Freely Available Tool (FAT) for automated quantification of lipid droplets in stained cells

In this study, wepropose an automatic procedure for digital image processing. Wedescribe a method that can efficiently quantify and characterizelipid droplets distributions in different cell types in culture.Prospectively, the lipid droplets detection method described in thiswork could be applied to static or time-lapse data, collected with asimple visible light or fluorescence microscopy equipment. Fullyautomated algorithms were implemented in Octave, a freely availablescientific package.Fil: Masone, Diego Fernando. Consejo Nacional de Investigaciones Científicas y Técnicas. Centro Científico Tecnológico Conicet - Mendoza. Instituto de Histología y Embriología de Mendoza Dr. Mario H. Burgos. Universidad Nacional de Cuyo. Facultad de Ciencias Médicas. Instituto de Histología y Embriología de Mendoza Dr. Mario H. Burgos; Argentina. Universidad Nacional de Cuyo. Facultad de Ingeniería; ArgentinaFil: Gojanovich, Aldana Daniela. Consejo Nacional de Investigaciones Científicas y Técnicas. Centro Científico Tecnológico Conicet - Mendoza. Instituto de Histología y Embriología de Mendoza Dr. Mario H. Burgos. Universidad Nacional de Cuyo. Facultad de Ciencias Médicas. Instituto de Histología y Embriología de Mendoza Dr. Mario H. Burgos; ArgentinaFil: Frontini López, Yesica Romina. Consejo Nacional de Investigaciones Científicas y Técnicas. Centro Científico Tecnológico Conicet - Mendoza. Instituto de Histología y Embriología de Mendoza Dr. Mario H. Burgos. Universidad Nacional de Cuyo. Facultad de Ciencias Médicas. Instituto de Histología y Embriología de Mendoza Dr. Mario H. Burgos; ArgentinaFil: del Veliz, Samanta. Consejo Nacional de Investigaciones Científicas y Técnicas. Centro Científico Tecnológico Conicet - Mendoza. Instituto de Histología y Embriología de Mendoza Dr. Mario H. Burgos. Universidad Nacional de Cuyo. Facultad de Ciencias Médicas. Instituto de Histología y Embriología de Mendoza Dr. Mario H. Burgos; ArgentinaFil: Uhart, Marina. Consejo Nacional de Investigaciones Científicas y Técnicas. Centro Científico Tecnológico Conicet - Mendoza. Instituto de Histología y Embriología de Mendoza Dr. Mario H. Burgos. Universidad Nacional de Cuyo. Facultad de Ciencias Médicas. Instituto de Histología y Embriología de Mendoza Dr. Mario H. Burgos; ArgentinaFil: Bustos, Diego Martin. Consejo Nacional de Investigaciones Científicas y Técnicas. Centro Científico Tecnológico Conicet - Mendoza. Instituto de Histología y Embriología de Mendoza Dr. Mario H. Burgos. Universidad Nacional de Cuyo. Facultad de Ciencias Médicas. Instituto de Histología y Embriología de Mendoza Dr. Mario H. Burgos; Argentin

