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Good morning.
Good morning.

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So, what I would like to do today
is pick up on our basic theme of

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molecular biology. We've
talked about DNA replication.

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The transcription of DNA into
RNA, and the translation of RNA

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into protein. We discussed last
time some of the variations between

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different types of organisms:
viruses, prokaryotes,

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eukaryotes, with respect to the
details of how they do that in

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general that bacteria have
circular DNA chromosomes typically

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that eukaryotes have
linear chromosomes,

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etc. What I'd like to talk
about today is variation,

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but variation not between organisms
but within an organism from time to

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time and place to place, namely,
how it is that some genes or

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gene activities are turned on, on
some occasions, and turned off on

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other occasions.
This is, obviously,

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a very important problem
to an organism, particularly

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to somebody like you who's
a multi-cellular organism,

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and has the same DNA instruction
set in all of your cells.

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It's obviously quite important to
make sure that the same basic code

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is doing different
things in different cells.

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It's important, also, to a
bacterium to make sure that

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it's doing different
things at different times,

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depending on its environment.
So, I'm going to talk about a very

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particular system today as an
illustration of how genes are

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regulated, but before
we do that, let's

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Ask, where are the different
places in this picture?

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DNA goes to DNA goes to RNA goes
to protein, in which you might,

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in principle, regulate the activity
of a gene. Could you regulate the

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activity of a gene by actually
changing the DNA encoded in the

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genome? So, why not?
Because what? It becomes a

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different gene. Yeah,
that's just a definition.

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Why couldn't the cell just decide
that I want this gene now to change

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in some way? Oh, I don't
know, I'll alter the DNA

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sequence in some way. And,
that'll make the gene work.

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Could that happen? Is that allowed?
Yeah, it turns out to happen.

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It's not the most common thing,
and it's not the thing they'll talk

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about in the textbooks a lot but
you can actually do regulation.

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So, the levels of regulation are
many, and one is actually at the

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level of DNA rearrangement.
As we'll come to later in the

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course, for example, your
immune system creates new,

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functional genes by rearranging
locally some pieces of DNA,

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some bacteria, particularly
infectious organisms control whether

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genes are turned on or off
by actually going in there,

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and flipping around a piece
of DNA in their chromosome.

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And, that's how they turn the gene
on or off is they actually go in and

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change the genome. There's
some protein that actually

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flips the orientation of a segment
of DNA. Now, these are a little

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funky, and we're not going
to talk a lot about them,

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but you should know, almost
anything that can happen does

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happen and gets exploited in
different ways by organisms.

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So, DNA rearrangement
certainly happens. It's rare,

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but it's always
cool when it happens.

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So, it's fun to look at.
And, something like the immune

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system can't be dismissed as simply
an oddity. That's an incredibly

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important thing. The
most common form is at the

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level of transcriptional regulation,
where whether or not a transcript

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gets made is how it's processed
can be different. First off,

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the initiation of transcription
that RNA polymerase should happen to

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sit down at this gene on this
occasion and start transcribing it

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is a potentially regulatable (sic)
step that maybe you're only going to

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turn on the gene for beta-globin and
alpha-globin that together make the

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two components of hemoglobin,
and you're only going to turn them

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on in red blood cells, or
red blood cell precursors,

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and that could be done at the
level of whether or not you make the

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message in the first place.
That's one place it can be done.

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Another place is the splicing
choices that you make.

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With respect to your message, you
get this thing with a number of

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different potential exons, and
you can regulate how this gene

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is used by deciding to splice it
this way, and skip over that exon

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perhaps, or not skip over that
exon. That alternative spicing is a

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powerful way to regulate.
And then finally, you can also

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regulate at the level
of mRNA stability.

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Stability means the persistence of
the message, the degradation of the

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message. It could be
that in certain cells,

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the message is protected so
that it hangs around longer.

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And, in other cells, perhaps,
it's unprotected and it's

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degraded very rapidly. If
it's degraded very rapidly,

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it doesn't get a chance to make a
protein or maybe it doesn't get to

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make too many copies of the protein.
If it's persistent for a long time,

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it can make a lot
of copies of protein.

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All of those things can and
do occur. Then, of course,

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there is the regulation at
the level of translation.

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Translation, if I give you an mRNA,
is it automatically going to be

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translated? Maybe the cell has a
way to sequester the RNA to ramp it

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up in some way so that it
doesn't get to the ribosome under

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some conditions, and under
other conditions it does

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get to the ribosome, or
some ways to block in other

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manners than just sequestering it,
but to physically block whether or

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not this message gets translated,
what turns out that there's a

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tremendous amount of that.
It's, again, not the most common,

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but we're learning, particularly
over the last couple of years,

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that regulation of the translation
of an mRNA is important.

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There are, although I won't
talk about them at length,

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an exciting new set of
genes called micro RNA's,

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teeny little RNAs that encode 21-22
base pair segments that are able to

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pair with a messenger RNA and
interfere in some ways partially

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with its translatability. And
so, by the number and the kinds

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of little micro RNAs that are there,
organisms can tweak up or down how

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actively a particular
message is being translated.

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So, the ability to regulate
translation in a number of different

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ways is important.
And then, of course,

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there's post-translational
control. Once a protein is made,

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there's post-translational
regulation that could happen.

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It could be that the protein
is modified in some way.

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The proteins say completely
inactive unless you put a phosphate

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group on it, and some enzyme comes
along and puts a phosphate group on

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it. Or, it's inactive until you
take off the phosphate group.

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All sorts of post-translational
modifications can occur to proteins

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after the amino acid chain is made
that can affect whether or not the

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protein is active. Every
one of these is potentially a

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step by which an organism can
regulate whether or not you have a

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certain biochemical activity present
in a certain amount at a certain

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time. And, every one of these
gets used. This is the thing about

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coming to a system that has been in
the process of evolution for three

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and a half billion years is that
even little differences can be

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fought over as competitive
advantages, and can be fixed

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by an organism. So, if a
tiny little thing began to

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help the organism slightly,
it could reach fixation. And,

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you're coming along to this system,
which has had about three and a half

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billion years of patches
to the software code,

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and it's just got all sorts of
layers and regulation piled on top

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of it. All of these things happen.
But, what we think is the most

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important out of this whole
collection is this guy.

