Promoting Anthocyanin Biosynthesis in Purple Lettuce through Sucrose Supplementation under Nitrogen Limitation

Abstract

Although nitrogen deficiency and sucrose are linked to anthocyanin synthesis, the potential role of sucrose in regulating anthocyanin biosynthesis under low nitrogen conditions (LN) in purple lettuce (Lactuca sativa L.) remains unclear. We found that adding exogenous sucrose enhanced anthocyanin biosynthesis but significantly inhibited lettuce growth at high concentrations. Optimal results were obtained using 1 mmol/L sucrose in a low-nitrogen nutrient solution (LN + T1). Chlorophyll fluorescence imaging indicated that the addition of exogenous sucrose induced mild stress. Meanwhile, the activities of antioxidant enzymes (SOD, CAT, and POD) and antioxidant capacity were both enhanced. The mild stress activated the antioxidant system, thereby promoting the accumulation of anthocyanins induced by exogenous sucrose. LN + T1 (low nitrogen nutrient solution supplemented with 1 mmol/L sucrose) up-regulated enzyme genes in the biosynthetic pathway of anthocyanins, including phenylalanine ammonia-lyase (PAL), chalcone synthase (CHS), dihydroflavonol reductase (DFR), flavanone 3-hydroxylase (F3H), flavonoid 3′-hydroxylase (F3′H), flavone synthase II (FNSII), and anthocyanidin synthase (ANS). Additionally, various transcription factors such as AP2/ERF, MYB, bHLH, C2H2, NAC, C2C2, HB, MADS, bZIP, and WRKY were found to be up-regulated. This study elucidates the regulatory mechanism of anthocyanin metabolism in response to the addition of exogenous sucrose under low nitrogen conditions and provides a nutrient solution formula to enhance anthocyanin content in modern, high-quality agricultural cultivation.

1. Introduction

In recent years, based on epidemiological studies, humans have become more aware of the health benefits that phytochemicals provide [1,2]. Purple lettuce (Lactuca sativa L.) is one of the most widely consumed vegetables due to its high nutritional value [3,4]. Purple lettuce is notably abundant in anthocyanins, along with a comprehensive array of total phenols and flavonoids, which are prevalent secondary metabolites within the plant kingdom. Anthocyanins, which belong to the most prominent group of flavonoids, are crucial plant pigments responsible for the vibrant purple, pink, red, and blue hues observed in various plants [5,6]. Anthocyanins are powerful antioxidants that can help remove free radicals and protect cells from oxidative damage, thereby helping to prevent chronic diseases and promote health [7]. Therefore, exploring agricultural cultivation practices that promote the accumulation of anthocyanins in vegetables would greatly benefit human health.

The biosynthesis of anthocyanins in plants is primarily regulated by a set of structural genes in in the anthocyanin biosynthetic pathway [8]. Anthocyanin biosynthesis occurs through the phenylpropanoid pathway, where phenylalanine ammonia-lyase (PAL) facilitates the deamination of phenylalanine to produce precursor compounds [9]. The subsequent structural genes involved in this process encompass chalcone synthase (CHS), chalcone isomerase (CHI), flavanone 3-hydroxylase (F3H), and anthocyanidin synthase (ANS) [10]. A variety of environmental elements, such as light [11,12,13], drought [14,15], phytohormone [16], temperature [17,18], and nutrition [19,20], have been identified to play a role in enhancing the biosynthesis of anthocyanins. Among these, several studies have indicated that nitrogen deficiency can lead to increased anthocyanin content in various plant tissues [21,22,23,24]. The phenolic content in lettuce was negatively correlated with nitrogen supply levels [25]. When the nitrogen content decreased to a certain threshold, the leaves of Malus spectabilis transitioned from green to red, accompanied by an elevation in anthocyanin accumulation [26]. Nitrogen deficiency can lead to increased anthocyanin content in various plant tissues by upregulating the expression of specific MYB and bHLH transcription factors [27]. An interesting phenomenon worth noting is that plants grown under low nitrogen conditions often exhibit higher sucrose production [28,29]. Therefore, there may be a certain association between low nitrogen and sucrose in enhancing anthocyanin biosynthesis. Sucrose plays a pivotal role in signaling and modulating various processes throughout the plant life cycle, encompassing critical functions such as photosynthesis, nutrient mobilization, and allocation [30]. In addition, sucrose has traditionally been considered the metabolic resource needed for carbon skeleton construction and energy supply in plants [31]. The effect of sucrose on anthocyanin gene expression is specific to Arabidopsis [32]. Anthocyanin accumulation involves crosstalk between sucrose and plant hormone signaling pathways, where sucrose-mediated signals play a pivotal role in regulating plant development and responses to stress [33,34]. Several studies have found that exogenous sucrose and the accumulation of endogenous sugar have been shown to increase the expression of anthocyanin biosynthesis genes [35,36,37]. In conclusion, sucrose may influence the regulation of anthocyanin accumulation under low nitrogen conditions. However, the mechanisms mediating anthocyanin biosynthesis in lettuce remain poorly understood. Therefore, the potential mechanisms of sucrose-regulating low-nitrogen-induced anthocyanins in purple lettuce need to be further elucidated.

Our experimental design was aimed at investigating the effects of exogenous sucrose in both normal and low-nitrogen nutrient solutions on anthocyanin synthesis in purple lettuce (Lactuca sativa L.). Transcriptome sequencing, chlorophyll fluorescence imaging of the lettuce canopy, and leaf biochemical properties were characterized. We anticipate that exogenous sucrose may play a significant role in regulating low nitrogen conditions and promoting anthocyanin accumulation in lettuce. We offer new insights into the regulatory mechanisms governing anthocyanin metabolism in response to exogenous sucrose added to a low-nitrogen nutrient solution.

