# Presentation: 702916

## Nature's Nanomachines:

**Joshua W. Shaevitz**
**Departments of IB, MCB, and BioE**
**Miller Institute for Basic Research in Science**
**Univ. of California, Berkeley **
_**jshaevitz@berkeley.edu**_

**Nature's Nanomachines:**
**The Physics of **
**Biomolecular Motors**

- Fermilab Colloquium
- Wednesday October 13, 2004

**Notes:**
Give and outline

The first half of the talk will be an introduction to molecular motors and optical traps

The second half of the talk will be about a really neat enzyme called RNA polymerase and a proofreading mechanism that it
uses to correct mistakes in messenger RNA.

## Motion is the defining characteristic of life 

- Mitosis:	http://www.bio.unc.edu/faculty/salmon/lab/mitosis/
- Bacteria: 	http://www.rowland.org/labs/bacteria/index_movies.html
- 	http://cmgm.stanford.edu/theriot/movies.htm
- Insects:   	http://www.uku.fi/~holopain/ento/digivideo.htm
- Gazelle:	http://tva.canoe.com/emissions/salutbonjourwe/salutptcom/
- Human:   	http://www.sip.uiuc.edu/tdwg/baby/videos.html

**Notes:**
I hope that seeing these movies leaves you with the feeling that life is full of motion.  From the separation of individual chromosomes during cell division to the stochastic movements of a typical human specimen, life is defined by motion.  Indeed, the word animate, a moving thing, means that which is alive.  Biology has developed many clever tools for producing motion.  Single cells can swim by using a propeller, by pulling in a grappling hook, and by building a road behind them from which to push off.  As the organisms gets larger the motions become more impressive.  This gazzelle can run up to the amazing speed of 40 mph, quite a bit faster a typical San Fran Bay area commute!

## Biological motion is produced by molecular motors

- Myosin: muscle contraction, cargo transport
- Kinesin: cargo transport, chromosome separation
- Dynein: cargo transport, sperm swimming
- Lambda exonuclease: chews up a strand of DNA
**RNA polymerase: copies DNA into RNA**
- ATP synthase: a rotary turbine that generates ATP
- and many others . . .

- Molecular motors are enzymes that convert chemical energy into mechanical work to produce movement

**Notes:**
The truly amazing thing about the large variety of motions produced in nature is that they are all caused by molecular motors.  Molecular motors are single proteins or protein complexes that convert chemical energy into mechanical work.  As you can imagine, there are a large number of different motors that perform different tasks.  Myosin is the motor responsible for muscle contraction.  Kinesin and dynein ferry vesicles across your cells in order to deliver vital nutrients.  There are motors that move along DNA and even rotary motors.  And I’ll tell you a little more about some of them in a few minutes.

## Molecular motors live in a nanoworld

- Molecular motors . . .

- are small in size (1 – 10 nm)
- move in tiny steps (1 – 10 nm)
- produce tiny forces (1 – 100 pN)
- use a chemical energy source (e.g. 	by breaking a chemical bond)
- care about Brownian motion
- can be very efficient (50 – 100%)

- Molecular motors are true nanotechnology!

**Notes:**
Molecular motors live in a nanoworld, and by that I mean that their dimensions and the motions that they produce are measured in the units of nanometers.  They typically measure between one and 100 nm in size, and they move in steps of tens of nm.  The forces they produce are in the range of 1-100 pN.  In order to produce mechanical work, molecular motors use a chemical energy source, usually they use the free energy released from breaking a chemical bond.  They tend to use this energy very efficiently.  As technology starts to move towards the nanoscale, we should all remember that nature has been there for a long time.  These molecular motors are true nanotechnology.

## Biology presents a window into the nanoworld

- Foresight Institute

- “Development of the ability to design protein molecules will open a path to the fabrication of devices to complex atomic specifications, thus sidestepping obstacles facing conventional microtechnology.”

*P.N.A.S.*
- 1981

**Notes:**
A big deal has been made out of the “nanotech” revolution and miniaturization.  Eric Drexler, of the infamous Foresight institute, has some pretty crazy ideas about how the world will change when the nano-revolution comes about.  Now, while I don’t subscribe to very much he says I do think that he had the right idea when he said the following in a paper in 1981 when he essentially said by studying the design of proteins, specifically molecular motors, we can learn what the tools are for working at the nanolevel.  I think that its clear that the current methods for fabricating nano-scale will never produce anything as complex as a moving protein and what we need to do is gain a new skill set.

REWORD!!!!

## Relevant (biological) length scales

- 1011 nanometers

- 103 nanometers

- 109 nanometers

- 102 nanometers

- 104 nanometers

- 10 nanometers

- Red Blood
- Cells

- E. Coli Bacteria

- Viruses

- Proteins

- Humans

**Notes:**
I wanted to put this slide in to get everyone thinking on the right scale when we talk about these biological motors, and thinking about the nanometer scale.  Starting with what should be a familiar structure here at Fermilab, Wilson Hall is about 10^11 nanometers.  Humans, you probably recognize this famous picture of Watson and Crick from 1953, fall in at about 10^9 nanometers, and out tissuse is made up of cells that are on the order of 10^4 nanometers.  Now, most bacteria are simpler cells than our cells and they’re typcally 10^3 nanometers.  Viruses are MUCH simpler entities.  This bacriophage is a virus that infects E. coli and you can see how small it is compared to the bacteria its infecting.  You might notice that this virus looks like a miniature lunar lander and in fact that’s pretty much what it is.  I encourage you to learn more about viruses because that are truly one of the most cool and terrifying things you can learn about in biology.  Molecular motors, the focus of my talk today, are proteins, and as I said they tend to be ~10 nm in size.

Watson left, Crick right

Red blood cell 8 um

E coli 1 um

Bacteriophage on E coli 24-200 nm

Enzymes 1-100 nm

DNA

## Biological filaments are the cell’s highways

- Microtubules
- Actin filaments
- DNA

- 25 nm

- 8 nm

- 36 nm

- 9 nm

- 2 nm

- 3.4 Å

- 3.4 nm

**Notes:**
Most motors move along some sort of filament.  Microtubules and Actin filaments are members of the cytoskeleton, which provides much of the structural rigidity and shape to your cells.  Kinesins and dyneins move along microtubules, which are long helical polymers that are usually 13 protofilaments running parallel to the long axis.  The helical is hollow inside with a diameter of ~25 nm.  Each protofilament is made up single a-b tubulin subunits.  The spacing between adjacent subunits is 8 nm, and we’ll see that kinesin walks along MT in 8 nm steps, one step per filament.  MT are extremely important to cell biology, and during cell division make up the mitotic spindle which you may have seen some amazing pictures of.

