Effects of lipopolysaccharide on glial phenotype and activity of glutamate transporters: Evidence for delayed up-regulation and redistribution of GLT-1

Excitatory amino acid transporters (EAATs) are responsible for homeostasis of extracellular L-glutamate, and the glial transporters are functionally dominant. EAAT expression or function is altered in acute and chronic neurological conditions, but little is known about the regulation of EAATs in reactive astroglia found in such neuropathologies. These studies examined the effects of the bacterial endotoxin lipopolysaccharide (LPS) on glial EAATs in vitro. The effects of LPS (1 microg/ml, 24-72 h) on EAAT activity and expression were examined in primary cultures of mouse astrocytes. [(3)H]D-aspartate uptake increased to 129% of control by 72 h treatment with LPS. Saturation analysis revealed that apparent K(m) was unchanged whilst V(max) was significantly increased to 172% of control by 72 h LPS treatment. Biotinylation and Western blotting indicated that cell-surface expression of GLT-1 was significantly elevated (146% control) by LPS treatment whereas GLAST expression was unchanged. Confocal analyses revealed that LPS treatment resulted in cytoskeletal changes and stellation of astrocytes, with rearrangement of F-actin (as shown by phalloidin labelling). Immunocytochemistry revealed clustering of GLAST, and increased expression and redistribution of GLT-1 to the cell-surface following treatment with LPS. Similar experiments were conducted in microglia, where LPS (50 ng/ml) was found to up-regulate expression of GLT-1 at 24 and 72 h in concert with cytoskeletal changes accompanying activation. These findings suggest an association of cytoskeletal changes in glia with EAAT activity, with the predominant adaptation involving up-regulation and redistribution of GLT-1.     

Infant neural sensitivity to dynamic eye gaze is associated with later emerging autism

Autism spectrum disorders (henceforth autism) are diagnosed in around 1% of the population [1]. Familial liability confers risk for a broad spectrum of difficulties including the broader autism phenotype (BAP) [2, 3]. There are currently no reliable predictors of autism in infancy, but characteristic behaviors emerge during the second year, enabling diagnosis after this age [4, 5]. Because indicators of brain functioning may be sensitive predictors, and atypical eye contact is characteristic of the syndrome [6-9] and the BAP [10, 11], we examined whether neural sensitivity to eye gaze during infancy is associated with later autism outcomes [12, 13]. We undertook a prospective longitudinal study of infants with and without familial risk for autism. At 6-10 months, we recorded infants' event-related potentials (ERPs) in response to viewing faces with eye gaze directed toward versus away from the infant [14]. Longitudinal analyses showed that characteristics of ERP components evoked in response to dynamic eye gaze shifts during infancy were associated with autism diagnosed at 36 months. ERP responses to eye gaze may help characterize developmental processes that lead to later emerging autism. Findings also elucidate the mechanisms driving the development of the social brain in infancy.     

Assessing strategies for improved superfamily recognition

There are more than 200 completed genomes and over 1 million nonredundant sequences in public repositories. Although the structural data are more sparse (approximately 13,000 nonredundant structures solved to date), several powerful sequence-based methodologies now allow these structures to be mapped onto related regions in a significant proportion of genome sequences. We review a number of publicly available strategies for providing structural annotations for genome sequences, and we describe the protocol adopted to provide CATH structural annotations for completed genomes. In particular, we assess the performance of several sequence-based protocols employing Hidden Markov model (HMM) technologies for superfamily recognition, including a new approach (SAMOSA [sequence augmented models of structure alignments]) that exploits multiple structural alignments from the CATH domain structure database when building the models. Using a data set of remote homologs detected by structure comparison and manually validated in CATH, a single-seed HMM library was able to recognize 76% of the data set. Including the SAMOSA models in the HMM library showed little gain in homolog recognition, although a slight improvement in alignment quality was observed for very remote homologs. However, using an expanded 1D-HMM library, CATH-ISL increased the coverage to 86%. The single-seed HMM library has been used to annotate the protein sequences of 120 genomes from all three major kingdoms, allowing up to 70% of the genes or partial genes to be assigned to CATH superfamilies. It has also been used to recruit sequences from Swiss-Prot and TrEMBL into CATH domain superfamilies, expanding the CATH database eightfold.     

EFFECTS OF DISTURBANCE ON EPIPHYTIC COMMUNITY ARCHITECTURE1

Microdistributional patterns of attached algal communities on Cladophora and glass slides were compared under varying disturbance regimes in the Upper Mississippi River, using light and scanning electron microscopy. Localized physical disturbance, induced by boat traffic and wind-generated wave action in the main channel, inhibited development of complex attached algal communities and maintained an adnate flora with two-dimensional architecture. In contrast, communities protected from disturbance developed a more complex, three-dimensional architecture. A high degree of architectural similarity was observed between communities on Cladophora and glass substrates exposed to similar levels of disturbance. Communities exposed to severe disturbance resembled ones in early stages of colonization and development, whereas less disturbed communities were similar to ones in advanced stages of development. These results demonstrated that turbulence strongly influences the community structure of periphyton on both micro and macro scale levels.     

Owlifier: Creating OWL-DL ontologies from simple spreadsheet-based knowledge descriptions

Discovery and integration of data is important in many ecological studies, especially those that concern broad-scale ecological questions. Data discovery and integration are often difficult and time consuming tasks for researchers, which is due in part to the use of informal, ambiguous, and sometimes inconsistent terms for describing data content. Ontologies offer a solution to this problem by providing consistent definitions of ecological concepts that in turn can be used to annotate, relate, and search for data sets. However, unlike in molecular biology or biomedicine, few ontology development efforts exist within ecology. Ontology development often requires considerable expertise in ontology languages and development tools, which is often a barrier for ontology creation in ecology. In this paper we describe an approach for ontology creation that allows ecologists to use common spreadsheet tools to describe different aspects of an ontology. We present conventions for creating, relating, and constraining concepts through spreadsheets, and provide software tools for converting these ontologies into equivalent OWL-DL representations. We also consider inverse translations, i.e., to convert ontologies represented using OWL-DL into our spreadsheet format. Our approach allows large lists of terms to be easily related and organized into concept hierarchies, and generally provides a more intuitive and natural interface for ontology development by ecologists.     

The New York Consortium on Membrane Protein Structure (NYCOMPS): a high-throughput platform for structural genomics of integral membrane proteins

The New York Consortium on Membrane Protein Structure (NYCOMPS) was formed to accelerate the acquisition of structural information on membrane proteins by applying a structural genomics approach. NYCOMPS comprises a bioinformatics group, a centralized facility operating a high-throughput cloning and screening pipeline, a set of associated wet labs that perform high-level protein production and structure determination by x-ray crystallography and NMR, and a set of investigators focused on methods development. In the first three years of operation, the NYCOMPS pipeline has so far produced and screened 7,250 expression constructs for 8,045 target proteins. Approximately 600 of these verified targets were scaled up to levels required for structural studies, so far yielding 24 membrane protein crystals. Here we describe the overall structure of NYCOMPS and provide details on the high-throughput pipeline.