In this study, based on chito-oligosaccharide, manganese sulfate, amino acid complex, γ-polyglutamic acid, polyaluminium chloride, magnesium sulfate, and calcium monophosphate were used to prepare a new chito-oligosaccharide modifier COS-PA. The specific procedures were as follows:

(1) Deionized water (1 L) was heated to 40-45°C, and then mixed with 1–3 g of citric acid in a flat-bottomed flask on a magnetic stirrer. After stirring, 100 g of chito-oligosaccharides were added, stirred for 2–3 h, to obtain mixture A (pH: 4.8). (2) Manganese sulfate (10–15 g) was added to the mixture A. After cooling to 25-35°C, the mixture was stirred until completely dissolved, to obtain mixture B (pH: 4.8). (3) Amino acid complex (10–15 g) and γ-polyglutamic acid (5–10 g) were added to the mixture B, heated to 50-60°C, and stirred for 0.5–1 h until completely dissolved, to obtain mixture C (pH: 4.8). (4) Polyaluminium chloride (5–10 g) was mixed with mixture C, followed by 12–15 h stirring while keeping the temperature unchanged, to obtain mixture D (pH: 4.7). (5) Anhydrous magnesium sulfate (10–15 g) was mixed with mixture D, heated to 65-75°C, stirred for 0.5–1 h until completely dissolved, to obtain mixture E (pH: 4.7). (6) Calcium monophosphate (5–10 g) was mixed with mixture E, followed by 5–8 h stirring while the temperature was kept unchanged, to obtain mixture F (pH: 4.6). (7) After 24 hours, the mixture F was centrifuged (Thermo Fisher, USA) at 4000 r for 10 min and filtered for 10 min. The precipitation was discarded, and the supernatant (a new chito-oligosaccharide modifier COS-PA) was transferred into a bottle and sealed.

This indoor pot trial was carried out in May 2024 in the Plant Cultivation Room, Xinjiang University, China. For the potted plants, the ambient temperature ranged from 24°C-28°C. The light regime was set at 16 h (light)/8 h (darkness), with a light intensity of 3000 lx. The relative humidity was maintained at 70%-75%. A total of four treatments were designed, namely (1) CK, no salt stress and no COS-PA application; (2) COS-P treatment, no salt stress but 100 mg·L^-1 of COS-PA was applied; (3) SA treatment, salt stress (salt concentration: 10 g·L^-1) but no COS-PA application; (4) CP treatment, salt stress (salt concentration: 10 g·L^-1) plus 100 mg·L^-1 of COS-PA application. Each treatment had three replicates/pots (height: 25 cm; diameter: 20 cm). The salts for salt stress were prepared as follows: NaCl, Na₂SO₄, NaHCO₃, and NaCO₃ were mixed according to the ratio of 12: 9: 8: 1 (molar ratio). Then, 25.0 g of the mixed salts was dissolved in 2.5 L of distilled water, and added to the pots according to the mass ratio of 1: 1 (water: mixed salts) (Wang et al., 2021b).

Cotton seeds (Xinluzao 72) were subjected to 5-min disinfection with 70% alcohol, three times of rinsing with sterile water, and 10–15 min soaking in 3% hydrogen peroxide solution. Vigor seeds were selected and 40 seeds were sown in each pot in May 2024. After the seedlings had two true leaves, 3 plants were retained in each pot. Insecticide (imidacloprid) was sprayed every three days. Irrigation was conducted every three days using deionized water, maintaining a stable water-holding capacity (60%). Seedlings were fertilized every seven days (0.077 g of urea, 0.128 g of diammonium, and 0.026 g of potassium sulfate per 1 kg of soil). Mixed salt solution and COS-PA were added on the second day after extra seedling removing, specifically, 100 mL of the salt solution was added every day for five consecutive days, and a total of 500 mL was added in each pot. This approach aimed to stabilize the salt ion in the soil, thereby avoiding salt shock. Meanwhile, to ensure the salt solution concentration remained constant across all treatments, the pots were weighed and water was replenished twice a day. The concentration of COS-PA was 100 g·L^-1, and 100 mL of COS-PA solution was added every day for three consecutive days. The staged application of COS-PA was primarily intended to facilitate the slow release of its major components. This is beneficial for extending the control effect of COS-PA on salt ions. Root fresh weight, leaf fresh weight, and plant height were determined after 60 days. After that, one part of the fresh leaves were used for the determination of K⁺, Na⁺, Ca²⁺ contents and photosynthetic characteristics of cotton, and the other part was used for the determination of metabolomics.

The stem thickness & plant height of cotton seedlings (three seedlings per treatment) were measured using vernier caliper and ruler, respectively. After absorbing the surface moisture of cotton seedlings, the fresh weight of leaves, stems, roots, and total weight were measured using an electronic balance.

The contents of K⁺, Na⁺, Ca²⁺, and physiological parameters (photosynthetic parameters & chlorophyll content) of cotton seedlings (three seedlings per treatment) were measured, followed by the calculation of the average values. Specifically, leaf samples were pre-processed by nitric acid-perchloric acid mixture digestion method, and the Ca²⁺, Na⁺, and K⁺ contents of cotton seedling leaves were measured by ICP-AES (Optima-7000DV, PE, USA) (Ren et al., 2024).