Actin filaments are quite a bit thinner than MTs.  These double helixes have a diameter of 9 nm and a helical pitch of 36 nm.  Myosins are the motors that walk along actin and we’ll see how these proteins are arranged in your muscle cells.

Finally, a large class of motors move along DNA, performing such tasks as copying, editing, fixing, cutting, and untangling the polymer contains the genetic code.  DNA is not actually a protein, but polymeric acid structure.  The well known double-helix is 2-nm wide with a pitch of 34 nm, or 10 bases.  The separation between adjacent bases is 3.4 angstroms, an incredibly small distance.

## Myosin: the motor that flexes your muscles

- movement is driven by ATP hydrolysis
- each myosin strokes by ~5 nm and then lets go
- maximum force generation ≥10 pN

- Sale and Sabbadini, UCSD

**Notes:**
Our first example is myosin, the protein responsible for flexing your muscles.  Being that I am from Cal-I-Fornia I couldn’t help but use our esteemed governor as a nice example.  Now each muscle is made up of a series of muscle fibers each of which contains many individual sarcomeres shown here.  In a sarcomere, two kinds of filaments can be seen, thick and thin.  The thin filaments are actin which we just talked about.  The thick filaments are actually bundles of myosin motors.  These motors are stroking motors, during ATP hydrolysis they bind an actin filament and transplace it by ~5 nm, shortening the sarcomere and then let go as shown in this movie.  The collective action of about a billion of these motors results in the contraction of your muscle by a cm or so.  You can imagine a crew team with a million people all stroking at once!

## Kinesin: the cell’s railroad engine

- Vale & Milligan, *Science* (2000)

**kinesin**

- Hirokawa, *Science* (1998)

- is driven by ATP hydrolysis
- has two small catalytic feet (~4 nm)	 that walk hand-over-hand on a 	microtubule
- walks in 8-nm steps
- moves at ~100 steps/sec for ~1 sec
- is ~70% fuel efficient at maximum force 	(~6 pN)

- Time (s)

- Distance (nm)

**Notes:**
The kinesin motor serves a quite different role in your cells.  Its job is to ferry other molecules from one side of your cells to another.  In your nerve cells, the neuro-transmitter chemicals are manufactured at the cell body in your spinal column but need to end up, say, at the synapses in your big toe.  So, the cell packages up these chemicals in a small lipid vesicle and starts it on a long journey walking along the microtubules that lie along the axis of the nerve cell.  Now, kinesin can only move ~1 um/s at its fastest, so you can imagine that this process takes a while.  In a giraffe it can be months!  This micrograph shows a picture of a kinesin, which I’ve colored in yellow, carrying this veiscle here.  Now we know quite a bit about this motor.  We know that it has two feet that both hydrolyse ATP and walk hand-over-hand, hydrolyzing 1 ATP molecule per 8-nm step along the MT subunit lattice.  It can move about 100 steps/s for approx a sec before it falls off and has to diffuse back to the MT.  You can watch this enzyme step, shown here, as you apply a force to it and because you know how much energy is stored in and ATP phosphate bond you can calculated the efficiency of the motor.  Kinesin stalls out at about 6 or 7 pN which yields an efficiency of something like 70%.  Now, people have taken all this information and developed some crazy models for how it might work.  Here’s just one example from a team at UCSF.  Ignore the bounding proteins which violate low-Reynolds # hydro 

## ATP synthase: a molecular turbine

- Wang and Oster *Nature* (1998)

- makes ~10 ATP/s
- 1 ATP ~ 10-19 J
- → Power output ~ 1 attowatt

**Notes:**
The third example of a motor I’m going to tell you about is actually a molecular turbine that is responsible for generating much of the energy in your cell.  Now of course this is a little bit different that your normal generator, this protein syntesizes the ATPs that are then used by other enzymes (like kinesin and myosin).   IN a mitochondria, the so-called power-house of the cell a group of enzymes lies in the inner-membrane.  These shown here transport protons from the inner matrix to the space between the two membranes setting up a proton gradient.  The ATP synthase then uses this proton gradient to produce a rotation of a central shaft of the protein shown here called the epsilon subunit.  This rotation causes the enzyme to adopt a series of configurations favors the binding of a free phosphate to an ADP molecule.  A movie of some of these motions is shown here.  The whole enzyme is about 20 nm, 7 in the membrane and 13 below.  This rotary motor can make up to 10 ATPs/s and since each one is worth about 10^-19 J this is an attowatt generator.

## ATP synthase is a reversible engine!

- If you give the turbine fuel (ATP), it spins backwards

- Yoshida et al. *Nature Reviews Molecular Cell Biology* (2001)

**Notes:**
Now, this generator is actually reversible.  If you give it enough ATP, it will hydrolyse it and run the shaft backwards and drive a a proton gradient the other way.  This is used by some fermenting bacteria which do not have an electron transport chain, and hydrolyze ATP to make a proton gradient, which they use for flagellar movement and transport of nutrients into the cell.  A really clever group in Japan figured out how to study this.  They attached actin filament to the shaft of the motor and gave it lots of ATP as is shown in this movie.  On this side you can see the actual experiment, notice this filament twirl around and around. Since then they’ve actually been able to apply torque to the shaft and show that it makes ATP!

## Molecular motors require an interdisciplinary approach

**Biochemistry ****	**(Molecular Reaction)
**Biostructure** 	(Molecular Geometry)
**Biophysics** 	(Molecular Mechanics)

- Displacements and Forces
- in salty H2O at room temp!

**Notes:**
By now I hope that you’ve come to the conclusion that molecular motors are truly fascinating and that in order to understand them we really need to take an interdiscplinary approach.  Firstly, they’re all enzymes and need to be studied using conventional biochemical techniques in order to understand the molecular reactions involves in movement.  Secondly,  its hard to think about how they might work without a good picture of the motor.  X-ray cystallography, Cryo EM and other structural techniques are used to create static pictures of these enzymes.  And then finally we’d like to understand the physics of how they work, the molecular mechanics if you will.  In order to understand how these motors function we really need a good understanding of all of these topics.  Now the mechanics questions usually boil down to measurments of force and displacements, although there are other things to be done as well.  Well, you tell you’re neighborhood exp physicist that you want to study the nano-scale motions of these proteins and his answer will probably be to study them in a vacuum at 100 nK.  The only problem is that biology doesn’t work that well in that regime!  You need to be able to study these nano-scale events in salty water at room temp.

FORCE TELLS ABOUT MOTION THINGS...

## Tools for measuring displacements and forces

- and many more ...

