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- [Ryan] All right, it
gives me great pleasure

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to pass the microphone
over to my colleague,

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Dr. Ethel Gordon, who will now
introduce our guest speaker,

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Dr. Bonnie Bassler.

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- Good evening, Dr. Bassler,

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Salem State community, and guest.

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My name is Dr. Ethel
Gordon and I'm a member

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of the Biology Faculty here

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as well as a member of the
Darwin Festival Committee.

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It is my great pleasure today

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to introduce Dr. Bonnie Bassler.

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Dr. Bassler received
her BS in biochemistry

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at the University of California in Davis

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and her PhD in biochemistry
from John Hopkins University.

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Dr. Bassler has received numerous
awards, honorary degrees,

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and positions over her
distinguished career,

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including being an officer

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for the American Society for Microbiology,

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the National Science Foundation,

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and the American Association
for the Advancement of Science.

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She is also a member of the
National Academy of Science

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and the National Academies of Medicine.

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Dr. Bassler is currently the

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Squibb Professor of Molecular Biology

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and the Chair of the Department
of Molecular Biology,

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and a Howard Hughes Medical Institute

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Investigator at Princeton.

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She will describe her
research on a unique form

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of cell communication among bacteria.

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Her talk is entitled,

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"Tiny Conspiracies: Cell-to-Cell
Communication in Bacteria."

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Her talk today is sponsored
by the Biology Department

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in the College of Arts and Sciences.

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I am honored to present
Dr. Bonnie Bassler.

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- Oh, thank you, for the nice introduction

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and for the invitation.

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I'm super delighted to get to be here,

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even in 2D, I think that it's wonderful

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that we can share
science and keep thinking

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about the future during these trying times

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and I really appreciate
that everybody came.

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I appreciate that you
invited me to give this talk

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and I'm happy just to get
the chance to share some

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of the science that my gang
is doing here at Princeton.

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So with that start, let
me share my screen, and...

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Let's see.

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(softly mumbling)

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And, I think that should be good.

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So I know that that
everybody in the audience,

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that we all have very diverse backgrounds.

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And so I'll start with an introduction

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and then I'll get into the work.

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And so my lab always
works on thinking about

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how bacteria get any bang
for their buck, right?

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So they're these itty bitty puny organisms

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and so what we always wonder is

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how can they do all the powerful
things they do on earth?

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And so that's what I'm
gonna tell you about

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and what I hope that
you get from this talk,

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I'll just give you the punchline,

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is that bacteria communicate.

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They work in groups to carry out tasks

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that they couldn't accomplish
as they acted as individuals

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because they're too small individually.

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And that if we could learn
enough about this communication,

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maybe we could disrupt it to
make new kinds of medicines.

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So that's where we're going tonight.

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And let me start by just
making sure we're all

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on the same page with a
cartoon of a bacterial cell.

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So this picture looks like a pretty,

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is a schematic of a
pretty generic bacterium,

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like an E. coli that might
be living in your gut.

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And the bacteria all
kind of have this form,

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which is they are single-cell
microscopic organisms.

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And so they are so small that you have

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to have a microscope to see them.

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You can't see them with your eye.

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They are Earth's first living organisms.

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They've been on the earth
for a few billion years.

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And when you look at 'em,
they seem very simple.

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They're all covered by a membrane,

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which keeps the outside world
out and the inside world in,

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and then inside of them,
they have one piece of DNA,

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so the chromosome that has all
of their genetic information.

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And so they're very
stripped-down organisms.

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They have a couple thousand genes.

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So not very many bits of information

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to give them their physical forms

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and the traits that they carry out.

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And if you just look at
bacteria under a microscope,

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what you'll see is that
they consume nutrients

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from their environment, they
grow to twice their size,

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they double all of the
components inside of the cell,

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and then they cut themselves in half.

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And so they divide in two,
two cells become four,

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four becomes eight.

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So a pretty mundane existence, seemingly.

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And so scientists have known
about bacteria for 500 years.

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And for about 470 of those years,

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it's always been thought
that when bacteria divide,

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they have no knowledge, if you will,

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of their sister cell, right?

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So they just act as individuals

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and each bacterium does its own thing.

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And I wanna try to convince
you that that can't be true

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because they couldn't be as powerful

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as they are if that were the case.

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And so to get us there,
let me make sure that I,

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that we all get a little flavor of

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how our own bodies interact with bacteria.

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So this next slide will give
you a sort of perspective

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about how I see the world.

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So this is my idea, this
cartoon that I made,

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of a human being and
all the little circles

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in it are supposed to be
some of the human cells.

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So we know there's a few trillion cells

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that it takes to make up a human being,

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that's how many cells are in us,

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that allow us to be alive and
give us our physical form.

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So at any moment in your life,

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there are 10 times more bacterial cells

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than human cells in you or on you.

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So by that metric, you're 10% human.

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The other 90% of you is bacterial.

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But of course, we now know

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it's not all about the cells, right?

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There's this magical molecule, the DNA.

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And so I've remade my human being

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out of the As, Ts, Gs, and Cs

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that make up the famous
double helix of the DNA.

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And so of course we have the human genome.

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So we know about how many genes
there are in a human being.

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So there are about 25,000 genes.

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So that's how many bits of information

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it takes to make you be alive,

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do all the things you do and
give you your physical form.

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And so, again, talking
about bacteria here,

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at any moment in your life,

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there are 100 times more
bacterial genes in you or on you.

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So these bacteria provide
all of these genes

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and these genes are necessary
to make life happen.

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So every higher organism lives
in a consortium with bacteria

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that provide it genes and
proteins and functions

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that higher organism genomes don't have.

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So there is no life on earth
without these bacteria.

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And these are called the microbiome

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because they provide us
these necessary products.

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So you can pick whichever metric you like.

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At best, you're 10% human.

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Really, you're only 1% human,

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because the other 99% of those genes

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come from your bacteria.

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So hopefully that makes
you interested in bacteria.

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And now if I sort of zoom out again,

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I don't wanna be Pollyanna here, right?

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What we're now learning
about microbiome is

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that there are all these
beneficial bacteria

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that live innocent on us

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and give us these traits that we need.

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But there's also all kinds
of harmful bacteria as well.

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So this slide shows just some pictures

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taken under a microscope
of famous bacteria.

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And on the top line,

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you're looking at some
notorious pathogens.

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So there's all these
bacteria in the environment

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that have no business
being in us or on us.

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And if they do get a toehold
on us or an animal or a plant,

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they can make us sick or
they can kill us, right?

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So there are all these pathogens
and as I've just told you,

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there's this magical microbiome
of all these good bacteria

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that normally do live with us.

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And they do all of these functions,

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like help us digest our food

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when we eat plant food or salad,

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they educate our immune defense
to keep these bad guys out,

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they provide us micronutrients,
and that list is expanding,

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'cause we're only learning
about the microbiome now.

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So these are facts,
bacteria can be harmful

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or they can be beneficial.

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So my lab gets that and we understand

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at some level that that's the case.

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but the question that's
always at the heart of studies

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is not that bacteria can be
bad or can be beneficial.

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The question we wanna ask is no matter

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which of these kinds of
bacteria you're thinking about,

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how can they do any of these things?

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These bacteria are so small.

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How can they kill us on the
one hand and give us our lives,

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give us life itself on the other hand?

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And so that's what we
study and what I wanna try

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to show you is the way they do
these bad and good things is

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by working in groups and communicating.

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So to get to that idea,

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I wanna tell you where
this field came from,

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the idea that the
bacteria could communicate

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and orchestrate collective behaviors

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because it came out of a really
sort of curious observation

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that had to do with this squid.

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So what you're looking at is
the Hawaiian bobtail squid

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and it's in a tank, and this
squid is about this big.

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It's about an inch big, full grown.

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And this animal is nocturnal.

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So it sleeps during the day

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and at night it comes out to hunt.

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And so what we've done
is we've put this squid

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in this tank and the light is turned on.

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So the squid thinks that it's daytime.

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So it looks kind of
spastic and uncoordinated,

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that's because it's never
supposed to be out during the day.

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If it were out in the day, somebody,

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a predator would see it and eat it.

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So now what we've done is
given the squid sediments.

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The light is on, the
squid thinks it's day,

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and so the squid does this behavior.

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It buries itself in the sediments

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in order to avoid predators.

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So what it's trying to
do is to be invisible

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to predators that might see it.

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And so what you can see
is that she's thorough.

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You get eaten by a predator once.

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So she's gonna cover herself
up with those tentacles

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and when she's done, she'll
retract those tentacles

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and then she's in bed and
ready to sleep for the day.

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So if I showed you this tank,

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of course you wouldn't know
there's a squid in there.

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There's actually about
10 of them in there.

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Okay, so this is a fantastic strategy

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for this squid to escape from
predators during the day.

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The problem for the squid
is it can't stay there 24/7,

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it's gotta come out at
to hunt, it needs to eat.

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And so this is where bacteria

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and bacteria communicating come in.

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It turns out that this squid lives

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in a beautiful one-to-one symbiosis

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with a marine bacterium
that's called Vibrio fischeri.

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And this bacterium makes,
has the special property

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that it makes bioluminescence.

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So it makes light like
fireflies make light,

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except the light is blue,

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which is what travels far in the water.

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So now what you're
looking at is the squid,

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it's been turned on its back,

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and I hope you can see
these two glowing lobes.

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And so the way that this works is

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that the squid under the mantle

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or the body of the squid has
a specialized light organ

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that houses this Vibrio fischeri bacteria.

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And the bacteria are in there at something

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like 10 to the 12th of cells per millets,

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like toothpaste, thick with bacteria.

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And so they're in there and
the bacteria make light.

252
00:11:14,700 --> 00:11:16,390
They make bioluminescence.

253
00:11:16,390 --> 00:11:19,880
And so what the squid does when
it emerges at night to hunt,

254
00:11:19,880 --> 00:11:22,710
when it comes out of the sediments
and it's swimming around,

255
00:11:22,710 --> 00:11:26,185
it just lives in this sort
of shallow, knee-deep water.

256
00:11:26,185 --> 00:11:29,350
And so the problem at night
is that on bright nights

257
00:11:29,350 --> 00:11:31,410
where there's lots of stars or moonlight,

258
00:11:31,410 --> 00:11:34,160
that light would shine down on the squid,

259
00:11:34,160 --> 00:11:35,680
penetrate the depth of the water,

260
00:11:35,680 --> 00:11:37,686
and the squid would make a shadow.

261
00:11:37,686 --> 00:11:41,511
So what the squid does is
it has detectors on its back

262
00:11:41,511 --> 00:11:43,430
that it senses how much starlight

263
00:11:43,430 --> 00:11:45,170
or moonlight is hitting its back.

264
00:11:45,170 --> 00:11:47,350
And then it opens and closes a shutter

265
00:11:47,350 --> 00:11:50,510
under this light organ
that allows the same amount

266
00:11:50,510 --> 00:11:53,980
of light made by the bacteria
to come out of the bottom

267
00:11:53,980 --> 00:11:55,800
that's hitting the back of the squid

268
00:11:55,800 --> 00:11:57,310
from the moon or the starlight.

269
00:11:57,310 --> 00:11:59,040
So it counter illuminates itself

270
00:11:59,040 --> 00:12:01,130
by matching the starlight and moonlight

271
00:12:01,130 --> 00:12:03,397
with the light made by the bacteria.

272
00:12:03,397 --> 00:12:04,530
And so in this way,

273
00:12:04,530 --> 00:12:08,000
the squid sort of has this cloaking device

274
00:12:08,000 --> 00:12:09,170
that makes it invisible.

275
00:12:09,170 --> 00:12:10,853
Because it doesn't make a shadow,

276
00:12:11,920 --> 00:12:15,270
predators can't calculate
its trajectory and eat it.

277
00:12:15,270 --> 00:12:16,220
And so now you get it,

278
00:12:16,220 --> 00:12:18,220
the squid has these two great behaviors.

279
00:12:18,220 --> 00:12:20,280
It's asleep in the sand during the day,

280
00:12:20,280 --> 00:12:24,744
it's got this special property
of being invisible at night,

281
00:12:24,744 --> 00:12:27,040
which the bacteria give it

282
00:12:27,040 --> 00:12:29,950
and so that helps the squid survive.

283
00:12:29,950 --> 00:12:31,810
But the question that is in my lab is

284
00:12:31,810 --> 00:12:33,490
how do these bacteria do that?

285
00:12:33,490 --> 00:12:36,208
So it turns out that they only make light

286
00:12:36,208 --> 00:12:38,150
when they're at high cell density,

287
00:12:38,150 --> 00:12:41,150
which is in that squid light organ.

288
00:12:41,150 --> 00:12:44,440
And so the way the bacteria understand

289
00:12:44,440 --> 00:12:47,650
that situation is
because they communicate.

290
00:12:47,650 --> 00:12:49,300
And so now what I wanna do is change

291
00:12:49,300 --> 00:12:51,210
to the bacterial perspective.

