Automation and analysis of high-dimensionality experiments in biocatalytic reaction screening

Biological catalysts are increasingly used in industry in high-throughput screening for drug discovery or for the biocatalytic synthesis of active pharmaceutical intermediates (APIs). Their activity is dependent on high-dimensionality physiochemical processes which are affected by numerous potentially interacting factors such as temperature, pH, substrates, solvents, salinity, and so on. To generate accurate models that map the performance of such systems, it is critical to developing effective experimental and analytical frameworks. However, investigating numerous factors of interest can become unfeasible for conventional manual experimentation which can be time-consuming and prone to human error. In this thesis, an effective framework for the execution and analysis of highdimensionality experiments that implement a Design of Experiments (DoE) methodology was created. DoE applies a statistical framework to the simultaneous investigation of multiple factors of interest. To convert the DoE design into a physically executable experiment, the Synthace Life Sciences R&D cloud platform was used where experimental conditions were translated into liquid handling instructions and executed on multiple automated devices. The framework was exemplified by quantifying the activity of an industrially relevant biocatalyst, the CV2025 ωtransaminase enzyme from Chromobacterium violaceum, for the conversion of Smethylbenzylamine (MBA) and pyruvate into acetophenone and sodium alanine. The automation and analysis of high-dimensionality experiments for screening of the CV2025 TAm biocatalytic reaction were carried out in three sequential stages. In the first stage, the basic process of Synthace-driven automated DoE execution was demonstrated by executing traditional DoE studies. This comprised of a screening study that investigated the impact of nine factors of interest, after which an optimisation study was conducted by taking forward five factors of interest using two automated devices to optimise assay conditions further. In total, 480 experimental conditions were executed and analysed to generate mathematical models that identified an optimum. Robust assay conditions were identified which increased enzyme activity >3-fold over the starting conditions. In the second stage, nonbiological considerations that impact absorbance-based assay performance were systematically investigated. These considerations were critical to ensuring reliable and precise data generation from future high-dimensionality experiments and include confirming spectrophotometer settings, selecting microplate type and reaction volume, testing device precision, and managing evaporation as a function of time. The final stage of the work involved development of a framework for the implementation of a modern type of DoE design called a space-filling design (SFD). SFDs sample factors of interest at numerous settings and can provide a fine-grained characterisation of high-dimensional systems in a single experimental run. However, they are rarely used in biological research due to a large number of experiments required and their demanding, highly variable pipetting requirements. The established framework enabled the execution and analysis of an automated end-toend SFD where 3,456 experimental conditions were prepared to investigate a 12- dimensional space characterising CV2025 TAm activity. Factors of interest included temperature, pH, buffering agent types, enzyme stability, co-factor, substrate, salt, and solvent concentrations. MATLAB scripts were developed to calculate important biocatalysis metrics of product yield and initial rate which were then used to build mathematical models that were physically validated to confirm successful model prediction. The implementation of the framework provided greater insight into numerous factors influencing CV2025 TAm activity in more dimensions than what was previously reported in the literature and to our knowledge is the first large-scale study that employs a SFD for assay characterisation. The developed framework is generic in nature and represents a powerful tool for rapid one-step characterisation of high-dimensionality systems. Industrial implementation of the framework could help reduce the time and costs involved in the development of high throughput screens and biocatalytic reaction optimisation

