Looking back on 2013 (part I): A dozen publications, some zombies, but no pandemics

By Jonas Waldenström

Post-apocalyptic dawn will have to wait some time more

Post-apocalyptic dawn will have to wait some time more

A year goes by so fast, and soon it is time to close the book on 2013. One thing we can conclude, at least, is that there was no apocalypse, and no end-of-humanity pandemic. However, there have been some worrying notes on new emerging pathogens in 2013. On top of the list of concern we find the MERS coronavirus in the Middle East, and the H7N9 low-pathogenic influenza virus in China. Neither of them has caused many human casualties, nor are they common or widespread. No, it is not what they do, but what they potentially could do that worries the disease world. The MERS virus is related to SARS – a deadly viral pathogen that in 1997 jumped from bats, to civets, and further to humans, and which was on the brink of causing a pandemic before it was fortunately contained and stopped. The other bad guy, the H7N9 influenza virus, carries novel antigenic properties to which the human population lacks immunity; thus, if it becomes adapted to spread between people (and not as today, between infected poultry and humans) it could turn into pandemic flu. Both viruses face strong guilt by association, you can say. These pathogens, and others, are like butterflies, fluttering in and out of detection. Worrisome echoes on the radar screens at WHO and CDC. They are also good examples to why field biology is needed in medicine: we need to track reservoirs of diseases, new and old, and we need to understand how diseases evolve. And that’s exactly what we try to do in ZEE. (In sale pitch jargon: we are the good guys!)

So what happened in ZEE during 2013? In this and other posts we will give you a hint of what we did, and how things went.

Publications. 2013 has been a productive year for the ZEE group! More than a dozen publications were published from Linnaeus University (plus a bunch from Uppsala). Most of these are available freely and you can reach them by following the links below. This year was also the year when this blog was launched! A motto we have is to provide popular accounts on the science we do. Thus, for some of the publications there is a link to a blog post in the list below. Read them – lots of fun!

