NEB Podcast #44 -
Transcript
Interviewers: Lydia Morrison, Marketing Communications Writer & Podcast Host, New England Biolabs, Inc. & Betsy Young, Product Marketing Manager, New England Biolabs, Inc.
Interviewees: Nídia Trovão, Scientist, Fogarty International Center, National Institute of Health
Lydia Morrison:
Welcome to the Lessons from Lab and Life podcast, brought to you by New England Biolabs. I'm your host, Lydia Morrison, and I hope this episode offers you some new perspective. I'm joined today by my colleague, Betsy Young, as we interview Dr. Nídia Trovão, scientist at Fogarty International Center of the National Institute of Health, where Nídia studies the evolution of viral pathogens in human and animal populations. Nídia, thank you so much for taking time out of your schedule to be here today.
Nídia Trovão:
Thank you for having me. No, it's a pleasure.
Lydia Morrison:
So by way of an introduction, I was wondering if you could tell us about your role at the Fogarty International Center at the NIH.
Nídia Trovão:
I'm a molecular epidemiology, that studies the evolution of viral pathogens. So more precisely, I investigate viral genetic sequences to trace the occurrence and accumulation of mutations over time. So besides obtaining a wealth of information on the viral genetic diversity and being able to identify genomic regions that tend to change more rapidly, or that are more conserved using biogenetic models, which is like building a family tree for viruses, I am also able to map mutations spatially, to trace how pathogens are transmitted from one location to another, be it from one country to another country or within a specific city or region. And this allows us to identify sites that serve as viral sources, routes that may pose an increased risk of viral transmission, identify variants and which ones dominate in specific locations or periods of time. All of this knowledge that will then assist with strain selection for vaccine development and inform implementation of control strategies.
Lydia Morrison:
Wow, that's a really important role. So your role also involves training scientists in genomic epidemiology. Can you tell us a little more about that process and what you've learned about teaching scientists from different diverse backgrounds?
Nídia Trovão:
Yeah, that's right. So besides my research work, I am also involved in building capacity on genomic epidemiology, with an emphasis on scientists from low and middle income countries. At Fogarty, I've initially thought these concepts applied to influenza viruses, which are also respiratory viruses with pandemic potential, and that serve as an excellent test bed for training, but with the COVID-19 pandemic, we ramped up our efforts in adapting to this new reality and transformed our intensive in-person workshops into virtual workshops, workshops with hundreds of hours of materials focused on these viruses and its variants. So right from the start of the pandemic in March 2020, in a collaboration with partners from the Johns Hopkins Applied Physics Laboratory, we mounted an initiative to train scientists across the US on sequencing COVID samples using the Oxford nano technologies platform. And besides generating genomic data, we also taught how to analyze the viral sequences and perform phylogenetic analysis that would enable the comparative study of different samples. For instance, to trace if two samples are part of the same outbreak, or the results of separate viral introductions.
Nídia Trovão:
So the demand for such training was even higher for scientists in low and middle income countries. And so, by capitalizing on the virtual era, we were able to train close to 400 scientists throughout the Americas, Africa and Asia, which we really believe to be critical work necessary to improve surveillance coming from these locations, and therefore the ability to better trace and control the current pandemic. These scientists are not only reporting viral genome sequences, but they are now able to analyze this genomic data to provide more informed advice to their public health agencies.
Nídia Trovão:
So not to answer your second question, teaching, of course, such a diverse public has been a great honor and learning experience. The team and I definitely notice how different cultural norms shape interactions so we try to tailor each workshop to provide the best learning environment, conducive to acquiring knowledge and implementation in their own labs and countries. It has also been very gratifying to see the improvements resulting from these trainings. We observed the considerable rise in the number of samples sequenced from these locations, making it possible to study SARS‑CoV‑2 dynamic in these understudied locations and culminating in scientific publications. Specifically what I've learned and that's stuck with me the most is that these brilliant scientists are very motivated and created. And they do so much with the minimal resources available, be it on the surveillance side or the computational sides. I mean, and of course these are lessons that can be most definitely applied to laboratories from locations with more resources.
Lydia Morrison:
That's really amazing. It sounds like the ability to meet virtually has allowed you to reach a lot more people with the training, and I'm sure it's been really powerful and important during the pandemic to allow for that uptick in testing.
Betsy Young:
You're a member of the Multinational Influenza Seasonal Mortality Study, can you explain a little bit more what that's about?
