2 I. Perpetual Molecular Warfare: Viral Evolution in HIV

This section of the course has four goals. The first is to bring story of AIDS and HIV to an end by

telling why the initial application of the drugs that David described to you failed and use this failure to

introduce you to the connection between the chemical reactions that make up DNA replication and the

process of evolution. The second is to use the initial beneficial effect of the anti-HIV drugs to introduce

you to the difference between steady states and equilibrium, two different ways that the properties of

biological systems can become constant over some period of time, the third is to discuss how the central

dogma of DNA makes RNA makes protein evolved, and the fourth is to briefly explain the evidence for

evolution by natural selection and to explain its connection to AIDS and cancer, the two diseases that

this course focuses on.

Slide 1: 2I: Disease and Evolution: An Overview

Slide 2: Learning objectives

At the end of this section you should understand,

1) How mutations can arise, and how beneficial ones can alter populations.

2) Why steady states requires the continual input of energy, as distinct from equilibria.

3) How altering the kinetics of processes can greatly alter steady states.

4) Current thoughts on the evolution of the central dogma.

5) How DNA and protein sequences provide the best evidence for Darwinian evolution.

6) That evolution can be observed within individual patients in two human diseases, AIDS and cancer.

1: NATURAL SELECTION AND EVOLVING HOST-PATHOGEN INTERACTIONS IN AIDS

Resistance appears rapidly in patients treated with single anti-viral drugs

The discovery of inhibitors of HIV protease promised help for AIDS patients. But although drug

treatment did decrease the levels of virus in patients circulation and restore their immune systems, these

changes were only temporary. Within 12 months the T cell counts of half the treated patients had fallen,

and viral levels in their circulation had begun to rise. Isolating the virus from their blood and studying

its behavior in cell culture allowed scientists to ask whether the change had occurred in the virus or the

patient. The result was clear. The virus from the drug-treated patients had changed to become resistant

to the drugs; adding protease inhibitors to infected cells no longer reduced the amount of virus they

produced. Biochemical studies showed the protease was now more resistant to the inhibitors when its

activity was assayed in a test tube. Because the change has occurred in the protease gene of the virus,

the genetic material of the virus has been permanently altered and we refer to the change as a mutation.

The ability of these mutant viruses to take over the population is an example of evolution in action

Slide 3: Mutations make HIV drug-resistant

Unfortunately for patients, these mutations arise surprisingly rapidly, appearing roughly once for every

30,000 times a virus infects a cell and is copied into DNA. Because at least this many new cells are

infected each day, an individual cell carrying a resistant virus arises every day. As we will see later,

HIV is extremely careless with how it copies DNA into RNA compared to the care our cells take when

they replicate our DNA.

Slide 4: Types of mutation

Each mistake is a mutation. If the mutation is in the part of the viral genome that encodes one of the

viral proteins, it has a high chance of changing the amino acid sequence of the protein and thus altering

the protein’s three dimensional structure and chemical activities. The effects of the altered amino acid

sequence can be divided into three classes. Deleterious mutations impair or destroy the protein’s

function, neutral mutations have no effect on the protein’s function, and beneficial mutations improve at

least one aspect of the protein’s function. The most severe deleterious mutations kill the organisms that

possess them and are called lethal mutations. The distinction between deleterious, neutral, and

beneficial mutations is illustrated on this slide in a context that is directly relevant to you. Deleterious

and beneficial mutations are roughly equally common and both are far more frequent than advantageous

mutations.

If advantageous mutations are so much rarer than neutral or deleterious ones, why are they so important.

The answer is simple, the advantageous mutations confer a benefit to the viruses that have them,

whereas the neutral ones confer neither cost not benefit, and the deleterious ones impose a cost. Viruses

that have deleterious mutations do less well than the wild type virus and are quickly outcompeted and

eliminated from the viral population. Viruses with neutral mutations do as well as wild type and the

details of what happens to them lie beyond the scope of this course. The summary is that the vast

majority of neutral mutations are eliminated by chance rather than by selection, but over a very long

period a very tiny fraction of them go on to coexist with and occasionally replace the original wild type

virus.

