Hardware and software integration and testing for the automation of bright-field microscopy for tuberculosis detection

Automated microscopy for the detection of tuberculosis (TB) in sputum smears would reduce the load on technicians, especially in countries with a high TB burden. This dissertation reports on the development and testing of an automated system built around a conventional microscope for the detection of TB in Ziehl-Neelsen (ZN) stained sputum smears. Microscope auto-focusing, image analysis and stage movement were integrated. Images were captured at 40x magnification

Image Analysis Algorithms for Single-Cell Study in Systems Biology

With the contiguous shift of biology from a qualitative toward a quantitative field of research, digital microscopy and image-based measurements are drawing increased interest. Several methods have been developed for acquiring images of cells and intracellular organelles. Traditionally, acquired images are analyzed manually through visual inspection. The increasing volume of data is challenging the scope of manual analysis, and there is a need to develop methods for automated analysis. This thesis examines the development and application of computational methods for acquisition and analysis of images from single-cell assays. The thesis proceeds with three different aspects.First, a study evaluates several methods for focusing microscopes and proposes a novel strategy to perform focusing in time-lapse imaging. The method relies on the nature of the focus-drift and its predictability. The study shows that focus-drift is a dynamical system with a small randomness. Therefore, a prediction-based method is employed to track the focus-drift overtime. A prototype implementation of the proposed method is created by extending the Nikon EZ-C1 Version 3.30 (Tokyo, Japan) imaging platform for acquiring images with a Nikon Eclipse (TE2000-U, Nikon, Japan) microscope.Second, a novel method is formulated to segment individual cells from a dense cluster. The method incorporates multi-resolution analysis with maximum-likelihood estimation (MAMLE) for cell detection. The MAMLE performs cell segmentation in two phases. The initial phase relies on a cutting-edge filter, edge detection in multi-resolution with a morphological operator, and threshold decomposition for adaptive thresholding. It estimates morphological features from the initial results. In the next phase, the final segmentation is constructed by boosting the initial results with the estimated parameters. The MAMLE method is evaluated with de novo data sets as well as with benchmark data from public databases. An empirical evaluation of the MAMLE method confirms its accuracy.Third, a comparative study is carried out on performance evaluation of state-ofthe-art methods for the detection of subcellular organelles. This study includes eleven algorithms developed in different fields for segmentation. The evaluation procedure encompasses a broad set of samples, ranging from benchmark data to synthetic images. The result from this study suggests that there is no particular method which performs superior to others in the test samples. Next, the effect of tetracycline on transcription dynamics of tetA promoter in Escherichia coli (E. coli ) cells is studied. This study measures expressions of RNA by tagging the MS2d-GFP vector with a target gene. The RNAs are observed as intracellular spots in confocal images. The kernel density estimation (KDE) method for detecting the intracellular spots is employed to quantify the individual RNA molecules.The thesis summarizes the results from five publications. Most of the publications are associated with different methods for imaging and analysis of microscopy. Confocal images with E. coli cells are targeted as the primary area of application. However, potential applications beyond the primary target are also made evident. The findings of the research are confirmed empirically

Organisation of the Mycobacterium smegmatis chromosome and its role in cell division

Tuberculosis remains a global health problem, exacerbated by the increasing emergence of multi‐drug resistant strains. The identification of new drug targets and the discovery of new anti‐tuberculosis drugs is therefore a high priority. Although little is currently known about mycobacterial cell division, the process is essential for the survival and expansion of all bacterial species so may involve proteins that represent excellent drug targets. In this thesis, proven tools for the study of bacterial cell division such as live‐cell time‐lapse imaging and Fluorescent Repressor Operator System (FROS) were adapted for use in mycobacteria. Application of such techniques, fluorescent tagging of cell division proteins and deletion of parA in M. smegmatis helped to elucidate some interesting characteristics of mycobacterial cell division. In contrast to model organisms, live cell imaging and septal staining indicated that M. smegmatis can grow and divide asymmetrically and divides at a range of lengths suggesting a fundamentally different mechanism of division regulation. The chromosome was hypothesised to play a key role in cell division so was investigated further by labelling a specific chromosomal loci. The key finding was that M. smegmatis cells only contain 1 or 2 chromosomal copies and that regardless of cell length, the nucleoid occupies almost the entire intracellular space. To examine if the nucleoid organisation is important for cell division, a putative chromosome segregation gene parA was disrupted. The ΔparA mutant displayed a classic cell division phenotype characterised by the production of anuclear mini‐cells. The mechanism responsible for the ΔparA mutant phenotype was studied further by applying live cell imaging, FROS and expressing a ParA‐mCherry fusion protein. The data obtained from all work presented was collated and used to propose a novel model of bacterial cell division regulation applicable to mycobacteria where the nucleoid plays a central role and ParA is required to ensure correct nucleoid placement