Nídia Trovão:
Yes. So our division at the Fogarty International Center leads the Multinational Influenza Seasonal Mortality Study, what we call MISMS, which is an international collaborative effort to analyze national and global mortality patterns associated with influenza virus circulation. And our goals are to describe the synchrony in seasonal variations of various causes of mortality associated with influenza, both within and among countries, and their association with changes in viral genetics, including the circulating flu subtypes, antigenic characteristics, population factors, and vaccine coverage. And we also aim to develop new methods for estimating seasonal influence's impact on tropical countries' mortality patterns, and hopefully derive a world map of influenza mortality burden and seasonal patterns.
Betsy Young:
So, that's no small task. Again, we thank you for your work there, we all do. In the past, you've studied HIV-1 and, as you've just mentioned, influenza. If we can personify viruses for a moment, what makes one virus more successful than another? And what does a virus consider successful?
Nídia Trovão:
Well, that's a great question. Yes, I've fortunately been able to work in a variety of viruses from plants to animal and human viruses. So first of all, in a anthropocentric view, what makes a virus successful would be to jump from its animal reservoir to humans. HIV-1, for instance, is a prime example of this, as we have identified four clear groups, M, N, O, and P, and this represents a sign that the virus successfully made the jump from their natural primate host into humans on at least four separate occasions. However, these groups of HIV-1 have experienced different degrees of success in their newfound hosts. For instance, group N and P viruses are very rare. Group O viruses have fared better, but are still mainly restricted to a few countries and represent less than 1% of the world's HIV infections.
Nídia Trovão:
And it was really the M viruses that have flourished into infecting millions of people and to understand why, we have to look also at a human hosts. So humans have several natural mechanisms of antiviral activity, but group M viruses were able to use different proteins altogether to antagonize those antiviral mechanisms far more efficiently than any other of the three groups. For influenza viruses, we have four main subtypes named after the hemagglutinin and the neuraminidase protein combination that's circulating humans and cause seasonal flu during winters, for which there are vaccines available. Now, the issue with flu is the immense genetic diversity of its surface proteins, the hemagglutinin, neuraminidase proteins implicated in the viral attachment and release. So of this diversity that circulates in other animals, some of this diversity, I mean, that circulates in other animals, are mutations away from being able to jump and successfully transmit to humans. Viruses like those that have emerged in the past and caused pandemics such as the 1918 H1N1 pandemic, the 1968 H3N2 pandemic, and more recently, the 2009 H1N1 pandemic.
Nídia Trovão:
The first two jumped from birds and the most recent jumped from pigs. Those that jumped from birds attached better to cells in our lower respiratory tract causing severe pneumonias and thus, have increased mortality. That's why there is so much concern about the potential jump in human to human transmission of bird flu H5N1, which is highly transmissible and deadly. So RNA viruses such as HIV, influenza, or SARS‑CoV‑2, have the ability to mutate incredibly fast and evolve into something our immune system has not seen before and spread rapidly. So in a nutshell, a successful virus is highly transmissible, it can easily adapt to the host, as we've seen with the ever emerging SARS‑CoV‑2 variants, particularly the most recent Omicron variant of concern that is both more transmissible and has adapted to partially evade immunity.
Betsy Young:
Wow. I feel like I have so many more questions now about what makes bird viruses more apt to attacking human lungs, but we don't have time for those today. But my next question is about you spending a lot of your time modeling disease outbreaks, and I'm not a disease modeler so I am not really sure how accurate mathematical modeling of diseases and disease outbreaks can be. Can you give me a quick primer on modeling of disease transmission?
Nídia Trovão:
So mathematical models that look at trends in cases, hospitalizations or deaths deal with large data sets, what we sometimes call big data. These large pools of data allow the construction of accurate representations of the overall patterns, to the degree that we are now using them to predict future trends. My work focuses on modeling genomic evolution, which is distinct from other epidemiological mathematical modeling. My work is achieved using phylogenetic models. With this, we can investigate the viral genetic diversity and map its transmission dynamics. Even though these models are very powerful in terms of the conclusions that could be made, they mainly rely on genetic sequences. And since we only sequence a small fraction of the number of cases of an outbreak, these models are hindered by the limited number of phylogenetic sequences available.
