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Julia just mentioned that a few
of you had commented,

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when we were talking about the
genetic code, that some of you

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thought the fact that it was
degenerate, it had some redundancy

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in it, like multiple codons or
threonine, that that was kind of

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cool, and some of you thought it was
sort of a waste and would have maybe

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designed the thing differently.
That's, you know, part of when you

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study biology you don't get to
design it from first principles.

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You found out what happened during
evolution and what got selected for.

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And once it gets selected for then
that gets sort of fixed in nature.

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If there were four nucleotides then
you could have one,

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two and three-letter words.
And it's going to be a three-letter

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word to have at least 20 then you've
got some degeneracy or redundancy,

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but that's not necessarily a bad
thing.  And, in fact,

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if you go into the evolution of the
code more deeply,

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people are beginning to suspect it
evolved from a simpler one.

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And there actually are some
relationships between some of the

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codons that go back to the
similarities, the chemical

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similarities between the amino acids.
And it also allows some things for

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some cells, for example,
if they want proteins to be present

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at very low levels they will use a
codon that has just a very low level

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of the corresponding tRNA.
And if they want to make a lot of

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the protein they'll use a tRNA that
it makes in abundance.

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And so it's sort of another way of
controlling levels of proteins.

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There are a lot of different
subtleties in here.

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And also in biology redundancy is
not necessarily a bad thing.

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It's just like on a space flight,
if something goes wrong and if

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there's some kind of redundant
function then you've got some

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backups, too.  OK.
Well, in any case,

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today is a pretty interesting first
part of the lecture.

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I've heard a few people express the
view that why can't I just teach

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what's in the textbook
and get on with it?

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And I think this part,
for those of you who are following,

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really trying to understand what I'm
trying to do with this course,

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I hope this will help you to see
this.  Because what I've talked

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about, this thing that Crick called
the "central dogma" which was the

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direction of information flow in
biology which was from DNA

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to RNA to proteins.
And I'll just remind you,

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although proteins do many things
they are, for example,

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enzymes that are biological
catalysts.  And it was pretty

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well-established,
even by the time I was an undergrad

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that this was the way information
flow went in biology and this was

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how it worked.
And there were various statements

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in the literature that what was true
for E. coli was true

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for an elephant.
And it is still true today in a

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broad sense that,
as I've tried to emphasize

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throughout the course,
when you get down to a cellular

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molecule level there's an awful lot
in common and things look much more

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alike than different compared to
what we see at a more macroscopic

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scale.  However,
that doesn't mean that all the

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details are the same.
And maybe you could begin to get a

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glimmering of that when I told you
that although the genetic code is

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virtually universal.
That almost every organism,

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with only a couple very tiny
exceptions, uses exactly the same

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genetic code to have nucleotides
correspond to three-letter words in

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the nucleic acid alphabet correspond
to particular amino acids in a

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protein.  But the other languages
that are written in there such as

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the sequence to start transcribing a
gene, making an RNA copy are stopped.

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Those are different between
different organisms.  Yeah?

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Glycolysis enzymes are amazingly

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similar.  They are very clearly,
they arose once, and they have

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stayed right through evolution.
You could, in principle, sometimes

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in evolution you get something that
creates a function and something

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that starts out,
and then like what they call

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convergent evolution you end up with
two things that came from a

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different evolutionary origin but
have learned to do,

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let's say, catalyze the same
biochemical reaction or something.

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Glycolysis came once.
But if you were to look inside E.

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coli or yeast, let's say E. coli and
look at how those enzymes are

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regulated, the thing that says this
is the start of a gene,

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start making the RNA, it would look
totally different than if you looked

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in a mouse because the language,
the promoter does not have the same

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sequence in an E.
coli and in a human or in a mouse.

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And I'll tell you more about that
today.  But there were --

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I want to just now tell you sort of
three things that were sort of

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exceptions to this general way of
thinking.  Every one of them

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generated a Nobel Prize.
And this is a fun lecture for me to

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give because the individuals
involved in all of these things had

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a very, very close association with
MIT.  And when I told you when Crick

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called this a central dogma he meant
a hypothesis, or at least an idea

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for which there was not
reasonable evidence.

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And he learned later it was
something a true believer cannot

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doubt.  And once this gets
established it does get in the

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textbook and it does get in your
thinking.  And so information goes

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down this way.
But there were a few oddities.

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I mean there were some viruses that
had RNA inside them.

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They didn't have DNA.
So how where these handled?

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Well, there turned out to be two
classes of RNA virus.

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One that was studied quite heavily
called, it's a plant virus called

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the tobacco mosaic virus.
And it had a coat.  And then it had

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in it a piece of RNA.
Now, you can see if that virus were

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to inject RNA in the cell it could
encode proteins.

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But that genetic material has to be
copied.  And the RNA was copied --

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-- by an RNA dependent

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RNA polymerase.
And so it's sort of just like the

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RNA polymerase before,
except instead of using DNA as its

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template it can use RNA.
So that sort of somehow would be a

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little loop in here about RNA being
able to copy itself that hadn't been

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anticipated.  And although this is
an important virus in the plant

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industry, for plants and agriculture,
it's not so important for humans.

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But there's another class of RNA
viruses that are very important.

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And these are called retroviruses.
And the reason these are so

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important is that the HIV-1 virus
that's associated with AIDS is such

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a retrovirus.  It's a virus that has
a coat and it has an RNA that's it

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genetic material.
And the person who worked out how

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this goes was a person at MIT,
Dave Baltimore.  He was a colleague

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of mine here for many years.
He was the person who founded the

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White Head Institute and got that up
and going.  And he then finally,

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to move up one more administrative
challenge, went to Caltech

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to be president.
And that's where he is today.

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And David was working on this
problem trying to figure out how

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these retroviruses work.
And they're important.  Not only

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the HIV-1 virus,
but there are certain viruses that

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are associated with cancer.
In general, what they do is they've

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picked up what's called an oncogene
which is sort of often a mutated

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version of one of your
normal genes.

