γ-Aminobutyric acid enhances nitrogen use efficiency in soybean through coordinated regulation of root architecture and nitrogen metabolism under low nitrogen stress

doi:10.21203/rs.3.rs-7629577/v1

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γ-Aminobutyric acid enhances nitrogen use efficiency in soybean through coordinated regulation of root architecture and nitrogen metabolism under low nitrogen stress

https://doi.org/10.21203/rs.3.rs-7629577/v1

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To investigate the physiological mechanisms by which exogenous γ-aminobutyric acid (GABA) alleviates low nitrogen (LN) stress in soybean (Glycine max L.), this study employed a sand culture system under LN conditions (2.9 mmol·L⁻¹, 1/5 of the normal nitrogen level of 14.5 mmol·L⁻¹). Nutrient solutions with normal nitrogen (CK) and LN (LN treatment) were applied from the V1 stage (designated as day 0), followed by root application of 5 mmol·L⁻¹ GABA for three consecutive days starting at the V2 stage (LN + GABA treatment). The effects of GABA on root and shoot morphology, nitrogen metabolism, and photosynthetic parameters were systematically analyzed. The results demonstrated that GABA enhances root system architecture and activity, thereby improving nitrogen acquisition capacity. This is accompanied by elevated activities of key nitrogen assimilation enzymes, including glutamine synthetase (GS) and glutamate synthase (GOGAT), which synergistically optimize nitrogen utilization efficiency. The coordinated regulation of carbon metabolism further stabilizes carbon-nitrogen balance, ensuring the integrity of chlorophyll synthesis and photosynthetic enzyme functionality. Consequently, GABA significantly improves photosynthetic performance and overall plant growth under LN stress. This study reveals a cascade regulatory mechanism involving root system architecture, nitrogen metabolism, carbon-nitrogen balance, and photosynthetic performance, providing a theoretical foundation for developing GABA-based biostimulants to enhance nitrogen use efficiency and support sustainable agriculture with reduced nitrogen fertilizer dependency.

γ-Aminobutyric acid

Soybean

Low nitrogen stress

Root system architecture

Nitrogen use efficiency

Soybean (Glycine max L. Merr.) is a globally valuable biological resource, providing high-quality protein and oil for human consumption (Pagano et al. 2016) while contributing to the stability and sustainability of agricultural systems through biological nitrogen fixation (BNF) and soil improvement properties (Soratto et al. 2022). However, in practical production, N deficiency often occurs due to natural soil impoverishment and anthropogenic factors such as insufficient or improper N fertilization and excessive nitrate leaching through irrigation (Galloway et al. 2008). Although BNF can meet 50%–70% of soybean N demand (Ribeiro et al. 2000), inorganic N deficiency during early growth stages—when BNF capacity is not yet fully established—inevitably restricts plant development.

Nitrogen is a fundamental component of structural materials (nucleic acids, proteins, cell walls) and functional molecules (chlorophyll, enzymes, hormones, ATP, NAD(P)+) essential for plant growth (Raven et al. 2004). Its deficiency disrupts physiological metabolism, leading to growth inhibition (Zambon et al. 2023). In soybean, N shortage first affects N metabolism, manifesting as reduced nitrate content in roots (Feng et al. 2025) and decreased activities of key assimilatory enzymes such as nitrate reductase (NR) and glutamine synthetase (GS) (Wang et al. 2022), indicating impaired N assimilation. Although N remobilization efficiency may initially increase with rising C/N ratio, it eventually declines (Xie et al. 2023), and internal N recycling becomes insufficient under prolonged deficiency (Zambon et al. 2023). Classically, N deficiency reduces chlorophyll synthesis (Wen et al. 2023) and suppresses activities of Rubisco and sucrose phosphate synthase (SPS) (Tantray et al. 2020; Panagiotidou et al. 2023), resulting in decreased net photosynthetic rate and hindered sugar transport. Accumulated soluble sugars and starch in leaves likely reflect reduced carbon use efficiency rather than carbon source limitation. Moderate N deficiency may enhance flavonoid secretion from roots, activating nod genes in rhizobia and promoting nodulation (Zhao et al. 2025). However, severe N scarcity limits carbohydrate (e.g., sucrose) allocation to nodules (Lepetit and Brouquisse 2023), impairing cell division and differentiation in nodule primordia and leading to fewer, smaller, and often immature nodules (Luan et al. 2025). Nitrogenase activity may initially increase to compensate for mineral N shortage (Bosse et al. 2024) but eventually declines under prolonged N deficit due to restricted carbon supply (Wang et al. 2025). Additionally, N deficiency limits synthesis and signaling of growth-promoting hormones (auxins, cytokinins, gibberellins) (Hua et al. 2024) while enhancing levels and regulation of stress- and senescence-related hormones (ethylene, ABA, jasmonic acid, salicylic acid) (Hajibarat et al. 2022). Ultimately, these changes result in stunted plants, chlorotic leaves, thin stems, reduced branching, diminished leaf size and thickness, and poorly developed root systems.

Supplemental N fertilization is the most direct remedy for low N stress, but factors like soil type (sandy, saline-alkaline) often cause rapid N loss and low use efficiency. Increasing evidence shows that exogenous hormones can mitigate N limitation. For example, brassinosteroids enhance N uptake in Arabidopsis under low N by inducing high-affinity N transporters and increasing root length (Wang et al. 2023), while improving antioxidant capacity in tomato. Melatonin promotes ammonium assimilation in soybean under N stress by elevating GS/GOGAT/GDH activities and enhancing nodulation (Wang et al. 2022). Cytokinins improve N acquisition in rice via root development and delayed leaf senescence (Kamada-Nobusada et al. 2013). GABA, a non-protein amino acid, plays key roles in plant responses to abiotic stresses, including nutrient deficiencies (Vijayakumari et al. 2016). Combined GABA and gibberellic acid application increased root length and volume in tomato under Pb stress, improving nutrient uptake and alleviating oxidative damage (Shoaib et al. 2025). Under P deficiency, GABA promoted root growth and upregulated antioxidant enzymes in wheat, enhancing P acquisition (Kumari et al. 2025). In salt-stressed cucumber, GABA improved K⁺, Ca²⁺, and Mg²⁺ uptake and activated H⁺-ATPase to acidify the rhizosphere (Zarbakhsh et al. 2023; Yuan et al. 2023). Exogenous GABA also improved poplar seedling growth under low N, increasing height, leaf area, dry weight, chlorophyll content, and photosynthesis (Chen et al. 2020). However, studies on GABA regulation of soybean growth under low N stress are lacking.

