I

Single-molecule Nanoscopy of RNA

Polymerase II Transcription at a Single

Gene in Live Cells

by

Ankun Dong

Submitted in partial fulfillment of the requirements

for the Degree of Doctor of Philosophy in the

Department of Physics at Brown University

Providence, Rhode Island

May 2017

II

@Copyright 2017 by Ankun Dong

III

This dissertation by Ankun Dong is accepted in its present form

by the Department of Physics as satisfying the

dissertation requirement for the degree of Doctor of Philosophy.

Date_____________ _________________________________

Professor Xinsheng Sean Ling, Advisor

Recommended to the Graduate Council

Date_____________ _________________________________

Professor J. Michael Kosterlitz, Reader

Date_____________ _________________________________

Professor Gerald J.Diebold, Reader

Approved by the Graduate Council

Date_____________ _________________________________

Andrew G. Campbell

Dean of the Graduate School

IV

Acknowledgements

Life is a journey, the six-year PhD study will definitely be an extremely valuable

experience for me.

Firstly, I would like to thank Dr. Alexandros Pertsinidis for providing the

opportunity to conduct the cutting edge research at Memorial Sloan Kettering Cancer

Center. I am grateful for the financial support and academic guidance. I also thank

him for initiating me into the cult of single molecule imaging, and for answering my

questions - usually in 10 seconds or less. I admire his tireless pursuit of knowledge

and full commitment in science even at the expense of sleep and repast.

Secondly, I am forever indebted to my advisor at Brown University Professor

Xinsheng Sean Ling for his professional advice and valuable suggestions. His

enthusiasm for science, how he helped other people and how he loved his family, have

made huge impact on me and set me a good example. I still remember his

encouraging and incentive conversations with me in his office.

Thirdly, I thank Professor John Michael Kosterlitz for taking interests in my

research and listening to my presentation right after his medical procedure on Mar,

27th

, 2017. I thank Prof Gerald. J. Diebold for inviting me to give a talk in the

Department of Chemistry as a practice of my thesis defense. It is a great honor for

V

me to have them on my defense committees. I thank them for reading my Ph.D.

dissertation and providing valuable advices.

Then I thank all my friends around for their companionship, the sharing and

mental support.

Last but not least, I am especially grateful to my parents. They supported me

when I was under a mountain (either literally or figuratively) and shared with me all

the happy moments.

VI

Abstract of “Single-molecule Nanoscopy of RNA Polymerase II Transcription at a

Single Gene in Live Cells” by Ankun Dong, Ph.D., Brown University, May 2017

Single-molecule approaches enable us to follow the movement, interactions and

conformational dynamics of individual molecules in real-time, thus providing novel

insights in complex biochemical systems that have remained masked in the ensemble

averaging of traditional bulk biochemical approaches. Recent advances in

single-molecule tracking, fluorescence spectroscopy and subdiffraction optical

microscopy have unveiled unprecedented views of molecular processes in live cells.

To extract quantitative information from individual molecules in the high background

noise, these techniques are often based on in vitro reconstituted systems with either

surface-immobilized or freely-diffusing biomolecules in dilute conditions. Live cell,

real-time imaging, tracking and counting biomolecules in their native, crowded

intracellular environment currently remain an extremely challenging task.

Based on the numerical simulation, I built the real time tracking 3D STED nanoscopy

enabling single molecule detection. With the new technique, I perform

oligo-nucleotide hybridization detection experiment in vitro as well as study the

mechanism of RNA Polymerase II transcription in living cells at single molecule level.

Basically, I reveal the accumulation of Pol II molecules and quantified nearly 10 Pol

II molecules in the cluster during active transcription at a tagged mini-gene in the

native environment. In addition, mini-gene transcription does not involve transient Pol

VII

II clustering at pre-initiation by kinetic analysis enabled by target-locking over

multiple transcription rounds, arguing against the persistence of accumulated Pol IIs

in the absence of transcription or extensive Pol II recycling-related spatial

compartmentalization. What’s more, I find that single Pol II molecules are

stochastically recruited from the nucleoplasm, enter into productive elongation and

are predominantly released instead of recycled upon termination. The results set up a

quantitative framework for investigating Pol II dynamics at single genes at single

molecule level, and also demonstrate that the potential and powerful use of real time

tracking 3D STED nanoscopy in elucidating the complex biological mechanisms in

vivo.

VIII

List of Acronyms

FWHM Full Width with Half Maximum

STED Stimulated Emission Depletion

TIR Total Internal Reflection

SIM Structured Illumination Microscopy

STORM Stochastic Optical Reconstruction Microscopy

NSOM Near-field Scanning Optical Microscopy

Epi Epifluorescence

PALM Photoactivated Localization Microscopy

pcPALM Pair-correlation PALM

GFP Green Fluorescent Protein

mRNA message RNA

Pol II polymerase II

NTP Nucleoside triphosphate

TBP TATA-binding protein

TFB transcription factor B

TFE Transcription factor E

TFIIA Transcription factor II A

TFIIB Transcription factor IIB

TFIID Transcription factor IID

TFIIE Transcription factor IIE

IX

TFIIF Transcription factor IIF

TFIIH Transcription factor IIH

CTD C-terminal domain

BrUTP bromouridine triphosphate

CHO Chinese hamster ovary

TMR Tetramethylrhodamine

RPB1 RNA polymerase II large subunit

NSF N-ethylmaleimide sensitive fusion proteins

SNAP Soluble NSF Attachment Protein

SiR Silicon Rhodamine

3D 3 dimensional

PSF Point Spread Function

PBS Polarized Beam Splitter

SLM Spatial Light Modulator

LCOS-SLM Liquid Crystal on Silicon-Spatial Light Modulator

APD Avalanche photodiode

CCD charge coupled device

PMT Photomultiplier

BNC Bayonet Neill–Concelman

PEG Poly-ethylene-glycol

CW Continuous Wave

OPO Optical Parametric Oscillator

X

SNR Signal to Noise Ratio

BSA Bovine serum albumin

FRET Förster resonance energy transfer

ROI Region of Interest

KD Dissociation constant

CMV-IE Cytomegalovirus immediate-early

BFP Blue Fluorescent Protein

FCS Fluorescence correlation spectroscopy

PID Proportional–integral–derivative

SD Standard Deviation

fps Frame per second

DMSO Dimethyl sulfoxide

Contents

1. Introduction 1

1.1 Super Resolution Fluorescent microscope in life science 2

1.1.1 Introduction 2

1.1.2 Near field 3

1.1.3 TIR 5

1.1.4 Confocal 6

1.1.5 Two Photon Excitation 8

1.1.6 SIM 11

1.1.7 STED 13

1.1.8 TORM/PALM 15

1.1.9 Summary 16

1.2 Gene Expression 18

1.2.1 Mechanism: Transcription, RNA processing, Non-coding RNA

maturation, RNA export, Translation, Folding, Translocation, Protein

transport

18

1.2.2 Transcription of Eukaryotic Protein-Coding Genes: Initiation,

Promoter escape, Elon1gation, Termination

19

1.2.3 RNA Polymerase II in transcription 19

1.2.3.1 RNA Polymerase II and initiation cofactors 20

1.2.3.2 RNA Polymerase II and elongation cofactors 21

1.2.4 Polymerase II Clustering 21

2. Simulation of single molecule detection using STED 30

2.1 Numerical Simulation Theory 31

2.2 Excitation beam 32

2.3 Vortex doughnut 35

2.4 Z doughnut 36

2.4.1 Central intensity with different phase modulation 36

2.4.2 Z doughnut with the optimal phase modulation 38

2.5 Emission of a dipole 38

2.6 Resolution with different combinations of xy and z doughnut 40

3. Setup 42

3.1 Schematic 43

3.2 Setup components(excitation lasers ,STED lasers, Objectives, Filters,

Detectors, piezo Stage, vortex plate, SLM)

43

3.3 Align the setup 45

3.3.1 Coarse alignment based on the reflected images on the CCD camera 45

3.3.2 Calibrate the beams using gold nanoparticle (PMT used) 46

3.3.2.1 xz scanning 46

3.3.2.2 xy scanning 47

3.3.3 Quarter wave plate adjustment 48

3.3.4 Optimal collar position for Silicon oil and regular oil objective 48

3.3.5 Optimize z doughnut by changing the collimation and phase

modulation

49

3.3.6 Overlap all the beams 50

3.4 Resolution vs power 50

3.4.1 Immobile molecules sample preparation 50

3.4.2 Later resolution vs STED power 51

3.4.3 Axial resolution vs STED power 53

3.5 Time gating 55

3.5.1 Take data with APD detector and Picoharp (T2 mode and T3 mode) 55

3.5.2 Lifetime of the fluorescence 56

3.5.3 STED changes the lifetime 57

3.5.4 Time gating improves the resolution 58

3.6 CW laser vs pulsed mode laser 59

3.6.1 Pulsed mode properties 59

3.6.2 Optimize the phase to achieve the highest depletion 60

3.6.3 Compare the two modes 60

4. STED improves SNR and enable single molecule

detection in vivo

61

4.1 STED principle 62

4.2 The reversible depletion of STED on single fluorophore 63

4.3. The general Background properties 64

4.3.1 Closed system 64

4.3.2 Open system 65

4.4 The STED depletion in the Atto647N solution at different concentration 65

4.4.1 Background and noise from the solution and surface 65

4.4.2 Background and noise with different excitation power 66

4.4.3 Background and noise with different excitation power Background

and noise with and without STED of the Atto647N solution at different

concentration

67

4.5 Detection of immobile single molecules at elevated concentrations 72

4.5.1 Experiment design 72

4.5.2 Cy3-Atto647N duplex preparation 73

4.5.3 Map the yellow channel and red channel 73

4.5.4 Scan the regions with yellow, red and red with sted at elevated

concentrations (100nM, 300nM, 600nM)

74

4.5.5 Construct and compare the images 75

4.5.6 Quantify the SNR with and without STED (The distribution of the

signal from the Cy3 colocalized regions and random regions)

77

4.6 DNA hybridization on off binding detection 78

4.6.1 Experiment design 78

4.6.2 The on off rate optimization 79

4.6.2.1 Kd of different oligos (10nt, 9nt, 8nt) 79

4.6.2.2 Adjust the Kd with NaCl at different concentrations 81

4.6.3 Map the yellow channel and red channel 81

4.6.4 Interlace the yellow laser and red laser 81

4.6.5 Take time traces with the interlaced yellow and red laser w/wo STED 82

4.6.6 Data analysis 82

4.6.6.1 Separate the direct red excitation and FRET traces 82

4.6.6.2 SNR of the direct excitation traces with/without STED 83

5. Single molecule detection for RNA Polymerase II

transcription

85

5.1 Mini gene 86

5.2 Sample preparation (Rpb1 and Rpb9) 87

5.3 Background and noise in living Rpb9 cells 88

5.3.1 FCS experiment 88

5.3.2 Background and noise reduction with STED 88

5.4 Pol II accumulates at sites of active nascent transcription(wide field

imaging)

91

5.5 Studying the Pol II using STED setup (methods) 92

5.5.1 STED alignment 92

5.5.2 Quad-view camera registration 93

5.5.3 GFP tracking 94

5.5.4 Data analysis (extracting the time traces) 96

5.6 Colocalization of Pol II and mRNA 96

5.6.1 Check the Colocalization using the initial images with the

background subtracted from the quad-view camera

96

5.6.2 Check the Colocalization by direct 3D scanning images 98

5.6.2.1 Find the GFP spots and roughly center the spots 98

5.6.2.2 3D real time imaging using FPGA 98

5.7 Bleaching traces for counting Pol II numbers 100

5.7.1 Calibrate the step size of the bleaching time traces using less stained

sample

101

5.7.2 Count Pol II numbers using fully stained sample 103

5.7.3 Compare the bleaching traces with\without STED (2 fold SNR

improvement)

104

5.8 Quantification of Pol II at transcription sites 106

5.8.1 The initial peak of the traces at transcription sites and 536nm away 107

5.8.2 The decay time of the traces at transcription sites and 536nm away 108

5.8.3 The images of the Polymerase 0.536um away from transcription sites 109

5.8.4 The actual Pol II numbers involved in transcription 111

5.9 Size of the Pol II spots at transcription sites 112

5.9.1 Measure the sizes of the initial images with the background

subtracted from the quad-view camera referring to nanoparticle size

calibration

113

5.9.1.1 Calibrate the image sizes on the quad-view camera using

100,200,500nm nanoparticles without z tracking

114

5.9.1.2 Calibrate the image sizes on the quad-view camera using

100,200,500nm nanoparticles with z tracking

117

5.9.1.3 Compare the sizes of the Pol II images with that of the

nanoparticles

119

5.9.2 Check the sizes of the initial images with the background subtracted

from the quad-view camera with xy doughnut of different power

122

5.9.2.1 Resolution, Signal remaining with different power xy doughnut 123

5.9.2.2 Fit the size with calibrated data 123

5.9.3 Measure the Pol II sizes by 3D scanning 125

5.10 Dynamics of the Pol II transcription cycle at the CMV mini-gene 126

5.10.1 Pol II recovery experiment 126

5.10.1.1Bleaching the Pol II and retake the bleaching traces after certain

minutes

126

5.10.1.2 10-minute recovery time trace with low duty cycle excitation 128

5.10.1.3 3D scanning images before and after bleaching as well as after

10-minute recovery

130

5.10.2 SiR-Rpb1 FRAP experiments from wide field imaging 131

5.10.2.1 Take bleaching traces with time information recorded from

many cells using high excitation power

132

5.10.2.2 Take the 8-minute trace with low excitation power from each

cells

133

5.10.2.3 Data analysis and Conclusion 134

Bibliography 135

1

Chapter One

Introduction

2

1. Introduction

1.1 Super Resolution Fluorescent microscope in life science

1.1.1 Introduction

The 2014 Nobel Prize in Chemistry was awarded to Eric Betzig, W.E Moerner

and Stefan Hell for the development of super-resolved fluorescence microscopy.

Fluorescence microscopy has become an essential and powerful tool in biology. It

is widely used in imaging protein expression, localization, and activity in living cells.

Due to the diffraction limit, the resolution of conventional microscopy is

characterized by the excitation wavelength, first stated by Ernst Abbe in 1873 [1]. The

resolution of the microscopy is usually denoted by the full width at half

maximum (FWHM) of the point spread function, and a typical wide field microscope

with a high numerical aperture [2] reaches a resolution of roughly half the excitation

wavelength. This makes sharp point-like objects to appear blurry under the

microscope and many fine cellular structures unresolvable.

In biological systems, people often need to deal with densely packed, brightly

labeled diffraction limited structures. Over the past several decades, people have

developed several super-resolution techniques for breaking the diffraction barrier. In

this chapter, I will briefly summarize near-field super-resolution microscopy. TIR,

Confocal, Two Photon excitation, SIM, STED and STORM microscopy which are

now most widely used have great impact on biological research. I am not going into

particularly some other microscopy that are developed from these ones.

3

1.1.2 Near field

Near-field scanning optical microscopy (NSOM), by its name, breaks the far

field resolution limit by taking advantage of the properties of evanescent waves. As

the diffraction limit is for the far field description, in the evanescent region, which is

near the surface of the object, the intensities drop off exponentially with distance from

the object [3].

Figure 1.1: Diagram illustrating near field optics

To realize this, the detector is placed very close to the sample, and actually the

distance between the detector and the specimen need to be much smaller than the

excitation wavelength λ. In this way, the resolution of the image is limited by the size

of the aperture instead of the wavelength of the excitation beam. NSOM can be easily

used to study different properties, such as refractive index, chemical structure and

local stress. Dynamic properties can also be studied at a sub-wavelength scale. In

particular, lateral resolution of 20 nm and vertical resolution of 2–5 nm have been

demonstrated. Step and terrace structure has been observed in the 1mm by 1 mm area

on the cleaved surface of KCl–KBr solid-solution single crystal using NSOM. In the

experiment, a small sphere probe of 500 nm diameter is used [4].

4

Figure 1.2: The magnified SNOM image of the small area in a river pattern existing on the cleaved surface of KCl–KBr solid-solution single crystal [4].

As the detector is very close to the sample, NSOM has some limitations: The

working distance need be very low, so this technique could only work for surface

study. It is not conducive for studying soft materials. What‟s more, long scan time is

needed for large sample areas for high resolution imaging.

5

1.1.3 TIR

In molecular biology, in the case of studying a large

number of molecular events in cellular surfaces such

as cell adhesion, the surfaces attached molecules as well

as much more non-bound molecules in the medium will

be excited using conventional microscopy. The

non-bound molecules will lead to very high background

and make it changeling to observe the molecules bound

to the surface. A TIRFM uses an evanescent wave to

selectively illuminate and excite fluorophores in a

restricted region close to the glass-water interface,

making it a perfect method for the above surface

experiment.

Figure 1.4: Diagram showing the internal totally reflection

According to Snell‟s law [5],

where n1,n2 are the refractive index of the glass and water.

When is 90 degree,

θ1

θ2

n1

n2

Evanescent wave

range

Figure 1.3: Human skin fibroblasts labeled with dil and viewed at (a) TIRF, (b) Epi fluorescence of the same field. (c) Phase contrast of the same field [6].

6

= arcsin(n2/n1)

If , the incident beam will be totally reflected at the glass-water

interface. The electromagnetic field decays exponentially from the glass-water

interface, the penetration depth of nearly 100 nm into the medium is under the

diffraction limit.

Comparison of the labeled human skin fibroblasts images from TIRF, Epic

fluoresce and Phase contrast in Figure 1.3 [6] demonstrate that for TIRF only the

fluorophores near the surface would be excited, thus the TIRFM enables a selective

visualization of surface regions and have potential applications, including

visualization of the membrane and underlying cytoplasmic structures at cell-substrate

contacts, mapping of membrane topography, and visualization of reversibly bound

fluorescent ligands at membrane receptors.

1.1.4 Confocal

Figure 1.5: Confocal point sensor principle from Minsky's patent [7]

7

Confocal microscopy aims to overcome the limitations of traditional

wide-field fluorescence microscopes. In wide field microscopy, a large part of the

sample is illuminated at the same time and all the fluorescent light is collected.

