Nutrient addition and light supplementation modulate the growth of Glechoma longituba and soil microbial communities

Abstract

BACKGROUND

The interactive effects of nutrient supply and light supplementation on medicinal plants remain unclear. This study aimed to investigate these effects on Glechoma longituba, a widely used traditional medicinal plant.

METHODS

This greenhouse experiment used a fully factorial design (with/without nutrients, with/without supplemental lighting) to investigate these effects on G. longituba.

RESULTS

Nutrient addition and supplemental lighting synergistically increased total mass and node number. Supplemental lighting enhanced the bioactive and nutritional constituents. Nutrient addition increased the levels of protein and sugars but reduced the levels of flavonoids and chlorogenic acid. However, supplemental light partially reversed the decreases in chlorogenic acid. Nutrients were the primary driver of microbial shifts, reducing bacterial diversity but increasing fungal diversity and altering metabolic pathways. Supplemental lighting affected bacterial communities only when no nutrients were added. Bacterial communities correlated with aboveground biomass and root–shoot ratio, indicating roles in nutrient cycling and plant growth promotion. Fungi correlated only with root–shoot ratio, suggesting functions in carbon allocation and resource partitioning.

CONCLUSION

Nutrient addition and supplemental lighting synergistically enhance growth but have contrasting effects on medicinal quality of G. longituba. Supplemental lighting improves yield and medicinal constituents, mitigating medicinal quality decline from nutrient addition. Nutrients dominate soil microbial community shifts, while light affects bacteria only under nutrient limitation. These findings reveal the differential regulatory effects of light and nutrients on the yield and medicinal quality of G. longituba, and highlight the importance of balanced nutrient and light management for the sustainable cultivation of this medicinal plant. © 2026 Society of Chemical Industry.

INTRODUCTION

Medicinal plants have served as a cornerstone of traditional healthcare systems for millennia, particularly in regions with rich phytotherapeutic traditions such as China and India.^{1, 2, 3} In recent decades, global demand for these plants has surged, driven by several key factors: the rising incidence of chronic diseases has intensified the search for safer, natural therapeutic alternatives^{4, 5, 6}; a paradigm shift in health consciousness has encouraged the adoption of natural remedies for preventive care^{7, 8}; and the expanding pharmaceutical industry's need for plant‐derived active compounds continues to grow.^{9, 10} This escalating demand poses significant challenges for medicinal plant cultivation.^{11, 12} A primary challenge lies in the urgent need to enhance yield through scientific cultivation methods. Crucially, however, the therapeutic efficacy of medicinal plants is predominantly determined by their secondary metabolite profiles (e.g. flavonoids, terpenoids, alkaloids), which are highly sensitive to environmental conditions.^{13, 14, 15} Consequently, strategies to boost production must simultaneously ensure the preservation and consistency of these plants' unique quality and medicinal value.

The growth and metabolic processes of plants are fundamentally governed by nutrient availability and light conditions.^{16, 17, 18} Soil nutrients supply essential elements for structural development and physiological functions, directly influencing biomass accumulation, metabolic pathways, and, ultimately, yield and quality.^{19, 20, 21} Simultaneously, light acts as both the primary energy source for photosynthesis and a key environmental signal regulating photomorphogenesis, photosynthetic efficiency, and the biosynthesis of secondary metabolites.^{22, 23, 24} In conventional agriculture, nutrient management and light environment control are well‐established strategies for improving crop productivity.^{25, 26, 27} For medicinal plants, however, the optimization of cultivation conditions must extend beyond mere yield enhancement to encompass the quality and standardized concentration of bioactive constituents, which are often modulated by these environmental factors.^{28, 29, 30}

A critical knowledge gap persists regarding the potential antagonisms or synergies between yield enhancement and medicinal quality under modified cultivation practices. While increased nutrient availability and extended photoperiods have demonstrated significant positive effects on the biomass production of medicinal plants, their concurrent impact on quality remains ambiguous.^{14, 31, 32} For instance, while adequate nutrient supply promotes vigorous growth, excessive or imbalanced fertilization may alter internal resource allocation, potentially diverting resources away from the synthesis of secondary metabolites and thereby compromising quality.^{30, 31, 33} Similarly, although optimized light conditions can enhance photosynthetic carbon assimilation, light intensity and duration requirements are species‐specific. Both light deficiency and excess can disrupt secondary metabolic pathways, adversely affecting the accumulation of therapeutically relevant compounds.^{34, 35, 36} Therefore, a systematic investigation integrating plant growth, phytochemical metabolism, and rhizosphere microbial communities is essential to delineate the optimal growth conditions for specific medicinal plants, aiming for synergistic enhancement of both yield and quality to support sustainable cultivation.