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The fundamental place at which
you're going to regulate whether or

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not you have the product of a gene
is whether you bother to transcribe

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its RNA. But I do want
to say because, yes? And,

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which exons you used
and which aren't? Yeah,

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well, there are tissue-specific
factors that are gene-specific

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that can influence that. And,
surprisingly little is known

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about the details. There
are a couple of cases where

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people know, but as you'd imagine,
you actually need a regulatory

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system in that tissue to be able
to decide to skip over that exon.

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And, the mechanics of that
surprisingly are understood in very

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few cases. And, you
might think that evolution

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wouldn't like to use that as the
most common thing because you really

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do have to make a specialized
thing to do that. So, that's what

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happens on these. That's
one in particular where I

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think a tremendous amount
of more work has to happen.

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mRNA stability, we understand some
of it but not all the factors in

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this business. I was
telling you about translation

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with these little micro-RNAs is
stuff that's really only a few years

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old that people have
come to understand. So,

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there's a lot to be understood about
these things. I'm going to tell you

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about initiation of mRNAs,
because it's the area where we know

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the most, and I think it'll give you
a good idea of the general paradigm.

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But, any of you who want to go
into this will find that there's a

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tremendous amount more to still
be discovered about these things.

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So, the amount of protein that
a cell might make varies wildly.

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Your red blood cells, 80%
of your red blood cells,

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protein, is alpha or beta-globin.
It's a huge amount. That's not

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true in any other cell in your body.
So, we were talking about pretty

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significant ranges of difference
as to how much protein is made.

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How do things like that happen?
Well, I'm going to describe the

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simplest and classic case of
gene regulation and bacteria,

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and in particular, the
famous lack operon of E coli.

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So, this was the first case in
which regulation was ever really

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worked out, and it stands today
as a very good paradigm of how

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regulation works. E
coli, in order to grow,

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needs a carbon source. In
particular, E coli is fond of sugar.

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It would like to have a sugar
to grow on. Given a choice,

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what's E coli's favorite sugar?
It's glucose, right, because we

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have the whole cycle of glucose.
The whole pathway of glucose goes

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to pyruvate, which we've talked
about, and glucose is the preferred

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sugar to go into that
pathway, OK, of glycolysis.

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Glycolysis: the breakdown of glucose.
But, suppose there's no glucose

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available. Is E coli willing
to have a different sugar?

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Sure, because E coli's not stupid.
If it were to refuse another sugar,

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it wouldn't be able to grow. So, it
has a variety of pathways that will

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shunt other sugars to glucose,
which will then allow you to go

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through glycolysis,
etc. Now, given a choice,

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it would prefer to use the glucose.
But if not, suppose you gave it

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lactose. Lactose is a disaccharide.
It's milk sugar, and I'll just

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briefly sketch, so lactose
is a disaccharide where

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you've got a glucose
and a galactose.

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Glucose plus galactose equals
lactose. So, if E coli is given

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galactose, it is able to break it
down into glucose plus galactose.

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And it does that by a particular
enzyme called beta galactosidase,

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which breaks down glactosides.
And, it'll give you galactose plus

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glucose. How much
beta-galactosidase does an E coli

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cell have around? Sorry?
None? But how does it do this?

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When it needs it, it'll
synthesize it. When it needs it,

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like, there's no glucose and
there's a lot of galactose around,

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how much of it will there be?
A lot. It turns out that in

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circumstances where E coli is
dependent on galactose as its fuel,

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something like 10%
of total protein

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can be beta-gal under the
circumstances when you have

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galactose but no glucose.
Sorry? Sorry, when you have

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lactose but no glucose.
Thank you. So, when you have

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lactose but no glucose, E coli
has 10% of its protein weight

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as beta-galactosidase. Wow.
But when you have glucose

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around or you don't have lactose
around, you have very little.

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It could be almost none,
trace amounts. So, why do this?

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Why not, for example, just have a
far more reasonable some compromise?

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Like, let's always just have
1% of beta-galactosidase.

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Why do we need the 0-10%?
10%'s actually extremely high.

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So what. It's a good insurance
policy. So, if I only have

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galactose, I need more. Well,
I mean, 1% will still digest

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it. I'll still do it.
What's the problem? Sorry?

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So what, I do it at a slower rate.
Life's long. Why not? Ah, it has

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to compete. So, if the
cell to the left had a

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mutation that got it to
produce four times as much,

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then it would soak up the
lactose in the environment,

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grow faster, etc. etc.,
and we could have competed.

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So, these little tuning mutations
have a huge effect amongst this

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competing population of bacteria.
And so, if E coli currently thinks

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that it's really good to have almost
non at sometimes and 10% at other

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times, you can bet that it's worked
that out through the product of

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pretty rigorous competition,
that it doesn't want to waste the

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energy making this when you don't
need it, and that when you do need

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it, you really have to compete hard
by growing as fast as you can when

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you have that lactose around.
OK. So, how does it actually get

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the lactose, sorry, keep
me honest on lactose versus

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galactose, into the cell?
It turns out that it also has

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another gene product, another
protein, which is a lactose

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permease. And, any
guesses as to what a

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lactose permease does? It
makes the cell permeable to

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lactose, right, good. So,
the lactose can get into

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the cell, and then beta-gal can
break it down into galactose plus

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glucose. These two things,
in fact, both get regulated,

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beta-gal and this lactose
permease. So, how does it work?

220
00:18:00,000 --> 00:18:07,000
Let's take a look now at the
structure of the lack operon.

221
00:18:07,000 --> 00:18:14,000
So, I mentioned briefly last time,
what's an operon? Remember we said

222
00:18:14,000 --> 00:18:21,000
that in bacteria, you often
made a transcript that had

223
00:18:21,000 --> 00:18:29,000
multiple proteins that
were encoded on it.

224
00:18:29,000 --> 00:18:33,000
A single mRNA could get made, and
multiple starts for translation

225
00:18:33,000 --> 00:18:37,000
could occur, and you could
make multiple proteins.

226
00:18:37,000 --> 00:18:41,000
And, this would be a good thing
if you wanted to make a bunch of

227
00:18:41,000 --> 00:18:45,000
proteins that were a part of
the same biochemical pathway.

228
00:18:45,000 --> 00:18:49,000
Such an object, a regulated piece
of DNA that makes a transcript

229
00:18:49,000 --> 00:18:53,000
encoding multiple polypeptides is
called an operon because they're

230
00:18:53,000 --> 00:18:57,000
operated together. So,
let's take a look here at the

231
00:18:57,000 --> 00:19:03,000
lack operon. I said
there was a promoter.

