Abstract

   Asarum (Asarum sieboldii Miq. f. seoulense (Nakai) C. Y. Cheng et C. S.
   Yang) is a medicinal plant that contains asarinin and sesamin, which
   possess extensive medicinal value. The adaptation and distribution of
   Asarum’s plant growth are significantly affected by altitude. Although
   most studies on Asarum have concentrated on its pharmacological
   activities, little is known about its growth and metabolites with
   respect to altitude. In this study, the physiology, ionomics, and
   metabolomics were investigated and conducted on the leaves and roots of
   Asarum along an altitude gradient, and the content of its medicinal
   components was determined. The results showed that soil pH and
   temperature both decreased along the altitude, which restricts the
   growth of Asarum. The accumulation of TOC, Cu, Mg, and other mineral
   elements enhanced the photosynthetic capacity and leaf plasticity of
   Asarum in high-altitude areas. A metabolomics analysis revealed that,
   at high altitude, nitrogen metabolism in leaves was enhanced, while
   carbon metabolism in roots was enhanced. Furthermore, the metabolic
   pathways of some phenolic substances, including syringic acid, vanillic
   acid, and ferulic acid, were altered to enhance the metabolism of
   organic acids. The study uncovered the growth and metabolic responses
   of Asarum to varying altitudes, providing a theoretical foundation for
   the utilization and cultivation of Asarum.

   Keywords: Asarum, altitude, metabolism, phyto-chemicals, asarinin,
   sesamin

1. Introduction

   Global climate change has had a significant impact on ecological
   environments, leading to changes in the physiological–ecological
   adaptations and distribution ranges of plants. Altitude has a regular
   impact on ecological factors, such as temperature, water, and UV
   radiation, by affecting the vertical variation of water and heat in the
   environment [[38]1,[39]2]. Altitude-dependent natural climate gradients
   serve as space-for-time substitutions, allowing for potential
   characteristics of plant responses to temporal climate change to be
   inferred [[40]3,[41]4]. Therefore, examining how plants respond to
   existing climatic gradients is critical for understanding and
   predicting whether and how plants may persist in severe climate change.

   Plants adapt to environmental change by overcoming environmental
   stresses through the phenotypic plasticity and variation in
   physiological and metabolic pathways. For instance, the leaf area and
   specific leaf area of plants decreased significantly with an increasing
   altitude gradient [[42]5]. Previous studies have shown that a higher
   altitude promotes the synthesis of flavonoids, which adjusts the
   antioxidant capacity of plants [[43]6]. Golob et al. [[44]7] found
   that, in high-altitude areas, plant investment in secondary metabolites
   increased, while the investment in primary metabolites decreased.

   Medicinal plants are no exception. Several studies have shown that the
   synthesis and accumulation of active ingredients in medicinal plants
   are closely related to their specific climatic environment
   [[45]8,[46]9,[47]10]. Zhao et al. [[48]11] examined the response of the
   medicinal plant Herpetospermum pedunculosum (Ser.) C. B. Clarke to
   altitude gradients and found that its capacity for adaptation at high
   elevations is directly correlated with amino acid and carbon
   metabolism. Kumari et al. [[49]12] detected Picrorhiza kurroa’s primary
   and secondary metabolites and found that source-sink carbon
   partitioning, the tricarboxylic acid (TCA) cycle, ascorbate metabolism,
   and other metabolic pathways participate in the adaptation of plants to
   alpine environment. In addition, essential and trace elements are
   important active, primary, and secondary components in medicinal plants
   [[50]13]. A variety of mineral elements have been reported to be
   closely related to the enhancement of plant stress tolerance. For
   example, Ca, B, Mn, and Cu are closely related to the flavonoid
   composition of plants and their content, antioxidant capacity, and cell
   wall synthesis [[51]14,[52]15,[53]16].

   Asarum (Asarum sieboldii Miq. f. seoulense (Nakai) C. Y. Cheng et C. S.
   Yang) is a perennial herb of the genus Asarum of Aristolochiaceae,
   mainly distributed in northeast China and Korea [[54]17,[55]18]. Asarum
   is widely used clinically as an herbal medicine for the treatment of
   colds, headaches, toothaches, rheumatism, and coughs, which is
   attributed to a number of active constituents, including essential
   oils, acid amides, and lignans (especially asarinin and sesamin)
   [[56]19]. Asarinin is the main medicinally active ingredient in Asarum,
   which is classified as a quality control standard for Pharmacopoeia
   [[57]20]. Asarinin and sesamin have been shown to have antiviral,
   allergic, and therapeutic effects on arthritis [[58]21]. The current
   research on Asarum mainly focuses on the extraction of chemical
   components and pharmacological activities [[59]22]. However, little is
   known about the changes in the physiological and medicinal active
   substances in Asarum caused by altitude.

   This study employed physiological, metabolomic, and ionomic methods to
   investigate the adaptability and survival of Asarum roots and leaves
   under different altitude gradients. The assessment involved measuring
   the biomass, antioxidant capacity, elemental content, active
   substances, primary metabolites, and phenolic metabolites to uncover
   adaptive mechanisms and survival strategies. The results have key
   implications for future research and the comprehension of Asarum’s
   survival strategies.

2. Materials and Methods

2.1. Growth Condition and Plant Materials

   The study area, Sifang Mountain, was located in the Laoling Mountains
   of South Changbai Mountain, in the northeast of Tonghua City, Jilin
   Province. The experimental area belongs to the East Asian monsoon
   climate, influenced by the topography of Changbai Mountain. The
   continental climate is obvious: the average annual temperature is 5.5
   °C, and the annual precipitation is 880 mm. The soil types are slightly
   acidic and neutral, and the vegetation types mainly include deciduous
   broad-leaved forest and mixed coniferous broad-leaved forest. Based on
   altitudes, the samples were divided into three groups: L (620.79–625.50
   m), M (827.60–834.94 m), and H (1020.37–1022.74 m). In this study,
   based on the longitude and latitude of the sample plots, we collected
   mean annual temperature (MAT), mean annual precipitation (MAP), and
   mean annual solar radiation (MASR) under different altitudes at
   Worldclim ([60]https://www.worldclim.org/, (accessed on 12 September
   2023)). Detailed description of sample plots is shown in [61]Table 1.

