Abstract

Microalgae have recently been gaining attention for their versatile uses and environmentally friendly benefits. Accurate characterization and classification of a large population of microalgal cells with single-cell resolution are highly valuable for their diverse applications such as water treatment, biofuel production, food, and nitrogen-fixing biofertilization. Here we demonstrate accurate classification of spherical microalgal species using recently developed frequency-division-multiplexed fluorescence imaging flow cytometry and machine learning. We obtained three-color (bright-field and two-color fluorescence) images of microalgal cells, quantified morphological features of the cells using the images, and classified six microalgae using features via a support vector machine. By virtue of the rich information content of the three-color images of microalgal cells, we classified six microalgae with a high accuracy of 99.8%. Our method can evaluate large populations of microalgal cells with single-cell resolution and hence holds promise for various applications such as environmental monitoring of the hydrosphere.

© 2020 Optical Society of America under the terms of the OSA Open Access Publishing Agreement

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References

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2019 (1)

A. Isozaki, H. Mikami, K. Hiramatsu, S. Sakuma, Y. Kasai, T. Iino, T. Yamano, A. Yasumoto, Y. Oguchi, N. Suzuki, Y. Shirasaki, T. Endo, T. Ito, K. Hiraki, M. Yamada, M. Matsusaka, T. Hayakawa, H. Fukuzawa, Y. Yatomi, F. Arai, D. Di Carlo, A. Nakagawa, Y. Hoshino, Y. Hosokawa, S. Uemura, T. Sugimura, Y. Ozeki, N. Nitta, and K. Goda, “A practical guide to intelligent image-activated cell sorting,” Nat. Protoc. 14(8), 2370–2415 (2019).
[Crossref]

2018 (4)

H. Mikami, C. Lei, N. Nitta, T. Sugimura, T. Ito, Y. Ozeki, and K. Goda, “High-speed imaging meets single-cell analysis,” Chem 4(10), 2278–2300 (2018).
[Crossref]

N. Nitta, T. Sugimura, A. Isozaki, H. Mikami, K. Hiraki, S. Sakuma, T. Iino, F. Arai, T. Endo, Y. Fujiwaki, H. Fukuzawa, M. Hase, T. Hayakawa, K. Hiramatsu, Y. Hoshino, M. Inaba, T. Ito, H. Karakawa, Y. Kasai, K. Koizumi, S. Lee, C. Lei, M. Li, T. Maeno, S. Matsusaka, D. Murakami, A. Nakagawa, Y. Oguchi, M. Oikawa, T. Ota, K. Shiba, H. Shintaku, Y. Shirasaki, K. Suga, Y. Suzuki, N. Suzuki, Y. Tanaka, H. Tezuka, C. Toyokawa, Y. Yalikun, M. Yamada, M. Yamagishi, T. Yamano, A. Yasumoto, Y. Yatomi, M. Yazawa, D. Di Carlo, Y. Hosokawa, S. Uemura, Y. Ozeki, and K. Goda, “Intelligent image-activated cell sorting,” Cell 175(1), 266–276.e13 (2018).
[Crossref]

C. Lei, H. Kobayashi, Y. Wu, M. Li, A. Isozaki, A. Yasumoto, H. Mikami, T. Ito, N. Nitta, T. Sugimura, M. Yamada, Y. Yatomi, D. Di Carlo, Y. Ozeki, and K. Goda, “High-throughput imaging flow cytometry by optofluidic time-stretch microscopy,” Nat. Protoc. 13(7), 1603–1631 (2018).
[Crossref]

H. Mikami, J. Harmon, H. Kobayashi, S. Hamad, Y. Wang, O. Iwata, K. Suzuki, T. Ito, Y. Aisaka, N. Kutsuna, K. Nagasawa, H. Watarai, Y. Ozeki, and K. Goda, “Ultrafast confocal fluorescence microscopy beyond the fluorescence lifetime limit,” Optica 5(2), 117–126 (2018).
[Crossref]

2016 (5)

