Time-Lapse Microscopy

Time-lapse microscopy is a powerful, versatile and constantly developing tool for real-time imaging of living cells. This review outlines the advances of time-lapse microscopy and refers to the most interesting reports, thus pointing at the fact that the modern biology and medicine are entering the thrilling and promising age of molecular cinematography

AN EFFECTIVE MITOSIS RECOGNITION AND SEGMENTATION TOOL FOR STEM CELL EXPLORATION

ABSTRACT Stem cells, on regenerative medicine, has enormous potential and impact, lead to the rapidly growing interest for tools to analyze and characterize the behaviors of these cells in-vitro in an automated and high throughput fashion. Measurement of the proliferative behaviors of cells in-vitro is important to many biomedical applications for the measurement of the accurate counting and localization of occurrences of mitosis, or cell division, in a cell culture. In this paper, the performance analysis of clustering for segmenting the mitosis detection is proposed. It is possible to manually identify incidents of mitosis because mitotic cells in culture tend to exhibit intensified surrounding halos under phase contrast illumination. This halo artifact is eliminated by using Diffusion corona filter. Using this method of segmentation precision of 97.1% is obtained which is 1.3% higher when compared with the semi Markov process of segmentation

A Novel Validation Algorithm Allows for Automated Cell Tracking and the Extraction of Biologically Meaningful Parameters

Automated microscopy is currently the only method to non-invasively and label-free observe complex multi-cellular processes, such as cell migration, cell cycle, and cell differentiation. Extracting biological information from a time-series of micrographs requires each cell to be recognized and followed through sequential microscopic snapshots. Although recent attempts to automatize this process resulted in ever improving cell detection rates, manual identification of identical cells is still the most reliable technique. However, its tedious and subjective nature prevented tracking from becoming a standardized tool for the investigation of cell cultures. Here, we present a novel method to accomplish automated cell tracking with a reliability comparable to manual tracking. Previously, automated cell tracking could not rival the reliability of manual tracking because, in contrast to the human way of solving this task, none of the algorithms had an independent quality control mechanism; they missed validation. Thus, instead of trying to improve the cell detection or tracking rates, we proceeded from the idea to automatically inspect the tracking results and accept only those of high trustworthiness, while rejecting all other results. This validation algorithm works independently of the quality of cell detection and tracking through a systematic search for tracking errors. It is based only on very general assumptions about the spatiotemporal contiguity of cell paths. While traditional tracking often aims to yield genealogic information about single cells, the natural outcome of a validated cell tracking algorithm turns out to be a set of complete, but often unconnected cell paths, i.e. records of cells from mitosis to mitosis. This is a consequence of the fact that the validation algorithm takes complete paths as the unit of rejection/acceptance. The resulting set of complete paths can be used to automatically extract important biological parameters with high reliability and statistical significance. These include the distribution of life/cycle times and cell areas, as well as of the symmetry of cell divisions and motion analyses. The new algorithm thus allows for the quantification and parameterization of cell culture with unprecedented accuracy. To evaluate our validation algorithm, two large reference data sets were manually created. These data sets comprise more than 320,000 unstained adult pancreatic stem cells from rat, including 2592 mitotic events. The reference data sets specify every cell position and shape, and assign each cell to the correct branch of its genealogic tree. We provide these reference data sets for free use by others as a benchmark for the future improvement of automated tracking methods

Conference of Advance Research and Innovation (ICARI-2014) 118 ICARI

Abstract With the advent of highly advanced optics and imaging system, currently biological research has reached a stage where scientists can study biological entities and processes at molecular and cellular-level in real time. However, a single experiment consists of hundreds and thousands of parameters to be recorded and a large population of microscopic objects to be tracked. Thus, making manual inspection of such events practically impossible. This calls for an approach to computer-vision based automated tracking and monitoring of cells in biological experiments. This technology promises to revolutionize the research in cellular biology and medical science which includes discovery of diseases by tracking the process in cells, development of therapy and drugs and the study of microscopic biological elements. This article surveys the recent literature in the area of computer vision based automated cell tracking. It discusses the latest trends and successes in the development and introduction of automated cell tracking techniques and systems

An objective comparison of cell-tracking algorithms

We present a combined report on the results of three editions of the Cell Tracking Challenge, an ongoing initiative aimed at promoting the development and objective evaluation of cell segmentation and tracking algorithms. With 21 participating algorithms and a data repository consisting of 13 data sets from various microscopy modalities, the challenge displays today's state-of-the-art methodology in the field. We analyzed the challenge results using performance measures for segmentation and tracking that rank all participating methods. We also analyzed the performance of all of the algorithms in terms of biological measures and practical usability. Although some methods scored high in all technical aspects, none obtained fully correct solutions. We found that methods that either take prior information into account using learning strategies or analyze cells in a global spatiotemporal video context performed better than other methods under the segmentation and tracking scenarios included in the challenge

A dynamic mode of mitotic bookmarking by transcription factors.

