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Until very recently, super-resolution localization and tracking of fluorescent particles used camera-based wide-field imaging with uniform illumination. Then it was demonstrated that structured illuminations encode additional localization information in images. The first demonstration of this uses scanning and hence suffers from limited throughput. This limitation was mitigated by fusing camera-based localization with wide-field structured illumination. Current implementations, however, use effectively only half the localization information that they encode in images. Here we demonstrate how all of this information may be exploited by careful calibration of the structured illumination. Our approach achieves maximal resolution for given structured illumination, has a simple data analysis, and applies to any structured illumination in principle. We demonstrate this with an only slightly modified wide-field microscope. Our protocol should boost the emerging field of high-precision localization with structured illumination. The structure and processes of life’s molecules at the nanoscale are probed with optical super resolution techniques. The authors present a method that combines conventional localization information and information from structured illumination, which outperforms other methods by localizing single molecules with a theoretically optimal doubling of precision.

Mesoscopic environments and particles diffusing in them are often studied by tracking such particles individually while their Brownian motion explores their environment. Environments may be, e.g., a domain in a cell membrane, an interior compartment of a cell, or an engineered nanopit. Particle trajectories are typically determined from time-lapse recorded movies. These are recorded with sufficient exposure time per frame to be able to detect and localize particles in each frame. Since particles move during this exposure time, particles image with motion blur. This motion blur can compromise estimates of diffusion coefficients and the size of the confining domain if not accounted for correctly. We do that here. We give explicit and exact expressions for the variance of measured positions and the mean-squared displacement of a Brownian particle confined in, respectively, a 1D box, a 2D box, a 2D circular disc, and a 3D sphere. Our expressions are valid for all exposure times, irrespective of the size of the confining space and the value of the diffusion coefficient. They apply also in the common case where the exposure time is smaller than the time-lapse due, e.g., to “dead time” caused by the readout process in the camera. These expressions permit determination of diffusion coefficients and domain sizes for given movies for the simple geometries we consider. More important, the trends observed in our exact results when parameter values are varied are valid also for more complex geometries for which no exact analytical solutions exist. Wherever the underlying physics is the same, the exact quantitative description of its consequences provided here is portable as a qualitative and semi-quantitative understanding of its consequences in general. The results may also be useful for other types of reflected Brownian motion than those occurring in single-particle tracking, e.g., in nuclear magnetic resonance imaging techniques. For use in that particular context, we briefly discuss the effects of confinement on anisotropic Brownian motion imaged with motion blur.

Cells moving on microprinted tracks reveal a preference for regions that they have already visited, suggesting an update to a century of dynamical models for cell trajectories.

International audience; The REvolutionary Approaches and Devices for Nucleic Acid analysis (READNA) project received 12 million s funding under the European Union Framework Programme 7 from 1st June 2008 to 30th November 2012. The 19 project partners from both academia and industry from in total 7 countries had a project budget of 16 Ms with which they have discovered, created and developed a huge body of insights into nucleic acid analysis. Results have been presented widely in publications and in innumerous public presentations. Results have been moved to spin-offs such as the Olink enrichment kits (now sold by Agilent as Haloplex) and are findingtheir way to the market, such as the Oxford Nanopore MinIon sequencer that was first released to early-access user sites in 2014.

The endothelial cells that form the blood-brain barrier (BBB) are coated with glycocalyx, on the luminal side, and with the basement membrane and astrocyte endfeet, on the abluminal side. However, it is unclear how exactly the glycocalyx and extravascular structures contribute to BBB properties. We used two-photon microscopy in anesthetized mice to record passive transport of four different-sized molecules-sodium fluorescein (376 Da), Alexa Fluor (643 Da), 40-kDa dextran, and 150-kDa dextran-from blood to brain, at the level of single cortical capillaries. Both fluorescein and Alexa penetrated nearly the entire glycocalyx volume, but the dextrans penetrated less than 60% of the volume. This suggested that the glycocalyx was a barrier for large but not small molecules. The estimated permeability of the endothelium was the same for fluorescein and Alexa but several-fold lower for the larger dextrans. In the extravascular compartment, co-localized with astrocyte endfeet, diffusion coefficients of the dyes were an order of magnitude lower than in the brain parenchyma. This suggested that the astrocyte endfeet and basement membrane also contributed to BBB properties. In conclusion, the passive transport of small and large hydrophilic molecules through the BBB was determined by three separate barriers: the glycocalyx, the endothelium, and the extravascular compartment. All three barriers must be taken into account in drug delivery studies and when considering BBB dysfunction in disease states.

