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[gentle music]

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- Samantha Mulrooney:
Hello, everybody.

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We'll go ahead and get started.

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Thank you all for being here.

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Good evening, and welcome

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to Crossroads of Ideas:
When Antibiotics Fail.

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My name is Sam Mulrooney.

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I'm the Outreach Program Manager
here at the Discovery Building

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and also the director of the
Wisconsin Science Festival.

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So, thank you all
for being here.

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And before we get started,

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just a couple
of opening remarks for you all.

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Today's event marks the third

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and final installment
of our three-part miniseries

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on productive failure
in science.

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Crossroads of Ideas
is a program series presented

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by the Illuminating
Discovery Hub here

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at the Wisconsin Institute
for Discovery

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and developed collaboratively
with UW-Madison

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and other discovery
building partners.

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Crossroads brings together
campus experts

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and community members to explore
thought-provoking topics

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at the intersection of science,
society, and the arts.

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Since its launch in 2014,

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the series has been
a cornerstone

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of public programming
at the Discovery Building,

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fostering dialogue,
curiosity, and connection

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across disciplines.

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So, we're delighted
to have you all with us

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for this conversation tonight.

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So, throughout this miniseries,

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we've been exploring the idea
that sits at the heart

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of scientific progress:
productive failure.

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In science, failure is rarely
the end of the story.

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Often, it's the moment that
reveals something unexpected,

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challenges assumptions,

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or points researchers
towards a new path.

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Tonight's conversation
looks at this idea

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through a pressing
global challenge:

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What happens
when antibiotics fail,

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and how scientists
are working to understand

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and respond
to antimicrobial resistance.

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So, to help us tonight--
It's a big question.

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To help us tonight,
we have two of my colleagues

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here at the Discovery Building,

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Executive Director
of the Tiny Earth Program,

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Sarah Miller,
and Assistant Professor

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in the Department
of Plant Pathology,

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Dr. Marc Chevrette.

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First, Sarah will explain
a bit more about

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her amazing work
with the Tiny Earth program.

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And then, Marc will help us
explore antimicrobial resistance

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and what researchers
are doing to discover

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and understand
this global challenge.

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We'll be sure to save time
at the end for Q&A.

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So, it is my pleasure
to first introduce Sarah,

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Executive Director
of the Tiny Earth Program,

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and which is
an international network

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of more than 800 instructors
across 33 countries

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that engages roughly 16,000
students each year--

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incredible--

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in the search for new
antibiotics from soil bacteria.

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Her work focuses
on STEM education,

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particularly active
and inclusive learning,

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large-scale
institutional change,

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and faculty development.

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Sarah is a coauthor of several
science education publications,

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including work
in <i>Science</i> magazine,

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and has received
the UW-Madison Teaching Academy

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Distinguished Teaching Award.

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So, without further ado,
I welcome Sarah.

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[audience applauds]

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- Sarah Miller: Hi, everyone.

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Nice to see you.

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I'm Sarah Miller, Executive
Director of Tiny Earth,

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and we are housed here
at WID.

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As Sam mentioned,

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Tiny Earth is a global network
of college students

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who are crowdsourcing,
or we like to say,

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student sourcing antibiotics
from soil bacteria.

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So, we face several
pressing global challenges

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with respect to all kinds
of things.

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First one is increasing gaps
with respect to achievement

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and access
in science in college,

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increasing
antibiotic resistance,

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and increasing soil erosion.

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Each of these
constitutes a global crisis,

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which the Tiny Earth Initiative
is designed to address.

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Tiny Earth's three goals,
therefore,

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are to inspire students
to have access to

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and to persist in the sciences,

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to address the dwindling supply
of antibiotics,

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and to protect
our precious soils.

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I will be unpacking
only the first two in this talk.

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So, first,
let's start with the goal

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of inspiring diverse students
to persist in science.

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So, there
are two problems here.

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Students leave science
in college

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after declaring science majors.

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And there is a stubborn gap
in performance.

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So, first,
nearly 600,000 students

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leave STEM majors every year,

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citing poor teaching methods
as the primary reason.

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Worse, women,
students of color,

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and all underrepresented groups

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leave at higher rates
than majority students.

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In addition,
the gap in performance

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between underrepresented
and overrepresented students,

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as measured by exams or grades
has been called,

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quote, "one of the most urgent
and intractable problems

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in higher education."

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So, in order to have
a diverse STEM workforce,

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students need access
to scientific opportunities.

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They need environments
designed for success,

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and they need to feel
like they belong in science.

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Colleges
are often falling short,

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relying largely
on didactic lectures

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despite overwhelming evidence
in support of active

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and inclusive
learning strategies.

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So, Tiny Earth provides students
with access and opportunity

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to do real scientific research.

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So, Tiny Earth is a CURE,
which stands for

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a course-based undergraduate
research experience.

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Students engage
in a full semester

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of authentic science research,

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designing their own experiments,
working collaboratively,

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failing, troubleshooting,

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failing again,
collecting and analyzing data,

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trying again, and all the while
building the lab skills needed

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to be part
of the STEM workforce,

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or simply to be
well-informed citizens

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who are able to think critically
about scientific issues

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by weighing evidence.

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CUREs have been shown again
and again

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to promote student learning.

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They increase research skills.

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They increase project ownership.

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They boost confidence,
self-efficacy,

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and belonging in science,

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and they lead
to retention in science.

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They focus on relevant problems

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and they lead
to new discoveries.

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Students who take a CURE
like Tiny Earth in college

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are less likely
to leave science.

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In fact,
just one CURE in college

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can increase persistence
in science.

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And the positive effect
is even greater for students

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who are from groups that
have been historically excluded

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from STEM.

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CUREs also provide access to
research experiences at scale,

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because they are taught
as courses

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that enroll tens or hundreds
of students simultaneously,

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rather than a more traditional

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one-on-one faculty-student
research experience in a lab,

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where the math ain't mathing,
right?

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Better yet,
CUREs can be and are taught

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at all types of colleges.

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Technical colleges,
community colleges,

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tribal colleges,
not just research universities.

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Okay, so we've established
that CUREs provide access to

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and support for students
to engage in research.

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But what are the students doing
for that research?

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In Tiny Earth, the answer is the
dwindling supply of antibiotics.

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Antibiotics are the medicines,
of course,

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that we take to cure
bacterial infections.

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They're also used
in other applications,

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like veterinary clinics or farms
or on crops.

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However, largely due to overuse,

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bacteria are becoming
increasingly resistant

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to the antibiotics that we have,
rendering them useless.

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And you can see here
that antibiotic resistance

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has risen sharply this century,

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especially for seniors.

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Scientists worldwide
are warning of a looming crisis

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as antibiotic resistance
surges globally,

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predicting 40 million deaths
by 2050.

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And yet,
pharmaceutical companies

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have largely abandoned
antibiotic discovery.

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So, why, you may ask.

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Well, it's simply
not that lucrative.

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It takes a billion
or billions of dollars

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to move a new drug
from discovery to market.

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But then you, the consumer,

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only takes it for about
five days, seven days, ten days,

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how long you take an antibiotic,

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in contrast to other drugs
that are taken for much longer,

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like statins or SSRIs,
which you might take for life,

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and therefore those are
much more lucrative.

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So, once again,
enter Tiny Earth.

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So, Tiny Earth students turn
to the soil,

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a rich repository of bacteria

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where many of our medicines
come from.

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Tiny Earth students spend
a semester

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working on this problem.

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First, they collect
a soil sample,

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just a tablespoon or two from
their soil of their choosing.

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It could be from their backyard.

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It could be from a local park.

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It could be from their campus,
a field.

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It doesn't matter;
they get to choose.

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They dilute their soil
in sterile water.

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They inoculate petri plates
with those soil dilutions.

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They wait a few days
to see what grows.

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And this is the first discovery
in Tiny Earth.

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The students see
how alive the soil is

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when their plates
are just covered with bacteria.

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Next, they choose
a few bacteria to screen,

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so now I'm in module two here,

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to screen
for antibiotic activity

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by growing them with safe
relatives of known pathogens.

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We do not use
the actual pathogens in the lab,

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in the class,

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and the experiments
usually result

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in several bacteria showing a
quote, "zone of inhibition"

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where the soil bacteria,

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that's what's circled in red
up on the slide,

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where the soil
bacteria basically stopped

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the safe relative
of that pathogen in its tracks.

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And so, you can see
that zone of inhibition,

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that clearing area
on that plate.

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And so, discovering that
bacteria

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that is an antibiotic producer,

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that's the second discovery
in Tiny Earth.

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So, here we are,
only in module two,

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and the students have already
had two pretty major discoveries

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that literally no one
has ever looked at before,

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because it's the soil
of their choosing

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and the isolates
that grew from it.

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At this point,
the students don't know

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what their bacteria are,

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but they're hooked
on figuring it out.

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So, that leads
to countless more discoveries.

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They can try a battery
of classic microbiology tests.

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They can do all kinds
of genomic applications

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to characterize and possibly
even identify the soil bacteria

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that have shown
antibiotic activity.

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Some Tiny Earth courses
even take it a step further,

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moving into module four,

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where the students further
elucidate the actual molecules

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that bacteria are making.

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Because at the end of the day,

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antibiotics are, in fact,
molecules.

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So, that's the gist
of Tiny Earth.

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The students usually write
their results up, you know,

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lab report or whatever
they have in their class.

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But they can also present
their research findings,

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at, for example,
a symposium.

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What you're looking at here

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is our annual Tiny Earth
in Titletown Symposium

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that we hold at Lambeau Field
every December

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at the end of the semester.

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And so, on a dark night,
usually on a Friday,

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about 200 students
from Wisconsin

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convene to present
their research,

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00:11:12,072 --> 00:11:13,574
and they invite
their family and friends.

256
00:11:13,640 --> 00:11:18,412
This event is attended by about
550 people from the community.

257
00:11:18,478 --> 00:11:20,414
It's pretty remarkable
to celebrate

258
00:11:20,480 --> 00:11:22,049
the students
doing this research.

259
00:11:22,115 --> 00:11:25,085
And these students are coming
from UW system schools,

260
00:11:25,152 --> 00:11:26,753
technical colleges,

261
00:11:26,820 --> 00:11:28,956
the private colleges,
you name it.

262
00:11:29,022 --> 00:11:30,657
Sometimes, we get others
from outside the state,

263
00:11:30,724 --> 00:11:32,593
but mostly,
that particular event

264
00:11:32,659 --> 00:11:33,894
is for the state of Wisconsin.

265
00:11:33,961 --> 00:11:36,864
We also hold
an international symposium here

266
00:11:36,930 --> 00:11:38,832
at WID in the summer.

267
00:11:41,969 --> 00:11:43,070
All right, here's our map.

268
00:11:43,136 --> 00:11:45,906
So, I have some,
from even what Sam said,

269
00:11:45,973 --> 00:11:47,474
we have some new numbers.