During mitosis, transcription is shut off, chromatin condenses, and most transcription factors (TFs) are reported to be excluded from chromosomes. How do daughter cells re-establish the original transcription program? Recent discoveries that a select set of TFs remain bound on mitotic chromosomes suggest a potential mechanism for maintaining transcriptional programs through the cell cycle termed mitotic bookmarking. Here we report instead that many TFs remain associated with chromosomes in mouse embryonic stem cells, and that the exclusion previously described is largely a fixation artifact. In particular, most TFs we tested are significantly enriched on mitotic chromosomes. Studies with Sox2 reveal that this mitotic interaction is more dynamic than in interphase and is facilitated by both DNA binding and nuclear import. Furthermore, this dynamic mode results from lack of transcriptional activation rather than decreased accessibility of underlying DNA sequences in mitosis. The nature of the cross-linking artifact prompts careful re-examination of the role of TFs in mitotic bookmarking

Monitoring and mathematical modeling of in vitro human megakaryocyte expansion and maturation dynamics

La mégakaryopoïèse est un processus complexe, qui prend naissance à partir des cellules souches hématopoïétiques (HSC). Ces dernières se différencient par étapes successives en mégakaryocytes (MKs) qui, suite à leur maturation, libèrent les plaquettes. Afin de modéliser le sort des HSCs lors de la mégakaryopoïèse en culture, un nouveau modèle mathématique a été développé, basé sur un programme de différenciation tridimensionnelle (3-D) où chaque sous-population est représentée par un compartiment. Dans le but d’évaluer la prolifération, la différenciation des MKs immatures puis matures, la cinétique de mort cellulaire ainsi que le nombre de plaquettes produites, à partir des cellules de sang de cordon (CB) ombilical enrichies en CD34+, un ensemble d'équations différentielles a été déployé. Les cellules CD34+ ont été placées en culture dans un milieu optimisé pour la différenciation mégakaryocytaire. Les paramètres cinétiques ont été estimés pour deux températures d'incubation (37°C versus 39°C). Les résultats des régressions ont été validés par l'évaluation de l'estimabilité des paramètres, en utilisant des analyses de sensibilité locale et globale, puis la détermination d'un intervalle de confiance. Ceux-ci ont été comparés par le biais de tests statistiques et d’analyses en composante principale (ACP). Le modèle proposé pourrait permettre de mieux comprendre les phénomènes complexes observés. Les MKs sont uniques parmi les cellules hématopoïétiques, étant les seules à devenir polyploïdes au cours de leur développement par l’entremise de l’endomitose, un processus mitotique qui se termine prématurément durant la cytocinèse. Pour obtenir une image plus complète et exhaustive de la mégacaryopoïèse, une approche d’imagerie cellulaire à grand champ et à long terme a été développée permettant de suivre individuellement l'évolution des HSCs lors de leur différenciation ex vivo. Cela a permis de démontrer que les MKs polyploïdes sont encore capables de se diviser et de produire des cellules filles polyploïdes, et que ce processus est plus fréquent chez les MKs issues de CB que de moelle osseuse d'adulte. De plus, le processus de formation des proplaquettes semble également réversible. Les phénomènes énoncés plus haut étaient inversement proportionnels au niveau de ploïdie des MKs. En conclusion, cette étude a dévoilé de nouvelles propriétés jusqu’ici inconnues des MKs.Megakaryopoiesis is a complex process, which is initiated with the proliferation and the differentiation of hematopoietic stem cells (HSC) into megakaryocytes (MK), followed by the maturation of MK and ended by platelet release. To describe the fates of HSC during ex vivo megakaryopoiesis, a new mathematical model was developed based on a 3-dimensional kinetic developmental program. To address this, a set of differential equations was applied to analyze the proliferation, differentiation and death kinetic rates of purified cord blood (CB)-CD34+ cells, immature and mature MKs, as well as platelet number and productivity. CB-CD34+ cells were placed in culture optimized for MK differentiation. The kinetic parameters were estimated for two incubation temperatures (37°C vs. 39°C). The regression results have been validated by assessing the parameter identifiability using local and global sensitivity analyses and confidence intervals, and compared using statistical tests and principal component analysis (PCA). Furthermore, PCA was applied on the solution matrix to construct a simplified MK differentiation pathway model, and to reveal dependencies among the model parameters. The proposed model provides insight into phenomena that would be otherwise difficult to interpret. MKs are unique among mammalian marrow cells as they polyploidize during their natural development. It is universally accepted that MK becomes polyploid by repeatedly deviating from normal cell cycling, where it ceases to complete cytokinesis and divide. To challenge this long-standing hypothesis and to obtain a more comprehensive picture of megakaryopoiesis, a long-term and large-field live cell imaging approach of in vitro MK culture was developed. Using CB- and bone marrow (BM)-CD34+ as starting cells, the direct observation of cells undergoing differentiation and maturation over a 5-day culture period is reported for the first time. Herein, direct visual proof that polyploid MKs can complete cytokinesis during its normal development is presented. This phenomenon was found not restricted to CB- as the BM-derived polyploid MK also underwent division. However the latter showed significantly lower proliferation rate. This new finding explains in part the unresolved issue of low ploidy levels observed in CB-MK and contests the notion that polyploid MKs do not divide