Q. T. K. Lai, K. C. M. Lee, A. H. L. Tang, K. K. Y. Wong, H. K. H. So, and K. K. Tsia, “High-throughput time-stretch imaging flow cytometry for multi-class classification of phytoplankton,” Opt. Express 24(25), 28170–28184 (2016).
[Crossref]

M. Hildebrand, A. Davis, R. Abbriano, H. Pugsley, J. Traller, S. Smith, R. P. Shrestha, O. Cook, E. Sanchez-Alvarez, K. Manandhar-Shrestha, and B. Alderette, “Applications of imaging flow cytometry for microalgae,” Methods in Mol. Bio. 1389, 47–67 (2016).
[Crossref]

W. Li, X. Xu, M. Fujibayashi, Q. Niu, N. Tanaka, and O. Nishimura, “Response of microalgae to elevated CO2 and temperature: impact of climate change on freshwater ecosystems,” Environ. Sci. Pollut. Res. 23(19), 19847–19860 (2016).
[Crossref]

T. Blasi, H. Hennig, H. D. Summers, F. J. Theis, J. Cerveira, J. O. Patterson, D. Davies, A. Filby, A. E. Carpenter, and P. Rees, “Label-free cell cycle analysis for high-throughput imaging flow cytometry,” Nat. Commun. 7(1), 10256 (2016).
[Crossref]

C. Lei, T. Ito, M. Ugawa, T. Nozawa, O. Iwata, M. Maki, G. Okada, H. Kobayashi, X. Sun, P. Tiamsak, N. Tsumura, K. Suzuki, D. Di Carlo, Y. Ozeki, and K. Goda, “High-throughput label-free image cytometry and image-based classification of live Euglena gracilis,” Biomed. Opt. Express 7(7), 2703–2708 (2016).
[Crossref]

2014 (1)

K. Lee, M. Eisterhold, F. Rindi, S. Palanisami, and P. Nam, “Isolation and screening of microalgae from natural habitats in the Midwestern United States of America for biomass and biodiesel sources,” J. Nat. Sci. Biol. Med. 5(19), 333–339 (2014).
[Crossref]

2013 (2)

E. D. Diebold, B. W. Buckley, D. R. Gossett, and B. Jalali, “Digitally synthesized beat frequency multiplexing for sub-millisecond fluorescence microscopy,” Nat. Photonics 7(10), 806–810 (2013).
[Crossref]

K. Goda and B. Jalali, “Dispersive fourier transformation for fast continuous single-shot measurements,” Nat. Photonics 7(2), 102–112 (2013).
[Crossref]

2012 (2)

K. Goda, A. Ayazi, D. R. Gossett, J. Sadasivam, C. K. Lonappan, E. Sollier, A. M. Fard, S. C. Hur, J. Adam, C. Murray, C. Wang, N. Brackbill, D. Di Carlo, and B. Jalali, “High-throughput single-microparticle imaging flow analyzer,” Proc. Natl. Acad. Sci. U. S. A. 109(29), 11630–11635 (2012).
[Crossref]

D. R. Georgianna and S. P. Mayfield, “Exploiting diversity and synthetic biology for the production of algal biofuels,” Nature 488(7411), 329–335 (2012).
[Crossref]

2010 (1)

M. Hannon, J. Gimpel, M. Tran, B. Rasala, and S. Mayfield, “Biofuels from algae: challenges and potential,” Biofuels 1(5), 763–784 (2010).
[Crossref]

2009 (2)

K. Goda, K. K. Tsia, and B. Jalali, “Serial time-encoded amplified imaging for real-time observation of fast dynamic phenomena,” Nature 458(7242), 1145–1149 (2009).
[Crossref]

F. Kasai, M. Kawachi, M. Erata, F. Mori, K. Yumoto, M. Sato, and M. Ishimoto, “NIES-Collection List of Strains, 8th ed.,” Jpn. J. Phycol. 57(Suppl), 1–350 (2009).

