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So, for today's lecture as you can
see up there is molecular --

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evolution, and ecology.

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And what I mean by this,

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it's basically the study or what we
try to figure out in molecular

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evolution and ecology is what genes
or gene sequences can tell us about

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the evolution and ultimately also
the ecology of organisms

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in the environment.
And it's particularly relevant for

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thinking about microorganisms,
prokaryotes and the environment.

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And I hope I can actually convince
you today of that.

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This is interesting.
The topics that I want to cover

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today is, first of all,
I want to review a little bit what

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we know about life on Earth,
sort of give an overview of the

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evolution of life on Earth.
Then, I want to go into specific

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topic that's of particular relevance
for the evolution of eukaryotes.

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That's the endosymbiosis theory.
And then I'll explain how we can

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use gene sequences to actually
reconstruct events that have

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happened a very, very
long time ago.

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OK, so we'll look at what we call
molecular phylogenies,

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with the use of gene sequences to
reconstruct the evolutionary history

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of organisms on Earth.
Derived from that, we'll look at

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what we call the tree of life.
That's sort of the big picture

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overview of the evolutionary
relationships of all organisms on

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the planet.  And then finally,
I'll introduce you to a topic called

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molecular ecology.
Again, that's how we can use gene

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sequences to learn something about
the diversity of microorganisms in

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the environment that lead us then,
next time, when I come back on

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Monday, into this big topic of
environmental genomics,

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how we can actually expand this
analysis to learn much more about

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organisms in the environment.
So, first of all, let's look at

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life on Earth.
Does anybody know how old we think

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Earth is?  Say again?
Yeah, 4.5 to 4.6, I haven't my

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notes 4.6.  So,
Earth's thought to have originated

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about 4.6 billion years ago.
When did the first solid rocks

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appear on earth?
So, when was the surface kind of

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solidified?  Anybody know?
About 3.9 billion years ago, OK?

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And when do we think life started to
develop on the planet?

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Any ideas?  Take a guess.
Two?  One?  3.5 billion years ago,

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OK?  So, this is really
remarkable.

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We think it didn't,
I mean, of course it took a long

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time because were talking about
millions of years and hundreds of

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millions of years,
but still, if you look at the big

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picture, it didn't actually take
life that long to evolve on the

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planet.  So, why do we think that is
the case?  What's the evidence for

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that?  Well, we look into
sedimentary rocks,

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so old rocks that arose from
sediments, what you find around this

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time, you find that chemicals start
to appear, organic molecules that

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really resemble organic molecules
in modern life.

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So, we have sort of chemical tracers,
or chemical fossils.

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So, tracers that indicate the

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presence of organisms.
But what we also find is so-called

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micro-fossils,
and I have a picture of that here

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where when you actually take rocks
and actually slice them into very,

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very then slices, you can put them
under specific microscopes.

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And what you then find is that many
rocks that are very,

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very old, have those kinds of
inclusions in them.

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And these things really resemble
very much modern prokaryotic cells,

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modern bacterial cells, for example.
And so, those micro-fossils are

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generally taken as an indication,
also, that life is already present

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during those times.
Now, when we take a quick sort of

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overlook of the evolution of life on
the planet, again this graph here

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summarizes sort of the last 4.
billion years or so when life

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originated.  We see that there was a
period of chemical evolution,

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and then somewhere here that region,
it's, of course, not really well

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understood when that exactly happens,
the origin of life is placed.

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But I want to alert you to a couple
of really, really critical steps

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here that are shown on this graph
which we'll actually talk more about.

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It is thought that life very early
on is split into three major

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lineages: the bacteria,
the archaea, in what is called here

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nuclear line.  And I'll come back to
that in a minute or so.

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Then, a further major event which
you may remember is oxygenic

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photosynthesis actually evolved --
-- which means that cyanobacteria

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evolved that started to produce
oxygen as a byproduct of

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photosynthesis.
And that really fundamentally

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changed the chemistry of the Earth.
It actually became an oxidizing

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atmosphere.  And what you see here
is, once the oxygen concentration

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goes over a certain level,
it allowed the development of an

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ozone shield.  Now, what
does that mean?

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What was the critical significance
of the presence of an ozone shield?

