The multidomain protein Trio binds the LAR transmembrane tyrosine phosphatase, contains a protein kinase domain, and has separate rac-specific and rho-specific guanine nucleotide exchange factor domains.

rho-like GTP binding proteins play an essential role in regulating cell growth and actin polymerization. These molecular switches are positively regulated by guanine nucleotide exchange factors (GEFs) that promote the exchange of GDP for GTP. Using the interaction-trap assay to identify candidate proteins that bind the cytoplasmic region of the LAR transmembrane protein tyrosine phosphatase (PT-Pase), we isolated a cDNA encoding a 2861-amino acid protein termed Trio that contains three enzyme domains: two functional GEF domains and a protein serine/threonine kinase (PSK) domain. One of the Trio GEF domains (Trio GEF-D1) has rac-specific GEF activity, while the other Trio GEF domain (Trio GEF-D2) has rho-specific activity. The C-terminal PSK domain is adjacent to an Ig-like domain and is most similar to calcium/calmodulin-dependent kinases, such as smooth muscle myosin light chain kinase which similarly contains associated Ig-like domains. Near the N terminus, Trio has four spectrin-like repeats that may play a role in intracellular targeting. Northern blot analysis indicates that Trio has a broad tissue distribution. Trio appears to be phosphorylated only on serine residues, suggesting that Trio is not a LAR substrate, but rather that it forms a complex with LAR. As the LAR PTPase localizes to the ends of focal adhesions, we propose that LAR and the Trio GEF/PSK may orchestrate cell-matrix and cytoskeletal rearrangements necessary for cell migration.

Disease specificity of kinase domains: the src-encoded catalytic domain converts erbB into a sarcoma oncogene.

src and erbB are two tyrosine kinase-encoding oncogenes carried by retroviruses, which have distinct disease specificities. The former induces predominantly sarcomas, and the latter, leukemias. Src and ErbB have similar catalytic domains but have very different regulatory domains. A wealth of information exists concerning how different regulatory domains [Src homology 2 (SH2) and SH3 domains and autophosphorylation sites] control substrate and disease specificities. Whether the catalytic domain helps determine these specificities remains to be explored. Here we show that the Src catalytic domain is enzymatically active when substituted into the ErbB backbone and interacts with the ErbB regulatory domain. This ErbB/Src chimera displays autophosphorylation and substrate phosphorylation patterns different from those of both Src and ErbB. Neither SH2 and SH3 nor autophosphorylation sites are required for the Src catalytic domain to exert its fibroblast transforming ability. Most significantly, the catalytic domain can convert erbB from a leukemogenic oncogene into a sarcomagenic oncogene, suggesting that the leukemogenic determinants in part reside within the ErbB catalytic domain.

Novel protein domains and motifs in the marine planctomycete Rhodopirellula baltica

The planctomycetes are a phylum of bacteria that have a unique cell compartmentalisation and yeast-like budding cell division and peptidoglycan-less proteinaceous cell walls. We wished to further our understanding of these unique organisms at the molecular level by searching for conserved amino acid sequence motifs and domains in the proteins encoded by Rhodopirellula baltica. Using BLAST and single-linkage clustering, we have discovered several new protein domains and sequence motifs in this planctomycete. R. baltica has multiple members of the newly discovered GEFGR protein family and the ASPIC C-terminal domain family, whilst most other organisms for which whole genome sequence is available have no more than one. Many of the domains and motifs appear to be restricted to the planctomycetes. It is possible that these protein domains and motifs may have been lost or replaced in other phyla, or they may have undergone multiple duplication events in the planctomycete lineage. One of the novel motifs probably represents a novel N-terminal export signal peptide. With their unique cell biology, it may be that the planctomycete cell compartmentalisation plan in particular needs special membrane transport mechanisms. The discovery of these new domains and motifs, many of which are associated with secretion and cell-surface functions, will help to stimulate experimental work and thus enhance further understanding of this fascinating group of organisms. (C) 2004 Federation of European Microbiological Societies. Published by Elsevier B.V. All rights reserved.