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And if that virus gets inside one of
your cells and brings in this

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mutated gene it's sort of kind of
the same consequence as mutating one

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of your own genes along that
progression of cancer.

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So it can kind of, say,
bring in a cell that screws up the

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control on when cells are supposed
to replicate and stop dividing and

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so on.  So David started to work on
these, and what he discovered was

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that these viruses encoded,
they had information encoding

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proteins.
And one of the proteins encoded in

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their RNA is an enzyme
de-characterized which is given the

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name "reverse transcriptase".
And what this can do is take an RNA

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template and make the corresponding
complimentary DNA strand in this way.

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So that if we took the --
We'll just take this RNA out of the

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virus.  What this virus encodes then
is an enzyme that's able to take

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this RNA and make the corresponding
DNA copy.  So there's the original

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RNA that was in the virus.
There is the RNA that it started

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out.  And so what is happening,
if you will in that case, is the

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information is flowing in
the other direction.

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That was a marvelous discovery.

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And it was discovered by someone
who wasn't willing just to take what

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was in the textbooks but was trying
to figure out what could possibly be

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going on here.
Now, the way these viruses work

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then, once they've done this it's
not so bad because they've got their

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information now in the form of DNA.
So this strand of DNA can be made

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into a double-stranded DNA by just
using the kinds of enzymes that

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we've already talked about.
A DNA dependent DNA polymerase will

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be able to copy the other thing.
And now you've got a DNA copy of

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the information that used to be in
the virus.  But what happens to that

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is that you have a piece
of the host DNA.

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And this viral DNA then inserts into
it, so you end up with this

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situation where you have DNA from
the host, and this

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is the virus DNA.
So this is the DNA that encodes the

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information needed for the virus.
And if this was our DNA then it

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would be inserted that way.
And there are just a handful of

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health messages I've tried to drive
home in this thing.

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I mentioned smoking the other day.
If you smoke --

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If you stop smoking you basically,
well, let me try another way.  The

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risk of smoking is about equal to
the sum of everything else you can

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possibly do in your life that will
affect your chances of getting

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cancer, leaving aside what you
inherited from mom and dad.

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The one single thing to not do if
you want to avoid cancer,

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or to help loved ones who smoke
avoid cancer, is just don't smoke,

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or if you do smoke, stop.
You freeze the risk of whatever

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increased risk you've got,
and then just live with that,

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but it doesn't keep getting worse
with time.  The other one is

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practice safe sex,
and this is why.  HIV-1 is a

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retrovirus.  If you get infected
with it, it makes a DNA copy of the

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RNA, it makes the other strand of
the DNA, and it sticks itself in.

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So what you've got is your DNA here,
your DNA there.

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And HIV-1 is a permanent traveling
companion for the rest of your life.

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There's no way of getting that out
of there right now.

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All the systems for dealing with
AIDS are just managing the infection.

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So when someone is HIV-1 positive,
they've got those viral genes now

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permanently integrated
into their DNA.

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So it's extremely important that you
be aware of that,

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or if you know people who don't
appreciate this because they haven't

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got so much of a biology background
that you help them understand that.

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OK.  So I just wanted to show you,
I found one other picture last night.

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And this is you see all these old
scientists, right?

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Of course, David didn't look like
this when he was doing his work.

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In fact, I think he's fairly
cleaned up here.

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I found this one in the Cold Spring
Harbor archives last night.

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I've seen pictures of him looking
considerably more shaggy and perhaps

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disreputable and stuff.
But anyway, when David was making

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all these discoveries he was still
quite a young man.

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I believe he got his Nobel Prize
when he was still in his thirties.

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And so many of these discoveries
are made by people that are not all

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that much older than you.
But, again, it's trying to

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understand why we know what we know
and then trying to fit

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other things into it.
Now, the next thing I want to tell

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you about that has some of this same
character, I've sort of told you

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that you have a piece of DNA.
Let's say there's a gene here and

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this is the coding region,
and then we make a mRNA copy,

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and then we use the genetic code and
we make the protein.

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And so if we sequence the DNA and
find the beginning of this protein

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we can read along using that genetic
code and away it should go.

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And that was beautifully worked out,
understood, just like I sort of

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finished up telling you the other
day.  So Phil Sharp who got a Nobel

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Prize for this work and his
colleague in the Biology

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Department.
He's in the Cancer Center just

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across the street from the building
I'm in.  That was the cancer center

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that Salvador Laurier,
who Jim Watson trained with,

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had founded.  And Phil was studying
this process.  It was before we

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could sequence DNA.
It was in the mid '70s.

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And he was working with the tools
we had then trying to map the

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relationship of an RNA to a gene
that was on a virus.

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It was a DNA virus,
not an RNA virus, so don't get

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yourself mixed up with that.
But what he had was basically a

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fragment of DNA that he knew encoded
the gene.  So he knew somewhere on

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this piece of DNA there was a gene
somewhere in here,

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and he had isolated the mRNA.
And one way you could map,

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physically see the relationship of
an RNA and a DNA would be to take,

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let's just take away one of these
strands.

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So we have the complimentary strand
of the DNA to the RNA.

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And if we mix them together and let
them slowly cool down they will form

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hydrogen bonds.
They'll form a DNA-RNA hybrid just

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the same way two strands of DNA come
on.  And so if the gene was a little

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shorter than the piece of DNA then
you might have expected to see

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something that looked like this.
And the way you'd see this,

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if you looked in an electron
microscope --

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-- perhaps it would look sort of

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like this.  You cannot actually see
the two strands,

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but you'd see a thick part.
That would be the RNA duplex.

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So this would be just DNA.
And the thick part is RNA base

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00:18:06,000 --> 00:18:12,000
paired with a single strand of DNA.
You got it?  That's what textbooks

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00:18:12,000 --> 00:18:18,000
said you should have seen.
And so this is more.  This is data

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00:18:18,000 --> 00:18:24,000
from Phil's paper describing this.
And let me focus on this one in

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00:18:24,000 --> 00:18:31,000
particular.  That's what
he actually saw.