To elucidate cellular diversity and clonal evolution in tissues and tumors, one must resolve genomic heterogeneity in single cells. To this end, we have developed low-cost, mass-producible micro-/nanofluidic chips for DNA extraction from individual cells. These chips have modules that collect genomic DNA for sequencing or map genomic structure directly, on-chip, with denaturation-renaturation (D-R) optical mapping [Marie R, et al. (2013) Proc Natl Acad Sci USA 110:4893-4898]. Processing of single cells from the LS174T colorectal cancer cell line showed that D-R mapping of single molecules can reveal structural variation (SV) in the genome of single cells. In one experiment, we processed 17 fragments covering 19.8 Mb of the cell's genome. One megabase-large fragment aligned well to chromosome 19 with half its length, while the other half showed variable alignment. Paired-end single-cell sequencing supported this finding, revealing a region of complexity and a 50-kb deletion. Sequencing struggled, however, to detect a 20-kb gap that D-R mapping showed clearly in a megabase fragment that otherwise mapped well to the reference at the pericentromeric region of chromosome 4. Pericentromeric regions are complex and show substantial sequence homology between different chromosomes, making mapping of sequence reads ambiguous. Thus, D-R mapping directly, from a single molecule, revealed characteristics of the single-cell genome that were challenging for short-read sequencing.

Next-generation sequencing of marker genes such as 16S ribosomal RNA is widely used to survey microbial communities. The abundance distribution (AD) of Operational Taxonomic Units (OTUs) in a sample is typically summarized by alpha diversity metrics, e.g. richness and entropy, discarding information about the AD shape. In this work, we describe octave plots, histograms which visualize the shape of microbial ADs by binning on a logarithmic scale with base 2. Optionally, histogram bars are colored to indicate possible spurious OTUs due to sequence error and cross-talk. Octave plots enable assessment of (a) the shape and completeness of the distribution, (b) the effects of noise on measured diversity, (c) whether low-abundance OTUs should be discarded, (d) whether alpha diversity metrics and estimators are reliable, and (e) the additional sampling effort (i.e., read depth) required to obtain a complete census of the community. The utility of octave plots is illustrated in a re-analysis of a prostate cancer study showing that the reported core microbiome is most likely an artifact of experimental error.

Next-generation sequencing (NGS) of marker genes such as 16S ribosomal RNA is widely used to survey microbial communities. The in-sample (alpha) diversity of Operational Taxonomic Units (OTUs) is often summarized by metrics such as richness or entropy which are calculated from observed abundances, or by estimators such as Chao1 which extrapolate to unobserved OTUs. Most such measures are adopted from traditional biodiversity studies, where observational error can often be neglected. However, errors introduced by next-generation amplicon sequencing tend to induce spurious OTUs and spurious counts in OTU tables, both of which are especially prevalent at low abundances. In consequence, traditional metrics may be grossly inaccurate if they are naively applied to NGS OTU tables. In this work, we describe two novel alpha diversity estimators which are calculated from OTU abundances above a specified threshold. The singleton-free estimator (SFE) is a non-parametric estimator which is derived from a similar approach to Chao1 but extrapolates using doublet and triplet abundances rather than singletons and doublets. The octave estimator (OE) fits a log-normal distribution to non-singleton bars of an octave plot. We show that these estimators are effective under suitable conditions, but these conditions rarely apply in practice. We conclude that extrapolating to unobserved OTUs remains an open problem which is unlikely to be solved in the near future.

Given a theoretical model for a self-propelled particle or micro-organism, how does one optimally determine the parameters of the model from experimental data in the form of a time-lapse recorded trajectory? For very long trajectories, one has very good statistics, and optimality may matter little. However, for biological micro-organisms, one may not control the duration of recordings, and then optimality can matter. This is especially the case if one is interested in individuality and hence cannot improve statistics by taking population averages over many trajectories. One can learn much about this problem by studying its simplest case, pure diffusion with no self-propagation. This is an interesting problem also in its own right for the very same reasons: interest in individuality and short trajectories. We summarize our recent results on this latter issue here and speculate about the extent to which similar results may be obtained also for self-propelled particles.

Scientific Reports 6: Article number: 28680; published online: 06 July 2016; updated: 06 September 2017. In the original version of this Article, the Supplementary Software files were omitted. This has been corrected in the HTML version of the Article; the PDF version was correct at the time of publication.

We reanalyze trajectories of hOGG1 repair proteins diffusing on DNA. A previous analysis of these trajectories with the popular mean-squared-displacement approach revealed only simple diffusion. Here, a new optimal estimator of diffusion coefficients reveals two-state kinetics of the protein. A simple, solvable model, in which the protein randomly switches between a loosely bound, highly mobile state and a tightly bound, less mobile state is the simplest possible dynamic model consistent with the data. It yields accurate estimates of hOGG1's (i) diffusivity in each state, uncorrupted by experimental errors arising from shot noise, motion blur and thermal fluctuations of the DNA; (ii) rates of switching between states and (iii) rate of detachment from the DNA. The protein spends roughly equal time in each state. It detaches only from the loosely bound state, with a rate that depends on pH and the salt concentration in solution, while its rates for switching between states are insensitive to both. The diffusivity in the loosely bound state depends primarily on pH and is three to ten times higher than in the tightly bound state. We propose and discuss some new experiments that take full advantage of the new tools of analysis presented here., National Institutes of Health (U.S.) (Grant ST32 GM07598-25)

