No Arabic abstract
We report an accurate method to determine DNA barcodes from the dwell time measurement of protein tags (barcodes) along the DNA backbone using Brownian dynamics simulation of a model DNA and use a recursive theoretical scheme which improves the measurements to almost 100 % accuracy. The heavier protein tags along the DNA backbone introduce a large speed variation in the chain that can be understood using the idea of non-equilibrium tension propagation theory. However, from an initial rough characterization of velocities into fast (nucleotides) and slow (protein tags) domains, we introduce a physically motivated interpolation scheme that enables us to determine the barcode velocities rather accurately. Our theoretical analysis of the motion of the DNA through a cylindrical nanopore opens up the possibility of its experimental realization and carries over to multi-nanopore devices used for barcoding.
The potential of a double nanopore system to determine DNA barcodes has been demonstrated experimentally. By carrying out Brownian dynamics simulation on a coarse-grained model DNA with protein tag (barcodes) at known locations along the chain backbone, we demonstrate that due to large variation of velocities of the chain segments between the tags, it is inevitable to under/overestimate the genetic lengths from the experimental current blockade and time of flight data. We demonstrate that it is the tension propagation along the chains backbone that governs the motion of the entire chain and is the key element to explain the non uniformity and disparate velocities of the tags and DNA monomers under translocation that introduce errors in measurement of the length segments between protein tags. Using simulation data we further demonstrate that it is important to consider the dynamics of the entire chain and suggest methods to accurately decipher barcodes. We introduce and validate an interpolation scheme using simulation data for a broad distribution of tag separations and suggest how to implement the scheme experimentally.
The ability to measure or manipulate network connectivity is the main challenge in the field of connectomics. Recently, a set of approaches has been developed that takes advantage of next generation DNA sequencing to scan connections between neurons into a set of DNA barcodes. Individual DNA sequences called markers represent single neurons, while pairs of markers, called barcodes contain information about connections. Here we propose a strategy for copying or cloning connectivity contained in barcodes into a clean slate tabula rasa network. We show that a one marker one cell (OMOC) rule, which forces all markers with the same sequence to condense into the same neuron, leads to fast and reliable formation of desired connectivity in a new network. We show that OMOC rule yields convergence in a number of steps given by a power law function of the network size. We thus propose that copying network connectivity from one network to another is theoretically possible.
We investigate the dynamics of DNA translocation through a nanopore using 2D Langevin dynamics simulations, focusing on the dependence of the translocation dynamics on the details of DNA sequences. The DNA molecules studied in this work are built from two types of bases $A$ and $C$, which has been shown previously to have different interactions with the pore. We study DNA with repeating blocks $A_nC_n$ for various values of $n$, and find that the translocation time depends strongly on the {em block length} $2n$ as well as on the {em orientation} of which base entering the pore first. Thus, we demonstrate that the measurement of translocation dynamics of DNA through nanopore can yield detailed information about its structure. We have also found that the periodicity of the block sequences are contained in the periodicity of the residence time of the individual nucleotides inside the pore.
We investigate the dynamics of DNA translocation through a nanopore driven by an external force using Langevin dynamics simulations in two dimensions (2D) to study how the translocation dynamics depend on the details of the DNA sequences. We consider a coarse-grained model of DNA built from two bases $A$ and $C$, having different base-pore interactions, {textit e.g.}, a strong (weak) attractive force between the pore and the base $A$ ($C$) inside the pore. From a series of studies on hetero-DNAs with repeat units $A_mC_n$, we find that the translocation time decreases exponentially as a function of the volume fraction $f_C$ of the base $C$. %($epsilon_{pC} < epsilon_{pA}$). For longer $A$ sequences with $f_C le 0.5$, the translocation time strongly depends on the orientation of DNA, namely which base enters the pore first. Our studies clearly demonstrate that for a DNA of certain length $N$ with repeat units $A_mC_n$, the pattern exhibited by the waiting times of the individual bases and their periodicity can unambiguously determine the values of $m$, $n$ and $N$ respectively. Therefore, a prospective experimental realization of this phenomenon may lead to fast and efficient sequence detection technic.
DNA methylation plays a pivotal role in the genetic evolution of both embryonic and adult cells. For adult somatic cells, location and dynamics of methylation has been very precisely pinned down with the 5-cytosine markers on cytosinephosphate- guanine (CpG) units. Unusual methylation on CpG islands are identified as one of the prime causes for silencing the tumor suppressant genes. Early detection of such methylation can diagnose the potentially harmful oncogenic evolution of cells, and provide a promising guideline for cancer prevention. With this motivation, we propose a cytosine methylation detection technique.Our hypothesis is that electronic signatures of DNA acquired as a molecule translocates through a nanopore, would be significantly different for methylated and non-methylated bases. This difference in electronic fingerprints would allow for reliable real-time differentiations of methylated DNA. We calculate transport currents through a punctured graphene membrane while the cytosine and methylated cytosine translocate through the nanopore. We also calculate the transport properties for uracil and cyanocytosine for comparison. Our calculations of transmission, current, and tunneling conductance show distinct signatures in their spectrum for each molecular type. Thus, in this work, we provide a theoretical analysis that points to a viability of our hypothesis.