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00:18:31,000 --> 00:18:38,000
You guys got any idea what's going

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00:18:38,000 --> 00:18:43,000
on?  Why don't you take a minute,
find somebody who's near you and see

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00:18:43,000 --> 00:18:48,000
if you can come up with any ideas.
Here's the hybrid.  Forget about

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00:18:48,000 --> 00:18:54,000
this little bit at the 3 prime end.
That's not a worry.  Here is the

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00:18:54,000 --> 00:18:59,000
thing.  And this,
I think, is a piece of single

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00:18:59,000 --> 00:19:05,000
stranded DNA sticking out the end.
But it looks a bit more complicated.

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00:19:05,000 --> 00:19:11,000
Any ideas?  Most people put this
data in their drawers.

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00:19:11,000 --> 00:19:17,000
Phil didn't.  Phil and his
colleagues didn't.

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00:19:17,000 --> 00:19:23,000
What they realized was,
I'm going to try and redraw this

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00:19:23,000 --> 00:19:30,000
just very slightly to help you see
what's going on.

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00:19:30,000 --> 00:19:35,000
What they were seeing was something
that looked rather like what they

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00:19:35,000 --> 00:19:40,000
were expecting.
They were seeing a region of hybrid

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00:19:40,000 --> 00:19:45,000
DNA and they were seeing a region of
single-stranded DNA like this,

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00:19:45,000 --> 00:19:50,000
but what it looked like was there
were little loops of single-stranded

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00:19:50,000 --> 00:19:55,000
DNA sticking out.
And what Phil had discovered was a

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00:19:55,000 --> 00:20:01,000
phenomenon we now know
as RNA splicing.

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00:20:01,000 --> 00:20:08,000
And here's what goes on.

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00:20:08,000 --> 00:20:12,000
In bacteria, with very few
exceptions, you can look at the DNA,

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00:20:12,000 --> 00:20:16,000
you can find the open reading frame
and you can just read off the

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00:20:16,000 --> 00:20:20,000
sequence of the protein.
You find the ATG, AUG, methionine

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00:20:20,000 --> 00:20:24,000
codon, and then it keeps going no
stops, and finally you come to a

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00:20:24,000 --> 00:20:28,000
stop codon and you see there is the
protein.  So the coding information

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00:20:28,000 --> 00:20:33,000
is essentially continuous in almost
all bacterial genes.

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00:20:33,000 --> 00:20:37,000
And there's a few,
some genes like that in eukaryotes,

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00:20:37,000 --> 00:20:41,000
but many eukaryotic genes are
constructed, it's almost as if you

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00:20:41,000 --> 00:20:45,000
took the gene you'd find in a
bacterium and then you'd cut it in a

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00:20:45,000 --> 00:20:50,000
bunch of places and stuck extra DNA
in between all of the pieces.

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00:20:50,000 --> 00:20:54,000
So you'd get something like this
where there's,

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00:20:54,000 --> 00:20:59,000
in the DNA there'd be coding
information.

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00:20:59,000 --> 00:21:07,000
And then non-coding information and
another block of coding information.

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00:21:07,000 --> 00:21:16,000
And then a block of non-coding and
say another one of coding

254
00:21:16,000 --> 00:21:24,000
information.  So this is a
double-stranded DNA.

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00:21:24,000 --> 00:21:33,000
And what happens then when the cell
makes RNA is the whole thing gets

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00:21:33,000 --> 00:21:42,000
copied into what's known now as a
pre-messenger RNA.

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00:21:42,000 --> 00:21:47,000
And so there's a bit of coding stuff
here, there's a bit of coding stuff

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00:21:47,000 --> 00:21:52,000
here, and there's some more coding
stuff there.  But what the cell has

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00:21:52,000 --> 00:21:57,000
is sort of like your unedited
footage from your family summer

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00:21:57,000 --> 00:22:03,000
vacating when you were running
the video camera.

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00:22:03,000 --> 00:22:07,000
And maybe you don't want to show
everybody ever second of video that

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00:22:07,000 --> 00:22:11,000
you took during the thing.
So what you do, you get in there

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00:22:11,000 --> 00:22:16,000
and you edit it.
In the old days you used to have to

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00:22:16,000 --> 00:22:20,000
take the film and splice it.
And now you can all do it with

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00:22:20,000 --> 00:22:25,000
iMovie or something like that.
But what you do is take the pieces

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00:22:25,000 --> 00:22:29,000
of information you want,
and this is what the cell is doing.

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00:22:29,000 --> 00:22:36,000
It takes this part of the RNA.
And this part of the RNA,

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00:22:36,000 --> 00:22:45,000
and joins it together, and then this
part.  And when it's done it has the

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00:22:45,000 --> 00:22:54,000
mRNA that now looks like the kind of
mRNA that you would find in a

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00:22:54,000 --> 00:23:03,000
bacterium where you can
find the start codon.

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00:23:03,000 --> 00:23:09,000
And then you could read in
three-letter words all the way

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00:23:09,000 --> 00:23:15,000
through to the end of the protein.
So, in essence, what Phil found was

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00:23:15,000 --> 00:23:21,000
that in many organisms at least
there's another step in here where

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00:23:21,000 --> 00:23:27,000
we get RNA splicing.
And only after that you get down to

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00:23:27,000 --> 00:23:33,000
proteins.
What was quite remarkable about this

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00:23:33,000 --> 00:23:37,000
result and why I'm kind of hammering
on it a little bit is this is the

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00:23:37,000 --> 00:23:41,000
data that's out of Phil's paper.
You can look it up on the Internet.

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00:23:41,000 --> 00:23:45,000
Type in Phil Sharp 1977 and you'll
find this original paper with that

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00:23:45,000 --> 00:23:49,000
figure in it.  The moment Phil
realized what he was and talked

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00:23:49,000 --> 00:23:53,000
about it at a meeting,
a whole lot of people suddenly sort

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00:23:53,000 --> 00:23:57,000
of almost simultaneously discovered
RNA splicing because they opened

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00:23:57,000 --> 00:24:01,000
their drawers and there were all
these uninterpretable electron

283
00:24:01,000 --> 00:24:06,000
micrographs they had.
And they were in very short order

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00:24:06,000 --> 00:24:10,000
able to save it in the system.
The same thing was going on, but it

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00:24:10,000 --> 00:24:14,000
was just confusing,
it didn't fit, and to some extent

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00:24:14,000 --> 00:24:18,000
most people's minds were set by this
paradigm, this central dogma as

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00:24:18,000 --> 00:24:22,000
something that a true believer
cannot doubt.  And you had to have a

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00:24:22,000 --> 00:24:27,000
flexible enough mind to
be able to see that.