  1. Tolf, C., Wille, M., Haidar, A-K., Avril, A., Zohari, S. & Waldenström, J. Prevalence of avian paramyxovirus type 1 in Mallards during autumn migration in the western Baltic Sea region. Virology Journal 10: 285  [Ebola, Chikungunya and Newcastle – of places, names and Mallard viruses] http://bit.ly/IToOVG
  1. Gillman, A., Muradrasoli, S., Söderström, H., Nordh, J., Bröjer, C., Lindberg, R.H., Latorre-Margalef, N., Waldenström, J., Olsen, B. & Järhult, J. 2013. Resistance mutation R292K is induced in influenza A(H6N2) virus by exposure of infected Mallards to low levels of oseltamivir. PLoS ONE 8(8): e71230. [This flu, that flu, and Tamiflu®] http://bit.ly/1gw2roa
  1. Safi, K., Kranstauber, B., Weinzierl, R., Griffin, L., Rees, E., Cabot, D., Cruz, S., Proaño, C., Takekawa, J. Y., Waldenström, J., Bengtsson, D., Kays, R., Wikelski, M. & Bohrer, G. Flying with the wind: scale dependency of speed and direction measurements in modelling wind support in avian flight. Movement Ecology 1: 4. [As the Mallard flies] http://bit.ly/19mFVtC
  1. Wille, M., Tolf, C., Avril, A., Latorre-Margalef, N., Bengtsson, D., Wallerström, S., Olsen, B. & Waldenström, J. 2013. Frequency and direction of reassortment in natural influenza A virus infection in a reservoir host. Virology 443: 150-160. [How do you do, the things that you do, Mr Flu?] http://bit.ly/18JpZkp
  1. Latorre-Margalef, N., Grosbois, V., Wahlgren, J., Munster, V.J., Tolf, C., Fouchier, R.A.M., Osterhaus, A.D.M.E., Olsen, B. & Waldenström, J. Heterosubtypic immunity to influenza A virus infections in Mallards may explain existence of multiple virus subtypes. PLoS Pathogens 9(6):  e1003443. [Why are there so many flu viruses?] http://bit.ly/IUiwoM
  1. van Toor, M. L., Hedenström, A., Waldenström, J., Fiedler, W., Holland, R.A., Thorup, K. & Wikelski, M. Flexibility of continental navigation and migration in European mallards. PLoS ONE 8(8): e72629. [Perdeck revisited – or how does a Mallard know its way?] http://bit.ly/1904O0h
  1. Tolf, C., Latorre-Margalef, N., Wille, M., Bengtsson, D., Gunnarsson, G., Grosbois, V., Hasselquist, D., Olsen, B., Elmberg, J. & Waldenström, J. 2013. Individual variation in influenza A virus infection histories and long-term immune responses in Mallards. PLoS ONE 8(4): e61201. [Disease is a property of the individual] http://bit.ly/1ebcGOz
  1. Hellgren, O., Wood, M. J., Waldenström, J., Hasselquist, D., Ottosson, U., Stervander, M. & Bensch, S. 2013. Circannual variation in blood parasitism in a sub-Saharan migrant passerine bird, the garden warbler. Journal of Evolutionary Biology 26: 1047-1059.
  1. Griekspoor, P., Colles, F.M., McCarthy, N.D., Hansbro, P.M., Ashhurst-Smith, C., Olsen, B., Hasselquist, D., Maiden, M.C.J. & Waldenström, J. 2013. Marked host specificity and lack of phylogeographic population structure of Campylobacter jejuni in wild birds. Molecular Ecology 22: 1463-1472. [Of chickens, wild birds and men – host specificity in Campylobacter jejuni] http://bit.ly/1bCcFeu
  1. Griekspoor, P., Olofsson, J., Axelsson-Olsson, D., Waldenström, J. & Olsen, B. 2013. Multilocus Sequence Typing and FlaA sequencing reveal the genetic stability of Campylobacter jejuni enrichment during coculture with Acanthamoeba polyphaga. Applied and Environmental Microbiology 79: 2477-2479.
  1. Hernandez, J., Johansson, A., Stedt, J., Bengtsson, S., Porczak, A., Granholm, S., Gonzalez-Acuna, D., Olsen, B., Bonnedahl, J. & Drobni, M. 2013. Characterization and comparison of Extended-Spectrum β-Lactamase (ESBL) resistance genotypes and population structure of Escherichia coli isolated from Franklin’s gulls (Leucophaeus pipixcan) and humans in Chile. PLoS ONE 8(9): e76150. [Travel the world – can antibiotic resistant bacteria hitchhike with migratory birds?] http://bit.ly/19mF2kV
  1. Olofsson, J., Axelsson-Olsson, D., Brudin, L., Olsen, B. & Ellström, P. 2013. Campylobacter jejuni actively invades the amoeba Acanthamoeba polyphaga and survives within non-digestive vacuoles. PLoS ONE 8(11): e78873. [doi:10.1371/journal.pone.0078873]. [Good morning Mr Amoeba, may I come in?] http://bit.ly/1cqPybs
We study ducks, and they study us.

We study ducks, and they study us.

Staff and students. A year is also a quarter of a PhD time span, and half of a master student’s time. This means that there are many comings and goings in a research group over time. This year, one PhD left the nest and graduated, and four are due in 2014. No new PhD student started, but there were three babies born, thereby boosting the current ZEE children count to more than 10, enough for a football team!

Two former PhD students got a flying start: Dr Neus Latorre-Margalef is on a postdoc in Athens, Georgia, funded from the Swedish Research Council (VR), and Dr Josef Järhult in Uppsala got a huge researcher grant from VR to build up his own group! Fantastic news!

After finishing her MSc last year, Anna Schager got a PhD position in Italy in the spring. Olivia Borg and Anu Helin made their honors’ degree in the lab and then moved to Uppsala for MSc studies, while Johanna Carlbrand and Andras Turai stayed on with MScs at Linnaeus University.

With no real apocalypse in sight, 2013 instead became the zombie year, a trend that culminated with the WWZ movie. If you want to prepare for the coming zombie apocalypse, the author and blogger Colin M. Drysdale has a range of tips for you, including how to make projectile weapons with toilet brushes. You never know, such a skill may come in handy one day when the undead are going for your entrails. Next week we will get back on the-end-of-year-theme and present the best and the worst links/papers/topics of 2013! Cheers!

