A Digital Image Processing Technique for the ...

Plant & Cell Physiol. 24(2): 225-234 (1983)

A Digital Image Processing Technique for the Analysis of Particle Movements: Its Application to Organdie Movements during Mitosis in Adiantum Protonemata Yoshinobu Mineyuki1, Mitsuru Yamada 2 ' 3 , Mikio Takagi 2 , Masamitsu Wada1>4 and Masaki Furuya 1 ' 5 1

Department of Botany, Faculty of Science, University of Tokyo, Hongo, Tokyo 113, Japan 2 Institute of Industrial Science, University of Tokyo, Roppongi, Tokyo 106, Japan

Key words: Adiantum capillus-veneris (mitosis) — Brownian motion — Cell division — Digital image processing — Fern protonema — Organelle movement.

The speed and pattern of organelle movements is known to change during cell division (Chambers 1917, Leblond 1919, Seifritz 1920, Schaede 1925). Changes in cytoplasmic viscosity at different positions in a cell were observed during mitosis as Brownian motion (Carlson 1946). No quantitative analysis of this Brownian motion of densely packed particles in the cell, however, has ever been reported. Recently, the digital image processing technique has rapidly progressed (Huang et al. 1971) and has been applied widely in medical electronics (Hounsfield 1973) and space science (Rindfleisch et al. 1971). This technique has the advantage of being useful in the analysis of both static images and dynamic ones such as VTR images. We, therefore, have used digital image processing to analyze the Brownian motion of crowded particles in cells quantitatively. In the protonemata of the fern, Adiantum, the rate of protoplasmic streaming did not change in the Gi and S phases, but it decreased in the mitotic phase (Wada et al. 1982). In that study, Abbreviations: VTR, Video tape recorder; TV, television. Present address: Ibaraki Satellite Communication Center, Kokusai Denshin Denwa Co. Ltd., Takahagi, Ibaraki 318, Japan. 4 Present address: Biology Department, Faculty of Science, Tokyo Metropolitan University, Fukazawa, Tokyo 158, Japan. 5 To whom correspondence should be addressed. 3

225

Downloaded from http://pcp.oxfordjournals.org/ at JSPP Member on March 19, 2014

A digital image processing technique was developed for the simultaneous detection of changes in organelle movements in different regions of a cell from the protonemata of the fern, Adiantum. The speed of particle movements at a chosen position in a series of dynamic images that had been recorded by a time-lapse video system was determined in terms of standard error of brightness changes with a gray scale level. Using this new method and microscopy we could distinguish 3 different regions during mitosis in terms of organelle movement patterns. Organelles located outside of the nucleus were in movement until the nucleolus disappeared at prophase, whereas organelles in the boundary region between the nucleus and cytoplasm became active after prophase. The organelles located outside the nucleus again began to move rapidly after chromosome separation. The nuclear pole region showed movement throughout mitosis.

226

Y. Mineyuki et al.

movement of organelles in the nuclear region was difficult to measure quantitatively because the organdies were very crowded around the nucleus and showed undirectional Brownian-motion like movement. For our study, we developed a digital image processing technique that shows changes in the speed of organelle movements in the nuclear region by a pseudo-color display. We then used this technique to investigate changes in the speed and in the pattern of organelle movements during mitosis in Adiantum protonemata.

Materials and Methods Plant material and aseptic culture—Spores of the fern Adiantum capillus-veneris L. were collected in the summer of 1977 in a green house of the Botanic Gardens, Faculty of Science, University of Tokyo, Koishikawa, Tokyo.

