Introduction

The Orchidaceae is the largest, highly evolved and most various family, accounting for almost 10% of flowering plants, and is comprised of about 35,000 species belonging to 850 genera (Arditti 1992; Dressler 1993; Chase et al. 2015). Orchids have a high economical value both in commercial horticulture, as potted plants or cut flowers, and in traditional Chinese medicine for their secondary metabolites production. Dendrobium is the third largest genus of Orchidaceae, where more than 1000 species with high ornamental and medicinal values have been identified (Zeng and Hu 2004; Takamiya et al. 2011; Ng et al. 2012).

In China, one of the most exploited species of Dendrobium is Dendrobium loddigesii, characterized by beautiful flowers with short bloom and also producing an extraordinary number of metabolites with antioxidant and antitumoral activities (reviewed in Gutierrez 2010; Hossain 2011), as loddigesinols (Ito et al. 2010), moscatilin (Ho and Chen 2003) and moscatine (Lam et al. 2015), that have been widely investigated (Singh et al. 2012; Bulpitt 2005). The increasing demand of D. loddigesii plants in health care applications (Halberstein 2005; Shoemaker et al. 2005; Wojcikowski and Gobe 2014) is provoking a severe depletion of its wild resources. Due to their recalcitrant in vitro habit and intense over-collecting, wild species of D. loddigesii are becoming rare, drastically reducing the global genetic resources and impacting potential economic value of this species.

In such a scenario, plant cell culture technology has received great attention for the improvement of ornamental traits and for producing useful plant secondary metabolites (Hossain et al. 2013; Teixera da Silva et al. 2015) safeguarding the wild species. In particular, artificial in vitro polyploidization can facilitate the achievements of both purposes in orchids (Miguel and Leonhardt 2011; Lavania et al. 2012; Teixera da Silva et al. 2015). Polyploid plants have been reported to bloom several times a year and to have larger and longer lasting flowers (Griesbach 1985, 2002; Chen and Chen 2007), all features greatly demanded by consumers (Griesbach 2002; Tang and Chen 2007). Finally, the polyploid condition is also known to enable the production of new metabolites and/or to increase the amounts of interesting molecules (Dhawan and Lavania 1996; Lavania 2005; Lavania et al. 2012).

Chromosome doubling is an acknowledged mechanism to obtain different ploidy levels in plants, and it is usually achieved by chemical treatments using anti-microtubule agents such as colchicine or oryzalin (Dhooghe et al. 2011; Blasco et al. 2015; Zhou et al. 2017). In Dendrobium it has been proved to be a closely genotype-dependent process and, to date, no unique protocol is available (Nakasone and Kamemoto 1961; Chaicharoen and Saejew 1981; Atichart and Bunnag 2007; Sarathum et al. 2010; Atichart 2013; Vichiato et al. 2014; Bunnag and Hongthongkham 2015). The development of a proper method for in vitro polyploidization requires the conduction of several tests to obtain the most suitable combination of antimitotic agent concentration and exposure time for each species (Dhooghe et al. 2011; Sattler et al. 2016). Often, these aspects limited the polyploidization process efficiency in Dendrobium, since it clashes with its very slow growth rate (from 2 to 13 years to get flowering), and to the intense labour required to grow this species, which accounts for almost 60% of total cost, as recently stated by Chen (2016).

We have focused our work to develop an effective and fast procedure to select, through an early in vitro screening by flow cytometry, the best conditions to obtain D. loddigesii polyploids, making possible the rapid elimination of the diploid materials. To overcome the slow growing attitude of D. loddigesii in vitro (Chen et al. 2010), hybrids derived from crosses of D. phalaenopsis × D.loddigesii were used as starting material. The effect of the microtubule inhibitor Amiprophos-methyl (APM) was tested for the first time in orchids, along with colchicine (COL) on protocorms like bodies (PLBs), a particular orchids protocorms structure that resemble somatic embryos in form and development (Lee et al. 2013). A recovery, up to 80%, of polyploids was achieved and the production of their high-value secondary metabolites was evaluated. According to our estimates, the use of whole set of methodologies presented in this work could allow a reduction up to 65%, in terms of materials to work with, reducing time and cost for orchids polyploids production.