Table 1.

   Descriptions of the sampling sites.
   Site Vegetation Type Elevation
   (m) Longitude
   and Latitude Aspect MAT
   (°C) MAP
   (mm) MASR
   (kJ m^−2 day^−1) Dominant Species
   1 Deciduous broad-leaved forest 620.79–
   625.50 126°6′37.67″ N
   41°53′54.10″ E East 3.58 894.00 6907.00 Erythronium japonicum Decne.,
   Polygonatum acuminatifolium Kom., Hylomecon japonica (Thunb.) Prantl &
   Kündig, Cardamine leucantha (Tausch) O. E. Schulz, Meehania urticifolia
   (Miq.) Makino
   2 Deciduous broad-leaved forest 827.60–
   834.94 126°5′25.39″ N
   41°55′50.56″ E West 2.80 911.00 6941.00 Erythronium japonicum Decne.,
   Anemone amurensis (Korsh.) Kom., Anemone raddeana Regel, Hylomecon
   japonica (Thunb.) Prantl & Kündig, Lilium distichum Nakai ex
   Kamibayashi
   3 Deciduous broad-leaved forest 1020.37–
   1022.74 126°4′39.67″ N
   41°56′1.46″ E Southeast 2.97 897.00 7263.00 Gymnospermium
   microrrhynchum (S. Moore) Takht., Erythronium japonicum Decne.,
   Maianthemum japonicum (A. Gray) LaFrankie, Anemone amurensis (Korsh.)
   Kom., Anemone raddeana Regel
   [62]Open in a new tab

   Note: MAT is mean annual temperature. MAP is mean annual precipitation.
   MASR is mean annual solar radiation.

   Asarum (Asarum sieboldii Miq. f. seoulense (Nakai) C. Y. Cheng et C. S.
   Yang) is a perennial herb capable of both sexual reproduction through
   the production of seeds, and vegetative reproduction by the rhizomes.
   Asarum was collected at different elevations between 10–12 am in clear
   weather on 22 May 2022. Five replicate 10 × 10 m plots were demarcated
   at each site. Expanded and healthy leaves of similar flowering periods
   and fibrous roots with a diameter of 1–2 mm were collected from each
   plot. The samples were stored using two methods. One sub-sample was
   frozen immediately in liquid nitrogen and stored at −80 °C for
   metabolomic analyses. The second sub-sample was dried in an oven at 60
   °C until constant weight and then ground into powder.

   Samples of soil were taken at every altitude. At each sampling site,
   soil was collected from the 0–20 cm soil layer using a stainless-steel
   soil corer, providing a total of five soil cores per plots. Soil
   samples from each plot were mixed to form a total of five composite
   samples at each elevation, and then removed to check for visible roots,
   rocks, and litter. Samples of soil were air-dried and put through a
   0.25 mm sieve, facilitating comprehensive analysis of the soil’s
   physico-chemical characteristics.

2.2. Determination of Nutrient Element and Soil Properties

   The electrical conductivity (EC) and pH value of soil sample were
   determined using a conductivity meter (DDS-307, Shanghai, China) and a
   pH meter (PHS-3C, Shanghai, China), respectively.

   The total organic carbon (TOC) and total nitrogen (TN) content in plant
   and soil samples were determined using an elemental analyzer (Elementar
   Inc., Hanau, Hessen, Germany). The total phosphorus (TP) content was
   determined using a UV spectrophotometer after digestion with H[2]SO[4]
   and H[2]O[2] [[63]23]. The determination of other elements (Mg, Al, Fe,
   Zn, Mn, Cu, B, and Mo) was performed by inductively coupled plasma
   optical emission spectroscopy (ICP OES Optima 8 × 00) (PerkinElmer,
   Inc., 10 Waltham, MA, USA) [[64]24]. The plant powder 0.25 g (0.15 g of
   soil sample), moistened with water, was added with 5 mL of HNO[3] and 1
   mL of HClO[4] (and 2 mL of HF for soil samples), and then nitrated
   using a hotplate at 200 °C until the contents became viscous. After
   cooling, 10 mL of 2% (v/v) HNO[3] was added to ensure that the contents
   were completely dissolved, then transferred to a 100 mL volumetric
   flask, and ultra-pure water was added to scale for elemental
   determination. ICP operation method was as follows: RF power 1200 W;
   plasma Argon (Ar) gas flow rate 12 L/min; auxiliary gas flow rate 1
   L/min; nebulizer Ar gas flow 0.7 L/min; and sample uptake rate of 0.8
   L/min. Elemental standards with different concentration gradients were
   established and standard curves were calculated to obtain the
   concentration of the elements in the samples.

2.3. Determination of Growth and Physiological Indices

2.3.1. Growth Indices Measurement

   The leaves and roots of Asarum were dissected and dried to constant
   weight at 60 °C, and the biomass of the leaves and roots were weighed.
   Healthy and complete leaves were selected from each altitude; leaf area
   was determined using a Uniscan M1 violet scanner, and then were dried
   and weighed.

