Modeling and optimizing plant growth regulators for in vitro culture and antioxidant activity of Thymus daenensis

doi:10.21203/rs.3.rs-4338496/v1

Denaian thyme, also known as Thymus daenensis (Lamiaceae), is an endangered and endemic medicinal plant in Iran. It is commonly utilized in traditional remedy for its antioxidant, immunomodulatory, and insecticidal effects. The aerial parts of this plant include a variety of bioactive compounds. for instance, flavonoid, phenolic acids, and high levels of terpenoids. until now, wild plants are the primary source of these compounds. However, if harvesting methods are not altered soon, they may become endangered. Alternative production methods for medicinal plants using tissue culture are gaining more interest. no protocol for in vitro culture of T. daenensis has been reported so far. To address this, we carried out a study to investigate the impact of various auxins and cytokinins, both in isolation and in combination, on cell growth, development, and secondary metabolite accumulation. The objective was to assess how certain factors affect the accumulation of phenolic compounds and biomass growth in T. daenensis tissue culture. The response surface methodology modeling outcomes have shown that the use of plant growth regulators (PGRs) and their combinations significantly impacts the in vitro culture of T. daenensis. g plots summarized results showing that the best accumulation of biomass and secondary metabolites can be achieved by using 1-Naphthaleneacetic acid (NAA) followed by 2,4-Dichlorophenoxyacetic acid (2-4-D). Optimizing the induction of secondary metabolites and large-scale biomass production could greatly benefit this species.

In vitro

Medicinal plants

Phytochemicals

R software

Response surface methodology

Secondary metabolite

The demand for medicinal plants as consumable products is increasing in the pharmaceutical industry nowadays [1]. Due to their high concentration of essential oils, the mint (Lamiaceae) family is the largest family of herbs used in pharmaceuticals [2]. Thyme, as a member of this family, is noteworthy for its high levels of volatile oils and phenolic compounds in Iran and other regions [3].

The phenolic monoterpenoids thymol and carvacrol are the main examples of thymus species secondary metabolites that have distinguished radical scavenging and antimicrobial activity [4]. Additionally, the radical scavenging ability of thyme extracts is significantly influenced by the phenolic acids rosmarinic acid and cinnamic acid, as well as the flavonoids luteolin and apigenin [5]. These substances also play significant roles in postponing the onset of cancer and chronic inflammation [6]. Therefore, the beneficial effects of thyme and other plant spices in which they occur are due to these compounds. as known, the biosynthesis of phenolic acids, flavonoids, and volatile oils is promoted by biotic and abiotic factors, including plant growth regulators (PGRs) [7].

T. daenensis, one of the mint family, is an endangered and endemic species that grows in the Zagros mountains of Iran. In Iranian tradition, the aerial parts of this plant are used for culinary purposes, such as spice and herbal tea, as well as for medicinal use to treat digestive issues and inflammation [8].

Plant tissue culture techniques can provide a sustainable system for the accumulation of secondary metabolites with various benefits, even though limited marketable successes have been achieved to date [9, 10]. Challenges in achieving consistent commercial yields with in vitro plant culture systems are primarily attributed to low and variable production of secondary metabolites. Some secondary metabolites do not produce in undifferentiated cells in significant amounts. In these cases, In vitro cell cultures require overexpression of related genes among biosynthesis pathways for bulk production, which is currently unrealistic due to a lack of knowledge about biosynthesis pathways [11]. Regarding this, plant in vitro culture is a valuable tool for studying secondary metabolism regulation and producing plant cells under controlled conditions. This helps to reduce the variations that typically occur in field plantings. Another advantage is that it provides for an extensive number of experiments to be conducted in a relatively small space. for instance, Plant in vitro culture has proven to be a valuable tool in studying phenolic biosynthesis. Although in vitro cultured cells cannot always demonstrate a similar secondary metabolite (SM) profile to that of their parents, they can be utilized to identify the biosynthetic genes and discover the mechanisms that regulate these genes.

In order to achieve success with plant tissue culture, it is necessary to use appropriate nutrient media, which should be optimized for each specific plant or organ. Furthermore, natural physiological variations and varying growth requirements among plant species necessitate the optimization of protocols for individual species.

The existence of PGRs in culture media is one of the most significant factors affecting cell proliferation, differentiation, and Plant‑made pharmaceuticals accumulation. according to earlier investigations, radical scavenging activity in plant in vitro cultures was significantly influenced by the type and concentration of PGRs utilized [12].

Optimization of PGRs type and dosage can be regarded as an effective and simple way for encouraging the efficiency of cell in vitro culture in case of phenolics [13]. in the case of phenolics, optimization of PGR type and dosage can be seen as an efficient and effective method to promote the productivity of cell in vitro culture [14, 15]. though, sometimes the accumulation of active molecules in cultured tissues is not related to the induction of cell division. as a result, sometimes it might be challenging to select experimental media that give both high doses of desirable components and acceptable biomass yields [16]. In this manner, by using response surface methodology (RSM), it is possible to predict how changes in these factors will impact plant growth and optimize experimental conditions accordingly. An RSM model can study multiple plant growth regulators simultaneously, predicting optimal doses. Then, optimize media based on plant response [17].

