Introduction

An interdisciplinary field of research on low temperature non-equilibrium plasma, also termed cold plasma (CP) and electromagnetic field (EMF) applications for agriculture1,2 is directed towards exploiting the potential of plant functional plasticity. Seed treatment with CP or EMF is a modern eco-agricultural technology for increasing plant agricultural performance. Numerous studies have demonstrated that such treatments are effective for enhancing agronomic seed quality and have potential to be used for seed decontamination, activation of germination and seedling growth.

The majority of studies in this area are focused on assessment of CP and EMF effects on physiological (germination), structural (changes in seed coat surface) and morphometric (early seedling growth) estimates (reviewed by3,4,5). A few reports have also considered changes in biochemical characteristics, such as amount of pigments and secondary metabolites, enzymatic activities or antioxidative capacity6,7,8,9,10,11,12. Stressor-induced changes in physiological or biochemical activities are associated with selective modulation of protein expression in the growing seedling, e.g., activation of photosynthesis is expected to be related to changes in the leaf proteome13,14. Although several studies described morphological, genotoxic or biochemical changes induced by the CP and EMF treatments14,15,16,17,18,19, the proteomic profiles of plant response to CP and EMF treatments have not been reported so far.

On the other hand, although germination tests are commonly used as a hallmark of the response to treatments, until now there has been no attempt to estimate CP and EMF effects on the content of seed phytohormones, which are known to be key regulators of germinationMeasurement of seed germination and seedling morphological parameters

Germination tests were started four days after the treatment both in vitro and in the substrate. For germination test in vitro seeds were evenly distributed on three layers of filter paper in 13.5 mm diameter plastic Petri dishes (three replicates of 30 seeds each) and watered with 6 mL distilled water. Petri dishes with seeds were placed in a climatic chamber KK 750 (Pol-Eko-Aparatura, Poland) with automatic control of moisture (60%), light, and temperature. Alternating light and temperature regimes were maintained in the chamber (darkness: 14 °C for 8 h; light: 21 °C for 16 h). Seeds were provided with additional water in a Petri dish, if necessary, to prevent drying. Germinated seeds (judged by the appearance of a visible 1-mm radicle) were counted daily until their number stopped increasing. For the germination tests in the substrate, the seeds were sown into plastic containers (12 × 18 × 30 cm) filled with peat substrate, placing the seeds in 0.5 cm depth from the substrate surface. Germination tests were replicated three times for all experimental conditions including control seeds (3 × 30 seeds, n = 30 for one replicate). Germinated seeds were counted daily as judged by the appearance of the top of green sprout from the surface of the substrate.

The germination results of each experimental replicate were analyzed using the application of Richards’ function66 for the analysis of germinating seed population67. The indices of germination kinetics derived from Richards plots were: Vi (%) – final germination percentage indicating seed viability, Me (days) – median germination time (t50%) indicating the germination halftime of a seed lot or germination rate67.

The containers with grown seedlings were kept for 2 weeks in the climatic chamber with constant humidity (60%) and alternating light and temperature regimes (darkness: 14 °C for 8 h; light: 21 °C for 16 h). For morphometric analysis seedlings were carefully removed from containers, their roots washed to remove the substrate and wiped well with a moisture absorbent paper. Fresh weight and length of all seedlings and their parts (roots, shoots and leaves) was estimated.

Phytohormone extraction from seeds and detection by HPLC analysis

For the extraction of plant hormones 1 g of seeds was ground and extracted in 5 mL of 85% methanol for 24 hours at 4 °C. The homogenate was centrifuged at 13500 × g for 5 min, the supernatant was collected and kept at −80 °C until HPLC analysis. Extractions were performed in triplicates.