Materials and Methods

Plant material and growth condition

A Dendrobium hybrid, obtained by crossing Dendrobium phalaenopsis (violet) (2n = 2X = 40) as maternal donor with Dendrobium loddigesii (2n = 2X = 38) as paternal donor, was used as starting material (Kindly provided by Dimitri Paskulov and Benedetto Aracri, Floramiata Research Laboratory, Piancastagnaio, Siena, Italy). For PLBs induction, seeds were surface-sterilized for 5–7 min in a 2% sodium hypochlorite solution, rinsed three times in sterilized water and then placed in Petri dishes (9 cm diameter) containing 25 ml of 1/2 strength MS medium (Murashige and Skoog 1962), supplemented with 20 g l−1 sucrose and 8.5 g l−1 of Plant Agar (Duchefa). The medium was adjusted to pH 5.8 and then autoclaved at 121 °C for 20 min. The cultures were incubated at 25 ± 2 °C in the dark for 14 days and then shifted to light under a 16/8 h L/D photoperiod (10 µmol−2 s−1), provided by Philips fluorescent light tubes. PLBs sub-culturing was performed each 2 weeks for two times.

Treatment for polyploidy induction

Single seed derived PLBs were single cultured onto solid medium and their derived clones were used. PLBs of 3–5 mm in size were used as explants for polyploid induction. About 1 g of fresh PLBs (about 50 PLBs) were separated individually and transferred to 200 ml flasks containing 40 ml of 1/2 strenght NDM liquid medium (Tokuara and Mii 1993) and incubated on a rotatory shaker at 120 rpm under a photoperiod of 16/8 L/D at 25 ± 2 °C. PLBs suspension cultures were supplemented with COL (0.000, 0.025, 0.050 and 0.075% (wt/vol)) and APM (0.00, 1.25 and 2.5 µM). Each treatment was replicated three times. After an incubation period of 3, 10 and 21 days, PLBs were transferred onto fresh antimitotic free NDM medium for 2 months, and subcultured each 2 weeks.

Plants regeneration

To obtain plant regeneration PLBs were transferred from liquid medium to solid MS medium and cultured at 25 ± 2 °C in 16/8 h L/D photoperiod for 6 months and sub-cultured each 4 weeks.

Nuclei isolation and flow cytometry analysis

Flow cytometry (FCM) analyses were performed: (i) on control PLBs at 3, 10 and 28 days of culture; (ii) on PLBs at 28 days after polyploidization treatment, using ten PLBs for each analysis; (iii) on young leaves of regenerated 6-months-old plantlets, by analysing 50 leaves for each treatment. All samples were run in triplicates.

Ploidy analysis on PLBs and DNA content on young leaves (0.5–0.7 cm2) were determined by FCM using Raphanus sativus (2C = 1.1) as standard (Dolezel et al. 2007a). Briefly, fresh tissues, from samples and reference standard, were simultaneously chopped with a sharp scalpel blade in glass Petri dishes containing 500 µl of TRIS-MgCl2 extraction buffer (Pfosser et al. 1995), following the procedure described by Galbraith et al. (1983). After chopping, the suspension was filtered through a 36 µm nylon mesh and stained with 100 µg/ml of propidium iodide and 100 µg/ml RNase. About 2500–5000 nuclei were analysed for each sample using a FACS Vantage SE flow cytometer (Becton Dickinson, San Josè, CA), equipped with an argon-ion laser Innova Coherent 90/5UV, with emission at λ = 514 nm and 200 mW power output. The Vantage SE was provided with a 70 µm flow tip running at 27 psi, using a solution of 50 mM NaCl as the sheath fluid. The data from each sample were collected and analysed using the CellQuest Pro 4.01 software (Becton Dickinson, La Jolla, CA).

Early PLBs ploidy evaluation

To control the trend of polyploidization on PLBs, we detect the endopolyploidy distribution pattern by flow cytometry, according to the procedure described above. The means and the standard deviations of the percentage of the total amount of nuclei in all peaks of the histograms generated by FCM were calculated and analysed. To estimate the polyploidy induction, we used a synthetic index, the cycle value (Barow and Meister 2003), with some little modifications (Chen et al. 2011) as follows:

$${\text{Cycle Value }}={\text{ }}0 \times {{\text{n}}_{{\text{p1}}}}+{\text{ 1}} \times {{\text{n}}_{{\text{p2}}}}+{\text{ 2}} \times {{\text{n}}_{{\text{p3}}}}+{\text{ 3}} \times {{\text{n}}_{{\text{p4}}}} \ldots /{{\text{n}}_{{\text{p1}}}}+{{\text{n}}_{{\text{p2}}}}+{{\text{n}}_{{\text{p3}}}}+{{\text{n}}_{{\text{p4}}}} \ldots$$

where np1, np2, np3, np4 represent the number of nuclei within the corresponding peaks.

