OK, so I need to work on my stage name.
Back in May 2017, I tweeted at Bill Nye:
And it turns out that Bill, and the great writers and producers and everyone else behind Bill Nye Saves the World, were paying attention. Shortly after the tweet I was contacted by a producer of the show and asked if I would like to come on and give a demonstration about the evolution of “super-bugs”, i.e. antibiotic-resistant bacteria.
An opportunity for science outreach involving Bill Nye? Yes, please.
In this post, I first want to talk about the science in my 5 minutes (at the end of Season 2 Episode 3 of Bill Nye Saves the World). Then, I’ll touch on the experience of being on the show.
The Science
I wanted to convey three things in my demo:
- Antibiotics work really well!
- So does natural selection. In the presence of an antibiotic, bacteria resistant to that antibiotic survive and proliferate more than non-resistant bacteria, leading to the spread of the information conferring that resistance (i.e. the evolution of “super-bugs”).
- And that’s why it is important to be judicious about antibiotic use.
all while conveying how scientists can use models of reality to study biology.
So, for my demo I created a model of the evolutionary dynamics of bacterial strains within a person. In this model, bacteria either replicate or die—similar to a common mathematical model used to study evolutionary dynamics called a “birth-death process”. If there is more birth than death, the bacteria grow too big and overflow from the host—the infection spreads to other hosts. If there is more death than birth (as in a typical situation where the immune system does a good job), the bacteria die off —the infection is cleared.
What makes this a model of evolution is that we can introduce two different bacterial strains into the model and observe how the relative abundance of these two strains change within the total bacterial population over time. Let’s say one strain has a mutation in their genome that makes them resistant to antibiotics, and the other strain is still susceptible to antibiotics.
Let’s also assume that the host’s immune system is compromised, all strains are growing more than they are dying. The person goes to their physician, and gets some antibiotics that decrease the birth rate of only the susceptible strain. Growth of the susceptible strain is stopped, but the resistant strain grows and grows, and when the model “overflows” it is the resistant strain that spreads to other hosts.
By continually providing selective pressures favoring resistance, we drive susceptible strains to extinction. As the model suggests, we would expect the spread of antibiotic resistant bacteria to be especially prevalent in areas that have a high concentration of individuals with compromised immune systems that take antibiotics, such as hospitals and nursing homes.
But, there is hope! Many of the mechanisms of resistance are actually costly to bacteria when antibiotics are not present. It may be possible to reverse many of the mechanisms of resistance (select for non-resistant strains) by being extremely judicious about when to apply antibiotics. The original focus of the demo was on how to reverse resistance through exploiting this cost of resistance, however due to time constraints I refocused on the emergence of resistance.
My Experience
Everything was awesome. I had no idea just how much went on behind the scenes to get a show produced. From the props people helping with my demo, to the writers and producers working around the clock anticipating every little thing that will happen. Everyone really cared about being true to the science and explaining the information in an accessible and exciting way. Especially Bill Nye, who was extremely genuine and kind throughout the whole experience. I’m very grateful for the opportunity to help #savetheworld!
P.S.
For those who arrived at my blog curious about my current research: I use mathematical models and simulations to investigate how tumors evolve from our tissues, how evolution has structured our tissues to minimize the risk of cancer, the effects of mutations in growing tumors, and how cancers evolve resistance to chemotherapy. Relating to pathogen evolution, during graduate school, I was part of a team that used mathematical models to study the evolutionary dynamics of pathogens and their hosts.
Vincent Cannataro, Ph.D. 
