SPIRO - the automated Petri plate imaging platform designed by biologists, for biologists.
3D printing
Arabidopsis thaliana
ImageJ macro
R
automated image analysis
automated imaging
laboratory automation
open science hardware
phenotyping
plant autophagy
raspberry pi
root growth
seed dormancy
seed germination
technical advance
time-lapse imaging
Journal
The Plant journal : for cell and molecular biology
ISSN: 1365-313X
Titre abrégé: Plant J
Pays: England
ID NLM: 9207397
Informations de publication
Date de publication:
23 Dec 2023
23 Dec 2023
Historique:
received:
20
09
2023
accepted:
04
12
2023
medline:
23
12
2023
pubmed:
23
12
2023
entrez:
23
12
2023
Statut:
aheadofprint
Résumé
Phenotyping of model organisms grown on Petri plates is often carried out manually, despite the procedures being time-consuming and laborious. The main reason for this is the limited availability of automated phenotyping facilities, whereas constructing a custom automated solution can be a daunting task for biologists. Here, we describe SPIRO, the Smart Plate Imaging Robot, an automated platform that acquires time-lapse photographs of up to four vertically oriented Petri plates in a single experiment, corresponding to 192 seedlings for a typical root growth assay and up to 2500 seeds for a germination assay. SPIRO is catered specifically to biologists' needs, requiring no engineering or programming expertise for assembly and operation. Its small footprint is optimized for standard incubators, the inbuilt green LED enables imaging under dark conditions, and remote control provides access to the data without interfering with sample growth. SPIRO's excellent image quality is suitable for automated image processing, which we demonstrate on the example of seed germination and root growth assays. Furthermore, the robot can be easily customized for specific uses, as all information about SPIRO is released under open-source licenses. Importantly, uninterrupted imaging allows considerably more precise assessment of seed germination parameters and root growth rates compared with manual assays. Moreover, SPIRO enables previously technically challenging assays such as phenotyping in the dark. We illustrate the benefits of SPIRO in proof-of-concept experiments which yielded a novel insight on the interplay between autophagy, nitrogen sensing, and photoblastic response.
Types de publication
Journal Article
Langues
eng
Sous-ensembles de citation
IM
Subventions
Organisme : Carl Tryggers Foundation
ID : CTS14-326
Organisme : Carl Tryggers Foundation
ID : CTS20-287
Organisme : Crops for the Future Research Programme at the Swedish University of Agricultural Sciences
Organisme : Deutsche Forschungsgemeinschaft
ID : CRC1101
Organisme : Deutsche Forschungsgemeinschaft
ID : TPA02
Organisme : HORIZON EUROPE Marie Sklodowska-Curie Actions
ID : 799433
Organisme : Knut och Alice Wallenbergs Stiftelse
ID : 2018.0026
Organisme : The Swedish Foundation for Strategic Research
Organisme : The Swedish Research Council for Environment, Agricultural Sciences and Spatial Planning (Formas)
ID : 2016-20031
Organisme : The Swedish Research Council for Environment, Agricultural Sciences and Spatial Planning (Formas)
ID : 2017-00541
Organisme : The Swedish Research Council for Environment, Agricultural Sciences and Spatial Planning (Formas)
ID : 2019-01565
Organisme : The Swedish Research Council for Environment, Agricultural Sciences and Spatial Planning (Formas)
ID : 2021-01812
Organisme : The Swedish Research Council (VR)
ID : 621-2013-4707
Informations de copyright
© 2023 The Authors. The Plant Journal published by Society for Experimental Biology and John Wiley & Sons Ltd.
Références
Abley, K., Formosa-Jordan, P., Tavares, H., Chan, E.Y.T., Afsharinafar, M., Leyser, O. et al. (2021) An aba-ga bistable switch can account for natural variation in the variability of arabidopsis seed germination time. eLife, 10, e59485. Available from: https://doi.org/10.7554/eLife.59485
Aravind, J., Vimala Devi, S., Radhamani, J., Jacob, S.R. & Kalyani, S. (2020) Germinationmetrics: seed germination indices and curve fitting. R package version 0.1.3.9000.