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00:24:27,000 --> 00:24:33,000
And so this is an important piece of
biology that hadn't been anticipated.

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00:24:33,000 --> 00:24:39,000
And it can be quite remarkable.
I'm just going to give you a couple

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00:24:39,000 --> 00:24:45,000
of extreme examples.
Well, not even extreme examples.

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00:24:45,000 --> 00:24:51,000
But just show you how much
non-coding information there can be.

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00:24:51,000 --> 00:24:57,000
Factor 8 is a protein that plays a
part in blood clotting.

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00:24:57,000 --> 00:25:03,000
And the gene is 200 kilobase pairs.
And the pre-mRNA is just a direct

295
00:25:03,000 --> 00:25:11,000
copy, so it's 200 kilobases.
It's just a single strand so it's

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00:25:11,000 --> 00:25:19,000
not a base pair.
And the actually spliced mRNA when

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00:25:19,000 --> 00:25:27,000
it's done is 10 kilobases.
So that means that only 5% of the

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00:25:27,000 --> 00:25:35,000
gene is coding information and 95%
of that information gets thrown away

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00:25:35,000 --> 00:25:42,000
when the RNA gets spliced.
And even a more extreme example is a

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00:25:42,000 --> 00:25:48,000
protein called dystrophin.
This is what's affected in a human

301
00:25:48,000 --> 00:25:55,000
genetic disease known as Duchenne
muscular dystrophy.

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00:25:55,000 --> 00:26:06,000
In this case, the gene is two mega

303
00:26:06,000 --> 00:26:17,000
base pairs.  So of course then the
pre-mRNA is also two mega bases but

304
00:26:17,000 --> 00:26:28,000
the pre-RNA is 16 kilobases.
So in this case less than 1% of the

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00:26:28,000 --> 00:26:40,000
gene has coding information
for making a protein.

306
00:26:40,000 --> 00:26:44,000
There are a lot of interesting
reasons as to why it would be like

307
00:26:44,000 --> 00:26:49,000
this.  One this,
things can evolve more rapidly

308
00:26:49,000 --> 00:26:54,000
sometimes because you have parts of
proteins that are sort of like

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00:26:54,000 --> 00:26:59,000
modules and evolution can
probably connect them.

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00:26:59,000 --> 00:27:03,000
I fact, it also provides ways of
regulating because we now know there

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00:27:03,000 --> 00:27:08,000
are alternative ways of splicing RNA.
So you can take one RNA and then

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00:27:08,000 --> 00:27:12,000
splice it in different ways in
different cells and end up

313
00:27:12,000 --> 00:27:17,000
generating different proteins that
were all encoded by one particular

314
00:27:17,000 --> 00:27:21,000
gene.  And so it gives cells
different kinds of regulatory

315
00:27:21,000 --> 00:27:26,000
strategies they can use.
Now, the third sort of thing that

316
00:27:26,000 --> 00:27:31,000
came out that falls in this same
kind of thing of people having their

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00:27:31,000 --> 00:27:36,000
minds open and not fixed by the
current understanding or bounded by

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00:27:36,000 --> 00:27:41,000
the current understanding is the
discovery that RNA can act as an

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00:27:41,000 --> 00:27:46,000
enzyme.  And I've already talked to
you about that and I've told it was

320
00:27:46,000 --> 00:27:51,000
ribozyme, but it was discovered by
Tom Cech.  Tom is currently

321
00:27:51,000 --> 00:27:56,000
president of the Howard Hughes
Medical Institute,

322
00:27:56,000 --> 00:28:02,000
but he did his post-doctoral work at
MIT with Mary Lou Pardue.

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00:28:02,000 --> 00:28:05,000
I've been a post-doc at Berkeley
when he was just finishing his

324
00:28:05,000 --> 00:28:09,000
graduate work,
and I met him out there.

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00:28:09,000 --> 00:28:13,000
And then he came to MIT to do his
post-doc.  And a year later I got a

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00:28:13,000 --> 00:28:17,000
job so I'd become friends there and
became friends when we started here.

327
00:28:17,000 --> 00:28:21,000
So I had a pretty close link to
this particular story.

328
00:28:21,000 --> 00:28:25,000
Here's a picture of Tom together
with Phil.  That's actually my wife

329
00:28:25,000 --> 00:28:29,000
right there who was in this picture.
But Tom actually looks much more

330
00:28:29,000 --> 00:28:35,000
like that.
He's very colorful,

331
00:28:35,000 --> 00:28:43,000
very fun, a very interesting person.
But anyway, when Tom left MIT to

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00:28:43,000 --> 00:28:51,000
take a faculty position at Bolder he
was interested in trying to

333
00:28:51,000 --> 00:29:00,000
understand the biochemistry of RNA
splicing.  And so he went --

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00:29:00,000 --> 00:29:03,000
He did what a good scientist will do.
They'll try and find an

335
00:29:03,000 --> 00:29:07,000
experimental system where the
question they want to address is

336
00:29:07,000 --> 00:29:10,000
simple enough you can actually get
an answer.  There's a kind of way of

337
00:29:10,000 --> 00:29:14,000
doing science where you pick a
system that's too complicated and

338
00:29:14,000 --> 00:29:17,000
you never actually get an answer.
It sounds very important because

339
00:29:17,000 --> 00:29:21,000
you're working on something that's
important but you cannot,

340
00:29:21,000 --> 00:29:24,000
you don't have the tools you need to
get to the answer.

