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So in this last lecture,
what I'd like to do is I'd like to

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now begin to talk about genetics.
And when we talked early on in the

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semester I was showing you this way
that you can study biological

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function.  Biochemists,
for the most part, study how

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proteins work.
And what genetics does,

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steadying function, it's enable one
to discover genes.

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And the molecular biology that we're
going to be talking about in the

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back part of the course has been
really totally amazing because it's

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allowed one to go back and forth
between genes and proteins,

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something that used to be very,
very hard until recombinant DNA came

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into the picture.
Now, up until now I've sort of

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mentioned genetics
as we went along.

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But we haven't really talked about
it as a discipline and the kind of

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power that this experimental
approach has.  Thank you.

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I could have done this without
notes but it's easier to have them.

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I just have my little help here.
So I know some of you have written

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in your comments I didn't think
there was going to be

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so much chemistry.
Well, we had a little bit of a bout

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with chemistry.
And then some of you found that we

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were going away from bonds and
thinking about 3-dimensionality,

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and that was another kind of
thinking.  And then sort of trying

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to work through the genetic code is
almost another.

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And I think you'll find here,
as we start to go through genetics

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that you have to stretch your brain
in another direction.

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And part of one of the really
interesting things about biology

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today is you cannot just sort of
think about it in one kind of very

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comfortable way of thinking and
really take advantage of everything

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that's out there.
You need to be able to talk in

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multiple languages and multiple
disciplines.  And so today I want to

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just kind of briefly give you an
introductory sense of how genetics,

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that I hope will give you, let you
see the power of it by very,

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very simple techniques.  And
remember what you're doing here is

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you're studying variants of the
living organism.

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So if you see something that's
wrong with it you know it's

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important, but you know the rest of
the job is to figure out what's

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wrong.  And I've sort of given you
and used some examples.

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When we talked about the
streptococcus with the smooth

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colonies, I talked about how people
had noticed rough colonies.

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Well, those sorts of things had
been a change in the DNA and they

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weren't making these polysaccharide
capsules anymore.

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Or when I talked to you about the
mutant bacteria that had lost

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mismatch repair,
they had a high mutation frequency

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compared to a wild type.
So up until now I've sort of

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mentioned them,
but we haven't really talked about

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how one goes about studying things
in a systematic genetic way.

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So let me begin with just a few
definitions.  I realize this is a

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little dry but we need to make sure
that we're all on the same page in

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terms of the language.
So a mutant is a variant of a

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normal organism.

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It has a change in its DNA and the
kinds of mutants can vary all over

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the map.  For example,
if we had an E. coli that was,

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we might call it penn-resistant,
that could mean it was resistant to

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penicillin and would grow in the
presence of the antibiotics.

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Whereas, ordinary ones would die.
Or if we had what we call a

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his-minus mutant broken in the
biosynthesis of histidine

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won't grow --

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-- unless you add histidine to the
medium.  Those are a couple of

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simple examples.
When we start right after lecturing,

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when I come back,
I'm going to begin with Mendel,

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which is the more classic and usual
way of teaching genetics.

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And he used various traits of peas.
Yellow and green seeds and wrinkled

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and round.  And you can see what he
was working with there.

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Another favorite organism for
genetic study has been the fruit fly

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or drosophila.
You can even see that they have red

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eyes.  If you take a close look next
time if one lands on your sandwich

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or your drink or something in the
summer.  But you can see,

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for example, people were able to get
white mutants that have white eyes.

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There's something broken in making
the pigment that's going to make it

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red.  Here's an even weirder one.
This is a single mutation in

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drosophila.  It affects a
developmental process instead of

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something else.
And what happens is this is a

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drosophila head.
And normally there are antennae

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that grow out of the top of the head.
And you can see what's happened in

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this mutant is there's a pair of
legs growing out of the top of the

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head.  It's just a single gene
that's been changed,

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but it's a gene that plays a role in
the developmental program,

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the patterning that makes certain
cells become specialized to become

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certain other things.
So it's just to give you an idea.

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And I showed you these.  We've
talked about the xeroderma

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pigmentosum, one change.
A person with this has got a gene

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that's broken in dealing with damage
from UV.  Or I've given you an

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example of what they call Werner
syndrome where a change in a single

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gene, it's actually a kind of gene
whose proteins are involved in

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unwinding DNA,
of all things, can give you this

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premature aging phenotype where the
woman looks normal at 16 but older

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at the age of 48.
So all of these are,

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if you will, mutants that are a
variant of a wild type.

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And then this is something people
often get confused between these two

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terms.  The mutation is the actual
change in the DNA.

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Now, one other thing that's sort of
implicit in this definition is that

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we know what a normal organism is.
Well, if you look around this room,

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what's a normal human?  Well, I'm OK
but I don't know about the rest of

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you.  I'm sure we all feel that way,
but we have a lot of variation in it.

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So, to some extent,
it's an operational definition.

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And most often it's applied, if
you're studying something like

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drosophila or E.
coli, someone has been propagating a

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particular bacterial isolate in the
lab for a long time.

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And you call that one the wild type,
even though, in fact, in the case of

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an E. coli, it may have changed a
bit so it likes to grow in the

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conditions that it finds in the lab.
But this sort of normal is an

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operational definition.
Now, another important term that

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geneticists use all the time is the
phenotype.  The word phenotype.

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And that's the ensemble --

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-- of observable characteristics --

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-- of an organism.

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For example, in these resistance to

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penicillin would be an example of a
phenotype.  A mutant that had

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acquired the resistance would have
the phenotype of being resistant.

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Sometimes these phenotypes can be a
little subtle.

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A conditional phenotype would be a
phenotype that you could observe

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under one characteristic
and not in another.

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For example, a temperature
sensitive phenotype --

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Whatever it might be.

