Search

The transport of polymers across nanoscale pores underpins many biological processes, such as the ejection of bacteriophage DNA into a host cell and the transfer of genes between bacteria. The movement of polymers into and out of confinement is also the basis for a wide range of sensing technologies used for single-molecule detection and sequencing. Acquiring an accurate understanding of the translocation dynamics is an essential step in the quantitative analysis of polymer structure, including the localization of binding sites or sequences. Here we use synthetic nanopores and nanostructured DNA molecules to directly measure the velocity profile of driven polymer translocation through synthetic nanopores. Our results reveal a two-stage behaviour in which the translocation initially slows with time before accelerating close to the end of the process. We also find distinct local velocity correlations as the DNA polymer chain passes through the nanopore. Brownian dynamics simulations show that the two-stage behaviour is associated with tension propagation, with correlations arising from the random-walk conformation in which the DNA begins. A study of the dynamics of polymer translocation through synthetic nanopores provides a direct observation of tension propagation—a non-equilibrium description of the process of unfolding that a polymer undergoes during translocation.

Stochastic resonance (SR) describes the synchronization between noise of a system and an applied oscillating field to achieve an optimized response signal. In this work, we use simulations to investigate the phenomenon of SR of a single stranded DNA driven through a nanopore when an oscillating electric field is added. The system is comprised of a MspA protein nanopore embedded in a membrane and different lengths of DNA is driven from one end of the pore to the other via a constant potential difference. We superimposed an oscillating electric field on top of the existing electric field. The source of noise is due to thermal fluctuations, since the system is immersed in solution at room temperature. Here, the signal optimization we seek is the increase in translocation time of DNA through the protein nanopore. Normally, translocation time scales linearly with DNA length and inversely with driving force in a drift dominated regime. We found a non-monotonic dependence of the mean translocation time with the frequency of the oscillating field. This non-monotonic behavior of the translocation time is observed for all lengths of DNA, but SR occurs only for longer DNA. Furthermore, we also see evidence of DNA extension being influenced by the oscillating field while moving through the nanopore.

Biofilms are a multicellular way of life, where bacterial cells are close together and embedded in a hydrated macromolecular matrix which offers a number of advantages to the cells. Extracellular polysaccharides play an important role in matrix setup and maintenance. A water-insoluble polysaccharide was isolated and purified from the biofilm produced by Burkholderia cenocepacia strain H111, a cystic fibrosis pathogen. Its composition and glycosidic linkages were determined using Gas&ndash, Liquid Chromatography&ndash, Mass Spectrometry (GLC&ndash, MS) on appropriate carbohydrate derivatives while its complete structure was unraveled by 1D and 2D NMR spectroscopy in deuterated sodium hydroxide (NaOD) aqueous solutions. All the collected data demonstrated the following repeating unit for the water-insoluble B. cenocepacia biofilm polysaccharide: [3)-&alpha, d-Galp-(1&rarr, 3)-&alpha, d-Glcp-(1&rarr, d-Manp-(1&rarr, ]n Molecular modelling was used, coupled with NMR Nuclear Overhauser Effect (NOE) data, to obtain information about local structural motifs which could give hints about the polysaccharide insolubility. Both modelling and NMR data pointed at restricted dynamics of local conformations which were ascribed to the presence of inter-residue hydrogen bonds and to steric restrictions. In addition, the good correlation between NOE data and calculated interatomic distances by molecular dynamics simulations validated potential energy functions used for calculations.

We have investigated the dynamics of single-stranded DNA as it translocates through charge-mutated protein nanopores. Translocation of DNA is a crucial step in nanopore-based sequencing platforms, where control over translocation speed remains one of the main challenges. Taking advantage of the interactions between negatively charged DNA and positively charged amino acid residues, the translocation speed of DNA can be manipulated by deliberate charge decorations inside the nanopore. We employed coarse-grained Langevin dynamics simulations to monitor the step-by-step movement of DNA through different mutations of α-hemolysin protein nanopores. We found that although the average translocation time per nucleotide is longer, in agreement with experiments, the DNA nucleotides do not translocate with a uniform speed. Furthermore, the location and spacing of the charge decorations can alter the translocation dynamics significantly, trapping DNA in some cases. Our findings can give insights when designing charge patterns in nanopores.