2.3.2. Extraction and HPLC Analysis of Asarinin and Sesamin

   The root and leaf of Asarum samples (0.5 g) were combined with 25 mL of
   70% (v/v) methanol and extracted for 1 h in an ultrasonic bath. After
   centrifuging the extract for 10 min at 8000 rpm, the resulting solution
   was filtered through 0.45 µm membranes in preparation for HPLC
   injection. A Zorbax SB-C18 (5 µm, 4.6 mm × 25 cm, Agilent Technologies,
   Santa Clara, CA, USA) column was used for the separation. The column
   temperature was 30°C and the flow rate was maintained at 1.0 mL/min.
   Methanol (solvent B) and phosphoric acid (solvent A) at a ratio of
   0.05% (v/v) made up the mobile phase. The injection volume was 10 μL,
   and peaks were observed at 245 nm. The following was the gradient
   program: 70% A/30% B 3–6 min, and 60% A/40% B 0–3 min. The peaks of the
   samples were identified based on the matching retention times compared
   to those of the authentic standards.

2.3.3. Total Phenolic and Total Flavonoid Contents

   The dried powder (0.2 g) of the Asarum sample was mixed with 10 mL of
   70% methanol for 15 min and centrifuged at 8000 rpm for 10 min at 4 °C.
   After collecting the supernatant, the process was repeated one more
   time. Total phenol and flavonoid contents were determined from the
   methanolic extracts. The modified Folin–Ciocalteu method was used to
   determine the total phenolic content [[65]25]. The reaction mixture
   contained 5 mL of 10% (v/v) Folin–Ciocalteu reagent, 4 mL of 7.5% (v/v)
   Na[2]CO[3], 2.5 mL deionized water, and 1 mL of the methanolic extract.
   The reaction mixture was incubated in the dark for 1 h to develop color
   and the absorbance was determined at 760 nm. Gallic acid was used to
   prepare the standard curve. The aluminum chloride reaction was used to
   calculate the total flavonoid content [[66]26]. To the supernatant (0.5
   mL), 0.15 mL of 5% NaNO[2] solution was added and incubated for 5 min,
   followed by 0.15 mL of 10% AlCl[3]-6H[2]O solution. After 5 min, 1 mL
   of 1 M NaOH solution was added to the reaction mixture. The above
   reactions were carried out at room temperature. The absorbance was
   measured at 415 nm and a standard curve was constructed using rutin
   standards.

2.3.4. Antioxidant Activity

   The 2,2-diphenyl-1-picrylhydrazyl (DPPH) radical scavenging rate was
   determined by referring to the method of Szabo et al. [[67]27]. The
   methanol extract was diluted with 70% (v/v) methanol to a concentration
   gradient of 60, 80, 100, 200, and 300 μg/mL, and three replicates were
   set up for each group. As a positive control, 10–100 μg/mL of Trolox
   was obtained from Sigma-Aldrich Chemical Co. (St. Louis, MO, USA). For
   each group, 1 mL was mixed with 3 mL of distilled water and 6 mL of 0.1
   mM DPPH solution, and the absorbance values were measured in a water
   bath at 37 °C for 30 min, and then we measured the absorbance at a
   wavelength of 517 nm. The Dong et al. method [[68]28] was used to
   determine the 2,2′-azinobis (3-ethylbenzothiazoline-6-sulfonic acid)
   (ABTS) radical scavenging rate. The methanol extract was diluted with
   70% methanol to a concentration gradient of 60, 100, 200, 300, 400, and
   600 μg/mL, and three replicates were set up for each group. Trolox, at
   a concentration of 5–200 μg/mL, serves as a positive control. Then, 2
   mL of each extract was mixed with 2 mL of ABTS, and the reaction was
   performed at 25 °C for 6 min with protection from light, and we
   measured the absorbance value at a wavelength of 734 nm. A fitted curve
   function was constructed to calculate the effective concentration
   required when the clearance of DPPH and ABTS was 50% (50% inhibiting
   concentration, IC50).

2.4. Metabolite Extraction and Detection

2.4.1. Primary Metabolite Analysis

   In 0.1 g of sample was added 0.8 mL of 80% (v/v) methanol solution and
   5 μL of 2-chloro-L-phenylalanine (0.3 mg/mL), sonicated at 4 °C for 30
   min, then centrifuged for 15 min at 4 °C and 12,000 rpm. The 200 μL
   supernatant was taken in a 1.5 mL centrifuge tube, concentrated by
   rotary evaporation; 35 μL of 20 mg/mL methoxypyridine solution was
   added, and the reaction was allowed to proceed for 90 min at 37 °C with
   vigorous shaking for 30 s. Then, 35 μL of N, O-Bis (trimethylsilyl)
   trifluoroacetamide (BSTFA) (containing 1% TMCS) was added for
   derivatization and the reaction was carried out at 70 °C for 60 min.
   The obtained material was then left at room temperature for 30 min, and
   then analyzed by GC-MS. The GC–MS data were obtained using the Agilent
   7890A-5975C (Agilent, USA) and a non-polar DB-5 capillary column (30
   m × 250 um I.D., J&W Scientific, Folsom, CA, USA). Instrument
   parameters are as follows: the temperature is 280 °C, the EI ion source
   is 230 °C, the carrier gas is high purity helium (purity ≤ 99.999%),
   the shunt ratio is 10:1, the injection volume is 1.0 μL, and the
   solvent delay is 5 min. The ramp-up procedure is as follows: initial
   temperature 70 °C, ramp-up to 200 °C at 10 °C/min, then ramp-up to 280
   °C at 5 °C/min, and maintain for 10 min. Solvent delay 5 min. ramp-up
   procedure is as follows: initial temperature 70 °C, ramp-up to 200 °C
   at 10 °C/min, then ramp-up to 280 °C at 5 °C/min, and maintain for 10
   min.

2.4.2. Phenol Metabolites Analysis

   Dried powder (1.0 g) was added to 6 mL of 70% methanol, and the mixture
   was sonicated and ultra-sonicated for 30 min. The mixture was then
   centrifuged, with the supernatant being kept. This extract process was
   repeated twice, and the supernatants were combined. The supernatant
   from both times was concentrated by rotary evaporation. Subsequently,
   the dried sample was re-dissolved in 1 mL of 70% methanol. Solution
   collected was analyzed by UPLC/Q-TOF-MS, with a reversed Acquity UPLC
   BEH C18 Column (1.7 μm, 2.1 mm × 50 mm), and a Waters ^® Xevo G2 QTOF
   mass spectrometer.