In this study, researchers estimated the effect of some PGRs to identify optimal in vitro culture conditions for T. daenensis. RSM models were used to visualize PGR reactions and interactions with the surface in order to increase plant biomass. In the same time, Plant tissues obtained in various growing media were simultaneously extracted for phenolic components and antioxidant activity. Afterwards, the spectrophotometric analysis was used to detect the total phenolics content and radical scavenging activity in the plant material.

Therefore, it was possible to select protocols that produced a high content of the desired plant‑made pharmaceuticals as well as a suitable biomass yield. This approach demonstrates the advantages of short-term production of SM, leading to massive SM accumulation and biomass yield in cultures. Using a similar approach, it can also be used for endangered plant species or protected area bio-networks.

2.1. Plant materials

Seeds of Thymus daenensis were purchased from Pakan bazr (a local seed company), Esfahan, Iran.

2.2. Chemicals

The following plant growth regulators (PGRs) were purchased from Merck (Darmstadt, Germany): Indole-3-acetic acid (IAA), 2,4-Dichlorophenoxyacetic acid (2-4-D), Indole-3-butyric acid (IBA), 1-Naphthaleneacetic Acid (NAA), 6-Benzylaminopurine (BA) and Kinetin (KIN). Additionally, 2,2-diphenyl-1-picrylhydrazil (DPPH), Folin– Ciocalteu reagent, and gallic acid (GAE) were obtained from the Sigma Chemical Co. (USA).

2.3. Seed germination and surface sterilization

The seeds were subjected to a 5-hour cleaning process using running tap water to eliminate any loose dirt. Subsequently, they underwent surface sterilization by immersing them in NaOCl (20% V/V, 5 min), followed by 10 rinses with purified water. The aseptic seed explants were then cultivated on T Murashige and F Skoog [18] (MS) medium supplemented with 3.0% sucrose and 8 g l^− 1 agar for germination.

2.4. Explant preparation

Cotyledon leaves of 10-day old seedlings were isolated and sterilized to culture on MS medium [18] supplemented with 3.0% sucrose, 8 g l^− 1 agar and different PGRs. The pH of the medium was adjusted to 5.6–5.8 using 1N sodium hydroxide and hydrochloric acid before adding agar. The prepared medium was sterilized by autoclaving at 121°C and 1.2 kgf.cm^− 2 pressure for 15 minutes. This was carried out based on the MS medium formula.

2.5. Impact of single PGR on explants development

Several different culture media were utilized in order to enhance the in vitro culture of T. daenensis. In the first set of research, single-growth regulator treatments were tested: 4 auxins 2, 4-D, IBA, NAA and IAA and 2 Cytokinin (BA and Kin) ranging from 0.5 mg l^− 1 – 4 mg l^− 1 for the purposes of callus growth and development. For these tests, five inoculums were put in petri dishes with four replicates each. calluses also were cultured in a hormone-free medium as a control.

2.6. Effect of PGRs combination on explants development

According to results with single phytohormones, the combined effects of auxin–cytokinin PGRs were investigated using factorial experimental designs for callusing and SM accumulation purposes. The solid mediums are the same than those described for the single PGRs studies.

2.7. Cultural conditions

The plant cells used for the single and combination phytohormone studies were kept at a temperature of 25 ± 2°C, with a 16-hour photoperiod provided by white fluorescent light (40 µ mol m^− 2 s^− 1) and a relative humidity of 55–60%. The explants were sub cultured 3 times at 4 weeks intervals.

2.8. Morphological analysis

Calluses were harvested from MS culture media and weighed for wet weight and dry weight (40°C). Water content was calculated using the next equation:

$\text{w}\text{a}\text{t}\text{e}\text{r} \text{c}\text{o}\text{n}\text{t}\text{e}\text{n}\text{t}=\frac{\text{F}\text{r}\text{e}\text{s}\text{h} \text{w}\text{e}\text{i}\text{g}\text{h}\text{t} – \text{D}\text{r}\text{y} \text{w}\text{e}\text{i}\text{g}\text{h}\text{t}}{\text{F}\text{r}\text{e}\text{s}\text{h} \text{w}\text{e}\text{i}\text{g}\text{h}\text{t}}$ × 100

Furthermore, the rate of callus induction was determined by applying the following formula:

$$\text{C}\text{a}\text{l}\text{l}\text{u}\text{s}\text{e}\text{s} \text{i}\text{n}\text{d}\text{u}\text{c}\text{t}\text{i}\text{o}\text{n} \text{r}\text{a}\text{t}\text{e}=\frac{\text{n}\text{u}\text{m}\text{b}\text{e}\text{r} \text{o}\text{f} \text{i}\text{n}\text{d}\text{u}\text{c}\text{e}\text{d} \text{c}\text{a}\text{l}\text{l}\text{u}\text{s}}{\text{n}\text{u}\text{m}\text{b}\text{e}\text{r} \text{o}\text{f} \text{i}\text{n}\text{c}\text{u}\text{b}\text{a}\text{t}\text{e}\text{d} \text{e}\text{x}\text{p}\text{l}\text{a}\text{n}\text{t}\text{s}} \times 100$$

2.9. Phytochemical analysis

2.9.1. Callus extract

Briefly, callus powder (0.1 g) was sonicated with methanol (80%; 1 ml) for 20 min (500 W, 40 C). The supernatant was used for phytochemical studies.