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Does anybody know?  What does it
block out?  Anybody remember that?

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What's the big significance of the
ozone hole over Antarctica for

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example?  It allows UV radiation to
heat the Earth's surface,

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and in fact if there were no ozone,
the UV radiation would be so strong

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that there would be no life
possible on land.

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So, once the ozone shield actually
developed, organisms could conquer,

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basically, the land's surface and
settle on the land surface.

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In this, then, is thought to be at
least correlated with the

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development of endosymbiosis.
And I'll explain what I mean by

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that.  But it basically led to the
origin of modern eukaryotes,

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so your ancestors essentially.
But there was still a long time,

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obviously, until humans appeared.
We have here the origin of animals

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and metazoans,
and then the age of the dinosaurs is

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already a very small blip here on
this graph.  And humans don't even

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get featured on that because we are
so recent.  So,

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but what I want to show you here is
that three major lineages

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evolved early on.
These are the bacteria,

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archaea, and what we call a nuclear
lineage.  And the significance of

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those nuclear lineages is that it
basically combined with bacteria to

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form the modern eukaryotic cell.
So, the eukarya, or eukaryotes

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they're also called.
And it was this combination that we

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called the endosymbiosis event.
I want to explain this a little bit

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more, and then I'll show you finally
why we actually know that those

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things are very likely to have
occurred a long time ago.

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Yes?  It means the bacteria and the
nuclear lineages combine to form a

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eukaryote, OK?
And I'm actually going to explain

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this on the slide here.
So, if you have any more questions

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after that, please let me know.
So, again, this shows you this early

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evolution, this early split in two
archaea, bacteria,

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and this sort of nuclear line.
It is thought that this nuclear

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line, this was single celled
organisms that increased in cell

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size, and then developed or
partitioned the DNA into a nucleus,

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basically.  So exactly how you find
it in modern eukaryotic cells.

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But then what happened is the cell
took up a bacterial cell,

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and over time this bacterial cell
became symbiont.

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In fact it became the mitochondria.
And so what this mitochondria now

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does in the moderate eukaryotic cell
as you all know is it really took

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over the energy metabolism.
So, the proto-eukaryotic cell took

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up a heterotrophic bacteria that
form the mitochondria.

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And this ultimately then gave rise
to protozoa and to modern-day

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animals.  But there was a secondary
symbiotic event.

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This cell, once it had taken up a
heterotrophic bacterium,

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it took up an autotrophic bacterium,
a cyanobacterium, an oxygenic

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photosynthesizer.
And this actually that led to the

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development of modern algae
and modern plants.

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So what we can say is that
mitochondria our ancient

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heterotrophic bacteria --

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And the chloroplasts are ancient
cyanobacteria,

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so, oxygenic, photosynthetic
bacteria.  And these obviously have

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coevolved to then form animals and
finally your plants.

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So now, obviously we are talking
here about events that happened a

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very, very long time ago.
And so, the big question is really

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how do we really know this?
But this takes me to the third

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topic, which is that of molecular
evolution.  So, we can state

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the problem again,
And that is very simply put,

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evolution is incredibly slow,
OK?  And therefore, its processes

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are not directly observable.

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And we need to actually use
inference techniques to reconstruct

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evolutionary processes.
Now, what do we use when we want to

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reconstruct the evolutionary history
of animals and plants usually?

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Anybody?  Fossils.  Exactly.  So
you take a shovel,

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essentially, and dig down into the
different layers.

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And there's different techniques
that you can actually determine the

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age of different sedentary rocks.
For example, and then you can

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construct, if you're lucky,
you'll find enough fossils of a

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particular lineage.
You can reconstruct the evolution

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of the lineage.
I'm sure you all have seen the

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example of the horse,
for example, where we have actually

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quite good evidence when ancient
horses look like.

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And we can reconstruct the sequence
of events that led to the evolution

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of modern-day horses.
Now, you can imagine,

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though, that when we talk about such
ancient events like these there

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really is no fossil record.
OK, so what people have figured out,

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then, is that that was really a
stroke of genius that came about in

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the late 60s, that DNA molecules can
act as evolutionary chronometers.

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OK, now what do I mean by that?