270
00:11:47,541 --> 00:11:50,244
The problem of antibiotic
resistance is so massive

271
00:11:50,310 --> 00:11:53,847
that it requires
a massive crowdsourced effort.

272
00:11:53,914 --> 00:11:56,617
So, we have trained actually
more than 900 instructors now,

273
00:11:56,683 --> 00:11:59,620
mostly college faculty,
to teach Tiny Earth.

274
00:11:59,686 --> 00:12:01,121
And estimating
conservatively,

275
00:12:01,188 --> 00:12:02,856
if you imagine
that each of those

276
00:12:02,923 --> 00:12:05,225
is teaching, on average,
20 students per year,

277
00:12:05,292 --> 00:12:08,328
that means
18,000 students have access

278
00:12:08,395 --> 00:12:14,034
to the Tiny Earth CURE research
experience every single year.

279
00:12:14,101 --> 00:12:16,803
And this is where I think
Tiny Earth is really clever

280
00:12:16,870 --> 00:12:19,406
and how we get around
the overwhelming numbers game.

281
00:12:19,473 --> 00:12:22,442
Our main expansion tool is the
Tiny Earth partner instructor.

282
00:12:22,509 --> 00:12:24,945
We call them TEPIs, T-E-P-I.

283
00:12:25,012 --> 00:12:26,146
The TEPI training,

284
00:12:26,213 --> 00:12:27,814
it's a week-long immersive
summer camp.

285
00:12:27,881 --> 00:12:30,350
We hold it here
in the Discovery Building,

286
00:12:30,417 --> 00:12:33,620
and we teach faculty
how to teach Tiny Earth.

287
00:12:33,687 --> 00:12:35,889
It's based on
evidence-based pedagogical

288
00:12:35,956 --> 00:12:38,025
and peer mentoring practices.

289
00:12:38,091 --> 00:12:39,259
And during the week,

290
00:12:39,326 --> 00:12:41,395
the TEPIs work
in facilitated groups

291
00:12:41,461 --> 00:12:44,798
to adapt the curriculum
for their particular students

292
00:12:44,865 --> 00:12:48,368
and their particular version
of Tiny Earth.

293
00:12:48,435 --> 00:12:50,304
They learn scientific
teaching principles

294
00:12:50,370 --> 00:12:53,407
such as course design, active
learning, inclusive learning,

295
00:12:53,473 --> 00:12:55,175
and they apply them all
to the development

296
00:12:55,242 --> 00:12:57,511
of their Tiny Earth course.

297
00:12:57,578 --> 00:13:00,380
And they go through all
the lab protocols along the way,

298
00:13:00,447 --> 00:13:02,983
just as if they were students
while thinking about the course

299
00:13:03,050 --> 00:13:05,285
that they're building.

300
00:13:05,652 --> 00:13:06,854
So, bringing this all together,

301
00:13:06,920 --> 00:13:09,089
Tiny Earth is
an antibiotic discovery pipeline

302
00:13:09,156 --> 00:13:10,924
that starts
with training instructors,

303
00:13:10,991 --> 00:13:13,560
but really focuses
on students engaging

304
00:13:13,627 --> 00:13:16,830
in authentic research
for a full semester.

305
00:13:16,897 --> 00:13:19,700
Students enter their data
into the Tiny Earth database,

306
00:13:19,766 --> 00:13:21,869
and they can send
any interesting isolates

307
00:13:21,935 --> 00:13:25,606
they find here to WID
to our Tiny Earth chemistry hub,

308
00:13:25,672 --> 00:13:28,609
which is upstairs in
Professor Jo Handelsman's lab.

309
00:13:28,675 --> 00:13:31,478
Today, we have more than 4,300
isolates in the collection

310
00:13:31,545 --> 00:13:35,282
and several of interest
that we're pursuing further.

311
00:13:35,349 --> 00:13:37,084
So, I just wanna thank you all
for coming

312
00:13:37,150 --> 00:13:38,585
and thank our sponsors
for Tiny Earth,

313
00:13:38,652 --> 00:13:40,687
in a particular,
Dr. Jo Handelsman,

314
00:13:40,754 --> 00:13:43,757
who is the founder
of Tiny Earth.

315
00:13:44,858 --> 00:13:47,160
All right, and with that,

316
00:13:47,227 --> 00:13:49,730
I get the pleasure
of introducing Marc Chevrette.

317
00:13:49,796 --> 00:13:53,133
He is a relatively new assistant
professor of plant pathology.

318
00:13:53,200 --> 00:13:55,335
He is a Discovery Fellow
here at WID.

319
00:13:55,402 --> 00:13:58,839
He was hired as part of the
Wisconsin RISE-EARTH initiative,

320
00:13:58,906 --> 00:14:00,674
and is one
of those rare scientists

321
00:14:00,741 --> 00:14:04,344
who did both his PhD
and his postdoc here at UW.

322
00:14:04,411 --> 00:14:07,147
The PhD was in bacteriology
in the Currie Lab,

323
00:14:07,214 --> 00:14:10,551
and the postdoc was here
at WID in the Handelsman Lab.

324
00:14:10,617 --> 00:14:12,119
Previously, Marc was
an assistant,

325
00:14:12,186 --> 00:14:13,287
[clears throat]
excuse me,

326
00:14:13,353 --> 00:14:14,988
professor
at the University of Florida,

327
00:14:15,055 --> 00:14:16,456
and before grad school,

328
00:14:16,523 --> 00:14:18,125
he was head
of the experimental genomics

329
00:14:18,192 --> 00:14:20,661
at Warp Drive Bio,
now Ginkgo Bioworks,

330
00:14:20,727 --> 00:14:22,462
where he was one
of the lead developers

331
00:14:22,529 --> 00:14:24,598
of the ubiquitous software
called antiSMASH,

332
00:14:24,665 --> 00:14:29,303
which identifies and annotates
genes in bacteria and fungi.

333
00:14:29,369 --> 00:14:31,171
According to Marc, quote,

334
00:14:31,238 --> 00:14:33,073
"Microbes are
the best chemists in the world,

335
00:14:33,140 --> 00:14:34,875
"and their metabolites
are the language

336
00:14:34,942 --> 00:14:36,977
of microbial interactions."

337
00:14:37,044 --> 00:14:39,379
He is an incredibly
interdisciplinary scientist,

338
00:14:39,446 --> 00:14:41,982
drawing from fields
as broad as genomics, chemistry,

339
00:14:42,049 --> 00:14:45,652
microbiology, data science,
plant pathology, and ecology,

340
00:14:45,719 --> 00:14:49,089
with impacts bleeding
into medicine and public health,

341
00:14:49,156 --> 00:14:52,092
agriculture and the environment.

342
00:14:52,159 --> 00:14:54,995
His lab uses both computational
and experimental approaches

343
00:14:55,062 --> 00:14:57,898
to study the ecology and
evolution of bacterial genes

344
00:14:57,965 --> 00:14:59,066
and how bacteria interact

345
00:14:59,132 --> 00:15:01,134
using compounds encoded
in those genes.

346
00:15:01,201 --> 00:15:03,871
He has 75 peer-reviewed
publications in systems

347
00:15:03,937 --> 00:15:06,507
ranging from natural products,
discovery and bacteria

348
00:15:06,573 --> 00:15:09,576
to drug resistance and fungi
and antimicrobial potential

349
00:15:09,643 --> 00:15:13,647
and insect biomes,
biofilms, and even Tiny Earth.

350
00:15:13,714 --> 00:15:15,249
I've had the pleasure
of working with Marc

351
00:15:15,315 --> 00:15:17,117
for almost seven years now
in his role

352
00:15:17,184 --> 00:15:19,119
as Tiny Earth genomics director,

353
00:15:19,186 --> 00:15:20,888
and he is, at heart,
a Renaissance man

354
00:15:20,954 --> 00:15:23,090
who loves to solve
wicked problems.

355
00:15:23,156 --> 00:15:25,092
We share this,
and thank goodness,

356
00:15:25,158 --> 00:15:26,493
because as you've
already learned,

357
00:15:26,560 --> 00:15:28,362
antibiotic resistance is in fact

358
00:15:28,428 --> 00:15:30,597
one of those wicked problems
that requires us all

359
00:15:30,664 --> 00:15:33,267
to draw on all of these
disciplines to address it.

360
00:15:33,333 --> 00:15:36,003
So, without further ado,
Marc Chevrette.

361
00:15:36,069 --> 00:15:38,071
[audience applauds]

362
00:15:45,112 --> 00:15:46,246
- Marc Chevrette:
Thank you, Sarah.

363
00:15:46,313 --> 00:15:49,516
That was a very warm
and friendly introduction

364
00:15:49,583 --> 00:15:51,752
to a rather unfriendly topic

365
00:15:51,818 --> 00:15:53,153
that I'm gonna be talking about,

366
00:15:53,220 --> 00:15:56,456
which is what happens
when antibiotics fail

367
00:15:56,523 --> 00:15:58,792
and what types of strategies

368
00:15:58,859 --> 00:16:04,631
we as researchers are using to
try and overcome that failure.

369
00:16:04,698 --> 00:16:07,935
So, firstly,
what are antibiotics?

370
00:16:08,001 --> 00:16:10,170
As Sarah introduced,
antibiotics are chemicals

371
00:16:10,237 --> 00:16:13,207
that are made
by bacteria and fungi,

372
00:16:13,273 --> 00:16:15,676
just living their
everyday lives in nature

373
00:16:15,742 --> 00:16:18,011
that we as humans
have discovered

374
00:16:18,078 --> 00:16:22,049
and found uses for them
to treat infections.

375
00:16:22,115 --> 00:16:25,786
So, there are two main flavors
of these antibiotics.

376
00:16:25,853 --> 00:16:29,590
Those that are bacteriocidal,
think of those as kill switches.

377
00:16:29,656 --> 00:16:32,926
They're actively going
and killing bacterial infections

378
00:16:32,993 --> 00:16:35,462
or things
that are bacteriostatic.

379
00:16:35,529 --> 00:16:38,532
So, these are arresting
the growth of bacteria

380
00:16:38,599 --> 00:16:41,668
so that other mechanisms can
help you overcome the infection.

381
00:16:41,735 --> 00:16:44,171
So, think like stopping
their growth

382
00:16:44,238 --> 00:16:48,742
so that your immune system can
then go fight off the disease.

383
00:16:48,809 --> 00:16:50,544
One of the
more famous antibiotics

384
00:16:50,611 --> 00:16:52,913
that I'll use to introduce this
is penicillin.

385
00:16:52,980 --> 00:16:56,316
This is a molecule whose
discovery was born of failure.

386
00:16:56,383 --> 00:16:57,918
Some of you
may already know the story,

387
00:16:57,985 --> 00:17:02,789
but in 1928, Alexander Fleming
left to go to a conference.

388
00:17:02,856 --> 00:17:04,391
His lab,
in charge of--

389
00:17:04,458 --> 00:17:06,293
All of the grad students
in charge

390
00:17:06,360 --> 00:17:08,462
basically took the week off

391
00:17:08,529 --> 00:17:10,564
and left all
of their bacterial plates out.