Slide 5: Beneficial mutations take over populations

To see why advantageous mutations matter, imagine a mutant so strong that infected with the mutant

virus produces twice as many infectious virus particles as cells infected with the wild type virus in

patients treated with protease inhibitors. Thus in every round of cellular infection the mutant virus

enters twice as many cells as the wild type one. If we start from a single mutant viral genome, in a

patient with a billion infected cells, it takes about 30 rounds of infection for the mutant virus to

extinguish the wild type one, since the fraction of mutant virus goes from one in billion to two in a

billion in the first round of infection from two in a billion to four in a billion in the second round from

four in a billion to eight in a billion in the third and so on. Even after 20 rounds of viral replication and

cellular infection, the mutant virus accounts for only one a thousand viruses and even by the 25th round

that it accounts for only 3% of the patient’s virus. After that, it rapidly takes over. The fraction of the

viruses that are mutant has been doubling in every generation since its origin, but in large populations,

the fraction of mutant virus only becomes noticeably large after many doublings.

Mutations affect the structure and activity of proteins

Slide 6: HIV protease mutants

This slide shows how HIV’s protease can mutate to become resistant to inhibitors. The slide shows two

versions of the sequence of the HIV protease, depicted using a one letter code in which 20 different

letters of the alphabet represent the 20 different amino acids. The first is the wild type form of the

enzyme, the second a mutant form isolated from an individual who had become resistant to inhibitor

therapy. The mutant contains two amino acid changes relative to the wild type and together they have

two effects: they help the virus by reducing the sensitivity of the enzyme to the inhibitor, but they hurt

by reducing its catalytic activity. But because these mutations interfere more with drug binding than

they do with protease activity, they help HIV circumvent therapy.

Slide 7: HIV protease mutants reduce inhibitor binding

This slide shows the structure of the protease, which is a dimer made up of two identical proteins. The

course of the polypeptide chain is shown as the ribbon of white lines, the catalytic aspartates whose

function David explained to you are shown in green (and there are two such residues because the protein

is a dimer), the inhibitor, saquinavir, is shown in purple, and the two amino acids which have been

mutated are shown in yellow and blue. Note that one of them touches the inhibitor, but the other is far

away showing how perturbations of the protein that are far from the site of substrate binding and

catalysis can have important effects on the protein’s enzymatic activity.

Mutations due to mistakes in DNA synthesis and defenses against them

We now consider the details of how the mutations appear. As Rob told you, when HIV infects cells, its

RNA genome is copied into DNA. This slide reminds you about the basics of this process and reverse

transcriptase, the enzyme that does the copying by starting at one end of the RNA strand and copying

the information all the way down to the other to create the first DNA strand, and then using this new

strand as the template for synthesizing a second to produce a double stranded DNA molecule that is

ultimately integrated into the host cell’s genome. Reverse transcriptase makes occasional mistakes and

puts the wrong base into the DNA (shown as a star in the figure). These mistakes are mutations and will

appear in every RNA molecule that is copied from the viral DNA that contains the initial mistake and

when these RNA molecules are incorporated into viruses they will transmit this mutation to the cell they

infect, and so on.

Slide 8: Reverse transcriptase copies HIV RNA into DNA

Why is HIV’s reverse transcriptase so sloppy compared to the DNA polymerases that replicate our own

DNA? To answer this question we must go back to David’s lectures on the structure of DNA and the

enzymes that replicate it. When reverse transcriptase copies the viral RNA into DNA it is like DNA

polymerase taking one of the two strands of a DNA duplex and using it as the template to produce the

new strand of the daughter double helix. Reverse transcriptase and DNA polymerase both use an

existing nucleic acid strand as a template to synthesize a new DNA strand, but the template is RNA for

reverse transcriptase and DNA is the template for DNA polymerase. In each case, an A in the template

strand tells the polymerase to put a T in the new strand it is synthesizing, a template G tells polymerase

to insert a C, and so on.