Glechoma longituba is widely used in traditional medicine owing to its abundant bioactive constituents, specifically flavonoids and chlorogenic acid, which are responsible for its anti‐inflammatory, antioxidant, and therapeutic activities.^{33, 37, 38} These secondary metabolites are extremely sensitive to environmental factors, especially nutrient availability and light conditions.^{14, 31} Generally, an appropriate nutrient supply facilitates primary metabolism and plant growth. Nevertheless, excessive or imbalanced nutrients frequently divert resource allocation from secondary metabolic pathways to biomass accumulation, thus reducing the concentrations of flavonoids, phenolic acids, and other vital medicinal components.^{30, 31, 39} Additionally, light acts as a crucial regulator of the phenylpropanoid pathway, which controls the biosynthesis of both flavonoids and chlorogenic acid in medicinal plants.^{24, 34, 40} Research indicates that appropriate light supplementation can enhance the activities and expression of key enzymes in this pathway, such as phenylalanine ammonia‐lyase and chalcone synthase, thereby effectively promoting the accumulation of flavonoids and chlorogenic acid in G. longituba.^{38, 41, 42} However, the interactive effects of nutrient addition and light supplementation on these medicinal constituents remain unclear, and the underlying regulatory mechanisms have not been systematically explored.

Soil microorganisms are pivotal components of agroecosystems, functioning as sensitive indicators of soil health and playing essential roles in nutrient cycling, organic matter decomposition, and the maintenance of plant health.^{43, 44, 45} For medicinal herbs, nutrient addition exerts a strong influence on rhizosphere microbial communities by selectively favoring copiotrophic or oligotrophic taxa, while light variations modify root exudation and carbon allocation, thereby indirectly driving shifts in the microbial community.^{46, 47, 48} Most studies have concentrated on the effects of nutrients on soil microbes. However, the way in which supplemental light interacts with nutrients to shape the rhizosphere microbial communities of medicinal plants remains inadequately understood.^{49, 50, 51} We hypothesize that the manipulation of nutrients and light alters plant growth and metabolism. Subsequently, through plant–soil feedbacks, this reshapes the diversity, community structure, and functional pathways of the rhizosphere microbial community.

To address these research gaps, we conducted a controlled greenhouse experiment to investigate the individual and interactive effects of nutrient supplementation and photoperiod extension on the growth, phytochemical quality, and associated rhizosphere microbial communities of G. longituba, an important species in traditional Chinese medicine. Specifically, we tested two hypotheses: (1) that both nutrient addition and light supplementation would enhance plant biomass and promote the accumulation of key bioactive and nutritional constituents and (2) that these treatments would induce significant shifts in soil microbial community structure and diversity.

MATERIALS AND METHODS

Plant material and growth conditions

Glechoma longituba (Nakai) Kupr. (Lamiaceae), a perennial stoloniferous herb with clonal propagation capacity,^{41, 42, 52} was selected for this study. This species is widely distributed across China (except Qinghai, Gansu, Xinjiang, and Tibet), typically inhabiting moist environments like woodland edges and stream banks.^{53, 54, 55} The entire plant is of medicinal value, rich in bioactive compounds such as chlorogenic acid and flavonoids, and is traditionally used to treat inflammatory and respiratory disorders.^{33, 37, 38, 56} Plant material was sourced from a commercial supplier in Shanghai and pre‐cultivated for acclimatization in a greenhouse at Handan University (36°34′ N, 114°29′ E), Handan, China.

On 13 May 2024, 20 uniform fragments, each containing a single node with two fully expanded opposite leaves and an axillary bud, were excised from the stock plants. Each fragment was transplanted into an individual pot (upper diameter: 20 cm; height: 15.4 cm) filled with a 1:1 (v/v) mixture of vermiculite and soil. The soil (pH: 7.8; total organic matter: 17.1 g kg⁻¹; total N: 0.83 g kg⁻¹; total C: 20.37 g kg⁻¹; total P: 0.8 g kg⁻¹) was collected from the 0–20 cm topsoil layer on the campus of Handan University. The soil was chosen for feasibility and because it represents the local soil type, allowing for reasonable extrapolation of our findings to similar soils. The collected soil was sieved through a 2 mm mesh and air‐dried.

Experimental design and treatments

A complete 2 × 2 factorial design was implemented, with factors being nutrient addition (with or without) and light supplementation (with or without), resulting in four treatment combinations. Each treatment was replicated five times, totaling 20 experimental units. For the nutrient addition treatments, a controlled‐release fertilizer (4 g L⁻¹, N:P:K = 14:10:13; The Scotts Miracle‐Gro Co., USA) was uniformly incorporated into the growth substrate. Supplemental lighting was provided by full‐spectrum LED grow lights (WEGA‐T8, 30 W, 400–700 nm; Guixiang Optoelectronics Co. Ltd, China), positioned 20 cm above the plant canopy. The supplemental lights operated daily from 20:00 to 04:00, extending the natural photoperiod by 8 h. This schedule was chosen because the period from 20:00 to 04:00 fell completely within the nighttime hours under our seasonal and geographic conditions (no natural sunlight), ensuring that the light supplementation created a clear contrast in photoperiod without overlapping with natural daylight.

The experiment was conducted over 50 days, from 13 May to 2 July 2024. Throughout the study, the greenhouse environment was monitored with a temperature logger, recording data at 2 h intervals. The average air temperature and relative humidity were 28.8 °C and 46.6%, respectively. Pots were watered daily to maintain soil moisture.