292
00:12:51,210 --> 00:12:53,020
Okay, so this cartoon is supposed

293
00:12:53,020 --> 00:12:56,540
to be my Vibrio fischeri bacterial cell.

294
00:12:56,540 --> 00:13:00,280
So at low cell density, when
there's few bacteria around,

295
00:13:00,280 --> 00:13:02,350
it does no good for the
bacteria to make light

296
00:13:02,350 --> 00:13:03,860
'cause individually they can't make

297
00:13:03,860 --> 00:13:05,790
enough light to be perceivable.

298
00:13:05,790 --> 00:13:08,100
So under low cell density conditions,

299
00:13:08,100 --> 00:13:11,050
Vibrio fischeri does not
make light, it's dark.

300
00:13:11,050 --> 00:13:13,610
But what it does do is that it makes

301
00:13:13,610 --> 00:13:16,810
and secretes small
molecules that I have drawn

302
00:13:16,810 --> 00:13:18,510
as these red triangles,

303
00:13:18,510 --> 00:13:20,270
that you can think of like hormones,

304
00:13:20,270 --> 00:13:22,610
and we call them autoinducers.

305
00:13:22,610 --> 00:13:24,500
And so what happens is
that low cell density,

306
00:13:24,500 --> 00:13:26,630
the bacteria make the autoinducers,

307
00:13:26,630 --> 00:13:29,480
but the world is big
and bacteria are small.

308
00:13:29,480 --> 00:13:31,890
So the autoinducers diffuse away,

309
00:13:31,890 --> 00:13:33,690
the bacteria can't detect them,

310
00:13:33,690 --> 00:13:37,098
that says, "You're
alone, don't make light."

311
00:13:37,098 --> 00:13:40,251
But then as the bacteria grow and divide,

312
00:13:40,251 --> 00:13:42,670
since all of the bacteria in the community

313
00:13:42,670 --> 00:13:44,660
are making a share of these hormone,

314
00:13:44,660 --> 00:13:46,860
these autoinducer-like molecules,

315
00:13:46,860 --> 00:13:49,620
the concentration of
these autoinducers outside

316
00:13:49,620 --> 00:13:53,570
of the cells increases in
proportion to cell number.

317
00:13:53,570 --> 00:13:56,940
And when the molecules hit a
particular threshold amount,

318
00:13:56,940 --> 00:13:59,810
the bacteria detect it and they infer

319
00:13:59,810 --> 00:14:02,310
from that detection moment

320
00:14:02,310 --> 00:14:04,150
that they must have neighbors around.

321
00:14:04,150 --> 00:14:06,648
And so in unison, all of the bacteria

322
00:14:06,648 --> 00:14:09,680
turn on bioluminescence together.

323
00:14:09,680 --> 00:14:12,330
And so of course, when they're
in the squid light organ,

324
00:14:12,330 --> 00:14:14,500
there's a lot of them there,
they're all making light,

325
00:14:14,500 --> 00:14:17,930
and the squid uses the
light to protect itself.

326
00:14:17,930 --> 00:14:20,070
So in fact, these bacteria have no idea

327
00:14:20,070 --> 00:14:22,090
how many other cells are around them.

328
00:14:22,090 --> 00:14:23,710
They're measuring the concentration

329
00:14:23,710 --> 00:14:25,810
of this chemical, this autoinducer,

330
00:14:25,810 --> 00:14:28,458
and they use it as a
proxy for cell number.

331
00:14:28,458 --> 00:14:31,040
And we actually know
we're right about this

332
00:14:31,040 --> 00:14:34,846
because if we spin the cells
out of the test tube, say,

333
00:14:34,846 --> 00:14:37,920
in a centrifuge and we
collect up the liquid,

334
00:14:37,920 --> 00:14:39,250
the cell-free supernatants,

335
00:14:39,250 --> 00:14:42,800
we can squirt that
liquid on to dilute cells

336
00:14:42,800 --> 00:14:44,090
and they will turn on light.

337
00:14:44,090 --> 00:14:45,790
So they don't know how
many cells are around.

338
00:14:45,790 --> 00:14:47,400
They just believe if, you will,

339
00:14:47,400 --> 00:14:49,170
that if there's a lot of that chemical,

340
00:14:49,170 --> 00:14:51,730
it means that they're
at high cell density.

341
00:14:51,730 --> 00:14:54,270
So this means these bacteria
are talking to each other

342
00:14:54,270 --> 00:14:57,420
with a chemical word and
it lets them know times

343
00:14:57,420 --> 00:14:59,680
when they're alone and times
when they're in community

344
00:14:59,680 --> 00:15:01,100
so they can do something different

345
00:15:01,100 --> 00:15:03,357
under those two scenarios.

346
00:15:03,357 --> 00:15:06,140
So that's how it works and
we wanted to bring the tools

347
00:15:06,140 --> 00:15:08,620
of molecular biology and
genetics to the table

348
00:15:08,620 --> 00:15:11,480
to actually understand
the components involved.

349
00:15:11,480 --> 00:15:13,500
Okay, and so now I'll tell
you what was discovered.

350
00:15:13,500 --> 00:15:16,649
So again, this is supposed
to be a representation

351
00:15:16,649 --> 00:15:18,763
of the Vibrio fischeri cell.

352
00:15:18,763 --> 00:15:21,643
So what was found was
that there is a protein

353
00:15:21,643 --> 00:15:26,150
in the Vibrio fischeri cells
that makes that autoinducer.

354
00:15:26,150 --> 00:15:29,320
So there's an enzyme
that makes the chemical

355
00:15:29,320 --> 00:15:32,480
and that molecule
diffuses out of the cells,

356
00:15:32,480 --> 00:15:35,470
and as I just told you,
the more cells there are,

357
00:15:35,470 --> 00:15:37,640
the more of that molecule there is.

358
00:15:37,640 --> 00:15:39,430
And then there's a partner protein,

359
00:15:39,430 --> 00:15:41,580
a receptor protein that sits

360
00:15:41,580 --> 00:15:43,680
on the Vibrio fischeri membrane.

361
00:15:43,680 --> 00:15:46,280
And so this protein has part of itself

362
00:15:46,280 --> 00:15:47,980
on the outside of the cell

363
00:15:47,980 --> 00:15:50,290
and part of itself on
the inside of the cell.

364
00:15:50,290 --> 00:15:52,370
So it connects the outside world

365
00:15:52,370 --> 00:15:55,030
to the inside world, the bacterial cell.

366
00:15:55,030 --> 00:15:58,279
And so this receptor
protein has a slot in it.

367
00:15:58,279 --> 00:16:00,930
It's basically like puzzle pieces

368
00:16:00,930 --> 00:16:05,930
that allows the autoinducer
molecule to lock into that slot,

369
00:16:06,070 --> 00:16:08,910
which occurs when there's a
lot of that molecule around.

370
00:16:08,910 --> 00:16:10,520
And so at high cell density,

371
00:16:10,520 --> 00:16:13,830
this autoinducer will
increase in concentration.

372
00:16:13,830 --> 00:16:17,110
It'll bump into that receptor,
and when that happens,

373
00:16:17,110 --> 00:16:19,930
information gets sent inside the cells

374
00:16:19,930 --> 00:16:22,097
to tell the cells to turn on the genes

375
00:16:22,097 --> 00:16:25,700
that make the enzymes
that make bioluminescence.

376
00:16:25,700 --> 00:16:27,760
And so it's a really simple circuit.

377
00:16:27,760 --> 00:16:29,400
The more bacteria there are,

378
00:16:29,400 --> 00:16:32,900
the more of this molecule is
at a critical threshold amount

379
00:16:32,900 --> 00:16:34,710
which has to do with cell number,

380
00:16:34,710 --> 00:16:38,584
all of the bacteria
turn on light together.

381
00:16:38,584 --> 00:16:40,907
And so now you understand how that works

382
00:16:40,907 --> 00:16:43,910
and these receptors are
a lot like the receptors

383
00:16:43,910 --> 00:16:45,816
on the surfaces of human cells

384
00:16:45,816 --> 00:16:48,890
that detect hormones and other molecules.

385
00:16:48,890 --> 00:16:51,770
So, you've probably heard
about this kind of thing.

386
00:16:51,770 --> 00:16:55,080
Okay, so that's how Vibrio
fischeri communicates

387
00:16:55,080 --> 00:16:57,527
and turns on bioluminescence, and--

388
00:17:12,150 --> 00:17:14,610
Into the fray and at
last we have thousands

389
00:17:14,610 --> 00:17:16,590
and thousands of examples

390
00:17:16,590 --> 00:17:19,430
of bacteria that have similar circuits.

391
00:17:19,430 --> 00:17:22,060
And so what I mean by
that is it's the norm

392
00:17:22,060 --> 00:17:24,020
in the bacterial world for the bacteria

393
00:17:24,020 --> 00:17:26,570
to have a protein that
makes an autoinducer,

394
00:17:26,570 --> 00:17:29,770
a signal molecule, there's
always a partner receptor,

395
00:17:29,770 --> 00:17:33,217
and when those two things lock
together at high cell density

396
00:17:33,217 --> 00:17:36,372
information gets sent into
the cells to tell bacteria

397
00:17:36,372 --> 00:17:40,544
to turn on hundreds and
hundreds of group behaviors

398
00:17:40,544 --> 00:17:42,770
so that they can carry out tasks

399
00:17:42,770 --> 00:17:44,840
when they're acting together

400
00:17:44,840 --> 00:17:47,764
that wouldn't be productive
when they act alone.

401
00:17:47,764 --> 00:17:50,620
And so now we have a fancy name for this.

402
00:17:50,620 --> 00:17:52,950
We call this quorum sensing.

403
00:17:52,950 --> 00:17:55,570
The bacteria vote with
these chemical votes.

404
00:17:55,570 --> 00:17:57,740
The vote gets counted and in unison,

405
00:17:57,740 --> 00:17:59,000
they sort of go along with this

406
00:17:59,000 --> 00:18:01,330
democratic decision-making processing

407
00:18:01,330 --> 00:18:04,323
and they carry out these
collective behaviors.

408
00:18:05,280 --> 00:18:07,810
So quorum sensing is widespread

409
00:18:07,810 --> 00:18:09,490
across the bacterial kingdom.

410
00:18:09,490 --> 00:18:13,990
It's how bacteria get any
bang for their buck, we think.

411
00:18:13,990 --> 00:18:15,690
Okay, so that's how it works

412
00:18:15,690 --> 00:18:18,310
and we know a lot about
the molecules as well.

413
00:18:18,310 --> 00:18:21,880
So in my cartoons, of course,
I'm showing them as triangles,

414
00:18:21,880 --> 00:18:23,460
but they are actually chemicals.

415
00:18:23,460 --> 00:18:26,480
And so here's the structure,
this is the chemical,

416
00:18:26,480 --> 00:18:28,823
the Vibrio fischeri, the
bioluminescent bacterium

417
00:18:28,823 --> 00:18:32,000
that I told you about, uses as its word.

418
00:18:32,000 --> 00:18:33,970
And so we and lots of
other scientists started

419
00:18:33,970 --> 00:18:36,030
to purify more of these molecules.

420
00:18:36,030 --> 00:18:37,830
And so what I've done on this slide

421
00:18:37,830 --> 00:18:40,290
is simply put a smattering of different

422
00:18:40,290 --> 00:18:43,480
quorum sensing bacteria and the molecule

423
00:18:43,480 --> 00:18:47,463
that each one uses as
its word, if you will.

424
00:18:47,463 --> 00:18:49,280
And what I hope you can see is

425
00:18:49,280 --> 00:18:51,620
that all of the molecules are related.

426
00:18:51,620 --> 00:18:53,960
So this left-hand part is identical

427
00:18:53,960 --> 00:18:56,620
in every single species of bacteria.

428
00:18:56,620 --> 00:18:58,170
But these right-hand tails,

429
00:18:58,170 --> 00:19:00,760
these are just carbons, long carbon tails.

430
00:19:00,760 --> 00:19:03,400
These right-hand tails
are a little bit different

431
00:19:03,400 --> 00:19:05,350
in every single species.

432
00:19:05,350 --> 00:19:08,810
And what these little differences do is

433
00:19:08,810 --> 00:19:12,990
to confer exquisite species specificities

434
00:19:12,990 --> 00:19:14,850
to each of these languages.

435
00:19:14,850 --> 00:19:16,490
So what I mean by that is

436
00:19:16,490 --> 00:19:18,820
that these receptors really do work

437
00:19:18,820 --> 00:19:21,970
like puzzle pieces or locks
and keys with one another.

438
00:19:21,970 --> 00:19:25,370
So for example, if we take
the Vibrio fischeri molecule

439
00:19:25,370 --> 00:19:28,450
and put it on Pseudomonas,
nothing happens.

440
00:19:28,450 --> 00:19:31,160
And likewise, Vibrio
fischeri is impervious

441
00:19:31,160 --> 00:19:33,523
to the Pseudomonas molecule.

442
00:19:34,470 --> 00:19:37,290
So these molecules allow intra,

443
00:19:37,290 --> 00:19:40,280
or within the species, communication.