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For example, it could be wild type
at let's say 30 degrees but mutant

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at 37 degrees centigrade.
That may sound like a sort of

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fiddly little thing.
Why am I telling you about a

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conditional phenotype right off?
Well, suppose you wanted to study a

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DNA polymerase.
be it E. coli or me,

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and it's the one that replicates
your DNA?  If we get a mutant that

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just kills, knocks out the activity
of the gene we have no living

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organism to study,
we cannot do any genetics.

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But you can work around that.
You can do genetics with essential

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functions if you get a mutant where
you see the mutant phenotypes,

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let's say, at the high temperature
but not at a low temperature.

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And what that kind of thing usually
comes from is a change in the

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protein where the protein has one
amino acid changed to something else

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and it folds up,
and at the lower temperature it's

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able to fold up and do its thing.
But it's not quite as stable as the

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original protein.
And if you raise the temperature it

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unfolds a bit,
and once it unfolds it doesn't work

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or it gets degraded or something
like that.  OK.

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So that's phenotype.
The genotype then refers to the

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state of the organism's genetic
material with respect to whether its

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wild type differs from it.
So let me just put that down.

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So this refers to the state --

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-- of the organism's

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genetic material --

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-- with respect to whether it's wild
type or it's mutant.

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There's a key distinction,
even though they sort of sound the

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same.  This is what you can see if
you look at it but this is what's

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actually changed.
The genotype is what's actually

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changed in the DNA.
And there's a caution.

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If it's something like a bacterium
it's fine because it's only got one

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copy of every gene.
If I knock out a gene for making

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histidine it cannot make histidine.
The genotype and the phenotype are

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the same.  But if you have a diploid
organism, which is the kind of

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organism that we are and peas are
and fruit flies are,

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there are two copies of most genes,
one from mom and one from dad.

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And the only exceptions are the ones
involved with the sex chromosomes.

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Then you can get to something else,
a more complicated situation.

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Because let's say we have a usual
thing where both copies of the gene

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are plus, then the phenotype is wild
type, but if we were to break one of

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those copies by a mutation this one
is still wild type.

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The phenotype is still its wild type.
You cannot tell from looking at it

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that this one is different than that
one.  And one of the really

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brilliant insights that Mendel had
when he was looking at peas was he

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would take things that were wrinkled
and round and crossed them and he'd

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see mixtures of things.
And he realized some of those things

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in there weren't the same as either
the parents but they resembled one

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of the parents.
And I'll take you through that in

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the next thing.
So it's just a caution at the

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moment that you have to be careful
that phenotype and genotype are not

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always the same.
And then I've used the word gene.

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That's the discrete unit --

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-- of genetic information.
We talked the other day about the

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lacZ gene that encodes
beta-galactosidase.

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OK.  So I think what I'd like to do,
if I tell you,

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for example, we made a lot of
mutants of E. coli that were broken

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by the biosynthesis of histidine and
gave them to you,

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if you were a good biochemist you
might be able to work out how they

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differed by studying
them biochemically.

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And let me just sort of give you a
sense of how that would work so you

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can see histidine or any of these
amino acids.  They're sort of

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complicated and they have to be
built up by a sequence of

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biochemical steps with one enzyme
catalyzing each step in the pathway.

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And when people started out trying
to study that kind of thing they

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didn't know how it was made.
All they knew was what the end

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product was.
And furthermore it was more of a

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biosynthetic challenge even then
trying to work out the steps of

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glycolysis because actually quite a
reasonable proportion of the protein

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in any cell is devoted towards
making energy.

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So, relatively speaking,
there's a fair amount of the protein.

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Each of those proteins that are
enzymes that we learned about,

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for example, in glycolysis in a cell,
if you crack a cell open they're

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made in larger quantities.
However, all the biosynthetic

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enzymes, the things for making amino
acids, for making purines,

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pyrimidines, nucleotides or vitamins,
which are only needed tiny amounts,

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there are only little tiny bits of
those enzymes.

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So trying to work out the
biosynthetic pathways for how those

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things were made was much more
difficult.  And it was helped by

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genetics in the following way.
I'm not going to go into any great

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detail, but if you imagine that
there's a pathway for making

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histidine.  We don't
know what it is.

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But we know that the end product is
histidine.  We could get mutants.

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His-minus mutants, which I've said
up there, have the property of

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growing only if you add histidine.
So if we had just a minimal glucose

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plate, just some salts with glucose
and we were to streak a wild type

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bacterium on it, it would
grow just fine.

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But if we had a his-minus mutant on
a minimal glucose plate and we

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streaked it out,
it couldn't grow because it couldn't

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make histidine.
If it couldn't make histidine it

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couldn't make proteins.
But if we take the same plate,

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minimal glucose plus some histidine,
now this same mutant will grow

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fine.
And that's how we could tell that it

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was specifically broken in making
histidine.  So if you were to go

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into a undergrad lab,
and I won't talk for the moment on

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how you would isolate those
his-minus bacteria,

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it's not hard, you can do it in an
undergrad lab,

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you can make a whole lot of mutants
that were broken in making histidine.

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So one of the sort of things
biochemists could do was they didn't

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know what the intermediates were,
but let's just say there's

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intermediate-1,
intermediate-2, intermediate-3,

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intermediate-4 and intermediate-5.
And finally it goes to histidine.

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Well, if we break the gene that
makes that, what will happen in that

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pathway is the cell will make this
intermediate, this intermediate,

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and then this one will kind of build
up.  And, furthermore,

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if I'm able to figure out what
intermediate-4 is,

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if I add intermediate-4 to this
mutant it will grow because the

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defect was earlier in the pathway.
And if I added intermediate-1 it

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won't grow.  And so by sort of using
very fine features of the phenotype,

221
00:17:09,000 --> 00:17:14,000
I mean getting in there, breaking it
open and discovering when

222
00:17:14,000 --> 00:17:19,000
intermediate was up,
or I could add an intermediate back

223
00:17:19,000 --> 00:17:24,000
and forth, sort of playing with the
phenotype you can learn a lot about

224
00:17:24,000 --> 00:17:29,000
the mutants that you've isolated and
so on.  But genetics as --

225
00:17:29,000 --> 00:17:32,000
And we'll sort of go into this just
a little bit more.