2008 (2)

P. He, S. Xu, H. Zhang, S. Wen, Y. Dai, S. Lin, and C. Yarish, “Bioremediation efficiency in the removal of dissolved inorganic nutrients by the red seaweed, Porphyra yezoensis, cultivated in the open sea,” Water Res. 42(4-5), 1281–1289 (2008).
[Crossref]

G. C. Dismukes, D. Carrieri, N. Bennette, G. M. Ananyev, and M. C. Posewitz, “Aquatic phototrophs: efficient alternatives to land-based crops for biofuels,” Curr. Opin. Biotechnol. 19(3), 235–240 (2008).
[Crossref]

2004 (2)

O. Pulz and W. Gross, “Valuable products from biotechnology of microalgae,” Appl. Microbiol. Biotechnol. 65(6), 635–648 (2004).
[Crossref]

X. Irigoien, J. Huisman, and R. Harris, “Global biodiversity patterns of marine phytoplankton and zooplankton,” Nature 429(6994), 863–867 (2004).
[Crossref]

2003 (1)

F. Kubota, “Analysis of red cell and platelet morphology using an imaging-combined flow cytometer,” Clin. Lab. Haematol. 25(2), 71–76 (2003).
[Crossref]

2001 (1)

A. Vaishampayan, R. P. Sinha, D. P. Hader, T. Dey, A. K. Gupta, U. Bhan, and A. L. Rao, “Cyanobacterial biofertilizers in rice agriculture,” Bot. Rev. 67(4), 453–516 (2001).
[Crossref]

1995 (1)

F. Kubota, H. Kusuzawa, T. Kosaka, and H. Nakamoto, “Flow cytometer and imaging device used in combination,” Cytometry 21, 129–132 (1995).
[Crossref]

1989 (1)

L. Lin, “A concordance correlation coefficient to evaluate reproducibility,” Biometrics 45(1), 255–268 (1989).
[Crossref]

Abbriano, R.

M. Hildebrand, A. Davis, R. Abbriano, H. Pugsley, J. Traller, S. Smith, R. P. Shrestha, O. Cook, E. Sanchez-Alvarez, K. Manandhar-Shrestha, and B. Alderette, “Applications of imaging flow cytometry for microalgae,” Methods in Mol. Bio. 1389, 47–67 (2016).
[Crossref]

Adam, J.

K. Goda, A. Ayazi, D. R. Gossett, J. Sadasivam, C. K. Lonappan, E. Sollier, A. M. Fard, S. C. Hur, J. Adam, C. Murray, C. Wang, N. Brackbill, D. Di Carlo, and B. Jalali, “High-throughput single-microparticle imaging flow analyzer,” Proc. Natl. Acad. Sci. U. S. A. 109(29), 11630–11635 (2012).
[Crossref]

Aisaka, Y.

Alderette, B.

M. Hildebrand, A. Davis, R. Abbriano, H. Pugsley, J. Traller, S. Smith, R. P. Shrestha, O. Cook, E. Sanchez-Alvarez, K. Manandhar-Shrestha, and B. Alderette, “Applications of imaging flow cytometry for microalgae,” Methods in Mol. Bio. 1389, 47–67 (2016).
[Crossref]

Ananyev, G. M.

G. C. Dismukes, D. Carrieri, N. Bennette, G. M. Ananyev, and M. C. Posewitz, “Aquatic phototrophs: efficient alternatives to land-based crops for biofuels,” Curr. Opin. Biotechnol. 19(3), 235–240 (2008).
[Crossref]

Arai, F.

A. Isozaki, H. Mikami, K. Hiramatsu, S. Sakuma, Y. Kasai, T. Iino, T. Yamano, A. Yasumoto, Y. Oguchi, N. Suzuki, Y. Shirasaki, T. Endo, T. Ito, K. Hiraki, M. Yamada, M. Matsusaka, T. Hayakawa, H. Fukuzawa, Y. Yatomi, F. Arai, D. Di Carlo, A. Nakagawa, Y. Hoshino, Y. Hosokawa, S. Uemura, T. Sugimura, Y. Ozeki, N. Nitta, and K. Goda, “A practical guide to intelligent image-activated cell sorting,” Nat. Protoc. 14(8), 2370–2415 (2019).
[Crossref]