2.9.2. Total phenolic compounds

The Folin & Ciocalteu assay [19] was employed to calculate the total phenol content (TPC) of extracts. In this method, 100 µl of the extract was mixed with Folin- Ciocalteu reagent (1 ml) and distilled water (2 ml), followed by neutralization with sodium carbonate (20%, W/V) after 3 min. For color development, the mixture was vortexed (15 s) and let to stand at 40°C for 30 min. The absorbance of the mixture was then recorded at 765 nm using Shimadzu UV-1800 UV/Vis Spectrometer Double. As control a blank contain of aqueous methanol (80%) was used instead of sample extracts. The quantification of TPC in the extracts was carried out using the gallic acid standard curve. TPC content was determined in mg GAE g DW^− 1 using the equation Y = 0.0026X, where y represents absorbance.

2.9.3. DPPH (1, 1-diphenyl-2-picrylhydrazyl) free radical-scavenging assay

The antioxidant activity of callus methanol extract (80%) was evaluated by testing its ability to scavenge the free radical DPPH ((Sigma–Aldrich, Munich, Germany), as per M Burits and F Bucar [20]. The test involved adding callus extracts to a 0.2 mM DPPH reagent methanol solution, followed by incubation for 1 hour. The absorbance of the reaction mixtures was measured at 517 nm against a blank to determine the decrease in the intensity of the purple color. DPPH free radical inhibition percentage (IC (%)) was calculated according to next equation:

IC (%) = [(A_blank – A_sample) / A_blank] × 100

At the shown formula, A sample and A blank refer to the absorbance values of the plant extract sample and blank, respectively.

2.10. Data Analysis

The results were expressed as means ± SD. R studio [21] was used for G plot analysis, while Excel 2016 and Design Expert V.13 (Demo) were used for response surface methodology modeling (RSM).

2.11. Statistical modelization

Following the application of PGR combinations, we utilized RSM modeling methods by Design Expert V.13 (Demo) software to analyze the resulting data. Our software meticulously selected the most optimal models for each respective pair and proceeded to process the input data accordingly, as equations represented in Table 1. Our primary objective was to ascertain the degree to which PGR combinations influence callus induction percentage, WW, TPC, and DPPH activity.

3.1. Influence of single PGRs

In the first step, researches were started with PGRs alone at various doses (0.5, 1, 2, 3, and 4 µg ml^− 1) added to the MS medium to understand their effect on T. daenesis cells regeneration and differentiation (Fig. 1). In vitro culture descriptions, biomass calculations, TPC and DPPH activity were recorded after 3 subcultures (4 weeks each) (Table 1). Upon conducting observations, it was revealed that the application of PGRs had varied effects on the treated explants. The utilization of 2-4-D and NAA resulted in the formation of callus, with the rate of induction increasing up to a certain point as the concentration rise. In contrast, BA application prompted the development of shoots, and the number of shoots grew with the applied concentration. In the case of IBA and IAA treatments, root induction was promoted in the treated explants. Notably, the percentage of root induction remained constant across all concentrations used in these treatments.

use of 2-4-D had a negative impact on induced callus weight as its dosage increased. Conversely, for other tested PGRs, the induced weight initially increased up to a certain dose and then decreased. The treated PGRs were also observed to have an effect on TPC and DPPH activity. The results indicated that as the concentration of IAA, IBA, and NAA PGRs increased, the content of TPC and DPPH activity decreased. However, in the case of BA-treated explants, the content initially increased up to a certain dose and then decreased. Finally, it is worth noting that there was no significant difference in the concentration of 2-4-D (Table 1).

