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Technologies to Enable Autonomous Detection for BioWatch: Ensuring Timely and Accurate Information for Public Health Officials: Workshop Summary (2014)

Chapter:Appendix I: White Paper 4: State of the Art for Autonomous Detection Systems Using Genomic Sequencing

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Suggested Citation:"Appendix I: White Paper 4: State of the Art for Autonomous Detection Systems Using Genomic Sequencing." Institute of Medicine and National Research Council. 2014. Technologies to Enable Autonomous Detection for BioWatch: Ensuring Timely and Accurate Information for Public Health Officials: Workshop Summary. Washington, DC: The National Academies Press. doi: 10.17226/18495.
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I

State of the Art for Autonomous Detection
Systems Using Genomic Sequencing

John Chris Detter, Ph.D., and I. Gary Resnick, Ph.D.

A white paper prepared for the June 25–26, 2013, workshop on Strategies for Cost-Effective and Flexible Biodetection Systems That Ensure Timely and Accurate Information for Public Health Officials, hosted by the Institute of Medicine’s Board on Health Sciences Policy and the National Research Council’s Board on Life Sciences. The authors are responsible for the content of this article, which does not necessarily represent the views of the Institute of Medicine or the National Research Council.

BACKGROUND

The BioWatch Program at the Department of Homeland Security (DHS) was developed and is currently operating to provide warnings of aerosol attacks with biological threat agents. A select number of urban centers have had BioWatch deployed for a number of years on a round-the-clock basis. These deployments have provided a great amount of operational experience that indicates great need for technology improvement. While the current BioWatch capability provides an important risk mitigation capability against biological warfare and terrorist (BW/BT) threats; many operationally significant challenges remain to be addressed. A brief description of the desired capability, with extant challenges, is presented below to provide a framework for discussion of technical approaches employing sequencing to address current technology limitations.

Suggested Citation:"Appendix I: White Paper 4: State of the Art for Autonomous Detection Systems Using Genomic Sequencing." Institute of Medicine and National Research Council. 2014. Technologies to Enable Autonomous Detection for BioWatch: Ensuring Timely and Accurate Information for Public Health Officials: Workshop Summary. Washington, DC: The National Academies Press. doi: 10.17226/18495.
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Affordable Continuous Coverage of At-Risk Populations

The population of the United States is dispersed across a large landmass. People converge to great population densities at numerous venues for varying lengths of time (e.g., day/night workday cycles between cities and suburbs and special-event gatherings). Therefore, BioWatch must cover a large geographic area and varied indoor structures (e.g., special event centers, office buildings, transit centers, and underground rail systems). To achieve this in a sustainable manner the capital and annual operating costs of the system must be commensurate with the assessed relative risk from BW/BT and the myriad of other needs faced by local, state, and federal officials.

The current BioWatch system uses field aerosol concentration and sample collection, followed by the transport of samples back to a central laboratory and laboratory analysis of the samples. BioWatch data outputs are provided to a decision-making body for an integrated analysis prior to taking response actions. Major decreases in the resources required for BioWatch as well as improvements in the overall efficiency and effectiveness can be achieved through technical advances that provide for field in situ detection and identification (an autonomous deployed detector) to eliminate sample transport and laboratory analysis costs; amplification-free nucleic acid detection to decrease reagent costs; reagent-free detection to decrease reagent costs, eliminate the need for environmental engineering controls, and minimize the need for electrical power for the deployed autonomous detector; inexpensive analysis of agent recognition events within the autonomous detector to decrease sensor unit production cost and maintenance; and system modularity to minimize technology refresh costs.

Accuracy and Precision Supporting High-Regret Responses

Surveillance derives its value by informing response management systems that have the potential for eliminating or mitigating the impacts of risks. Response options vary in efficacy, cost, and associated negative consequences. There are also negative impacts associated with false-positive system outputs. Therefore, the accuracy and precision of the BioWatch system have a profound impact on overall system performance, value, and sustainability.

Operational experience with the current BioWatch system indicates a strong need for improved accuracy while maintaining robust precision.

Suggested Citation:"Appendix I: White Paper 4: State of the Art for Autonomous Detection Systems Using Genomic Sequencing." Institute of Medicine and National Research Council. 2014. Technologies to Enable Autonomous Detection for BioWatch: Ensuring Timely and Accurate Information for Public Health Officials: Workshop Summary. Washington, DC: The National Academies Press. doi: 10.17226/18495.
×

The great diversity of the microbial world coupled with the fact that only a fraction of this diversity has been identified and characterized has resulted in a significant number of “environmental positives” that have adversely impacted BioWatch performance. The fact that no aerosol attacks have been detected and that no impacts of such attacks have been observed provides little evidence for understanding the false-negative potential. This is greatly compounded by the inherent uncertainty of the biothreat.

Responsiveness to Full Scope of Biological Warfare
and Terrorist Threats

The uncertainty associated with the biothreat (e.g., which agents will be encountered at which locations, when it will occur, how much will be delivered, and how it will be dispersed) provides great operational constraints on BioWatch. A large number of detector units are needed to cover populations at risk, and the system should be responsive to all potential biothreat agents (including emerging, re-emerging, and engineered pathogens) that may be presented as aerosol threats. In addition, an indication of unique agent phenotypic characteristics is desirable in order to guide response decisions (e.g., whether the specific strain encountered is responsive to a particular antibiotic).

