1. This Week’s Schedule smFRET

2. Single molecule FRET R↓ E↑ R↑ E↓ Reminder about FRET

3. sm FRET data

4. Total Internal Reflection (TIR) Microscopy
Imaging (Single Molecules) with very good S/N
(at the cost of seeing only a thin section very near the surface)
Total Internal Reflection (TIR) Microscopy
Free dyes don’t contribute background
TIR- (q > qc) Exponential decay
dp=(l/4p)[n12sin2i) - n22]-1/2
For glass (n=1.5), water (n=1.33):
TIR angle = >57° Penetration depth = dp = 58 nm
With dp = 58 nm , can excite sample and not much background.

5. Experimental Setup: Imaging Single Molecules
Total Internal Reflection Microscopy
Prism TIR (Wide-field)
Objective TIR (Wide-field)
Laser
Objective (NA=1.49)
Filter
Dichroic
Sample
CCD
Detector
Lens
Excite donor-only
(or can use two wavelength, i.e. ALEX)
Objective: + somewhat higher collection efficiency,
(-) autofluorescence of objective

6. Lots of approximationsqA __ qD
In fact IDID/qD : IAIA/qA
Often, though not always, use FRET to say that A is closer than B
Assuming that k2 doesn’t change too much.

7. Fold up to make sure not recognized as double-stranded breaks.
smFRET on Telomeric DNA Folded [G-quadruplex: 6- telomeric sequence (TTAGGG)4]  Unfolded
Telomeres: single-stranded ends of DNA.
Fold up to make sure not recognized as double-stranded breaks.
G-quadruplex: at least 3G, repeated 4 times
Salt titration is donor-only
G-quadruplex “hides” the double-stranded break of DNA

8. G-Quadruplex DNA
Salt stabilizes G-quadruplex
Excite 1 wavelength,
look at D-only and A-only.
At given [salt] will have stochastic (random) amount of Energy Transfer

9. HMM Analysis How fast transitions occur
Determine the average transition state between two conformations.
Assume Markov state where probability per unit time depends only on current state the lifetime of each state is exponential.
Process is hidden because we don’t observe FRET state, but rather the fluorescence

10. What is Hidden Markov Method (HMM)?
Hidden Markov Methods (HMM) –powerful statistical data analysis methods initially developed for single ion channel recordings – but recently extended to FRET on DNA, to analyze motor protein steps sizes – particularly in noisy traces.
What is a Markov method?
the transition rates between the states are independent of time.
Why is it called Hidden?
Often times states have the same current, and hence are hidden.
Also, can be “lost” in noise.
What is it good for?
Can derive signals where it appears to be only noise!
Lec 17: 4/2010, Physics 498:

11. Hidden Markov Models
An impressive feature of combining Hidden Markov & Maximum Likelihood models is the ability to extract signal from noise. Indeed, they are often called Hidden Markov Methods because the observable (ionic current, or position in the case of molecular motors) is often hidden in the noise. a. b. c.
Use of Hidden Markov Methods to analyze single ion channel recordings. a) Ideal current vs. time, showing ion channel transitions with two different conductivities and forward and backward rate constants of 0.3 and 0.1. B) Data of (a) added to white noise such that noise level = signal level. C) Extraction of kinetic parameters using HMM from noisy data in b, showing kinetic constants can be recovered. (Venkataramanan et al., IEEE Transactions, 1998, Part I.)

12. The End