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I mean that you can take DNA
sequences or gene sequences from

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different kinds of organisms.
Based on those gene sequences you

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can reconstruct the relationships to
each other.  You can determine

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whether two organisms are closely
related or whether they are only

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very distantly related.
And the underlying mechanism of that,

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is that mutations happen with a
certain probability all the time.

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So, the idea is that as time passed
on, DNA molecules will change.

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So they will accumulate, actually,
mutations, and so this will lead to,

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and that the idea is that the amount
of change in a particular DNA

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sequence is proportional to the time
of separate evolution of two

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different lineages or two
different organisms.

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So, the amount is more or
less proportional --

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-- to time since the last

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common ancestry.

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So, let me explain how this is
actually done.

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What you really need in order to do
this, is you need genes that are

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related to each other,
OK?  So, genes, they need to be

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universally distributed.
That meets all organisms that you

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want to compare need to have this
type of gene.  And,

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those genes need to have conserved
function.

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In these genes,

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we can then compare to each other,
and I will explain how this is

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actually done.  Any
questions so far?

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OK, so the example that I actually
want to bring is the 16S

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ribosomal RNA genes.

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We oftentimes abbreviate this rRNA.
Now, does anybody remember what the

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ribosomal RNAs are and do?
What's the ribosome?  Yes?

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Right, and what does it do?
Exactly, it's the location where

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messenger RNA is translated
into protein.

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Now, the ribosomal RNAs are an
integral part of the ribosome.

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They play both a catalytic role as
well as a structural role in the

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ribosome.  And so,
fundamentally, because this is such

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a fundamental organelle,
all living organisms possess it.

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So, all organisms have it.  So this
allows us to use these genes to

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really compare all living organisms
to each other.

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OK, so this is a very important
point.

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I wanted to show you a,
OK, if it wakes up.  There we go.

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An example of these ribosomal RNA
genes, now this is actually,

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what you see here is a secondary
structure of the actual RNA,

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the ribosomal RNA.  Now, these
molecules have a secondary structure

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because they play a catalytic and
structural role.

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And so, the really amazing thing is
when you look at the structure,

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the structure determines really the
function of those molecules in

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different organisms.
And then look at this.

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We have here a bacterium,
and here are an archaea.  Now,

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if you think back to the first
couple of slides,

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what I showed you is that those
organisms have not shared a common

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evolutionary history for about four,
or so, billion years, or 3 billion

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years, excuse me.
But, if you just glance very

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quickly at the structures,
you see that they look very similar

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to each other.
So, there's an indication that the

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function is really very highly
conserved of those molecules.

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However, when you actually look at
the sequences in detail,

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what you'll find is that there's
different regions.

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And I'd given some examples here
denoted by A, B,

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C in those molecules.
And these different regions of the

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molecules are really the key to its
usefulness in figuring out the

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evolution and ecology
of many organisms.

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The region number A here,
or denoted by A, a sequence

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stretches that are the same in all
living organisms.

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So they are universally conserved,
which means that if you get a

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mutation in a gene in that
particular region,

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you are dead.  OK, that's why it's
conserved essentially.

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Then we have those regions B where
the length is conserved,

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but the sequence is not.
So, there are sequence change

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allowed, but the length needs to be
conserved.  And then there's the

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region C were neither length nor
sequence is actually conserved,

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and where we get a lot of variation.
So, let me write this down.  We

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have three types of sequence
stretches.

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We have A, what I called the

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universally conserved sequences.
We have B where length, but not

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sequence is conserved.
And, we have C where neither length

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nor sequence is actually conserved.

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And the first two stretches,
the first two types of sequence

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stretches, are very important in
figuring out the phylogeny or the

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evolutionary relationships amongst
organisms.  Whereas the sequence

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stretches number C because they vary
so dramatically,

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are very important in identifying
organisms.

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And we'll talk more about this
actually next time.

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So what can we actually know do
with those sequences?

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Well, the first step is we need to
generate an alignment.

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OK, and this is actually shown here,

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where each row denotes a gene from a
particular organism.

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OK, so these are all abbreviated
here.

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These actually aren't ribosomal RNA
genes, but other genes.