The current BioWatch system is focused on a specific set of pathogens and provides some level of identification. To be fully responsive to the potential bioaerosol threat, the scope of agents addressed must be greatly increased and the cost of coverage must be drastically decreased.

CURRENT STATE OF SEQUENCING

Next-generation sequencing (NGS) platforms have remarkable performance specifications. Most of them produce very high quality data in an automated or semiautomated fashion. Some are small, benchtop models, able to produce large amounts of data in a relatively short time and for a relatively low cost. The rapid advancement in NGS technologies will soon enable pathogen detection devices to rely on sequencing to provide a wealth of information about the environment in a cost-effective and timely manner.

NGS technologies can be used to sequence almost any sample containing biological material, such as clinical (human, animal), environ-

Suggested Citation:"Appendix I: White Paper 4: State of the Art for Autonomous Detection Systems Using Genomic Sequencing." Institute of Medicine and National Research Council. 2014. Technologies to Enable Autonomous Detection for BioWatch: Ensuring Timely and Accurate Information for Public Health Officials: Workshop Summary. Washington, DC: The National Academies Press. doi: 10.17226/18495.
×

mental (water, soil, surfaces, plants, etc.), or pure cultures of organisms of interest. Sequencing can include DNA, RNA (in the form of cDNA), or both, depending on the type of information needed. For example, DNA sequencing can reveal which organisms are present in a sample and some of their phenotypic characteristics (e.g., antibiotic resistance). However, RNA sequencing (RNAseq) must be used for RNA viruses. RNAseq is also used to study the transcriptional profile of organisms at specific time points, allowing for a better understanding of their metabolic activity and for identification of genes that play key roles in disease, genetic disorders, inflammatory response, cancer, and so on.

NGS technologies require that DNA molecules are converted to NGS libraries. RNA is always converted to DNA first, as currently there are no direct RNA sequencing technologies (although the potential exists with the Pacific Biosciences (PacBio) real-time sequencer (RS), which is not evaluated here because of its very large footprint). Standard library preparation processes include DNA fragmentation and the addition of appropriate adapter molecules to the ends of DNA fragments. Adapters are unique DNA sequences (usually 30 to 60 base pairs long), which allow sequencing to occur, and they can also incorporate barcodes (or indices) that enable analysis of many samples in parallel. Depending on the application, library preparation methods take between 2 hours and 3 days. Once the libraries are prepared, each DNA fragment present in the library is clonally amplified before sequencing. This process and its degree of automation depend on the NGS platform. For example, the Illumina platforms use clustering (MiSeq is fully automated), whereas 454 and IonTorrent platforms use emulsion polymerase chain reaction (PCR) techniques (which will soon be mostly automated on IonTorrent).

NGS produces vast amounts of data, which are output as reads. A read is a string of DNA nucleotides corresponding to the sequence of the original DNA or RNA molecule in the sample. Each NGS platform outputs reads with three important characteristics for interpretation: read length, the number of reads, and their quality (fidelity). Read lengths vary from less than 50 base pairs (bps) to >3,000 bps, depending on the platform and sequencing kits. Read numbers vary from as few as 1.5 million to 4 billion per run. Reads can be evaluated independently, or they can be combined into much longer strings of DNA or RNA sequences using a variety of computational tools.

Sequencing of any sample generally requires four steps: nucleic acid extraction (sample preparation), library preparation, sequencing, and data analysis. Figure I-1 outlines a standard NGS workflow. Sequencing can

Suggested Citation:"Appendix I: White Paper 4: State of the Art for Autonomous Detection Systems Using Genomic Sequencing." Institute of Medicine and National Research Council. 2014. Technologies to Enable Autonomous Detection for BioWatch: Ensuring Timely and Accurate Information for Public Health Officials: Workshop Summary. Washington, DC: The National Academies Press. doi: 10.17226/18495.
×

be performed on any one of the current NGS platforms, with each having different requirements and often their own unique set of data output and management. Table I-1 briefly lists the facilities, personnel, equipment, software, and reagents needed for each platform.

For many applications, sequencing offers great advantages over the traditional methods. For example, in the field of pathogen detection, NGS can identify not only known organisms but also indications of novel, emerging, and engineered ones. Comparative analysis to known pathogens, the presence of virulence genes, and recombinant engineering markers and phylogenetic placement would provide indication of novel threat agents. This is highly relevant, especially for rapidly evolving and highly diverse organisms, such as RNA viruses and Burkholderia spp. In addition, NGS does not require prior knowledge of pathogens present in a sample as do the traditional detection methods. Therefore, NGS shows promise as the ultimate pathogen detection tool. Other application areas in which NGS will play a significant role include pathogen characterization (strain typing, antibiotic resistance, etc.), bioforensics, biometrics, and biosurveillance. For NGS to succeed in all these applications, basic studies and databases that correlate genotype (genetic sequence of an organism) to phenotype (the behavior of an organism, such as its pathogenicity, transmissibility, resistance, etc.) are required. Without bioinformatic analysis, the data cannot be used to make these determinations and inferences.

image

FIGURE I-1 Overview of the next-generation sequencing process.