**Microscopic markers**

**Fluid flow**

**Atomic Force Microscopy**

**Magnetic Force Microscopy**

**Notes:**
Many different tools have been developed for studying the motions and forces from individual motor molecules.  Most of these proteins are too small to be seen with conventional light microscopy and so you can put probes on a motor, either a glass or polystyrene bead or a flourescent molecule, in order to watch the position of a motor as it moves along.  AFMs have been used to study forces.  Here we have a motor molecule attached to a surface which the AFM pulls on the polymer the motor walks on.  As the motor moves the cantilever gets deflected and you can measure both the position of the motor and the force that its generating.  In addition to mechanical forces you can apply forces with fluid flow.  In this experiment the bead on the right experiences a drag force that is felt by the motor.  Magnetic fields can be used to pull and rotate nanoscale objects.  Here a paramagnetic bead is attached to a single piece of DNA.  As the magnetic field is rotated the bead also rotates and this causes twist to be built up in the DNA.  There are quite a few other techniques that have been developed including the one that I’d like to highlight here, the one I used for all my measurements in graduate school, and that’s the optical trap or optical tweezers.

## Optical traps are three-dimensional springs made of light

- Ashkin et al., *Optics Letters* (1986)

**Notes:**
In the Block lab we use optical traps to study many different molecular motors.  Optical traps are springs made of light, and a lot of the early work was done by Art Ashkin and Steve Chu at Bell labs.  If you focus a laser beam down to a very tight focus, then a small particle, such as a glass bead, will be trapped in the focus as if it were held by a 3D spring.  Optical traps have been used to move things around and to measure the motions of single motors with very high resolution.  Because they act like springs, you can use them to apply controlled forces to biological molecules.  This is a cute movie that Steve took along time ago that I think is just really cool.  Here you see a bunch of E. coli bacteria swimming in a microscope slide and when the laser is turned on we can trap one of them.  Now, being the sadist that he is, Steve is not content just watching this bacteria hold still, so he wiggles the trap around and even moves it in a square by steering the laser beam.  This one must have been bad because now Steve rams it into the surface.  You can imagine what its like to be his graduate student!

## Small particles bend the trapping laser light

- Objective

- The trapping laser imparts a force onto the particle directed towards the laser focus.
- The magnitude of this force is:
*P* = laser power
*n* = particle refractive index
*c* = speed of light
*Q* = trapping efficiency

- Reviewed in Svoboda and Block, *Annu Rev Biophys Biomol Struct* (1994)

- Force

**Notes:**
So how do optical traps work?  Well, the trapped particle, a bead here, scatters the laser light laterally if the bead is displaced from the center of the trap, that’s the blue and red arrows.  Because light carries momentum, the bead has to change the momentum of the light when it bends the direction, and thus the light imparts an equal and opposite force onto the bead directed in the opposite direction, to the left.  The magnitude of this force depends on a few things.  It is obviously proportional to the total laser power, the more photons you have the more momentum change you get.  The bending angle depends on the index of refraction of the bead, and Q here is a geometric factor that depends on the specifics of what the laser focus looks like and how large the bead is.

## Tiny particles can be treated as dipoles (r << λ)

- Tiny particles can be treated as dipoles (r << λ)

- The particle feels a Lorentz force:

- For a CW laser the Poynting vector is constant:

- Also a force from the light scattered by the particle:

**Notes:**
If the bead is much smaller than the wavelength of light you can think of it as a tiny dipole at the focus of the laser beam.  In this inhomogeneous field the dipole feels a Lorentz force which scales like the gradient of the E-field squared.  There’s also a scattering force that pushes the particle along the direction of laser propagation.

## Large objects require ray optics (r >> λ)

- Large objects require ray optics (r >> λ)

- Integrate over all the rays in the beam (usually a gaussian TEM00 mode)

- Refraction of each ray in the laser beam imparts a momentum change to the sphere.

**Notes:**
For really big objects you can use simple ray-optics to calculate the force.  Each ray is refracted by the particle and the resultant force is given by the integral of the displacement for all the rays.

## Trapping force scales with particle size

- nparticle = 1.57
- nmedium = 1.33
- λn = 800 nm

**Notes:**
If you have a particle that’s in the middle of the two regimes the answer is a little trickier and you need to use a more sophisticated EM model.  Here are some calculations of the force on particles of different size.  For small objects the force scales like r^3 but as you approach lambda it rolls over (which makes sense).

## Our optical trapping apparatus

**Notes:**
This is a picture of the optical trap that I’ve worked with for my time in the Block Lab.  Its based on a commercial Nikon microscope, which you can see here in white, but then we add a whole lot of stuff to it!  The whole apparatus is housed in a temperature controlled room that greatly reduces drift in our experiments.

TALK ABOUT STAGE, SOOUND PROOFING, CLEAN ROOM, VIBRATION CONTROL ...  TECH STUFF!!

## Optics Diagram

**Notes:**
This is an optics diagram of the optical trap I just showed a picture of.  The trapping laser can actually be split into two independently controlled beams with the pol cube here in order to form two optical traps.  I’ll talk more about the two-trap stuff later on in the second half of the talk.  We use acousto-optic devices to steer the trapping beam and hence move the trap around. 

## Acousto-optic deflectors allow the trap to be moved quickly

-  Position accuracy ~ 1 Å
-  Can change position at speeds exceeding 100 kHz

- Christoff Schmidt, Vrije University, Amsterdam

**Notes:**
An acousto-optic deflector is just a Bragg cell in which the incoming light interacts with the acoustic wavefronts of crystal density.  The light diffracts off and by changing the frequency of the piezo driver, you change the diffraction grating spacing and hence the diffraction angle.  Using a pair of these aligned orthogonally we are able to steer the trap around in 2D in the microscope with and accuracy of ~1 angstrom.  The time response of the system is governed by the time it takes the acoustic wave to travel across the laser beam diameter.  In practice, the trap position can be changed at rates exceeding 100 kHz.  Its worth noting that unlike other beam steering technologies, this process is inherently random access and so you can create multiple traps by switching the light back and forth between a series of positions.  In this movie, which I got from Christoff Schmidt, a former postdoc from the Block Lab, you can see that the same laser beam has been used to form a 7x6 grids of 42 optical traps.  Micron-sized beads are held in each one of them and you can tell that this graduate student had way too much time on his hands.

## We measure the angle that the light is bent

- Objective

- Condenser

- The position of the bead relative to the laser focus is proportional to the bending angle.
- We measure this angle by calculating the center of intensity of the laser beam at the back focal plane of the condenser with a position sensitive detector.

- Pacific Silicon Sensors, Inc.

**Notes:**
We can take advantage of the bending of the light to measure the position of the bead relative to the focus.  If the bead is off-center, it bends the light, and this produces a translation of the center of intensity of the laser beam after the condenser lens.  By imaging a position sensitive detector like the one shown here onto the back-focal plane of the microscope condenser lens we can detect these changes..