226
00:17:32,000 --> 00:17:36,000
But genetics as a science is able
to figure out whether mutations are

227
00:17:36,000 --> 00:17:40,000
in the same genes and work out their
order without having to do any of

228
00:17:40,000 --> 00:17:44,000
these sort of specialized knowledge
of a phenotype.

229
00:17:44,000 --> 00:17:47,000
It's a very general,
very powerful way of doing business.

230
00:17:47,000 --> 00:17:51,000
And I want to show you that.  I
want to use a system where we can

231
00:17:51,000 --> 00:17:55,000
see this very clearly.
And I want to introduce you to a

232
00:17:55,000 --> 00:17:59,000
bacterial virus.
The idea of a bacterial virus,

233
00:17:59,000 --> 00:18:03,000
which are called bacteriophage, but
it's just a bacterial virus.

234
00:18:03,000 --> 00:18:08,000
And what's a bacteriophage?
Well, it's got a protein coat of

235
00:18:08,000 --> 00:18:14,000
some kind.  They don't all look the
same, but just some of them look

236
00:18:14,000 --> 00:18:19,000
like this.  So this is protein and
this is DNA.  That's it genetic

237
00:18:19,000 --> 00:18:25,000
material.  And it's basically a
syringe.  It's got a coat and it's

238
00:18:25,000 --> 00:18:30,000
got stuff that will let it find a
bacterial host.

239
00:18:30,000 --> 00:18:36,000
And it's able to squirt its DNA
from the bacterium into the host.

240
00:18:36,000 --> 00:18:40,000
So if we take,
for example, an E.

241
00:18:40,000 --> 00:18:44,000
coli cell and this phage,
which I'm drawing not to scale,

242
00:18:44,000 --> 00:18:49,000
it would be smaller than this
relative to the bacterium.

243
00:18:49,000 --> 00:18:53,000
If it were to infect, it would
inject its DNA into the E.

244
00:18:53,000 --> 00:18:58,000
coli cell.  And what it's sort of
done is it's put a bunch of new

245
00:18:58,000 --> 00:19:02,000
genetic information into a cell
that's all capable of making

246
00:19:02,000 --> 00:19:07,000
RNA and proteins.
And so it kind of reprograms the

247
00:19:07,000 --> 00:19:12,000
cell in the way I'm going to show
you in a minute.

248
00:19:12,000 --> 00:19:17,000
So when this new DNA comes in,
this is the E. coli DNA.  And the

249
00:19:17,000 --> 00:19:22,000
virus kind of takes over the cell.
And what it does is it makes it

250
00:19:22,000 --> 00:19:27,000
into a machine or a factor for
making baby virus,

251
00:19:27,000 --> 00:19:32,000
if you will.  So first it makes
phage DNA.

252
00:19:32,000 --> 00:19:36,000
And then it also makes the proteins
that self-assemble to give [its code?

253
00:19:36,000 --> 00:19:41,000
.  So it's kind of reprogrammed the
cell.  And some of the viruses that

254
00:19:41,000 --> 00:19:45,000
infect our cells are essentially
doing the same thing.

255
00:19:45,000 --> 00:19:50,000
They stick their genetic material
into our cells and it takes over.

256
00:19:50,000 --> 00:19:55,000
So unlike the retrovirus that we
were talking about,

257
00:19:55,000 --> 00:20:00,000
this thing is not inserting its DNA
into the genome of the host.

258
00:20:00,000 --> 00:20:07,000
It's just using the cell as a
factory for making more of its own.

259
00:20:07,000 --> 00:20:15,000
So then these assemble so that the
host has now got phage inside it

260
00:20:15,000 --> 00:20:23,000
like this.  And the cells then lice,
which means that they burst open.

261
00:20:23,000 --> 00:20:31,000
The phage, once it's done all of
this, makes a special enzyme that

262
00:20:31,000 --> 00:20:38,000
degrades the bacterial cell wall.
And it makes the cell pop open.

263
00:20:38,000 --> 00:20:46,000
And it releases these free phage.
And if you start with one of them

264
00:20:46,000 --> 00:20:54,000
you might get,
for example, 150 coming out of the

265
00:20:54,000 --> 00:21:02,000
cell when it bursts.
And then each one of these is able

266
00:21:02,000 --> 00:21:10,000
to grab hold of another uninfected E.
coli and start the cycle again.

267
00:21:10,000 --> 00:21:14,000
And the cycle takes usually
something like 20 to 30 minutes for

268
00:21:14,000 --> 00:21:19,000
a bacteriophage.
So it's pretty quick.

269
00:21:19,000 --> 00:21:24,000
One phage absorbing to a bacterium,
injecting its DNA can make that 150

270
00:21:24,000 --> 00:21:29,000
copies of itself in about 20 minutes,
and then each of those can infect.

