For users who need simplistic, high-confidence, actionable information from genomic data, Battelle’s UltraSEQ software provides a cloud-deployed flexible system architecture, high-quality data, and algorithms for pathogen and biothreat identification. UltraSEQ’s base functionality takes input genomic data and efficiently outputs prediction results for taxonomy, biothreat function, and a user-defined rules engine backed by Battelle's curated Sequence of Concern Database. Applications in sample analysis, biosurveillance, and diagnostics will be presented.

We have leveraged innovations in sensor miniaturization and rapid thermocycling to develop xBIRD, a fully integrated and automated biothreat agent detection system. The device draws in an aerosolized sample, performs sample extraction and lysis, amplifies target nucleic acids, and generates a result in under 5 minutes. Current work is underway to adapt the device to a form factor which can adapt to multiple operational scenarios.

Diagnostic assays are crucial tools to test, diagnose and treat infectious and other diseases. They continue to remain extremely valuable in the current COVID-19 pandemics not only to provide appropriate health care for infected and symptomatic individuals as needed but also for implementing public health measures such as test, trace and isolate infected and asymptomatic individuals to prevent further transmission of the virus. Sustained transmission and unhindered proliferation of the pathogen across the population during a continuous, ongoing pandemic such as COVID-19, has resulted in many variants with mutations. These mutations may lead to signature erosion, a phenomenon wherein diagnostic tests developed using the genetic sequence of the original pathogen may fail and cause false-negative results in a sample containing a new variant. We have developed a tool called PSET (PCR Signature Erosion Tool) to monitor the performance of diagnostic tests in silico using the genome sequences of pathogens. We will present and discuss our data on Ebola, Lassa, and SARS-CoV-2 in demonstrating the power of real-time in silico monitoring on identifying diagnostics failures, thereby driving rapid modification of assays if signature erosion is evident.

Nanopore sequencing technology has enabled numerous applications for rapidly identifying and characterizing biological threats. Warfighters are being trained to execute these protocols, which will revolutionize biothreat detection in the field. Methods for sample/library preparation are being further simplified/automated for use by non-laboratory trained operators, and bioinformatics software was designed to automatically identify biothreats in real-time. In addition, protocols have been used to monitor for SARS-CoV-2 variants among warfighter populations.

Air sampling for SARS-CoV-2 within the built environment has been challenging due to the interaction of many factors. Sampling strategies must account for aerosol emission rates from infectious individuals, environmental factors including controls and mitigation efforts, collection techniques, and identification methods. An overall synopsis of these factors and an approach to determining a sampling and analysis strategy will be discussed.

A fluorescently-labeled fibrin clot lysis assay utilizing a unique annular clot geometry will be discussed. Physiologically-relevant fibrin formulations, with microstructure that resembles in vivo, were validated achieving high assay sensitivity. Clot characteristics were examined using thromboelastography (TEG), turbidity, SEM, and confocal microscopy. Sample fibrinolytic activities at varying plasmin, plasminogen, and tissue plasminogen activator (tPA) concentrations were assessed to demonstrate assay capabilities for use in determining a subject’s fibrinolytic state.

Oligo supply delays slow down the labs responsible for biothreat detection and monitoring, hindering rapid response. With the SYNTAX System, powered by Enzymatic DNA Synthesis from DNA Script, any lab can print DNA primers and probes on-demand multiple times per day, allowing labs to maintain security and control over the biothreat response. In this talk, we present data from qPCR, FISH, and NGS applications for viral detection and variant analysis.

Available methods for biological aerosol collection and identification are slow and require manual intervention. In order to achieve rapid, automated, and unmanned identification of aerosolized biothreats, we have developed a portable low-cost prototype that couples a customized microwell aerosol collector with an automated elution module and conducts fully-automated sample preparation and loop-mediated isothermal amplification (LAMP) analysis for rapid and accurate biothreat identification.

In light of the COVID pandemic, detecting airborne pathogens is more important than ever. For an aerosol diagnostic to be useful, it must be able to supply accurate results within minutes of detection, which in turn will facilitate the rapid deployment of the appropriate mitigations. During my presentation, I will detail how Smiths Detection, a global leader in threat detection, adapted its BioFlash instrument to be capable of detecting SARS-CoV-2.

A fast, sensitive, specific, and accurate detection method to determine active infection by Bacillus anthracis in plasma has been developed. The inhalation form of Bacillus anthracis infection can rapidly lead to a serious blood infection.  There is a limited window of time for diagnosis and successful use of antibiotics.  The List method detects the presence of anthrax lethal factor (LF), which appears in the blood early in an infection. A fluorescently labeled peptide substrate, MAPKKide Plus, which is not cleaved by plasma proteases and thus is specific for LF, was identified and is adaptable to a point-of-care diagnostic.

Biodefense laboratories have relied on traditional molecular methods such as PCR and immunological assays for rapid detection of biological threats for over 20 years. While these methods are sensitive and provide critical early warning of biological threats, they are limited to detecting specific pathogens that can be present in the environment naturally. Characterizing the environmental background is important to interpreting results from these methods. Developing pathogen-agnostic methods is needed to detect emerging and advanced biological threats to address advances in biotechnology and the biothreat landscape. We developed and piloted a metagenomics method to characterize the environmental background of indoor and outdoor aerosol samples for spatial and temporal differences. Results from this characterization can provide additional information during a biothreat incident to ensure confidence in results and enhance decision-making and response.

Building from our prior work developing a degenerate k-mer method to accommodate high intra-sequence variation of RNA virus genomes for modeling frameworks, and leveraging a taxonomic ‘group-shuffle-split’ paradigm on complete coronavirus assemblies from prior to October 2018, we trained multiple regularized logistic regression classifiers at the nucleotide k-mer level capable of accurately predicting withheld SARS-CoV-2 genome sequences as human pathogens and accurately predicting withheld Swine Acute Diarrhea Syndrome coronavirus (SADS-CoV) genome sequences as non-human pathogens. LASSO feature selection identified several degenerate nucleotide predictor motifs with high model coefficients for the human pathogen class that were present across widely disparate classes of coronaviruses. We discuss the utility of predictive models (and their associated predictor motifs) to novel biosurveillance protocols that substantially increase the ‘pound-for-pound’ information content of field-collected sequencing data and make a strong argument for the necessity of routine collection and sequencing of zoonotic viruses.

About 60% of known human pathogens are known to have originated from animals. The emergence and re-emergence of zoonotic infectious agents pose a considerable risk to global health. The increased frequency of international movement of the human and animal population can potentially lead to a rapid spread of the emerging zoonotic pathogens. Early detection is vital for developing a comprehensive approach to contain outbreaks of zoonotic pathogens. Here I will discuss sensitive detection tools and efficient sampling strategies for surveillance studies.