Mammalian GRIP domain proteins differ in their membrane binding properties and are recruited to distinct domains of the TGN

The four mammalian golgins, p230/golgin-245, golgin-97, GCC88 and GCC185 are targeted to trans-Golgi network ITGN) membranes by their C-terminal GRIP domain in a G-protein-dependent process. The Arf-like GTPase, Arl1, has been shown to mediate TGN recruitment of p230/golgin245 and golgin-97 by interaction with their GRIP domains; however, it is not known whether all the TGN golgins bind to Arl1 and whether they are all recruited to the same or different TGN domains. Here we demonstrate differences in membrane binding properties and TGN domain recruitment of the mammalian GRIP domain proteins. Overexpression of full-length GCC185 resulted in the appearance of small punctate structures dispersed in the cytoplasm of transfected cells that were identified as membrane tubular structures by immunoelectron microscopy. The cytoplasmic GCC185-labelled structures were enriched for membrane binding determinants of GCC185 GRIP, whereas the three other mammalian GRIP family members did not colocalize with the GCC185-labelled structures. These GCC185-labelled structures included the TGN resident protein alpha2,6 sialyltransferase and excluded the recycling TGN protein, TGN46. The Golgi stack was unaffected by overexpression of GCC185. Overexpression of both full-length GCC185 and GCC88 showed distinct and nonoverlapping structures. We also show that the GRIP domains of GCC185 and GCC88 differ in membrane binding properties from each other and, in contrast to p230/golgin245 and golgin-97, do not interact with Arl1 in vivo. Collectively these results show that GCC88, GCC185 and p230/golgin245 are recruited to functionally distinct domains of the TGN and are likely to be important for the maintenance of TGN subdomain structure, a critical feature for mediating protein sorting and membrane transport.

Two Axes of Domains for Domain Analysis

This paper adds two analytical devices to domain analysis, claiming that for domain analysis to work cumulatively transferable definitions of domains must be written. To establish this definition the author provides two axes to consider: Ar- eas of Modulation and Degrees of Specialization. These axes may serve as analytical devices for the domain analyst to delineate what is being studied and what is not being studied in a domain analysis.

The contribution of different androgen receptor domains to receptor dimerization and signaling

The androgen receptor (AR) is a ligand-activated transcription factor of the nuclear receptor superfamily that plays a critical role in male physiology and pathology. Activated by binding of the native androgens testosterone and 5-dihydrotestosterone, the AR regulates transcription of genes involved in the development and maintenance of male phenotype and male reproductive function as well as other tissues such as bone and muscle. Deregulation of AR signaling can cause a diverse range of clinical conditions, including the X-linked androgen insensitivity syndrome, a form of motor neuron disease known as Kennedy’s disease, and male infertility. In addition, there is now compelling evidence that the AR is involved in all stages of prostate tumorigenesis including initiation, progression, and treatment resistance. To better understand the role of AR signaling in the pathogenesis of these conditions, it is important to have a comprehensive understanding of the key determinants of AR structure and function. Binding of androgens to the AR induces receptor dimerization, facilitating DNA binding and the recruitment of cofactors and transcriptional machinery to regulate expression of target genes. Various models of dimerization have been described for the AR, the most well characterized interaction being DNA-binding domain- mediated dimerization, which is essential for the AR to bind DNA and regulate transcription. Additional AR interactions with potential to contribute to receptor dimerization include the intermolecular interaction between the AR amino terminal domain and ligand-binding domain known as the N-terminal/C-terminal interaction, and ligand-binding domain dimerization. In this review, we discuss each form of dimerization utilized by the AR to achieve transcriptional competence and highlight that dimerization through multiple domains is necessary for optimal AR signaling.

Automatic domain ontology extraction for context-sensitive opinion mining

Automated analysis of the sentiments presented in online consumer feedbacks can facilitate both organizations’ business strategy development and individual consumers’ comparison shopping. Nevertheless, existing opinion mining methods either adopt a context-free sentiment classification approach or rely on a large number of manually annotated training examples to perform context sensitive sentiment classification. Guided by the design science research methodology, we illustrate the design, development, and evaluation of a novel fuzzy domain ontology based contextsensitive opinion mining system. Our novel ontology extraction mechanism underpinned by a variant of Kullback-Leibler divergence can automatically acquire contextual sentiment knowledge across various product domains to improve the sentiment analysis processes. Evaluated based on a benchmark dataset and real consumer reviews collected from Amazon.com, our system shows remarkable performance improvement over the context-free baseline.

