Authors: Martha Powell, Future Science Group
This month we’ve been taking a closer look at zoonoses, including Leptospirosis and Nipah; however, with viruses such as avian influenza causing mortalities and morbidities in humans, a question is often raised regarding what viruses could jump the species barrier next. In light of this, we spoke to Tracey Goldstein, Co-Principal Investigator and Pathogen Diagnostics Co-Lead for the viral emergence early-warning project PREDICT.
Tracey, who has a background in marine ecosystems and disease surveillance, is Associate Director and Professor at the University of California Davis (UC Davis; CA, USA) One Health Institute. Here, she gives us an overview of the PREDICT project, what brought it about and its some of the findings thus far – read more below.
First, could you outline the PREDICT project and the rationale behind it?
When the US Agency for International Development (USAID) created the Emerging Pandemic Threats program I think they realized there had been a lot of investment globally in avian influenza but that wildlife had been left out of the equation despite being the source of many viruses. In addition, although there’s a lot of surveillance for disease in humans, and some in livestock, surveillance in wild animals was happening on a small scale, such as by research groups and agencies, thus there was need for disease monitoring. So what USAID were hoping to do was to help bring wildlife into the surveillance and monitoring system, and this was the focus for the PREDICT project.
“Within PREDICT we’re working in places where people and animals have high-risk contact”
Within PREDICT we’re working in places where people and animals have high-risk contact, for example, in markets, hunters or in individuals farming for commodities such as guano. The idea is that we sample animals and people in these high-contact locations and then we try to understand what viruses these animals have and the potential for these to spill over into people.
Why do you think your approach to viral detection in particular sets this project apart?
I think there are a few things that make us different. Originally the project was supposed to have two arms – one was to test for the known agents and the second, PREDICT, was to perform discovery for new agents. In year two we were asked to change our strategy so that we could look for both the known and the new agents.
This led us to go to what we do currently, which is broad viral-family based testing using consensus-PCR. This is broad-based testing, for example, instead of looking just for Ebola we test more broadly for viruses in that group, so for all Filoviruses, and that means you might find Ebola but you would also find other new filoviruses. This is something that’s done in wildlife quite a lot, compared with many labs that perform more specific, quantitative real-time PCR tests to detect specific viruses this approach really sets us apart and the screening helps us get an idea of what is out there.
“…this approach really sets us apart and the screening helps us get an idea of what is out there.”
In addition, I think the types of places we’re working in are very different, looking in the locations with high risk-of-contact means we’re going right back to the source where people and animals are interacting.
Then finally, I think that in many cases there’s more of a strategic paradigm, for example, if you were looking for hanta viruses in rodents you would likely test the feces because that’s where traditionally those viruses have been found. However, as we’re looking for new viruses we test samples that we think will represent how transmission might be occurring based on the interface and contact between animals and people. So for example, if individuals are being bitten by rodents then we would test the rat’s saliva or oral swabs, alternatively if individuals had bats living in their house we might test urine and feces because that’s the way they may come into contact with potential viral pathogens.
Could you describe some of the research that is currently being undertaken?
A question that we are focusing on is what allows some viruses, such as MERS, to infect both camels and humans, and possibly bats as well, whereas other viruses are far more host-specific. We’ve recently published a paper on coronavirus diversity and virus evolution and in this we report around 100 new viruses across rodents, humans, bats and primates. So we have begun to examine the sequences of the coronavirus spike protein, which is the part of the virus that binds the host cell.
To do this, we are currently sequencing the genomes of as many coronaviruses as we can across the coronavirus tree and from different species as well as countries. The aim of this is to see if we can find differences between some of these viruses that may help to explain how some are able to infect multiple hosts and some that are not – and hopefully this will give rise to additional tools, so when we find a new virus we can better understand whether it could be a potential new pathogen.
“…hopefully this will give rise to additional tools, so when we find a new virus we can better understand whether it could be a potential new pathogen.”
Overall, the idea is to move from just discovering the viruses that might be out there to using a risk-based approach to further understand and characterize prioritized viruses to try to better understand where they are in the chain of events that allows them to move from animals into people.
How are these findings translated into ‘action’? And have any of your results been particularly surprising or promising so far?
So first, we work in these countries at the permission of the host country governments. We first share our results in reports for the host country governments to explain our findings and emphasize what our findings are to the relevant parties. We give our results an interpretation in the context of what is either known or not known about the virus – so if we find something that’s related to say MERS or SARS we will include that, although being careful to note that we don’t know yet if it’s a pathogen or not, then we’ll work more to understand the virus further. With completely new viruses, our general approach is to include that they’re not a risk to human health at this time.
Once we’ve been given permission to share our results with the world we share them publically and as well as publish them. We have a partnership with HealthMap and they host a PREDICT site on the HealthMap website – so that is where our data are initially released. In addition, we enter sequences we obtain into the GeneBank database – we haven’t entered everything yet but we’re working on getting them all out there for the world!
“I think one of the things that I’ve been quite surprised by is just the diversity of viruses that we’re finding and that these are different across species.”
In terms of something surprising, I think one of the things that I’ve been quite surprised by is just the diversity of viruses that we’re finding and that these are different across species. For example, we’re finding a lot of different coronaviruses and paramyxoviruses in bats but in primates we’re finding more herpesviruses and simian foamy viruses.
Over the course of the first 5 years we’ve found a little over a thousand viruses and of those about 800 of them were new. Of course, not all are potential pathogens so we to prioritize based on a number of factors, such as host species, where they were found or if they’re related to potential pathogens before characterizing them to try and further understand if they may be pathogenic.
“Over the course of the first 5 years we’ve found a little over a thousand viruses and of those about 800 of them were new.”
What are some of the challenges with the way your data is shared?