Based on previous research, we hypothesized that exogenous GABA could improve soybean growth under N deficiency. This study simulated low N stress using sand culture with controlled N supply. Exogenous GABA was applied to roots, and its effects on seedling morphology, dry matter accumulation, key N metabolic enzymes, and photosynthetic parameters were analyzed to elucidate the physiological mechanisms underlying GABA-mediated improvement in N uptake, assimilation, and carbon metabolism under low N stress. 19

Plant materials and growth conditions

This study was conducted in 2024 at the experimental station of the National Coarse Cereals Engineering Technology Research Center, located in the High-Tech Industrial Development Zone of Daqing City, Heilongjiang Province, China. The soybean (Glycine max L.) cultivar ‘Heihe 43’, a predominant cultivar in Heilongjiang Province characterized by semi-determinate growth habit, was used as plant material. Prior to sowing, uniformly sized seeds free from disease spots and physical damage were selected. Surface sterilization was performed by treating seeds with 5% sodium hypochlorite solution for 10 min, followed by three rinses with sterile distilled water. Plants were grown in plastic pots (height: 33 cm; diameter: 30 cm). To prevent waterlogging, five drainage holes (1 cm diameter) were drilled at the bottom of each pot, which was then lined with a mesh screen to contain the root system within the pot. The pots were filled with quartz sand that had been pre-washed with tap water to remove impurities and subsequently rinsed twice with distilled water. The sand was filled to a level 7 cm below the rim of the pot. Before sowing, each pot was irrigated with sufficient distilled water to achieve complete saturation of the sand substrate. Nine seeds were evenly placed on the sand surface and covered with a 2 cm layer of sand. To avoid potential effects of natural precipitation on experimental conditions, all pots were maintained under a movable rain-out shelter throughout the experiment.

Experimental Design

From sowing until the emergence of the first true leaf, each pot received daily irrigation with 500 mL of distilled water. At the full expansion of the first true leaf, three uniformly growing seedlings per pot were retained, and the remaining ones were carefully removed. Upon reaching the V1 stage (first trifoliate fully unfolded), the cotyledons of all seedlings were excised to eliminate potential confounding effects of residual nitrogen reserves within these organs. The seedlings were then randomly assigned to three experimental groups. Each group received daily irrigation with 500 mL of a modified nutrient solution based on half-strength Hoagland's formulation, differing primarily in nitrogen concentration:

CK (Control): Plants were irrigated with a nutrient solution containing a standard nitrate nitrogen concentration (91 mg∙L⁻¹ NO₃⁻-N).

LN (Low Nitrogen): Plants were subjected to nitrogen deficiency stress by irrigation with a nutrient solution containing one-fifth of the standard nitrate nitrogen concentration (1/5 of CK level).

LN + GABA: Plants initially received the low nitrogen solution (identical to LN). At the V2 stage, this group was treated for three consecutive days with the low nitrogen solution supplemented with 5 mmol∙L⁻¹ GABA. Following this 3-day period, irrigation reverted to the standard low nitrogen solution (without GABA) for the remainder of the experiment.

To prevent salt accumulation in the substrate, all pots were leached every 5 days with 3 L of distilled water. The day of initial GABA application (coinciding with the V2 stage) was designated as day 0 of the treatment period. The experiment was terminated 30 days after the initiation of treatments (Day 30).

Composition of nutrient solutions

The nitrogen sources for the standard nitrogen concentration solution were Ca(NO₃)₂ and KNO₃, applied at concentrations of 328 mg∙L⁻¹ and 252 mg∙L⁻¹, respectively. For the low nitrogen stress solution, the concentrations of Ca(NO₃)₂ and KNO₃ were reduced to 65.64 mg∙L⁻¹ and 50.55 mg∙L⁻¹, respectively. To maintain potassium ion balance, KCl was supplemented at 33.55 mg∙L⁻¹ in the low nitrogen solution. All other macro- and micronutrient components remained identical between the two solutions, consisting of: 53.49 mg∙L⁻¹ (NH₄)₂SO₄, 120.37 mg∙L⁻¹ MgSO₄, 1 mL∙L⁻¹ Fe–EDTA stock solution (prepared by dissolving 5.57 g FeSO₄·7H₂O and 7.45 g Na₂EDTA per liter), 8.6 mg∙L⁻¹ ZnSO₄·7H₂O, 6.2 mg∙L⁻¹ H₃BO₃, 0.08 mg∙L⁻¹ CuSO₄·5H₂O, 22.3 mg∙L⁻¹ MnSO₄, and 0.025 mg∙L⁻¹ Na₂MoO₄·H₂O.

Sampling schedule

Plant samplings were conducted at 0, 20, and 30 days after treatment initiation. Whole plants were harvested at these time points for the determination of morphological parameters, biomass, and nitrogen accumulation. Additionally, leaf and root samples were collected at 5, 10, 20, and 30 days. A subset of these samples was immediately used for the assay of nitrate reductase activity, chlorophyll content, and root activity. Another subset was rapidly frozen in liquid nitrogen and subsequently stored at − 80 ℃ for later analysis of enzymatic activities and other physiological indicators. Photosynthetic gas exchange parameters were measured directly using portable instruments without destructive sampling.

Measurement Indices and Methods

Measurement of morphological and dry matter-related parameters

Plant height and root length were measured using a standard ruler. Stem diameter was determined as the mid-internode diameter of the first fully expanded internode (counting the cotyledonary node as node 0) using a digital vernier caliper. Leaf area was quantified with a Yaxin-1241 leaf area meter (Beijing Yaxin Liyi Technology Co., Ltd., China). For root system analysis, roots were scanned using an EPSON Perfection V800 flatbed scanner (Seiko Epson Corporation, Japan) and parameters including root volume, root surface area, and number of root tips were analyzed with the WinRHIZO Pro 2016a image analysis system (Regent Instruments Inc., Canada).