444
00:19:40,280 --> 00:19:43,130
These are secret, private conversations

445
00:19:43,130 --> 00:19:45,883
that bacteria have with their kin.

446
00:19:47,320 --> 00:19:50,020
So that's the quorum
sensing and how it works.

447
00:19:50,020 --> 00:19:52,610
And we also know a lot
about these behaviors

448
00:19:52,610 --> 00:19:54,410
the bacteria are controlling

449
00:19:54,410 --> 00:19:57,600
with quorum sensing across
the bacterial domain.

450
00:19:57,600 --> 00:19:59,330
So of course, this story started

451
00:19:59,330 --> 00:20:02,580
with bioluminescence in
this marine bacterium,

452
00:20:02,580 --> 00:20:06,630
but as scientists began to
study lots of other bacteria,

453
00:20:06,630 --> 00:20:09,710
many, many clinically or globally-relevant

454
00:20:09,710 --> 00:20:12,330
pathogens started to be studied.

455
00:20:12,330 --> 00:20:15,250
And sure enough, the ability of pathogens

456
00:20:15,250 --> 00:20:19,500
to make biofilms, which is
how bacteria sit on surfaces,

457
00:20:19,500 --> 00:20:21,610
like on your skin, on your intestine,

458
00:20:21,610 --> 00:20:24,730
how they sit and adhere to surfaces,

459
00:20:24,730 --> 00:20:28,850
and make communities, that is
controlled by quorum sensing.

460
00:20:28,850 --> 00:20:30,490
And likewise, the production

461
00:20:30,490 --> 00:20:32,830
and the secretion of virulence factors,

462
00:20:32,830 --> 00:20:34,960
the toxins that make us sick,

463
00:20:34,960 --> 00:20:37,393
are also under quorum sensing control.

464
00:20:38,360 --> 00:20:40,140
So the idea is, for example,

465
00:20:40,140 --> 00:20:42,720
I'll just tell you the idea
for Pseudomonas aeruginosa,

466
00:20:42,720 --> 00:20:46,330
Pseudomonas aeruginosa is
a opportunistic pathogen.

467
00:20:46,330 --> 00:20:49,180
It lives in the dirt, you and
I encounter it all the time.

468
00:20:49,180 --> 00:20:52,070
It's harmless, unless
you're immune-compromised,

469
00:20:52,070 --> 00:20:53,090
you're a burn victim,

470
00:20:53,090 --> 00:20:56,000
or you have the disease cystic fibrosis.

471
00:20:56,000 --> 00:20:58,340
So you probably know
people who have the disease

472
00:20:58,340 --> 00:21:00,720
called CF have a genetic mutation

473
00:21:00,720 --> 00:21:04,531
and so they can't clear
their lungs of bacteria.

474
00:21:04,531 --> 00:21:07,970
Typically when a person
is in his or her teens,

475
00:21:07,970 --> 00:21:10,130
for reasons that we don't understand,

476
00:21:10,130 --> 00:21:12,340
they become permanently colonized

477
00:21:12,340 --> 00:21:15,670
with Pseudomonas aeruginosa
and that's what kills people

478
00:21:15,670 --> 00:21:18,400
who have the disease cystic fibrosis.

479
00:21:18,400 --> 00:21:21,880
And the reason is because
Pseudomonas has quorum sensing.

480
00:21:21,880 --> 00:21:24,350
So what it does is it gets into the host

481
00:21:24,350 --> 00:21:26,090
or an immune-compromised person,

482
00:21:26,090 --> 00:21:28,053
a burn victim, people in hospitals,

483
00:21:29,250 --> 00:21:31,410
it's sort running
rampant in hospitals now,

484
00:21:31,410 --> 00:21:34,560
it gets into a host, and it's tiny.

485
00:21:34,560 --> 00:21:36,570
The worst thing that
Pseudomonas wants to do

486
00:21:36,570 --> 00:21:39,320
is be spewing out its virulence factors.

487
00:21:39,320 --> 00:21:41,570
It won't do any good if a couple bacteria

488
00:21:41,570 --> 00:21:43,580
dribble out some of these toxins.

489
00:21:43,580 --> 00:21:46,600
And moreover, your immune system evolve

490
00:21:46,600 --> 00:21:49,470
to see invading pathogens, hunt them down,

491
00:21:49,470 --> 00:21:50,450
and get rid of them.

492
00:21:50,450 --> 00:21:55,350
So these compounds are red
flags to the immune system.

493
00:21:55,350 --> 00:21:58,330
So the better idea for
Pseudomonas and other pathogens is

494
00:21:58,330 --> 00:22:00,720
to wait and to count yourself

495
00:22:00,720 --> 00:22:03,610
and recognize when you have
the right number of cells

496
00:22:03,610 --> 00:22:08,200
if all the bacteria make this
onslaught of toxins together,

497
00:22:08,200 --> 00:22:09,970
they'll be able to affect the host

498
00:22:09,970 --> 00:22:12,760
and overcome the immune system.

499
00:22:12,760 --> 00:22:15,470
So now what we get is that quorum sensing

500
00:22:15,470 --> 00:22:19,590
frequently controls virulence in pathogens

501
00:22:19,590 --> 00:22:21,430
because it's a great strategy

502
00:22:21,430 --> 00:22:23,410
from the bacterium's point of view

503
00:22:23,410 --> 00:22:25,793
for making a successful infection.

504
00:22:27,070 --> 00:22:29,430
Okay, so that's quorum sensing

505
00:22:29,430 --> 00:22:32,300
and when we got sort of
that far in our studies,

506
00:22:32,300 --> 00:22:34,250
we started to understand or have this idea

507
00:22:34,250 --> 00:22:36,170
that bacteria could communicate.

508
00:22:36,170 --> 00:22:37,830
But then we started to wonder

509
00:22:37,830 --> 00:22:40,580
how this could really
work in the real world.

510
00:22:40,580 --> 00:22:42,500
So I've told you about this wonderful,

511
00:22:42,500 --> 00:22:45,750
pristine lifestyle that
Vibrio fischeri lives,

512
00:22:45,750 --> 00:22:48,810
in this one-to-one
symbiosis with this squid.

513
00:22:48,810 --> 00:22:50,630
But that's not the norm.

514
00:22:50,630 --> 00:22:54,160
Usually bacteria lived in
mixed-species communities

515
00:22:54,160 --> 00:22:57,050
with hundreds or
thousands of other species

516
00:22:57,050 --> 00:22:58,500
of bacteria present.

517
00:22:58,500 --> 00:23:00,470
And so that's supposed to be depicted

518
00:23:00,470 --> 00:23:02,270
or illustrated on this slide.

519
00:23:02,270 --> 00:23:04,210
This is a picture of human skin.

520
00:23:04,210 --> 00:23:07,230
This is your elbow skin
taken under the microscope

521
00:23:07,230 --> 00:23:09,010
and what you can see is it's covered

522
00:23:09,010 --> 00:23:11,370
with bacteria, that's a biofilm,

523
00:23:11,370 --> 00:23:13,330
and every one of these different shapes

524
00:23:13,330 --> 00:23:17,189
and sizes of bacteria
is a different species.

525
00:23:17,189 --> 00:23:19,180
And so what we started to wonder is

526
00:23:19,180 --> 00:23:21,740
if these bacteria are really
out there chitchatting

527
00:23:21,740 --> 00:23:25,610
and these languages are
so species-specific,

528
00:23:25,610 --> 00:23:28,640
how can bacteria count
when they find themselves

529
00:23:28,640 --> 00:23:30,820
in these mixed-species communities?

530
00:23:30,820 --> 00:23:33,197
And so we wanted to explore that question.

531
00:23:33,197 --> 00:23:36,810
And so the strategy we
decided to take is analogous

532
00:23:36,810 --> 00:23:38,670
to the one I just told you.

533
00:23:38,670 --> 00:23:42,630
We knew about a bacterium
named Vibrio harveyi.

534
00:23:42,630 --> 00:23:44,420
This is a marine bacterium,

535
00:23:44,420 --> 00:23:46,580
it's related to Vibrio fischeri.

536
00:23:46,580 --> 00:23:48,600
It makes bioluminescence,

537
00:23:48,600 --> 00:23:50,720
but it lives free-living in the ocean.

538
00:23:50,720 --> 00:23:53,560
And we knew that it lives in consortia

539
00:23:53,560 --> 00:23:57,130
with all kinds of other
species of marine bacteria.

540
00:23:57,130 --> 00:23:58,940
So we wondered if we could figure out

541
00:23:58,940 --> 00:24:01,310
how Vibrio harveyi does quorum sensing,

542
00:24:01,310 --> 00:24:03,670
given that it sort of
lives in the Wild West.

543
00:24:03,670 --> 00:24:05,460
We thought that quorum sensing would be

544
00:24:05,460 --> 00:24:08,225
more interesting in this bacterium.

545
00:24:08,225 --> 00:24:11,770
And so the reason that I'm
showing you this slide is

546
00:24:11,770 --> 00:24:13,870
to actually show you bioluminescence

547
00:24:13,870 --> 00:24:17,120
and give you an idea of how
we do these experiments.

548
00:24:17,120 --> 00:24:19,369
So what you're looking
at is a flask and some,

549
00:24:19,369 --> 00:24:22,501
there's some test tubes
and some Petri plates

550
00:24:22,501 --> 00:24:25,107
with Vibrio harveyi on them.

551
00:24:25,107 --> 00:24:27,250
And these cells are at high cell density,

552
00:24:27,250 --> 00:24:28,740
they're doing quorum sensing

553
00:24:28,740 --> 00:24:30,590
and they're making bioluminescence.

554
00:24:30,590 --> 00:24:32,090
So to take this picture,

555
00:24:32,090 --> 00:24:34,170
all we did was turn the
lights off in the room

556
00:24:34,170 --> 00:24:35,490
and we actually took the picture

557
00:24:35,490 --> 00:24:37,270
with the light that the cells are making.

558
00:24:37,270 --> 00:24:38,963
So we are not doing anything to them.

559
00:24:38,963 --> 00:24:41,130
They're simply making this light

560
00:24:41,130 --> 00:24:43,110
because quorum sensing is happening.

561
00:24:43,110 --> 00:24:45,470
And so what, we're geneticists in my lab,

562
00:24:45,470 --> 00:24:47,750
and so what we thought is
that we could make mutants,

563
00:24:47,750 --> 00:24:51,200
just randomly mutagenize the
Vibrio harveyi chromosome,

564
00:24:51,200 --> 00:24:53,130
put 'em on Petri plates like this,

565
00:24:53,130 --> 00:24:55,420
and look for bacteria
that didn't make light

566
00:24:55,420 --> 00:24:58,750
when they should or that did
make light when they shouldn't.

567
00:24:58,750 --> 00:25:01,640
And by finding those kinds
of defective mutants,

568
00:25:01,640 --> 00:25:03,970
we could hunt down what
genes were involved

569
00:25:03,970 --> 00:25:07,425
in controlling this trait and
learn about quorum sensing.

570
00:25:07,425 --> 00:25:09,760
So that's what we did for Vibrio fischeri

571
00:25:09,760 --> 00:25:12,001
and now we did it for Vibrio harveyi.

572
00:25:12,001 --> 00:25:14,400
And so what we found when we studied,

573
00:25:14,400 --> 00:25:16,710
when we got the genes
and proteins involved

574
00:25:16,710 --> 00:25:19,330
in the Vibrio harveyi
system is that sure enough,

575
00:25:19,330 --> 00:25:21,720
we found quorum sensing, we knew we would.

576
00:25:21,720 --> 00:25:23,210
We found that there was an enzyme

577
00:25:23,210 --> 00:25:25,620
that makes one of these
autoinducer molecules,

578
00:25:25,620 --> 00:25:28,860
I actually showed it to
you on a couple slides ago,

579
00:25:28,860 --> 00:25:31,710
and there was a partner
receptor that responded to it.

580
00:25:31,710 --> 00:25:34,065
So that was something we understood.

581
00:25:34,065 --> 00:25:36,780
But to our surprise, what we found was

582
00:25:36,780 --> 00:25:39,260
that there was another autoinducer system.

583
00:25:39,260 --> 00:25:41,290
So we found a second enzyme

584
00:25:41,290 --> 00:25:43,830
that made a different autoinducer molecule

585
00:25:43,830 --> 00:25:48,350
and that autoinducer also
had its own partner receptor.

586
00:25:48,350 --> 00:25:50,080
And so somehow the information

587
00:25:50,080 --> 00:25:54,360
from both of these systems
gets transduced into the cells

588
00:25:54,360 --> 00:25:56,880
to tell the bacteria at high cell density

589
00:25:56,880 --> 00:25:59,570
to turn on bioluminescence and hundreds

590
00:25:59,570 --> 00:26:01,850
and hundreds of other group behaviors.

591
00:26:01,850 --> 00:26:04,560
But we're measuring
bioluminescence in our assay.

