Suchergebnisse

Addressing the threat of infectious diseases, whether natural, the results of a laboratory accident, or a deliberate act of bioterrorism, requires no corner of the world be ignored. The mobility of infectious agents and their rapid adaptability, whether to climate change or socioeconomic drivers or both, demand the science employed to understand these processes be advanced and tailored to a country or a region, but with a global vision. In many parts of the world, largely because of economic struggles, scientific capacity has not kept pace with the need to accomplish this goal and has left these regions and hence the world vulnerable to infectious disease outbreaks. To build scientific capability in a developing region requires cooperation and participation of experienced international scientists who understand the issues and are committed to educate the next generations of young investigators in the region. These efforts need to be coupled with the understanding and resolve of local governments and international agencies to promote an aggressive science agenda. International collaborative scientific investigation of infectious diseases not only adds significantly to scientific knowledge, but it promotes health security, international trust, and long-term economic benefit to the region involved. This premise is based on the observation that the most powerful human inspiration is that which brings peoples together to work on and solve important global challenges. The republics of the former Soviet Union provide a valuable case study for the need to rebuild scientific capacity as they are located at the crossroads where many of the world's great epidemics began. The scientific infrastructure and disease surveillance capabilities of the region suffered significant decline after the breakup of the Soviet Union. The U.S. Cooperative Threat Reduction (CTR) Program, a part of the U.S. Department of Defense, together with partner countries, have worked diligently to improve the capabilities in this region to guard ...

Background The detection of pathogens in complex sample backgrounds has been revolutionized by wide access to next-generation sequencing (NGS) platforms. However, analytical methods to support NGS platforms are not as uniformly available. Pathosphere (found at Pathosphere.org) is a cloud - based open - sourced community tool that allows for communication, collaboration and sharing of NGS analytical tools and data amongst scientists working in academia, industry and government. The architecture allows for users to upload data and run available bioinformatics pipelines without the need for onsite processing hardware or technical support. Results The pathogen detection capabilities hosted on Pathosphere were tested by analyzing pathogen-containing samples sequenced by NGS with both spiked human samples as well as human and zoonotic host backgrounds. Pathosphere analytical pipelines developed by Edgewood Chemical Biological Center (ECBC) identified spiked pathogens within a common sample analyzed by 454, Ion Torrent, and Illumina sequencing platforms. ECBC pipelines also correctly identified pathogens in human samples containing arenavirus in addition to animal samples containing flavivirus and coronavirus. These analytical methods were limited in the detection of sequences with limited homology to previous annotations within NCBI databases, such as parvovirus. Utilizing the pipeline-hosting adaptability of Pathosphere, the analytical suite was supplemented by analytical pipelines designed by the United States Army Medical Research Insititute of Infectious Diseases and Walter Reed Army Institute of Research (USAMRIID-WRAIR). These pipelines were implemented and detected parvovirus sequence in the sample that the ECBC iterative analysis previously failed to identify. Conclusions By accurately detecting pathogens in a variety of samples, this work demonstrates the utility of Pathosphere and provides a platform for utilizing, modifying and creating pipelines for a variety of NGS technologies developed to detect pathogens in complex sample backgrounds. These results serve as an exhibition for the existing pipelines and web-based interface of Pathosphere as well as the plug-in adaptability that allows for integration of newer NGS analytical software as it becomes available.