Sub-diffraction error mapping for localisation microscopy images

Assessing the quality of localisation microscopy images is highly challenging due to the difficulty in reliably detecting errors in experimental data. The most common failure modes are the biases and errors produced by the localisation algorithm when there is emitter overlap. Also known as the high density or crowded field condition, significant emitter overlap is normally unavoidable in live cell imaging. Here we use Haar wavelet kernel analysis (HAWK), a localisation microscopy data analysis method which is known to produce results without bias, to generate a reference image. This enables mapping and quantification of reconstruction bias and artefacts common in all but low emitter density data. By avoiding comparisons involving intensity information, we can map structural artefacts in a way that is not adversely influenced by nonlinearity in the localisation algorithm. The HAWK Method for the Assessment of Nanoscopy (HAWKMAN) is a general approach which allows for the reliability of localisation information to be assessed

Uncertainty and reconciliation of multi-scale measurements of methane emissions from oil and gas facilities

Methane emissions from oil and natural gas facilities contribute significantly to global greenhouse gas emissions. Identifying pathways for emission reductions relies on accurate emission accounting across different spatial and temporal scales, from the source-level, which guides mitigation strategies, to the global-level in order to benchmark reduction progress. Regulatory and voluntary reporting initiatives are moving towards measurement-informed methane emission inventories, as recent studies have determined that generic estimation methods tend to underestimate emissions. Methane measurements can be used to account for changes in operation or equipment that lead to emission reductions, and to identify and quantify large emission events that contribute significantly to overall emissions. Measurement technologies span a wide spatiotemporal range, providing many different types of data. Measurement data can range from weekly satellite column concentration measurements to near-continuous source-level flowmeter data. Multi-scale measurements are an important part of advancing methane reporting and mitigation initiatives, as different forms of technology are optimal for observing different types of emissions. Estimates from different measurements will likely never precisely agree, which is both a function of technology diversity and the underlying variability of the emissions themselves. Uncertainty quantification of methane measurements is a necessary step in reconciling multi-scale measurements for the construction of measurement-informed inventories. Accurate interpretation of measurement data requires uncertainty quantification, which can contextualize measurements and estimates against one another. This thesis identifies the types of uncertainty that arise when methane measurements are used in the construction of annual inventories. This work proposes frameworks to quantify different types of extrapolation uncertainty through a series of case studies in the Barnett Shale, Permian Basin, and Green River Basin. This work also proposes metrics that can be used to inform methane measurement campaign design in order to minimize extrapolation uncertainty and improve the statistical significance of collected data.Chemical Engineerin