## Two-dimensional position detection

**Notes:**
Here’s a plot of the response function of our 2D detector to movements in the X and Y directions.  In all we have about a 300-nm radius in which we can detect the position of the bead.

## Control experiment: 1 Ångstrom stability and resolution

- Position (Å)

- Time (s)

**Notes:**
We work very hard to reduce the noise and drift in our experiments.
If we look at the position of a trapped bead the resolution is something like one angstrom.  
Here you can see a trace of the position of a trapped bead moved in 1-angstrom steps!
So, we can detect a 500-nm bead move through 1/5,000th of its diameter.

## Measuring the spring constant

*α* ~ 0.1 pN/nm

**Notes:**
Now I told you we could calculate the forces on the bead, but being experimentalists we’d really like to measure the trap spring constant.  One of the ways we do this is by measuring the frequency spectrum of the Brownian motion of a trapped bead.  You probably recognize the equation for the power spectrum of a massless, damped oscillator; it’s a Lorentzian.  A fit to this equation yields the spring constant

## RNA Polymerase:

**RNA Polymerase:**
**the DNA transcribing machine**
**with a Backspace key**

**Notes:**
Now I’d like to switch gears and talk in more detail about one specific motor called RNA polymerase, specifically a mechanism that it uses to fix spelling mistakes!

## The central dogma of molecular biology

- Crick, *Symp Soc Exp Biol* (1958)

**Notes:**
Very generally, the central dogma of molecular biology, first discussed by Francis Crick in 1958, describes the transfer of genetic information from DNA into functional proteins.  When you cells divide, genomic DNA is replicated forming two copies.  In order to produce proteins, specific sections of DNA are transcribed into RNA which then serves as a template for the sequence of amino acids that are put together during translation to form a protein.

## RNA polymerase (RNAP) carries out transcription

**3 stages of transcription:**
**Initiation**
- RNAP recognizes a start sequence in the DNA called the promoter
- Separates the two strands of DNA  to expose the template strand
- Initiates RNA synthesis using free nucleotides from solution
**RNA Elongation**
- Copies the sequence of DNA following the promoter into a new strand of RNA
**Termination**
- RNAP recognizes a stop sequence in the DNA called a terminator
- Stops elongation and lets go of both the DNA and RNA

**Notes:**
Talk about the 3 stages.  Today I’ll be focusing on the Elongation stage, during which RNAP copies to information from the DNA into the RNA.

## RNA polymerase as an enzyme

**Notes:**
Enzymaticaly speaking, RNAP catalyses the addition of a free base to a growing RNA chain.  Here we have the template strand of the DNA, where some bases are basepaired to the growing RNA chain.  The RNAP stabilizes the new RNA base causing the nreakage of this phosphate bond and the addition of the base to the nascent RNA.  Interestingly RNAP doesn’t use ATP as an energy source.  There’s enough energy stroed int eh phosphate bond on the new nucleotide to power the whole reaction.

## RNA polymerase as a motor!

- E. Coli RNAP:
- moves along the DNA as it transcribes – it’s a motor!
- is small ~10x10x16 nm
- can synthesize up to 1,000,000 bases without letting go
- is driven by the free energy of PPi release, ~50 kJ/mol (80 pN·nm)
- moves at 3 – 7 nm/s
- has a putative single-nucleotide step-size (3.3 Å)
- can produce up to 25 pN of force
- is ~10% energy efficient

- Gelles and Landick, *Cell* (1998)

**Notes:**
On the left here I’ve shown a cartoon of what we think a transcribing RNAP looks like.  I’ll be showing similar cartoons throughout the talk for illustrative purposes.  There are three major players: The polymerase itself shown in green, the DNA being copied in blue, and the nascent RNA in brown.  The polymerase interacts with ~40 bases of DNA, of which about 12 basepairs are broken forming the transcription bubble.  About 8 bases of the new RNA is base-paired with one of the strands of the DNA to form an RNA-DNA hybrid duplex.  As the polymerase adds new bases to the RNA it has to move along the DNA to the new sequence, and hence RNAP is a motor.  It is pretty small, about 10 nm on a side, and can faithfully synthesize up to a million bases without letting go.  It is driven by the free energy of pyrophosphate release after an ribonucleotide triphosphate is added to the RNA chain.  It moves at speeds of 3-7 nm/s with a step size, presumably, of one base along the DNA or 3.4 angstroms.  I’ll show you in a sec that the stall force of RNAP is 25 pN, which makes it only 10% energy efficient, but remember its main job is to faithfully copy the DNA sequence into RNA, NOT to transport cargo.  Motion is really a byproduct of the whole thing.

## Dumbbell optical trap avoids noise & drift arising from motions of the microscope stage

**Notes:**
Fancy resolutioin and noise
Highest precision measurements every made with an optical trap – approaching single-basepair resolution

So here’s what we did.  We used the polarization of the trapping laser beam to split it into two independently steered traps.  We can go even further by video tracking the position of beads stuck to
the surface in real time.  Even though the whole experiment is levitated above the coverslip, motion of the stage in the vertical direction can change the focusing of the laser beams ever so slightly,
Which introduces noise and drift into our measurements.  By tracking the position of a stuck bead with video and using the microscope stage to keep it in a constant position we are able to avoid this artifact
In our experiments.
 In the experiment, one bead is attached to E. coli RNA polymerase
Via a biotin-streptavidin linkage, while the distal end of the DNA is attached to the other bead.  This allows us to perform our experiments levitating above the microscope surface, retaining the
Angstrom-level stability and resolution.  As the polymerase is transcribing the RNA it moves from base-to-base along the DAN template, causing the two beads to get closer together 

## Both the DNA and the optical traps have elastic compliance

**k****trap**

**k****trap**

**k****DNA**

**Notes:**
In order to measure the position of the polymerase along the DNA we have to measure how much DNA is between the two beads.  We know that the optical traps act as springs, but so does the DNA, and so you need to understand the series elastic compliance in order to measure the position of the RNAP.

## DNA acts like an extensible worm-like chain

**Notes:**
In order to think about the actual stiffness of the DNA you need two think in two regimes.  We’ll call the actual length, in basepairs say, the contour length.  When the extension, or end-to-end distance is much less that the contour length then the DNA acts like an entropic spring.  As you pull it apart, the molecule has fewer configurations it can explore and hence you get some stiffness just entropically.  This stiffness can be described in terms of a persistance length, which is roughly the smallest bend you can put in the DNA, and which governs the number of states accessible to the DNA.  As the DNA becomes taught you start to stretch the individual bonds and you get an enthalpic stiffness which can be described by an elastic modulus.

