PLD3 affects axonal spheroids and network defects in Alzheimer's disease.

The precise mechanisms that lead to cognitive decline in Alzheimer's disease are unknown. Here we identify amyloid-plaque-associated axonal spheroids as prominent contributors to neural network dysfunction. Using intravital calcium and voltage imaging, we show that a mouse model of Alzheimer's disease demonstrates severe disruption in long-range axonal connectivity. This disruption is caused by action-potential conduction blockades due to enlarging spheroids acting as electric current sinks in a size-dependent manner. Spheroid growth was associated with an age-dependent accumulation of large endolysosomal vesicles and was mechanistically linked with Pld3-a potential Alzheimer's-disease-associated risk gene1 that encodes a lysosomal protein2,3 that is highly enriched in axonal spheroids. Neuronal overexpression of Pld3 led to endolysosomal vesicle accumulation and spheroid enlargement, which worsened axonal conduction blockades. By contrast, Pld3 deletion reduced endolysosomal vesicle and spheroid size, leading to improved electrical conduction and neural network function. Thus, targeted modulation of endolysosomal biogenesis in neurons could potentially reverse axonal spheroid-induced neural circuit abnormalities in Alzheimer's disease, independent of amyloid removal.

Determining the effects of Class I landfill leachate on biological nutrient removal in wastewater treatment.

The disposal of landfill leachate is a chronic problem facing the municipal solid waste industry. The composition of landfill leachate is highly variable and often dependent on site-specific conditions. Due to the potentially disruptive impact on wastewater treatment processes, wastewater treatment plants (WWTP) are reluctant to accept landfill leachate for co-treatment. To improve the ability of WWTPs to screen the impact of landfill leachate and reduce landfill owners' cost of disposal, two bench scale methods were evaluated. First, six landfill leachates were screened with the specific oxygen uptake rate (SOUR) test, and second, the effect of leachate on the efficacy of activated sludge processes using lab scale sequencing batch reactors (SBRs) was determined with volumetric loading rates ranging from 5% to 20%. Results suggested that these tools can be used to estimate the impacts of leachate loading on biological processes. Both tools were able to identify loadings where biological activity was increased and inhibition of biological processes was minimized. The loading that maximized microbial activity was leachate specific and typically ranged from 5% to 10%. Taken together, these results suggest that improved landfill leachate screening and testing may improve outcomes at WWTPs by identifying a "Goldilocks" loading rate that increases biological activity. Nevertheless, our results also demonstrated that the effluent quality was degraded even at loading rates that increased biological activity. It is uncertain at this time if biological acclimation can remedy increased effluent nutrient mass loadings, suggesting further research is needed.

Twenty years of ModelDB and beyond: building essential modeling tools for the future of neuroscience.

Neuron modeling may be said to have originated with the Hodgkin and Huxley action potential model in 1952 and Rall's models of integrative activity of dendrites in 1964. Over the ensuing decades, these approaches have led to a massive development of increasingly accurate and complex data-based models of neurons and neuronal circuits. ModelDB was founded in 1996 to support this new field and enhance the scientific credibility and utility of computational neuroscience models by providing a convenient venue for sharing them. It has grown to include over 1100 published models covering more than 130 research topics. It is actively curated and developed to help researchers discover and understand models of interest. ModelDB also provides mechanisms to assist running models both locally and remotely, and has a graphical tool that enables users to explore the anatomical and biophysical properties that are represented in a model. Each of its capabilities is undergoing continued refinement and improvement in response to user experience. Large research groups (Allen Brain Institute, EU Human Brain Project, etc.) are emerging that collect data across multiple scales and integrate that data into many complex models, presenting new challenges of scale. We end by predicting a future for neuroscience increasingly fueled by new technology and high performance computation, and increasingly in need of comprehensive user-friendly databases such as ModelDB to provide the means to integrate the data for deeper insights into brain function in health and disease.

Structural and functional characterization of a complex between the acidic transactivation domain of EBNA2 and the Tfb1/p62 subunit of TFIIH.