Single-molecule stochastic localization fluorescence nanoscopy

Hasta hace unos 20 años se creía que la difracción de la luz imponía un límitefundamental de unos 200 nm a la resolución espacial de un microscopio óptico. Lasnanoscopías de fluorescencia, también llamadas microscopías de superresolución,han quebrado esta barrera y permiten en teoría alcanzar la máxima resoluciónespacial con sentido físico, es decir el tamaño mismo de la fuente de luz. En lapráctica, sin embargo, la resolución se ve limitada a unos 20 nm por efecto devariables experimentales como la relación señal-ruido y el fotoblanqueo de losmarcadores fluorescentes. Además, las nanoscopías de fluorescencia mantienenlas ventajas de la microscopía de fluorescencia tradicional, como el acceso pocoinvasivo y la alta sensibilidad y especificidad. Se denomina "localización de una molécula individual" al proceso numéricopor el cual se extrae la posición de un emisor único a partir de la medición desu patrón de intensidad. La nanoscopía por localización estocástica de moléculasindividuales (o simplemente "nanoscopía por localización") consiste en la adquisición secuencial de imágenes en las que en cada una un subconjunto estocástico delos fluoróforos de una muestra son resueltos individualmente. Como los patronesde emisión no se superponen, la precisión de localización solo depende del númerode fotones detectados de cada emisión. La imagen final se construye con las posicionesde cada fluoróforo previamente localizado. Para obtener una imagen desuperresolución es necesario que los marcadores estén separados por distanciasmenores a su imagen limitada por difracción y que éstos emitan de manera intermitente (que se enciendan y apaguen), de manera que en algún momento puedanobservarse individualmente. La nanoscopía por localización comprende a un conjunto de técnicas diferenciadas entre sí de acuerdo al mecanismo que permite elencendido y apagado de los marcadores fluorescentes. En la presente Tesis se estudian aspectos fundamentales e instrumentales dela nanoscopía por localización y se la aplica al estudio de preguntas biológicas. En el Capítulo 1 se desarrollan los conceptos fundamentales y limitaciones dela microscopía de uorescencia, y se introducen las técnicas de superresolución. En el Capítulo 2 se detallan los métodos y estado del arte de la nanoscopía porlocalización. En el Capítulo 3 se caracteriza el nanoscopio por localización conposibilidad de obtener imágenes en 3D y a dos colores de emisión, que fuera construidocomo parte del trabajo de Tesis. Finalmente, en los Capítulos 4 y 5 sedescriben aplicaciones de dicho nanoscopio en dos proyectos de relevancia biológica:el estudio en neuronas hipocampales de la estructura periódica de espectrina yla distribución espacial de proteínas presentes en la membrana del Trypanosomacruzi que median la interacción entre el parásito y el huésped.Until twenty years ago it was considered that the diffraction of light imposeda fundamental limit of around 200 nm to the resolution of an optical microscope. Fluorescence nanoscopy, also known as super-resolution uorescence microscopy,has overcome this limit. It achieves the theoretical maximum spatial resolution,which is the size of the light source itself. In practice, however, the resolution islimited to around 20 nm by experimental factors like the signal-to-noise ratio andthe photobleaching of uorescent markers. Besides, fluorescence nanoscopy maintainsthe advantages of traditional fluorescence microscopy, like its low invasivityand its high sensitivity and specificity. Single-molecule localization is the numerical process that extracts the single moleculeposition from measuring its emission pattern. Sigle-molecule stochasticlocalization nanoscopy (or simply "localization nanoscopy") consists of the sequentialacquisition of images of well separated fluorophores from a stochasticsubset of all fluorophores in the sample. As their emission patterns do not overlap,the position of each molecule can be determined with a precision only limitedby the number of detected photons. A final super-resolved image is reconstructedfrom the localizations of all the fluorophores of the sequence of images. In orderto obtain a super-resolved image, it is essential to have fluorescent markerscloser to each other than the diffraction limit. Also, they must intermittentlyswitch on and off, so that at a given point in time they can be imaged individually. Stochastic localization nanoscopy denotes a group of techniques each with adifferent mechanism for the on-off switching of the fluorophores. In this thesis we study fundamental and instrumental aspects of localizationnanoscopy and we apply it to the study of biological questions. In Chapter 1the fundamental concepts, potential and limitations of fluorescence microscopyare presented, followed by an introduction to super-resolution techniques. Thefundamental principles and methods of single-molecule localization fluorescencenanoscopy are explained in detail in Chapter 2. Chapter 3 gives a complete descriptionof the nanoscope built as part of this thesis work at the Centro de Investigaciones en Bionanociencias (CIBION), along with guidelines for its operationand an illustration of its performance. In Chapters 4 and 5 two biologicalapplications of the nanoscope are presented, that address nanoscale organizationproteins: firstly, the quantification of the periodic spectrin structure present inhippocampal neurons and secondly, the spatial distribution of proteins on theouter membrane of the Trypanosoma cruzi that mediate the parasite-host interaction. Finally, the conclusions of this thesis and future perspectives are unfoldedin Chapter 6.Fil: Barabas, Federico Martín. Universidad de Buenos Aires. Facultad de Ciencias Exactas y Naturales; Argentina