Plants were separated into leaves, stems, and roots, and each component was placed in individual paper envelopes. Samples were first oven-dried at 105 ℃ for 30 min to deactivate enzymes, followed by drying at 80 ℃ until a constant weight was achieved. Dry matter mass was then measured using an analytical balance. The growth rate from day 0 to day 20 was calculated based on dry weight accumulation using the following formula:

Growth Rate (g∙plant^− 1∙day^− 1\(\:=\frac{\text{D}{\text{M}}_{20}\:\left({\text{g}\bullet\:\text{p}\text{l}\text{a}\text{n}\text{t}}^{-1}\right)-\text{D}{\text{M}}_{0}\:\left({\text{g}\bullet\:\text{p}\text{l}\text{a}\text{n}\text{t}}^{-1}\right)}{21\:\text{d}\text{a}\text{y}\text{s}}\)

\(\:\text{D}{\text{M}}_{20}\) represents the dry weight of soybean plants on the 20th day, respectively, while \(\:\text{D}{\text{M}}_{0}\)indicates the dry weight of soybean plants on day 0.

Determination of root activity

Root activity was assessed using the triphenyltetrazolium chloride (TTC) reduction assay following the established method (Zhang et al. 2022). Briefly, root systems were carefully washed with deionized water to remove adhering soil particles and gently blotted dry. The cleaned roots were then immersed in a 0.4% (w/v) TTC solution and incubated in the dark at 37℃ for 2–4 hours to allow for adequate TTC penetration and enzymatic reduction. After the incubation period, roots were removed from the TTC solution. The formed formazan (TTF) was extracted from the root tissues using ethyl acetate as the solvent. The extract was transferred to centrifuge tubes and subjected to centrifugation at an appropriate speed to obtain a clear supernatant. The absorbance of the supernatant was measured at a wavelength of 485 nm using a spectrophotometer. Root activity, expressed as TTC reduction intensity in units of µg TTC reduced per gram of root fresh weight per hour (µg TTC·g⁻¹·h⁻¹), was calculated based on the measured absorbance values and a pre-established standard curve.

Photosynthetic Indices

Determination of photosynthetic pigment content

The concentrations of chlorophyll a (Chl a), chlorophyll b (Chl b), total chlorophyll (Chl a + b), and carotenoids (Car) were determined according to the method described by Lichtenthaler (Lichtenthaler 1987). Fully expanded functional leaves (100 mg fresh weight) were cut into segments and immersed in 10 mL of absolute ethanol for 24 hours in darkness until the tissues became completely bleached. The optical density (OD) of the extracts was measured at wavelengths of 470, 649, and 665 nm using a Jenway 6850 UV-Vis spectrophotometer (Cole-Parmer Ltd., UK). Pigment concentrations were calculated using the following equations:

Chl a (µg·mL⁻¹) = 13.95 × OD₆₆₅ – 6.88 × OD₆₄₉

Chl b (µg·mL⁻¹) = 24.96 × OD₆₄₉ – 7.32 × OD₆₆₅

Total chlorophyll (µg·mL⁻¹) = Chl a + Chl b

Car (µg·mL⁻¹) = (1000 × OD₄₇₀ – 2.05 × Chl a – 111.48 × Chl b) / 245

Final pigment contents were expressed per gram fresh weight of the leaf tissue.

Measurement of photosynthetic gas exchange parameters

Gas exchange parameters were measured between 9:00 and 11:00 AM following the methodology described by Wang (Wang et al. 2021). Measurements were conducted on the second fully expanded leaf from the apex of the main stem using a Li-6400 portable photosynthesis system (LI-COR Biosciences, Lincoln, NE, USA) equipped with a red-blue LED light source chamber. The parameters recorded included net photosynthetic rate (Pₙ), transpiration rate (T_r), stomatal conductance (Gₛ), and intercellular CO₂ concentration (C_i). During measurements, the following environmental conditions were maintained within the leaf chamber: photosynthetic photon flux density (PPFD) of 1000 µmol·m⁻²·s⁻¹, CO₂ concentration of 400 µmol·mol⁻¹, leaf temperature of 25 ℃, and relative humidity of 25%.

Determination of key nitrogen metabolism enzyme activities and nitrogen-containing compounds

Nitrate reductase (NR) activity was determined according to Mancuso (Mancuso and Caviness

et al. 1991). Fresh leaf samples (0.5 g) were homogenized in 5 mL of phosphate buffer (0.1 mol·L⁻¹, pH 7.5) and 5 mL of potassium nitrate solution (0.2 mol·L⁻¹). The reaction mixture was incubated in darkness at 25 ℃ for 1 h and terminated by adding 1 mL of 30% (w/v) trichloroacetic acid (TCA). Then, 2 mL of the reaction mixture was combined with 8 mL of nitration reagent, incubated at 20 ℃, and the absorbance was measured at 540 nm.

Glutamine synthetase (GS) activity was assayed following the method of Ribeiro (Ribeiro et al. 2000). Fresh leaf or root samples (0.1 g) were ground into powder with liquid nitrogen and extracted with 8 mL of extraction buffer (100 mmol·L⁻¹ Tris-HCl, 0.5 mmol·L⁻¹ EDTA, 5 mmol·L⁻¹ β-mercaptoethanol, pH 7.5). The homogenate was centrifuged at 15,000 × g for 20 min at 4 ℃, and the supernatant was used for enzyme activity determination. A mixture of 1.6 mL reaction buffer and 0.6 mL enzyme extract was pre-incubated at 25 ℃ for 5 min. The reaction was initiated by adding 0.2 mL of hydroxylamine reagent, continued for 15 min at 25 ℃, and stopped with 1 mL of FeCl₃ reagent.

Glutamate synthase (GOGAT) activity was measured according to An (An et al. 2023), using the same extraction method as for GS. The reaction mixture (3 mL total volume) contained 0.4 mL of 20 mmol·L⁻¹ L-glutamine, 0.05 mL of 0.1 mol·L⁻¹ α-ketoglutarate, 0.1 mL of 10 mmol·L⁻¹ KCl, 0.1 mL of 3 mmol·L⁻¹ NADH, and 0.3 mL enzyme extract, with the volume made up with 25 mmol·L⁻¹ Tris-HCl (pH 7.6). The reaction was initiated by adding L-glutamine, and the decrease in absorbance at 340 nm was recorded every 30 s. Enzyme activity was calculated from the linear decrease in optical density.

