Nucleic Acid Observatory

Fund the Nucleic Acid Observatory to Detect Stealth Pandemics

Authors Jeff Kaufman, Mike McLaren, & Will Bradshaw
Date November 18, 2024

Summary

The Nucleic Acid Observatory (NAO) aims to improve humanity’s ability to detect new pathogens, especially engineered ones. We are evaluating disease surveillance methods, developing pathogen detection algorithms, and running a pilot biosurveillance system. Additional funding would allow us to expand and continue our work on computational detection and directly increase the sensitivity of our pilot detection system. You can donate on our website.

The Problem

Among the most dangerous biorisk scenarios is that of a ‘stealth’ pathogen, spreading without distinctive symptoms1 and only later causing severe health impacts.2 Such a pathogen could cause enormous harm, as a very large fraction of humanity could be infected before anyone notices. The world today is not equipped to detect a stealth pathogen before it’s too late; however, improvements in monitoring technology could enable dramatically earlier detection and response, substantially reducing the harm caused.

While the ‘stealth’ scenario is one where we think the benefits of early detection are strongest, it is not the only one where our work is valuable. We discuss other benefits below.

Our Approach

If a new pandemic were spreading, how would we know? At a high level, we’d need to get samples that might contain the pathogen, learn what the samples contain, and analyze that data for pathogen signatures. We’re working to improve the state of the art in all three areas:

Sampling

We currently work with two sample types:

  • Municipal wastewater: Each sewage sample represents a large population, and so is very low cost per covered individual. On the other hand, it requires very deep sequencing to make up for the extremely small fraction of nucleic acids (DNA and RNA) that come from human-infecting pathogens. We are currently receiving data from weekly samples from three metropolitan areas, in collaboration with Marc Johnson’s group at the University of Missouri.

  • Nasal swabs from volunteers: Collecting samples one person at a time means the per-person cost is much higher, but because the nose is a great place to look for respiratory pathogens we can use much cheaper sequencing methods. We are currently collecting weekly samples in public places around greater Boston.

We’ve also put substantial effort into evaluating other sampling options, such as indoor air, blood, and pooled airplane lavatory waste, and hope to expand the range of sample types we work with in the future.

Sequencing

After collecting the samples we need to extract the nucleic acids. Among the many potential extraction methods, we’ve identified ones that optimize for viruses. These methods select for properties common to viruses, such as being smaller than human or bacterial cells. After extraction we use metagenomic sequencing to learn what raw nucleic acid sequences our samples contain.

Computational Analysis

Sequencing data needs substantial analysis and interpretation to be useful, and identifying novel or engineered pathogens is a serious difficult research problem. We’ve identified a wide range of data signatures that could indicate the presence of a new pathogen and are exploring how to apply them to the detection problem. Some of these we’ve developed into tools we can apply today, others we expect to have ready in the next few quarters, while others remain substantial research projects where we’re collaborating with outside academics.

We expect work in this area to be our largest effort over the next few quarters.

What We Would Do With Your Money

Expanding our Team

We would like to hire additional staff in a few areas:

  • Computational: our current best detection method is an important step forward, but it’s far from solving the whole problem. There are many more potential strategies for computational threat detection than we’ve been able to explore, and another junior or senior researcher would allow us to make faster progress here. This work is very parallelizable, where there are several independent lines of exploration we’d like to pursue.

  • Wet lab: we recently opened our own wet lab, have hired a second wet lab research scientist, and don’t intend to hire additional wet lab staff in the next few months. Depending on how our methods development and pilot biosurveillance work goes, however, by mid 2025 we might want to invest in hiring a wet lab technician to free up our research scientists for work where they’re uniquely capable.

  • Partnerships: it would be valuable to have someone working full-time on developing partnerships between the NAO and external organizations. At one end of the process, we think better partnerships with sample and data providers could dramatically increase the rate and quality of incoming data to the NAO. At the other, our work would be more impactful if other groups (including but not limited to policymakers) were better prepared to take actions downstream from our findings.

Pilot Detection

We are running a pilot biosurveillance system that we estimate would flag blatantly engineered viral threats today. At our current scale, however, it would likely fail to do so before the majority of people had been infected (simulator). We would like to scale this system to, and ideally beyond, where it could flag such a pathogen before 1% of people had been infected.3 Piloting the system has also been giving us valuable operational experience, illuminating the real-world problems that come up in building and running a biosurveillance operation; a larger scale pilot, especially of swab sequencing, would bring new challenges and insights. We don’t want to end up in a position where we have a good model of how a biosurveillance system would work in theory if only someone would build one, and then building one turns out to be much harder or generate very different data than our modeling assumed.

