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      Lentiviral Vectors and Protocols for Creation of Stable hESC Lines for Fluorescent Tracking and Drug Resistance Selection of Cardiomyocytes

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          Abstract

          Background

          Developmental, physiological and tissue engineering studies critical to the development of successful myocardial regeneration therapies require new ways to effectively visualize and isolate large numbers of fluorescently labeled, functional cardiomyocytes.

          Methodology/Principal Findings

          Here we describe methods for the clonal expansion of engineered hESCs and make available a suite of lentiviral vectors for that combine Blasticidin, Neomycin and Puromycin resistance based drug selection of pure populations of stem cells and cardiomyocytes with ubiquitous or lineage-specific promoters that direct expression of fluorescent proteins to visualize and track cardiomyocytes and their progenitors. The phospho-glycerate kinase (PGK) promoter was used to ubiquitously direct expression of histone-2B fused eGFP and mCherry proteins to the nucleus to monitor DNA content and enable tracking of cell migration and lineage. Vectors with T/Brachyury and α-myosin heavy chain (αMHC) promoters targeted fluorescent or drug-resistance proteins to early mesoderm and cardiomyocytes. The drug selection protocol yielded 96% pure cardiomyocytes that could be cultured for over 4 months. Puromycin-selected cardiomyocytes exhibited a gene expression profile similar to that of adult human cardiomyocytes and generated force and action potentials consistent with normal fetal cardiomyocytes, documenting these parameters in hESC-derived cardiomyocytes and validating that the selected cells retained normal differentiation and function.

          Conclusion/Significance

          The protocols, vectors and gene expression data comprise tools to enhance cardiomyocyte production for large-scale applications.

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          Most cited references32

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          Cluster analysis and display of genome-wide expression patterns.

          A system of cluster analysis for genome-wide expression data from DNA microarray hybridization is described that uses standard statistical algorithms to arrange genes according to similarity in pattern of gene expression. The output is displayed graphically, conveying the clustering and the underlying expression data simultaneously in a form intuitive for biologists. We have found in the budding yeast Saccharomyces cerevisiae that clustering gene expression data groups together efficiently genes of known similar function, and we find a similar tendency in human data. Thus patterns seen in genome-wide expression experiments can be interpreted as indications of the status of cellular processes. Also, coexpression of genes of known function with poorly characterized or novel genes may provide a simple means of gaining leads to the functions of many genes for which information is not available currently.
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            Feature point tracking and trajectory analysis for video imaging in cell biology.

            This paper presents a computationally efficient, two-dimensional, feature point tracking algorithm for the automated detection and quantitative analysis of particle trajectories as recorded by video imaging in cell biology. The tracking process requires no a priori mathematical modeling of the motion, it is self-initializing, it discriminates spurious detections, and it can handle temporary occlusion as well as particle appearance and disappearance from the image region. The efficiency of the algorithm is validated on synthetic video data where it is compared to existing methods and its accuracy and precision are assessed for a wide range of signal-to-noise ratios. The algorithm is well suited for video imaging in cell biology relying on low-intensity fluorescence microscopy. Its applicability is demonstrated in three case studies involving transport of low-density lipoproteins in endosomes, motion of fluorescently labeled Adenovirus-2 particles along microtubules, and tracking of quantum dots on the plasma membrane of live cells. The present automated tracking process enables the quantification of dispersive processes in cell biology using techniques such as moment scaling spectra.
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              Stresses at the cell-to-substrate interface during locomotion of fibroblasts.

              Recent technological improvements in the elastic substrate method make it possible to produce spatially resolved measurements of the tractions exerted by single motile cells. In this study we have applied these developments to produce maps of the tractions exerted by 3T3 fibroblasts during steady locomotion. The resulting images have a spatial resolution of approximately 5 micrometers and a maximum intensity of approximately 10(2) kdyn/cm2 (10(4) pN/micrometers2). We find that the propulsive thrust for fibroblast locomotion, approximately 0.2 dyn, is imparted to the substratum within 15 micrometers of the leading edge. These observations demonstrate that the lamellipodium of the fibroblast is able to generate intense traction stress. The cell body and posterior seem to be mechanically passive structures pulled forward entirely by this action.
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                Author and article information

                Contributors
                Role: Editor
                Journal
                PLoS ONE
                plos
                plosone
                PLoS ONE
                Public Library of Science (San Francisco, USA )
                1932-6203
                2009
                8 April 2009
                : 4
                : 4
                : e5046
                Affiliations
                [1 ]Burnham Institute for Medical Research, La Jolla, California, United States of America
                [2 ]Department of Bioengineering, University of California San Diego, La Jolla, California, United States of America
                [3 ]Division of Cardiology, Department of Medicine, University of California San Diego, La Jolla, California, United States of America
                [4 ]Gladstone Institute of Cardiovascular Disease, University of California San Francisco, San Francisco, California, United States of America
                Ordway Research Institute, United States of America
                Author notes

                Conceived and designed the experiments: HKM MB NP NGS KW JGJ BN ADM JP HSVC MM. Performed the experiments: HKM MB NP NGS KW JGJ BN SS RH CK MT RB DC HSVC. Analyzed the data: HKM MB NP NGS JGJ SS RH CK DC ADM JP BRC HSVC MM. Contributed reagents/materials/analysis tools: CK AVT ADM BRC HSVC. Wrote the paper: HKM HSVC MM.

                [¤]

                Current address: Department of Chemical and Systems Biology, Stanford University, Stanford, California, United States of America

                Article
                08-PONE-RA-06962R1
                10.1371/journal.pone.0005046
                2662416
                19352491
                8c49d3db-c2ea-47ae-b308-36152e400b47
                Kita-Matsuo et al. This is an open-access article distributed under the terms of the Creative Commons Attribution License, which permits unrestricted use, distribution, and reproduction in any medium, provided the original author and source are credited.
                History
                : 22 October 2008
                : 17 February 2009
                Page count
                Pages: 15
                Categories
                Research Article
                Cardiovascular Disorders
                Developmental Biology/Cell Differentiation
                Developmental Biology/Stem Cells

                Uncategorized
                Uncategorized

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