Towards Predictive Rendering in Virtual Reality

The strive for generating predictive images, i.e., images representing radiometrically correct renditions of reality, has been a longstanding problem in computer graphics. The exactness of such images is extremely important for Virtual Reality applications like Virtual Prototyping, where users need to make decisions impacting large investments based on the simulated images. Unfortunately, generation of predictive imagery is still an unsolved problem due to manifold reasons, especially if real-time restrictions apply. First, existing scenes used for rendering are not modeled accurately enough to create predictive images. Second, even with huge computational efforts existing rendering algorithms are not able to produce radiometrically correct images. Third, current display devices need to convert rendered images into some low-dimensional color space, which prohibits display of radiometrically correct images. Overcoming these limitations is the focus of current state-of-the-art research. This thesis also contributes to this task. First, it briefly introduces the necessary background and identifies the steps required for real-time predictive image generation. Then, existing techniques targeting these steps are presented and their limitations are pointed out. To solve some of the remaining problems, novel techniques are proposed. They cover various steps in the predictive image generation process, ranging from accurate scene modeling over efficient data representation to high-quality, real-time rendering. A special focus of this thesis lays on real-time generation of predictive images using bidirectional texture functions (BTFs), i.e., very accurate representations for spatially varying surface materials. The techniques proposed by this thesis enable efficient handling of BTFs by compressing the huge amount of data contained in this material representation, applying them to geometric surfaces using texture and BTF synthesis techniques, and rendering BTF covered objects in real-time. Further approaches proposed in this thesis target inclusion of real-time global illumination effects or more efficient rendering using novel level-of-detail representations for geometric objects. Finally, this thesis assesses the rendering quality achievable with BTF materials, indicating a significant increase in realism but also confirming the remainder of problems to be solved to achieve truly predictive image generation

High-fidelity imaging : the computational models of the human visual system in high dynamic range video compression, visible difference prediction and image processing

As new displays and cameras offer enhanced color capabilities, there is a need to extend the precision of digital content. High Dynamic Range (HDR) imaging encodes images and video with higher than normal bit-depth precision, enabling representation of the complete color gamut and the full visible range of luminance. This thesis addresses three problems of HDR imaging: the measurement of visible distortions in HDR images, lossy compression for HDR video, and artifact-free image processing. To measure distortions in HDR images, we develop a visual difference predictor for HDR images that is based on a computational model of the human visual system. To address the problem of HDR image encoding and compression, we derive a perceptually motivated color space for HDR pixels that can efficiently encode all perceivable colors and distinguishable shades of brightness. We use the derived color space to extend the MPEG-4 video compression standard for encoding HDR movie sequences. We also propose a backward-compatible HDR MPEG compression algorithm that encodes both a low-dynamic range and an HDR video sequence into a single MPEG stream. Finally, we propose a framework for image processing in the contrast domain. The framework transforms an image into multi-resolution physical contrast images (maps), which are then rescaled in just-noticeable-difference (JND) units. The application of the framework is demonstrated with a contrast-enhancing tone mapping and a color to gray conversion that preserves color saliency.Aktuelle Innovationen in der Farbverarbeitung bei Bildschirmen und Kameras erzwingen eine Präzisionserweiterung bei digitalen Medien. High Dynamic Range (HDR) kodieren Bilder und Video mit einer grösseren Bittiefe pro Pixel, und ermöglichen damit die Darstellung des kompletten Farbraums und aller sichtbaren Helligkeitswerte. Diese Arbeit konzentriert sich auf drei Probleme in der HDR-Verarbeitung: Messung von für den Menschen störenden Fehlern in HDR-Bildern, verlustbehaftete Kompression von HDR-Video, und visuell verlustfreie HDR-Bildverarbeitung. Die Messung von HDR-Bildfehlern geschieht mittels einer Vorhersage von sichtbaren Unterschieden zweier HDR-Bilder. Die Vorhersage basiert dabei auf einer Modellierung der menschlichen Sehens. Wir addressieren die Kompression und Kodierung von HDR-Bildern mit der Ableitung eines perzeptuellen Farbraums für HDR-Pixel, der alle wahrnehmbaren Farben und deren unterscheidbaren Helligkeitsnuancen effizient abbildet. Danach verwenden wir diesen Farbraum für die Erweiterung des MPEG-4 Videokompressionsstandards, welcher sich hinfort auch für die Kodierung von HDR-Videosequenzen eignet. Wir unterbreiten weiters eine rückwärts-kompatible MPEG-Kompression von HDR-Material, welche die übliche YUV-Bildsequenz zusammen mit dessen HDRVersion in einen gemeinsamen MPEG-Strom bettet. Abschliessend erklären wir unser Framework zur Bildverarbeitung in der Kontrastdomäne. Das Framework transformiert Bilder in mehrere physikalische Kontrastauflösungen, um sie danach in Einheiten von just-noticeable-difference (JND, noch erkennbarem Unterschied) zu reskalieren. Wir demonstrieren den Nutzen dieses Frameworks anhand von einem kontrastverstärkenden Tone Mapping-Verfahren und einer Graukonvertierung, die die urspr ünglichen Farbkontraste bestmöglich beibehält