Suggested Citation:"Appendix I: White Paper 4: State of the Art for Autonomous Detection Systems Using Genomic Sequencing." Institute of Medicine and National Research Council. 2014. Technologies to Enable Autonomous Detection for BioWatch: Ensuring Timely and Accurate Information for Public Health Officials: Workshop Summary. Washington, DC: The National Academies Press. doi: 10.17226/18495.
×

TABLE I-1 Characteristic Differences Between Sequencing Platforms

Sequencer Facilities and Equipment Personnela Software and Hardware Reagents
MiSeq—Illumina 68.6×56.5×52.3 cm (W×D×H). Total weight: 57.2 kg. Suggested lab bench space about 1.5× that size available prior to installation. The laboratory must be maintained at 22±3ºC for proper functioning. Can run on standard electrical systems. One to two individuals are needed for sample receipt through sequence data generation. One or two individuals are suggested for data interpretation. Instrument includes all software required through data generation. Analytical tools are available from multiple sources and can utilize platforms from a PC laptop through a large server system. Library preparation and sequencing run reagents are available through Illumina and can be ordered via phone or the Internet. Alternate library preparation kits are offered through multiple scientific supply vendors.
Roche454 Full size Roche454 GS FLX+Upper assembly
  • 74.3×69.8×36.1 cm (W×D×H)
  • Includes an 82.5-cm monitor
Lower assembly
  • 75.2×90.8×92.7 cm (W×D×H)
Total weight: 242 kg. Can run on standard electrical systems.
One to two individuals are needed for sample receipt through sequence data generation. One or two individuals are suggested for data interpretation. Includes sufficient software for data generation and a multitude of tools exist for data analysis and assembly. The full-size sequencer is well suited to computational systems ranging from large desktop PCs to servers. All standard library preparation and sequence run reagents can be purchased directly from Roche and integrate well with the platform. Orders can be easily placed via phone or Internet.
GS Junior 40×60×40 cm (W×L×H) Total weight: 25 kg. Can run on standard electrical systems, also GS Junior may be analyzed with less computational power, however (as with analyzing any NGS data on such a small
Suggested Citation:"Appendix I: White Paper 4: State of the Art for Autonomous Detection Systems Using Genomic Sequencing." Institute of Medicine and National Research Council. 2014. Technologies to Enable Autonomous Detection for BioWatch: Ensuring Timely and Accurate Information for Public Health Officials: Workshop Summary. Washington, DC: The National Academies Press. doi: 10.17226/18495.
×
able to operate between 85 and 264 VAC. system), the time required may be substantial.
IonTorrent 61×51×53 cm (W×D×H). Total weight: 30 kg. Operates best between 20 and 25ºC with a humidity of 40—60%. Optimal elevation is below 2,000 m (LANL has successfully operated instrument at >2,200 m). The instrument runs on 100- to 240-V power (standard electrical system) and requires 35 to 45 PSI argon gas for operation. One to two individuals are needed for sample receipt through sequence data generation. One or two individuals are suggested for data interpretation. Includes a server to support primary analysis through output file generation and variant calling. Additional processes can be handled through “apps” available through the plug-in store. PGM supports cloud-based processing, much of the analysis can be done from any Internet-linked portal, not requiring on-site computational hardware. Library preparation and sequencing run kits can be purchased directly through LifeTech, the vendor (phone or Internet sales both supported). Library preparation reagents other than those sold by LifeTech are also commonly used and can be purchased from a variety of scientific supply companies

aSeparate personnel required for sequence generation and sequence analysis due to the highly specific training required for each skill.
NOTE: When comparing the current NGS technologies consisting of Illumina, IonTorrent, PacBio, and 454, each technology has its own strengths and weaknesses, including the cost of sequencing. If sample and library preparation processes are excluded (they are relatively similar), the cost of sequencing a mega base pair (Mbp) of DNA on each sequencing platform is as follows: Illumina MiSeq, $0.13/Mbp; IonTorrent PGM, $0.57/Mbp; PacBio, $1.40/Mbp; and 454, $6.7/Mbp.
NOTE: FLX = flexibility; GS = genome sequencer; LANL = Los Alamos National Laboratory; m = meters; NGS = next-generation sequencing; PGM = personal genome machine; PSI = pounds per square inch; VAC = volts alternating currents.
SOURCE: Adapted from 2013 Los Alamos National Laboratory sequencing report to Department of Defense.

The promise of NGS cannot be realized without significant investments in the analysis of the produced data, typically referred to as bioin-

Suggested Citation:"Appendix I: White Paper 4: State of the Art for Autonomous Detection Systems Using Genomic Sequencing." Institute of Medicine and National Research Council. 2014. Technologies to Enable Autonomous Detection for BioWatch: Ensuring Timely and Accurate Information for Public Health Officials: Workshop Summary. Washington, DC: The National Academies Press. doi: 10.17226/18495.
×

formatics. Analysis of NGS data is highly specialized, depending on the types and detail desired from a particular analysis. For the identification and characterization of a pathogen, there are several levels of analysis possible, each with different requirements and able to reach more or less detailed conclusions. For the BioWatch application it may be of value to have two levels of analysis available. The first would be a simple percent match to selected microorganisms that is automatically performed. The second would be an in-depth genomic analysis that would be performed as required.

In conclusion, NGS shows promise for improving current microbiology, molecular biology, and analytical biochemistry methods and for providing new data streams that will help us understand the current state of pathogens and anticipate future changes in the microbial world.