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00:29:24,000 --> 00:29:28,000
So Tom wanted to work on the
biochemistry of RNA splicing because

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00:29:28,000 --> 00:29:32,000
that had just been discovered.
And so he went to a small little

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00:29:32,000 --> 00:29:37,000
tiny organism called tetrahymena.
And the reason he looked at that

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00:29:37,000 --> 00:29:41,000
was because it had a ribosomal RNA,
so it was an RNA that was made in

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00:29:41,000 --> 00:29:46,000
great abundance within the organism.
And it only had one of these

346
00:29:46,000 --> 00:29:51,000
non-coding regions.
I'll tell you the words for these

347
00:29:51,000 --> 00:29:56,000
coding and non-coding.
To me they're non-intuitive,

348
00:29:56,000 --> 00:30:01,000
but I guess you should know them.

349
00:30:01,000 --> 00:30:10,000
The coding region is called,
the part that codes is called an

350
00:30:10,000 --> 00:30:19,000
exon and the non-coding part is
called an intron.

351
00:30:19,000 --> 00:30:29,000
So, anyway, Tom worked on this
organism because the pre-mRNA

352
00:30:29,000 --> 00:30:37,000
was basically this.
Or the pre-RNA before the splicing
And whenever I got out to Bolder
we'd try and get in a squash game.

353
00:30:37,000 --> 00:30:45,000
looked like this.
This was going to give this like

354
00:30:45,000 --> 00:30:52,000
that.  He could get large quantities
of this RNA, so he was all set to

355
00:30:52,000 --> 00:31:00,000
make extracts of the cells of this
organism and then start cooking up
here.  And he went off to,
I guess it was Denmark to learn how

356
00:31:00,000 --> 00:31:08,000
this RNA substrate with all sorts of
cell extracts.
And so I first heard about this,
Tom was working on this when he was

357
00:31:08,000 --> 00:31:00,000
And then his plan was to purify the
enzymes that did the RNA splicing.

358
00:30:44,000 --> 00:30:36,000
to grow this organism.
Then they were back and he was off

359
00:30:36,000 --> 00:30:29,000
at Bolder.  And we used to play
squash all the time.

360
00:30:40,000 --> 00:30:51,000
So I was out there at a meeting and
we were sitting around in the locker

361
00:30:51,000 --> 00:31:03,000
room.  And I said so how's the
splicing biochemistry projecting

362
00:31:03,000 --> 00:31:14,000
going?  Tom says,
well, it's going OK,

363
00:31:14,000 --> 00:31:25,000
I guess.  There's only one little
problem, he says.

364
00:31:25,000 --> 00:31:37,000
The controls are splicing.
Now, what he meant was if you were

365
00:31:37,000 --> 00:31:48,000
trying to add cell extract and get
this thing to go what you would

366
00:31:48,000 --> 00:32:00,000
start out with is the RNA
in a tube basically.

367
00:32:00,000 --> 00:32:04,000
And that would be your control.
And then you'd start adding stuff

368
00:32:04,000 --> 00:32:08,000
to it and start looking for splicing.
And what Tom was finding was that

369
00:32:08,000 --> 00:32:12,000
if you just took this RNA and let it
sit in a test tube that the splicing

370
00:32:12,000 --> 00:32:17,000
happened without him putting
anything in.  And here he was

371
00:32:17,000 --> 00:32:21,000
already to find all the enzymes,
the proteins that did it.  And Tom

372
00:32:21,000 --> 00:32:25,000
did an absolutely gorgeous piece of
science to prove that what was

373
00:32:25,000 --> 00:32:30,000
happening was the RNA was catalyzing
its own splicing.

374
00:32:30,000 --> 00:32:33,000
And he had to work very,
very hard to prove that it wasn't a

375
00:32:33,000 --> 00:32:37,000
contaminating protein.
Remember we had this sort of

376
00:32:37,000 --> 00:32:41,000
discussion?  We were talking about
is DNA the genetic material and how

377
00:32:41,000 --> 00:32:45,000
would we know that it wasn't just a
little tiny bit of something else in

378
00:32:45,000 --> 00:32:49,000
our DNA perhaps that was doing it.
Tom had to go through pretty much a

379
00:32:49,000 --> 00:32:53,000
similar exercise,
but this was one of these key

380
00:32:53,000 --> 00:32:57,000
insights that lead to the proof that
RNA could function as a catalyst,

381
00:32:57,000 --> 00:33:02,000
what we now know as a ribozyme.
And I've shown you now we now sort

382
00:33:02,000 --> 00:33:08,000
of accept that the actual ribosome
itself is a ribozyme and that the

383
00:33:08,000 --> 00:33:15,000
formation of the peptide bond,
the thing that's the heart of all

384
00:33:15,000 --> 00:33:22,000
proteins is made by a ribozyme,
not catalyzed by ribosomes and not

385
00:33:22,000 --> 00:33:28,000
by a protein.  OK.
So the next topic that I want to

386
00:33:28,000 --> 00:33:35,000
try on which sort of we've already
set up from this is that if the

387
00:33:35,000 --> 00:33:42,000
information is all in DNA to begin
with then if you make an RNA copy

388
00:33:42,000 --> 00:33:49,000
you're only taking a segment of that
information at a time.

389
00:33:49,000 --> 00:33:55,000
And that gives the cells a lot of
possibilities for regulating how

390
00:33:55,000 --> 00:34:01,000
they respond to the environment or
just controlling what genes are

391
00:34:01,000 --> 00:34:07,000
expressed.  And there are basically
two kinds of strategies that are

392
00:34:07,000 --> 00:34:14,000
involved in these regulatory
decisions.  They can either be --

393
00:34:14,000 --> 00:34:29,000
Can either be reversible changes.