Slide 9: A rare isomer of guanine pairs with thymine instead of cytosine

Mutations arise, because at a low frequency the wrong two bases can pair with each other. One reason

that this can happen is that all of the bases can exist in more than one form, an example of what is

referred to as a constitutional isomer, an alternative molecule that contains the same number and same

type of atoms but with the atoms connected to each other in a different way. The rare forms account for

0.1 to 1 % of each base, which gives them the potential to cause many mutations in each newly

polymerized strand of DNA. As an example, this slide shows the normal and the rare form of G. Each

has the same chemical formula, but the position of the atoms differs, with affected atoms being indicated

in red, and you can think of the change as the movement of a hydrogen atom from a nitrogen to an

oxygen atom. The rare form of G fails to base pair with its normal partner C and base pairs with T

instead, with the disastrous consequence that a T gets inserted into the newly synthesized DNA strand

instead of a C. The DNA molecule now contains a G:T base pair and if nothing else happens, when it

replicates it will produce two daughter molecules, one with the correct G:C base pair and the other with

a mutant A:T base pair.

Slide 10: Abnormal base pairing causes mutation

During DNA replication there are two defenses against putting in the wrong base as the DNA

polymerase makes the new strand. The first is called proof-reading, and it means that after inserting

each new base, the DNA polymerase goes back and checks whether it has put the right base in. If it

hasn’t, it cuts the errant base out and tries again. The second is called mismatch repair and David

referred to it when he discussed DNA replication. The basic idea is simple: an abnormal base pair like

the G:T one we discussed above leaves a tell-tale bulge in the DNA helix and the proteins of the

mismatch repair system detect these bulges and cut out the mistakenly incorporated base allowing DNA

polymerase to try again.

Slide 11: Defenses against mutation

These three lines of defense against error illustrate an important biological principle. Many biological

processes work so supremely well that it seems hard to believe that they could have been put together by

gradual improvement. But if we study them carefully we can see the traces of the progressive

refinement that comes from taking an initially error-prone way of doing things and then adding several

layers of checking machinery that catch and then rectify mistakes. In the case of DNA replication, we

will see that all the layers of checking and correction are crucial to preventing cancer in humans, which

contain 10 trillion cells and go through 10,000 trillion rounds of DNA replication in their 70 year life

span.

For HIV, the tragedy is that none of the methods for finding and fixing errors are used; reverse

transcriptase does not proof-read each newly incorporated base as it copies RNA into DNA, and the

mismatch repair system doesn’t work on the DNA strand that is being copied from RNA. The result is

that during reverse transcription of the viral RNA into DNA, the chance of making a mutation at any

given base is roughly 1 in 30,000, whereas for the replication of cellular DNA it is somewhere between

one in a billion and one in 10 billion.

It is HIV’s high rate of mutation that makes AIDS such a difficult disease to cure. It allows the virus to

mutate so that if can infect different cells in the body, explaining how the virus can start by infecting T

cells and then later infect macrophages or vice versa, as Rob discussed. It allows the virus to mutate so

that it becomes resistant to what were originally extremely potent inhibitors of its reverse transcriptase

and protease. And finally, the high rate of mutation has made an effective vaccine against HIV elusive,

because we need to find a part of the virus so crucial to its function that any mutation that allows the

virus to escape from the vaccine-induced immune response will also kill the virus.

It is HIV’s high rate of mutation that makes AIDS such a difficult disease to cure. It allows the virus to

mutate so that if can infect different cells in the body, explaining how the virus can start by infecting T

cells and then later infect macrophages or vice versa, as Rob discussed. It allows the virus to mutate so

that it becomes resistant to what were originally extremely potent inhibitors of its reverse transcriptase

and protease. And finally, it has made an effective vaccine against HIV elusive, because we need to find

a part of the virus so crucial to its function that any mutation that allows the virus to escape from the

vaccine-induced immune response will also kill the virus.