Table 1

Effect of single PGRs on morphological and phytochemical analysis of *T. daenensis* callus derived from *in vitro* culture.
PGRs	Treat	Effect	Callus%	WW (gr)	Water	TPC mg	DPPH (0.1 g DW)
2-4-D	0.5	Callus	20.00 ± 0.0^c	0.29 ± 0.05^a	0.39 ± 0.05^a	12.90 ± 2.2^a	20.39 ± 2.2^a
	1	Callus	95.00 ± 1.2^a	0.29 ± 0.07^a	0.42 ± 0.03^a	13.74 ± 1.3^a	18.82 ± 2.79^a
	2	Callus	100.00 ± 0.0^a	0.13 ± 0.10^b	0.23 ± 0.02^b	14.83 ± 3.07^a	21 ± 2.2^a
	3	Callus	80.00 ± 16.3^b	0.04 ± 0.01^c	0.11 ± 0.01^c	11.02 ± 2.1^a	18 ± 1.7^a
	4	Callus	80.00 ± 0.0^b	0.04 ± 0.02^c	0.10 ± 0.03^c	11.73 ± 1.5^a	18 ± 2.8^a
BA	0.5	Shoot	5.00 ± 1.2 ^b	0.56 ± 0.18^c	1.63 ± 0.04^b	10 ± 0.2^b	29.90 ± 3.34^c
	1	Shoot	5.00 ± 1.6^b	0.8 ± 0.05^c	2.59 ± 0.06^b	10.21 ± 0.6^b	37.98 ± 2.5^bc
	2	Shoot	20.00 ± 2^a	5.14 ± 0.08^a	4.80 ± 0.13^a	14.87 ± 1.03^a	45.00 ± 2.26^b
	3	Shoot	20.00 ± 2.1^a	2.1 ± 0.01^b	2.36 ± 0.29^b	15.59 ± 1.59^a	64.95 ± 1.61^a
	4	Shoot	20.00 ± 2.3^a	0.6 ± 0.02^c	0.67 ± 0.19^c	16.70 ± 0.48^a	18.07 ± 0.09^d
IAA	0.5	Root	70.00 ± 9.15^a	0.12 ± 0.03^d	0.99 ± 0.14^b	14.43 ± 2.67^a	32.37 ± 0.53^a
	1	Root	75.00 ± 7.86^a	0.22 ± 0.10^c	1.91 ± 0.21^a	12.52 ± 0.54^a	33.20 ± 0.92^a
	2	Root	80.00 ± 6.51^a	0.46 ± 0.10^b	1.63 ± 0.51^a	11.81 ± 1.19^a	34.19 ± 1.72^a
	3	Root	75.00 ± 9.15^a	0.98 ± 0.23^a	1.5 ± 0.28^a	5.30 ± 0.61^b	35.33 ± 2.81^a
	4	Root	75.00 ± 5.82^a	0.41 ± 0.07^b	1.32 ± 0.53^ab	4.07 ± 0.79^b	30.34 ± 1.19^a
IBA	0.5	Root	60.00 ± 1.55^b	0.18 ± 0.02^b	0.64 ± 0.29^c	16.08 ± 1.93^a	28.01 ± 2.43^a
	1	Root	60.00 ± 3.20^b	1.27 ± 0.36^a	1.76 ± 0.52^a	15.07 ± 1.65^a	23.78 ± 2.3^ab
	2	Root	80.00 ± 2.03^a	2.36 ± 0.51^a	2.24 ± 0.16^a	7.64 ± 0.29^b	20.12 ± 2.78^ab
	3	Root	80.00 ± 4.16^a	1.6 ± 0.22^a	1.25 ± 0.19^b	6.19 ± 0.05^b	23.43 ± 1.2^ab
	4	Root	80.00 ± 0.40^a	1.4 ± 0.28^a	0.85 ± 0.24^c	4.47 ± 1.13^b	17.73 ± 0.53^b
NAA	0.5	Callus	50.00 ± 1.55^b	1.19 ± 0.54^b	0.68 ± 0.40^d	17.09 ± 0.53^a	36.56 ± 3.2^a
	1	Callus	50.00 ± 1.33^b	1.4 ± 1.13^b	0.95 ± 0.04^d	14.60 ± 1.87^ab	38.44 ± 4.1^a
	2	Callus	80.00 ± 2.82^a	1.84 ± 1.44^ab	1.49 ± 0.03^c	10.26 ± 1.76^b	39.24 ± 5.48^a
	3	Callus	80.00 ± 1.30^a	2.56 ± 0.77^a	5.18 ± 0.24^b	1.94 ± 0.30^c	32 ± 1.36^a
	4	Callus	80.00 ± 6.33^a	2.73 ± 0.92^a	7.30 ± 0.24^a	2.15 ± 0.21^c	17 ± 1.42^b

Where, DPPH = DPPH Free Radical Scavenging Activity, TPC = Total Phenolic Content, Callus = Callus Percentage, WW = Wet Weight, Water = Water Content Percentage, PGR = Plant Growth Regulator, 2-4-D = 2,4-Dichlorophenoxyacetic acid, NAA = 1-Naphthaleneacetic acid, IAA = Indole-3-acetic acid, IBA = Indole-3-butyric acid, BA = 6-Benzylaminopurine, KIN = Kinetin.