Betegón-Putze, I., González, A., Sevillano, X., Blasco-Escámez, D. & Caño-Delgado, A.I. (2019) MyROOT: a method and software for the semiautomatic measurement of primary root length in Arabidopsis seedlings. Plant Journal, 98(6), 1145-1156. Available from: https://doi.org/10.1111/tpj.14297
Bewley, J.D. (1997) Seed germination and dormancy. The Plant Cell, 44(8), 1055-1066. Available from: https://doi.org/10.1105/tpc.9.7.1055
Carrera, E., Holman, T., Medhurst, A., Peer, W., Schmuths, H., Footitt, S. et al. (2007) Gene expression profiling reveals defined functions of the ATP-binding cassette transporter COMATOSE late in phase II of germination. Plant Physiology, 143(4), 1669-1679. Available from: https://doi.org/10.1104/pp.107.096057
Chahtane, H., Kim, W. & Lopez-Molina, L. (2017) Primary seed dormancy: a temporally multilayered riddle waiting to be unlocked. Journal of Experimental Botany, 68(4), 857-869. Available from: https://doi.org/10.1093/jxb/erw377
Chen, Q., Shinozaki, D., Luo, J., Pottier, M., Havé, M., Marmagne, A. et al. (2019) Autophagy and nutrients management in plants. Cells, 8(11), 1426. Available from: https://doi.org/10.3390/cells8111426
Chung, T., Phillips, A.R. & Vierstra, R.D. (2010) ATG8 lipidation and ATG8-mediated autophagy in Arabidopsis require ATG12 expressed from the differentially controlled ATG12A and ATG12B loci. Plant Journal, 62(3), 483-493. Available from: https://doi.org/10.1111/j.1365-313X.2010.04166.x
De Ligne, L., Vidal-Diez de Ulzurrun, G., Baetens, J.M., Van den Bulcke, J., Van Acker, J. & De Baets, B. (2019) Analysis of spatio-temporal fungal growth dynamics under different environmental conditions. IMA Fungus, 10(1), 1-13. Available from: https://doi.org/10.1186/s43008-019-0009-3
Ding, X., Vogel, M., Boschke, E., Bley, T. & Lenk, F. (2015) PetriJet platform technology: an automated platform for culture dish handling and monitoring of the contents. Journal of Laboratory Automation, 20(4), 447-456. Available from: https://doi.org/10.1177/2211068215576191
Dobos, O., Horvath, P., Nagy, F., Danka, T. & Viczián, A. (2019) A deep learning-based approach for high-throughput hypocotyl phenotyping. Plant Physiology, 181(4), 1415-1424. Available from: https://doi.org/10.1104/pp.19.00728
El-Kassaby, Y.A., Moss, I., Kolotelo, D. & Stoehr, M. (2008) Seed germination: mathematical representation and parameters extraction. Forest Science, 54(2), 220-227. Available from: https://doi.org/10.1093/forestscience/54.2.220
Eriksson, M.E. & Millar, A.J. (2003) The circadian clock. A plant's best friend in a spinning world. Plant Physiology, 132(2), 732-738. Available from: https://doi.org/10.1104/pp.103.022343
Erlichman, O.A., Weiss, S., Abu Arkia, M., Ankary-Khaner, M., Soroka, Y., Jasinska, W. et al. (2023) Autophagy in maternal tissues contributes to Arabidopsis seed development. Plant Physiology, 193, 611-626. Available from: https://doi.org/10.1093/plphys/kiad350
Fernandez, R., Crabos, A., Maillard, M., Nacry, P. & Pradal, C. (2022) High-throughput and automatic structural and developmental root phenotyping on Arabidopsis seedlings. Plant Methods, 18(1), 127. Available from: https://doi.org/10.1186/s13007-022-00960-5
Folta, K.M. & Maruhnich, S.A. (2007) Green light: a signal to slow down or stop. Journal of Experimental Botany, 58(12), 3099-3111. Available from: https://doi.org/10.1093/jxb/erm130