Fighting on two fronts: How combination therapies hold AIDS in check

Mutations in the genome of HIV play two important roles in AIDS. They can alter the cell preference of

the virus and they can interfere with therapy. How can we overcome the rapid mutation of HIV to drug

resistance so that we can cure patients? The answer is familiar to students of military history: attack on

two fronts. For HIV, the two fronts are the reverse transcriptase that copies the viral genome into DNA

as it enters new cells and the virally encoded protease that clips the original polypeptides that are

translated from the virus’s mRNA into the mature proteins. In both cases, scientists have developed

drugs that bind tightly to the active site of the enzymes, preventing them from binding their natural

substrates and Rob and David have described these drugs and their mechanisms of action to you.

Combination therapies attack both targets, the reverse transcriptase and the protease, at once. Patients

are treated with a mixture of two drugs, one inhibiting the protease and the other reverse transcriptase.

Mutations that confer resistance to either drug don’t help, because the other drug still blocks viral

replication. In order to escape the virus has to become resistant to both drugs at the same time.

Slide 12: Combination therapy makes mutating to resistance harder

We can make a rough estimate of how likely such an event is. Assume that we need mutation at one

position in the viral genome to give resistance to protease inhibitors and at another position to give

resistance to reverse transcriptase inhibitors. Each mutation arises at a frequency of 3 x 10–5, so the

frequency of getting both mutations at once is 3 x 10-5 x 3 x 10-5 ≈ 10-9 per round of viral replication.

This means that resistance will arise once in every trillion copyings of the viral RNA into DNA.

Is this rare enough and can combination therapy cure patients to the point where they can stop taking the

drugs? The answers are almost but not quite and no, and we will now discuss both of them in more

detail. We begin with the first and start by using an analogy to games of chance. If you are throwing

one dice, and need to throw a six to stop the game, your chance of doing so on the first throw is 1/6.

Using the laws of probability you can calculate the chance that you will have thrown a six at least once

in any given number of throws, thus constructing the graph that is shown on the slide. It reveals that by

the time you’ve thrown the dice 30 times you are almost sure to have rolled a six. Now imagine that you

have two dice, that you throw them together, and that both must come up six in order to stop the game.

The chance of this happening in the first throw is simply the chance of the first dice showing six time the

chance that the second dice shows six, that is 1/6 x 1/6 = 1/36. Now it take much longer on average to

end the game, and even after 100 throws there is some reasonable chance that you have failed to throw

two sixes.

Slide 13: Mutating once versus mutating twice: a dice analogy

We can make an exactly similar calculation for the generation of singly and doubly mutant viruses, and

focus on combination therapy where we need two mutations to happen at the same time and place. For a

single infected cell, this is the chance of mutating to resistance to protease inhibitors times the chance of

mutating to resistance to reverse transcriptase inhibitors. We have already calculated this chance as

being 9 x 10-10 or roughly one in a billion. For a patient, we need to know what the chance of this event

happening anywhere in their body is. To know the chance that a doubly resistant virus appears on a

given day, we multiply the probability that the infection of one cell leads to resistant virus by the

number of new cells that are being infected each day. This is like our dice analogy in the sense that we

are requiring two events to happen at once, and differs only because we are now doing the equivalent of

shaking the dice many time each day.

Slide 14: HIV can become doubly drug resistant

The graph shows the fraction of patients who will have generated doubly resistant viruses against the

time of treatment in months. One of the curves is for patients where 1,000,000 new cells are infected

every day, despite the combination therapy, and the other is for patients where 100,000 new cells are

infected each day. Both numbers are miniscule compared to the roughly a billion cells which are being

infected each day in an untreated patient, but the two curves make it clear that the difference between

100,000 and 1,000,000 cells being infected every day can be the difference between life and death.

Many factors determine this difference, some known and some unknown. Three are prominent:

different patients do a better or worse job of managing to stick to a demanding and long-term schedule

for when they take their medications, in some patients the drugs cause toxic side effects limiting the

doses that they can tolerate, and some patients metabolize and eliminate the drugs faster than others.