Nídia Trovão:
Now, the accuracy of phylogenetic models of disease transmission also depends on the virus one is studying. No other virus has been sequenced as much as SARS‑CoV‑2, for which there are currently more than 10 million sequences available. So this gives the ability to produce very accurate reconstructions of both the viral genetic diversity and the viral movements. For instance, in one of my recent manuscripts published in the journal of Virus Evolution, we were looking at the dynamics of the alpha variant of concerning Pakistan. We targeted the population that had traveled to the UK so the expectation was that the patients had acquired the infection while in the UK. However, the models persistently inferred that one of those infections came from Bahrain. So after asking my collaborators for more precise metadata, we realized that the patient had a layover stop in Bahrain, where they likely got infected, and thus confirming the inference obtained by the phylogenetic models. So I would say that with enough sequence data and appropriate metadata, phylogenetic models can accurately uncover the detailed routes of viral transmission.
Betsy Young:
There's definitely a lot to it, so thank you for that great explanation.
Lydia Morrison:
I feel like we're talking about viruses more than ever over the last couple years, I was curious how you feel COVID-19 has impacted infectious disease research?
Nídia Trovão:
Well, it definitely had an impact. We neglected research on other infectious diseases because the attention was directed to SARS‑CoV‑2 and people were not seeking healthcare as much. But on a positive side, there was a big boom in several areas of infectious disease research that were developed, or rapidly matured, to tackle the current pandemic with the new mRNA vaccine technology being one of the most notable examples. So the impact on other pathogens is also notable because, for instance, this mRNA technology will potentially revolutionize influenza vaccines as these are produced much faster than the traditional ones, likely allowing the selection of more up-to-date vaccines strains, instead of relying on flu strains that were surveilled several months prior to when the vaccines are delivered. So we're rather excited about this prospect.
Betsy Young:
Actually to follow on that, can you give me your opinion, how has COVID-19 impacted preparedness for the next virus of interest, if it's a coronavirus or something else?
Nídia Trovão:
Well, we are still learning from this one in a hundred years event, particularly on how to better detect and contain the virus as new SARS‑CoV‑2 variants emerge and cause new disease waves, as well as how we can coordinate efforts globally in a more cohesive way. But in doing so, we are also increasing readiness for the next emerging infectious disease to threaten the world. Besides this, there are a few other areas where I believe we need to work on for an improved response to a future pandemic. So firstly would be to strengthen early alert frameworks like those implemented in many east Asian countries to monitor the constant threat of communicable upper respiratory diseases. Many of these diseases have been identified and mitigated efficiently using this outer perimeter that serves as a reliable early alert system made by scientists that are able to identify the science that a novel pathogen is emerging and know when to sound the alarm.
Nídia Trovão:
Of course, this can only be achieved if these systems are funded and not politicized or stigmatized, as we've seen repeatedly during the COVID-19 pandemic. And talking about funding, one of the risk management conundrums in pandemic preparedness and biodefense is that the risk feels intangible. So experts who warn about the threats of emerging infectious diseases are frequently dismissed with little funding being directed to zoonotic surveillance or to surveillance at the human animal interface where potential animal to human jumps will likely occur. So to that end, global coordination and open collaboration will be crucial for appropriate reporting and analysis of the data in a more comprehensive way. However, we do see such discoordination even at the country level, with different regions surveilling, analyzing and reporting data using different or unstandardized methodologies and timeframes. So to achieve all of this, we need to have a large skilled workforce in the different disciplines of emerging infectious diseases all over the globe, including epidemiologists, virologists, computational and public health scientists, policy makers, nurses, and doctors, of course.
Nídia Trovão:
So investment in capacity building efforts is an investment with the future in mind. And besides training, we also need to have ready a robust stockpile of medical and laboratory materials, PPE and similar support equipment. We also need to create global mechanisms in which treatments of vaccines become more readily available to all parts of the world, both in terms of costs, and distribution logistics. So finally, further support should be allocated for the preemptive development of vaccines and treatments aiming at specific pathogens identified as potential pandemic risks. And besides development, the rapid vaccine capability that emerged to tackle the COVID-19 pandemic should not be disbanded once COVID-19 is contained, primarily since many low and middle income countries still rely on coordinated international assistance to contain domestic threats and outbreaks and prevent mutations from leaping over national borders.
Betsy Young:
That feels like a complete plan. So if our future leaders would just watch this podcast, they'll have the blueprint to our next pandemic. So thank you for putting it out there.
Lydia Morrison:
So where do you hope to see your work in the next five years?
Nídia Trovão:
Well, when I start in the field of phylodynamics, during my PhD, I was mainly focused on expanding this nascent field by developing models so we could better reconstruct the transmission dynamics of the plethora of pathogens infecting the variety of hosts. But joining NIH gave me the opportunity to expand these efforts beyond borders, gain access to an enormous collaborative network so I could reach farther, especially to low and middle income countries constantly battling with low resources, where I can have the greatest impact towards improving public health. So in the next five years, and with the continuous development of the field, I see my work being part of the real time analysis necessary for implementation of policy. Also, with the advent of genomic surveillance, I hope that my work will be able to shed light on the mechanisms leading to the emergence of infectious diseases in understudied locations.
