Hostname: page-component-8448b6f56d-dnltx Total loading time: 0 Render date: 2024-04-24T12:24:17.327Z Has data issue: false hasContentIssue false
  • English
  • Français

DSeg: A Dynamic Image Segmentation Program to Extract Backbone Patterns for Filamentous Bacteria and Hyphae Structures

Published online by Cambridge University Press:  21 March 2019

Hanqing Zhang ,
Niklas Söderholm ,
Linda Sandblad ,
Krister Wiklund  and
Magnus Andersson Open the ORCID record for Magnus Andersson [Opens in a new window]
Hanqing Zhang
Affiliation:
Department of Physics, Umeå University, 901 87 Umeå, Sweden
Niklas Söderholm
Affiliation:
Department of Molecular Biology, Umeå University, 901 87 Umeå, Sweden
Linda Sandblad
Affiliation:
Department of Molecular Biology, Umeå University, 901 87 Umeå, Sweden
Krister Wiklund
Affiliation:
Department of Physics, Umeå University, 901 87 Umeå, Sweden
Magnus Andersson*
Affiliation:
Department of Physics, Umeå University, 901 87 Umeå, Sweden
*
*Author for correspondence: Magnus Andersson, E-mail: magnus.andersson@umu.se
Get access

Abstract

Analysis of numerous filamentous structures in an image is often limited by the ability of algorithms to accurately segment complex structures or structures within a dense population. It is even more problematic if these structures continuously grow when recording a time-series of images. To overcome these issues we present DSeg; an image analysis program designed to process time-series image data, as well as single images, to segment filamentous structures. The program includes a robust binary level-set algorithm modified to use size constraints, edge intensity, and past information. We verify our algorithms using synthetic data, differential interference contrast images of filamentous prokaryotes, and transmission electron microscopy images of bacterial adhesion fimbriae. DSeg includes automatic segmentation, tools for analysis, and drift correction, and outputs statistical data such as persistence length, growth rate, and growth direction. The program is available at Sourceforge.

Keywords

filamentoushyphaeimage segmentationMATLABsoftware
Type
Software and Instrumentation
Information
Microscopy and Microanalysis , Volume 25 , Issue 3 , June 2019 , pp. 711 - 719
Copyright
Copyright © Microscopy Society of America 2019 

Access options

Get access to the full version of this content by using one of the access options below. (Log in options will check for institutional or personal access. Content may require purchase if you do not have access.)