Plant harvest and growth analysis

At harvest, plants were carefully uprooted and rinsed with water to remove adhering soil. The node number was recorded for each plant. Subsequently, plants were separated into aboveground (leaves and stolons) and root mass. All plant tissues were subjected to enzyme deactivation at 105 °C for 20 min, followed by drying at 70 °C until a constant mass was achieved. Dry weights of aboveground and root parts were measured, and the root–shoot ratio was calculated. For each treatment, four experimental replicates were randomly selected to undergo high‐throughput sequencing analysis of soil microbial communities. The soil closely adhering to the root system (root‐zone soil) was collected from each pot in these replicates, sieved (2 mm mesh) to remove root fragments and debris, and stored at −40 °C for subsequent molecular analysis.

Biochemical analyses

The content of key biochemical constituents in aboveground parts was determined using standard spectrophotometric assays. The total flavonoid content was quantified according to a modified aluminium chloride method. ⁵⁷ Chlorogenic acid content was determined following the protocol described by Oteef et al. ⁵⁸ Soluble sugar content was measured using the anthrone–sulfuric acid method, and soluble protein concentration was assessed via the Coomassie Brilliant Blue G‐250 binding assay. ⁵⁹

Soil DNA extraction and amplicon sequencing

Genomic DNA was extracted from soil microorganisms using a FastDNA SPIN Kit (MP Biomedicals, Santa Ana, CA, USA) following the manufacturer's instructions. The V4 region of bacterial 16S rRNA gene was amplified with primers 515F (5′‐GTGYCAGCMGCCGCGGTAA‐3′) and 806R (5′‐GACTACNVGGGTWTCTAAT‐3′) as previously described. ⁶⁰ For fungal community analysis, the ITS1 region of the internal transcribed spacer (ITS) was targeted using primers ITS1f (5′‐CTTGGTCATTTAGAGGAAGTAA3′) and ITS2 (5′‐GCTGGTTCTTCATCGATGC‐3′) following the same reference methodology. ⁶⁰ Purified amplicons were subjected to paired‐end sequencing on an Illumina NovaSeq platform (Illumina Inc., San Diego, CA, USA) at Shanghai Personal Biotechnology Co. Ltd (Shanghai, China).

Bioinformatic and statistical analysis

Two‐way analysis of variance (ANOVA) tests were performed to examine main and interactive effects of nutrient addition and supplemental lighting on plant growth, biochemical constituents, and microbial community metrics. All analyses were performed using SPSS Statistics 22.0 (IBM Corporation, USA). Soluble protein content could not be measured in two experimental replicates without both nutrient addition and supplemental lighting, as well as in one replicate without nutrient addition but with supplemental lighting, due to insufficient sample amounts. Additionally, soluble sugar content could not be determined in one replicate without both nutrient addition and supplemental lighting for the same reason. These samples were therefore excluded from further analyses.

Raw sequence data were filtered and preprocessed using QIIME2. ⁶¹ The Dada2 method was employed for trimming adapter sequences and primers, removing low‐quality sequences, chimeras, denoising, and splicing. The resulting deduplicated sequences were defined as amplicon sequence variants (ASVs), with singleton ASVs excluded during subsequent analyses. Bacterial taxonomies were assigned through alignment against the Silva database, ⁶² while fungal taxonomies were assigned using the UNITE database. ⁶³ Subsequently, resampling was performed on bacterial and fungal ASV tables to achieve a uniform count of 99 294 and 74 267 sequences per sample, respectively.

The diversity of bacterial and fungal communities was assessed by calculating Simpson index in QIIME2. ⁶⁴ Principal coordinate analysis (PCoA) was used to visualize the beta diversity across different treatments. Functional pathways of microbial taxa across treatments were predicted using PICRUSt2 (Phylogenetic Investigation of Communities by Reconstruction of Unobserved States) based on the MetaCyc database. ⁶⁵ To characterize microbial–environmental factor associations and environmental factor pairwise relationships, we employed Mantel tests and Pearson correlation analysis, integrating statistical visualization of correlation strengths and significances.

RESULTS

Plant growth and morphological responses

Nutrient treatment exerted significant main effects on all plant growth measurements (Table 1). Supplemental lighting significantly affected biomass (total mass, aboveground mass, and root mass) and node number (Table 1). Biomass and node number were significantly higher in treatments with nutrients compared to those without nutrients, whereas root–shoot ratio exhibited the opposite trend (Table 1; Figs 1 and 2). Plants under supplemental lighting showed significantly greater biomass and node number than those without supplemental lighting (Table 1; Figs 1 and 2(A)). The interaction between nutrient addition and light supplementation significantly affected total biomass and node number (Table 1). Specifically, under supplemental lighting conditions, treatments with nutrients demonstrated greater increases in total biomass and node number compared to conditions without supplemental lighting (Fig. 1(A),(C)).

Table 1.

Two‐way ANOVA results for the effects of nutrient addition and light supplementation on total mass, aboveground mass, root mass, node number, and root–shoot ratio of Glechoma longituba

Variable	df	Nutrient (N)		Light (L)		N × L
		F	P	F	P	F	P
Total mass	1,16	93.859	<0.001	24.481	<0.001	9.411	0.007
Aboveground mass a	1,16	86.643	<0.001	18.662	0.001	3.706	0.072
Root mass	1,16	15.160	0.001	6.742	0.019	0.588	0.454
Node number a	1,16	53.786	<0.001	26.281	<0.001	7.602	0.014
Root–shoot ratio b	1,16	50.120	<0.001	1.289	0.273	3.172	0.094

F and P values and the number of degrees of freedom are presented. Values are in bold where P < 0.05.

