Explore the vast range of titles available.

Hydrophobic base stacking is a major contributor to DNA double-helix stability. We report the discovery of specific unstacking effects in certain semihydrophobic environments. Water-miscible ethylene glycol ethers are found to modify structure, dynamics, and reactivity of DNA bymechanisms possibly related to a biologically relevant hydrophobic catalysis. Spectroscopic data and optical tweezers experiments show that base-stacking energies are reduced while base-pair hydrogen bonds are strengthened. We propose that a modulated chemical potential of water can promote “longitudinal breathing” and the formation of unstacked holes while base unpairing is suppressed. Flow linear dichroism in 20% diglyme indicates a 20 to 30% decrease in persistence length of DNA, supported by an increased flexibility in single-molecule nanochannel experiments in poly(ethylene glycol). A limited (3 to 6%) hyperchromicity but unaffected circular dichroism is consistent with transient unstacking events while maintaining an overall average B-DNA conformation. Further information about unstacking dynamics is obtained from the binding kinetics of large thread-intercalating ruthenium complexes, indicating that the hydrophobic effect provides a 10 to 100 times increased DNA unstacking frequency and an “open hole” population on the order of 10−2 compared to 10−4 in normal aqueous solution. Spontaneous DNA strand exchange catalyzed by poly(ethylene glycol) makes us propose that hydrophobic residues in the L2 loop of recombination enzymes RecA and Rad51 may assist gene recombination via modulation of water activity near the DNA helix by hydrophobic interactions, in the manner described here. We speculate that such hydrophobic interactions may have catalytic roles also in other biological contexts, such as in polymerases.

Fluorescence microscopy is an effective tool for imaging biological samples, yet captured images often contain noises, including photon shot noise and camera read noise. To analyze biological samples accurately, separating background pixels from signal pixels is crucial. This would ideally be guided by the knowledge of a parameter called the Poisson parameter, λ bg , representing the mean number of photons collected in a background pixel (for the case when quantum efficiency = 1 and the dark current is negligible). This study introduces a method for estimating λ bg , from an image which contains both background and signal pixels, using probabilistic noise modeling for an sCMOS camera. The approach incorporates Poisson-distributed photon shot noise and sCMOS camera read noise modelled with a Tukey-Lambda distribution. We apply a chi-square test and a truncated fit technique to estimate λ bg directly from a general sCMOS image, with camera parameters determined through calibration experiments. We validate our method by comparing λ bg estimates in images captured by sCMOS and EMCCD cameras for the same field of view. Our analysis shows strong agreement for low to moderate exposure images, where estimated values for λ bg align well between the sCMOS and EMCCD images. Based on our estimated λ bg , we perform image thresholding and segmentation using our previously introduced procedure. Our publicly available software provides a platform for photophysical image analysis for sCMOS camera systems.

In optical genome mapping (OGM), large numbers of individual DNA maps-sequence-specific data series along single DNA molecules-are produced. Such individual maps have to be stitched together in a process called de novo OGM assembly in order to create consensus OGM maps for corresponding regions along the chromosomes. While there are several types of experimental OGM assays, not all of them have de novo OGM assembly tools available. In particular, in densely-labelled OGM there are no such tools. Here, we present and evaluate DOGMA, a de novo OGM assembly algorithm for densely labelled OGM data which uses matrix profiles. Matrix profile has transformed how data mining problems are approached in time series analysis. Yet, this algorithm has not been widely explored outside of the time series community- we here use it for OGM de novo assembly for the first time. Further novelties in our algorithm are the introduction of two scores for each individual alignment, use of p-values, a visual representation as barcode islands and the introduction of a method for generating consensus barcodes using amplitude adjustment. Utilizing p-values helps mitigate the risk of errors in the assemblies as caused by false positives. We demonstrate our algorithm by applying it for de novo OGM assembly of synthetic datasets and of an experimental dataset from an Escherichia coli genome. We validate the assemblies using corresponding reference genomes and investigate the strengths and limitations of the algorithm. De novo OGM assembly of dense optical DNA maps shows promise as a complement or an alternative to current OGM techniques for other types of genome mapping assays. The code is available at: https://github.com/dnadevcode/dogma.