N. Nitta, T. Sugimura, A. Isozaki, H. Mikami, K. Hiraki, S. Sakuma, T. Iino, F. Arai, T. Endo, Y. Fujiwaki, H. Fukuzawa, M. Hase, T. Hayakawa, K. Hiramatsu, Y. Hoshino, M. Inaba, T. Ito, H. Karakawa, Y. Kasai, K. Koizumi, S. Lee, C. Lei, M. Li, T. Maeno, S. Matsusaka, D. Murakami, A. Nakagawa, Y. Oguchi, M. Oikawa, T. Ota, K. Shiba, H. Shintaku, Y. Shirasaki, K. Suga, Y. Suzuki, N. Suzuki, Y. Tanaka, H. Tezuka, C. Toyokawa, Y. Yalikun, M. Yamada, M. Yamagishi, T. Yamano, A. Yasumoto, Y. Yatomi, M. Yazawa, D. Di Carlo, Y. Hosokawa, S. Uemura, Y. Ozeki, and K. Goda, “Intelligent image-activated cell sorting,” Cell 175(1), 266–276.e13 (2018).
[Crossref]

Ayazi, A.

K. Goda, A. Ayazi, D. R. Gossett, J. Sadasivam, C. K. Lonappan, E. Sollier, A. M. Fard, S. C. Hur, J. Adam, C. Murray, C. Wang, N. Brackbill, D. Di Carlo, and B. Jalali, “High-throughput single-microparticle imaging flow analyzer,” Proc. Natl. Acad. Sci. U. S. A. 109(29), 11630–11635 (2012).
[Crossref]

Bennette, N.

G. C. Dismukes, D. Carrieri, N. Bennette, G. M. Ananyev, and M. C. Posewitz, “Aquatic phototrophs: efficient alternatives to land-based crops for biofuels,” Curr. Opin. Biotechnol. 19(3), 235–240 (2008).
[Crossref]

Bhan, U.

A. Vaishampayan, R. P. Sinha, D. P. Hader, T. Dey, A. K. Gupta, U. Bhan, and A. L. Rao, “Cyanobacterial biofertilizers in rice agriculture,” Bot. Rev. 67(4), 453–516 (2001).
[Crossref]

Blasi, T.

T. Blasi, H. Hennig, H. D. Summers, F. J. Theis, J. Cerveira, J. O. Patterson, D. Davies, A. Filby, A. E. Carpenter, and P. Rees, “Label-free cell cycle analysis for high-throughput imaging flow cytometry,” Nat. Commun. 7(1), 10256 (2016).
[Crossref]

Brackbill, N.

K. Goda, A. Ayazi, D. R. Gossett, J. Sadasivam, C. K. Lonappan, E. Sollier, A. M. Fard, S. C. Hur, J. Adam, C. Murray, C. Wang, N. Brackbill, D. Di Carlo, and B. Jalali, “High-throughput single-microparticle imaging flow analyzer,” Proc. Natl. Acad. Sci. U. S. A. 109(29), 11630–11635 (2012).
[Crossref]

Buckley, B. W.

E. D. Diebold, B. W. Buckley, D. R. Gossett, and B. Jalali, “Digitally synthesized beat frequency multiplexing for sub-millisecond fluorescence microscopy,” Nat. Photonics 7(10), 806–810 (2013).
[Crossref]

Carpenter, A. E.

T. Blasi, H. Hennig, H. D. Summers, F. J. Theis, J. Cerveira, J. O. Patterson, D. Davies, A. Filby, A. E. Carpenter, and P. Rees, “Label-free cell cycle analysis for high-throughput imaging flow cytometry,” Nat. Commun. 7(1), 10256 (2016).
[Crossref]

Carrieri, D.

G. C. Dismukes, D. Carrieri, N. Bennette, G. M. Ananyev, and M. C. Posewitz, “Aquatic phototrophs: efficient alternatives to land-based crops for biofuels,” Curr. Opin. Biotechnol. 19(3), 235–240 (2008).
[Crossref]

Cerveira, J.

T. Blasi, H. Hennig, H. D. Summers, F. J. Theis, J. Cerveira, J. O. Patterson, D. Davies, A. Filby, A. E. Carpenter, and P. Rees, “Label-free cell cycle analysis for high-throughput imaging flow cytometry,” Nat. Commun. 7(1), 10256 (2016).
[Crossref]

Cook, O.