2. Materials and Methods

2.1. Plant Material and Growth Conditions

We used purple lettuce (Lactuca sativa, ‘Purple Ruffles’) as plant material. Purple lettuce seeds were obtained from the China Vegetable Seed Industry (Beijing) Co., Ltd. (Beijing, China) and subsequently germinated in complete darkness at a controlled temperature of 22.5 °C and a relative humidity of 60%. The seeds germinated under dark conditions at a temperature of 22.5 °C and 60% relative humidity. The three-day-old seedlings were transplanted into planting sponge for planting and were grown for 7 days under white light (30 μmol·m⁻²·s⁻¹). Lettuces showing consistent growth and true leaves were transferred to a hydroponic tank and irrigated with a modified Hoagland nutrient solution (EC = 1.4 dSm⁻¹, pH = 6.5) for 14 days. Subsequently, they were transferred to a low-nitrogen nutrient solution supplemented with exogenous sucrose for 5 days. Afterward, they were harvested and subjected to testing. The normal nitrogen nutrient solution was characterized by the following concentrations: Ca(NO₃)₂ at 945 mg/L, KCl at 200 mg/L, KH₂PO₄ at 250 mg/L, MgSO₄ at 493 mg/L, H₃BO₃ at 2.86 mg/L, MnSO₄·4H₂O at 2.13 mg/L, ZnSO₄·7H₂O at 0.22 mg/L, CuSO₄·5H₂O at 0.08 mg/L, (NH₄)₆MO₇O₂₄·4H₂O at 0.02 mg/L, and Na₂ [Fe(EDTA)] at 20 mg/L. The low nitrogen nutrient solution differed from the normal solution primarily in the concentration of Ca(NO₃)₂, which was at 189 mg/L, and also included CaCl₂ at 756 mg/L. All other components were consistent with those in the normal solution. The addition of exogenous sucrose (T) was implemented across three gradients: T1 at 1 mmol/L, T2 at 3 mmol/L, and T3 at 5 mmol/L. The intelligent artificial climate chamber was manufactured by the Ningbo Jiangnan Instrument Factory (Ningbo, China). The environmental indicators of the artificial climate chamber are day temperature (22.5 ± 1) °C, night temperature (16 ± 1) °C, air relative humidity 50–60%, white light (200 μmol·m⁻²·s⁻¹), and photoperiod of 16 h·d⁻¹.

The experimental groups were as follows:

• CK: Normal nitrogen nutrient solution without the addition of sucrose.
• LN: Low nitrogen nutrient solution without the addition of sucrose.
• LN + T1: Nitrogen deficiency nutrient solution supplemented with 1 mmol/L sucrose.
• LN + T2: Nitrogen deficiency nutrient solution supplemented with 3 mmol/L sucrose.
• LN + T3: Nitrogen deficiency nutrient solution supplemented with 5 mmol/L sucrose.
• CK + T1: Normal nitrogen nutrient solution supplemented with 1 mmol/L sucrose.
• CK + T2: Normal nitrogen nutrient solution supplemented with 3 mmol/L sucrose.
• CK + T3: Normal nitrogen nutrient solution supplemented with 5 mmol/L sucrose.

2.2. Plant Growth Characteristics

Leaf area, leaf length, and leaf width of lettuce leaves were measured using the leaf area detecting instrument (Yaxin-1242, Beijing, China). The fresh mass measurement of lettuce leaves started with the removal of the roots, leaving only the leaf blades. Subsequently, the lettuce leaves were weighed using an electronic balance (ME104E, Freiburg, Switzerland) accurate to 1/10,000. The average value was calculated from three replicates and recorded as the fresh mass.

2.3. Plant Biochemical Characteristic

The total anthocyanin content was determined using the pH differential method [38]. Leaves (0.3 g) were homogenized in 1 mL of 0.1 mol/L citric acid and then centrifuged at 6500 rpm for 10 min. Furthermore, 100 μL aliquot of the liquid supernatant was incubated in a water bath at 40 °C for 20 min, and absorbance was measured at 530 nm and 700 nm. Next, 900 μL of 0.025 mol/L KCl was added, followed by adding 100 μL of the liquid supernatant and 900 μL CH₃CO₂Na 3H₂O. The mixture was incubated in a water bath at 40 °C for 20 min, and absorbance was measured at 530 nm and 700 nm. The content of anthocyanins was calculated using the formula: ΔA×V ÷ (ϵ × d) × M × F × 10⁶ ÷ W, where ΔA represents the absorbance, V represents the volume of the extraction solution in milliliters (mL), ϵ represents the molar extinction coefficient of anthocyanins, d represents the path length of the cuvette (1 cm), M represents the molar mass of anthocyanins, F represents the dilution factor, and W represents the sample mass in grams (g).

The content of total phenolic compounds was measured according to the colorimetric method described earlier [39]. Under alkaline conditions, phenolic substances reduce tungstate molybdic acid to produce blue compounds. Leaves (0.1 g) were homogenized in 2 mL of 60% ethyl alcohol and subjected to shake extraction at 60 °C for 2 h at 8000 rpm. Subsequently, the mixture was centrifuged at 25 °C for 10 min. Approximately 50 μL of the sample was added to 250 μL of undiluted Folin–Ciocalteu phenol reagent. The mixture was mixed at 25 °C and allowed to stand for 2 min. Then, 250 μL of 20% (w/v) aqueous Na₂CO₃ was added, followed by adding 700 μL H₂O. Absorbance was measured at 760 nm. The standard gallic acid was diluted to various concentrations to replace the supernatant of the sample using the same procedure, and a standard curve was constructed based on the obtained results. The results were expressed as milligrams per gram of dry weight.

The total flavonoid content was estimated according to the colorimetric method [40]. Leaves (0.1 g) were placed in 70% ethanol and subjected to sonication for 45 min at 35 °C. Subsequently, 1 mL of this solution was mixed with 5 mL of H₂O in a 25 mL tube. Then, 1 mL of 5% (w/v) sodium nitrite (NaNO₂) was added to the reaction mixture and allowed to stand at 25 °C for 6 min. Next, 1 mL of 10% (w/v) aluminum chloride (AlCl₃ 6H₂O) was added to the mixture, which was allowed to stand at 25 °C for an additional 6 min. Finally, 1 mL of sodium hydroxide (NaOH) was added, and the final volume was brought up to 25 mL with H₂O. The absorbance of the resulting solution was measured at 510 nm to determine the total flavonoid content. The standard rutin was diluted to various concentrations to replace the supernatant of the sample using the same procedure, and a standard curve was constructed based on the obtained results. The results were expressed as milligrams per gram of dry weight.

