298 research outputs found

    Fluorescent Labeling, Co-Tracking, and Quantification of RNA In Cellulo.

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    RNA plays a fundamental, pervasive role in cellular physiology, through the maintenance and controlled readout of all genetic information, a functional landscape we are only beginning to understand. In particular, the cellular mechanisms for the spatiotemporal control of the plethora of RNAs are still poorly understood. Intracellular single-molecule fluorescence microscopy provides a powerful emerging tool for probing the pertinent biophysical and biochemical parameters that govern cellular RNA functions, including those of protein-encoding mRNAs. Yet progress has been hampered by the scarcity of high-yield, efficient methods to fluorescently label RNA molecules without the need to drastically increase their molecular weight through artificial appendages that may result in altered behavior. Herein, we employ a series of in vitro enzymatic techniques to efficiently, extensively and in high-yield, incorporate chemically modified nucleoside triphosphates into a transcribed messenger RNA body, between its body and tail (BBT), or randomly throughout the poly(A) tail (tail). Of these, BBT and tail modified strategies proved the most promising methods to functionally label messenger RNA and single-particle track their behaviors using our in-house single-molecule assay: intracellular single-molecule high resolution localization and counting (iSHiRLoC). From this research also was spawned a novel method to anchor an RNA to the actin cytoskeleton for the study of long-term interactions within a cellular context, termed: Gene-Actin Tethered Intracellular Co-tracking Assay (GATICA). Here, biotinylated RNA is tethered to the actin surface, either through complexation with a streptavidin coupled to a biotinylated phalloidin molecule or actin protein. Taken together, this body of work represents strategies for the labeling and visualizing, both freely diffusing and actin tethered, long-RNAs and their interactome in real-time.PHDChemical BiologyUniversity of Michigan, Horace H. Rackham School of Graduate Studieshttp://deepblue.lib.umich.edu/bitstream/2027.42/135832/1/tcuster_1.pd

    Bayesian multi-target tracking: application to total internal reflection fluorescence microscopy

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    This thesis focuses on the problem of automated tracking of tiny cellular and sub-cellular structures, known as particles, in the sequences acquired from total internal reflection fluorescence microscopy (TIRFM) imaging technique. Our primary biological motivation is to develop an automated system for tracking the sub-cellular structures involving exocytosis (an intracellular mechanism) which is helpful for studying the possible causes of the defects in diseases such as diabetes and obesity. However, all methods proposed in this thesis are generalized to be applicable for a wide range of particle tracking applications. A reliable multi-particle tracking method should be capable of tracking numerous similar objects in the presence of high levels of noise, high target density and complex motions and interactions. In this thesis, we choose the Bayesian filtering framework as our main approach to deal with this problem. We focus on the approaches that work based on detections. Therefore, in this thesis, we first propose a method that robustly detects the particles in the noisy TIRFM sequences with inhomogeneous and time-varying background. In order to evaluate our detection and tracking methods on the sequences with known and reliable ground truth, we also present a framework for generating realistic synthetic TIRFM data. To propose a reliable multi-particle tracking method for TIRFM sequences, we suggest a framework by combining two robust Bayesian filters, the interacting multiple model and joint probabilistic data association (IMM-JPDA) filters. The performance of our particle tracking method is compared against those of several popular and state-of-the art particle tracking approaches on both synthetic and real sequences. Although our approach performs well in tracking particles, it can be very computationally demanding for the applications with dense targets with poor detections. To propose a computationally cheap, but reliable, multi-particle tracking method, we investigate the performance of a recent multi-target Bayesian filter based on random finite theory, the probability hypothesis density (PHD) filter, on our application. To this end, we propose a general framework for tracking particles using this filter. Moreover, we assess the performance of our proposed PHD filter on both synthetic and real sequences with high level of noise and particle density. We compare its results from both aspects of accuracy and processing time against our IMM-JPDA filter. Finally, we suggest a framework for tracking particles in a challenging problem where the noise characteristic and the background intensity of sequences change during the acquisition process which make detection profile and clutter rate time-variant. To deal with this, we propose a bootstrap filter using another type of the random finite set based Bayesian filters, the cardinalized PHD (CPHD) filter, composed of an estimator and a tracker. The estimator adaptively estimates the required meta parameters for the tracker such as clutter rate and the detection probability while the tracker estimates the state of the targets. We evaluate the performance of our bootstrap on both synthetic and real sequences under these time-varying conditions. Moreover, its performance is compared against those of our other particle trackers as well as the state-of-the art particle tracking approaches

    Group Decisions Influence Emergence and Regulation of Leaders during Collective Migration of Epithelial Cells