Stomata measurement for ploidy evaluation

The stomatal size was measured on control, PDP and TT 6 months old regenerated plantlets. The third newly formed leaf was used as sample tissue. The lower leaf was sprinkled with a mixture of polyvinilic glue and water (1:10 ratio), and incubated for 18 h at room temperature. The dried glue layer was then gently removed and placed on a microscope slide for observations. One hundred stomata per leaf were measured. Stomata were analysed under a Nikon Eclipse TE2000-S inverted microscope, at 200× enlargements. Images were collected using a DXM1200F Nikon camera and analysed by the NIS AR 3.1 software (Nikon Instruments S.p.A., Florence, Italy) and ImageJ v. 1.46 programs (rsbweb.nih.gov/ij/index.html).

LC-HRMS of secondary metabolites

Clonally propagated PLBs, derived from (i) control, (ii) partial duplicated polyploidy (PDP) and (iii) total tetraploid (TT) lines, were used as sources material. The samples were collected 10 months after treatment and at 14 days from the subculture, when the explants were in active growth. About 12 lines were chosen for metabolomic analysis, including the control (one line, identified with the code NT), PDP genotypes (six lines, identified with codes 289, 301, 304, 325, 407, 439) and TT genotypes (five lines, named 428, 441, 442, 450, 452). LC-HRMS analysis of Dendrobium secondary metabolites was performed as previously described (Fasano et al. 2016; Rambla et al. 2016) with minor modifications: 10 mg of freeze-dried, homogenized PLBs powder were extracted with 0.75 ml cold 75% (v/v) methanol, 0.1% (v/v) formic acid, spiked with 5 µg ml−1 formononetin. After shaking for 40 min at 20 Hz using a Mixer Mill 300 (Qiagen), samples were centrifuged for 15 min at 20.000 g at 4 °C; 0.6 ml of supernatant were removed and transferred to HPLC tubes. For each sample, one extraction from four independent pools was performed.

LC-HRMS analyses were carried out using a Q-exactive quadrupole Orbitrap mass spectrometer (ThermoFisher Scientific), operating in positive/negative heated electrospray ionization (HESI), and coupled to an Ultimate HPLC-DAD system (Thermo Fisher Scientific, Waltham, MA). Liquid chromatography was performed using a Phenomenex C18 Luna column (100 × 2.1 mm, 2.5 μm) and the mobile phase was composed of water −0.1% formic acid (A) and acetonitrile −0.1% formic acid (B). The gradient was: 95%A:5%B (0.5 min), a linear gradient to 25%A:75%B over 24 min, 1 min isocratic, before going back to the initial LC conditions in 7 min. 5 μl of each sample were injected, and a flow of 0.25 ml was used throughout the LC runs. All solvents used were LC-MS grade quality (CHROMASOLV® from Sigma-Aldrich). Metabolites were quantified in a relative way by normalization on the internal standard amounts. HESI-MS ionization was performed using the following parameters: sheath and aux gas flow rate at, respectively, 45 and 30 units; vaporizer and capillary temperature at 270 and 30 °C, while discharge current was set at 5 μA and S-lens RF level at 50. The acquisition was carried out in the 110/1600 m/z scan range, with the following parameters: resolution 70,000, microscan 1, AGC target 1e6, maximum injection time 50. Metabolite identification was performed by comparing chromatographic and spectral properties with authentic standards, if available, on literature data, on the basis of the m/z accurate masses, as reported in the Pubchem database (http://pubchem.ncbi.nlm.nih.gov/) for monoisotopic mass identification, or on the Metabolomics Fiehn Lab Mass Spectrometry Adduct Calculator (http://fiehnlab.ucdavis.edu/staff/kind/Metabolomics/MS-Adduct-Calculator/) in the case of adduction detection, and on ms/ms validation.

Statistic and bioinformatics

Statistical analyses were performed on morphological and cytometric data by using the SPSS statistical software (IBM, http://www.ibm.com). ANOVA and Duncan MRT’s were carried out on polyploidization treatment growth rate, cycle value and stomata data. Heatmaps and hierarchical clusterings (HCLs) of metabolite data were performed as previously described (Rambla et al. 2016); metabolite–metabolite correlation matrix was achieved as reported in Diretto et al. (2010).

Results

Cycle Value evaluation on PLBs

Isolated nuclei from 1 month old untreated PLBs hybrid, transferred in liquid medium, were preliminarily screened by FCM to assess the tissue degree of endopolyploidy, and the cell cycle dinamics during tissue culture (Fig. 1). FCM analysis revealed endopolyploidy explants with a cycle value of about 0.4 (Fig. 2). During PLBs growth, the cycle value followed a distribution similar to a Gaussian curve, with a starting value of 0.4, a mode value of 0.76 after 3–6 days and reverting to a value comparable to the baseline situation after 28 days (Fig. 2). This time was chosen to evaluate polyploid induction efficiency.