Confocal microscopy increases the resolution and contrast of the images by adding

a spatial pinhole at the confocal plane of the lens before the detector to cut the

out-of-focus light. The first confocal scanning microscope was built by Marvin

Minsky in 1955, as seen in Figure 1.5 [7]. It enables the reconstruction of

three-dimensional structures from the obtained images by optical sectioning for a

thick object. Confocal laser scanning microscopes utilize multiple mirrors to scan the

laser across the sample or move the sample while keeping the beam. This technique is

widely used in life sciences, semiconductor inspection and materials science.

In Figure 1.6, restorations of confocal and wide-field images of a Drosophila

melanogaster embryo are compared. The confocal images show high resolution and

the images look more similar to the raw data [8].

8

Figure 1.6: Restorations of confocal and wide-field images of a Drosophila melanogaster embryo. Top two rows: XY and XZ sections of the wide-field data and restorations. Bottom two rows: XY and XZ sections of the confocal data and restorations. From left to right: Raw data, result of the MAPGG restoration, result of the MAPPR restoration [8].

1.1.5 Two Photon Excitation

Two photon excited fluorescence microscopy [9] is similar to confocal laser

scanning microscopy. Differing from the traditional fluorescence microscopy in

which the excitation wavelength is shorter than the emission wavelength, two-photon

excitation microscopy uses near-infrared excitation light which can also excite

fluorescent dyes. For each excitation, two photons of infrared light will be absorbed,

illustrated by the Jablonski diagram in Figure 1.7 (a). The possibility of absorbing two

photons will be much lower where is far from the focal plane, so the background

9

signal is strongly suppressed. The spatial confinement of signal generation with

nonlinear excitation is demonstrated in Figure 1.7 (b). And the actual excitation

volume will be smaller, resulting in an increased penetration depth. A typical two

photon microscopy would be schemed as Figure 1.7 (c) [10].

Figure 1.7: (a) Jablonski diagram, illustrating two-photon absorption (2PA), second-harmonic generation (SHG) and coherent anti-Stokes Raman scattering (CARS). Note that in second-harmonic generation and Raman scattering no actual electronic excitation takes place(b) Spatial confinement of signal generation with nonlinear excitation. Visible ('blue-ish') light is used for excitation in single-photon microscopy, whereas near-infrared ('red-ish') light is used in 2PLSM. In single-photon microscopy an entire cone of fluorescence light (green) is generated, whereas nonlinear signal production is localized to the vicinity of the focal spot. (c) Generic nonlinear laser-scanning microscope. A laser source provides near-infrared ultrashort pulses; intensity and beam size are adjusted before coupling the laser beam to the microscope. The focal lengths of the scan lens (fS), the tube lens (fT) and the objective (fO) are indicated. Two-photon excited fluorescence (2PEF), which is isotropically emitted (inset), can be collected in epi- and/or trans-collection mode, using whole-area detection by photomultiplier tubes (PMTs). Forward-directed optical-harmonic and Raman signals are detected in transcollection mode in transparent samples. For in vivo experiments epicollection is used exclusively [10].

10

Two-photon excitation can be a superior alternative to confocal microscopy due

to its deeper tissue penetration, efficient light detection, and reduced phototoxicity.

Figure 1.8: In vivo two-photon imaging in the intact neocortex. (a) Different types of brain access. Open cranial window with the dura mater removed so that micropipettes for cell labeling and electrophysiological recordings can be inserted (top). Pulsation of the exposed brain is reduced by covering the craniotomy with agar and a coverglass. Thinned-skull (20–40 m thickness) preparation (middle). Cellular structures are either prelabeled (for example, with fluorescent proteins in transgenic mice) or stained through a tiny hole lateral to the thinned area. Chronically implanted glass window replacing the skull (bottom). Agar is used underneath the window for stabilization. (b) Example of deep two-photon imaging in mouse neocortex. Maximum-intensity side projection of a fluorescence image stack, obtained in a transgenic mouse expressing Clomeleon, a genetically-encoded chloride indicator101, under the control of the Thy1-promoter102, preferentially in deep layer 5 (L5) pyramidal cells. Data were taken with a 10 W pumped Ti:sapphire oscillator using a 40 , NA 0.8 water-immersion lens (Zeiss). Note that nearly the entire depth of the neocortex can be imaged [10].

11

The Two Photon Excitation microscopy has been used for high-resolution

imaging in various organs of living animals for its great advantages of imaging deep

within intact tissue. Figure 1.8 [10] demonstrates the cellular and subcellular imaging

in the intact brain.

1.1.6 SIM

Structured illumination is a wide field technique. Instead of the whole sample is

excited laterally, a grid pattern is generated through interference of diffraction orders

and superimposed on the sample, which cause normally inaccessible high-resolution

information to be encoded into the observed image. Most information for

reconstructing the image of a small object is mainly from the high-intensity

component. In reciprocal space from Fourier transformation, high-frequency

information can be extracted from the raw data to produce a reconstructed image

having a lateral resolution approximately twice that of diffraction-limited instruments

and an axial resolution reaching 120 nm, seen from Figure 1.9 [11].

12

Figure 1.9: (a) SIM overview of the cortical microtubule array of a hypocotyl cell stably expressing GFP-MBD microtubule marker. (b) The respective WF image corresponding to (a). (c) Transverse 1 μm profile (small diagonal line) across individual microtubule from the left boxed area of (a). (d) Transverse 1 μm profile (small diagonal line) across three closely adjacent microtubules from the right boxed area of (a). (e) Normalized intensity scatterplot corresponding to the individual microtubule profile of (c) by both SIM and WF. The width of the respective curves (green for SIM and red for WF) at 0.5 of normalized intensity corresponds to the FWHM of the individual microtubule. (f) Normalized intensity scatterplots corresponding to the microtubule bundle profile of (d). In both cases SIM (green lines) clearly separates three peaks instead of a single broad one in WF mode (red lines). All scale bars correspond to 5 μm [11].

SIM could allow for background free excitation and reduce the out of focus

emission, which is similar to confocal microscopy. Unlike confocal microscopy, the

resolution improvement is achieved without cutting any of the emission signals.

13

1.1.7 STED

STED microscopy improves the resolution by the selective deactivation of

fluorophores, minimizing the active emission area at the focal point [12]. When the

fluorophore is excited by the laser beam, the electron will be excited to the excitation

state and it will drop to the ground state and emit the photon through spontaneous

decay. No such photon will be emitted if an addition STED is introduced to pull the

electron to the ground state via stimulated emission. The STED microscopy utilizes

the STED to deplete the emission. The shape of the STED beam is engineered as

doughnut, and the minimum of the doughnut is overlapped with the excitation beam,

thus it could deplete the emission in the periphery and keep the signal in the central

part. In this way, the lateral and axial resolution could be improved using the 3D

doughnut.

The xy doughnut can be obtained through a vortex plate which is a twisted light

beam with an orbital angular momentum, causing a zero point at the center. The step

plate of which the central part has a pi phase difference with the outer part, provides a

doughnut in axis.

Ideally, the doughnut with a perfect zero overlapping with the excitation beam

could make the resolution infinitesimal with high STED power. The FWHM can be

described as

√

Where, I, Isat are the STED intensity and saturation intensity [13].

14

Figure 1.11: Imaging of 200 nm self assembled colloidals: (a) confocal image with the STED counterpart. (b). Scale bar 1 μ m, in insets scale bar 250 nm (movie2, avi, 2.8 MB). All images are raw data [13]

Figure 1.12: Experimental platform; (a) Setup. PMF: polarisation maintaining fibre; APD: avalanchephoto diode; PH: pinhole; TL: tube lens; DM: dichroic mirror; OL: objective lens; SF6: glass rods. (b) Absorption and emission spectrum of a solution of 24 nm fluorescent beads used in the presented measurements. (c) 3D view of the phase masks used for the measurements [13].

From Figure 11, a much better resolution with STED compared to confocal

microscopy is shown [13]. STED doesn‟t require specific dyes for the imaging and it

has very high sensitivity which is promising for observing the dynamics in cells.

15

While it remains a concern since the high power of STED may cause damage to the

sample, especially for the living cells.

1.1.8 STORM/PALM

Storm microscopy is based on high-accuracy localization of photo switchable

fluorophores. The storm imaging consists of a series of cycles. In each cycle, only a

small fraction of fluorophores is switched on, in other words, these fluorophores are

not overlapping, so their localizations could be obtained by 2D Gaussian fitting. The

localization accuracy is determined by the emitted photon numbers and usually in

nanometer scale. Repeating this for many cycles, each causing a stochastically

different subset of fluorophores to be switched on allows the positions of many

fluorophores to be determined and thus an overall image to be reconstructed [14].

The development of PALM [15] was quite prompted by the discovery of new

species and the engineering of mutants of fluorescent proteins displaying a

controllable photochromism, such as photo-activatable GFP. Similarly, STORM uses

paired cyanine dyes. Both techniques have been widely used and taken great

developments, in particular allowing multicolor imaging and the extension to three

dimensions, with the best current axial resolution of 10 nm in the third dimension

obtained using an interferometric approach [16].

These technique could enhance the resolution greatly, while the duty cycle is

really low, which limits its application in observing the dynamic in cell imaging.

16

Figure 1.13: Comparative summed-molecule TIRF ( A)and PALM ( B) images of the same region within ac ryo-prepared thin section from a CO S-7 cell expressing the lysosomal transmembrane protein C D63 tagged with the PA-FP Kaede. The larger boxed region in (B), when viewed at higher magnification ( C)reveals smaller associated membranes that may represent in teracting lyso somes or late endosomes that are not resolvable by TIRF. In a region where the section i s n early orthogonal to the lysosomal membrane, the most highly localized molecules fall on a line of width È10 nm (inset). In an obliquely cut re g ion [(D), from the smaller boxed region in (B)], the distribution of CD63 within the membrane plane can be discerned [15].

1.1.9 Summary

In my point of view, among all the techniques, STED, PALM/STORM seem

particularly promising for solving exciting biological problem. The advantage of

STED microscopy is that it has no strict requirement of the dyes and fluorescent

proteins. It not only enhances the resolution, but also improves the sensitivity.

17

Furthermore, it enables direct observation of the dynamic at native environment in

cells. The disadvantage is that STED is technically complicated and the photon

toxicity remains a concern. On the other hand, PALM/ STORM are technically easier

to implement and a resolution of 20nm is possible to achieve, making it a very

powerful tool for studying the biological problem at single molecule level. However,

PALM / STORM require special photoactivatable or photoswitchable dyes [17], and

the low time duty will restrict the use of detecting the single molecules dynamically.

Over the last few decades, the super-resolution techniques have already had a

great impact on modern cell biology. These microscopy show great advance over

conventional microscopy, they also have their specific strengths and weaknesses as

discussed above. Among, I want to emphasis that as for photon statistics that create a

trade-off between spatial and temporal resolution [18], there still could be

improvement. And all these techniques would also depend on the rapid development

of more sensitive detectors, stable dyes and flexible lasers together with steady

electronic device. It is firmly believed that better techniques would continue showing

up. Another promising direction is the combinations of these super-resolution

techniques, such as the combination of 4pi with STED. With these techniques, many

new insights into cellular structure and function are to be expected in the near future.

18

1.2 Gene Expression

1.2.1 Mechanism: Transcription, RNA processing, Non-coding RNA maturation,

RNA export, Translation, Folding, Translocation, Protein transport

Gene is located on chromosomes and is the fundamental unit of heredity that

encodes genetic characteristics. Gene regulation controls the structure and function of

the cells, and is the basis for cellular differentiation, morphogenesis and the versatility

and adaptability of any organism [19]. Gene expression is the process by which the

information stored in a gene is used in the synthesis of a functional gene product,

typically proteins or functional RNAs. The process is tightly regulated so that a cell

could respond to its changing environment. Several steps featuring gene expression

may be modulated, including the transcription, RNA processing, Non-coding RNA

maturation, RNA export, Translation, Folding, Translocation, Protein transport.

Among them the two key steps in gene expression are transcription and translation.

Figure 1.13: an overview of the flow of information from DNA to protein in a eukaryote [20].

19

1.2.2 Transcription of Eukaryotic Protein-Coding Genes: Initiation, Promoter escape,

Elongation, Termination

Transcription is the first phase of gene expression, in which the encoded gene

information is copied into message RNA (mRNA) with the help of the RNA

polymerase and other transcription factors. The mRNA will function as the template

for the protein product during the translation process. The transcription consists of

Initiation, Promoter escape, Elongation and Termination.

1.2.3 RNA Polymerase II in transcription

In the thesis, I mainly focus on the role and properties of RNA polymerase II in

transcription. RNA polymerase is an enzyme that remarkably signatures transcription.

In the bacteria, RNA polymerase carries out the transcription of DNA into RNA in

which RNA polymerase initiates transcription at a promoter, synthesizes the RNA by

chain elongation, stops transcription at a terminator, and releases both the DNA

template and the completed mRNA molecule [21]. In eukaryotic cells, the process of

transcription is much more complicated, and there are three RNA polymerases:

polymerase I, II, and III among which RNA polymerase II plays the most important

role in synthesizing eukaryotic mRNA [22]. RNA polymerase II requires several

additional proteins and the general transcription factors to initiate transcription on a

purified DNA template, and still more proteins to initiate transcription on its

chromatin templates inside the cell.

20

1.2.3.1 RNA Polymerase II and initiation cofactors

First, with the transcription factor, the polymerase binds to the specific DNA

sequence called promoter to form a closed complex [23, 24]. The RNA polymerase

II–containing transcription initiation apparatus to promoters of protein-coding genes

is recruited by transcriptional activators. The assembled apparatus contains the

12-subunit RNA polymerase II core enzyme, the general transcription factors, and one

or more multisubunit complexes called coactivators or mediators. Second, assisted by

one or more general transcription factors, the polymerase unwinds the 14 nucleotides

of DNA to form open complex. Then polymerase finds the start site in the

transcription bubble, binds to an initiating NTP and an extending NTP complementary

to the sequence, and catalyzes bond formation to yield an initial RNA product.

In bacteria, RNA polymerase core enzyme consists of five subunits [25]: 2 α

subunits, 1 β subunit, 1 β' subunit, and 1 ω subunit and one general RNA transcription

factor: sigma. RNA polymerase core enzyme associate to sigma factor to form

holoenzyme and then binds to a promoter. In archaea and eukaryotes, RNA

polymerase contains additional subunits in addition to the five RNA polymerase

subunits in bacteria [26]. In archaea and eukaryotes, the functions performed by the

bacterial general transcription factor sigma are performed by multiple general

transcription factors that work together. In archaea, there are three general

transcription factors: TBP, TFB, and TFE. In eukaryotes, in RNA polymerase

II-dependent transcription, there are six general transcription

factors: TFIIA, TFIIB , TFIID , TFIIE , TFIIF, and TFIIH. Additional protein,

activators and repressors also take part in regulating the initiation.

21

1.2.3.2 RNA Polymerase II and elongation cofactors

One strand of DNA is used as a template for RNA synthesis [27]. As transcription

proceeds, RNA polymerase traverses the template strand and uses base pairing

complementary with the DNA template to create an RNA copy. The switch from

initiation to elongation involves phosphorylation of the RNA polymerase II CTD and

an exchange of cofactors associated with the polymerase. RNA polymerase II

molecules found in initiation complexes lack phosphate on their CTDs, while

elongating polymerase molecules contain heavily phosphorylated CTDs. The

Mediator complex is tightly associated with RNA polymerase II molecules that lack

phosphate on their CTDs in the holoenzyme. In contrast, the elongation complex and

various RNA processing factors become associated with RNA polymerase II

molecules with hyperphosphorylated CTDs. CTD phosphorylation must occur during

the transition from transcription initiation to elongation, because the phosphorylated

CTD has a role in recruiting the 1mRNA capping enzyme to the nascent transcript,

and mRNA capping occurs soon after promoter clearance. The exact mechanisms that

control the switch from initiation to elongation remain unknown.

1.2.4 Polymerase II Clustering

RNA polymerase II plays a significant role in gene expression, especially

transcription. Most related investigations are based on in vitro biochemical

experiments. The mechanism and properties of the RNA polymerase II in vivo is not

very clearly understood. In fact, a series of experiments regarding RNA polymerase

II in transcription argue on the existence of clustered Polymerase II [28, 29]. In higher

eukaryotes, messenger RNA (mRNA) synthesis is believed to involve foci of

22

clustered RNA polymerase II called transcription factories. However, clustered Pol II

has not yet been resolved in living cells, raising the debate about their existence in

vivo and what role, if any, they play in nuclear organization and regulation of gene

expression.

Different experiments have been performed to investigate the existence of the

accumulation of RNA polymerase II in living cells. Brief descriptions of some

classical experiments holding different views are listed below.

The first evidence suggesting that several transcription units cluster together dates

to the visualization of focal sites of transcription within human nuclei experiment [30].

The cells were permeabilized and the engaged polymerases were allowed to extedn

their transcripts in BrUTP (bromouridine triphosphate). And nascent BrRNA was

seen in a few discrete foci, basically the factories. From these fixed cells studies

emerged theories interpreting the Pol II clusters as static pre-assemblies termed

“transcription factories.” However, attempts to directly visualize Pol II clusters in

living cells had been initially unsuccessful, raising a debate over their existence in

vivo [31, 32].

Quantitative analysis [33] suggested that a typical transcription factory in the

nucleoplasm of a HeLa cell contains nearly 8 Polymerases, each involved a different

unit.

Two theoretical arguments suggest that components of the transcriptional

machinery are likely to cluster and so form factories [34]. First, many transcription

factors dimerize [35], and if they also bind to two sites on DNA that are a few kb

apart, they will inevitably loop the intervening DNA when they come together. As

GFP (green fluorescent protein)-tagging shows that many transcription factors remain

23

bound to DNA for only a second or so, such ties would be transient. Secondly, two

polymerases engaged several kb apart on one template are likely to come together

spontaneously in the crowded nucleus through what physicists call the

„depletion-attraction‟ [36, 37]. Loops formed in this way would last for as long as the

polymerases remain engaged, which can be for many hours in humans.