The activity of superoxide dismutase (SOD) was determined using an activity assay kit (BC5165, Solarbio, Beijing, China). Initially, 1 mL of extraction solution was added to 0.1 g of sample powder, followed by centrifugation at 8000× g for 10 min at 4 °C. Subsequently, the mixture was incubated in a 37 °C water bath for 30 min after adding the reagent, and absorbance was measured at 450 nm. A represents percentage inhibition: (ΔA_CK − ΔA_s) ÷ ΔA_CK. The SOD activity of the sample was calculated using the formula: [A ÷ (1 − A) × V₁] ÷ (W × V₂ ÷ V₃) × F, where ΔA_s and ΔA_CK represent the absorbance of the sample and control at 450 nm, respectively, W represents the sample mass in grams (g), F is the sample dilution factor. V₁ represents the total volume in milliliters (mL), V₂ represents the sample volume in milliliters (mL), V₃ represents the extraction solvent volume in milliliters (mL). Catalase (CAT) activity was measured using an activity assay kit (BC0200, Solarbio, Beijing, China). CAT activity was monitored by observing the consumption of hydrogen peroxide. Initially, 0.1 g of sample powder was mixed with 1 mL extraction solution and centrifuged at 4 °C for 10 min at 8000× g. The absorbance at 240 nm was measured. The CAT activity of the sample was calculated using the formula: [ΔA × V₁ ÷ (ϵ × d) × 10⁶] ÷ (W × V₂ ÷ V₁) ÷ T, where ΔA represents the absorbance of the sample, V₁ represents the volume of the extraction solution in milliliters (mL), ϵ represents the molar absorptivity of H₂O₂, d represents the path length of the cuvette (1 cm), V₂ represents the sample volume in milliliters (mL), W represents the sample mass in grams (g), and T represents the reaction time (1 min). The measurement of POD activity was conducted following the manual of the assay kit (BC0090, Solarbio, Beijing, China). Initially, 1 mL of extraction solution was mixed with 0.1 g of sample powder and was centrifuged at 4 °C for 10 min at 8000× g. After adding the reagents into the sample tube, the absorbance was measured at the 470 nm. The POD activity of the sample was calculated using the formula: ΔA × V₁ ÷ (W × V₂ ÷ V₃) ÷ 0.01 ÷ T, where ΔA represents the absorbance of the sample, V₁ the total volume in milliliters (mL), ϵ stands for the molar absorptivity of H₂O₂, d represents the path length of the cuvette (1 cm), V₂ represents the sample volume in milliliters (mL), V₃ represents the volume of the extraction solution (mL), W represents the sample mass in grams (g), and T represents the reaction time (1 min).

The antioxidant capacity was assessed using a colorimetric method [41]. The fresh leaves (0.5 g) were extracted with 8 mL of alcohol. The homogenate was centrifuged at 3000 rpm for 10 min at 4 °C after being left to stand for 30 min. A solution containing 0.4 mL of the sample was combined with 3.6 mL of a solution consisting of 0.3 mol/L acetate buffer, 10 mmol·L⁻¹ 2, 4, 6-tripyridyl-S-triazine (TPTZ), and 20 mmol/L FeCl₃ at a ratio of 10:1:1 (v/v/v). The resulting mixture was incubated at 37 °C for 10 min. Subsequently, the ferric-reducing antioxidant power (FRAP) of the mixture was measured at 593 nm. The antioxidant capacity was quantified by establishing a standard curve using a 40 μmol/mL FeSO₄ standard solution, which was prepared by dissolving 10 mg of FeSO₄·7H₂O in 0.9 mL of distilled water and adding 20 μL of concentrated sulfuric acid.

2.4. Chlorophyll Fluorescence Imaging

Chlorophyll fluorescence imaging was performed using the Mobile PlantExplorer XS (PhenoVation, Wageningen, The Netherlands). The Mobile PlantExplorer XS (PhenoVation, Wageningen, The Netherlands) is based on machine vision and chlorophyll fluorescence imaging technology, which integrates modulated and non-modulated chlorophyll fluorescence imaging measurement functions to achieve simultaneous measurement of plant photosynthetic physiology and morphological structure. Chlorophyll fluorescence imaging was analyzed with image analysis software (Version 5.8.3-64b; PhenoVation, Wageningen, The Netherlands) Chlorophyll fluorescence imaging encompassed a range of measurements, including the maximal quantum yield of PSII during the dark reaction (Fv/Fm), the photochemical efficiency of PSII during the light reaction (Fq′/Fm′), non-photochemical quenching (NPQ), and the electron transport rate (ETR).

2.5. RNA-Seq Sequencing

Lettuce samples (LN + T1 and CK) were collected for RNA sequencing (RNA-seq) on an Illumina HiSeq platform at Nanjing Jisi Huiyuan Biotechnology Co., Ltd. (Nanjing, China). Sample detection mainly used Nanodrop to measure the purity (OD 260/280), concentration, and nucleic acid absorption peak of RNA, while Agilent 2100 was used to accurately detect the integrity of RNA. For library construction, eukaryotic mRNA was enriched with magnetic beads containing oligo (dT), and fragmentation buffer was added to randomly break the mRNA. Using mRNA as the template, the first cDNA strand was synthesized with six-base random hexamers, followed by the addition of buffer, dNTPs, RNase H, and DNA polymerase I to synthesize the second cDNA strand. The cDNA was purified using AMPure XP beads, and the purified double-stranded cDNA was subjected to end repair, A-tailing, and connection of sequencing adapters. Subsequently, fragment size selection was performed using AMPure XP beads, and PCR enrichment was conducted to obtain a cDNA library. Qubit 2.0 was used for initial quantification of library quality, Agilent 2100 was used to detect the insert size of the library, and Q-PCR was utilized for accurate quantification of the effective concentration of the library (with an effective concentration of the library > 2 nM). Different libraries were pooled according to the target data volume and sequenced using the Nova platform with a read length of PE150. Pathway enrichment analysis was further identified using the genomes (GO) database and genomes (KEGG) database. The Gene Ontology (GO) database is a structured standard biological annotation system built by the Gene Ontology Consortium. The GO annotation system consisted of three primary branches: biological process, cellular component, and molecular function. The Kyoto Encyclopedia of Genes and Genomes (KEGG) analysis is to convert large amounts of genetic data into biologically significant information.