How bats in Peru change our view of flu (and it rhymes!)

By Jonas Waldenström

I am the real Bat Man and here to bite y'all

I am the real Bat Man and here to bite y’all

One of the major news in the virology community last year was the publication in PNAS describing a completely new influenza A virus. In line with the taxonomy traditionally used for influenza viruses it got the name H17N10, illustrating that it possessed novel hemagglutinin (H17) and neuraminidase variants (N10). However, it wasn’t the numbers that was the ground breaking news, it was the fact that the virus was detected in a Central American bat, and not in a bird. A tropical bat is very far from the ‘normal’ diversity of influenza A viruses seen in wetland birds and waterfowl. Although bats and ducks both have wings, in evolutionary terms they separate a very, very long time ago in the age of dinosaurs. In fact, there are more differences than similarities between bats and gulls in ecology, physiology and aspects of cellular biology. Hence, the bat flu was a remarkable observation. A real shaker. In one sweep, the whole flu field needed to come with terms that not all viruses are bird viruses.

The initial findings also hinted that the first bat influenza virus was unlikely to be alone. An influenza-iceberg, of sorts, made up of fluffy, winged mammals. This week, a first follow-up was published in PLOS Pathogens. A crew of (mainly American) scientists analyzed samples from bats sampled in the Amazonian parts of Peru in 2010, collected as part of CDC’s tropical pathogen surveys. In total, 114 individuals of 18 bat species were taken out from the freezers and different sample types were screened with a molecular method designed to broadly pick-up the RNA of any influenza A virus. They got one hit from a fecal sample in a single bat! A lucky shot at the Tivoli, given the low sample size. Prompted by this, the authors brought in the big machinery and sequenced the totality of the genetic material in the samples from this poor, long-dead bat and used bioinformatic tools to resolve the genome of the virus that had infected its intestines. When bit by bit was added it became clear that it was indeed a completely new influenza A virus, very different from avian viruses, and similar, but still distinctly different from the earlier H17N10 bat virus. And the name? H18N11 of course!

Please take a close look at the figure below. It shows the phylogenetic relationships of each of the influenza A virus’ eight RNA segments – in black are all ‘non-bat viruses’ and in red the two new bat viruses H17N10 and H18N11. For all the segments coding for ‘internal’ proteins, i.e. those involved in the polymerase machinery or the structural properties of the virus, you see that the two bat viruses are always found in a neat little red outgroup. This signals a long evolution away from other known influenza A viruses. It is a little prematurely to say exactly how long, but the branch lengths indicate that this happened a long time ago.

Phylogenetic trees for the 8 different IAV segements, see http://www.plospathogens.org/article/info%3Adoi%2F10.1371%2Fjournal.ppat.1003657

Phylogenetic trees for the 8 different IAV segements, see http://www.plospathogens.org/article/info%3Adoi%2F10.1371%2Fjournal.ppat.1003657

Now look at the hemagglutinin and the neuraminidase trees (HA and NA, respectively). The same pattern is repeated for the NA, but not the HA. In fact, the two novel hemagglutinins are nested within avian hemagglutinins. How can we interpret this? At first this doesn’t make any sense, but one has to remember that influenza viruses don’t evolve in the same way you or me, trees, shrimps or ferns do. Influenza viruses can reassort, meaning that if two viruses of different origin infect the same cell the different RNA segments can be put in new combinations in the resulting virions. Imagine two decks of cards being shuffled, one red and one black, and that each virion randomly consists of a draw of card from the combined shuffled deck, sometimes red, sometimes black, and sometimes mixed.  This is a rapid way in which new variants can arise, and a reason behind the genesis of pandemic flu in humans.

Returning to the bats, it seems that bat and avian viruses have met in a not too distant evolutionary past, and that a HA variant have sailed into the bat influenza gene pool. It will be interesting to see how the picture changes when more bat viruses are sequenced. Has there been one reassortment event, followed by drift and a subsequent separation into H17 and H18? Or, has there been many? Are there, perhaps, avian H17 and H18 to be found in South American birds? What about bats in North America, Europe, Africa and Asia?

