Known and Unknown Transboundary Infectious Diseases as Hybrid Threats.

The pathogenicity, transmissibility, environmental stability, and potential for genetic manipulation make microbes hybrid threats that could blur the distinction between peace and war. These agents can fall below the detection, attribution, and response capabilities of a nation and seriously affect their health, trade, and security. A framework that could enhance horizon scanning regarding the potential risk of microbes used as hybrid threats requires not only accurately discriminating known and unknown pathogens but building novel scenarios to deploy mitigation strategies. This demands the transition of analyst-based biosurveillance tracking a narrow set of pathogens toward an autonomous biosurveillance enterprise capable of processing vast data streams beyond human cognitive capabilities. Autonomous surveillance systems must gather, integrate, analyze, and visualize billions of data points from different and unrelated sources. Machine learning and artificial intelligence algorithms can contextualize capability information for different stakeholders at different levels of resolution: strategic and tactical. This document provides a discussion of the use of microorganisms as hybrid threats and considerations to quantitatively estimate their risk to ensure societal awareness, preparedness, mitigation, and resilience.

What We Need to Consider During and After the SARS-CoV-2 Pandemic.

Even though extreme containment and mitigation strategies were implemented by numerous governments around the world to slow down the spread of severe acute respiratory syndrome coronavirus-2 (SARS-CoV-2), the number of critically ill patients and fatalities keeps rising. This crisis has highlighted the socioeconomic disparities of health care systems within and among countries. As new CoVID policies and responses are implemented to lessen the impact of the virus, it is imperative (1) to consider additional mitigation strategies critical for the development of effective countermeasures, (2) to promote long-term policies and strict regulations of the trade of wildlife and live animal markets, and (3) to advocate for necessary funding and investments in global health, specifically for the prevention of and response to natural and manmade pandemics. This document considers some of these challenges.

Biosurveillance enterprise for operational awareness, a genomic-based approach for tracking pathogen virulence.

To protect our civilians and warfighters against both known and unknown pathogens, biodefense stakeholders must be able to foresee possible technological trends that could affect their threat risk assessment. However, significant flaws in how we prioritize our countermeasure-needs continue to limit their development. As recombinant biotechnology becomes increasingly simplified and inexpensive, small groups, and even individuals, can now achieve the design, synthesis, and production of pathogenic organisms for offensive purposes. Under these daunting circumstances, a reliable biosurveillance approach that supports a diversity of users could better provide early warnings about the emergence of new pathogens (both natural and manmade), reverse engineer pathogens carrying traits to avoid available countermeasures, and suggest the most appropriate detection, prophylactic, and therapeutic solutions. While impressive in data mining capabilities, real-time content analysis of social media data misses much of the complexity in the factual reality. Quality issues within freeform user-provided hashtags and biased referencing can significantly undermine our confidence in the information obtained to make critical decisions about the natural vs. intentional emergence of a pathogen. At the same time, errors in pathogen genomic records, the narrow scope of most databases, and the lack of standards and interoperability across different detection and diagnostic devices, continue to restrict the multidimensional biothreat assessment. The fragmentation of our biosurveillance efforts into different approaches has stultified attempts to implement any new foundational enterprise that is more reliable, more realistic and that avoids the scenario of the warning that comes too late. This discussion focus on the development of genomic-based decentralized medical intelligence and laboratory system to track emerging and novel microbial health threats in both military and civilian settings and the use of virulence factors for risk assessment. Examples of the use of motif fingerprints for pathogen discrimination are provided.

Biodefense Oriented Genomic-Based Pathogen Classification Systems: Challenges and Opportunities.

Countermeasures that will effectively prevent or diminish the impact of a biological attack will depend on the rapid and accurate generation and analysis of genomic information. Because of their increasing level of sensitivity, rapidly decreasing cost, and their ability to effectively interrogate the genomes of previously unknown organisms, Next Generation Sequencing (NGS) technologies are revolutionizing the biological sciences. However, the exponential accumulation microbial data is equally outpacing the computational performance of existing analytical tools in their ability to translate DNA information into reliable detection, prophylactic and therapeutic countermeasures. It is now evident that the bottleneck for next-generation sequence data analysis will not be solved simply by scaling up our computational resources, but rather accomplished by implementing novel biodefense-oriented algorithms that overcome exiting vulnerabilities of speed, sensitivity and accuracy. Considering these circumstances, this document highlights the challenges and opportunities that biodefense stakeholders must consider in order to exploit more efficiently genomic information and translate this data into integrated countermeasures. The document overviews different genome analysis methods and explains concepts of DNA fingerprints, motif fingerprints, genomic barcodes and genomic signatures. A series of recommendations to promote genomics and bioinformatics as an effective form of deterrence and a valuable scientific platform for rapid technological insertion of detection, prophylactic, therapeutic countermeasures are discussed.

Bioinformatics for biodefense: challenges and opportunities.

The intentional release of traditional or combinatorial bioweapons remains one of the most important challenges that will continue to shape homeland security. The misuse of dual-use and how-to methods and techniques in the fields of molecular, synthetic, and computational biology can lessen the technical barriers for launching attacks, even for small groups or individuals. Bioinformatics is guiding the implementation of several biodefense countermeasures. However, existing algorithms have not effectively translated available pathogen genomic data into standardized diagnostics, rational vaccine development, or broad spectrum therapeutics. Despite its potential, bioinformatics has a limited impact on forensic and intelligence operations. More than 12 biodefense databases and information exchange architectures lack interoperability and a common layer that restricts scalability and the development of biodefense enterprises. Therefore, in order to use next-generation genome sequencing for medical intelligence, forensic operations, biothreat awareness, and mitigation, the attention has to be redirected toward the development of computational biology applications. This article debates some of the challenges that the bioinformatics field confronts in terms of biodefense problems and proposes potential opportunities to use pathogen genomic data. Issues related to the analysis of pathogen genomes and emerging methods including genomic barcoding, active curation, and knowledge management and their impact on intelligence, forensics, and policymaking are discussed.

Transcriptional interactions during smallpox infection and identification of early infection biomarkers.

Smallpox is a deadly disease that can be intentionally reintroduced into the human population as a bioweapon. While host gene expression microarray profiling can be used to detect infection, the analysis of this information using unsupervised and supervised classification techniques can produce contradictory results. Here, we present a novel computational approach to incorporate molecular genome annotation features that are key for identifying early infection biomarkers (EIB). Our analysis identified 58 EIBs expressed in peripheral blood mononuclear cells (PBMCs) collected from 21 cynomolgus macaques (Macaca fascicularis) infected with two variola strains via aerosol and intravenous exposure. The level of expression of these EIBs was correlated with disease progression and severity. No overlap between the EIBs co-expression and protein interaction data reported in public databases was found. This suggests that a pathogen-specific re-organization of the gene expression and protein interaction networks occurs during infection. To identify potential genome-wide protein interactions between variola and humans, we performed a protein domain analysis of all smallpox and human proteins. We found that only 55 of the 161 protein domains in smallpox are also present in the human genome. These co-occurring domains are mostly represented in proteins involved in blood coagulation, complement activation, angiogenesis, inflammation, and hormone transport. Several of these proteins are within the EIBs category and suggest potential new targets for the development of therapeutic countermeasures.