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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.

ObjectivesCarbapenemase-producing Enterobacterales (CPE) are high priority targets of global antimicrobial surveillance. Herein, we determined the colonization rate of CPE on admission to intensive care units in Vientiane, Lao PDR in August-September 2019.MethodsData regarding clinical conditions, infection control, and antibiotic usage were collected during admission. Rectal swab samples (n = 137) collected during admission were inoculated to selective chromogenic agars, followed by confirmatory tests for extended-spectrum beta-lactamases and carbapenemases. All CPE isolates were sequenced on Illumina (HiSeq2500), reads assembled using SPAdes 3.13, and the draft genomes used to query a database (https://www.genomicepidemiology.org) for resistome, plasmid replicons, and sequence types (ST). Optical DNA mapping (ODM) was used to characterize plasmids and to determine location of resistance genes. Minimum spanning tree was generated using the Bacterial Isolate Genome Sequence database (BIGSdb) and annotated using iTOL.ResultFrom 47 Enterobacterales isolated on selective agars, K. pneumoniae (25/47) and E. coli (12/47) were the most prevalent species, followed by K aerogenes (2/47), K. variicola (1/47), and K. oxytoca (1/47). The overall prevalence of ESBLs was 51.0%; E. coli 83.3% (10/12) and Klebsiella spp. 41.3% (12/29). Twenty percent of the K. pneumoniae (5/25) isolates were carbapenem-resistant, and 4/5 contained the blaNDM-1 gene. All blaNDM-1 isolates belonged to ST147 and were indistinguishable with cgMLST. ODM showed that the blaNDM-1 gene was located on identical plasmids in all isolates.ConclusionThe prevalence of ESBL-producing Enterobacterales was high, while carbapenemases were less common. However, the detection of clonal dissemination of blaNDM-1-producing K. pneumoniae isolates in one of the intensive care units calls for vigilance. Stringent infection prevention and antimicrobial stewardship strategies are highly important measures.

Carbapenem-resistant Klebsiella pneumoniae are a major global threat in healthcare facilities. The propagation of carbapenem resistance determinants can occur through vertical transmission, with genetic elements being transmitted by the host bacterium, or by horizontal transmission, with the same genetic elements being transferred among distinct bacterial hosts. This work aimed to track carbapenem resistance transmission by K. pneumoniae in a healthcare facility. The study involved a polyphasic approach based on conjugation assays, resistance phenotype and genotype analyses, whole genome sequencing, and plasmid characterization by pulsed field gel electrophoresis and optical DNA mapping. Out of 40 K. pneumoniae clinical isolates recovered over two years, five were carbapenem- and multidrug-resistant and belonged to multilocus sequence type ST147. These isolates harboured the carbapenemase encoding blaKPC-3 gene, integrated in conjugative plasmids of 140 kbp or 55 kbp, belonging to replicon types incFIA/incFIIK or incN/incFIIK, respectively. The two distinct plasmids encoding the blaKPC-3 gene were associated with distinct genetic lineages, as confirmed by optical DNA mapping and whole genome sequence analyses. These results suggested vertical (bacterial strain-based) transmission of the carbapenem-resistance genetic elements. Determination of the mode of transmission of antibiotic resistance in healthcare facilities, only possible based on polyphasic approaches as described here, is essential to control resistance propagation.

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.

Optical DNA mapping (ODM) is based on fluorescent labeling, stretching and imaging of single DNA molecules to obtain sequence-specific fluorescence profiles, DNA barcodes. These barcodes can be mapped to theoretical counterparts obtained from DNA reference sequences, which in turn allow for DNA identification in complex samples and for detecting structural changes in individual DNA molecules. There are several types of DNA labeling schemes for ODM and for each labeling type one or several types of match scoring methods are used. By combining the information from multiple labeling schemes one can potentially improve mapping confidence; however, combining match scores from different labeling assays has not been implemented yet. In this study, we introduce two theoretical methods for dealing with analysis of DNA molecules with multiple label types. In our first method, we convert the alignment scores, given as output from the different assays, into p-values using carefully crafted null models. We then combine the p-values for different label types using standard methods to obtain a combined match score and an associated combined p-value. In the second method, we use a block bootstrap approach to check for the uniqueness of a match to a database for all barcodes matching with a combined p-value below a predefined threshold. For obtaining experimental dual-labeled DNA barcodes, we introduce a novel assay where we cut plasmid DNA molecules from bacteria with restriction enzymes and the cut sites serve as sequence-specific markers, which together with barcodes obtained using the established competitive binding labeling method, form a dual-labeled barcode. All experimental data in this study originates from this assay, but we point out that our theoretical framework can be used to combine data from all kinds of available optical DNA mapping assays. We test our multiple labeling frameworks on barcodes from two different plasmids and synthetically generated barcodes (combined competitive-binding- and nick-labeling). It is demonstrated that by simultaneously using the information from all label types, we can substantially increase the significance when we match experimental barcodes to a database consisting of theoretical barcodes for all sequenced plasmids.

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.

In optical DNA mapping technologies sequence-specific intensity variations (DNA barcodes) along stretched and stained DNA molecules are produced. These "fingerprints" of the underlying DNA sequence have a resolution of the order one kilobasepairs and the stretching of the DNA molecules are performed by surface adsorption or nano-channel setups. A post-processing challenge for nano-channel based methods, due to local and global random movement of the DNA molecule during imaging, is how to align different time frames in order to produce reproducible time-averaged DNA barcodes. The current solutions to this challenge are computationally rather slow. With high-throughput applications in mind, we here introduce a parameter-free method for filtering a single time frame noisy barcode (snap-shot optical map), measured in a fraction of a second. By using only a single time frame barcode we circumvent the need for post-processing alignment. We demonstrate that our method is successful at providing filtered barcodes which are less noisy and more similar to time averaged barcodes. The method is based on the application of a low-pass filter on a single noisy barcode using the width of the Point Spread Function of the system as a unique, and known, filtering parameter. We find that after applying our method, the Pearson correlation coefficient (a real number in the range from -1 to 1) between the single time-frame barcode and the time average of the aligned kymograph increases significantly, roughly by 0.2 on average. By comparing to a database of more than 3000 theoretical plasmid barcodes we show that the capabilities to identify plasmids is improved by filtering single time-frame barcodes compared to the unfiltered analogues. Since snap-shot experiments and computational time using our method both are less than a second, this study opens up for high throughput optical DNA mapping with improved reproducibility.