OVERCOMING THE SHORTCOMINGS OF THE CURRENT BIOWATCH SYSTEM

Next-generation sequencing will soon become the ultimate tool for pathogen detection and characterization in clinical and environmental samples. Until recently, NGS was a slow and costly process. However, it is becoming cost-competitive and sufficiently rapid for many applications. Even though NGS is unlikely to replace the current rapid and portable pathogen detection platforms in the next couple of years, in many cases it will provide actionable information faster than the rapid systems. This is mainly due to the comprehensive information provided by an organism’s entire sequence versus a few selected segments of the genome. It is the only technology that can perform all of the following tasks in parallel from almost any sample: (1) detect all known pathogens, including viruses, bacteria, and protozoa; (2) identify emerging pathogens, whether they have evolved naturally or been engineered; and (3) characterize the pathogens (e.g., determine antibiotic resistance or pathogenicity).

Over the next 2 to 3 years NGS applications will likely help generate a world map displaying the real-time status of all infectious diseases. The data will be provided by a global network of interconnected facilities that use NGS platforms. Sequencing data, combined with the computational models of disease progression and easy visualization, will enable the accurate prediction and monitoring of disease spread and will reduce the effects on human lives and local economies.

Suggested Citation:"Appendix I: White Paper 4: State of the Art for Autonomous Detection Systems Using Genomic Sequencing." Institute of Medicine and National Research Council. 2014. Technologies to Enable Autonomous Detection for BioWatch: Ensuring Timely and Accurate Information for Public Health Officials: Workshop Summary. Washington, DC: The National Academies Press. doi: 10.17226/18495.
×

With the existing or forthcoming hardware and software upgrades, NGS technology will provide actionable information in 8 to 48 hours (including sample preparation, analysis, and interpretation), depending on the platform, the number of samples, and types of information needed. The simplest process includes detection of known pathogens and determination of some of their features, such as antibiotic resistance. More complex processes will involve identification of novel pathogens in mixed samples (clinical or environmental samples such as BioWatch aerosol samples), prediction of their pathogenicity and susceptibility to antibiotics, vaccine efficacy, and matching their identities to pathogens that previously caused serious outbreaks.

The major types of sequencing data can generally be obtained with three different pipelines, each providing different amounts and types of information, depending on the user's requirements (see Table H-2).

It is the only technology that can perform all of the following tasks in parallel from almost any sample:

•   Sequencing provides complete genomic picture of all microorganisms, not dependent on a priori selection of a small number of agents.

•   Phenotype can be predicted from the sequence, providing response guidance, such as which antibiotics to use and whether existing diagnostic tests will work.

•   Organisms altered by genetic engineering can be identified, providing coverage for the engineered threat.

•   Previously unidentified pathogens can be presumptively identified by comparative analysis, as was done with SARS and novel coronavirus. This and the previous point should decrease false-negative issues.

•   The more in-depth information provided by a draft sequence should give greater accuracy, decreasing false-positive issues and facilitating response decision.

•   Can sequencing be done in a reagent-free system? If so, it would eliminate the need for reagents and environmental control, which will radically decrease cost.

•   Sequencing can achieve single organism’s recognition, providing extreme sensitivity without compromising accuracy.

Below, we will attempt to address many of the current and future needs of the BioWatch Program as we understand them in key areas im-

Suggested Citation:"Appendix I: White Paper 4: State of the Art for Autonomous Detection Systems Using Genomic Sequencing." Institute of Medicine and National Research Council. 2014. Technologies to Enable Autonomous Detection for BioWatch: Ensuring Timely and Accurate Information for Public Health Officials: Workshop Summary. Washington, DC: The National Academies Press. doi: 10.17226/18495.
×

TABLE I-2 Overview of the Three Next-Generation Sequencing Pipelines for Pathogen Detection and Characterization

Pipeline

Description

Actionable Information

1. Amplicon Sequencing

Rapid sequencing of very small portions of pathogen genomes

Identify and characterize known pathogens, and some emerging ones. Able to test hundreds of samples in parallel.

2. Pathogen identifi-cation and charac-terization in mixed samples

Full sequencing of environmental and clinical samples

Identify and characterize known and emerging pathogens, including bacteria, viruses, and protozoa.

3. Pure-culture (iso-late) whole-genome sequencing

Whole-genome sequencing of one pathogen isolated from a sample and grown in the lab

Can identify sequences associated with specific outbreaks. Allows rapid detection of the same pathogen in future outbreaks.

SOURCE: Adapted from 2013 Los Alamos National Laboratory sequencing report to Department of Defense.

portant to its mission. The information content generated from today’s sequencing technologies already provides the base of what BioWatch needs. The challenge is to engineer a fieldable pathogen-detection platform based on nucleic acid sequencing.

Sensitivity

There is high confidence that a robust data stream will be generated from any sample type. Successful sequencing has been achieved at the level of a single bacterium. In addition, metagenomics and ancient DNA sequencing have also been successfully used for identification of small amounts of microorganisms. One drawback of sequencing all of the DNA (and/or RNA) in a sample is that a small amount of pathogen DNA can be overwhelmed by the background, so clever enrichment strategies may significantly increase the sensitivity. For example, some of the current NGS platforms isolate and amplify individual nucleic acid segments in oil vesicles leading to clonal nucleic acid samples for analysis. Future generations of sequencing technologies are expected to achieve even better sensitivities.

Suggested Citation:"Appendix I: White Paper 4: State of the Art for Autonomous Detection Systems Using Genomic Sequencing." Institute of Medicine and National Research Council. 2014. Technologies to Enable Autonomous Detection for BioWatch: Ensuring Timely and Accurate Information for Public Health Officials: Workshop Summary. Washington, DC: The National Academies Press. doi: 10.17226/18495.
×

Specificity

This is one of the greatest strengths of sequencing, which should eliminate most false-positive and false-negative results. Thousands of sequencing centers around the world are sequencing various environments for many different reasons. These activities are generating a valuable knowledge base that will keep growing at no expense to BioWatch, which will improve the specificity over time even further. Comparative analysis of novel strains of microorganisms will be robust and automated due to the availability of comprehensive microbial databases and analytical algorithms.