Gaggion, N., Ariel, F., Daric, V., Lambert, É., Legendre, S., Roulé, T. et al. (2020) ChronoRoot: high-throughput phenotyping by deep segmentation networks reveals novel temporal parameters of plant root system architecture. BioRxiv. Available from: https://doi.org/10.1101/2020.10.27.350553
Guichard, M., Holla, S., Wernerová, D., Grossmann, G. & Minina, E.A. (2021) RoPod, a customizable toolkit for non-invasive root imaging, reveals cell type-specific dynamics of plant autophagy. Biology, Environmental Science, Engineering, 1-21. Available from: https://doi.org/10.1101/2021.12.07.471480
Hofius, D., Schultz-Larsen, T., Joensen, J., Tsitsigiannis, D.I., Petersen, N.H.T., Mattsson, O. et al. (2009) Autophagic components contribute to hypersensitive cell death in Arabidopsis. Cell, 137(4), 773-783. Available from: https://doi.org/10.1016/j.cell.2009.02.036
Ibarra, S.E., Auge, G., Sánchez, R.A. & Botto, J.F. (2013) Transcriptional programs related to phytochrome a function in arabidopsis seed germination. Molecular Plant, 6(4), 1261-1273. Available from: https://doi.org/10.1093/mp/sst001
Iglesias-Fernández, R. & Vicente-Carbajosa, J. (2022) A view into seed autophagy: from development to environmental responses. Plants, 11(23), 3247. Available from: https://doi.org/10.3390/plants11233247
Joosen, R.V.L., Kodde, J., Willems, L.A.J., Ligterink, W., van der Plas, L.H.W. & Hilhorst, H.W.M. (2010) Germinator: a software package for high-throughput scoring and curve fitting of Arabidopsis seed germination. The Plant Journal, 62(1), 148-159. Available from: https://doi.org/10.1111/j.1365-313X.2009.04116.x
Korbel, J.O. & Stegle, O. (2020) Effects of the COVID-19 pandemic on life scientists. Genome Biology, 21(1), 113. Available from: https://doi.org/10.1186/s13059-020-02031-1
Lobet, G., Draye, X. & Périlleux, C. (2013) An online database for plant image analysis software tools. Plant Methods, 9(1), 38. Available from: https://doi.org/10.1186/1746-4811-9-38
Lube, V., Noyan, M.A., Przybysz, A., Salama, K. & Blilou, I. (2022) MultipleXLab: a high-throughput portable live-imaging root phenotyping platform using deep learning and computer vision. Plant Methods, 18(1), 38. Available from: https://doi.org/10.1186/s13007-022-00864-4
Lucas, M., Swarup, R., Paponov, I.A., Swarup, K., Casimiro, I., Lake, D. et al. (2011) SHORT-ROOT regulates primary, lateral, and adventitious root development in Arabidopsis. Plant Physiology, 155(1), 384-398. Available from: https://doi.org/10.1104/pp.110.165126
Maia Chagas, A. (2018) Haves and have nots must find a better way: the case for open scientific hardware. PLoS Biology, 16(9), e3000014. Available from: https://doi.org/10.1371/journal.pbio.3000014
Marshall, R.S., McLoughlin, F. & Vierstra, R.D. (2016) Autophagic turnover of inactive 26S proteasomes in yeast is directed by the ubiquitin receptor Cue5 and the Hsp42 chaperone. Cell Reports, 16(6), 1717-1732. Available from: https://doi.org/10.1016/j.celrep.2016.07.015
Nagatani, A., Reed, J.W. & Chory, J. (1993) Isolation and initial characterization of Arabidopsis mutants that are deficient in phytochrome a. Plant Physiology, 102(1), 269-277. Available from: https://doi.org/10.1104/pp.102.1.269
Nagel, K.A., Lenz, H., Kastenholz, B., Gilmer, F., Averesch, A., Putz, A. et al. (2020) The platform GrowScreen-Agar enables identification of phenotypic diversity in root and shoot growth traits of agar grown plants. Plant Methods, 16(1), 1-17. Available from: https://doi.org/10.1186/s13007-020-00631-3