Next-generation sequencing (NGS) has caused a revolution, yet left a gap: long-range genetic information from native, non-amplified DNA fragments is unavailable. It might be obtained by optical mapping of megabase-sized DNA molecules. Frequently only a specific genomic region is of interest, so here we introduce a method for selection and enrichment of megabase-sized DNA molecules intended for single-molecule optical mapping: DNA from a human cell line is digested by the NotI rare-cutting enzyme and size-selected by pulsed-field gel electrophoresis. For demonstration, more than 600 sub-megabase- to megabase-sized DNA molecules were recovered from the gel and analysed by denaturation-renaturation optical mapping. Size-selected molecules from the same gel were sequenced by NGS. The optically mapped molecules and the NGS reads showed enrichment from regions defined by NotI restriction sites. We demonstrate that the unannotated genome can be characterized in a locus-specific manner via molecules partially overlapping with the annotated genome. The method is a promising tool for investigation of structural variants in enriched human genomic regions for both research and diagnostic purposes. Our enrichment method could potentially work with other genomes or target specified regions by applying other genomic editing tools, such as the CRISPR/Cas9 system.

It has been theoretically suggested and experimentally demonstrated that fast and low-cost sequencing of DNA, RNA, and peptide molecules might be achieved by passing such molecules between electrodes embedded in a nanochannel. The experimental realization of this scheme faces major challenges, however. In realistic liquid environments, typical currents in tunnelling devices are of the order of picoamps. This corresponds to only six electrons per microsecond, and this number affects the integration time required to do current measurements in real experiments. This limits the speed of sequencing, though current fluctuations due to Brownian motion of the molecule average out during the required integration time. Moreover, data acquisition equipment introduces noise, and electronic filters create correlations in time-series data. We discuss how these effects must be included in the analysis of, e.g., the assignment of specific nucleobases to current signals. As the signals from different molecules overlap, unambiguous classification is impossible with a single measurement. We argue that the assignment of molecules to a signal is a standard pattern classification problem and calculation of the error rates is straightforward. The ideas presented here can be extended to other sequencing approaches of current interest.

We show how a bird’s-eye view of genomic structure can be obtained at ∼1-kb resolution from long (∼2 Mb) DNA molecules extracted from whole chromosomes in a nanofluidic laboratory-on-a-chip. We use an improved single-molecule denaturation mapping approach to detect repetitive elements and known as well as unique structural variation. Following its mapping, a molecule of interest was rescued from the chip; amplified and localized to a chromosome by FISH; and interrogated down to 1-bp resolution with a commercial sequencer, thereby reconciling haplotype-phased chromosome substructure with sequence.

We provide a tool for data-driven modeling of motility, data being time-lapse recorded trajectories. Several mathematical properties of a model to be found can be gleaned from appropriate model-independent experimental statistics, if one understands how such statistics are distorted by the finite sampling frequency of time-lapse recording, by experimental errors on recorded positions, and by conditional averaging. We give exact analytical expressions for these effects in the simplest possible model for persistent random motion, the Ornstein-Uhlenbeck process. Then we describe those aspects of these effects that are valid for any reasonable model for persistent random motion. Our findings are illustrated with experimental data and Monte Carlo simulations.

Transition state theory (TST) provides a simple interpretation of many thermally activated processes. It applies successfully on timescales and length scales that differ several orders of magnitude: to chemical reactions, breaking of chemical bonds, unfolding of proteins and RNA structures and polymers crossing entropic barriers. Here we apply TST to out-of-equilibrium transport through confined environments: the thermally activated translocation of single DNA molecules over an entropic barrier helped by an external force field. Reaction pathways are effectively one dimensional and so long that they are observable in a microscope. Reaction rates are so slow that transitions are recorded on video. We find sharp transition states that are independent of the applied force, similar to chemical bond rupture, as well as transition states that change location on the reaction pathway with the strength of the applied force. The states of equilibrium and transition are separated by micrometres as compared with angstroms/nanometres for chemical bonds., Transition state theory has proven to be a powerful tool for the analysis of a number of processes, perhaps most commonly chemical reactions. Here, the authors use transition state theory to model a directly observable, micron scale process—the transport of DNA molecules in a confined environment.

Structure and function of an individual biomolecule can be explored with minimum two fluorescent markers of different colors. Since the light of such markers can be spectrally separated and imaged simultaneously, the markers can be colocalized. Here, we describe the method used for such two-color colocalization microscopy. Then we extend it to fluorescent markers with fixed orientations and in intramolecular proximity. Our benchmarking of this extension produced two extra results: (a) we established short double-labeled DNA molecules as probes of 3D orientation of anything to which one can attach them firmly; (b) we established how to map with super-resolution between color-separated channels, which should be useful for all dual-color colocalization measurements with either fixed or freely rotating fluorescent molecules. Throughout, we use only simple means: from each color-separated microscope image in a time-lapse movie, we simultaneously determine both the relative (x,y)-separation of the fluorophores and their individual orientations in space, both with accuracy and precision. The relative positions and orientations of two domains of the same molecule are thus time-resolved. Using short double-stranded DNA (dsDNA) molecules internally labeled with two fixed fluorophores, we (i) demonstrate the accuracy and precision of our localization- and mapping-methods, using the known structure of dsDNA as benchmark; (ii) resolve 10 base pair differences in fluorophore separations; (iii) determine the unique 3D orientation of each DNA molecule.