232
00:19:03,000 --> 00:19:09,000
Here is a promoter for the operon,
and we'll call it P lack, promoter

233
00:19:09,000 --> 00:19:16,000
for the lack operon. Here
is the first gene that is

234
00:19:16,000 --> 00:19:23,000
encoded. So, the message will
start here, actually about here,

235
00:19:23,000 --> 00:19:30,000
and start going off. And, the
first gene is given the name lack Z.

236
00:19:30,000 --> 00:19:34,000
It happens to encode
beta-galactosidase enzyme.

237
00:19:34,000 --> 00:19:38,000
Remember, they did a mutant hunt,
and when they did the mutant hunt,

238
00:19:38,000 --> 00:19:42,000
they didn't know what each gene
was as they isolated mutants.

239
00:19:42,000 --> 00:19:46,000
So, they just gave them
names of letters. And so,

240
00:19:46,000 --> 00:19:50,000
it's called lack Z. And,
everybody in molecular biology

241
00:19:50,000 --> 00:19:54,000
knows this is the lack Z gene,
although Z has nothing to do with

242
00:19:54,000 --> 00:19:58,000
beta-galactosidase. It was
just the letter given to it.

243
00:19:58,000 --> 00:20:02,000
But, it's stuck.
Next is lack Y.

244
00:20:02,000 --> 00:20:07,000
And, that encodes the permease.
And, there is also lack A, which

245
00:20:07,000 --> 00:20:12,000
encodes a transacetylase, and
as far as I'm concerned you can

246
00:20:12,000 --> 00:20:17,000
forget about it. OK, but
I just mentioned that it is

247
00:20:17,000 --> 00:20:22,000
there, and it actually does
make three polypeptides.

248
00:20:22,000 --> 00:20:27,000
We won't worry about it,
OK, but it does make a

249
00:20:27,000 --> 00:20:32,000
transacetylase, OK? But it
won't figure in what we're

250
00:20:32,000 --> 00:20:36,000
going to talk about, and
actually remarkably little is

251
00:20:36,000 --> 00:20:41,000
known about the transacetylase.
There's also one other gene I need

252
00:20:41,000 --> 00:20:46,000
to talk about, and
that's over here,

253
00:20:46,000 --> 00:20:50,000
and that's called lack I.
And, it too has a promoter,

254
00:20:50,000 --> 00:20:55,000
which we can call PI, for
the promoter for lack I.

255
00:20:55,000 --> 00:21:00,000
And, this encodes a
very interesting protein.

256
00:21:00,000 --> 00:21:05,000
So, we get here one message
encoding one polypeptide here.

257
00:21:05,000 --> 00:21:11,000
This mRNA encodes one polypeptide.
It is monocystronic. This guy here

258
00:21:11,000 --> 00:21:17,000
is a polycystronic message. It
has multiple cystrons, which is

259
00:21:17,000 --> 00:21:23,000
the dusty old name for these regions
that were translated into distinct

260
00:21:23,000 --> 00:21:29,000
proteins. And so,
that's that mRNA.

261
00:21:29,000 --> 00:21:40,000
So, lack I, this encodes
a very interesting protein,

262
00:21:40,000 --> 00:21:52,000
which is called the lack repressor.
The lack repressor, actually I'll

263
00:21:52,000 --> 00:22:04,000
bring this down a
moment, is not an enzyme.

264
00:22:04,000 --> 00:22:10,000
It's not a self-surface channel
for putting in galactose.

265
00:22:10,000 --> 00:22:17,000
It is a DNA binding protein.
It binds to DNA. But, it's not a

266
00:22:17,000 --> 00:22:23,000
nonspecific DNA binding protein
that binds to any old DNA.

267
00:22:23,000 --> 00:22:30,000
It has a sequence-specific preference.

268
00:22:30,000 --> 00:22:35,000
It's a protein that has a particular
confirmation, a particular shape,

269
00:22:35,000 --> 00:22:40,000
a particular set of amino acids
sticking out, that it combined into

270
00:22:40,000 --> 00:22:46,000
the major groove of DNA in a
sequence-specific fashion such that

271
00:22:46,000 --> 00:22:51,000
it particularly likes to recognize
a certain sequence of nucleotides and

272
00:22:51,000 --> 00:22:57,000
binds there. Where is the specific
sequence of nucleotides where this

273
00:22:57,000 --> 00:23:03,000
guy likes to bind? It so
happens that it's there.

274
00:23:03,000 --> 00:23:11,000
And this is called the operator
sequence or the operator site.

275
00:23:11,000 --> 00:23:18,000
So, this protein likes
to go and bind there. Now,

276
00:23:18,000 --> 00:23:26,000
I've drawn this, by the way,
so that this operator site is

277
00:23:26,000 --> 00:23:34,000
actually right overlapping
the promoter site.

278
00:23:34,000 --> 00:23:40,000
Who likes to bind at the
promoter site? RNA polymerase.

279
00:23:40,000 --> 00:23:46,000
What's going to happen if the lack
repressor protein is sitting there?

280
00:23:46,000 --> 00:23:52,000
RNA polymerase can't
bind. It's just physically,

281
00:23:52,000 --> 00:23:58,000
blocked from binding. So,
let's examine some cases here.

282
00:23:58,000 --> 00:24:06,000
Let's suppose that
we look at here

283
00:24:06,000 --> 00:24:14,000
at our gene. We've got our promoter,
P lack. We've got the operator site

284
00:24:14,000 --> 00:24:22,000
here. We've got the lack Z gene
here, and we've got the lack

285
00:24:22,000 --> 00:24:31,000
repressor, lack I, the
repressor sitting there.

286
00:24:31,000 --> 00:24:38,000
Polymerase tries to come along
to this, and it's blocked.

287
00:24:38,000 --> 00:24:45,000
So, what will happen in terms
of the transcription of the lack

288
00:24:45,000 --> 00:24:52,000
operon: no mRNA.
So, that's great.

289
00:24:52,000 --> 00:24:59,000
So, we've solved one
problem right off the bat.

290
00:24:59,000 --> 00:25:03,000
We want to be sure that sometimes
there's going to be no mRNA made.

291
00:25:03,000 --> 00:25:07,000
This way, we're not going to
waste any metabolic energy,

292
00:25:07,000 --> 00:25:11,000
making beta-galactosidase.
Are we done? No? Why not.