392
00:17:10,631 --> 00:17:13,567
And when he came back,
a few of them were contaminated.

393
00:17:13,634 --> 00:17:17,304
One of those contaminations had
one of those zones of inhibition

394
00:17:17,371 --> 00:17:19,206
that Sarah introduced

395
00:17:19,273 --> 00:17:21,241
that's part
of the Tiny Earth curriculum.

396
00:17:21,308 --> 00:17:23,844
He found one of those
on his plates just by accident.

397
00:17:23,911 --> 00:17:26,246
And over the course
of the next couple of years,

398
00:17:26,313 --> 00:17:29,116
he tried to understand
what was actually being produced

399
00:17:29,183 --> 00:17:30,984
and how that zone was happening.

400
00:17:31,051 --> 00:17:35,522
And that, to cut
the story short, was penicillin.

401
00:17:35,589 --> 00:17:38,058
Penicillin is one
of the more famous drugs,

402
00:17:38,125 --> 00:17:42,329
because it's one of the ones
that has had a massive impact

403
00:17:42,396 --> 00:17:44,231
in human health.

404
00:17:44,298 --> 00:17:47,701
How it works is
it enters the bacterial cell

405
00:17:47,768 --> 00:17:50,537
and targets an enzyme that's
responsible for building up

406
00:17:50,604 --> 00:17:52,573
the cell wall
of that bacteria.

407
00:17:52,639 --> 00:17:54,474
So, you're not able to build
your cell wall,

408
00:17:54,541 --> 00:17:57,978
you're not able to reproduce,
and the bacteria die.

409
00:17:58,045 --> 00:18:02,049
So, think of these as kind of
lock and key type interactions.

410
00:18:02,115 --> 00:18:05,018
The antibiotic needs
to go into the cell,

411
00:18:05,085 --> 00:18:07,921
find its cellular target,
and interact with it

412
00:18:07,988 --> 00:18:10,757
in a way that disrupts
the bacteria so it either dies

413
00:18:10,824 --> 00:18:12,092
or stops growing.

414
00:18:12,159 --> 00:18:13,994
So, these are
very specialized tools.

415
00:18:14,061 --> 00:18:17,297
They're not used
as all-purpose medicines.

416
00:18:17,364 --> 00:18:19,166
And so, what that means is that

417
00:18:19,233 --> 00:18:22,002
different infections are
gonna require different keys

418
00:18:22,069 --> 00:18:24,638
to unlock different locks.

419
00:18:25,205 --> 00:18:27,641
Antibiotics,
as a very general term,

420
00:18:27,708 --> 00:18:32,646
can be these molecules that
target either bacteria or fungi.

421
00:18:32,713 --> 00:18:35,849
So, the ones that target
bacteria are antibacterial,

422
00:18:35,916 --> 00:18:39,286
antifungal
for the ones that target fungi.

423
00:18:39,353 --> 00:18:41,154
And you'll notice
that I didn't mention viruses

424
00:18:41,221 --> 00:18:44,358
because antibiotics do
nothing against viruses.

425
00:18:44,424 --> 00:18:46,860
So, everything
that we know about antibiotics

426
00:18:46,927 --> 00:18:50,931
and how they work are them
disrupting cellular processes.

427
00:18:50,998 --> 00:18:53,934
And viruses operate in
a completely different biology.

428
00:18:54,001 --> 00:18:57,804
So, they're not active
against viruses.

429
00:18:58,238 --> 00:19:00,941
So, antibiotics are
very important.

430
00:19:01,008 --> 00:19:02,943
But not too long ago,
we were in a world

431
00:19:03,010 --> 00:19:05,279
before antibiotics
were widely used.

432
00:19:05,345 --> 00:19:08,248
This picture here
is of Calvin Coolidge's son,

433
00:19:08,315 --> 00:19:10,217
Calvin Coolidge Jr,

434
00:19:10,551 --> 00:19:15,455
who was in 1924 playing
tennis on the White House lawn

435
00:19:16,256 --> 00:19:20,227
and developed a
relatively minor cut on his hand

436
00:19:20,294 --> 00:19:21,929
that turned into an infection.

437
00:19:21,995 --> 00:19:24,565
That infection, over the course
of the next four days,

438
00:19:24,631 --> 00:19:25,732
led to his death.

439
00:19:25,799 --> 00:19:29,036
So, even just about
100 years ago,

440
00:19:29,102 --> 00:19:31,572
people who were the sons
of world leaders

441
00:19:31,638 --> 00:19:33,607
that had access
to top medical care

442
00:19:33,674 --> 00:19:36,743
were still in very life
or death situations

443
00:19:36,810 --> 00:19:39,479
from bacterial infections.

444
00:19:40,347 --> 00:19:44,751
Now, this is an ad
from Listerine from 1930.

445
00:19:44,818 --> 00:19:46,987
Basically, just minor cuts

446
00:19:47,054 --> 00:19:50,123
that men were facing
with their razor blades

447
00:19:50,190 --> 00:19:53,594
could end them in the hospital
or even death.

448
00:19:53,660 --> 00:19:56,396
So, one of the major
primary uses for Listerine

449
00:19:56,463 --> 00:19:58,398
in the early days in the 1930s

450
00:19:58,465 --> 00:20:02,002
was to guard against
these bacterial infections.

451
00:20:02,069 --> 00:20:04,371
And penicillin
that I mentioned before,

452
00:20:04,438 --> 00:20:06,840
it's credited with, in part,

453
00:20:06,907 --> 00:20:09,977
the reason why the Allied troops
in World War II

454
00:20:10,043 --> 00:20:13,313
were able to get an advantage
on the battlefield.

455
00:20:13,380 --> 00:20:15,482
So, battlefield injuries

456
00:20:15,549 --> 00:20:20,354
were not as much of a problem
for the U.S. and U.K. forces

457
00:20:20,420 --> 00:20:23,056
because we had access
to penicillin

458
00:20:23,123 --> 00:20:25,225
that was getting our soldiers
out

459
00:20:25,292 --> 00:20:26,860
from underneath
the infectious disease

460
00:20:26,927 --> 00:20:29,763
that they could pick up
in the battlefield.

461
00:20:29,830 --> 00:20:31,965
So, how do we use antibiotics?

462
00:20:32,032 --> 00:20:35,169
Typically, we're using them
to treat infections in humans,

463
00:20:35,235 --> 00:20:39,206
in us that are caused
by either bacteria or fungi.

464
00:20:39,273 --> 00:20:40,874
And in parallel, though,

465
00:20:40,941 --> 00:20:43,744
I think something
that isn't as well noticed

466
00:20:43,810 --> 00:20:47,414
is that antibiotics
are the reason why we're able

467
00:20:47,481 --> 00:20:50,684
to have so many other
breakthroughs across medicine.

468
00:20:50,751 --> 00:20:52,653
So, when you're getting
treatments for cancer,

469
00:20:52,719 --> 00:20:56,123
or you undergo an organ
transplantation or surgeries

470
00:20:56,190 --> 00:20:59,693
or even relatively routine
things like dental cleanings,

471
00:20:59,760 --> 00:21:01,161
antibiotics enable us

472
00:21:01,228 --> 00:21:04,598
to be able to not worry
about infections.

473
00:21:04,665 --> 00:21:06,934
So, they're very,
very important.

474
00:21:07,000 --> 00:21:08,101
Aside from human health,

475
00:21:08,168 --> 00:21:10,404
they're also very important
in agriculture.

476
00:21:10,470 --> 00:21:13,740
And so, crop and livestock
bacterial and fungal diseases

477
00:21:13,807 --> 00:21:15,876
are combated
with antibiotics the same way

478
00:21:15,943 --> 00:21:18,779
that we combat diseases
in humans,

479
00:21:18,846 --> 00:21:21,081
but we also use them
as prophylactics.

480
00:21:21,148 --> 00:21:23,016
So, to prevent
infectious disease

481
00:21:23,083 --> 00:21:25,752
from even occurring
within our food.

482
00:21:25,819 --> 00:21:28,755
Different countries have
different regulations on this.

483
00:21:28,822 --> 00:21:32,559
But I think what's very telling
is that in the United States,

484
00:21:32,626 --> 00:21:36,096
at least, 80% of the antibiotics
that are sold

485
00:21:36,163 --> 00:21:37,631
go directly to agriculture.

486
00:21:37,698 --> 00:21:39,032
So, even though
we think of these

487
00:21:39,099 --> 00:21:42,336
as very human-centric
medicinal molecules,

488
00:21:42,402 --> 00:21:46,073
we're using them
across the food chain.

489
00:21:46,740 --> 00:21:48,108
So, how do they work?

490
00:21:48,175 --> 00:21:49,776
They work,
like I mentioned before,

491
00:21:49,843 --> 00:21:52,312
by disrupting
key cellular processes

492
00:21:52,379 --> 00:21:55,716
that the bacteria
are needing to survive.

493
00:21:55,782 --> 00:21:58,819
This could be interacting
with the cell wall,

494
00:21:58,886 --> 00:22:01,655
the things
that biosynthesize the cell wall

495
00:22:01,722 --> 00:22:03,590
and build it
as they're replicating.

496
00:22:03,657 --> 00:22:05,058
They interfere with those.

497
00:22:05,125 --> 00:22:06,894
They can interfere
with the membranes,

498
00:22:06,960 --> 00:22:08,462
how they make proteins,

499
00:22:08,529 --> 00:22:10,964
different types
of key metabolic pathways,

500
00:22:11,031 --> 00:22:14,468
and how they reproduce and copy
their genetic information.

501
00:22:14,535 --> 00:22:16,069
And so, again,
kind of think of this

502
00:22:16,136 --> 00:22:17,671
as a lock and key mechanism.

503
00:22:17,738 --> 00:22:20,474
Different bacteria are gonna
have different strategies

504
00:22:20,541 --> 00:22:23,844
to live their lives
and be fit in their environment.

505
00:22:23,911 --> 00:22:26,513
And so, antibiotics that are
active against one bacterium

506
00:22:26,580 --> 00:22:28,282
may not be active
against another.

507
00:22:28,348 --> 00:22:32,152
So, different tools
for different jobs.

508
00:22:33,487 --> 00:22:36,456
Now, what happens
when antibiotics fail?

509
00:22:36,523 --> 00:22:40,427
This typically is thought of in
through the lens of resistance.

510
00:22:40,494 --> 00:22:43,063
Bacteria,
over the course of evolution,

511
00:22:43,130 --> 00:22:45,465
have figured out ways
to deal with antibiotics

512
00:22:45,532 --> 00:22:49,870
so that they're no longer
susceptible to them.

513
00:22:50,304 --> 00:22:53,907
This could be by using pumps
to actively remove them

514
00:22:53,974 --> 00:22:55,175
outside of the cell.