Based on the fact [32] that the largest catalytic subunit of the polymerase bears a

temperature-sensitive mutation in the CHO cell line, tsTM4 and the wild-type subunit

from human cells was tagged with GFP and expressed in tsTM4; this construct

complemented the defect at the restrictive temperature, enabling the mutant cells to

grow normally . This indicates that the tagged polymerase must be functional. As

these cells contain both endogenous and tagged polymerases, then they estimated their

relative contributions to the total polymerizing activity as follows: during elongation,

the COOH-terminal domain of the largest catalytic subunit becomes

hyperphosphorylated and reactive to the H5 antibody. As a result, this

hyperphosphorylated form is widely used as a marker for the active enzyme. Under

this growth conditions, immunoblotting indicates that most of the H5-reactive form in

the cell is the GFP-polymerase (GFP-pol) instead of the endogenous enzym. They use

these cells to analyze the mobility of the GFP-pol, concentrating on changes occurring

over the minutes required to complete a transcription cycle. Determining whether

GFP-pol diffuses as a core enzyme of nearly 500 kD or a larger complex of 1,000–

2,000 kD requires analysis over fractions of a second and the development of

fluorescent standards of appropriate size. However, no larger complexes involved in

repair have been detected. The kinetics are consistent with the result that roughly75%

of the GFP-polymerases are able to move rapidly, with the remainder being

transiently immobile (association t1/2 ≈ 20 min). No fraction immobilized in an

24

inactive preinitiation complex could be detected. They also used a conventional

biochemical approach of radiolabeling nascent transcripts with [3H]uridine to confirm

that the endogenous enzyme in wild-type cells completes a transcription cycle with

roughly similar kinetics. By estimating the length of a typical gene and the rate of

elongation, they calculate that a polymerase would be engaged for only one half to

five sixths of a transcription cycle; then, a typical expressed transcription unit would

actually be transcribed for only a minority of the time. In this paper, they didn‟t detect

the immobilized but in active polymerases, arguing against the existence of

polymerase clustering.

Sunney Xie‟s paper [38] argues against the existence of transcription factories in the

mammalian nucleaus. Combining reflected light-sheet illumination with

superresolution microscopy (PALM), they were able to image inside mammalian

nuclei at subdiffration limit resolution. With superior signal-to-background ratio as

well as molecular counting with single-copy accuracy, they probed the spatial

organization of transcription by RNA polymerase II (RNAP II) molecules and

quantified their global extent of clustering inside the mammalian nucleus. Knowing

that the photoblinking events of TMR tend to be clustered temporally, they developed

a reliable density-based clustering algorithm that pools multiple localizations based on

their proximity in space as well as in time. In this way, they could accurately assign

localizations to spatiotemporal clusters. Applying this technique to the one on one

labeled RNA polymerase II fixed RPB1 cells, they found that nearly 70% of the foci

consist of only 1 st-cluster, corresponding to only one RNAP II molecule, whereas the

fraction with 4 or more st-clusters is minimal (<10%).

25

Figure 1.14: Spatial organization of RNAP II molecules shows no significant clustering. (A) Distribution of SNAP-RPB1 molecules in a thin optical section of the nucleus of a fixed U2OS cell labeled with TMR. (Inset) Zoomed-in area where individual transcription foci are discernible; yellow crosses indicate the centroid position of the st-clusters identified. (Scale bar, 2 μm; Inset, 500 nm.) (B) Distribution of the number of st-clusters in transcription foci indicates that at least 70% of the foci consist of only one RNAP II molecule (n = 4,465). (C) Distribution of spatial NND for transcription foci shows that the majority of the RNAP II molecules do not associate with each other within the reported diameter of transcription factories (40–130 nm). Dotted line indicates the mean [38].

In addition, they quantified the polymerase II clustering using two color

colocalization. They labeled the SNAP-RPB1 molecules simultaneously with SiR and

TMR dyes approximately equally under the fine-tuned labeling conditions. If there is

clustering of two or more RNAP II molecules, at least half of them will be revealed as

colocalized signals of the two dyes. Two-color superresolution imaging and

colocalization analysis detected 17.9 ± 1.0% (n = 8,929 in six cells) of the molecules

that colocalize with each other, thus yielding a maximum of 35.8 ± 2.0% of the

clusters with more than one RNAP II molecule, supporting the conclusion that most

of the foci contains only 1 polymerase II.

26

Figure 1.16: Quantification of RNAP II clustering by two-color colocalization. SNAP-RPB1 molecules are simultaneously labeled with either SiR (cyan) or TMR (green), so that approximately half of the molecules are labeled with each dye. Molecules that colocalize with each other are highlighted with white circles in the Inset. (Scale bar, 2 μm; Inset, 500 nm.) [38]

In contrast, Xavier Darzacq‟s paper [39] supports the existence of RNA

polymerase II clusters. They developed a quantitative single-cell approach (PALM) to

characterize protein spatiotemporal organization at single-molecule sensitivity in live

eukaryotic cells. TheU2OS cell stably expressing the Pol II catalytic subunit (RPB1)

labeled with a photoconvertible fluorescent protein, Dendra2 enabled superresolution

imaging of the distribution of Pol II in living cells by means of photoactivation

localization microscopy (PALM). As illustrated in Fig 7, a nonhomogeneous

distribution of Pol II was demonstrated in living cells, indicating Pol II clustering.

Pair-correlation PALM (pcPALM) analysis was used to infer spatial clustering of

proteins at the cell membrane.

27

Figure 1.15: Fig. 1Live-cell superresolution imaging reveals spatial Pol II clustering. (A)

Preconverted (Dendra2-RPB1 green emission) fluorescence image shows Pol II primarily

localized in nucleus [compare (A) and (B)]. (B) Two-dimensional superresolution reconstruction

reveals nonhomogeneous distribution of detected Pol II (red). Nuclear contour (white outline) is

approximated from preconverted fluorescence in (A). (C) A pair-correlation analysis was

implemented as previously described (12) to quantitatively analyze the spatial distribution.

Represented is the pair-correlation function computed from the spatial coordinates of the raw

PALM detections (black), fitted to a general function (orange) that accounts for contributing

factors from the protein clusters and single-molecule stochastic effects as detailed in

supplementary text and fig. S3. The corrected spatial correlation function for the protein (green)

is decoupled from the fluorophore stochastic contributions (blue). The corrected protein

correlation function shows statistically significant clustering, above the theoreticalg(r) = 1 (gray

dashes) with a fit parameter of rprotein ~ 220 (± 17) nm, distinct from the single-molecule

stochastic fit parameter of rstoch ~ 45 (± 1) nm. Errors (in parentheses) represent standard

error of the fitted value [39].

TcPALM, namely combining time-correlated detection counting and PALM as

28

time-correlated PALM, revealed that the time series representing the rate of detection

of Dendra2Pol II fluorescence are not uniformly distributed and these temporal

clustering events are more evident in the cumulative count of detections, where they

appear as large steps.

Figure 1.16: tcPALM analysis reveals temporal clustering of Pol II in live cells. (A to D)

Representative time-dependent detections from two Pol II clusters in living cells show bursts of

temporally correlated, high counts of detections. The cumulative detection profiles (B and D)

illustrate dynamic cluster assembly (arrows) and disassembly (plateaus). (E) The distribution of

apparent burst lifetimes (τon) is represented with a Gaussian fit. Average τon obtained was 5.1 (±

0.4) s, and the fit mean obtained was 4.2 (± 0.4) s. Errors (in parentheses) represent standard

error of the mean. We analyzed 104 clusters from four cells [39].

In conclusion, these results suggest that Pol II clusters exist transiently, with an

average lifetime of 5.1 (± 0.4) seconds, providing solid evidence that they are

statically assembled substructures.

Many other papers besides the above discuss about controversies regarding

transcription. Does transcriptional activity from polymerase II really occur in the

context of a specific nuclear? How is the transcription foci formed? What are the

other structural components of the factories? Are they self-assembling transcription

zones during the process of gene expression? Visualizing nascent RNA production

from genes in living mammalian cells is currently limited, by sensitivity issues, to the

transcripts from multicopy transgenes. Current molecular techniques for visualizing

genomic interactions give little information on the intimacy, dynamics or duration of

29

interactions. Development of techniques to better visualize chromosomal interactions

over time would greatly enhance our understanding of these processes.

In this thesis, I demonstrate a real-time tracking, ultra-sensitive optical nanoscopy

system that enables single-molecule detection in addressable sub-diffraction volumes,

at high background concentrations within crowded intracellular environments.

Basically, the STED beam could deplete the emission and we engineer the STED

beam like a 3D doughnut and overlap the beam with the excitation beam, so that the

STED beam would deplete the background in the periphery and keep the central

signal. By spatial on off control of the fluorescence, the signal to noise ratio is

enhanced and sensitivity is improved. This idea is initially brought up by my advisor

Dr. Alexandros Pertsinidis. To investigate the properties of polymerase II as well as

other transcriptional units, a tracking system is built to restrain the units of interest at

the minimum of the STED beam. The proof of principle experiments in vivo

proposed by Dr. Alexandros Pertsinidis show that the nanoscopy could greatly

increase the sensitivity and enable single molecule detection at hundreds of

nanomolar, which is close to the endogenous environment of living cells. To image

Pol II dynamics in relation to transcription from a defined promoter, a “mini-gene”

system is designed by Dr. Alexandros Pertsinidis and my labmate Jieru Li to

visualize the position of the genomic locus in the nucleus and track production of

nascent RNA simultaneously in real-time. The clustered polymerase II is observed and

the properties are quantified.

30

Chapter Two

Numerical simulation of single molecule

detection using STED

31

2. Numerical Simulation of single molecule detection using STED

Prior to building the STED nanoscopy, I conducted some numerical simulation in

order to have a better understanding of the mechanism and choose the optimal and

practical optical setup. Basically there are 4 parts in the simulation: excitation, STED,

Emission and Detection.

The 642nm red excitation and the 780nm STED beam are used for the simulation.

The xy doughnut is from a vortex plate with a helical ramp which leads to the

continuous phase change from 0 to 2π in the azimuthal direction. The light will cancel

each other at the center thus leading to a zero intensity there. For the z doughnut, the

step plate with a π phase shift in the central circle would give a z doughnut by

adjusting the relative size of the inner circle of step plate.

2.1 Numerical Simulation Theory

As we know, not all integrals can be computed. However, we could always

estimate values of definite integrals by regarding the integral as an area problem and

using simply shapes to approximate the area under the curve. In my simulation, I did

the numerical calculations using the Midpoint Rule [40].

To estimate the integral,

∫

We divide the interval [a, b] into n subintervals of equal width,

32

Let us denote each of the intervals as follows,

[ , ], [ , ],……, [ , ], where = a and = b

Next let be the midpoint of the interval. We can easily find the area for each could

be approximated by the area of a collection of rectangles whose heights are

determined by

∫

∑

2.2 Excitation beam

According to the theory by Wolf and Richards [41], I numerically investigated the

vectorial electric field near the focus point.

Figure 2.1: The meridional plane of a ray. The axis Ox is in the direction of the electric vector e𝑜 in the object space. From the paper of Wolf and Richards [41]

The equations describing the x, y, z components of the electric field are derived by

Wolf and Richards.

33

After numerically calculating the values of e , e , e , we further computed the

intensity distribution in the focal volume using the relationship that

e e +e e e e

With the calculated intensity distribution, I quantified the lateral and axial full width

at half maximum (FWHM) using Gaussian fitting.

The FWHMs were investigated on the conditions with different numerical

aperture values ranging from 0.3 to 1.35. Next, I studied how FWHM would vary

with NA with all the other parameters fixed.

In lateral, I got the fitting result as

. ( = 642nm, n =1.33)

e e e e

√

No surprisingly, and behaved the same way on NA as

circularly polarized light was used for the simulation. As a matter of fact, the intensity

distribution in xy plane is isotropic.

34

Figure 2.2: FWHM(nm) vs NA in x direction

Figure 2.3: FWHM(nm) vs NA in y direction

Figure 2.4: FWHM(nm) vs NA in z direction

35

2.3 Vortex doughnut

The vortex plate shown in Figure 2.5 [42] introduces continuous phase change

from 0 to 2Mπ in the azimuthal direction. Here M is a positive integer and the so

called charge. Mathematically, an additional term shall be multiplied by the

integrand for calculating the electric field for excitation beam.

Figure 2.5: Vortex plate [42]

Without any calculation, I derived analytically that at the very center (0, 0, 0), the

intensity is perfect zero. If I focus on the integrations on , we can get the following

conclusions as well (M is the charge of the vortex):

a. M = 1,

For left-handed circularly polarized light, I (0, 0, 0) = (0, 0, 0);

For right-handed circularly polarized light, I (0, 0, 0) = (0, 0, a), (a ! =0)

b. M >= 2,

For both left-handed and right-handed circularly polarized light,

I (0, 0, 0) = (0, 0, 0)

The numerical approximation provided us with the intensity distribution of the xy

doughnut sometimes called vortex doughnut. Figure 2.6 and 2.7 illustrates the nice

36

looking xy doughnut in focal plane and in xz plane respectively. The zero in the

center is vital since no depletion is desired in the center.

Figure 2.6: The intensity of the donut on the focal plane, the wavelength of the beam is 780nm

Figure 2.7: The intensity of the donut on xz plane (y=0), the wavelength of the beam is 780nm

2.4 Z doughnut

2.4.1 Central intensity with different phase modulation

To realize 3D super resolution imaging, I utilized z depletion pattern with step

plate z-beam depletion [43]. The extra Pi phase shift in the center could result in

37

nearly zero intensity at the focus point by modifying the radius of the shifted central

part.

Figure 2.8: By introduction of a step phase plate, the focus point has zero intensity surrounded by a wall of bright light [43]

I studied how to the focus point intensity will be with different angles

corresponding to the radius of the shifted central part. It turns out in Figure 2.8, at

certain radius for the inner circle; the intensity at focal center could be an order of

smaller than the maximum value along the axis, indicating a good zero for z

doughnut as well.

Figure 2.9: The focus intensity vs angle corresponding to the radius of the shifted central

part, n = 1.33, NA = 1.27

38

2.4.2 Z doughnut with the optimal phase modulation

The middle angle was set to be 0.641 radians to achieve extremely small focus

intensity. With the path modulation from the step plate, the intensity distribution of xz

doughnut in xz plane is as shown in Fig 2.10.

Figure 2.10: The intensities of the step plate depletion beam in x,z plane

2.5 Emission of a dipole

The molecules should be regarded as dipoles with regards to emission. To start

with, the image of a single dipole was investigated.

According to the paper [44] for a single dipole,

e ( )

∫

Where,

39

J0, J1, J2 denote Bessel function of the first kind with argument k

√

Upon these equations, I got the intensity following roughly Gaussian distribution

in the focal plane by numerical simulation. Simulation of dipoles with different

orientations showed different distributions. What‟s more, the center coordinates of

detected image will vary with the initial object positions in the focal space.

Figure 2.10: The image of a dipole at x=y=z=0, theta = Pi

40

Figure 2.11: The image of a dipole at x=50, y=100, z=150, theta = Pi

2.6 Resolution with different combinations of xy and z doughnut

A combination of xy and z step plate doughnut beam will not only deplete the

emissions on z axis but also on the xy plane. By adjusting the ratio of xy and z

doughnut power, I could achieve a isotropic 3D doughnut in the space.

I_sted = M*I_donut + N*I_stedz.

Different values set for M and N in table 2.1 lead to spherical spots of different

sizes. Typically, it is commonsensible that higher Power gives rise to sharper PSF.

M(100*Is) N(100*Is) FWHMxy(nm) FWHMz (nm)

1.7 0.07 120.09 120.80

7.2 0.75 60.16 60.24

30 3.8 30.12 30.16

Table 2.1: Choose different input powers of the donut beam and step plate beam to get nearly spherical spots with radius of 60nm, 30nm, 15nm

41

From Fig 2.12, we would notice that the doughnut beams will deplete a large area

in the space except the focus point, resulting in a sub-diffracted spot, which

demonstrate how STED beam would improve the resolution as well as the sensitivity.

Figure 2.12: Log(Power) VS xz for FWHM 60nm

42

Chapter Three

Experimental Setup

43

3. Experimental Setup

3.1 Schematic

Based on the simulated results and heated discussion with Dr. Alexandros

Pertsinidis, the STED microscopy is designed as Figure 3.1. Basically, the

microscopy consists of 3 modules: Excitation part; STED part; Detection part.

Figure 3.1: Schematic of the Setup

3.2 Setup components

As for key components, I refer to the excitation lasers, STED lasers, Objectives,

Filters, Detectors, piezo Stage, vortex plate, SLM. Based on the simulation, Dr.

Alexandros Pertsinidis chose all the specific optical components. Those components

are chose specifically based on the simulation. The setup built around an inverted

optical microscope base (Olympus, IX-71) with a two-tier multi-port design which

provides switchable confocal/STED and wide-field light paths.

44

For the excitation part, there are two pulsed laser diodes operating at 490nm and

640nm (Pico-Quant, LDH-P-C-485B and LDH-P-C-640B, controlled by Sepia 828-S 2

channel driver) and a 561nm CW solid-state laser (Cobolt, Jive 500).

Beam from Titanium-sapphire oscillator passed through an Electro-optic

Modulator (Conoptics, model 350-80) that enabled fast modulation of laser intensity,

and then was coupled into the fiber. In Figure 3.1, the STED beam was split into two

beams by the PBS: one went through the vortex plate which is a helical ramp providing

a smooth angular increase from 0 to 2π, resulting in a doughnut like beam in xy plane;

the other beam got reflected by the spatial light modulator (Hamamatsu, LCOS-SLM

X10468-02) which imposed programmed spatially varying modulation. In our case, the

SLM functioned as a step plate, adding additional π phase shift in the inner circle with

adjustable size on the beam. The SLM modulated the beam to a z doughnut beam. After

going through a couple of optics including the 60x silicon oil immersed objective lens,

the two doughnut beams merged and overlapped with the excitation beams on the

sample. Some 1x focusing telescopes would be used for adjusting the collimations of

all the beams to overlap the beams. The sample sit on a direct drive, high-dynamics 3D

nanopositioning stage equipped with capacitive sensors (Physik Instrumente,

P-561.3DD), interfaced to a digital controller (Physik Instrumente E-710 or E-712).