293
00:25:11,000 --> 00:25:16,000
We've got to sometimes
make beta-galactosidase.

294
00:25:16,000 --> 00:25:20,000
So, we've got to get that
repressor off there. Well,

295
00:25:20,000 --> 00:25:24,000
how is the repressor going to
come off there? When do we want the

296
00:25:24,000 --> 00:25:29,000
repressor off there: when
there's lactose present.

297
00:25:29,000 --> 00:25:34,000
So, somehow we need to build
some kind of an elaborate sensory

298
00:25:34,000 --> 00:25:39,000
mechanism that is able to
tell when lactose is present,

299
00:25:39,000 --> 00:25:44,000
and send a signal to the
repressor protein saying,

300
00:25:44,000 --> 00:25:49,000
hey, lactose is around. The
signal gets transmitted all the

301
00:25:49,000 --> 00:25:55,000
way to the repressor protein, and
the repressor protein comes off.

302
00:25:55,000 --> 00:26:00,000
What kind of an elaborate
sensory mechanism might be built?

303
00:26:00,000 --> 00:26:05,000
Use lactose as what? So, this
is actually pretty simple.

304
00:26:05,000 --> 00:26:11,000
You're saying just take lactose,
and you want lactose to be its own

305
00:26:11,000 --> 00:26:16,000
signal? So, if lactose were
to just bind to the repressor,

306
00:26:16,000 --> 00:26:21,000
the repressor might then know
that there was lactose around.

307
00:26:21,000 --> 00:26:27,000
Well, what would it do if
lactose bound to it? Sorry? Why

308
00:26:27,000 --> 00:26:33,000
would it fall off? Yep. More
interested in the lactose.

309
00:26:33,000 --> 00:26:39,000
So, if you're suggestion,
this is good. I like the design

310
00:26:39,000 --> 00:26:45,000
work going on here. The
suggestion is that if lactose

311
00:26:45,000 --> 00:26:51,000
binds to this here,
binds to our repressor,

312
00:26:51,000 --> 00:26:57,000
it's going to fall off because
it's more interested in lactose

313
00:26:57,000 --> 00:27:03,000
than in the DNA. Now, how
is the interest actually

314
00:27:03,000 --> 00:27:07,000
conveyed into something material?
Because the actual level of

315
00:27:07,000 --> 00:27:11,000
cognitive like or dislike for DNA
on the part of this polypeptide is

316
00:27:11,000 --> 00:27:15,000
unclear, you may be
anthropomorphizing slightly with

317
00:27:15,000 --> 00:27:19,000
regard to this polypeptide chain.
So, mechanistically, what's going

318
00:27:19,000 --> 00:27:23,000
to happen? Shape. Yes,
shape? Change confirmation,

319
00:27:23,000 --> 00:27:27,000
the binding act, the act of
binding lactose creates some energy,

320
00:27:27,000 --> 00:27:31,000
may change the
shape of the protein,

321
00:27:31,000 --> 00:27:35,000
and that shape of the protein may,
in the process of wiggling around to

322
00:27:35,000 --> 00:27:40,000
bind lactose may de-wiggle some
other part of it that now no longer

323
00:27:40,000 --> 00:27:44,000
binds so well to DNA. That
is exactly what happens.

324
00:27:44,000 --> 00:27:49,000
Good job. So, you guys
have designed, in fact,

325
00:27:49,000 --> 00:27:54,000
what really happens. What
happens is what's called an

326
00:27:54,000 --> 00:27:58,000
allosteric change. It
just means other shape.

327
00:27:58,000 --> 00:28:03,000
So, it just changes its shape,
that it changes shape on binding of

328
00:28:03,000 --> 00:28:10,000
lactose. And it falls
off because it's less

329
00:28:10,000 --> 00:28:18,000
suitable for binding this particular
DNA sequence when it's bound to

330
00:28:18,000 --> 00:28:26,000
lactose there.
So, in this case,

331
00:28:26,000 --> 00:28:34,000
in the presence of lactose,
lack I does not bind.

332
00:28:34,000 --> 00:28:44,000
And, the lack operon is transcribed.
Yes? Uh-oh. OK, all right

333
00:28:44,000 --> 00:28:54,000
designers, here we've got a
problem. You have such a cool system,

334
00:28:54,000 --> 00:29:03,000
right? You were going
to sense lactose.

335
00:29:03,000 --> 00:29:10,000
Lactose was going to bind
to the lack repressor,

336
00:29:10,000 --> 00:29:17,000
change its confirmation falloff:
uh-oh. But, as you point out,

337
00:29:17,000 --> 00:29:25,000
how's it going to get any lactose,
because there's not a lactose

338
00:29:25,000 --> 00:29:32,000
permease because the
lactose permease is made by

339
00:29:32,000 --> 00:29:37,000
the same operon.
So, what if, in fact,

340
00:29:37,000 --> 00:29:40,000
instead of getting one of these DOD
mill speck kind of things of some

341
00:29:40,000 --> 00:29:43,000
repressor that is absolutely so
tight that it never falls off under

342
00:29:43,000 --> 00:29:47,000
any circumstances, what if
we build a slightly sloppy

343
00:29:47,000 --> 00:29:50,000
repressor that occasionally
falls off, and occasionally allows

344
00:29:50,000 --> 00:29:53,000
transcription of the lack operon?
Then, we'll have some trace

345
00:29:53,000 --> 00:29:56,000
quantities of permease around.
With a little bit of permease

346
00:29:56,000 --> 00:30:00,000
around, a little
lactose will get in.

347
00:30:00,000 --> 00:30:04,000
And, as long as even a
little lactose gets in,

348
00:30:04,000 --> 00:30:08,000
it'll now shift the equilibrium
so that the repressor is off more,

349
00:30:08,000 --> 00:30:12,000
and of course that will make
more permease, and shift,

350
00:30:12,000 --> 00:30:16,000
and shift, and shift, and
shift. So, as long as it's not

351
00:30:16,000 --> 00:30:21,000
so perfectly engineered as to
have nothing being transcribed,

352
00:30:21,000 --> 00:30:25,000
so no mRNA is really very little
mRNA. See, this is what's so good,

353
00:30:25,000 --> 00:30:29,000
I think, about having MIT students
learn this stuff because there are

354
00:30:29,000 --> 00:30:33,000
all sorts of wonderful design
principles here about how

355
00:30:33,000 --> 00:30:38,000
you build systems. And, I
think this is just a very

356
00:30:38,000 --> 00:30:43,000
good example of how you
build a system like this.