Development of Phenotypic Drug Discovery Models for Tropical Parasitic Diseases

Malaria and visceral leishmaniasis are major killer parasitic diseases. These diseases though occur primarily in tropical countries; economic burden and overall health impacts of malaria and leishmaniasis are global. The emergence of drug-resistant and more-virulent strains of the pathogens has further amplified the problems. New drug discovery approaches primarily rely on in vitro and in vivo models of the disease. The pathogens causing leishmaniasis and malaria are intracellular. Leishmania parasite grows as amastigotes in macrophages cells, and malaria parasite grows within the hepatocytes or erythrocytes. The intracellular forms of the pathogens are responsible for the pathophysiology of the diseases. New phenotypic cell-based models have been developed for leishmaniasis and malaria, those have been employed for in vitro/in vivo screening for new drug discovery. A parasite-rescue and transformation assay was developed for macrophage-internalized Leishmania donovani amastigotes. The assay has been applied for high-throughput screening of a library of plants’ fractions. Two fluorescent transgenic cell lines of L. donovani were developed with mCherry and Citrine reporter genes by stable transfection approach. The transgenic cell lines have shown stable and constitutive expression of the fluorescent reporter proteins. The in vitro screening methods were developed with the transgenic leishmania cells employing flow-cytometric and fluorescent microscopy analyses. Analysis of parasitemia and intra-erythrocytic growth of the parasite are hallmarks of malaria research. A flow-cytometric assay, based on staining of the malaria parasites with LDS-751, a fluorescent cell-permeant nucleic acid stain, was developed for parasitemia analysis. Staining of malaria-infected RBCs may be performed directly without additional processing. Selective staining of malaria-infected erythrocytes by LDS-751 was confirmed with fluorescent microscopy. The method has been applied for flow-cytometric analysis of parasitemia in mice blood infected with Plasmodium berghei and human blood infected with P. falciparum. The utility of this developed method was established for both in vitro and in vivo antimalarial drug screenings. Establishment of the new phenotypic assay will expedite the process of new drug discovery against the tropical parasitic diseases. These assays would also have utility for understanding biology, virulence, and pathogenesis of malaria and leishmania pathogens

Flow Cytometric Analysis of Avian Blood Cells: Differentiation of Erythrocytes and Leukocytes by Fluorescence.

Automated analyzers have revolutionized diagnostic hematology in mammalian species. These commercial instruments utilize flow cytometric technology to enumerate blood cell concentrations. Because of the nuclei present in most non-mammalian erythrocytes and thrombocytes, these instruments are unable to calculate leukocyte counts in birds, amphibians, reptiles, and fish. These investigations sought to determine if three commonly used methodologies in flow cytometry could sufficiently differentiate avian erythrocytes, leukocytes, and thrombocytes, and ultimately form a basis for performing total leukocyte counts. Fluorescein isothiocyanate (FITC) and thiazole orange (TO) were used to stain samples of whole, erythrocyte-, and leukocyte-enriched chicken blood. Although fluorescent microscopic and flow cytometric results obtained using both stains suggested a higher propensity for these dyes in leukocytes and thrombocytes, the difference in fluorescence intensity with erythrocytes was not sufficient to assess their concentration. Furthermore, leukocytes stained with FITC were found consistently in the large erythrocyte peak in cell sorting experiments. Cell counts performed on a population of cells defined by higher TO staining correlated poorly with manual total leukocyte counts. Chicken blood cells were also examined for reactivity with anti-spectrin, anti-vimentin, and anti-$\beta$-tubulin antibodies. Leukocytes demonstrated a higher non-specific staining with secondary antibodies. The inclusion of normal serum as a blocking step essentially eliminated this reactivity. The non-specific staining was not detected by flow cytometry. Although these investigations verified that standard flow cytometric techniques may be utilized to analyze avian leukocytes, sufficient differentiation of these cells from erythrocytes was not achievable for quantitative purposes. Methods with increased sensitivity of fluorescence detection or improved specificity of leukocyte staining are needed to develop a system by which this important diagnostic evaluation can be automated in non-mammalian hematology