Infection with the Epstein-Barr virus (EBV) can lead to a number of human diseases including Hodgkin's and Burkitt's lymphomas. The development of these EBV-linked diseases is associated with the presence of nine viral latent proteins, including the nuclear antigen 2 (EBNA2). The EBNA2 protein plays a crucial role in EBV infection through its ability to activate transcription of both host and viral genes. As part of this function, EBNA2 associates with several host transcriptional regulatory proteins, including the Tfb1/p62 (yeast/human) subunit of the general transcription factor IIH (TFIIH) and the histone acetyltransferase CBP(CREB-binding protein)/p300, through interactions with its C-terminal transactivation domain (TAD). In this manuscript, we examine the interaction of the acidic TAD of EBNA2 (residues 431-487) with the Tfb1/p62 subunit of TFIIH and CBP/p300 using nuclear magnetic resonance (NMR) spectroscopy, isothermal titration calorimeter (ITC) and transactivation studies in yeast. NMR studies show that the TAD of EBNA2 binds to the pleckstrin homology (PH) domain of Tfb1 (Tfb1PH) and that residues 448-471 (EBNA2448₋471) are necessary and sufficient for this interaction. NMR structural characterization of a Tfb1PH-EBNA2448₋471 complex demonstrates that the intrinsically disordered TAD of EBNA2 forms a 9-residue α-helix in complex with Tfb1PH. Within this helix, three hydrophobic amino acids (Trp458, Ile461 and Phe462) make a series of important interactions with Tfb1PH and their importance is validated in ITC and transactivation studies using mutants of EBNA2. In addition, NMR studies indicate that the same region of EBNA2 is also required for binding to the KIX domain of CBP/p300. This study provides an atomic level description of interactions involving the TAD of EBNA2 with target host proteins. In addition, comparison of the Tfb1PH-EBNA2448₋471 complex with structures of the TAD of p53 and VP16 bound to Tfb1PH highlights the versatility of intrinsically disordered acidic TADs in recognizing common target host proteins.

A computational analysis of antisense off-targets in prokaryotic organisms.

The adoption of antisense gene silencing as a novel disinfectant for prokaryotic organisms is hindered by poor silencing efficiencies. Few studies have considered the effects of off-targets on silencing efficiencies, especially in prokaryotic organisms. In this computational study, a novel algorithm was developed that determined and sorted the number of off-targets as a function of alignment length in Escherichia coli K-12 MG1655 and Mycobacterium tuberculosis H37Rv. The mean number of off-targets per a single location was calculated to be 14.1 ± 13.3 and 36.1 ± 58.5 for the genomes of E. coli K-12 MG1655 and M. tuberculosis H37Rv, respectively. Furthermore, when the entire transcriptome was analyzed, it was found that there was no general gene location that could be targeted to minimize or maximize the number of off-targets. In an effort to determine the effects of off-targets on silencing efficiencies, previously published studies were used. Analyses with acpP, ino1, and marORAB revealed a statistically significant relationship between the number of short alignment length off-targets hybrids and the efficacy of the antisense gene silencing, suggesting that the minimization of off-targets may be beneficial for antisense gene silencing in prokaryotic organisms.

Reduction of invasive bacteria in ethanol fermentations using bacteriophages.

Invasive Lactobacillus bacteria inhibit ethanol fermentations and reduce final product yields. Due to the emergence of antibiotic resistant strains of Lactobacillus spp., alternative disinfection strategies are needed for ethanol fermentations. The feasibility of using the bacteriophage (phage) 8014-B2 to control Lactobacillus plantarum in ethanol fermentations by Saccharomyces cerevisiae was investigated. In 48 h media-based shake flask fermentations, phages achieved greater than 3-log inactivation of L. plantarum, protected final ethanol yields, and maintained yeast viability. The phage-based bacterial disinfection rates depended on both the initial phage and bacterial concentrations. Furthermore, a simple set of kinetic equations was used to model the yeast, bacteria, phage, reducing sugars, and ethanol concentrations over the course of 48 h, and the various kinetic parameters were determined. Taken together, these results demonstrate the applicability of phages to reduce L. plantarum contamination and to protect final product yields in media-based fermentations.

Structural and functional characterization of an atypical activation domain in erythroid Kruppel-like factor (EKLF).