The emitted fluorescent light propagated back to the detectors. A 50:50 PBS could be

inserted to divide the signals into two parts: one arrives at the APDs suited for

scanning confocal/STED images; the other half signal would be collect by the

quad-view CCD camera. The quad-view images are used for real time tracking.

45

3.3 Align the setup

The quality of the doughnuts and how well they overlap with the excitation beam

is crucial to the performance of the setup. All the beams need to be well overlapped so

that the background would be quenched without losing too much signal. As for the

alignment, the minimum of both STED beams shall overlap with the maximum of the

excitation beam. Usually I first roughly overlapped all the beams based on the

reflected images on the side port CCD camera, and then I calibrated all the beams

referring to the scattered light from the gold nanoparticle. In the final, the

fluorophores were employed to check the quality of the beams and how well they

overlapped.

3.3.1 Coarse alignment based on the reflected images on the CCD camera

For overlapping the beams in xy plane, I usually referred to the reflected beams

from the water cover slip interface on the side port CCD camera. The Figure 3.2

implies the typical images of xy doughnut and z doughnut at focal plane as well as

above and below focus.

Figure 3.2: xy-depletion beam (left) and z-depletion beam (the three in the right: above

focus, in focus and below focus)

46

3.3.2 Calibrate the beams using gold nanoparticle (PMT used)

Based on the simulated results, I have a sense of the shapes of the beams. It is

indispensable to calibrate the exact shape of all the beams for this specific setup.

Furthermore, the calibration provides a point of reference for overlapping the beams.

3.3.2.1 xz scanning

The way to calibrate the setup is to scan over the gold nanoparticles and collect the

scattered light by gold nanoparticles. The gold nanoparticles stick to the glass cover slip

nonspecifically with glue the fraction index of which is close to the immersion oil was

prepared and mounted on the piezo stage. Once one particle was found, I roughly

centered it on the focus by checking the reflected images on the side port CCD camera.

Next the wave generator in E710\E712 scans a pre-defined trajectory over the particle

with stationary excitation and STED beams. The actual trajectory was recorded using

the stage capacitive sensors. A typical 4um×4um in xz or xy plane, 8second scan

consisted of 80 lines and 8000 points were sampled to obtain the actual trajectory of the

stage (100 points/line)

The scattered back propagated to the PMT. PMT converted the photon into

electronic signal and amplified the signal. Later the signal sampled at a frequency of

200 KHz, together with the trigger signal from E710\E712 for marking the first point of

each trajectory lines, was sent to shielded connector block with BNC (BNC2110,

National Instrument). Labview software was written to send commands to E710\E712

and dynamically acquire the signals from BNC 2110. The matlab script embedded in

the Labview constructed the 4by4um cofocal images. In matlab2010, the signals after

low pass filtration and smoothing over every 40 sample points were first binned to

100ms and synchronized with the scanning positions. Then I interpolated the irregular

47

sample trajectory with the corresponding photon signals to a 200 by 200 mesh grid. At

last, I binned the pixel to make the pixel size 40 nm.

In Figure 3.3, the xz profiles of the red excitation, vortex doughnut and z doughnut

were calibrated. I optimized the beams, especially for the z doughnut and then

overlapped them in xz plane. Different step phase modulations were tried to obtain a

symmetrical z doughnut with a close to zero central part, referring to these calibrations.

Figure 3.3: xz profiles of a. Excitation; b. Vortex doughnut; c. Z doughnut

3.3.2.2 xy scanning

Similarly, I calibrated the xy profiles of the red excitation, vortex doughnut and z

doughnut. The calibration process was exactly the same as that for xz profile calibration

except that the scanning pattern applied to xy plane. The xy profiles of the exaction,

vortex doughtnut and z doughnut beam in Figure 3.4 look tight and symmetrical, more

importantly the beams are well overlapped.

Figure 3.4: xy profiles of a. Excitation; b. Vortex doughnut; c. Z doughnut

48

3.3.3 Quarter wave plate adjustment

We learnt from the simulation that the orientation of the quarter wave plate is

crucial to the quality of the vortex doughnut. Left-handed circularly polarized beam is

requisition of perfect zero for xy doughnut. Referring to the reflected image on the

side port CCD camera, the angle of the quarter wave plate was optimized.

3.3.4 Optimal collar position for Silicon oil and regular oil objective

Most microscope objectives are designed to work with a cover glass that has a

standard thickness of 0.17 millimeters and a refractive index of 1.515, which is

satisfactory when the objective numerical aperture is less than 0.4. However, when

using high numerical aperture dry objectives, cover glass thickness variations of only

a few micrometers result in dramatic image degradation due to aberration, which

grows worse with increasing cover glass thickness. To compensate for this error, the

objectives are equipped with a correction collar to allow adjustment of the central lens

group position to coincide with fluctuations in cover glass thickness. The objectives

are composed of a series of optical components. The collar position corresponds to the

different position of those optical components. Although coverslips with a thickness

of 0.17 millimeters are used in our situation, the high numerical value of 1.3 requires

optimization of the collar positions to ensure the quality of the beams. The scale of

objective ranges from 1.3 to 1.9. Comparing the calibrated profiles of excitation,

vortex doughnut and z doughnut at each collar positions with a rotating step size of

0.1, I Figured out the optimal collar position for the silicon oil objective is 0.15 at 25

degree, and 0.16 at 37 degree. The optimization was characterized by tightest focus

spots, less spherical aberration and minimal center of the doughnuts.

49

3.3.5 Optimize z doughnut by changing the collimation and phase modulation

As stated in the simulation, a certain phase modulation leads to the best zero of

the step plate doughnut. The LCOS-SLM (Liquid Crystal on Silicon-Spatial Light

Modulator) functions as the step plate which introduces additional π phase shift in the

central circular part of the beam, resulting in the doughnut in axis. The SLM is a

reflection type spatial light modulator that freely modulates the light phase as needed.

This ability to accurately control the light wavefront makes the LCOS-SLM ideal for

applications such as optical beam pattern forming. The grey level images generated in

matlab were sent to the SLM. The dark inner circle stands for π phase shift from the

rest white space. Both the beam size and internal circle size determine the profile of

the z doughnut. In the beginning, the beam size was adjusted to collimated beams

centered to the SLM screen, referring to the high power sted beam profile at different

positions of the path. Second, the xy profile of the z doughnut was calibrated using

gold nanoparticle scattering while different phase modulations were added. It turns

out that the circular phase modulation with a radius of from 28 to 36 is suitable for a

symmetrical z doughnut with minimal zeros. A dense layer of Atto647N molecules on

the glass coverslip are prepared to test the quality of z doughnut, further details will

be discussed in the resolution part.

Figure 3.5: Gray level images of inner circle with a radius of 45 pixels

50

3.3.6 Overlap all the beams

Generally, the vortex doughnut and z doughnut are overlapped and in some cases

the collimation of xy doughnut could be modified to overlap the two doughnuts by

adjusting the relative distance of the telescope. Usually aligning the beams is a matter

of overlapping the excitation beams with the STED beams. The focus could be

modified by changing the collimation of the beams. The telescopes for each excitation

beams, together with the fiber ports, provide ranges of collimation. The xz profiles

were measured by gold nanoparticle calibration. All the beams could be aligned to

focus with 100nm.

3.4 Resolution vs power

One remarkable feature of STED microscopy is the enhancement of its resolution

[45]. With the optimized and overlapped beams, I demonstrated the improvement of the

resolution with STED beams.

3.4.1 Immobile molecules sample preparation

To verify the lateral resolution, I prepared a sample of Atto647N binding on the

glass coverslips. Glass coverslips and slides were passivated with 4-arm

Poly-ethylene-glycol (PEG) [465]. The 15bp Cy3-Atto647N duplex was immobilized

on the PEG coverslip surface through biotin-streptavidin interactions. An

Atto647N-labeled oligo was then diluted at 100-600nM in imaging buffer (75mM

HEPES-KOH pH 7.5, 55mM Potassium Glutamate, 1.8% w/v Glucose, 1mM Ascorbic

Acid, 1mM Methyl Viologen, glucose oxidase and catalase enzymes and 500µM

random10nt oligo), flowed in and the sample was sealed with tape. The buffer could

scavenge the oxygen in the solution, which would lower the possibility of photon

beaching.

51

An extremely dense layer of Atto647N was prepared in xz plane to quantify the

axial resolution. Similarly, 20uL 250nM 15bp Cy3-Atto647N duplex was injected in

the channel between the PEG glass coverslip and slide via the drained holes in the slide.

The channel was then rinsed with 20uL 1x PBS after over 30 minutes incubation. Again,

the oxygen scavenger was put into the channel to reduce photon bleaching.

3.4.2 Later resolution vs STED power

A 2µm×2µm region was first scanned in 8 seconds with 66µW 642nm excitation

only, followed by a second scanning with 66µW 642nm plus STED 780nm beams. The

single photon sensitive τ-SPAD detectors have very high sensitivity and good timing

resolution of 350 picoseconds (FWHM), making a great candidate for STED

microscopy. The NIM signal, together with the markers for E712\E710, was first saved

as binary file in Picoharp. The offline analysis was performed in matlab2010. The

arrival times of each photon were extracted from the binary file. The photon signals

were synchronized with the 8000 sampling positions by the markers at the first point of

each scanning trajectory lines sent by E710\E712. Similar way as described in the

calibration part was used to construct the 2D images. By comparison of the 2D cofocal

images with and without STED, we apparently visualized the enhancement of lateral

resolution with xy STED doughnut. The cofocal image was a typical diffraction limited

spot with a FWHM of 250nm, while with 250mw 780nm vortex doughnut STED beam,

the sharp image was characterized with a FWHM of 93nm.

52

Figure 3.6: 2by2um regions in xy with immobile Atto647N molecules with different STED power

Intuitively, the resolution would get better with higher STED power. To verify this,

I measured the resolution at different STED power, and quantified how exactly the

resolution changed with STED power. Laterally, I scanned a 2by2um region which had

a few immobile Atto647N in xy with 64uW red excitation, followed by the same region

scanned with 250mW, 500mW, 1000mW xy doughnut, as illustrated in Figure 3.6. 2D

Lorentz fitting was performed to get the resolutions. The resolution is characterized by

the following equation:

√

where Ps is the saturation power.

The measured results in Figure 3.7 were in accord with the equation, except that at

higher power, such as at 1000mW, the resolution was expected to be better. This could

53

possibly result from the imperfection of the 2D Lorentz fitting of the images with a

40nm pixel size. The fitted resolution was likely to be overestimated

Figure 3.7: Lateral resolution vs STED power

3.4.3 Axial resolution vs STED power

The images of a 2by2 um region in the xz plane with and without the step plate

STED demonstrated the improvement of the axial resolution. The FWHM was

decreased from 750nm without STED to 463nm with 250mW z doughnut STED.

,Ps is the saturation power

54

Figure 3.8: 2by2um regions in xz with a dense layer of Atto647N molecules with different STED power

Analogously, I measured the axial resolution by scanning in xz over a dense layer of

Atto647N molecules with different Z doughnut power. And the results kept with the

equation.

Figure 3.9: Figure 3.7: Lateral resolution vs STED power

, Ps is the saturation power

55

The saturation power was 50mW for xy doughnut and 150mW for z doughnut, which

agreed with the dimensions of the xy and z doughnut. A higher Ps value in xz compared

to in xy corresponds to the larger dimension of xz doughnut compared to xy doughnut.

In conclusion, a lateral resolution of 72nm and an axial resolution of 287nm were

achieved with roughly 1W xy and z doughnut STED laser respectively.

3.5 Time gating

3.5.1 Take data with APD detector and Picoharp (T2 mode and T3 mode)

The τ-SPAD photon counting modules combines Laser Components' ultra-low

noise VLoK silicon avalanche photodiode with specially developed quenching

electronics from PicoQuant. The low dark counts, high time resolution (FWHM < 350

picoseconds) and high photon detection efficiency (up to 70%) make it an ideal

detector for single molecule experiment. The photon signal detected by APD was

converted to NIM signal, which later on was sent to Picoharp and saved as binary file.

Picoharp could record the signal in two formats: T2 and T3 modes. In two T3 mode, a

refer clock signal was connected to channel 1 of Picoharp. In our case, the 80MHz

internal clock of red excitation was employed; the relative time to the latest clock

pulse from channel 2 was recorded. While in T2 modes, no clock source is needed,

instead the time referring to the initial time point is taken. Thus, T3 mode is suitable

for lifetime measurement. And T2 mode enables both the input channels to receive

signal from APDs.

56

3.5.2 Lifetime of the fluorescence

As mentioned above, the APDs could record the arrival time of each photon. I

noticed that the arrival time distributions were not uniform with time. The 80MHz red

excitation sent trigger to the Picoharp so that I was able to synchronize the emission

with the excitation pulses. When Picoharp was operated in T3 mode, the relative time

was saved in reference to the each excitation pulses. Each time one photon was

registered within 90ns which was the dead time of the APDs. Time-correlated

single-photon counting histograms of the fluorescence from multiple cycles would be

a typical Poisson distribution. Indeed, the lifetime fitted well with the Poisson

distribution.

Figure 3.10: Lifetime of Cy5 fitted by Possion

57

Figure 3.11: Lifetime of Atto647N fitted by Possion

The fitted results in Figure 3.10 and 3.11 indicated that lifetime is 2.16ns for Cy5

and 1.59 ns for Atto647N in oxygen scavenger. Even though the lifetime of these

fluorophores would vary at different conditions such as solution ingredient,

temperature, the fitted lifetime values were quite close to the reported values [47].

3.5.3 STED changes the lifetime

It is interesting to note that with STED the time distribution will change as the

emitted photons tend to arrive earlier compared to that without STED. In such case,

the photon arrival times could be exploited to improve the spatial resolution. In

conjunction with time gating, finer details are gained with lower intensities. Time

gating means choosing the photons from specific time period so as to the photon are

more likely to from the central part with almost zero STED intensity. In this way, the

selected photons are inclined to be from the very central part, resulting in an

improvement of the resolution. Here, CW laser was compromised by ongoing

excitation and therefore a less pronounced fluorescence on-off contrast at the

doughnut slope.

58

Figure 3.12: The photon arrival time distribution of Atto647N. Red is for excitation and black line is for excitation plus STED

3.5.4 Time gating improves the resolution

The gated-STED (g-STED) analysis can be realized by offline processing of

time-correlated single-photon counting binary files recorded by Picoharp in T3 mode.

I constructed the cofocal images using the photons whose arrival times were between

5ns to 8ns with regards to the excitation pulses. Laterally, the resolution of individual

Atto647N molecules dropped from 264nm with excitation only to 94nm with 290mW

780 xy CW STED. Applying time gating, I got images in the right. For excitation only,

the image with time gating showed the same resolution without time gating, while for

the STED image, the resolution increased to 82nm. In axial, an xz image was scanned

over a dense layer of molecules. Similarly, the axial resolution with z doughnut

improved from 446nm to 383nm with time gating. Instead of using all the photons,

time gating would provide an option of increased resolution at the expense of losing

some signals. For some experiment, two colors scanning images in Figure 3.13 were

obtained by two APDs. Since the only two Picoharp inputs were occupied to the two

59

APDs, the Picoharp would only function in T2 mode. In such case, time gating could

not be applied [48].

Figure 3.13 Confocal images of Atto647N in xz plane without (left) and with(right) time gating : a. 642nm Excitation only; b. 642nm Excitation and 418mW 780nm z doughnut STED

3.6 CW laser vs pulsed mode laser

3.6.1 Pulsed mode properties

The previously demonstrated results were with CW STED lasers. Historically,

Stephen Hell first built STED with pulsed lasers. Pulsed lasers would deplete the

fluorescence more efficiently. However, pulsed lasers are more complicated to handle

with. What‟s more, the temporal alignment between excitation pulses and STED

pulses is required. In other words, the STED pulses need to be synchronized with the

excitation pulses with an adjustable time delay. Only the two pulses arrived at the

sample at the same time, we could get the most efficient depletion. Furthermore, the

width of the STED pulses should be optimized to overlay the excitation pulses without

getting stretched too much. To achieve the same resolution, less power is required for

Pulsed STED laser.

60

3.6.2 Optimize the phase to achieve the highest depletion

In practice, the Mira OPO enables the Ti:Sapphire to switch from CW mode to

pulsed mode. Two 6-inch glass rods stretched the pulse width to ~300fs to avoid

unwanted non-linear effects and damage to the fiber. The 80MHz trigger signals were

sent out from the STED laser controller. The phase was adjusted by the Analog

Voltage Control Phase Shifter 60-80MHz 180° Full Band before it was sent to

trigger the excitation controller (Sepia II).The Phase Shifter has a 0–15 V control

voltage range, corresponding to a 180 degree phase shift range.

A 300nM Atto647N molecules solution with oxygen scavenger was prepared to

Figure out the optimal voltage to achieve best depletion for the pulsed STED laser. I

measured the depletion with a starting voltage of 0V and a 0.1 V step increase to 15V.

3.6.3 Compare the two modes

When the laser was in pulsed mode, the maximum power is roughly quarter of that

in CW mode. The maximum power in pulsed mode was approximately 80mW,

corresponding to 290mW in CW mode. In spite of which mode the laser was in, the

depletion efficiency tested was quite close. Considering this situation, I operated the

STED laser in CW to avoid the process of synchronizing the pulsed STED with

excitation pulses.