^a Square root transformation.

^b Natural log transformation.

Figure 1.

Effects of nutrient addition and light supplementation on total mass (A), aboveground mass (B), root mass (C), node number (D), and root–shoot ratio (E) of Glechoma longituba. Bars and vertical lines are means and SE.

Figure 2.

Effects of nutrient addition and light supplementation on total flavonoids (A), chlorogenic acid (B), protein (C), and soluble sugar (D) of Glechoma longituba. Bars and vertical lines are means and SE.

Accumulation of bioactive and nutritional constituents

Nutrient addition and light supplementation had significant effects on the accumulation of total flavonoids, chlorogenic acid, protein, and soluble sugar (Table 2). The levels of total flavonoids and chlorogenic acid were reduced in treatments with nutrient addition, while protein and soluble sugar showed the opposite pattern (Fig. 2). All measured bioactive and nutritional constituents increased under conditions of light supplementation (Fig. 2). A significant interactive effect of nutrient addition and light supplementation was observed on chlorogenic acid content (Table 2). Specifically, in the absence of supplemental lighting, nutrient addition led to a more pronounced decrease in chlorogenic acid compared to conditions with supplemental lighting (Fig. 1(B)).

Table 2.

Two‐way ANOVA results for the effects of nutrient addition and light supplementation on contents of total flavonoids, chlorogenic acid, protein, and soluble sugar of Glechoma longituba

Variable	df	Nutrient (N)		Light (L)		N × L
		F	P	F	P	F	P
Total flavonoids	1,16	6.478	0.022	6.093	0.025	2.862	0.110
Chlorogenic acid	1,16	13.666	0.002	11.010	0.004	7.133	0.017
Protein	1,13	14.145	0.002	22.852	<0.001	0.686	0.423
Soluble sugar	1,15	10.672	0.005	5.562	0.032	1.567	0.230

All data were transformed to natural log. F and P values and the number of degrees of freedom are presented. Values are in bold where P < 0.05.

Soil microbial community structure and diversity

After quality filtering, a total of 1 774 819 bacterial 16S rRNA and 1 643 966 fungal ITS high‐quality sequences were obtained for community analysis. At the phylum level, analysis of bacterial community composition revealed significant shifts in relative abundance across the experimental treatments with nutrient addition and light supplementation (Fig. 3(A); Table 3). Specifically, nutrient addition significantly increased the relative abundance of Proteobacteria, Actinobacteria, and Crenarchaeota, while decreasing that of Acidobacteria, Chloroflexi, Planctomycetes, Myxococcota, and Methylomirabilota. Supplemental lighting significantly increased the relative abundance of Proteobacteria and Myxococcota but reduced that of Acidobacteria. No significant interaction effect was observed on bacterial phyla. For fungi, Ascomycota, Basidiomycota, and Mortierellomycota were the dominant phyla. Nutrient addition significantly increased the relative abundance of Basidiomycota and Mortierellomycota while reducing the dominance of Ascomycota (Fig. 3(B); Table 3). Fungal community composition at the phylum level was not significantly affected by supplemental lighting or its interaction with nutrient addition.

Figure 3.

Dominant phyla of bacterial (A) and fungal (B) communities in the different treatments. oNoL: without nutrients + without light; wNoL: with nutrients + without light; oNwL: without nutrients + with light; wNwL: with nutrients + with light.

Table 3.

ANOVA results for the effects of nutrient addition and light supplementation on bacterial and fungal community composition of rhizosphere soil in all treatments at phylum level

Variable	Nutrient (N)		Light (L)		N × L
	F 1,12	P	F 1,12	P	F 1,12	P
Bacteria
Proteobacteria a	5.1	0.043	6.9	0.022	2.0	0.185
Acidobacteriota	136.9	<0.001	6.4	0.027	4.0	0.068
Actinobacteriota	82.2	<0.001	0.1	0.718	3.2	0.097
Gemmatimonadota a	2.8	0.122	3.9	0.073	<0.1	0.914
Chloroflexi a	11.6	0.005	4.3	0.060	1.3	0.268
Planctomycetota	20.6	0.001	<0.1	0.846	0.3	0.604
Crenarchaeota a	164.6	<0.001	0.2	0.660	1.4	0.258
Myxococcota	71.9	<0.001	5.5	0.036	1.1	0.319
Methylomirabilota a	154.6	<0.001	2.7	0.128	1.3	0.270
Bacteroidota a	0.8	0.382	0.3	0.626	0.7	0.420
Fungi
Ascomycota a	6.2	0.029	3.3	0.095	1.6	0.224
Basidiomycota b	19.1	0.001	0.3	0.593	0.3	0.612
Mortierellomycota b	4.9	0.047	0.8	0.389	0.4	0.529
Chytridiomycota a	1.1	0.323	1.5	0.241	1.6	0.230
Aphelidiomycota a	<0.1	0.930	<0.1	0.857	0.1	0.813
Glomeromycota a	21.1	0.001	0.9	0.349	3.0	0.108
Olpidiomycota	0.2	0.661	0.4	0.553	3.0	0.109
Calcarisporiellomycota	1.0	0.337	1.0	0.337	1.0	0.337

F and P values and degree of freedom (subscript for ‘F’) are provided. Values are in bold when P < 0.05.