One thing we can be sure of is that there are more viruses waiting to be detected and described. One sign of this comes from the current paper. The authors used the sequenced genomes to construct recombinant HA and NA molecules (using fancy virologist tricks) and used these to build assays (ELISAs) where bat sera could be screened for antibodies against the new HA and NA variants. Where the molecular screening yielded one positive bat, the serology approach found 55 of 110 bats showing signs of having been infected with flu earlier in life. This clearly indicates that influenza viruses are widespread in Peruvian bats, and likely in other parts of the world too. Moreover, they found cases of bats with antibodies to one of the recombinant HA or NA, but not to the other, suggesting that are more combinations of HA/NA to be found.

Finally, and perhaps the most interestingly of all results was that the hemagglutinin of bat influenza viruses does not to behave in the same way as avian hemagglutinins. When a virus is to infect a cell it needs the hemagglutinin protein to serve as a key, docking with a sialic acid receptor – the lock – on the cell. If the key and the lock don’t fit infection will not occur. For instance, a major division between human flu and avian flu is the preferred conformation of a galactose residue on the sialic acid receptors. This little difference makes it hard for avian viruses to infect humans, and vice versa. But with bat viruses it seems sialic acid receptors are not used at all! Instead bat HA uses an unknown receptor for cell entry. Holy Moses!

More to follow shortly, I suppose. Major obstacle at present is the lack of a culturing method for bat influenza viruses. Neither cell lines nor eggs have worked so far. Without the means to grow the virus it is very tricky to study it. But there are many clever virologists out there, so it is likely not too far away.

But I still prefer feathers to fur, and will stick with ducks.

Links to articles:

Tong S, Zhu X, Li Y, Shi M, Zhang J, et al. (2013) New World Bats Harbor Diverse Influenza A Viruses. PLoS Pathog 9(10): e1003657. doi:10.1371/journal.ppat.1003657

Tong S, Li Y, Rivailler P, Conrardy C, Castillo DA, et al. (2012) A distinct lineage of influenza A virus from bats. Proc Natl Acad Sci USA 109: 4269–4274.

Why are there so many flu viruses?

967259_10151436300376338_1637333899_oThe only thing constant in flu epidemiology is that it is always changing. New subtypes appear, old ones retreat; like a play where actors constantly change masks and costumes. Names are put forward in the press, such as the Mexican flu, which changed to swine flu, which changed to the new flu A/H1N1 (but, of course, the swine flu label stuck). The current evildoers in humans are H1N1 and H3N2. These are seasonal flu viruses, meaning that they circulate predominantly in humans, and only occasionally give infections in other animals. Both of them made the leap from another animal reservoir before becoming human flu viruses, and both, in turn, have once been avian influenza viruses.

Most readers will also remember the ‘bird flu’ virus H5N1. First of all: it still exists, endemic in parts of Asia, and in Egypt. It hasn’t left the scene. This virus is a highly-pathogenic avian influenza virus that cause rare, but often fatal infections in humans. The highly-pathogenic prefix means that it is an efficient poultry killer – with close to 100% mortality in infected chicken flocks. That’s like tossing in a mini nuke, closing the barn door and wait for the explosion. A mean virus, for a chicken.

However, the norm among avian influenza viruses is to be low-pathogenic, only causing mild infections in their hosts. For domestic poultry that equals a mild cold, in wild ducks even less so. Recently, yet another flu actor entered the scene: H7N9. This virus has caused a number of human infections and deaths in China, but contrary to H5N1 has not been associated with die-off of domestic poultry. New costume, new play, but still a deadly mix.

So, there is H1N1, H3N2, H5N1 and H7N9 out there – all with the capacity of infecting humans. Earlier flu pandemics have been caused by yet other viruses, and from studies of poultry workers and veterinarians we know that there are viruses with other H and N letters that can infected humans, but without leading to severe symptoms. Even if the list seems long, it is nothing compared to the total diversity of influenza A viruses. The H and the N are shorts for the two surface proteins hemagglutinin (responsible for attachment to cells, and to invasion) and neuraminidase (responsible for letting new virus progeny leave an infected cell). There are 16 H variants, and 9 N variants and as they are encoded on different genome segments, they can end up in any of 144 possible combinations, or subtypes. More than 100 of these subtypes have been found in ducks, and more than 70 of them have been found in our study population of Mallards at Ottenby, in SE Sweden. Thus, there are many, many more flu viruses out there lurking in the shadows.

