Hostname: page-component-78c5997874-mlc7c Total loading time: 0 Render date: 2024-11-19T05:32:39.208Z Has data issue: false hasContentIssue false
  • English
  • Français

A Novel Algorithm for the Determination of Bacterial Cell Volumes That is Unbiased by Cell Morphology

Published online by Cambridge University Press:  13 September 2011

M. Zeder ,
E. Kohler ,
L. Zeder  and
J. Pernthaler
M. Zeder*
Affiliation:
Max Planck Institute for Marine Microbiology, Department of Molecular Ecology, Celsiusstrasse 1, 28359 Bremen, Germany Technobiology GmbH, Rütiweidhalde 7a, 6033 Buchrain, Switzerland Department of Limnology, Institute of Plant Biology, University of Zürich, Seestrasse 187, 8802 Kilchberg, Switzerland
E. Kohler
Affiliation:
Department of Limnology, Institute of Plant Biology, University of Zürich, Seestrasse 187, 8802 Kilchberg, Switzerland
L. Zeder
Affiliation:
Technobiology GmbH, Rütiweidhalde 7a, 6033 Buchrain, Switzerland
J. Pernthaler
Affiliation:
Department of Limnology, Institute of Plant Biology, University of Zürich, Seestrasse 187, 8802 Kilchberg, Switzerland
*
Corresponding author. E-mail: [email protected]
Get access

Abstract

The determination of cell volumes and biomass offers a means of comparing the standing stocks of auto- and heterotrophic microbes of vastly different sizes for applications including the assessment of the flux of organic carbon within aquatic ecosystems. Conclusions about the importance of particular genotypes within microbial communities (e.g., of filamentous bacteria) may strongly depend on whether their contribution to total abundance or to biomass is regarded. Fluorescence microscopy and image analysis are suitable tools for determining bacterial biomass that moreover hold the potential to replace labor-intensive manual measurements by fully automated approaches. However, the current approaches to calculate bacterial cell volumes from digital images are intrinsically biased by the models that are used to approximate the morphology of the cells. Therefore, we developed a generic contour based algorithm to reconstruct the volumes of prokaryotic cells from two-dimensional representations (i.e., microscopic images) irrespective of their shape. Geometric models of commonly encountered bacterial morphotypes were used to verify the algorithm and to compare its performance with previously described approaches. The algorithm is embedded in a freely available computer program that is able to process both raw (8-bit grayscale) and thresholded (binary) images in a fully automated manner.

Keywords

cell volumehigh-throughput microscopymodel-based object-oriented image analysismicrobial ecologyscreening
Type
Biological Applications
Information
Microscopy and Microanalysis , Volume 17 , Issue 5 , October 2011 , pp. 799 - 809
Copyright
Copyright © Microscopy Society of America 2011