61

Chapter Four

STED improves SNR and enable single

molecule detection in vivo

62

4. STED improves SNR and enable single molecule detection in vivo

4.1 STED principle

Figure 4.7: Simplified Jablonski diagram a typical fluorophore

Illustrated by the simplified Jablonski diagram [49] in Figure 4.1, S0 and S1 stand

for the ground state and the excited state of an electron. When excited with a photon,

the electron will be pushed to the excited state. The excited unstable electron will

drop to the ground and meanwhile emit a photon. This process is called spontaneous

decay, and the emitted photon is in fact the fluorescent signal. When STED beams

brought in, another mechanism will compete with the spontaneous decay process.

Alternatively, the excited electron will go back to the ground state through stimulated

emission in which process no fluorescence is gave off. The STED beam is red-shifted

in frequency to the emission spectrum of the fluorophore, quenching them to the

ground state by stimulated emission.

S0

S1

1

2

3

4

Fluorescence

Absorption Stimulated

Emission

63

4.2 The reversible depletion of STED on single fluorophore

Figure 4.2 demonstrates the reversible, instantaneous on-off control of STED on

single-molecule fluorescence, making the STED beam a powerful tool to selectively

inhibit the fluorescence at its outer part. I overlapped the no phase modulation STED

beam with the excitation beam, so basically two Gaussian beams overlapped with

each other. A single immobile Atto647N on the PEG glass surface was utilized to

demonstrate the depletion effect of STED beam.

Experimentally I engineered the STED beam to a doughnut-like beam.

Overlapping with the excitation spot, the doughnut STED beam could deplete the

emission in periphery and keep the signal in the central. The net effect is that STED

helps break the diffraction limit in a fundamental way.

Figure 4.8: The reversible on off control on single Atto647N using STED

STED

ON

STED

OFF

STED

OFF

64

4.3 The general Background properties

For realizing single molecule detections in living cells which usually feature with

high background and very noisy, I need focus on reducing the background

fluctuations. Before that, it is necessary to study the properties of the background and

noise. Two main types of background fluctuations are assumed to dominate for

different systems: open system and closed system [50, 51,52]. Dr. Alexandros

Pertsinidis figured out the theory for the background properties. It turns out the

background noise is super Possion rather than Possion as people assumed. Dr.

Alexandros Pertsinidis explained the behaviors of noise in closed system and open

system as follows.

4.3.1 Closed system

In a closed system which does not allow the molecules transfer in or out of the

system, the number of the molecules in the system is constant; hence shot noise due to

the stochastic nature of fluorescence emission would dominate. In this case, the

intensity follows Poisson distribution. Assuming the intensity is given by

Where n is the total number of the molecules in the system, is the brightness of

single molecule.

Following the Poisson distribution, the variance is noted as

65

Thus we could derive that the SNR is

√ √

Based on this equation, we can only be able to achieve single molecule detection

when is high enough.

4.3.2 Open system

Accordingly, in an open system, such as the freely diffusing molecules in the

detection volume, the number of the molecules n would fluctuate and is Poisson

distributed.

√

The intensity fluctuate will be

In this case,

√

Irrespective of molecular brightness, single-molecule detection becomes

impossible since SNR will be always less than 1 for certain concentrations (n>>1).

4.4 The STED depletion in the Atto647N solution at different concentration

4.4.1 Background and noise from the solution and surface

Under low brightness conditions (0.5 < ε < 3), often used in fluorescence

correlation spectroscopy, small deviations from Poisson (characteristic of number

66

fluctuations) were seen in the tails of the photon-counting (intensity) histogram at

~1-50nM molecules in solution. It was further intuitively proposed that the relative

effect of number fluctuations diminishes at high concentrations, with the largest

deviations from Poisson expected at increasing ε and decreasing n. However, the

molecular concentration and brightness regimes where (Poisson) shot noise and

(super-Poisson) number fluctuations respectively dominate, and how these relate to

conditions relevant to single-molecule detection (ε >> 1), have not been fully

characterized. I measured the background level and noise for Atto647N-streptavidin

solutions at concentrations ranging from 15nM to 1µM. Strikingly, under illumination

conditions used for real-time single-molecule detection we observe noise that exceeds

several-fold the Poisson limit, while the Fano factor (variance/mean) increases

proportionally with excitation power (i.e. molecular brightness ε), independently of

concentration. These results strongly suggest that single-molecule detection at up to

1µM solution concentrations is largely limited by super- Poisson noise due to number

fluctuations.

4.4.2 Background and noise with different excitation power

To validate the noise at high concentration is super-Poisson, the background and

noise were investigated with different excitation power. As we expected, when the

excitation power exceeded a level which ensured ε >> 1, the SNR should be

independent of the excitation power, which was observed from the 15nM and 500nM

Atto647N solution. 5.53uW, 15.2uW and 66uW excitation power were illumined in

67

the Atto647N solution. The SNR stayed nearly the same level as the power increased,

indicating the noise is super Poisson.

Figure 4.9: SNR with different excitatio power at Atto647N solution of 15nM (black) and 500nM

(red)

4.4.3 Background and noise with and without STED of the Atto647N solution at

different concentration

The engineered 3D doughnuts will reduce the molecular brightness and thus

background level by a factor inversely proportional to the depletion saturation. The

backgrounds in the Atto647N solution at 15, 50, 150, 500 and 1200nM were

compared with and without STED. The Atto647n streptavidin solution in the

oxygen scavenger buffer was injected into the channel between the glass coverslip

and glass slide. The channel was previously blocked by 10% BSA for 10 minutes.

0 10 20 30 40 50 60 70

10

20

30

40

50

60

70

SN

R

Excitation power (uW)

15nM

500nM

68

Also 10uM streptavidin was mixed in the solution to reduce nonspecific binding of

Atto647N to the surface.

The STED was periodically turned on-off. Illustrated in Figure 22, fluorescence

intensity trace from 150nM Atto647N-streptavidin solution was less noisy and the

level got lower with 900mw xy doughnut beam on. Photon-counts were binned

every 10 milliseconds.

STED On

0 200 400 600 800 1000

500

1000

1500

2000

2500

3000

3500

4000

4500

ba

ckg

rou

nd

(co

un

ts/0

.01

s)

time(0.1s)

Figure 10.4: the background with periodically on off 900mW xy doughnut in 150nM Atto647N

solution

According to the quantified background level and noise reduction, the noise

reduction was proportional to the background level reduction. Application of STED

69

reduces the background level by a factor inversely proportional to the depletion

saturation [53],

√

Importantly, we find that which type of noise dominates the background has

profound implications for the achievable SNR improvement using STED. When shot

noise dominates, background fluctuations are reduced proportionally to the square

root of background level, thus SNR is improved by ~√ . While for number

fluctuation, the noise will reduce proportionally to the background level, then the

SNR is improved by . Our results indeed show proportional reduction of

background level and noise, further validating the notion that number fluctuations are

the dominant source of noise under our conditions, and indicating that STED is

particularly effective in suppressing background fluctuations at elevated solution

concentrations. In other words, to achieve the same SNR, STED improves the

working concentration of single molecule detection by . For our STED setup,

a 3-4 fold background reduction means an order-of-magnitude increase in

concentration range for single-molecule experiments.

The background and noise reduction with STED at 15, 50, 150, 500, 1200 nM

Atto647N solution validated the effective depletion with STED.

70

100 1000 10000

10

100

no STED

w/STED

No

ise

(co

un

ts/0

.01

s)

Level(counts/0.01s)

Freely diffusing Atto647N-streptavidin

Poisson Limit

Figure 4.11: Noise with and without sted from 15, 50, 150, 500, 1200 nM freely diffusing

Atto647N-streptavidin (black circle: no sted; red circle: with STED)

The background level reduction with 900mW xy STED is roughly 3 fold, and so

is the noise reduction, providing solid evidence of the powerful depletion with STED

background level reduction noise reduction

1.0

1.5

2.0

2.5

3.0

3.5

4.0

4.5

5.0

Re

lative

de

cre

ase

sted on/sted off

sted on/sted off

Figure 4.12: background level and SNR decrease with STED

71

As a matter of fact, we cared more about whether this applied to the in vivo

situation. While how STED would work in living cells remained unclear. Thus, I

measured the background and noise reduction with STED inside Rpb9 SiR Hela cells.

The cells were fully stained to retain the high background and noise level. 5.5uW red

excitation and 400mW xy doughnut and 700mW z doughnut were used. The

background and noise inside RPB9 cells behaved the way as in vitro that the noise

level reduction is proportional to background level reduction, proving STED is

potential for live cell imaging.

10 100 1000 10000

1

10

100

1000 red only

sted on

No

ise

(co

un

ts/0

.01

s)

Level (counts/0.01s)

Figure 4.13: Background level and noise with and without STED in RPB9 cells

3~4 fold reduction for the background level as well as for the noise was

demonstrated, verifying STED would also work inside the cells as efficiently as in

vitro. The data analysis was conducted by Dr. Alexandros Pertsinidis and me.

Alexandros drawed figure 4.11 and 4.12.

72

background level reduction noise reduction

1

2

3

4

5

6

Ra

ng

e

Figure 4.14: Background level and noise reduction with STED in RPB9 cells

4.5 Detection of immobile single molecules at elevated concentrations

4.5.1 Experiment design

Figure 4.15: Resolving immobile Atto647N on the surface at the presence of the Atto647N

solution above

Freely diffusing

Atto647Nmolecules

73

To demonstrate that STED enables single molecule detection at high

concentrations, I aimed to resolve the immobile molecules on the surface with the

background from the solution above. 15nt Cy3-Atto647N duplexes (IDT,

Cy3-biotin target oligo and 5‟Atto647N-AGATGAGGAAGAGAGT-3‟, HPLC

purified) were bound to the PEG surface. 100nM, 300Nm, 600nM Atto647N solution

with oxygen scavenger was put into the channels respectively to act as the

background. Alexandros designed the experiment.

4.5.2 Cy3-Atto647N duplex preparation

The two complementary oligos, Plac-70...-48 FWD 5‟Cy3 biotin and

Plac-48…-70 REV 5‟ Atto647N, were annealed to get the Cy3-Atto647N duplex.

1.5uL FWD Primer and 1.5uL REV Primer were diluted by 47uL 0.22um filtered

TE50 buffer. The mixture was incubated in the PCR machine with the Cyler settings:

the initial temperature was 95 degree, followed by a decrease of 10 degree every

minute till 25 degree, and then the temperature was set to 4 degree for 10 minutes.

The colocalization of Cy3 and Atto647N via FRET [54] indicated that the duplex

usually have a colocalization rate of over 40%, which is suitable for the following

surface experiment.

4.5.3 Map the yellow channel and red channel

The Cy3 was used to identify the corresponding Atto647N.Coordinate mapping

transformations were calibrated using cofocal images of stable 15bp Cy3-Atto647N

74

duplexes obtained with 561nm, 642nm only and 642nm+STED lasers before the

Atto647N solution was added. The focus position was adjusted by looking at the

reflected images of the lasers beams on the left-side port CCD camera. The

colocalization rate was 40%-60% so that we should not expect to see a colocalized

Atto647N to every cy3 molecule. The Cy3 and Atto647N molecules were featured

and fitted. Next, the offsets between yellow, red and STED were calibrated.

Figure 4.16: Two color 6by6um imaging of Cy3-Atto647N duplex

4.5.4 Scan the regions with yellow, red and red with sted at elevated

concentrations (100nM, 300nM, 600nM)

A 2µm×2µm region was first scanned in 8 seconds with 200µW 561nm

excitation to localize immobile Cy3 molecules. The fret effect could help identify the

0 1 2 3 4 5 60

1

2

3

4

5

6

X/um

Y/u

m

0 1 2 3 4 5 60

1

2

3

4

5

6

X/um

Y/u

m

Red laser excitation Yellow laser excitation

5’

Cy3

Atto647N

3’

3’

Atto647N-Cy3 Duplex

75

colocalized Atto647N. The same region was then scanned two more times, once with

66µW 642nm excitation only, followed by 66µW 642nm plus 200mW STEDxy and

600mW STEDz 780nm beams.

4.5.5 Construct and compare the images

At the presence of the 300nM Atto647N solution, we could hardly visualize the

Atto647N molecules from the red only cofocal image; while with STED beams on,

we could clearly observe there were 3 molecules showing up. The same results

applied to the 100nM, 600nM Atto647N solutions. With 600nM Atto647N solution

above, we could visualize nothing from red excitation cofocal image. In contrast, the

molecules could be resolved with STED on and colocalized with the Cy3s as well as

the Atto647Ns through Fret effect, which directly demonstrated the powerful effect of

STED.

76

Figure 4.17: 2by2um images of Cy3, Atto647N through fret, direct red excitation and with STED

on

no STED, SNR=1 w/ STED, SNR=3

Cy3 Atto647N (fret)

Atto647N (red) Atto647N (red+sted)

77

4.5.6 Quantify the SNR with and without STED (The distribution of the signal from

the Cy3 colocalized regions and random regions)

Reconstructed 2D images were analyzed by calculating the total Atto647N

photon counts within a certain radius r from the Cy3 position and comparing with

total photon counts from equal size regions where there was no Cy3 detected. The

parameter r was set to 180 nm for excitation only and 100 nm for excitation and

STED respectively, which were roughly the sizes of the excitation beam without and

with STED. The peak of the signal from the cy3 colocalized regions was more

separate with that from random regions with STED beam (Background) since the

STED would reduce the background and the noise.

Figure 4.18: the total counts distribution from the cy3 colocalized regions (Molecules) and

random regions (Background) without and with STED

135000 150000 165000 180000 1950000

5

10

15

20

25

30

35

40

# r

egio

ns

Total counts

Background

Molecules

12000 13500 15000 16500 18000 195000

10

20

30

40

50

60

70

80

# r

egio

ns

Total counts

Background

Molecules

No STED With STED

78

To demonstrate the effect of STED quantitatively, I calculated the SNR denoted

by the signal over the sigma from the histogram distributions. And the SNRs

increased 2-3 time folds with STED.

Figure 4.19: SNR with and without STED at 100nM, 300nM and 600nM

4.6 DNA hybridization on off binding detection

4.6.1 Experiment design

Figure 4.20: Hybridization of Cy3 labeled oligo with Atto647N-probes

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The DNA hybridization on off binding detection is another proof of principle

experiment designed by Alexandros to test whether the high efficiency of STED in

reducing noise from number fluctuations can enable single-molecule detection at high

background concentrations. I immobilized a Cy3- labeled ssDNA target on the coveslip

surface and measured the real-time on-off binding of a short Atto647N-labeled

complementary probe from the solution. Under yellow illumination, when the cy3 oligo

anneals with the Atto647N probe, the FRET effect in which the energy of cy3 is

transferred to Atto647N could be observed. Reflected on the time trace, we would

observe the anti-correlated traces in the red and greed channels: an off state of Cy3

corresponds to the on state of Atto647N.

4.6.2 The on off rate optimization

4.6.2.1 Kd of different oligos (10nt, 9nt, 8nt)

Nearly 50% on-rate at 100 milliseconds to 1 second time scale would be ideal for

the on off binding detection. Then Oligos of different complimentary nucleotide were

tested to obtain a proper on off time. In addition, salt of different concentrations were

added in the solution to adjust the Kd rate [55]. The quad view CCD camera images

under yellow TIR excitation enabled the lifetime measurement for different DNA

hybridization with different amount of salt. Typical wide field FRET traces was

illustrated in Figure 4.15 and 4.16. On the top left are the wide field images of

Atto647N (Cy5) and Cy3. The featured cy3 molecules and the corresponding

Atto647N molecules are zoomed in shown as the top right. The total signals are

80

computed by summing up the intensities from the 5 pixels by 5 pixels ROIs. In the

traces between the red trace is for cy3 while the blue trace corresponds to Atto647N.

The script for extract the time traced was initially written by Guanshi Wang and

modified by me.

Figure 4.21: Fret traces of 300nM 9nt Atto647Nwith Cy3 at 1mM NaCl

Figure 4.22: Fret traces of 300nM 8nt Atto647Nwith Cy3 at 1mM NaCl

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4.6.2.2 Adjust the Kd with NaCl at different concentrations

It turned out that 8nt oligo the imaging buffer contained a variable concentration

of NaCl (750, 500 and 100 µM NaCl for 300, 600 and 1000 nM probe respectively)

would achieve ~50:50 on-off binding equilibrium of the probe to the target

4.6.3 Map the yellow channel and red channel

For the wide field images, the 100nm beads were used for registration. For

extracting traces from images, firstly the cy3 was featured and intensity was

calculated by summation of the ROI with a radius of 3 pixels. Secondly, the intensity

of Atto647N was calculated by adding up the corresponding region in the red channel.

For the STED images, the cy3-Atto647N duplex was utilized. The scanned

images of the colocalized duplex in yellow and red with\without STED provided

information about the offset between them, which later was referred to bring the

molecule at the minimum of STED doughnuts.

4.6.4 Interlace the yellow laser and red laser

The function generator sent two pulses with roughly 180 degree phase difference

to trigger the red laser and the shutter that blocked the yellow laser. The interlaced

yellow and red excitation time trace in Atto647N solution was examined to optimize

the phase shift. The direct excitation trace from red laser and Fret trace were separated

by the 1ms bin time trace, from which the 50Hz yellow excitation period could be

identified, shown in Figure 4.17.

82

Figure 4.23: the time traces in red (top) and yellow channel (bottom) under interlaced red and

yellow excitation.

4.6.5 Take time traces with the interlaced yellow and red laser w/wo STED

Based on the image of the Cy3 and calibrated offset, I managed to center the

target molecule in the excitation peak/zero STED. As the Cy3 and Atto647N dyes

come in close proximity upon duplex DNA formation, I employed the time-interlaced

561nm and 642nm laser beams to detect binding events through Cy3-Atto647N

fluorescence-resonance- energy-transfer (FRET) and direct Atto647N excitation

respectively. Typically, a 40 second trace was taken in which the first 20 seconds

there was no STED and the remaining 20 seconds the STED was turned on.

4.6.6 Data analysis

4.6.6.1 Separate the direct red excitation and FRET traces

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83

The time data was saved in binary file through Picoharp. In matlab, the time

traces were extracted with 1ms time bin size. Next, the direct red excitation and Fret

traces were separated based on the periodical intensity changes, similar to Figure 4.23.