Spatial and spectral brightness improvement of single-mode laser diode arrays

This thesis addresses the strong need for efficient and compact techniques for brightness enhancement of laser diode arrays and responds to the challenges created for high performance optics and techniques for laser characterisation. A novel optical inter-leaving method for a 7-bar stack of single-mode emitters, providing a nearly 2-fold improvement in the slow axis beam parameter product, enabling fibre-coupling, is demonstrated. A laser-written dual-axis optics approach is used to perform challenging slow axis collimation combined with fast axis correction for closely-packed 49-single-mode emitter bars, to provide low-loss collimation with high pointing accuracy of less than 3% and 10% of a beam divergence in the fast and slow axis direction, respectively. This produces excellent source for application beam-combined laser diode systems. An emitter-by-emitter simultaneous analysis is used to provide spectra and far field pointing for all emitters and evaluate the performance of various external cavity configurations with Volume Holographic Gratings (VHGs). For the ultra-collimated bars, high efficiency VHG-locking is shown to be maintained over enhanced range of temperatures (>17˚C) and large laser-VHG distances (>110 mm). Highly effective feedback enables the use of a folded cavity configuration for wavelength selection over a range of 8 nm for the full 49-emitter bar, giving a prospect for multi-wavelength single-VHG-locking of bars for cost-effective spectral combining. An innovative technique of wavelength stepping by individually-formed folded cavities for 5 and 7 sections along the bar demonstrates a potential to produce a source for high performance dense spectral beam combining. In a VHG-based Talbot cavity, eight emitters are coherently locked with a highvisibility interference pattern at 1W of output power. The results of phase-locking for full 49-emitter bar show that the slow axis pointing variation of ± 2mrad produces different supermodes, for a fixed alignment of the cavity, thus it must be additionally corrected for further improvement

Part I: Super-resolution Microscopy Method Development Part II: Investigations of Transcription Regulation by Chromosomal Organization in Bacteria

Part I: SMLM provides not only high-resolution images of molecular assemblies beyond the diffraction limit but also enables quantitative analysis of the dynamics and compositions. However, challenges in imaging and analysis due to cell geometry, resolution limit, and fluorophore properties impede the full potential of SMLM. To address these challenges, I first developed a single- molecule tracking methodology that minimizes the confinement of diffusing molecules to obtain accurate diffusion coefficients and transition rates. Next, I developed a methodology to improve three-dimensional (3D)-SMLM imaging by directly taking into account the variability of 3D point-spread-functions, which produces superior resolution compared to existing methodologies. Finally, I developed a method to correct for blinking-artifacts. Blinking-artifacts are caused by repeated localizations of the same fluorophores, which distort images and produce false nanoclusters. I derived a method to find the ”ground- truth” of the underlying pairwise distribution without any additional calibration. This ground truth enables me to identify the true underlying spatial distribution of molecules in the SMLM image, solving a problem that has long persisted in the field. Part II: It is well established that chromosomal organization dramatically influences transcription, but the underlying mechanisms remain elusive. We hypothesize that supercoiling constrained by the chromosomal topology has an effect on transcription rate and hence coordinates expression within the same topological domain. To examine this hypothesis, I developed a theoretical model to account directly for the buildup of supercoiling due to transcription in a DNA-loop. To investigate how the topology of the chromosome influences transcription further, I then developed the first in vivo assays to manipulate the formation of a “large” chromosomal DNA topological domain in E. coli cells to examine transcription activity of multiple genes enclosed in the domain. My experiments showed that domain formation decreases expression levels of genes both inside and outside the domain — demonstrating a ”long-range” cis-regulatory mechanism due to the “architecture” of the chromosome within bacteria. Finally, using quantitative SMLM, we investigated how ”large-scale” chromosome organization affects the spatial organization of RNA-polymerase (RNAP). We discovered RNAP clusters engaged in active ribosomal RNA synthesis; whose organization is “driven” by the chromosomal organization