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

REFERENCES

Bergey, D. (1994). Bergey's Manual of Determinative Bacteriology, 9th ed.Baltimore, MD: Williams & Wilkins.Google Scholar
Bertoni, R., Callieri, C., Corno, G., Rasconi, S., Caravati, E. & Contesini, M. (2010). Long-term trends of epilimnetic and hypolimnetic bacteria and organic carbon in a deep holo-oligomictic lake. Hydrobiologia 644, 279–287.CrossRefGoogle Scholar
Bjørnsen, P.K. (1986). Automatic determination of bacterioplankton biomass by image analysis. Appl Environ Microbiol 51, 1199–1204.CrossRefGoogle ScholarPubMed
Blackburn, N., Hagstrom, A., Wikner, J., Cuadros-Hansson, R. & Bjørnsen, P.K. (1998). Rapid determination of bacterial abundance, biovolume, morphology, and growth by neural network-based image analysis. Appl Environ Microbiol 64, 3246–3255.CrossRefGoogle ScholarPubMed
Bloem, J., Veninga, M. & Shepherd, J. (1995). Fully automatic determination of soil bacterium numbers, cell volumes, and frequencies of dividing cells by confocal laser scanning microscopy and image analysis. Appl Environ Microbiol 61, 926–936.CrossRefGoogle ScholarPubMed
Boyde, A. & Williams, R.A. (1971). Estimation of the volumes of bacterial cells by scanning electron microscopy. Arch Oral Biol 16, 259–267.CrossRefGoogle ScholarPubMed
Bratbak, G. (1985). Bacterial biovolume and biomass estimations. Appl Environ Microbiol 49, 1488–1493.CrossRefGoogle ScholarPubMed
Burger, W. (2008). Digital Image Processing: An Algorithmic Introduction Using Java. New York: Springer.CrossRefGoogle Scholar
Carlson, C., Ducklow, H. & Sleeter, T. (1996). Stocks and dynamics of bacterioplankton in the northwestern Sargasso Sea. Deep Sea Research Part II: Topical Studies in Oceanography 43, 491–515.CrossRefGoogle Scholar
Chrzanowski, T.H. & Simek, K. (1990). Prey-size selection by freshwater flagellated protozoa. Limnol Oceanogr 35, 1429–1436.CrossRefGoogle Scholar
Daims, H. & Wagner, M. (2007). Quantification of uncultured microorganisms by fluorescence microscopy and digital image analysis. Appl Microbiol Biotechnol 75, 237–248.CrossRefGoogle ScholarPubMed
Falkowski, P.G., Barber, R.T. & Smetacek, V. (1998). Biogeochemical controls and feedbacks on ocean primary production. Science 281, 200–207.CrossRefGoogle ScholarPubMed
Freeman, H. (1961). On the encoding of arbitrary geometric configurations. IEEE Trans Electron Comput EC-10, 260–268.CrossRefGoogle Scholar
Fry, J.C. (1990). Direct methods and biomass estimation. Methods Microbiol 22, 41–85.CrossRefGoogle Scholar
Fry, J.C. & Davies, A.R. (1985). An assessment of methods for measuring volumes of planktonic bacteria, with particular reference to television image-analysis. J Appl Bacteriol 58, 105–112.CrossRefGoogle Scholar
Gest, H. (2004). The discovery of microorganisms by Robert Hooke and Antoni Van Leeuwenhoek, fellows of the Royal Society. Notes Rec R Soc Lond 58, 187–201.CrossRefGoogle Scholar
Gretz, J.E. & Duling, B.R. (1995). Measurement uncertainties associated with the use of bright-field and fluorescence microscopy in the microcirculation. Microvasc Res 49, 134–140.CrossRefGoogle ScholarPubMed
Gundersen, H.J., Bagger, P., Bendtsen, T.F., Evans, S.M., Korbo, L., Marcussen, N., Møller, A., Mnielsen, K., Nvengaard, J.R., Pakkenberg, B., Sørensen, F.B., Vesterby, A. & West, J.M. (1988). The new stereological tools: Disector, fractionator, nucleator and point sampled intercepts and their use in pathological research and diagnosis. APMIS 96, 857–881.CrossRefGoogle Scholar
Hillebrand, H., Durselen, C.D., Kirschtel, D., Pollingher, U. & Zohary, T. (1999). Biovolume calculation for pelagic and benthic microalgae. J Phycol 35, 403–424.CrossRefGoogle Scholar
Hobbie, J.E., Daley, R.J. & Jasper, S. (1977). Use of nucleopore filters for counting bacteria by fluorescence microscopy. Appl Environ Microbiol 33, 1225–1228.CrossRefGoogle Scholar
Isao, K., Hara, S., Terauchi, K. & Kogure, K. (1990). Role of sub-micrometre particles in the ocean. Nature 345, 242–244.CrossRefGoogle Scholar
Krambeck, C., Krambeck, H.J. & Overbeck, J. (1981). Microcomputer-assisted biomass determination of plankton bacteria on scanning electron micrographs. Appl Environ Microbiol 42, 142–149.CrossRefGoogle ScholarPubMed
Kuhl, F. & Giardina, C. (1982). Elliptic Fourier features of a closed contour. Comp Graph Image Processing 18, 236–258.CrossRefGoogle Scholar
Massana, R., Gasol, J.M., Bjørnsen, P.K., Blackburn, N., Hagstrom, Å., Hietanen, S., Hygum, B.H., Kuparinen, J. & Pedrós-Alió, C. (1997). Measurement of bacterial size via image analysis of epifluorescence preparations: Description of an inexpensive system and solutions to some of the most common problems. Sci Mar 61, 397–407.Google Scholar