In the following, the corresponding signals were selected and rebinned to 20

milliseconds or the multiple times of 20 milliseconds. In this way, I was able to

measure the FRET and direct excitation simultaneously.

4.6.6.2 SNR of the direct excitation traces with/without STED

The anti-correlated Fret traces could help identify when the hybridization took

place. Thus, I could compare the SNR for this on off hybridization events.

Remarkably, I could recognize the on off events with STED shown in Figure 4.24

drawn by Alexandros. Meanwhile, without STED the binding events were too noisy

to be identified. Real-time traces of directly excited Atto647N revealed noisy intensity

fluctuations, while application of STED resulted in markedly improved SNR,

enabling unambiguous identification of binding events under direct excitation. The

SNR improvements at 100nM, 300nM, 600nM were investigated. 2-3 fold SNR

improvement were achieved with 200mW xy and 500-700mW z doughnut beam.

These results demonstrate that STED can enable single- molecule detection for the

time trace measurement at up to 0.6-1µM solution concentrations. Note that this

approach can also be used to detect transient, weak molecular interactions

(KD~100-1000nM range).

84

Figure 4.24: The anti-correlated FRET trace on the bottom could help identify the on off binding

event. The direct red excitation trace contained 15 seconds red excitation only trace followed by

another 15 seconds trace with STED on.

Figure 4.19: SNR enhancement with STED

85

Chapter Five

Single molecule detection for RNA

Polymerase II transcription

86

5. Single molecule detection for RNA Polymerase II transcription

Our lab focused on the study of RNA Polymerase II transcription in live cells at

single molecule level. All the related experiments were designed by Alexandros. I

worked closely with Alexandros for most of the data acquisition and data analsysis.

5.1 Mini gene

Figure 5.1: The schematic of the mini gene design

To image Pol II dynamics in relation to transcription from a defined promoter, a

“mini-gene” system is designed by Alexandros and Jieru to visualize the position of the

genomic locus in the nucleus and track production of nascent RNA simultaneously in

real-time. Our construct contains a single Cytomegalovirus immediate-early (CMV-IE)

promoter and enhancer sequence that drives expression of an mRNA coding for Blue

Fluorescent Protein (BFP) (for visualizing protein production), followed by a

Puromycin resistance gene and a cassette of phage PP7-derived stem-loop structures

(24×PP7) in the 3‟ un-translated region (3‟UTR) (for visualizing the RNA transcript).

Finally, upstream tetracycline operators (28×TetO) are used for tracking the construct.

Insu

lato

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SV40pA 24×PP7 IRES-Puro BFP CMV-IE 28×TetO

tdPCP-EGFP TetR-RFP

87

Single copies of our mini-gene, flanked by genomic insulators, are stably integrated in

the genome of U2-OS cells using the piggyBac transposase system.

5.2 Sample preparation (Rpb1 and Rpb9)

Figure 25 HeLa cell expressing SiR labeled polymerase

U2-OS cells (ATCC) were transfected by Alexandros and my lab mate Mallette

Asmuth with Flag-SNAP-Rpb1 (amaR) plasmid and selected with 1µg/mL α-amanitin.

Individual α-amanitin-resistant colonies were selected and expanded, then labeled

with SiR-BG for imaging. α-amanitin prohibits the endogenous Rpb1 but not the cells

with the SNAP-tagged version of Pol II.

Similarly, T-Rex HeLa cells (Invitrogen) were transfected with Rpb9-SNAP-Flag

plasmid and selected with zeocin. Individual zeocin-resistant colonies were selected

and expanded, and then labeled with SNAP-Cell TMR reagent (NEB) for imaging.

Only in presence of tetracycline, strong TMR signal was observed. Rpb1 clone 2-5

cells were transfected with the CMV mini-gene plasmid with either a plasmid

expressing piggyBac transposase (Transposagen, sPBo) or GFP (Lonza, pMaxGFP) as

a control. Cells were selected with 1µg/mL puromycin for 2 weeks.

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transposasespecific genomic integration resulted in ~5-fold more

puromycin-resistant colonies for sPBo vs. pMaxGFP. Individual puromycin-resistant

colonies were selected and expanded, and then transfected with tdPCP-EGFP and

tetR-RFP plasmids for imaging. We kept using those samples. Alexandros and Jieru

helped prepare the sample. Basically they cultured the tissues and stained the cells.

5.3 Background and noise in living Rpb9 cells

5.3.1 FCS experiment

Fluorescence correlation spectroscopy [56] is based on the fact that the number of

the particles following Brownian motion in the defined optical focal space is randomly

changing around the average number. FCS experiment will provide the information of

the concentration of the sample by analysis the fluorescence intensity fluctuations using

temporal autocorrelation. The Picoharp software could realize the temporal

autocorrelation using the signal from the APD. The FCS experiment was performed to

estimate the rough concentration inside the stained cells.

5.3.2 Background and noise reduction with STED

It is convincing that STED reduces the noise efficiently and enables the detection

of single molecule at high concentrations in vitro. While, whether the same case

applies to that in vivo required further examination inside cells. In order to do this, the

time traces upon 70% red excitation with\without periodical 400mW xy and 700mW z

STED were taken inside the nuclei of SiR fully stained Rpb9 cells. From the time

89

trace in Figure 5.3, we have a sense that the noise was suppressed efficiently with

STED.

Figure 5.3: Time trace inside the Rpb9 cell stained with SiR. The STED was on after about 30

seconds.

By adjusting the amount of SiR dyes for the Staining, we could harvest cells

labeled with SiR at different concentrations. Furthermore, even with the same staining

condition, the cells would be characterized with a variety of background level. Hence,

We adopted two concentrations for the staining and ended up with a range of

background levels. The noise reduction was proportional to the background level

reduction in Figure 5.4 drawn by Alexandros, basically the same as in vitro. With

400mW xy and 700mW z STED, the SNR would improve by 3-4 folds, in agreement

with the results from the in vitro solutions. The time traces were measured close to the

center of the nuclei, ensured by looking at the images on the side port camera. Firstly,

the image of cells was centered in xy and the beam was focus on the surface by

moving the stage. Secondly, the stage was moved up 2-3um based on the estimation

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Figure 26 Background level and noise reduction with 400mW xy and 700mW z doughnut

These results further validate that the STED could be a powerful tool to achieve

single molecule detection inside living cells which usually feature with high

concentrations and noisy background.

5.4 Pol II accumulates at sites of active nascent transcription(wide field imaging)

The bright field image demonstrated the shape, especially the nuclei of the cell; the

purple image indicated the observed cell was active; the bright green image referred to

tdPCP-EGFP; the red image was suited for visualizing the TetR-RFP; the blue image

denoted the SiR-Rpb1. Strikingly, from the multi-color images of the same active

nuclei, we could clearly visible SiR-Rpb1 foci co-localized with TetR-RFP and

tdPCP-EGFP. As SiR-Rpb1, TetR-RFP, tdPCP-EGFP correspond to Pol II, promoter

and mRNA, we could conclude from the co-localized spots that the accumulation of

Pol IIs as well as mRNAs at active promoter. All the wide field images in Figure 5.6

were taken by Alexandros.

Figure 5.6: From left to right: bright field, BFP, tdPCP-EGFP, RFP, tetR-RFP and SiR-Rpb1

92

5.5 Studying the Pol II using STED setup (methods)

5.5.1 STED alignment

To align the setup, first of all, the beams needed to be overlapped. The same

procedure as before, a dense layer of Atto647N molecules was prepared to align the

APD. The position of the APD was optimized by maximizing its count rate. Then the

xz scanning images help examine and align the z doughnut. Similarly, the immobile

single Atto647N on the PEG coverslip was scanned in xy to optimize the xy doughnut.

With the beams overlapped, the PBS was placed to reflect the emitted fluorescence to

the CCD camera. The PBS was adjusted to ensure the emission not to reach the edge

of field of view based on the reflected beam from the gold coverslip or the

fluorescence of Atto647N solution. Next, the focus on the CCD camera was localized

by maximizing the brightness of single immobile Atto647N. The focus of red

excitation beam and the minimum of the STED beams could be obtained and usually

they should be nearly at the same place. Once the minimum of the STED beams were

known, a single Atto647N was brought to the minimum with the STED periodically

on to quantify the remaining signal. Typically, at least 80% signal would remain with

100mw xy and 400mw z doughnut, seen in figure 5.7.

93

Figure 27 Calibrate the STED setup by measuring the intensity of single Atto647N with and

without STED

5.5.2 Quad-view camera registration

The alignment of the STED mostly related to the red channel. In most cases, the

experiment would be performed in a way that the SiR image is investigated while

GFP spot is tracked. Namely, the GFP spot is tracked to ensure the SiR spot at the

minimum of the STED beams. Hence, the registration between the red channel and

green channel is realized by the 100nm bead, which would be excited by both red and

blue laser. The bead was put at the previously localized minimum of STED or

maximum of the red beam under red excitation, while the corresponding positions in

blue channel were recorded. The averaged position from at least 5 different beams

would be in fact the locked target position.

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5.5.3 GFP tracking

One great challenge of living cell imaging at single molecule level is that the sites

of interest as well as the transcription factors are moving around instead of immobile

in the nuclei. To overcome this, we came up with the idea of tracking the gene sites to

a specific location to make sure the transcription factors at the minimum of STED.

Figure 5.8: GFP spots on the CCD camera used for tracking. (Scale bar 1um)

A 21 by 21 pixels region of interest of which the target position was often at the

center was monitored and fitted by the 2D Gaussian embedded in Labview. Next, the

fitted centroids were used to control the stage adjustment via PID. The PID controller

continuously calculated an error value as the difference between a desired set

point and a measured process centroids of the tracked spots. The controller attempts to

minimize the error over time by adjustment of the fitted centroids to a new value

determined by a weighted sum. The data acquisition including the fitting and data

95

recording could be as fast as 30 frames per seconds, which is of great importance to

look deep into some dynamics at ultra-fast rate. The GFP spot is normally quite bright

and unlikely to get bleached in a short time, making it a good candidate for tracking.

For the cell imaging, the GFP spots were first found and moved close to the blue

beam focus through the eyepiece and the CCD camera at the side port. Switching the

dichroic to reflect the emitted photons to the cofocal CCD camera, we were able to

track GFP spots through PID in labview while the images of polymerases were

recorded in binary files.

In figure 5.9, the GFP tracking was examined in terms of the stability of the

position. A tracking accuracy of 20-30nm in both x and y was achieved, enabling us

to zoom into the right target region.

Figure 5.9: GFP tracking accuracy

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5.5.4 Data analysis (extracting the time traces)

Offline analysis was performed in matlab to extract the images from the binary

files. I calculated the time intensity trace from a region with a radius of 4 pixels, here

1pixel was equivalent to 67nm and the region size was almost an Airy disc. A typical

time trace would have an initial peak value and decay to the plateau (figure 5.10). The

bleached part was mainly the polymerase spots while the plateau came from the

remaining background.

Figure 5.10: The time trace (right) extracted from the CCD camera image (left). The red circle

indicated the selected area for the trace

5.6 Colocalization of Pol II and mRNA

5.6.1 Check the Colocalization using the initial images with the background

subtracted from the quad-view camera

From the quad view wide field image, I could visualize there were RFP, GFP and

SiR Spots showing up roughly at the same positions in the nuclei. As the limitation of

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accuracy of the wide field images, little is known on how well the mRNA and

Polymerase spots were colocalized. In order to get the images of the polymerase spot,

I subtracted the images of the first few frames when the polymerase hadn‟t got

bleached from the background, which was the averaged image of 100-300 frames at

the plateau. The centroid of the bleached polymerase spots was obtained by 2D

Gaussian fitting. A few ten cell images were investigated. By comparison of the

centroids between the bleached polymerase spots and the GFP spots used for tracking,

we had a sense of how well mRNA and polymerase spots were colocalized.

According to the tdPCP-EGFP and SiR-Rpb1 coordinates of multiple transcription

sites in figure 5.11, tdPCP-EGFP and SiR-Rpb1 are within 22-25nm and 30-33nm

r.m.s. from the set-point respectively. Considering the tracking had an accuracy of

20-30 nm and the background could fluctuate, I come to the conclusion that the two

kinds of spots colocalized even better than the measured results.

Figure 5.11: tdPCP-EGFP and SiR-Rpb1 coordinates of multiple transcription sites from 3

independent experiments (red, blue, black symbols).

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5.6.2 Check the Colocalization by direct 3D scanning images.

5.6.2.1 Find the GFP spots and roughly center the spots.

The eyepiece and wide field images provided a large field of view to help find

and roughly locate the spots. With the 50:50 beam splitter that split the emitted

fluorescence, half to the APDs and half to the CCD camera, we were able to easily

switch between the cofocal CCD quad view image and the scanning cofocal image

using APD. The spots were moved to the predefined position by checking the GFP

images on the CCD camera. Next, as scanning starting point located at (6um, 1um)

based on the trajectory the stage was moved in x by 6um and in y by1 um so that the

spot would be roughly centered at the scanned regions.

5.6.2.2 3D real time imaging using FPGA

To directly visualize the colocalization between GFP and SiR spots, a 2by2um

region was scanned in 0.2 second and after each scanning the stage moved in z by a

500nm step.

The signals from the two APDs, together with the markers from E712, were

transferred to FPGA in which the online analysis could be performed simultaneously.

In total, 5 frames were scanned in the space. The 3D cofocal images in figure 5.12

demonstrated how the GFP spot and SiR spot looked like

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Figure 5.12: The two color cofocal scanning images in 3D. 2umby2um in xy and 0.5um step size in

z. The pixel size is 40nm.

One out of the five frames closest to the best focus was selected. In the case of

figure 5.12, the forth frame was selected. Both a selected 9 by 9 pixel (1pixel =40nm)

regions containing the GFP and SiR spots from that frame were fitted with 2D

Gaussian. Relative xy coordinates of tdPCP-EGFP and SiR-Rpb1 from n=42 images

reached to the similar conclusion that the mRNA and Polymerase spots were

colocalized within 50-60nm. We shall notice that the fitted results would be noisy

partially because the background was not homogonous inside the cells, especially for

the polymerases.

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5.7 Bleaching traces for counting Pol II numbers

It is proved that the Polymerases would accumulate at the transcription sites and

colocalize with the promoter and mRNAs. However, the exact number of the

polymerases accumulating at the transcription sites remains unknown and is quite an

interesting question featuring the transcription initiation. Even we could directly

visualize the spot above the background, we are not able to directly count how many

copies there are in the spots. We recognized that while GFP locked, the polymerases

would gradually get beached with time. Thus we could easily figure out the initial

intensity and the level of the plateau the difference of which would be from the

bleached Polymerase.

101

5.7.1 Calibrate the step size of the bleaching time traces using less stained sample

The intensity of single Polymerase was calibrated using the less stained cell

samples, which was 20-25% of maximal SiR staining level. For less stained cells, the

background was lower and less noisy, and intensity traces usually contained one or

two step event.

Figure 5.14: Time trace from less stained sample with red only

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Figure 5.15: Time trace from less stained sample with 100mw xy and 400mw z doughnut

2 and 3 steps could be identified with the same size in the trace from Figure 5.14

and 5.15 respectively. I took the images with Alexandros, and then I wrote the scipt

for initial data analysis such as extract the time traces and selected the traces

demonstrating bleaching steps, Alexandros quantified the step size and distributions

shown in Figure 5.16. Collecting the intensity traces from the less stained cells, I

derived the intensity of single polymerase. A step size of 320±115A.U with 100mW

xy and 400mW z STED and 242±83A.U with red only was obtained by fitting the

intensity histogram. The step size would be smaller with STED since the imperfection

of the minimum of the doughnut beams would lead to the loss of some signal.

Figure 5.16: steps quantified from the less stained sample with and without STED

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5.7.2 Count Pol II numbers using fully stained sample

Next I took the time trace from the fully stained sample right after from the less

stained sample to avoid the unnecessary differences such as the alignment change. As

we expected, no such clear steps could be identified in the time trace from the fully

stained sample due to the noisy background and fast bleaching time.

Figure 28 bleaching time trace with STED from fully stained cells

Figure 5.18: bleaching time trace with red excitation only from fully stained cells

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Instead, the bleached intensity over the intensity of single polymerase gave the

number of polymerase bleached. The 4 experiments with fully-labeled samples

indicated average 17±3 and 13±2 detected Pol II molecules with excitation only and

with excitation + STED respectively. The detected number with STED was tightly

lower, possibly resulting from the finer excitation volume with doughnut STED beams.

Figure 5.19: Number of Pol II molecules detected at the transcription site in four independent

experiments with fully-labeled samples.

5.7.3 Compare the bleaching traces with\without STED (2 fold SNR improvement)

STED could reduce the background fluctuations and enable single-molecule

detection sensitivity. I employed STED to quantify the number of Pol II molecules that

accumulate at the transcription sites. Comparing the bleaching traces with and without

STED, we found the traces with STED were less noisy. We can clearly identify the

bleaching step with STED. When using STED, single-molecule bleaching steps were

105

also evident in traces of fully stained samples, while very few steps were identifiable

in traces without STED. In Figure 5.20 and 5.21, the SNRs with STED were obviously

above the SNR with red excitation only for both 100% labeled cells and 20-25%

labeled cells. Alexandros helped quantified the SNR for both samples and compared

them in the situation with and without STED. The signal to noise ratio was superior

(2-fold) when using STED than with excitation only, an improvement commensurate

with a 2-fold reduction in background level and noise for the STED configuration in

use. Furthermore, the SNR obtained in fully stained samples with STED is comparable

to SNR in the under-labeled samples without STED, highlighting the ability of STED

to enable single-molecule detection at 4-5-fold elevated concentrations in live cells.