515
00:22:55,242 --> 00:22:57,177
So, they get in
and they get right back out

516
00:22:57,244 --> 00:22:58,946
before they can do their job.

517
00:22:59,012 --> 00:23:01,114
They can modify
those cellular targets

518
00:23:01,181 --> 00:23:06,420
so the antibiotics can no longer
fit the lock that they used to.

519
00:23:06,486 --> 00:23:08,856
They can get degraded
by specialized enzymes.

520
00:23:08,922 --> 00:23:13,327
So, breaking down the antibiotic
before it has a chance to act.

521
00:23:13,393 --> 00:23:16,430
They can modify their cell wall
basically to put up a fence

522
00:23:16,496 --> 00:23:19,466
so the antibiotic doesn't get in
in the first place.

523
00:23:19,533 --> 00:23:21,568
And, of course,
they can crowdsource the problem

524
00:23:21,635 --> 00:23:23,070
by talking to their neighbors

525
00:23:23,136 --> 00:23:25,906
and potentially taking
on new genetic material

526
00:23:25,973 --> 00:23:28,408
to do all these different types
of things.

527
00:23:28,475 --> 00:23:32,346
And so, evolution is
a real driving force here.

528
00:23:32,412 --> 00:23:34,748
And the way
that we use antibiotics

529
00:23:34,815 --> 00:23:37,684
contributes to the evolution
of resistance.

530
00:23:37,751 --> 00:23:41,488
So, one of the core key concepts
of bacterial evolution

531
00:23:41,555 --> 00:23:44,658
is that the more fit
will survive.

532
00:23:44,725 --> 00:23:46,293
And if we're changing
the environment

533
00:23:46,360 --> 00:23:49,930
that they live in by bombarding
them with antibiotics,

534
00:23:49,997 --> 00:23:52,866
there's a really large pressure
on these bacteria

535
00:23:52,933 --> 00:23:54,968
to evolve
in these different ways

536
00:23:55,035 --> 00:23:58,105
to circumvent
that antibiotic treatment.

537
00:23:58,172 --> 00:24:00,073
And this is
how resistance develops.

538
00:24:00,140 --> 00:24:02,709
And so, if you have
an infection,

539
00:24:02,776 --> 00:24:05,546
realize that that infection
is gonna contain many,

540
00:24:05,612 --> 00:24:08,348
many different bacteria,
not just one.

541
00:24:08,415 --> 00:24:11,084
Some of those
will be drug resistant.

542
00:24:11,151 --> 00:24:12,619
You apply an antibiotic,

543
00:24:12,686 --> 00:24:15,556
that antibiotic will kill
the ones that are susceptible,

544
00:24:15,622 --> 00:24:20,260
and the ones that are resistant
will stay alive, multiply,

545
00:24:20,327 --> 00:24:24,031
and then potentially transfer
that resistance to others.

546
00:24:24,097 --> 00:24:25,465
And so, this is a major problem.

547
00:24:25,532 --> 00:24:27,634
And mechanisms like Tiny Earth

548
00:24:27,701 --> 00:24:30,504
and some of the research
going on here at UW-Madison

549
00:24:30,571 --> 00:24:34,408
is directed at this problem
to try and find new ways

550
00:24:34,474 --> 00:24:37,144
to stay ahead of resistance.

551
00:24:39,112 --> 00:24:41,348
So, what
are the major causes here?

552
00:24:41,415 --> 00:24:44,351
One is overprescribing
of antibiotics.

553
00:24:44,418 --> 00:24:46,954
I think the United States,
Canada, and the U.K.

554
00:24:47,020 --> 00:24:48,856
have done a really good job
in their policy

555
00:24:48,922 --> 00:24:53,327
over the last 20 years
to make medical doctors aware

556
00:24:53,393 --> 00:24:58,632
and educated about antibiotic
use and in stewardship.

557
00:24:58,699 --> 00:25:01,568
However,
in many other countries,

558
00:25:01,635 --> 00:25:05,272
developed
and underdeveloped alike,

559
00:25:05,339 --> 00:25:07,307
those policies are not in place,

560
00:25:07,374 --> 00:25:09,743
meaning that prescription
of antibiotics

561
00:25:09,810 --> 00:25:12,012
or just over-the-counter use
of antibiotics

562
00:25:12,079 --> 00:25:14,414
for things that are
not bacterial infections

563
00:25:14,481 --> 00:25:16,450
still commonly occurs
in the world.

564
00:25:16,517 --> 00:25:18,819
So, for example,
I'm sure everyone here

565
00:25:18,886 --> 00:25:23,023
is familiar with having a cold
or COVID-19.

566
00:25:23,090 --> 00:25:24,725
These are viral infections.

567
00:25:24,791 --> 00:25:28,795
So, antibiotics will not be
useful against those infections.

568
00:25:28,862 --> 00:25:31,932
Yet in some countries, they're
available over the counter

569
00:25:31,999 --> 00:25:33,600
and people
are taking them anyway.

570
00:25:33,667 --> 00:25:37,004
So, this is one way
that antimicrobial resistance,

571
00:25:37,070 --> 00:25:42,176
that extra evolutionary pressure
to have this resistance rise up

572
00:25:42,242 --> 00:25:46,580
is due to taking antibiotics
when you're not supposed to.

573
00:25:46,647 --> 00:25:48,615
We also use them
quite ubiquitously

574
00:25:48,682 --> 00:25:50,951
in livestock and fish farming.

575
00:25:51,018 --> 00:25:53,554
So, I mentioned that
on an earlier slide,

576
00:25:53,620 --> 00:25:56,223
80% of the antibiotics
that are sold in the U.S.

577
00:25:56,290 --> 00:25:57,925
go right into agriculture.

578
00:25:57,991 --> 00:25:59,126
So, perhaps we can be smarter

579
00:25:59,193 --> 00:26:02,329
about use in agriculture
as well.

580
00:26:02,896 --> 00:26:04,231
And one of the major problems

581
00:26:04,298 --> 00:26:07,634
that I'm gonna highlight
for the rest of my time with you

582
00:26:07,701 --> 00:26:10,771
is the lack of new antibiotics
being developed.

583
00:26:10,838 --> 00:26:13,941
So, Sarah introduced this topic
as kind of a divestment

584
00:26:14,007 --> 00:26:16,944
in Big Pharma
because the money wasn't there.

585
00:26:17,010 --> 00:26:18,412
The economics don't work.

586
00:26:18,478 --> 00:26:21,415
If you're spending $1 billion,
$2 billion

587
00:26:21,481 --> 00:26:22,883
to get a drug developed

588
00:26:22,950 --> 00:26:26,520
and you only make half a billion
dollars back for something

589
00:26:26,587 --> 00:26:28,222
that patients are
not taking over the course

590
00:26:28,288 --> 00:26:29,623
of their lifetime.

591
00:26:29,690 --> 00:26:30,991
And so, that's where really,

592
00:26:31,058 --> 00:26:35,062
I think, academia and our
student-sourcing Tiny Earth

593
00:26:35,128 --> 00:26:40,133
can come in to really address
this goal and challenge.

594
00:26:40,634 --> 00:26:44,204
So, resistance is a major
problem both across the world

595
00:26:44,271 --> 00:26:46,306
and locally here in Wisconsin.

596
00:26:46,373 --> 00:26:48,375
In the U.S. alone,
2 million infections

597
00:26:48,442 --> 00:26:50,611
are caused by resistant bacteria

598
00:26:50,677 --> 00:26:53,914
that cost about $20 billion
every year.

599
00:26:53,981 --> 00:26:55,582
What I'm showing you here
on the bottom

600
00:26:55,649 --> 00:26:58,619
is a heat map
of resistant bacteria

601
00:26:58,685 --> 00:27:02,289
for the antibiotics
ampicillin and ciprofloxacin.

602
00:27:02,356 --> 00:27:03,724
You can see
that the hotter colors,

603
00:27:03,790 --> 00:27:05,125
the ones that are more red

604
00:27:05,192 --> 00:27:07,661
are where there's more cases
of resistance.

605
00:27:07,728 --> 00:27:09,963
The greener colors are where
our antibiotics

606
00:27:10,030 --> 00:27:11,698
are working well.

607
00:27:12,065 --> 00:27:15,135
So, in different population
densities across the state,

608
00:27:15,202 --> 00:27:18,972
as infection can spread,
you get these kind of dynamics

609
00:27:19,039 --> 00:27:21,375
that are somewhat scary.

610
00:27:21,875 --> 00:27:23,777
They require us
to find new ways

611
00:27:23,844 --> 00:27:27,114
to address
these bacterial infections.

612
00:27:27,181 --> 00:27:29,983
We are getting good at this
in some ways.

613
00:27:30,050 --> 00:27:32,786
And we still have a lot of room
to run in others.

614
00:27:32,853 --> 00:27:35,055
And so, that's what I'm
showing you here on the right.

615
00:27:35,122 --> 00:27:38,125
The green bars are
where we were at for the number

616
00:27:38,192 --> 00:27:40,460
of deaths per year in 1990.

617
00:27:40,527 --> 00:27:41,728
And the blue bars are

618
00:27:41,795 --> 00:27:45,332
where we're at
for the deaths per year in 2021.

619
00:27:45,399 --> 00:27:47,501
And as we go up the page,

620
00:27:47,568 --> 00:27:51,104
you can see the different age
groups that are being affected.

621
00:27:51,171 --> 00:27:52,739
So, early on in life,
there was,

622
00:27:52,806 --> 00:27:56,543
there used to be a major problem
with bacterial infections

623
00:27:56,610 --> 00:27:59,279
that we've basically have--

624
00:27:59,947 --> 00:28:03,016
We have 50% of the incidence
rates in deaths

625
00:28:03,083 --> 00:28:05,886
that we did
about 30 years ago.

626
00:28:06,453 --> 00:28:10,324
However, the problem is
worsening in older age groups.

627
00:28:10,390 --> 00:28:12,492
Forty years of age and up,

628
00:28:12,559 --> 00:28:15,329
you can see that the blue bars
are bigger than the green bars.

629
00:28:15,395 --> 00:28:18,966
And so, resistance is
really affecting

630
00:28:19,032 --> 00:28:23,036
these different age groups
in different ways.

631
00:28:23,103 --> 00:28:27,508
And it's estimated that by 2050,
if there's no interventions,

632
00:28:27,574 --> 00:28:29,776
one person every three seconds

633
00:28:29,843 --> 00:28:32,479
could die
from antimicrobial resistant

634
00:28:32,546 --> 00:28:35,115
or related complications.

635
00:28:35,549 --> 00:28:38,218
So, it's a very dire problem.

636
00:28:38,752 --> 00:28:43,123
I mentioned agriculture is
a big focus for antibiotics.

637
00:28:43,190 --> 00:28:45,292
And that's because
plant pathogens

638
00:28:45,359 --> 00:28:48,529
cause big economic issues
as well.