   The settings of the UPLC system were 0.1% formic acid (v/v) in
   acetonitrile (B) and 0.1% formic acid (v/v) in aqueous solution (A),
   with a flow rate of 0.3 mL/min. The employed gradient flow rates were
   as follows: 0–10 min at 95% A-5% A, 5% B-95% B; 10–18 min at 5% A-95%
   A, 95% B-5% B; and 18–25 min at 95% A-95% A, 5% B-5% B, respectively.
   The column temperature was kept at 30 °C, and 2 μL injection volume was
   used. The conditions of the mass spectrometer were as follows: sampling
   cone voltage (45 eV), source temperature (400 °C), capillary voltage in
   positive ESI (+3000 V), and desolvation temperature (500 °C). The
   scanning range was set between 50–1000 m/z, with an ion acquisition
   rate of 0.2 per second. The identification of major compounds was
   facilitated by their MS/MS spectra and by comparison with authentic
   standards.

2.5. Statistical Analysis

   The presentation of all the data was mean ± standard deviation (SD).
   One-way ANOVA was used to analyze the data using SPSS 19.0 (SPSS, Santa
   Clara, CA, USA). In all cases, differences were considered to be
   significant at a probability level of p < 0.05. Plots were made with
   GraphPad Prism 8.

   The metabolites detected by GC-MS were identified through structural
   comparison, specifically by comparing the retention time and mass
   spectra with those of known compounds in the National Institute of
   Standards and Technology (NIST) library. The LC–MS data were analyzed
   and normalized through the mass spectrometry software, MassLynxTM 4.1
   (Waters Corporation, Milford, DE, USA). This detected peaks and listed
   both the detected and matched peaks with the retention time and m/z
   pair, as well as their intensities.

   Multivariate statistics was performed using the Soft Independent
   Modeling of Class Analogy (SIMCA)-P (version 11.0, Umetrics AB, Umea,
   Sweden). Prior to principal component analysis (PCA) and partial
   least-squares discriminant analysis (PLS-DA), all variables were unit
   variance (UV)-scaled. Differential metabolites were identified based on
   a threshold variable importance in projection value (VIP > 1.0) and
   p-value (p < 0.05). To determine pathway connections, annotated
   metabolites were mapped to the Kyoto Encyclopedia of Genes and Genomes
   (KEGG) pathway database ([69]http://www.kegg.jp/kegg/pathway.html,
   (accessed on 9 September 2023)).

   After log transformation for primary metabolites, phenolic metabolites,
   two active ingredients, and elements, a two-way ANOVA was performed
   using SPSS 19.0 to identify analytes for further analysis. The
   correlation coefficients between analytes were calculated using
   Pearson’ s correlation analysis. Based on Pearson’ s correlation
   coefficient (r^2 > 0.50 and p < 0.05), two nodes were considered
   linked. These relationships were visualized globally for all analytes
   using Arena3D ([70]http://arena3d.org (accessed on 15 October 2023))
   [[71]29].

3. Results

3.1. Soil Chemical Properties

   Along the altitudes, the soil pH was slightly acidic. The total organic
   carbon (TOC), ranging from 6.84–11.24%, increased with altitude and was
   demonstrated to be negatively correlated with the pH. An analysis of
   variance showed that other soil characteristics were significantly
   affected by the elevation ([72]Table 2). The highest contents of most
   nutrients, including TOC, total nitrogen (TN), aluminum (Al), iron
   (Fe), zinc (Zn), manganese (Mn), copper (Cu), and molybdenum (Mo), were
   observed at high elevations. Notably, TOC, Al, Zn, Cu, and Mo increased
   with elevation.

Table 2.

   Soil chemical properties at different altitudes.
   LOD (mg/L) L (Low Altitude) M (Middle Altitude) H (High Altitude)
   pH - 6.19 ± 0.18 ^a 5.77 ± 0.16 ^a 5.62 ± 0.46 ^a
   EC (ms/cm) - 1.76 ± 72.99 ^a 1.32 ± 17.58 ^a 1.63 ± 11.02 ^a
   TOC (%) - 6.84 ± 4.53 ^c 8.88 ± 5.14 ^b 11.24 ± 1.55 ^a
   TN (%) - 0.93 ± 0.04 ^ab 0.81 ± 0.70 ^b 1.16 ± 0.18 ^a
   TP (%) - 0.08 ± 0.05 ^b 0.1 ± 0.03 ^a 0.06 ± 0.02 ^c
   Mg (mg/kg) 0.0001 4104.79 ± 148.61 ^b 4948.05 ± 79.02 ^a 4151.74 ±
   62.78 ^b
   Al (mg/kg) 0.0001 33,945.73 ± 1902.79 ^c 39,451.17 ± 863.20 ^b
   53,979.69 ± 2747.76 ^a
   Fe (mg/kg) 0.0005 20,733.57 ± 1464.33 ^b 18,692.84 ± 182.27 ^c 25,240 ±
   519.97 ^a
   Zn (mg/kg) 0.0004 78.59 ± 4.03 ^b 82.71 ± 3.56 ^b 123.56 ± 11.24 ^a
   Mn (mg/kg) 0.0002 552.36 ± 53.24 ^b 534.11 ± 9.02 ^b 850.42 ± 29.29 ^a
   Cu (mg/kg) 0.001 11.22 ± 0.84 ^c 13.09 ± 0.46 ^b 16.4 ± 0.76 ^a
   B (mg/kg) 0.0014 35.05 ± 1.08 ^a 27.27 ± 0.35 ^b 27.6 ± 2.35 ^b
   Mo (mg/kg) 0.0001 0.53 ± 0.06 ^c 0.63 ± 0.01 ^b 0.79 ± 0.06 ^a
   [73]Open in a new tab

   Different lower-case letters indicate a significant difference (p <
   0.05) as determined by one-way ANOVA. All data shown were the means ±
   SD. TOC, total organic carbon; TN, total nitrogen; and TP, total
   phosphorus.

