Molecular dynamics of biomolecules, like proteins and nucleic acids dictate essential biological processes allowing life to function. They are involved in a vast number of cellular tasks including DNA replication, genetic recombination, transcription and translation, as well as signalling, translational motion, structure formation, biochemical synthesis, immune response, and many more. Developed over billions of years by evolution they constitute fine-tuned networks modulated by temperature and regulatory mechanisms. A better understanding of the thermodynamic fundamentals of inter- and intramolecular conformational changes can shed light on the underlying processes of diseases and enables the transfer of biological architectures, properties and compositions to nanotechnological applications.
Dynamics of biomolecules occur on a wide range of timescales covering more than twelve orders of magnitude. Fluorescence spectroscopy techniques like time-correlated single photon counting (TCSPC), fluorescence correlation spectroscopy (FCS), and immobilized and freely diffusing single-molecule Förster resonance energy transfer (FRET) spectroscopy represent powerful tools monitoring the dynamics at different ranges within this large span of timescales.
However, a unified approach covering all biological relevant timescales remains a goal in the field of fluorescence spectroscopy. This would comprise a methodological workflow for qualitative and quantitative analysis of biomolecular dynamics ranging from nanoseconds to hours.
In this work, a custom built single-molecule fluorescence spectroscopy set-up was constructed combining confocal single-molecule FRET spectroscopy with TCSPC, FCS and fluorescence anisotropy techniques for multiparameter fluorescence detection (MFD). The set-up allows the complementary observation of single-molecules over an extensive timescale ranging from fast reconfiguration dynamics of polymers (nanoseconds) to slow membrane protein folding (hours) without the need of molecular synchronization. Freely diffusing molecules enable high throughput measurements in heterogeneous membrane-mimetic and denaturing environments.
Additionally, routines for data acquisition and processing were developed followed by the elaboration of a methodological workflow for the qualitative and quantitative analysis of biomolecular dynamics. Finally, the applicability was demonstrated on a big diversity of biological systems (DNA hairpin, Holliday junction, soluble and membrane proteins) in aqueous, membrane-mimetic and denaturing environments covering conformational dynamics from nanoseconds to hours.:Chapter 1: Introduction
Chapter 2: Dynamics of Biomolecules
2.1 Dynamics of Nucleic Acids
2.1.1 DNA Hairpin Dynamics
2.1.2 Dynamics of Holliday Junctions
2.2 Dynamics of Proteins
2.2.1 Model Systems of Protein Folding
Chapter 3: Fundamentals of Fluorescence Spectroscopy
3.1 Basics of Fluorescence
3.2 Förster Resonance Energy Transfer (FRET)
Chapter 4: Multiparameter Fluorescence Detection
4.1 Single-Molecule FRET Spectroscopy
4.1.1 Confocal Microscopy
4.1.2 Freely Diffusing Molecules
4.1.3 Fluorescence Spectroscopy
4.2 Time-Correlated Single-Photon Counting (TCSPC)
4.3 Pulsed Interleaved Excitation (PIE)
4.4 Fluorescence Anisotropy
4.5 Fluorescence Correlation Spectroscopy (FCS)
4.6 MFD Setup
4.7 Analysis Software
Chapter 5: Analysis of Molecular Dynamics
5.1 Sub-Microseconds – Peptide Chain Dynamics
5.1.1 Identification of Peptide Chain Dynamics
5.1.2 Quantification of Peptide Chain Dynamics
5.1.3 Discussion
5.2 Microseconds – Dynamics of Barrier Crossing
5.2.1 Maximum Likelihood Estimation of the Transition-Path Time