Figure 5.20: SNR vs step size from 100% labeled sample

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Figure 5.21: SNR vs step size from 20-25% labeled sample

5.8 Quantification of Pol II at transcription sites

We observed 17±3 Pol II molecules accumulating at the transcription sites

according to the bleaching time traces. A typical time trace had an initial peak value,

and then gradually decayed to a stationary plateau. This indicated that the observed

Pol II molecules at transcription site did not all take part in transcription, part of the

accumulated Pol II molecules were possible stably bound to other genomic regions

and/or other nuclear structures near-by. To further verify this, we measured the

bleaching time trace while the blue laser was displaced to track the transcription site

536nm away instead of at exact transcription site. In such case, the molecules

bleached would not involve with transcription, which needed to be subtracted to

quantify the actual Pol II numbers participating transcription. Figure 5.22 (right)

drawn by Alexandros demonstrated a smaller initial peak and slowly bleaching trace

0.536um away from the transcription site.

107

Figure 5.22: SiR-Rpb1 signal with tdPCP- EGFP locked at the transcription site and 0.536µm away

5.8.1 The initial peak of the traces at transcription sites and 536nm away

Figure 5.23: Distribution of S+Bi, Bi and Bd

Quantifying many bleaching traces from transcription sites and 0.536um away

from transcription sites, as demonstrated in Figure 5.23 we obtained the distributions

of the S+Bi, Bi and Bd, from which we could derive the exact number of Polymerase

involved in transcription.

SiR-Rpb1 Signal (A.U.)

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5.8.2 The decay time of the traces at transcription sites and 536nm away

As seen in the bleaching traces, Bi 0.5um away would bleach more slowly

compared to that at transcription site, which contained signal S as well as Bi.

Alexandros suggested using the stretched exponential function

e

, where y0, A0, x0, t0

and a stand for the plateau level, the bleached amplitude, bleaching starting point,

decay constant time and stretched constant, to fit the amplitude and bleaching time for

at the transcription site and 0.536um away. As we expected, the bleaching time was

much slower 0.536um away since fewer Polymerases leaded to a slower bleaching.

(Figure 5.25)

0 200 400 600 800 1000

-10000

0

10000

20000

30000

40000

50000

60000

70000

Co

un

t

frame(10fps)

Modeltime_decay (User)

Equationy0+A0*exp(-((x-x0)/t0)^a)

Reduced Chi-Sqr

3.5665E6

Adj. R-Square 0.93519

Value Standard Error

B y0 16865.43745 173.42802

B A0 46976.57869 1299.63951

B x0 243 0

B t0 51.32669 2.53303

B a 0.60984 0.02215

Figure 5.24: Stretched exponential fitting of the time trace at transcription site

109

0 200 400 600 800 1000

0

10000

20000

30000

40000

50000

60000

Co

un

t

frame(10fps)

Modeltime_decay (User)

Equationy0+A0*exp(-((x-x0)/t0)^a)

Reduced Chi-Sqr

7.56335E6

Adj. R-Square 0.64982

Value Standard Error

B y0 30316.87899 466.32286

B A0 14694.84446 1060.42146

B x0 218 0

B t0 196.17923 14.77932

B a 0.98909 0.12062

Figure 5.25: Stretched exponential fitting of the time trace 0.536um away from transcription site

Figure 5.26: The decay time at transcription sites and 0.536um away

5.8.3 The images of the Polymerase 0.536um away from transcription sites

When the GFP was locked 0.536um away from the transcription site with xy

doughnut, surprisingly we found that after everything was bleached at transcription

site a spot showed up at the corresponding position in the red channel colocalized

Decay Time (sec)

at trxn site 0.5um away

15

0

110

with the tracked GFP (Figure 5.27), while when the GFP locked at transcription sites,

no such spot appeared (Figure 5.28). Hence we drew a conclusion that the spots

(circled in red) should be the Polymerase accumulated at the transcription site. When

tracked at transcription site, the Polymerase spot together with the diffusing

background would focus at the same place on the CCD camera and it was impossible

to resolve them. On the contrast, when the blue laser was 0.536 um shifted and the

GFP was locked 0.536 um away, we had a chance to visualize the spot 0.536um away

from the center in spite of the background focus at the center. The GFP spot was

locked 0.536um away, which was roughly the dimension of the xy doughnut. This

accounted for the Polymerase spots 0.536um away didn‟t get bleached much with xy

doughnut. The xy doughnut increased the resolution and reduced the noise. With and

only with the xy doughnut, we were able to visualize these spots 8 pixels away.

Figure 5.27: Four 21by21 pixels ROIs with the Polymerase spots showing up 8 pixels away (red

circle region) when the GFP was locked at the corresponding place colocalized with the red

2 4 6 8 10 12 14 16 18 20

2

4

6

8

10

12

14

16

18

20

2 4 6 8 10 12 14 16 18 20

2

4

6

8

10

12

14

16

18

20

2 4 6 8 10 12 14 16 18 20

2

4

6

8

10

12

14

16

18

20

2

4 6 8

1

1

111

circled region after bleaching.

Figure 5.28: Four 21by21 pixels ROIs when the GFP was locked at transcription site after

bleaching

5.8.4 The actual Pol II numbers involved in transcription

Comparing the bleaching traces at transcription sites and 536nm away from the

transcription sites, we observed that the initial peak 536nm away from the

transcription sites was roughly 1/3 that at the transcription sites and the decay time

was slower, indicating: (i) the SiR-Rpb1 signal from the transcription site consists of

67±1.6% Pol II accumulating at the mini-gene (S) and 33±1.6% immobile background

(Bi); (ii) the total Pol II background consists of 37±3.5% immobile (Bi) and 63±3.5%

diffusing (Bd) background (mean±SD, n=3 experiments, >10 transcription sites each).

112

5.9 Size of the Pol II spots at transcription sites

Next, as we concluded roughly 10 Pol II involved with transcription at the sites,

we wondered in which way these Pol II were organized. Measuring the sizes of these

Pol II spots would give some information in terms of this question.

At certain circumstances, a cylindrical lens would be set before the CCD camera

to realize 3D tracking. The orientation of the cylindrical lens was adjusted to

introduce additional phase in x axis. To verify this, the image of a bead or a molecule

was indeed elongated in one axis. Figure 5.29 demonstrated the σx , σy at different z

places and the σx /σy was no longer roughly 1 at all z positions, instead the σx /σy

would be sensitive to the z position. The parameter of σx /σy could be set to a fixed

value via PID to track the object in a fixed z positions, usually the focal plane. With

the cylindrical lens, I repeated the calibration and got the results shown in Figure

5.30.

Comparing the (σx, σy) distributions of the Pol II spots with that of the beads, we

found that the distributions of the Pol II spots were quite spreading even with STED,

making it difficult to quantify the sizes of the Pol II spots. This is not surprising as the

fitting of the images over very noise background would be quite noisy even the

averaged background was subtracted. In addition, the tracking held an accuracy of

roughly 30nm. What‟s more, the images could be from out of focus, resulting in the

113

blurring of the images. All these proved that it was not a decent way to quantify the

sizes by 2D Gauss fitting of the images with averaged background subtracted.

5.9.1 Measure the sizes of the initial images with the background subtracted from

the quad-view camera referring to nanoparticle size calibration

As mentioned before, we could visualize the images on the quad-view CCD

camera. By subtracting the averaged background from the stationary plateau part, we

ended up with the images of the bleached Pol II. At the condition of 10 fps or 30 fps

acquisition rate and 6.7uW excitation power, the Pol II usually lasted a few frames

before they started getting bleached. Then we were able to obtain the size of these

images by 2D Gauss fitting. In order to relate the sizes of the images on the quad view

CCD camera to the actual sizes of the Pol II spots, we calibrated the image sizes of

100nm, 200nm and 500nm beads as well as single immobile Atto647N molecules.

The beads were bound on the glass coverslip nonspecifically. The bead was found and

centered in xy, and then was placed 500nm or 1umbelow the focus. I tried taking data

for 2000 frame at a frame rate of 10 fps and 30 fps. The stage was move up by 50nm

or 100nm every 50 frames. While data acquisition, the images were fitted using 2D

Gauss in labview and the parameters were saved in matlab. In the end, we obtained

the σx and σy of the bead images at different focal planes. For each size, the images

of 6 beads were acquired. And the (σx , σy) distributions were very similar from bead

114

to bead. Furthermore, the (σx , σy) distributions were quite separate for 100nm,

200nm and 500nm beads.

5.9.1.1 Calibrate the image sizes on the quad-view camera using 100,200,500nm

nanoparticles without z tracking

Figure 5.29 illustrated how σx, σy and

changed with the z positions. 100nm

bead was imaged while the stage moved 100nm up roughly every 100 frames. σx, σy

were close to symmetrical below and above the focus and

was close to 1, as we

expected. The same trends applied to the 200nm and 500nm beads

Figure 5.29: Sigma_x, sigma_y and sigma_y/sigma_x at different z positions

In addition, I investigated the σx, σy at different xy positions at focal plane to

ensure that σx, σy would not vary much with xy positions since the positions in xy at

different z planes may shift. It turned out the σx, σy kept the same in spite of the

position shifted in xy (figure 5.30).

0 200 400 600 800 1000 1200 1400 1600 1800 20001.5

2

2.5

3

3.5

4

sig

ma

x

0 200 400 600 800 1000 1200 1400 1600 1800 20001.5

2

2.5

3

3.5

4

sig

ma

y

0 200 400 600 800 1000 1200 1400 1600 1800 20000

0.5

1

1.5

2

2.5

frame

sig

ma

y/sig

ma

x

115

Figure 5.30: Sigma_x, sigma_y and sigma_y/sigma_x at different xy positions and focal plane

The stage moved in xy by 100nm nearly every 100frames. The 2D Gauss fitting

provided the values of σx, σy as well as the coordinates. As a matter of fact, the

coordinates shown in figure 5.31 can be utilized to quantify the actual pixel size. The

100nm step size corresponds to 1.5 pixels, namely, 1 pixel on the quad view CCD

camera stands for nearly 67nm at the stage.

0 200 400 600 800 1000 1200 1400 1600 1800 20001.5

2

2.5

3

3.5

4

sig

ma

x

0 200 400 600 800 1000 1200 1400 1600 1800 20001.5

2

2.5

3

3.5

4

sig

ma

y

0 200 400 600 800 1000 1200 1400 1600 1800 20000

0.5

1

1.5

2

2.5

frame

sig

ma

y/sig

ma

x

116

Figure 5.31: the positions where the sigma_x and sigma_y were investigated

The scatter plot of (σx, σy) at different z plane of 100nm, 200nm and 500nm

served as a good reference of the profiles of an object with certain size. For instance,

the (σx, σy) of a 200nm object would follow the 200nm beads curve (red in figure

5.32). The (σx, σy) was calibrated at different z positions with a range of over 1um,

which was more than enough to characterize the size of an object by its image on the

CCD camera.

5 10 15 20

5

10

15

20

X(pixel)

Y(p

ixel)

117

Figure 5.32: (sigma_x, sigma_y) of 100nm 200nm and 500nm beads at different z

5.9.1.2 Calibrate the image sizes on the quad-view camera using 100,200,500nm

nanoparticles with z tracking

At certain circumstances, a cylindrical lens would be set before the CCD camera

to realize 3D tracking. The orientation of the cylindrical lens was adjusted to

introduce additional phase in x axis or in y axis. The image of a bead or a molecule

was ensured to be elongated in one axis. Figure 5.33 demonstrated the σx , σy at

different z places and the σx /σy was no longer roughly 1 at all z positions, instead the

σx /σy would be sensitive to the z position.

118

Figure 5.33: Sigma_x, sigma_y and sigma_y/sigma_x at different z positions with the cylindrical

lens

The parameter of σx /σy could be set to a fixed value via PID to track the object

in a fixed z positions, usually the focal plane. And the corresponding value of σx /σy

is roughly 0.95. Furthermore, 0.1 value change of σx /σy equates roughly 50nm in z.

Typically the stage could be tracked with σx /σy in a range of 0.2, suggesting a good z

tracking accuracy with the help of the cylindrical lens.

With the cylindrical lens, I repeated the calibration with 100nm, 200nm and

500nm beads, and I got the results shown in Figure 5.34.

Compared to that without the cylindrical lens, the (σx , σy) distributions were

significantly more spreading over the space, denoting a profile more sensitive to the z

0 200 400 600 800 1000 1200 1400 1600 1800 2000

2

4

6

sig

ma

x

0 200 400 600 800 1000 1200 1400 1600 1800 2000

2

4

6

sig

ma

y

0 200 400 600 800 1000 1200 1400 1600 1800 20000

1

2

frame

sig

ma

y/sig

ma

x

119

position. Thus, the distribution of the 100nm, 200nm and 500nm could be referred to

by the CCD images with z tracking applied.

Figure 5.34: (sigma_x, sigma_y) of 100nm 200nm and 500nm beads at different z with cylindrical

lens

5.9.1.3 Compare the sizes of the Pol II images with that of the nanoparticles

Comparing the (σx, σy) distributions of the Pol II spots with that of the beads, we

found that the distributions of sizes of the Pol II spots were quite spreading even with

STED, making it difficult to quantify the sizes of the Pol II spots. This is not

surprising as the fitting of the images over very noise background would be quite

noisy even the averaged background was subtracted. In addition, the tracking held an

accuracy of roughly 30nm. What‟s more, the images could be from out of focus,

120

resulting in the blurring of the images. All this accounted for the inaccurate

quantification of the sizes by 2D Gauss fitting of the images with averaged

background subtracted. With STED on, a smaller spot was expected and indeed from

the distributions in figure 5.36 (with STED) and figure 5.35(red only) we observed

that the σx and σy tended to be smaller with STED. In summary, the calibrations with

100nm, 200nm and 500nm beads suggested the potential to quantify the sizes of the

Pol II spots as the profiles 100nm, 200nm and 500nm showed remarkable differences.

However, the spreading distributions of sizes of the Pol II spots couldn‟t lead to a

certain value for the spot size.

Figure 5.35: the (σx, σy) of the Pol II images with beads (no cylindrical lens, red only)

121

Figure 5.36: Compare the (σx, σy) of the Pol II images with beads (no cylindrical lens, with STED)

Figure 5.37: compare the (σx, σy) of the Pol II images with beads (with cylindrical lens, red only)

122

5.9.2 Check the sizes of the initial images with the background subtracted from the

quad-view camera with xy doughnut of different power

As we know, the convolution of two Gaussian functions (f, g) is also Gaussian.

And the width of convolution could be described as

√

Assuming that the Pol II spot is Gaussian shaped, the width is denoted

as 𝑜 , the point spread function of the excitation beam is also

approximately Gaussian. Hence we derive the width of the detected images on the

CCD to be

√

Where is the width of the PSF.

The image size could be measured by fitting the background subtracted

image, while could be calibrated with single Atto647N. More importantly, the

effective PSF could be modified by progressively increasing xy doughnut (0 ~

400mW). The scanning images provided us with the widths of the effective PSFs for

0mW, 100mW, 200mW, 400mW xy doughnut, as well as the remaining signal at the

minimum of the doughnut beam. After intense discussion, we adopted this method

brought by Alexandros for quantified the size of Pol II cluster.

123

5.9.2.1 Resolution, Signal remaining with different power xy doughnut

Basically, 2um by 2um regions containing immobile Atto647N molecules were

scanned in 8 seconds with red excitation as well as progressively increasing xy

doughnut. The resolution with 0mW, 100mW, 200mW and 400mW xy doughnut

provided a range of , enabling the fitting of equation

regarding , , In addition, the remaining signals were

calibrated for each STED power by comparing the peak values of the images of the

molecules.

STED power(mW) Resolution sigma(nm) Signal remaining

0 113.221541 1

100 82.10521 0.889349

200 76.63468 0.799906

400 64.8654 0.74167

Table 5.1: Resolution and signal remaining change with STED power

5.9.2.2 Fit the size with calibrated data

With a range of from different xy doughnut and the derived equation, we

could unveil the transcription spot size. The resolution and the signal remaining in

table 2 needed to be included for calculating the actual PSF. Moreover, a (first-order)

correction factor of e

, where =32nm is the r.m.s of the tracking

displacement from the set point, was conducted to compensation of the tracking

124

fluctuation. For each STED power, over 10 transcription sites were measured. Data

from two experiments using clone 5 cells (open symbols) and one experiment using

clone 6 cells (solid symbols) are shown in Figure 5.38. Applying the derived

relationship to the measured and , we estimated the transcription size to be

85±11nm. The data analysis in Figure 5.38 was done by Alexandros.

Figure 5.38: Relative signal (top) and relative background level (bottom) locked at transcription

site with different PSFs

125

5.9.3 Measure the Pol II sizes by 3D scanning

A third method was performed to measure the Pol II spot size. Instead of using

the images on the quad-view CCD camera, I directly scanned the 3D images of the

transcription spots with\without STED beams. At first, the GFP spots were found

through the eyepiece and the wide field images on the side port CCD camera. Second,

the GFP spots were moved close to the scanning center based on the wide field images

on the side port CCD camera and the cofocal image quad-view CCD camera. The 50:50

PBS could split the fluorescence, half to the APDs, and half to the quad-view camera.

In the end, five 2umby2um frames were scanned and after each scanning the stage

moved up in z by 500nm with yellow and red excitations in 1 second. One of five

frames at the best focus was selected.

Figure 5.39: The confocal image of mRNA and Pol II spots without STED (top) and with STED

(down)

126

The colocalized spots were featured and a region of 9 pixels containing the spot

was fitted 2D Gaussian peak functions with sigma s sx, sy and r.m.s. size s was

estimated as √ . Median values are 168nm and 98nm for excitation and

excitation + STEDxy respectively, indicating an r.m.s size strxn site~40-50nm,

according to the equation

. The non-uniform background and the

possible out of focus case leaded to the uncertainty of the results.

Figure 5.40: The fitted SiR sizes with and without STEDxy

5.10 Dynamics of the Pol II transcription cycle at the CMV mini-gene.

In order to investigate the dynamics of the Pol II transcription, the experiments

designed by Alexandros were performed.

5.10.1 Pol II recovery experiment

5.10.1.1 Bleaching the Pol II and retake the bleaching traces after certain minutes

127

The accumulation of the Pol II at transcription remains a matter of debate.