3.2. Nutritional Element Distribution and Physiological Indices in Asarum at
Different Altitudes

   The principal component analysis (PCA) showed a separation in
   nutritional element samples at varying altitudes ([74]Figure 1). The
   leaf and root samples at distinct altitudes were discernibly separated
   by PC1, which accounted for 61.90% and 60.4% of the total variation
   ([75]Figure 1a,c). The principal elements contributing to PC1 in leaves
   were Fe, Mn, Zn, Mo, and B, while, in roots, it was TOC, Mg, Al, Zn,
   and B ([76]Table S1, [77]Figure 1b,d), respectively. PC2 clearly
   distinguished the samples of different altitudes in leaves and roots,
   representing 32.80% and 35.90% of the variations, respectively
   ([78]Figure 1a,c). The contribution of PC2 was dominated by Mg, Al, and
   Cu in the leaves, while it was dominated by TN, TP, Mn, and Mo in the
   roots ([79]Table S1, [80]Figure 1b,d), respectively.

Figure 1.

   [81]Figure 1
   [82]Open in a new tab

   Tissue nutritional element variation analysis using PCA at different
   altitudes. (a) The score plot of elements in leaves; (b) the loadings
   of elements to the PC1 and PC2 in leaves; (c) the score plot of
   elements in roots; and (d) the loadings of elements to the PC1 and PC2
   in roots.

   In addition, the nutritional elements in the leaves and roots of Asarum
   were compared at different altitudes ([83]Table S2). The variation
   trend of TOC, TN, TP, and Fe along the altitude were consistent in the
   leaves and roots. The TN, TP and Fe significantly increased at middle
   altitude, while the highest accumulation of TOC was observed at high
   altitude. Additionally, the change of Al, Cu, Mg, and B along the
   altitude were the opposite in the leaves and roots. The content of Al,
   Cu, and Mg along the altitude significantly increased in the leaves,
   while it significantly decreased in the roots.

   The growth indices of Asarum were also detected ([84]Figure 2). The
   biomass of the leaves and roots significantly reduced at middle
   altitude and high altitude ([85]Figure 2a,b). The leaf area decreased
   by 54.44% at high altitudes compared to low altitudes ([86]Figure 2c).
   The highest specific leaf weight (LMA) at high altitude was observed
   ([87]Figure 2d). These results suggest that Asarum thrived at low
   altitudes, whereas higher altitudes had a detrimental effect on its
   growth.

Figure 2.

   [88]Figure 2
   [89]Open in a new tab

   Effect of altitude on leaf biomass allocation (a); root biomass
   allocation (b); leaf area (c); and specific leaf weight (d) in Asarum.
   Different lower-case letters indicate a significant difference (p <
   0.05) as determined by one-way ANOVA. L indicates low-altitude areas, M
   indicates middle-altitude areas, and H indicates high-altitude areas.

   The medicinal ingredients and antioxidant capacity variables of Asarum
   exhibited varied sensitivity to altitude. The roots were found to
   contain high levels of asarinin and sesamin, with asarinin being
   highest at low elevations and sesamin at middle elevations ([90]Figure
   3a,b). The contents of total phenols and total flavonoids in the leaves
   showed a consistent trend with altitude, both significantly increasing
   with altitude and reaching the highest levels of 117.50 mg/g and 49.70
   mg/g at high altitude, respectively ([91]Figure 3c,d). The change trend
   of the total flavonoid content in roots was the opposite to that in the
   leaves. ([92]Figure 3d). The antioxidant capacity was evaluated by the
   IC50 values of DPPH and ABTS. The lower the IC50 value, the stronger
   the antioxidant capacity. The IC50 of DPPH decreased by 32.54% and
   28.41% in middle- and high-altitude leaves ([93]Figure 3e),
   respectively. The IC50 of ABTS in the leaves decreased by 10.43% and
   5.33% in middle- and high-altitude leaves ([94]Figure 3f),
   respectively, indicating an increase in antioxidant capacity in
   middle-altitude leaves.

Figure 3.

   [95]Figure 3
   [96]Open in a new tab

   The effect of altitude on the content of asarinin (a), sesamin (b),
   total phenols (c), total flavonoids (d), DPPH IC50 value (e), and ABTS
   IC50 value (f) in Asarum. Different lower-case letters indicate a
   significant difference (p < 0.05) as determined by one-way ANOVA; *
   indicates significant differences (p < 0.05) between roots and leaves
   at the same altitude. L indicates low-altitude areas, M indicates
   middle-altitude areas, and H indicates high-altitude areas.

3.3. Metabolic Profile in Asarum at Different Altitudes

   The metabolite profiling of the different altitude samples was
   conducted using GC-MS and UPLC/Q-TOF-MS. A total of 96 metabolites were
   identified in the leaves and roots by GC-MS ([97]Table S3), and 30
   phenolic metabolites were identified by UPLC-MS-MS ([98]Figure 4).
   According to the PCA score plots, there was evident variation in the
   leaves and roots at different altitudes ([99]Figure S1).

Figure 4.

   [100]Figure 4
   [101]Open in a new tab

   Relative content of phenolic metabolites in leaves and roots at
   different altitudes. L indicates low-altitude areas, M indicates
   middle-altitude areas, and H indicates high-altitude areas.