Establishing super-resolution imaging of biosilica-embedded proteins in diatoms

Kieselalgen – auch Diatomeen genannt – verfügen über die einzigartige Fähigkeit, nanostrukturierte, hierarchisch aufgebaute Zellwände aus Siliziumdioxid – auch als Biosilica bekannt – mit beispielloser Genauigkeit und Reproduzierbarkeit zu bilden. Ein tieferes Verständnis für diesen Prozess, der als “Biomineralisation“ bekannt ist, ist nicht nur auf dem Gebiet der Grundlagenforschung zu Kieselalgen sehr bedeutsam, sondern auch für die Nutzung dieser Nanostrukturierung in den Materialwissenschaften oder der Nanobiotechnologie. Nach dem derzeitigem Stand der Wissenschaft wird diese Strukturierung durch die Selbstorganisation von Proteinmustern, an denen sich das Siliziumdioxid bildet, erreicht. Um die Funktion und das Zusammenspiel einzelner Proteine, die an diesem Biomineralisationsprozess beteiligt sind, entschlüsseln zu können, ist es essentiell ihre strukturelle Organisation aufzuklären und diese mit den morphologischen Zellwandmerkmalen zu korrelieren. Die Größenordnung dieser Merkmale ist im Bereich von Nanometern angesiedelt. Mit Hilfe der Elektronenmikroskopie können diese Biosilicastrukturen aufgelöst werden, jedoch ist keine proteinspezifische Information verfügbar. Ziel dieser Arbeit war es daher, eine Technik zu etablieren, die in der Lage ist, einzelne Biosilica-assozierte Proteine mit Nanometer-Präzision zu lokalisieren. Um dieses Ziel zu erreichen, wurde Einzelmoleküllokalisationsmikroskopie (single-molecule localization microscopy, kurz: SMLM) beispielhaft in der Kieselalge Thalassiosira pseudonana etabliert. Die Position verschiedener Biosilica-assoziierte Proteine innerhalb des Biosilicas und nach dessen chemischer Auflösung wurde mit einer hohen räumlichen Auflösung bestimmt. Um quantitative Ergebnisse zu erhalten, wurde ein Analyse-Workflow entwickelt, der grafische Benutzeroberflächen und Skripte für die Visualisierung, das Clustering und die Kolokalisation von SMLM Daten beinhaltet. Um optimale Markierungen für SMLM an Biosilica-eingebetteten Proteinen zu finden, wurde ein umfassendes Screening von photo-schaltbaren fluoreszierenden Proteinen durchgeführt. Diese wurden als Fusionsproteine mit Silaffin3, einem Protein, welches eng mit der Biosilica-Zellwand assoziiert ist, exprimiert. Es konnte gezeigt werden, dass nur drei von sechs Kandidaten funktional sind, wenn sie in Biosilica eingebettet sind. Silaffin3 konnte indirekt mittels SMLM mit einer Lokalisationsgenauigkeit von 25 nm detektiert werden. Dies erlaubte es, seine strukturelle Organisation aufzulösen und Silaffin3 als eine Hauptkomponente in der Basalkammer der Fultoportulae zu identifizieren.:1 INTRODUCTION 1 1.1 Diatoms – a model system for biomineralization 3 1.2 Imaging of biosilica and associated organic components 8 1.3 Single-molecule localization microscopy (SMLM) 10 2 METHODS & METHOD DEVELOPMENT FOR SMLM DATASETS 17 2.1 Super-resolution reconstruction 19 2.2 Tools for SMLM resolution estimates 21 2.3 Voronoi tessellation for noise-removal and cluster estimation 25 2.4 Tools for SMLM cluster analysis 27 2.5 Coordinate-based co-localization 32 2.6 PairRice – A novel algorithm to extract distances between cluster pairs 33 2.7 SiMoNa – A new GUI for exploring SMLM datasets 35 3 RESOLUTION OF THE SMLM SETUP TESTED WITH DNA ORIGAMI NANOSTRUCTURES 41 3.1 DNA origami as a length standard 42 3.2 Global resolution estimates 44 3.3 Local resolution estimates 47 3.4 Conclusion 53 4 EVALUATION OF PHOTO-CONTROLLABLE FLUORESCENT PROTEINS FOR PALM IN DIATOMS 55 4.1 Selecting PCFPs to minimize interference with the diatom autofluorescence 56 4.2 Screening results for cytosolic and biosilica-embedded PCFPs 58 4.3 The underlying conversion mechanism 61 4.4 Conclusion 63 5 IMAGING THE SIL3 MESHWORK 65 5.1 Analyzing protein layer thickness using tpSil3-Dendra2 65 5.2 Imaging the valve region using tpSil3 68 5.3 Resolution and localization parameters of tpSil3 70 5.4 Conclusion 72 6 DECIPHERING CINGULIN PATTERNS WITH CO LOCALIZATION STUDIES 73 6.1 A two-color cingulin construct for PALM-STORM 73 6.2 Steps towards PALM-STORM: screening, alignment, and imaging routine 76 6.3 Co-localization studies: quantification, clustering, and correlations 83 6.4 Conclusion 91 7 OUTLOOK 93 8 MATERIALS & METHODS 97 8.1 Microscope specifications 97 8.2 DNA origami annealing and AFM measurements 99 8.3 Diatom sample preparations 100 8.4 Fluorescence imaging conditions 102 8.5 Buffer systems 103 9 APPENDICES 105 9.1 Tables and Protocols 105 9.2 Satellite projects 112 9.2.1 Quantitative fluorescence intensity analysis of 3D time-lapse confocal microscopy data in diatoms 112 9.2.2 Applying neural networks to filter SMLM localizations 118 9.2.3 In vivo imaging at super-resolution conditions using SOFI 121 9.2.4 Quantifying chromatic aberrations in the microscope using fiducials 123 10 REFERENCES 