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And that what you will see here is
we can recognize those three

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different regions that I've pointed
out before.  You have the regions A

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which tell you which nucleotides
line up with each other,

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so you use this sort of as an anchor
because the sequences never vary

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amongst organisms.
And that the sequence region B

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where you light up sequences that
vary or stretches that vary in

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sequence but not in length.
Now, why is this important?

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It's important because you have in
each column that nucleotides that

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have originated from a common
ancestral nucleotide,

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and whose variation over time you
can actually monitor.

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Is everybody with that?
Any questions?  OK, great.

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The second step,
then, is the calculation of a

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00:26:02 --> 00:26:16
similarity.

253
00:26:16 --> 00:26:20
And this is shown here.
Again, we have a very simplified

254
00:26:20 --> 00:26:24
alignment now of four different
organisms.  Here,

255
00:26:24 --> 00:26:29
we have the sequences that we want
to compare.  And what you'll see is

256
00:26:29 --> 00:26:33
that they're overall very similar,
but there are different sort of

257
00:26:33 --> 00:26:38
nucleotides.
And so, what we simply do is for

258
00:26:38 --> 00:26:43
each pair of sequence combinations,
we calculate the sequence similarity

259
00:26:43 --> 00:26:48
value.  So, what you see is that you
have 12 nucleotides,

260
00:26:48 --> 00:26:52
and the first pair differs in three
nucleotides.  OK,

261
00:26:52 --> 00:26:57
so that tells us, or it's called
actually a distance

262
00:26:57 --> 00:27:01
here, I'm sorry.
Let me write this down here.

263
00:27:01 --> 00:27:15
It's simply one minus the similarity,

264
00:27:15 --> 00:27:21
of course, but so basically a
quarter of the nucleotides differ

265
00:27:21 --> 00:27:27
where it's between A and C,
a third of the nucleotides

266
00:27:27 --> 00:27:33
difference on.
OK, so you do this for each pair of

267
00:27:33 --> 00:27:40
sequences, excuse me.
The third step,

268
00:27:40 --> 00:27:49
then, is to calculate the correction
for multiple mutations affecting the

269
00:27:49 --> 00:28:08
same nucleotides.

270
00:28:08 --> 00:28:12
Now, you can imagine that over time
there's a probability that a

271
00:28:12 --> 00:28:16
particular nucleotide mutates,
say, twice.  So, in the first

272
00:28:16 --> 00:28:20
instance it may change from A to a G,
, but then it changes to a C.

273
00:28:20 --> 00:28:24
But when you look at the modern-day
sequences, you don't know that this

274
00:28:24 --> 00:28:28
actually happened.
And so there's ways to

275
00:28:28 --> 00:28:32
statistically estimate what the
likelihood is that a sequence

276
00:28:32 --> 00:28:37
actually contains such
multiple events.

277
00:28:37 --> 00:28:41
OK, and this, we called,
a corrective evolutionary distance

278
00:28:41 --> 00:28:46
then.  And what you will note is
that the corrected evolutionary

279
00:28:46 --> 00:28:51
distance is invariably larger than
the actual observed one.

280
00:28:51 --> 00:28:56
Now, what can we can do with those
distances?  We can constrain them

281
00:28:56 --> 00:29:01
into a best fit tree
of relationships.

282
00:29:01 --> 00:29:07
So, we can draw what we call is a
best fit tree.

283
00:29:07 --> 00:29:14
That's shown here.
We have our four organisms,

284
00:29:14 --> 00:29:20
but when you look at those branches
of the tree what you'll see is that

285
00:29:20 --> 00:29:27
they add up roughly to the correct
evolutionary distance here.

286
00:29:27 --> 00:29:32
So, between A and B we have 0.
3 and 0.08, which roughly gives you

287
00:29:32 --> 00:29:37
0.3 here, OK, whereas between A and
C the tree is constrain such that we

288
00:29:37 --> 00:29:42
have 0.31, and here 0.
5, and so overall you roughly get

289
00:29:42 --> 00:29:48
the distance here that we have
calculated.  And so what this means

290
00:29:48 --> 00:29:53
is that you ordered the organisms by
their calculated evolutionary

291
00:29:53 --> 00:29:58
distance.  And so you have now
obtained, actually,

292
00:29:58 --> 00:30:04
a very intuitive picture of the
relationship of organisms to each

293
00:30:04 --> 00:30:09
other where A and B are obviously
the most closely related ones,

294
00:30:09 --> 00:30:15
and A and D are the most distantly
related.