5.2.2 Quantification of the Upper Bound of the Transition-Path Time
5.2.3 Discussion
5.3 Milliseconds – Fast Protein Folding Dynamics
5.3.1 Correlation of the Relative Donor Lifetime (τD(A) / τD(0)) with FRET Efficiency (E)
5.3.2 Burst-Variance Analysis (BVA)
5.3.3 FRET-Two-Channel Kernel-Based Density Distribution Estimator (FRET-2CDE)
5.3.4 Estimation of the Conformational Relaxation Rate using Bin-Time Analysis
5.3.5 Extracting Folding Kinetics using the Three-Gaussian (3G) Approximation
5.3.6 Dynamic Probability Distribution Analysis (dPDA)
5.3.7 Folding and Unfolding Rate Estimation using a Maximum-Likelihood Estimator
5.3.8 Discussion
5.4 Milliseconds to Seconds – Stacking Dynamics of DNA
5.4.1 Identification of Dynamics on the Recurrence Timescale
5.4.2 Quantification of Dynamics on the Recurrence Timescale
5.4.3 Discussion
5.5 Minutes to Hours – Slow Protein Folding Dynamics
5.5.1 Identification of Slow Protein Folding Dynamics
5.5.2 Quantification of Slow Protein Folding Dynamics
5.5.3 Discussion
Chapter 6: Conclusion and Outlook
Chapter 7: Appendices
7.1 Derivation of Equation 4.6 (inspired by Daniel Nettels)
7.2 Protein sequences
7.3 Identification of dynamics on the recurrence timescale
7.4 Dependency of psame on the sample concentration
7.5 Effect of fluorescence quenching on MFD parameters
Chapter 8: References / Biomoleküle, wie Proteine und Nukleinsäuren, sind essentielle Bausteine des Lebens und permanent an biologischen Prozessen beteiligt. Innerhalb der Zelle nehmen sie eine Vielzahl von Aufgaben wahr, darunter DNA-Replikation, genetische Rekombination, Transkription und Translation, sowie Signalübertragung, Transport, Strukturbildung, biochemische Synthese und Immunreaktion.
In Milliarden von Jahren evolutionärer Entwicklung wurden biomolekulare Prozesse immer feiner aufeinander Abgestimmt. Um den zugrundeliegenden Mechanismus von Krankheiten besser zu Verstehen und um die einzigartigen Eigenschaften und Kompositionen biologischer Systeme auf nanotechnologische Anwendungen übertragen zu können, ist es unbedingt notwendig ein besseres Verständnis thermodynamischer Grundlagen inter- und intramolekularer Konformationsänderungen zu erlangen.
Dabei finden sich Dynamiken von Biomolekülen über eine Zeitskale von mehr als zwölf Größenordnungen verteilt. Fluoreszenzspektroskopietechniken, wie zeitkorrelierte Einzel-photonenzählung (TCSPC), Fluoreszenzkorrelationsspektroskopie (FCS), und Förster-Resonanzenergietransfer (FRET)–Spektroskopie von immobilisierten und frei diffundierenden Molekülen, stellen leistungsfähige Werkzeuge dar, welche es ermöglichen Dynamiken in der den Techniken entsprechenden Zeitskala aufzulösen.
Dennoch, besteht der dringende Bedarf nach einer einheitlichen Methode, der in der Fluoreszenzspektroskopie alle biologisch relevanten Zeitskalen abdeckt. Dies würde einen methodischen Workflow für die qualitative und quantitative Analyse der biomolekularen Dynamik von Nanosekunden bis Stunden bedeuten.
In dieser Arbeit wurde ein speziell angefertigter Multiparamter-Fluoreszenzspektroskopie-Aufbau konstruiert, welcher die konfokale Einzelmolekül-FRET-Spektroskopie mit den TCSPC-, FCS- und Fluoreszenz-Anisotropie-Techniken kombiniert. Der Aufbau ermöglicht die Beobachtung komplementärer Eigenschaften von Einzelmolekülen über eine umfangreiche Zeitskala hinweg. Dynamiken von schnell rekonfigurierenden Polymeren (Nanosekunden) bis hin zu langsam faltenden Membranproteinen (Stunden) sind ohne molekulare Synchronisation möglich. Darüber hinaus, ermöglicht der Einsatz frei diffundierender Moleküle einen hohen Messdurchsatz und die Anwendung heterogener membranmimetischer und denaturierender Lösungen.
