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The Saclay Plant Sciences consortium together with the Imagerie-Gif core facility have largely exploited the power of cytometry to perform major breakthroughs in plant biology. Tomato, wheat, Arabidopsis, tobacco, vanilla are part of the many experimental models analysed in our cytometers, together with more discrete populations such as the flora of the Balkans or the Kerguelen Islands. Plants are processed by cytometry for diverse experiments: genome analysis, cell cycle studies, biosensors tracking, mapping of proteins over time and space, etc.
Genome size analyses by flow cytometry thus play an important role in guiding the policy of species conservation or varietal selection programs (Chaintreuil et al. 20176; Hajrudinović et al. 2015; Razafinarivo et al. 2012). For instance, such studies have helped identify and preserve populations of ancestral cacao trees among other plantations in the heart of the Amazonian forest (Argout et al. 2010). Thanks to cytometry again, a new process of DNA remodelling has recently been identified in orchids. The description of this unique and fascinating feature of strict partial endoreplication in vanilla (Fig. 1) (Brown et al. 2017, collaboration ESE, IPS2, I2BC, CIRAD) opens new ways for breeding programs.
Figure 1: Vanilla ×tahitensis is an example of strict partial endoreplication occurring in Orchidaceae. During plant development, only 28% of the genome undergoes endoreplication. Photo Maurice Wong, Service du Développement Rural, BP 100, 98713 Papeete Tahiti, French Polynesia
Cytometry versus Imaging
Flow cytometry and Imaging like to meet on the edges of fluorescence. On one hand, the strength of flow cytometry over microscopy relies on its ability to analyse a high number of fluorescent objects in one run, with a unique sensitivity to detect the weakest fluorescent signals. On the other hand, cytometers only deal with isolated biological objects, whereas microscopes allow looking at the object within its tissue environment.
Beyond these differences, microscopes and cytometers agree on one point: the complexity to play with plant cells. Indeed, the presence of a cell wall and highly refractive or even opaque organelles, and the presence of many autofluorescent compounds (chlorophylls, lignins, etc.) sometimes make subcellular exploration approaches based on fluorescence difficult.
By focusing on isolated objects (such as protoplasts, nuclei, organelles, etc.), flow cytometry bypasses these difficulties. Moreover, up to 22 detectors may be used to explore the whole range of fluorescent spectra within one object, allowing “multi-colour analyses” and subsequent correlation of biological data in space and time.
Multi-colour analysis, some examples
Multi-colour analysis of a biological object expressing distinct fluorescent markers is a powerful toolbox to study plant cell processes. “Bicolour” analysis of the expression of fluorescent proteins like GFP, used for chromosomes labelling, allowed Moussa Benhamed’s team (IPS2) to show that the variations in the expression of the nuclear protein Kip-Related Protein5 (GFP-tagged) are correlated with the endoreplication process (revealed by DAPI labelling), KRP5 expression increasing with the endoploidy level (Fig. 2) (Jegu et al. 2013).
Figure 2: Expression of KRP5 correlates with endoreplication. DNA content distribution of GFP-positive (GFP+) and GFP-negative (GFP-) nuclei isolated from 14-d-old rosette leaves of Arabidopsis KRP5::NTF-GFP plants. The panel shows how GFP+ nuclei were selected based on the intensity of GFP fluorescence (each nucleus is represented by a red point).
Similarly, detection of biological activities by multiple immunolabelling is one of the strengths of multi-colour analysis in cytometry. By using a “tricolour” analysis of nuclei isolated from tomato pericarp, differences in RNA-polymerase II (RNA-Pol II) activation according to the endoreplication level have been detected. In that case, phosphorylated active RNA-Pol II was labelled with an antibody coupled to Alexa-488 (green fluorescence), non-phosphorylated inactive RNA-Pol II was labelled with an antibody coupled to Alexa-647 (red fluorescence), and DNA was labelled with DAPI (blue fluorescence). The analysis of this 3-colour labelling has demonstrated that RNA-Pol II activity was increasing with endoreplication (Fig. 3) (Pirello et al. 2014).