A general procedure for the derivation of principal domains of higher-order spectra

A general procedure to determine the principal domain (i.e., nonredundant region of computation) of any higher-order spectrum is presented, using the bispectrum as an example. The procedure is then applied to derive the principal domain of the trispectrum of a real-valued, stationary time series. These results are easily extended to compute the principal domains of other higher-order spectra

Leveraging Web 2.0 data for scalable semi-supervised learning of domain-specific sentiment lexicons

Since manually constructing domain-specific sentiment lexicons is extremely time consuming and it may not even be feasible for domains where linguistic expertise is not available. Research on the automatic construction of domain-specific sentiment lexicons has become a hot topic in recent years. The main contribution of this paper is the illustration of a novel semi-supervised learning method which exploits both term-to-term and document-to-term relations hidden in a corpus for the construction of domain specific sentiment lexicons. More specifically, the proposed two-pass pseudo labeling method combines shallow linguistic parsing and corpusbase statistical learning to make domain-specific sentiment extraction scalable with respect to the sheer volume of opinionated documents archived on the Internet these days. Another novelty of the proposed method is that it can utilize the readily available user-contributed labels of opinionated documents (e.g., the user ratings of product reviews) to bootstrap the performance of sentiment lexicon construction. Our experiments show that the proposed method can generate high quality domain-specific sentiment lexicons as directly assessed by human experts. Moreover, the system generated domain-specific sentiment lexicons can improve polarity prediction tasks at the document level by 2:18% when compared to other well-known baseline methods. Our research opens the door to the development of practical and scalable methods for domain-specific sentiment analysis.

Objectifying early-number : a visual nomenclature to express mathematical domain knowledge

To address issues of divisive ideologies in the Mathematics Education community and to subsequently advance educational practice, an alternative theoretical framework and operational model is proposed which represents a consilience of constructivist learning theories whilst acknowledging the objective but improvable nature of domain knowledge. Based upon Popper’s three-world model of knowledge, the proposed theory supports the differentiation and explicit modelling of both shared domain knowledge and idiosyncratic personal understanding using a visual nomenclature. The visual nomenclature embodies Piaget’s notion of reflective abstraction and so may support an individual’s experience-based transformation of personal understanding with regards to shared domain knowledge. Using the operational model and visual nomenclature, seminal literature regarding early-number counting and addition was analysed and described. Exemplars of the resultant visual artefacts demonstrate the proposed theory’s viability as a tool with which to characterise the reflective abstraction-based organisation of a domain’s shared knowledge. Utilising such a description of knowledge, future research needs to consider the refinement of the operational model and visual nomenclature to include the analysis, description and scaffolded transformation of personal understanding. A detailed model of knowledge and understanding may then underpin the future development of educational software tools such as computer-mediated teaching and learning environments.

Effect of topic domain and task type on Web image searching

Many user studies in Web information searching have found the significant effect of task types on search strategies. However, little attention was given to Web image searching strategies, especially the query reformulation activity despite that this is a crucial part in Web image searching. In this study, we investigated the effects of topic domains and task types on user’s image searching behavior and query reformulation strategies. Some significant differences in user’s tasks specificity and initial concepts were identified among the task domains. Task types are also found to influence participant’s result reviewing behavior and query reformulation strategies.

Learning domain-specific sentiment lexicons for predicting product sales

Generic sentiment lexicons have been widely used for sentiment analysis these days. However, manually constructing sentiment lexicons is very time-consuming and it may not be feasible for certain application domains where annotation expertise is not available. One contribution of this paper is the development of a statistical learning based computational method for the automatic construction of domain-specific sentiment lexicons to enhance cross-domain sentiment analysis. Our initial experiments show that the proposed methodology can automatically generate domain-specific sentiment lexicons which contribute to improve the effectiveness of opinion retrieval at the document level. Another contribution of our work is that we show the feasibility of applying the sentiment metric derived based on the automatically constructed sentiment lexicons to predict product sales of certain product categories. Our research contributes to the development of more effective sentiment analysis system to extract business intelligence from numerous opinionated expressions posted to the Web

Solution methods for advection-diffusion-reaction equations on growing domains and subdomains, with application to modelling skin substitutes

Problems involving the solution of advection-diffusion-reaction equations on domains and subdomains whose growth affects and is affected by these equations, commonly arise in developmental biology. Here, a mathematical framework for these situations, together with methods for obtaining spatio-temporal solutions and steady states of models built from this framework, is presented. The framework and methods are applied to a recently published model of epidermal skin substitutes. Despite the use of Eulerian schemes, excellent agreement is obtained between the numerical spatio-temporal, numerical steady state, and analytical solutions of the model.