Glutamate dehydrogenase (GDH) activity was determined as described by Lin and Kao (Lin and Kao 1996), with extraction identical to GS. The assay mixture contained 2.6 mL of assay stock solution (23.1 mmol·L⁻¹ α-ketoglutarate, 231 mmol·L⁻¹ NH₄Cl, and 115.4 mmol·L⁻¹ Tris-HCl buffer, pH 8.0), 0.1 mL of 6 mmol·L⁻¹ NADH, and 0.1 mL of 30 mmol·L⁻¹ CaCl₂. The reaction was started by adding 0.1 mL enzyme extract, and the decrease in absorbance at 340 nm was monitored for 3 min.

Aspartate aminotransferase (GOT) and alanine aminotransferase (GPT) activities were measured according to Zhu (Zhu et al.2021). Samples (0.1 g) were dried at 70 ℃ to constant weight, ground into powder, and extracted with pre-chilled extraction buffer. After 30 min of ice-bath incubation, the homogenate was centrifuged at 10,000 × g for 20 min at 4 ℃. The supernatant was collected for assay. For GOT activity, 0.5 mL enzyme extract was mixed with 4.5 mL reaction solution containing 0.1 mol·L⁻¹ Tris-HCl buffer (pH 7.8), 0.25 mmol·L⁻¹ EDTA-Na₂, and 0.5 mmol·L⁻¹ DL-α-ketoglutarate. After incubation at 37 ℃ for 1 h, the reaction was stopped with 1 mL of 80 g·L⁻¹ TCA. Then, 0.5 mL of 0.6 mol·L⁻¹ NaOH and 3 mL distilled water were added to 1 mL of the reaction mixture. Subsequently, 1 mL of 0.1 mol·L⁻¹ 2,4-dinitrophenylhydrazine reagent was added, followed by incubation at 37 ℃ for 30 min. Then, 5 mL distilled water and 2.5 mL of 4 mol·L⁻¹ NaOH were added. After centrifugation at 3000 × g for 5 min, the absorbance of the supernatant was measured at 520 nm using a 1-cm cuvette. GPT activity was assayed similarly, except that DL-α-ketoglutarate was replaced with pyruvate in the reaction mixture.

Nitrate nitrogen (NO₃⁻–N) content was determined according to Oliveira (Oliveira et al.2013). Leaf samples (1 g) were extracted in 10 mL of ethanol:chloroform:water (12:5:3, v/v/v) for 24 h. After centrifugation at 2000 × g for 30 min, one-fourth volume of chloroform was added. The aqueous phase was collected after 24 h of phase separation, concentrated at 37 ℃ for 15 h, and used for analysis. Then, 0.1 mL of sample was mixed with 0.4 mL of 5% (w/v) salicylic acid–sulfuric acid reagent, incubated at room temperature for 20 min, followed by slow addition of 9.5 mL of 8% (w/v) NaOH. After cooling to room temperature, absorbance was measured at 410 nm against a blank.

Ammonium nitrogen (NH₄⁺–N) content was measured as described by Chien and Kao (Chien and Kao et al.2000). Fresh plant material (0.1 g) was homogenized in 2 mL of 0.3 mmol·L⁻¹ H₂SO₄ (pH 3.5). The homogenate was centrifuged at 10,000 × g for 10 min. Then, 200 µL of supernatant was diluted to 4 mL with 0.3 mmol·L⁻¹ H₂SO₄ (pH 3.5). Subsequently, 0.5 mL of color reagent A (containing 0.5 g·L⁻¹ phenol and 0.25 g·L⁻¹ sodium nitroprusside) and 0.5 mL of color reagent B (containing 400 mL·L⁻¹ of 5% sodium hypochlorite and 0.25 g·L⁻¹ NaOH) were added. The mixture was incubated at 37 ℃ for 20 min with gentle shaking. Absorbance was measured at 625 nm against a blank prepared with distilled water.

Soluble protein concentration was determined using the Bradford method (Bradford 1976). Samples (0.1 g) were homogenized in 5 mL of phosphate buffer (pH 7.0), kept on ice for 30 min, and centrifuged at 12,000 × g for 15 min at 4 ℃. The supernatant was reacted with Coomassie Brilliant Blue G-250 reagent for 5 min, and absorbance was measured at 595 nm. Soluble protein content was calculated based on a standard curve.

Free amino acid content was measured according to Liu (Liu et al.2019). Samples (0.1 g) were extracted in 5 mL distilled water at 80 ℃ for 30 min. After centrifugation at 4000 × g for 10 min, 1 mL of supernatant was mixed with 2 mL ninhydrin reagent, heated in a boiling water bath for 15 min, cooled, and absorbance was measured at 570 nm.

Determination of key sugar contents

Soluble sugar content was determined using the anthrone-sulfuric acid method (Hu et al.2009). A 0.1 g sample was accurately weighed and extracted with 5 mL distilled water at 80 ℃ for 30 min. After cooling, the homogenate was centrifuged at 4000 rpm for 10 min. One milliliter of supernatant was mixed with 4 mL anthrone reagent and incubated in boiling water for 10 min. Following cooling, absorbance was measured at 620 nm.

Sucrose and fructose contents were determined according to the method of Cao (Cao et al.2019). A 0.1 g sample was weighed into a centrifuge tube, homogenized with 5 mL distilled water, and extracted at 80 ℃ for 30 min. After cooling to room temperature, the mixture was centrifuged at 4000 rpm for 10 min to collect the supernatant. One milliliter of supernatant was transferred into two separate tubes: one was mixed with 2 mL resorcinol reagent and 5 mL concentrated hydrochloric acid (for fructose determination), and the other with 2 mL resorcinol reagent and 5 mL concentrated sulfuric acid (for sucrose determination). The mixtures were incubated in boiling water for 10 min, cooled, and absorbance was measured at 480 nm (fructose) and 620 nm (sucrose), respectively. Sucrose and fructose concentrations were calculated based on standard curves.