## DNA acts like an extensible worm-like chain

**Notes:**
As you can imagine DNA is a very non-linear spring.  When you stretch it from end-to-end it goes through two regimes.  At first the end-to-end distance is much less that the total length of the DNA (what we call the contour length).  Now, if this were an ideal rubber band you’d get no resultant stiffness, but that’s not quite true for DNA.  When you change the end-to-end distance you reduce the number of confirmations the DNA can adopt at that separation, and you get a stiffness just from the entropic change between the two lengths – we call this the entropic regime.  Right, there are many more conformations available when the DNA can bunch up with a very small end-to-end separation than when its stretched out in a straight line.  It turns out that the stiffness of DNA can be well-described by the so-called worm-like chain in which the the DNA is a polymer with a fixed persistence length.  This is sort-of like a freely-jointed chain in which the DNA is made up of little links that have free-swivels between them, but not exactly.  Once you stretch the DNA to beyond the contour length reach the other elastic regime where you are actually stretching the individual chemical bonds that make up the DNA and we call this the enthalpic regime.

In order to think about the actual stiffness of the DNA you need two think in two regimes.  We’ll call the actual length, in basepairs say, the contour length.  When the extension, or end-to-end distance is much less that the contour length then the DNA acts like an entropic spring.  As you pull it apart, the molecule has fewer configurations it can explore and hence you get some stiffness just entropically.  This stiffness can be described in terms of a persistence length, which is roughly the smallest bend you can put in the DNA, and which governs the number of states accessible to the DNA.  As the DNA becomes taught you start to stretch the individual bonds and you get an enthalpic stiffness which can be described by an elastic modulus.

## DNA is a very non-linear spring

- Contour Length = 894 ± 1 nm
- Persistence Length = 41 ± 2 nm

- Wang et al., *Biophys J* (1997)

**Notes:**
Here you can see that indeed the DNA acts like a very non-linear spring.  The entropic regime here is relatively weak in stiffness compared to this regime here.  Polymer physicists have thought a lot about these various chains and the theory that seems to fit the DNA force vs extension curve best is shown here.  Using this relationship with knowledge of the force in an optical trapping experiment allows you to calculate the contour length of DNA that subtends the two beads, and hence the RNAP position.

## A force clamp allows for longer runs and simplified analysis

- track
- this bead

- move
- this bead

- Servo the position of the **left** bead in order to maintain a constant force (position) of the **right** bead

**Notes:**
REWORD!!

IN addition to the stiffness problem, we’d like to be able to apply constant forces to the polymerase.  One reason is that it simplifies your analysis and makes for a more controlled experiment.  But another point is that if you remember we can only measure the position of the bead in a 300-nm radius.  In a force clamp we have essentially unlimited range.  We do this by servoing the position of the left bead in order to keep the right bead in one place.  This keeps the force constant and allows us to measure really long runs of transcription.  In the movie I’ll show next the polymerase is on the right bead as shown here, but you’ll see the left bead moving as we clamp the force. 

## RNAP motion with the dumbbell assay

- 60x speed
- 1 sec = 1 min

- 1 μm

**Notes:**
Here’s a movie of RNA polymerase motion from our assay sped up 60 times.  Again the polymerase is attached to the bead on the right, and the DNA to the bead on the left.  As the polymerase
Moves on the DNA the tether between then shortens and the two beads move closer together as the force is clamped.  Lets see it again.  What you notice right away is that the motion is not smooth,
but is interrupted by a very long pause in the middle.

## Two states: run and pause

**Time (s)**

**Template Position (bp)**

- 1mM NTPs

**Notes:**
When you look at polymerase motion at higher resolution using the optical trap you notice that the motion is interupted by pauses on many time scales.  This long one is a full 7 minutes long, but, if you zoom in on the this section shown in the box, so can see pauses shorter than one second.  So we can define two phases: run and pause.

## Force has a non-linear effect of run velocity

- Neuman et al., *Cell* (2003)

*******F*****stall******** ****= ****28 ± 2 pN**

- 30

- -30

- 15

- -15

- 0

**Force (pN)**

**Notes:**
With the optical trap you can change the force and study its affect on the run phase.  In this plot negative force is in the direction of motion, i.e. helping the RNAP along, and position force opposes the motion.  As you can see force does very little until you get to about 30 pN at which point the velocity very sharply drops off.  Because the force should really only be affecting things that move we can understand the FV relationship with a theory in which the time it takes you to add a base involves some chemical steps that don’t involve motion (and hence are insensitive to force) and some that do move.  Under zero force the chemical steps are taking all the time and you have to slow down the physical steps allot for them to become important for the overall velocity.

## Pausing is important for RNAP function

**RNA polymerase pauses in order to:**
-  Synchronize transcription and translation
-  Signal a damage site in the template DNA (MfD)
-  Perform termination

**Notes:**
Possibly more interesting than the run phase is the pause phase, because we know that pausing is VERY important for polymerase function.  In fact, RNAP pauses in order to ...

The only problem is that all of the pauses I mentioned happen at specific sequences in the DNA, and we specifically made out DNA so that it didn’t have these sequences.  Because we see pausing essentially constantly we don’t think its DNA damage.

## Pausing occurs on many timescales

- Pause Duration (s)

- Number

- 20 - 500

- Neuman et al., *Cell* (2003)
- Adelman et al., *PNAS* (2002)

**Notes:**
When you histogram the duration of the pauses we see you can see that they are well described by this double exponential distribution, except for this very long population at higher times.  These short pauses have been extensively characterized in two recent papers.  The red shows the expected level from the fit and the actual bin is quite a bit higher.  If you look at a log-log plot of the histogram you can easily see that there is a long tail to this distribution that is not well fit by the double-exponential.

In fact, 5% of these pauses are longer than 20 seconds and belong to a very wide distribution of pause durations. I’ll call pauses that last longer than 20 seconds “long” pauses, and the other ones “short” pauses.  I’ll talk briefly about the short pauses but its really the long pauses that I’ll focus the rest of the talk on.

“A LOT MORE THAN YOU”D EXPECT FROM THE OTHER DISTRIBUTION”...

## Short pauses are everywhere and are unaffected by force

- Neuman et al., *Cell* (2003)

- We don’t know what they are!

**Notes:**
When you look at the short pauses they seem to happen everywhere on the template, with about equal probability.  We also looked at the average pause probability and duration as a fnction of force and they don’t seem to change at all.  So at this point we don’t know what they pauses are.

## Modulating temperature in a single molecule experiment is difficult

- “A peripheral, not the central, portion of one of the aggregates is illuminated by focusing an IR laser beam. If the central portion is illuminated, the aggregate is frequently blown off or the surrounding medium gets boiled.”

