Single Molecule Statistics and the Polynucleotide Unzipping Transition

We present an extensive theoretical investigation of the mechanical unzipping of double-stranded DNA under the influence of an applied force. In the limit of long polymers, there is a thermodynamic unzipping transition at a critical force value of order 10 pN, with different critical behavior for homopolymers and for random heteropolymers. We extend results on the disorder-averaged behavior of DNA's with random sequences to the more experimentally accessible problem of unzipping a single DNA molecule. As the applied force approaches the critical value, the double-stranded DNA unravels in a series of discrete, sequence-dependent steps that allow it to reach successively deeper energy minima. Plots of extension versus force thus take the striking form of a series of plateaus separated by sharp jumps. Similar qualitative features should reappear in micromanipulation experiments on proteins and on folded RNA molecules. Despite their unusual form, the extension versus force curves for single molecules still reveal remnants of the disorder-averaged critical behavior. Above the transition, the dynamics of the unzipping fork is related to that of a particle diffusing in a random force field; anomalous, disorder-dominated behavior is expected until the applied force exceeds the critical value for unzipping by roughly 5 pN.Comment: 40 pages, 18 figure

Manipulating a single adsorbed DNA for a critical endpoint

We show the existence of a critical endpoint in the phase diagram of unzipping of an adsorbed double-stranded (ds) polymer like DNA. The competition of base pairing, adsorption and stretching by an external force leads to the critical end point. From exact results, the location of the critical end point is determined and its classical nature established.Comment: 6 pages, 5 figures, Published versio

Single DNA conformations and biological function

From a nanoscience perspective, cellular processes and their reduced in vitro imitations provide extraordinary examples for highly robust few or single molecule reaction pathways. A prime example are biochemical reactions involving DNA molecules, and the coupling of these reactions to the physical conformations of DNA. In this review, we summarise recent results on the following phenomena: We investigate the biophysical properties of DNA-looping and the equilibrium configurations of DNA-knots, whose relevance to biological processes are increasingly appreciated. We discuss how random DNA-looping may be related to the efficiency of the target search process of proteins for their specific binding site on the DNA molecule. And we dwell on the spontaneous formation of intermittent DNA nanobubbles and their importance for biological processes, such as transcription initiation. The physical properties of DNA may indeed turn out to be particularly suitable for the use of DNA in nanosensing applications.Comment: 53 pages, 45 figures. Slightly revised version of a review article, that is going to appear in the J. Comput. Theoret. Nanoscience; some typos correcte

Computing DNA Duplex Instability Profiles Efficiently with a Two-State Model: Trends of Promoters and Binding Sites

Background: DNA instability profiles have been used recently for predicting the transcriptional start site and the location of core promoters, and to gain insight into promoter action. It was also shown that the use of these profiles can significantly improve the performance of motif finding programs. Results: In this work we introduce a new method for computing DNA instability profiles. The model that we use is a modified Ising-type model and it is implemented via statistical mechanics. Our linear time algorithm computes the profile of a 10,000 base-pair long sequence in less than one second. The method we use also allows the computation of the probability that several consecutive bases are unpaired simultaneously. This is a feature that is not available in other linear-time algorithms. We use the model to compare the thermodynamic trends of promoter sequences of several genomes. In addition, we report results that associate the location of local extrema in the instability profiles with the presence of core promoter elements at these locations and with the location of the transcription start sites (TSS). We also analyzed the instability scores of binding sites of several human core promoter elements. We show that the instability scores of functional binding sites of a given core promoter element are significantly different than the scores of sites with the same motif occurring outside the functional range (relative to the TSS). Conclusions: The time efficiency of the algorithm and its genome-wide applications makes this work of broad interest to scientists interested in transcriptional regulation, motif discovery, and comparative genomics

Dynamics of DNA Breathing and Folding for Molecular Recognition and Computation

This thesis is centered on the development of the molecular beacon, as a new DNA probe for DNA genotyping, D N A computation and biophysical studies of DNA conformations. Molecular beacons are single-stranded DNA molecules that form a stem-and-loop structure. A fluorophore and a quencher are grafted at their two ends to report their conformations: when the molecular beacon is closed, fluorophore and quencher are held in close proximity and the fluorescence is quenched; when the molecular beacon is open, fluorophore and quencher are far apart, and the fluorescence is restored. Molecular beacons are ideal DNA probes coupling conformational switch with fluorescence signal turning-ON. We use molecular beacons to study the molecular recognition of single-stranded DNA (ssDNA) oligonucleotide. We present a thermodynamic diagram to show that structural constraints make the molecular beacon highly sensitive to the presence of mismatches in its target. We introduce a sequence sensitivity parameter to quantitatively compare different DNA probes, and propose an algorithm to optimally tune the probe\u27s structure for enhanced sequence discrimination. Logic gates (OR and AND gates) using molecular beacons are designed to carry most elementary molecular computations. The conformational changes associated with such computations can be used to concatenate many chemical reactions, and carry out complex molecular computations. Molecular beacons are also ideal probes to study DNA secondary structures and their fluctuations. We develop the fluorescence correlation spectroscopy (FCS) technique to monitor the dynamics of relaxation of DNA conformational fluctuations. We first measure the opening and closing timescales of DNA hairpin-loops. Activation barriers for opening and closing for different loop lengths and sequences are analyzed to better account for the stability of DNA secondary structures. A sequence dependent rigidity of ssDNA has been discovered, and analyzed in terms of base stacking. We then use F C S to study the dynamics of double-stranded DNA (dsDNA) breathing modes with synthetic DNA constructs. The analysis of the base pairing fluctuation dynamics, monitored by fluorescence, unravels lifetimes of breathing modes ranging from 1/us to 1ms. Long-range distortions of the d s DNA have been unraveled for purine-rich sequences, of relevance to the specificity of transcription initiation in prokaryotes