References

Bagchi, S, Tomenius, H, Belova, LM & Ausmees, N (2008). Intermediate filament-like proteins in bacteria and a cytoskeletal function in Streptomyces. Mol Microbiol 70, 1037–1050.Google Scholar
Barry, D & Williams, G (2011). Microscopic characterisation of filamentous microbes: Towards fully automated morphological quantification through image analysis. J Microsc 244, 1–20. Available at http://doi.wiley.com/10.1111/j.1365-2818.2011.03506.x.Google Scholar
Bradley, D & Roth, G (2007). Adaptive thresholding using the integral image. J Graph Tools 12, 13–21. Available at https://www.tandfonline.com/doi/full/10.1080/2151237X.2007.10129236.Google Scholar
Brown, JW, Badahdah, A, Iticovici, M, Vickers, TJ, Alvarado, DM, Helmerhorst, EJ, Oppenheim, FG, Mills, JC, Ciorba, MA, Fleckenstein, JM & Bullitt, E (2018). A role for salivary peptides in the innate defense against enterotoxigenic Escherichia coli. J Infect Dis 217, 1435–1441. Available at https://academic.oup.com/jid/advance-article/doi/10.1093/infdis/jiy032/4920821; https://academic.oup.com/jid/article/217/9/1435/4920821.Google Scholar
Dahlberg, T, Stangner, T, Zhang, H, Wiklund, K, Lundberg, P, Edman, L & Andersson, M (2018). 3D printed water-soluble scaffolds for rapid production of PDMS micro-fluidic flow chambers. Sci Rep 8, 3372. Available at http://www.nature.com/articles/s41598-018-21638-w.10.1038/s41598-018-21638-wGoogle Scholar
Dias, PA, Dunkel, T, Fajado, DAS, Gallegos, EDL, Denecke, M, Wiedemann, P, Schneider, FK & Suhr, H (2016). Image processing for identification and quantification of filamentous bacteria in in situ acquired images. Biomed Eng Online 15, 64. Available at http://biomedical-engineering-online.biomedcentral.com/articles/10.1186/s12938-016-0197-7.Google Scholar
Dimopoulos, S, Mayer, CE, Rudolf, F & Stelling, J (2014). Accurate cell segmentation in microscopy images using membrane patterns. Bioinformatics 30, 2644–2651. Available at https://academic.oup.com/bioinformatics/article-lookup/doi/10.1093/bioinformatics/btu302.Google Scholar
Fällman, E, Schedin, S, Jass, J, Andersson, M, Uhlin, BE & Axner, O (2004). Optical tweezers based force measurement system for quantitating binding interactions: System design and application for the study of bacterial adhesion. Biosens Bioelectron 19, 1429–1437. Available at http://linkinghub.elsevier.com/retrieve/pii/S0956566303004615.Google Scholar
Flärdh, K, Richards, DM, Hempel, AM, Howard, M & Buttner, MJ (2012). Regulation of apical growth and hyphal branching in Streptomyces. Curr Opin Microbiol 15, 737–743. Available at https://linkinghub.elsevier.com/retrieve/pii/S136952741200152X.Google Scholar
Fuchino, K, Flärdh, K, Dyson, P & Ausmees, N (2017). Cell-biological studies of osmotic shock response in Streptomyces spp. J Bacteriol 199, 1–14. Available at http://jb.asm.org/lookup/doi/10.1128/JB.00465-16.Google Scholar
Heller, D, Hoppe, A, Restrepo, S, Gatti, L, Tournier, AL, Tapon, N, Basler, K & Mao, Y (2016) Epitools: An open-source image analysis toolkit for quantifying epithelial growth dynamics. Dev Cell 36, 103–116. Available at http://dx.doi.org/10.1016/j.devcel.2015.12.012.Google Scholar
Hodneland, E, Kögel, T, Frei, D, Gerdes, HH & Lundervold, A (2013). CellSegm—a MATLAB toolbox for high-throughput 3D cell segmentation. Source Code Biol Med 8, 16. Available at http://scfbm.biomedcentral.com/articles/10.1186/1751-0473-8-16.10.1186/1751-0473-8-16Google Scholar
Jones, TR, Kang, I, Wheeler, DB, Lindquist, RA, Papallo, A, Sabatini, DM, Golland, P & Carpenter, AE (2008). Cellprofiler Analyst: Data exploration and analysis software for complex image-based screens. BMC Bioinf 9, 482. Available at http://bmcbioinformatics.biomedcentral.com/articles/10.1186/1471-2105-9-482.Google Scholar
Khan, MB, Nisar, H, Ng, CA, Yeap, KH & Lai, KC (2017). Segmentation approach towards phase-contrast microscopic images of activated sludge to monitor the wastewater treatment. Microsc Microanal 23, 1130–1142. Available at https://www.cambridge.org/core/product/identifier/S1431927617012673/type/journal{_}article.10.1017/S1431927617012673Google Scholar
Klein, J, Leupold, S, Biegler, I, Biedendieck, R, Munch, R & Jahn, D (2012). TLM-Tracker: Software for cell segmentation, tracking and lineage analysis in time-lapse microscopy movies. Bioinformatics 28, 2276–2277. Available at https://academic.oup.com/bioinformatics/article-lookup/doi/10.1093/bioinformatics/bts424.Google Scholar
Lamour, G, Kirkegaard, JB, Li, H, Knowles, TP & Gsponer, J (2014). Easyworm: An open-source software tool to determine the mechanical properties of worm-like chains. Source Code Biol Med 9, 16. Available at http://scfbm.biomedcentral.com/articles/10.1186/1751-0473-9-16.10.1186/1751-0473-9-16Google Scholar
Latychevskaia, T & Fink, HW (2015). Practical algorithms for simulation and reconstruction of digital in-line holograms. Appl Opt 54, 2424. Available at http://dx.doi.org/10.1364/AO.54.002424; https://www.osapublishing.org/abstract.cfm?URI=ao-54-9-2424.Google Scholar