Zusätzlich wurden Routinen zur Datenerfassung und -verarbeitung entwickelt, gefolgt von der Ausarbeitung eines methodischen Workflows zur qualitativen und quantitativen Analyse von biomolekularen Dynamiken. Abschließend wurde die Anwendbarkeit an fünf biologischen Modelsystemen (DNA-Haarnadel, Holliday-Junction, lösliche und Membranproteine) in wässrigen, membranmimetischen und denaturierenden Umgebungen demonstriert und alle biologisch relevanten Zeitskalen von Nanosekunden bis Stunden abgedeckt.:Chapter 1: Introduction
Chapter 2: Dynamics of Biomolecules
2.1 Dynamics of Nucleic Acids
2.1.1 DNA Hairpin Dynamics
2.1.2 Dynamics of Holliday Junctions
2.2 Dynamics of Proteins
2.2.1 Model Systems of Protein Folding
Chapter 3: Fundamentals of Fluorescence Spectroscopy
3.1 Basics of Fluorescence
3.2 Förster Resonance Energy Transfer (FRET)
Chapter 4: Multiparameter Fluorescence Detection
4.1 Single-Molecule FRET Spectroscopy
4.1.1 Confocal Microscopy
4.1.2 Freely Diffusing Molecules
4.1.3 Fluorescence Spectroscopy
4.2 Time-Correlated Single-Photon Counting (TCSPC)
4.3 Pulsed Interleaved Excitation (PIE)
4.4 Fluorescence Anisotropy
4.5 Fluorescence Correlation Spectroscopy (FCS)
4.6 MFD Setup
4.7 Analysis Software
Chapter 5: Analysis of Molecular Dynamics
5.1 Sub-Microseconds – Peptide Chain Dynamics
5.1.1 Identification of Peptide Chain Dynamics
5.1.2 Quantification of Peptide Chain Dynamics
5.1.3 Discussion
5.2 Microseconds – Dynamics of Barrier Crossing
5.2.1 Maximum Likelihood Estimation of the Transition-Path Time
5.2.2 Quantification of the Upper Bound of the Transition-Path Time
5.2.3 Discussion
5.3 Milliseconds – Fast Protein Folding Dynamics
5.3.1 Correlation of the Relative Donor Lifetime (τD(A) / τD(0)) with FRET Efficiency (E)
5.3.2 Burst-Variance Analysis (BVA)
5.3.3 FRET-Two-Channel Kernel-Based Density Distribution Estimator (FRET-2CDE)
5.3.4 Estimation of the Conformational Relaxation Rate using Bin-Time Analysis
5.3.5 Extracting Folding Kinetics using the Three-Gaussian (3G) Approximation
5.3.6 Dynamic Probability Distribution Analysis (dPDA)
5.3.7 Folding and Unfolding Rate Estimation using a Maximum-Likelihood Estimator
5.3.8 Discussion
5.4 Milliseconds to Seconds – Stacking Dynamics of DNA
5.4.1 Identification of Dynamics on the Recurrence Timescale
5.4.2 Quantification of Dynamics on the Recurrence Timescale
5.4.3 Discussion
5.5 Minutes to Hours – Slow Protein Folding Dynamics
5.5.1 Identification of Slow Protein Folding Dynamics
5.5.2 Quantification of Slow Protein Folding Dynamics
5.5.3 Discussion
Chapter 6: Conclusion and Outlook
Chapter 7: Appendices
7.1 Derivation of Equation 4.6 (inspired by Daniel Nettels)
7.2 Protein sequences
7.3 Identification of dynamics on the recurrence timescale
7.4 Dependency of psame on the sample concentration
7.5 Effect of fluorescence quenching on MFD parameters
Chapter 8: References
| Identifer | oai:union.ndltd.org:DRESDEN/oai:qucosa:de:qucosa:31103 |
| Date | 31 August 2018 |
| Creators | Hartmann, Andreas |
| Contributors | Schlierf, Michael, Diez, Stefan, Technische Universität Dresden |
| Source Sets | Hochschulschriftenserver (HSSS) der SLUB Dresden |
| Language | English |
| Detected Language | English |
| Type | doc-type:doctoralThesis, info:eu-repo/semantics/doctoralThesis, doc-type:Text |
| Rights | info:eu-repo/semantics/openAccess |
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