Contribution of DEAF1 structural domains to the interaction with the breast cancer oncogene LMO4

The proteins LMO4 and DEAF1 contribute to the proliferation of mammary epithelial cells. During breast cancer LMO4 is upregulated, affecting its interaction with other protein partners. This may set cells on a path to tumour formation. LMO4 and DEAF1 interact, but it is unknown how they cooperate to regulate cell proliferation. In this study, we identify a specific LMO4-binding domain in DEAF1. This domain contains an unstructured region that directly contacts LMO4, and a coiled coil that contains the DEAF1 nuclear export signal (NES). The coiled coil region can form tetramers and has the typical properties of a coiled coil domain. Using a simple cell-based assay, we show that LMO4 modulates the activity of the DEAF NES, causing nuclear accumulation of a construct containing the LMO4-interaction region of DEAF1.

Cell migration and proliferation on homogeneous and non-homogeneous domains : modelling on the scale of individuals and populations

Cell migration is a behaviour critical to many key biological effects, including wound healing, cancerous cell invasion and morphogenesis, the development of an organism from an embryo. However, given that each of these situations is distinctly different and cells are extremely complicated biological objects, interest lies in more basic experiments which seek to remove conflating factors and present a less complex environment within which cell migration can be experimentally examined. These include in vitro studies like the scratch assay or circle migration assay, and ex vivo studies like the colonisation of the hindgut by neural crest cells. The reduced complexity of these experiments also makes them much more enticing as problems to mathematically model, like done here. The primary goal of the mathematical models used in this thesis is to shed light on which cellular behaviours work to generate the travelling waves of invasion observed in these experiments, and to explore how variations in these behaviours can potentially predict differences in this invasive pattern which are experimentally observed when cell types or chemical environment are changed. Relevant literature has already identified the difficulty of distinguishing between these behaviours when using traditional mathematical biology techniques operating on a macroscopic scale, and so here a sophisticated individual-cell-level model, an extension of the Cellular Potts Model (CPM), is been constructed and used to model a scratch assay experiment. This model includes a novel mechanism for dealing with cell proliferations that allowed for the differing properties of quiescent and proliferative cells to be implemented into their behaviour. This model is considered both for its predictive power and used to make comparisons with the travelling waves which result in more traditional macroscopic simulations. These comparisons demonstrate a surprising amount of agreement between the two modelling frameworks, and suggest further novel modifications to the CPM that would allow it to better model cell migration. Considerations of the model’s behaviour are used to argue that the dominant effect governing cell migration (random motility or signal-driven taxis) likely depends on the sort of invasion demonstrated by cells, as easily seen by microscopic photography. Additionally, a scratch assay simulated on a non-homogeneous domain consisting of a ’fast’ and ’slow’ region is also used to further differentiate between these different potential cell motility behaviours. A heterogeneous domain is a novel situation which has not been considered mathematically in this context, nor has it been constructed experimentally to the best of the candidate’s knowledge. Thus this problem serves as a thought experiment used to test the conclusions arising from the simulations on homogeneous domains, and to suggest what might be observed should this non-homogeneous assay situation be experimentally realised. Non-intuitive cell invasion patterns are predicted for diffusely-invading cells which respond to a cell-consumed signal or nutrient, contrasted with rather expected behaviour in the case of random-motility-driven invasion. The potential experimental observation of these behaviours is demonstrated by the individual-cell-level model used in this thesis, which does agree with the PDE model in predicting these unexpected invasion patterns. In the interest of examining such a case of a non-homogeneous domain experimentally, some brief suggestion is made as to how this could be achieved.