-
I get out of bed for two reasons.
-
One, small-scale family farmers
need more food.
-
It's crazy that in 2019
farmers that feed us are hungry.
-
And two, science needs to be
more diverse and inclusive.
-
If we're going to solve
the toughest challenges on the planet,
-
like food insecurity for the millions
living in extreme poverty,
-
it's going to take all of us.
-
I want to use the latest technology
-
with the most diverse
and inclusive teams on the planet
-
to help farmers have more food.
-
I'm a computational biologist.
-
I know -- what is that
and how is it going to help end hunger?
-
Basically, I like computers and biology
-
and somehow,
putting that together is a job.
-
(Laughter)
-
I don't have a story
-
of wanting to be a biologist
from a young age.
-
The truth is, I played
basketball in college.
-
And part of my financial aid package
was I needed a work-study job.
-
So one random day,
-
I wandered to the nearest building
to my dorm room.
-
And it just so happens
it was the biology building.
-
I went inside and looked at the job board.
-
Yes, this is pre-the-internet.
-
And I saw a three-by-five card
-
advertising a job
to work in the herbarium.
-
I quickly took down the number,
-
because it said "flexible hours,"
-
and I needed that to work around
my basketball schedule.
-
I ran to the library
to figure out what an herbarium was.
-
(Laughter)
-
And it turns out
-
an herbarium is where they store
dead, dried plants.
-
I was lucky to land the job.
-
So my first scientific job
-
was gluing dead plants onto paper
for hours on end.
-
(Laughter)
-
It's so glamorous.
-
This is how I became
a computational biologist.
-
During that time,
-
genomics and computing were coming of age.
-
And I went on to do my masters
-
combining biology and computers.
-
During that time,
-
I worked at Los Alamos National Lab
-
in the theoretical biology
and biophysics group.
-
And it was there I had my first encounter
with the supercomputer,
-
and my mind was blown.
-
With the power of supercomputing,
-
which is basically thousands
of connected PCs on steroids,
-
we were able to uncover the complexities
of influenza and hepatitis C.
-
And it was during this time
that I saw the power
-
of using computers
and biology combined, for humanity.
-
And I wanted this to be my career path.
-
So, since 1999,
-
I've spent the majority
of my scientific career
-
in very high-tech labs,
-
surrounded by really expensive equipment.
-
So many ask me
-
how and why do I work
for farmers in Africa.
-
Well, because of my computing skills,
-
in 2013, a team of East African scientists
-
asked me to join the team
in the plight to save cassava.
-
Cassava is a plant whose leaves and roots
feed 800 million people globally.
-
And 500 million in East Africa.
-
So that's nearly a billion people
-
relying on this plant
for their daily calories.
-
If a small-scale family farmer
has enough cassava,
-
she can feed her family
-
and she can sell it at the market
for important things like school fees,
-
medical expenses and savings.
-
But cassava is under attack in Africa.
-
Whiteflies and viruses
are devastating cassava.
-
Whiteflies are tiny insects
-
that feed on the leaves
of over 600 plants.
-
They are bad news.
-
There are many species;
-
they become pesticide resistant;
-
and they transmit hundreds
of plant viruses
-
that cause cassava brown streak disease
-
and cassava mosaic disease.
-
This completely kills the plant.
-
And if there's no cassava,
-
there's no food or income
for millions of people.
-
It took me one trip to Tanzania
-
to realize that these women
need some help.
-
These amazing, strong,
small-scale family farmers,
-
the majority women,
-
are doing it rough.
-
They don't have enough food
to feed their families,
-
and it's a real crisis.
-
What happens is
-
they go out and plant fields of cassava
when the rains come.
-
Nine months later,
-
there's nothing, because of these
pests and pathogens.
-
And I thought to myself,
-
how in the world can farmers be hungry?
-
So I decided to spend
some time on the ground
-
with the farmers and the scientists
-
to see if I had any skills
that could be helpful.
-
The situation on the ground is shocking.
-
The whiteflies have destroyed the leaves
that are eaten for protein,
-
and the viruses have destroyed the roots
that are eaten for starch.
-
An entire growing season will pass,
-
and the farmer will lose
an entire year of income and food,
-
and the family will suffer
a long hunger season.
-
This is completely preventable.
-
If the farmer knew
-
what variety of cassava
to plant in her field,
-
that was resistant
to those viruses and pathogens,
-
they would have more food.
-
We have all the technology we need,
-
but the knowledge and the resources
-
are not equally distributed
around the globe.
-
So what I mean specifically is,
-
the older genomic technologies
-
that have been required
to uncover the complexities
-
in these pests and pathogens --
-
these technologies were not made
for sub-Saharan Africa.