2.6. Real-Time qPCR Analysis

Real-time qPCR validation is the process of verifying the results obtained from transcriptomic studies. The cDNA templates used for RT-qPCR were synthesized with the PrimeScriptTM RT reagent kit for qPCR synthesis (Takara Biomedical Technology, Dalian, China). RT-qPCR was performed using the FQD-96A Real-Time PCR Detection System (Bioer, Hangzhou, China). Actin was selected as the reference gene, and nine differentially expressed genes were selected to determine the expression level. These genes’ relative expression levels were normalized using the 2^−ΔΔCt method (Livak method) [42]. Table S1: Statistical summary of sequencing data and Table S2: RT-qPCR primers were in the Supplementary Materials.

2.7. Data Analysis

All the data are shown as the mean ± standard deviation. Significant differences in the data were determined using Duncan’s multiple range test (p < 0.05) following one-way analysis of variance (ANOVA). Statistical analyses were performed using IBM SPSS Statistics (Version 20; SPSS, Chicago, IL, USA), and figures were generated using Origin Pro 2018 software.

3. Results

3.1. Plant Growth Characteristics

For the treatments with normal nitrogen nutrient solution without sucrose (CK) and normal nitrogen nutrient solutions supplemented with 1 mmol/L, 3 mmol/L, and 5 mmol/L sucrose (CK + T1, CK + T2, and CK + T3), the leaf areas of CK and CK + T1 were similar but significantly greater than those of CK + T2 and CK + T3 (

Table 1. Plant growth characteristics.

	Treatments	Leaf Area (cm2)	Leaf Length (cm)	Leaf Width (cm)	Fresh Mass (g)
CK	CK	25.31 ± 1.55 a	6.95 ± 0.6 a	5.85 ± 0.61 a	8.85 ± 0.57 a
	CK + T1	24.94 ± 2.37 a	6.51 ± 0.65 abc	5.86 ± 0.34 a	8.28 ± 0.28 b
	CK + T2	21.71 ± 1.73 cd	6.41 ± 0.48 bcd	4.83 ± 0.62 b	7.56 ± 0.48 c
	CK + T3	20.04 ± 1.8 de	6.21 ± 0.48 cd	4.49 ± 0.46 b	6.95 ± 0.65 d
LN	LN	23.58 ± 2.12 ab	6.82 ± 0.32 ab	5.53 ± 0.54 a	8.25 ± 0.56 b
	LN + T1	23.51 ± 0.96 ab	6.54 ± 0.54 abc	5.67 ± 0.66 a	8.21 ± 0.33 b
	LN + T2	22.03 ± 2.41 bc	5.97 ± 0.59 d	4.91 ± 0.32 b	7.15 ± 0.7 cd
	LN + T3	19.01 ± 0.63 e	5.51 ± 0.22 e	4.79 ± 0.49 b	6.74 ± 0.47 d

Different lower-case letters indicate significant differences between treatments (Duncan’s multiple range test, p < 0.05).

). In the low nitrogen nutrient solution without sucrose (LN) and nitrogen deficiency nutrient solutions supplemented with 1 mmol/L, 3 mmol/L, and 5 mmol/L sucrose (LN + T1, LN + T2, and LN + T3), the leaf areas of LN, LN + T1, and LN + T2 were similar, while LN + T3 exhibited a significant decrease in leaf area. The leaf length of LN + T3 significantly decreased compared to CK. For the treatments involving normal nitrogen nutrient solutions (CK, CK + T1, CK + T2, and CK + T3), the leaf widths of CK and CK + T1 were similar but greater than those of CK + T2 and CK + T3. Similarly, in the low nitrogen nutrient solution (LN, LN + T1, LN + T2, and LN + T3), the leaf widths of LN and LN + T1 were comparable but higher than those of LN + T2 and LN + T3. The fresh mass of CK + T3 and LN + T3 significantly decreased compared to CK.

3.2. Plant Biochemical Characteristics

For the treatments with normal nitrogen nutrient solution without sucrose (CK) and normal nitrogen nutrient solutions supplemented with 1 mmol/L, 3 mmol/L, and 5 mmol/L sucrose (CK + T1, CK + T2, and CK + T3), the levels of anthocyanins demonstrated that CK + T1, CK + T3, and CK + T2 were higher than CK (

Table 2. Assessment of anthocyanin, total phenolics, and flavonoid content.

	Treatments	Anthocyanin Content (μg · g−1)	Total Phenolics (mg ∙ g−1)	Flavonoid Content (mg · g−1)
CK	CK	72.04 ± 3.02 g	3.9 ± 0.07 e	16.81 ± 0.91 g
	CK + T1	101.19 ± 4.18 e	4.04 ± 0.11 e	21.69 ± 1.24 d
	CK + T2	89.75 ± 6.11 f	4.06 ± 0.14 e	18.67 ± 0.88 f
	CK + T3	95.31 ± 4.9 ef	5.39 ± 0.17 c	19.95 ± 1.06 e
LN	LN	115.23 ± 7.27 d	5.13 ± 0.15 d	23.02 ± 0.6 c
	LN + T1	160.35 ± 4.25 c	6.1 ± 0.13 a	25.52 ± 0.47 b
	LN + T2	172.72 ± 13.52 b	5.89 ± 0.19 b	26.01 ± 0.36 ab
	LN + T3	183.88 ± 5.15 a	5.75 ± 0.1 b	26.46 ± 0.77 a
F value of ANOVA analysis
N		1833.713 **	1873.945 **	923.641 **
T		164.695 **	166.373 **	70.878 **
N × T		43.668 **	122.485 **	14.720 **

Different lower-case letters indicate significant differences between treatments (Duncan’s multiple range test, p < 0.05). ** indicate significance at p < 0.01, respectively.

). Additionally, the anthocyanin content of lettuce in normal nitrogen nutrient solutions supplemented with 1 mmol/L (CK + T1) was increased by 40.47% compared to CK. In the low nitrogen nutrient solution without sucrose (LN) and nitrogen deficiency nutrient solutions supplemented with 1 mmol/L, 3 mmol/L, and 5 mmol/L sucrose (LN + T1, LN + T2, and LN + T3), the levels of anthocyanins demonstrated that LN + T3 > LN + T2 > LN + T1 > LN. The anthocyanin content of lettuce in the low nitrogen nutrient solution with 3 mmol/L sucrose (LN + T3) was increased by 155% compared to CK (Table 2).