Instrument design and optimization of interferometric reflectance imaging sensors for in vitro diagnostics

Thesis (Ph.D.)--Boston UniversityIn the field of drug discovery and disease diagnostics, protein microarrays have generated much enthusiasm for their high-throughput monitoring of biomarkers; however, this technology has yet to translate from research laboratories to commercialization. The hindrance is the considerable uncertainty and skepticism regarding data obtained. The disparity in results from different laboratories performing identical tests is attributed to a lack of assay quality control. Unlike DNA microarrays, protein microarrays have a higher level of bioreceptor immobilization variability and non-specific binding because of the more complex molecular structure and broader physiochemical properties. Traditional assay detection modalities, such as fluorescence microscopy and surface plasmon resonance, are unable to overcome both of these sources of variation. This dissertation describes the hardware and software design and biological validation of three complementary platforms that overcome bioreceptor variability and non-specific binding for diagnostics. In order to quantify the bioreceptor quality, a label-free, nondestructive, low cost, and high-throughput interferometric sensor has been developed as a quality control tool. The quality control tool was combined with a wide-field fluorescence imaging system to improve fluorescence experimental repeatability. Lastly, a novel high-throughput and label-free platform for quality control and specific protein microarray detection is described. This platform overcomes the additional complexities and time required with labeled assays by discriminating between specific and nonspecific detection by including sizing of individual binding events. Protein microarrays may one day emerge as routine clinical laboratory tests; however, it is important that the proper quality control procedures are in place to minimize erroneous results. These platforms provide reliable and repeatable protein microarray measurements for new advancements in disease diagnostics with the potential for drug discovery

RNA interference screening identifies host factors involved in brucella infection

Intracellular pathogens rely to varying extents on cellular functions of the host cell for their own propagation. A number of bacteria have evolved strategies to invade human cells and to establish an intracellular niche, which often consists of a cellular compartment that is modified by the pathogen to its own benefit. To understand the infection strategies of such organisms and eventually design new medical interventions, knowledge on the host factors exploited by the pathogens is critical. To this end, the InfectX consortium attempts to decipher the human infectome for a number of bacterial and viral pathogens. In this framework, we study the zoonotic pathogen Brucella, which is able to invade phagocytic as well as non-phagocytic cells. The molecular mechanisms by which Brucella enters cells, evades lysosomal degradation, and finally replicates in an endoplasmic reticulum-like compartment, remain largely unknown. To identify host factors involved in these processes, genome-wide microscopy-based RNA interference (RNAi) screens of Brucella entry and replication in HeLa cells were performed. To assign the function of the hits from the genome-wide screen to either early or late stages of Brucella infection, a follow-up assay suitable for high-throughput screening of Brucella entry was established. Both screening protocols are described in detail in research article I. In-depth analysis of the genome-wide siRNA data generated within InfectX found that all screens including the one for Brucella infection show signs of miRNA-like off-target effects. Research article II focuses on the discovery and validation of this phenomenon in siRNAs screens and illustrates the potential of such an analysis to discover natural miRNAs and synthetic miRNA-like molecules that regulate the process of study. These findings motivated the screening of a library of human miRNA mimics for their involvement in Brucella infection. We identified miR-103 and miR-107 (miR-103/107), which strongly promote Brucella entry in non-phagocytic cells as presented in research article III. Interestingly, also the infection of other pathogens tested within InfectX was promoted by these miRNAs. Proteome and transcriptome analyses of cells with high levels of miR-103/107 indicated that this alters endocytic properties which manifested in reduced clathrin dependent uptake of transferrin in these cells. Furthermore, the abundance of several surface receptors required by different pathogens is increased. TGF-β receptor 2 showed elevated expression upon miR-103/107 transfection and independent experiments could confirm that high levels of this transmembrane kinase promote Brucella infection. Having analyzed the full scale of off-target effects, we set out to determine a strategy to validate candidate genes of the genome-wide screens. We thus assayed a set of human kinases with a total of eleven individual siRNAs and one siRNA pool. Research article IV shows that the true discovery rate is directly proportional to the number of siRNAs tested and that siRNA pools tend to give more reliable results than individual siRNAs. As a consequence of these findings, we used six independent siRNAs and one siRNA pool for the validation of genes discovered in the primary screen with one pooled and five single siRNAs. This allowed the identification of several host cell pathways relevant for Brucella infection. Besides previously known functions, which include actin cytoskeleton remodeling or maturation of endocytic vesicles, also novel ones such as FGF and TGF-β signaling were found. While most of these networks were connected to Brucella entry into HeLa cells, we were also able to identify retrograde trafficking between endosomes and the Golgi apparatus to regulate a post-entry process as presented in research article IV. Altogether, the results of our studies presented here point out limitations as well as the potential of siRNA technology. If off-target effects are accounted for and experimental confirmation is applied carefully on identified factors, RNAi allows to successfully reveal genes and pathways hitherto unrelated to the mechanism of interest. Additionally, and if analyzed accordingly, off-target effects also constitute a rich source of information for the discovery of miRNAs and miRNA-like molecules that regulate a certain process. Applied to the presented screens for human factors taking part in Brucella infection, this led to the description of miRNAs and several host pathways, which support pathogenicity. By that our results contribute to the expansion of the currently described infectome for this intracellular pathogen