Convolutional Neural Networks for Cellular Segmentation

Üha enam lülituvad algoritmid töö tegemisel väärtuslikeks abimeesteks. Tänapäevase tehnoloogia toel on võimalik inimesed vabastada lihtsamatest ülesannetest, et nad saaksid keskenduda teistele töödele, mis on arvuti jaoks keerulised. Üks abistavatest tehnoloogiatest on süvaõpe. Selle abil suudavad arvutid lahendada ülesandeid, mida varem peeti arvutite jaoks raskeks või koguni võimatuks.Üheks selliseks tööks on erevälja rakupiltide segmenteerimine. Seda on tarvis eelkõige biomeditsiinilaborites ning ravimifirmades, mis peavad suurt hulka mikroskoobipilte analüüsima ja kvantifitseerima. Praegused tööprotsessid väldivad ereväljapiltide kasutust, kuna nende segmenteerimiseks pole tööstuslikke lahendusi ning käsitsi töötlemine on keerukas ja aeganõudev.Magistritöö eesmärgiks on tõestada, et masinõpe suudab lahendada seni masinatele raskete ereväljapiltide segmenteerimise ülesande. Loodud lahendus aitab teadlastel üle maailma katsetada teisi uurimismeetodeid ja säästa palju aega.There is a persistent demand for work-assisting algorithms in industry. Using present-day technology, it is possible to free people from mundane tasks so they can concentrate on work that requires human skills and flexibility. Deep learning methods can complete tasks that were previously considered hard or even impossible for machines.One example of this kind of task is segmenting brightfield microscopy images of cells. This work is needed mostly in biomedical laboratories and pharmaceutical companies that must analyse and quantify vast amounts of image data. Current workflows avoid useful brightfield imagery because automatic industrial solutions for segmentation do not exist. Manual annotation is very challenging and time consuming, even for experienced professionals.The goal of the thesis is to demonstrate that deep learning can solve the task of segmenting challenging brightfield images. The developed solution opens new experimental approaches, saving time and resources for biomedical scientists across the globe

HIGH-THROUGHPUT FLUORESCENCE MICROSCOPY FOR AUTOMATED CLINICAL APPLICATIONS

Fluorescence in situ hybridization (FISH) is a powerful tool for visualizing and detecting genetic abnormalities. Manual scoring FISH analysis is a tedious and labor-and-time-consuming task. Automated image acquisition and analysis provide an opportunity to overcome the difficulties. However, conventional fluorescence microscopes, the mostly used instrument for FISH imaging, have deficiencies. A multi-spectral image modality must be employed in order to visualize fluorescently dyed FISH probes for analysis, and the existing technologies are either two expensive, too slow, or both. Aiming at upgrading the current employed cytogenetic instrumentation, we developed a new imaging technique capable of simultaneously imaging multiple color spectra. Using the principle, we implemented a prototype system and conduct various characterization experiments. Experiment results (<1% peripheral geometric distortion, consistent signal response linearity, and ~2000 lp/mm spatial resolution) show no significant compromise in terms of optical performance. A detector alignment scheme was developed and performed to minimize registration error. The system has significantly faster acquisition speed than conventional fluorescence microscopes albeit the extra cost is quite insignificant

Development of artificial cell culture platforms using microfluidics

Acquiring quantitative data about cells, cell-cell interactions and cellular responses to surrounding environments are crucial for medical diagnostics, treatment and cell biology research. Nowadays, this is possible through microfluidic cell culture platforms. These devices, lab-on-a-chip (LOC), are capable of culturing cells with the feature of mimicking in vivo cellular conditions. Through the control of fluids in small volumes, LOC closely mimics the nature of cells in the tissues compared to conventional cell culturing platforms such as flasks and cell culture plates. On the other hand, existing LOC-based cell culturing platforms are highly complicated to be used in clinics or laboratories without an expert who develops these microfluidic platforms. Therefore, in this thesis we developed simple and user-friendly microfluidic cell culturing platforms and compared our obtained data with the conventional methods. We performed our research on different human cancer cell lines including liver hepatocellular carcinoma, breast adenocarcinoma, and lymphoma cell lines; both monocytes and monocyte-differentiated macrophages. We examined proliferation rate, morphological and phenotypical differences of the cells in different scales. In addition to cell culturing platform, we developed a microfluidic gradient generator to precisely titrate the concentration of chemicals and observed cellular responses to these stresses. Moreover, we quantitatively inspected the effect of different intravenous fluids on different human cancer cell lines. Finally, we have developed simple, low-cost and integrable microfluidic platforms, those can be used by untrained people, and perform cell culture experiments in a population at single-cell resolution. Our microfluidic cell culture platforms provide more quantitative and qualitative data compared to traditional batch culture assay