Ramachandran conformational energy maps have been prepared for all of the glycosidic linkages found in the C1576 exopolysaccharide that constitutes the biofilms of the bacterial species Burkholderia multivorans, a member of the Burkholderia cepacian complex that was isolated from a cystic fibrosis patient. This polysaccharide is a rhamnomannan with a tetrasaccharide repeat unit containing two mannose residues and two rhamnose residues, –[3-α-D-Man-(1→2)-α-D-Man-(1→2)-α-D-Rha-(1→3)-α-D-Rha-(1→](n)–, where approximately 50% of the rhamnoses are randomly methylated on their O3 hydroxyl groups, further increasing the overall hydrophobicity of the chains. Because of the methylation, the tetrasaccharide repeat unit actually contains six possible linkages. The conformational energy maps are fully adiabatic relaxed maps in which the energy for each (ϕ,ψ) grid point on the map represents the lowest possible energy for the molecule in that conformation, considering all the combinations of the other degrees of freedom, such as hydroxyl orientations. Molecular dynamics simulations were used to verify that these maps indeed describe the conformational dynamics of these linkages. All six linkages were found to be quite restricted in possible ϕ angles, but to exhibit several possible low-energy ψ angles, suggesting that these chains could be quite flexible.

Burkholderia cenocepacia belongs to the Burkholderia Cepacia Complex, a group of 22 closely related species both of clinical and environmental origin, infecting cystic fibrosis patients. B. cenocepacia accounts for the majority of the clinical isolates, comprising the most virulent and transmissible strains. The capacity to form biofilms is among the many virulence determinants of B. cenocepacia, a characteristic that confers enhanced tolerance to some antibiotics, desiccation, oxidizing agents, and host defenses. Exopolysaccharides are a major component of biofilm matrices, particularly providing mechanical stability to biofilms. Recently, a water-insoluble exopolysaccharide produced by B. cenocepacia H111 in biofilm was characterized. In the present study, a water-soluble exopolysaccharide was extracted from B. cenocepacia H111 biofilm, and its structure was determined by GLC-MS, NMR and ESI-MS. The repeating unit is a linear rhamno-tetrasaccharide with 50% replacement of a 3-α-L-Rha with a α-3-L-Man. [2)-α-L-Rhap-(1→3)-α-L-[Rhap or Manp]-(1→3)-α-L-Rhap-(1→2)-α-L-Rhap-(1→]n Molecular modelling was used to obtain information about local structural motifs which could give information about the polysaccharide conformation.

Protein filtration is important in many fields of science and technology such as medicine, biology, chemistry, and engineering. Recently, protein separation and filtering with nanoporous membranes has attracted interest due to the possibility of fast separation and high throughput volume. This, however, requires understanding of the protein's dynamics inside and in the vicinity of the nanopore. In this work, we utilize a Brownian dynamics approach to study the motion of the model protein insulin in the membrane-electrolyte electrostatic potential. We compare the results of the atomic model of the protein with the results of a coarse-grained and a single-bead model, and find that the coarse-grained representation of protein strikes the best balance between the accuracy of the results and the computational effort required. Contrary to common belief, we find that to adequately describe the protein, a single-bead model cannot be utilized without a significant effort to tabulate the simulation parameters. Similar to results for nanoparticle dynamics, our findings also indicate that the electric field and the electro-osmotic flow due to the applied membrane and electrolyte biases affect the capture and translocation of the biomolecule by either attracting or repelling it to or from the nanopore. Our computational model can also be applied to other types of proteins and separation conditions.

