Thierry Dorval

Ischemia-Reperfusion Injury Leads to Distinct Temporal Cardiac Remodeling in Normal versus Diabetic Mice

Diabetes is associated with higher incidence of myocardial infarction (MI) and increased propensity for subsequent events post-MI. Here we conducted a temporal analysis of the influence of diabetes on cardiac dysfunction and remodeling after ischemia reperfusion (IR) injury in mice. Diabetes was induced using streptozotocin and IR performed by ligating the left anterior descending coronary artery for 30 min followed by reperfusion for up to 42 days. We first evaluated changes in cardiac function using echocardiography after 24 hours reperfusion and observed IR injury significantly decreased the systolic function, such as ejection fraction, fractional shortening and end systolic left ventricular volume (LVESV) in both control and diabetic mice. The longitudinal systolic and diastolic strain rate were altered after IR, but there were no significant differences between diabetic mice and controls. However, a reduced ability to metabolize glucose was observed in the diabetic animals as determined by PET-CT scanning using 2-deoxy-2-(18F)fluoro-D-glucose. Interestingly, after 24 hours reperfusion diabetic mice showed a reduced infarct size and less apoptosis indicated by TUNEL analysis in heart sections. This may be explained by increased levels of autophagy detected in diabetic mice hearts. Similar increases in IR-induced macrophage infiltration detected by CD68 staining indicated no change in inflammation between control and diabetic mice. Over time, control mice subjected to IR developed mild left ventricular dilation whereas diabetic mice exhibited a decrease in both end diastolic left ventricular volume and LVESV with a decreased intraventricular space and thicker left ventricular wall, indicating concentric hypertrophy. This was associated with marked increases in fibrosis, indicted by Masson trichrome staining, of heart sections in diabetic IR group. In summary, we demonstrate that diabetes principally influences distinct IR-induced chronic changes in cardiac function and remodeling, while a smaller infarct size and elevated levels of autophagy with similar cardiac function are observed in acute phase.

Three-dimensional point spread function model for line-scanning confocal microscope with high-aperture objective

Point Spread Function (PSF) modelling is an important task in image formation analysis. In confocal microscopy, the exact PSF is rarely known, thus one has to rely on its approximation. An initial estimation is usually performed experimentally by measuring fluorescent beads or analytically by studying properties of the optical system. Yet, fluorescent line‐scanning confocal microscopes are not widespread; therefore, very few adapted models are available in the literature. In this paper, we propose an analytical PSF model for line‐scanning confocal microscopes. Validation is performed by measuring the error between our model and an experimental PSF measured with fluorescent beads, assumed to represent the real PSF. Comparison with existing models is also presented.

A novel specific edge effect correction method for RNA interference screenings

MOTIVATION High-throughput screening (HTS) is an important method in drug discovery in which the activities of a large number of candidate chemicals or genetic materials are rapidly evaluated. Data are usually obtained by measurements on samples in microwell plates and are often subjected to artefacts that can bias the result selection. We report here a novel edge effect correction algorithm suitable for RNA interference (RNAi) screening, because its normalization does not rely on the entire dataset and takes into account the specificities of such a screening process. The proposed method is able to estimate the edge effects for each assay plate individually using the data from a single control column based on diffusion model, and thus targeting a specific but recurrent well-known HTS artefact. This method was first developed and validated using control plates and was then applied to the correction of experimental data generated during a genome-wide siRNA screen aimed at studying HIV-host interactions. The proposed algorithm was able to correct the edge effect biasing the control data and thus improve assay quality and, consequently, the hit-selection step.

HCS-Analyzer

MOTIVATION High-throughput screening is a powerful technology principally used by pharmaceutical industries allowing the identification of molecules of interest within large libraries. Originally target based, cellular assays provide a way to test compounds (or other biological material such as small interfering RNA) in a more physiologically realistic in vitro environment. High-content screening (HCS) platforms are now available at lower cost, giving the opportunity for universities or research institutes to access those technologies for research purposes. However, the amount of information extracted from each experiment is multiplexed and hence difficult to handle. In such context, there is an important need for an easy-to-use, but still powerful software able to manage multidimensional screening data by performing adapted quality control and classification. HCS-analyzer includes: a user-friendly interface specifically dedicated to HCS readouts, an automated approach to identify systematic errors potentially occurring during screening and a set of tools to classify, cluster and identify phenotypes of interest among large and multivariate data. AVAILABILITY The application, the C# .Net source code, as well as detailed documentation, are freely available at the following URL: http://hcs-analyzer.ip-korea.org.

