Integrative omics identifies conserved and pathogen-specific responses of sepsis-causing bacteria

Even in the setting of optimal resuscitation in high-income countries severe sepsis and septic shock have a mortality of 20-40%, with antibiotic resistance dramatically increasing this mortality risk. To develop a reference dataset enabling the identification of common bacterial targets for therapeutic intervention, we applied a standardized genomic, transcriptomic, proteomic and metabolomic technological framework to multiple clinical isolates of four sepsis-causing pathogens: Escherichia coli, Klebsiella pneumoniae species complex, Staphylococcus aureus and Streptococcus pyogenes. Exposure to human serum generated a sepsis molecular signature containing global increases in fatty acid and lipid biosynthesis and metabolism, consistent with cell envelope remodelling and nutrient adaptation for osmoprotection. In addition, acquisition of cholesterol was identified across the bacterial species. This detailed reference dataset has been established as an open resource to support discovery and translational research.

A web-based, patient driven registry for Angelman syndrome: the global Angelman syndrome registry

Angelman syndrome (AS) is a rare neurodevelopmental disorder that is characterised by severe global developmental delays, ataxia, loss of speech, epilepsy, sleep disorders, and a happy disposition. There is currently no cure for AS, though several pharmaceutical companies are anticipating drug trials for new therapies to treat AS. The Foundation for Angelman Therapeutics (FAST) Australia therefore identified a need for a global AS patient registry to identify patients for recruitment for clinical trials.The Global AS Registry was deployed in September 2016 utilising the Rare Disease Registry Framework, an open-source tool that enables the efficient creation and management of patient registries. The Global AS Registry is web-based and allows parents and guardians worldwide to register, provide informed consent, and enter data on individuals with AS. 286 patients have registered in the first 8 months since deployment.We demonstrate the successful deployment of the first patient-driven global registry for AS. The data generated from the Global AS Registry will be crucial in identifying patients suitable for clinical trials and in informing research that will identify treatments for AS, and ultimately improve the lives of individuals and their families living with AS.

Design of the Familial Hypercholesterolaemia Australasia Network Registry: Creating Opportunities for Greater International Collaboration

Familial Hypercholesterolemia (FH) is the most common and serious monogenic disorder of lipoprotein metabolism that leads to premature coronary heart disease. There are over 65,000 people estimated to have FH in Australia, but many remain undiagnosed. Patients with FH are often undertreated, but with early detection, cascade family testing and adequate treatment, patient outcomes can improve. Patient registries are key tools for providing new information on FH and enhancing care worldwide. The development and design of the FH Australasia Network Registry is a crucial component in the comprehensive model of care for FH, which aims to provide a standardized, high-quality and cost-effective system of care that is likely to have the highest impact on patient outcomes. Informed by stakeholder engagement, the FH Australasia Network Registry was collaboratively developed by government, patient and clinical networks and research groups. The open-source, webbased Rare Disease Registry Framework was the architecture chosen for this registry owing to its open-source standards, modular design, interoperability, scalability and security features; all these are key components required to meet the ever changing clinical demands across regions. This paper provides a high level blueprint for other countries and jurisdictions to help inform and map out the critical features of an FH registry to meet their particular health system needs.

Design of a framework for the deployment of collaborative independent rare disease-centric registries: Gaucher disease registry model

Orphan drug clinical trials often are adversely affected by a lack of high quality treatment efficacy data that can be reliably compared across large patient cohorts derived from multiple governmental and country jurisdictions. It is critical that these patient data be captured with limited corporate involvement. For some time, there have been calls to develop collaborative, non-proprietary, patient-centric registries for post-market surveillance of aspects related to orphan drug efficacy. There is an urgent need for the development and sustainable deployment of these ‘independent’ registries that can capture comprehensive clinical, genetic and therapeutic information on patients with rare diseases. We therefore extended an open-source registry platform, the Rare Disease Registry Framework (RDRF) to establish an Independent Rare Disease Registry (IRDR). We engaged with an established rare disease community for Gaucher disease to determine system requirements, methods of data capture, consent, and reporting. A non-proprietary IRDR model is presented that can serve as autonomous data repository, but more importantly ensures that the relevant data can be made available to appropriate stakeholders in a secure, timely and efficient manner to improve clinical decision-making and the lives of those with a rare disease.

Yabi: An online research environment for grid, high performance and cloud computing

BACKGROUND

There is a significant demand for creating pipelines or workflows in the life science discipline that chain a number of discrete compute and data intensive analysis tasks into sophisticated analysis procedures. This need has led to the development of general as well as domain-specific workflow environments that are either complex desktop applications or Internet-based applications. Complexities can arise when configuring these applications in heterogeneous compute and storage environments if the execution and data access models are not designed appropriately. These complexities manifest themselves through limited access to available HPC resources, significant overhead required to configure tools and inability for users to simply manage files across heterogenous HPC storage infrastructure.

RESULTS

In this paper, we describe the architecture of a software system that is adaptable to a range of both pluggable execution and data backends in an open source implementation called Yabi. Enabling seamless and transparent access to heterogenous HPC environments at its core, Yabi then provides an analysis workflow environment that can create and reuse workflows as well as manage large amounts of both raw and processed data in a secure and flexible way across geographically distributed compute resources. Yabi can be used via a web-based environment to drag-and-drop tools to create sophisticated workflows. Yabi can also be accessed through the Yabi command line which is designed for users that are more comfortable with writing scripts or for enabling external workflow environments to leverage the features in Yabi. Configuring tools can be a significant overhead in workflow environments. Yabi greatly simplifies this task by enabling system administrators to configure as well as manage running tools via a web-based environment and without the need to write or edit software programs or scripts. In this paper, we highlight Yabi's capabilities through a range of bioinformatics use cases that arise from large-scale biomedical data analysis.

CONCLUSION

The Yabi system encapsulates considered design of both execution and data models, while abstracting technical details away from users who are not skilled in HPC and providing an intuitive drag-and-drop scalable web-based workflow environment where the same tools can also be accessed via a command line. Yabi is currently in use and deployed at multiple institutions and is available at http://ccg.murdoch.edu.au/yabi.