Erythroid Krüppel-like factor (EKLF) plays an important role in erythroid development by stimulating ß-globin gene expression. We have examined the details by which the minimal transactivation domain (TAD) of EKLF (EKLFTAD) interacts with several transcriptional regulatory factors. We report that EKLFTAD displays homology to the p53TAD and, like the p53TAD, can be divided into two functional subdomains (EKLFTAD1 and EKLFTAD2). Based on sequence analysis, we found that EKLFTAD2 is conserved in KLF2, KLF4, KLF5, and KLF15. In addition, we demonstrate that EKLFTAD2 binds the amino-terminal PH domain of the Tfb1/p62 subunit of TFIIH (Tfb1PH/p62PH) and four domains of CREB-binding protein/p300. The solution structure of the EKLFTAD2/Tfb1PH complex indicates that EKLFTAD2 binds Tfb1PH in an extended conformation, which is in contrast to the α-helical conformation seen for p53TAD2 in complex with Tfb1PH. These studies provide detailed mechanistic information into EKLFTAD functions as well as insights into potential interactions of the TADs of other KLF proteins. In addition, they suggest that not only have acidic TADs evolved so that they bind using different conformations on a common target, but that transitioning from a disordered to a more ordered state is not a requirement for their ability to bind multiple partners.

Structure-based design of a potent artificial transactivation domain based on p53.

Malfunctions in transcriptional regulation are associated with a number of critical human diseases. As a result, there is considerable interest in designing artificial transcription activators (ATAs) that specifically control genes linked to human diseases. Like native transcriptional activator proteins, an ATA must minimally contain a DNA-binding domain (DBD) and a transactivation domain (TAD) and, although there are several reliable methods for designing artificial DBDs, designing artificial TADs has proven difficult. In this manuscript, we present a structure-based strategy for designing short peptides containing natural amino acids that function as artificial TADs. Using a segment of the TAD of p53 as the scaffolding, modifications are introduced to increase the helical propensity of the peptides. The most active artificial TAD, termed E-Cap-(LL), is a 13-mer peptide that contains four key residues from p53, an N-capping motif and a dileucine hydrophobic bridge. In vitro analysis demonstrates that E-Cap-(LL) interacts with several known p53 target proteins, while in vivo studies in a yeast model system show that it is a 20-fold more potent transcriptional activator than the native p53-13 peptide. These results demonstrate that structure-based design represents a promising approach for developing artificial TADs that can be combined with artificial DBDs to create potent and specific ATAs.

Monitoring coliphages to reduce waterborne infectious disease transmission in the One Water framework.

Coastal waters, surface waters, and groundwater are impacted by wastewater and stormwater discharges, as well as agricultural flows containing animal waste and nutrients. A One Water approach posits that components of the water system have overlapping and interactive impacts on other aspects of the system, for which a comprehensive approach to water management is needed to further inform public health decisions. Current frameworks for monitoring wastewater effluent and recreational surface waters include the measurement of fecal indicator bacteria. Although viral pathogens are likely to be transported further and can survive longer than bacterial pathogens, virus monitoring is not required for recreational waters. A scientific consensus is emerging that the use of bacterial indicators alone does not account for nor represent the health risks associated with viral pathogens due to the differences in the fate and transport of bacterial versus viral pathogens in wastewater treatment, surface water, and groundwater. Furthermore, it is likely that the public health risk associated with these waterborne pathogens is variable and diverse. For example, under drought conditions, effluents of urban water systems can comprise most of the dry weather flow in downstream waters, which are often used as sources of drinking water. This de facto reuse could increase viral risk for the end users of this water. A One Water approach will aid in protecting the health of the public from waterborne pathogens, regardless of where those pathogens entered the water system. In this review, we assert that monitoring for fecal indicator viruses can complement the monitoring of bacterial indicators, thereby improving public health protections. Bacteriophages have the strongest research foundation and correlation with viral pathogens along with some prediction power for risk to human health. Methods for detecting and quantifying coliphages are briefly summarized, as are challenges in the implementation of testing. Key knowledge gaps and research priorities are discussed so that the potential value and limitations of coliphage monitoring can be better addressed and understood.

Approaches to neuroscience data integration.

