Like most websites The Translational Scientist uses cookies. In order to deliver a personalized, responsive service and to improve the site, we remember and store information about how you use it. Learn more.
Tools & Techniques Infectious diseases, Drug discovery, Informatics

A Universal Shot

I’ve recently been involved in a project to design a potential universal flu vaccine using bioinformatics (1). There will be a lot of people who after reading our paper will say (and indeed have said): been there, done that, didn’t work – give up! But we can’t really afford that attitude when it comes to influenza. Currently, our situation regarding the flu is like living in a region prone to storms; we have a fairly reliable drill for dealing with storms, but very occasionally there will be a hurricane – and the standard storm drill will be fairly useless when that happens. Standard vaccination regimes are unlikely to cut it during a pandemic. We can simply wait for the big one, shrug our shoulders and see what fate brings, thinking about ways to deal with it in the meantime – or we could try to prevent it. In other words, we shouldn’t give up on the development of a universal flu vaccine just because it’s a tough challenge to solve.

Past R&D experience with universal flu vaccines has not been very encouraging. The general principle is obvious – if the HA and NA surface proteins on the flu particle evolve so fast, then why not use something slower moving as a therapeutic target? And the answer is obvious too – it’s the fact that the immune system mostly reacts to the surface proteins, which is why they are under such evolutionary pressure. You can choose to immunize with parts of the HA that are further from the surface – the “stalk” approach – or you can choose one or more of the other proteins, but the immune system won’t react as strongly. The optimal method so far has been to use real viruses – inactivated, of course – as the immunogen. You get the strongest response that way, at the cost of having to refurbish and redistribute the vaccine on an annual basis. Response to a synthetic vaccine may be longer-lasting, but if it’s many times weaker, what’s the point? Our current flu vaccination methods, although relatively safe and effective, can’t possibly be the best approach. It’s a massive undertaking to identify the dominant strains and to manufacture the vaccines – all credit to those who organize it.

I believe there is reason for renewed optimism that the industry can develop a one-shot vaccine. The field of biology continues to advance and we now know a lot more about flu genomes and the human immune system than we did 20 years ago – or even just 10 years ago. When researching a universal flu vaccine, the first step is to try to define the conserved regions of the viral genome. There are thousands of complete sequences of viral genomes, and at least one complete from almost every one of the 144 possible subtypes, so you can reliably identify the conserved regions. This has been done many times in the past, but new data are being added all of the time. Previous universal vaccines relied, to a large extent, on predicted immunogenicity, but now we can bring in evidence. In our work, we have combined available experimental data with informatics-based immunological predictions to help design vaccines that are potentially able to induce cross-protective T-cells against multiple influenza subtypes.

Our current flu vaccination methods, although relatively safe and effective, can’t possibly be the best approach.

There are a few technical difficulties when it comes to bioinformatics, but the main problem is simply that the field and its potential are not always fully appreciated. In physics, the theoretical physicist is regarded as the equal of the experimental physicist. Unfortunately, this is not quite the case in biology. Theoretical biologists, whether they describe themselves as computational biologists, bioinformaticists, or choose to identify more with one of the specialities (such as phylogenetics or genome analysis) can still find themselves cast into a service role – or not regarded as “the real thing” (look at #dataparasites on Twitter, if you want an example).

Bioinformatics is essential for everything in biology now – and more attention is being directed at this field and how it can benefit drug development. But for those of us who have been in the business for more than 30 years, it feels like very slow progress. With bioinformatics, I believe that we can solve many drug development challenges – including the design of a universal flu vaccine. Viruses, in particular, are excellent subjects for bioinformatics. You just need to have a little faith.

Receive content, products, events as well as relevant industry updates from The Translational Scientist and its sponsors.

When you click “Subscribe” we will email you a link, which you must click to verify the email address above and activate your subscription. If you do not receive this email, please contact us at [email protected].
If you wish to unsubscribe, you can update your preferences at any point.

  1. QM Sheikh et al., “Towards the knowledge-based design of universal influenza epitope ensemble vaccines”, Bioinformatics, Epub ahead of print (2016). PMID: 27402904.
About the Author
Derek Gatherer

Derek Gatherer is a lecturer at Lancaster University

Register to The Translational Scientist

Register to access our FREE online portfolio, request the magazine in print and manage your preferences.

You will benefit from:

  • Unlimited access to ALL articles
  • News, interviews & opinions from leading industry experts