In silico single strand melting curve: a new approach to identify nucleic acid polymorphisms in Totiviridae

CpG-island promoters of developmental genes are unmethylated. DNA methylation state of CpG islands overlapping and surrounding the promoter region of Pax3 (a) and Pax7 (b) genes in myogenic (MB, MT, MF) and non-myogenic samples (ESC). CpG islands are indicated in green and regions analysed by sodium bisulphite sequencing are shown in red. Each circle represents a CpG dinucleotide and its distance to the gene TSS is indicated below. The colour gradient represents the percentage of methylation indicated in the legend. Abbreviations: ESC, embryonic stem cell; MB, myoblast; MT, myotube; MF, myofiber; TSS, transcription start site. c. DNA methylation state of -5 kb distal regulatory region for MyoD was analysed by sodium bisulphite sequencing in ESC and myoblast samples, and represented as above. (PDF 171 kb

Single-molecule experiments in biological physics: methods and applications

I review single-molecule experiments (SME) in biological physics. Recent technological developments have provided the tools to design and build scientific instruments of high enough sensitivity and precision to manipulate and visualize individual molecules and measure microscopic forces. Using SME it is possible to: manipulate molecules one at a time and measure distributions describing molecular properties; characterize the kinetics of biomolecular reactions and; detect molecular intermediates. SME provide the additional information about thermodynamics and kinetics of biomolecular processes. This complements information obtained in traditional bulk assays. In SME it is also possible to measure small energies and detect large Brownian deviations in biomolecular reactions, thereby offering new methods and systems to scrutinize the basic foundations of statistical mechanics. This review is written at a very introductory level emphasizing the importance of SME to scientists interested in knowing the common playground of ideas and the interdisciplinary topics accessible by these techniques. The review discusses SME from an experimental perspective, first exposing the most common experimental methodologies and later presenting various molecular systems where such techniques have been applied. I briefly discuss experimental techniques such as atomic-force microscopy (AFM), laser optical tweezers (LOT), magnetic tweezers (MT), biomembrane force probe (BFP) and single-molecule fluorescence (SMF). I then present several applications of SME to the study of nucleic acids (DNA, RNA and DNA condensation), proteins (protein-protein interactions, protein folding and molecular motors). Finally, I discuss applications of SME to the study of the nonequilibrium thermodynamics of small systems and the experimental verification of fluctuation theorems. I conclude with a discussion of open questions and future perspectives.Comment: Latex, 60 pages, 12 figures, Topical Review for J. Phys. C (Cond. Matt