As the number of neuroscience databases increases, the need for neuroscience data integration grows. This paper reviews and compares several approaches, including the Neuroscience Database Gateway (NDG), Neuroscience Information Framework (NIF) and Entrez Neuron, which enable neuroscience database annotation and integration. These approaches cover a range of activities spanning from registry, discovery and integration of a wide variety of neuroscience data sources. They also provide different user interfaces for browsing, querying and displaying query results. In Entrez Neuron, for example, four different facets or tree views (neuron, neuronal property, gene and drug) are used to hierarchically organize concepts that can be used for querying a collection of ontologies. The facets are also used to define the structure of the query results.

NeuroML: a language for describing data driven models of neurons and networks with a high degree of biological detail.

Biologically detailed single neuron and network models are important for understanding how ion channels, synapses and anatomical connectivity underlie the complex electrical behavior of the brain. While neuronal simulators such as NEURON, GENESIS, MOOSE, NEST, and PSICS facilitate the development of these data-driven neuronal models, the specialized languages they employ are generally not interoperable, limiting model accessibility and preventing reuse of model components and cross-simulator validation. To overcome these problems we have used an Open Source software approach to develop NeuroML, a neuronal model description language based on XML (Extensible Markup Language). This enables these detailed models and their components to be defined in a standalone form, allowing them to be used across multiple simulators and archived in a standardized format. Here we describe the structure of NeuroML and demonstrate its scope by converting into NeuroML models of a number of different voltage- and ligand-gated conductances, models of electrical coupling, synaptic transmission and short-term plasticity, together with morphologically detailed models of individual neurons. We have also used these NeuroML-based components to develop an highly detailed cortical network model. NeuroML-based model descriptions were validated by demonstrating similar model behavior across five independently developed simulators. Although our results confirm that simulations run on different simulators converge, they reveal limits to model interoperability, by showing that for some models convergence only occurs at high levels of spatial and temporal discretisation, when the computational overhead is high. Our development of NeuroML as a common description language for biophysically detailed neuronal and network models enables interoperability across multiple simulation environments, thereby improving model transparency, accessibility and reuse in computational neuroscience.

Entrez Neuron RDFa: a pragmatic semantic web application for data integration in neuroscience research.

The amount of biomedical data available in Semantic Web formats has been rapidly growing in recent years. While these formats are machine-friendly, user-friendly web interfaces allowing easy querying of these data are typically lacking. We present "Entrez Neuron", a pilot neuron-centric interface that allows for keyword-based queries against a coherent repository of OWL ontologies. These ontologies describe neuronal structures, physiology, mathematical models and microscopy images. The returned query results are organized hierarchically according to brain architecture. Where possible, the application makes use of entities from the Open Biomedical Ontologies (OBO) and the 'HCLS knowledgebase' developed by the W3C Interest Group for Health Care and Life Science. It makes use of the emerging RDFa standard to embed ontology fragments and semantic annotations within its HTML-based user interface. The application and underlying ontologies demonstrate how Semantic Web technologies can be used for information integration within a curated information repository and between curated information repositories. It also demonstrates how information integration can be accomplished on the client side, through simple copying and pasting of portions of documents that contain RDFa markup.

Automated Metadata Suggestion During Repository Submission.

Knowledge discovery via an informatics resource is constrained by the completeness of the resource, both in terms of the amount of data it contains and in terms of the metadata that exists to describe the data. Increasing completeness in one of these categories risks reducing completeness in the other because manually curating metadata is time consuming and is restricted by familiarity with both the data and the metadata annotation scheme. The diverse interests of a research community may drive a resource to have hundreds of metadata tags with few examples for each making it challenging for humans or machine learning algorithms to learn how to assign metadata tags properly. We demonstrate with ModelDB, a computational neuroscience model discovery resource, that using manually-curated regular-expression based rules can overcome this challenge by parsing existing texts from data providers during user data entry to suggest metadata annotations and prompt them to suggest other related metadata annotations rather than leaving the task to a curator. In the ModelDB implementation, analyzing the abstract identified 6.4 metadata tags per abstract at 79% precision. Using the full-text produced higher recall with low precision (41%), and the title alone produced few (1.3) metadata annotations per entry; we thus recommend data providers use their abstract during upload. Grouping the possible metadata annotations into categories (e.g. cell type, biological topic) revealed that precision and recall for the different text sources varies by category. Given this proof-of-concept, other bioinformatics resources can likewise improve the quality of their metadata by adopting our approach of prompting data uploaders with relevant metadata at the minimal cost of formalizing rules for each potential metadata annotation.