592
00:26:04,560 --> 00:26:05,680
So at high cell density,

593
00:26:05,680 --> 00:26:08,310
these molecules accumulate
and the bacteria switch

594
00:26:08,310 --> 00:26:10,560
into quorum sensing mode
and they do all kinds

595
00:26:10,560 --> 00:26:12,690
of social behaviors.

596
00:26:12,690 --> 00:26:14,762
So the circuit seemed to be doubled

597
00:26:14,762 --> 00:26:17,780
and so what we next
wondered is what's the point

598
00:26:17,780 --> 00:26:20,940
of having these two different
quorum sensing molecules.

599
00:26:20,940 --> 00:26:22,880
We thought if these two molecules

600
00:26:22,880 --> 00:26:26,069
don't encode different
pieces of information,

601
00:26:26,069 --> 00:26:29,750
having two molecules is
not better than having one.

602
00:26:29,750 --> 00:26:31,550
And so we wondered what was the point

603
00:26:31,550 --> 00:26:33,537
of this second molecule?

604
00:26:33,537 --> 00:26:35,260
And so we did a lot of experiments

605
00:26:35,260 --> 00:26:36,809
and mostly what we did was we showed

606
00:26:36,809 --> 00:26:40,740
that this molecule
seemed to be broadly made

607
00:26:40,740 --> 00:26:42,620
across the bacterial domain.

608
00:26:42,620 --> 00:26:44,610
So this molecule was specific,

609
00:26:44,610 --> 00:26:46,900
but every bacterium we tested seemed

610
00:26:46,900 --> 00:26:49,520
to have this second activity.

611
00:26:49,520 --> 00:26:51,570
So we purified and
figured out the structure

612
00:26:51,570 --> 00:26:54,289
of that molecule from
many different bacteria

613
00:26:54,289 --> 00:26:58,710
and what we found out was that
it was exactly one molecule.

614
00:26:58,710 --> 00:27:01,080
So it's this molecule, it's five carbons

615
00:27:01,080 --> 00:27:03,340
and it's decorated with a lot of oxygens.

616
00:27:03,340 --> 00:27:06,490
We named it Autoinducer
2 for the second molecule

617
00:27:06,490 --> 00:27:07,850
that we discovered.

618
00:27:07,850 --> 00:27:10,160
And what is important about this is

619
00:27:10,160 --> 00:27:12,700
unlike in the first set of
molecules that I showed you

620
00:27:12,700 --> 00:27:14,969
that are each a little bit
different than the other,

621
00:27:14,969 --> 00:27:17,690
in this case, every bacterium makes

622
00:27:17,690 --> 00:27:20,180
exactly the same molecule.

623
00:27:20,180 --> 00:27:23,570
So this molecule is not species-specific.

624
00:27:23,570 --> 00:27:26,860
We think this is a universal
communication molecule,

625
00:27:26,860 --> 00:27:30,460
sort of the bacterial trade
language that allows bacteria

626
00:27:30,460 --> 00:27:34,401
to communicate across species boundaries.

627
00:27:34,401 --> 00:27:37,810
So now what we think is
that bacteria are bilingual,

628
00:27:37,810 --> 00:27:39,200
or they're multilingual.

629
00:27:39,200 --> 00:27:40,677
They have a molecule that says,

630
00:27:40,677 --> 00:27:43,597
"This is my kin, this is my relative."

631
00:27:43,597 --> 00:27:46,457
And then they use the
second molecule to say,

632
00:27:46,457 --> 00:27:49,041
"This is other, this is non-kin."

633
00:27:49,041 --> 00:27:51,550
And so the computation that we now know

634
00:27:51,550 --> 00:27:53,700
bacteria do is the following.

635
00:27:53,700 --> 00:27:55,767
Bacteria out there in the
world and they're deciding,

636
00:27:55,767 --> 00:27:57,717
"Should I go it alone or
should I act in a group,

637
00:27:57,717 --> 00:27:59,900
"should I go it alone or
should I act in a group?"

638
00:27:59,900 --> 00:28:01,610
And the way they decide that is

639
00:28:01,610 --> 00:28:04,655
by measuring these
quorum sensing molecules.

640
00:28:04,655 --> 00:28:06,547
So the first thing they do is they say,

641
00:28:06,547 --> 00:28:08,090
"Am I alone or in a group?"

642
00:28:08,090 --> 00:28:11,670
And they start to turn on
and off different genes

643
00:28:11,670 --> 00:28:13,940
depending on what they find out.

644
00:28:13,940 --> 00:28:16,830
But then the more sophisticated
computation they do is

645
00:28:16,830 --> 00:28:19,600
that they measure the ratio
of these two molecules.

646
00:28:19,600 --> 00:28:21,317
And what we think they're
doing, they're asking,

647
00:28:21,317 --> 00:28:25,070
"Is it mostly me and my
kin or is it the enemy?"

648
00:28:25,070 --> 00:28:27,700
So they're asking who
are they surrounded by

649
00:28:27,700 --> 00:28:30,427
and then they change their
behavior based on whether they

650
00:28:30,427 --> 00:28:33,150
and their family members
are in the majority

651
00:28:33,150 --> 00:28:35,420
or whether their foes are in the majority.

652
00:28:35,420 --> 00:28:39,520
So they say self or other,
and then they change.

653
00:28:39,520 --> 00:28:41,510
When they're with themselves,

654
00:28:41,510 --> 00:28:44,970
they turn on all kinds
of beneficial behavior

655
00:28:44,970 --> 00:28:46,870
and when they're surrounded by the enemy,

656
00:28:46,870 --> 00:28:49,280
they get kind of defensive
and they try to hide

657
00:28:49,280 --> 00:28:50,917
and they try to kill the other guy.

658
00:28:50,917 --> 00:28:52,920
And so they tailor these programs

659
00:28:52,920 --> 00:28:56,137
based on the blend of the molecules.

660
00:28:56,137 --> 00:28:58,550
So that's what we think quorum sensing is.

661
00:28:58,550 --> 00:29:01,070
It allows bacteria to
count and it allows them

662
00:29:01,070 --> 00:29:03,850
to distinguish self from other.

663
00:29:03,850 --> 00:29:06,053
And so once we got this
far in our studies,

664
00:29:06,053 --> 00:29:08,480
we think that bacteria are social,

665
00:29:08,480 --> 00:29:09,900
but we also thought that we could

666
00:29:09,900 --> 00:29:12,840
do something applied or something useful,

667
00:29:12,840 --> 00:29:16,340
having learned through these
basic discovery studies

668
00:29:16,340 --> 00:29:17,760
about quorum sensing.

669
00:29:17,760 --> 00:29:19,660
And what I mean by that is we knew

670
00:29:19,660 --> 00:29:22,290
that these molecules control virulence,

671
00:29:22,290 --> 00:29:24,670
and biofilm information, and pathogenicity

672
00:29:24,670 --> 00:29:26,600
in all kinds of bacteria.

673
00:29:26,600 --> 00:29:30,229
And so we thought perhaps we
could shut down quorum sensing

674
00:29:30,229 --> 00:29:33,100
with synthetic strategies and those could

675
00:29:33,100 --> 00:29:35,730
perhaps make new kinds of medicines.

676
00:29:35,730 --> 00:29:38,330
Because of course, you know
that we have a global problem

677
00:29:38,330 --> 00:29:40,730
with antibiotic resistance in bacteria

678
00:29:40,730 --> 00:29:43,610
and we need new kinds of strategies

679
00:29:43,610 --> 00:29:45,860
to combat harmful bacteria.

680
00:29:45,860 --> 00:29:48,321
So we wanted to give that a whirl.

681
00:29:48,321 --> 00:29:51,229
And so there's sort of two strategies.

682
00:29:51,229 --> 00:29:53,350
One is to interfere with the

683
00:29:53,350 --> 00:29:56,150
intra species communication language.

684
00:29:56,150 --> 00:29:59,410
So if one wants a narrow
spectrum therapeutic,

685
00:29:59,410 --> 00:30:03,190
you want a molecule for a
Pseudomonas or for cholera,

686
00:30:03,190 --> 00:30:07,110
what one would do is try to think about

687
00:30:07,110 --> 00:30:09,290
those very specific molecules

688
00:30:09,290 --> 00:30:11,473
and see if one could interfere.

689
00:30:11,473 --> 00:30:14,990
Other times, broad spectrum
therapeutics are appropriate.

690
00:30:14,990 --> 00:30:16,160
Like if you go to the hospital

691
00:30:16,160 --> 00:30:17,880
and your doctor doesn't
know what you have,

692
00:30:17,880 --> 00:30:21,400
you get treated with a
broad spectrum antimicrobial

693
00:30:21,400 --> 00:30:24,810
to try to cover all the
bases while your doctor tries

694
00:30:24,810 --> 00:30:26,070
to figure out what's wrong with you,

695
00:30:26,070 --> 00:30:27,950
what infection you have.

696
00:30:27,950 --> 00:30:30,400
So in that case, maybe
you'd like to interfere

697
00:30:30,400 --> 00:30:32,980
with this second quorum sensing system.

698
00:30:32,980 --> 00:30:34,710
So we're doing both and the logic

699
00:30:34,710 --> 00:30:36,970
for the experiments are exactly the same.

700
00:30:36,970 --> 00:30:38,620
So I thought I would
just tell you about some

701
00:30:38,620 --> 00:30:41,920
of our newest results that
have to do with this molecule,

702
00:30:41,920 --> 00:30:44,897
the intra species communication molecule.

703
00:30:44,897 --> 00:30:47,490
So we're doing all of these experiments

704
00:30:47,490 --> 00:30:50,860
in Pseudomonas aeruginosa,
and so that's the pathogen

705
00:30:50,860 --> 00:30:53,410
that I told you about a couple slides ago.

706
00:30:53,410 --> 00:30:55,720
So I told you this is
this opportunistic bug

707
00:30:55,720 --> 00:30:59,390
that lives in the dirt,
but it's very harmful

708
00:30:59,390 --> 00:31:01,600
for immune-compromised
people, burn victims,

709
00:31:01,600 --> 00:31:03,090
people with cystic fibrosis.

710
00:31:03,090 --> 00:31:05,073
And also I alluded to this a minute ago,

711
00:31:05,073 --> 00:31:07,250
it's one of these bacteria

712
00:31:07,250 --> 00:31:09,820
that's sort of invading hospitals.

713
00:31:09,820 --> 00:31:11,878
And so, you go in to
get your gallbladder out

714
00:31:11,878 --> 00:31:14,073
and you get these Pseudomonas infections

715
00:31:14,073 --> 00:31:15,910
that are actually more harmful than

716
00:31:15,910 --> 00:31:17,380
what you went to the hospital for.

717
00:31:17,380 --> 00:31:18,880
So it's a real problem in

718
00:31:18,880 --> 00:31:20,720
what's called nosocomial infections,

719
00:31:20,720 --> 00:31:24,180
infections that are
gotten at the hospital.

720
00:31:24,180 --> 00:31:27,970
And the reason is because
Pseudomonas has quorum sensing

721
00:31:27,970 --> 00:31:30,690
and it controls biofilms and virulence

722
00:31:30,690 --> 00:31:33,190
with its quorum sensing systems.

723
00:31:33,190 --> 00:31:36,000
So this bacterium is
really, really sticky.

724
00:31:36,000 --> 00:31:39,610
It uses quorum sensing to
sit down on human surfaces,

725
00:31:39,610 --> 00:31:42,460
but also hospital
surfaces, abiotic surfaces,

726
00:31:42,460 --> 00:31:44,150
and it makes these biofilms,

727
00:31:44,150 --> 00:31:47,380
these communities of
bacteria adhere to surfaces.

728
00:31:47,380 --> 00:31:50,220
So that's happening in all
the hospital equipment,

729
00:31:50,220 --> 00:31:51,860
but also inside the human body.

730
00:31:51,860 --> 00:31:53,660
It's the first step in infection,

731
00:31:53,660 --> 00:31:56,623
bacteria adhere to a surface,
they make a community,

732
00:31:56,623 --> 00:32:00,740
they grow to high cell number,
and then as I told you,

733
00:32:00,740 --> 00:32:03,790
then Pseudomonas turns on its toxins

734
00:32:03,790 --> 00:32:06,270
and it's got like 40 or 50 released

735
00:32:06,270 --> 00:32:10,070
virulence factors poisons that
actually make the human sick.

736
00:32:10,070 --> 00:32:12,910
So both of these things are
quorum sensing-controlled.

737
00:32:12,910 --> 00:32:17,113
So we thought this was a good
candidate to try this new idea

738
00:32:17,113 --> 00:32:19,730
that maybe interfering
with quorum sensing,

739
00:32:19,730 --> 00:32:22,422
make bacteria so they can't
talk, or they can't hear,

740
00:32:22,422 --> 00:32:25,283
and maybe those could be
new kinds of therapeutics.

741
00:32:26,200 --> 00:32:27,600
So here's what we did.

742
00:32:27,600 --> 00:32:31,320
We knew what the real autoinducer was.