394
00:34:29,000 --> 00:34:33,000
For example, a bacterium and a food
source.  If you're a bacterium and

395
00:34:33,000 --> 00:34:38,000
you've got enzymes that let you eat
a hundred different kinds of food

396
00:34:38,000 --> 00:34:42,000
and you're in an environment where
there's only one of them there,

397
00:34:42,000 --> 00:34:47,000
you're really wasting energy if you
make the proteins to make the other

398
00:34:47,000 --> 00:34:52,000
99.  So you might guess that somehow
evolution has selected four systems

399
00:34:52,000 --> 00:34:56,000
that have learned how to turn on and
off the things they need to eat

400
00:34:56,000 --> 00:35:01,000
certain food sources depending on
whether the food source

401
00:35:01,000 --> 00:35:06,000
is available.
We only carry umbrellas when it

402
00:35:06,000 --> 00:35:10,000
rains.  If you had to carry an
umbrella and a snowsuit and a

403
00:35:10,000 --> 00:35:14,000
surfboard, everything all the time,
it would slow you down in evolution.

404
00:35:14,000 --> 00:35:18,000
So the other type, which we've
talked about as well when we talked

405
00:35:18,000 --> 00:35:22,000
about starting as a single cell and
going up to the 14 cells that make

406
00:35:22,000 --> 00:35:26,000
us up, then many of those changes,
as those cells go along and

407
00:35:26,000 --> 00:35:31,000
progressively more specialized need
to be irreversible.

408
00:35:31,000 --> 00:35:36,000
And this is particularly important

409
00:35:36,000 --> 00:35:40,000
in development.
We don't want a cell in our retina

410
00:35:40,000 --> 00:35:44,000
suddenly deciding it should be part
of a heart and start to make a heart

411
00:35:44,000 --> 00:35:48,000
in the middle of your eye or
something like that.

412
00:35:48,000 --> 00:35:52,000
So things in development tend to be
once you're off you're off or once

413
00:35:52,000 --> 00:35:56,000
you're on you're on or something.
And just to give you another little

414
00:35:56,000 --> 00:36:00,000
look at that picture I've shown you
before of the nematode.

415
00:36:00,000 --> 00:36:03,000
And at the time,
the first time I showed you this,

416
00:36:03,000 --> 00:36:07,000
I was just trying to emphasize that
we could take the gene encoding

417
00:36:07,000 --> 00:36:11,000
green fluorescent protein and put it
in anything and it would go green.

418
00:36:11,000 --> 00:36:15,000
In this case, Barbara Meyer who is
at Berkeley now but used to be my

419
00:36:15,000 --> 00:36:19,000
office-mate at MIT for many years,
what she's done is she's taken that

420
00:36:19,000 --> 00:36:23,000
green fluorescent protein,
the gene for that, and she's put it

421
00:36:23,000 --> 00:36:27,000
under the control of a regulatory
system, a gene that is made to be

422
00:36:27,000 --> 00:36:31,000
expressed in the esophagus
of the worm.

423
00:36:31,000 --> 00:36:35,000
And so even though that gene is
present in all the cells of that

424
00:36:35,000 --> 00:36:39,000
organism, it's under the control of
a system that usually permits the

425
00:36:39,000 --> 00:36:44,000
genes to be made that are needed for
making esophagus but not in other

426
00:36:44,000 --> 00:36:48,000
parts of the body.
So you probably didn't pick that

427
00:36:48,000 --> 00:36:53,000
part up now but sort of take another
look at that same thing and see

428
00:36:53,000 --> 00:36:57,000
something different.
So how do we learn about gene

429
00:36:57,000 --> 00:37:03,000
regulation?
The key work, like so many of these

430
00:37:03,000 --> 00:37:09,000
things, started kind of
inauspiciously,

431
00:37:09,000 --> 00:37:16,000
if you will.  There were two French
scientists, Jacques Monod,

432
00:37:16,000 --> 00:37:23,000
who is a biochemist, Francois Jacob
who was a geneticist.

433
00:37:23,000 --> 00:37:30,000
And they were working on the
metabolism of lactose by E. coli.

434
00:37:30,000 --> 00:37:36,000
Lactose is galactose,
beta 1,4 glucose.  And you don't

435
00:37:36,000 --> 00:37:42,000
have to know exactly the structure.
You can just remember there were a

436
00:37:42,000 --> 00:37:49,000
lot of different hydroxyls,
and that was one particular linkage.

437
00:37:49,000 --> 00:37:55,000
And there's an enzyme that cleaves
this into galactose and glucose.

438
00:37:55,000 --> 00:38:01,000
And this can go right into
glycolysis and make energy

439
00:38:01,000 --> 00:38:07,000
for the organism.
And the galactose undergoes a couple

440
00:38:07,000 --> 00:38:12,000
of different transformations,
and it can get in there as well.

441
00:38:12,000 --> 00:38:17,000
But in order to get at the energy
that's in those carbohydrates,

442
00:38:17,000 --> 00:38:22,000
this linkage has to be broken.  And
it was broken by an enzyme called

443
00:38:22,000 --> 00:38:27,000
beta-galactosidase.
That's a protein that's able to

444
00:38:27,000 --> 00:38:32,000
catalyze the cleavage
of those two sugars.

445
00:38:32,000 --> 00:38:39,000
That's what Jacques Monod and
Francois Jacob were studying.

446
00:38:39,000 --> 00:38:46,000
They were helped out in this
exercise.  I guess part of the

447
00:38:46,000 --> 00:38:53,000
reason they got going on this was
people had noticed for many years

448
00:38:53,000 --> 00:39:00,000
that if you grew E.
coli in glucose there was no

449
00:39:00,000 --> 00:39:08,000
beta-gal.
I'm going to abbreviate this as

450
00:39:08,000 --> 00:39:16,000
beta-gal just so I won't have to
keep writing the same thing.

451
00:39:16,000 --> 00:39:25,000
But if they grew E. coli in lactose
beta-gal was present.