Development of an optical fiber probe for mercury detection

El mercurio presenta una alta toxicidad, pudiendo causar adversos efectos en la salud humana. Los procedimientos recomendados para la detección analítica de metales pesados no son apropiados para aquellas aplicaciones donde se requiere un bajo coste y equipos ligeros que permitan realizar medidas de campo. Por el contrario, los sensores opto-químicos son una tecnología con un alto potencial para el desarrollo de dispositivos detectores de bajo coste y dimensiones reducidas. Esta Tesis describe los aspectos más relevantes en el desarrollo de una sonda opto-química basada en fibra óptica para la determinación de mercurio en agua. La investigación se plantea a partir de un compuesto de rutenio(II) descubierto recientemente que presenta un cambio de color desde un rojo púrpura oscuro hasta el naranja en solución orgánica ante la exposición a iones de mercurio(II). Otro factor importante es la capacidad de anclaje de la molécula a finas capas de óxidos metálicos como puede ser el TiO2. Los logros principales alcanzados en este trabajo de investigación son: (1) un software de análisis espectral multi-variable que reduce notablemente las interferencias principales del reactivo en fase líquida. El modelo matemático se basa en la regresión lineal por mínimos cuadrados parciales (PLS), y además se ha optimizado el resultado mediante una comparativa entre diferentes modelos PLS que incluyen un tratamiento previo de los datos mediante wavelet, corrección ortogonal de la señal, algoritmos genéticos, y selección de características estadísticas. (2) Una mejora de la estabilidad acuosa de la molécula al soportarla sobre una matriz de nanopartículas de Al2O3. Algunos trabajos preliminares con el complejo de Ru(II) se centraron en la inmovilización de la molécula sobre capas finas mesoporosas de TiO2. No obstante, pérdidas del colorante son apreciables cuando se analizan muestras acuosas. Resultados de la presente investigación garantizan la estabilidad acuosa de la molécula soportada sobre películas de Al2O3 y tratadas con ácido sulfúrico, con pérdidas por debajo del 2% (durante 3 horas). (3) La construcción del transductor basado en fibra óptica consiste en la sustitución de un trozo de cubrimiento (2 cm) del núcleo de la fibra óptica por el material sensibilizado compuesto por las nanopartículas de Al2O3. El principio de funcionamiento se basa en los cambios ópticos del material reactivo ante la exposición a iones de Hg2+, modulando así la intensidad de luz que se transmite a través del núcleo óptico. Se intuye a priori que la configuración del dispositivo conlleva a admitir que la propagación de la luz en la interfase núcleo y película de alumina tratada es mediante la aparición del campo evanescente. Sin embargo, al tener la cubierta de alumina un mayor índice de refracción que el núcleo, la condición de reflexión interna total no se satisface completamente, y como resultado se tiene una respuesta de la sonda óptica a la que contribuye tanto el campo evanescente como el modo de radiación generado por la porción de luz que se refracta a través de la cubierta de alumina-molécula. Finalmente, si tenemos en cuenta que la respuesta de este tipo de sondas ópticas varía significativamente de sonda a sonda, la cuantificación de mercurio ha sido posible a través de una calibración multivariable. Se ha logrado un error en la predicción de mercurio de un 11.5 por ciento, considerando un rango de 0 a 6 mg L-1 de iones de Hg2+. De este modo, se ha conseguido una sonda opto-química basada en fibra óptica cuyo modo de funcionamiento no es muy habitual en la literatura. La originalidad del presente trabajo se fundamenta en los pocos ejemplos de dispositivos ópticos de estas características que existen para la detección de metales pesados. En lo referente al autor, este es el primer dispositivo con configuración de fibra óptica evanescente destinado a la determinación de mercurio en medio acuoso.The organic form of mercury (methylmercury) is highly toxic, affecting the nervous system and even causing death. In the last years, human activities on coal combustion, waste incineration, gold mining and other industrial processes have raised the level of mercury in the atmosphere, rivers and other sources. Several public bodies have demonstrated that the direct detection of inorganic