743
00:32:31,320 --> 00:32:34,130
So here's a picture of a
molecule I've showed you.

744
00:32:34,130 --> 00:32:36,640
This is the Pseudomonas natural signal

745
00:32:36,640 --> 00:32:38,460
that it uses to communicate.

746
00:32:38,460 --> 00:32:39,940
So we knew that structure.

747
00:32:39,940 --> 00:32:43,320
And so what we did was we
made a synthetic molecule

748
00:32:43,320 --> 00:32:45,030
that is an inhibitor.

749
00:32:45,030 --> 00:32:47,290
So what we did was we
took the known structure

750
00:32:47,290 --> 00:32:49,840
and we made a molecule
that looks kind of like it.

751
00:32:49,840 --> 00:32:52,710
So what you can see is that
here's the real molecule,

752
00:32:52,710 --> 00:32:55,610
the left hand part of our molecule looks

753
00:32:55,610 --> 00:32:57,930
almost just like this molecule,

754
00:32:57,930 --> 00:33:01,130
except there's a sulfur
here instead of an oxygen.

755
00:33:01,130 --> 00:33:02,923
And that's because our bodies have,

756
00:33:02,923 --> 00:33:07,150
human bodies have enzymes
that cut these rings.

757
00:33:07,150 --> 00:33:09,270
If you put a sulfur there,
that doesn't happen.

758
00:33:09,270 --> 00:33:10,780
So this is a stable end,

759
00:33:10,780 --> 00:33:12,557
but it really has the same shape

760
00:33:12,557 --> 00:33:14,614
as the real Pseudomonas molecule.

761
00:33:14,614 --> 00:33:17,640
And then what we did on the
right-hand end of the molecule

762
00:33:17,640 --> 00:33:19,510
is we put a big chemical group,

763
00:33:19,510 --> 00:33:22,098
it's sort of like a bump
on the end of the molecule.

764
00:33:22,098 --> 00:33:24,720
So now remember I told
you these molecules,

765
00:33:24,720 --> 00:33:26,710
the natural molecules, they sort of slot

766
00:33:26,710 --> 00:33:29,860
into their partner receptors
like locks and keys.

767
00:33:29,860 --> 00:33:32,410
And so our synthetic molecule slots

768
00:33:32,410 --> 00:33:34,500
into the Pseudomonas receptor,

769
00:33:34,500 --> 00:33:37,840
but because of this big bump,
it just sticks in there.

770
00:33:37,840 --> 00:33:40,950
It sort of jams the
receptor, it sticks there,

771
00:33:40,950 --> 00:33:44,030
and then the real molecule can't sneak in.

772
00:33:44,030 --> 00:33:47,450
So this is called an
inhibitor or an antagonist.

773
00:33:47,450 --> 00:33:51,340
So it blocks reception
of the real molecule.

774
00:33:51,340 --> 00:33:53,110
Okay, so that's the molecule we made

775
00:33:53,110 --> 00:33:56,310
and now I wanna prove to
you that perhaps this notion

776
00:33:56,310 --> 00:33:59,980
of blocking quorum
sensing could be useful.

777
00:33:59,980 --> 00:34:01,350
So you remember that I told you

778
00:34:01,350 --> 00:34:05,010
the first thing Pseudomonas
has to do is to make a biofilm.

779
00:34:05,010 --> 00:34:07,980
So we have an assay in
the lab in Petri plates

780
00:34:07,980 --> 00:34:10,700
that allow us to monitor Pseudomonas

781
00:34:10,700 --> 00:34:13,980
swarming over the surface in a biofilm.

782
00:34:13,980 --> 00:34:16,050
So what you're looking at is exactly that.

783
00:34:16,050 --> 00:34:18,750
This is a Petri plate and what we did was

784
00:34:18,750 --> 00:34:21,450
we've just put a little
drop of Pseudomonas

785
00:34:21,450 --> 00:34:23,750
right at the middle of this Petri plate.

786
00:34:23,750 --> 00:34:25,400
And then if we wait overnight,

787
00:34:25,400 --> 00:34:27,797
what you can see is the
Pseudomonas swarms out

788
00:34:27,797 --> 00:34:30,270
and it makes this beautiful pattern.

789
00:34:30,270 --> 00:34:32,367
That's biofilm formation.

790
00:34:32,367 --> 00:34:35,070
If we make the same Petri plate,

791
00:34:35,070 --> 00:34:38,700
but into it, we put
our inhibitor molecule,

792
00:34:38,700 --> 00:34:41,600
and then we put that drop of
Pseudomonas and we wait a day,

793
00:34:41,600 --> 00:34:44,630
what you can see is that
Pseudomonas can't swarm.

794
00:34:44,630 --> 00:34:46,300
So that was the first good result.

795
00:34:46,300 --> 00:34:48,510
It showed that our
inhibitors seemed to block

796
00:34:48,510 --> 00:34:51,270
that first step of
swarming over the surface.

797
00:34:51,270 --> 00:34:53,900
So we thought we were cooking
with gas at that point

798
00:34:53,900 --> 00:34:55,340
and so we wanted to test whether

799
00:34:55,340 --> 00:34:58,370
or not our inhibitor
could shut down virulence.

800
00:34:58,370 --> 00:35:00,954
And so here's the last
experiment that I'll show you.

801
00:35:00,954 --> 00:35:04,700
We have an animal assay
for Pseudomonas infection.

802
00:35:04,700 --> 00:35:06,594
So Pseudomonas is a pathogen

803
00:35:06,594 --> 00:35:11,292
and we can measure whether the
animals are alive over time.

804
00:35:11,292 --> 00:35:15,160
And so, of course, if we
don't infect the animal,

805
00:35:15,160 --> 00:35:18,672
a day later, all the
animal animals are alive.

806
00:35:18,672 --> 00:35:23,260
If we add Pseudomonas or infect
the animal with Pseudomonas,

807
00:35:23,260 --> 00:35:25,632
the pathogen, what you
can see is a day later,

808
00:35:25,632 --> 00:35:28,300
almost all of the animals have died.

809
00:35:28,300 --> 00:35:30,530
Okay, so that shows you it's a pathogen.

810
00:35:30,530 --> 00:35:32,400
So now, if we do this experiment

811
00:35:32,400 --> 00:35:34,102
where we infect the
animal with Pseudomonas,

812
00:35:34,102 --> 00:35:36,980
but we give our inhibitor molecule,

813
00:35:36,980 --> 00:35:40,450
what you can see is that
all of the animals live.

814
00:35:40,450 --> 00:35:43,532
So this shows you that
indeed, in this model system,

815
00:35:43,532 --> 00:35:48,532
in shutting down quorum sensing
in fact stops virulence.

816
00:35:48,604 --> 00:35:51,120
So this is not a medicine yet.

817
00:35:51,120 --> 00:35:53,180
This is what's called a lead molecule.

818
00:35:53,180 --> 00:35:55,360
It's not particularly potent yet.

819
00:35:55,360 --> 00:35:57,040
We have to build in potency.

820
00:35:57,040 --> 00:35:59,510
We have not tested whether it's safe.

821
00:35:59,510 --> 00:36:01,440
This molecule has to go
where we want it to go.

822
00:36:01,440 --> 00:36:03,440
It can't just go to your
liver and get excreted.

823
00:36:03,440 --> 00:36:07,260
So all of that medicinal
chemistry remains to be done.

824
00:36:07,260 --> 00:36:08,530
But we didn't wanna do all of that

825
00:36:08,530 --> 00:36:10,280
if this idea couldn't work at all.

826
00:36:10,280 --> 00:36:12,660
So this is sort of our proof
of principle experiment

827
00:36:12,660 --> 00:36:15,040
that is inspiring us, or encouraging us,

828
00:36:15,040 --> 00:36:17,240
I should say, to actually work on this

829
00:36:17,240 --> 00:36:19,110
and other molecules to try to see

830
00:36:19,110 --> 00:36:21,304
if we can make applications

831
00:36:21,304 --> 00:36:24,048
by interfering with quorum sensing.

832
00:36:24,048 --> 00:36:28,000
So that's the story that I
wanted to tell you tonight.

833
00:36:28,000 --> 00:36:30,860
And let me finish up by
giving you a little summary

834
00:36:30,860 --> 00:36:32,520
of what I've already said.

835
00:36:32,520 --> 00:36:34,088
I hope what you think is

836
00:36:34,088 --> 00:36:35,720
that bacteria can talk to each other.

837
00:36:35,720 --> 00:36:38,533
They use chemicals as their words.

838
00:36:39,496 --> 00:36:42,780
We think that what quorum sensing does is

839
00:36:42,780 --> 00:36:45,796
it allows bacteria to be multicellular.

840
00:36:45,796 --> 00:36:49,310
And so of course, we
all came from bacteria.

841
00:36:49,310 --> 00:36:52,280
We evolved from bacteria,
they're Earth's first organisms.

842
00:36:52,280 --> 00:36:54,120
And so we think that they invented,

843
00:36:54,120 --> 00:36:55,960
if you will, multicellularity.

844
00:36:55,960 --> 00:36:59,010
And so by studying how
groups of cells work together

845
00:36:59,010 --> 00:37:01,330
and use chemical communication

846
00:37:01,330 --> 00:37:02,610
to coordinate their behaviors,

847
00:37:02,610 --> 00:37:04,780
we think that beyond
learning about bacteria,

848
00:37:04,780 --> 00:37:06,370
we will learn about the evolution

849
00:37:06,370 --> 00:37:09,470
of multicellularity in
higher organisms as well.

850
00:37:09,470 --> 00:37:11,680
We think the principles are embedded

851
00:37:11,680 --> 00:37:16,612
in these ancient, primitive,
bacterial organisms.

852
00:37:16,612 --> 00:37:20,500
I showed you that bacteria
can distinguish self

853
00:37:20,500 --> 00:37:22,670
from other with those two molecules.

854
00:37:22,670 --> 00:37:24,700
It turns out I actually simplified that.

855
00:37:24,700 --> 00:37:26,640
There are multiple,
there are a lot of words

856
00:37:26,640 --> 00:37:27,610
in this languages.

857
00:37:27,610 --> 00:37:29,900
There's a molecule that says, "Me."

858
00:37:29,900 --> 00:37:30,837
There's a molecule that says,

859
00:37:30,837 --> 00:37:33,220
"You're my cousin but you're not my twin."

860
00:37:33,220 --> 00:37:34,053
There's a molecule that says,

861
00:37:34,053 --> 00:37:36,310
"You're the enemy," the
one that I showed you.

862
00:37:36,310 --> 00:37:38,770
And there's a molecule that
says, "You are the host."

863
00:37:38,770 --> 00:37:39,810
So we're starting to think

864
00:37:39,810 --> 00:37:41,830
that this lexicon is pretty diverse

865
00:37:41,830 --> 00:37:43,860
and that there's all kinds of information

866
00:37:43,860 --> 00:37:45,570
embedded in these molecules

867
00:37:45,570 --> 00:37:48,760
and the bacteria use
those blends of molecules

868
00:37:48,760 --> 00:37:50,940
to understand how many there are,

869
00:37:50,940 --> 00:37:53,490
and actually who their neighbors

870
00:37:53,490 --> 00:37:55,780
and their hosts are as well.

871
00:37:55,780 --> 00:37:58,556
So there's at least four
molecules that we know now.

872
00:37:58,556 --> 00:38:01,265
And then of course,
there's this applied part

873
00:38:01,265 --> 00:38:04,910
that I finished my talk with
that perhaps we could take

874
00:38:04,910 --> 00:38:07,240
what we've learned and develop strategies

875
00:38:07,240 --> 00:38:10,300
to impede quorum sensing
in harmful bacteria.

876
00:38:10,300 --> 00:38:11,470
But on the flip side of that,

877
00:38:11,470 --> 00:38:14,210
remember I told you that what
scientists are also learning

878
00:38:14,210 --> 00:38:17,438
about is this magical,
fantastic microbiome.

879
00:38:17,438 --> 00:38:19,590
And so we know those bacteria are

880
00:38:19,590 --> 00:38:21,610
chatting like crazy as well.

881
00:38:21,610 --> 00:38:23,550
And so maybe the better strategy is

882
00:38:23,550 --> 00:38:26,340
instead of fighting against
these harmful pathogens,

883
00:38:26,340 --> 00:38:28,480
maybe we could improve quorum sensing,

884
00:38:28,480 --> 00:38:30,740
make pro quorum sensing molecules

885
00:38:30,740 --> 00:38:34,660
to make our natural
microflora talk or communicate

886
00:38:34,660 --> 00:38:36,880
and carry out group behaviors even better.

887
00:38:36,880 --> 00:38:39,970
We know that your microbiome
works hand-in-hand

888
00:38:39,970 --> 00:38:43,700
with your immune system to
keep invading bacteria out.

889
00:38:43,700 --> 00:38:46,690
And so maybe the real way
forward in medicine is

890
00:38:46,690 --> 00:38:50,420
to actually try to
enhance that conversation.

