Photophysical image analysis: Unsupervised probabilistic thresholding for images from electron-multiplying charge-coupled devices.

We introduce the concept photophysical image analysis (PIA) and an associated pipeline for unsupervised probabilistic image thresholding for images recorded by electron-multiplying charge-coupled device (EMCCD) cameras. We base our approach on a closed-form analytic expression for the characteristic function (Fourier-transform of the probability mass function) for the image counts recorded in an EMCCD camera, which takes into account both stochasticity in the arrival of photons at the imaging camera and subsequent noise induced by the detection system of the camera. The only assumption in our method is that the background photon arrival to the imaging system is described by a stationary Poisson process (we make no assumption about the photon statistics for the signal). We estimate the background photon statistics parameter, λbg, from an image which contains both background and signal pixels by use of a novel truncated fit procedure with an automatically determined image count threshold. Prior to this, the camera noise model parameters are estimated using a calibration step. Utilizing the estimates for the camera parameters and λbg, we then introduce a probabilistic thresholding method, where, for the first time, the fraction of misclassified pixels can be determined a priori for a general image in an unsupervised way. We use synthetic images to validate our a priori estimates and to benchmark against the Otsu method, which is a popular unsupervised non-probabilistic image thresholding method (no a priori estimates for the error rates are provided). For completeness, we lastly present a simple heuristic general-purpose segmentation method based on the thresholding results, which we apply to segmentation of synthetic images and experimental images of fluorescent beads and lung cell nuclei. Our publicly available software opens up for fully automated, unsupervised, probabilistic photophysical image analysis.

Equilibrium melting probabilities of a DNA molecule with a defect: An exact solution of the Poland-Scheraga model.

In this study we derive analytically the equilibrium melting probabilities for basepairs of a DNA molecule with a defect site. We assume that the defect is characterized by a change in the Watson-Crick basepair energy of the defect basepair, and in the associated two stacking energies for the defect, as compared to the remaining parts of the DNA. The defect site could, for instance, occur due to DNA basepair mismatching, cross-linking, or by the chemical modifications when attaching fluorescent labels, such as fluorescent-quencher pairs, to DNA. Our exact solution of the Poland-Scheraga model for DNA melting provides the probability that the labeled basepair, and its neighbors, are open at different temperatures. Our work is of direct importance, for instance, for studies where fluorophore-quencher pairs are used for studying single basepair fluctuations of designed DNA molecules.

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

BACKGROUND: Identification 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. METHODS: In 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. RESULTS: We 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. CONCLUSION: The 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.

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.

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, and chromosome evolution. Optical DNA mapping (ODM), commonly categorized into sparsely-labelled ODM and densely-labelled ODM, provides sequence-specific continuous intensity profiles (DNA barcodes) along single DNA molecules and is a technique well-suited for detecting such alterations. For sparsely-labelled barcodes, the possibility to detect large genomic alterations has been investigated extensively, while densely-labelled barcodes have not received as much attention. In this work, we introduce HMMSV, a hidden Markov model (HMM) based algorithm for detecting structural variations (SVs) directly in densely-labelled barcodes without access to sequence information. We evaluate our approach using simulated data-sets with 5 different types of SVs, and combinations thereof, and demonstrate that the method reaches a true positive rate greater than 80% for randomly generated barcodes with single variations of size 25 kilobases (kb). Increasing the length of the SV further leads to larger true positive rates. For a real data-set with experimental barcodes on bacterial plasmids, we successfully detect matching barcode pairs and SVs without any particular assumption of the types of SVs present. Instead, our method effectively goes through all possible combinations of SVs. Since ODM works on length scales typically not reachable with other techniques, our methodology is a promising tool for identifying arbitrary combinations of genomic alterations.

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 (>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.

Optical DNA Mapping Combined with Cas9-Targeted Resistance Gene Identification for Rapid Tracking of Resistance Plasmids in a Neonatal Intensive Care Unit Outbreak.

The global spread of antibiotic resistance among Enterobacteriaceae is largely due to multidrug resistance plasmids that can transfer between different bacterial strains and species. Horizontal gene transfer of resistance plasmids can complicate hospital outbreaks and cause problems in epidemiological tracing, since tracing is usually based on bacterial clonality. We have developed a method, based on optical DNA mapping combined with Cas9-assisted identification of resistance genes, which is used here to characterize plasmids during an extended-spectrum ß-lactamase (ESBL)-producing Enterobacteriaceae outbreak at a Swedish neonatal intensive care unit. The outbreak included 17 neonates initially colonized with ESBL-producing Klebsiella pneumoniae (ESBL-KP), some of which were found to carry additional ESBL-producing Escherichia coli (ESBL-EC) in follow-up samples. We demonstrate that all ESBL-KP isolates contained two plasmids with the blaCTX-M-15 gene located on the smaller one (~80 kbp). The same ESBL-KP clone was present in follow-up samples for up to 2 years in some patients, and the plasmid carrying the blaCTX-M-15 gene was stable throughout this time period. However, extensive genetic rearrangements within the second plasmid were observed in the optical DNA maps for several of the ESBL-KP isolates. Optical mapping also demonstrated that even though other bacterial clones and species carrying blaCTX-M group 1 genes were found in some neonates, no transfer of resistance plasmids had occurred. The data instead pointed toward unrelated acquisition of ESBL-producing Enterobacteriaceae (EPE). In addition to revealing important information about the specific outbreak, the method presented is a promising tool for surveillance and infection control in clinical settings.IMPORTANCE This study presents how a novel method, based on visualizing single plasmids using sequence-specific fluorescent labeling, could be used to analyze the genetic dynamics of an outbreak of resistant bacteria in a neonatal intensive care unit at a Swedish hospital. Plasmids are a central reason for the rapid global spread of bacterial resistance to antibiotics. In a single experimental procedure, this method replaces many traditional plasmid analysis techniques that together provide limited details and are slow to perform. The method is much faster than long-read whole-genome sequencing and offers direct genetic comparison of patient samples. We could conclude that no transfer of resistance plasmids had occurred between different bacteria during the outbreak and that secondary cases of ESBL-producing Enterobacteriaceae carriage were instead likely due to influx of new strains. We believe that the method offers potential in improving surveillance and infection control of resistant bacteria in hospitals.

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.

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

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.