Lydia Morrison:
I think those are admirable goals. Where do you feel like the field is headed in the future?
Nídia Trovão:
Well, with the continuous development of new computational models, of course these development will allow more efficient mining of genomic data, resulting in more complete and accurate inferences. These models will also enable the integration of additional metadata sources to give us a clearer insight into the pathogen's evolution and transmission dynamics. We will continue to witness increased computational powers in terms of processing capabilities, reducing the considerable time necessary to process the ever increasing numbers of sequences and associated metadata. And on the other hand, models that may present too complex for current hardware may become viable in the near future. I also think we will see sequencing being employed more routinely and become even more approachable with the broader use of small portable sequencing technologies that will hopefully translate into sequencing being commonplace, even in rural locations on, and on mobile settings. This will cause a significant increase in the number and breadth of sequences, which will in turn improve the precision of our inferences for a variety of pathogens.
Nídia Trovão:
Now, of course, sequences are great, but we also need the respective appropriate metadata. So I hope that standardization and massification of technology will help gather more precise and complete metadata, which will seriously aid in the completeness of the reconstructions. I also think there will be new and inventive ways to gather samples and metadata, such as the nascent field of digital data for epidemiology, or wastewater surveillance, which has been improved beneficial to, for example, study the use of opioids or the emergence of new waves of SARS‑CoV‑2. And of course, with the ever-growing amount of genomic and metadata and additional computational power, I can also see how artificial intelligence and machine learning could be adopted for more efficiently infer a variety of patterns, such as which mutations could emerge in which parts of the viral genome, cohorts of patients and locations in the world.
Lydia Morrison:
Pretty interesting time to be in infectious disease research.
Nídia Trovão:
Absolutely.
Lydia Morrison:
I hope that some of your predictions about the future are true because it seems like those are changes that would have real effects on health outcomes of the community and the country and the world, so-
Nídia Trovão:
Rather sooner than later, right?
Betsy Young:
And if I can ask one last question, you maybe biased towards influenza, but what do you think is the most interesting virus out there and why?
Nídia Trovão:
Well, you really got me. It's definitely my favorite pathogen to work on, mainly due to a particular genomic characteristic. Flu has a segmented genome, meaning that its genome, instead of being a long RNA copy, is composed of eight RNA segments. Of these eight segments, as I mentioned earlier, two of them encode for the surface proteins, hemagglutinin, or HA, and neuraminidase, or NA. So HA and NA are quite diverse and have been organized into subtypes, that's why you sometimes hear H1N1 or H3N2. But in fact, to date, there have been identified 18 HA subtypes, and 11 NA subtypes from humans and a variety of other animals. So this means that the flu virus, besides accumulating mutations very fast, similar to that observed in SARS‑CoV‑2 or HIV, its segments can reshuffle in different combinations or constellations, a phenomenon that we call reassortment.
Nídia Trovão:
Now, reassortment in flu is of genuine concern as it is a mechanism for the quick generation of new diversity and has been described as how influenza pandemics have emerged. So if a new unique combination of genes or genomic constellation emerges for which there is no immunity, this can cause serious problems. Also, as we talked before, depending on the subtype and from which zoonotic host it originates, it can also translate into a more severe disease. So this high severity potential compels me to study it further so we can be better prepared if something arises. So yes, flu for sure.
Betsy Young:
I knew it. I could tell.
Lydia Morrison:
Thank you so much for taking time out of your schedule to talk to us today, Nídia. It's been such a pleasure.
Nídia Trovão:
No, the pleasure was all mine. Thank you so much.
Lydia Morrison:
Yeah. Thanks for joining us, Betsy. Thanks for co-hosting with me. I appreciate it.
Betsy Young:
Always happy to.
Lydia Morrison:
We can't wait to see what the future of infectious disease research holds and we'll continue to follow your publications. Thanks so much for all the work that you do.
Nídia Trovão:
Thank you. Bye, bye. Take care.
Lydia Morrison:
Bye, bye.
Lydia Morrison:
Thanks for joining us today. Please tune in next time when I interview Dr. Anu Rebbapragada of FH Health, based in Toronto, Canada. FH Health is a health tech company that was created early in the COVID-19 pandemic to address public diagnostic testing needs.