^a Square root transformation.

^b Natural log transformation.

The relative abundance of the top 20 bacterial and fungal genera and the results of UPGMA clustering analysis based on genus‐level abundance (displayed in a heatmap), and the effects of nutrient addition and light supplementation on bacterial and fungal community structure are shown in Fig. 4 and summarized in Tables 4 and 5. Analysis of the results indicated that nutrient addition significantly influenced 18 genera, while light supplementation affected 2 genera; their interaction affected 3 genera. Genera such as Vicinamibacteraceae, Rokubacteriales, and Sphingomonas were enriched in nutrient‐added soils, whereas Candidatus_Nitrososphaera, Gaiella, and Lysobacter were enriched in non‐amended soils. UPGMA clustering demonstrated that bacterial communities primarily clustered by nutrient availability (Fig. 4). These findings suggested that although both nutrient addition and light supplementation influenced bacterial community composition, the primary variations were predominantly driven by nutrient availability. For fungi, nutrient addition significantly influenced 5 major genera, and light supplementation affected 2, with no significant interaction observed. Genera including Stachybotrys and Acremonium were enriched with nutrient addition, while Arthrobotrys was enriched without it. Fungal communities also clustered primarily by nutrient treatment (Fig. 4). These results indicated that nutrient addition significantly altered fungal community composition.

Figure 4.

Relative abundance of the top 20 genera and UPGMA clustering analysis for bacterial communities (A) and fungal communities (B) based on the abundance. oNoL: without nutrients + without light; wNoL: with nutrients + without light; oNwL: without nutrients + with light; wNwL: with nutrients + with light.

Table 4.

ANOVA results for the effects of nutrient addition and light supplementation on bacterial community composition of rhizosphere soil in all treatments at genus level

Variable	Nutrient (N)		Light (L)		N × L
	F 1,12	P	F 1,12	P	F 1,12	P
RB41 a	88.3	<0.001	4.6	0.053	5.9	0.032
Vicinamibacteraceae	16.7	0.002	5.6	0.035	3.4	0.089
MND1 b	32.2	<0.001	<0.1	0.931	4.9	0.046
Rokubacteriales b	140.1	<0.001	1.7	0.222	1.1	0.321
Nitrososphaeraceae b	17.1	0.001	1.2	0.294	<0.1	0.979
JG30‐KF‐CM45 b	5.8	0.033	<0.1	0.832	<0.1	0.895
Candidatus_Nitrososphaera b	376.1	<0.001	<0.1	0.959	4.9	0.047
KD4‐96	8.7	0.012	0.5	0.501	0.1	0.738
Subgroup_7 b	13.7	0.003	2.0	0.179	0.6	0.465
MB‐A2‐108 a	13.5	0.003	0.2	0.629	4.7	0.051
Gaiella b	18.4	0.001	<0.1	0.874	0.3	0.592
WD2101_soil_group b	<0.1	0.882	4.6	0.053	0.7	0.435
S0134_terrestrial_group b	6.7	0.024	6.2	0.028	2.8	0.120
67–14	25.3	<0.001	0.3	0.593	1.8	0.210
Sphingomonas b	22.1	0.001	0.3	0.617	1.5	0.240
Lysobacter b	79.0	<0.001	2.8	0.117	0.4	0.524
TRA3‐20	<0.1	0.988	0.2	0.655	0.7	0.412
Marine_Group_II a	56.7	<0.001	3.8	0.072	1.3	0.273
Subgroup_10 b	14.2	0.003	0.3	0.564	1.4	0.266
Blastococcus b	6.4	0.027	0.3	0.584	0.1	0.775

F and P values and degree of freedom (subscript for ‘F’) are provided. Values are in bold when P < 0.05.

^a Square root transformation.

^b Natural log transformation.

Table 5.

ANOVA results for the effects of nutrient addition and light supplementation on fungal community composition of rhizosphere soil in all treatments at genus level

Variable	Nutrient (N)		Light (L)		N × L
	F 1,12	P	F 1,12	P	F 1,12	P
Arthrobotrys	60.9	<0.001	0.1	0.723	4.1	0.067
Humicola	0.3	0.586	<0.1	0.878	<0.1	0.978
Fusarium	0.4	0.549	0.1	0.733	0.1	0.750
Trichocladium	1.4	0.261	1.7	0.219	0.2	0.700
Chromelosporium a	1.9	0.192	0.3	0.589	0.7	0.427
Stachybotrys b	16.5	0.002	7.7	0.017	2.7	0.126
Aspergillus a	<0.1	0.892	0.7	0.427	1.6	0.232
Acremonium a	19.9	0.001	4.1	0.065	2.2	0.165
Herpotrichia a	2.5	0.143	1.0	0.337	0.1	0.777
Penicillium a	4.5	0.054	0.8	0.378	<0.1	0.990
Purpureocillium a	5.1	0.044	2.0	0.180	1.8	0.208
Solicoccozyma a	1.0	0.345	0.6	0.459	0.2	0.680
Preussia a	0.7	0.411	<0.1	0.931	0.4	0.552
Botryotrichum a	0.5	0.490	1.8	0.203	0.1	0.716
Acrophialophora a	0.6	0.436	0.1	0.761	1.0	0.335
Ascobolus b	10.5	0.007	<0.1	0.798	2.2	0.162
Mycochlamys a	<0.1	0.815	1.7	0.214	1.8	0.207
Rhizophlyctis a	0.8	0.380	1.2	0.295	0.9	0.366
Dactylonectria b	0.2	0.676	0.1	0.715	0.1	0.740
Emericellopsis a	4.3	0.061	0.2	0.639	0.7	0.434

F and P values and degree of freedom (subscript for ‘F’) are provided. Values are in bold when P < 0.05.