452
00:39:25,000 --> 00:39:34,000
And they had to be able to assay
for this enzyme.  And they used --

453
00:39:34,000 --> 00:39:43,000
There were standard types of

454
00:39:43,000 --> 00:39:47,000
biochemical assays you could use.
But some chemists that helped

455
00:39:47,000 --> 00:39:52,000
design a very cleaver kind of
substrate that helped them,

456
00:39:52,000 --> 00:39:57,000
that could be used in these kinds of
studies, and I'll show you one of

457
00:39:57,000 --> 00:40:01,000
them.  What this enzyme really looks
at is it looks at, let's

458
00:40:01,000 --> 00:40:06,000
see, galactose.
What it sees is sort of the

459
00:40:06,000 --> 00:40:10,000
galactose side of this linkage,
and then it reaches in and catalyzes

460
00:40:10,000 --> 00:40:14,000
the cleavage of what's joined to it.
And it turns out not to be specific

461
00:40:14,000 --> 00:40:18,000
for whether glucose is on the other
side.  It can accept substrates that

462
00:40:18,000 --> 00:40:22,000
have other things as well.
So some chemists made some variants

463
00:40:22,000 --> 00:40:26,000
like this.  This is a compound
that's commonly known as X-gal.

464
00:40:26,000 --> 00:40:31,000
If you talk to it in the lab it's
got a longer chemical name.

465
00:40:31,000 --> 00:40:36,000
But what happens if
beta-galactosidase is there,

466
00:40:36,000 --> 00:40:41,000
it's able to cleave this substrate
so you get galactose,

467
00:40:41,000 --> 00:40:46,000
which is colorless.  But if you get
just X, this is colored,

468
00:40:46,000 --> 00:40:51,000
but up here this original material
is also colorless.

469
00:40:51,000 --> 00:40:56,000
So this is very convenient because
if you use a substrate such as this

470
00:40:56,000 --> 00:41:02,000
you could put the cells on a plate
with this indicator.

471
00:41:02,000 --> 00:41:05,000
And if they are colored,
and the color is blue, you'd know

472
00:41:05,000 --> 00:41:09,000
they were making beta-galactosidase.
And if you don't see a color, you

473
00:41:09,000 --> 00:41:13,000
know they're not.
There are a variety of ways of

474
00:41:13,000 --> 00:41:17,000
assaying for this enzyme.
With that I'm just trying to give

475
00:41:17,000 --> 00:41:21,000
you a little bit of flavor of one of
the different ways that they could

476
00:41:21,000 --> 00:41:25,000
assay for it.  Now,
one of the issues was it looked as

477
00:41:25,000 --> 00:41:29,000
though E. coli didn't have any
beta-galactosidase activity if

478
00:41:29,000 --> 00:41:33,000
lactose was absent when
growing a glucose.

479
00:41:33,000 --> 00:41:36,000
And they made it if lactose was
present.  Well,

480
00:41:36,000 --> 00:41:40,000
that would be kind of what you would
expect evolution would have figured

481
00:41:40,000 --> 00:41:44,000
out how to do,
only make the enzyme for

482
00:41:44,000 --> 00:41:48,000
metabolizing lactose if the lactose
is present, but they had to figure

483
00:41:48,000 --> 00:41:52,000
out what the molecular basis of this
was.  And one of the possibilities

484
00:41:52,000 --> 00:41:56,000
was that the protein was made that
it was all sort of unfolded,

485
00:41:56,000 --> 00:42:00,000
and when the substrate came in then
it folded all around it and then it

486
00:42:00,000 --> 00:42:03,000
could cleave it.
Or another possibility,

487
00:42:03,000 --> 00:42:07,000
which would be the kind we're
talking about now,

488
00:42:07,000 --> 00:42:11,000
is the protein is not made until the
lactose is present,

489
00:42:11,000 --> 00:42:14,000
and then it makes it new.
So they had to figure out,

490
00:42:14,000 --> 00:42:18,000
between these two, which of these
two was true.  When you see the

491
00:42:18,000 --> 00:42:22,000
lactose present,
is it just beta-galactosidase is

492
00:42:22,000 --> 00:42:26,000
already made but it's inactive,
or is it being made de novo when you

493
00:42:26,000 --> 00:42:32,000
add the lactose?
So what they did was they grew cells

494
00:42:32,000 --> 00:42:40,000
in glucose plus radioactive
C14-leucine for a long time.

495
00:42:40,000 --> 00:42:53,000
So all the proteins --

496
00:42:53,000 --> 00:42:56,000
-- were radioactive.
And once they got, that's going for

497
00:42:56,000 --> 00:43:00,000
a long time.  So every protein being
made is radioactive.

498
00:43:00,000 --> 00:43:07,000
Then they add excess unlabeled
leucine.  So this means that from

499
00:43:07,000 --> 00:43:14,000
now on any new proteins that are
made will not be radioactive because

500
00:43:14,000 --> 00:43:21,000
you're just going to swamp out any
radioactive stuff with this.

501
00:43:21,000 --> 00:43:29,000
And they added glucose, excuse me,
now they added lactose through the

502
00:43:29,000 --> 00:43:35,000
cells.
And then they isolated the beta-gal

503
00:43:35,000 --> 00:43:40,000
enzyme.  It was actually pretty easy
to do.  It's a huge enzyme and it's

504
00:43:40,000 --> 00:43:45,000
a tetramer.  So very large.
Even in those days it was fairly

505
00:43:45,000 --> 00:43:50,000
easy to isolate this enzyme.
And then they looked to see is it

506
00:43:50,000 --> 00:43:55,000
radioactive?  If it's radioactive it
was there all along and it's

507
00:43:55,000 --> 00:44:00,000
refolded to become the
active enzyme.

508
00:44:00,000 --> 00:44:05,000
Or if it had been only after lactose
then it would be made de novo in

509
00:44:05,000 --> 00:44:10,000
response to it.
And what they found was that it was

510
00:44:10,000 --> 00:44:19,000
non-radioactive.

511
00:44:19,000 --> 00:44:32,000
Which implied that it was made after
you added the lactose.

512
00:44:32,000 --> 00:44:38,000
So they knew then that they were
studying a system in which a protein

513
00:44:38,000 --> 00:44:44,000
was only made after the cells had
experienced a particular growth

514
00:44:44,000 --> 00:44:50,000
substrate.  And so a lot of work
went into figuring out how this

515
00:44:50,000 --> 00:44:56,000
system worked.
Let's see.  We're a little short on

516
00:44:56,000 --> 00:45:01,000
time.
So I'll tell you what I'll do.