   To further screen the differential metabolites, the variable importance
   in the projection (VIP) by an orthogonal partial least-squares
   discriminant analysis (OPLS-DA) and the p-value by a one-way ANOVA, and
   metabolites satisfying both VIP > 1 and p < 0.05 were considered as
   differential metabolites. A total of 46 and 45 differential metabolites
   were identified in the leaves and roots, respectively ([102]Table S4).
   Moreover, the pathway enrichment analysis of these substances was
   performed using the Arabidopsis KEGG pathway library ([103]Figure 5).
   The enrichment pathway in different tissues was significantly
   different. According to the KEGG annotation and enrichment results,
   differential metabolites, which might relate to the altitude changes in
   leaves, were mainly annotated and enriched in flavone and flavonol
   biosynthesis, galactose metabolism, flavonoid biosynthesis, and
   aminoacyl-tRNA biosynthesis (−log p > 1, impact > 0.1) ([104]Figure 5a,
   [105]Table S5). In the roots, there were six biological pathways
   involved (−log p > 1, impact > 0.1), including flavonoid biosynthesis,
   ascorbate and aldarate metabolism, glyoxylate and dicarboxylate
   metabolism, and three amino acid metabolism pathways ([106]Figure 5b,
   [107]Table S5).

Figure 5.

   [108]Figure 5
   [109]Open in a new tab

   Enriched metabolic pathways of the differential metabolites at
   different altitudes for leaves (a) and roots (b). Each bubble in the
   plot represents a metabolic pathway whose abscissa and bubble size
   jointly indicate the magnitude of the impact factors of the pathway. A
   larger bubble size indicates a larger impact factor.

   To comprehend the metabolic regulation changes at varying altitudes, we
   constructed a simple metabolic network diagram ([110]Figure 6). In the
   leaves, L-serine, L-isoleucine, and L-proline related to nitrogen
   metabolism accumulated at high altitude, and all of them were involved
   in the aminoacyl-tRNA biosynthesis pathway, while galactinol and
   sucrose in the galactose metabolism pathway accumulated more at middle
   altitude ([111]Figure 6a). In roots, sugars including galactopyranose,
   D-fructose, L-rhamnose, and d-glucose associated with carbon metabolism
   accumulated significantly at high altitude ([112]Figure 6b).
   Significant metabolic responses were found in the phenolic compounds
   mediated by shikimic acid. With increasing altitude, most of the C6C1
   carbon-skeleton phenolic compounds in the leaves tended to decrease,
   while the C6C3 carbon-skeleton phenolic compounds accumulated
   ([113]Figure 4 and [114]Figure 6a). Most of the C6C1 carbon-skeleton
   phenolic compounds and C6C3 carbon-skeleton compounds in the roots
   showed a similar trend with altitude as in the leaves. The C6C3C6
   compounds showed significant tissue specificity in the metabolic
   response to different altitudes. Most of the them accumulated in the
   leaves and decreased in the roots at high altitude, such as quercitrin,
   genistein, galangin, apigenin, and kaempferol ([115]Figure 4 and
   [116]Figure 6).

Figure 6.

   [117]Figure 6
   [118]Open in a new tab

   Mapping of differential metabolites on metabolic pathway for leaves (a)
   and roots (b). L indicates low-altitude areas, M indicates
   middle-altitude areas, and H indicates high-altitude areas.

3.4. Correlations of Metabolites–Elements–Medicinal Ingredients in Asarum

   To obtain a global overview of the inter-analyte associations, a
   two-way ANOVA was performed after the log transformation of all
   metabolites shared in the roots and leaves, selecting analytes that
   showed significant differences (p < 0.05) related to the tissues,
   altitudes, or altitudes–tissues interactions. A layered network for
   visualization in three dimensions was constructed based on Pearson’s
   correlation coefficients (r^2 > 0.50 and p < 0.05), highlighting the
   connections between composite types ([119]Figure 7). The global network
   revealed many connections between primary metabolites and phenolic
   metabolites, as well as between primary metabolites and elements. In
   addition, node scores were calculated for the nodes in the network,
   listing the top ten nodes in the MCC ranking ([120]Figure S2). Notably,
   apart from two medicinal components, organic acids dominated the
   network.

Figure 7.

   [121]Figure 7
   [122]Open in a new tab

   Asarum correlation network based on Pearson’s correlation analyses for
   83 analytes and 11 elements. Significant correlations are ones with r^2
   > 0.50 and p < 0.05. Metabolites and elements are represented by
   circles, and edges refer to correlations in between. The four layers
   corresponded to the following compound types: primary metabolites,
   phenol metabolites, elements, and medicinal ingredients.

4. Discussion

   The effect of altitude on plant growth and the accumulation of
   metabolic substances are the result of the comprehensive effect of
   relevant climatic factors (temperature, light, water, etc.) [[123]30].
   In this study, there were significant changes in soil physico-chemical
   properties between different altitudes, with significant alterations in
   the annual average temperature (MAT) and annual rainfall (MAP) along
   the altitude gradient. In high-altitude areas, the soil pH was found to
   decrease, whereas the concentration of soil ions (Al, Fe, Zn, Mn, Cu,
   and Mo), total organic carbon (TOC), and total nitrogen (TN)
   substantially increased. This accumulation of TOC may be attributed to
   the combination of low temperatures and heightened soil acidity at high
   altitudes, which decelerate the process of the decomposition and
   mineralization of TOC [[124]31].

   The accumulation and distribution of biomass in plants are
   significantly influenced by external factors [[125]32]. Consequently,
   comprehending the patterns of biomass accumulation and distribution
   among plants at diverse altitudes serves as a critical approach to
   comprehending plant responses to climate alteration. In our study, the
   underground biomass, aboveground biomass, and leaf area of Asarum
   showed a downward trend along the altitude ([126]Figure 2). A smaller
   leaf area reduces the solar energy uptake and transpiration rates,
   thereby reducing the damage to the leaves from high-intensity UV
   radiation and strong winds [[127]33]. Ullah et al. also obtained
   similar results in the study of Primula nivalis. There exists a
   substantial negative correlation between morphological features and the
   altitude, temperature, and sunshine duration, which are the predominant
   factors influencing plant morphological attributes and resource
   allocation [[128]34]. Moreover, we also observed the highest specific
   leaf weight (LMA) at the high altitude ([129]Figure 2d). The LMA can
   reflect the balance between plant growth and nutrient absorption
   [[130]35]. In high-altitude areas, a high LMA is usually associated
   with enhanced defense. Plants will reduce growth and invest more
   resources in enhancing defense to help them survive in areas with
   strong radiation and low temperature [[131]36].