For the treatments involving low nitrogen nutrient solutions (LN, LN + T1, LN + T2, and LN + T3), the highest values of total phenolics were observed in the LN + T1 treatment (Table 2). For the treatments involving normal nitrogen nutrient solutions (CK, CK + T1, CK + T2, and CK + T3), CK + T3 showed a significant increase compared to CK, CK + T1, and CK + T2, while CK, CK + T1, and CK + T2 did not differ significantly. The total phenolics of lettuce in low nitrogen nutrient solutions supplemented with 1 mmol/L (LN + T1) were significantly increased by 56.45% compared to CK (Table 2).

For the treatments involving normal nitrogen nutrient solutions (CK, CK + T1, CK + T2, and CK + T3), the values of flavonoids demonstrated that CK + T1 > CK + T3 > CK + T2 > CK (Table 2). The flavonoids in normal nitrogen nutrient solutions supplemented with 1 mmol/L (CK + T1) were 29.07% higher than those in CK. For the treatments involving low nitrogen nutrient solutions (LN, LN + T1, LN + T2, and LN + T3), the levels of flavonoids were significantly higher in LN + T3, LN + T2, and LN + T1 compared to LN. The flavonoids in the low nitrogen nutrient solution with 3 mmol/L sucrose (LN + T3) were higher (57.43%) than CK. Nitrogen levels (normal nitrogen nutrient solution, low nitrogen nutrient solution), exogenous sucrose, and the interaction between nitrogen levels and exogenous sucrose significantly affected anthocyanin content, total phenolics, and flavonoid content (Table 2).

In the treatments including CK, CK + T1, CK + T2, CK + T3, LN, LN + T1, LN + T2, and LN + T3, levels of SOD, CAT, and POD exhibited an increasing trend with sucrose concentration, all significantly surpassing those of CK. The SOD, CAT, and POD activities of lettuce in low -nitrogen nutrient solutions supplemented with 3 mmol/L (LN + T3) were significantly increased.

In the treatments involving normal nitrogen nutrient solutions (CK, CK + T1, CK + T2, and CK + T3), the antioxidant abilities of CK + T2 and CK + T3 were similar but significantly higher than those of CK and CK + T1 (

Table 3. Assessment of enzymatic activities (SOD, CAT, POD) and antioxidant capacity.

	Treatments	SOD (U ∙ g−1)	CAT (U ∙ g−1)	POD (U ∙ mg−1)	Antioxidant Ability (μmol Trolox ∙ g−1)
CK	CK	120.1 ± 5.4 g	120.53 ± 4.52 d	6.4 ± 0.28 e	1.48 ± 0.09 d
	CK + T1	135.1 ± 7.15 f	129.57 ± 5.3 c	7.48 ± 0.29 d	1.53 ± 0.1 d
	CK + T2	145.27 ± 7.73 e	134.09 ± 7.41 c	8.49 ± 0.31 c	1.73 ± 0.11 c
	CK + T3	151.91 ± 9.94 d	156.69 ± 6.29 b	8.62 ± 0.2 c	1.79 ± 0.09 c
LN	LN	156.96± 6.3 cd	130.33 ± 6.59 c	8.45 ± 0.21 c	2.11 ± 0.06 a
	LN + T1	159.76 ± 7.47 c	135.6 ± 6.78 c	9.39 ± 0.37 b	2.04 ± 0.06 a
	LN + T2	167.29 ± 5.26 b	152.17 ± 5.98 b	9.42 ± 0.36 b	1.82 ± 0.09 c
	LN + T3	177.42 ± 4.28 a	175.53 ± 7.91 a	10.28 ± 0.34 a	1.93 ± 0.12 b

Different lower-case letters indicate significant differences between treatments (Duncan’s multiple range test, p < 0.05).

). Similarly, in the treatments involving low nitrogen nutrient solutions (LN, LN + T1, LN + T2, and LN + T3), the antioxidant ability indicated that LN and LN + T1 were comparable but significantly greater than LN + T3 and LN + T2.

3.3. Chlorophyll Fluorescence Imaging

By employing chlorophyll fluorescence imaging and analyzing chlorophyll fluorescence parameters of the lettuce canopy (Figure 1 and Figure 2), we observed that the maximal quantum yield of PSII (Fv/Fm) remained consistently around 0.8 for each distinct treatment (Figure 2a). The CK groups showed the highest values of Fq’/Fm’, followed by LN + TI, with LN and LN + T3 being the lowest (Figure 2b). The CK groups exhibited higher ETR values, followed by LN + T1, with LN + T3 being the lowest (Figure 2c). Compared to the control group, the NPQ values of all other groups increased, especially in LN + T3, LN, and CK + T3 (Figure 2d).

3.4. Transcriptional and Functional Enrichment Analysis

In this study, transcriptome sequencing was used to further analyze the effect of exogenous sucrose on anthocyanin biosynthesis in purple lettuce under low nitrogen conditions. Samples (CK and LN + T1) were selected for transcriptome sequencing. The sequencing of samples was completed, resulting in a total of 44.21 Gb of data. Additionally, each sample yielded clean data exceeding 6.00 Gb, with the percentage of Q30 bases being more than 91.18%. The efficiency of sequence alignment between the clean reads of each sample and the designated reference genome was 95.17%. Comparison between LN + T1 and CK revealed a total of 1955 differentially expressed genes (DEGs), with 869 upregulated DEGs and 1086 downregulated DEGs. The correlation analysis of samples can be presented through different display formats (Figure 3).

3.4.1. The GO Analysis of the Combined Effect of Low Nitrogen Nutrient Solution Supplemented with 1 mmol/L Sucrose

The differentially expressed genes (DEGs) affected a total of 14 cellular component units, 20 biological process units, and 11 molecular function units in the Gene Ontology (GO) analysis (Figure 4). The DEGs related to antioxidant activity were observed in the molecular function category of Gene Ontology (GO), whereas those associated with responses to stimulus were identified in the biological process category of GO.