Digital Image Processing

This book presents several recent advances that are related or fall under the umbrella of 'digital image processing', with the purpose of providing an insight into the possibilities offered by digital image processing algorithms in various fields. The presented mathematical algorithms are accompanied by graphical representations and illustrative examples for an enhanced readability. The chapters are written in a manner that allows even a reader with basic experience and knowledge in the digital image processing field to properly understand the presented algorithms. Concurrently, the structure of the information in this book is such that fellow scientists will be able to use it to push the development of the presented subjects even further

Dictyostelium discoideum as a model for the evaluation of teratogenic compounds

Before new chemicals can be put on the market, they must be evaluated for toxicological safety. Evaluating the safety of new chemicals, for either medical, cosmetic or environmental application, is tightly regulated by worldwide legislation. A critical aspect of toxicity evaluation is developmental and reproductive toxicity (DART) testing. Traditionally, DART testing has been conducted in vivo in mammalian model systems. In fact, current EU DART testing guidelines accounts for the majority of animals used and the financial costs of new compound compliance testing. Therefore, because of the need to reduce the financial and animal costs associated with DART testing, there is a growing demand for new alternative model systems for toxicity evaluation. Dictyostelium discoideum is a eukaryotic amoeba which due to its unique developmental cycle has the potential to serve as a non-animal alternative model in DART testing. However, for a new alternative model to be proven effective it must allow for high-throughput screening, whilst maintaining biological complexity; allowing developmental toxicity results to be predictive of mammalian systems. To address these concerns, we developed new high-throughput D. discoideum growth and developmental toxicity assays. We use the assays to characterise toxicity across a broad range of test compounds, thereby revealing a significant relationship between D. discoideum and mammalian toxicity values. Our data demonstrates that D. discoideum has the biological complexity necessary to be predictive of mammalian toxicity. We further assess whether D. discoideum could be used to genetically characterise developmentally toxic compounds. Using next generation functional genomic screens, we show how the developmentally toxicity compounds, lithium and VPA can be globally genetically phenotyped. Using this genetic phenotyping approach, we were also able to identify the biological targets and processes that mediate lithium and VPA toxicity. Together, these studies illustrate the potential of D. discoideum to be developed as a new alternative model in DART testing

Micro/nanofluidic and lab-on-a-chip devices for biomedical applications

Micro/Nanofluidic and lab-on-a-chip devices have been increasingly used in biomedical research [1]. Because of their adaptability, feasibility, and cost-efficiency, these devices can revolutionize the future of preclinical technologies. Furthermore, they allow insights into the performance and toxic effects of responsive drug delivery nanocarriers to be obtained, which consequently allow the shortcomings of two/three-dimensional static cultures and animal testing to be overcome and help to reduce drug development costs and time [2–4]. With the constant advancements in biomedical technology, the development of enhanced microfluidic devices has accelerated, and numerous models have been reported. Given the multidisciplinary of this Special Issue (SI), papers on different subjects were published making a total of 14 contributions, 10 original research papers, and 4 review papers. The review paper of Ko et al. [1] provides a comprehensive overview of the significant advancements in engineered organ-on-a-chip research in a general way while in the review presented by Kanabekova and colleagues [2], a thorough analysis of microphysiological platforms used for modeling liver diseases can be found. To get a summary of the numerical models of microfluidic organ-on-a-chip devices developed in recent years, the review presented by Carvalho et al. [5] can be read. On the other hand, Maia et al. [6] report a systematic review of the diagnosis methods developed for COVID-19, providing an overview of the advancements made since the start of the pandemic. In the following, a brief summary of the research papers published in this SI will be presented, with organs-on-a-chip, microfluidic devices for detection, and device optimization having been identified as the main topics.info:eu-repo/semantics/publishedVersio