Different models are raised to explain the existence of the accumulated Pol II cluster.

One of model postulated the accumulated Pol II cluster to be spatially restricted

compartments that prevent exchange with the nucleoplasm and facilitate multi-round

transcription through local Pol II recycling. The Pol II recovery experiment was

performed to verify this mode

Figure 5.41: The time trace (left) for bleaching and the trace (right) the recovery after 16minutes

First, I exposed the Pol II spots under high excitation beam for 500 frames to bleach

them. After certain time, usually ranging from 2-20 minutes, I investigated the intensity

at the transcription site again to check if the bleached spots would recover. In Figure

5.41, the left trace revealed the bleaching process with red laser; on the other hand, the

right trace demonstrated the recovery by rebleaching the SiR spot after 16 minutes. If

there were no recovery, no signal would be detected from the second bleaching trace. In

0 50 100 150 200-0.5

0

0.5

1

1.5

2

2.5x 10

4

0 50 100 150-5000

0

5000

10000

15000

20000

128

such case, the bleaching trace would be flat. Indeed I saw the intensity went back. The

experiment was performed both at 25 degree and 37 degree, and we cared more about

the situation at d37 degree which was the actual temperature suited for the cells.

However, I didn‟t harvest enough data to quantify the recovery rate due to the long

waiting time during which the GFP spots would be excited with laser multiple times and

was likely to disappear or be too dime to be tracked.

Figure 5.42: The recovery percentage with time from many traces at 37 degree (left) and 25

degree (right)

5.10.1.2 10-minute recovery time trace with low duty cycle excitation

To obtain more intensity points at different time, I took a 10-minute recovery time

trace with low duty cycle excitation beam so that we ended with much more points from

the same site. The low excitation power and low duty cycle ensured that the photon

bleaching was minimized, which was examined by applying the low duty cycle

0

0.2

0.4

0.6

0.8

1

0 10 20 30

0

0.2

0.4

0.6

0.8

1

0 10 20

129

excitation beam to an unbleached Pol II spot. tdPCP-EGFP was tracked using a

0.02-0.08µW 490nm beam. SiR-Rpb1 was initially probed with a 0.1µW 642nm

beam, bleached with 0.9µW for ~10 sec and recovery was then monitored every 10 sec

for 0.4 sec with 0.1µW. At this condition, the intensity would stay horizontal for at least

10 minutes. The pulses of the recovery trace was picked and organized with the time

coordinate. Overall, 9 traces were taken, from which we clearly observed that the

bleached Pol II cluster would recovery up to 60% of its initial intensity. The exponential

fitting of the combined 7 traces indicated that in general the recovery time is 289

seconds (Figure 5.45). With the quantified number of Polymerase at transcription site,

we came to the conclusion that the recovery rate was 2±1 Pol II/minute.

Figure 5.43: Recovery trace

Figure 5.44: Recovery trace 2

130

Figure 5.45: exponential fit of 9 recovery trace

5.10.1.3 3D scanning images before and after bleaching as well as after 10-minute

recovery

The 50:50 PBS enabled us to switch between the quad view CCD camera used

for tracking and time trace acquisition and APDs suited for cofocal scanning. For

direct visualization of the recovery, the 3D scanning cofocal images were investigated.

Firstly, we checked the initial image of the SiR spot before we bleached it using high

excitation laser. Secondly, the 3D images were taken right after the bleaching to make

sure that the SiR spots were totally bleached. In the end, after about 8 minutes, we

rescanned the same volume to see if the spot reappeared at the expected. From figure,

we actually saw a spot reappeared colocalized with the GFP spot and at the same

positions as the initial SiR spot, providing substantial evidence the recovery of the Pol II

cluster. The recovery would not take place if the Polymerases were recycling, meaning

the recycling model probably would not stand.

131

Figure 5.46: 1.2µm×1.2µm scans of a single transcription site, showing tdPCP-EGFP and SiR-Rpb1

before bleaching, after bleaching and after ~10 minutes recovery

5.10.2 Adding triptolide and flavopiridol that block initiation and promoter-proximal

pause release

Other models are proposed that the accumulation of the Pol II clusters could be

from closely spaced molecules engaged in transcription elongation or dynamic

self-assemblies that potentiate transcription (pre)-initiation through molecular

crowding effects. To further investigate this, we observed the behaviors of the Pol II

spots when treated with drugs to inhibit the transcription. Triptolide, an inhibitor of

the ATPase of the general transcription factor TFIIH, blocking initiation and

flavopiridol, a kinase inhibitor specific for the CDK9 subunit of P-TEFb, blocking

release of promoter-proximal pausing and transition to elongation were trialed.

DMSO without drugs was set as the control. For these three conditions: triptolide,

flavopiridol and DMSO, the evolvements of the Pol II cluster with time were record.

We took data in two ways. First, during the recording of 6000-frame images right

after adding the drug or DMSO, we found and tracked transcription sites from

different cells, for each of which, we bleached the Pol II spots with high excitation

power in a few hundred frames. In the other way, for the 6000-frame images we

132

focused on a single transcription site and obverse the changes with low duty time

excitation laser as before that would not bleach the spots. Hence, the intensity trace

behaviors would not represent the photon bleaching of the fluorophore but the

effects of the drugs.

5.10.2.1 Take bleaching traces with time information recorded from many cells using

high excitation power

Typically, we could investigate 3~6 cells in the 6000 frame periods (10fps). In

Figure 5.47, the nearly 300 frames bleaching traces with 0.9µW red excitation of 6

cells at different time was recorded. I could extract 6 points regarding the bleached

intensity change with time.

Figure 5.47: A 6000 frame time trace in which the bleaching of 6 cells was recorded

As time went by, lower intensities were to be bleached, revealing the blocking

effect of the drug. Dynamics of SiR-Rpb1 after addition of 10µM flavopiridol 10µM

0 1000 2000 3000 4000 5000 6000-2000

0

2000

4000

6000

8000

10000

12000

14000

frame(100ms)

Cou

nt

133

triptolide and 0.1% v/v DMSO in Figure 5.48 drawn by Alexandros unveiled that

SiR-Pol II accumulation at individual transcription sites gradually decreased over the

course of ~3-5 minutes after adding the drug.

Figure 5.48: Dynamics of SiR-Rpb1 after addition of 10µM flavopiridol 10µM triptolide and 0.1%

v/v DMSO

5.10.2.2 Take the 8-minute trace with low excitation power from each cells

Additionally, the 6000-frame images at a single transcription site with drug

treatment with low duty and low power excitation suggested the same conclusion.

SiR-Rpb1 was monitored for 0.4 sec every 10 sec using a weak probe beam (~0.1 µW

at 642nm). The extracted pulses from the 6000-frame images together with the

corresponding time stamp was fitted by single exponential function. The fitted results

from multiple transcription sites showed a decay times of 162±71 sec and 242±148 sec

(mean±S.D.) for flavopiridol (n=8) and triptolide (n=15) respectively.

134

Figure 5.49: The decay traces with drug treatment with the GFP locked

Figure 5.50: The fitted decay time from multiple transcription site with drug treatment

5.10.2.3 Data analysis and Conclusion

Based on the intensity traces, the Pol II clusters with drugs disappeared in 3-5

minutes, arguing against a stable pool of immobilized Pol II in a pre- existing nuclear

scaffold or “factory” that persists in the absence of ongoing transcription. The results

also disagree with proposals for molecular crowding effects taking place before

initiation.

135

Bibliography

[1] Abbe, Ernst, "Über einen neuen Beleuchtungsapparat am Mikroskop" [About a

New Illumination Apparatus to the Microscope]. Archiv für mikroskopische

Anatomie (in German). Bonn, Germany: Verlag von Max Cohen & Sohn. 9: 469–

480. (1873)

[2] Abbe, Ernst, "Über die Bedingungen des Aplanatismus der Linsensysteme" [The

Conditions Under Which Aplanatism of the Lens Systems]. Jenaische Zeitschrift

für Naturwissenschaft (in German). Jena, Germany: Verlag Von Gustav Fischer:

129–142. (1878).

[3] H.A.BETHE, Theory of Diffraction by Small Holes, The Physical Review Second

Series) Vol. 66, Nos.7 AND 8 (1944)

[4] Yasushi Oshikane, Toshihiko Kataoka, Mitsuru Okuda, Seiji Hara, Haruyuki

Inoue & Motohiro Nakano, Observation of nanostructure by scanning near-field

optical microscope with small sphere probe, Science and Technology of

Advanced Materials, ISSN: 1468-6996 (Print) 1878-5514 (Online) (2016)

[5] A. I. Sabra , Theories of Light from Descartes to Newton, Cambridge University

Press. (cf. Pavlos Mihas, Use of History in Developing ideas of refraction, lenses

and rainbow, p. 5, Demokritus University, Thrace, Greece.) (1981)

[6] DANIELAXELROD, Cell-Substrate Contacts Illuminated by Total Internal

Reflection Fluorescence, THE JOURNAL OF CELL BIOLOGY " VOLUME 89

136

(1981)

[7] Marvin Minsky: Microscopy Apparatus. US Patent 3.013.467, filed 7. November

1957, granted 19. December 1961.

[8] P. J. VERVEER, M. J. GEMKOW & T. M. JOVIN, A comparison of image

restoration approaches applied to three-dimensional confocal and wide-field

fluorescence microscopy, Journal of Microscopy, Vol. 193, Pt 1, January 1999,

pp. 50–61.

[9] Denk W.; Strickler J.H.; Webb W.W, Two-photon laser scanning fluorescence

microscopy. Science. 248 (4951): 73–76. (1990).

[10] Fritjof Helmchen, Winfried Denk, Deep tissue two-photon microscopy, Nature

Methods, 2005; DOI:10.1038/NMETH818

[11] George Komis, Martin Mistrik, Olga Šamajová, Miroslav Ovecˇka, Jiri Bartek &

Jozef Šamaj, Superresolution live imaging of plant cells using structured

illumination microscopy, Nature, 23 July 2015; doi:10.1038/n prot.2015.083

[12] Dyba, M.; Hell, S. W, Photostability of a Fluorescent Marker Under Pulsed

Excited-State Depletion through Stimulated Emission. Applied Optics. 42 (25):

5123–5129. (2003)

[13] Stefan W. Hell and Jan Wichmann, Breaking the diffraction resolution limit by

stimulated emission: stimulated-emission-depletion fluorescence microscopy,

OPTICS LETTERS / Vol. 19, No. 11 / June 1, 1994

[14] Benjamin Harke, Jan Keller, Chaitanya K. Ullal, Volker Westphal, Andreas

Schönle and Stefan W. Hell, Resolution scaling in STED microscopy, Vol. 16,

137

No. 6 / OPTICS EXPRESS(2008)

[15] Michael J Rust, Mark Bates& Xiaowei Zhuang, Sub-diffraction-limit imaging by

stochastic optical reconstruction microscopy (STORM), Nature Methods

DOI:10.1038/NMETH929(2006)

[16] Eric Betzig, † George H. Patterson, Rachid Sougrat, O. Wolf Lindwasser, Scott

Olenych, Juan S. Bonifacino, Michael W. Davidson, Jennifer

Lippincott-Schwartz, Harald F. Hess, Imaging Intracellular Fluorescent Proteins

at Nanometer Resolution, VOL 313 SCIENCE (2006)

[17] Patterson, George et al, Superresolution Imaging Using Single-Molecule

Localization. Annual review of physical chemistry 61 (2010): 345–367. PMC.

(2017)

[18] Rupprecht, Jean-François, Ariadna Martinez-Marrades, and Gilles Tessier.

Trade-offs between spatial and temporal resolutions in stochastic

super-resolution microscopy techniques. arXiv preprint

arXiv:1607.04190 (2016).

[19] Kirschner, Marc, and John Gerhart. Evolvability. Proceedings of the National

Academy of Sciences 95.15 (1998).

[20] http://www.nature.com/scitable/topicpage/gene-expression-14121669, Nature

Education (2010)

[21] Campbell, Elizabeth A., et al. Structural mechanism for rifampicin inhibition of

bacterial RNA polymerase. Cell 104.6 (2001)

[22] Liang, Peng, and Arthur B. Pardee. Differential display of eukaryotic messenger

138

RNA by means of the polymerase chain reaction. Science 257.5072 (1992).

[23] Conaway, Ronald C., and Joan Weliky Conaway. General initiation factors for

RNA polymerase II. Annual review of biochemistry 62.1 (1993)

[24] Orphanides, George, Thierry Lagrange, and Danny Reinberg. The general

transcription factors of RNA polymerase II. Genes & development 10.21 (1996)

[25] Vassylyev, Dmitry G., et al. Crystal structure of a bacterial RNA polymerase

holoenzyme at 2.6 Å resolution. Nature 417.6890 (2002)

[26] Allison, Lori A., et al. Extensive homology among the largest subunits of

eukaryotic and prokaryotic RNA polymerases. Cell 42.2 (1985)

[27] Dynan, William S., and Robert Tjian. Control of eukaryotic messenger RNA

synthesis by sequence-specific DNA-binding proteins.Nature 316.6031 (1985).

[28] Wansink, Derick G., et al. Fluorescent labeling of nascent RNA reveals

transcription by RNA polymerase II in domains scattered throughout the

nucleus. Journal of Cell Biology 122 (1993)

[29] Cisse, Ibrahim I., et al. Real-time dynamics of RNA polymerase II clustering in

live human cells. Science 341.6146 (2013)

[30] Jackson, Dean A., et al. Visualization of focal sites of transcription within human

nuclei. The EMBO journal 12.3 (1993)

[31] Sutherland, Heidi, and Wendy A. Bickmore. Transcription factories: gene

expression in unions?. Nature Reviews Genetics 10.7 (2009)

[32] Kimura, Hiroshi, Kimihiko Sugaya, and Peter R. Cook. The transcription cycle of

RNA polymerase II in living cells. J Cell Biol 159.5 (2002)

139

[33] Jackson, Dean A., et al. Numbers and organization of RNA polymerases, nascent

transcripts, and transcription units in HeLa nuclei. Molecular biology of the

cell 9.6 (1998).

[34] Carter, David RF, Christopher Eskiw, and Peter R. Cook. Transcription

factories. Biochemical Society Transactions 36.4 (2008).

[35] Ron, David, and Joel F. Habener. CHOP, a novel developmentally regulated

nuclear protein that dimerizes with transcription factors C/EBP and LAP and

functions as a dominant-negative inhibitor of gene transcription. Genes &

development 6.3 (1992)

[36] Feuerborn, Alexander, and Peter R. Cook. Why the activity of a gene depends on

its neighbors. Trends in Genetics 31.9 (2015)

[37] Marenduzzo, Davide, Kieran Finan, and Peter R. Cook. The depletion attraction:

an underappreciated force driving cellular organization. J Cell Biol 175.5

(2006).

[38] Zhao, Ziqing W., et al. Spatial organization of RNA polymerase II inside a

mammalian cell nucleus revealed by reflected light-sheet superresolution

microscopy. Proceedings of the National Academy of Sciences 111.2 (2014)

[39] Cisse, Ibrahim I., et al. Real-time dynamics of RNA polymerase II clustering in

live human cells. Science 341.6146 (2013)

[40] Dragomir, Sever S and Cerone, Pietro and Sofo, Anthony, Some Remarks on the

Midpoint Rule in Numerical Integration. RGMIA research report collection.

(1998)

140

[41] Richards, B., and E. Wolf. Electromagnetic diffraction in optical systems. II.

Structure of the image field in an aplanatic system. Proceedings of the Royal

Society of London A: Mathematical, Physical and Engineering Sciences. Vol.

253. No. 1274. The Royal Society (1959).

[42] http://cnqo.phys.strath.ac.uk/research/quantum-theory-of-light/optical-angular-m

omentum/producing-light-with-oam/ CNQO (2017).

[43] Rolf T. Borlinghaus, Dr.

http://www.leica-microsystems.com/science-lab/unlimited-resolution-sted/ Leica

Science Lab (2017)

[44] Enderlein, Jörg. Theoretical study of detection of a dipole emitter through an

objective with high numerical aperture. Optics letters 25.9 (2000)

[45] Rittweger, Eva, et al. STED microscopy reveals crystal colour centres with

nanometric resolution. Nature Photonics 3.3 (2009)

[46] Pertsinidis, A., Zhang, Y. & Chu, S. Subnanometre single-molecule localization,

registration and distance measurements. Nature 466, 647-51 (2010).

[47] Ha T, Tinnefeld P. Photophysics of Fluorescence Probes for Single Molecule

Biophysics and Super-Resolution Imaging. Annual review of physical chemistry.

(2012).

[48] Vicidomini, Giuseppe, et al. Sharper low-power STED nanoscopy by time

gating. Nature methods 8.7 (2011)

[49] Leutenegger, Marcel, Christian Eggeling, and Stefan W. Hell. Analytical

description of STED microscopy performance. Optics express 18.25 (2010)

141

[50] Liu, Hui Qing, and Alfredo Huete. A feedback based modification of the NDVI to

minimize canopy background and atmospheric noise. IEEE Transactions on

Geoscience and Remote Sensing 33.2 (1995)

[51] L. Bertalanffy, General system theory, G. Braziller New York, (1988)

[52] Wu, Shizhang. Noise Canceling Headphones. (2008).

[53] Donnert, G. et al. Macromolecular-scale resolution in biological fluorescence

microscopy. Proc Natl Acad Sci U S A 103, 11440-5 (2006).

[54] Selvin, Paul R. The renaissance of fluorescence resonance energy

transfer. Nature Structural & Molecular Biology 7.9 (2000)

[55] Lohman, Timothy M., and Peter H. von Hippel. Kinetics of Protein-Nucleic Acid

Interactions: Use of Salt Effects to Probe Mechanisms of Interactio. Critical

Reviews in Biochemistry 19.3 (1986)

[56] Magde, Douglas, Elliot Elson, and Watt W. Webb. Thermodynamic fluctuations

in a reacting system—measurement by fluorescence correlation spectroscopy.

Physical Review Letters 29.11 (1972)