Size and Functionality

This is currently an issue due to how the devices were built and to the audiences they have been built for. Currently the health care industry is driving the technology to a smaller, less complicated device for the benchtop in a diagnostic laboratory. With proper motivation and customary engineering designs, an even smaller platform can be built (i.e., look at the progress Apple is making on a regular basis to miniaturize for their market). Commercial drivers will push the industry without much investment from the BioWatch community. However, properly placed motivation will drive the technology to where BioWatch needs it to be in a timely fashion. The unique needs of an autonomous detector (e.g., extended mean-time-to-failure, multitier analyses outputs, remote data transmission, viability assessment) could be identified and shared with interested sequencing platform developers to establish collaborative research and development initiatives.

Flexibility

Multiplexing with standard protocols is a strength of the current sequencing platforms and will likely remain so for future devices. Computational adjustments allow for the ultimate flexibility in NGS. Identification from a mixed or complex sample (i.e., from a filter) is also a strength of sequencing, where one allows the sequencer to generate baseline data on everything that is in the sample and relies on automated bioinformatics tools to sort out the details. This is commonplace today, and capabilities will be even stronger as more data are generated and as computational advancements occur. Community or metagenomic analysis

Suggested Citation:"Appendix I: White Paper 4: State of the Art for Autonomous Detection Systems Using Genomic Sequencing." Institute of Medicine and National Research Council. 2014. Technologies to Enable Autonomous Detection for BioWatch: Ensuring Timely and Accurate Information for Public Health Officials: Workshop Summary. Washington, DC: The National Academies Press. doi: 10.17226/18495.
×

will decrease the sample processing requirements as well as provide an additional characterization modality. Suspect segments of nucleic acid will be assessed in the context of all nucleic acid in the aerosol sample, providing the opportunity to detect culture media constituents not normally found in ambient aerosols.

More Than Red/Green Decision Making

The information content of sequencing and analysis is so high that not only does one get identification down to the strain, but the confidence in this call is usually very high, even with today’s technology. The information content also includes identification of novel and engineered organisms by comparative and phylogenetic analysis. Traditional recombinant vectors can also be targeted to detect engineered pathogens. Results can be generated automatically from raw data using analytical tools and then presented at multiple levels of complexity for BioWatch technical, scientific personnel, and public health decision makers.

Measuring Timelines

Speed and process flow are enhanced for sequencing because one can gather small amounts of target for sequencing and because sensitivity is high by nature. Databases can also be pared down to do rapid on-board detector analyses. Capabilities are currently in hand to develop two levels or modes of analysis (Defense Threat Reduction Agency [DTRA] is developing one currently called EDGE). One can imagine mode 1 in which rapid analysis and identification is done on board the detector via a laptop-sized platform which looks at a pared-down database of pathogens and near neighbors. The second stage would involve the data being remotely ported to a larger comparative analysis server farm capable of doing a much more extensive analysis and confirmatory target identification. This greater level of analysis would support the BioWatch Actionable Result assessment process involving multiple participants.

Measuring Interval

Sequence throughput can allow for large batches of samples to be processed regularly. Technology will allow for an engineering decision to be made as needed in device or analysis design. One will likely be able to choose between a few samples at a faster throughput and at a

Suggested Citation:"Appendix I: White Paper 4: State of the Art for Autonomous Detection Systems Using Genomic Sequencing." Institute of Medicine and National Research Council. 2014. Technologies to Enable Autonomous Detection for BioWatch: Ensuring Timely and Accurate Information for Public Health Officials: Workshop Summary. Washington, DC: The National Academies Press. doi: 10.17226/18495.
×

higher cost (rapid mode) or a multiplexed process that is slower and has higher content (detailed mode). In doing this today, one may use amplicon sequencing of fewer primer pairs in rapid mode versus many primer sets in detailed mode. In tomorrow’s version one could do the same with sequencing a few samples at a time in rapid mode versus the detailed mode where the device would run one large, highly multiplexed run per day.

Cost

Initial investment on sequencing is relatively high compared with some of the other detector platforms. The payoff is in the throughput, single-stage analysis and associated need of less manpower. Future advancements will become even cheaper due to reagentless sequencing.

Automation

Sample preparation and sequencing are highly automatable. However, technical challenges exist due to the current reagent-based platforms. Next-generation, reagentless platforms will allow for a much more automatable system. The health care industry is highly focused on this issue, and it will help drive the mean time between failures down substantially.

Operation Environment

Current technology is aimed at the clinical laboratory and a standard research laboratory setting. As markets drive the development of smaller and more fieldable devices, the upcoming next-generation systems will be much more adaptable to field autonomous outdoor detection. Again, reagentless-type devices will naturally progress in this direction.

Overall, the health care and related technology industry has a desire to overcome many of the hurdles the BioWatch community is also focused on. These advances will happen naturally and at little to no expense to the BioWatch community. However, properly placed motivational tools and collaborations from the BioWatch community to NGS industry leaders will promote a quicker advancement aimed more precisely at BioWatch’s mission. Below we generally discuss the three phases we see the evolution being focused.

