Placeholder Image

字幕表 動画を再生する

  • Translator: Leslie Gauthier Reviewer: Camille Martínez

  • You don't know them.

  • You don't see them.

  • But they're always around,

  • whispering,

  • making secret plans,

  • building armies with millions of soldiers.

  • And when they decide to attack,

  • they all attack at the same time.

  • I'm talking about bacteria.

  • (Laughter)

  • Who did you think I was talking about?

  • Bacteria live in communities just like humans.

  • They have families,

  • they talk,

  • and they plan their activities.

  • And just like humans, they trick, deceive,

  • and some might even cheat on each other.

  • What if I tell you that we can listen to bacterial conversations

  • and translate their confidential information into human language?

  • And what if I tell you that translating bacterial conversations can save lives?

  • I hold a PhD in nanophysics,

  • and I've used nanotechnology to develop a real-time translation tool

  • that can spy on bacterial communities

  • and give us recordings of what bacteria are up to.

  • Bacteria live everywhere.

  • They're in the soil, on our furniture

  • and inside our bodies.

  • In fact, 90 percent of all the live cells in this theater are bacterial.

  • Some bacteria are good for us;

  • they help us digest food or produce antibiotics.

  • And some bacteria are bad for us;

  • they cause diseases and death.

  • To coordinate all the functions bacteria have,

  • they have to be able to organize,

  • and they do that just like us humans --

  • by communicating.

  • But instead of using words,

  • they use signaling molecules to communicate with each other.

  • When bacteria are few,

  • the signaling molecules just flow away,

  • like the screams of a man alone in the desert.

  • But when there are many bacteria, the signaling molecules accumulate,

  • and the bacteria start sensing that they're not alone.

  • They listen to each other.

  • In this way, they keep track of how many they are

  • and when they're many enough to initiate a new action.

  • And when the signaling molecules have reached a certain threshold,

  • all the bacteria sense at once that they need to act

  • with the same action.

  • So bacterial conversation consists of an initiative and a reaction,

  • a production of a molecule and the response to it.

  • In my research, I focused on spying on bacterial communities

  • inside the human body.

  • How does it work?

  • We have a sample from a patient.

  • It could be a blood or spit sample.

  • We shoot electrons into the sample,

  • the electrons will interact with any communication molecules present,

  • and this interaction will give us information

  • on the identity of the bacteria,

  • the type of communication

  • and how much the bacteria are talking.

  • But what is it like when bacteria communicate?

  • Before I developed the translation tool,

  • my first assumption was that bacteria would have a primitive language,

  • like infants that haven't developed words and sentences yet.

  • When they laugh, they're happy; when they cry, they're sad.

  • Simple as that.

  • But bacteria turned out to be nowhere as primitive as I thought they would be.

  • A molecule is not just a molecule.

  • It can mean different things depending on the context,

  • just like the crying of babies can mean different things:

  • sometimes the baby is hungry,

  • sometimes it's wet,

  • sometimes it's hurt or afraid.

  • Parents know how to decode those cries.

  • And to be a real translation tool,

  • it had to be able to decode the signaling molecules

  • and translate them depending on the context.

  • And who knows?

  • Maybe Google Translate will adopt this soon.

  • (Laughter)

  • Let me give you an example.

  • I've brought some bacterial data that can be a bit tricky to understand

  • if you're not trained,

  • but try to take a look.

  • (Laughter)

  • Here's a happy bacterial family that has infected a patient.

  • Let's call them the Montague family.

  • They share resources, they reproduce, and they grow.

  • One day, they get a new neighbor,

  • bacterial family Capulet.

  • (Laughter)

  • Everything is fine, as long as they're working together.

  • But then something unplanned happens.

  • Romeo from Montague has a relationship with Juliet from Capulet.

  • (Laughter)

  • And yes, they share genetic material.

  • (Laughter)

  • Now, this gene transfer can be dangerous to the Montagues

  • that have the ambition to be the only family in the patient they have infected,

  • and sharing genes contributes

  • to the Capulets developing resistance to antibiotics.

  • So the Montagues start talking internally to get rid of this other family

  • by releasing this molecule.

  • (Laughter)

  • And with subtitles:

  • [Let us coordinate an attack.]

  • (Laughter)

  • Let's coordinate an attack.

  • And then everybody at once responds

  • by releasing a poison that will kill the other family.

  • [Eliminate!]

  • (Laughter)

  • The Capulets respond by calling for a counterattack.

  • [Counterattack!]

  • And they have a battle.

  • This is a video of real bacteria dueling with swordlike organelles,

  • where they try to kill each other

  • by literally stabbing and rupturing each other.

  • Whoever's family wins this battle becomes the dominant bacteria.

  • So what I can do is to detect bacterial conversations

  • that lead to different collective behaviors

  • like the fight you just saw.

  • And what I did was to spy on bacterial communities

  • inside the human body

  • in patients at a hospital.