Fig. 1
figure 1

The “System” operational timeline: from setting up the in vitro polyploidization procedure to the early screening of mutants and LC-HMRS analysis. After single seeds generated PLBs, in vitro polyploidization was attempted and a FCM screening was performed. The entire process for in vitro growth, data validation and metabolite analysis required a year about

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Fig. 2
figure 2

PLBs Cycle Value trend: the trend of endopolyploidization on PLBs during 28 days culturing in liquid medium has shown. The Cycle Value was assessed measuring at four time-points (0–3–10–28 days) with three replicates each

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PLBs polyploidization treatments

PLBs liquid cultures were treated with different concentrations of colchicine (0.000, 0.025, 0.050 and 0.075% (wt/vol)) and APM (0.00, 1.25 and 2.5 µM), and each at three different exposure times (3, 10 and 21 days). After 21 days of treatment, a toxic effect was observed, independently from the antimitotic agent and the concentration used, which resulted in the death of all PLBs. Instead, for the other time of treatment under study, no necrotic tissue was detected, while a different growth rate between control PLBs, that duplicate every 14 days, compared to the treated PLBs was evidenced (Fig. 3). In particular, PLBs treated for 3 days, for all the tested concentrations, showed a growth rate significantly higher than the control, with a stronger effect of 2.5 µM APM for 3 days compared to COL at the same incubation timings.

Fig. 3
figure 3

PLBs growth rate: the growth rates are expressed as PLBs fresh weight (g) after 4–6 weeks of recovery from the polyploidization treatment. The concentration of COL was reported as % while APM was in µM. The starting material was 1 g for each sample. Mean values with different letters are significantly different at p ≤ 0.05

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Early flow cytometric screening for ploidy evaluation

FCM analysis of nuclei isolated from PLBs at 28 days from the antimitotic treatments was performed (Fig. 1) to detect their ploidy level and to define the best conditions for high recovery of polyploids. In Fig. 4, four histograms with several peaks are shown, corresponding to the most effective treatment conditions. Each peak relates to a different level of ploidy and/or to a distinct stage of the cell cycle of the 10 PLBs used for obtaining nuclei suspensions. Even if each histogram showed a similar number of peaks, the distribution of nuclei per peak was changing (Fig. 4a-d). In the 3 days treatment (Fig. 4b, d), peaks 2C, 4C and 8C were those encompassing the greatest number of nuclei, while in the 10 days treatment (Fig. 4c), the highest proportion of nuclei were in the 2C peaks, as for the control (Fig. 4a). Based on our FCM data, the Cycle Value was calculated as a synthetic index of polyploidization efficiency. The response to genome duplication varied significantly with the exposure time and the highest cycle value was assessed for the 3 days treatment, for both antimitotic agents and, in the case of COL, for all the tested concentrations (Table 1).

Fig. 4
figure 4

DNA content and distribution of nuclei after different PLBs polyploidization treatments: FCM analyses were conducted after 28 days from the antimitotic treatment. 2C, 4C, 8C, 16C, 32C represent peaks corresponding to different ploidy level and/or different stages of cell cycle. a Control PLBs. b PLBs treated for 3 days with COL at 0.075%. c PLBs treated with COL at 0.075% for 10 days. d PLBs treated with 2.5 µM APM for 3 days

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Table 1 PLBs polyploidization and FCM characterization of ploidy levels on in vitro explants
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Tetraploid regenerated plantlet assessment

The PLBs derived from COL/APM-treatments and transferred onto solid medium started to differentiate after 12 weeks of culture (Fig. 1). PLBs developed asynchronously, and not all were able to convert to plantlets, as reported in Table 1. The highest number of regenerated plants (152 plantlets) was observed for the 3 days APM treatment followed by 3 days colchicine treatment (92 plantlets).