271
00:21:29,000 --> 00:21:34,000
So how would you detect something
like this?  Well,

272
00:21:34,000 --> 00:21:40,000
the trick that's done is pretty
simple.  You take something like ten

273
00:21:40,000 --> 00:21:45,000
to the eighth bacteria.
Let's say you have some bacteria in

274
00:21:45,000 --> 00:21:51,000
a test tube and then maybe let's say
ten to the two phage,

275
00:21:51,000 --> 00:21:57,000
and then you spread it on just a
Petri plate that the bacteria

276
00:21:57,000 --> 00:22:01,000
can grow on.
So there are many,

277
00:22:01,000 --> 00:22:05,000
many bacteria.  So they're just
going to sort of grow up and form

278
00:22:05,000 --> 00:22:09,000
kind of a wand that will cover the
whole plate.  And if you were to

279
00:22:09,000 --> 00:22:12,000
hold it up to the light you'd see
it's sort of opaque now because the

280
00:22:12,000 --> 00:22:16,000
bacteria have grown up.
But anywhere there was a phage to

281
00:22:16,000 --> 00:22:19,000
start out with,
a single phage it would infect its

282
00:22:19,000 --> 00:22:23,000
original cell,
the cell would burst open,

283
00:22:23,000 --> 00:22:27,000
it would release 150 phage,
they'd infect the nearest 150

284
00:22:27,000 --> 00:22:31,000
bacteria, they'd break open.
And so what happens is the bacteria

285
00:22:31,000 --> 00:22:36,000
trying to grow and cover the plate,
the phage are growing and eating all

286
00:22:36,000 --> 00:22:41,000
the bacteria.  Basically at least
using up all the bacteria in that

287
00:22:41,000 --> 00:22:46,000
area.  So what you get from this are
little holes in the ìlawnî,

288
00:22:46,000 --> 00:22:51,000
and they're called a plaque.
That's the technical term.  Here.

289
00:22:51,000 --> 00:22:56,000
And so it's actually very easy to
see how many phage you have because

290
00:22:56,000 --> 00:23:01,000
you just put them out on a plate.
And I realize this might sound

291
00:23:01,000 --> 00:23:05,000
slightly fanciful.
There is a textbook picture of a

292
00:23:05,000 --> 00:23:09,000
bacteriophage with the DNAs all
packaged up in the head.

293
00:23:09,000 --> 00:23:13,000
It's got a sheath.  It's got little
things that will let it recognize a

294
00:23:13,000 --> 00:23:17,000
particular host.
And it really does look like a

295
00:23:17,000 --> 00:23:21,000
syringe.  And it's got stuff that
squirts, basically the mechanics to

296
00:23:21,000 --> 00:23:25,000
squirt the DNA in.
There's an electron micrograph.

297
00:23:25,000 --> 00:23:30,000
So that's a real one.  This is not
just a textbook cartoon.

298
00:23:30,000 --> 00:23:34,000
It's a pretty accurate depiction.
This was a little thing.  This is

299
00:23:34,000 --> 00:23:38,000
cycling, so don't get it mixed up.
This only happens once.  But this

300
00:23:38,000 --> 00:23:42,000
is basically depicting the idea that
the DNA starts out in the phage and

301
00:23:42,000 --> 00:23:47,000
then it gets injected into the cell.
And once it's in the cell the empty

302
00:23:47,000 --> 00:23:51,000
coat, it doesn't have anything else
to do in this story,

303
00:23:51,000 --> 00:23:55,000
but the DNA takes over.
And then you get, after a little

304
00:23:55,000 --> 00:24:00,000
while, when you've made these
progeny phage the cell breaks open.

305
00:24:00,000 --> 00:24:04,000
And if you assay them,
this is just a picture one of my

306
00:24:04,000 --> 00:24:08,000
post-docs made for me.
I think you can see here's a lawn.

307
00:24:08,000 --> 00:24:12,000
You can sort of see how it's opaque
and you can see those little holes.

308
00:24:12,000 --> 00:24:16,000
There were probably a thousand or
so phage that were put on this plate.

309
00:24:16,000 --> 00:24:21,000
There are several hundred anyway.
And you can just count the number

310
00:24:21,000 --> 00:24:25,000
of holes and then you know how many
phage you've got.

311
00:24:25,000 --> 00:24:29,000
OK?  So that's this system.
Now, what I'd like to now consider

312
00:24:29,000 --> 00:24:33,000
is how we could use genetics to try
and study the essential functions of

313
00:24:33,000 --> 00:24:38,000
that bacteriophage.
How does it replicate?

314
00:24:38,000 --> 00:24:42,000
How does it make its coat?
I want to study the things that are

315
00:24:42,000 --> 00:24:46,000
needed for it to be a phage,
not something that's dispensable.

316
00:24:46,000 --> 00:24:50,000
I want to know essential functions.
So that means I would have to use

317
00:24:50,000 --> 00:24:54,000
conditional mutants of some type so
that I could study it because

318
00:24:54,000 --> 00:24:58,000
otherwise if I broke something that
was critical for the phage's life

319
00:24:58,000 --> 00:25:02,000
cycle I'd never get any phage and I
couldn't do any genetics.

320
00:25:02,000 --> 00:25:09,000
So what I would do is I would look
for temperature sensitive mutants.

321
00:25:09,000 --> 00:25:23,000
The phage.  So they'll form plaques,

322
00:25:23,000 --> 00:25:34,000
let's say plaques at 30 degrees.

323
00:25:34,000 --> 00:25:38,000
No plaques at 37 degrees.
And you go through, and you could

324
00:25:38,000 --> 00:25:43,000
be laborious or cleaver depending on
how you set this up.

325
00:25:43,000 --> 00:25:47,000
But we could make a bunch of
mutants.  And let's call T1,

326
00:25:47,000 --> 00:25:52,000
T2, just give them names like that
as I isolate them.

327
00:25:52,000 --> 00:25:56,000
Now, what I want to show you are
two absolutely standard and critical

328
00:25:56,000 --> 00:26:01,000
genetic ways of analyzing
these mutants.