Obtained results indicated that the use of PGR- free medium (control sample) caused necrosis in cultured explants. These findings approve that hormonal treatment is required to maintain cellular activity. Normally, callus induction and growth in most plants requires the utilize of both auxin and cytokinin in the growing medium. These PGRs relate positively or negatively and can have pleiotropic influences (Table 1). In the case of T. daenensis, NAA and 2-4-D, as auxins, directed to the maximum variability of total biomass respectively. Also, current research showed that KIN (0.5- 4 µg ml^− 1), a cytokinin, was ineffective for change induction in T. daenaensis explants, requiring additional concentrations. Z Bakhtiar, MH Mirjalili and A Sonboli [22] as well reported that auxins induce callus, either in lack or abundance of cytokinin’s, and are required for callus induction.

Some PGRs specified a yellowish- brown callus within 12 weeks that might be associated to higher doses of PGRs and accumulation of phenolic content (Fig. 1). Moreover, our findings approved that TPC and antioxidant activity of the light green calluses was low indicating that PGR addition to the MS medium as well seems to be important for phenolic and antioxidant compounds production by T. daenensis cells (Table 1). certainly, plant growth regulators and other elicitors have been reported as secondary metabolites regulators in cultured plants and as appropriate factors to increase plant cells regeneration and to rise phenolic compounds and antioxidant activity [23, 24].

3.2. Influence of PGRs in combination

During the second phase of our research, we utilized a potent combination of auxin-cytokinin and auxin-auxin to evaluate the influence of PGRs on the reaction, physical characteristics, and secondary metabolite content of cultured explants grown in vitro. To gain a deeper understanding of this topic, we utilized RSM modeling to analyze the combination effects of PGRs.

Fit statics and ANOVA analysis for the response surface modeling

The obtained data was used by the software to determine the best modeling for analysis, as seen in Table 2. Analysis of BA × 2-4-D couples showed significant impact on callus induction rate, TPC, and DPPH, but no significant change on WW. Conversely, NAA × 2-4-D couples had no impact on callus induction rate but significantly affected WW, TPC, and DPPH. NAA × BA couples effectively regulated WW content and DPPH activity. Notably, KIN × NAA and KIN × 2-4-D couples did not have significant effects (Table 2).