   The relationship between plant size in high-altitude regions and
   nutrition has been demonstrated [[132]31]. Plant growth is restrained
   at high altitudes, which may be due to the harsh climatic conditions
   and low temperatures at high altitudes, diminished microbial activity,
   and diminished plant nutrient availability [[133]37]. TOC and Mo in the
   roots and leaves were significantly accumulated at the highest
   altitude, while Al, Cu, and Mg decreased in the roots and increased in
   the leaves at high altitude. Leaf carbon is a representative of leaf
   toughness and structural compound investment [[134]38], indicating
   higher plasticity and stress resistance in Asarum at high-altitude
   areas. Mo has been shown to regulate the antioxidant mechanisms and
   osmotic balance in plants and increase the chlorophyll and carotenoid
   content, as well as the photosynthetic rate [[135]39]. Meanwhile, Cu
   and Mg are also transferred to the leaves in the roots at high
   altitude. Cu and Mg are essential nutrients for plants and participate
   in photosynthesis, particularly in chlorophyll synthesis and
   photosynthetic electron transfer [[136]40]. Therefore, the accumulation
   of the elements at high altitude contributes to the enhancement of
   photosynthetic capacity and leaf defense. In addition, we observed that
   the content of B is generally higher in soils with different altitude
   gradients, and a significant accumulation of B in the roots increases
   with altitude. B is related to enzyme synthesis and mainly affects
   physiological processes such as cell wall structure, carbohydrate
   metabolism, and sugar transport in plants [[137]41]. However, high
   concentrations of B can cause toxicity in plants and inhibit plant
   growth, which may be one of the reasons for the inhibition of plant
   growth in high-altitude areas [[138]42]. Meanwhile, the interactions of
   B with other elements and metabolites in plants are complex and need to
   be further investigated.

   Plants are always faced with a trade-off between growth and defense,
   especially in primary and secondary metabolism. Primary metabolites are
   directly involved in plant growth and development. In this study,
   galactopyranose, D-fructose, L-rhamnose, and D-glucose were observed to
   accumulate significantly in the roots at high altitude, suggesting that
   carbon metabolism is enhanced in the roots of Asarum with increasing
   altitude. Sugars have been shown to be a positive regulatory factor for
   enhancing plant adaptability [[139]43]. Sucrose is the main product of
   photosynthesis, providing energy for cell metabolism. Ma et al.
   demonstrated enhanced photosynthetic rates and sugar accumulation along
   an increasing elevation gradient [[140]44]. This is consistent with our
   results. Although sugars primarily function to boost plant
   adaptability, they operate via distinct regulatory systems. For
   example, glucose can serve as a respiratory substrate or osmotic agent
   to maintain cellular homeostasis [[141]45]. Fructose and rhamnose act
   by forming substrates of secondary metabolites [[142]46].

   Similarly, significant alterations in amino acid metabolism subsequent
   to sugar metabolism were observed in the roots and leaves. In the
   leaves, L-serine, L-isoleucine, and L-proline, associated with nitrogen
   metabolism, accumulate at high altitude, and all of them are involved
   in the biosynthetic pathway of aminoacyl tRNA. Proline, a
   multifunctional amino acid, functions as a signaling molecule,
   regulating intracellular osmotic pressure, mitigating protein
   denaturation, preserving membrane integrity, shielding cells from
   stress, and curtailing ROS-induced damage [[143]47]. Aminoacyl-tRNA can
   catalyze the synthesis of amino acids into proteins [[144]48]. Previous
   studies have shown that proteins can resist low-temperature stress by
   controlling and activating metabolic pathways related to resistance
   [[145]4]. Similar results were observed in roots and most of the amino
   acids including L-threonine, L-isoleucine, and L-valine also
   accumulated at high altitude. Amino acids and their derivatives serve
   to activate plant defense mechanisms during plant growth and the
   development and stress response [[146]49]. Some investigations have
   suggested that the increase in amino acid levels caused by stress is
   related to increased nitrogen storage and serves as a precursor for the
   production of secondary metabolites in plants
   [[147]50,[148]51,[149]52].

   Changes in altitude will alter the accumulation of secondary
   metabolites in plant tissues, thereby adjusting the adaptability of
   plants to environmental changes [[150]53]. The increase of reactive
   oxygen species in high-altitude areas can damage the cell membrane
   system, resulting in abnormal metabolism, and even cell death
   [[151]36,[152]54]. The antioxidant activity of medicinal plants is
   commonly evaluated by the scavenging rate of DPPH radicals and ABTS
   radicals [[153]55]. In this study, a higher antioxidant capacity was
   observed in leaves at medium and high altitudes, corroborating the
   findings of Joshi et al. [[154]56]. Previous studies have shown that
   phenols and many flavonoids exert antioxidant effects by reducing the
   accumulation of reactive oxygen species [[155]36,[156]54].
   Specifically, our results show that vanillic acid, cinnamic acid,
   ferulic acid, caffeic acid, rosmarinic acid, sinapic acid,
   isoliquiritigenin, and rutin accumulated significantly in both the
   roots and leaves at high altitude. It has been found that cinnamic acid
   can disrupt the coupling of oxidative phosphorylation to the
   respiratory chain, which, in turn, affects plant respiration [[157]57].
   In our study, the negative impact of high altitude on respiration can
   be attributed to the interruption of electron transfer chains caused by
   lower environmental temperatures and high ion accumulation. Ferulic
   acid is an important insoluble phenolic compound that contributes to
   the antioxidant activity of plants [[158]58]. Furthermore, ferulic acid
   may be esterified by cell wall polysaccharides, establishing a link
   between lignin and cell wall polysaccharides, thereby increasing cell
   wall rigidity and facilitating the maintenance of expansion pressure
   [[159]59]. In addition, the accumulation of vanillic acid, ferulic
   acid, and caffeic acid showed a positive response with increasing
   altitude in several studies [[160]60,[161]61].