Automated Correlative Light and Electron Microscopy using FIB-SEM as a tool to screen for ultrastructural phenotypes

In Correlative Light and Electron Microscopy (CLEM), two imaging modalities are combined to take advantage of the localization capabilities of light microscopy (LM) to guide the capture of high-resolution details in the electron microscope (EM). However, traditional approaches have proven to be very laborious, thus yielding a too low throughput for quantitative or exploratory studies of populations. Recently, in the electron microscopy field, FIB-SEM (Focused Ion Beam -Scanning Electron Microscope) tomography has emerged as a flexible method that enables semi-automated 3D volume acquisitions. During my thesis, I developed CLEMSite, a tool that takes advantage of the semi-automation and scanning capabilities of the FIB-SEM to automatically acquire volumes of adherent cultured cells. CLEMSite is a combination of computer vision and machine learning applications with a library for controlling the microscope ( product from a collaboration with Carl Zeiss GmbH and Fibics Inc.). Thanks to this, the microscope was able to automatically track, find and acquire cell regions previously identified in the light microscope. More specifically, two main modules were implemented. First, a correlation module was designed to detect and record reference points from a grid pattern present on the culture substrate in both modalities (LM and EM). Second, I designed a module that retrieves the regions of interest in the FIB-SEM and that drives the acquisition of image stacks between different targets in an unattended fashion. The automated CLEM approach is demonstrated on a project where 3D EM volumes are examined upon multiple siRNA treatments for knocking down genes involved in the morphogenesis of the Golgi apparatus. Additionally, the power of CLEM approaches using FIB-SEM is demonstrated with the detailed structural analysis of two events: the breakage of the nuclear envelope within constricted cells and an intriguing catastrophic DNA Damage Response in binucleated cells. Our results demonstrate that executing high throughput volume acquisition in electron microscopy is possible and that EM can provide incredible insights to guide new biological discoveries

Suspension fluorescence in situ hybridization (S-FISH) combined with automatic detection and laser microdissection for STR profiling of male cells in male/female mixtures

Laser microdissection is a valuable tool for isolating specific cells from mixtures, such as male cells in a mixture with female cells, e.g., in cases of sexual assault. These cells can be stained with Y-chromosome-specific probes. We developed an automatic screening method to detect male cells after fluorescence in situ hybridization in suspension (S-FISH). To simulate forensic casework, the method was tested on female saliva after cataglottis (a kiss involving tongue-to-tongue contact) and on licking traces (swabs of dried male saliva on female skin) even after drying. After isolation of the detected cells, short tandem repeat profiling was performed. Full DNA profiles could consistently be obtained from as little as ten buccal cells. Isolation of five cells resulted in a mean of 98% (SD of 3.4%) of the alleles detected, showing that the developed S-FISH staining had no significant negative influence on DNA recovery and can be used in forensic casework

The watershed transform in pathological image analysis: application in rectiulocyte count from supravital stained smears

Background: Morphometric studies based on image analysis are a useful adjunct for quantitative analysis of microscopic images. However, effective separation of overlapping objects if often the bottleneck in image analysis techniques. We employ the watershed transform for counting reticulocytes from images of supravitally stained smears.Methods: The algorithm was developed with the Python programming platform, using the Numpy, Scipy and OpenCV libraries. The initial development and testing of the software were carried out with images from the American Society of Hematology Image Library. Then a pilot study with 30 samples was then taken up. The samples were incubated with supravital stain immediately after collection, and smears prepared. The smears were microphotographed at 100X objective, with no more than 150 RBCs per field. Reticulocyte count was carried out manually as well as by image analysis.Results: 600 out of 663 reticulocytes (90.49%) were correctly identified, with a specificity of 98%. The major difficulty faced was the slight bluish tinge seen in polychromatic RBCs, which were inconsistently detected by the software.Conclusions: The watershed transform can be used successfully to separate overlapping objects usually encountered in pathological smears. The algorithm has the potential to develop into a generalized cell classifier for cytopathology and hematology