Table 2

Fit statics and ANOVA analysis for the response surface modeling for optimization of callus induction percentage, wet weight, DPPH free radical scavenging activity and total phenolic content of T. *daenensis* callus. Where, DPPH = DPPH Free Radical Scavenging Activity, TPC = Total Phenolic Content, Callus = Callus Percentage, WW = Wet Weight, Water = Water Content Percentage, PGR = Plant Growth Regulator, 2-4-D = 2,4-Dichlorophenoxyacetic acid, NAA = 1-Naphthaleneacetic acid, IAA = Indole-3-acetic acid, IBA = Indole-3-butyric acid, BA = 6-Benzylaminopurine, KIN = Kinetin.
PGRs	Y		Selected model	Mean	SD	R²	Adjusted R²	F- value	P- value
BA × 2-4-D	WW	Quadratic	WW = 0.200793 + -0.000138637 * A + 0.0297874 * B + -0.175145 * AB -0.421799 * A² -0.0963839 * B² -0.0763829 * A²B -0.022082 * AB² -0.0252727 * A³ -0.00255218 * B³ + 0.162672 * A²B² + 0.156531 * A³B + 0.055379 * AB³ + 0.261537 * A⁴ -0.0341214 * B⁴	0.075	0.055	0.73	0.37	2.03	0.132	n. s
	Callus%	Quadratic	Callus% = 57.5761 + 0.154516 * A + -10.4068 * B + -10.0742 * AB + 14.6524 * A² + -23.9484 * B²	53.33	15.17	0.53	0.41	4.40	0.0079	Significant
	DPPH	Cubic	DPPH = 46.3348–47.9807 * A -6.56872 * B + 1.83646 * AB + 11.035 * A² -6.22252 * B² -10.1851 * A²B -9.54346 * AB² + 64.7052 * A³ -4.11591 * B³	51.06	14.59	0.735	0.577	4.64	0.0045	significant
	TPC	Cubic	TPC = 2.99113–4.6833 * A -0.779947 * B + 0.538449 * AB + 0.379568 * A² -0.0232844 * B² -1.22368 * A²B -0.768582 * AB² + 4.58537 * A³ + 0.45707 * B³	3.46	1.59	0.63	0.42	2.96	0.0308	significant
NAA × 2-4-D	WW	Linear	WW = 0.0482451 -0.0315 * A -0.0496402 * B	0.055	0.054	0.41	0.36	7.79	0.0028	significant
	Callus%	Quadratic	Callus%= 66.1557–6.37859 * A + 1.26784 * B -2.80471 * AB + 9.98603 * A² -0.947165 * B²	71.48	10.70	0.32	0.14	1.82	0.15	n. s
	DPPH	Quadratic	DPPH = 51.6697 + 7.14533 * A -1.54277 * B + 17.8667 * AB + 18.0188 * A² -26.7849 * B²	46.56	15.24	0.61	0.51	6.04	0.0017	significant
	TPC	Quadratic	TPC = 9.50891 + 0.541377 * A + -0.627907 * B + 0.771437 * AB + 0.28687 * A² + -4.84717 * B²	7.05	2.48	0.48	0.34	3.52	0.020	significant
NAA × BA	WW	Linear	WW = 0.021061 + 0.00597561 * A + 0.00640244 * B	0.02	0.007	0.42	0.37	8.23	0.0022	Significant
	Callus%	Cubic	Callus% = 32.5735–29.9586 * A + 10.8428 * B + 4.39615 * AB + 7.79583 * A² + 6.98898 * B² + 5.11417 * A²B + 2.70551 * AB² + 27.5932 * A³ -17.6616 * B³	41.33	20.70	0.25	− 0.195	0.56	0.80	n. s
	DPPH	Cubic	DPPH = 61.3645 + -5.74177 * A + -20.4148 * B + -14.3741 * AB + 5.19091 * A² -13.7653 * B² + 12.4414 * A²B + 1.65958 * AB² -18.5828 * A³ + 13.6993 * B³	58.47	10.53	0.83	0.73	8.27	0.0002	significant
	TPC	Quadratic	TPC = 4.02545 + -0.409362 * A -0.541149 * B + -0.958666 * AB + 0.0416461 * A² -1.39279 * B²	3.37	1.78	0.23	0.034	1.17	0.36	n. s
KIN × NAA	WW	Cubic	WW = 0.0127359 − 0.0040303 * A + 0.0188636 * B + 0.00359734 * AB -0.00808326 * A² + 0.0239447 * B² -0.0318964 * A²B -0.0542239 * AB² + 0.0227147 * A³ -0.0275067 * B³	0.02	0.002	0.99	0.93	16.22	0.19	n. s
	Callus%	Cubic	Callus%= 41.3032–12.0549 * A + 2.23767 * B + 1.36943 * AB -39.3479 * A² + 52.7492 * B² -118.781 * A²B -22.0133 * AB² + 1.96045 * A³ + 97.7702 * B³	47.87	5.35	0.989	0.88	9.36	0.24	n. s
	DPPH	Cubic	DPPH = 57.7977 + -16.9247 * A -50.3574 * B -15.0421 * AB + -38.6557 * A² + 21.4309 * B² + -102.454 * A²B + 124.616 * AB² + -61.738 * A³ + 203.85 * B³	53.63	11.58	0.95	0.59	2.60	0.449	n. s
	TPC	Cubic	TPC = 6.44111–2.47631 * A -3.07972 * B -2.61656 * AB -5.39344 * A² + 3.54077 * B² -17.1076 * A²B + 12.6995 * AB² -8.21382 * A³ + 22.2018 * B³	6.24	1.04	0.97	0.79	5.37	0.32	n. s
KIN × 2-4-D	WW	Quadratic	WW = 0.01769 -0.00533327 * A -0.00550702 * B -0.000865638 * AB -0.0129978 * A² + 0.0179657 * B²	0.02	0.005	0.72	0.27	1.6	0.37	n. s
	Callus%	Linear	Callus%= 44.5433–11.1187 * A -10.5323 * B	47.47	8.72	0.55	0.40	3.67	0.09	n. s
	DPPH	Quadratic	DPPH = 70.0895 + 0.762138 * A + 0.541808 * B -27.2035 * AB + -41.5034 * A² -8.5383 * B²	50.84	6.76	0.85	0.60	3.46	0.167	n. s
	TPC	Linear	TPC = 5.3584 + 0.88473 * A + 0.608328 * B	5.15	0.85	0.39	0.19	1.99	0.22	n. s

Callus morphological properties

The calluses' macroscopic observations were studied: based on culture media, calluses revealed high morphological differences. With the (NAA × BA, 2-4-D × KIN and NAA × KIN) combinations, a dark brown watery callus was reported. Greenish and brownish nodular calluses induced by (2-4-D; NAA and 2-4-D and BA) couple (Fig. 2). These structural studies indicate cellular heterogeneity among calluses induced by various hormonal treatments. These monitoring, connected with calluses secondary metabolite analysis, simplified to choose the best hormonal treatments for maximum TPC and antioxidant activity. Moreover, induced nodular calluses have been better choices for propagation purposes.

BA × 2-4-D couples

The modeling analysis revealed that the application of BA × 2-4-D couples significantly impacted callus induction percentage, TPC, and DPPH activity. However, their effect on inducing WW content was found to be insignificant. The obtained models indicated that sample treatments involving a combination of BA in the range of 1.2–2.6 µg ml^− 1 and 2-4-D in the range of 1.2–3.3 µg ml^− 1 induced maximum callus induction rate. The amount of TPC and DPPH radical scavenging activity was found to be at the lowest in this range (Fig. 3).