   The correlation between mineral elements and metabolite patterns is
   novel. Previous studies have shown that a variety of elements,
   including K, Ca, Fe, and Cu, involve many metabolic pathways such as
   signal transduction, photosynthesis, and carbon assimilation
   [[162]62,[163]63]. In this study, TN, Al, Cu, Mn, and Mg were
   significantly correlated with multiple metabolites. Among them, Al, Cu,
   and Mg were positively correlated with metabolites involved in
   flavonoid biosynthesis, such as chlorogenic acid, kaempferol,
   taxifolin, and galangin. Conversely, Al, Cu, and Mg were negatively
   correlated with compounds involved in glycoxylate and dicarboxylate
   metabolism, such as oxalic acid, D-glycerate, and succinic acid. In
   contrast, TN and Mn were positively correlated with compounds involved
   in glyoxylate and dicarboxylate metabolism. Glyoxylate and
   dicarboxylate metabolism are involved in the carbohydrate biosynthesis
   of double fatty acids [[164]64]. Carbohydrates serve as metabolic
   sources of energy and signaling molecules in plant growth regulation,
   and are integral to the regulation of plant stress responses [[165]65].
   Flavonoid metabolism contributes to the enhancement of antioxidant
   activity in plants to alleviate oxidative stress [[166]66]. In
   addition, organic acids such as protocatechuic acid, 2-Butenoic acid,
   syringic acid, galactaric acid, lactic acid, vanillic acid, and ferulic
   acid are the key metabolites in the related network. Among them,
   protocatechuic acid, syringic acid, vanillic acid, and ferulic acid are
   synthesized through a series of enzymatic reactions through the
   shikimic acid pathway, with various medicinal values and important
   sources of antioxidants [[167]67]. Thus, the enrichment of these
   metabolic pathways could reveal the activation of the corresponding
   processes or functions, including carbohydrate formation and
   antioxidant synthesis, which could help to alleviate the inhibition of
   Asarum growth by altitude.

5. Conclusions

   In summary, different altitudes have a significant impact on the growth
   and metabolism of Asarum. The growth of Asarum was inhibited at high
   altitudes, while the content of total phenols and flavonoids
   significantly increased with increasing altitude, enhancing its
   antioxidant capacity. Ionic omics results indicated that, at high
   altitudes, TOC, Mo, Al, Cu, and Mg in Asarum significantly accumulate
   in the leaves, enhancing their photosynthetic capacity and stress
   resistance. Based on the results of metabolomics, we found that, in
   high-altitude areas, the roots mainly activate defense mechanisms by
   accumulating sugars, amino acids, and organic acids, while sugars in
   the leaves are reduced and nitrogen metabolism is enhanced. Organic
   acids play a dominant role in regulating the adaptation strategy of
   Asarum with altitude. Meanwhile, the main active components of Asarum,
   asarinin and sesamin, are mainly accumulated in the roots, with higher
   levels in low- and medium-altitude areas. These results provide a
   theoretical basis for explaining the physiological and metabolic
   response mechanisms of Asarum to altitude, and are important for the
   collection of excellent wild Asarum seed sources and their biological
   research. Nonetheless, the environmental factors at different altitudes
   are multifaceted, and the response mechanism of Asarum to varying
   environmental factors necessitates further investigation.

Supplementary Materials

   The following supporting information can be downloaded at:
   [168]https://www.mdpi.com/article/10.3390/metabo13121193/s1, Figure S1:
   Multivariate analysis of primary metabolites (a,c) and phenolic
   metabolites (b,d) at different altitudes for leaves and roots; Figure
   S2: Top 10 nodes in Asarum ranked by MCC; Table S1: Variance
   contribution of each element; Table S2: Nutritional element
   distribution in leaves and roots at different altitudes; Table S3: List
   of the metabolites identified in Asarum; Table S4: List of the
   differential metabolites identified in Asarum; Table S5: Enriched
   metabolic pathways of the differential metabolites at different
   altitudes; Table S6: Statistics for two-way ANOVA, incorporating
   tissues, altitudes, and their interaction as fixed effects.
   [169]Click here for additional data file.^ (570.2KB, zip)

Author Contributions

   Conceptualization, N.Y.; methodology, L.P.; software, L.P.; validation,
   N.Y., Y.L. and W.Z.; formal analysis, Y.S.; investigation, L.Z.;
   resources, L.Z.; data curation, L.P.; writing—original draft
   preparation, L.P.; writing—review and editing, Z.T.; visualization,
   L.P.; supervision, L.M.; project administration, L.M.; and funding
   acquisition, L.Z. All authors have read and agreed to the published
   version of the manuscript.

Institutional Review Board Statement

   Not applicable.

Informed Consent Statement

   Not applicable.

Data Availability Statement

   The data presented in this study are available on request from the
   corresponding author. The data are not publicly available due to
   privacy.

Conflicts of Interest

   The authors declare no conflict of interest. The funders had no role in
   the design of the study; in the collection, analyses, or interpretation
   of data; in the writing of the manuscript; or in the decision to
   publish the results.

Funding Statement

   This research was funded by the Special Investigation Project on
   Science and Technology Basic Resources of the Ministry of Science and
   Technology—Investigation of Wild Economic Plant Germplasm Resources in
   Natural Forests of Changbai Mountain Forest Region, grant number
   2019FY100504.

Footnotes

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References