Mcquin, C, Goodman, A, Chernyshev, V, Kamentsky, L, Cimini, BA, Karhohs, KW, Doan, M, Ding, L, Rafelski, SM, Thirstrup, D, Wiegraebe, W, Singh, S, Becker, T, Caicedo, JC & Carpenter, AE (2018). Cellprofiler 3.0: Next-generation image processing for biology. PLoS Biol 16, e2005970. Available at https://dx.doi.org/10.1371/journal.pbio.2005970.Google Scholar
Meyer, F (1994). Topographic distance and watershed lines. Signal Processing 38, 113–125. Available at http://linkinghub.elsevier.com/retrieve/pii/0165168494900604.10.1016/0165-1684(94)90060-4Google Scholar
Mortezaei, N, Epler, CR, Shao, PP, Shirdel, M, Singh, B, Mcveigh, A, Uhlin, BE, Savarino, SJ, Andersson, M & Bullitt, E (2015). Structure and function of enterotoxigenic Escherichia coli fimbriae from differing assembly pathways. Mol Microbiol 95, 116–126. Available at http://doi.wiley.com/10.1111/mmi.12847.Google Scholar
Mortezaei, N, Singh, B, Bullitt, E, Uhlin, BE & Andersson, M (2013). P-fimbriae in the presence of anti-PapA antibodies: New insight of antibodies action against pathogens. Sci Rep 3, 3393. Available at http://www.pubmedcentral.nih.gov/articlerender.fcgi?artid=3848023{&}tool=pmcentrez{&}rendertype=abstract; http://www.ncbi.nlm.nih.gov/pubmed/24292100; http://www.pubmedcentral.nih.gov/articlerender.fcgi?artid=PMC3848023; http://www.nature.com/articles/srep03393.10.1038/srep03393Google Scholar
Otsu, N (1979). A threshold selection method from gray-level histograms. IEEE Trans Syst Man Cybern 9, 62–66. Available at http://ieeexplore.ieee.org/document/4310076/.Google Scholar
Riquelme, M, Aguirre, J, Bartnicki-García, S, Braus, GH, Feldbrügge, M, Fleig, U, Hansberg, W, Herrera-Estrella, A, Kämper, J, Kück, U, Mouriño-Pérez, RR, Takeshita, N & Fischer, R (2018). Fungal morphogenesis, from the polarized growth of hyphae to complex reproduction and infection structures. Microbiol Mol Biol Rev 82, e00068–17. Available at http://www.ncbi.nlm.nih.gov/pubmed/29643171; http://mmbr.asm.org/lookup/doi/10.1128/MMBR.00068-17.Google Scholar
Rueden, CT, Schindelin, J, Hiner, MC, Dezonia, BE, Walter, AE, Arena, ET & Eliceiri, KW (2017). Imagej2: ImageJ for the next generation of scientific image data. BMC Bioinf 18, 529. Available at https://bmcbioinformatics.biomedcentral.com/articles/10.1186/s12859-017-1934-z.Google Scholar
Schvartz, T, Aloush, N, Goliand, I, Segal, I, Nachmias, D, Arbely, E & Elia, N (2017). Direct fluorescent-dye labeling of α-tubulin in mammalian cells for live cell and superresolution imaging. Mol Biol Cell 28, 2747–2756. Available at http://www.molbiolcell.org/lookup/doi/10.1091/mbc.E17-03-0161.Google Scholar
Sethian, JA (1999). Level Set Methods and Fast Marching Methods: Evolving Interfaces in Computational Geometry, Fluid Mechanics, Computer Vision, and Materials Science, vol. 3. Cambridge, UK: Cambridge University Press.Google Scholar
Silverman, PM & Clarke, MB (2010). New insights into F-pilus structure, dynamics, and function. Integr Biol 2, 25–31. Available at http://xlink.rsc.org/?DOI=B917761B.Google Scholar
Stangner, T, Zhang, H, Dahlberg, T, Wiklund, K & Andersson, M (2017). A step-by-step guide to reduce spatial coherence of laser light using a rotating ground glass diffuser. Appl Opt 56, 1–7. Available at http://arxiv.org/abs/1703.05311; http://ao.osa.org/abstract.cfm?URI=ao-56-19-5427.10.1364/AO.56.005427Google Scholar
Strisciuglio, N & Petkov, N (2017). Delineation of line patterns in images using B-COSFIRE filters. 2017 International Conference and Workshop on Bioinspired Intelligence (IWOBI). pp. 1–6. Available at http://ieeexplore.ieee.org/document/7985538/.Google Scholar
Takeshita, N & Fischer, R (2011). On the role of microtubules, cell end markers, and septal microtubule organizing centres on site selection for polar growth in Aspergillus nidulans. Fungal Biol 115, 506–517. Available at http://dx.doi.org/10.1016/j.funbio.2011.02.009.Google Scholar
Wiesmann, V, Franz, D, Held, C, Münzenmayer, C, Palmisano, R & Wittenberg, T (2015). Review of free software tools for image analysis of fluorescence cell micrographs. J Microsc 257, 39–53. Available at http://doi.wiley.com/10.1111/jmi.12184.Google Scholar
Zhang, H, Stangner, T, Wiklund, K, Rodriguez, A & Andersson, M (2017). UmUTracker: A versatile MATLAB program for automated particle tracking of 2D light microscopy or 3D digital holography data. Comput Phys Commun 219, 390–399. Available at https://sourceforge.net/projects/umutracker/; http://linkinghub.elsevier.com/retrieve/pii/S0010465517301820.10.1016/j.cpc.2017.05.029Google Scholar
Zhang, K, Zhang, L, Song, H & Zhou, W (2010). Active contours with selective local or global segmentation: A new formulation and level set method. Image Vis Comput 28, 668–676. Available at http://linkinghub.elsevier.com/retrieve/pii/S0262885609002303.Google Scholar
Supplementary material: File

Zhang et al. supplementary material

Zhang et al. supplementary material 1

Download Zhang et al. supplementary material(File)
File 67 MB