Suggested Citation:"Appendix I: White Paper 4: State of the Art for Autonomous Detection Systems Using Genomic Sequencing." Institute of Medicine and National Research Council. 2014. Technologies to Enable Autonomous Detection for BioWatch: Ensuring Timely and Accurate Information for Public Health Officials: Workshop Summary. Washington, DC: The National Academies Press. doi: 10.17226/18495.
×

READINESS LEVELS

The Institute of Medicine provides three readiness levels for a BioWatch autonomous biodetector against which to assess sequencing technology. These levels are as described below. It was assumed that the engineering, testing, and fielding of an autonomous detector would require at least 2 years after the required components (TRL 4) were available.

•   Tier 1: fully automated biodetection system, capable of 24/7/365 unattended outdoor and indoor operation, that will be at a technology readiness level of TRL 6-plus by 2016.

•   Tier 2: similar requirements, but will not reach a TRL 6-plus level until sometime between 2016 and 2020.

•   Tier 3: technologies that have the potential of meeting or exceeding the BioWatch requirements, but a fully automated, TRL 6-plus system would take us beyond the 2020 time frame. For these technologies, describe the current critical paths (“long poles”) in meeting the BioWatch requirements and how they might be addressed.

Tier 1

One way to achieve a Tier 1 system would be to expedite the engineering of an available NGS technology for high-throughput amplicon sequencing to create an autonomous field-deployable biodetector for the BioWatch system.

This capability would allow inexpensive, rapid, and very detailed analysis of many samples in parallel. The parallel-processing capability could be used for analyzing multiple aerosol samples, providing narrower time cuts for sampling or numerous distinct amplicons. Currently available and validated primer sets can be easily utilized in this approach, but many others can be added. Amplicon sequencing can detect many known pathogens and their phenotypic features (antibiotic resistance markers and virulence factors). It can also detect and characterize some emerging pathogens, but this capability is limited.

Summary of features:

•   Detects all known pathogens, antibiotic resistance markers, and virulence factors.

Suggested Citation:"Appendix I: White Paper 4: State of the Art for Autonomous Detection Systems Using Genomic Sequencing." Institute of Medicine and National Research Council. 2014. Technologies to Enable Autonomous Detection for BioWatch: Ensuring Timely and Accurate Information for Public Health Officials: Workshop Summary. Washington, DC: The National Academies Press. doi: 10.17226/18495.
×

•   Uses multiplexed end-point PCR to generate amplicons that are directly sequenced.

•   Can sequence hundreds or thousands of amplicons.

•   Has limited ability to identify emerging threats, especially RNA viruses.

A fully automated platform should be smaller than 24 ft3, should use a regular 110-V outlet, and should automatically analyze samples every 8 hours following sample collection.

Tier 2

A Tier 2 system could be achieved by using improved NGS technology to provide for metagenomic sequencing and analysis. This capability would sequence all nucleic acids present in a sample. It would detect and characterize not only the known pathogens but also most emerging ones. Because small amounts of a pathogen in a large amount of background would severely compromise the platform sensitivity, a strategy for removal of environmental (non-informative) nucleic acids may be desirable or required. Since all NGS platforms require library preparation, sample-to-result time would still be 6 to 10 hours following sample collection.

Summary of features:

•   Detects all known pathogens, antibiotic resistance markers, and virulence factors.

•   Can detect many emerging pathogens, including engineered ones.

•   Even with improved sequencing speeds, the requirement to prepare libraries slows the overall process down.

A fully automated platform should be smaller than 24 ft3, should use a regular 110-V outlet, and should automatically analyze samples every 8 hours.

Tier 3

A Tier 3 system could be achieved through using a future sequencing technology (i.e., Oxford Nanopore or Gen2 PacBio) to rapidly perform metagenomic sequencing of environmental samples. This approach

Suggested Citation:"Appendix I: White Paper 4: State of the Art for Autonomous Detection Systems Using Genomic Sequencing." Institute of Medicine and National Research Council. 2014. Technologies to Enable Autonomous Detection for BioWatch: Ensuring Timely and Accurate Information for Public Health Officials: Workshop Summary. Washington, DC: The National Academies Press. doi: 10.17226/18495.
×

would have similar capabilities to the Tier 2 platform, but the sample-to-result times would be much shorter—approximately 1 hour. No library preparation would be required, and the sequencing itself would be much more rapid. The soon-to-be-released Oxford Nanopore technology is expected to offer such a technology advance.

Summary of features:

•   Detects all known pathogens, antibiotic resistance markers, and virulence factors.

•   Can detect many emerging pathogens, including engineered ones.

A fully automated platform should be smaller than 3 ft3, should use a regular 110-V outlet, and should automatically analyze a sample in 1 hour (in addition to air sampling, which can vary depending on the application). Reagent requirements should be minimal.

SUMMARY

Sequencing technology driven by strong and diverse markets has and will continue to make rapid advances. In addition, application of existing technologies is enabling rapid growth of genomic databases and filling in the microbial tree of life. The decrease in cost and increase in functionality of sequencing technology, coupled with publically available molecular databases, should drive a growing interest in genomics for decades. Major points to consider in assessing the utility of sequencing to the BioWatch mission are as follows:

•   Great market pressure will facilitate advances in sequencing that can be adopted by BioWatch. In particular, research and development for capabilities to satisfy point-of-care and field analysis capabilities will drive development of core sensor components of direct value to BioWatch.