Through the analysis of the GO classification of up-regulated genes in the biological process (Figure 5a), it was discovered that the differentially expressed genes (DEGs) were up-regulated and enriched in secondary metabolic biological processes, secondary metabolic processes, monoterpene biosynthetic process, cinnamic acid biosynthetic process, and response to wounding. The up-regulated genes were linked to cellular components such as UDP-glucose-glycosyltransferase activity, quercetin 7-O-glucosyltransferase activity, and quercetin 3-O-glucosyltransferase activity (Figure 5b).

3.4.2. The KEGG Analysis Revealed the Combined Impact of Low-Nitrogen Nutrient Solution Supplemented with 1 mmol/L Sucrose

Based on the classification of secondary pathways in KEGG, the up-regulated differentially expressed genes were found to be involved in biosynthesis of other secondary metabolites, metabolism of terpenoids and polyketides, and environmental adaptation (Figure 6a). The enrichment map of differentially expressed genes (DEGs) in the top 20 gene pathways of KEGG revealed that the DEGs were primarily enriched in terms of flavonoid biosynthesis, phenylalanine metabolism, monoterpenoid biosynthesis, terpenoid backbone biosynthesis, MAPK signaling pathway-plant, glutathione metabolism, flavone and flavonol biosynthesis (Figure 6b).

3.4.3. The Differential Gene Analysis of Anthocyanin Biosynthesis Pathway

The differentially expressed genes related to the synthesis of anthocyanins are primarily focused on the phenylalanine and flavonoid biosynthesis pathways (Figure 6b). The upregulation of phenylalanine ammonia-lyase (EC: 4.1.24) symbolizes the initiation of secondary metabolite production. Additionally, the genes of chalcone synthase (EC: 2.3.1.74), dihydroflavonol4-reductase (EC: 1.1.1.219), flavone synthase II (EC: 1.14.19.76), flavanone3-dioxygenase (EC: 1.14.11.9), flavonoid3′-monooxygenase (EC: 1.14.14.82), and anthocyanidin synthase (EC: 1.14.20.4) were significantly upregulated in the flavonoid synthesis pathway. The differentially expressed genes (DEGs) involved in anthocyanin synthesis are shown in

Table 4. The differentially expressed genes (DEGs) of the anthocyanin synthesis pathway.

Name	Gene ID	Found Change	Trends
phenylalanine ammonia-lyase (PAL)	LSAT_2x106540	2.6569	up
chalcone synthase (CHS)	LSAT_2x42860	3.7358	up
dihydroflavonol 4-reductase (DFR)	LSAT_2x77261	3.0585	up
flavanone 3-dioxygenase (F3H)	LSAT_3x74560	1.57485	up
flavonoid 3′-monooxygenase (F3′H)	LSAT_5x23101	1.5153	up
flavone synthase II (FNSII)	LSAT_9x70860	2.6246	up
anthocyanidin synthase (ANS)	LSAT_9x97280	1.8313	up

. The anthocyanin biosynthesis pathway is shown in Figure 7.

3.4.4. The Differential Expression of Transcription Factors in Low Nitrogen Nutrient Solution Supplemented with 1 mmol/L Sucrose

In Figure 8, there are 52 transcription factor families listed in descending order of quantity as follows: AP2/ERF family (220 members), MYB family (218 members), followed by the bHLH family (139 members), C2H2 family (134 members), NAC family (102 members), C2C2 family (100 members), HB family (92 members), MADS family (86 members), bZIP family (85 members), and WRKY family (75 members).

3.4.5. Real-Time qPCR Validation

To validate the differentially expressed genes (DEGs) under the treatment of low nitrogen nutrient solution combined with sucrose, nine specific DEGs (LSAT-2x106540 (PAL),LSAT_2x42860 (CHS), LSAT-3x74560 (F3H), LSAT-5x23101 (F3′H), LSAT_2x77261 (DFR), LSAT-9x97280 (ANS), LSAT-1x37841 (JAZ), LSAT-5x72101 (ETR), and LSAT-9x53561 (PP2C)) were chosen for the assessment of their expression levels (Figure 9). In general, the expression results of differential genes were consistent with those of transcriptome sequencing, indicating the reliability and accuracy of transcriptome data.

4. Discussion

4.1. Exogenous Sucrose Promoted Anthocyanin Biosynthesis, but High Sucrose Concentrations Significantly Inhibited Growth

In the normal nitrogen nutrient solutions, where sucrose was supplemented at concentrations of 1 mmol/L (CK + T1), 3 mmol/L (CK + T2), and 5 mmol/L (CK + T3), as well as in the low nitrogen group (LN), the anthocyanin content was found to be higher than that in the normal nitrogen group (CK). This suggests that both the individual low -nitrogen nutrient solution and the addition of sucrose promoted anthocyanin synthesis, consistent with previous studies [22,23,35,37,43]. In the group treated with normal nitrogen nutrient solution (CK, CK + T1, CK + T2, CK + T3), the anthocyanin content showed the sequence CK + T1 > CK + T3 > CK + T2 > CK. Anthocyanin levels did not exhibit a clear pattern of change with varying exogenous sucrose concentrations. However, in the group of low nitrogen nutrient solutions (LN, LN + T1, LN + T2, LN + T3), the anthocyanin content exhibited the sequence LN + T3 > LN + T2 > LN + T1 > LN, demonstrating that anthocyanin levels increased with the elevation of exogenous sucrose concentration under low nitrogen nutrient conditions (Table 2). In the high sucrose concentration treatment group (LN + T3), the anthocyanin content was highest. Some studies have found that 10 mmol L⁻¹ sucrose induced a threefold increase in anthocyanin compared to 0.5 mmol L⁻¹ sucrose [43]. Under high sucrose conditions (6%), anthocyanin synthesis in Arabidopsis seedlings is enhanced [44]. High sucrose concentrations induce the production of secondary metabolites in plants, exceeding those naturally occurring in ripe berries [45]. Furthermore, the overall levels of anthocyanins were relatively higher when exogenous sucrose was added to the low-nitrogen nutrient solution (LN, LN + T1, LN + T2, LN + T3) compared to when it was added to the normal nitrogen nutrient solution (CK, CK + T1, CK + T2, CK + T3). Two-way ANOVA results indicated that the formation of anthocyanins was significantly influenced by low nitrogen levels in nutrient solutions, different exogenous sucrose concentrations, and their interaction (Table 2). This suggested a synergistic effect between a low-nitrogen nutrient solution and sucrose in anthocyanin biosynthesis, where anthocyanin content increased with higher concentrations of exogenous sucrose. For the overall growth characteristics of lettuce, we found that in the normal nutrient solution (CK, CK + T1) and low nitrogen nutrient solution (LN, LN + T1), lettuce plants exhibited higher leaf area, leaf length, leaf width, and fresh mass compared to those in the normal nutrient solution (CK + T2, CK + T3) and low nitrogen nutrient solution (LN + T2, LN + T3). High concentrations of sucrose, whether in the normal nutrient solution or the low nitrogen nutrient solution, inhibited the growth of lettuce plants. Some research findings indicate that high concentrations of sucrose, instead of low concentrations, may inhibit plant growth and increase the levels of anthocyanins [43]. Based on the comprehensive analysis of anthocyanin content and growth characteristics, the nutrient solution under low nitrogen conditions combined with the addition of a low concentration of sucrose (LN + T1) was found to be the most optimal.