295
00:30:15 --> 00:30:23
Is everybody with it?
Any questions?  OK, now,

296
00:30:23 --> 00:30:31
this best fit tree is what we call a
phylogeny.

297
00:30:31 --> 00:30:52
Now, excuse me,

298
00:30:52 --> 00:31:00
these techniques really
revolutionized the study of

299
00:31:00 --> 00:31:08
evolutionary relationships,
and one of the things that it

300
00:31:08 --> 00:31:16
allowed us to do is to construct
universal phylogenetic trees or what

301
00:31:16 --> 00:31:23
we can also call the tree of life.
And I will show you this on the next

302
00:31:23 --> 00:31:30
slide, and that I want to make a few
general statements about this.

303
00:31:30 --> 00:31:37
So first of all,
when you analyze all known organisms,

304
00:31:37 --> 00:31:45
and obviously that would be a big
task, but representative of all

305
00:31:45 --> 00:31:52
known organisms,
what you'll find is that,

306
00:31:52 --> 00:32:00
indeed, we have three major
lineages: the bacteria,

307
00:32:00 --> 00:32:07
the archaea, and the eukarya.
OK, so we have what we call three

308
00:32:07 --> 00:32:15
domains of life: the archaea,
bacteria, and the eukarya.

309
00:32:15 --> 00:32:20
So, this really is the evidence that
life really split very,

310
00:32:20 --> 00:32:26
very early on into those three
lineages that I showed you before.

311
00:32:26 --> 00:32:32
Interestingly,
two of those major domains here are

312
00:32:32 --> 00:32:39
prokaryotic, OK?
So, two of the domains are

313
00:32:39 --> 00:32:46
prokaryotes.  Moreover,
if you actually look at the types of

314
00:32:46 --> 00:32:53
organisms that are on here,
you'll notice that even on the

315
00:32:53 --> 00:33:00
eukaryotic side of the tree,
most of the organisms here are

316
00:33:00 --> 00:33:07
actually microbial.
So, the single celled organisms: and

317
00:33:07 --> 00:33:14
that means that most of the life on
the planet is microbial.

318
00:33:14 --> 00:33:21
The vast diversity of organisms on
the planet are microorganisms.

319
00:33:21 --> 00:33:29
So, we can say that most life is
microbial.

320
00:33:29 --> 00:33:34
And when you, then,
look at analysis of mitochondria,

321
00:33:34 --> 00:33:39
and chloroplasts which all have
their own genetic machinery,

322
00:33:39 --> 00:33:44
and therefore also their own
ribosomes you'll see that the

323
00:33:44 --> 00:33:49
mitochondrion,
OK, and the chloroplasts both tree

324
00:33:49 --> 00:33:54
within the bacteria.
So, we really have an amazing

325
00:33:54 --> 00:33:59
confirmation of this endosymbiont
theory which actually developed in

326
00:33:59 --> 00:34:04
the absence of gene sequences by
some Russian scientists in the early

327
00:34:04 --> 00:34:13
20th century.
So, we have that mitochondria and

328
00:34:13 --> 00:34:27
chloroplasts tree within bacteria,
and this really supports the

329
00:34:27 --> 00:34:36
endosymbiont theory.
So really, you could say eukaryotes

330
00:34:36 --> 00:34:42
are really just walking,
and swimming, and flying incubators

331
00:34:42 --> 00:34:48
for bacteria, right?
So, just hosts for microorganisms.

332
00:34:48 --> 00:34:54
OK, so basically you can, what you
should take home from this is the

333
00:34:54 --> 00:35:00
three domains of life.
Two are prokaryotic, and even more

334
00:35:00 --> 00:35:06
so most of the diversity that we
find is actually microbial,

335
00:35:06 --> 00:35:12
and then finally the endosymbiont
theory is actually confirmed by

336
00:35:12 --> 00:35:17
those phylogenies.
Now, what I want to cover in the

337
00:35:17 --> 00:35:22
remaining time,
is how we can actually use now those

338
00:35:22 --> 00:35:27
sequences to learn something about
organisms in the environment.

339
00:35:27 --> 00:35:32
That's the topic of molecular
ecology.