The main challenge is that it can be slow to get results out there when you’re relying on a process where many different government partners need to be able to review, become familiar with and understand our project. We’re currently working with about 60 labs in 30 countries and of course they all have different priorities and different timelines for being able to carry out the testing and produce the results – so there can be a lag period between collecting the samples and releasing our findings.
We’re working on shortening this timeline as much as possible and as labs come on board and become familiar with the testing this does happen. One exception to this is if there is an outbreak or we find a pathogen of high-consequence. In these situations we have a much reduced timeline and so if something of importance is found we do share that as soon as possible.
As you’ve mentioned, PREDICT has partners in over 30 countries – how important do you think collaboration is to this project?
Collaboration is huge, it would be impossible to do this project without it. UC Davis is the lead of the consortium and our main partners here in the US are EcoHealth Alliance (NY, USA), Metabiota (CA, USA), Smithsonian Institution (DC, USA) and the Wildlife Conservation Society (NY, USA). We then have teams on the ground in all of these countries from many organizations and they’re the ones that do the work. Usually these teams are well known in the country, familiar to the ministry partners and are composed of field veterinarians, biologists and laboratatoirans, who can handle and test the animals in addition to training other people.
“Collaboration is huge, it would be impossible to do this project without it.”
We lead the project through objective groups, so for example myself and Simon Anthony at Columbia University (NY, USA) run the pathogen detection and discovery group, and we have partners from all the organizations that sit on these to try and ensure we can implement project activities in all the countries in a similar way.
So when you think about it, we have 62 labs, but that is just the labs! There’s at least 30 or more in-country teams and this reach is really the key to the project and the idea behind it. The reason I think we all feel this is so important is that its individuals from these countries doing the work, and we’re training people to do this, so hopefully we can leave something positive behind and eventually these locations can carry out the work independently.
In addition, you employ a ‘One Health’ approach – what do you feel are the benefits of this?
In the first 5 years we really just focused on wildlife but we report our results to the wildlife, livestock and health ministries, which we hope highlighted the importance of understanding the viruses in wildlife and how this affects humans and vice versa. For example, think of the Nipah story – the virus spilled from bats to pigs and then to humans, so if these sectors are not communicating these sorts of situations will perpetuate.
“In PREDICT we’ve gone even further down this path…”
In PREDICT we’ve gone even further down this path and we no longer just sample wildlife, we’re also sampling in people, their animals and the wildlife around their homes – or whatever the interface is that we’re working with. So the One Health approach has been translated to our teams – now when we go out into the field we have wildlife veterinarians, livestock veterinarians and biologists as well as sociologists and nurses or doctors to take samples and survey the participants. I think this has really galvanized the cross-sectoral co-operation as, not only do these teams go into the field together from a practical point of view, they also share and discuss results. It’s important to break down those silos and really understand how contact is occurring, how viruses are transmitting and how we can put prevention measure in place when they’re needed.
Finally, looking ahead, what do you think is the most promising (or important) strategy for combating pandemic potential in zoonoses?
That is a big question! What we’re doing in PREDICT is this broad screening, and not all of the viruses identified will be pathogens but I think the key might be to look at viruses with multiple hosts and start to understand what is it that allows these viruses to be shared and then what circumstances are allowing these viruses to move between animals and people.
I think there are many facets we need to understand – where people are interacting with animals, ecological data, animal and human behavior, the climate and season, and of course understanding the viruses themselves. It’s a huge job and I don’t think we’ll get there quickly but if we slowly chip away at small parts along this pathway of how a virus might move and what might govern that, then in the future we can understand what to look for in terms of identifying zoonotic infections.
This study was made possible by the generous support of the American people through the United States Agency for International Development (USAID) Emerging Pandemic Threats PREDICT project. We thank the governments for permission to conduct this study, the PREDICT Consortium, and the field teams and collaborating laboratories that performed sample collection and testing.
- Anthony SJ, Johnson CK, Greig DJ, Kramer S, Che X, Wells H, Hicks AL, Joly DO, Wolfe ND, Daszak P, Karesh W, Lipkin WI, Morse SS, PREDICT Consortium, Mazet JAK, Goldstein T. Global patterns in coronavirus diversity. Virus Evol, 3(1): vex012 (2017).
- Anthony SJ, Gilardi K, Menachery VD, Goldstein T, Ssebide B, Mbabazi R, Navarrete-Macias I, Liang E, Wells H, Hicks A, Petrosov A, Byarugaba DK, Debbink K, Dinnon KH, Scobey T, Randell SH, Yount BL, Cranfield M, Johnson CK, Baric RS, Lipkin WI, Mazet JAK. Further Evidence for Bats as the Evolutionary Source of Middle East Respiratory Syndrome Coronavirus. mBio, 8(2): e00373-17 (2017).
- Anthony SJ, Islam A, Johnson C, Navarrete-Macias I, Liang E, Jain K, Hitchens PL, Xiaoyu C, Soloyvov A, Hicks A, Ojeda-Flores R, Ulrich W, Rostal M, Epstein J, Petrosov A, Garcia J, Wolfe N, Goldstein T, Morse SS, Mazet J, Daszak P, Lipkin WI. Non-random patterns in viral diversity. Nat Comms, 6: 8147 (2015).
- Anthony SJ, Epstein JH, Murray KA, Navarrete-Macias I Zambrana-Torrelio CM, Solovyov A, Ojeda-Flores R, Arrigo NC, Islam A, Ali Khan S, Hosseini P, Bogich TL, Olival KJ, Sanchez-Leon MD, Karesh W, Goldstein T, Luby SP, Morse SS, Mazet JAK, Daszak P, Lipkin WI. A strategy to estimate unknown viral diversity in mammals. mBio, 4(5): e00598-13 (2013).