Determination of Key Enzyme Activities in Sucrose Metabolism

The activities of sucrose synthase (SS) and sucrose phosphate synthase (SPS) were determined according to the method described by Chopra (Chopra et al.2000). Briefly, 0.1 g of sample was homogenized and incubated in the respective reaction buffers for SS (pH 7.0) or SPS (pH 7.5) at 37°C for 30 min. The reaction was terminated by adding DNS reagent, followed by heating in a boiling water bath for 5 min. After cooling, the absorbance was measured at 540 nm. Enzyme activity was calculated based on a standard curve and expressed as the amount of reducing sugars produced per unit time per gram of fresh weight (µmol·min⁻¹·g⁻¹ FW).

The activities of acid invertase (AI) and neutral invertase (NI) were determined according to the method of Tsai (Tsai et al.1970). Briefly, 0.1 g of fresh sample was homogenized and incubated in phosphate buffer (pH 4.6 for AI or pH 7.0 for NI) at 37°C for 30 min. The reaction was terminated by adding DNS reagent, followed by heating in a boiling water bath for 5 min. After cooling, the absorbance was measured at 540 nm. Enzyme activity was calculated based on a standard curve and expressed as the amount of reducing sugar produced per minute per gram of fresh weight (µmol·min⁻¹·g⁻¹ FW).

Determination of plant nitrogen concentration and calculation of nitrogen accumulation

Plant tissue nitrogen concentration was determined using the Zheng method (Zheng et al.2020). Mature samples, dried at 105 ℃, were ground to a fine powder. Approximately 0.2 g of sample was accurately weighed, digested with H₂SO₄–H₂O₂, and analyzed for nitrogen concentration using an automatic Kjeldahl apparatus.

Nitrogen accumulation (g) was calculated as:

Nitrogen accumulation (g) = Dry matter accumulation (g) × Nitrogen concentration (%)

Determination of plant carbon content

Total carbon content in plant tissues was determined using the potassium dichromate-sulfuric acid oxidation method (Starr et al.1964). Briefly, 0.005 g of dried soybean sample was weighed into a test tube, and a known volume of potassium dichromate-sulfuric acid solution was added. The mixture was allowed to stand for 30 min and then boiled for 10 min to ensure complete oxidation of organic matter. After cooling to room temperature, the solution was transferred to a conical flask, and 2–3 drops of sodium diphenylamine sulfonate indicator were added. The solution was then titrated with a standardized ferrous sulfate solution (of known concentration) until the color changed from purple to green, and the titration volume was recorded. A blank titration was performed simultaneously. The total carbon content in the plant sample was calculated based on the difference in titration volumes between the blank and the sample, the concentration of the ferrous sulfate standard solution (C, mol/L), and the mass of the dried sample (m, g), according to the established formula.

Data Processing and Plotting

Microsoft Excel 2020 was used for data entry and organization, and RStudio was used for data analysis and plotting. Data statistics were performed using one-way analysis of variance (ANOVA) and Duncan's multiple range test (p < 0.05). In Mantel analysis, Pearson's r characterizes the linear dependence between two variables, with values close to 0 indicating no correlation; values between 0.1 and 0.3 or -0.1 and − 0.3 indicate weak correlation; values between 0.3 and 0.5 or -0.3 and − 0.5 indicate moderate correlation; and values greater than 0.5 or less than − 0.5 indicate strong correlation. Mantel's r represents the similarity or dissimilarity between two distance matrices, with threshold ranges similar to those of Pearson's r. Mantel's p-value assists in determining the significance of Mantel's r, with p-values less than 0.05 typically considered statistically significant, indicating that the correlation between the two matrices is unlikely to be due to random chance. A p-value less than 0.01 indicates an even stronger level of significance. Conversely, a p-value greater than 0.05 is generally regarded as not significant, suggesting insufficient evidence to indicate a correlation between the two matrices.

Effects of Exogenous GABA on the Growth of Soybean Seedlings under Low Nitrogen Stress

As shown in Fig. 1, compared with the control (CK), low nitrogen stress (LN) significantly suppressed the morphological development of both shoot and root systems in soybean seedlings. In contrast, exogenous GABA application under low nitrogen stress (LN + GABA) markedly promoted growth-related traits at 20 and 30 days. Specifically, plant height, stem diameter, leaf area, leaf dry weight, stem dry weight, and root dry weight increased by an average of 44.05%, 21.33%, 35.62%, 30.49%, 38.60%, and 29.02%, respectively. Similarly, root length, root volume, root surface area, root tip number, and root activity were enhanced by averages of 22.93%, 51.78%, 13.68%, 18.78%, and 21.10%, respectively. Furthermore, the growth rate of LN + GABA-treated seedlings exhibited average increases of 39.21% and 38.48% at 20 and 30 days, respectively.

Effects of Exogenous GABA on Nitrogen Accumulation and Distribution in Soybean Seedlings under Low Nitrogen Stress

Effects of Exogenous GABA on the Activities of Key Nitrogen Metabolism Enzymes and the Contents of Nitrogenous Compounds in Soybean Seedlings under Low Nitrogen Stress

As shown in Fig. 2, compared with the control (CK), low nitrogen stress (LN) significantly inhibited the contents of major nitrogenous compounds as well as the activities of nitrate reductase (NR), glutamine synthetase (GS), glutamate synthase (GOGAT), and glutamate dehydrogenase (GDH) in both leaves and roots of soybean seedlings. In contrast, exogenous GABA application under low nitrogen stress (LN + GABA) markedly increased the contents of nitrate nitrogen, ammonium nitrogen, soluble protein, and free amino acids in leaves and roots at 5, 10, 20, and 30 days, with average increases ranging from 11.56% to 18.67%, 12.95% to 21.94%, 32.12% to 31.06%, and 26.06% to 52.06%, respectively. Concurrently, the activities of NR, GS, GOGAT, and GDH were significantly enhanced in both organs. In leaves, the average increases were 11.65%, 17.40%, 29.74%, and 18.67%, respectively. In roots, the activities of GS, GOGAT, and GDH increased by an average of 11.96%, 51.99%, and 26.60%, respectively. Conversely, the activities of glutamate-oxaloacetate transaminase (GOT) and glutamate-pyruvate transaminase (GPT) were significantly reduced, with average decreases of 24.19% and 46.54% in leaves, and 7.85% and 12.96% in roots, respectively.

