Methods for barcode analysis in optical DNA mapping

This thesis is composed of six papers, which all concern different methods and tools used for the analysis of barcodes in nanochannel-based Optical DNA Mapping (ODM). The first four papers consider densely-labeled barcodes while the last two consider sparsely-labeled barcodes.Paper I presents a combinatorial auction algorithm for contig assembly ussing ODM barcodes as scaffolds.Paper II concerns mapping of ODM barcodes on the human genome.Paper III deals with bacterial typing.Paper IV solves structural variation detection problem for competitive binding barcodes using Hidden Markov Models.Paper V proposes the use of Sliding Frank-Wolfe methods for sparse-labeled single-frame ODM.Paper VI extends the Sliding Frank-Wolfe methods from the analysis of single frame barcodes to multi-frame setting, where barcodes over multiple time-frames are averaged to improve the resolution

Veilio algebra paremtas rakto apsikeitimo protokolas

In this article we introduce the Weyl algebras as a platform algebra for a key exchange protocol based on the decomposition problem. In order to use it as a platform, we prove one propery of the Weyl algebra, related to it’s centralizer. Furthermore, we provide a scheme for the protocol and examples for the Weyl algebra and for the Weyl algebra with additional relations.Šiame straipsnyje pateikiame rakto apsikeitimo protokolo, paremto dekompozijos uždaviniu nekomutatyvioms grupėms, pritaikymą Veilio algebroms. Tuo tikslu įrodome vieną Veilio algebros savybę, susijusią su centralizatoriumi. Be to, pateikiame rakto apsikeitimo aprašą bei pavyzdį Veilio algebrai bei Veilio algebrai su papildomais sąryšiais

Strain-level bacterial typing directly from patient samples using optical DNA mapping

For bacterial infections, it is important to rapidly and accurately identify and characterize the type of bacteria involved so that optimal antibiotic treatment can be given quickly to the patient. However, current diagnostic methods are sometimes slow and cannot be used for mixtures of bacteria. We have, therefore, developed a method to identify bacteria directly from patient samples. The method was tested on two common species of disease-causing bacteria - Escherichia coli and Klebsiella pneumoniae - and it could correctly identify the bacterial strain or subtype in both urine samples and mixtures. Hence, the method has the potential to provide fast diagnostic information for choosing the most suited antibiotic, thereby reducing the risk of death and suffering. Nyblom, Johnning et al. develop an optical DNA mapping approach for bacterial strain typing of patient samples. They demonstrate rapid identification of clinically relevant E. coli and K. pneumoniae strains, without the need for cultivation. BackgroundIdentification of pathogens is crucial to efficiently treat and prevent bacterial infections. However, existing diagnostic techniques are slow or have a too low resolution for well-informed clinical decisions.MethodsIn this study, we have developed an optical DNA mapping-based method for strain-level bacterial typing and simultaneous plasmid characterisation. For the typing, different taxonomical resolutions were examined and cultivated pure Escherichia coli and Klebsiella pneumoniae samples were used for parameter optimization. Finally, the method was applied to mixed bacterial samples and uncultured urine samples from patients with urinary tract infections.ResultsWe demonstrate that optical DNA mapping of single DNA molecules can identify Escherichia coli and Klebsiella pneumoniae at the strain level directly from patient samples. At a taxonomic resolution corresponding to E. coli sequence type 131 and K. pneumoniae clonal complex 258 forming distinct groups, the average true positive prediction rates are 94% and 89%, respectively. The single-molecule aspect of the method enables us to identify multiple E. coli strains in polymicrobial samples. Furthermore, by targeting plasmid-borne antibiotic resistance genes with Cas9 restriction, we simultaneously identify the strain or subtype and characterize the corresponding plasmids.ConclusionThe optical DNA mapping method is accurate and directly applicable to polymicrobial and clinical samples without cultivation. Hence, it has the potential to rapidly provide comprehensive diagnostics information, thereby optimizing early antibiotic treatment and opening up for future precision medicine management

Facilitated sequence assembly using densely labeled optical DNA barcodes:A combinatorial auction approach

<div><p>The output from whole genome sequencing is a set of contigs, i.e. short non-overlapping DNA sequences (sizes 1-100 kilobasepairs). Piecing the contigs together is an especially difficult task for previously unsequenced DNA, and may not be feasible due to factors such as the lack of sufficient coverage or larger repetitive regions which generate gaps in the final sequence. Here we propose a new method for scaffolding such contigs. The proposed method uses densely labeled optical DNA barcodes from competitive binding experiments as scaffolds. On these scaffolds we position theoretical barcodes which are calculated from the contig sequences. This allows us to construct longer DNA sequences from the contig sequences. This proof-of-principle study extends previous studies which use sparsely labeled DNA barcodes for scaffolding purposes. Our method applies a probabilistic approach that allows us to discard “foreign” contigs from mixed samples with contigs from different types of DNA. We satisfy the contig non-overlap constraint by formulating the contig placement challenge as a combinatorial auction problem. Our exact algorithm for solving this problem reduces computational costs compared to previous methods in the combinatorial auction field. We demonstrate the usefulness of the proposed scaffolding method both for synthetic contigs and for contigs obtained using Illumina sequencing for a mixed sample with plasmid and chromosomal DNA.</p></div