517
00:45:01,000 --> 00:45:06,000
I'll tell you, I'll just put out
quickly the mechanics of what they

518
00:45:06,000 --> 00:45:10,000
saw, and we'll start in on the
regulation on how this works.

519
00:45:10,000 --> 00:45:15,000
And some of you may be able to
figure it out.

520
00:45:15,000 --> 00:45:20,000
What we now know is that the gene
that encodes beta-galactosidase is

521
00:45:20,000 --> 00:45:25,000
in a stretch of DNA that's pretty
interesting.  It's got three genes.

522
00:45:25,000 --> 00:45:30,000
It's the gene lacZ.  This is the
gene for beta-galactosidase.

523
00:45:30,000 --> 00:45:37,000
And another gene called lacY and
lacZ.  There's a promoter.

524
00:45:37,000 --> 00:45:45,000
That's a start signal for
transcription.

525
00:45:45,000 --> 00:45:52,000
Remember that?
So there's a sequence here that

526
00:45:52,000 --> 00:46:00,000
says start transcription.
Down here is a terminator.

527
00:46:00,000 --> 00:46:06,000
Another word written in the nucleic
acid alphabet that means stop making

528
00:46:06,000 --> 00:46:12,000
mRNA.  And there is one long mRNA,
as you can see, that has the

529
00:46:12,000 --> 00:46:19,000
peculiarity of encoding three
different genes.

530
00:46:19,000 --> 00:46:25,000
So if you have more than one gene
in a single message then that's

531
00:46:25,000 --> 00:46:40,000
called an operon.

532
00:46:40,000 --> 00:46:46,000
You've got one mRNA.
But, in any case, so whenever

533
00:46:46,000 --> 00:46:52,000
beta-galactosidase was being made
then RNA has to start being made

534
00:46:52,000 --> 00:46:58,000
here, goes to there.
And we won't worry about the

535
00:46:58,000 --> 00:47:03,000
functions of these other two genes.
But, as you might guess from the way

536
00:47:03,000 --> 00:47:08,000
evolution has selected for it,
they have related activities to what

537
00:47:08,000 --> 00:47:12,000
beta-galactosidase does.
And for bacteria it's a very

538
00:47:12,000 --> 00:47:17,000
efficient way to control the
expression of a bunch of genes at

539
00:47:17,000 --> 00:47:22,000
once.  Then there was another gene
up here known as lacI that had a

540
00:47:22,000 --> 00:47:27,000
promoter and a terminator,
and it made an mRNA as well.

541
00:47:27,000 --> 00:47:34,000
And that mRNA encoded a protein
that's known as the lac repressor.

542
00:47:34,000 --> 00:47:42,000
And what that lac repressor does,
it's a protein that has the ability

543
00:47:42,000 --> 00:47:49,000
to recognize a very,
very specific DNA sequence and bind

544
00:47:49,000 --> 00:47:57,000
there.  And I'm just going to kind
of blow up this part of the thing.

545
00:47:57,000 --> 00:48:04,000
So what we have here is the,
this is the promoter here.  And it

546
00:48:04,000 --> 00:48:11,000
happens that the binding
sequence --

547
00:48:11,000 --> 00:48:22,000
-- for lac repressor overlaps with

548
00:48:22,000 --> 00:48:32,000
the promoter.  Weird,
right?  Maybe not.

549
00:48:32,000 --> 00:48:36,000
So I'll tell you,
well, you can think about this over

550
00:48:36,000 --> 00:48:41,000
the weekend, if you haven't run into
this system before.

551
00:48:41,000 --> 00:48:45,000
So this gene gets made all the time.
So this protein gets made all the

552
00:48:45,000 --> 00:48:50,000
time.  What does that protein do if
it's just like this?

553
00:48:50,000 --> 00:48:55,000
Its job in life is to look for this
sequence and bind to it.

554
00:48:55,000 --> 00:49:00,000
If it binds to it, it covers up the
promoter.

555
00:49:00,000 --> 00:49:04,000
And the beta-galactosidase gene is
not expressed because the cell

556
00:49:04,000 --> 00:49:09,000
cannot make mRNA.
So this may seem a little obscure,

557
00:49:09,000 --> 00:49:14,000
but there's something very important
here.  Now the conditionality on

558
00:49:14,000 --> 00:49:19,000
whether this gene is expressed or
not is controlled by a protein,

559
00:49:19,000 --> 00:49:23,000
right?  It's controlled by this lac
repressor.  If it's on there the

560
00:49:23,000 --> 00:49:28,000
gene will be made.
And if it's off the gene now you

561
00:49:28,000 --> 00:49:33,000
can make it.
There's a promoter and the RNA

562
00:49:33,000 --> 00:49:38,000
polymerase will see it.
And so you've learned something

563
00:49:38,000 --> 00:49:44,000
about proteins.
They can bind various things.

564
00:49:44,000 --> 00:49:49,000
And so what lac repressor has,
it's got a little binding site that

565
00:49:49,000 --> 00:49:54,000
lactose is able to bind to and
change the confirmation of the lac

566
00:49:54,000 --> 00:49:59,000
repressor.  So why don't you take
those pieces of information and see

567
00:49:59,000 --> 00:50:05,000
if you can figure out how
the circuitry goes.

568
00:50:05,000 --> 00:50:11,000
Yeah?  Did I do something wrong?
Sorry.  Oh, sorry.  Excuse me.  Yes,

569
00:50:11,000 --> 00:50:17,000
Z-Y-A.  Excuse me.
OK?  We'll walk through that on

570
00:50:17,000 --> 00:50:23,000
Monday, but focus on the fact that
if the repressor is there and

571
00:50:23,000 --> 00:50:30,000
lactose isn't, it binds
to this sequence.

572
00:50:30,000 --> 00:50:34,000
The repressor is made all the time,
but this repressor is something that

573
00:50:34,000 --> 00:50:39,000
can tell you whether lactose is
there or not.  So you can put the

574
00:50:39,000 --> 00:50:42,000
circuit together, OK?