340
00:35:32 --> 00:35:43
To introduce this,

341
00:35:43 --> 00:35:47
I just want to show you a couple
slides that really sort of capture

342
00:35:47 --> 00:35:51
what the big problem is that we're
facing here.  Now,

343
00:35:51 --> 00:35:55
when we look at the abundance of
prokaryotic cells in different types

344
00:35:55 --> 00:35:59
of environments,
what we see is that there is an

345
00:35:59 --> 00:36:04
enormous number of different
prokaryotes out there.

346
00:36:04 --> 00:36:08
This summarizes,
here, different types of

347
00:36:08 --> 00:36:12
environments.  We have the marine
environment, freshwater environment,

348
00:36:12 --> 00:36:16
sediment and soils, subsurface
sentiments and animal guts.

349
00:36:16 --> 00:36:20
And that this number here gives you
the average number of prokaryotic

350
00:36:20 --> 00:36:24
cells either per milliliter or per
gram.  And it here we have the total

351
00:36:24 --> 00:36:28
number of cells obtained by
multiplying the average number with

352
00:36:28 --> 00:36:33
the total volume of the particular
environment.

353
00:36:33 --> 00:36:37
So what you can see is that in the
marine environment,

354
00:36:37 --> 00:36:41
we have an average half a million
cells per milliliter of water,

355
00:36:41 --> 00:36:45
OK?  It freshwater, we have about a
million cells.

356
00:36:45 --> 00:36:49
What is that telling you?
There's a ton of prokaryotes out

357
00:36:49 --> 00:36:53
there.  What you go swimming,
you take a little gulp of water:

358
00:36:53 --> 00:36:57
you've probably eaten several
million prokaryotes,

359
00:36:57 --> 00:37:01
that it's nothing to worry about
because what this also tells us is

360
00:37:01 --> 00:37:05
that very, very few prokaryotes out
there are really pathogens because

361
00:37:05 --> 00:37:09
otherwise you'd be sick
all the time.

362
00:37:09 --> 00:37:15
Now, in sediments and soils,
in as little as a gram you have five

363
00:37:15 --> 00:37:22
times 10^9 prokaryotic cells almost.
5 billion prokaryotic cells are out

364
00:37:22 --> 00:37:29
there, and even in very,
very deep sediments that reach down

365
00:37:29 --> 00:37:36
to 3,000 m, you have a substantial
number of prokaryotic cells.

366
00:37:36 --> 00:37:40
Well, and here's your guts,
10^5 times 10^6 gives you 10^11 per

367
00:37:40 --> 00:37:45
gram.  So again,
you're just a walking incubator for

368
00:37:45 --> 00:37:50
a very complex microbial community.
Here's the global abundance.  You

369
00:37:50 --> 00:37:55
see that steeps of surface sediments
and the marine environment,

370
00:37:55 --> 00:38:00
probably in terms of numbers at
least, the most important

371
00:38:00 --> 00:38:05
microbial environments.
Now, faced with this enormous

372
00:38:05 --> 00:38:09
abundance of prokaryotes out there,
very important question is how many

373
00:38:09 --> 00:38:14
of them are out there?
Or, how diverse our prokaryotes in

374
00:38:14 --> 00:38:18
the environment?
That's important if you want to

375
00:38:18 --> 00:38:23
figure out their function and the
environment, and want to understand

376
00:38:23 --> 00:38:27
also their evolution.
And what I want to show you here is

377
00:38:27 --> 00:38:32
that we've gone through an amazing
development in our understanding of

378
00:38:32 --> 00:38:36
prokaryotic diversity in the
environment over the last

379
00:38:36 --> 00:38:42
10 to 15 years or so.
Who knows about E.

380
00:38:42 --> 00:38:48
. Wilson here?  One person?
So, he wrote a very famous book on

381
00:38:48 --> 00:38:54
biodiversity, which was published in
1988, where he tried to summarize,

382
00:38:54 --> 00:39:00
really, how diverse the known
organisms are on the planet it also

383
00:39:00 --> 00:39:06
try to extrapolate to
the total diversity.