329
00:26:01,000 --> 00:26:05,000
They all look the same.
Their phenotype is they form

330
00:26:05,000 --> 00:26:09,000
plaques at 30 degrees.
They don't form plaques at 37

331
00:26:09,000 --> 00:26:13,000
degrees.  They could be affecting
one gene.  We could have mutants in

332
00:26:13,000 --> 00:26:18,000
50 genes.  I don't know starting out.
All I know is I've got mutants that

333
00:26:18,000 --> 00:26:22,000
are temperature sensitive.
So genetics gives you a couple of

334
00:26:22,000 --> 00:26:26,000
ways of going at that that will tell
you not only are they in the same

335
00:26:26,000 --> 00:26:31,000
gene or in the different gene.
But it also will tell you something

336
00:26:31,000 --> 00:26:36,000
about their physical relationship
along the DNA.

337
00:26:36,000 --> 00:26:42,000
And this is without knowing
anything about what they do.

338
00:26:42,000 --> 00:26:47,000
So let me show you how that works.
So the first genetic operation is

339
00:26:47,000 --> 00:27:00,000
called a complementation test.

340
00:27:00,000 --> 00:27:03,000
And the thing that I hope will
strike you about particularly these

341
00:27:03,000 --> 00:27:06,000
bacteriophage things is these are so
simple.  I've already told you

342
00:27:06,000 --> 00:27:09,000
basically all the techniques we're
going to be using.

343
00:27:09,000 --> 00:27:12,000
We're going to be taking phage,
we're going to be mixing it with

344
00:27:12,000 --> 00:27:15,000
bacteria, we're going to be putting
them on a plate and we're going to

345
00:27:15,000 --> 00:27:18,000
be counting plaques.
But we're not going to do anything

346
00:27:18,000 --> 00:27:21,000
else and we're going to learn stuff
about whether mutations are in the

347
00:27:21,000 --> 00:27:24,000
same gene or different genes,
between different mutants and

348
00:27:24,000 --> 00:27:28,000
something about the order of the
genes on the chromosome.

349
00:27:28,000 --> 00:27:34,000
And that's the point I'm trying to
drive home right now.

350
00:27:34,000 --> 00:27:41,000
So here's the first idea.
Let's add the T1 mutant plus the T2

351
00:27:41,000 --> 00:27:48,000
mutant to some bacteria.
So we'll put them both into the

352
00:27:48,000 --> 00:27:55,000
same test tube.
And what we want is enough phage --

353
00:27:55,000 --> 00:28:06,000
So every bacterium gets both.

354
00:28:06,000 --> 00:28:12,000
So we want to take, if we take T1
by itself it will grow plagues at 30

355
00:28:12,000 --> 00:28:19,000
degrees, not at 37.
T2 plaques at 30 degrees,

356
00:28:19,000 --> 00:28:25,000
no plaques at 37.  Now we're going
to take some bacteria and put enough

357
00:28:25,000 --> 00:28:32,000
that both of them will get
into the same thing.

358
00:28:32,000 --> 00:28:37,000
Now, of course,
those bacteria are doomed because if

359
00:28:37,000 --> 00:28:42,000
anything happens,
because they've got things inside

360
00:28:42,000 --> 00:28:47,000
them.  So what we do now is then we
add a whole bunch of what we would

361
00:28:47,000 --> 00:28:52,000
call indicator bacteria.
These are ones that haven't been.

362
00:28:52,000 --> 00:28:57,000
And we'll put lots of those in, and
we'll put many fewer of these and

363
00:28:57,000 --> 00:29:02,000
we'll mix these together.
And then we'll plate them out under

364
00:29:02,000 --> 00:29:06,000
two different conditions.
Let's try it at 30 degrees.

365
00:29:06,000 --> 00:29:10,000
Well, in that case, I think we can
figure out what would happen.

366
00:29:10,000 --> 00:29:14,000
Both T1 and T2 can form plaque,
so you'd expect to see plaques.  And

367
00:29:14,000 --> 00:29:18,000
you would indeed see that if you did
this experiment.

368
00:29:18,000 --> 00:29:22,000
Now, the other thing,
though, this is where it gets

369
00:29:22,000 --> 00:29:26,000
interesting, is what would happen if
we plated them at 37 degrees?

370
00:29:26,000 --> 00:29:32,000
Well, on their own neither of them
can form a plaque.

371
00:29:32,000 --> 00:29:38,000
But we've engineered it so that
there are two within each bacterium.

372
00:29:38,000 --> 00:29:44,000
So there are two possible outcomes,
and let's think what they could be.

373
00:29:44,000 --> 00:29:50,000
We could either have mutations in
the same gene that some particular

374
00:29:50,000 --> 00:29:56,000
gene, let's say a gene required for
making the major protein in the coat,

375
00:29:56,000 --> 00:30:02,000
that mutant one is affected in that
gene and mutant two is affected in

376
00:30:02,000 --> 00:30:08,000
the same protein.
So both of them got a broken coat

377
00:30:08,000 --> 00:30:12,000
protein.  And so inside this
bacterium, when the phage are trying

378
00:30:12,000 --> 00:30:17,000
to grow, what you've got is this one
gene.  And this is the T1 mutant and

379
00:30:17,000 --> 00:30:21,000
this is the T2 mutant.
And maybe this one has got a

380
00:30:21,000 --> 00:30:26,000
mutation somewhere and the other one
has got it somewhere else in the

381
00:30:26,000 --> 00:30:31,000
gene, but this gene
is not functional.

382
00:30:31,000 --> 00:30:35,000
So we wouldn't get any plaques.
But what if they were in different

383
00:30:35,000 --> 00:30:47,000
genes?

384
00:30:47,000 --> 00:30:52,000
Let's say one of the mutants was
altered in the gene for a coat

385
00:30:52,000 --> 00:30:57,000
protein and the other one was
altered in a gene that was necessary

386
00:30:57,000 --> 00:31:02,000
for replicating the phage DNA.
So it's a situation like this.