^a Square root transformation.

^b Natural log transformation.

Beta diversity patterns of bacterial and fungal communities were further visualized using PCoA based on Bray–Curtis distances (Fig. 5). In the two‐dimensional PCoA plot, bacterial communities were clearly separated along principal coordinate 1 (PCoA1) according to the presence or absence of nutrients. Within the treatments without nutrients, distinct clustering along principal coordinate 2 (PCoA2) indicated that light supplementation further differentiated bacterial communities, suggesting that light plays a significant role in reshaping bacterial community composition under nutrient‐limited conditions. Fungal communities were separated primarily by nutrient amendment along PCo1, with no discernible effect of light supplementation.

Figure 5.

PCoA plots of bacterial communities (A) and fungal communities (B) based on Bray–Curtis distances. oNoL: without nutrients + without light; wNoL: with nutrients + without light; oNwL: without nutrients + with light; wNwL: with nutrients + with light.

Simpson diversity indices were calculated to evaluate the effects of nutrient addition and light supplementation on soil microbial alpha‐diversity (Fig. 6 and Table 6). Nutrient addition significantly reduced bacterial alpha‐diversity but increased fungal alpha‐diversity. Supplemental lighting increased bacterial diversity but had no significant effect on fungal diversity. No significant interaction was detected for alpha‐diversity in either community.

Figure 6.

Simpson index of bacterial (A) and fungal (B) communities in the different treatments. oNoL: without nutrients + without light; wNoL: with nutrients + without light; oNwL: without nutrients + with light; wNwL: with nutrients + with light.

Table 6.

ANOVA results for the effects of nutrient addition and light supplementation on Simpson index of bacteria and fungi of rhizosphere soil in all treatments.

Variable	Nutrient (N)		Light (L)		N × L
	F 1,12	P	F 1,12	P	F 1,12	P
Bacteria
Simpson	70.4	< 0.001	9.5	0.010	1.045	0.327
Fungi
Simpson	88.6	< 0.001	1.2	0.295	1.7	0.223

All data were transformed to natural log. F and P values and degree of freedom (subscript for ‘F’) are provided. Values are in bold when P < 0.05.

Microbial functional profiles were inferred from 16S rRNA and ITS1 region gene sequences using PICRUSt2 to predict associated ecological processes. PICRUSt2 functional prediction revealed that nutrient addition significantly altered the abundance of numerous metabolic pathways, while light supplementation had no significant effect. Compared to non‐amended treatments, nutrient addition resulted in 29 significantly upregulated and 21 downregulated bacterial pathways, and 9 upregulated and 34 downregulated fungal pathways. Furthermore, we identified and quantified the top 10 significantly enriched and depleted bacterial and fungal metabolic pathways under the treatments with nutrient addition relative to the treatments without nutrient addition (Fig. 7). Nutrient addition enriched bacterial pathways involved in carbon degradation (e.g. lactose and galactose degradation I) and biosynthesis (e.g. mevalonate pathway I), while depleting pathways related to cofactor biosynthesis (e.g. coenzyme M biosynthesis I). In fungi, nutrient addition enriched pathways such as ubiquinol biosynthesis and glucose degradation, but depleted pathways including nucleotide salvage and aerobic respiration.

Figure 7.

PICRUSt predicted the top 10 significantly upregulated and downregulated bacterial (A) and fungal (B) MetaCyc pathways in with nutrient treatments comparing without nutrients.

Relationships between microbial communities, plant traits, and environmental factors

The integrated analysis revealed distinct environmental drivers for bacterial and fungal communities, as well as interrelationships among environmental factors (Fig. 8). Mantel tests indicated that nutrient availability was a significant driver of both bacterial and fungal community composition. Bacterial community structure was significantly correlated with total biomass, aboveground mass, and root–shoot ratio, whereas fungal communities correlated only with the root–shoot ratio. Nutrient addition was positively correlated with node number and biomass parameters, but negatively correlated with the root–shoot ratio. Light supplementation showed a significant positive correlation with soluble protein content. A strong positive correlation was observed between chlorogenic acid and total flavonoid content.

Figure 8.

Network heatmap integrating Pearson correlations among environmental factors and Mantel test‐based associations with bacterial and fungal community structures.