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    Collective migration is a central event involving coordinated movement of several individuals. One of the critical events during collective migration is the emergence of leading individuals, who provide directional guidance for the group movement. While on the move, animals select their leaders by a collective decision making process, which require active participation of the followers. On the contrary, the prevalent view on collective cell migration, especially in the context of epithelial cells during wound healing, assumes a hierarchical leader-follower organization and belittles the contribution of follower cells in choosing or regulating the leaders. Furthermore, how the dynamics of cells located at the wound margin evolve as the wound heals, remains illusive. Here, we report and analyse distinct phases of collective migration during wound closure and demonstrate how cellular-level shared decision-making process and collective mechanical dynamics influence selection, regulation and kinematics of leader cells in these phases. We found that in the preparatory phase, before the initiation of migration (Phase 0), the selection of leader cells at the epithelial wound margin depends on the pre-migratory dynamics of the follower cells situated immediately behind the future leaders. Long before the prospective leaders actually start displaying their phenotypic peculiarities, cells behind them manifest stochastic augmentations in the traction forces and monolayer stresses, and display large perimeter-to-area ratio indicating a local unjamming in the followers much before the leaders are selected. Further, introducing an unjammed or fluidic follower at the back stimulates leader cell formation at the margin thereby indicating the role of collective bulk dynamics in leader cell selection. Interestingly, the length upto which cells cooperatively join forces, corresponds very well with the distance between the two emerging leaders and this mechano-biological control remains preserved even in the presence of geometric bias or physiological levels of chemical cue at the interface. Immediately after the initiation of migration (Phase 1), leaders show their distinct phenotypes and drive the cellular outgrowths. In this phase, pluricellular actin belt at the margin regulates the fraction of marginal leaders, which therefore remains unchanged, while the number of followers per leader increases with time. As the migration progresses, fraction of leader cells increases while the latter settles to a steady level set again by the length scale of cell-cell force transmission (Phase 2). Any perturbations in mechanical forces that modifies the force correlation lengths, invariably enforces a change in the number of followers per leader thereby modifying the time required to transit from one phase to the other. Furthermore, orientation of focal adhesions and persistence of cellular motions also display this phase specific behaviour. Together, these findings provide a novel system insight into collective cell migration and indicate integrative leader-follower interactions during wound closure. Given the physiological and pathological importance of leader cell formation in epithelial wound healing, in organogenesis and in metastatic migration of cancer cells, the system-view that the results offer here is anticipated to have to a long-standing impact on the design and discovery of avant-garde therapeutic strategies in future

    Advances in Artificial Intelligence: Models, Optimization, and Machine Learning

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    The present book contains all the articles accepted and published in the Special Issue “Advances in Artificial Intelligence: Models, Optimization, and Machine Learning” of the MDPI Mathematics journal, which covers a wide range of topics connected to the theory and applications of artificial intelligence and its subfields. These topics include, among others, deep learning and classic machine learning algorithms, neural modelling, architectures and learning algorithms, biologically inspired optimization algorithms, algorithms for autonomous driving, probabilistic models and Bayesian reasoning, intelligent agents and multiagent systems. We hope that the scientific results presented in this book will serve as valuable sources of documentation and inspiration for anyone willing to pursue research in artificial intelligence, machine learning and their widespread applications

    Image Processing and Simulation Toolboxes of Microscopy Images of Bacterial Cells

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    Recent advances in microscopy imaging technology have allowed the characterization of the dynamics of cellular processes at the single-cell and single-molecule level. Particularly in bacterial cell studies, and using the E. coli as a case study, these techniques have been used to detect and track internal cell structures such as the Nucleoid and the Cell Wall and fluorescently tagged molecular aggregates such as FtsZ proteins, Min system proteins, inclusion bodies and all the different types of RNA molecules. These studies have been performed with using multi-modal, multi-process, time-lapse microscopy, producing both morphological and functional images. To facilitate the finding of relationships between cellular processes, from small-scale, such as gene expression, to large-scale, such as cell division, an image processing toolbox was implemented with several automatic and/or manual features such as, cell segmentation and tracking, intra-modal and intra-modal image registration, as well as the detection, counting and characterization of several cellular components. Two segmentation algorithms of cellular component were implemented, the first one based on the Gaussian Distribution and the second based on Thresholding and morphological structuring functions. These algorithms were used to perform the segmentation of Nucleoids and to identify the different stages of FtsZ Ring formation (allied with the use of machine learning algorithms), which allowed to understand how the temperature influences the physical properties of the Nucleoid and correlated those properties with the exclusion of protein aggregates from the center of the cell. Another study used the segmentation algorithms to study how the temperature affects the formation of the FtsZ Ring. The validation of the developed image processing methods and techniques has been based on benchmark databases manually produced and curated by experts. When dealing with thousands of cells and hundreds of images, these manually generated datasets can become the biggest cost in a research project. To expedite these studies in terms of time and lower the cost of the manual labour, an image simulation was implemented to generate realistic artificial images. The proposed image simulation toolbox can generate biologically inspired objects that mimic the spatial and temporal organization of bacterial cells and their processes, such as cell growth and division and cell motility, and cell morphology (shape, size and cluster organization). The image simulation toolbox was shown to be useful in the validation of three cell tracking algorithms: Simple Nearest-Neighbour, Nearest-Neighbour with Morphology and DBSCAN cluster identification algorithm. It was shown that the Simple Nearest-Neighbour still performed with great reliability when simulating objects with small velocities, while the other algorithms performed better for higher velocities and when there were larger clusters present

