Inside the PLOS ONE Academic Editor studio, part 1.

How did you end up being an Academic Editor at PLOS ONE?

Well, I was asked, then pondered on it for a day, and said yes. Quite simple, actually. And apparently, this is how it is usually done: another editor recommends you, you get an invitation from the journal office, submit your CV for perusal, and then you’re either in or out.

That’s all good, but why did you choose to become and editor?

I am an editor for two smaller societal journals, one aimed for amateur ornithologists and one on infection ecology and epidemiology, so I knew what was expected of me. However, the main reasons were academic solidarity and promotion open access publishing. That may sounds a bit presumptuous and aloft, but I think it is important to see science as something that is different from other lines of business. In my case, I have published >100 papers. If we assume that 1-6 reviewers have read each paper, depending on whether they were accepted in the first journal or passed on to other journals, this means several hundred peers have been evaluating my work. That is quite a work load, done by unpaid peers – and without that commitment science wouldn’t work. I have always tried to do as many referee assignments as possible, but now I am in a position to also contribute to the editor role more widely.

I heard the word ‘open access’ there, is that an important concept for you?

Yes, it is. Good science should be accessible for everyone, especially when based on taxpayers’ money. However, open access is not a religion, and I think it is important that we acknowledge that there are pros and cons with this way of publishing, including the balance on how much auxiliary data that need to go with a publication, for instance. In any case, the plus side is way larger than the down side, and I sincerely believe that open access journals are the future of scholarly publishing.

Why PLOS ONE, and not any of the other journals out there?

Well, PLOS ONE was first to ask, he he he. But flattery aside, I also have a very good publishing history with the journal, and its sister journals. My first paper in PLOS ONE was published in 2007, back when it was a very new journal. In fact, we hadn’t really figured out how the journal worked, and thought it was the most selected of the PLOS’ journals. That paper on avian malaria speciation was first submitted to Science, where it was out on review, but rejected in the second round. Anyway, it found a good home in PLOS ONE and has to date been viewed more than 7000 times and cited 44 times. I am pleased.

After that I have submitted many articles to PLOS ONE, sometimes as the first choice, sometimes after being turned down in general societal journals. My experience has been very positive, and we have nearly always got constructive critique from reviewers. What I really, really like is that the articles are accessible directly after publication, and that figures and other materials can be shared – for instance, on our blog. Collectively, this has made me very positive to the journal, and I am happy to now serve as an Academic Editor.

Thank you very much, Jonas. I think we need to stop here for a commercial break, but when we return I would like to ask you more of what you do as an editor, and what authors that submit articles should think about.

You’re welcome. I’d love to chat about that.

TO BE CONTINUED… (at a later date)

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Where have all the subtypes gone, long time passing?

Illustration from Roche et al (2014) on an individual-based transmission model for influenza A viruses in waterfowl. The drawing was made by John Megahan, and is used under CC-BY 4.0 license.

Illustration from Roche et al (2014) on an individual-based transmission model for influenza A viruses in waterfowl. The drawing was made by John Megahan, and is used under CC-BY 4.0 license.

By Jonas Waldenström

Ducks and men differ in some obvious ways. Whereas a Mallard is a fluffy, winged animal that dabbles, a man is an elongated, mostly fur-free mammal that intoxicates itself with beverages and too much screen time. There are, however, also shared traits and even shared pathogens, such as the influenza A virus.

But where you and I will experience only a single, or a couple of different influenza virus subtypes in our lives – for instance the H1N1 or the H3N2 that are touring the world today – an average Mallard can walk through up to 4 or 5 over the course of a few weeks in autumn. The diversity of influenza viruses in Mallards and other waterfowl is simply astounding.

For example, in our studies we have isolated 74 subtypes from Mallards caught in single little pond at the edge of a lagoon opening to the Baltic Sea. This is more than any other sampling site on the planet, and a large chunk of the global diversity for this virus.

There are some patterns to this mess. Some subtypes are actually fairly common at all times in autumn, such as H1 and H4 viruses, other subtypes are detected each autumn, but show more outbreak-like patterns. However, there are some subtypes that just pop up seemingly randomly in the population, sometimes years apart. So where do all subtypes go? A single animal is rarely excreting viruses for more than a couple of days, so the viruses have to go somewhere.

Of course there are hypotheses, and opinions. Perhaps some subtypes reside in other hosts, spilling over occasionally to Mallards? Perhaps the viruses can be maintained in the environment, in the water or in the sediment, or even in ice? Perhaps Mallards do not have long-term efficient immune memory to influenza? Perhaps the population size and annual recruitment of juveniles are large enough to maintain transmission of even rare subtypes? Perhaps they are seeded in from aliens?

A lot of hypotheses in the air, but not too much synthesis. Until now. A recent paper published by American researchers in PLOS Biology examines the existing evidence and model how well data fit different hypotheses. The method they used is phylodynamics. And the results are pretty cool.