Effects of Exogenous GABA on Nitrogen Content, Accumulation, and Distribution in Soybean Plants under Low Nitrogen Stress

As shown in Table 1, compared with the control (CK), low nitrogen stress (LN) significantly inhibited nitrogen content and nitrogen accumulation in the leaves, stems, roots, and whole plants of soybean. In contrast, exogenous GABA application under low nitrogen stress (LN + GABA) markedly increased nitrogen content in the leaves and roots at both 20 and 30 days, as well as in the whole plants at 30 days, with average increases of 10.75%, 19.26%, and 5.29%, respectively. Furthermore, nitrogen accumulation in the leaves, stems, roots, and whole plants was also significantly enhanced by the LN + GABA treatment at both time points, showing average improvements of 52.09%, 32.67%, 49.76%, and 47.59%, respectively.

Table 1
Effects of exogenous GABA on nitrogen content, accumulation and nitrogen composition of soybean plants under low nitrogen stress
Days after treatment	treatment	Leaf (mg·plant)			Stem (mg·plant)			Root (mg·plant)			Plant (mg·plant)
Days after treatment	treatment	Nitrogen content	Nitrogen accumulation	Percentage of total plant	Nitrogen content	Nitrogen accumulation	Percentage of total plant	Nitrogen content	Nitrogen accumulation	Percentage of total plant	Nitrogen content	Nitrogen accumulation
	CK	7.48 ± 0.86a	8.34 ± 0.73a	42.46%	6.02 ± 0.44b	7.61 ± 0.57a	42.46%	8.87 ± 1.01c	3.7 ± 0.36a	42.46%	130.06 ± 0.86a	19.65 ± 0.95a
20d	LN	5.01 ± 0.72c	3.04 ± 0.26c	34.75%	9.10 ± 0.95a	3.38 ± 0.18c	34.75%	9.55 ± 0.72b	2.33 ± 0.17c	34.75%	123.58 ± 0.93c	8.75 ± 0.46c
	LN + GABA	6.15 ± 0.81b	5.24 ± 0.34b	36.77%	4.71 ± 0.73c	6.25 ± 0.45b	36.77%	11.76 ± 1.02a	2.76 ± 0.27b	36.77%	127.28 ± 0.79b	14.24 ± 0.65b
	CK	6.02 ± 0.44a	13.85 ± 0.73a	42.22%	2.77 ± 0.27c	13.46 ± 0.99a	42.22%	10.64 ± 0.73b	5.5 ± 0.51a	42.22%	125.30 ± 0.62b	32.81 ± 1.83a
30d	LN	5.61 ± 0.43b	5.44 ± 0.37c	36.35%	6.20 ± 0.49a	6.22 ± 0.13c	36.35%	9.65 ± 0.52c	3.3 ± 0.32c	36.35%	116.93 ± 0.89c	14.94 ± 0.66c
	LN + GABA	5.78 ± 0.62b	8.26 ± 0.81b	33.77%	4.90 ± 0.56b	11.58 ± 0.62b	33.77%	11.98 ± 0.66a	4.63 ± 0.39b	33.77%	127.82 ± 0.66a	24.47 ± 1.68b

Note: Different letters indicate significant differences in vertical comparison between treatments (P<0.05). Same below.

Effects of Exogenous GABA on Key Physiological Processes of Photosynthetic Carbon Assimilation in Soybean Seedlings under Low Nitrogen Stress

Effects of Exogenous GABA on Photosynthetic Pigment Content and Photosynthetic Gas Exchange Parameters in Soybean Seedlings under Low Nitrogen Stress

As shown in Fig. 3, compared with the control (CK), low nitrogen stress (LN) significantly suppressed photosynthetic pigment contents and photosynthetic gas exchange parameters in soybean seedlings. In contrast, exogenous GABA application under low nitrogen stress (LN + GABA) notably enhanced the contents of chlorophyll a (Chl a), chlorophyll b (Chl b), total chlorophyll (Chl), and carotenoids (Car) at 5, 10, 20, and 30 days, with average increases of 44.88%, 46.23%, 45.44%, and 44.96%, respectively. Moreover, the LN + GABA treatment significantly improved photosynthetic gas exchange parameters, including the net photosynthetic rate (Pₙ), transpiration rate (T_r), and stomatal conductance (Gₛ), which increased by an average of 71.17%, 34.56%, and 50.79%, respectively. By contrast, the intercellular CO₂ concentration (C_i) was significantly reduced, with an average decrease of 5.34%.

Effects of Exogenous GABA on Sucrose Metabolism in Soybean Seedlings under Low Nitrogen Stress

As shown in Fig. 4, compared with the control (CK), low nitrogen stress (LN) significantly suppressed the activities of sucrose synthase (SS) and sucrose phosphate synthase (SPS), as well as sucrose content in both leaves and roots of soybean plants, whereas it markedly promoted the activities of neutral invertase (NI) and acid invertase (AI), together with the contents of fructose and soluble sugars. In contrast, exogenous GABA application under low nitrogen stress (LN + GABA) significantly enhanced the activities of SS, SPS, NI, and AI, and increased the contents of sucrose, fructose, and soluble sugars in soybean leaves and roots at 5, 10, 20, and 30 days. The average increases were 20.78% and 13.39%, 25.07% and 22.10%, 13.43% and 14.29%, 14.52% and 12.08%, 42.15% and 37.01%, 18.41% and 19.16%, and 17.22% and 12.96%, respectively.

Effects of Exogenous GABA on Carbon Content and Carbon/Nitrogen Ratio in Soybean Seedlings under Low Nitrogen Stress

As shown in Fig. 5, compared with the control (CK), low nitrogen stress (LN) significantly reduced the carbon content and carbon/nitrogen (C/N) ratio in the leaves, stems, roots, and whole plants of soybean. In contrast, exogenous GABA application under low nitrogen stress (LN + GABA) markedly increased the carbon content in the leaves, stems, roots, and whole plants at 20 and 30 days, with average increases of 3.85%, 2.73%, 10.33%, and 5.72%, respectively. Meanwhile, the C/N ratio was significantly enhanced in the leaves at 30 days, as well as in the stems and whole plants at both 20 and 30 days, showing average improvements of 2.75%, 36.93%, and 5.52%, respectively.