NAA × 2-4-D couples

Based on the modeling results for the combination of NAA and 2-4-D, it was found that these two substances had a significant impact on wet weight content, TPC, and DPPH activity (Fig. 4). However, it did not have a significant effect on the callus induction rate. The models suggest that lower concentrations of both NAA (0.5–1.9 µg ml^− 1) and 2-4-D (0.5–1.2 µg ml^− 1) lead to maximum wet weight. Gradually increasing the concentration of PGRs resulted in a decrease in WW content. The suggested models for TPC and DPPH activity indicated that all concentrations of NAA had the same impact. When combined with 2-4-D at 1.2–2.6 µg ml^− 1, it induced maximum content.

BA × NAA couples

modelling results revealed that the combination of BA × NAA had a significant effect on WW and DPPH activity (Fig. 5). However, changes were not significant with regards to callus induction rate and TPC. It was observed that the WW content gradually increased with an increase in NAA and BA doses. The highest WW content was obtained when treated with 4 µg ml^− 1 NAA and 4 µg ml^− 1 BA. The DPPH activity, on the other hand, decreased as the NAA dosage increased. The maximum content was achieved at 0.5 µg ml^− 1 of NAA in combination with 1.5 up to 4 µg ml^− 1 of BA, according to the DPPH model.

Current research involves modeling and optimizing T. daenesis in vitro culture through the use of an RSM analysis. This methodology has already proven successful in optimizing the in vitro culture of select plant species [17, 25, 26]. RSM offers two distinct advantages over traditional factorial analysis: firstly, it calculates the effects of independent variables between actual experimental data points [27], and secondly, it enables the inclusion of more than five experimental variables, which is not feasible with a normal factorial design. Our findings suggest that the use of RSM can be potentially beneficial for optimizing in vitro culture and in vitro SM production in the future. However, it is important to note that a thorough understanding of the complex reactions of PGRs is necessary to achieve successful outcomes. These findings have the potential to make significant contributions to the field and may be of interest to researchers alike.

In this study, we compared the outcomes of individual and in combination PGR treatments by R software package (g plot) (Fig. 6 and Table 3). Based on the analysis of the g plot, it appears that using NAA singularly in the culture medium is the ideal way to achieve the highest possible wet weight yield, secondary metabolite (SM) accumulation, and callus induction. The best results were observed in cells treated with NAA doses of 3 µg ml^− 1 and 4 µg ml^− 1, respectively. However, all NAA doses (ranging from 0.5 µg ml^− 1 to 4 µg ml^− 1) were found to be effective in achieving optimal outcomes. The next best group was cells treated with 2-4-D, followed by cells treated with BA at a dose of 4 µg ml^− 1 plus 2-4-D at doses of 0.5, 1, and 2 µg ml^− 1. Among combination treatments, these couples were found to be the most effective option.

Auxins play a significant role in promoting various growth processes in plants such as root induction, cell division, differentiation, and elongation, in addition to their well-known function of promoting dominance [28, 29]. Given the potent auxin effects of NAA and 2-4-D, it was expected that these treatments would result in high callus induction rates and growth.

Table 3

Information of used data for g plot analysis
Numbering	Treat 1	Treat 2	Numbering	Treat 1	Treat 2	Numbering	Treat 1	Treat 2	Numbering	Treat 1	Treat 2	Numbering	Treat	Treat
	BA	2-4-D		NAA	2-4-D		NAA	BA		KIN	NAA	100	2-4-D	4.0
1	.5	.5	26	0.5	0.5	51	0.5	0.5	76	0.5	10	101	NAA	.5
2		1.0	27		1.0	52		1.0	77	2.0	2.0	102	NAA	1.0
3		2.0	28		2.0	53		2.0	78		4.0	103	NAA	2.0
4		3.0	29		3.0	54		3	79		8.0	104	NAA	3.0
5		4.0	30		4.0	55		4.0	80	4.0	2.0	105	NAA	4.0
6	1.0	0.5	31	1.0	.5	56	1.0	.5	81		4.0
7		1.0	32		1.0	57		1	82		8.0
8		2	33		2.0	58		2.0	83	8.0	2.0
9		3.0	34		3.0	59		3	84		4.0
10		4	35		4.0	60		4.0	85		8.0
11	2.0	.5	36	2.0	0.5	61	2.0	.5	86	10.0	.5
12		1	37		1.0	62		1.0		KIN	2-4-D
13		2.0	38		2.0	63		2.0	87	0.5	10
14		3	39		3	64		3.0	88	2.0	2.0
15		4.0	40		4.0	65		4.0	89		4.0
16	3.0	0.5	41	3.0	.5	66	3.0	.5	90		8.0
17		1.0	42		1.0	67		1.0	91	4.0	2.0
18		2	43		2.0	68		2.0	92	4.0	4.0
19		3.0	44		3.0	69		3.0	93	8.0	4.0
20		4	45		4.0	70		4.0	94	8.0	8.0
21	4.0	.5	46	4.0	.5	71	4.0	.5	95	10.0	.5
22		1	47		1	72		1.0	96	2-4-D	.5
23		2.0	48		2.0	73		2.0	97	2-4-D	1.0
24		3	49		3.0	74		3	98	2-4-D	2.0
25		4.0	50		4.0	75		4.0	99	2-4-D	3

Where, 2-4-D = 2,4-Dichlorophenoxyacetic acid, NAA = 1-Naphthaleneacetic acid, IAA = Indole-3-acetic acid, IBA = Indole-3-butyric acid, BA = 6-Benzylaminopurine, KIN = Kinetin.