To confirm the polyploid nature of regenerate plants and to endorse the predictive power of cycle value as an index of polyploidization, 6-month-old plantlets, regenerated from treated and untreated PLBs, were analysed via flow cytometry (Fig. 1). The percentage of polyploid plantlets obtained for each treatment is presented in Table 1. A positive correlation was found between Cycle Value and polyploid recovery: in particular, the sample showing a cycle value > 1.00 after antimitotic treatment at 28 days yielded the highest percentage of polyploids. By using COL at a concentration of 0.025 and 0.075% for 3 days, a high percentage of polyploids, equal to 60 and 80%, respectively, was obtained. A lower percentage, up to 20% (Table 1), was achieved in all the other samples, except for treatment 0.050% COL for 3 days, which did not produce any polyploid. In addition, although the 3 days treatment was effective in polyploids induction, it also rised a high percentage of partially duplicated polyploids (PDP, Fig. 5), showing a 4C DNA content, lower than expected (4C = 4.4 pg), and ranging from 3.9 to 4.3 pg. Regarding APM, only the 2.5 µM treatment for 3 days was successful in generating polyploids, with a percentage of 55% but without PDP plantlet recovery (Table 1).

Fig. 5
figure 5

Flow cytometry histograms of nuclear DNA content of 6-months-old plants of Dendrobium regenerated from treated PLBs: a analysis of diploid samples from untreated plantlets, b histogram corresponding to PDP plantlets, c tetraploid plantlets. Empty peaks correspond to the internal standard Raphanus sativus (STD), while solid peaks represent the Dendrobium samples. For STD, the first peak corresponds to the G1 phase and the second one to the G2 phase, respectively

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Stomata analysis for ploidy evaluation

Length and number of stomata were evaluated both in control, PDP and TT plants and the results are shown in Table 2. The average length and density of stomata from TT leaves were significantly different compared to diploids but similar to PDP plants (Table 2; Fig. 6). The stomata length was higher in the TT (16.14 ± 1.1 µm) and PDP plants (15.86 ± 0.74 µM) respect to control plantlets while the stomata density was higher in the control plants (55.3 ± 0.45/mm2).

Fig. 6
figure 6

Stomatal size of 6-months-old diploid and polyploid plants. a diploid, b PDP and c tetraploids plants. Scale bar 10 µm.

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Table 2 Measurements of stomatal characteristics on leaves from control, PDP and TT explants of D. phalaenopsis × D. loddigesii
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LC-HESI-MS of secondary metabolites

We measured, by LC-HRMS and in PLBs at 48 weeks from the beginning (Fig. 1), the levels of 23 secondary metabolites, including two alkaloids (shihunidine and shihunine), 12 bibenzyl derivatives/phenanthrenes (batatasin III, crepidatuol B, 9,10-dihydrophenanthrene-2,4,7-triol, gigantol, hircinol, loddigesiinol A-B, moscatilin, moscatilin diacetate, moscatin, rotundatin, tristin), 2 lignans (lirioresinol B and pinoresinol), 7 other polyphenols (Cyanidin 3-(2G-galloylrutinoside), loddigesiinol C-D-G-H-I-J). Metabolites were quantified in a relative way, by through the normalization on the internal standard amounts (for more details, see materials and methods), and the complete dataset is shown in Supplemental Table 1. Overall, we observed fluctuations in all the metabolites under investigation in at least one PDP or TT polyploid over the control. To evaluate metabolic remodeling post-polyploidization, we used HCL visualization, applied both on columns (genotypes) and rows (metabolites) (Fig. 7). No consistent trends were found about the metabolic class with some exceptions in the group of the bibenzyl derivatives/phenanthrenes (moscatin/rotundatin; hircinol/batatasin III; loddigesiinol A-moscatilin-tristin) and of polyphenols (loddigesiinol D/J; loddigesiinol G/H). On the contrary, HCL applied on the columns revealed a common attitude of the total polyploids to cluster together and with the control, while partial polyploids, with the exception of line 304, placed on the right side of the HCL (Fig. 7). With the purpose to more clearly investigating polyploidization-derived alterations, we normalized metabolite data on the diploid genotype and exploited a heatmap visualization (Fig. 8; Supplemental Table 2). In most of the cases, independent PDP/TT polyploids displayed distinct metabolite accumulation compared to the control, thus suggesting a more stochastic base underlying the biochemical phenotypes. In this context, exceptions were represented by tristin and shihunidine, which resulted, respectively, down- and over-accumulated in the TT polyploids; and loddigesiinol C-D and moscatilin, and hircinol, exhibiting lower contents, the first two metabolites, and higher amount, the latter, over the control. Furthermore, the majority of the changes were of negative sign. In few cases, high-value secondary metabolites resulted over-accumulated in most of the PDP or TT polyploids: for instance, batatasin III, and hircinol, or loddigesiinol I, and shihunidine, whose levels were higher in, respectively, most of the PDP and in all the TT genotypes. Interestingly, some health-related metabolites resulted specifically over-represented in one or few polyploids: crepidatuol B (TT genotypes 428 and 441), loddigesiinol G (TT genotypes 452 and PDP genotypes 304) and loddigesiinol J (TT genotypes 441 and PDP genotypes 301 and 439); cyanidin 3-(2G-galloylrutinoside) in TT lines 441, 442 and PDP lines 304; moscatilin diacetate (TT lines 452 and PDP lines 289 and 304) and moscatin (TT lines 428, 441, 442, 452, and PDP lines 304). Since several detected metabolites took place in the same metabolic departments (e.g. alkaloids, phenylpropanoids etc), we used Pearson correlation analysis and metabolite–metabolite matrix representation to verify the presence of metabolic coordination events: anyhow, as evidenced in Supplemental Table 3, we could not identify clear areas of positive or negative correlation, confirming the stochastic origin of these events.

