Advanced fluorescence fluctuation spectroscopy with pulsed interleaved excitation [Elektronische Ressource] / Matthias Höller

Matthias Hoeller

Informations

• Publié par: ludwig-maximilians-universitat_munchen
• Publié le: 01 janvier 2011
• Nombre de lectures: 25
• Langue: Deutsch
• Poids de l'ouvrage: 6 Mo

Extrait

Dissertation zur Erlangung des Doktorgrades
der Fakultät für Chemie und Pharmazie
der Ludwig-Maximilians-Universität München
Advanced Fluorescence Fluctuation Spectroscopy
with Pulsed Interleaved Excitation
Development and Applications
Matthias Höller
aus
Bergisch Gladbach
2011Erklärung
Diese Dissertation wurde im Sinne von §13 Abs. 3 bzw. 4 der Promotionsordnung
vom 29. Januar 1998 von Herrn Professor Lamb betreut.
Ehrenwörtliche Versicherung
Diese Dissertation wurde selbständig, ohne unerlaubte Hilfe erarbeitet.
München, am 07.01.2011
(Unterschrift des Autors)
Dissertation eingereicht am: 11. Januar 2011
1. Gutachter: Prof. Dr. Don C. Lamb
2.hter: Prof. Dr. Christoph Bräuchle
Mündliche Prüfung am: 03. Februar 2011Contents
1 Introduction 1
2 Fluorescence 3
2.1 Fundamentals . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 3
2.2 Fluorescence Anisotropy . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 5
2.3 Förster Resonance Energy Transfer . . . . . . . . . . . . . . . . . . . . . . . . . 5
3 Optical system 7
3.1 Confocal Microscopy . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 7
3.2 The Confocal Principle . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 7
3.3 Pulsed Interleaved Excitation . . . . . . . . . . . . . . . . . . . . . . . . . . . . 9
3.4 Confocal setups used for this work . . . . . . . . . . . . . . . . . . . . . . . . . 9
3.4.1 Two-color PIE multi-parameter setup . . . . . . . . . . . . . . . . . . . 10
3.4.2 Three-color PIE scanning setup . . . . . . . . . . . . . . . . . . . . . . . 10
4 Fluorescence Fluctuation Spectroscopy 15
4.1 Basic Considerations . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 15
4.2 Number&Brightness Analysis . . . . . . . . . . . . . . . . . . . . . . . . . . . . 16
4.2.1 Detector noise correction . . . . . . . . . . . . . . . . . . . . . . . . . . 17
4.3 The Photon Counting Histogram . . . . . . . . . . . . . . . . . . . . . . . . . . 19
4.3.1 Theory of photon detection: Mandel’s formula . . . . . . . . . . . . . . 19
4.3.2 From Mandel to number and brightness . . . . . . . . . . . . . . . . . . 20
4.3.3 Multiple fluorescent species . . . . . . . . . . . . . . . . . . . . . . . . . 23
4.4 Fluorescence-Intensity Distribution Analysis . . . . . . . . . . . . . . . . . . . . 24
4.4.1 The Point Spread Function in FIDA . . . . . . . . . . . . . . . . . . . . 24
4.4.2 The Generating F . . . . . . . . . . . . . . . . . . . . . . . . . . 26
4.5 Fluorescence Cumulant Analysis . . . . . . . . . . . . . . . . . . . . . . . . . . 28
4.5.1 Moments . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 28
4.5.2 Factorial moments . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 29
4.5.3 Moment generating function . . . . . . . . . . . . . . . . . . . . . . . . . 29
4.5.4 Factorial moment generating function . . . . . . . . . . . . . . . . . . . 30
4.5.5 Cumulants and the CGF . . . . . . . . . . . . . . . . . . . . . . . . . . . 31
4.5.6 Factorial Cumulants and the FCGF . . . . . . . . . . . . . . . . . . . . 32
4.5.7 Derivation of FCA . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 32
4.6 Fluorescence Correlation Spectroscopy . . . . . . . . . . . . . . . . . . . . . . . 35
4.6.1 The autocorrelation function . . . . . . . . . . . . . . . . . . . . . . . . 35
4.6.2 Fluorescence intensity time dependence . . . . . . . . . . . . . . . . . . 37
4.6.3 Model for linear regression . . . . . . . . . . . . . . . . . . . . . . . . . . 37
4.6.4 Triplet states . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 41
4.7 Fluorescence Cross-Correlation Spectroscopy . . . . . . . . . . . . . . . . . . . 42
4.7.1 The cross-correlation function . . . . . . . . . . . . . . . . . . . . . . . . 42
I4.8 Scanning FCS . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 44
4.8.1 The Scanning correlation curve . . . . . . . . . . . . . . . . . . . . . . . 45
4.9 Raster Image Correlation Spectroscopy . . . . . . . . . . . . . . . . . . . . . . . 47
4.10 Burst Analysis . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 48
4.10.1 Burst analysis with PIE . . . . . . . . . . . . . . . . . . . . . . . . . . . 50
4.11 Photon Distribution Analysis . . . . . . . . . . . . . . . . . . . . . . . . . . . . 52
4.11.1 PDA theory . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 52