Contextual Automated 3D Analysis of Subcellular Organelles Adapted to High-Content Screening

Advances in automated imaging microscopy allow fast acquisitions of multidimensional biological samples. Those microscopes open new possibilities for analyzing subcellular structures and spatial cellular arrangements. In this article, the authors describe a 3D image analysis framework adapted to medium-throughput screening. Upon adaptive and regularized segmentation, followed by precise 3D reconstruction, they achieve automatic quantification of numerous relevant 3D descriptors related to the shape, texture, and fluorescence intensity of multiple stained subcellular structures. A global analysis of the 3D reconstructed scene shows additional possibilities to quantify the relative position of organelles. Implementing this methodology, the authors analyzed the subcellular reorganization of the nucleus, the Golgi apparatus, and the centrioles occurring during the cell cycle. In addition, they quantified the effect of a genetic mutation associated with the early onset primary dystonia on the redistribution of torsinA from the bulk endoplasmic reticulum to the perinuclear space of the nuclear envelope. They show that their method enables the classification of various translocation levels of torsinA and opens the possibility for compound-based screening campaigns restoring the normal torsinA phenotype.

Automated Confocal Microscope Bias Correction

Illumination artifacts systematically occur in 2D cross‐section confocal microscopy imaging . These bias can strongly corrupt an higher level image processing such as a segmentation, a fluorescence evaluation or even a pattern extraction/recognition. This paper presents a new fully automated bias correction methodology based on large image database preprocessing. This method is very appropriate to the High Content Screening (HCS), method dedicated to drugs discovery. Our method assumes that the amount of pictures available is large enough to allow a reliable statistical computation of an average bias image. A relevant segmentation evaluation protocol and experimental results validate our correction algorithm by outperforming object extraction on non corrupted images.

Biased Image Correction Based on Empirical Mode Decomposition

The automated analysis of images is an active field of research in image processing and pattern recognition. In many applications, the first issue is to face illuminations artifacts that can appear due to bad imaging conditions. These artifacts often have direct consequences on the efficiency of the image analysis algorithms but also on the quantitative measures. This paper presents a fully automated nonuniformity correction based on empirical mode decomposition. The performances are outlined using both synthetic and real data.

High Content Screening for Compounds that Induce Early Stages of Human Embryonic Stem Cell Differentiation

Embryonic stem cells, due to their self-renewal and pluripotency properties, can be used to repair damaged tissues and as an unlimited source of differentiated cells. Although stem cells represent an important opportunity for cell based therapy and small molecules screening (in the context of drug or target discovery) many drawbacks are still preventing their widespread use. One of the most significant limitations is related to the complexity, as well as the reliability, of current protocols driving stem cells into any homogeneously differentiated cellular population. In this respect there is a strong demand for molecular agents promoting differentiation and thereby enabling robust, efficient and safe production of differentiated cells. In order to identify novel molecules that enhance early stages of differentiation, we developed an image based high content screening (HCS) approach using human embryonic stem cells (hESC). In our approach, we took advantage of custom image mining software specifically adapted for the selection of stem cell differentiation agents and the rejection of false positive hits. As a proof of concept -3500 small molecules originating from commercial libraries were screened and a number of molecules of interests were identified. These molecules show stem cell differentiation properties comparable to the phenotypic signature obtained with the reference compound retinoic acid.

A modified fluorescence in situ hybridization protocol for Plasmodium falciparum greatly improves nuclear architecture conservation.

Fluorescence in situ hybridization (FISH) has been used extensively in the study of nuclear organization and gene positioning in Plasmodium falciparum. While performing FISH with published protocols, we observed large variations in parasite nuclear morphology. We hypothesized that these inconsistencies might be due to the type of parasite preparation prior to FISH, which commonly involves air-drying, prompting us to develop a new fixation protocol. Here we show both qualitatively and quantitatively that compared to air-dried and briefly fixed parasites, longer fixation in suspension leads to improved conservation of nuclear structure and lower intra-population variation of nuclear shape as well as area after FISH development. While the fixation protocol per se does not cause detectable disruptions in nuclear morphology, it greatly influences the conservation of nuclear shape and size during the most stringent steps of FISH. The type of fixation used also influences the detection of telomeric clusters, and we show that the new fixation protocol permits improved conservation of the chromosome end cluster perinuclear distribution and higher colocalization indexes for two adjacent chromosome end probes, Rep20 and telomere. Overall, the results indicate that our alternative protocol dramatically improves conservation of the nuclear architecture compared to previously reported Plasmodium DNA-FISH protocols and highlights the necessity of carefully choosing the fixation protocol for FISH.

BIAS FREE FEATURES DETECTION FOR HIGH CONTENT SCREENING

Recent automated confocal microscopes used in high content screening (HCS) platforms require fully automated quantitative analysis due to the large amount of images they produce. Tuning the imaging process can not be manually performed on each image, therefore these automated acquisitions may come along with strong illumination artifacts due to poor physical imaging conditions. Such artifacts obviously have direct consequences on the efficiency of the image analysis algorithms but also on the quantitative measures. In this paper, we propose a method robust to illumination artifacts to extract any kind of small and isotropic objects within cells. To do so, we include a pre-processing step where a bias correction algorithm first attempts to retrieve original images from corrupted observations. We validate our framework with two different and independent statistical criteria