891
00:38:50,420 --> 00:38:53,060
So we're making both
anti-quorum sensing molecules

892
00:38:53,060 --> 00:38:54,860
and pro-quorum sensing molecules

893
00:38:54,860 --> 00:38:56,860
'cause we don't know
which way will work better

894
00:38:56,860 --> 00:38:58,434
if either of those.

895
00:38:58,434 --> 00:39:00,720
And then the final
thing to do is to finish

896
00:39:00,720 --> 00:39:04,370
with a confession that we
didn't think any of this up.

897
00:39:04,370 --> 00:39:05,880
And so now that we know these things,

898
00:39:05,880 --> 00:39:09,380
lots of scientists have
sort of gone out into nature

899
00:39:09,380 --> 00:39:11,850
and they're mining these
bacterial communities

900
00:39:11,850 --> 00:39:14,020
and sure enough, the bacteria have

901
00:39:14,020 --> 00:39:15,970
a four-billion-year headstart on us.

902
00:39:15,970 --> 00:39:19,700
They make themselves, they're
duking it out in nature

903
00:39:19,700 --> 00:39:21,310
in these competitive environments.

904
00:39:21,310 --> 00:39:22,696
And so now scientists have found

905
00:39:22,696 --> 00:39:25,400
that bacteria eat each
other's autoinducers,

906
00:39:25,400 --> 00:39:27,670
they make antagonists, they make enzymes,

907
00:39:27,670 --> 00:39:29,820
they clip them in half, they free ride,

908
00:39:29,820 --> 00:39:31,370
they cheat, they eavesdrop,

909
00:39:31,370 --> 00:39:34,680
they do all kinds of miscommunicating

910
00:39:34,680 --> 00:39:36,550
and sending of misinformation.

911
00:39:36,550 --> 00:39:38,670
And so we know these strategies exist

912
00:39:38,670 --> 00:39:40,636
and of course the ones that we can find

913
00:39:40,636 --> 00:39:42,890
in natural bacteria communities

914
00:39:42,890 --> 00:39:44,740
have evolved over billions of years.

915
00:39:44,740 --> 00:39:46,790
So those are probably the best,

916
00:39:46,790 --> 00:39:49,970
not some molecule that I'm
gonna make in my own lab.

917
00:39:49,970 --> 00:39:51,470
And so now what we'd like to do is

918
00:39:51,470 --> 00:39:53,490
to use nature as our inspiration

919
00:39:53,490 --> 00:39:55,200
and go out and get these molecules

920
00:39:55,200 --> 00:39:58,830
and bring those into the
lab as the starting blocks

921
00:39:58,830 --> 00:40:01,690
or the building blocks
that we should tinker with

922
00:40:01,690 --> 00:40:05,250
in our efforts to make
these kinds of application.

923
00:40:05,250 --> 00:40:08,320
So anyway, there's a lot
of energy in the field now,

924
00:40:08,320 --> 00:40:12,140
trying to use natural pro
and anti-quorum sensing

925
00:40:13,274 --> 00:40:18,274
molecules as fodder for
making applications.

926
00:40:18,520 --> 00:40:21,410
And so that's my talk, and
let me show you my lab.

927
00:40:21,410 --> 00:40:24,210
This is obviously a
picture taken before COVID.

928
00:40:24,210 --> 00:40:27,120
This is my lab and our
families out on my porch.

929
00:40:27,120 --> 00:40:29,710
I think somebody must
have been graduating.

930
00:40:29,710 --> 00:40:32,847
And so of course I get the
good fortune to give the talk.

931
00:40:32,847 --> 00:40:36,330
But I do wanna say that
these are the people

932
00:40:36,330 --> 00:40:38,035
that made all of those discoveries.

933
00:40:38,035 --> 00:40:41,270
It's an absolute thrill and
a pleasure to work with them.

934
00:40:41,270 --> 00:40:43,300
They are boundlessly energetic

935
00:40:43,300 --> 00:40:46,869
and they are filled with
curiosity and ingenious

936
00:40:46,869 --> 00:40:49,130
and they are the ones that have changed

937
00:40:49,130 --> 00:40:53,010
the world's perception
about how bacteria function

938
00:40:53,010 --> 00:40:55,460
and their profound influence in nature.

939
00:40:55,460 --> 00:40:59,690
And I guess since a lot of
people are undergraduates

940
00:40:59,690 --> 00:41:03,960
in biology in the audience,
I hope, if you like this,

941
00:41:03,960 --> 00:41:07,585
or you hear something cool
about a biological system

942
00:41:07,585 --> 00:41:09,830
or you read it in the newspaper,

943
00:41:09,830 --> 00:41:11,877
I just wanna remind you that the people

944
00:41:11,877 --> 00:41:15,420
who are making those
discoveries are your age

945
00:41:15,420 --> 00:41:18,010
or only a couple years away.

946
00:41:18,010 --> 00:41:21,900
It's always students and graduate students

947
00:41:21,900 --> 00:41:24,160
and so if you like this, you
should just stick with it.

948
00:41:24,160 --> 00:41:26,410
Even if it's challenging or seems hard,

949
00:41:26,410 --> 00:41:27,976
challenging, hard is fun,

950
00:41:27,976 --> 00:41:31,660
but these are the people
that had these ideas

951
00:41:31,660 --> 00:41:33,900
that nobody else in the
world had before them.

952
00:41:33,900 --> 00:41:37,230
And I would just say to the
undergrads, that could be you.

953
00:41:37,230 --> 00:41:39,400
So I do hope that you'll stick with it

954
00:41:39,400 --> 00:41:42,520
because being a biologist or a scientist,

955
00:41:42,520 --> 00:41:45,120
in my view, is the
greatest life in the world.

956
00:41:45,120 --> 00:41:46,500
Anyway, so let me stop there

957
00:41:46,500 --> 00:41:49,160
and then if there's questions,
I think I take them now

958
00:41:49,160 --> 00:41:50,620
and before I forget to do this,

959
00:41:50,620 --> 00:41:52,970
I wanna just thank
everyone for inviting me

960
00:41:52,970 --> 00:41:54,370
and thank you for listening.

961
00:41:57,370 --> 00:41:59,886
- Thank you, Dr. Bassler.

962
00:41:59,886 --> 00:42:02,090
Everybody, my colleague, Dr. Paul Kelly,

963
00:42:02,090 --> 00:42:03,810
and I will moderate the questions.

964
00:42:03,810 --> 00:42:04,833
Over to you, Paul.

965
00:42:11,080 --> 00:42:12,540
- [Paul] Thank you, Dr. Bassler.

966
00:42:12,540 --> 00:42:14,653
A few questions from the audience.

967
00:42:17,370 --> 00:42:20,503
In reference to a TED
Talk you did, apparently,

968
00:42:22,000 --> 00:42:25,620
have you ever modified
cells to make antibiotics?

969
00:42:25,620 --> 00:42:29,416
- Yeah, so, (feedback softly echoes)

970
00:42:29,416 --> 00:42:32,020
oh, it's sort of, oh,
that's better, echoing.

971
00:42:32,020 --> 00:42:35,160
Yeah, so hopefully this was
an update from that TED Talk,

972
00:42:35,160 --> 00:42:37,570
which was like 10 years ago.

973
00:42:37,570 --> 00:42:40,140
So the molecule, so during the TED Talk,

974
00:42:40,140 --> 00:42:42,430
we were dreaming about
that, and so the molecule

975
00:42:42,430 --> 00:42:44,920
that I just showed you
right now is the outcome,

976
00:42:44,920 --> 00:42:46,290
one of the outcomes of that dream.

977
00:42:46,290 --> 00:42:48,990
I showed you one but
we have several of them

978
00:42:48,990 --> 00:42:50,890
and they're not antibiotics yet--

979
00:42:50,890 --> 00:42:53,070
- I'm gonna get an echo
(feedback drowns out Bonnie)

980
00:42:53,070 --> 00:42:53,930
through speakers.
(crosstalk drowns out speaker)

981
00:42:53,930 --> 00:42:55,200
- Anyway, so it takes a long time

982
00:42:55,200 --> 00:42:58,070
to really make them safe and potent.

983
00:42:58,070 --> 00:43:00,850
But the molecule I just
showed you right now,

984
00:43:00,850 --> 00:43:02,943
that's sort of the update from that talk

985
00:43:02,943 --> 00:43:05,370
where we didn't have that at that point.

986
00:43:05,370 --> 00:43:08,190
So yeah, the answer is still in progress

987
00:43:08,190 --> 00:43:09,423
but getting much closer.

988
00:43:12,350 --> 00:43:15,150
- Thanks Dr. Bassler,
I'll ask another question

989
00:43:15,150 --> 00:43:18,920
from the audience and I'm
sort of paraphrasing it.

990
00:43:18,920 --> 00:43:22,110
How recent is the discovery
of quorum sensing?

991
00:43:22,110 --> 00:43:24,360
Did we know about it 50 years ago,

992
00:43:24,360 --> 00:43:26,370
30 years ago, 20 years ago?

993
00:43:26,370 --> 00:43:28,100
- Okay, so I actually know exactly that,

994
00:43:28,100 --> 00:43:29,263
the answer to this one.

995
00:43:30,821 --> 00:43:35,199
So the Vibrio fischeri
that it made a molecule,

996
00:43:35,199 --> 00:43:38,950
that was discovered by a dear
colleague, Woody Hastings.

997
00:43:38,950 --> 00:43:41,980
He's from Massachusetts,
he was at Harvard.

998
00:43:41,980 --> 00:43:43,720
He's unfortunately passed away.

999
00:43:43,720 --> 00:43:45,740
And so he and his student, Ken Nealson

1000
00:43:45,740 --> 00:43:49,510
discovered that Vibrio
fischeri did that trick.

1001
00:43:49,510 --> 00:43:51,913
That was in the early '70s.

1002
00:43:51,913 --> 00:43:54,890
And then Mike Silverman,
who was my post-doc boss,

1003
00:43:54,890 --> 00:43:59,367
and a graduate student, Joanne
Engebrecht, in 1984 and '85,

1004
00:44:00,630 --> 00:44:02,640
they discovered the first genes.

1005
00:44:02,640 --> 00:44:07,134
And then now it's now with
thousands of, in Vibrio fischeri,

1006
00:44:07,134 --> 00:44:09,280
and then I went to Mike's
lab to work on that,

1007
00:44:09,280 --> 00:44:10,550
and then now it's now.

1008
00:44:10,550 --> 00:44:12,530
So, we've sort of known,

1009
00:44:12,530 --> 00:44:16,463
we've known about Vibrio
fischeri since the '70s.

1010
00:44:18,030 --> 00:44:20,510
The first finding that other

1011
00:44:20,510 --> 00:44:23,103
bacteria did it was in the '90s.

1012
00:44:25,390 --> 00:44:27,400
- Great, Paul, do you have a question

1013
00:44:27,400 --> 00:44:29,363
or do you want me to ask another one?

1014
00:44:32,020 --> 00:44:34,510
- [Paul] Sure, are there
cooperative bacteria

1015
00:44:34,510 --> 00:44:36,920
that work across different species?

1016
00:44:36,920 --> 00:44:38,700
- Yeah, right, okay, so
that's a really good,

1017
00:44:38,700 --> 00:44:40,066
all of these are good questions.

1018
00:44:40,066 --> 00:44:43,578
So it's not just out
there fighting it out,

1019
00:44:43,578 --> 00:44:47,822
there's tens of millions
probably of bacterial species

1020
00:44:47,822 --> 00:44:50,340
and they all live in
these different niches.

1021
00:44:50,340 --> 00:44:52,040
And then sometimes, they're out there

1022
00:44:52,040 --> 00:44:53,470
really try to kill each other.

1023
00:44:53,470 --> 00:44:56,230
But other times they actually
have to work together,

1024
00:44:56,230 --> 00:44:59,590
like, I'm the librarian,
you're the car maker

1025
00:44:59,590 --> 00:45:00,700
or you're the grocer,

1026
00:45:00,700 --> 00:45:02,750
because otherwise they're
subsistence farmers.

1027
00:45:02,750 --> 00:45:06,780
And so we also have real
examples, like in your teeth.

1028
00:45:06,780 --> 00:45:08,640
You have a biofilm on your teeth

1029
00:45:08,640 --> 00:45:10,568
with 600 species of bacteria,

1030
00:45:10,568 --> 00:45:14,190
but only the first couple can
actually stick to your teeth.

1031
00:45:14,190 --> 00:45:16,430
But then the next ones give them a,

1032
00:45:16,430 --> 00:45:18,500
have an enzyme to give them
a product that they need.

1033
00:45:18,500 --> 00:45:20,340
So, right, it's very cooperative.

1034
00:45:20,340 --> 00:45:24,797
And so we know both competitive
and cooperative situations

1035
00:45:26,330 --> 00:45:28,360
where the bacteria, I
think this is the question,

1036
00:45:28,360 --> 00:45:29,193
I'm being long-winded,

1037
00:45:29,193 --> 00:45:31,070
where the bacteria use the autoinducers

1038
00:45:31,070 --> 00:45:33,510
to help each other do things together

1039
00:45:33,510 --> 00:45:35,810
or to prevent each other
from doing things together.