Fig. 7
figure 7

Hierarchical clustering of Dendrobium secondary metabolites. Gradual hues of red colored squares represent the relative values of a metabolite with respect to the internal standard. Gray squares indicate no detectable accumulation of the corresponding metabolite. Hierarchical clustering was calculated both on columns and rows, applying the Pearson correlation coefficient with the average linkage algorithm. (Color figure online)

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Fig. 8
figure 8

Heatmap plot of Dendrobium secondary metabolites. Colored squares represent the values of log2-transformed fold changes of a metabolite with respect to the control (NT not treated), according to the color scale shown (Blue: down-accumulated; Red: over-accumulated). Gray squares indicate no detectable accumulation of the corresponding metabolite. (Color figure online)

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Discussion

There is a general agreement that polyploidization plays an important role in plants breeding (Dhooghe et al. 2011; Sattler et al. 2016). Dendrobium orchids do not except to this circumstance (Hossain 2013), and favourable characteristics as the increase of flower size (Griesbach 2002; Tang and Chen 2007), stress resistence (Xu et al. 2016) and useful secondary metabolites production (Lavania 2005; Lavania et al. 2012) have been reported as linked to ploidy changes.

During in vitro polyploidization experiments, the choice of the antimitotic agents, the concentration used and the duration of treatment, are critical parameters to gain good results, which have also been reported to be highly genotype-dependent (Dhooghe et al. 2011). Colchicine and oryzalin are the most widely used antimitotic agents for polyploid induction in the plants (Sattler et al. 2016), while APM is scarcely utilized, despite its greater affinity with the plant microtubules and relative lower toxicity in respect to COL (Melchinger et al. 2016; Khosravi et al. 2008). In this work, the effect of APM was tested for the first time on orchid PLBs and it was compared with the most used COL. Our results showed a lower APM inhibition of PLBs yield, growth and plantlets conversion rate PLBs, compared to COL, especially for the treatment at 2.5 µM for 3 days, which also gave one of the largest amount of polyploids. Possibly, the cells located on the PLBs surface were more affected by COL higher concentration and toxicity, which caused a lower plantlets regeneration rate rather than PLBs whole death (Acanda et al. 2015). Our observations reported a stimulatory effect for the 3 days treatment for both used APM and COL, in comparison to the growth rate of control PLBs. These results are in agreement with previous works reporting that, for short exposures to the antimitotic agent, the growth rate of the treated explants is greater than for the control (Thao et al. 2003). To witness more the main relevance of the exposure timing and the type of antimitotic agents, we report that the highest conversion rate of PLBs to plantlet and the largest total amount of regenerated plants has been found for the 3 days APM treatments after 6 months culturing, at all the tested concentrations.

In vitro ploidy can be effectively assessed by classic chromosome counting and/or flow cytometry (Ochatt et al. 2011), last one being a rapid, sample sparing and reliable method to measure DNA content, thus allowing the analysis of a large number of explants in a short period (Dolezel et al. 2007b; Ochatt 2008). During our research, we have tried to perform classic cytogenetic analyses on Dendrobium hybrid explants, but the difficult explants and the very small sizes of chromosomes (less than 1 µm for the smallest ones, data not shown) prevented us to use this approach also. Therefore, FCM was the technique of choose for DNA content evaluation, as reviewed by Dolezel et al. (2007b) and confirmed by our stomatal analysis.

The flow cytometry analysis of ploidy has been previously reported in Dendrobium wild species and hybrids (Jones and Kuehnle 1998; Galdiano et al. 2014; Teixeira da Silva et al. 2014), and was also used to detect tetraploid recovery, after polyploidization treatments, although it has been usually applied to regenerated plants and not to PLBs (Sarathum et al. 2010; Atichart and Bunnag 2007; Atichart 2013). Here FCM analysis was conducted to achieve three different goals: (1) on untreated PLBs, to assess the native level of ploidy of the explant and the trend of endopolyploid during tissue culture; (2) on PLBs liquid culture, to monitor the trend of polyploidization after PLBs initial treatments; (3) on regenerated plantlets, to finally detect the ploidy level.