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Enzyme-free optical DNA mapping of the human genome using competitive binding

Optical DNA mapping (ODM) allows visualization of long-range sequence information along single DNA molecules. The data can for example be used for detecting long range structural variations, for aiding DNA sequence assembly of complex genomes and for mapping epigenetic marks and DNA damage across the genome. ODM traditionally utilizes sequence specific marks based on nicking enzymes, combined with a DNA stain, YOYO-1, for detection of the DNA contour. Here we use a competitive binding approach, based on YOYO-1 and netropsin, which highlights the contour of the DNA molecules, while simultaneously creating a continuous sequence specific pattern, based on the AT/GC variation along the detected molecule. We demonstrate and validate competitive-binding-based ODM using bacterial artificial chromosomes (BACs) derived from the human genome and then turn to DNA extracted from white blood cells. We generalize our findings with in-silico simulations that show that we can map a vast majority of the human genome. Finally, we demonstrate the possibility of combining competitive binding with enzymatic labeling by mapping DNA damage sites induced by the cytotoxic drug etoposide to the human genome. Overall, we demonstrate that competitive-binding-based ODM has the potential to be used both as a standalone assay for studies of the human genome, as well as in combination with enzymatic approaches, some of which are already commercialized

Detection of structural variations in densely-labelled optical DNA barcodes: A hidden Markov model approach

Large-scale genomic alterations play an important role in disease, gene expression, andchromosome evolution. Optical DNA mapping (ODM), commonly categorized into sparsely-labelled ODM and densely-labelled ODM, provides sequence-specific continuous intensityprofiles (DNA barcodes) along single DNA molecules and is a technique well-suited fordetecting such alterations. For sparsely-labelled barcodes, the possibility to detect largegenomic alterations has been investigated extensively, while densely-labelled barcodeshave not received as much attention. In this work, we introduce HMMSV, a hidden Markovmodel (HMM) based algorithm for detecting structural variations (SVs) directly in densely-labelled barcodes without access to sequence information. We evaluate our approach usingsimulated data-sets with 5 different types of SVs, and combinations thereof, and demon-strate that the method reaches a true positive rate greater than 80% for randomly generatedbarcodes with single variations of size 25 kilobases (kb). Increasing the length of the SV fur-ther leads to larger true positive rates. For a real data-set with experimental barcodes onbacterial plasmids, we successfully detect matching barcode pairs and SVs without any par-ticular assumption of the types of SVs present. Instead, our method effectively goes throughall possible combinations of SVs. Since ODM works on length scales typically not reachablewith other techniques, our methodology is a promising tool for identifying arbitrary combina-tions of genomic alterations

Bacterial identification by optical mapping of genomic DNA in nanofluidic channels

A variety of pathogenic bacteria can infect humans and the increase in bacteria resistant to common antibiotics is a large threat to human health worldwide. This work presents a method, based on optical DNA mapping (ODM) in nanofluidic channels, that can detect the type of bacterial present in a sample by matching the obtained maps of large DNA molecules to a database of fully assembled bacterial genomes. The extraction and labelling protocol has been designed to work for both Gram-positive and Gram-negative bacteria, not requiring any prior knowledge about the sample content

Bacterial identification by optical mapping of genomic DNA in nanofluidic channels

A variety of pathogenic bacteria can infect humans and the increase in bacteria resistant to common antibiotics is a large threat to human health worldwide. This work presents a method, based on optical DNA mapping (ODM) in nanofluidic channels, that can detect the type of bacterial present in a sample by matching the obtained maps of large DNA molecules to a database of fully assembled bacterial genomes. The extraction and labelling protocol has been designed to work for both Gram-positive and Gram-negative bacteria, not requiring any prior knowledge about the sample content

Cultivation-Free Typing of Bacteria Using Optical DNA Mapping

A variety of pathogenic bacteria can infect humans, and rapid species identification is crucial for the correct treatment. However, the identification process can often be time-consuming and depend on the cultivation of the bacterial pathogen(s). Here, we present a stand-alone, enzyme-free, optical DNA mapping assay capable of species identification by matching the intensity profiles of large DNA molecules to a database of fully assembled bacterial genomes (&gt;10 000). The assay includes a new data analysis strategy as well as a general DNA extraction protocol for both Gram-negative and Gram-positive bacteria. We demonstrate that the assay is capable of identifying bacteria directly from uncultured clinical urine samples, as well as in mixtures, with the potential to be discriminative even at the subspecies level. We foresee that the assay has applications both within research laboratories and in clinical settings, where the time-consuming step of cultivation can be minimized or even completely avoided