These spores were filtered through a fine mesh screen then stored Downloaded from http://pcp.oxfordjournals.org/ at JSPP Member on March 19, 2014

in a plastic container in a cold room at ca. 5°C. The cold-stored spores were used in all the experiments of this study. The culture medium was composed of 1/10-strength Murashige-Skoog (1962) mineral salt solution as modified by Wada and Furuya (1970) and was solidified with 0.5% agar (Junsei Chemical Co. Ltd., Tokyo). The medium then was autoclaved at 120°C for 15 min. Spores were sown on the surface of the solidified medium by Ito's (1969) aseptic technique and allowed to imbibe the medium for 1 day in the dark, after which they were cultured for 6 days at 25°C under continuous red light of about 0.5 Wm~ 2 . Light was provided horizontally by a fluorescent tube (Toshiba FL 40 SD/NL, Tokyo Shibaura Electric Co., Kawasaki) behind a 3-mm-thick red plastic plate (Torayglas 130, Toray Co. Ltd., Osaka). Consequently, singlecelled protonemata grew horizontally at the apex towards the red light source at a very low rate of cell division. Cell division was induced by irradiating the single-celled protonemata with blue light of about 0.6 Wm- 2 from 20 W fluorescent tubes (Toshiba FL 20 SW/NL) given through a filter of 3-mm-thick blue Plexiglas (Rohm and Haas, 2045, Philadelphia, PA., U.S.A.), after which the cells were transferred to darkness. Cell division was observed through Nomarski differential interference contrast optics (Nippon Kogaku K. K., Tokyo). The protonemata were placed on a slide glass, covered with a cover slip then sealed with silicone rubber (Dow Corning 3140 RTV Coating, Dow Corning Co., Mich., U.S.A.). Time-lapse video system—The movements of latex particles, or organelle movements during mitosis were monitored and recorded at intervals of 3 s under infrared light from a tungsten lamp equipped with an infrared filter (IR85, Hoya Glass Co. Ltd., Tokyo) and a Nikon Biophot microscope fitted with Nomarski differential interference contrast optics and a x 100 objective (Nippon Kogaku K. K., Tokyo) coupled with a video camera equipped with an infrared sensitive tube that was connected to a video recorder and video monitor (Furuya et al. 1980). Digital image processing system—A TV digitizer was used to convert images stored on the video tape to 256 X 256 digital images with 256 levels of brightness (Fig. 1), after which the images were stored in the intelligent image memory (Takemoto 1980). The digital images stored on magnetic tape were transferred to a minicomputer system (HP2112, Hewlett Packard, Palo Alto, California, U.S.A.) for processing. The resulting images were stored in the multifunctional image memory (Takagi and Onoe 1981). Color monitor was used for the pseudo-color display. The final image was recorded by a photographic camera focused on the face of the monitor. Principle and procedure of dynamic image processing—Changes in organelle movements were observed as sequential dynamic images on a screen in terms of brightness change at each pixel (picture element) (Fig. 1). When a particle moves slightly on a monitor screen, the brightness

Digital image processing method and organelle movements

227

Fig. 1 Diagram of digital image processing for the analysis of organelle movement. VTR images were digitized so that the images have 256 X 256 pixels with a 256 gray scale level of brightness. Fifteen dynamic images, recorded at 6-s intervals, were processed at one processing. The resulting image is composed of a set of I r values. I: Brightness of a pixel on an image described with a 256 gray scale level. I r : Value of the standard error of I at a pixel of the 15 images.

K/J): Pixel

Computer processing

Resulting image

at that position becomes brighter or darker. When the particle moves frequently, the change in brightness at that pixel changes more frequently. When no particles move, no change of brightness is found at the position. Fifteen sequential dynamic images recorded every 6 s were processed for one final image (Fig. 1). Each was arranged at the same coordinates to compare the brightnesses of the pixel. A 2 X 2 low pass filter was used so that the signal to noise ratio was improved for the main processing. All calculations were made with the software system for interactive image processing at the Multidimensional Image Processing Center, the Institute of Industrial Science, University of Tokyo (Sakaue and Takagi 1978). The brightness change in the sequential dynamic images at each pixel was displayed as an image in which each pixel had the value (I r ) of standard error among the values of brightness (I