357
00:30:43,000 --> 00:30:48,000
Now, all right, so we now have the
ability to have lack on and lack off,

358
00:30:48,000 --> 00:30:52,000
and that is lack off, mostly
off because of your permease

359
00:30:52,000 --> 00:30:57,000
problem: very good. Now,
let's take a little digression

360
00:30:57,000 --> 00:31:02,000
about, how do we know this?
This kind of reasoning,

361
00:31:02,000 --> 00:31:06,000
I've now told you the answer.
But let's actually take a look at

362
00:31:06,000 --> 00:31:10,000
understanding the evidence
that lets you conclude this.

363
00:31:10,000 --> 00:31:14,000
So, in order to do this, and
this is the famous work in

364
00:31:14,000 --> 00:31:18,000
molecular biology of Jacobin Manoux
in the late '50s for which they won

365
00:31:18,000 --> 00:31:22,000
a Nobel Prize, they wanted
to collect some mutants.

366
00:31:22,000 --> 00:31:26,000
Remember, this is before the time
of DNA sequence or anything like

367
00:31:26,000 --> 00:31:30,000
that, and wanted to collect
mutants that affected this process.

368
00:31:30,000 --> 00:31:37,000
So, in order to collect mutants
that screwed up the regulation,

369
00:31:37,000 --> 00:31:45,000
they knew that beta-galactosidase
was produced in much higher quantity

370
00:31:45,000 --> 00:31:53,000
if lactose was around. The
difficulty with that was that

371
00:31:53,000 --> 00:32:01,000
wild type E coli, when
you had no lactose would

372
00:32:01,000 --> 00:32:07,000
produce very little beta-gal,
one unit of beta-gal,

373
00:32:07,000 --> 00:32:11,000
and in the presence of lactose,
would produce a lot, let's call it 1,

374
00:32:11,000 --> 00:32:16,000
00 units of beta-gal. But,
the problem with playing

375
00:32:16,000 --> 00:32:20,000
around with this is lactose
is serving two different roles.

376
00:32:20,000 --> 00:32:25,000
Lactose is both the inducer of the
expression of the gene by virtue of

377
00:32:25,000 --> 00:32:30,000
binding to the
repressor, etc., etc.

378
00:32:30,000 --> 00:32:34,000
But, it's also the substrate for the
enzyme because as beta-galactosidase

379
00:32:34,000 --> 00:32:38,000
gets made, it breaks down the
lactose. So, there's less lactose

380
00:32:38,000 --> 00:32:43,000
in binding, and if you wanted to
really study the regulatory controls,

381
00:32:43,000 --> 00:32:47,000
you have the problem that the thing
that's inducing the gene by binding

382
00:32:47,000 --> 00:32:52,000
to the repressor is the thing that's
getting destroyed by the product of

383
00:32:52,000 --> 00:32:56,000
the gene. So, it's going
to make the kinetics of

384
00:32:56,000 --> 00:33:01,000
studying such a process really messy.
It would be very nice if you could

385
00:33:01,000 --> 00:33:05,000
make a form of lactose that could
induce beta-galactosidase by binding

386
00:33:05,000 --> 00:33:10,000
to the repressor, but
wasn't itself digested.

387
00:33:10,000 --> 00:33:17,000
Chemically, in fact, you
can do that. Chemically,

388
00:33:17,000 --> 00:33:24,000
it's possible to make a
molecule called IPTG, which is a

389
00:33:24,000 --> 00:33:32,000
galactoside analog. And,
what it does is this molecule

390
00:33:32,000 --> 00:33:41,000
here which I'll just sketch very
quickly here, it's a sulfur there,

391
00:33:41,000 --> 00:33:50,000
and you can see vaguely similar,
this is able to be an inducer.

392
00:33:50,000 --> 00:33:59,000
It'll induce beta-gal, but not a
substrate. It won't get digested.

393
00:33:59,000 --> 00:34:04,000
So, it'll stick around as long as
you want. It's also very convenient

394
00:34:04,000 --> 00:34:09,000
to use a molecule that was
developed called ex-gal.

395
00:34:09,000 --> 00:34:15,000
Ex-gal again has a sugar moiety,
and then it also has this kind of a

396
00:34:15,000 --> 00:34:20,000
funny double ring here, which
is a chlorine, and a bromine,

397
00:34:20,000 --> 00:34:25,000
and etc. And, this guy here is
not an inducer. It's not capable of

398
00:34:25,000 --> 00:34:31,000
being induced, of
inducing beta-galactosidase

399
00:34:31,000 --> 00:34:37,000
expression. But,
it is a substrate.

400
00:34:37,000 --> 00:34:43,000
It will be broken down by the
enzyme, and rather neatly when it's

401
00:34:43,000 --> 00:34:49,000
broken down it turns blue.
These two chemicals turned out to

402
00:34:49,000 --> 00:34:55,000
be very handy in trying to
work out the regulation of the

403
00:34:55,000 --> 00:35:00,000
lack operon. So, if I,
instead of adding lactose,

404
00:35:00,000 --> 00:35:06,000
if I think about adding IPTG, my
inducer, when I add IPTG I'm going

405
00:35:06,000 --> 00:35:12,000
to get beta-gal produced.
When I don't have IPTG, I won't

406
00:35:12,000 --> 00:35:18,000
produce beta-gal. But then
I don't have a problem of

407
00:35:18,000 --> 00:35:24,000
this getting used up. So now,
what kind of a mutant might

408
00:35:24,000 --> 00:35:29,000
I look for? I might look
for a mutant that even

409
00:35:29,000 --> 00:35:34,000
in the absence of the inducer,
IPTG, still produces a lot of

410
00:35:34,000 --> 00:35:39,000
beta-gal. Now, I can also
look for mutants that no

411
00:35:39,000 --> 00:35:44,000
matter what never produce beta-gal,
right? But, what would they likely

412
00:35:44,000 --> 00:35:50,000
be? They'd likely be structural
mutations affecting the coding

413
00:35:50,000 --> 00:35:55,000
sequence of beta-gal,
right? Those will happen.

414
00:35:55,000 --> 00:36:00,000
I can collect mutations that
cause the E coli never to

415
00:36:00,000 --> 00:36:05,000
produce beta-gal. But
that's not as interesting as

416
00:36:05,000 --> 00:36:11,000
collecting mutations that block the
repression that cause beta-gal to be

417
00:36:11,000 --> 00:36:16,000
produced all of the time. So,
how would I find such a mutant?

