Osmotic pressure: resisting or promoting DNA ejection from phage

Recent in vitro experiments have shown that DNA ejection from bacteriophage can be partially stopped by surrounding osmotic pressure when ejected DNA is digested by DNase I on the course of ejection. We argue in this work by combination of experimental techniques (osmotic suppression without DNaseI monitored by UV absorbance, pulse-field electrophoresis, and cryo-EM visualization) and simple scaling modeling that intact genome (i.e. undigested) ejection in a crowded environment is, on the contrary, enhanced or eventually complete with the help of a pulling force resulting from DNA condensation induced by the osmotic stress itself. This demonstrates that in vivo, the osmotically stressed cell cytoplasm will promote phage DNA ejection rather than resisting it. The further addition of DNA-binding proteins under crowding conditions is shown to enhance the extent of ejection. We also found some optimal crowding conditions for which DNA content remaining in the capsid upon ejection is maximum, which correlates well with the optimal conditions of maximum DNA packaging efficiency into viral capsids observed almost 20 years ago. Biological consequences of this finding are discussed

Design, modeling and synthesis of an in vitro transcription rate regulatory circuit

This paper describes the design, modeling and realization of a synthetic in vitro circuit that aims at regulating the rate of mRNA transcription. Two DNA templates are designed to interact through their transcripts, creating negative feedback loops that will equate their transcription rates at steady state. A mathematical model is developed for this circuit, consisting of a set of ODEs derived from the mass action laws and Michaelis-Menten kinetics involving all the present chemical species. The DNA strands were accordingly designed, following thermodynamics principles and minimizing unwanted interactions. Preliminary experimental results show that the circuit is performing the expected task, by matching at steady state the transcription rates of the two DNA templates

Modeling DNA beacons at the mesoscopic scale

We report model calculations on DNA single strands which describe the equilibrium dynamics and kinetics of hairpin formation and melting. Modeling is at the level of single bases. Strand rigidity is described in terms of simple polymer models; alternative calculations performed using the freely rotating chain and the discrete Kratky-Porod models are reported. Stem formation is modeled according to the Peyrard-Bishop-Dauxois Hamiltonian. The kinetics of opening and closing is described in terms of a diffusion-controlled motion in an effective free energy landscape. Melting profiles, dependence of melting temperature on loop length, and kinetic time scales are in semiquantitative agreement with experimental data obtained from fluorescent DNA beacons forming poly(T) loops. Variation in strand rigidity is not sufficient to account for the large activation enthalpy of closing and the strong loop length dependence observed in hairpins forming poly(A) loops. Implications for modeling single strands of DNA or RNA are discussed.Comment: 15 pages, 17 figures, submitted to Eur. J. Phys.

Determining DfT Hardware by VHDL-AMS Fault Simulation for Biological Micro-Electronic Fluidic Arrays

The interest of microelectronic fluidic arrays for biomedical applications, like DNA determination, is rapidly increasing. In order to evaluate these systems in terms of required Design-for-Test structures, fault simulations in both fluidic and electronic domains are necessary. VHDL-AMS can be used successfully in this case. This paper shows a highly testable architecture of a DNA Bio-Sensing array, its basic sensing concept, fluidic modeling and sensitivity analysis. The overall VHDL-AMS fault simulation of the system is shown

From Nonspecific DNA–Protein Encounter Complexes to the Prediction of DNA–Protein Interactions

©2009 Gao, Skolnick. This is an open-access article distributed under the terms of the Creative Commons Attribution License, which permits unrestricted use, distribution, and reproduction in any medium, provided the original author and source are credited.doi:10.1371/journal.pcbi.1000341DNA–protein interactions are involved in many essential biological activities. Because there is no simple mapping code between DNA base pairs and protein amino acids, the prediction of DNA–protein interactions is a challenging problem. Here, we present a novel computational approach for predicting DNA-binding protein residues and DNA–protein interaction modes without knowing its specific DNA target sequence. Given the structure of a DNA-binding protein, the method first generates an ensemble of complex structures obtained by rigid-body docking with a nonspecific canonical B-DNA. Representative models are subsequently selected through clustering and ranking by their DNA–protein interfacial energy. Analysis of these encounter complex models suggests that the recognition sites for specific DNA binding are usually favorable interaction sites for the nonspecific DNA probe and that nonspecific DNA–protein interaction modes exhibit some similarity to specific DNA–protein binding modes. Although the method requires as input the knowledge that the protein binds DNA, in benchmark tests, it achieves better performance in identifying DNA-binding sites than three previously established methods, which are based on sophisticated machine-learning techniques. We further apply our method to protein structures predicted through modeling and demonstrate that our method performs satisfactorily on protein models whose root-mean-square Ca deviation from native is up to 5 Å from their native structures. This study provides valuable structural insights into how a specific DNA-binding protein interacts with a nonspecific DNA sequence. The similarity between the specific DNA–protein interaction mode and nonspecific interaction modes may reflect an important sampling step in search of its specific DNA targets by a DNA-binding protein

A Liquid Crystal Model of Viral DNA Encapsidation

A liquid crystal continuum modeling framework for icosahedra bacteriophage viruses is developed and tested. The main assumptions of the model are the chromonic columnar hexagonal structure of confined DNA, the high resistance to bending and the phase transition from solid to fluid-like states as the concentration of DNA in the capsid decreases during infection. The model predicts osmotic pressure inside the capsid and the ejection force of the DNA as well as the size of the isotropic volume at the center of the capsid. Extensions of the model are discussed