According to the our results (PGRs in combination), all parameters were observed to decrease as the concentration of BA increased in cells treated with BA + 2-4-D. Cytokinins are plant growth regulators that are essential in the process of bud formation and in governing the differentiation and division of cells [28]. It has been established that cytokinins can reduce plant height and apical dominance. This aligns with the findings of this study, which suggests a decrease in these parameters with an increase in BA doses. Plant growth regulators (PGRs) such as cytokinins and auxins are frequently combined to encourage plant growth and regeneration [30]. It's important to recognize that the effectiveness of PGRs and their combinations in promoting growth or eliciting a specific response can differ depending on the species and circumstances. As noted by LA Colombo, AMd Assis, RTd Faria and SR Roberto [31], the utilization of PGRs and their combinations in in vitro culture is closely tied to the plant's natural hormone levels.

This report presents the first study on the optimization of plant growth regulators (PGRs) in Thymus daenensis, both individually and in combination. Although the effect of PGRs on Thymus vulgaris has been previously investigated, this study provides novel insights into T. daenensis. Prior research on T. vulgaris showed that 5 µM of BA stimulated the maximum shoot growth rate, while 1, 5, and 10 µM doses of IAA increased rooting frequency up to 100% [32]. Moreover, among the BA, kinetin (KIN), zeatin (ZEA), and IAA treatments, 1.0 µM of IAA was found to be the most effective in increasing essential oil content, particularly thymol. Another study found that 0.05 mg L^− 1 of 2-4-D induced the highest rooting rate in both T. vulgaris and T. longicaulis [33].

Callus growth is achieved through coordinated cell elongation and division, which are influenced by the presence of auxin and cytokinin [34, 35]. In contrast, the production of phenolic compounds is dependent on the activation of complex secondary metabolism pathways. Despite the existence of a considerable amount of literature on the optimization of plant growth media, there is currently no definitive concentration of PGRs that can guarantee the formation of various secondary metabolites in species. It is widely accepted that plant growth and differentiation occur under optimal conditions, while the accumulation of secondary metabolites tends to favor suboptimal conditions. Various stress factors, such as mechanical damage, toxic compound accumulation, and nutrient hunger, stimulate secondary metabolism in a species-specific manner [36]. While there has been research on the genes associated with essential oil composition in T. vulgaris and T. daenensis and their response to abiotic stresses, [37, 38] there remains a need for more in-depth analysis, particularly through microarray techniques. A detailed examination of the complex pathways involved in secondary metabolism is also necessary.

Current research designed to optimize cell growth and regeneration and enhance the phenolic content and radical scavenging activity of T. daenensis tissue cultures. We have demonstrated that the application of PGRs is necessary for the viability of calluses and the production of TPC in this context. Analysis also showed that to achieve satisfactory phenolic compounds and biomass yield, various factors must be considered: PGR types, quantities, and their relationships. This optimization should be done for each plant species since the effects of PGRs vary depending on the nature of the plant. By utilizing a factorial design and an RSM modelling approach to determine PGR doses and associations, it has been found that the application of NAA alone 3 µM resulted in a desired callus biomass yield of T. daenensis, which exhibited an optimum antioxidant activity and total phenolic content. IBA and IAA had a significant positive effect on root induction while negatively reduced TPC and antioxidant activity among the independent variables.

PGRs Plant growth regulators

2-4-D 2,4-Dichlorophenoxyacetic acid

NAA 1-Naphthaleneacetic acid

SM Secondary metabolite

RSM Response surface methodology

IAA Indole-3-acetic acid

IBA Indole-3-butyric acid

BA 6-Benzylaminopurine

KIN Kinetin

DPPH 2,2-diphenyl-1-picrylhydrazil

GAE gallic acid

medium

TPC total phenol content

Acknowledgements

Not applicable.

Author contributions

Saba Samadi: conducted and designed the experiment, analyzed the data using Design Expert V.13, R and SPSS software, and wrote the manuscript.

Funding

This research did not receive any funding.

Data availability

The corresponding author can provide the datasets used and analyzed in this study upon request, provided that the request is reasonable.

Ethics approval and consent to participate

In the current study, all methods are based on relevant international guidelines and legislation.

Consent for publication

Not applicable.

Competing interests

The author declares no competing interests

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No competing interests reported.

Modeling and optimizing plant growth regulators for in vitro culture and antioxidant activity of Thymus daenensis

Status:

Version 1

Abstract

Figures

1. Introduction

2. Materials and Methods