387
00:31:02,000 --> 00:31:08,000
And let's say this is gene A and
that's gene B.

388
00:31:08,000 --> 00:31:14,000
What do you think could happen now?
Get plaques?  Wouldn't get plaques?

389
00:31:14,000 --> 00:31:19,000
Yeah?  I see a lot of nodding.
We'd get plaques because this one

390
00:31:19,000 --> 00:31:25,000
has a good gene A,
so it would make let's say the coat

391
00:31:25,000 --> 00:31:31,000
protein.  This one has a good gene B
so it could make the DNA polymerase

392
00:31:31,000 --> 00:31:36,000
for copying the phage DNA.
And things would be fine.

393
00:31:36,000 --> 00:31:41,000
And so by this very, very simple
test, we could take a whole lot of

394
00:31:41,000 --> 00:31:45,000
TS mutants and we could go through
in a pare-wise fashion,

395
00:31:45,000 --> 00:31:50,000
and we could say oh, I see,
number one, number seven and number

396
00:31:50,000 --> 00:31:55,000
54 apparently affect all mutations
affecting one gene,

397
00:31:55,000 --> 00:32:00,000
and we could put them into
categories by doing this.

398
00:32:00,000 --> 00:32:04,000
And we haven't done anything other
than mix phage and bacteria and look

399
00:32:04,000 --> 00:32:08,000
to see whether they're plaques or
not.  I mean this is very different

400
00:32:08,000 --> 00:32:13,000
than what a biochemist does.
It's a different kind of thinking.

401
00:32:13,000 --> 00:32:17,000
And yet it's enormously powerful.
So this procedure,

402
00:32:17,000 --> 00:32:22,000
which is one of the workhorses of a
geneticist, is known as a

403
00:32:22,000 --> 00:32:26,000
complementation test.
And depending on the organism it

404
00:32:26,000 --> 00:32:31,000
takes a whole bunch of different
sort of technical forms.

405
00:32:31,000 --> 00:32:36,000
But that's the principle of the
thing, that if you have one good

406
00:32:36,000 --> 00:32:41,000
copy of the gene and a broken one
then you can survive in most cases

407
00:32:41,000 --> 00:32:46,000
because usually the one will be
enough to get you through here.

408
00:32:46,000 --> 00:32:51,000
So that's one of the things that
geneticists do.

409
00:32:51,000 --> 00:32:56,000
And see how powerful it is for
something that's a very

410
00:32:56,000 --> 00:33:02,000
simple manipulation.
But let me now tell you the other

411
00:33:02,000 --> 00:33:08,000
kind of test that geneticists do.
It's a slightly different principle

412
00:33:08,000 --> 00:33:15,000
but just as powerful and gives you a
different kind of information.

413
00:33:15,000 --> 00:33:22,000
This is known as a recombination
test.  So what we're going to do in

414
00:33:22,000 --> 00:33:28,000
this case now is we're going to
allow two mutants to grow together

415
00:33:28,000 --> 00:33:36,000
in the same cell.
Let's say two mutants.

416
00:33:36,000 --> 00:33:45,000
And we'll use T1 and T2 again to
grow together in the same cell.

417
00:33:45,000 --> 00:33:53,000
Now, for example, remember up here
we mixed both of them in this so

418
00:33:53,000 --> 00:34:02,000
they both were inside this bacteria
and then when we plated it up,

419
00:34:02,000 --> 00:34:09,000
up here at 30 degrees we got plaques?
We would have gotten plaques from

420
00:34:09,000 --> 00:34:14,000
every single infected bacteria.
Well, those plaques probably have

421
00:34:14,000 --> 00:34:19,000
ten to the ninth phage in them.
And those were phage that grew

422
00:34:19,000 --> 00:34:24,000
together under permissive conditions.
OK?  So let's take those,

423
00:34:24,000 --> 00:34:33,000
re-suspend them --

424
00:34:33,000 --> 00:34:38,000
-- and bring them over here.
Now, we'll add them to some

425
00:34:38,000 --> 00:34:43,000
bacteria.  So bacteria in here.
But we're going to do it under

426
00:34:43,000 --> 00:34:48,000
different conditions now.
We don't want complementation

427
00:34:48,000 --> 00:34:54,000
taking place, so we'll make sure
that we have less than one phage --

428
00:34:54,000 --> 00:35:03,000
-- per bacterium.

429
00:35:03,000 --> 00:35:09,000
So we cannot do this
complementation thing anymore.

430
00:35:09,000 --> 00:35:16,000
We just got rid of it by using a
different ratio of phage to the

431
00:35:16,000 --> 00:35:23,000
bacteria.  So now what I want to do,
I'm going to plate this out at 37

432
00:35:23,000 --> 00:35:30,000
degrees.  We could add an indicator
if we wanted again.

433
00:35:30,000 --> 00:35:37,000
Well, that may seem like a stupid

434
00:35:37,000 --> 00:35:42,000
experiment in the sense that T1
wouldn't grow by itself and T2

435
00:35:42,000 --> 00:35:47,000
wouldn't grow by itself at 37
degrees.  And all I've done is let

436
00:35:47,000 --> 00:35:52,000
them grow together.
So if all we had in that population

437
00:35:52,000 --> 00:35:57,000
was what we started with there
wouldn't be any plaques.

438
00:35:57,000 --> 00:36:02,000
But if you do that what you will
find is you'll find

439
00:36:02,000 --> 00:36:12,000
some rare plaques.

440
00:36:12,000 --> 00:36:18,000
And these are what are known as
recombinants.  And let me now just

441
00:36:18,000 --> 00:36:24,000
give you a sense of how these
recombinants arise.

442
00:36:24,000 --> 00:36:30,000
So let's imagine that this is the
mutation and here's

443
00:36:30,000 --> 00:36:35,000
our T1 bacterium.
Here's its DNA.