- - Kato et al., *PNAS* (1999)

- Potential Problems:
-  Boiling (!)
-  Heats the microscope object, possibly ruining it
-  Local temperature distribution is not well understood

**randomly shaped **
**metal aggregate**

**Notes:**
A standard procedure in biochemistry is to measure the effect of temperature on a biological process because it tells you about the relative contributions of entropy and enthalpy.  People have tried to do this for single molecules, motors in particular, and it turns out to be hard.  In this example Kato et al absorbed randomly shaped metal aggregates (i.e. clumps) onto the microscope slide.  They then heated the metal by shining an IR laser onto it.  But you’ll notice that if the laser got too close to the metal some bad things might happen.  Besides the boiling problems, Heating of the surface also can cause problems with the microscope objective, and which such a random distribution of metal you don’t really understand the temp distribution very well.

## The answer: Use the laser to heat the liquid directly

**Notes:**
The answer, it turns out, is that life is much simpler if you use the laser to locally heat the liquid directly.  Now we weren’t the first people to think of this, and here is a series of references of people who’ve thought about the absorption of a focused laser in a liquid sample, but I think that we were the first to use it with optical traps and biological systems.  At the wavelength that we use,1064 nm, the absorption in water is actually pretty low, but its good enough to get about 4 K per watt of laser power, and I’ll tell you a bit about how we measure the temp.

## Calibrating the temperature with two optical traps

**Notes:**
The trick that really simplifies things is to use two traps.  If you remember the optics diagram I showed earlier we use polarization to create two separate laser traps.  One of the traps is called the heater and we vary to the power in this laser in order to heat up the surrounding fluid.  The other laser trap is made very weak and is used only as a thermometer to measure the local temperature, let me tell you how that works.

## Calibrating the temperature in an optical trap

*η**(T)* 	viscosity of water at temperature T
*α* 	trap stiffness
*r* 	bead radius

**Notes:**
If you remember the power spectrum formula I shows before, it depended on the drag coefficient which is proportional to the fluid viscosity.  Here I’ve written it out more explicitely.  We use the thermometer trap to measure the local viscosity by taking its PS and fitting to this formula.  The temperature difference is most readily seen in the high freq portion of the curve where the Power is inv proportional to the viscosity, and hence roughly proportional to the temperature.  As we go from ~300 mW to ~2 W of power you can see these curves deviate significantly.  Here’s is a plot of the temperature of the local environment as a function of input laser power and we get ~4 K/W.  Because we have a separate thermometer trap we can move it around the heater trap and measure how the temperature propagates as a function of distance.  Here you can see that its fairly constant for a distance of 4 um.

## Run velocity changes with temperature, but short pauses don’t

- ΔH=91±11 pN∙nm
- (55±7 kJ/mol)
- (13±2 kcal/mol)

- ΔH=-11±11 pN∙nm
- (-7±7 kJ/mol)
- (-2±2 kcal/mol)

**Notes:**
Using the optical trap as a heater we were able to study how the pausing and run velocity changed with temperature.  Here you see three example traces taken at three different temperatures.  This plot shows the resolutant velocity versus temperature plot.  You can plot this same data as a Van t’Hoft plot with ln(V) vs 1/temp.  A line fit to this tells you the enthalpy change for the reaction and we did it for both run velocity and the short pauses.  The velocity as we said changes with force and yields an enthalpy of ~90 pN nm which is in the range with other enzymatic reactions.  The pauses on the other hand don’t change at all with temperature.  So once again these short pauses are just a mystery.

## What happens when RNAP makes a mistake?

- Shaevitz et al., *Nature* (2003)

**Notes:**
Obviously, mistakes in RNA chain can lead to mistakes in the amino acid sequence of a protein.
What we wanted to do was find out what RNAP does when it makes a mistake

Animation

## What happens when RNAP makes a mistake?

**incorrect**
**base**

**DNA**

**RNA**

**RNA**
**Polymerase**

- Shaevitz et al., *Nature* (2003)

## Support for a proofreading mechanism

- Error rates *in vitro* : 	10-3- 10-4
- Error rates *in vivo* : 	10-5-10-6

- Erie et al., *Science* (1993)

**Notes:**
If you look in the literature, you can see that RNAP makes a lot more mistakes when run in vitro, than it does in vivo, where there are a lot of accessory factors and other enzymes around.  This has led some people to propose a proofreading mechanism that RNAP might use to edit out mistakes.

## Error rates for different processes

| PROCESS | -ln(error rate) |
| --- | --- |
| Digital Computing | >50 |
| Crystal purity | ~28 |
| IC components | 21 |
| DNA replication (with error correction) |  18-23 |
| Telescope mirror, large | 20 |
| Book typesetting | 15 |
| RNA transcription, in vivo | 12-14 |
| Precision Machining | 12 |
| RNA transcription, in vitro | 7-9 |
| Human typing (without spell checker) | 3-5 |
| Microparticle size dispersion | 2-4 |
| Nanoparticle size dispersion | ~2 |
| Polymer dispersion | 1-2 |

- perfection

- chaos

## Consensus model of RNA proofreading

- The paused RNAP can:
- slide forward again, **leaving the mistake**
- cleave the RNA, **correcting the mistake**

- Erie et al., *Science* (1993)
- Jeon and Agarwal, *PNAS* (1996)
- Thomas et al., *Cell *(1998)

**Notes:**
A consensus model has been emerging over the last decade based on some indirect biochemical evidence on both prokaryotic and eukaryotic polymerases.
Describe action of GreA and GreB proteins as cleavage enhancing factors.
Similar to DNA polymerase proofreading
Mention refs for both e coli and eukaryotic RNA polII

## Why single molecules and optical traps?

**Misincorporation is a low probability, stochastic event**
- Look at single molecule instead of bulk behavior
**Proofreading involves tiny motions of the polymerase relative to DNA**
- Use optical tweezers with sub-nanometer resolution

## Observations about the long pauses

**Time (s)**

**Template Position (bp)**

- 1mM NTPs

## Observations about the long pauses

- Long pauses are sequence independent
- Long pauses happen about once every thousand bases
- RNAP’s *in vitro* error rate is about one mistake per thousand bases

- Are the long pauses associated with misincorporation and proofreading?

**Notes:**
Do this slide quickly. 

One of the first things we noticed was that these long pauses seem to happen at random places along the template, but that they happen about once every thousand bases.
If you recall this is about the same order of magnitude as the error rate I told you for RNA polymerase in vitro.  So we started wondering whether these pauses might
have something to do with the proofreading mechanism. Of course the first thing to look for is whether we could see any backtracking behavior during the pause, which
You remember is a key feature of the proofreading model I presented.

## Are long pauses associated with proofreading?

- Do the long pauses backtrack?
- Are the long pauses associated with misincorporation?
- Do the cleavage factors GreA and GreB relieve long pauses?
- Does the polymerase cleave the RNA at the end of long pauses in the presence of the GreA and GreB?