127Diatoms feature the unique ability to form nanopatterned hierarchical silica cell walls with unprecedented accuracy and reproducibility. Gathering a deeper understanding of this process that is known as “biomineralization” is vitally important not only in the field of diatom research. In fact, the nanopatterning can also be exploited in the fields of material sciences or nanobiotechnology. According to the current understanding, the self-assembly of protein patterns along which biosilica is formed is key to this nanopatterning. Thus, in order to unravel the function of individual proteins that are involved in this biomineralization process, their structural organization has to be deciphered and correlated to morphological cell wall features that are in the order of tens of nanometer. Electron microscopy is able to resolve these features but does not provide protein-specific information. Therefore, a technique has to be established that is able to localize individual biosilica-associated proteins with nanometer precision. To achieve this objective, single-molecule localization microscopy (SMLM) for the diatom Thalassiosira pseudonana has been pioneered and exploited to localize different biosilica associated proteins inside silica and after silica removal. To obtain quantitative data, an analysis workflow was developed including graphical user interfaces and scripts for SMLM visualization, clustering, and co-localization. In order to find optimal labels for SMLM to target biosilica-embedded proteins, a comprehensive screening of photo-controllable fluorescent proteins has been carried out. Only three of six candidates were functional when embedded inside biosilica and fused to Silaffin3 – a protein that is tightly associated with the biosilica cell wall. Silaffin3 could be localized using SMLM with a localization precision of 25 nm. This allowed to resolve its structural organization and therefore identified Silaffin3 as a major component in the basal chamber of the fultoportulae. Additionally, co-localization studies on cingulins – a protein family hypothesized to be involved in silica formation – have been performed to decipher their pattern-function relationship. Towards this end, novel imaging strategies, co-localization calculations and pattern quantifications have been established. With the help of these results, the spatial arrangement of cingulins W2 and Y2 could be compared with unprecedented resolution. In summary, this work has laid ground for quantitative SMLM studies of proteins in diatoms in general and contributed insights into the spatial organization of proteins involved in biomineralization in the diatom T. pseudonana.:1 INTRODUCTION 1 1.1 Diatoms – a model system for biomineralization 3 1.2 Imaging of biosilica and associated organic components 8 1.3 Single-molecule localization microscopy (SMLM) 10 2 METHODS & METHOD DEVELOPMENT FOR SMLM DATASETS 17 2.1 Super-resolution reconstruction 19 2.2 Tools for SMLM resolution estimates 21 2.3 Voronoi tessellation for noise-removal and cluster estimation 25 2.4 Tools for SMLM cluster analysis 27 2.5 Coordinate-based co-localization 32 2.6 PairRice – A novel algorithm to extract distances between cluster pairs 33 2.7 SiMoNa – A new GUI for exploring SMLM datasets 35 3 RESOLUTION OF THE SMLM SETUP TESTED WITH DNA ORIGAMI NANOSTRUCTURES 41 3.1 DNA origami as a length standard 42 3.2 Global resolution estimates 44 3.3 Local resolution estimates 47 3.4 Conclusion 53 4 EVALUATION OF PHOTO-CONTROLLABLE FLUORESCENT PROTEINS FOR PALM IN DIATOMS 55 4.1 Selecting PCFPs to minimize interference with the diatom autofluorescence 56 4.2 Screening results for cytosolic and biosilica-embedded PCFPs 58 4.3 The underlying conversion mechanism 61 4.4 Conclusion 63 5 IMAGING THE SIL3 MESHWORK 65 5.1 Analyzing protein layer thickness using tpSil3-Dendra2 65 5.2 Imaging the valve region using tpSil3 68 5.3 Resolution and localization parameters of tpSil3 70 5.4 Conclusion 72 6 DECIPHERING CINGULIN PATTERNS WITH CO LOCALIZATION STUDIES 73 6.1 A two-color cingulin construct for PALM-STORM 73 6.2 Steps towards PALM-STORM: screening, alignment, and imaging routine 76 6.3 Co-localization studies: quantification, clustering, and correlations 83 6.4 Conclusion 91 7 OUTLOOK 93 8 MATERIALS & METHODS 97 8.1 Microscope specifications 97 8.2 DNA origami annealing and AFM measurements 99 8.3 Diatom sample preparations 100 8.4 Fluorescence imaging conditions 102 8.5 Buffer systems 103 9 APPENDICES 105 9.1 Tables and Protocols 105 9.2 Satellite projects 112 9.2.1 Quantitative fluorescence intensity analysis of 3D time-lapse confocal microscopy data in diatoms 112 9.2.2 Applying neural networks to filter SMLM localizations 118 9.2.3 In vivo imaging at super-resolution conditions using SOFI 121 9.2.4 Quantifying chromatic aberrations in the microscope using fiducials 123 10 REFERENCES 12