•   Tier 1 and Tier 2 timelines would benefit from comprehensive information provided by NGS, but the engineered autonomous detector would continue to require environmental controls and electrical power. Reagent costs could be decreased and have an analysis time of less than 10 hours following sample collection. Complexity of system fluidics would require routine maintenance.

Suggested Citation:"Appendix I: White Paper 4: State of the Art for Autonomous Detection Systems Using Genomic Sequencing." Institute of Medicine and National Research Council. 2014. Technologies to Enable Autonomous Detection for BioWatch: Ensuring Timely and Accurate Information for Public Health Officials: Workshop Summary. Washington, DC: The National Academies Press. doi: 10.17226/18495.
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•   Tier 3 capabilities hold promise for eliminating reagents and minimizing the need for environmental controls. This would provide the benefits of information derived from sequencing while decreasing the costs associated with reagent systems. Again, a sequencing and analysis time of less than 10 hours following sample collection should be possible.

•   An acquisition strategy for DHS should be considered that fosters research and development of specific technology components within the private sector, toward common desired capabilities.

In summary, the inherent information content from sequencing and analysis should meet all the needs of BioWatch, addressing false-positive and false-negative issues. However, for at least the Tier 1 and Tier 2 timelines, significant engineering challenges will have to be overcome to adapt the existing reagent-based systems into an autonomous biodetector with desired attributes. Fortunately, extensive investments are being made by many public- and private-sector entities to develop technology that should provide the core sensor technology meeting the Tier 3 timeline and system requirements.