**Notes:**
Tell them how you answer each question i.e.:

Do they backtrack: Through trace averaging we are able to directly observe a backtracking motion of a few basepairs.
 Long pauses and misincorporation:  We can induce more long pauses by forcing RNAP to make mistakes.
3. Can test for the action of GreA and GreB proteins on the long pauses
4. Can measure error correction in gels

## Long pauses start with a backtrack

- Time (s)

- Position (bp)

**Notes:**
Here I’m showing one of our lowest-noise long pause traces.  Normal elongation is proceeding upward, and you can see that in the beginning of the long pause the polymerase actually moves backwards by about 10 bases before pausing for 30 seconds or so.  Viola, backtracking!  Another interesting feature you’ll notice that at the end of the pause the polymerase doesn’t just recover normal elongation, but instead moves slowly for awhile before resuming transcription at the normal speed.

## Backtracking accompanies long pauses

*n=56*

**backtracking**
**(4.7 ****±**** 0.8 bp)**

**slow**
**recovery**

- Time (s)

- Position (bp)

**elongation**

**elongation**

**Notes:**
Point out time scales and resolution – w/averaging resolution ~ 1 bp

In order to reduce the noise in individual traces we decided to average all the long pauses together, lining them up along their front and back edges.  This process reduces noise in individual traces, and also pulls out features that are common to all traces so that one can study the average behavior.  You’ll notice again that the beginning of the pause is characterized by a ~5 bp backtracking that takes on the order of a few seconds, and that the recovery phase is slow relative to the normal elongation rate. You can understand the slow recovery in light of the model I described earlier.  In the absence of the Gre proteins the polymerase is not able to cleave the RNA that is presumably blocking the nucleotide entry channel.  Instead it has to slide back and forth along the template DNA until it happens to find its way back to the place it started from where it can resume elongation.

## Short pauses don’t backtrack

- Time (s)

- Position (bp)

**Notes:**
Here I’m showing a blow up of one of the shorter pauses to show you that they don’t backtrack.  This is in agreement with an earlier paper from our lab that measured the affect of force on the short pauses.

## Backtracking pauses are force dependent

- Force (pN)

- Pauses per kb

- Characteristic
- Distance
- 4 ± 1 bp
- (4.7 ± 0.8 bp)

- Unloaded Rate
- 1.2 × 10-4

**Notes:**
As another check to ensure that these pauses really do involve backtracking, we looked at the effect of force.  Because backtracking involves a motion along the DNA
The tension in the DNA supplied by the optical trap should effect these pauses.  If you pull backwards it makes backtracking easier, whereas a forward force makes backtracking
Harder.  This is just what we see with a decrease in the number of pauses per kb as we go from high backward load to high forward.  This went a long way to assuring us that these were really backtracking pauses.  The exponential fit gives a distance parameter of 4 bp, and the long pauses rate in the absence of force is about 1 per 10,000 bases.

## Evidence that long pauses are associated with proofreading

- Do the long pauses backtrack?
- YES!
- Are the long pauses associated with misincorporation?
- Do the cleavage factors GreA and GreB relieve long pauses?
- Does the polymerase cleave the RNA at the end of long pauses in the presence of the GreA and GreB?

## Inosine looks like a “bad” guanine

- RNAP selectively misincorporates an inosine at sites coding for guanine

**Prediction: **Addition of ITP should increase the number of long pauses.

- Inosine

- Guanine

- Thomas et al., *Cell *(1998)

**Notes:**
Inosine is a purine that looks just like guanine but without this amine group.  It has been shown previously that inosine gets selectively misincorporated by RNA polymerase at sites that code for guanine.

## Incorporation of ITP increases the number and duration of the long pauses

- Time (s)

- Template Position (bp)

- 1mM NTPs + 200 μM ITP

- 1mM NTPs

- Inosine

- Guanine

**Notes:**
Here are two representative traces, in red is the same trace I showed earlier with 1mM ntps, and in black I’ve added a contaminating amount of ITP.  The ITP appears to cause the polymerase to pause more frequently for longer periods of time.

## Incorporation of ITP increases the number and duration of the long pauses

- 1 mM NTPs

- + 200 μM ITP

- Pauses per kb

- Mean duration (s)

- 1 mM NTPs

- + 200 μM ITP

- Inosine

- Guanine

**Notes:**
We can quantify change this by measuring the average number of long pauses per kb, and the mean duration of these pauses.  As you can see both the frequency and duration of the pauses increased when we added 200 uM ITP.

## Backtracking occurs at the beginning of ITP-induced pauses

- 1mM NTPs

*n=56*

- 1mM NTPs + 200 uM ITP

*n=26*

- Time (s)

- Position (bp)

- Position (bp)

- Inosine

- Guanine

**Notes:**
When you look at the long pause average with ITP (shown in blue), you see the same behavior as we saw without ITP.  There is a backtracking event at the beginning of the pause, and a slow recovery at the end.

## Evidence that long pauses are associated with proofreading

- Do the long pauses backtrack?
- YES!
- Are the long pauses associated with misincorporation?
- YES!
- Do the cleavage factors GreA and GreB relieve long pauses?
- Does the polymerase cleave the RNA at the end of long pauses in the presence of the GreA and GreB?

## GreA and GreB stimulate RNA cleavage

- RNAP has an intrinsic cleavage ability at the polymerization active site that is stimulated by Gre proteins or high pH
-  Functional analogs of GreA and GreB have been found in over 60 organisms, including TFIIS in eukaryotes

**Prediction: **Addition of GreA and GreB should reduce the duration, but not number of long pauses

**GreB**

*Opalka et al., Cell 2003*

**DNA**

**RNA**

**RNAP**

**Notes:**
As I said before the proteins GreA and GreB stimulate polymerases intrinsic ability to cleavage the RNA from the backtracked state.  These proteins are quite universal, with functional analogs in
Over 60 organisms, including humans!  A cryo-EM structure of E. coli bound to GreB has been solved by the Darst lab and you can see here that the protein protrudes into that channel, similar to the way I’ve cartooned it on the top.

EXPLAIN GRE ACTION BETTER

## Cleavage factors reduce the duration of long pauses

- 1 mM NTPs,
- 200 μM ITP

- + 2 μM GreA,
- 1 μM GreB

- Duration (s)

- Pauses per kb

- Inosine

**DNA**

**RNA**

**RNAP**

**Notes:**
Here I’m comparing the pause frequency and duration with ITP with and without GreA and GreB.  As you can see the number of pauses per kilobase remained roughly the same, while the duration of these pauses changed dramatically.  So, this seems to fit in with our model quite well in that the Gre proteins seem to be able to relieve polymerase from these pauses.