DISCUSSION

Plant growth and morphological responses

The supplementation of nutrients and light are established agronomic practices for enhancing plant productivity.^{17, 25, 41} Consistent with previous studies on the medicinal herb G. longituba ^{41, 42} and other Lamiaceae medicinal plants, ¹⁶ nutrient addition (N/P/K supply) enhanced biomass accumulation and node number by enhancing primary metabolism. Meanwhile, supplemental lighting extended photosynthetic duration to increase photosynthate production. The synergistic interaction between nutrients and light on biomass has also been reported in leafy medicinal plants,^{66, 67} which supports our observation that combined nutrient and light supply optimizes yield formation. In this study, the addition of nutrients, providing essential N, P, and K, facilitated the synthesis of structural components in G. longituba, thus promoting its growth. This was further supported by the significant increase in soluble protein content, indicative of enhanced metabolic activity and tissue development.^{33, 38, 41} Similarly, supplemental lighting extended the photosynthetic period,^{66, 68, 69} leading to greater photosynthate accumulation, as evidenced by elevated soluble sugar content, which supports growth and structural integrity. The synergistic interaction between nutrient and light supplements on total biomass and node number underscores the interdependence of resource availability and energy capture in driving plant growth.

The increase in node number, a key determinant of clonal reproductive potential in G. longituba,^{52, 53, 70} closely mirrored the biomass accumulation trend. Nutrient addition also prompted a shift in biomass allocation toward aboveground tissues, consistent with optimal partitioning theory where resources are allocated to the organs that acquire the most limiting factor.^{31, 67, 71} This reallocation enhances aboveground yield, a primary agronomic objective. In contrast, supplemental lighting alone did not significantly alter biomass partitioning, suggesting that biomass allocation in G. longituba is more responsive to belowground nutrient availability than to photoperiod extension under these conditions. Collectively, these results demonstrate that both nutrient and light supplementation effectively enhance the yield of G. longituba, with nutrient input particularly favoring aboveground productivity.

Bioactive and nutritional constituent accumulation

Nutrient addition and light supplementation differentially modulate the accumulation of bioactive constituents in G. longituba. Consistent with previous studies on medicinal plants, nutrient addition significantly reduced the levels of total flavonoids and chlorogenic acid by prioritizing primary metabolism over secondary metabolite synthesis, whereas supplemental lighting upregulated the phenylpropanoid pathway to enhance the accumulation of these bioactive constituents.^{40, 72} This tension between yield and quality under nutrient enrichment has been widely documented in medicinal plants,^{14, 34, 35} and the compensatory effect of light on chlorogenic acid accumulation has also been verified in Ocimum basilicum and other Lamiaceae herbs.^{34, 73} Nutrient addition significantly reduced the concentrations of total flavonoids and chlorogenic acid, whereas supplemental lighting enhanced them. This contrasting pattern can be explained by plant resource allocation strategies. Under nutrient‐sufficient conditions, plants often prioritize primary metabolism and growth over the production of secondary metabolites.^{39, 74, 75} Thus, nutrient enrichment likely suppressed the accumulation of these bioactive compounds by alleviating stress signals and reallocating resources toward growth. Supplemental lighting, particularly from the full‐spectrum source used here, can promote secondary metabolism through multiple mechanisms. ³⁴ While red light enhances photosynthetic efficiency and carbohydrate accumulation, ¹⁸ blue‐light wavelengths are known to upregulate key enzymes in the phenylpropanoid pathway, such as phenylalanine ammonia‐lyase and chalcone synthase,^{40, 76} thereby stimulating the biosynthesis of flavonoids and phenolic acids.^{24, 34} Notably, supplemental lighting mitigated the suppressive effect of nutrient addition on chlorogenic acid,^{30, 31} highlighting its compensatory role in maintaining secondary metabolite production under high‐nutrient conditions.^{40, 72}

In contrast to the responses of bioactive constituents, both nutrient addition and light supplementation increased the contents of soluble proteins and sugars, underscoring their roles in supporting primary metabolic processes. This indicates that while light promotes both primary and secondary metabolism, nutrient addition preferentially stimulates growth‐related pathways, potentially at the expense of certain therapeutic metabolites.^{18, 73, 77} These findings demonstrate that supplemental lighting can simultaneously enhance both yield and quality traits in G. longituba, whereas nutrient addition alone may lead to a yield–quality tension, consistent with our previous observations (unpublished data). Consequently, cultivation protocols should strategically balance light environment management with nutrient application to achieve optimal yield without compromising medicinal quality.

Soil microbial community dynamics

Soil microbial communities are fundamental mediators of ecosystem responses to environmental changes.^{76, 78, 79} Our finding that nutrient availability was the primary driver of microbial community restructuring aligns with extensive studies on grassland and agricultural soils, ⁸⁰ as well as recent research on medicinal plant rhizospheres. ⁴² Nutrient addition favored copiotrophic bacteria (e.g. Proteobacteria and Actinobacteria), which thrive in nutrient‐rich environments, over oligotrophic bacteria (e.g. Acidobacteria and Chloroflexi), which are adapted to nutrient‐poor soils and exhibit slow growth – a typical response to increased resource availability. This classic response to nutrient enrichment has been widely reported in multiple medicinal plant systems.^{48, 81} Fungal communities also shifted significantly with nutrient amendment, reflecting their high nutrient dependence and niche specialization.^{81, 82}

The limited effect of light supplementation on bacterial communities only under nutrient‐limited conditions suggests an indirect, plant‐mediated pathway. Enhanced photosynthesis under extended photoperiods likely increased root exudation, stimulating specific rhizobacterial groups without overriding the dominant influence of nutrient availability. ⁸³ The negligible impact of light on fungal communities aligns with their heterotrophic nature, lack of phototropism, and reliance on soil organic matter rather than direct plant‐photosynthate inputs.^{84, 85, 86}

Notably, nutrient addition reduced bacterial diversity but increased fungal diversity. This divergent response is widely observed in soil ecosystems: copiotrophic bacteria can rapidly dominate in high‐nutrient conditions, reducing overall diversity through competitive exclusion,^{87, 88, 89} whereas fungi with strong decomposing ability maintain higher diversity under nutrient enrichment.^{90, 91} This pattern has also been documented in the rhizosphere of G. longituba under nutrient heterogeneity, ⁴² which validates our microbial diversity results.

