Changes in attachment and metabolic activity of rat neonatal cardiomyocytes and nonmyocytes caused by Macrovipera lebetina obtusa venom

The Caucasian viper Macrovipera lebetina obtusa (MLO) is one of the most prevalent and venomous snakes in the Caucasus and the surrounding regions, yet the effects of MLO venom on cardiac function remain largely unknown. We examined the influence of MLO venom (crude and with inhibited metalloproteinases and phospholipase A2) on attachment and metabolic activity of rat neonatal cardiomyocytes (CM) and nonmyocytes (nCM), assessed at 1 and 24 h. After exposing both CM and nCM to varying concentrations of MLO venom, we observed immediate cytotoxic effects at a concentration of 100 μg/ml, causing detachment from the culture substrate. At lower MLO venom concentrations both cell types detached in a dose-dependent manner. Inhibition of MLO venom metalloproteinases significantly improved CM and nCM attachment after 1-hour exposure. At 24-hour exposure to metalloproteinases inhibited venom statistically significant enhancement was observed only in nCM attachment. However, metabolic activity of CM and nCM did not decrease upon exposure to the lower dose of the venom. Moreover, we demonstrated that metalloproteinases and phospholipases A2 are not the components of the MLO venom that change metabolic activity of both CM and nCM. These results provide a valuable platform to study the impact of MLO venom on prey cardiac function. They also call for further exploration of individual venom components for pharmaceutical purposes.

Open Source Health Intelligence (OSHINT) for Foodborne Illness Event Characterization

Objective

We propose a cloud-based Open Source Health Intelligence (OS-HINT) system that uses open source media outlets, such as Twitter and RSS feeds, to automatically characterize foodborne illness events in real-time. OSHINT also forecasts response requirements, through predictive models, to allow more efficient use of resources, personnel, and countermeasures in biological event response.

Introduction

An increasing amount of global discourse reporting has migrated to the online space, in the form of publicly accessible social media outlets, blogs, wikis, and news feeds. Social media also presents publicly available and highly accessible information about individual, real-time activity that can be leveraged to detect, monitor, and more efficiently respond to biological events.

Methods

Salmonella and Escherichia Coli (E. coli) events were selected based on the magnitude and number of reported outbreaks to the Centers for Disease Control (CDC) in the last ten years (1). These events affect multiple states and were large enough to ensure appropriate confidence levels when developing response metrics obtained from our prediction models. We collected social media data between 2006 – 2012 due to the emergence of Twitter, Facebook, and other social media utilization during this time period.

Characterization is defined as the process of identifying specific event features that inform overall situational awareness. The number hospitalized, dead, or injured, in addition to patient demographics and symptoms were determined to be useful for our characterization and forecast event metrics. Analytical methods, such as term-frequency-inverse document frequency (TF-IDF), natural language processing (NLP), and information extraction, were used to characterize events according to our metrics. Lexicon development, during NLP implementation, was generated from online news articles used to describe the events. Lastly, forecasting algorithms were developed to predict the potential response based on similar historical events that were initially characterized by our information extraction algorithms.

Results

The OSHINT system was developed in Amazon Web Services and includes real-time social media collection for event characterization (see Figure 1). OSHINT currently characterizes number of victims ill, hospitalized, and dead due to foodborne illness events.

OSHINT was used to characterize the recent national 2012 Salmonella event related to cantaloupes, during which OSHINT characterized social media posts related to the event, as news articles and Twitter tweets streamed into the system (Figure 2). On August 17, 2012 the OSHINT system identified a large increase in Twitter tweets mentioning salmonella. Social media data found absent (victims missing work or school day), death, hospital, and sick events to involve 2, 4, 17, 283 media mentions, respectively. Our TF-IDF algorithm characterized the salmonella event impact as two dead and 150 sickened by salmonella-tainted cantaloupe. Retrospective analysis of CDC reported data on August 30, 2012 indicated the salmonella event involved two deaths in 204 cases (2).