In this work, we theoretically study the interaction between a solid state membrane equipped with a nanopore and a tethered, negatively charged polymer chain subjected to a time-dependent applied electrolyte bias. In order to describe the movement of the chain in the biomolecule-membrane system immersed in an electrolyte solution, Brownian dynamics is used. We show that we can control the polymer's equilibrium position with various applied electrolyte biases: for a sufficiently positive bias, the chain extends inside the pore, and the removal of the bias causes the polymer to leave the pore. Corresponding to a driven process, we find that the time it takes for a biomolecular chain to enter and extend into a nanopore in a positive bias almost increases linearly with chain length while the amount of time it takes for a polymer chain to escape the nanopore is mainly governed by diffusion.

Recently, we developed a computational model that allowed us to study the influence a semiconductor membrane has on a DNA molecule translocating through a nanopore in this membrane. Our model incorporated both the self-consistent Poisson-Nernst-Planck simulations for the electric potential of a solid state membrane immersed in an electrolyte solution together with the Brownian dynamics of the biomolecule. In this paper, we study how the applied electrolyte bias, the semiconductor membrane bias, and the semiconductor material type ($n$-Si or $p$-Si) affect the translocation dynamics of a single-stranded DNA moving through a nanopore in a single-layered semiconductor membrane. We show that the type of semiconductor material used for the membrane has a prominent effect on the biomolecule's translocation time, with DNA exhibiting much longer translocation times through the $p$-type membrane than through the $n$ type at the same electrolyte and membrane potentials, while the extension of the biomolecule remains practically unchanged. In addition, we find the optimal combination for the membrane-electrolyte system's parameters to achieve the longest translocation time and largest DNA extension. With our single-layered electrically tunable membranes, the DNA translocation time can be manipulated to have an order of magnitude increase.

Understanding protein dynamics through an artificial nanopore has implications in many areas such as sensing and filtering. Collecting statistical information while tracking the movement of a full atomic protein model is computationally expensive since number of atoms ranges in the thousands. The need to represent protein with a computationally cost effective model is imperative, along with understanding its dynamics through the nanopore. In this work we studied the dynamics of the protein insulin placed near a nanopore of an electrically tunable semiconductor membrane. Using Brownian dynamics method we calculated the trajectory of the modeled protein in the electrolyte-membrane electrostatic potential. The time spent by the protein before a successful translocation and the translocation times were both analyzed. Our results indicate that the localized electric field within the nanopore affects the movement of the protein. Also, by comparing the results of the full atomic protein model with a coarse grained model and a single bead model, we evaluate which model best approximates the full atomic protein model.

We study the applicability of an electrically tunable nanoporous semiconductor membrane for the separation of nanoparticles by charge. We show that this type of membrane can overcome one of the major shortcomings of nanoporous membrane applications for particle separation: the compromise between membrane selectivity and permeability. The computational model that we have developed describes the electrostatic potential distribution within the system and tracks the movement of the filtered particle using Brownian dynamics while taking into consideration effects from dielectrophoresis, fluid flow, and electric potentials. We found that for our specific pore geometry, the dielectrophoresis plays a negligible role in the particle dynamics. By comparing the results for charged and uncharged particles, we show that for the optimal combination of applied electrolyte and membrane biases the same membrane can effectively separate same-sized particles based on charge with a difference of up to 3 times in membrane permeability.

We study the applicability of tunable nanoporous semiconductor membranes made of the heavily doped silicone for separation of nanoparticles and proteins by their size and charge. We demonstrate that this type of membrane can overcome one of the major shortcomings of membrane applications for particle separation: the compromise between membrane selectivity and permeability. The microscopic computational model that we have developed describes the translocation process of filtered objects with the translational-rotational Brownian Dynamics taking into consideration effects from the dielectrophoresis, the electrolyte solution flow, and the self-consistent electrostatic potential distribution within the continuum Poisson-Nernst-Planck approach. Our results indicate that the tunable local electric field arising inside the membrane can effectively control interaction of filtered objects with the nanopore to either block its passage or increase the translocation rate by modulating the electroosmotic flow direction and magnitude. By extracting the membrane permeability from our microscopic simulations, we compute the macroscopic sieving factors and show that the size and charge selectivity of the membrane can be tuned by the applied voltage in the broad range.View Large Image | View Hi-Res Image | Download PowerPoint Slide