418
00:36:16,000 --> 00:36:22,000
I want to find a mutant that's
producing a lot of beta-gal even

419
00:36:22,000 --> 00:36:27,000
when there's no IPTG. So,
let's place some E coli on a

420
00:36:27,000 --> 00:36:33,000
plate. Should we put IPTG
on a plate? No, so no IPTG.

421
00:36:33,000 --> 00:36:37,000
What do I look for? How do
I tell whether or not any of

422
00:36:37,000 --> 00:36:42,000
these guys here is producing
a lot of beta-gal? Yep?

423
00:36:42,000 --> 00:36:46,000
So, no IPTG, but put on ex-gal,
and if anybody's producing a lot of

424
00:36:46,000 --> 00:36:51,000
beta-gal, what happens? They
turn blue: very easy to go

425
00:36:51,000 --> 00:36:55,000
through lots of E coli like
that looking for something blue.

426
00:36:55,000 --> 00:37:00,000
And so, lots of mutants were
collected that were blue.

427
00:37:00,000 --> 00:37:05,000
And, these chemicals are still used
today. They're routinely used in

428
00:37:05,000 --> 00:37:10,000
labs, ex-gal and stuff like that,
making bugs turn blue because this

429
00:37:10,000 --> 00:37:15,000
has turned out to be such a
well-studied system that we use it

430
00:37:15,000 --> 00:37:20,000
for a lot of things. So,
mutants were found that were

431
00:37:20,000 --> 00:37:25,000
constituative. So, mutants
were found that were

432
00:37:25,000 --> 00:37:30,000
constituative mutants.
Constituative mutants: meaning

433
00:37:30,000 --> 00:37:35,000
expressing all the time,
no longer regulated, so,

434
00:37:35,000 --> 00:37:40,000
characterizing these
constituative mutants.

435
00:37:40,000 --> 00:37:44,000
It turns out that they fell into two
different classes of constituative

436
00:37:44,000 --> 00:37:48,000
mutants. If we had enough time,
and you could read the papers and

437
00:37:48,000 --> 00:37:52,000
all, what I would do is give you
the descriptions that Jacobin Maneaux

438
00:37:52,000 --> 00:37:56,000
had of these funny mutants which
they'd isolated and were trying to

439
00:37:56,000 --> 00:38:00,000
characterize, and how to
puzzle out what was going on.

440
00:38:00,000 --> 00:38:04,000
But, it's complicated and hard,
and makes your head hurt if you

441
00:38:04,000 --> 00:38:08,000
don't know what the answer is.
So, I'm going to first tell you the

442
00:38:08,000 --> 00:38:12,000
answer of what's going on, and
then sort of see how you would

443
00:38:12,000 --> 00:38:17,000
know that this was the case.
But, imagine that you didn't know

444
00:38:17,000 --> 00:38:21,000
this answer, and had to
puzzle this out from the data.

445
00:38:21,000 --> 00:38:25,000
So, suppose we had, so if
there were going to be two

446
00:38:25,000 --> 00:38:30,000
kinds of mutants: mutant number
one are operator constituents.

447
00:38:30,000 --> 00:38:38,000
They have a defective operator
sequence. Mutations have occurred

448
00:38:38,000 --> 00:38:46,000
at the operator site. Mutant
number two have a defective

449
00:38:46,000 --> 00:38:54,000
repressor protein, the gene
for the repressor protein.

450
00:38:54,000 --> 00:39:00,000
How can I tell
the difference?

451
00:39:00,000 --> 00:39:04,000
So, I could have a problem
in my operator site.

452
00:39:04,000 --> 00:39:08,000
What would be the problem
with the operator site?

453
00:39:08,000 --> 00:39:12,000
Some mutation to the sequence
causes the repressor not to bind

454
00:39:12,000 --> 00:39:16,000
there anymore, OK? So,
a defective operator site

455
00:39:16,000 --> 00:39:20,000
doesn't bind repressors.
Defective repressor, the operator

456
00:39:20,000 --> 00:39:24,000
site is just fine, but I
don't have a repressor to bind

457
00:39:24,000 --> 00:39:28,000
at it. So how do I tell the
difference? One way to tell the

458
00:39:28,000 --> 00:39:32,000
difference is to begin crossing
the mutants together to wild type,

459
00:39:32,000 --> 00:39:36,000
and asking, are they dominant or
recessive, or things like that?

460
00:39:36,000 --> 00:39:39,000
Now, here's a little problem.
E Coli is not a diploid, so you

461
00:39:39,000 --> 00:39:43,000
can't cross together two E
colis and make a diploid E coli,

462
00:39:43,000 --> 00:39:46,000
right? It's a prokaryote.
It only has one genome. But,

463
00:39:46,000 --> 00:39:50,000
it turns out that you can
make temporary diploids,

464
00:39:50,000 --> 00:39:53,000
partial diploids out of E coli
because it turns out you can mate

465
00:39:53,000 --> 00:39:57,000
bacteria. Bacteria, which
have a bacterial chromosome

466
00:39:57,000 --> 00:40:01,000
here also engage in sex and
in the course of bacterial sex,

467
00:40:01,000 --> 00:40:05,000
plasmids can be transferred called,
for example, an F factor, is able to

468
00:40:05,000 --> 00:40:10,000
be transferred from another bacteria.
And, through the wonders of partial

469
00:40:10,000 --> 00:40:15,000
merodiploid, you can temporarily get
E colis, or you can permanently get

470
00:40:15,000 --> 00:40:20,000
E colis, that are partially diploid.
So, you can do what I'm about to

471
00:40:20,000 --> 00:40:25,000
say. But, in case you were worried
about my writing diploid genotypes

472
00:40:25,000 --> 00:40:30,000
for E coli, you can
actually do this.

473
00:40:30,000 --> 00:40:36,000
You can make partial diploids.
So, let's try out a genotype here.

474
00:40:36,000 --> 00:40:43,000
Suppose the repressor is a wild
type, the operator is wild type,

475
00:40:43,000 --> 00:40:49,000
and the lack Z gene is wild type.
And, suppose I have no IPTG, I'm

476
00:40:49,000 --> 00:40:56,000
un-induced. I have one unit of
beta-gal. When I add my inducer,

477
00:40:56,000 --> 00:41:03,000
what happens? I get
1,000 units of beta-gal.