But why are there so many viruses? And especially, why so many in Mallards?

In study published last week in PLOS Pathogens, we returned to this question and analyzed infection histories of more than 7,000 Mallards sampled at Ottenby during 8 years! Together these ducks were caught and sampled more than 18,000 times! The repeated capture and recaptures of ducks is a major benefit of our trapping scheme, as it allows us to follow the course of natural infections in different birds. This is a gospel I have been singing in two previous posts on individuals and reassortment, and a topic I am likely to return to. Predictable fellow, yes, yes. But let’s turn back to the subject.

What did we do? Well, we analyzed all cases where we had at least two characterized virus isolates from the same bird in the same season. Then we used this data to investigate how frequent reinfection with a particular subtype was given the first detected subtype and how this depended on time. This sounds rather simple, doesn’t it? In truth it was a rather large statistical undertaking, as the 25 supplementary files tells. The devil is in the detail – in this case in dealing with potential pseudo replication and test assumptions. Anyway, we leave the finer details of the stats for now and instead take a look at the table below. It is a contingency table, where rows and columns relate to H subtype at first and second infection, respectively. This means that the diagonal shows cases where the same subtype was isolated at both occasions. The colors highlight combinations that were either overrepresented (blue), or had a deficiency of cases (red) compared to the expected. The first thing to note is the diagonal, where very few cases of reinfections were noted. In other words, a bird infected with, let’s say, an H4 virus, will have a low probability of being infected with the same subtype again the same autumn. This is called homosubtypic immunity, and not different from what we want to achieve with vaccination in humans. Once you have had it you are immune (at least for some time…).

journal.ppat.1003443.g003 However, we also found a great degree of heterosubtypic immunity, meaning that an infection with one H subtype made reinfections with other related subtypes less frequent than expected. If you check the figure again, you can see that there are patterns to these cases of heterosubtypic immunity. In fact, they follow higher order clustering of hemagglutinin gene relationships, as can be seen in the next figure. H1, H2, H5 and H6 viruses belong to the H1 Clade, and a primary infection with any of these will make it less likely to be reinfected with other viruses of the same clade. The pattern was similar for other clades and was actually also detectable at the H Group level (the highest level of structure).


But what does this mean?

It is actually big business. It gives a very strong case for existing selection pressures for hemagglutinin gene diversification. Subtypes as a term predates the genomic area and is based on immune reactions. Typically, a subtype is defined as a group of viruses recognized by the same antisera (antibodies towards a particular virus). Subtypes are well resolved for hemagglutinin and neuraminidase, both in phylogenetic relationships and in responses to antisera. Things match. You would be tempted to think that virus subtypes have diversified until their antigenic properties are different enough for the immune system of the host animal to be unable to treat them with the same set of weapons. For instance, antibodies to an H1 virus shouldn’t interfere with an H2 virus infection.

Here, we show that heterosubtypic immunity is strong for hemagglutinin (but absent for neuraminidase), and that it follows genetic relationships. This means that there is ongoing warfare among hemagglutinin subtypes. If an individual is infected with one subtype, it then becomes harder for other related subtypes to enter and cause reinfections. The strength of this response, and its longevity, will be extremely important for infection dynamics at the population scale and drive which viruses that peak at different times. This is especially interesting in a migratory species like the Mallard, where viruses need to follow their hosts, not in only time, but also in geography. And it means that H subtypes are still diverging. The pace of this divergence would be very interesting to tackle, but will require good time series of influenza genomes (rest assured, we are sequencing like crazy and will return to this subject).

To conclude, our study provides evidence from the field on how natural selection in influenza A virus is driven by host immune processes and that it is evident for the most antigenic protein. The question ‘why’ is therefore dependent on disruptive selection. It also raises a bundle of additional questions. Is the diversification we see in influenza A virus the result of geographic allopatric processes, or through separation in different host species, or is there sympatric diversification going on?

