Erin Merritt
Most surveillance detection methods are designed with a specific target in mind. For instance, when you take a flu test, it will tell you if you’ve tested positive for only the flu. But what if you aren’t sure what your target is, and you’re just trying to determine what viruses, bacteria, or fungi are in the environment and may pose a risk.
Elaine Bradford is a staff scientist whose work has focused on the development of a CRISPR-based detection tool capable of detecting more than 500 human pathogens. Today on the show, Agnostic Detection, translating customer needs into panel design, its importance in pandemic preparedness, and the trade-offs associated with agnostic targeting.
I’m Erin Merritt, and this is Science Diction from MRIGlobal.
Elaine Bradford
New pathogens are emerging at an unprecedented rate and global travel allows them to spread faster than ever before, so the ability to detect these threats is more critical than ever. But here’s the thing – traditional methods often require knowing exactly what you’re looking for, but then what happens when the next big threat doesn’t fit with what we know about viruses or bacteria?
This is where agnostic biothreat detection comes in. Imagine a technology that can identify any pathogen, whether it’s a known virus, a novel bacteria, or something entirely new. It helps us tackle that problem before it becomes a real threat.
Erin Merritt
What are agnostic detection methods and how do they differ from traditional detection methods?
Elaine Bradford
So agnostic detection methods are unbiased approaches that can detect a broad range of pathogens, including viruses, bacteria, and fungi, without needing to know the specific threat in advance. Traditional detection techniques on the other hand, are typically target specific.
This means that they require prior knowledge of the organism you’re looking for, like using PCR to detect a known virus gene. Agnostic methods such as metagenomic sequencing analyze all the genetic material in a sample which allows us to detect unknown or unexpected pathogens. This makes them particularly useful for emerging infectious diseases or engineered biothreats that may not be on anyone’s radar yet.
Erin Merritt
Why are agnostic detection methods crucial in infectious disease and biothreat preparedness?
Elaine Bradford
In today’s world, pathogens can emerge suddenly evolve rapidly, or even be deliberately bio-engineered. Agnostic methods allow us to detect these threats quickly, even if they’re previously unknown or potentially designed to evade traditional tests.
In infectious disease outbreaks, time is critical and waiting to identify a pathogen using traditional target specific methods could mean losing valuable response time. Agnostic approaches provide a broader safety net, ensuring that even unexpected or novel pathogens are identified early, improving response efforts and saving lives.
Erin Merritt
So how can agnostic detection methods contribute to biothreat surveillance and prevention?
Elaine Bradford
Agnostic detection methods can play a pivotal role in threat surveillance by providing the ability to monitor and identify a wide array of pathogens from environmental
samples, human samples, or even animal reservoirs without prior knowledge about the target.
This could help us detect engineered pathogens or bioweapons early, even if they’re designed to mimic naturally occurring organisms. By continuously monitoring high risk areas and populations using agnostic techniques, we can stay ahead of potential biothreats and intervene before they lead to large scale outbreaks or attacks.
Erin Merritt
What are the challenges or limitations associated with agnostic detection methods?
Elaine Bradford
One of the main challenges is the sheer volume of data generated by agnostic methods like metagenomic sequencing. Analyzing this amount of data can require significant computational resources and expertise.
Additionally, there’s a risk of detecting harmless or background microbes that can convolute the interpretation of results leading to false positives. Another limitation is the cost. While prices for sequencing have dropped significantly, these methods can still be significantly more expensive than targeted approaches.
But despite these challenges, advances in technology and bioinformatics are steadily improving the efficiency, speed, and affordability of agnostic methods.
Erin Merritt
Can agnostic detection methods help with the unknown unknowns in biothreat detection?
Elaine Bradford
Absolutely. The concept of unknown unknowns refers to pathogens or threats we aren’t aware of yet, similar to the well-known phrase, “We don’t know what we don’t know.”
Agnostic methods really shine in this area because they don’t rely on prior knowledge of specific organisms. Instead, they cast a wide net identifying any genetic material present in a sample.
This means we can detect novel or engineered pathogens that may not be on the radar of traditional tests. By staying ahead of the curve, we can respond to emerging threats, whether naturally occurring or man-made with greater speed and precision.
Erin Merritt
How do agnostic methods fit into a broader infectious disease surveillance system?
Elaine Bradford
Agnostic methods can be incorporated into multilayered infectious disease surveillance by complimenting targeted approaches like PCR, which is fast and accurate for known threats.
Together, they create a more comprehensive system where targeted methods handle routine diagnostics, while agnostic approaches act as a safeguard for emerging or unexpected pathogens. This integration allows public health systems to balance speed, cost and preparedness, ensuring we can respond effectively to both known and unknown infectious threats.
Erin Merritt
So thinking about this pandemic that we all we lived through, what role could agnostic detection play in future pandemic preparedness?
Elaine Bradford
Agnostic detection can play a transformative role in pandemic preparedness by enabling early identification of novel pathogens before they spread widely. During the COVID-19 pandemic, for example, sequencing was key in identifying the SARS-CoV-2 virus and tracking its mutations.
