult for users to find which databases support the standards and interfaces that they need. To solve these problems, several groups are developing registries of databases that capture key metadata describing the biological scope, utility, accessibility, ease-of-use and existence of web services allowing interoperability between resources. Here, we describe some of these initiatives including a novel formalism, the Database Description Framework, for describing database operations and functionality and encouraging good database practise. We expect such approaches will result in improved discovery, uptake and utilization of data resources. Database URL: http://www.casimir.org.uk/casimir_ddf.

Mouse Resource Browser--a database of mouse databases

The laboratory mouse has become the organism of choice for discovering gene function and unravelling pathogenetic mechanisms of human diseases through the application of various functional genomic approaches. The resulting deluge of data has led to the deployment of numerous online resources and the concomitant need for formalized experimental descriptions, data standardization, database interoperability and integration, a need that has yet to be met. We present here the Mouse Resource Browser (MRB), a database of mouse databases that indexes 217 publicly available mouse resources under 22 categories and uses a standardised database description framework (the CASIMIR DDF) to provide information on their controlled vocabularies (ontologies and minimum information standards), and technical information on programmatic access and data availability. Focusing on interoperability and integration, MRB offers automatic generation of downloadable and re-distributable SOAP application-programming interfaces for resources that provide direct database access. MRB aims to provide useful information to both bench scientists, who can easily navigate and find all mouse related resources in one place, and bioinformaticians, who will be provided with interoperable resources containing data which can be mined and integrated.

Database URL: http://bioit.fleming.gr/mrb

Pyridinyl aminohydantoins as small molecule BACE1 inhibitors

A novel class of pyridinyl aminohydantoins was designed and prepared as highly potent BACE1 inhibitors. Compound (S)-4g showed excellent potency with IC(50) of 20 nM for BACE1. X-ray crystallography indicated that the interaction between pyridine nitrogen and the tryptophan Trp76 was a key feature in the S2' region of the enzyme that contributed to increased potency.