More to do, more to do. This virus will keep us busy for sure.

Jonas Waldenström

Link to the article:


Bubbles and dots – novel ways of perceiving scientific impact


Science is a very competitive business. We compete with our colleagues for positions, grants and tenures. The main currency is publications – the more the better, and in as good journals as possible. (Teaching is often portrayed as being important for your career, but in most cases that are simply not true – just lip service from the system). But how can we measure quality?

Quantity – the number of articles – is one way to show it. This is probably most important in the early part of your career, where each and every publication counts and competition for postdoc money is fierce. But for established scientists this is not as relevant; really, is a scientist with 60 publications better than one with 50? And of course the number of publications is a function of time too, and the old silverback will always win in such comparisons.

Everyone agrees that it should be quality, not quantity that should be most important. But we can’t read everything everyone is publishing – it is simple beyond the realms of possibilities, given the enormous flow of articles in peer-reviewed fora. So how, then, can we put a quality brand on our work? For the last 10 years, the light from the journal Impact Factor has been the beacon to which scientists have set their course. This is an index on how much the average article in a specific journal is cited by other articles in the years that follow. Undoubtedly a very crude measure, and an AVERAGE measure of the journal, not a metric of the specific articles that appears in the journal. (Or in other words: just because an article is published in Nature, it doesn’t need to be a gold nugget.)

Thus science has a huge problem in measuring researcher, article and journal qualities. The quest of publishing in journals with highest possible impact factors, rather than in the journal with the best scope for your study, overloads the peer-review system with an ever-increasing number of reviews.

For individual researchers, the total number of citations, and the arithmetic H2 factor (a value of 3 means the person has 3 articles that have been cited at least 3 times; a value of 23 means the person has 23 articles that have been cited at least 23, etc.) are becoming more and more used.

But impact can also be at the societal level; how well it gets across to the public. The journal family PLOS just released a beta-version of a new article-level metric system that measure a range of factors in articles published in their journals. Quick and easy you can see the number of viewings of a particular article (and all PLOS articles are open access, by the way), the number of downloads, the number of citations in different databases, the social media impact (twitter, Facebook, Wikipedia etc.) and how all these things change over time. You can also play around and compare different articles and journals. A fun exercise, but potentially informative too.

Five hundred PLOS articles matching the keyword 'avian influenza'

Five hundred PLOS articles matching the keyword ‘avian influenza’

The graph above shows the change over time in citations for 500 articles matching the keyword avian influenza. Different journals in different colors, PLOS One in yellow, and the high impact journals PLOS Biology, PLOS Medicine and PLOS Pathogens in green and shades of purple, respectively. And, yes, over time the average article seem to do better in the ‘best’ journals, but the spread in PLOS One is more interesting – with many articles with as good, or better impact than those published in the top-notch journals.

You can also gain insights in where science is made. For instance have a look at where researchers on sexual selection have their headquarters. The dominance of Europe and America is monumental; partly of course due to historic reasons, research infrastructure, funding etc., but likely also because of language (Russians still publish a lot in Russian, Latin American researchers in Spanish, etc.).

Affiliations of researchers on 500 sexual selection papers.

Affiliations of researchers on 500 sexual selection papers.

Speaking about sexual selection. Guess which article that has had highest ALM impact? The dot in the graph below is an article that appeared in PLOS One on fellatio in bats. Perhaps not the most important paper in terms of science, but a curiosity teaser likely picked up by a lot of newspapers. This paper has been cited 6 times, but have more than 9000 shares on social media and 288,000 views at the homepage.

fellatio in batsFinally, what could PLOS do to make it better?

  • It would be awesome if this could be more in Gapminder style, where the user could use combinations of search terms to contrast the results. For instance, if I want to see how well my articles on flu are doing in relation to other articles on flu – how can I do that?
  • It would also be interesting to add journal or keyword-based regression lines.
  • The author institution map is very slow when many articles are chosen. Speed it up please!
  • And of course, it would be nice to see a similar system incorporating other journals too. But, that’s something for the future.

A good initiative!

Jonas Waldenström