mercury (the precursor of mehtylmercury) will be beneficial in order to prevent mercury contamination. The detection of inorganic mercury through simple and low cost systems is possible by using colorimetric chemical sensors.Thus, several research groups worldwide have shown that the use of molecular probes, which change their optical properties upon the binding of inorganic mercury, is a promising topic for the development of detector devices for pollutant species.This Thesis describes the most remarkable aspects in the development of an optical fiber probe designed for mercury determination in aqueous samples. The research arises from the discovery of a novel molecule (IUPAC name bis(2,2'-bipyridyl-4,4'-dicarboxylato) ruthenium(II) bistetrabutylammonium bis-thiocyanate) that upon mercury binding induces a color change from dark red-purple to orange in solution. The selectivity towards mercury of this ruthenium complex is high when compared to other known chemical reagents. Yet, in this work, we have been able to increase the selectivity through a fully multivariate calibration of the absorbance measurements. We have analyzed the mercury-containing solutions under the co-existence of higher concentrations (19.5 mg L-1) of other potential competitors such as Cd2+, Pb2+, Cu2+ and Zn2+ ions. Our experimental model is based on partial least squares (PLS) linear regression and other general techniques as wavelet, orthogonal signal correction, genetic algorithm and statistical feature selection that have been used to refine, a priori, the analytical data. In summary, we have demonstrated that the root mean square error of mercury prediction with statistical feature selection, as compared to the absence of pre-treatment, can be reduced from 10.5 to 5.2 percent, which improves the prediction ability of the calibration model by a factor of 2.On the other hand, the possibility of working in solid-liquid phase increases the integration ability of the molecule in a device, making easier the measurement process. Nevertheless, the immobilization of the molecule onto a surface constitutes one of the challenges of this Thesis.Some preliminary works with the Ru(II) complex focussed on the immobilization of the molecule onto TiO2 mesoporous thin films.However, some leaching problems were apparent when aqueous samples were analysed. Accordingly, we have improved the water stability of the molecule by anchoring the dye onto Al2O3 nanoparticles thin films treated with sulphuric acid. Moreover, the good optical properties of the alumina support allow a better transparency of the films, which translates in a higher amount of available spectral absorbance information.A compact mercury read-out system has been achieved by coating an unclad optical fiber piece with Al2O3 paste. The proof-of-principle is based on the optical changes of the reagent upon Hg2+ ions exposure, which modulates the light intensity transmitted through the optical core.There are many theoretical studies that explore a particular research case of the evanescent optical fibers. As the alumina cladding has higher refractive index than the core, both evanescent field and radiative mode may appear in the modified cladding. This Thesis exposes a brief explanation of this behavior in order to understand the mechanisms of the response of our mercury optical fiber probe. Moreover, several experiments have been carried out in mercury aqueous samples so as to find the proper working conditions, such as the optimum dye concentration adsorbed onto the alumina cladding, which has a great effect on the device performance. Finally, mercury quantification has been possible through multivariate calibration, direct partial least squares being the most robust procedure if we take into account the fact that the response of this kind of optical probes varies significantly from one to another. A root mean square error for mercury predictions of 11.5 percent has been achieved within a range from 0 to 6 mg L-1 of Hg2+ ions.Overall, this thesis work has illustrated all the steps that come into play in the design of an optical fiber chemical-based probe, providing a simplified measurement process and a lower cost if it is compared to traditional analysis equipment. As far as the author is concerned, an optical fiber probe for mercury determination is presented for the first time