5 Method Development with PIE 56
5.1 Scanning FCS with PIE . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 56
5.2 PIE-Scanning FCS in aqueous solution . . . . . . . . . . . . . . . . . . . . . . . 57
5.3 Raster Image Correlation Spectroscopy with PIE . . . . . . . . . . . . . . . . . 60
5.4 PIE-RICS in aqueous solution . . . . . . . . . . . . . . . . . . . . . . . . . . . . 61
5.5 in living cells . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 64
5.6 Application to Ca 1.4 channel domain . . . . . . . . . . . . . . . . . . . . . . . 69v
5.7 to Ca 1.4 channel ICDI subdomain . . . . . . . . . . . . . . . . . . 71v
5.8 Discussion . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 73
6 Dnmt1 75
6.1 Introduction . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 75
6.2 Sample preparation . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 76
6.3 Excitation power analysis . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 76
6.4 GFP/GBP . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 78
6.5 Dnmt1:DNA complexes . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 82
6.6 Dnmt1 cross-correlation . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 86
6.7 DNA cross-correlation . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 88
6.8 Further investigation of the Dnmt1:DNA bonds . . . . . . . . . . . . . . . . . . 91
6.9 Discussion . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 93
7 Burst Analysis study of conformational changes of BiP 96
7.1 BiP . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 96
7.2 Sample preparation . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 97
7.3 Monitoring BiP conformations . . . . . . . . . . . . . . . . . . . . . . . . . . . 99
7.3.1 Inter-domain communication . . . . . . . . . . . . . . . . . . . . . . . . 101
7.3.2 Conformation of the lid . . . . . . . . . . . . . . . . . . . . . . . . . . . 102
7.4 The co-chaperone ERdJ3 . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 105
7.5 Discussion . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 109
8 Summary and Outlook 112
A Spectra 114
A.1 Two-color PIE multi-parameter setup . . . . . . . . . . . . . . . . . . . . . . . 115
A.2 Three-color PIE scanning setup . . . . . . . . . . . . . . . . . . . . . . . . . . . 116
A.2.1 Dnmt1 configuration . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 116
A.2.2 RICS . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 118
B Computer code 119
B.1 Number & Brightness . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 119
B.2 Fast correlation algorithm [1] . . . . . . . . . . . . . . . . . . . . . . . . . . . . 120
IIB.3 Fit algorithm for PCH and FIDA . . . . . . . . . . . . . . . . . . . . . . . . . . 121
B.4 Cumulant Analysis . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 123
III1 Introduction
Life, in the biophysicist’s eye, is governed by the interactions of an enormously complex net-
work of biomolecules, including DNA, RNA, and proteins. All organisms can be regarded as
mere accumulations of cells, and the cellular life cycle is maintained by their molecular ma-
chinery, constituted, to a large extent, by proteins. The genetic information that encodes this
machinery, and therefore life as such, is encoded in DNA. It is then transcribed into messenger
RNA by interaction with RNA polymerase and other proteins. Subsequently, it is translated
into a vast diversity of proteins suited to perform all different kinds of functions in a cell (and
even outside). Therefore, studying proteins, their cellular localizations, their interactions with
other biomolecules, and properties such as their conformational states leads to a deeper under-
standing of how life works on a cellular level.
Today, thanks to the recent decades of technological advances, many biochemical and bio-
physical methods are available to investigate proteins. For example, their internal structure,
formed by the spatial arrangement of peptide chains, can be resolved by X-ray crystallography
or nuclear magnetic resonance spectroscopy; electron microscopy or optical super-resolution
techniques show their localization within a cell; gel electrophoresis yields information about
their abundance and about binding partners; ultracentrifugation or mass spectroscopy can
measure their molecular weight; and force spectroscopy probes the strength of intra- or inter-
molecular bonds.
Few of these methods, however, allow the scientist to observe a protein in its natural envi-
ronment, a living cell. Crystallization, for example, alters the energy landscape and therefore
the tertiar