The last two relate to two important issues with medical drugs, toxicity, the need to do as much as

possible to make sure that the drugs do not have dangerous and unintended effects as well as treating the

patient’s illness, and pharmacokinetics, which David explained to you dealt with the metabolism of

drugs after they have been given to patients. In both cases, scientists and doctors have come to realize

that there are substantial differences between individuals in both drug toxicity and pharmacokinetics,

and that some of these differences are due to genetic differences between individuals in the human

population, a topic that you will hear more about if you take LS1b.

2 STEADY STATES PREVAIL IN BIOLOGY

There are two reasons why combination therapy can’t eliminate the virus from HIV-infected patients.

First, and most importantly, the drugs don’t kill infected cells and any new cells they divide to form.

Because the viral genome has been copied into DNA and integrated into the chromosomes of these cells,

they can only lose their potential to secrete virus when they die, either because the virus becomes

activated and kills the cell or the cell reaches the end of its natural life. Since some of the cells are

memory cells of the immune system, they can persist for years in a quiescent state in which they do not

grow, proliferate, or express the viral genome they contain. The second drawback is that although the

drugs enormously reduce the rate at which new cells are infected, they do not eliminate new infection,

so that the virally infected cells that are dying are partially offset by new cells that are being infected.

Slide 15: Steady states prevail in biology

These two features mean that you cannot quit combination therapy. If you do, the combination of the

low level of virus in your blood, and the ability of already infected cells to make new virus leads to a

dramatic rise in the frequency at which new T cells get infected and patients can progress to full-blown

AIDS. What this tells us is that combination therapy has created a state of détente in HIV-positive

patients; the level of virus in the blood and the number of infected cells has fallen dramatically but even

at these low levels, a new cell is infected for every infected cell that dies, meaning that the virus can

never be eliminated.

Slide 16: Equilibrium revisited

This stand off is an example of something that we see again and again in biology, a balance, or steady

state being set between two opposing forces. These stand offs are often referred to as equilibria, but this

is wrong. In its strict sense, and as David explained, equilibrium refers to a situation in which no net

chemical change is occurring because the backwards and forwards rate of a process balance and no

energy is being consumed or released. This slide shows a hypothetical reaction between A and B to

make C and D. The rate constants for the forward and backwards reactions are both 1, meaning that the

equilibrium constant is 1. The graph shows four different quantities over time:

1) The fall in the concentration of A.

2) The rise in the concentration of C

3) The rate at which C is being formed

4) The free energy change for the reaction

All of these quantities change quickly at first, then fall more slowly, and eventually become constant. In

particular at the end of the reaction the concentrations of A and C are equal, the rate at which new C is

being formed has become zero, and the free energy change has fallen to zero. These last two are crucial

points and you should remember them from David’s lectures. At equilibrium, the rates of these the

forwards and backwards reactions must be equal, there can be no net expenditure or consumption of

energy, and ∆G under these conditions is zero.

In biology, a steady state implies three things:

1) That the rates of two opposing processes are exactly equal to each other (as they are at an

equilibrium).

2) The backwards and forwards reactions take different chemical paths and neither is close to

equilibrium.

3) Cells must harvest energy from their environment to keep these reactions from approaching

equilibrium.

Slide 17: Rates of infection and death balance

The progress of AIDS and the response to combination therapy provide an interesting example of a

steady state. When a patient is infected, an acute phase where virus levels are very high is followed by a

long latent phase during which the level of T cells and virus in the blood is substantially lower than it is

during the acute phase. We now describe how this state is reached by considering the balance between

the rate at which cells are born and the rate at which they are infected, and thus become destined to die.

In the acute phase there are many virus particles and many cells to infect, so many T cells get infected.

The crucial point is that the rate at which cells are infected is much higher than the rate at which new T

cells are born. Since more cells are being infected than are being born, the number of uninfected T cells

falls. As it does so, it gets harder to find new cells to infect and since there are less cells to infect, the

rate at which cells are getting infected goes down. But as long as the rate of infection is greater than that

rate at which T cells are being born, the population keeps falling, albeit more slowly. You can see that

as this process continues, the number of uninfected T cells must eventually reach a point at which the

rate of infection precisely matches the rate at which new T cells are born. The number of T cells is now

at steady state, since on average precisely one new T cell is born for every one which is infected and

then dies.