639
00:28:48,595 --> 00:28:50,497
So, 40% loss in yield

640
00:28:50,864 --> 00:28:56,603
and $220 billion annually
are the cost of plant pathogens

641
00:28:56,670 --> 00:28:58,906
that are infecting our crops.

642
00:28:58,972 --> 00:29:01,308
What I'm showing you
in the world map at the top

643
00:29:01,375 --> 00:29:05,512
is where we at for the abundance
of plant pathogens in 2020.

644
00:29:05,579 --> 00:29:07,814
And by 2050,
if nothing changes,

645
00:29:07,881 --> 00:29:10,884
we're expected to have
extremely high incidence rates

646
00:29:10,951 --> 00:29:12,619
across the globe.

647
00:29:14,054 --> 00:29:15,455
So, what do we do?

648
00:29:15,522 --> 00:29:16,924
We need to find better ways

649
00:29:16,990 --> 00:29:19,826
to use antibiotics
and practice stewardship.

650
00:29:19,893 --> 00:29:21,728
We need to discover
new antibiotics

651
00:29:21,795 --> 00:29:23,430
that work in new ways.

652
00:29:23,497 --> 00:29:25,399
And we need to develop new ways

653
00:29:25,465 --> 00:29:27,234
of thinking about treating
infections

654
00:29:27,301 --> 00:29:30,170
that are maybe
outside the box of antibiotics.

655
00:29:30,237 --> 00:29:32,573
And what I'm gonna focus
on now is what my lab does,

656
00:29:32,639 --> 00:29:33,974
which is the one in the middle.

657
00:29:34,041 --> 00:29:35,309
Discovering new antibiotics.

658
00:29:35,375 --> 00:29:39,379
Where do we go and find them
and how do we look for them?

659
00:29:39,446 --> 00:29:40,614
So, as Sarah mentioned,

660
00:29:40,681 --> 00:29:43,250
bacteria are a major source
of antibiotics.

661
00:29:43,317 --> 00:29:46,253
Nature has the
most promising routes

662
00:29:46,320 --> 00:29:48,889
for these new
antibiotic discoveries.

663
00:29:48,956 --> 00:29:51,792
Bacteria and fungi,
over millions of years,

664
00:29:51,859 --> 00:29:55,529
are evolving to live
in competitive environments.

665
00:29:55,596 --> 00:29:57,598
And so, even though
some bacteria

666
00:29:57,664 --> 00:29:58,932
and fungi cause disease,

667
00:29:58,999 --> 00:30:01,468
and that's been the topic
that I've talked about so far,

668
00:30:01,535 --> 00:30:06,874
many or most microbes are
beneficial to their hosts,

669
00:30:06,940 --> 00:30:09,042
so they live on and with humans

670
00:30:09,109 --> 00:30:11,578
and contribute to their health
on and with plants

671
00:30:11,645 --> 00:30:13,714
on and with other organisms.

672
00:30:13,780 --> 00:30:16,083
And often, they're making
their own antibiotics to compete

673
00:30:16,149 --> 00:30:19,786
with other bacteria or members
of their environment.

674
00:30:19,853 --> 00:30:21,755
So, that gives them
a survival advantage.

675
00:30:21,822 --> 00:30:23,924
And we can study
how they make them,

676
00:30:23,991 --> 00:30:26,560
what they're making,
and maybe get some inspiration

677
00:30:26,627 --> 00:30:27,761
to bring into medicine

678
00:30:27,828 --> 00:30:30,831
and crop management
practices.

679
00:30:31,098 --> 00:30:34,101
And so, interactions
between species

680
00:30:34,168 --> 00:30:36,837
are really shaping all
of the diversity of life

681
00:30:36,904 --> 00:30:38,539
that we see across the planet.

682
00:30:38,605 --> 00:30:41,742
And so, this is pretty obvious,
I think, at the macro scale.

683
00:30:41,808 --> 00:30:44,845
You can have predator-prey
dynamics.

684
00:30:44,912 --> 00:30:46,880
You can have, you know,
different fish

685
00:30:46,947 --> 00:30:48,415
and their schooling behavior

686
00:30:48,482 --> 00:30:52,019
and how that's contributing
to their fitness as a species.

687
00:30:52,085 --> 00:30:54,221
We farm crops for food.

688
00:30:54,521 --> 00:30:57,224
Ants also farm crops for food.

689
00:30:57,291 --> 00:30:59,393
And, you know,
the intricate interactions

690
00:30:59,459 --> 00:31:03,864
between insects and pollen
and how they pollinate plants

691
00:31:03,931 --> 00:31:05,666
also contributes to all
of this lifestyle.

692
00:31:05,732 --> 00:31:07,668
This is something that
I think we're very familiar with

693
00:31:07,734 --> 00:31:10,470
because we can see
that at the macro level.

694
00:31:10,537 --> 00:31:12,105
But at the micro level,

695
00:31:12,172 --> 00:31:14,041
all of this
is happening in large part

696
00:31:14,107 --> 00:31:15,642
due to their chemistry.

697
00:31:15,709 --> 00:31:17,244
And the way
that they're interacting

698
00:31:17,311 --> 00:31:20,214
with their environment,
competing with others,

699
00:31:20,280 --> 00:31:22,783
signaling to others
is through their chemistry.

700
00:31:22,850 --> 00:31:24,518
And it's very, very diverse.

701
00:31:24,585 --> 00:31:26,320
So, I don't mean for you
to take home

702
00:31:26,386 --> 00:31:27,754
all of these structures
and memorize them.

703
00:31:27,821 --> 00:31:30,924
I just want to impress upon you
that it's very,

704
00:31:30,991 --> 00:31:33,760
very different
across the tree of life.

705
00:31:33,827 --> 00:31:37,431
And there's a lot
of capacity for new molecules.

706
00:31:37,497 --> 00:31:39,366
All of these molecules
have functions

707
00:31:39,433 --> 00:31:41,001
in their natural environment.

708
00:31:41,068 --> 00:31:43,203
And some of the things
I have listed on the left

709
00:31:43,270 --> 00:31:45,405
are how we've
kind of co-opted these molecules

710
00:31:45,472 --> 00:31:47,174
and used them
for human purposes.

711
00:31:47,241 --> 00:31:50,844
So, either as antibacterials,
antifungals,

712
00:31:50,911 --> 00:31:54,281
or manipulating
host-microbe interactions.

713
00:31:54,348 --> 00:31:56,817
This is where most
of our drugs come from.

714
00:31:56,884 --> 00:31:59,086
So, on the left,
I'm showing you a pie chart

715
00:31:59,152 --> 00:32:01,989
where all of the colors
are antibiotic

716
00:32:02,055 --> 00:32:04,925
or anticancer drugs
approved by the FDA

717
00:32:04,992 --> 00:32:07,628
that have been either
directly sourced from nature

718
00:32:07,694 --> 00:32:11,131
or inspired by these
bacterially-produced compounds.

719
00:32:11,198 --> 00:32:13,033
And on the right,

720
00:32:13,100 --> 00:32:15,335
what I'm showing you are
the very important

721
00:32:15,402 --> 00:32:17,271
key access antibiotics

722
00:32:17,337 --> 00:32:19,306
that the World Health
Organization holds

723
00:32:19,373 --> 00:32:21,175
in the highest regard.

724
00:32:21,241 --> 00:32:23,710
These are largely
from nature or nature derived.

725
00:32:23,777 --> 00:32:26,847
Very few of them are
thought up by chemists in a lab

726
00:32:26,914 --> 00:32:29,383
and are purely synthetic.

727
00:32:29,883 --> 00:32:32,019
So, where have we looked
for new antibiotics?

728
00:32:32,085 --> 00:32:33,453
Sarah introduced this well.

729
00:32:33,520 --> 00:32:35,455
We can start in soil,

730
00:32:35,522 --> 00:32:38,325
isolate bacteria,
screen them for activity.

731
00:32:38,392 --> 00:32:39,860
Who's killing who?

732
00:32:39,927 --> 00:32:42,296
And then, hopefully,
we make a discovery.

733
00:32:42,362 --> 00:32:44,865
And this has been
relatively successful.

734
00:32:44,932 --> 00:32:47,734
So, since that 1928 discovery
of penicillin,

735
00:32:47,801 --> 00:32:49,469
there have been many,
many new classes

736
00:32:49,536 --> 00:32:52,139
of antibiotics discovered
where kind of the heyday,

737
00:32:52,206 --> 00:32:56,643
the golden age of which
was between 1940 and 1960.

738
00:32:56,710 --> 00:33:00,147
Streptomycin
was discovered in 1943,

739
00:33:00,214 --> 00:33:02,649
and as soon
as that was used in the clinic

740
00:33:02,716 --> 00:33:07,554
to treat tuberculosis,
mortality decreased by over 85%.

741
00:33:07,621 --> 00:33:10,224
Before streptomycin
was discovered,

742
00:33:10,290 --> 00:33:12,459
people that were suffering
from tuberculosis

743
00:33:12,526 --> 00:33:14,895
had their beds moved out of the
hospital and onto the street,

744
00:33:14,962 --> 00:33:17,731
because the standard of care
was for them to get fresh air.

745
00:33:17,798 --> 00:33:23,170
That was the only way that this
infectious disease was treated.

746
00:33:23,237 --> 00:33:24,938
But introduced streptomycin,

747
00:33:25,005 --> 00:33:29,977
and 85% mortality decrease
within just 20 years.

748
00:33:31,712 --> 00:33:33,380
But recently,

749
00:33:33,714 --> 00:33:37,985
we've been kind of striking out
in finding new antibiotics.

750
00:33:38,051 --> 00:33:40,053
Like I mentioned, 1940 to 1960,

751
00:33:40,120 --> 00:33:42,990
where we were getting a lot
of success looking in soil

752
00:33:43,056 --> 00:33:44,625
in the bacteria
that are found there

753
00:33:44,691 --> 00:33:46,159
and seeing what they
could produce.

754
00:33:46,226 --> 00:33:48,228
But since about 1987,

755
00:33:48,595 --> 00:33:50,631
there has been a void
in discovery

756
00:33:50,697 --> 00:33:53,300
of new classes of antibiotics.

757
00:33:53,367 --> 00:33:58,105
And that's largely in part due
to the problem of rediscovery.

758
00:33:58,172 --> 00:34:01,775
So, when you do these kind
of isolations of bacteria

759
00:34:01,842 --> 00:34:03,177
and looking for activity,

760
00:34:03,243 --> 00:34:06,780
you can find streptomycin
over and over and over again.

761
00:34:06,847 --> 00:34:08,715
So, one of the strategies
that our lab

762
00:34:08,782 --> 00:34:10,250
and what Tiny Earth is doing

763
00:34:10,317 --> 00:34:12,586
is to try and be smarter about
where we're looking

764
00:34:12,653 --> 00:34:14,922
for these antibiotics.

765
00:34:14,988 --> 00:34:17,491
What are the different types
of bacteria that we can exploit,

766
00:34:17,558 --> 00:34:18,992
or the different types
of environments

767
00:34:19,059 --> 00:34:21,562
where we haven't looked
in the past?