Oh, E., Kang, H., Yamaguchi, S., Park, J., Lee, D., Kamiya, Y. et al. (2009) Genome-wide analysis of genes targeted by PHYTOCHROME INTERACTING FACTOR 3-LIKE5 during seed germination in arabidopsis. Plant Cell, 21(2), 403-419. Available from: https://doi.org/10.1105/tpc.108.064691
Pan, R., Liu, J. & Hu, J. (2019) Peroxisomes in plant reproduction and seed-related development. In. Journal of Integrative Plant Biology, 61(7), 784-802. Available from: https://doi.org/10.1111/jipb.12765
Patterson, K., Walters, L.A., Cooper, A.M., Olvera, J.G., Rosas, M.A., Rasmusson, A.G. et al. (2016) Nitrate-regulated glutaredoxins control arabidopsis primary root growth. Plant Physiology, 170(2), 989-999. Available from: https://doi.org/10.1104/pp.15.01776
Pearce, J.M. (2016) Return on investment for open source scientific hardware development. Science and Public Policy, 43(2), 192-195. Available from: https://doi.org/10.1093/scipol/scv034
Pearce, J.M. (2020) Economic savings for scientific free and open source technology: a review. HardwareX, 8, e00139. Available from: https://doi.org/10.1016/j.ohx.2020.e00139
Quint, M., Delker, C., Franklin, K.A., Wigge, P.A., Halliday, K.J. & Van Zanten, M. (2016) Molecular and genetic control of plant thermomorphogenesis. Nature Plants, 2(January), 1-9. Available from: https://doi.org/10.1038/nplants.2015.190
Reed, J.W., Nagpal, P., Poole, D.S., Furuya, M. & Chory, J. (1993) Mutations in the gene for the red/far-red light receptor phytochrome B alter cell elongation and physiological responses throughout arabidopsis development. Plant Cell, 5(2), 147-157. Available from: https://doi.org/10.1105/tpc.5.2.147
Satbhai, S.B., Göschl, C. & Busch, W. (2017) Automated high-throughput root phenotyping of Arabidopsis thaliana under nutrient deficiency conditions. Methods in Molecular Biology, 1610, 135-153. Available from: https://doi.org/10.1007/978-1-4939-7003-2_10
Schindelin, J., Arganda-Carreras, I., Frise, E., Kaynig, V., Longair, M., Pietzsch, T. et al. (2012) Fiji: an open-source platform for biological-image analysis. Nature Methods, 9(7), 676-682. Available from: https://doi.org/10.1038/nmeth.2019
Shen, H., Moon, J. & Huq, E. (2005) PIF1 is regulated by light-mediated degradation through the ubiquitin-26S proteasome pathway to optimize photomorphogenesis of seedlings in Arabidopsis. Plant Journal, 44(6), 1023-1035. Available from: https://doi.org/10.1111/j.1365-313X.2005.02606.x
Shinomura, T., Nagatani, A., Hanzawa, H., Kubota, M., Watanabe, M. & Furuya, M. (1996) Action spectra for phytochrome A- and B-specific photoinduction of seed germination in Arabidopsis thaliana. Proceedings of the National Academy of Sciences of the United States of America, 93(15), 8129-8133. Available from: https://doi.org/10.1073/pnas.93.15.8129
Slovak, R., Göschl, C., Su, X., Shimotani, K., Shiina, T. & Busch, W. (2014) A scalable open-source pipeline for large-scale root phenotyping of Arabidopsis. Plant Cell, 26(6), 2390-2403. Available from: https://doi.org/10.1105/tpc.114.124032
Stawska, M. & Oracz, K. (2019) Phyb and hy5 are involved in the blue light-mediated alleviation of dormancy of arabidopsis seeds possibly via the modulation of expression of genes related to light, ga, and aba. International Journal of Molecular Sciences, 20(23), 5882. Available from: https://doi.org/10.3390/ijms20235882