444
00:36:35,000 --> 00:36:41,000
And let's say there's a function
here that it's wild type for and

445
00:36:41,000 --> 00:36:47,000
it's got a mutation down here.
The other one, T2 has got the

446
00:36:47,000 --> 00:36:53,000
mutation here but it's wild type for
there.  That's the kind of thing we

447
00:36:53,000 --> 00:36:59,000
were talking about,
a gene A and a gene B,

448
00:36:59,000 --> 00:37:04,000
although it's more general than that.
But what happens when these things

449
00:37:04,000 --> 00:37:10,000
are growing together is under rare
circumstances this interesting thing

450
00:37:10,000 --> 00:37:15,000
happens.  Since this is the two
strands of DNA and since these

451
00:37:15,000 --> 00:37:21,000
phages are almost identical and this
piece of DNA is the same as that

452
00:37:21,000 --> 00:37:26,000
piece of DNA.  And if a break every
happened in one of these strands,

453
00:37:26,000 --> 00:37:32,000
what can happen is it can invade the
other strand and displace it.

454
00:37:32,000 --> 00:37:38,000
And this strand can do a little
switcheroo and come over here like

455
00:37:38,000 --> 00:37:45,000
this.  So now we've got the plus and
the plus and the minus and the minus.

456
00:37:45,000 --> 00:37:52,000
So this is an intermediate but
these things happen.

457
00:37:52,000 --> 00:37:59,000
You get little breaks in DNA from
DNA damage and other things.

458
00:37:59,000 --> 00:38:02,000
And the other piece of DNA can go
off and pioneer and find another

459
00:38:02,000 --> 00:38:06,000
molecule.  And then there are
enzymes that resolve this.

460
00:38:06,000 --> 00:38:09,000
And if we cut it right here,
we'd just go back to what we had

461
00:38:09,000 --> 00:38:13,000
before.  But if you cut this strand
here, and you may have to sit down

462
00:38:13,000 --> 00:38:16,000
and draw this out because this,
for me, was not intuitive when I was

463
00:38:16,000 --> 00:38:20,000
learning this thing.
You'll see what happens now.

464
00:38:20,000 --> 00:38:23,000
The end of this strand will go over
and join to there.

465
00:38:23,000 --> 00:38:27,000
The end of this strand will join
and go here.

466
00:38:27,000 --> 00:38:32,000
And what you will get out of that is
one phage that's got both of the

467
00:38:32,000 --> 00:38:38,000
pluses and one of the phage that's
got both of the minuses.

468
00:38:38,000 --> 00:38:43,000
And I'll call this sort of T1,
T2 to indicate that it has got both

469
00:38:43,000 --> 00:38:49,000
of the mutations.
So this would be what we could

470
00:38:49,000 --> 00:38:55,000
detect over there.
That would be one of the rare wild

471
00:38:55,000 --> 00:39:00,000
types.
And I'll assert to you that this guy

472
00:39:00,000 --> 00:39:06,000
here has two mutations in
it instead of one.

473
00:39:06,000 --> 00:39:13,000
What's the phenotype of the one that

474
00:39:13,000 --> 00:39:17,000
has both mutations?
It cannot grow.  It can make

475
00:39:17,000 --> 00:39:21,000
plaques at 30 degrees.
It cannot make plaques at 37.

476
00:39:21,000 --> 00:39:25,000
If I got up and said I'm sure this
phage has two mutations.

477
00:39:25,000 --> 00:39:29,000
It has both T1 and T2 mutations in
it.

478
00:39:29,000 --> 00:39:33,000
And I say prove it to me.
Anybody see how you could do it

479
00:39:33,000 --> 00:39:40,000
given what I've already told you?

480
00:39:40,000 --> 00:39:44,000
Exactly.  If I tried it in a
complementation test with T1 it

481
00:39:44,000 --> 00:39:48,000
wouldn't compliment because both
would be broken in T1.

482
00:39:48,000 --> 00:39:52,000
If I tried to complement T2 it
wouldn't work because it's broken in

483
00:39:52,000 --> 00:39:56,000
T2.  And just by using these tiny
little simple manipulations that

484
00:39:56,000 --> 00:40:00,000
I've told you,
I can even see that something that

485
00:40:00,000 --> 00:40:05,000
has got a double mutant we could
sort it out at the bench.

486
00:40:05,000 --> 00:40:09,000
You could walk in and tell me the
next morning what the result was.

487
00:40:09,000 --> 00:40:13,000
In fact, phage grows so fast you
might even be able to do it in the

488
00:40:13,000 --> 00:40:17,000
morning and tell me before you went
home at night.

489
00:40:17,000 --> 00:40:21,000
So this is, as I say,
called a recombination test.

490
00:40:21,000 --> 00:40:25,000
And it's giving you a different
kind of information,

491
00:40:25,000 --> 00:40:29,000
but it's an extraordinarily powerful
technique for another reason,

492
00:40:29,000 --> 00:40:33,000
is that the recombination frequency
can be measured.

493
00:40:33,000 --> 00:40:41,000
We'll call RF.

494
00:40:41,000 --> 00:40:45,000
And this is the recombinants over
the total.  So,

495
00:40:45,000 --> 00:40:49,000
in our case, this would be the
number of wild type,

496
00:40:49,000 --> 00:40:53,000
plus the number of these double
mutants over the total of T1 plus

497
00:40:53,000 --> 00:40:57,000
the total of T2,
which would be the dominant members

498
00:40:57,000 --> 00:41:03,000
of this population.
Because this is a relatively rare

499
00:41:03,000 --> 00:41:10,000
event, plus the wild type,
plus the T1, T2.  And the thing that

500
00:41:10,000 --> 00:41:17,000
is so useful is the probability of,
geneticists call this a crossover,

501
00:41:17,000 --> 00:41:24,000
this kind of crossover happening is
proportional to the distance between

502
00:41:24,000 --> 00:41:30,000
these things.
If they're a very long distance

503
00:41:30,000 --> 00:41:34,000
apart there's a lot of DNA,
and the chances of it happening are

504
00:41:34,000 --> 00:41:38,000
much higher than if the two
mutations are very close together.