Musat, N., Halm, H., Winterholler, B., Hoppe, P., Peduzzi, S., Hillion, F., Horreard, F., Amann, R., Jørgensen, B.B. & Kuypers, M.M. (2008). A single-cell view on the ecophysiology of anaerobic phototrophic bacteria. Proc Nat Acad Sci USA 105, 17861–17866.CrossRefGoogle ScholarPubMed
Pernthaler, J., Pernthaler, A. & Amann, R. (2003). Automated enumeration of groups of marine picoplankton after fluorescence in situ hybridization. Appl Environ Microbiol 69, 2631–2637.CrossRefGoogle ScholarPubMed
Pernthaler, J., Zöllner, E., Warnecke, F. & Jürgens, K. (2004). Bloom of filamentous bacteria in a mesotrophic lake: Identity and potential controlling mechanism. Appl Environ Microbiol 70, 6272–6281.CrossRefGoogle Scholar
Porter, K.G. & Feig, Y.S. (1980). The use of DAPI for identifying and counting aquatic microflora. Limnol Oceanogr 25, 943–948.CrossRefGoogle Scholar
Posch, T., Franzoi, J., Prader, M. & Salcher, M.M. (2009). New image analysis tool to study biomass and morphotypes of three major bacterioplankton groups in an alpine lake. Aquat Microb Ecol 54, 113–126.CrossRefGoogle Scholar
Posch, T., Loferer-Krossbacher, M., Gao, G., Alfreider, A., Pernthaler, J. & Psenner, R. (2001). Precision of bacterioplankton biomass determination: A comparison of two fluorescent dyes, and of allometric and linear volume-to-carbon conversion factors. Aquat Microb Ecol 25, 55–63.CrossRefGoogle Scholar
Schattenhofer, M., Fuchs, B.M., Amann, R., Zubkov, M.V., Tarran, G.A. & Pernthaler, J. (2009). Latitudinal distribution of prokaryotic picoplankton populations in the Atlantic Ocean. Environ Microbiol 11, 2078–2093.CrossRefGoogle ScholarPubMed
Seo, E.Y., Ahn, T.S. & Zo, Y.G. (2010). Agreement, precision, and accuracy of epifluorescence microscopy methods for enumeration of total bacterial numbers. Appl Environ Microbiol 76, 1981–1991.CrossRefGoogle ScholarPubMed
Sieracki, M.E., Viles, C.L. & Webb, K.L. (1989). Algorithm to estimate cell biovolume using image analyzed microscopy. Cytometry 10, 551–557.CrossRefGoogle ScholarPubMed
Singleton, S., Cahill, J.G., Watson, G.K., Allison, C., Cummins, D., Thurnheer, T., Guggenheim, B. & Gmür, R. (2001). A fully automated microscope bacterial enumeration system for studies of oral microbial ecology. J Immunoassay Immunochem 22, 253–274.CrossRefGoogle ScholarPubMed
Sommer, U., Gliwicz, Z.M., Lampert, W. & Duncan, A. (1986). The Peg-Model of seasonal succession of planktonic events in fresh waters. Archiv für Hydrobiologie 106, 433–471.CrossRefGoogle Scholar
Straza, T.R.A., Cottrell, M.T., Ducklow, H.W. & Kirchman, D.L. (2009). Geographic and phylogenetic variation in bacterial biovolume as revealed by protein and nucleic acid staining. Appl Environ Microbiol 75, 4028–4034.CrossRefGoogle ScholarPubMed
Suzuki, M.T., Sherr, E. & Sherr, B.F. (1993). DAPI direct counting underestimates bacterial abundances and average cell size compared to AO direct counting. Limnol Oceangr 38, 1566–1570.CrossRefGoogle Scholar
van Veen, J.A. & Paul, E.A. (1979). Conversion of biovolume measurements of soil organisms, grown under various moisture tensions, to biomass and their nutrient content. Appl Environ Microbiol 37, 686–692.CrossRefGoogle ScholarPubMed
Viles, C.L. & Sieracki, M.E. (1992). Measurement of marine picoplankton cell size by using a cooled, charge-coupled device camera with image-analyzed fluorescence microscopy. Appl Environ Microbiol 58, 584–592.CrossRefGoogle ScholarPubMed
Wommack, K.E. & Colwell, R.R. (2000). Virioplankton: Viruses in aquatic ecosystems. Microbiol Mol Biol Rev 64, 69–114.CrossRefGoogle ScholarPubMed
Young, K.D. (2006). The selective value of bacterial shape. Microbiol Mol Biol Rev 70, 660–703.CrossRefGoogle ScholarPubMed
Zeder, M. & Pernthaler, J. (2009). Multispot live-image autofocusing for high-throughput microscopy of fluorescently stained bacteria. Cytometry A 75A, 781–788.CrossRefGoogle Scholar
Zeder, M., Peter, S., Shabarova, T. & Pernthaler, J. (2009). A small population of planktonic Flavobacteria with disproportionally high growth during the spring phytoplankton bloom in a prealpine lake. Environ Microbiol 11, 2676–2686.CrossRefGoogle Scholar
Zhou, Z., Pons, M.N., Raskin, L. & Zilles, J.L. (2007). Automated image analysis for quantitative fluorescence in situ hybridization with environmental samples. Appl Environ Microbiol 73, 2956–2962.CrossRefGoogle ScholarPubMed
Supplementary material: PDF

Zeder Supplementary Material

Zeder Supplementary Material

Download Zeder Supplementary Material(PDF)
PDF 81.6 KB