This is not an equilibrium in two obvious senses: the birth and death of cells are clearly different

processes, and energy and raw materials are being used to produce the new, uninfected cells that allow

the steady state to be maintained. Unfortunately for the patients, this concentration of T cells is so low

that their immune system is severely compromised and they are easy prey to a wide variety of infectious

diseases.

Although the latent phase is long, most patients who are not treated will eventually develop full blown

AIDS and succumb to opportunistic infections. Combination therapy prevents this by taking the patients

immune system to a different steady state. By interfering with infection by inhibiting reverse

transcriptase, and with the production of new virus by inhibiting the HIV protease, combination therapy

independently reduces the level of circulating virus and the probability that an individual virus will

succeed in infecting a T cell. This combination dramatically reduces the rate at which cells get infected,

and as a result cells are now being born much faster than they are being infected. This imbalance means

that the number of T cells starts to rise. As it does so, the rate of infection rises, but as long as it is still

lower than the rate at which cells are born, the number of circulating T cells continues to rise, albeit

more slowly. Again, this rise continues until the rate of infection exactly matches the rate of cell birth

and the patient’s immune system has reached a new steady state. Because the virus is still present,

however much its level has been reduced, patients cannot quit combination therapy. If they do, the virus

particles succeed more often in infecting cells, and the number of virus particles each infected cell

releases goes up. As a result the level of circulating virus rapidly rises and the patients will return to

their previous steady state in which virus levels are high and T cell numbers are low.

Thus both before and after combination therapy, the patient is in steady state, but the two steady states

are radically different. This difference reflects the fact that the rate at which T cells are born is

essentially constant, but the rate of infection is far higher in untreated patients. In these individuals, the

rate of infection can only equal the rate of birth when the level of T cells has fallen so low that they are

hard to find and infect. But once the rate of infection has been reduced by therapy, the virus now needs

a much higher level of T cells to achieve the same rate of infection. In the case of T cells in AIDS

patients, it is particularly clear that neither of the opposing process, the death of infected cells or the

creation of new ones, can be described a chemical equilibrium. Death is clearly irreversible, and

creating new cells must require the input of substantial amounts of energy and raw materials. In most

biological steady states, both of the opposing processes require the input of energy, most often as a

result of the hydrolysis of ATP.

Slide 18: Equilibrium versus steady state 1

This slide contrasts the concepts of equilibrium and steady state in more conceptually. The red and blue

circles represent the substrate and product of the forward reaction, and their sizes are proportional to the

concentrations of these compounds. Hopefully, you will now be able to instantly appreciate that we can

turn the tables and think of the blue circle as the substrate for and the red circles as the product of the

back reaction. For simplicity, I have shown an reaction whose equilibrium concentration is 1, but you

should be aware that this is not a typical value. In an equilibrium, the reaction proceeds until the rates of

the forward and back reactions are equal. When they are, as David explained to you, ∆G is zero, and the

system is at thermodynamic equilibrium.

Now contrast this to a steady state system typical of biological systems. In this case the reaction that

converts red to blue is a chemically different reaction from the one that converts blue to red. Both

reactions are coupled to ATP hydrolysis and as a result of this coupling, they have a strongly negative

free energy, meaning that they are far from equilibrium inside the cell. Now what determines when the

rates of the forward and backward balance is not thermodynamics but kinetics. This is good news for

biological systems that want to be able to use information from their environments to alter steady states

inside cells, since you will remember from David’s lectures that enzymes affect the kinetics of reactions

but cannot affect their equilibria. The bad news is that although biological steady states can be

maintained at positions far from thermodynamic equilibria, this only happens because two chemically

distinct and biologically opposing reactions have each been coupled to ATP hydrolysis so that they are

far from equilibrium, this ATP hydrolysis implies that ∆G for the entire system is strongly negative.

The consequence of this is that living systems require the continual input of energy to maintain steady

states, which explains why one of the central requirements of life is the ability of organisms to harvest

energy from their environment.