4.2. Adding Exogenous Sucrose Induced Slight Stress, Thereby Promoting Anthocyanin Accumulation

Chlorophyll fluorescence emitted by plants provides a complex reflection of photosynthetic activities [46]. By utilizing chlorophyll fluorescence imaging and chlorophyll fluorescence parameters of the lettuce canopy, the maximal quantum yield of PSII (Fv/Fm) showed no remarkable differences among the different treatments of nutrient solutions. Compared to the control group, the Fq′/Fm′ and ETR values in other treatment groups exhibited varying degrees of decline, especially noticeable in the LN + T3 treatment group. The decreases in Fv/Fm and ΦPSII indicate injury to the PSII reaction center [47,48]. We hypothesized that the high sucrose concentration treatment group had an effect on the photosynthetic efficiency but did not damage the plant photosystem. The non-photochemical quenching coefficient (NPQ) represents the fraction of light energy absorbed by PSII reaction center antenna pigment that cannot participate in photosynthetic electron transport, instead dissipating as heat [47,48,49]. This process of heat dissipation plays a crucial role in safeguarding the plant’s photosynthetic apparatus against potential damage [50]. Compared to the control group, NPQ values were higher in the other treatments, particularly in the LN + T3, CK + T3, and LN treatments (Figure 2d). In conclusion, we speculated that the exogenous sucrose induced slight stress in purple lettuce. Observing all treatment groups, the activities of the three antioxidant enzymes SOD (superoxide dismutase), CAT (catalase), and POD (peroxidase) have all increased compared to the control group. Overall, the enzyme activities of the three antioxidant enzymes SOD, CAT, and POD increased with the rising concentration of exogenous sucrose. SOD, CAT, and POD are vital enzymes in plants’ antioxidant systems, crucial for neutralizing reactive oxygen species (ROS) and free radicals within cells. This process maintains cellular balance [51]. These enzymes help plants cope with various environmental stresses, such as drought, salt stress, high temperatures, and other adverse conditions [46,52]. Research indicates that environmental factors play a substantial role in regulating anthocyanin production, often in response to stress-induced conditions [53,54]. Through comprehensive analysis of transcriptome sequencing, we found that a low nitrogen nutrient solution supplemented with 1 mmol/L sucrose (LN + T1) led to differential expression of genes (DEGs). The GO functional analysis indicated that the DEGs were enriched in the categories of response to stimulus and antioxidant activity (Figure 4). Additionally, the analysis of the GO classification in biological processes showed that the DEGs associated with secondary metabolic processes and response to wounding were upregulated and enriched (Figure 5a). Through KEGG analysis, it was found that the DEGs involved in the biosynthesis of other secondary metabolites and environmental adaptation were upregulated (Figure 6a). Based on the analysis of the top 20 gene pathways in KEGG, the DEGs involved in glutathione metabolism and the MAPK signaling pathway were significantly upregulated and enriched (Figure 6b). Glutathione metabolism is crucial in plants as it interacts with reactive oxygen species such as superoxide anions and hydrogen peroxide, thereby protecting cells from oxidative damage [55]. Additionally, glutathione metabolism and ascorbic acid metabolism synergize to form the crucial antioxidant system known as the AsA-GSH cycle [56,57]. Some studies suggest that brassinolide alleviates drought stress by enhancing the AsA-GSH cycle and reducing ROS damage [58]. Exogenous glutathione has been shown to boost the AsA-GSH cycle and enhance antioxidant capacity [59]. The MAPK signaling pathway plays a critical role in plant stress responses by initiating adaptive reactions such as ion balance regulation, protection of cell membranes, activation of antioxidant systems, and modulation of water utilization [60]. The modulation of anthocyanin biosynthesis in Arabidopsis thaliana is controlled by sucrose signaling through a MAPK cascade [33]. The analysis of antioxidant performance indicators showed that LN + T1 increased the antioxidant capacity of lettuce (Table 3). Anthocyanins enhance antioxidant capacity and mitigate oxidative stress by scavenging free radicals and modulating signaling pathways [61]. Previous studies have shown that applying exogenous selenium to purple lettuce significantly increased antioxidant enzyme activities and anthocyanin levels [62]. A strong positive correlation is found between anthocyanin content and the antioxidant potential index [63]. The accumulation of sucrose concentrations, linked to both abiotic and biotic stresses, leads to increased reactive oxygen species and anthocyanin production as secondary metabolites [64]. Overall, the study showed that the combined treatment of exogenous sucrose and low nitrogen induced a response in the antioxidant system of lettuce, thereby promoting anthocyanin biosynthesis.