    Removal of antagonistic spindle forces can rescue metaphase spindle length and reduce chromosome segregation defects

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    Regular Abstracts - Tuesday Poster Presentations: no. 1925Metaphase describes a phase of mitosis where chromosomes are attached and oriented on the bipolar spindle for subsequent segregation at anaphase. In diverse cell types, the metaphase spindle is maintained at a relatively constant length. Metaphase spindle length is proposed to be regulated by a balance of pushing and pulling forces generated by distinct sets of spindle microtubules and their interactions with motors and microtubule-associated proteins (MAPs). Spindle length appears important for chromosome segregation fidelity, as cells with shorter or longer than normal metaphase spindles, generated through deletion or inhibition of individual mitotic motors or MAPs, showed chromosome segregation defects. To test the force balance model of spindle length control and its effect on chromosome segregation, we applied fast microfluidic temperature-control with live-cell imaging to monitor the effect of switching off different combinations of antagonistic forces in the fission yeast metaphase spindle. We show that spindle midzone proteins kinesin-5 cut7p and microtubule bundler ase1p contribute to outward pushing forces, and spindle kinetochore proteins kinesin-8 klp5/6p and dam1p contribute to inward pulling forces. Removing these proteins individually led to aberrant metaphase spindle length and chromosome segregation defects. Removing these proteins in antagonistic combination rescued the defective spindle length and, in some combinations, also partially rescued chromosome segregation defects. Our results stress the importance of proper chromosome-to-microtubule attachment over spindle length regulation for proper chromosome segregation.postprin

    Psr1p interacts with SUN/sad1p and EB1/mal3p to establish the bipolar spindle

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    Regular Abstracts - Sunday Poster Presentations: no. 382During mitosis, interpolar microtubules from two spindle pole bodies (SPBs) interdigitate to create an antiparallel microtubule array for accommodating numerous regulatory proteins. Among these proteins, the kinesin-5 cut7p/Eg5 is the key player responsible for sliding apart antiparallel microtubules and thus helps in establishing the bipolar spindle. At the onset of mitosis, two SPBs are adjacent to one another with most microtubules running nearly parallel toward the nuclear envelope, creating an unfavorable microtubule configuration for the kinesin-5 kinesins. Therefore, how the cell organizes the antiparallel microtubule array in the first place at mitotic onset remains enigmatic. Here, we show that a novel protein psrp1p localizes to the SPB and plays a key role in organizing the antiparallel microtubule array. The absence of psr1+ leads to a transient monopolar spindle and massive chromosome loss. Further functional characterization demonstrates that psr1p is recruited to the SPB through interaction with the conserved SUN protein sad1p and that psr1p physically interacts with the conserved microtubule plus tip protein mal3p/EB1. These results suggest a model that psr1p serves as a linking protein between sad1p/SUN and mal3p/EB1 to allow microtubule plus ends to be coupled to the SPBs for organization of an antiparallel microtubule array. Thus, we conclude that psr1p is involved in organizing the antiparallel microtubule array in the first place at mitosis onset by interaction with SUN/sad1p and EB1/mal3p, thereby establishing the bipolar spindle.postprin

    Dichotomic role of NAADP/two-pore channel 2/Ca2+ signaling in regulating neural differentiation of mouse embryonic stem cells

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    Poster Presentation - Stem Cells and Pluripotency: abstract no. 1866The mobilization of intracellular Ca2+stores is involved in diverse cellular functions, including cell proliferation and differentiation. At least three endogenous Ca2+mobilizing messengers have been identified, including inositol trisphosphate (IP3), cyclic adenosine diphosphoribose (cADPR), and nicotinic adenine acid dinucleotide phosphate (NAADP). Similar to IP3, NAADP can mobilize calcium release in a wide variety of cell types and species, from plants to animals. Moreover, it has been previously shown that NAADP but not IP3-mediated Ca2+increases can potently induce neuronal differentiation in PC12 cells. Recently, two pore channels (TPCs) have been identified as a novel family of NAADP-gated calcium release channels in endolysosome. Therefore, it is of great interest to examine the role of TPC2 in the neural differentiation of mouse ES cells. We found that the expression of TPC2 is markedly decreased during the initial ES cell entry into neural progenitors, and the levels of TPC2 gradually rebound during the late stages of neurogenesis. Correspondingly, perturbing the NAADP signaling by TPC2 knockdown accelerates mouse ES cell differentiation into neural progenitors but inhibits these neural progenitors from committing to the final neural lineage. Interestingly, TPC2 knockdown has no effect on the differentiation of astrocytes and oligodendrocytes of mouse ES cells. Overexpression of TPC2, on the other hand, inhibits mouse ES cell from entering the neural lineage. Taken together, our data indicate that the NAADP/TPC2-mediated Ca2+signaling pathway plays a temporal and dichotomic role in modulating the neural lineage entry of ES cells; in that NAADP signaling antagonizes ES cell entry to early neural progenitors, but promotes late neural differentiation.postprin
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