We determine the nonuniform stretching of and tension in a mega base pairs-long fragment of deoxyribonucleic acid (DNA) that is flow stretched in a nanofluidic chip. We use no markers, do not know the contour length of the DNA, and do not have the full DNA molecule inside our field of view. Instead, we analyze the transverse thermal motion of the DNA. Tension at the center of the DNA adds up to 16 pN, giving almost fully stretched DNA. This method was devised for optical mapping of DNA, specifically, DNA denaturation patterns. It may be useful also for other studies, e.g., DNA-protein interactions, specifically, their tension dependence. Generally, wherever long strands of DNA---e.g., native DNA extracted from human cells or bacteria---must be stretched with ease for inspection, this method applies.

Optical-tweezers experiments in molecular and cell biology often take place near the surface of the microscope slide that defines the bottom of the sample chamber. There, as elsewhere, force measurements require force-calibrated tweezers. In bulk, one can calculate the tweezers force from first principles, as recently demonstrated. Near the surface of the microscope slide, this absolute calibration method fails because it does not account for reverberations from the slide of the laser beam scattered by the trapped microsphere. Nor does it account for evanescent waves arising from total internal reflection of wide-angle components of the strongly focused beam. In the present work we account for both of these phenomena. We employ Weyl's angular spectrum representation of spherical waves in terms of real and complex rays and derive a fast-converging recursive series of multiple reflections that describes the reverberations, including also evanescent waves. Numerical simulations for typical setup parameters evaluate these effects on the optical force and trap stiffness, with emphasis on axial trapping. Results are in good agreement with available experimental data. Thus, absolute calibration now applies to all situations encountered in practice.

In localization-based microscopy, super-resolution is obtained by analyzing isolated diffraction-limited spots imaged, typically, with EMCCD cameras. To compare experiments and calculate localization precision, the photon-to-signal amplification factor is needed but unknown without a calibration of the camera. Here we show how this can be done post festum from just a recorded image. We demonstrate this (i) theoretically, mathematically, (ii) by analyzing images recorded with an EMCCD camera, and (iii) by analyzing simulated EMCCD images for which we know the true values of parameters. In summary, our method of calibration-on-the-spot allows calibration of a camera with unknown settings from old images on file, with no other info needed. Consequently, calibration-on-the-spot also makes future camera calibrations before and after measurements unnecessary, because the calibration is encoded in recorded images during the measurement itself, and can at any later time be decoded with calibration-on-the-spot.

Up to one in four lung-transplanted patients develop pulmonary infiltrates and impaired oxygenation within the first days after lung transplantation. Known as primary graft dysfunction (PGD), this condition increases mortality significantly. Complex interactions between donor lung and recipient immune system are the suspected cause. We took an integrative, systems-level approach by first exploring whether the recipient's immune response to PGD includes the development of long-lasting autoreactivity. We next explored whether proteins displaying such differential autoreactivity also display differential gene expression in donor lungs that later develop PGD compared with those that did not. We evaluated 39 patients from whom autoantibody profiles were already available for PGD based on chest radiographs and oxygenation data. An additional nine patients were evaluated for PGD based on their medical records and set aside for validation. From two recent donor lung gene expression studies, we reanalysed and paired gene profiles with autoantibody profiles. Primary graft dysfunction can be distinguished by a profile of differentially reactive autoantibodies binding to 17 proteins. Functional analysis showed that 12 of these proteins are part of a protein-protein interaction network (P=3 x 10⁻⁶) involved in proliferative processes. A nearest centroid classifier assigned correct PGD grades to eight out of the nine patients in the validation cohort (P=0·048). We observed significant positive correlation (r=0·63, P=0·011) between differences in IgM reactivity and differences in gene expression levels. This connection between donor lung gene expression and long-lasting recipient IgM autoantibodies towards a specific set of proteins suggests a mechanism for the development of autoimmunity in PGD.

Obliterative bronchiolitis (OB) continues to be the major limitation to long-term survival after lung transplantation. The specific aetiology and pathogenesis of OB are not well understood. To explore the role of autoreactivity in OB, we spotted 751 different self molecules onto glass slides, and used these antigen microarrays to profile 48 human serum samples for immunoglobulin G (IgG) and IgM autoantibodies; 27 patients showed no or mild bronchiolitis obliterans syndrome (BOS; a clinical correlate of OB) and 15 patients showed medium to severe BOS. We now report that these BOS grades could be differentiated by a profile of autoantibodies binding to 28 proteins or their peptides. The informative autoantibody profile included down-regulation as well as up-regulation of both IgM and IgG specific reactivities. This profile was evaluated for robustness using a panel of six independent test patients. Analysis of the functions of the 28 informative self antigens showed that eight of them are connected in an interaction network involved in apoptosis and protein metabolism. Thus, a profile of autoantibodies may reflect pathological processes in the lung allograft, suggesting a role for autoimmunity in chronic rejection leading to OB.