478
00:41:03,000 --> 00:41:07,000
Now, suppose I would have an
operator constituative mutation.

479
00:41:07,000 --> 00:41:12,000
Then, the operator site is
defective. It doesn't bind the

480
00:41:12,000 --> 00:41:17,000
repressor. Beta-gal is going
to be expressed all the time,

481
00:41:17,000 --> 00:41:22,000
even in the absence. All right,
well that was, of course, what we

482
00:41:22,000 --> 00:41:27,000
selected for. Now, suppose
I made the following diploid.

483
00:41:27,000 --> 00:41:32,000
I plus, O plus, Z
plus, over I plus,

484
00:41:32,000 --> 00:41:38,000
O constituative, Z plus. So,
here's my diploid. What would

485
00:41:38,000 --> 00:41:44,000
be the phenotype?
So, in other words,

486
00:41:44,000 --> 00:41:50,000
one of the chromosomes
has an operator problem.

487
00:41:50,000 --> 00:41:56,000
Well, that means that this
chromosome here is always going to

488
00:41:56,000 --> 00:42:02,000
be constituatively
expressing beta-gal.

489
00:42:02,000 --> 00:42:06,000
But, what about this
chromosome here? It won't. So,

490
00:42:06,000 --> 00:42:10,000
this would be about 1, 01,
give or take, because it's got

491
00:42:10,000 --> 00:42:14,000
one chromosome doing that
and one chromosome doing this,

492
00:42:14,000 --> 00:42:18,000
and this one would be about
2, 00. Now, that quantitative

493
00:42:18,000 --> 00:42:22,000
difference doesn't matter a lot.
What you really saw when you did

494
00:42:22,000 --> 00:42:26,000
the molecular biology was that when
you had one copy of the operator

495
00:42:26,000 --> 00:42:30,000
constituative mutation, you
still got a lot of beta-gal here

496
00:42:30,000 --> 00:42:36,000
even in the absence of IPTG. So,
that operator constituative site

497
00:42:36,000 --> 00:42:44,000
looked like it was dominant
to this plus site here.

498
00:42:44,000 --> 00:42:52,000
But now, let's try this one here.
I plus, O plus, Z plus, over I plus,

499
00:42:52,000 --> 00:43:00,000
operator constituative, Z
minus. What happens then?

500
00:43:00,000 --> 00:43:05,000
This operator constituative site
allows constant transcription of

501
00:43:05,000 --> 00:43:10,000
this particular copy. But,
can this particular copy make

502
00:43:10,000 --> 00:43:15,000
a working, functional beta-gal?
No. So, this looks, when you do

503
00:43:15,000 --> 00:43:20,000
your genetic crosses,
you find that the operator

504
00:43:20,000 --> 00:43:25,000
constituative, now, if
I reverse these here,

505
00:43:25,000 --> 00:43:30,000
suppose I reverse these, I
plus, O plus, Z minus, I plus, O

506
00:43:30,000 --> 00:43:35,000
constituative, Z
plus, same genotypes,

507
00:43:35,000 --> 00:43:40,000
right, except that I flipped
which chromosome these are on.

508
00:43:40,000 --> 00:43:46,000
Now, what happens? This chromosome
here: always making beta-gal and it

509
00:43:46,000 --> 00:43:51,000
works. This chromosome
here: not making beta-gal.

510
00:43:51,000 --> 00:43:56,000
Even though it's regulated, it's
a mutant. So, in other words,

511
00:43:56,000 --> 00:44:01,000
from this very experiment, you can
tell that the operator site is only

512
00:44:01,000 --> 00:44:07,000
affecting the chromosome
that it's physically on,

513
00:44:07,000 --> 00:44:13,000
that it doesn't make a
protein that floats around.

514
00:44:13,000 --> 00:44:19,000
What it does is it's said to work
in cys. In cys means on the same

515
00:44:19,000 --> 00:44:26,000
chromosome. It physically
works on the same chromosome.

516
00:44:26,000 --> 00:44:32,000
Now, let's take a look, by
contrast, of the properties of

517
00:44:32,000 --> 00:44:38,000
the lack repressor mutants.
If I give you a lack repressor

518
00:44:38,000 --> 00:44:43,000
mutant, I plus, O plus,
Z plus is the wild type.

519
00:44:43,000 --> 00:44:49,000
I constituative, O plus,
Z plus: what happens here?

520
00:44:49,000 --> 00:44:54,000
This wild type is one in 1,
00. This guy here: 1,000 and 1,

521
00:44:54,000 --> 00:45:00,000
00, and then here
let's look at a diploid:

522
00:45:00,000 --> 00:45:05,000
I plus, O plus, Z
plus, I constituative,

523
00:45:05,000 --> 00:45:10,000
O plus, Z plus. What's the effect?
The I constituative doesn't make a

524
00:45:10,000 --> 00:45:15,000
functioning repressor. But,
I plus makes a functioning

525
00:45:15,000 --> 00:45:21,000
repressor. So, will
this show regulation?

526
00:45:21,000 --> 00:45:26,000
Yeah, this will be regulated just
fine. This works out just fine,

527
00:45:26,000 --> 00:45:32,000
and in fact it'll make 2,000,
and it'll make two copies there.

528
00:45:32,000 --> 00:45:37,000
But again, the units
don't matter too much. And,

529
00:45:37,000 --> 00:45:42,000
by contrast, if I give you I plus,
O plus, Z minus, and I constituative,

530
00:45:42,000 --> 00:45:47,000
O plus, Z plus,
what will happen?

531
00:45:47,000 --> 00:45:53,000
Here, I have my mutation
on this chromosome. But,

532
00:45:53,000 --> 00:45:58,000
it doesn't matter because I've got
my mutation on this chromosome in

533
00:45:58,000 --> 00:46:03,000
the repressor. I've got
a mutation on lack Z here,

534
00:46:03,000 --> 00:46:09,000
but as long as I have a functional
copy, one functional copy of the

535
00:46:09,000 --> 00:46:15,000
lack repressor, it works
on both chromosomes.

536
00:46:15,000 --> 00:46:20,000
It will work on both chromosomes,
and so in other words this lack

537
00:46:20,000 --> 00:46:26,000
repressor, one copy works on
both chromosomes. In other words,

538
00:46:26,000 --> 00:46:32,000
it makes a product that diffuses
around, and can work on either

539
00:46:32,000 --> 00:46:38,000
chromosome, and it's said to
work in trans, that is, across.