M. Hildebrand, A. Davis, R. Abbriano, H. Pugsley, J. Traller, S. Smith, R. P. Shrestha, O. Cook, E. Sanchez-Alvarez, K. Manandhar-Shrestha, and B. Alderette, “Applications of imaging flow cytometry for microalgae,” Methods in Mol. Bio. 1389, 47–67 (2016).
[Crossref]

Cristianini, N.

N. Cristianini and J. Shawe-Taylor, “An introduction to support vector machines: and other kernel-based learning methods,” (Cambridge University, 2000), Chap. 7.5.

Dai, Y.

P. He, S. Xu, H. Zhang, S. Wen, Y. Dai, S. Lin, and C. Yarish, “Bioremediation efficiency in the removal of dissolved inorganic nutrients by the red seaweed, Porphyra yezoensis, cultivated in the open sea,” Water Res. 42(4-5), 1281–1289 (2008).
[Crossref]

Davies, D.

T. Blasi, H. Hennig, H. D. Summers, F. J. Theis, J. Cerveira, J. O. Patterson, D. Davies, A. Filby, A. E. Carpenter, and P. Rees, “Label-free cell cycle analysis for high-throughput imaging flow cytometry,” Nat. Commun. 7(1), 10256 (2016).
[Crossref]

Davis, A.

M. Hildebrand, A. Davis, R. Abbriano, H. Pugsley, J. Traller, S. Smith, R. P. Shrestha, O. Cook, E. Sanchez-Alvarez, K. Manandhar-Shrestha, and B. Alderette, “Applications of imaging flow cytometry for microalgae,” Methods in Mol. Bio. 1389, 47–67 (2016).
[Crossref]

Dey, T.

A. Vaishampayan, R. P. Sinha, D. P. Hader, T. Dey, A. K. Gupta, U. Bhan, and A. L. Rao, “Cyanobacterial biofertilizers in rice agriculture,” Bot. Rev. 67(4), 453–516 (2001).
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Figures (4)

Fig. 1.
Fig. 1. High-speed accurate classification of microalgae by intelligent FDM fluorescence imaging flow cytometry. (a) Procedure. (b) Schematic of the FDM fluorescence imaging flow cytometer. HWP, half-wave plate; PBS, polarizing beam splitter; AOD, acousto-optic deflector; HBS, half beam splitter; DM, dichroic mirror; APD, avalanche photodetector; OL, objective lens; ND, neutral density filter. The inset shows an enlarged schematic of the flow channel and excitation beam spots inside the channel. (c) Flow chart of digital image processing.
Fig. 2.
Fig. 2. Three-color images of the six microalgal species obtained by the FDM fluorescence imaging flow cytometer. Green represents the nucleus stained with SYTO 16. Red represents autofluorescent chlorophyll. Gray represents bright-field images. (a) Chlorella sorokiniana, (b) Chlamydomonas reinhardtii, (c) Haematococcus lacustris, (d) Hamakko caudatus, (e) Scenedesmus aff. acutus, (f) Gloeomonas anomalipyrenoide. The arrows indicate the flow direction. Color scales have been adjusted per species. Scale bars: 10 µm.
Fig. 3.
Fig. 3. Classification results corresponding to the number of cells that were classified for each species. (a) Confusion matrix showing the results of all 251 parameters with an accuracy of 99.8%. (b) Confusion matrix results showing the classification of the bright-field imaging flow cytometry results having an accuracy of 89.5%. (c) Confusion matrix results showing the classification of the non-imaging flow cytometry results having an accuracy of 84.9%.
Fig. 4.
Fig. 4. Statistical plots of the morphological features of the six microalgal species. (a) 2D scatter plot with two parameters (Feret diameter and nucleus mean intensity edge). (b) Histogram of the congested region in the 2D scatter plot, showing how an additional parameter assists the classification.

Tables (4)

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Table 1. Top 10 features of the classification.

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Table 2. Morphological features of microalgal cells in bright-field images (127 features).

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Table 3. Top 10 features of the classification.

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Table 4. Top 10 features of the classification.

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