-
They cost upwards of a million dollars;
-
they require constant power
-
and specialized human capacity.
-
These machines are few
and far between on the continent,
-
which is leaving many scientists
battling on the front lines no choice
-
but to send the samples overseas.
-
And when you send the samples overseas,
-
samples degrade, it costs a lot of money,
-
and trying to get the data back
over weak internet
-
is nearly impossible.
-
So sometimes it can take six months
to get the results back to the farmer.
-
And by then, it's too late.
-
The crop is already gone,
-
which results in further poverty
and more hunger.
-
We knew we could fix this.
-
In 2017,
-
we had heard of this handheld,
portable DNA sequencer
-
called an Oxford Nanopore MinION.
-
This was being used
in West Africa to fight Ebola.
-
So we thought:
-
Why can't we use this
in East Africa to help farmers?
-
So, what we did was we set out to do that.
-
At the time, the technology was very new,
-
and many doubted we could
replicate this on the farm.
-
When we set out to do this,
-
one of our "collaborators" in the UK
-
told us that we would never
get that to work in East Africa,
-
let alone on the farm.
-
So we accepted the challenge.
-
This person even went so far as to bet us
two of the best bottles of champagne
-
that we would never get that to work.
-
Two words:
-
pay up.
-
(Laughter)
-
(Applause)
-
Pay up, because we did it.
-
We took the entire high-tech molecular lab
-
to the farmers of Tanzania,
Kenya and Uganda,
-
and we called it Tree Lab.
-
So what did we do?
-
Well, first of all,
we gave ourselves a team name --
-
it's called the Cassava Virus
Action Project.
-
We made a website,
-
we gathered support from the genomics
and computing communities,
-
and away we went to the farmers.
-
Everything that we need for our Tree Lab
-
is being carried by the team here.
-
All of the molecular and computational
requirements needed
-
to diagnose sick plants is there.
-
And it's actually all
on this stage here as well.
-
We figured if we could get the data
closer to the problem,
-
and closer to the farmer,
-
the quicker we could tell her
what was wrong with her plant.
-
And not only tell her what was wrong --
-
give her the solution.
-
And the solution is,
-
burn the field and plant varieties
-
that are resistant to the pests
and pathogens she has in her field.
-
So the first thing that we did
was we had to do a DNA extraction.
-
And we used this machine here.
-
It's called a PDQeX,
-
which stands for
"Pretty Damn Quick Extraction."
-
(Laughter)
-
I know.
-
My friend Joe is really cool.
-
One of the biggest challenges
in doing a DNA extraction
-
is it usually requires
very expensive equipment,
-
and takes hours.
-
But with this machine,
-
we've been able to do it in 20 minutes,
-
at a fraction of the cost.
-
And this runs off of a motorcycle battery.
-
From there, we take the DNA extraction
and prepare it into a library,
-
getting it ready to load on
-
to this portable, handheld
genomic sequencer,
-
which is here,
-
and then we plug this
into a mini supercomputer,
-
which is called a MinIT.
-
And both of these things are plugged
into a portable battery pack.
-
So we were able to eliminate
-
the requirements
of main power and internet,
-
which are two very limiting factors
on a small-scale family farm.
-
Analyzing the data quickly
can also be a problem.
-
But this is where me being
a computational biologist came in handy.
-
All that gluing of dead plants,
-
and all that measuring,
-
and all that computing
-
finally came in handy
in a real-world, real-time way.
-
I was able to make customized databases
-
and we were able to give the farmers
results in three hours
-
versus six months.
-
(Applause)
-
The farmers were overjoyed.
-
So how do we know
that we're having impact?
-
Nine moths after our Tree Lab,
-
Asha went from having
zero tons per hectare
-
to 40 tons per hectare.
-
She had enough to feed her family
-
and she was selling it at the market,
-
and she's now building a house
for her family.
-
Yeah, so cool.
-
(Applause)
-
So how do we scale Tree Lab?
-
The thing is,
-
farmers are scaled already in Africa.
-
These women work in farmer groups,
-
so helping Asha actually helped
3,000 people in her village,
-
because she shared the results
and also the solution.
-
I remember every single
farmer I've ever met.
-
Their pain and their joy
-
is engraved in my memories.
-
Our science is for them.
-
Tree Lab is our best attempt
to help them become more food secure.
-
I never dreamt
-
that the best science
I would ever do in my life
-
would be on that blanket in East Africa,
-
with the highest-tech genomic gadgets.
-
But our team did dream
-
that we could give farmers answers
in three hours versus six months,
-
and then we did it.
-
Because that's the power
of diversity and inclusion in science.
-
Thank you.
-
(Applause)
-
(Cheers)