Comprehensive Analysis

As shown in Fig. 6A, a highly significant positive correlation was observed between root volume (RVol) and root surface area (RSur), indicating coordinated expansion of the root physical architecture. Furthermore, RVol was strongly positively correlated with both photosynthetic performance and nitrogen accumulation, underscoring the pivotal role of a well-developed root system in enhancing photosynthetic capacity and total nitrogen acquisition. Additionally, RVol showed highly significant positive correlations with the activities of nitrogen assimilation enzymes and the contents of nitrogenous compounds in both leaves and roots, demonstrating that root development drives nitrogen assimilation and accumulation in aboveground and belowground organs. The nitrogen metabolism network within the root system appeared highly integrated, with widespread significant positive correlations among all measured indicators.

As shown in Fig. 7B, a highly significant positive correlation was observed between plant morphology and nitrogen metabolism as a whole. Key nitrogen metabolism enzymes and major nitrogenous compounds in both leaves and roots exhibited widespread strongly significant positive correlations with each other. Plant morphology showed an overall significant positive correlation with photosynthetic gas exchange parameters, whereas its correlations with sucrose metabolism indicators were generally weak or non-significant.The carbon/nitrogen (C/N) ratio demonstrated a highly significant positive correlation with photosynthetic gas exchange parameters overall, particularly exhibiting a very strong positive correlation with net photosynthetic rate (Pₙ). Similarly, the C/N ratio showed a highly significant positive correlation with sucrose metabolism indicators at the overall level; however, soluble sugars and sucrose synthase activity often correlated negatively with the C/N ratio. Although the C/N ratio was significantly positively correlated with nitrogen metabolism indicators collectively, Pearson correlation analysis frequently revealed a negative trend. A high degree of internal coordination among physiological indicators was observed: key nitrogen metabolic enzymes and major nitrogen-containing compounds in both leaves and roots showed consistently strong positive correlations with one another.

Nitrogen deficiency inevitably restricts the synthesis of nitrogenous compounds—such as nucleic acids, amino acids, and proteins—that play crucial roles in plant growth and development, thereby exerting broad detrimental effects on plant performance. It particularly limits chlorophyll content and the synthesis of photosynthetic enzymes, leading to stunted growth, thinner stems, and significantly reduced biomass. Consistent with this, the present study demonstrated that low nitrogen stress indeed suppressed the growth of soybean seedlings. However, exogenous GABA application under low nitrogen stress significantly improved morphological traits of both roots and shoots, and promoted dry matter accumulation (Fig. 1). Correspondingly, physiological activities related to nitrogen metabolism and photosynthesis were also enhanced (Fig. 2). Based on these findings, we propose that exogenous GABA enhances nitrogen metabolism intensity in soybean seedlings under low nitrogen stress, thereby facilitating photosynthetic performance and ultimately improving phenotypic growth.

Upregulation of the GS/GOGAT cycle is critical for the efficient conversion of ammonium nitrogen into organic nitrogen, a process that is typically suppressed under nitrogen stress. The results of this present study demonstrate that exogenous GABA application significantly increased the contents of nitrate nitrogen, ammonium nitrogen, soluble protein, and free amino acids in both leaves and roots of soybean under low nitrogen stress (Fig. 2A, B), while enhancing the activities of key nitrogen assimilation enzymes, including nitrate reductase (NR), glutamine synthetase (GS), glutamate synthase (GOGAT), and glutamate dehydrogenase (GDH) (Fig. 2C, D). These findings indicate that GABA directly enhances the primary nitrogen assimilation pathway in soybean seedlings under low nitrogen stress, particularly facilitating the GS/GOGAT cycle. This enhancement not only promotes efficient conversion of ammonium into organic nitrogen but also improves nitrogen transport and utilization within the plant, thereby significantly increasing nitrogen use efficiency. These results are consistent with those reported by Barbosa (Barbosa et al. 2010). in Arabidopsis thaliana.

The study by Li (Li et al. 2025)demonstrated that GABA application significantly enhanced the activities of GS and GOGAT in rice leaves under low nitrogen stress. They further established a clear link between increased enzyme activities and improvements in nitrogen assimilation efficiency, nitrogen use efficiency (NUE), and final grain yield, thereby providing a complete evidence chain supporting the role of GABA in enhancing nitrogen utilization in crop production.Chen (Chen et al. 2020) further revealed that exogenous GABA application upregulates the expression of glutamine synthetase (GLN1;2) and glutamate synthase (GLU1) genes under low nitrogen stress, offering a molecular explanation for the observed increase in enzymatic activities. Additionally, Shelp (Shelp et al. 1999)highlighted that the GS/GOGAT cycle relies on α-ketoglutarate as an amino acceptor, and proposed that the interaction between GABA metabolism and the tricarboxylic acid (TCA) cycle may supply critical precursors for nitrogen assimilation, thereby physiologically supporting the maintenance or enhancement of GS/GOGAT activity.These two mechanisms collectively explain, at both molecular and physiological levels, the intrinsic role of exogenous GABA in promoting GS/GOGAT activity. The enhanced nitrogen assimilation and utilization capacity facilitates the synthesis of essential biomolecules such as proteins and nucleic acids, which directly accounts for the restoration of plant biomass observed in the LN + GABA treatment.

Numerous studies have confirmed that root phenotype and vitality are closely associated with nutrient acquisition under low nitrogen stress (Lynch et al. 2019; Hirel et al. 2007). We employed Mantel test to evaluate the correlation network among morphological traits, metabolic activities, and functional status (Fig. 7). The analysis revealed strong positive correlations between root vitality/root volume and both total nitrogen accumulation and net photosynthetic rate (Pₙ), highlighting the central role of a well-developed root system in enhancing nitrogen acquisition and whole-plant carbon assimilation capacity. Furthermore, root vitality and root volume were also significantly positively correlated with the activities of GS and GOGAT, as well as soluble protein content in both leaves and roots.Pei (Pei et al. 2022)suggested that GABA-promoted root growth in woody plant root system is a key factor in improving nitrogen nutritional status. This effect may be attributed to the ability of exogenous GABA application to upregulate the expression of auxin (IAA)-responsive genes and modulate genes involved in cell wall loosening and elongation, thereby regulating cell elongation and division and ultimately promoting root growth, particularly in primary and lateral roots. Additionally, Ramesh (Ramesh et al. 2018)reported that GABA can bind to the ALMT (aluminum-activated malate transporter) protein on the plasma membrane of root cells and regulate SOS2-LIKE PROTEIN KINASE 24 (PKS24), consequently influencing the activity of H⁺-ATPase and K⁺/H⁺ antiporters. This regulation directly affects turgor pressure and cell elongation in roots, thereby modulating root system architecture. The present findings, particularly those illustrated in Fig. 1C and Fig. 7A, are consistent with and further substantiate the results reported in previous studies.