505
00:41:38,000 --> 00:41:42,000
It makes sense just from First
Principles.  So the recombination

506
00:41:42,000 --> 00:41:52,000
frequency varies as the distance --

507
00:41:52,000 --> 00:41:58,000
-- between the mutations.
So let's imagine that I do a cross

508
00:41:58,000 --> 00:42:05,000
like this.
We'd grow T1 plus T2 and we measure

509
00:42:05,000 --> 00:42:11,000
the recombination frequency,
and I find that it's 4%.  4% of the

510
00:42:11,000 --> 00:42:17,000
plaques are mutants out of
everything that's in there.

511
00:42:17,000 --> 00:42:23,000
And let me try another one.
I'll take T2 and I'll cross it with

512
00:42:23,000 --> 00:42:29,000
the next mutant phage of isolated T3.
And let's say,

513
00:42:29,000 --> 00:42:35,000
in this case, the recombination
frequency is 5%.

514
00:42:35,000 --> 00:42:40,000
Because I know they're different
distances, but if you think about it

515
00:42:40,000 --> 00:42:45,000
you'll realize there are two kinds
of maps we can draw.

516
00:42:45,000 --> 00:42:50,000
These data are compatible with the
gene order being one,

517
00:42:50,000 --> 00:42:55,000
two, with this being a distance that
corresponds to a 4% recombination

518
00:42:55,000 --> 00:43:00,000
frequency, and three with this being
the distance that corresponds

519
00:43:00,000 --> 00:43:05,000
to the 5%.
But it's also compatible,

520
00:43:05,000 --> 00:43:11,000
isn't it, with this where we have
one, two and three here.

521
00:43:11,000 --> 00:43:17,000
There's the 4%.  And from there to
there is the 5%.

522
00:43:17,000 --> 00:43:23,000
Yeah, that's right.
Two to three.  One to two is 4% and

523
00:43:23,000 --> 00:43:29,000
two to three is 5%
in both of these.

524
00:43:29,000 --> 00:43:36,000
One to two is 4%.
What did I do wrong?

525
00:43:36,000 --> 00:43:43,000
Two.  I guess I've got to do it
this way, two,

526
00:43:43,000 --> 00:43:51,000
one.  Is that going to do it?
What did I do with my example here?

527
00:43:51,000 --> 00:44:00,000
Yeah.  Hang on a second.  OK.

528
00:44:00,000 --> 00:44:04,000
Let's go back to where I was and see
if I can reconstruct this.

529
00:44:04,000 --> 00:44:08,000
OK.  There's one, and two is 4%,
and we want two to three 5%.  OK,

530
00:44:08,000 --> 00:44:13,000
right.  So it's going to be here.
Here we go.  Two to three.  Excuse

531
00:44:13,000 --> 00:44:17,000
me.  It's got to be farther over
here.  There's three.

532
00:44:17,000 --> 00:44:25,000
There's the 5%.

533
00:44:25,000 --> 00:44:32,000
OK.  Now we've got it,
once I change these numbers.

534
00:44:32,000 --> 00:44:38,000
The 4%, the 5%,
the 4%, the 5%.  OK.

535
00:44:38,000 --> 00:44:44,000
I thought I was over this cold.
I guess I'm not quite over this

536
00:44:44,000 --> 00:44:50,000
cold.  OK.  Could you devise an
experiment that would distinguish

537
00:44:50,000 --> 00:44:56,000
between those maps?
Yeah?  Yeah.  You've got it.

538
00:44:56,000 --> 00:45:02,000
Take T1 and T3.
One of those you'll get a 9%.

539
00:45:02,000 --> 00:45:08,000
One of them you'll get a 1%.  Isn't
that amazing?  I mean it's so simple,

540
00:45:08,000 --> 00:45:14,000
but I think you can perhaps see some
of the power of genetics here.

541
00:45:14,000 --> 00:45:19,000
All we've done is we've got things
that we know can form plaques at 30

542
00:45:19,000 --> 00:45:25,000
and not at 37.
We haven't done anything other than

543
00:45:25,000 --> 00:45:31,000
mix them with bacteria and
then count plaques.

544
00:45:31,000 --> 00:45:35,000
And we've been able to make
inferences in a living organism

545
00:45:35,000 --> 00:45:39,000
about mutations in genes that are
absolutely essential for that

546
00:45:39,000 --> 00:45:44,000
organism to grow.
So what phage geneticists were able

547
00:45:44,000 --> 00:45:48,000
to do over the years then was they
would make a map of all of these

548
00:45:48,000 --> 00:45:53,000
different genes down to the phage
genome and then the biochemist would

549
00:45:53,000 --> 00:45:57,000
go in and work it out.
And people studying mice would make

550
00:45:57,000 --> 00:46:02,000
maps of genes along mice.
And it's only been in the last

551
00:46:02,000 --> 00:46:06,000
handful of years we've been able to
go in and sequence the DNA and find

552
00:46:06,000 --> 00:46:11,000
out where all of these things are.
So I will see you guys after.  I

553
00:46:11,000 --> 00:46:15,000
hope you have a wonderful spring
break.  And I think you'll really

554
00:46:15,000 --> 00:46:20,000
enjoy hearing Penny.
And we'll start in on diploid

555
00:46:20,000 --> 00:46:24,000
genetics and Mendel and stuff as
soon as we get back.

556
00:46:24,000 --> 00:46:27,000
OK?  So see you in a little bit.