1040
00:45:35,810 --> 00:45:39,928
And again, these bacteria
have so many different niches,

1041
00:45:39,928 --> 00:45:43,150
the different variations and many more

1042
00:45:43,150 --> 00:45:46,370
that we don't know about
have clearly evolved.

1043
00:45:46,370 --> 00:45:48,113
So yeah, so they, yeah.

1044
00:45:50,140 --> 00:45:53,080
- Here's another one from
our audience, Dr. Bassler,

1045
00:45:53,080 --> 00:45:55,500
referring to that beautiful
star pattern you showed

1046
00:45:55,500 --> 00:45:57,990
in that red-colored Petri dish.

1047
00:45:57,990 --> 00:46:00,320
And the question is, have
you explored quorum sensing

1048
00:46:00,320 --> 00:46:02,660
in colony or pattern formation?

1049
00:46:02,660 --> 00:46:04,260
- In colony or what?

1050
00:46:04,260 --> 00:46:07,100
- Or pattern for formation?

1051
00:46:07,100 --> 00:46:08,670
- Oh, pattern, right, oh, yeah.

1052
00:46:08,670 --> 00:46:10,721
Okay, so that we're doing right now.

1053
00:46:10,721 --> 00:46:13,554
So we, meaning the gang in the lab,

1054
00:46:13,554 --> 00:46:15,889
I'm in my office, they're out there.

1055
00:46:15,889 --> 00:46:17,160
They better be out there.

1056
00:46:17,160 --> 00:46:21,573
Anyway, the gang in the lab,
we built new microscopes

1057
00:46:21,573 --> 00:46:24,640
that are capable of seeing individual,

1058
00:46:24,640 --> 00:46:26,560
and following with fluorescent markers,

1059
00:46:26,560 --> 00:46:29,400
individual cells within biofilms.

1060
00:46:29,400 --> 00:46:31,850
So the problem with
biofilms is they're opaque

1061
00:46:31,850 --> 00:46:33,390
and the cells are really dense in there.

1062
00:46:33,390 --> 00:46:37,300
And so these guys and girl,
ladies and men in my lab,

1063
00:46:37,300 --> 00:46:39,380
they built these new
microscopes so that we can see

1064
00:46:39,380 --> 00:46:42,260
and track biofilm formation
from a founder cell

1065
00:46:42,260 --> 00:46:47,073
all the way to the community
to do exactly that.

1066
00:46:47,073 --> 00:46:51,680
Which is to understand, is it
homogeneous, heterogeneous?

1067
00:46:51,680 --> 00:46:53,740
Where they have these
beautiful architectures.

1068
00:46:53,740 --> 00:46:55,760
And so it turns out that we are

1069
00:46:55,760 --> 00:46:58,110
absolutely following the patterns,

1070
00:46:58,110 --> 00:47:00,530
and the autoinducers
scooting around in there,

1071
00:47:00,530 --> 00:47:02,820
and beyond the big pattern,

1072
00:47:02,820 --> 00:47:05,360
the mini patterns of just gene expression

1073
00:47:05,360 --> 00:47:08,090
among single cells over a biofilm,

1074
00:47:08,090 --> 00:47:09,770
the patterns are beautiful.

1075
00:47:09,770 --> 00:47:12,970
I am typing as fast as
I can on that paper.

1076
00:47:12,970 --> 00:47:17,003
So stay tuned, it's really, to me,

1077
00:47:18,160 --> 00:47:21,710
it's reminiscent, not the
same, but reminiscent,

1078
00:47:21,710 --> 00:47:26,710
I think, of like morphogen
gradients in embryos that set up,

1079
00:47:27,180 --> 00:47:29,080
the molecules diffuse round
and they set up these patterns

1080
00:47:29,080 --> 00:47:33,290
and then a fly gets wings
and a head and a tail.

1081
00:47:33,290 --> 00:47:35,740
I think there's some incredible

1082
00:47:35,740 --> 00:47:38,350
similarity here in these biofilms.

1083
00:47:38,350 --> 00:47:39,500
But it was a real

1084
00:47:40,700 --> 00:47:44,610
bottleneck in the field because
we couldn't see into them

1085
00:47:44,610 --> 00:47:45,820
until a couple years ago.

1086
00:47:45,820 --> 00:47:49,623
So I'm super excited about that area.

1087
00:47:52,950 --> 00:47:54,240
- [Paul] Dr. Bassler,

1088
00:47:54,240 --> 00:47:56,450
here's a question from a microbiologist.

1089
00:47:56,450 --> 00:47:59,190
I'm not sure I understand the question.

1090
00:47:59,190 --> 00:48:01,240
What are the natural sources you're mining

1091
00:48:01,240 --> 00:48:03,438
for pro and anti-quorum sensing,

1092
00:48:03,438 --> 00:48:06,994
something like OSMAC
and brute force testing

1093
00:48:06,994 --> 00:48:10,610
of various compounds in a microbial brew?

1094
00:48:10,610 --> 00:48:13,638
- Yeah, I think, I don't know
that one word, but yeah--

1095
00:48:13,638 --> 00:48:15,810
- [Paul] O-S-M-A-C.

1096
00:48:15,810 --> 00:48:17,734
- Yeah, I don't know that word.

1097
00:48:17,734 --> 00:48:20,070
Anyway, but I think I know the answer.

1098
00:48:20,070 --> 00:48:24,470
So yeah, so people are
just getting exotic,

1099
00:48:24,470 --> 00:48:29,443
and mundane collection,
sewage, dirt, seawater,

1100
00:48:31,073 --> 00:48:32,620
and then you're absolutely right,

1101
00:48:32,620 --> 00:48:36,140
then what you do is try
to grow as much as you can

1102
00:48:36,140 --> 00:48:38,710
and then we have assays for interference

1103
00:48:40,309 --> 00:48:43,730
and inducing quorum sensing,
we have a lot of assays.

1104
00:48:43,730 --> 00:48:46,140
And you're right, and then
you have to track back

1105
00:48:46,140 --> 00:48:49,140
if you get activity to try to figure out

1106
00:48:49,140 --> 00:48:51,110
who's making it and what it is.

1107
00:48:51,110 --> 00:48:55,240
But yeah, it's not fancy.

1108
00:48:55,240 --> 00:48:58,890
It isn't fancy, it's just
sampling and testing.

1109
00:48:58,890 --> 00:49:01,697
And then of course we're
doing it synthetically.

1110
00:49:01,697 --> 00:49:05,955
Lots of places have put
together all kinds of libraries,

1111
00:49:05,955 --> 00:49:09,930
both of natural molecules,
or natural products,

1112
00:49:09,930 --> 00:49:13,385
and synthetic molecules, by the millions.

1113
00:49:13,385 --> 00:49:15,200
And we're just getting access to the,

1114
00:49:15,200 --> 00:49:16,430
you can buy those sort of,

1115
00:49:16,430 --> 00:49:19,043
and we just get access to
those and screen as well.

1116
00:49:21,550 --> 00:49:23,500
I do think that the ones where you look

1117
00:49:24,360 --> 00:49:25,880
for naturally-made ones,

1118
00:49:25,880 --> 00:49:27,970
there's probably people
get all distracted,

1119
00:49:27,970 --> 00:49:30,080
'cause there's gonna be
beautiful biology under that.

1120
00:49:30,080 --> 00:49:32,680
Like, "What's that guy
doing with that molecule?"

1121
00:49:32,680 --> 00:49:35,560
And so I think there's
a extra special part

1122
00:49:35,560 --> 00:49:37,770
when you get the naturally-made ones

1123
00:49:37,770 --> 00:49:41,810
'cause you could ask what's
the molecule's normal function?

1124
00:49:41,810 --> 00:49:46,810
So that's the strategy, it's
not particularly elegant

1125
00:49:48,100 --> 00:49:50,120
to screen a lot, yeah.

1126
00:49:50,120 --> 00:49:52,440
- Dr. Bassler, we have
some great questions

1127
00:49:52,440 --> 00:49:54,012
and I just wanna remind our audience,

1128
00:49:54,012 --> 00:49:56,080
we'll try and get through as many

1129
00:49:56,080 --> 00:49:57,470
of these question as we can,

1130
00:49:57,470 --> 00:50:00,183
but we probably won't be
able to get to all of them.

1131
00:50:00,183 --> 00:50:02,850
Dr. Bassler, this sounds
like a great question.

1132
00:50:02,850 --> 00:50:05,950
Is there something like
quorum sensing with viruses?

1133
00:50:05,950 --> 00:50:09,750
And if so, could viruses and
bacteria communicate too?

1134
00:50:09,750 --> 00:50:13,831
- So it turns out that
got discovered in 2019

1135
00:50:13,831 --> 00:50:16,240
by a graduate student in
the lab, Justin Silpe.

1136
00:50:16,240 --> 00:50:20,380
So the viruses, so I think,
okay, I'm brainwashed.

1137
00:50:20,380 --> 00:50:22,693
I think communication
goes across all domains.

1138
00:50:24,023 --> 00:50:25,460
But what he showed,

1139
00:50:25,460 --> 00:50:27,513
I'll tell you actually something specific.

1140
00:50:28,900 --> 00:50:31,540
The bacteria quorum
sensing, you guys get that.

1141
00:50:31,540 --> 00:50:35,429
What Justin discovered was viruses

1142
00:50:35,429 --> 00:50:40,429
that have encoded in
their genomes receptors.

1143
00:50:40,490 --> 00:50:42,840
So these are viruses that infect bacteria.

1144
00:50:42,840 --> 00:50:46,110
So those are called phages,
just like COVID infects us,

1145
00:50:46,110 --> 00:50:48,110
but phages infect bacteria.

1146
00:50:48,110 --> 00:50:51,280
So he found phages that,
encoded in their genomes,

1147
00:50:51,280 --> 00:50:53,650
they have quorum sensing receptors.

1148
00:50:53,650 --> 00:50:55,769
And so the phages are eavesdropping.

1149
00:50:55,769 --> 00:50:59,330
And so, phages, so viruses,
when they get into bacteria,

1150
00:50:59,330 --> 00:51:01,480
just like when they get into our cells,

1151
00:51:01,480 --> 00:51:05,010
they have to decide, "Should
I stay in my host or kill it?"

1152
00:51:05,010 --> 00:51:07,667
So, "Stay, go, or make more of me,

1153
00:51:07,667 --> 00:51:09,750
"bust out, and go to the next cell."

1154
00:51:09,750 --> 00:51:11,250
So that's called lysogeny,

1155
00:51:11,250 --> 00:51:13,650
where they just get passed
down through generations,

1156
00:51:13,650 --> 00:51:15,930
and lysis, where they multiply like crazy,

1157
00:51:15,930 --> 00:51:19,070
bust out, and then infect the next cell.

1158
00:51:19,070 --> 00:51:22,570
So if a phage decides to
the latter and bust out,

1159
00:51:22,570 --> 00:51:25,525
if it doesn't get to
another cell, it's a goner.

1160
00:51:25,525 --> 00:51:29,070
So when is a good time to kill your host?

1161
00:51:29,070 --> 00:51:30,470
Well, when they're at high cell density

1162
00:51:30,470 --> 00:51:31,630
because that means there's lots

1163
00:51:31,630 --> 00:51:33,200
of other bacterial cells around.

1164
00:51:33,200 --> 00:51:35,860
So these freaking viruses
are eavesdropping,

1165
00:51:35,860 --> 00:51:36,870
the poor bacteria.

1166
00:51:36,870 --> 00:51:38,210
Anyway, they're eavesdropping,

1167
00:51:38,210 --> 00:51:40,230
they're measuring the host cell density

1168
00:51:40,230 --> 00:51:43,748
and they tune lysis to high cell density

1169
00:51:43,748 --> 00:51:46,460
and that maximizes transmission

1170
00:51:46,460 --> 00:51:48,067
of the virus to the next cell.

1171
00:51:48,067 --> 00:51:51,640
And so we think that's really insidious

1172
00:51:51,640 --> 00:51:53,677
and really, afterwards, just think,

1173
00:51:53,677 --> 00:51:54,970
"Of course it had to be like that."

1174
00:51:54,970 --> 00:51:56,880
But anyway, so now we're starting to get

1175
00:51:56,880 --> 00:51:58,640
that there's all these connections

1176
00:51:58,640 --> 00:52:00,388
between viruses and bacteria.

1177
00:52:00,388 --> 00:52:01,650
And then the other thing
that Justin did was

1178
00:52:01,650 --> 00:52:03,460
he turned that virus on its head

1179
00:52:03,460 --> 00:52:05,204
and he made a little phage therapy

1180
00:52:05,204 --> 00:52:08,264
where we can kill bacteria on demand

1181
00:52:08,264 --> 00:52:11,148
by infecting them with these phages

1182
00:52:11,148 --> 00:52:13,873
and then turning on the
quorum sensing system.