Some possible epidemiological pathways are depicted in the figure at the start of this post (except the alien one, strangely enough). Viruses can be transmitted directly between individuals or move via the environment, including possible time delay. Both the environment and the host populations experience seasonal changes, some of which we can quantify and use as parameters in epidemiological models. The effect of these parameters can then be used to illustrate how the relationships between strains of the virus would do in simulated phylogenetic trees over time. If you change a parameter, say herd immunity, how will the resulting trees and stats look like after simulations? Will it look like the data we observe in natural populations, or will it look different?

In the left hand panels in the figure below you see how a tree based on human influenza typically looks like. There is little diversity, the antigenetic landscape (the part the immune system reacts to) changes with small steps, with accumulating mutations (A), and the phylogenetic tree has few, but long branches that stretches forward (G). A typical avian-based set, as seen in the panels to the right, show a mix of colors of different co-occurring lineages with large antigenic diversity (C), and the tree is more a thorny bush (I). In the middle panel you have an example of avian viruses based on direct transmission only. This model isn’t overly well matched with what is observed in nature, and predicts fewer circulating viruses (B), and a different tree topology (H). By doing this sort of analyses over and over again, one is left with the most plausible models. (I know this description is over simplistic, but this is a blog piece after all)

Figure from Roche et al (2014) used under CC-BY 4.0 license. Original caption: (A–C) Time series of influenza prevalence in humans, avian system with only direct transmission, and avian system with mixed transmission, respectively. Basic reproduction ratio, R0, is set to 1.5 for direct transmission, and environmental durability is set at 20 d when this transmission route is included. Colors represent antigenic distance between the introduced strain and the dominant variant at time t. (D–F) The black line represents antigenic diversity through time (i.e., number of antigenic strains), whereas the grey line demonstrates temporal changes in the antigenic distance of the dominant strain to the introduced strain. Time is expressed in years. (G–I) Associated reconstructed phylogenies. (J–L) Co-infection patterns for the situations depicted previously.

Figure from Roche et al (2014) used under CC-BY 4.0 license. Original caption: (A–C) Time series of influenza prevalence in humans, avian system with only direct transmission, and avian system with mixed transmission, respectively. Basic reproduction ratio, R0, is set to 1.5 for direct transmission, and environmental durability is set at 20 d when this transmission route is included. Colors represent antigenic distance between the introduced strain and the dominant variant at time t. (D–F) The black line represents antigenic diversity through time (i.e., number of antigenic strains), whereas the grey line demonstrates temporal changes in the antigenic distance of the dominant strain to the introduced strain. Time is expressed in years. (G–I) Associated reconstructed phylogenies. (J–L) Co-infection patterns for the situations depicted previously.

By tweaking the models and conducting lots of statistics, the research team could show that the two main factors explaining the diversity of co-existing avian influenza hemagglutinin subtypes were “subtype-specific differences in host immune selective pressure and the ecology of transmission (in particular, the durability of subtypes in aquatic environments).” Host immunity is interesting, and something we have worked with ourselves (see here, for instance). The most notable finding was however that they could show the importance of the environmental “storage effect”. Viruses could reenter the population of ducks from the environment – hidden in water or in sediment, perhaps – and start new chains of infection.

The question now is how to prove this, experimentally. Several studies have shown that virus can retain infectiousness for long time if stored in water in the laboratory, and some epidemiological work has suggested that reinfection from the aquatic environment can happen from one breeding season to the next. On the other hand, in our duck trap we see very little evidence for this being a frequent mode of transmission. During autumn, we have a massive deposition of fecal matter from infected ducks in and outside the trap, but when we put in naïve ducks in the trap again in spring, they rarely become infected until the next autumn.

However, perhaps even rare re-introductions of subtypes may be sufficient to re-establish locally extinct subtypes, cause new events of short-lived infection cycles, and then disappear again? Or maybe these virus transmission events are more prone to take place in certain environments than in others? In our case, the duck trap regularly freezes over, sometimes all the way to the bottom, and that may be too hard for our RNA virus friends/foes?

Anyway, always exiting with new well-written articles. Go read it yourself, and don’t forget the 22 supplementary files and appendices.

On a final note, let’s sing:

Where have all the subtypes gone, long time passing?
Where have all the subtypes gone, long time ago?
Where have all the subtypes gone?
Water and mud swallowed them everyone?
Oh, when will we ever learn?
Oh, when will we ever learn?

 

Link to the article:

Roche, B., Drake, J.M., Brown, J., Stallknecht, D.E., Bedford, T. & Rohani, P. 2014. Adaptive Evolution and Environmental Durability Jointly Structure Phylodynamic Patterns in Avian Influenza Viruses. PLOS Biology, 10.1371/journal.pbio.1001931

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