4.3. N + T1 Enhanced Anthocyanin Biosynthesis by Upregulating Enzymatic and Transcription Factor Gene Expression

Purple lettuce is rich in antioxidants and anthocyanins, which are believed to possess anti-inflammatory and anti-cancer properties [65,66]. The secondary metabolites of plants can be divided into terpenes, phenolics, and secondary nitrogen-containing compounds [67]. Through the analysis of the GO classification of up-regulated genes in biological processes, we observed that the DEGs of the secondary metabolite biosynthetic process, secondary metabolic process, monoterpene biosynthetic process, and cinnamic acid biosynthetic process were significantly up-regulated and enriched (Figure 5a). The up-regulated genes were linked to cellular components such as UDP-glucose-glycosyltransferase activity, quercetin 7-O-glucosyltransferase activity, and quercetin 3-O-glucosyltransferase activity, which are closely related to the regulation of anthocyanins (Figure 5b). UDP-glucose-glycosyltransferases (UGTs) transfer sugars from UDP-glucose donors to molecules, forming glycosidic bonds crucial for plant pigment biosynthesis, especially anthocyanins [68,69]. Two key enzymes, quercetin 7-O-glucosyltransferase and quercetin 3-O-glucosyltransferase, attach glucose from UDP-glucose to specific positions on quercetin molecules. This process produces glucosylated quercetin derivatives, essential precursors for anthocyanin production [70,71,72]. According to the classification of secondary metabolic pathways in KEGG, the DEGs of biosynthesis of other secondary metabolites, metabolism of terpenoids, and polyketides were significantly enriched (Figure 6a). The analysis of the top 20 gene pathways revealed that the DEGs were predominantly enriched in phenylalanine metabolism, monoterpenoid biosynthesis, terpenoid backbone biosynthesis, flavonoid biosynthesis, flavone biosynthesis, and flavonol biosynthesis (Figure 6b). Secondary metabolites such as total phenols, flavonoids, and anthocyanins were also increased (Table 2). Flavonoids, a subset of phenolic compounds, exhibited higher concentrations relative to total phenolics in our experiment. This discrepancy can be attributed to variations in the spectrophotometric methods used to quantify total phenolics and flavonoids. In conclusion, LN + T1 enhanced the accumulation of secondary metabolites. The KEGG analysis revealed that the DEGs primarily targeted the phenylpropanoid and flavonoid biosynthesis pathways (Figure 6b), which elucidated the regulatory patterns of enzyme genes involved in the anthocyanin synthesis pathway. In this study, the DEGs of phenylalanine ammonia-lyase (PAL), chalcone synthase (CHS), dihydroflavonol 4-reductase (DFR), flavanone 3-dioxygenase (F3H), flavonoid 3′-monooxygenase (F3′H), flavone synthaseII (FNSII), anthocyanidin synthase (ANS) were significantly upregulated in the anthocyanin synthesis pathway (Table 4). Some studies have shown that anthocyanin biosynthesis genes such as PAL, C4H, 4CL, CHS, FLS, F3H, F3′H, DFR, ANS, GT, OMT, and MAT were significantly upregulated in the colored highland barley variety (Hordeum vulgare) compared to the non-colored variety [73]. Flavone synthase II is an enzyme responsible for transforming flavanones into flavones. Flavones serve as co-pigments with anthocyanins to intensify flower color. FNSII is classified within the P450 enzyme family, specifically in the CYP93B subfamily [74]. Interactions are observed between FNSII and other flavonoid enzymes in torenia, and the suppression of FNSII expression led to a reduction in petal anthocyanin levels [75]. LN + T1 resulted in significant differences in enzyme gene expression, which was likely the primary factor contributing to the promotion of anthocyanin synthesis. To further understand the role of differential genes in regulating anthocyanin synthesis, significant genes in the anthocyanin synthesis pathway are annotated according to the principles of the KEGG map, as shown in Figure 7. Transcription factors are proteins that regulate gene expression by binding to specific DNA sequences. They play an important role in plants’ responses to changes in environmental conditions and in activating cellular defense mechanisms [51]. In plants, anthocyanin production is a consistent process regulated by transcription factors like MYB, bHLH, and WD-repeat proteins [44]. These factors typically assemble into the MBW complex to control anthocyanin synthesis [76,77]. Different types of transcription factors were found to be differentially expressed in both Gall oak (Quercus infectoria) [78] and Ginkgo biloba [79], influencing the synthesis of phenylpropanoids and flavonoids. After the addition of exogenous sucrose treatment under low nitrogen conditions, the most differentially expressed transcription factor families were AP2/ERF and MYB, followed by bHLH, C2H2, NAC, C2C2, HB, MADS, bZIP, and WRKY families (Figure 7). The upregulation of metabolites involved in the phenylpropane pathway, sucrose pathway, multiple amino acid metabolism, and lipid metabolism pathways is closely associated with AP2/ERF transcription factors in Betula platyphylla [80]. RHA2b triggers the breakdown of MYB30, which in turn promotes the MYB75 regulated synthesis of anthocyanins in response to sucrose in Arabidopsis seedlings [44]. Therefore, the regulation of sucrose in low nitrogen environments led to high expression of transcription factors, thereby promoting the formation of anthocyanins.

5. Conclusions

Anthocyanins are phytochemicals present in vegetables that contribute to human health. We employed two sets of nutrient solutions with different nitrogen concentrations (normal nitrogen concentration (CK), low nitrogen concentration (LN)) and sucrose concentrations (1 mmol/L (T1), 2 mmol/L (T2), and 5 mmol/L (T3)), totaling eight experimental treatments. We investigated the potential role of sucrose in regulating the anthocyanin biosynthesis of lettuce under low-nitrogen (LN) conditions. We used transcriptome sequencing, chlorophyll fluorescence imaging, and biochemical measurements to evaluate the impacts of different treatments. The findings revealed that adding exogenous sucrose promoted anthocyanin biosynthesis, while high concentrations of sucrose inhibited the growth of lettuce. We thereby concluded that adding a low concentration of exogenous sucrose (1 mmol/L) to a low nitrogen nutrient solution is the optimal formulation for enhancing anthocyanin content. Chlorophyll fluorescence imaging indicated that the addition of exogenous sucrose induced mild stress. Meanwhile, the activities of antioxidant enzymes (SOD, CAT, and POD) and overall antioxidant capacity were both enhanced. LN + T1 facilitated anthocyanin production and up-regulated genes (PAL, CHS, DFR, F3H, F3′H, FNSII, ANS) involved in the anthocyanin biosynthesis pathway. Additionally, transcription factors including AP2/ERF, MYB, bHLH, C2H2, NAC, C2C2, HB, MADS, bZIP, and WRKY were found to be up-regulated. We provided new insights into the regulations of anthocyanin metabolism in response to the addition of exogenous sucrose to a low -nitrogen nutrient solution. Additionally, it improved the aesthetic and nutritional value of lettuce, providing valuable insights for cultivating high-quality vegetables in modern practices.