768
00:34:21,628 --> 00:34:23,964
So, my lab tackles this
not through soil,

769
00:34:24,031 --> 00:34:26,300
but looking
at host-microbe interactions

770
00:34:26,366 --> 00:34:28,001
and the microbiome.

771
00:34:28,068 --> 00:34:32,539
In particular, microbiomes
that are associated with hosts

772
00:34:32,606 --> 00:34:34,408
that have to deal with disease.

773
00:34:34,474 --> 00:34:36,443
So, plants and crops,
we already talked about,

774
00:34:36,510 --> 00:34:39,880
they have to fight off
infectious disease all the time.

775
00:34:39,947 --> 00:34:41,982
They're microbes that are
either in the soil

776
00:34:42,049 --> 00:34:44,785
or on their leaves are helping
fight off that infection.

777
00:34:44,852 --> 00:34:47,020
And so, we're taking
that kind of discovery approach

778
00:34:47,087 --> 00:34:49,656
to see what type of molecules
they're producing.

779
00:34:49,723 --> 00:34:53,393
And maybe we can use those
to develop new antibiotics.

780
00:34:53,460 --> 00:34:55,028
Frogs, salamanders and snakes

781
00:34:55,095 --> 00:34:56,864
are also a major focus
of our lab.

782
00:34:56,930 --> 00:34:58,932
So, looking for frogs

783
00:35:00,033 --> 00:35:02,369
and salamanders
out in the environment,

784
00:35:02,436 --> 00:35:04,438
swabbing them
for their bacteria,

785
00:35:04,505 --> 00:35:05,873
and seeing
what kind of chemistry

786
00:35:05,939 --> 00:35:09,877
that bacteria might provide
to help combat

787
00:35:09,943 --> 00:35:13,247
against their
infectious diseases.

788
00:35:13,313 --> 00:35:15,249
So, we integrate new methods
in this too.

789
00:35:15,315 --> 00:35:19,386
Getting this big culture
collections from various hosts,

790
00:35:19,453 --> 00:35:22,256
diverse hosts, seeing
how these bacteria interact,

791
00:35:22,322 --> 00:35:23,590
who's killing who,

792
00:35:23,657 --> 00:35:26,360
and then bringing
in some kind of new technologies

793
00:35:26,426 --> 00:35:29,363
like transcriptomics,
genomics, and metabolomics

794
00:35:29,429 --> 00:35:32,699
to make this a high throughput
discovery exercise.

795
00:35:32,766 --> 00:35:35,569
Sarah impressed upon you
the massive numbers

796
00:35:35,636 --> 00:35:40,107
of Tiny Earth students that are
taking the course every year.

797
00:35:40,174 --> 00:35:43,277
That, to be able to screen
all of the isolates

798
00:35:43,343 --> 00:35:45,779
from all of those students
would be impossible

799
00:35:45,846 --> 00:35:47,514
without these
high throughput methods.

800
00:35:47,581 --> 00:35:49,249
So, we're both actively involved
in running them,

801
00:35:49,316 --> 00:35:52,119
but also developing new ones.

802
00:35:52,686 --> 00:35:54,721
And yeah, new methods
lead to new discoveries.

803
00:35:54,788 --> 00:35:56,123
So, this involves integrating

804
00:35:56,190 --> 00:35:59,493
all different types of genomic
and metabolomic information.

805
00:35:59,560 --> 00:36:01,762
Also screening them
against organisms

806
00:36:01,828 --> 00:36:03,730
that we haven't tried
to kill before.

807
00:36:03,797 --> 00:36:07,734
<i>Acinetobacter baumannii</i>
is a major priority

808
00:36:07,801 --> 00:36:12,172
of the U.S. Army right now,
because infections that

809
00:36:12,239 --> 00:36:13,874
are getting picked up
by soldiers

810
00:36:13,941 --> 00:36:15,976
in the battlefield
tend to be resistant

811
00:36:16,043 --> 00:36:17,778
if they're caused
by this organism.

812
00:36:17,845 --> 00:36:19,680
And we only really knew about
this organism

813
00:36:19,746 --> 00:36:21,882
in around 1990 to 1995.

814
00:36:22,816 --> 00:36:24,985
So, it was not part
of the screening methods

815
00:36:25,052 --> 00:36:28,488
from Big Pharma that were
pretty much over by 1980.

816
00:36:28,555 --> 00:36:29,723
So, looking in new places,

817
00:36:29,790 --> 00:36:32,526
but also screening
for new targets.

818
00:36:32,593 --> 00:36:35,429
Integrating all these different
high throughput data sets

819
00:36:35,495 --> 00:36:36,730
can be very challenging.

820
00:36:36,797 --> 00:36:39,333
And so, one of the things
that our lab is doing as well

821
00:36:39,399 --> 00:36:40,801
is trying to integrate
machine learning

822
00:36:40,868 --> 00:36:43,570
and artificial intelligence
to make sense of all this data,

823
00:36:43,637 --> 00:36:46,673
to point us towards
the new antibiotics.

824
00:36:46,740 --> 00:36:47,875
So, these are the
major challenges

825
00:36:47,941 --> 00:36:49,409
that we're going after.

826
00:36:49,476 --> 00:36:52,212
Finding new
and useful molecules

827
00:36:52,279 --> 00:36:56,049
and using high throughput
and new school omics methods

828
00:36:56,116 --> 00:36:58,986
to try and mine that chemistry.

829
00:36:59,052 --> 00:37:01,588
Getting the bacteria
that make these molecules

830
00:37:01,655 --> 00:37:04,224
to actually produce them can be
a major challenge as well,

831
00:37:04,291 --> 00:37:06,960
because most bacterial
chemistry is going to be

832
00:37:07,027 --> 00:37:08,962
not produced
under lab conditions.

833
00:37:09,029 --> 00:37:11,064
They're used to being
living out in nature

834
00:37:11,131 --> 00:37:12,466
in very different environments.

835
00:37:12,533 --> 00:37:13,867
When we bring them into the lab,

836
00:37:13,934 --> 00:37:15,869
sometimes they don't behave
in the same way.

837
00:37:15,936 --> 00:37:19,039
And so, synthetic biology
and high-throughput elicitation

838
00:37:19,106 --> 00:37:21,575
is a major focus of our group
as well.

839
00:37:21,642 --> 00:37:23,377
And then, of course,
we don't really know much

840
00:37:23,443 --> 00:37:26,480
about what antibiotics
are actually doing in nature.

841
00:37:26,547 --> 00:37:28,615
And if we did,
then we might be smarter about

842
00:37:28,682 --> 00:37:30,284
where to look for the next ones.

843
00:37:30,350 --> 00:37:32,152
So, understanding
these ecological roles

844
00:37:32,219 --> 00:37:33,687
is a major frontier
that our lab

845
00:37:33,754 --> 00:37:37,558
is very interested
in studying further.

846
00:37:37,991 --> 00:37:39,526
And so, just to wrap up,

847
00:37:39,593 --> 00:37:43,330
antibiotics are the cornerstone
of modern medicine

848
00:37:43,397 --> 00:37:46,466
and our major defense against
bacterial and fungal diseases,

849
00:37:46,533 --> 00:37:48,135
not just for our diseases,

850
00:37:48,202 --> 00:37:52,139
but the diseases that affect us
through the food chain.

851
00:37:52,206 --> 00:37:54,908
So, the diseases
of our crops as well.

852
00:37:54,975 --> 00:37:57,177
Most antibiotics
that we know about

853
00:37:57,244 --> 00:38:00,280
are made by bacteria and fungi
themselves.

854
00:38:00,347 --> 00:38:04,084
And resistance is a major threat
to their effectiveness.

855
00:38:04,151 --> 00:38:07,120
So, both in my lab and
at research across the globe,

856
00:38:07,187 --> 00:38:08,555
we're aimed at developing
new strategies

857
00:38:08,622 --> 00:38:09,957
for combating this resistance

858
00:38:10,023 --> 00:38:13,894
and to find new antibiotics
that work in new ways.

859
00:38:13,961 --> 00:38:16,630
And with that, I just
want to acknowledge my team.

860
00:38:16,697 --> 00:38:17,998
Some of them are pictured here.

861
00:38:18,065 --> 00:38:19,333
Others are not.

862
00:38:19,399 --> 00:38:21,301
We need to take
a new picture soon.

863
00:38:21,368 --> 00:38:24,071
And then, our funding sources
at the bottom.

864
00:38:24,137 --> 00:38:25,906
And thank you
for your attention.

865
00:38:25,973 --> 00:38:27,975
[audience applauds]

866
00:38:30,978 --> 00:38:34,515
So, Sarah, I'll invite you up
and we can have a conversation.

867
00:38:34,581 --> 00:38:37,918
- Sarah: A little chat.
- Marc: Yeah.

868
00:38:43,624 --> 00:38:45,859
- Sarah: All right,
thanks, Marc.

869
00:38:45,926 --> 00:38:47,027
- Marc: Yeah.
[Sarah chuckles]

870
00:38:47,094 --> 00:38:48,662
- I always learn something
from you.

871
00:38:48,729 --> 00:38:52,032
So, let's start with soil.
- Marc: Okay.

872
00:38:52,099 --> 00:38:55,035
- Sarah: What makes soil
such a powerful place

873
00:38:55,102 --> 00:38:57,905
to look for new antibiotics?

874
00:38:57,971 --> 00:39:00,407
- Marc:
Well, it's all comes back

875
00:39:00,474 --> 00:39:02,976
to the microbes that are there.

876
00:39:03,043 --> 00:39:05,846
And so, both soil and seawater

877
00:39:07,147 --> 00:39:08,782
are the two
most diverse environments

878
00:39:08,849 --> 00:39:10,050
that we know about on Earth

879
00:39:10,117 --> 00:39:12,686
in terms of the different types
of bacteria

880
00:39:12,753 --> 00:39:14,588
and fungi
that you might find there.

881
00:39:14,655 --> 00:39:18,559
And so, the more diverse
a environment is,

882
00:39:18,625 --> 00:39:20,994
the more diverse its
interactions are gonna be.

883
00:39:21,061 --> 00:39:22,996
And like I mentioned
in the talk,

884
00:39:23,063 --> 00:39:25,265
those interactions
are largely driven by chemistry.

885
00:39:25,332 --> 00:39:27,467
So, if we wanna find new
and exciting things

886
00:39:27,534 --> 00:39:30,737
that have activity against stuff
that humans are interested in,

887
00:39:30,804 --> 00:39:32,406
it follows that you wanna look

888
00:39:32,472 --> 00:39:34,274
in the most diverse places
on Earth.

889
00:39:34,341 --> 00:39:36,910
And so, soil has been
extremely fruitful in the past.