For future pandemics, agnostic methods could provide even earlier warnings by detecting new pathogens before they’re widely recognized. This would allow health authorities to implement control measures faster, preventing a localized outbreak from becoming a global crisis.
Erin Merritt
What are some of the promising developments or technologies and agnostic detection for bio threats?
Elaine Bradford
Some of the exciting developments that we’ve seen include improvements in portable sequencing technologies such as nanopore sequencing, which can bring agnostic detection into the field for real-time surveillance.
Advances in bioinformatics and AI driven analysis tools are also making it much easier to interpret complex data sets, enabling quicker identification of pathogens.
Erin Merritt
Tell me more about this idea.
Elaine Bradford
Additionally, researchers are working on more affordable and accessible platforms, reducing the barriers to agnostic detection methods and resource limited settings. For example, if someone is out in the field and they only have access to the one platform.
These innovations are making it possible to deploy agnostic approaches more widely and effectively in both routine public health monitoring and in response to potential biothreats.
Erin Merritt
But in developing agnostic detection methods, there are also associated trade-offs. Elaine likens it to the difficulty of trying to get a specific answer without asking a specific question.
Elaine Bradford
When designing any detection assay, there are two major characteristics to keep in mind: sensitivity and specificity. Sensitivity is the lowest concentration of a pathogen that the assay will be able to detect.
So for example, for a test designed to detect HIV, high sensitivity is critical to ensure that no one with the virus goes undetected, especially in the early stages of infection when viral load in a patient might be low.
Meanwhile, specificity in the context of assay design refers to what an assay is supposed to detect. For example, a highly specific assay might detect a singular pathogen strain versus a low specificity assay that can detect everything within a given genus. But there are trade-offs between optimizing for sensitivity versus specificity.
Erin Merritt
So what are those trade-offs that we’re making when we’re trying to optimize between sensitivity and specificity?
Elaine Bradford
So as you can imagine, having high sensitivity and high specificity are typically mutually exclusive of each other and must be balanced for the best outcome.
This means that you, as the assay designer, have to consider the end use case and what question
you’re trying to answer. Is the end use case a clinician who just needs to identify a pathogen to inform a treatment plan?
Or is it an epidemiologist who needs to track specific strains or will this assay be used on its own or as part of a larger panel of tests? As a designer, you have to balance all of these questions to help dictate what level of sensitivity and specificity you’ll need to incorporate in your design platform.
Erin Merritt
What else should we know about agnostic detection?
Elaine Bradford
I’m so glad you asked because this is something I feel really passionate about. The concept of agnostic detection is great, but what often gets overlooked is that there’s no such thing as an omniscient test.
We see people ask for this pretty often, but this method fundamentally relies on an established library of knowns to which it can compare the input.
While these libraries can be huge with thousands of references, they by definition cannot identify complete unknowns. Something has to be in the library for it to match to it. So typically what you see is smaller libraries or databases that are highly curated with well annotated and labeled items, while larger databases have lower quality input labeling or even mislabeling.
Even something like NCBI, which is a cornerstone of the biological research community is known to have flawed inputs.
Erin Merritt
How can we make agnostic detection more accessible and scalable in global health efforts?
Elaine Bradford
I think that to make agnostic detection more accessible, we need to focus on reducing costs and increasing the availability of portable technologies. Training the global workforce and bioinformatics is also crucial so that more countries can analyze these complex data sets that the methods generate.
Investments in infrastructure such as building more global surveillance networks will allow for the rapid sharing of pathogen data across borders. Partnerships between governments, the private sector, and international organizations are all key to making these technologies scalable and adaptable in diverse settings, especially in low and middle income countries where infectious disease threats are often the highest.
Erin Merritt
And how does this concept transfer to agnostic detection?
Elaine Bradford
While the sensitivity and specificity concepts rule traditional molecular and immune assay design, agnostic detection is actually free from those constraints. This is because in traditional detection assays, you typically have to choose a singular protein or singular gene target.
Versus in agnostic methods, you’re blasting an entire pathogen’s profile, whether that’s a genomic sequence, fatty acid profile, et cetera, against a large library of potential identifications. Instead, a question you might ask yourself is, is this profile type you’re using best suited for the scenario at hand?
For example, fatty acid profiles can be really useful in environmental samples with a potentially wide range of bacteria. On the other hand, sequencing is ideal for detecting novel pathogens, tracking mutations, and being able to screen against huge genomic databases.
Erin Merritt
So what challenges are our customers facing that make them want to ask for these agnostic detection methods?
Elaine Bradford
Right now, our customers rely on traditional assay detection methods, and this means that every time there is a new pathogen that they want to be able to detect, we have to go through the entire research and development process in order to deploy that particular assay.
With something like an agnostic detection method, it’s more of a one and done approach as far as development goes. So once that method is in place and deployed, they don’t have to go back to the drawing board every single time a new biothreat or bio concern even emerges.
It can be put in place and then ideally, or at least in theory, be able to detect any concern that might come down the line. So while agnostic detection is not an all-in-one panacea, it is a really exciting development and offers critical advantages in health surveillance.