Conclusions

The OSHINT team is continually developing and refining characterization and forecasting algorithms used in the system. Upon completion, OSHINT will characterize symptoms, geography, and demographics for E. coli and Salmonella events. The system will also forecast number sick, dead, and hospitalized for an effective and quick response. We will refine our algorithms and evaluate the system against past and future events to provide confidence in our results.

Characterization of coding synonymous and non-synonymous variants in ADAMTS13 using ex vivo and in silico approaches

Synonymous variations, which are defined as codon substitutions that do not change the encoded amino acid, were previously thought to have no effect on the properties of the synthesized protein(s). However, mounting evidence shows that these “silent” variations can have a significant impact on protein expression and function and should no longer be considered “silent”. Here, the effects of six synonymous and six non-synonymous variations, previously found in the gene of ADAMTS13, the von Willebrand Factor (VWF) cleaving hemostatic protease, have been investigated using a variety of approaches. The ADAMTS13 mRNA and protein expression levels, as well as the conformation and activity of the variants have been compared to that of wild-type ADAMTS13. Interestingly, not only the non-synonymous variants but also the synonymous variants have been found to change the protein expression levels, conformation and function. Bioinformatic analysis of ADAMTS13 mRNA structure, amino acid conservation and codon usage allowed us to establish correlations between mRNA stability, RSCU, and intracellular protein expression. This study demonstrates that variants and more specifically, synonymous variants can have a substantial and definite effect on ADAMTS13 function and that bioinformatic analysis may allow development of predictive tools to identify variants that will have significant effects on the encoded protein.

Analysis of F9 point mutations and their correlation to severity of haemophilia B disease

Haemophilia B is an X-linked recessive disorder caused by deficiency of functional coagulation factor IX, which results almost exclusively from mutations in the F9 gene. We sought to determine features, which could distinguish between mutations that cause severe disease symptoms from those that cause non-severe disease symptoms. Towards this objective, we have performed a statistical analysis of reported point mutations in F9. These include: potential local changes in mRNA free energy, codon usage, charge and type of mutated amino acid, location of the mutation with regard to protein secondary structure and functional domain and amino acids' evolutionary conservation scores. Wilcoxon signed-rank tests showed highly significant differences between severe and non-severe disease causing mutations in their effect on free energy of small mRNA fragments and evolutionarily conserved amino acids. Our results suggest that information at the mRNA level as well as conservation of the amino acid correlate well with disease severity. This study demonstrates that computational tools may be used to characterize the severity of haemophilia B associated with point mutations and suggests their utility in predicting the outcome of sequence changes in recombinant proteins.

Characterization of conformation-sensitive antibodies to ADAMTS13, the von Willebrand cleavage protease

Background

The zinc metalloprotease ADAMTS13 is a multidomain protein that cleaves von Willebrand Factor (VWF) and is implicated in Thrombotic Thrombocytopenic Purpura (TTP) pathogenesis. Understanding the mechanism of this protein is an important goal. Conformation sensitive antibodies have been used to monitor protein conformation and to decipher the molecular mechanism of proteins as well as to distinguish functional and non-functional mutants.

Methodology/Principal Findings

We have characterized several antibodies against ADAMTS13, both monoclonal and polyclonal. We have used flow cytometry to estimate the binding of these antibodies to ADAMTS13 and demonstrate that antibodies raised against the TSP and disintegrin domains detect conformation changes in the ADAMTS13. Thus for example, increased binding of these antibodies was detected in the presence of the substrate (VWF), mainly at 37°C and not at 4°C. These antibodies could also detect differences between wild-type ADAMTS13 and the catalytically deficient mutant (P475S). The flow cytometry approach also allows us to estimate the reactivity of the antibody as well as its apparent affinity.

Conclusions/Significance

Our results suggest that these antibodies may serve as useful reagents to distinguish functional and non-functional ADAMTS13 and analyze conformational transitions to understand the catalytic mechanism.