## Evidence that long pauses are associated with proofreading

- Do the long pauses backtrack?
**YES!**
- Are the long pauses associated with misincorporation?
**YES!**
- Do the cleavage factors GreA and GreB relieve long pauses?
**YES!**
- Does the polymerase cleave the RNA at the end of long pauses in the presence of the GreA and GreB?

## GreA and GreB remove inosine from the transcript

- radiolabeled
- ITP

- + GreA

- + GreB

- full-length
- transcript

- cleavage
- products

- ~log (RNA Transcript Size)

- single nucleotides

**Notes:**
This is a very recent experiment in which we were able to measure the amount of inosine incorporation into the RNA transcript with and without the Gre proteins.  We ran RNAP in the presence of radiolabeled ITP, so that all the bands you see in the gel things that have inosine in them.  At the top we have the full-length transcript, and at the bottom we have the small cleavage products that the Gre proteins make when they help the RNAP cleave.  You can see that without the Gre proteins, shown here on the left, a lot of inosine gets incorporated into the transcript and very little is found in the cleavage products.  With the Gre proteins, we see a lighter band for the transcript and the cleavage products are much darker.  We can quantify these results and you can see that GreA is able to remove 46% of the inosine, and GreB an impressive 96%!  So it does look like RNAP is able to proofread the inosine out of the transcript and that this requires the Gre proteins.

## Recovery of motion is abrupt upon cleavage

- Time (s)

- NTPs + ITP

- NTPS + ITP + GreA,GreB

*n=22*

*n=26*

- Position (bp)

- Position (bp)

- sliding

- cleavage

- Inosine

**DNA**

**RNA**

**RNAP**

**Notes:**
As you can see in the presence of ITP, and the Gre proteins this slow recovery phase disappeared and instead the recovery is abrupt, with the polymerase resuming normal transcription right out of the pause.  We think that this is good evidence that the Gre proteins are actually stimulating RNA cleavage, and that without them the slow recovery happens because of the lack of cleavage ability.  

## The model of a molecular backspace key

-  RNAP backtracks by ~5 bp during long pauses.
- These pauses occur about once every thousand bases, and are likely due to misincorporation.
- Without GreA and GreB, the polymerase escapes from pause via slow forward sliding – **does not remove the error.**
- With GreA and GreB, the polymerase escapes from pause by cleaving the newest RNA – **removes the error.**

**Notes:**
Ok.  It seems that we’ve been able to just about answer all of these questions.  TO recap:

RNAP pauses for greater than 20 seconds about once every thousand bases, likely due to the misincorporation of a transciptional mistake.
The polymerase backtracks by about 5 bp at the beginning of these pauses.
Without GreA and GreB the recovery from these pauses is slow due a diffusive search along the DNA template.
With the Gre proteins, the polymerase is able to cleavage the protruding RNA from the backtracked state, correcting the mistake.

## Biology presents a window into the nanoworld

**Notes:**
Bring back to forces, and what we still need to learn about biology in order to get a handle on nano

## Conclusions

- Molecular motors are fascinating machines that are important for both Biology and Nanotechnology
- Single molecule techniques offer a lot to these studies
- Optical traps are particularly useful for studying molecular motors: displacements, force, temperature
- RNA polymerase is a VERY sophisticated enzyme able to correct errors

## Acknowledgments

- Bob Landick, U. Wisc.

**Steven Block**
- Elio Abbondanzieri
- Keir Neuman
- Charles Asbury
- Matt Lang
- Tom Perkins
- Megan Valentine

- Michael Woodside
- Ravi Dalal
- Adrian Fehr
- Polly Fordyce
- Will Greenleaf
- Nicholas Guydosh
- Kristina Herbert

- Will Parks
- Viviana Risca
- Becky Wong

- http://www.stanford.edu/group/blocklab

## Slide 76

## Motors are everywhere in the cell

**Notes:**
This is a drawing of a typical cell and I put it up just so that I could point out all the places where motion takes place in the cell.  The cell has developed motors that can:

Transport cargo from one end of the cell to the other

Copy, break, repair and move DNA

. . .

## Nanobotsto the rescue!

- Nanobotsto the rescue!

- sources:  *Scientific American*, Apr ’96
- & Foresight online Nanomedicine Art Gallery

## Popular Science, March 1989

**Popular Science**, March 1989
- work of R. Muller, UC Berkeley

## Optical traps are tools used to study individual motor proteins

## More temp figs

## The DNA polymerase proofreading mechanism

- When a mismatched base is incorporated, the polymerase stalls
- The 3’ end of the nascent strand is moved to a second active site
- An exonuclease activity removes the mismatched base
- Polymerization resumes after editing

*http://ww2.mcgill.ca/biology/*
*undergra/c200a/sec2-4.htm*

**Is something similar happening in RNA polymerase?**

## Short pause average (durations < 5 seconds)

## GreA and GreB promote cleavage of different lengths of RNA

- Time (s)

- Position (bp)

- GreA

- GreB

*n=8*

*n=3*

- Position (bp)

**GreB**

**DNA**

**RNA**

**RNAP**

## GreA and GreB reduce the number of long pauses

- Pauses per kb

- Duration (s)

- 1 mM NTP

- +2 μM GreA

- +1 μM GreB

**GreB**

**DNA**

**RNA**

**RNAP**

**Notes:**
When we added GreA and GreB to the buffer we found that the number of long pauses decreased substantially, while the duration appeared to decrease a bit.  Now, at this point we need to stop and think about what we mean by pause duration and frequency.  The Gre proteins are supposed to induce RNA cleavage, which would presumably reduce the lifetime of a backtracking pause.  But since we only score pauses longer than 20 seconds, pauses that whose duration gets reduced to below this limit don’t get scored.  So what we see as a reduction in the number of pauses is probably due to a reduction in the pause durations!  In order to verify this we looked at the effect of GreA and GreB with ITP in the buffer.  Because the ITP pauses are normally so long, shortening them a bit wouldn’t drop their duration below the 20s threshold and we would still be able to count them.

## GreB edits out XX% of the mistakes

- Length of transcribed region:	262
- Number of G sites:	66
- Hot I conc:	0.15 uM
- Cold G conc:	0.50 uM
- I/(I+G) ratio:	23%
- GreB edits out 96%
- GreA edits out 46%
- Denaturing Sequencing gel
- 10% Polyacrylimide
- RXns ran out long, ~3 hours

## Force tilts the energy landscape

**elongation**
**state**

**pause**
**state**

- free
- energy

- reaction
- coordinate

- position

**F**

***k******p***

***k******-p***

************

*******2*

- Two parameters:
- Pause Frequency
- (pauses per kb)
-  kp
- Pause Lifetime
- (seconds)
- = 1 / k-p

**Notes:**
Mathematically, the forward and backward rates vary exponentially with the force, and depend on the dot product between the force and the vector pointing from the initial state to the transition state as shown here.