Suggested Citation:"Appendix I: White Paper 4: State of the Art for Autonomous Detection Systems Using Genomic Sequencing." Institute of Medicine and National Research Council. 2014. Technologies to Enable Autonomous Detection for BioWatch: Ensuring Timely and Accurate Information for Public Health Officials: Workshop Summary. Washington, DC: The National Academies Press. doi: 10.17226/18495.
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Suggested Citation:"Appendix I: White Paper 4: State of the Art for Autonomous Detection Systems Using Genomic Sequencing." Institute of Medicine and National Research Council. 2014. Technologies to Enable Autonomous Detection for BioWatch: Ensuring Timely and Accurate Information for Public Health Officials: Workshop Summary. Washington, DC: The National Academies Press. doi: 10.17226/18495.
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Suggested Citation:"Appendix I: White Paper 4: State of the Art for Autonomous Detection Systems Using Genomic Sequencing." Institute of Medicine and National Research Council. 2014. Technologies to Enable Autonomous Detection for BioWatch: Ensuring Timely and Accurate Information for Public Health Officials: Workshop Summary. Washington, DC: The National Academies Press. doi: 10.17226/18495.
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Suggested Citation:"Appendix I: White Paper 4: State of the Art for Autonomous Detection Systems Using Genomic Sequencing." Institute of Medicine and National Research Council. 2014. Technologies to Enable Autonomous Detection for BioWatch: Ensuring Timely and Accurate Information for Public Health Officials: Workshop Summary. Washington, DC: The National Academies Press. doi: 10.17226/18495.
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Suggested Citation:"Appendix I: White Paper 4: State of the Art for Autonomous Detection Systems Using Genomic Sequencing." Institute of Medicine and National Research Council. 2014. Technologies to Enable Autonomous Detection for BioWatch: Ensuring Timely and Accurate Information for Public Health Officials: Workshop Summary. Washington, DC: The National Academies Press. doi: 10.17226/18495.
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Suggested Citation:"Appendix I: White Paper 4: State of the Art for Autonomous Detection Systems Using Genomic Sequencing." Institute of Medicine and National Research Council. 2014. Technologies to Enable Autonomous Detection for BioWatch: Ensuring Timely and Accurate Information for Public Health Officials: Workshop Summary. Washington, DC: The National Academies Press. doi: 10.17226/18495.
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Suggested Citation:"Appendix I: White Paper 4: State of the Art for Autonomous Detection Systems Using Genomic Sequencing." Institute of Medicine and National Research Council. 2014. Technologies to Enable Autonomous Detection for BioWatch: Ensuring Timely and Accurate Information for Public Health Officials: Workshop Summary. Washington, DC: The National Academies Press. doi: 10.17226/18495.
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Suggested Citation:"Appendix I: White Paper 4: State of the Art for Autonomous Detection Systems Using Genomic Sequencing." Institute of Medicine and National Research Council. 2014. Technologies to Enable Autonomous Detection for BioWatch: Ensuring Timely and Accurate Information for Public Health Officials: Workshop Summary. Washington, DC: The National Academies Press. doi: 10.17226/18495.
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Suggested Citation:"Appendix I: White Paper 4: State of the Art for Autonomous Detection Systems Using Genomic Sequencing." Institute of Medicine and National Research Council. 2014. Technologies to Enable Autonomous Detection for BioWatch: Ensuring Timely and Accurate Information for Public Health Officials: Workshop Summary. Washington, DC: The National Academies Press. doi: 10.17226/18495.
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Suggested Citation:"Appendix I: White Paper 4: State of the Art for Autonomous Detection Systems Using Genomic Sequencing." Institute of Medicine and National Research Council. 2014. Technologies to Enable Autonomous Detection for BioWatch: Ensuring Timely and Accurate Information for Public Health Officials: Workshop Summary. Washington, DC: The National Academies Press. doi: 10.17226/18495.
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Suggested Citation:"Appendix I: White Paper 4: State of the Art for Autonomous Detection Systems Using Genomic Sequencing." Institute of Medicine and National Research Council. 2014. Technologies to Enable Autonomous Detection for BioWatch: Ensuring Timely and Accurate Information for Public Health Officials: Workshop Summary. Washington, DC: The National Academies Press. doi: 10.17226/18495.
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Suggested Citation:"Appendix I: White Paper 4: State of the Art for Autonomous Detection Systems Using Genomic Sequencing." Institute of Medicine and National Research Council. 2014. Technologies to Enable Autonomous Detection for BioWatch: Ensuring Timely and Accurate Information for Public Health Officials: Workshop Summary. Washington, DC: The National Academies Press. doi: 10.17226/18495.
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Suggested Citation:"Appendix I: White Paper 4: State of the Art for Autonomous Detection Systems Using Genomic Sequencing." Institute of Medicine and National Research Council. 2014. Technologies to Enable Autonomous Detection for BioWatch: Ensuring Timely and Accurate Information for Public Health Officials: Workshop Summary. Washington, DC: The National Academies Press. doi: 10.17226/18495.
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Suggested Citation:"Appendix I: White Paper 4: State of the Art for Autonomous Detection Systems Using Genomic Sequencing." Institute of Medicine and National Research Council. 2014. Technologies to Enable Autonomous Detection for BioWatch: Ensuring Timely and Accurate Information for Public Health Officials: Workshop Summary. Washington, DC: The National Academies Press. doi: 10.17226/18495.
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Suggested Citation:"Appendix I: White Paper 4: State of the Art for Autonomous Detection Systems Using Genomic Sequencing." Institute of Medicine and National Research Council. 2014. Technologies to Enable Autonomous Detection for BioWatch: Ensuring Timely and Accurate Information for Public Health Officials: Workshop Summary. Washington, DC: The National Academies Press. doi: 10.17226/18495.
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Suggested Citation:"Appendix I: White Paper 4: State of the Art for Autonomous Detection Systems Using Genomic Sequencing." Institute of Medicine and National Research Council. 2014. Technologies to Enable Autonomous Detection for BioWatch: Ensuring Timely and Accurate Information for Public Health Officials: Workshop Summary. Washington, DC: The National Academies Press. doi: 10.17226/18495.
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Suggested Citation:"Appendix I: White Paper 4: State of the Art for Autonomous Detection Systems Using Genomic Sequencing." Institute of Medicine and National Research Council. 2014. Technologies to Enable Autonomous Detection for BioWatch: Ensuring Timely and Accurate Information for Public Health Officials: Workshop Summary. Washington, DC: The National Academies Press. doi: 10.17226/18495.
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Suggested Citation:"Appendix I: White Paper 4: State of the Art for Autonomous Detection Systems Using Genomic Sequencing." Institute of Medicine and National Research Council. 2014. Technologies to Enable Autonomous Detection for BioWatch: Ensuring Timely and Accurate Information for Public Health Officials: Workshop Summary. Washington, DC: The National Academies Press. doi: 10.17226/18495.
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Suggested Citation:"Appendix I: White Paper 4: State of the Art for Autonomous Detection Systems Using Genomic Sequencing." Institute of Medicine and National Research Council. 2014. Technologies to Enable Autonomous Detection for BioWatch: Ensuring Timely and Accurate Information for Public Health Officials: Workshop Summary. Washington, DC: The National Academies Press. doi: 10.17226/18495.
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Next: Appendix J: White Paper 5: State of the Art for Autonomous Detection Systems Using Mass Spectrometry »
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The BioWatch program, funded and overseen by the Department of Homeland Security (DHS), has three main elements--sampling, analysis, and response--each coordinated by different agencies. The Environmental Protection Agency maintains the sampling component, the sensors that collect airborne particles. The Centers for Disease Control and Prevention coordinates analysis and laboratory testing of the samples, though testing is actually carried out in state and local public health laboratories. Local jurisdictions are responsible for the public health response to positive findings. The Federal Bureau of Investigation is designated as the lead agency for the law enforcement response if a bioterrorism event is detected. In 2003 DHS deployed the first generation of BioWatch air samplers. The current version of this technology, referred to as Generation 2.0, requires daily manual collection and testing of air filters from each monitor. DHS has also considered newer automated technologies (Generation 2.5 and Generation 3.0) which have the potential to produce results more quickly, at a lower cost, and for a greater number of threat agents.

Technologies to Enable Autonomous Detection for BioWatch is the summary of a workshop hosted jointly by the Institute of Medicine and the National Research Council in June 2013 to explore alternative cost-effective systems that would meet the requirements for a BioWatch Generation 3.0 autonomous detection system, or autonomous detector, for aerosolized agents . The workshop discussions and presentations focused on examination of the use of four classes of technologies--nucleic acid signatures, protein signatures, genomic sequencing, and mass spectrometry--that could reach Technology Readiness Level (TRL) 6-plus in which the technology has been validated and is ready to be tested in a relevant environment over three different tiers of temporal timeframes: those technologies that could be TRL 6-plus ready as part of an integrated system by 2016, those that are likely to be ready in the period 2016 to 2020, and those are not likely to be ready until after 2020. Technologies to Enable Autonomous Detection for BioWatch discusses the history of the BioWatch program, the role of public health officials and laboratorians in the interpretation of BioWatch data and the information that is needed from a system for effective decision making, and the current state of the art of four families of technology for the BioWatch program. This report explores how the technologies discussed might be strategically combined or deployed to optimize their contributions to an effective environmental detection capability.

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