Stem Cell Reports , Volume 2 Supplemental Information A Rapid and Efficient 2 D / 3 D Nuclear Segmentation Method for Analysis of Early Mouse Embryo and Stem Cell Image Data

Summary Segmentation is a fundamental problem that dominates the success of microscopic image analysis. In almost 25 years of cell detection software development, there is still no single piece of commercial software that works well in practice when applied to early mouse embryo or stem cell image data. To address this need, we developed MINS (modular interactive nuclear segmentation) as a MATLAB/C++-based segmentation tool tailored for counting cells and fluorescent intensity measurements of 2D and 3D image data. Our aim was to develop a tool that is accurate and efficient yet straightforward and user friendly. The MINS pipeline comprises three major cascaded modules: detection, segmentation, and cell position classification. An extensive evaluation of MINS on both 2D and 3D images, and comparison to related tools, reveals improvements in segmentation accuracy and usability. Thus, its accuracy and ease of use will allow MINS to be implemented for routine single-cell-level image analyses.

[1]  H. Lee,et al.  Quantitative neurite outgrowth measurement based on image segmentation with topological dependence , 2009, Cytometry. Part A : the journal of the International Society for Analytical Cytology.

[2]  J. Nichols,et al.  Suppression of Erk signalling promotes ground state pluripotency in the mouse embryo , 2009, Development.

[3]  J A Sethian,et al.  A fast marching level set method for monotonically advancing fronts. , 1996, Proceedings of the National Academy of Sciences of the United States of America.

[4]  K. Niakan,et al.  Derivation of extraembryonic endoderm stem (XEN) cells from mouse embryos and embryonic stem cells , 2013, Nature Protocols.

[5]  Minjung Kang,et al.  FGF4 is required for lineage restriction and salt-and-pepper distribution of primitive endoderm factors but not their initial expression in the mouse , 2013, Development.

[6]  Aly A. Farag,et al.  MultiStencils Fast Marching Methods: A Highly Accurate Solution to the Eikonal Equation on Cartesian Domains , 2007, IEEE Transactions on Pattern Analysis and Machine Intelligence.

[7]  R. Waterston,et al.  Automated cell lineage tracing in Caenorhabditis elegans. , 2006, Proceedings of the National Academy of Sciences of the United States of America.

[8]  Dorin Comaniciu,et al.  Mean Shift: A Robust Approach Toward Feature Space Analysis , 2002, IEEE Trans. Pattern Anal. Mach. Intell..

[9]  Robert C. Bolles,et al.  Random sample consensus: a paradigm for model fitting with applications to image analysis and automated cartography , 1981, CACM.

[10]  H. Van de Velde,et al.  The roles of FGF and MAP kinase signaling in the segregation of the epiblast and hypoblast cell lineages in bovine and human embryos , 2012, Development.

[11]  Ullrich Köthe,et al.  Learning to segment dense cell nuclei with shape prior , 2012, 2012 IEEE Conference on Computer Vision and Pattern Recognition.

[12]  Wolfgang Huber,et al.  Cell-to-cell expression variability followed by signal reinforcement progressively segregates early mouse lineages , 2013, Nature Cell Biology.

[13]  Alessandro Sarti,et al.  Cells Segmentation From 3-D Confocal Images of Early Zebrafish Embryogenesis , 2010, IEEE Transactions on Image Processing.

[14]  Daniel Brélaz,et al.  New methods to color the vertices of a graph , 1979, CACM.

[15]  T. Kanda,et al.  Histone–GFP fusion protein enables sensitive analysis of chromosome dynamics in living mammalian cells , 1998, Current Biology.

[16]  C. Rueden,et al.  Metadata matters: access to image data in the real world , 2010, The Journal of cell biology.

[17]  Anna-Katerina Hadjantonakis,et al.  Anatomy of a blastocyst: Cell behaviors driving cell fate choice and morphogenesis in the early mouse embryo , 2013, Genesis.

[18]  Adrienne H K Roeder,et al.  A computational image analysis glossary for biologists , 2012, Development.

[19]  Mikael Huss,et al.  Resolution of cell fate decisions revealed by single-cell gene expression analysis from zygote to blastocyst. , 2010, Developmental cell.

[20]  J. Nichols,et al.  Oct4 is required for lineage priming in the developing inner cell mass of the mouse blastocyst , 2014, Development.

[21]  G. Ringel,et al.  Solution of the heawood map-coloring problem. , 1968, Proceedings of the National Academy of Sciences of the United States of America.

[22]  Kevin Eggan,et al.  Analysis of human embryos from zygote to blastocyst reveals distinct gene expression patterns relative to the mouse. , 2013, Developmental biology.