Flexibility

A final way additional funding would help would be by giving us the operational flexibility to test out new approaches without needing to raise funds specifically for that purpose. For example, we were able to start work on our swab sampling effort relatively quickly once we realized how promising it was because we had some flexible funding on hand. If other opportunities come up we would like to be in a position to move quickly on them.

Prioritization

In general, we hope that donors will trust us to consider these and other options and spend NAO funds in the way that most improves our ability to detect stealth pathogens. On the other hand, some of the tradeoffs here are not about our core area of expertise but instead about the broader world: how likely is it that someone tries to create a pandemic like this in the next year vs farther in the future? How much of the risk comes from very clearly engineered things that are easier to detect vs more sophisticated attempts that put substantial effort into hiding what they’re doing? If you’re interested in contributing a substantial amount and have strong views on these questions, please reach out to [email protected]: we have many efforts that are primarily funding-limited and are open to considering your priorities in our prioritization.

Where We Are Now

Resources

The best way to get an overview of our recent work is to read our recent blog posts, and especially our Fall 2024 Updates post. These give the most detail about where we’re putting our work and how that’s been going.

Organization

The NAO began as a collaboration between the research non-profit SecureBio and Kevin Esvelt’s Sculpting Evolution group at MIT. We are in the process of transitioning the project to be entirely under SecureBio, and we expect to complete this by the end of 2024.

The NAO is structured as two sections, a Near-Term Detection project to build, operate, and improve a pilot early warning system, and a Robust Detection project to develop methods that can identify threats beyond the capabilities of our current systems.

Staff

There are nine people working full-time on the NAO. On Near-Term Detection we have one lead, one computational research scientist, two wet-lab research scientists, one research analyst, and one research assistant. On Robust Detection we have one lead and two computational research scientists.

Budget

If we continue at our current level of operations, in 2025 we will spend $2.2M:

Expense Amount
Staff $1.3M
Pilot Detection System $520k
SecureBio Overhead $125k
Wet lab consumables $120k
Compute $100k
Lab space $85k
Office Space

Our office space is generously covered by Open Philanthropy.

The NAO currently has $2.2M available in funds and firm commitments, for a runway of 12 months.

Benefits

A successful NAO would create a system able to detect stealth pathogens early enough in their spread that there’s time to avert the worst outcomes. This has additional benefits through deterrence: the best way to stop someone from creating a stealth pandemic is a detection system that reduces their chances of success to where it’s no longer worth their effort and risk.

There are also benefits in the case of non-stealth pathogens, because a system based on untargeted sequencing can be very rapidly applied to any new pathogen once the genome is known. For example, if we had been operating this kind of system in January 2020 when the SARS-CoV-2 genome was first shared we could have immediately checked whether any of our samples had ever had a match. We could then have continued using our system to track that genome until a more sensitive targeted system was in place.

There are also a range of other benefits:

  • An operational NAO at a scale capable of detecting stealth pathogens early will also generate a wealth of information about existing pathogens, which we’re happy to share.
  • We have been sharing the protocols we develop, which may be useful to other groups analyzing similar samples.
  • Our work comparing different sampling approaches for biosurveillance is strategically relevant to other efforts to detect novel pathogens.
  • Metagenomic sequencing data is an extremely rich data source, and the data we’ve collected so far is larger than the entire catalog of similar data available publicly. This data can be a valuable resource to advance scientific understanding of these complex microbiomes. We share our data, which allows others to analyze it for these and other purposes.

How to Fund the NAO

If you’d like to support the NAO you can make a donation to SecureBio earmarked for the NAO project on our website. Our donation form supports credit cards, debit cards, and, more efficiently, bank transfers. Donations from US residents are tax-deductible. To explore making a tax-deductible donation from the UK or EU, or to discuss alternative ways to give, please write to [email protected].

Footnotes

  1. This could be something spreading with no symptoms, or with symptoms that are generic enough that no one notices anything unusual.↩︎

  2. HIV is a good example of a pathogen with this pattern, though it spreads relatively slowly. An engineered stealth pathogen could combine rapid spread with a long asymptomatic period.↩︎

  3. We estimate that expanding to weekly wastewater sequencing would, in the median case, allow detection of a viral pathogen that sheds like influenza or SARS-CoV-2 before 1-3% of people in the monitored sewersheds had ever been infected (simulator). This would double our annual wastewater sequencing costs, from $470k to $940k. Similarly, our swab sequencing efforts are very promising. While this portion of our pilot is at a much earlier stage and there are a lot of unknowns, we estimate that at a given cost it would be about five times more sensitive in flagging a respiratory pathogen than wastewater sequencing (simulator). We would be enthusiastic to expand this work to daily sampling, at an additional cost of about $100k annually.↩︎