1183
00:52:15,600 --> 00:52:16,610
So we think that there might be

1184
00:52:16,610 --> 00:52:18,890
even more applications there as well.

1185
00:52:18,890 --> 00:52:21,960
Yeah, so the answer, I
think this goes, yeah,

1186
00:52:21,960 --> 00:52:24,050
that's the start of a new field, I think,

1187
00:52:24,050 --> 00:52:25,980
that now there's a lot of interest

1188
00:52:25,980 --> 00:52:30,403
in these social interactions
between viruses and bacteria.

1189
00:52:32,980 --> 00:52:35,560
- [Paul] And Dr. Bassler,
a student question.

1190
00:52:35,560 --> 00:52:38,510
Was there any point you felt
discouraged in your research?

1191
00:52:38,510 --> 00:52:40,580
How did you move forward?

1192
00:52:40,580 --> 00:52:43,836
- Well, about 6:50 tonight when,

1193
00:52:43,836 --> 00:52:47,692
(loudly laughs) yeah, of course, always.

1194
00:52:47,692 --> 00:52:50,440
So first of all, I have no
other marketable skills,

1195
00:52:50,440 --> 00:52:52,730
so I didn't really have many choices.

1196
00:52:52,730 --> 00:52:56,460
No, but being serious, and I
wanna be really careful here.

1197
00:52:56,460 --> 00:52:58,610
I'm terribly discouraged.

1198
00:52:58,610 --> 00:53:01,840
So first, people thought
this was crazy fringe.

1199
00:53:01,840 --> 00:53:04,803
Like it was a non-medical bacteria,

1200
00:53:04,803 --> 00:53:07,492
this beautiful, it was a one-off.

1201
00:53:07,492 --> 00:53:10,060
Bacteria can't talk to each other,

1202
00:53:10,060 --> 00:53:11,290
they're not sophisticated enough.

1203
00:53:11,290 --> 00:53:13,190
So there was a part of just...

1204
00:53:16,270 --> 00:53:18,600
Skepticism, I guess I would call it that,

1205
00:53:18,600 --> 00:53:19,790
in the early days.

1206
00:53:19,790 --> 00:53:22,690
And then also, of course, most
of our experiments don't work

1207
00:53:22,690 --> 00:53:26,070
and mostly they don't work
and we don't understand why.

1208
00:53:26,070 --> 00:53:28,280
Because these viruses and bacteria

1209
00:53:28,280 --> 00:53:31,010
have been keeping these
secrets for four billion years.

1210
00:53:31,010 --> 00:53:34,100
We've only had 30 years
to try to figure 'em out.

1211
00:53:34,100 --> 00:53:35,510
But anyway, but I think the,

1212
00:53:35,510 --> 00:53:37,440
so I'm discouraged all the time.

1213
00:53:37,440 --> 00:53:38,880
I never think I'm good enough.

1214
00:53:38,880 --> 00:53:40,400
I never think I'm smart enough.

1215
00:53:40,400 --> 00:53:42,580
I always think if I'd just try harder,

1216
00:53:42,580 --> 00:53:44,120
maybe I could get there faster.

1217
00:53:44,120 --> 00:53:48,684
And now I worry because
people's careers depend on me.

1218
00:53:48,684 --> 00:53:53,233
And so I worry even more than
I did when it was just me.

1219
00:53:54,180 --> 00:53:57,380
But, okay, so the answer
is just categorically,

1220
00:53:57,380 --> 00:53:59,144
yes, and it hasn't gone away.

1221
00:53:59,144 --> 00:54:01,989
But then what I would say is that I love,

1222
00:54:01,989 --> 00:54:04,020
I still loved doing it.

1223
00:54:04,020 --> 00:54:08,040
I love the puzzles and I believe in them,

1224
00:54:08,040 --> 00:54:11,383
the gang in my lab, I know
they're as smart as can be.

1225
00:54:13,320 --> 00:54:14,830
And then I also, I don't wanna go home

1226
00:54:14,830 --> 00:54:16,690
and just watch reality TV.

1227
00:54:16,690 --> 00:54:18,480
So, again, I don't think students,

1228
00:54:18,480 --> 00:54:19,910
and I used to do this too.

1229
00:54:19,910 --> 00:54:23,993
I would confuse being
challenged and being stumped,

1230
00:54:25,580 --> 00:54:28,256
sometimes for long, dry periods,

1231
00:54:28,256 --> 00:54:32,412
with it being too hard, and
they're not the same thing.

1232
00:54:32,412 --> 00:54:35,816
Or me not being any good at
it, that's not the same thing.

1233
00:54:35,816 --> 00:54:39,040
Being challenged, being
stumped, you want that.

1234
00:54:39,040 --> 00:54:42,610
Because then it keeps you on your toes

1235
00:54:42,610 --> 00:54:43,900
and it keeps you interested.

1236
00:54:43,900 --> 00:54:45,410
If it was really easy to figure out,

1237
00:54:45,410 --> 00:54:47,340
somebody else would already done it.

1238
00:54:47,340 --> 00:54:49,110
And so I do think, so I don't know

1239
00:54:49,110 --> 00:54:50,690
if that's the right answer,

1240
00:54:50,690 --> 00:54:53,627
is that I was just like,
"I'm gonna figure this out

1241
00:54:53,627 --> 00:54:56,544
"'cause this is fascinating
and there's an answer."

1242
00:54:56,544 --> 00:55:00,580
And me against this
bacterium, who's gonna win?

1243
00:55:00,580 --> 00:55:04,070
Well, we know, but anyways,
so I hope that helps.

1244
00:55:04,070 --> 00:55:08,610
I always don't think I'm
smart enough and we're always

1245
00:55:09,750 --> 00:55:12,350
in a mess of lack of clarity.

1246
00:55:12,350 --> 00:55:14,170
But we help each other,

1247
00:55:14,170 --> 00:55:15,820
everybody helps each other in the lab.

1248
00:55:15,820 --> 00:55:17,711
There's infrastructure to help

1249
00:55:17,711 --> 00:55:21,763
and I'm still just
totally taken by this idea

1250
00:55:21,763 --> 00:55:24,360
that these crazy bacteria do this.

1251
00:55:24,360 --> 00:55:27,180
And so that's all that
keeps me going and it's fun.

1252
00:55:27,180 --> 00:55:30,300
We're out there and we
laugh at how our foibles

1253
00:55:30,300 --> 00:55:32,443
and how once we do figure something out,

1254
00:55:32,443 --> 00:55:35,420
again, I'm like, "Oh, how
come it took us so long?"

1255
00:55:35,420 --> 00:55:39,599
But, it's still a fun, you
have to like the process of it

1256
00:55:39,599 --> 00:55:42,780
and you have to be willing to live

1257
00:55:42,780 --> 00:55:45,730
in the murkiness of not understanding,

1258
00:55:45,730 --> 00:55:49,103
waiting for the cliche aha moment.

1259
00:55:51,869 --> 00:55:54,743
And you have to learn
to like that, and I do.

1260
00:55:57,700 --> 00:55:59,330
- Yeah, I think you're proven inspiration

1261
00:55:59,330 --> 00:56:01,260
to us all, Dr. Bassler.

1262
00:56:01,260 --> 00:56:04,280
I have one question and I think Dr. Kelly

1263
00:56:04,280 --> 00:56:07,330
could probably ask one more as well.

1264
00:56:07,330 --> 00:56:09,381
But before I ask the question,

1265
00:56:09,381 --> 00:56:11,560
just to let you know that
microbiology colleagues

1266
00:56:11,560 --> 00:56:15,087
in our department are involved
in the Tiny Earth program,

1267
00:56:15,087 --> 00:56:17,460
which I'm sure you've heard of.

1268
00:56:17,460 --> 00:56:19,637
I'm not a microbiologist.
- Great.

1269
00:56:19,637 --> 00:56:21,710
- But the question that we have is,

1270
00:56:21,710 --> 00:56:23,630
I think it's a clarifying question,

1271
00:56:23,630 --> 00:56:26,230
is how do you elucidate
and distinguish structures

1272
00:56:26,230 --> 00:56:29,471
of goods quorums versus bad ones?

1273
00:56:29,471 --> 00:56:33,023
- Yeah, I think that's context-specific.

1274
00:56:35,131 --> 00:56:36,943
And I think they can be both.

1275
00:56:39,910 --> 00:56:43,070
The field has focused on

1276
00:56:43,070 --> 00:56:48,070
model bacteria, like the two
Vibrio bioluminescent bacteria

1277
00:56:48,690 --> 00:56:50,830
and these terrible pathogens

1278
00:56:50,830 --> 00:56:53,040
that we know we need medicines for.

1279
00:56:53,040 --> 00:56:54,612
When we get into the microbiome

1280
00:56:54,612 --> 00:56:58,090
and there's hundreds and species
and you don't really know

1281
00:56:58,090 --> 00:57:00,900
what their different roles
is, it's a different game.

1282
00:57:00,900 --> 00:57:02,592
Because you don't know,

1283
00:57:02,592 --> 00:57:04,900
when you're messing
around with that stuff,

1284
00:57:04,900 --> 00:57:06,410
who's the good guy and who's the bad guy.

1285
00:57:06,410 --> 00:57:11,218
And so I think there's a
complexity issue that is unsolved

1286
00:57:11,218 --> 00:57:14,290
and it's really fine to
work in these model systems.

1287
00:57:14,290 --> 00:57:16,457
But when you really wanna
deploy this in real life,

1288
00:57:16,457 --> 00:57:17,940
and you really wanna understand

1289
00:57:17,940 --> 00:57:20,220
how quorum sensing works in real life,

1290
00:57:20,220 --> 00:57:24,163
not in a flask in Princeton,
New Jersey out in that hallway,

1291
00:57:26,185 --> 00:57:28,693
we don't have the answer for that yet.

1292
00:57:33,870 --> 00:57:36,190
- [Paul] Thank you, and maybe one more.

1293
00:57:36,190 --> 00:57:38,210
Antibiotics often interfere

1294
00:57:38,210 --> 00:57:40,993
with a bacterial structure
like a cell membrane.

1295
00:57:40,993 --> 00:57:44,580
Are you trying to damage
the quorum sensing mechanism

1296
00:57:44,580 --> 00:57:46,640
by jamming the receptor protein?

1297
00:57:46,640 --> 00:57:50,790
Can you jam the production
of the autoinducer molecule?

1298
00:57:50,790 --> 00:57:53,300
- Right, so there's sort
of two questions in there.

1299
00:57:53,300 --> 00:57:57,630
One I think is that we're
not killing the bacteria.

1300
00:57:57,630 --> 00:57:59,380
Like a regular antibiotic kills them

1301
00:57:59,380 --> 00:58:01,740
and then that selects
for resistant mutants.

1302
00:58:01,740 --> 00:58:04,665
So the fantasy of the first
part of that question is

1303
00:58:04,665 --> 00:58:07,573
that we make 'em so they can't talk.

1304
00:58:07,573 --> 00:58:09,760
They can't communicate, they can't count.

1305
00:58:09,760 --> 00:58:11,550
They don't launch their virulence factors.

1306
00:58:11,550 --> 00:58:14,862
So then all you're doing is buying time

1307
00:58:14,862 --> 00:58:17,340
for the immune system to come in

1308
00:58:17,340 --> 00:58:21,100
and get rid of 'em as it normally does.

1309
00:58:21,100 --> 00:58:24,720
So we think the selection for
resistance will be much lower

1310
00:58:24,720 --> 00:58:26,780
because we're not damaging them.

1311
00:58:26,780 --> 00:58:29,700
And then the second part of
the question answer is just,

1312
00:58:29,700 --> 00:58:32,450
yes, I showed you one strategy,

1313
00:58:32,450 --> 00:58:34,918
which is to make synthetic autoinducers.

1314
00:58:34,918 --> 00:58:37,800
But absolutely, if you
can block the enzymes

1315
00:58:37,800 --> 00:58:39,480
so they never make the autoinducer,

1316
00:58:39,480 --> 00:58:42,780
if you can make a sponge that
slurps up the autoinducer,

1317
00:58:42,780 --> 00:58:44,690
if you can get rid of the receptor,

1318
00:58:44,690 --> 00:58:48,270
anything that interferes with
any part of that circuit,

1319
00:58:48,270 --> 00:58:49,810
we are trying to target.

1320
00:58:49,810 --> 00:58:52,331
It's just the easiest
to understand, I think,

1321
00:58:52,331 --> 00:58:55,060
the anti-quorum sensing molecule.

1322
00:58:55,060 --> 00:58:56,110
But you're absolutely right,

1323
00:58:56,110 --> 00:58:58,856
if they can't make the autoinducer,

1324
00:58:58,856 --> 00:59:01,620
they're avirulent, we've
shown that with mutants.

1325
00:59:01,620 --> 00:59:03,803
So that's another strategy we're after.

1326
00:59:05,930 --> 00:59:07,790
- Dr. Bassler, thanks for providing

1327
00:59:07,790 --> 00:59:10,570
such a wonderfully
illuminating and engaging talk.