The Appearance of Platelet-Polymer Composite Coatings: Microstructural Characterization, Hybrid Modeling, and Predictive Design.

The appearance of a platelet-containing polymer composite coating is governed by the microstructure and optical properties included scattering particles and platelets. Many models attempt to predict the coating's appearance, but do not utilize the complete 3D-microstructure, reducing their predictive utility. In this thesis, laser scanning confocal microscopy was used to measure the effect of platelet orientation on angle-dependent lightness, and quantify the spacing between platelets, from which a new microstructural property, the gap factor, was determined. The gap factor is a measure of the average gap size between platelets per unit material surface length. It ranged from 0 to 2 for the systems studied in this thesis. An increase in gap factor of about 0.1, keeping the orientation similar, reduced the near-specular lightness of the physical samples by more than 20%. A 3D hybrid-simulation was created using wave-optics to simulate the bidirectional-reflection-distribution-function (BRDF) for individual platelets. This was combined with ray-tracing to quantify the scattering behavior of a platelet array. This model more accurately predicted the lightness of a silver paint sample than an orientation-based microfacet-model, and was used to study how the surface roughness of the platelets influences lightness. The lightness at 15 degrees off-specular was about 130 when the root-mean square of the amplitude of the roughness, sigma(RMS), was much less than the wavelength of light. Lightness reduced to about 80 when sigma(RMS) was about equal to the wavelength of light. This effect of sigma(RMS) on lightness was found to be more significant with decreases in the roughness correlation length. The hybrid model was also used to study how width, thickness, and volume concentration of the platelets change the near-specular and backscattered lightness. The observed reduction in near-specular lightness with gap factor was verified. However, the resultant 2nd-order exponential decay was weaker than observed. This was attributed wave-scattering by faces and edges, behavior not included in the current model, but may be added in the future. This hybrid model can be used in the future to design unique microstructures to produce new and novel visual or functional effects using manufacturing techniques such as 3D-printing.PhDMaterials Science and EngineeringUniversity of Michigan, Horace H. Rackham School of Graduate Studieshttp://deepblue.lib.umich.edu/bitstream/2027.42/133404/1/cseubert_1.pd

Nanoparticle-based Sample Preparation and High- Resolution Mass Spectrometry for Bioprocess and Quality Control in Biopharmaceutical Production

Biopharmaceuticals, such as monoclonal antibodies (mAb), have recently become increasingly important in the treatment of many different diseases. Usually these molecules have complex molecular structures which poses great challenges for their characterization. However, full characterization is essential for FDA and EMA drug approval. Nowadays, antibodies are usually analyzed by high-resolution mass spectrometry (HR-MS). One approach is the middle-down analysis, where enzymes such as pepsin are used to digest the antibodies into specific fragments which are in a more suitable size-range and can be more easily analyzed. However, mAb characterization usually starts with top-down analysis of intact antibodies using HR-MS or liquid chromatography (LC) hyphenated to HR-MS (LC-MS) for determining the molecular mass to charge (m/z) of the protein. In this work new methods for sample preparation in protein analytics of biopharmaceuticals have been developed. In particular, the main approach discussed herein describes the sample preparation of therapeutic proteins with heterogeneous nanobiocatalysts based on gold nanoparticles (GNPs) with coated or immobilized enzymes such as pepsin. The different synthesis steps of the nanoparticulate carriers were investigated and compared in size and function using classical methods, such as Vis-spectroscopy, dynamic light scattering (DLS), Lowry assay and Michaelis-Menten kinetic analysis. Newer methods such as Resonant Mass Measurement and Taylor Dispersion Analysis were also used for this purpose. In order to extend the toolbox of methods in this regard, the results of these modern characterization methods were compared with those of the classical ones. For functional studies of the gold nanoparticle-conjugated enzyme, the comparison of enzyme activities with free, unbound enzymes (e.g. pepsin) is an important aspect for the performance evaluation of the new nanobiocatalysts. The immobilization of enzymes to nanoparticulate carriers has some advantageous. Since the gold nanoparticles have a high density, separation of the nano biocatalysts from the sample is easily possible with simple benchtop centrifuges, as they are present in almost every modern laboratory. Thus, the enzyme can be easily removed after reaction and does not contaminate the sample with another protein (enzyme) which might XII give interferences in subsequent MS analysis. However, it has to be ascertained that immobilization does not reduce the enzyme activity. In this work it is documented that pepsin immobilized on gold nanoparticles has even higher enzymatic efficiencies than pepsin in free solution. The aim of the present work is to provide an overview of the synthesis and characterization of GNPs as a nano framework for enzymes used for protein and antibody analysis. Also, the current state of technology in methods for the use of GNPs should be pointed out here