  • I followed 62 patients in an experiment,

  • where I tested the patient samples for one particular infection,

  • without knowing the results of the traditional diagnostic test.

  • Now, in bacterial diagnostics,

  • a sample is smeared out on a plate,

  • and if the bacteria grow within five days,

  • the patient is diagnosed as infected.

  • When I finished the study and I compared the tool results

  • to the traditional diagnostic test and the validation test,

  • I was shocked.

  • It was far more astonishing than I had ever anticipated.

  • But before I tell you what the tool revealed,

  • I would like to tell you about a specific patient I followed,

  • a young girl.

  • She had cystic fibrosis,

  • a genetic disease that made her lungs susceptible to bacterial infections.

  • This girl wasn't a part of the clinical trial.

  • I followed her because I knew from her medical record

  • that she had never had an infection before.

  • Once a month, this girl went to the hospital

  • to cough up a sputum sample that she spit in a cup.

  • This sample was transferred for bacterial analysis

  • at the central laboratory

  • so the doctors could act quickly if they discovered an infection.

  • And it allowed me to test my device on her samples as well.

  • The first two months I measured on her samples, there was nothing.

  • But the third month,

  • I discovered some bacterial chatter in her sample.

  • The bacteria were coordinating to damage her lung tissue.

  • But the traditional diagnostics showed no bacteria at all.

  • I measured again the next month,

  • and I could see that the bacterial conversations became even more aggressive.

  • Still, the traditional diagnostics showed nothing.

  • My study ended, but a half a year later, I followed up on her status

  • to see if the bacteria only I knew about had disappeared

  • without medical intervention.

  • They hadn't.

  • But the girl was now diagnosed with a severe infection

  • of deadly bacteria.

  • It was the very same bacteria my tool discovered earlier.

  • And despite aggressive antibiotic treatment,

  • it was impossible to eradicate the infection.

  • Doctors deemed that she would not survive her 20s.

  • When I measured on this girl's samples,

  • my tool was still in the initial stage.

  • I didn't even know if my method worked at all,

  • therefore I had an agreement with the doctors

  • not to tell them what my tool revealed

  • in order not to compromise their treatment.

  • So when I saw these results that weren't even validated,

  • I didn't dare to tell

  • because treating a patient without an actual infection

  • also has negative consequences for the patient.

  • But now we know better,

  • and there are many young boys and girls that still can be saved

  • because, unfortunately, this scenario happens very often.

  • Patients get infected,

  • the bacteria somehow don't show on the traditional diagnostic test,

  • and suddenly, the infection breaks out in the patient with severe symptoms.

  • And at that point, it's already too late.

  • The surprising result of the 62 patients I followed

  • was that my device caught bacterial conversations

  • in more than half of the patient samples

  • that were diagnosed as negative by traditional methods.

  • In other words, more than half of these patients went home thinking

  • they were free from infection,

  • although they actually carried dangerous bacteria.

  • Inside these wrongly diagnosed patients,

  • bacteria were coordinating a synchronized attack.

  • They were whispering to each other.

  • What I call \"whispering bacteria\"

  • are bacteria that traditional methods cannot diagnose.

  • So far, it's only the translation tool that can catch those whispers.

  • I believe that the time frame in which bacteria are still whispering

  • is a window of opportunity for targeted treatment.

  • If the girl had been treated during this window of opportunity,

  • it might have been possible to kill the bacteria

  • in their initial stage,

  • before the infection got out of hand.

  • What I experienced with this young girl made me decide to do everything I can

  • to push this technology into the hospital.

  • Together with doctors,

  • I'm already working on implementing this tool in clinics

  • to diagnose early infections.

  • Although it's still not known how doctors should treat patients

  • during the whispering phase,

  • this tool can help doctors keep a closer eye on patients in risk.

  • It could help them confirm if a treatment had worked or not,

  • and it could help answer simple questions:

  • Is the patient infected?

  • And what are the bacteria up to?

  • Bacteria talk,

  • they make secret plans,

  • and they send confidential information to each other.

  • But not only can we catch them whispering,

  • we can all learn their secret language

  • and become ourselves bacterial whisperers.

  • And, as bacteria would say,

  • \"3-oxo-C12-aniline.\"

  • (Laughter)

  • (Applause)

  • Thank you.

Translator: Leslie Gauthier Reviewer: Camille Martínez

字幕と単語

動画の操作 ここで「動画」の調整と「字幕」の表示を設定することができます

B2 中上級

TED】ファティマ AlZahra'a Alatraktchi.病気を早く発見するために、細菌の秘密の言葉を話しましょう (病気を早く発見するために、細菌の秘密の言葉を話しましょう|ファティマ AlZahra'a Alatraktchi) (【TED】Fatima AlZahra'a Alatraktchi: To detect diseases earlier, let's speak bacteria's secret language (To detect diseases earlier, let

  • 56 3
    林宜悉 に公開 2021 年 01 月 14 日
動画の中の単語