890
00:39:36,977 --> 00:39:38,912
I would-- I don't have
an exact number for you,

891
00:39:38,979 --> 00:39:41,949
but I'd say probably
around three quarters of all

892
00:39:42,015 --> 00:39:44,151
of the antibiotics
that we use right now

893
00:39:44,218 --> 00:39:45,485
are not just from bacteria,

894
00:39:45,552 --> 00:39:47,054
but bacteria that are
from the soil.

895
00:39:47,120 --> 00:39:48,222
- Sarah: Yeah.

896
00:39:48,288 --> 00:39:49,623
- Marc:
So, that's the major source.

897
00:39:49,690 --> 00:39:52,059
- Yeah, let's talk a little
about those conversations,

898
00:39:52,125 --> 00:39:55,729
those chemical conversations
that bacteria are having.

899
00:39:55,796 --> 00:39:58,532
How can understanding
<i>those</i> interactions

900
00:39:58,599 --> 00:40:01,502
help us discover
new medicines like antibiotics?

901
00:40:01,568 --> 00:40:02,836
- Mm-hmm.

902
00:40:02,903 --> 00:40:05,873
Well, I think one of the things

903
00:40:05,939 --> 00:40:11,111
to keep in mind there is that
medicine is a very human topic,

904
00:40:11,178 --> 00:40:13,447
a very human-centric way
of thinking.

905
00:40:13,514 --> 00:40:16,016
And the bacteria
and other microbes

906
00:40:16,083 --> 00:40:18,852
that are making antibiotics
in the soil,

907
00:40:18,919 --> 00:40:22,055
for example, may not
be using them in the same ways,

908
00:40:22,122 --> 00:40:25,325
and maybe almost surely
not the same concentrations

909
00:40:25,392 --> 00:40:29,062
that we use them
when we try and combat disease.

910
00:40:29,129 --> 00:40:33,834
So, if we can better
understand what these molecules

911
00:40:33,901 --> 00:40:37,304
are actually being used for
in their natural environments,

912
00:40:37,371 --> 00:40:39,072
then we can take
those principles

913
00:40:39,139 --> 00:40:43,043
and apply them forward
to finding new ones.

914
00:40:43,110 --> 00:40:44,778
Yeah, so in terms of,

915
00:40:44,845 --> 00:40:47,181
in terms of medicine,
I think it's helpful

916
00:40:47,247 --> 00:40:49,650
to separate
those two ways of thinking.

917
00:40:49,716 --> 00:40:52,753
It's us kind of stealing
the ideas of bacteria

918
00:40:52,819 --> 00:40:55,155
and really applying them
for human problems.

919
00:40:55,222 --> 00:40:58,926
But how they're evolving
and found naturally distributed

920
00:40:58,992 --> 00:41:00,227
is a very different context.

921
00:41:00,294 --> 00:41:02,029
- Sarah: Mm-hmm.

922
00:41:02,095 --> 00:41:04,097
So, it sounds like...

923
00:41:06,366 --> 00:41:08,135
...this type of research
really requires

924
00:41:08,202 --> 00:41:10,504
interdisciplinary thinking,
right?

925
00:41:10,571 --> 00:41:13,106
I know you in particular draw
on multiple disciplines.

926
00:41:13,173 --> 00:41:14,842
I do as well.

927
00:41:15,442 --> 00:41:17,945
How important is that kind
of interdisciplinary thinking

928
00:41:18,011 --> 00:41:19,947
when we're addressing
antimicrobial resistance?

929
00:41:20,013 --> 00:41:22,049
And what types of skills

930
00:41:22,115 --> 00:41:24,885
would you say the next
generation of scientists

931
00:41:24,952 --> 00:41:28,622
needs to be honing now
in order to be helping us

932
00:41:28,689 --> 00:41:31,825
to solve the antibiotic
resistance crisis

933
00:41:31,892 --> 00:41:33,060
or keep ahead of it?

934
00:41:33,126 --> 00:41:34,561
- Yeah.

935
00:41:34,628 --> 00:41:37,564
I'd say it's not just important,
but it's necessary.

936
00:41:37,631 --> 00:41:40,467
I think inherent
to this problem of resistance

937
00:41:40,534 --> 00:41:43,971
is approaches
that come from different angles

938
00:41:44,037 --> 00:41:46,340
that complement
each other really well.

939
00:41:46,406 --> 00:41:48,809
And so, we're definitely
in the information

940
00:41:48,876 --> 00:41:50,644
and omics era right now.

941
00:41:50,711 --> 00:41:52,546
And to be able to understand

942
00:41:52,613 --> 00:41:55,782
and utilize the crazy amounts
of information

943
00:41:55,849 --> 00:41:59,219
that we're generating
about resistance rates,

944
00:41:59,286 --> 00:42:01,154
about the mechanisms
of resistance,

945
00:42:01,221 --> 00:42:03,524
that requires people
to be very well trained

946
00:42:03,590 --> 00:42:04,925
in the data sciences.

947
00:42:04,992 --> 00:42:06,727
It also requires
people to be trained

948
00:42:06,793 --> 00:42:08,161
in the basic biology

949
00:42:08,228 --> 00:42:10,197
and microbiology
of these organisms,

950
00:42:10,264 --> 00:42:12,065
to really understand
the mechanisms

951
00:42:12,132 --> 00:42:13,967
through which
antibiotics are working

952
00:42:14,034 --> 00:42:17,104
or not working in the case
of resistance.

953
00:42:17,171 --> 00:42:19,640
And there's a huge gray area
in between

954
00:42:19,706 --> 00:42:24,278
with newly evolving fields that
weren't there five years ago.

955
00:42:24,344 --> 00:42:25,746
So, I'm thinking in particular

956
00:42:25,812 --> 00:42:28,782
about the recent advances
of genomics and metabolomics

957
00:42:28,849 --> 00:42:30,484
that, you know,
just 20 years ago

958
00:42:30,551 --> 00:42:31,685
would have been a pipe dream

959
00:42:31,752 --> 00:42:33,453
to generate the data
that we have now.

960
00:42:33,520 --> 00:42:35,322
Now it's relatively commonplace,

961
00:42:35,389 --> 00:42:37,558
and the challenge is making
sense of all that data.

962
00:42:37,624 --> 00:42:39,960
- Sarah: Yeah.
- So that's where I would put--

963
00:42:40,027 --> 00:42:41,995
I would point
the next generation

964
00:42:42,062 --> 00:42:46,400
of scientists to is, you know,
really trying to find a way

965
00:42:46,466 --> 00:42:49,736
to integrate new methods in ways

966
00:42:49,803 --> 00:42:52,639
that doesn't pigeonhole you
into one discipline or another,

967
00:42:52,706 --> 00:42:54,675
because it's reaching
across disciplines

968
00:42:54,741 --> 00:42:58,278
that, I think, is where the hard
problems in biology are going,

969
00:42:58,345 --> 00:43:00,647
which antimicrobial resistance
is one of them.

970
00:43:00,714 --> 00:43:02,049
- Sarah: Absolutely.

971
00:43:02,115 --> 00:43:03,317
Let's shift gears a little bit

972
00:43:03,383 --> 00:43:05,752
to policy, stewardship,
things like that.

973
00:43:05,819 --> 00:43:09,890
So, what role do systems
like health care,

974
00:43:09,957 --> 00:43:13,694
agriculture, policy play
in protecting the antibiotics

975
00:43:13,760 --> 00:43:15,195
that we already have?

976
00:43:15,262 --> 00:43:17,865
- Mm-hmm, yeah,
and I think, you know,

977
00:43:17,931 --> 00:43:21,101
something that you brought up
in your portion of the talk

978
00:43:21,168 --> 00:43:24,271
makes sense
to bring up again here in that,

979
00:43:24,338 --> 00:43:28,809
you know, if you are taking a
successful round of antibiotics,

980
00:43:28,876 --> 00:43:30,577
it's not a lifelong endeavor.

981
00:43:30,644 --> 00:43:33,313
It's going to be a week
or a couple of weeks.

982
00:43:33,380 --> 00:43:35,482
And so, because of that,

983
00:43:35,549 --> 00:43:39,019
I think we need to expand
and keep safe

984
00:43:40,087 --> 00:43:42,022
the medicine cabinet
that we can reach for.

985
00:43:42,089 --> 00:43:45,893
- Sarah: Mm-hmm.
- So, that has two angles to it.

986
00:43:45,959 --> 00:43:49,630
One is finding new antibiotics,
which was not your question,

987
00:43:49,696 --> 00:43:51,231
but I think it's very important.

988
00:43:51,298 --> 00:43:53,200
And the second is deploying them
in ways

989
00:43:53,267 --> 00:43:54,535
that are rational and smart

990
00:43:54,601 --> 00:43:57,104
so that we don't encourage
resistance.

991
00:43:57,171 --> 00:44:01,208
I mentioned the United Kingdom,
Canada, and the U.S.

992
00:44:01,275 --> 00:44:04,478
during my talk as being
kind of the global leaders

993
00:44:04,545 --> 00:44:08,682
in shaping policy around
proper use of antibiotics,

994
00:44:08,749 --> 00:44:10,284
but there's still a long way
to go.

995
00:44:10,350 --> 00:44:12,319
And I don't mean that
just globally,

996
00:44:12,386 --> 00:44:14,721
I mean within the United States
as well.

997
00:44:14,788 --> 00:44:17,558
So, this takes place
at many different levels.

998
00:44:17,624 --> 00:44:19,159
It's at the level of policy.

999
00:44:19,226 --> 00:44:22,329
It's at the level of insurance
companies and best practices.

1000
00:44:22,396 --> 00:44:26,567
And it's at the level of
patient-doctor relationships

1001
00:44:26,633 --> 00:44:29,102
and how they're actually

1002
00:44:29,169 --> 00:44:33,307
understanding what diseases
might be treated with what.

1003
00:44:33,373 --> 00:44:37,244
- So, is, so public awareness is
playing a role in this as well.

1004
00:44:37,311 --> 00:44:39,947
- Yeah, and I think I'll call
out Canada in particular

1005
00:44:40,013 --> 00:44:41,782
of taking a really firm stance
on this

1006
00:44:41,849 --> 00:44:45,452
and training all of their MDs
with cutting-edge science

1007
00:44:45,519 --> 00:44:48,088
that is recently peer reviewed

1008
00:44:48,155 --> 00:44:51,158
that they may not have gotten
20, 30, 40 years ago

1009
00:44:51,225 --> 00:44:53,293
when they were
in medical school.

1010
00:44:53,360 --> 00:44:55,896
And so, I think the rest
of the world is catching up.

1011
00:44:55,963 --> 00:44:59,566
The U.S. definitely has a little
bit of progress to go

1012
00:44:59,633 --> 00:45:02,736
before we reach the level
of Canada and the U.K.,

1013
00:45:02,803 --> 00:45:04,171
but we can see that these

1014
00:45:04,238 --> 00:45:06,373
stewardship practices
actually work.

1015
00:45:06,440 --> 00:45:09,510
So, the rates of infection
for places

1016
00:45:09,576 --> 00:45:11,912
that have these kind
of principles in place

1017
00:45:11,979 --> 00:45:14,615
versus those that don't are
very drastically different.