Improved MUSIC-based SMOS RFI source detection and geolocation algorithm

©2015 IEEE. Personal use of this material is permitted. Permission from IEEE must be obtained for all other uses, in any current or future media, including reprinting/republishing this material for advertising or promotional purposes, creating new collective works, for resale or redistribution to servers or lists, or reuse of any copyrighted component of this work in other works.The European Space Agency's Soil Moisture and Ocean Salinity (SMOS) mission has been providing L-band brightness temperature (BT) using its instrument, the Microwave Imaging Radiometer using Aperture Synthesis. In the measurements, the negative effect of radio frequency interference (RFI) is clearly present, deteriorating the quality of geophysical parameter retrieval. Detection and geolocation of RFI sources are essential to remove or at least mitigate the RFI impacts and ultimately improve the performance of parameter retrieval. This paper discusses a new approach to SMOS RFI source detection, based on the MUltiple SIgnal Classification (MUSIC) algorithm. Recently, the feasibility of MUSIC direction-of-arrival estimation has been shown for the RFI source detection of the synthetic aperture interferometric radiometer. This paper refines the MUSIC RFI source detection algorithm and tailors it to the SMOS scenario. To consolidate the RFI source detection procedure, several required steps are devised, including the rank estimation of the covariance matrix, local peak detection and thresholds, andmultiple-snapshot processing. The developed method is tested using a number of SMOS visibility samples. In the test results, the MUSIC method shows an improvement on the accuracy and precision of the RFI source geolocation, compared with a simple detection method based on the local peaks of BT images. The MUSIC results especially outperform the SMOS BT image on the spatial resolution.Peer ReviewedPostprint (author's final draft

Automated greenhouse gas plume detection from satellite data using an unsupervised clustering algorithm

A crucial part of tackling the problem of climate change is the monitoring of human-caused greenhouse gas emissions. To reach a global scale, greenhouse gas measuring satellites appear to be the best solution. The massive amounts of data produced by the satellites has increased the need for automated, efficient tools to extract knowledge from the data. Emissions from point sources, such as power plants, can produce distinct plumes that are visible from satellite data. Automated plume detection is key to identify and monitor the largest sources of human-caused greenhouse gas emissions. This thesis presents a comprehensive literature review of existing plume detection methods. Moreover, a new unsupervised plume detection method, called SCEA (Spatial Clustering of Elevated-valued Areas), is introduced. Inspired by the DBSCAN algorithm, SCEA is a clustering algorithm that finds distinct high-valued areas in non-gridded data points. The performance of the SCEA algorithm is evaluated with the simulated satellite data set of SMARTCARB in its ability to find point sources with co-located plumes in different noise scenarios. The SCEA algorithm reached a precision of 0.974, 0.884, and 0.661 in noise-free, low-noise, and high-noise scenarios, respectively. For point sources with annual emissions of 1000 tonnes, the SCEA reached a recall of 0.758, 0.660, and 0.548 for noise-free, low-noise, and high-noise scenarios, respectively