Seed extracts were treated and analysed by a modified method of Bendokas et al.68 Plant hormones were separated and quantified using high performance liquid chromatography (HPLC). Agilent 1200 series HPLC system (Agilent Technologies Inc., USA) with a diode array detector and a reversed phase column (Spherisorb ODS2, 4 × 125 mm, Waters Corporation, USA) were used. Quaternary solvent (A 50% methanol, B 50% methanol, 1.2% acetic acid, C water, D methanol) gradient elution was used as follows: initial conditions 10% B, 60% C; 10.5 min 50% B, 15.75 min 50% B; 23 min 40% B, 60% D, 30 min 40% B, 60% D, and 32 min 10% B, 60% C. Gibberellins (GA3 and GA7) and ABA were detected at a wavelength of 254 nm, while auxins (IAA and IBA), Z and SA − at 280 nm. Peak positions of analytes were identified by the retention time, peak spiking and spectral properties. Hormone concentrations were valued via a linear regression equation of standard calibration curves. The analyses were performed in triplicate and the results were presented as mean ± standard error of mean.

Sunflower seedling proteome analysis using two-dimensional electrophoresis

Seedlings grown from the control and vacuum, CP and EMF treated seeds were maintained in a climatic chamber as described above and the analysis was performed after 2 weeks of cultivation. Four and three biological repeats of protein samples from shoots and roots, respectively were prepared using phenol extraction and ammonium acetate precipitation, as described previously69. Internal standards were prepared from a pooled mixture of all protein extracts. Protein separation and detection was performed using a differential gel electrophoresis procedure as described previously70. Sample aliquots of 50 µg were labeled with Cy3 and Cy5 fluorescent dyes, and the internal standard was labeled with Cy2 dye (Lumiprobe, USA). For the preparative gel, 500 µg of unlabeled internal standard was mixed with 50 µg of Cy2 labeled internal standard. Isoelectric focusing was performed on 24 cm IPG strips with a linear gradient of pH 4–7 using Ettan IPGphor (GE Healthcare, USA). Further, the proteins were separated on 1-mm thick 10–16% polyacrylamide gradient gels using Ettan DALTsix (GE Healthcare, USA). Gels were scanned using a fluorescence scanner FLA 9000 (GE Healthcare, USA). Relative protein quantification was performed using DeCyder 2-D Differential Analysis Software, v.7.0 (GE Healthcare, USA).

Preparative gel was fixed in 50% methanol and 10% acetic acid. Protein spots were excised manually and subjected to protein digestion with trypsin, according to a method described previously71. Protein digests were loaded and desalted on a 100 μm × 20 mm Acclaim PepMap C18 trap column and separated on a 75 μm × 150 mm Acclaim PepMap C18 column using an Ultimate3000 RSLC system (Thermo-Scientific, USA), coupled to a Maxis G4 Q-TOF mass spectrometer detector with a Captive Spray nano-electrospray ionization source (Bruker Daltonics, Germany). Peptide identification was performed using the MASCOT server (Matrix Science, USA) against Helianthus annuus L., genome database v.1.025. Threshold value for the identification of proteins was a Mascot score of >50 and at least 2 peptides.

Blast2GO software72 was used for the annotation and gene ontology analysis of the protein sequences identified with the NCBI Protein database. The obtained GO terms were summarized using the REVIGO server73, the A. thaliana database and the SimRel semantic similarity method with the level set at 0.7 value. A. thaliana homologues of the identified proteins were obtained by a search against TAIR10 gene models using the BLAST tool at the Sunflower Genome Database (https://sunflowergenome.org/blast/) and interactions were assessed using the String database with default settings74.

Statistical data analysis

The Biological Variation Analysis module of the DeCyder software was used to match protein spots in biological repeats across different gels and ANOVA analysis was used to identify statistically significant (p ≤ 0.01) differences in protein abundance. Additionally, a threshold value of at least a 1.5-fold difference in protein abundance was used. Since CP treatments require application of a vacuum, the effect of CP treatment was compared to control and vacuum treated experimental groups.

Means of various parameters between the control and treatment groups were compared using Student’s t-tests for independent samples, as there was no reason for comparing different conditions of affected groups. The differences were considered to be statistically significant at p ≤ 0.05. The number of measured seeds or plants in the control and treatment groups varied from 17–24 (analysis of morphometric parameters) to 30 (germination tests and estimation of phytohormones content) for one replicate. Data are presented as means of 3 independent experiments ± standard error of mean.