In Dendrobium orchids the recovery of tetraploids depends on a much greater extent on treatment duration than the concentration of antimitotic agent (Griesbach 1981; Sarathum et al. 2010; Miguel and Leonhardt 2011). In this context, preliminary FCM analyses, conducted to estimate the Cycle Value index on untreated PLBs can guide to set up an effective experimental protocol for polyploidization. Many species and hybrids of Dendrobium, have been reported to display a different degree of endopolyploidy with a distinct tissue- and organ-specificity (Chen et al. 2011). In agreement with previous paper (Chen et al. 2009), our FCM analysis on Dendrobium hybrid PLBs confirmed the endopolyploid nature of the explants. The estimates of cycle value on untreated PLBs (Barow and Meister 2003) allowed us to assess the optimal timing for treatments, and time-course FCM analyses showed an exponential increase of the cycle value between 0 and 6 days, with a maximum between day 3 and day 6, after explants sub-culturing. Since the main target of polyploidization are cycling G2 cells, this means that, between day 3 and day 6, PLBs explants are best suited for our APM and COL treatments. Based on this observations, we could also define the optimum duration treatments to get the highest amount of polyploids which is of about 3–4 days, as confirmed by our ploidy evaluation results.

In the present study, the Cycle Value for diploid was scored at 0.4, while after the polyploidization treatments the Cycle Value went up to more than 1; we have found that treatments with a cycle value ≥ 1 ± 0.1 were those effective and statistically significant to generate tetraploids, assessing positive correlation between cycle value and polyploids recovery. These data show that the Cycle Value can be successfully applied for the determination of the polyploidization efficiency.

As regards the treated regenerate plantlets, FCM analysis was performed to confirm the cycle value clue and the effective regeneration of polyploid plants. The classes of ploidy levels were assessed and the corresponding DNA content histograms, based on fluorescence intensity, were generated. Interestingly, some samples showed a DNA content which was smaller than 4C, indicating they were incomplete tetraploids or PDP. In recent years, several studies have demonstrated that the loss of DNA, or genome downsizing, is a common feature in polyploids (Leitch and Bennett 2004). Also in orchid natural polyploids and allopolyploids, this phenomenon has been described (Bory et al. 2008; Travnicek et al. 2011, 2015). Moreover, in the Orchidaceae family, progressively partially endoreduplication (PPE) was observed (Bory et al. 2008; Travnicek et al. 2015; Hribova et al. 2016); early experiment with orchid PLBs, in fact, indicate differential amplification in AT- and GC-rich regions (Nagl 1972; Schweizer and Nagl 1976). In PPE orchid explants, the ratio of FCM consecutive peaks, were less than 2 and ranged from 1.43 to 1.89 (Bory et al. 2008; Travnicek et al. 2011, 2015). Also for our Dendrobium hybrid PLBs, the ratio between 2C and 4C peaks was about 1.85. The PPE mechanism was recently investigated (Hribova et al. 2016), and the authors claimed that the partial endoreduplication probably started because the cells enter into a modified S-phase, during which some parts of the genome are not replicated. From Illumina sequence data (Hribova et al. 2016), it was found that the DNA losses were due to the presence/absence of repetitive sequences: in particular, a reduction in the amount of tandem repetitive sequences was observed in PPE nuclei. This observation implies also that the chromosome number among PPE and standard explants is the same. In our results, we obtained a high number of PDP polyploids, that might have been generated from PPE nuclei. Overall, these data seem confirming the hypothesis that the polyploidization events partially takes origin from the PLBs nuclei that were in a PPE state. In agreement with our FCM analysis, each PDP plantlet has a proper value of DNA content, thus confirming that the lack of repetitive sequence is sometimes erratic and generated by random errors during the DNA duplication process (Hribova et al. 2016). Taking into consideration this finding, each PDP plant could be considered as a unique from a genetic point of view. Khosravi et al. (2009) already reported a genetic variability, ranging from 6 to 26% between tetraploids and mother plants after COL treatments, as assessed by RAPD analysis.