Slide 19: Equilibrium versus steady state 2

We can summarize the differences between equilibria and steady state as follows:

1) In both situations the rates of the forward and backwards processes are equal, so that, over time, there

is no net change in the part of the system we are observing.

2) In equilibria, the backwards reaction is simply the forward one running backwards, and the reaction

diagram of one can be converted into that of the other simply by reversing the roles of substrates and

products. In steady states, the forwards and backwards reactions are chemically distinct, are catalyzed

by different enzymes, and have different reaction diagrams.

3) In equilibria, enzymes can affect how fast the system reaches equilibrium but cannot affect the ratio

between products and substrates at equilibrium. In steady states, the ratio of substrates and products is

determined by the rate constants of the enzymes that catalyze the forwards and backwards reactions, so

that regulating the activity of one enzyme while the other is left constant affects the balance between

substrates and products.

4) At equilibrium there is no net loss or gain of free energy. At steady state there is a net loss of free

energy, implying that a biological system can only remain at steady state as long as it can harvest energy

from its environment or from internal stores.

3: EVOLUTION OF THE CENTRAL DOGMA (Slide 20)

This is a useful point to look back and see what we have learnt in the course so far. We have used HIV

and its behavior to illustrate what Francis Crick called the central dogma, the idea that information flows

from DNA to RNA to protein. In HIV, the DNA is the viral DNA that is integrated into the host cell’s

genome, the RNA is the mRNA that is copied from it by the cellular RNA polymerase, and the proteins

are the structural proteins of the virus, the reverse transcriptase and various small peptides that regulate

the behavior of the host cell. HIV also illustrates that the rules of the central dogma are not immutable,

since during infection, the reverse transcriptase copies the viral RNA into a DNA copy that is then

integrated into the host genome. Although this behavior is exceptional, it serves as an important

reminder that even though it is much less chemically stable than DNA, RNA can be used as the genome

of an organism.

Slide 21: The central dogma

Slide 22: Evidence for RNA as the original catalyst

Scientists now believe that the most ancient ancestors of today’s organisms used RNA not only as their

genomes but also as catalytically active molecules that were used for genome replication, energy

harvesting, and other essential functions. The best evidence for this idea is the discovery that RNA

molecules exist in nature that can catalyze chemical reactions and that these reactions are exactly the

sort of reaction that might have been needed early in life’s evolution. One example is self-splicing

RNA. Rob discussed the splicing of mRNA in eukaryotic cells and this depends on a complicated

mixture of RNA and protein molecules, but there are a few specialized RNA molecules that are capable

of splicing out their introns without any help from proteins. The slide shows one with the intron shown

in green and the two exons that are about to be joined together appearing in blue and red. Perhaps even

more tellingly, the ribosome, the machine that synthesizes proteins, uses its RNA rather than its protein

components to catalyze the reaction that joins one amino acid to the next. This is exactly what we

would expect if the original protein synthesizing machine was made of RNA, and the protein

components were only added later.

Slide 23: Life began in an RNA world

In this view of the evolution of life, RNA came first both as catalytic and information carrying

molecules. In this era, RNA was responsible for everything, including harvesting energy from the

primitive cell’s environment, making new RNA molecules for the next generation of cells, and the

metabolism of any small molecules that went on in these cells.

Slide 24: Evolving dogma: proteins come next

We believe that the next stage was the use of small proteins as catalysts for various processes and the

selection of a general mechanism for using the information encoded in RNA to instruct the synthesis of

proteins. Today’s descendant of that general mechanism is protein synthesis, which as Rob and Dan

have discussed, uses a combination of transfer RNA and the ribosome to convert a linear string of bases

encoded in the messenger RNA into a linear string of amino acids, which then folds up to form a unique

three dimensional structure. Once a general scheme for protein synthesis had been invented, many of

the catalytic functions of RNA molecules were taken over by proteins whose structure and chemistry is

inherently more flexible, with only the most central functions, such as protein synthesis, retaining an

RNA component. Today the vast majority of enzymes and structural components of the cell are

proteins.