384
00:39:06 --> 00:39:10
And what you see is that he came up
with about 1.4 million different

385
00:39:10 --> 00:39:14
species here, mostly dominated by
insects.  That's the big section

386
00:39:14 --> 00:39:19
here on this pie chart.
The plants: very important.

387
00:39:19 --> 00:39:23
And if you look, the prokaryotes
feature with about 3,

388
00:39:23 --> 00:39:27
00 different species.  So,
in 1988 we thought there were very

389
00:39:27 --> 00:39:32
few prokaryotic species out there.
If you look about 10 years into the

390
00:39:32 --> 00:39:36
future and take the assessment here,
and this just exemplifies how the

391
00:39:36 --> 00:39:41
thinking has changed,
you see that we think now that there

392
00:39:41 --> 00:39:45
is about 11 million different
species out there,

393
00:39:45 --> 00:39:50
and that the vast majority of them
are prokaryotic,

394
00:39:50 --> 00:39:54
OK, 10 million.  So,
this big part of the pie chart is

395
00:39:54 --> 00:39:59
really the prokaryotic diversity.
Now, what really has changed is

396
00:39:59 --> 00:40:03
that we've actually started to use
molecular techniques to determine

397
00:40:03 --> 00:40:08
the diversity of prokaryotes
in the environment.

398
00:40:08 --> 00:40:18
So molecular ecology is really the
use of molecular gene sequences

399
00:40:18 --> 00:40:29
obtained directly from
the environment --

400
00:40:29 --> 00:40:42
-- to learn about the diversity

401
00:40:42 --> 00:40:54
prokaryotic --

402
00:40:54 --> 00:40:58
-- diversity out there.
Now, this slide just quickly

403
00:40:58 --> 00:41:03
summarizes this.
Basically, the idea is that you go

404
00:41:03 --> 00:41:08
out into the environment and collect
either water or soil samples that,

405
00:41:08 --> 00:41:13
as I just showed you, invariably
contain a lot of different

406
00:41:13 --> 00:41:17
prokaryotic cells.
You then lyse the cells and purify

407
00:41:17 --> 00:41:22
their DNA.  And so that you end up
with a mixture of DNA that

408
00:41:22 --> 00:41:27
represents the organisms out there,
and then you can use universal PCR

409
00:41:27 --> 00:41:32
primers to actually amplify
ribosomal RNA genes from all the

410
00:41:32 --> 00:41:37
organisms that are present
in your samples.

411
00:41:37 --> 00:41:42
Now, why can you use universal PCR
primers?  Well,

412
00:41:42 --> 00:41:48
they target the regions number A
that I showed you before.

413
00:41:48 --> 00:41:53
Those regions in the genes are
invariant amongst all organisms.

414
00:41:53 --> 00:41:59
You guys all remember how the PCR
works, right?  We cover this.

415
00:41:59 --> 00:42:04
OK?  Yes?  No?  Who doesn't?
You don't?  All right,

416
00:42:04 --> 00:42:09
come to the board.  Just kidding.
OK, you should look it up.  I don't

417
00:42:09 --> 00:42:15
have time to cover this,
unfortunately, but basically it's a

418
00:42:15 --> 00:42:20
technique that allows you to amplify
specific types of genes millions to

419
00:42:20 --> 00:42:25
billion fold.  And once you have
done this, what you can do is that

420
00:42:25 --> 00:42:31
you can purify the genes on gels,
and then separate them by cloning

421
00:42:31 --> 00:42:36
them into individual plasmids.
And those plasmids have been

422
00:42:36 --> 00:42:41
inserted into E.
coli cells, and the E.

423
00:42:41 --> 00:42:46
coli cells are then individually
grown up so that each culture

424
00:42:46 --> 00:42:50
contains only a single plasmid,
and you can then sequence these

425
00:42:50 --> 00:42:55
ribosomal DNAs or ribosomal RNA
genes from those clones.

426
00:42:55 --> 00:43:00
And so, you have obtained a library
of the ribosomal RNA genes

427
00:43:00 --> 00:43:08
from the environment.
So, we use environmental ribosomal

428
00:43:08 --> 00:43:18
RNA gene libraries from which we
then can actually compare how many

429
00:43:18 --> 00:43:28
different types of genes
are out there.