Modeling biomolecules: interactions, forces and free energies

La biología ha sido tradicionalmente una ciencia cualitativa. El principal problema que presenta es que trata con sistemas muy complejos, mucho más que las moléculas de las que se ocupa la química, o que muchos sistemas físicos. Sin embargo, en los últimos años, hemos sido testigos de un desarrollo enorme hacia planteamientos cuantitativos para resolver problemas biológicos, impulsado principalmente por el desarrollo de diversas técnicas avanzadas en biofísica, o por la emergencia de las herramientas computacionales. En particular, en biofísica computacional, dado un determinado problema a estudiar, la estrategia es proponer un modelo que describa el comportamiento de nuestro sistema y realizar simulaciones numéricas sobre este modelo. Este planteamiento presenta una dificultad principal que es la elección de la escala a la cual realizamos nuestro modelo. Es necesario llegar a un compromiso entre el nivel de detalle y la capacidad computacional de que disponemos. Así, modelos muy detallados son capaces de proporcionar información de gran resolución, sin embargo sólo para sistemas moleculares de tamaño limitado, con propiedades que se manifiesten a escalas temporales cortas. Si necesitamos tratar con sistemas de mayor tamaño, o nos interesan propiedades que se manifiestan en escalas temporales mayores, es necesario identificar cuáles son los grados de libertad relevantes para nuestro sistema y despreciar el resto. Aparte de este problema, el siguiente reto que se nos plantea es transformar todos los datos numéricos producidos en información relevante que pueda responder de manera objetiva a las preguntas que nos planteamos. Para ello, debemos disponer de métodos de análisis lo bastante robustos como para transformar la información en bruto producida en nuestras simulaciones, en conocimiento directo de una manera no sesgada. La presente Tesis Doctoral se enmarca en este ámbito, ya que estudiaremos tres problemas biológicos diferentes haciendo énfasis en la fase de modelización de nuestro sistema, así como en el empleo de técnicas de análisis avanzadas para comprenderlo. En la primera parte, nos centramos en el análisis de la dinámica de proteínas, enfatizando las distintas descripciones que pueden usarse para comprender su paisaje de energía libre. Para ello escogemos un sistema relativamente simple, una proteína modelo coarse-grained a la cual aplicamos una fuerza constante para promover su desplegamiento. Realizaremos simulaciones numéricas en este sistema y nos plantearemos cuál es la mejor manera de obtener una descripción fiel de su espacio configuracional así como de su mecanismo de desplegamiento. Para ello emplearemos dos métodos distintos. Primero, proyectaremos su paisaje de energía libre –de gran dimensión- sobre distintos parámetros de orden, obteniendo representaciones unidimensionales. Éstas proporcionarán una visión globalmente correcta del sistema, sin embargo fallarán en la descripción adecuada de su mecanismo de desnaturalización. Por otra parte, emplearemos modelos de Markov para representar el paisaje de energía libre. Estos revelarán un espacio configuracional más complejo que el previsto anteriormente, con varios intermediarios que tendrán un papel relevante, especialmente para comprender el mecanismo de desplegamiento. En la segunda parte de la Tesis Doctoral, mostramos el estudio de un modelo de DNA al nivel del par de bases, el modelo de Peyrard-Bishop-Dauxois. En particular, extenderemos este modelo para introducir la interacción proteína-DNA. Proponiendo un método de análisis adecuado basado en modelos de Markov, podremos emplear este modelo para analizar secuencias de promotores, relacionando los estados que encontramos en la dinámica del sistema con sitios de unión proteína-DNA. Este modelo lo emplearemos para el análisis de nueve secuencias de promotores de una cianobacteria en particular. Nos centraremos en la identificación del sitio de inicio de la transcripción (TSS), región donde se une la RNA polimerasa para iniciar este proceso. En cada uno de los promotores, gracias al modelo somos capaces de identificar esta región como un estado de relevancia en la dinámica, con tendencia a que la partícula se una, formando una burbuja. Asimismo, gracias al método de análisis, cuantificamos estos estados, proporcionando magnitudes estadísticas que podemos relacionar con el conocimiento biológica acerca de estos promotores. La tercera parte está dedicada a los experimentos de molécula individual. Presentamos una colaboración experimental en la cual analizamos experimentos de disociación mecánica de dos complejos proteína:proteína. Nuestro objetivo es proporcionar una visión adecuada del paisaje de energía libre que gobierna este proceso. Para ello proponemos un método que permite recuperar la barrera de energía libre así como la energía libre de disociación para complejos biológicos. En particular, emplearemos este método para analizar experimentos de espetroscopía de fuerza, permitiendo obtener estas magnitudes y discutirlas en el contexto de la biología del sistema. Asimismo, proponemos un modelo físico para este tipo de experimentos, sobre el cual realizamos simulaciones numéricas que analizamos con el mismo método, con objeto de validarlo y respaldar su empleo

Mesoscopic model and free energy landscape for protein-DNA binding sites: Analysis of cyanobacterial promoters

This is an open-access article distributed under the terms of the Creative Commons Attribution License.The identification of protein binding sites in promoter sequences is a key problem to understand and control regulation in biochemistry and biotechnological processes. We use a computational method to analyze promoters from a given genome. Our approach is based on a physical model at the mesoscopic level of protein-DNA interaction based on the influence of DNA local conformation on the dynamics of a general particle along the chain. Following the proposed model, the joined dynamics of the protein particle and the DNA portion of interest, only characterized by its base pair sequence, is simulated. The simulation output is analyzed by generating and analyzing the Free Energy Landscape of the system. In order to prove the capacity of prediction of our computational method we have analyzed nine promoters of Anabaena PCC 7120. We are able to identify the transcription starting site of each of the promoters as the most populated macrostate in the dynamics. The developed procedure allows also to characterize promoter macrostates in terms of thermo-statistical magnitudes (free energy and entropy), with valuable biological implications. Our results agree with independent previous experimental results. Thus, our methods appear as a powerful complementary tool for identifying protein binding sites in promoter sequences.This work was supported by the Spanish Goverment under DGICYT Projects No. FIS2011-25167, BFU2009-07424, BFU2012-31458 cofinanced by FEDER funds, Gobierno de Aragon (projects B18 and E19), “Proyecto Intramural” (BIFI) and Spanish government fellowship FPU-2012-2608 (RTR).Peer Reviewe