Episode 13: Evolutionary Arms Race
Origin Stories
Meredith Johnson
4.8 • 554 Ratings
🗓️ 29 April 2016
⏱️ 21 minutes
🧾️ Download transcript
Summary
In this episode we take a closer look at the evolutionary arms race between humans and the microbes that make us sick. What does each side bring to the fight? Dr. Pardis Sabeti of Harvard University is a computational biologist who uses math and computers to look into the genomes of humans and infectious microbes to see how both humans and microbes are evolving. She was named one of TIME Magazine's People of the Year in 2014 for her role in the fight against ebola.
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| 0:00.0 | This is Origin Stories, the Leaky Foundation podcast. |
| 0:10.4 | I'm Meredith Johnson. |
| 0:14.9 | On a previous episode, for World Tuberculosis Day, we talked about new research on the origins of TB in the Americas, |
| 0:23.2 | and the terrible toll this disease has taken on humankind for thousands of years. |
| 0:28.6 | In this episode, we'll take a deeper look at the evolutionary arms race between us and the microbes that make us sick. |
| 0:36.7 | When Ebola started to spread across West Africa in 2014, it was terrifying. |
| 0:43.1 | There is no cure for the disease, and the only way to stop an outbreak from turning into a devastating |
| 0:48.1 | pandemic is to isolate people who get sick and hope it doesn't spread. |
| 1:01.0 | Partis Sibeti is a professor of evolutionary biology at Harvard University and the Brode Institute. She had been working in West Africa for many years in Sierra Leone at a place called Kenema. |
| 1:07.0 | She was part of a team there focused on fighting a different disease called Lhasa fever. |
| 1:12.6 | And when the first cases of Ebola started to arrive at Kenema, |
| 1:15.6 | Sabetti and her team jumped into action. |
| 1:18.6 | Her labs sent advanced diagnostic equipment to Kenema, |
| 1:21.6 | so health workers there could quickly detect cases of Ebola. |
| 1:25.6 | She knew that to stop this deadly disease from spreading, |
| 1:28.6 | they first had to understand how it was evolving, and they had to do it fast. They needed some |
| 1:34.7 | intelligence on the enemy. All the diagnostic tests, drugs, and treatments depended on understanding |
| 1:41.3 | how the Ebola virus was evolving. |
| 1:47.1 | To understand how she and her colleagues figure that out, |
| 1:50.5 | you have to understand a little more about this evolutionary arms race between humans and microbes. |
| 1:53.7 | Well, I think infectious diseases have always been really intriguing, |
| 1:56.9 | particularly from an evolutionary standpoint. |
... |
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