We optimally localize isolated fluorescent beads and molecules imaged as diffraction-limited spots, determine the orientation of molecules, and present reliable formulae for the precisions of various localization methods. For beads, theory and experimental data both show that unweighted least-squares fitting of a Gaussian squanders one third of the available information, a popular formula for its precision exaggerates beyond Fisher's information limit, and weighted least-squares may do worse, while maximum likelihood fitting is practically optimal.

We show that arrays of nanopit structures etched in a nanoslit can control the positioning and conformation of single DNA molecules in nanofluidic devices. By adjusting the spacing, organization and placement of the nanopits it is possible to immobilize DNA at predetermined regions of a device without additional chemical modification and achieve a high degree of control over local DNA conformation. DNA can be extended between two nanopits and in closely spaced arrays will self-assemble into “connect-the-dots” conformations consisting of locally pinned segments joined by fluctuating linkers. These results have broad implications for nanotechnology fields that require methods for the nanoscale positioning and manipulation of DNA.

The historical co-evolution of biological motility models with models of Brownian motion is outlined. Recent results for how to derive cell-type-specific motility models from experimental cell trajectories are reviewed. Experimental work in progress, which tests the generality of this phenomenological model building is reported. So is theoretical work in progress, which explains the characteristic time scales and correlations of phenomenological models in terms of the dynamics of cytoskeleton, lamellipodia, and pseudopodia.

Turbulent water vapour fluxes measured with closed-path eddy correlation (EC) systems are unintentionally low-pass filtered by the system in a manner that varies with environmental conditions. Why and how is described here. So is the practical method that systematically corrects long-term flux datasets for this substantial measurement error. In contrast to earlier studies, a large number of spectra and raw data have been used in the analysis to define the low-pass filtering characteristic of the EC system. This revealed that the cut-off frequency of the closed-path EC system for water vapour concentration measurements decreases exponentially with increasing relative humidity. After correction for this unintended filtering, the fluxes are consistent with CO2 and H2O fluxes that were measured with an open-path sensor at the same time. The correction of water vapour flux measurements over a Beech forest in Soro, Zealand, Denmark, amounted on average to 42% of the measured flux, while it was only 4% for the CO2 flux, which was measured with the same EC system. We recommend using the described method to correct water vapour fluxes measured in any closed-path EC system for unintended low-pass filtering effects. Other than for CO2 is the magnitude of the correction for water vapour flux measurements unsatisfactorily high, i.e. the EC system needs to be technically improved. Our results suggest that such high correction can be avoided by keeping relative humidity in the entire gas transport system of the EC system lower than 30%, e.g. by heating intake filters and tubes.

We demonstrate a novel, yet simple tool for the study of structure and function of biomolecules by extending two-colour co-localization microscopy to fluorescent molecules with fixed orientations and in intra-molecular proximity. From each colour-separated microscope image in a time-lapse movie and using only simple means, we simultaneously determine both the relative (x,y)-separation of the fluorophores and their individual orientations in space with accuracy and precision. The positions and orientations of two domains of the same molecule are thus time-resolved. Using short double-stranded DNA molecules internally labelled with two fixed fluorophores, we demonstrate the accuracy and precision of our method using the known structure of double-stranded DNA as a benchmark, resolve 10-base-pair differences in fluorophore separations, and determine the unique 3D orientation of each DNA molecule, thereby establishing short, double-labelled DNA molecules as probes of 3D orientation of anything to which one can attach them firmly., Single molecule super-resolution microscopy can reliably localize objects with high precision, but the accuracy can be called into question. Here the authors present a methodology to accurately and precisely measure nanometre separation and orientation of two fixed fluorophores from colour-separated images.

Molecular motors are responsible for numerous cellular processes from cargo transport to heart contraction. Their interactions with other cellular components are often transient and exhibit kinetics that depend on load. Here, we measure such interactions using ‘harmonic force spectroscopy'. In this method, harmonic oscillation of the sample stage of a laser trap immediately, automatically and randomly applies sinusoidally varying loads to a single motor molecule interacting with a single track along which it moves. The experimental protocol and the data analysis are simple, fast and efficient. The protocol accumulates statistics fast enough to deliver single-molecule results from single-molecule experiments. We demonstrate the method's performance by measuring the force-dependent kinetics of individual human β-cardiac myosin molecules interacting with an actin filament at physiological ATP concentration. We show that a molecule's ADP release rate depends exponentially on the applied load, in qualitative agreement with cardiac muscle, which contracts with a velocity inversely proportional to external load., Single molecule methods for measuring load dependence are fundamental for molecular motor research. Here, Sung et al. introduce harmonic force spectroscopy, a method that randomly applies varying loads at high frequency, allowing the determination of load dependent parameters of human β-cardiac myosin at physiological ATP concentration.