Functional predictions revealed divergent microbial strategies underpinning these diversity patterns. Bacteria upregulated pathways related to growth and substrate utilization (e.g. carbon degradation, biosynthesis), supporting rapid proliferation in nutrient‐amended soils. In contrast, fungi exhibited widespread pathway downregulation except for key processes like ubiquinone biosynthesis. Ubiquinone is critical for mitochondrial electron transport and energy metabolism^{92, 93}; its enhanced production likely improves respiratory efficiency, providing a competitive advantage in nutrient‐rich environments.^{94, 95} By prioritizing energy production over other metabolic functions, fungi optimize resource allocation toward essential biochemical processes. This mechanism explains the observed increase in fungal diversity despite the widespread suppression of other metabolic pathways. Bacteria upregulated diverse anabolic pathways related to growth and substrate utilization, such as carbon degradation and biosynthesis, supporting rapid proliferation in soil with nutrient addition.^{87, 88} In contrast, fungi exhibited widespread pathway downregulation, except for key processes like ubiquinone biosynthesis.^{92, 94} These distinct adaptive responses between bacteria and fungi represent the key mechanisms underlying the contrasting diversity patterns triggered by nutrient enrichment.

Correlation analysis further highlighted this functional differentiation. The strong association between bacterial communities and plant growth parameters (e.g. aboveground mass, root–shoot ratio) implicates their role in nutrient cycling and phytohormone modulation.^{96, 97} In contrast, fungal communities correlated specifically with root–shoot ratio, suggesting a more specialized role in carbon allocation and belowground resource partitioning, potentially through organic matter decomposition or mycorrhizal associations.^{98, 99}

A limitation of this study is that we did not measure changes in key physicochemical properties of the soil (e.g. SOM, C:N ratio, mineral composition) while investigating the effects of nutrient and light treatments. Given that these properties are key drivers of soil microbial community assembly and plant nutrient acquisition, future studies should include a comprehensive analysis of soil physicochemical characteristics to better elucidate the regulatory mechanisms by which environmental factors affect medicinal plant cultivation.

CONCLUSION

This study demonstrates that both nutrient addition and supplemental lighting are effective strategies for enhancing the yield of G. longituba, with their combination exhibiting a significant synergistic effect. However, a critical imbalance between yield and medicinal quality was identified. While nutrient addition primarily drove biomass accumulation, it concomitantly reduced the content of key bioactive compounds (e.g. flavonoids and chlorogenic acid). In contrast, supplemental lighting consistently improved both growth and the accumulation of these medicinal constituents, positioning it as a more favorable practice for medicinal quality enhancement. Furthermore, soil bacterial and fungal communities responded divergently to the treatments. Nutrient availability emerged as the predominant factor shaping microbial community structure and function, exerting a stronger influence than light supplementation. The distinct correlations observed suggest that bacteria may be more involved in processes supporting plant yield, whereas fungi appear to play a greater role in mediating plant resource allocation. These findings underscore the necessity of adopting integrated cultivation management that strategically balances nutrient and light regimes. Future research should focus on optimizing these parameters to simultaneously maximize yield and medicinal quality. Such efforts are crucial for developing science‐based, standardized protocols to support the sustainable production of high‐value medicinal plants like G. longituba.

FUNDING INFORMATION

This study was supported by the National Natural Science Foundation of China (32101264), the Science Research Project of Hebei Education Department (QN2025233), and the Scientific Research and Innovation Team of Handan University (XKYTD202302).

CONFLICT OF INTEREST

The authors have no relevant financial or non‐financial interests to disclose. The authors declare that they have no known competing financial interests or personal relationships that could have appeared to influence the work reported in this paper.

AUTHOR CONTRIBUTIONS

Xiao‐Gai Wang: Investigation, Writing – original draft, Writing – review & editing. Rui Zhang: Methodology, Formal analysis, Writing – review & editing. Yuan‐Yuan Qin: Methodology, Formal analysis, Investigation. Bing‐Nan Zhao: Methodology, Formal analysis, Investigation. Yu‐Ting Du: Methodology, Formal analysis, Investigation. Jin Yan: Methodology, Formal analysis, Investigation. Zi‐Yang Xie: Methodology, Formal analysis, Investigation. Xiao‐Ran Chen: Methodology, Formal analysis, Investigation. Chao Si: Conceptualization, Formal analysis, Writing – original draft, Writing – review & editing, Supervision.

DATA AVAILABILITY STATEMENT

The datasets presented in this study are available in the SRA database under the BioProject accession number PRJNA1290905: https://www.ncbi.nlm.nih.gov/sra/PRJNA1290905 (accessed on 15 July 2025).