Subramanian, R., Spalding, E.P. & Ferrier, N.J. (2013) A high throughput robot system for machine vision based plant phenotype studies. Machine Vision and Applications, 24(3), 619-636. Available from: https://doi.org/10.1007/s00138-012-0434-4
Thompson, A.R., Doelling, J.H., Suttangkakul, A. & Vierstra, R.D. (2005) Autophagic nutrient recycling in Arabidopsis directed by the ATG8 and ATG12 conjugation pathways. Plant Physiology, 138(4), 2097-2110. Available from: https://doi.org/10.1104/pp.105.060673
Topham, A.T., Taylor, R.E., Yan, D., Nambara, E., Johnston, I.G. & Bassel, G.W. (2017) Temperature variability is integrated by a spatially embedded decision-making center to break dormancy in Arabidopsis seeds. Proceedings of the National Academy of Sciences of the United States of America, 114(25), 6629-6634. Available from: https://doi.org/10.1073/pnas.1704745114
Tovar, J.C., Hoyer, J.S., Lin, A., Tielking, A., Callen, S.T., Elizabeth Castillo, S. et al. (2018) Raspberry Pi-powered imaging for plant phenotyping. Applications in Plant Sciences, 6(3), e1031. Available from: https://doi.org/10.1002/aps3.1031
Trusiak, M., Plitta-Michalak, B.P. & Michalak, M. (2023) Choosing the right path for the successful storage of seeds. Plants, 12(1), 72. Available from: https://doi.org/10.3390/plants12010072
Vidal, E.A., Moyano, T.C., Canales, J. & Gutiérrez, R.A. (2014) Nitrogen control of developmental phase transitions in Arabidopsis thaliana. Journal of Experimental Botany, 65(19), 5611-5618. Available from: https://doi.org/10.1093/jxb/eru326
Wenzel, T. (2023) Open hardware: from DIY trend to global transformation in access to laboratory equipment. PLoS Biology, 21(1), e3001931. Available from: https://doi.org/10.1371/journal.pbio.3001931
Wientjes, E., Philippi, J., Borst, J.W. & van Amerongen, H. (2017) Imaging the photosystem I/photosystem II chlorophyll ratio inside the leaf. Biochimica et Biophysica Acta - Bioenergetics, 1858(3), 259-265. Available from: https://doi.org/10.1016/j.bbabio.2017.01.008
Yanovsky, M.J., Casal, J.J. & Luppi, J.P. (1997) The VLF loci, polymorphic between ecotypes Landsberg erecta and Columbia, dissect two branches of phytochrome A signal transduction that correspond to very-low-fluence and high-irradiance responses. The Plant Journal, 12(3), 659-667. Available from: https://doi.org/10.1046/j.1365-313x.1997.00659.x
Yasrab, R., Atkinson, J.A., Wells, D.M., French, A.P., Pridmore, T.P. & Pound, M.P. (2019) RootNav 2.0: deep learning for automatic navigation of complex plant root architectures. GigaScience, 8(11), 1-16. Available from: https://doi.org/10.1093/gigascience/giz123
Yazdanbakhsh, N. & Fisahn, J. (2009) High throughput phenotyping of root growth dynamics, lateral root formation, root architecture and root hair development enabled by PlaRoM. Functional Plant Biology, 36(11), 938-946. Available from: https://doi.org/10.1071/FP09167
Yoshida, Y., Sarmiento-Mañús, R., Yamori, W., Ponce, M.R., Micol, J.L. & Tsukaya, H. (2018) The arabidopsis phyB-9 mutant has a second-site mutation in the VENOSA4 gene that alters chloroplast size, photosynthetic traits, and leaf growth. Plant Physiology, 178(1), 3-6. Available from: https://doi.org/10.1104/pp.18.00764
Zhou, J., Wang, J., Cheng, Y., Chi, Y.J., Fan, B., Yu, J.Q. et al. (2013) NBR1-mediated selective autophagy targets insoluble ubiquitinated protein aggregates in plant stress responses. PLoS Genetics, 9(1), e1003196. Available from: https://doi.org/10.1371/journal.pgen.1003196