540
00:46:38,000 --> 00:46:41,000
So, the operator is working in
cys. It's operating on its own

541
00:46:41,000 --> 00:46:45,000
chromosome only. A mutation
in the operator only

542
00:46:45,000 --> 00:46:48,000
affects the chromosome it lives
on, whereas a functional copy of the

543
00:46:48,000 --> 00:46:52,000
lack repressor will float
around because it's a protein,

544
00:46:52,000 --> 00:46:55,000
and that's how Jacobin
Maneaux knew the difference.

545
00:46:55,000 --> 00:46:59,000
They proved their model by showing
that these two kinds of mutations

546
00:46:59,000 --> 00:47:03,000
had very different properties.
Operator mutations affected only the

547
00:47:03,000 --> 00:47:07,000
physical chromosome on which they
occurred, which of course they had

548
00:47:07,000 --> 00:47:11,000
to infer from the genetics they did,
whereas repressor, a functional copy

549
00:47:11,000 --> 00:47:15,000
repressor, could act on
any chromosome in the cell.

550
00:47:15,000 --> 00:47:20,000
So, OK, we've got that. Now,
last point, what about glucose?

551
00:47:20,000 --> 00:47:24,000
I haven't said a word about glucose.
See, this was a big deal to people.

552
00:47:24,000 --> 00:47:28,000
This model, the repressor model,
we have this repressor. What

553
00:47:28,000 --> 00:47:36,000
about glucose? What's
glucose doing in this picture?

554
00:47:36,000 --> 00:47:47,000
So, glucose control: so here's
my gene. Here's my promoter,

555
00:47:47,000 --> 00:47:58,000
P lack. Here's my
operator, beta-gal.

556
00:47:58,000 --> 00:48:03,000
It's encoded by lack Z. You've
got all that. When this guy

557
00:48:03,000 --> 00:48:08,000
is present, sorry,
when lactose is present,

558
00:48:08,000 --> 00:48:13,000
the repressor comes off.
Polymerase sits down. Wait a second,

559
00:48:13,000 --> 00:48:18,000
polymerase isn't supposed to sit
down unless there's no glucose.

560
00:48:18,000 --> 00:48:23,000
We need another sensor to
tell if there's glucose,

561
00:48:23,000 --> 00:48:28,000
or if there's low glucose. So,
we're going to need us a sensor

562
00:48:28,000 --> 00:48:34,000
that tells that.
Any ideas? Yep?

563
00:48:34,000 --> 00:48:40,000
Yeah, if you work that one through,
I don't think it quite works. But,

564
00:48:40,000 --> 00:48:46,000
you've got the basic idea.
You're going to want another

565
00:48:46,000 --> 00:48:52,000
something, and it turns out
there's another site over here,

566
00:48:52,000 --> 00:48:58,000
OK? There's a second site on
which a completely different

567
00:48:58,000 --> 00:49:05,000
protein binds. And, this
protein is the cyclic AMP

568
00:49:05,000 --> 00:49:13,000
regulatory protein, and it
so happens that in the cell,

569
00:49:13,000 --> 00:49:20,000
when there's low amounts of glucose,
let me make sure I've got this right,

570
00:49:20,000 --> 00:49:28,000
when there's low amounts of glucose,
what we have is high amounts of

571
00:49:28,000 --> 00:49:34,000
cyclic AMP. Cyclic
AMP turns out,

572
00:49:34,000 --> 00:49:38,000
whereas lactose is used directly
as the signal, cyclic AMP is used as

573
00:49:38,000 --> 00:49:42,000
the signal here. When the
cell has low amounts of

574
00:49:42,000 --> 00:49:46,000
glucose, it has high
amounts of cyclic AMP. Now,

575
00:49:46,000 --> 00:49:50,000
what do you want your cyclic AMP to
do? How are we going to design this?

576
00:49:50,000 --> 00:49:54,000
It's going to bind to a protein,
cyclic AMP regulatory protein, it's

577
00:49:54,000 --> 00:49:58,000
going to sit down, and
now what's it going to do?

578
00:49:58,000 --> 00:50:02,000
Is it going to
block RNA polymerase?

579
00:50:02,000 --> 00:50:06,000
What do we want to do?
If there's low glucose,

580
00:50:06,000 --> 00:50:10,000
high cyclic AMP, we sit down
at the site, we want to turn on

581
00:50:10,000 --> 00:50:15,000
transcription now, right?
So, what it's got to do is

582
00:50:15,000 --> 00:50:19,000
not block RNA polymerase,
but help RNA polymerase. So,

583
00:50:19,000 --> 00:50:24,000
what it actually does is
instead of being a repressor,

584
00:50:24,000 --> 00:50:28,000
it's an activator. And what it does
is it makes it more attractive for

585
00:50:28,000 --> 00:50:32,000
RNA polymerase to bind, and
it actually does that by,

586
00:50:32,000 --> 00:50:36,000
actually it does it
slightly by bending the DNA.

587
00:50:36,000 --> 00:50:40,000
But, what it does is it makes it
easier for RNA polymerase to bind.

588
00:50:40,000 --> 00:50:44,000
It turns out that the promoter
is kind of a crummy promoter.

589
00:50:44,000 --> 00:50:48,000
It's actually just like, remember
the repressor wasn't perfect; the

590
00:50:48,000 --> 00:50:52,000
promoter's not perfect either.
The promoter's kind of crummy.

591
00:50:52,000 --> 00:50:56,000
And, unless RNA polymerase gets
a little help from this other

592
00:50:56,000 --> 00:51:00,000
regulatory protein,
it doesn't work.

593
00:51:00,000 --> 00:51:04,000
We have two controls: a negative
regulator responding to an

594
00:51:04,000 --> 00:51:09,000
environmental cue, a positive
activator responding to

595
00:51:09,000 --> 00:51:13,000
an environmental cue, helping
polymerase decide whether to

596
00:51:13,000 --> 00:51:18,000
transcribe or not, and
basically that's how a human egg

597
00:51:18,000 --> 00:51:22,000
goes to a complete adult
and lives its entire life,

598
00:51:22,000 --> 00:51:27,000
minus a few other details.
There are some details left out,

599
00:51:27,000 --> 00:51:32,000
but that's a sketch of how
you turn genes on and off.