Thus, considering the PDPs like a complete tetraploid, the 3 days treatment in 0.075% colchicine was the most efficient one, with a high recovery of polyploids plants (up to 80%) which outperforms results from previous polyploidization experiments (Sarathum et al. 2010). By using APM, we obtained both a high yield of tetraploids (up to 55%) and a good regeneration plant rate, proving its suitability for in vitro polyploidization in orchids. Noteworthy, all APM treatments did not rised PDP plantlets: a possible explanation for could be its higher affinity for plant microtubules (Dhooghe et al. 2011) than COL, which is known to produce chromosomal damage and alteration, DNA loss and abnormal growth (Luckett 1989). Despite the high polyploids recovery with a 3 days APM treatment, the cycle value was not such high like in the case of the COL treatment, suggesting that the lower toxicity of APM could determine a faster recovery of explants from the antimitotic treatment, as was shown by its higher growth rate, which could be even double if compared to control and colchicine treated explants. The higher values of COL concentration were more efficient in obtaining polyploids than the 0.050%, which yielded a very lower percentage of polyploids recovery, despite the great cycle value reported after 28 days. This phenomenon is still under investigation but it is in agreement with previous remarks in Dendrobium (Saranthum et al. 2010) and do not breach our observation about correlation between a high cycle value and a higher number of regenerated polyploids on 28 days materials after treatment.

A classical parameter for distinguishing diploid and polyploid plants, other than FCM, is stomata measurement, as was reported in Phalaenopsis species (Chen et al. 2009) and Dendrobium orchids (Atichart and Bunnag 2007). Analysing stomatal morphometric data, no significant differences in size as well as density between TT and PDP plants were highlighted, although both were significantly different from diploids hybrids.

FCM analysis demonstrate its superior discrimination power for: (i) defining best timings and duration of antimitotic agents treatment; (ii) early screening of interesting material; (iii) judging the effective polyploid nature of regenerated plantlets and fine-tuning for the presence of PDP genotypes.

Induced-polyploidization has also been broadly used to investigate the molecular basis underlying the “genomic shock” following chromosome set doubling (Levy and Feldman 2004; Fasano et al. 2016), as well to induce accumulation of valuable secondary metabolites (Banyai et al. 2010; Mishra et al. 2010; Xing et al. 2011). In this context, we evaluated the accumulation of 23 secondary compounds involved in the alkaloid, phenolic, particularly bibenzyl derivatives/phenanthrenes, and lignan metabolisms. A large set of negative and positive variations was found, either in TT as well in PDP polyploids; despite these changes, it was not possible to evidence, with few exceptions, consistent metabolic trends within Dendrobium TT polyploids. Additionally, in our growth conditions, most of the listed alterations resulted in decreased metabolite contents. Anyhow, generation of total and/or partial polyploids can also be considered as a powerful tool to increase genetic variability and causing potential metabolic changes. In the view of this aspect, several polyploid genotypes of interest, accumulating higher amounts of valuable compounds were found; for instance, two effective natural antiplateles, moscatilin diacetate and moscatin (Chen et al. 1994), whose levels were enhanced respectively in three and five polyploids genotypes, and the alkaloid shihunidine, which has been shown to own Na+/K+ATPase inhibitor activity (Li et al. 1991), which resulted over-accumulated in all the total polyploids. Further analysis with optimization of culture conditions (only on promising lines), could potentially led to an over-accumulation of interesting metabolites (Yang et al. 2015). In this context, our screening system could be very useful to exploit the potentiality of PLBs liquid cultures in bioreactors (Gao et al. 2014), and to resolve the lengthy manual handling of in vitro culturing. This will in turn, decrease the production costs (Chen 2016) and positively impact on the generation of bioactive-based products, without exploiting and endangering wild resources, since PLBs explants exhibited a metabolite production comparable to the one of the adult plants (Zha et al. 2007).

Our work highlights the power of FCM analysis for the in vitro manipulation of orchids. Here we present (Fig. 1) a screening system that simplify in vitro protocol optimization and cell cycle study removing main limiting aspects for ploidy manipulation in D. loddigesii. Overall, 15 different treatment conditions to obtain polyploids were tested and one month after the polyploidization treatments, we could identify the most suited procedure to yield polyploid plantlets. By using the positive correlation existing between cycle value and polyploidization, we selected the best treatments generating polyploidy explants, and this made possible to discard the 2/3 (about 65%) of the PLBs not of interest. Finally, several Dendrobium polyploids over-producing some secondary metabolite with valuable properties (like shihunidine and hircinol) have been identified and are now proposed to a further characterization.

Our data support a new strategy for screening of polyploidization in orchids since an early monitoring on PLBs shows a consistent correlation to a high yield of polyploid explants and regenerated plants after 6 months culturing, thus reducing costs and efforts to introduce new genetic variability and interesting features in Dendrobium.