We demonstrate all-polymer injection molded devices for optical mapping of denaturation–renaturation (DR) patterns on long, single DNA-molecules from the human genome. The devices have channels with ultra-low aspect ratio, only 110 nm deep while 20 μm wide, and are superior to the silica devices used previously in the field. With these polymer devices, we demonstrate on-chip recording of DR images of DNA-molecules stretched to more than 95% of their contour length. The stretching is done by opposing flows Marie et al (2013 Proc. Natl Acad. Sci. USA 110 4893–8). The performance is validated by mapping 20 out of 24 Mbp-long DNA fragments to the human reference genome. We optimized fabrication of the devices to a yield exceeding 95%. This permits a substantial economies-of-scale driven cost-reduction, leading to device costs as low as 3 USD per device, about a factor 70 lower than the cost of silica devices. This lowers the barrier to a wide use of DR mapping of native, megabase-size DNA molecules, which has a huge potential as a complementary method to next-generation sequencing.

Magnetic biosensors detect magnetic beads that, mediated by a target, have bound to a functionalized area. This area is often larger than the area of the sensor. Both the sign and magnitude of the average magnetic field experienced by the sensor from a magnetic bead depends on the location of the bead relative to the sensor. Consequently, the signal from multiple beads also depends on their locations. Thus, a given coverage of the functionalized area with magnetic beads does not result in a given detector response, except on the average, over many realizations of the same coverage. We present a systematic theoretical analysis of how this location-dependence affects the sensor response. The analysis is done for beads magnetized by a homogeneous in-plane magnetic field. We determine the expected value and standard deviation of the sensor response for a given coverage, as well as the accuracy and precision with which the coverage can be determined from a single sensor measurement. We show that statistical fluctuations between samples may reduce the sensitivity and dynamic range of a sensor significantly when the functionalized area is larger than the sensor area. Hence, the statistics of sampling is essential to sensor design. For illustration, we analyze three important published cases for which statistical fluctuations are dominant, significant, and insignificant, respectively.

Motivation: Next-generation sequencing produces vast amounts of data with errors that are difficult to distinguish from true biological variation when coverage is low. Results: We demonstrate large reductions in error frequencies, especially for high-error-rate reads, by three independent means: (i) filtering reads according to their expected number of errors, (ii) assembling overlapping read pairs and (iii) for amplicon reads, by exploiting unique sequence abundances to perform error correction. We also show that most published paired read assemblers calculate incorrect posterior quality scores. Availability and implementation: These methods are implemented in the USEARCH package. Binaries are freely available at http://drive5.com/usearch. Contact: robert@drive5.com Supplementary information: Supplementary data are available at Bioinformatics online.

Optical tweezers are a versatile tool in biophysics and have matured from a tool of manipulation to a tool of precise measurements. We argue here that the data analysis with advantage can be developed to a level of sophistication that matches that of the instrument. We review methods of analysis of optical tweezers data, primarily based on the power spectra of time series of positions for trapped spherical objects. The majority of precise studies in the literature are performed on in vitro systems, whereas in the present work, an example of an in vivo system is presented for which precise power spectral analysis is both useful and necessary. The biological system is the cytoplasm of fission yeast, Schizosaccharomyces pombe in which we observe subdiffusion of lipid granules. In a search for the cause of subdiffusion, we chemically disrupt the actin network in the cytoplasm and further consider in vitro networks of filamenteous actin undergoing similar chemical disruption.

Sequence-specific binding to DNA in the presence of competing non-sequence-specific ligands is a problem faced by proteins in all organisms. It is akin to the problem of parking a truck at a loading bay by the side of a road in the presence of cars parked at random along the road. Cars even partially covering the loading bay prevent correct parking of the truck. Similarly on DNA, non-specific ligands interfere with the binding and function of sequence-specific proteins. We derive a formula for the probability that the loading bay is free from parked cars. The probability depends on the size of the loading bay and allows an estimation of the size of the footprint on the DNA of the sequence-specific protein by assaying protein binding or function in the presence of increasing concentrations of non-specific ligand. Assaying for function gives an 'activity footprint'; the minimum length of DNA required for function rather than the more commonly measured physical footprint. Assaying the complex type I restriction enzyme, EcoKI, gives an activity footprint of similar to 66 bp for ATP hydrolysis and 300 bp for the DNA cleavage function which is intimately linked with translocation of DNA by EcoKI. Furthermore, considering the coverage of chromosomal DNA by proteins in vivo, our theory shows that the search for a specific DNA sequence is very difficult; most sites are obscured by parked cars. This effectively rules out any significant role in target location for mechanisms invoking one-dimensional, linear diffusion along DNA.