Evaluating the fate of bacterial indicators, viral indicators, and viruses in water resource recovery facilities.

A year-long sampling campaign at nine water resource recovery facilities (WRRFs) was conducted to assess the treatability and fate of bacterial indicators, viral indicators, and viruses. Influent concentrations of viral indicators (male-specific and somatic coliphages) and bacterial indicators (Escherichia coli and enterococci) remained relatively constant, typically varying by one order of magnitude over the course of the year. Annual average bacterial indicator reduction ranged from 4.0 to 6.7 logs, and annual average viral indicator reduction ranged from 1.6 to 5.4 logs. Bacterial and viral indicator reduction depended on the WRRF's treatment processes, and bacterial indicator reduction was greater than viral indicator reduction for many processes. Viral reduction (adenovirus 41, norovirus GI, and norovirus GII) was more similar to viral indicator reduction than bacterial indicator reduction. Overall, this work suggests that viral indicator reduction in WRRFs is variable and depends on specific unit processes. Moreover, for the same unit treatment process, viral indicator reduction and bacterial indicator reduction can vary. PRACTITIONER POINTS: A year-long sampling campaign was conducted at nine water resource recovery facilities (WRRFs). The treatability and fate of bacterial indicators, viral indicators, and viruses were assessed. Viral indicator reduction in WRRFs is variable and depends on specific unit processes. For the same unit treatment process, viral indicator reduction and bacterial indicator reduction can vary.

AlzPharm: integration of neurodegeneration data using RDF.

BACKGROUND: Neuroscientists often need to access a wide range of data sets distributed over the Internet. These data sets, however, are typically neither integrated nor interoperable, resulting in a barrier to answering complex neuroscience research questions. Domain ontologies can enable the querying heterogeneous data sets, but they are not sufficient for neuroscience since the data of interest commonly span multiple research domains. To this end, e-Neuroscience seeks to provide an integrated platform for neuroscientists to discover new knowledge through seamless integration of the very diverse types of neuroscience data. Here we present a Semantic Web approach to building this e-Neuroscience framework by using the Resource Description Framework (RDF) and its vocabulary description language, RDF Schema (RDFS), as a standard data model to facilitate both representation and integration of the data. RESULTS: We have constructed a pilot ontology for BrainPharm (a subset of SenseLab) using RDFS and then converted a subset of the BrainPharm data into RDF according to the ontological structure. We have also integrated the converted BrainPharm data with existing RDF hypothesis and publication data from a pilot version of SWAN (Semantic Web Applications in Neuromedicine). Our implementation uses the RDF Data Model in Oracle Database 10g release 2 for data integration, query, and inference, while our Web interface allows users to query the data and retrieve the results in a convenient fashion. CONCLUSION: Accessing and integrating biomedical data which cuts across multiple disciplines will be increasingly indispensable and beneficial to neuroscience researchers. The Semantic Web approach we undertook has demonstrated a promising way to semantically integrate data sets created independently. It also shows how advanced queries and inferences can be performed over the integrated data, which are hard to achieve using traditional data integration approaches. Our pilot results suggest that our Semantic Web approach is suitable for realizing e-Neuroscience and generic enough to be applied in other biomedical fields.

Respiration Gates Sensory Input Responses in the Mitral Cell Layer of the Olfactory Bulb.

Respiration plays an essential role in odor processing. Even in the absence of odors, oscillating excitatory and inhibitory activity in the olfactory bulb synchronizes with respiration, commonly resulting in a burst of action potentials in mammalian mitral/tufted cells (MTCs) during the transition from inhalation to exhalation. This excitation is followed by inhibition that quiets MTC activity in both the glomerular and granule cell layers. Odor processing is hypothesized to be modulated by and may even rely on respiration-mediated activity, yet exactly how respiration influences sensory processing by MTCs is still not well understood. By using optogenetics to stimulate discrete sensory inputs in vivo, it was possible to temporally vary the stimulus to occur at unique phases of each respiration. Single unit recordings obtained from the mitral cell layer were used to map spatiotemporal patterns of glomerular evoked responses that were unique to stimulations occurring during periods of inhalation or exhalation. Sensory evoked activity in MTCs was gated to periods outside phasic respiratory mediated firing, causing net shifts in MTC activity across the cycle. In contrast, odor evoked inhibitory responses appear to be permitted throughout the respiratory cycle. Computational models were used to further explore mechanisms of inhibition that can be activated by respiratory activity and influence MTC responses. In silico results indicate that both periglomerular and granule cell inhibition can be activated by respiration to internally gate sensory responses in the olfactory bulb. Both the respiration rate and strength of lateral connectivity influenced inhibitory mechanisms that gate sensory evoked responses.