1018
00:45:14,681 --> 00:45:16,049
- Sarah: Mm-hmm.

1019
00:45:16,116 --> 00:45:17,484
- And so, so yeah,

1020
00:45:17,551 --> 00:45:21,054
I think it's more of a public
awareness issue at all levels.

1021
00:45:21,121 --> 00:45:23,423
So, not just the general public,

1022
00:45:23,490 --> 00:45:26,760
but those that are going to be
making these policies,

1023
00:45:26,827 --> 00:45:28,262
those that are in politics.

1024
00:45:28,328 --> 00:45:31,698
- Yep, yeah, one of the things
I didn't mention in my talk,

1025
00:45:31,765 --> 00:45:34,835
I mentioned the symposium
that we do in Green Bay, here,

1026
00:45:34,902 --> 00:45:36,970
and other institutions
do them too.

1027
00:45:37,037 --> 00:45:39,606
We also have our students
doing social media campaigns,

1028
00:45:39,673 --> 00:45:42,943
for example, during World
Antibiotic Awareness Week

1029
00:45:43,010 --> 00:45:46,046
to help get the message out
with the tools

1030
00:45:46,113 --> 00:45:47,247
and the concepts
that they've learned

1031
00:45:47,314 --> 00:45:50,651
in the Tiny Earth curriculum,
yeah.

1032
00:45:51,051 --> 00:45:53,387
Well, since the theme here
is productive failure,

1033
00:45:53,453 --> 00:45:57,858
how about we talk about
the role of failure in science

1034
00:45:57,925 --> 00:46:00,794
as something that helps us
to advance discoveries,

1035
00:46:00,861 --> 00:46:03,597
but also in terms
of the next generation learning

1036
00:46:03,664 --> 00:46:05,999
how to fail productively.
- Sure.

1037
00:46:06,066 --> 00:46:07,668
- Yeah,
what are your thoughts on that?

1038
00:46:07,734 --> 00:46:09,536
- Well,
it's an interesting phrasing

1039
00:46:09,603 --> 00:46:12,940
because I think
failure is science.

1040
00:46:14,107 --> 00:46:16,176
So, like, the scientific method

1041
00:46:16,243 --> 00:46:19,546
and the way that we approach
designing experiments

1042
00:46:19,613 --> 00:46:20,814
is you have an idea,

1043
00:46:20,881 --> 00:46:22,216
you think you know
how it works,

1044
00:46:22,282 --> 00:46:23,684
but you're not really sure.

1045
00:46:23,750 --> 00:46:27,754
And then, you try your damndest
to disprove that idea, right?

1046
00:46:27,821 --> 00:46:32,125
And so, failure or being wrong
about your hypothesis

1047
00:46:32,192 --> 00:46:35,229
is inherent
to the scientific process.

1048
00:46:35,295 --> 00:46:36,864
I guess another way
to interpret failure

1049
00:46:36,930 --> 00:46:40,400
is, you know, unexpected results
or something that you didn't,

1050
00:46:40,467 --> 00:46:42,135
you weren't necessarily
looking for.

1051
00:46:42,202 --> 00:46:44,004
But it's difficult to explain

1052
00:46:44,071 --> 00:46:46,673
and you're not sure yet
how it works.

1053
00:46:46,740 --> 00:46:48,775
For me, I see that
as extremely exciting.

1054
00:46:48,842 --> 00:46:51,311
And that's where
the frontiers of science are.

1055
00:46:51,378 --> 00:46:52,813
If you don't know
how something works,

1056
00:46:52,880 --> 00:46:54,047
then it's our job as scientists

1057
00:46:54,114 --> 00:46:55,749
to try and figure out
how it works,

1058
00:46:55,816 --> 00:46:58,719
even if we were wrong
about that initial guess.

1059
00:46:58,785 --> 00:47:01,021
- So, are you optimistic
that we can stay ahead

1060
00:47:01,088 --> 00:47:02,456
of antimicrobial resistance,

1061
00:47:02,523 --> 00:47:04,758
and what breakthroughs
or discoveries would make

1062
00:47:04,825 --> 00:47:07,261
the biggest difference
in the next decade or two?

1063
00:47:07,327 --> 00:47:08,762
- So, I'm very optimistic.

1064
00:47:08,829 --> 00:47:10,597
I think, over the last 20 years,

1065
00:47:10,664 --> 00:47:13,867
we've really accelerated the
development of new technologies

1066
00:47:13,934 --> 00:47:15,669
that are just
in the last five years

1067
00:47:15,736 --> 00:47:17,437
now getting implemented
for this problem

1068
00:47:17,504 --> 00:47:19,439
of antimicrobial resistance.

1069
00:47:19,506 --> 00:47:21,308
And so, we're kind of, I think,

1070
00:47:21,375 --> 00:47:24,578
at a, not a golden age
of antibiotic discovery,

1071
00:47:24,645 --> 00:47:26,947
but a golden age
of data integration.

1072
00:47:27,014 --> 00:47:30,584
And so, you know, all
of the different breakthroughs

1073
00:47:30,651 --> 00:47:32,186
to generate lots of data,

1074
00:47:32,252 --> 00:47:34,621
but also using artificial
intelligence to make sense

1075
00:47:34,688 --> 00:47:36,423
of all of that data,

1076
00:47:36,490 --> 00:47:38,258
we're really at the cusp
of right now.

1077
00:47:38,325 --> 00:47:39,860
And so, that's, you know,

1078
00:47:39,927 --> 00:47:43,263
continued funding and
breakthroughs in those areas,

1079
00:47:43,330 --> 00:47:44,665
I think,
are where the major discoveries

1080
00:47:44,731 --> 00:47:45,933
are gonna come from.

1081
00:47:45,999 --> 00:47:48,202
- Right, very exciting.

1082
00:47:48,268 --> 00:47:50,737
Do you have any suggestions
for our audience members

1083
00:47:50,804 --> 00:47:53,273
about what further reading
they might do

1084
00:47:53,340 --> 00:47:57,377
and popular science
to explore this topic further?

1085
00:47:57,444 --> 00:47:59,112
- Sure.

1086
00:48:00,180 --> 00:48:01,849
Let's see.

1087
00:48:02,716 --> 00:48:05,385
So, one that comes to mind
immediately

1088
00:48:05,452 --> 00:48:07,788
is a book called <i>Plucked,</i>

1089
00:48:09,389 --> 00:48:14,595
which is a nonfiction account
of antibiotic use and misuse

1090
00:48:14,661 --> 00:48:17,564
in the poultry, food industry.

1091
00:48:19,666 --> 00:48:21,702
It's a really interesting story
that

1092
00:48:21,768 --> 00:48:26,340
kind of layers in the topics
that you had just brought up.

1093
00:48:26,406 --> 00:48:28,609
And so, how-- What is
the role of policy makers?

1094
00:48:28,675 --> 00:48:31,445
What is the role
of the different stakeholders?

1095
00:48:31,512 --> 00:48:33,514
What is the role of the public?

1096
00:48:33,580 --> 00:48:35,315
And so, that's one
that kind of brings that

1097
00:48:35,382 --> 00:48:38,619
agricultural,
livestock focus into it.

1098
00:48:38,685 --> 00:48:40,120
I think another
that I would recommend

1099
00:48:40,187 --> 00:48:43,190
is <i>Everything is Tuberculosis.</i>

1100
00:48:43,257 --> 00:48:46,627
So, that's a book that kind of
takes the perspective

1101
00:48:46,693 --> 00:48:49,596
of a bacterial-centric view
of the world

1102
00:48:49,663 --> 00:48:51,398
that I think is really useful
to think of

1103
00:48:51,465 --> 00:48:53,433
when we're trying
to solve problems at that scale.

1104
00:48:53,500 --> 00:48:55,068
- Sarah: Yeah, yeah, one--

1105
00:48:55,135 --> 00:48:56,770
I know one
that I've read is called

1106
00:48:56,837 --> 00:49:00,774
<i>Perfect Predator</i>
by Steffanie Strathdee,

1107
00:49:00,841 --> 00:49:04,344
I think, and that one is
the story of an infection

1108
00:49:04,411 --> 00:49:07,347
her husband got,
<i>Acinetobacter,</i>

1109
00:49:07,414 --> 00:49:10,851
that was resistant
to every drug we have.

1110
00:49:10,918 --> 00:49:13,053
And I think it's
an interesting example

1111
00:49:13,120 --> 00:49:15,889
of when they started to look
at alternative therapies,

1112
00:49:15,956 --> 00:49:18,525
in particular, they were looking
at what's called phage therapy,

1113
00:49:18,592 --> 00:49:22,329
basically using viruses
to treat the infection,

1114
00:49:22,396 --> 00:49:23,864
the bacterial infection.

1115
00:49:23,931 --> 00:49:25,832
It's a rippin' read.
[laughs]

1116
00:49:25,899 --> 00:49:27,267
- Yeah.
- It's very-- Yeah.

1117
00:49:27,334 --> 00:49:28,669
You're not sure
how it's gonna end.

1118
00:49:28,735 --> 00:49:29,837
But it's, yeah.

1119
00:49:29,903 --> 00:49:31,338
All of these are nonfiction.

1120
00:49:31,405 --> 00:49:34,408
- Yeah, and that disease was
extremely fast progressing too,

1121
00:49:34,474 --> 00:49:35,709
If I remember right,

1122
00:49:35,776 --> 00:49:38,612
they were just on vacation
in Egypt

1123
00:49:38,679 --> 00:49:41,114
and he was wearing the wrong
kind of sandals

1124
00:49:41,181 --> 00:49:44,318
and some sand
got into an open cut,

1125
00:49:44,785 --> 00:49:47,521
and the bacteria came
along for the ride,

1126
00:49:47,588 --> 00:49:51,925
and it was completely unfazed
by antibiotics.

1127
00:49:52,526 --> 00:49:55,529
So, they had to engineer
some viruses

1128
00:49:55,596 --> 00:49:57,531
that selectively go
after the bacteria

1129
00:49:57,598 --> 00:49:59,132
to be able to actually treat
that disease.

1130
00:49:59,199 --> 00:50:00,901
- Sarah: Yeah.
- So, that's one example

1131
00:50:00,968 --> 00:50:03,770
that I didn't talk about,
but, like, how we're kind of

1132
00:50:03,837 --> 00:50:05,873
thinking as a community
to get outside the box

1133
00:50:05,939 --> 00:50:07,407
of antibiotics when they fail.

1134
00:50:07,474 --> 00:50:09,576
- Yep, yep, great, thank you.

1135
00:50:09,643 --> 00:50:11,512
I wanna thank you, Marc.

1136
00:50:11,578 --> 00:50:13,146
Thanks for coming.

1137
00:50:13,213 --> 00:50:14,314
- Thank you all.

1138
00:50:14,381 --> 00:50:16,383
[audience applauds]