Optical tweezers are used as force transducers in many types of experiments. The force they exert in a given experiment is known only after a calibration. Computer codes that calibrate optical tweezers with high precision and reliability in the (x, y)-plane orthogonal to the laser beam axis were written in MatLab (MathWorks Inc.) and are presented here. The calibration is based on the power spectrum of the Brownian motion of a dielectric bead trapped in the tweezers. Precision is achieved by accounting for a number of factors that affect this power spectrum. First, cross-talk between channels in 2D position measurements is tested for, and eliminated if detected. Then, the Lorentzian power spectrum that results from the Einstein– Ornstein–Uhlenbeck theory, is fitted to the low-frequency part of the experimental spectrum in order to obtain an initial guess for parameters to be fitted. Finally, a more complete theory is fitted, a theory that optionally accounts for the frequency dependence of the hydrodynamic drag force and hydrodynamic interaction with a nearby cover slip, for effects of finite sampling frequency (aliasing), for effects of anti-aliasing filters in the data acquisition electronics, and for unintended “virtual” filtering caused by the position detection system. Each of these effects can be left out or included as the user prefers, with user-defined parameters. Several tests are applied to the experimental data during calibration to ensure that the data comply with the theory used for their interpretation: Independence of x -a ndy-coordinates, Hooke’s law, exponential distribution of power spectral values, uncorrelated Gaussian scatter of residual values. Results are given with statistical errors and covariance matrix.

The force exerted by an optical trap on a dielectric bead in a fluid is often found by fitting a Lorentzian to the power spectrum of Brownian motion of the bead in the trap. We present explicit functions of the experimental power spectrum that give the values of the parameters fitted, including error bars and correlations, for the best such χ2 fit in a given frequency range. We use these functions to determine the information content of various parts of the power spectrum, and find, at odds with lore, much information at relatively high frequencies. Applying the method to real data, we obtain perfect fits and calibrate tweezers with less than 1% error when the trapping force is not too strong. Relatively strong traps have power spectra that cannot be fitted properly with any Lorentzian, we find. This underscores the need for better understanding of the power spectrum than the Lorentzian provides. This is achieved using old and new theory for Brownian motion in an incompressible fluid, and new results for ...

Without exceptions, in all living cells NADH is a key metabolite linking a large number of metabolic pathways. Flux rates through such pathways are an essential component in the understanding of the functioning of living cells. Knowledge about the way these fluxes depend on the concentrations of the metabolites involved (including NADH/NAD + ) allows calculation of these fluxes. Therefore, a method to determine the concentration of free NADH is necessary. A distinction between the free and protein-bound NADH can be made on the basis of fluorescence emission spectra and fluorescence lifetimes. A method for such measurements using a microscopic set-up for time-gated fluorescence spectroscopy has been introduced by Schneckenburger and co-workers (Paul RJ, Schneckenburger H. Naturwissenschaften 83 , pp. 32-35, 1996). We further improve this method by first characterizing NADH binding to model proteins by isothermal titration calorimetry and fluorescence. This allows a precise calculation of bound and free NADH and their respective spectra. An analysis of experimental data is advanced by applying two-component deconvolution and subsequent fitting. Using this method we can detect a significant proportion of free NADH in isolated potato tuber mitochondria respiring malate. Taken together these improvements allow a more accurate characterization of the NADH turnover in biological systems.

The motion of a single protein, a λ-receptor in the outer membrane of E. coli, is studied with optical tweezers. We present improved measurements and an analysis that accounts for stochastic errors, filters in the detection system, aliasing and hydrodynamic effects. We test a simple model for the protein's motion and find it in agreement with the low-frequency part of the data. We thus determine physical parameter values for the system with improved precision. The diffusion coefficient describing the motion of the λ-receptor is now obtained with 2% relative error for individual receptors, and varies between bacteria with roughly 70% root-mean-square deviation about the mean. This improved analysis also reveals that the simple model must be revised in order to agree with the high-frequency part of the power spectrum.

We characterize the frequency-dependent response of a photo detection system based on a Si-PIN photodiode and a laser with wavelength 1064 nm, a system commonly used with optical tweezers. We chopped the laser beam with chopper frequencies from 200 Hz to 14 kHz, and found an exponentially delayed response of the detection system with a characteristic delay time of ∼20 μs. The physical mechanism causing this time delay is silicon’s transparency to 1064 nm light: Photons are absorbed and create charge carriers not only in the diode’s depletion layer, where they are detected within nano-seconds, but predominantly in the n-layer, where they remain undetected till transported out by thermal diffusion. The diode’s response is dominated by this delay which can be characterized as a first-order low-pass filter with a 3dB-frequency of 8–9 kHz, depending on laser intensity. Measurements exploiting frequencies near or above this 3dB-frequency must be corrected for this unintended filter effect. We describe how to do...