Kant (Kant et al. 2011) suggested that the decline in photosynthesis under low nitrogen stress is primarily attributed to reduced light energy capture capacity caused by impaired chlorophyll biosynthesis, as well as decreased content and activity of key enzymes in the photosynthetic carbon reduction cycle, such as Rubisco and FBPase, since both processes heavily rely on nitrogen supply. Therefore, any measures that improve the plant’s nitrogen status—such as exogenous GABA application—are expected to alleviate photosynthetic inhibition by restoring chlorophyll and photosynthetic enzyme levels. Our results showed that the LN + GABA treatment significantly increased the contents of Chl a, Chl b, and total chlorophyll, with average increases ranging from 44.88% to 46.96% (Fig. 4A), which was closely associated with enhanced nitrogen accumulation. Although Rubisco activity was not directly determined in this study, the marked improvement in Pₙ (average increase of 71.17%) (Fig. 4B) indirectly reflects enhanced functionality of the photosynthetic apparatus.On the other hand, Mantel analysis further revealed that the carbon/nitrogen (C/N) ratio was strongly positively correlated with photosynthetic gas exchange parameters overall, exhibiting a particularly strong correlation with net photosynthetic rate (Pn) (Fig. 7B), indicating that maintaining an appropriate C/N ratio is a key factor in promoting photosynthesis. Yuan (Yuan et al. 2023)also reported that under low nitrogen stress, exogenous GABA regulates the flux of carbon skeletons (such as α-ketoglutarate) through the GABA shunt, thereby helping to mitigate carbon excess (high C/N ratio) caused by nitrogen deficiency and creating a favorable metabolic environment for normal photosynthetic function.Furthermore, improved stomatal conductance (Gₛ) may be another mechanism by which exogenous GABA enhances photosynthesis in soybean seedlings under low nitrogen stress. Under such conditions, stomatal conductance often decreases to reduce water loss, which simultaneously limits CO₂ uptake. GABA may help maintain better stomatal opening by improving the overall physiological status of the plant, thereby facilitating CO₂ diffusion into mesophyll cells for photosynthetic carbon assimilation (Li et al. 2017). In summary, exogenous GABA effectively alleviates the inhibitory effects of low nitrogen stress on soybean growth through multifaceted synergistic regulation. It not only directly enhances the activities of key nitrogen metabolism enzymes and promotes nitrogen assimilation but also improves carbon metabolism, photosynthetic performance, and root development, collectively forming an integrated physiological regulatory network. Mantel test systematically revealed a cascade effect of "root development → enhanced nitrogen metabolism → improved photosynthesis → promoted plant growth," and highlighted the central regulatory role of the carbon/nitrogen ratio. These findings provide novel insights into the mechanistic role of GABA in plant stress responses and establish a theoretical foundation for developing GABA-based agricultural regulation strategies.

Exogenous GABA significantly alleviates low nitrogen stress in soybean by synergistically improving root architecture and vitality, enhancing nitrogen assimilation, and promoting nitrogen remobilization efficiency. The core mechanism involves optimized root configuration facilitating nitrogen acquisition, coupled with synchronized improvement in nitrogen assimilation and redistribution capacity, ultimately achieving a coordinated balance between carbon and nitrogen metabolism and optimizing photosynthetic performance. This study provides key theoretical support for the use of GABA as a biostimulant to improve nitrogen use efficiency and reduce dependence on synthetic nitrogen fertilizers in sustainable agricultural practices. Our findings elucidate the hitherto unknown physiological mechanism through which γ-aminobutyric acid (GABA) mitigates low-nitrogen stress and facilitates soybean growth, paving the way for the design of next-generation biostimulants.

Author contribution: Minjia Lu and Yuanhao Duan: Conceptualisation, Investigation, Funding acquisition, Writing and Reviewing and Editing;Peiyu Chu, Yaokun Wu, Xunqi Chen, Sijia Wen, Xufan Zhang, and Zihao Zhang: Investigation, Project administration, Validation, Formal analysis, Resources;Xijun Jin: Supervision

Institutional Review Board Statement: Not applicable

Informed Consent Statement: Not applicable

Data Availability Statement: All data analysed during the current study are included in this published article. The detailed data can be provided on reasonable request.

Acknowledgements:This study was supported by An Integrated Model for Planosol Amendment with Rapid Fertility Improvement and Synergistic Productivity Enhancement in the Sanjiang Plain (2022YFD1000105),Heilongjiang Province’s “Revealing the List and Commanding the Leaders” Scientific and Technological Research Project (2021ZXJ05B011), Natural Science Foundation of Heilongjiang Province(LH2022C063).

Conflicts of interest: The authors declare no conflicts of interest in the current study.

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γ-Aminobutyric acid enhances nitrogen use efficiency in soybean through coordinated regulation of root architecture and nitrogen metabolism under low nitrogen stress

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Abstract

Figures

Introduction

Materials and Methods

Plant materials and growth conditions

Experimental Design

Composition of nutrient solutions

Sampling schedule

Measurement Indices and Methods

Measurement of morphological and dry matter-related parameters

Determination of root activity

Photosynthetic Indices

Determination of photosynthetic pigment content

Measurement of photosynthetic gas exchange parameters

Determination of key nitrogen metabolism enzyme activities and nitrogen-containing compounds

Determination of key sugar contents

Determination of Key Enzyme Activities in Sucrose Metabolism

Determination of plant nitrogen concentration and calculation of nitrogen accumulation

Determination of plant carbon content

Data Processing and Plotting

Results

Effects of Exogenous GABA on the Growth of Soybean Seedlings under Low Nitrogen Stress

Effects of Exogenous GABA on Sucrose Metabolism in Soybean Seedlings under Low Nitrogen Stress

Comprehensive Analysis

Discussion

Conclusion

Declarations

References

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