[23]  J. Heath,et al.  Characterization of a binding protein for leukemia inhibitory factor localized in extracellular matrix , 1993, The Journal of cell biology.

[24]  Anna-Katerina Hadjantonakis,et al.  Distinct sequential cell behaviours direct primitive endoderm formation in the mouse blastocyst , 2008, Development.

[25]  Stephen T. C. Wong,et al.  3D cell nuclei segmentation based on gradient flow tracking , 2007, BMC Cell Biology.

[26]  P. Bourgine,et al.  Cell Lineage Reconstruction of Early Zebrafish Embryos Using Label-Free Nonlinear Microscopy , 2010, Science.

[27]  K. Appel,et al.  Every Planar Map Is Four Colorable , 2019, Mathematical Solitaires & Games.

[28]  Philipp J. Keller,et al.  Reconstruction of Zebrafish Early Embryonic Development by Scanned Light Sheet Microscopy , 2008, Science.

[29]  A. Hadjantonakis,et al.  Live-imaging fluorescent proteins in mouse embryos: multi-dimensional, multi-spectral perspectives. , 2009, Trends in biotechnology.

[30]  Janet Rossant,et al.  Blastocyst lineage formation, early embryonic asymmetries and axis patterning in the mouse , 2009, Development.

[31]  A. Hadjantonakis,et al.  Troika of the mouse blastocyst: lineage segregation and stem cells. , 2012, Current stem cell research & therapy.

[32]  Anna-Katerina Hadjantonakis,et al.  Dynamic in vivo imaging and cell tracking using a histone fluorescent protein fusion in mice , 2004, BMC biotechnology.

[33]  A. Hadjantonakis,et al.  BMP4 signaling directs primitive endoderm-derived XEN cells to an extraembryonic visceral endoderm identity. , 2012, Developmental biology.

[34]  B. Doble,et al.  The ground state of embryonic stem cell self-renewal , 2008, Nature.

[35]  Camille Couprie,et al.  Power Watershed: A Unifying Graph-Based Optimization Framework , 2011, IEEE Transactions on Pattern Analysis and Machine Intelligence.

[36]  J. Nichols,et al.  Human hypoblast formation is not dependent on FGF signalling , 2012, Developmental biology.

[37]  J. García-Ojalvo,et al.  Correlations Between the Levels of Oct4 and Nanog as a Signature for Naïve Pluripotency in Mouse Embryonic Stem Cells , 2012, Stem cells.

[38]  James C. W. Locke,et al.  Using movies to analyse gene circuit dynamics in single cells , 2009, Nature Reviews Microbiology.

[39]  Tony Pawson,et al.  Early lineage segregation between epiblast and primitive endoderm in mouse blastocysts through the Grb2-MAPK pathway. , 2006, Developmental cell.

[40]  J. Nichols,et al.  Nanog safeguards pluripotency and mediates germline development , 2007, Nature.

[41]  A. Hadjantonakis,et al.  A role for PDGF signaling in expansion of the extra-embryonic endoderm lineage of the mouse blastocyst , 2010, Development.

[42]  Philipp J. Keller,et al.  Fast, high-contrast imaging of animal development with scanned light sheet–based structured-illumination microscopy , 2010, Nature Methods.

[43]  Azriel Rosenfeld,et al.  Computer Vision , 1988, Adv. Comput..

[44]  Andrew W. Fitzgibbon,et al.  Direct Least Square Fitting of Ellipses , 1999, IEEE Trans. Pattern Anal. Mach. Intell..

[45]  J. Nichols,et al.  The origin and identity of embryonic stem cells , 2011, Development.

[46]  G. Malandain,et al.  Imaging plant growth in 4D: robust tissue reconstruction and lineaging at cell resolution , 2010, Nature Methods.

[47]  Anne E Carpenter,et al.  CellProfiler: image analysis software for identifying and quantifying cell phenotypes , 2006, Genome Biology.

[48]  Minjung Kang,et al.  Live imaging, identifying, and tracking single cells in complex populations in vivo and ex vivo. , 2013, Methods in molecular biology.

[49]  Anne E Carpenter,et al.  A call for bioimaging software usability , 2012, Nature Methods.

[50]  J. Rossant,et al.  Imprinted X-inactivation in extra-embryonic endoderm cell lines from mouse blastocysts , 2005, Development.

[51]  C. Lim,et al.  Regulated Fluctuations in Nanog Expression Mediate Cell Fate Decisions in Embryonic Stem Cells , 2009, PLoS biology.

[52]  M. Torres-Padilla,et al.  Control of ground-state pluripotency by allelic regulation of Nanog , 2012, Nature.

[53]  A. Hadjantonakis,et al.  PDGF signaling is required for primitive endoderm cell survival in the inner cell mass of the mouse blastocyst , 2013, Stem cells.