ModelView for ModelDB: Online Presentation of Model Structure.

ModelDB ( modeldb.yale.edu ), a searchable repository of source code of more than 950 published computational neuroscience models, seeks to promote model reuse and reproducibility. Code sharing is a first step; however, model source code is often large and not easily understood. To aid users, we have developed ModelView, a web application for ModelDB that presents a graphical view of model structure augmented with contextual information for NEURON and NEURON-runnable (e.g. NeuroML, PyNN) models. Web presentation provides a rich, simulator-independent environment for interacting with graphs. The necessary data is generated by combining manual curation, text-mining the source code, querying ModelDB, and simulator introspection. Key features of the user interface along with the data analysis, storage, and visualization algorithms are explained. With this tool, researchers can examine and assess the structure of hundreds of models in ModelDB in a standardized presentation without installing any software, downloading the model, or reading model source code.

Modeling phage induced bacterial disinfection rates and the resulting design implications.

The phage induced disinfection rates of Escherichia coli K-12 MG1655 in the presence of coliphage Ec2 were determined under a wide range of phage and bacterial concentrations. These rates were elucidated to determine if phages could be used in water and wastewater treatment systems as a biological based disinfectant. Disinfection rates ranging from 0.13 ± 0.1 to 2.03 ± 0.1 h⁻¹ were observed for E. coli K12. A multiple linear regression model was used to explain the variance in the disinfection rates, and this model demonstrated an interaction effect between the initial phage and bacterial concentrations. Furthermore, the results were modeled with particle aggregation theory, which over predicted the disinfection rates at higher phage and bacterial concentrations, suggesting additional interactions. Finally, the observed and predicted disinfection rates were used to determine additional design parameters. The results suggested that a phage based disinfection process may be suitable for the inactivation of specific pathogens in plug flow reactors, such as the pathogens in hospital wastewater effluents and the bacteria responsible for foaming and sludge bulking in activated sludge processes.

Semi-automated population of an online database of neuronal models (ModelDB) with citation information, using PubMed for validation.

Citations play an important role in medical and scientific databases by indicating the authoritative source of the data. Manual citation entry is tedious and prone to errors. We describe a method and make available computer scripts which automate the process of citation entry. We use an open citation project PERL module (PARSER) for parsing citation data that is then used to retrieve PubMed records to supply the (validated) reference. Our PERL scripts are available via a link in the web references section of this article.

The long-term effects of phage concentration on the inhibition of planktonic bacterial cultures.

Since the early 1920s there has been an interest in using bacteriophages (phages) for the control of bacterial pathogens. While there are many factors that have limited the success of phage bio-control, one particular problem is the variability of outcomes between phages and bacteria. Specifically, there is a significant need for a better understanding of how initial phage concentrations affect long-term bacterial inhibition. In work reported herein three phages were isolated for Escherichia coli K12, Pseudomonas aeruginosa PAO1, as well as Bacillus cereus and bio-control experiments were performed with phage concentrations ranging from 10(5) to 10(8) plaque forming units per mL over the course of 72 h. For four of the nine phages isolated there was a linear relationship between inhibition and phage concentration, suggesting the effect of phage concentration is important at longer time scales. For three of the isolated phages, phage concentrations had no effect on bacterial inhibition suggesting that even at the lowest concentration the method of action was saturated and lower concentrations might still be effective. Additionally, a cocktail was created and was compared to the previously isolated phages. There was no statistical difference between the cocktail and the best performing phage highlighting the importance of selecting the appropriate phages for treatment. These results suggest that, for certain phages, there is a strong relationship between phage concentration and long-term bacterial growth inhibition and the initial phage concentration is an important indicator of the long-term outcome.