We demonstrate that a microfabricated bump array can concentrate genomic-length DNA molecules efficiently at continuous, high flow velocities, up to 40 μm=s, if the single-molecule DNA globule has a sufficiently large shear modulus. Increase in the shear modulus is accomplished by compacting the DNA molecules to minimal coil size using polyethylene glycol (PEG) derived depletion forces. We map out the sweet spot, where concentration occurs, as a function of PEG concentration and flow speed using a combination of theoretical analysis and experiment. Purification of DNA from enzymatic reactions for next-generation DNA-sequencing libraries will be an important application of this development.

We stretch a single DNA molecule with thermophoretic forces and measure these forces with a spring balance: the DNA molecule itself. It is an entropic spring which we calibrate, using as a benchmark its Brownian motion in the nanochannel that contains and prestretches it. This direct measurement of the thermophoretic force in a static configuration finds forces up to 130 fN. This is eleven times stronger than the force experienced by the same molecule in the same thermal gradient in bulk, where the molecule shields itself. Our stronger forces stretch the middle of the molecule up to 80% of its contour length. We find the Soret coefficient per unit length of DNA at various ionic strengths. It agrees, with novel precision, with results obtained in bulk for DNA too short to shield itself and with the thermodynamic model of thermophoresis.

How does one optimally determine the diffusion coefficient of a diffusing particle from a single-time-lapse recorded trajectory of the particle? We answer this question with an explicit, unbiased, and practically optimal covariance-based estimator (CVE). This estimator is regression-free and is far superior to commonly used methods based on measured mean squared displacements. In experimentally relevant parameter ranges, it also outperforms the analytically intractable and computationally more demanding maximum likelihood estimator (MLE). For the case of diffusion on a flexible and fluctuating substrate, the CVE is biased by substrate motion. However, given some long time series and a substrate under some tension, an extended MLE can separate particle diffusion on the substrate from substrate motion in the laboratory frame. This provides benchmarks that allow removal of bias caused by substrate fluctuations in CVE. The resulting unbiased CVE is optimal also for short time series on a fluctuating substrate. We have applied our estimators to human 8-oxoguanine DNA glycolase proteins diffusing on flow-stretched DNA, a fluctuating substrate, and found that diffusion coefficients are severely overestimated if substrate fluctuations are not accounted for.

A muscle contracts rapidly under low load, but slowly under high load. Thisload-dependent muscle shortening has been described with a hyperbolicload-velocity curve. Its molecular mechanisms remain to be elucidated, however.During muscle contraction, myosins in thick filaments interact with actin inthin filaments in the sarcomere, cycling between a strongly bound state (forceproducing state) and a weakly bound state (relaxed state). Huxley and Simmonshave previously proposed that the transition from the strong to the weak interaction can be modulated by an external load, i.e., the transition is slow underhigh load and fast under low load.We use a new, simple method we call "harmonic force spectroscopy" toextract a load-velocity relationship from a single human beta cardiac myosinII motor (S1). With a dual-beam optical trap, we hold an actin dumbbell over asingle myosin molecule that is anchored to the microscope stage, which weoscillate sinusoidally in the direction of the dumbbell. Upon binding of themotor to the actin filament, it experiences an oscillatory load with a meanvalue that may be directed forward or backward, depending on where the binding took place. We find that the duration of the strongly bound state at saturating [ATP] is exponentially correlated with the mean load applied to themyosin during the bound state, which is explained by Arrhenius transition theory.With an independent stroke size measurement, we obtained an exponentialload-velocity curve from a single human beta cardiac myosin S1. We alsocompare load-velocity curves for wild-type motors with load-velocity curvesof mutant forms that cause hypertrophic or dilated-cardiomyopathy (HCMor DCM), in order to understand the effects of mutations on the contractile cycleat the single molecule level.

Intention of movement of left or right index finger, or right foot is recognized in electroencephalograms (EEGs) from three subjects. The authors present a multichannel classification method that uses a "committee" of artificial neural networks to do this. The classification method automatically finds spatial regions on the skull relevant for the classification task. Depending on subject, correct recognition of intended movement was achieved in 75%-98% of trials not seen previously by the committee, on the basis of single EEGs of one-second duration. Frequency filtering did not improve recognition. Classification was optimal during the actual movement, but a first peak in the classification success rate was observed in all subjects already when they had been cued which movement later to perform.

We have studied 56-channel electroencephalograms (EEG) from three subjects who planned and performed three kinds of movements, left and right index finger, and right foot movement. Using autoregressive modeling of EEG time series and artificial neural nets (ANN), we have developed a classifier that can tell which movement is performed from a segment of the EEG signal from a single trial. The classifier's rate of recognition of EEGs not seen before was 92-99% on the basis of a 1s segment per trial. The recognition rate provides a pragmatic measure of the information content of the EEG signal. This high recognition rate makes the classifier suitable for a so-called 'Brain-Computer Interface', a system that allows one to control a computer, or another device, with ones brain waves. Our classifier Laplace filters the EEG spatially, but makes use of its entire frequency range, and automatically locates regions of relevant activity on the skull.