Figure 3: Endoreplication leads to increased transcriptional activity during tomato fruit development. A fruit pericarp nuclear suspension was dual-immunolabelled using antibodies recognizing the active (S2P phosphorylated) form and inactive (NP unphosphorylated) form of RNA polymerase II, stained with DAPI and analyzed by flow cytometry to quantify antibody labelling in nuclei according to endoreplication levels (coded in colour).
Multicolour analysis can also be combined with the use of photoconvertible proteins to achieve “pulse-chases” in cellulo, as shown by an assay quantifying Golgi membrane synthesis, based on the quantification of a Golgi marker linked to photoconvertible protein Kaede. Golgi membranes were first assessed using the green fluorescence of the Kaede-linked reporter during the different phases of the cell cycle. The conversion of the Kaede fluorescence from green to red marked the starting time of the pulse chase experiment. The reappearance of green fluorescence was then associated with the de novo synthetized Golgi proteins. This multi-colour analysis showed for the first time that, beside the S phase, the late G1 phase was a major step in Golgi protein synthesis (Bourge et al. 2015).
Come benefit from this equipment
Quantifying, sorting, measuring, analysing plethora of fluorescent objects are therefore a true prerogative of the new generation of cytometers, with captors that are more and more sensitive for the detection of fluorescent signals. A whole range of protocols is available on the SPS Cytometry platform to deal with the methodological barriers inherent to plant cells. Our Cytoflex analyser is able to detect up to 17 colours. This user-friendly equipment allows anyone to transform into a capable cytometrist in a few hours, for instance to quantify your favourite fluorescent proteins or perform cell cycle analyses and genome size studies. Our Astrios cell sorter, on the other hand, is operated by our cytometry experts Mick Bourge and Nicolas Valentin to isolate, purify, and characterize fluorescent populations.
Both cytometers are ready to tackle your biological questions. Come and see us to discuss your projects!
Béatrice SATIAT-JEUNEMAITRE (Scientific manager) Mickael BOURGE (Scientific and technical manager) Nicolas VALENTIN (Engineer)
Argout, X. et al. (2011). The genome of Theobroma cacao. Nat. Genet. 43: 101–108.
Bourge, M., Fort, C., Soler, M.-N., Satiat-Jeunemaître, B., and Brown, S.C. (2014). A pulse-chase strategy combining click-EdU and photoconvertible fluorescent reporter: tracking Golgi protein dynamics during the cell cycle. New Phytol. 205: 938–950.
Brown, S.C., Bourge, M., Maunoury, N., Wong, M., Bianchi, M.W., Lepers-Andrzejewski, S., Besse, P., Siljak-Yakovlev, S., Dron, M., and Satiat-Jeunemaitre, B. (2017). DNA Remodeling by Strict Partial Endoreplication in Orchids, an Original Process in the Plant Kingdom. GENOME Biol. Evol. 9: 1051–1071.
Chaintreuil, C. et al. (2016). The evolutionary dynamics of ancient and recent polyploidy in the African semiaquatic species of the legume genus Aeschynomene. New Phytol. 211: 1077–1091.
Hajrudinovic, A., Siljak-Yakovlev, S., Brown, S.C., Pustahija, F., Bourge, M., Ballian, D., and Bogunic, F. (2015). When sexual meets apomict: genome size, ploidy level and reproductive mode variation of Sorbus aria s.l. and S. austriaca (Rosaceae) in Bosnia and Herzegovina. Ann. Bot. 116: 301–312.
Jegu, T. et al. (2013). Multiple Functions of Kip-Related Protein5 Connect Endoreduplication and Cell Elongation. Plant Physiol. 161: 1694–1705.
Pirrello, J., Bourdon, M., Cheniclet, C., Bourge, M., Brown, S.C., Renaudin, J.-P., Frangne, N., and Chevalier, C. (2014). How Fruit Developmental Biology Makes Use of Flow Cytometry Approaches. Cytom. PART A 85: 115–125.
Razafinarivo, N.J., Rakotomalala, J.-J., Brown, S.C., Bourge, M., Hamon, S., de Kochko, A., Poncet, V., Dubreuil-Tranchant, C., Couturon, E., Guyot, R., and Hamon, P. (2012). Geographical gradients in the genome size variation of wild coffee trees (Coffea) native to Africa and Indian Ocean islands. TREE Genet. Genomes 8: 1345–1358.