430
00:43:28 --> 00:43:32
So let me show you an example of
this.  What we have done recently,

431
00:43:32 --> 00:43:37
we've gone out in one of the first
really comprehensive samplings of

432
00:43:37 --> 00:43:42
coastal bacteria plankton,
which means the bacteria that are

433
00:43:42 --> 00:43:47
present free living in ocean water.
And so, we've done this, we've

434
00:43:47 --> 00:43:52
collected all those clones,
and then basically we constructed

435
00:43:52 --> 00:43:57
those phylogenetic trees that I
showed you before that really allow

436
00:43:57 --> 00:44:02
us see how many different types are
out there, and how closely related

437
00:44:02 --> 00:44:07
they are to one another.
And what we found is that in this

438
00:44:07 --> 00:44:12
environment that you think might be
very simple because it just the

439
00:44:12 --> 00:44:17
water column right?
No, not much structure in there.

440
00:44:17 --> 00:44:22
We found over 1500 bacterial 16S
ribosomal RNA sequences to occur,

441
00:44:22 --> 00:44:27
so an enormous diversity of
prokaryotes of bacteria in that

442
00:44:27 --> 00:44:32
particular environment.
And the important point is that when

443
00:44:32 --> 00:44:36
you actually look at a collection of
such studies that I just showed you,

444
00:44:36 --> 00:44:40
what you find is that the vast
majority of microorganisms in the

445
00:44:40 --> 00:44:44
environment have never been cultured.
So traditionally what we do of

446
00:44:44 --> 00:44:49
course to learn about microorganisms
when you grow E.

447
00:44:49 --> 00:44:53
coli, or so, you throw them onto
culture plates.

448
00:44:53 --> 00:44:57
You make lots of different cells,
and that allows you to study some of

449
00:44:57 --> 00:45:02
their properties.
But when you look,

450
00:45:02 --> 00:45:06
for example, at results from the
ocean, this summarizes now coastal

451
00:45:06 --> 00:45:10
and open ocean environments,
again, the bacteria plankton is

452
00:45:10 --> 00:45:15
those free-floating bacterial
cells in the water.

453
00:45:15 --> 00:45:19
And you compare this to what we've
actually been able to culture from

454
00:45:19 --> 00:45:23
those environments.
What you see is that you have some

455
00:45:23 --> 00:45:27
dominant groups here.
They have all funny names,

456
00:45:27 --> 00:45:32
most of them, because they're just
clones and clone libraries.

457
00:45:32 --> 00:45:36
But these are the dominant groups
that show up in clone libraries.

458
00:45:36 --> 00:45:40
Here's their relative
representation in different clone

459
00:45:40 --> 00:45:44
libraries from a variety of
environments.  And so here you have

460
00:45:44 --> 00:45:48
one very important one,
the SAR11 group, or this one,

461
00:45:48 --> 00:45:53
the SAR86, that always show up in
clone libraries.

462
00:45:53 --> 00:45:57
But we've never see them in culture,
so the important point to realize

463
00:45:57 --> 00:46:01
here is that what is actually
happening is that whenever we go out,

464
00:46:01 --> 00:46:05
we find a great diversity of
bacteria out there,

465
00:46:05 --> 00:46:10
but we have no idea what they
actually do.

466
00:46:10 --> 00:46:14
And this is one of the big questions
that we need to answer to understand,

467
00:46:14 --> 00:46:18
really, how the planet actually
works.  What are those uncultured

468
00:46:18 --> 00:46:22
microorganisms out in the
environment really doing,

469
00:46:22 --> 00:46:26
and what is their importance?
And we'll talk about this next time.

470
00:46:26 --> 00:46:30
We're going to talk about
environmental genomics because

471
00:46:30 --> 00:46:34
essentially what we can do now,
is we have techniques available that

472
00:46:34 --> 00:46:38
allow us to isolate and least large
fragments of the genomes,

473
00:46:38 --> 00:46:42
sequence those, and look at what
kinds of genes they have present.

474
00:46:42 --> 00:46:46
And that allows us,
then, to infer some of their

475
00:46:46 --> 00:46:51
function in the biogeochemical
cycles in the environment.

476
00:46:51 --> 00:46:55
OK, so with this I'm going to close
today unless you have

477
00:46:55 --> 00:46:58
any more questions.