Studying single catalyst nanoparticles, during reaction, eliminates averaging effects that are an inherent limitation of ensemble experiments. It enables establishing structure–function correlations beyond averaged properties by including particle-specific descriptors such as defects, chemical heterogeneity and microstructure. Driven by these prospects, several single particle catalysis concepts have been implemented. However, they all have limitations such as low throughput, or that they require very low reactant concentrations and/or reaction rates. In response, we present a nanofluidic device for highly parallelized single nanoparticle catalysis in solution, based on fluorescence microscopy. Our device enables parallel scrutiny of tens of single nanoparticles, each isolated inside its own nanofluidic channel, and at tunable reaction conditions, ranging from the fully mass transport limited regime to the surface reaction limited regime. In a wider perspective, our concept provides a versatile platform for highly parallelized single particle catalysis in solution and constitutes a promising application area for nanofluidics. Single nanoparticle catalysis studies enable structure–function correlations beyond averaged properties. Here, the authors present a versatile nanofluidics- and fluorescence-based platform for highly parallelized single particle catalysis in solution.

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.

Plasmids encoding bla CTX-M genes have greatly shaped the evolution of E. coli producing extended-spectrum beta-lactamases (ESBL- E. coli ) and adds to the global threat of multiresistant bacteria by promoting horizontal gene transfer (HGT). Here we screened the similarity of 47 bla CTX-M -encoding plasmids, from 45 epidemiologically unrelated and disperse ESBL- E. coli strains, isolated during the early phase (2009–2014) of the ESBL pandemic in western Sweden. Using optical DNA mapping (ODM), both similar and rare plasmids were identified. As many as 57% of the plasmids formed five ODM-plasmid groups of at least three similar plasmids per group. The most prevalent type (28%, IncIl, pMLST37) encoded bla CTX-M-15 (n = 10), bla CTX-M-3 (n = 2) or bla CTX-M-55 (n = 1). It was found in isolates of various sequence types (STs), including ST131. This could indicate ongoing local HGT as whole-genome sequencing only revealed similarities with a rarely reported, IncIl plasmid. The second most prevalent type (IncFII/FIA/FIB, F1:A2:B20) harboring bla CTX-M-27 , was detected in ST131-C1-M27 isolates, and was similar to plasmids previously reported for this subclade. The results also highlight the need for local surveillance of plasmids and the importance of temporospatial epidemiological links so that detection of a prevalent plasmid is not overestimated as a potential plasmid transmission event in outbreak investigations.

The early steps of DNA double-strand break (DSB) repair in human cells involve the MRE11-RAD50-NBS1 (MRN) complex and its cofactor, phosphorylated CtIP. The roles of these proteins in nucleolytic DSB resection are well characterized, but their role in bridging the DNA ends for efficient and correct repair is much less explored. Here we study the binding of phosphorylated CtIP, which promotes the endonuclease activity of MRN, to single long (∼50 kb) DNA molecules using nanofluidic channels and compare it to the yeast homolog Sae2. CtIP bridges DNA in a manner that depends on the oligomeric state of the protein, and truncated mutants demonstrate that the bridging depends on CtIP regions distinct from those that stimulate the nuclease activity of MRN. Sae2 is a much smaller protein than CtIP, and its bridging is significantly less efficient. Our results demonstrate that the nuclease cofactor and structural functions of CtIP may depend on the same protein population, which may be crucial for CtIP functions in both homologous recombination and microhomology-mediated end-joining.

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, λ bg , 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 λ bg , 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.

Mycobacterium tuberculosis ( Mtb ), the causative agent of tuberculosis (TB), is estimated to infect nearly one-quarter of the global population. A key factor in its resilience and persistence is its robust DNA repair capacity. Non-homologous end joining (NHEJ) is the primary pathway for repairing DNA double-strand breaks (DSBs) in many organisms, including Mtb , where it is mediated by the Ku protein and the multifunctional LigD enzyme. In this study, we demonstrate that Ku is essential for mycobacterial survival under DNA-damaging conditions. Using cryogenic electron microscopy (cryo-EM), we solved high-resolution structures of both the apo and DNA-bound forms of the Ku- Mtb homodimer. Our structural and biophysical analyses reveal that Ku forms an extended proteo-filament upon binding DNA. We identify critical residues involved in filament formation and DNA synapsis and show that their mutation severely impairs bacterial viability. Furthermore, we propose a model in which the C-terminus of Ku regulates DNA binding and loading and facilitates subsequent recruitment of LigD. These findings provide unique insights into bacterial DNA repair and guide future therapeutics. Mycobacterium tuberculosis protein Ku is involved in DNA repair and a potential drug target. Here, using cryo-EM and complementary approaches, the authors obtain insights into Ku oligomerization and mechanisms of function in DNA synapsis.