The intercellular carbon dioxide concentration (Ci), net photosynthetic rate (A), G_H₂O, photosynthetic rate, as well as transpiration rate (E) of cotton seedlings (three seedlings per treatment) were measured by a photosynthetic instrument (WLZG-FS-3000, Heinz Walz GmbH, German). Each leaf was measured three times (Grinberg et al., 2022).

Then, the leaves were subjected to dark adaption, to determine the maximum optical quantum yield (Fv/Fm), maximum fluorescence (Fm), and initial fluorescence (F0) using the chlorophyll fluorescence imaging system. Three plants were measured for each treatment. Then, the non-regulated energy dissipation Y(NO), regulated energy dissipation Y(NPQ), effective quantum efffciencies of PSII (Y(II)), and maximum quantum yield (Fv/Fm) were computed (Zhao et al., 2024).

Cotton seedling leaves were extracted with 95% ethanol solution for 24 hours in dark. Absorbance values were then measured with a spectrophotometer (Shandong Ouleibo Instrument Co., LTD, China) at 470 nm (OD470), 649 (OD649), and 665 (OD665). Based on the following formulas (Wang et al., 2024), the Chla concentration (Equation 1), Chlb concentration (Equation 2), Chla/Chlb ratio, as well as total chlorophyll concentration (Chl) (Equation 3) were computed:

where C denotes pigment concentration in extraction solution, V denotes extraction solution volume, and W denotes sample mass.

After 60 days of cultivation, three true leaves were selected in each treatment and sent to Beijing Biotech Biotechnology Co., Ltd, China. After rinsing, cutting into sections, and frozing in liquid N, 100 mg of leaf samples were ground in liquid N, followed by addition of methanol aqueous solution (80%, 500 μL), vortexing, and ice bath for five minutes. Then, the samples were subjected to a 20-min centrifugation (15,000 g, 4°C), and the supernatant was diluted using water to make the methanol content reach 53%. After another 20-min centrifugation (15,000 g, 4°C), the supernatant was collected for following measurements. Equivalent-volume QC (Quality control) samples were prepared through sample mixing, and sample blank solution was prepared using methanol aqueous solution (53%) (Li et al., 2020).

A chromatograph and a chromatographic column were used for chromatography, with the flow rate of 0.2 mL/min and the column temperature of 40°C. For the negative mode, 5 mmol/L ammonium acetate (pH: 9.0) and methanol were used as the mobile phase A and B, respectively. For the positive mode, 0.1% formic acid and methanol were used as the mobile phase A and B, respectively. A mass spectrometer was used for mass spectrometry, with the scan range of 100–1500 m/z, the aux gas heater temperature of 350°C, the S-lens RF level of 60, the capillary temperature of 320°C, the aux gas flow rate of 10 L/min, the sheath gas flow rate of 35 psi, and the spray voltage of 3.5 kV. To further understand the interaction of DAMs, the KEGG database was used to annotate DAMs.

Duncan’s test, one-way ANOVA, and statistical analysis were carried out on growth parameters, ion content, and photosynthetic parameters of cotton seedlings in Origin 8.0 & SPSS 25.0 (p< 0.05). Charts were drawn in Origin 8.0 and Adobe Illustrator CS6 (Adobe, USA). KEGG pathways and PCA results were plotted with “ggplot2” package in R 3.6.1. Mantel test was conducted with “linkET” package for clarifying the correlations between key DAMs and cotton seedling growth indexes, ion content, and photosynthetic characteristics under different treatments.

COS-P significantly regulated salt-stressed cotton growth and ion homeostasis ( Figure 1 ). The plant height of cotton seedlings of the SA and CP treatments reduced by 29.50% and 24.77%, respectively compared to CK (p< 0.05) ( Figure 1a ), and COS-P, SA, and CP treatments had no effect on the stem diameter of cotton seedlings ( Figure 1a ). The leaf, stem, root, and total fresh weight of the COS-P treatment increased (p< 0.05) by 11.06%, 30.45%, 96.44%, and 25.95%, respectively, and those of SA treatment reduced (p< 0.05) by 32.66%, 33.22%, 34.87%, and 33.06%, respectively ( Figure 1b ), compared to CK. The leaf, stem, root, as well as total fresh weight of CP treatment enhanced (p< 0.05) by 96.36%, 46.33%, 64.13%, and 74.06%, respectively compared to SA treatment ( Figure 1b ). The leaf Na⁺ & Ca²⁺ contents of COS-P treatment reduced (p< 0.05) by 12.43% and 8.95%, respectively, while leaf K⁺ content enhanced by 2.85% (p< 0.05), compared with CK. The leaf Na⁺ content of the SA treatment enhanced (p< 0.05) by 146.42%, and the leaf K⁺ and Ca²⁺ content reduced (p< 0.05) by 11.96% and 24.80%, respectively, compared to CK ( Figure 1c ). The Na⁺ content in the CP treatment reduced (p< 0.05) by 69.70% and the Ca²⁺ content increased by 7.22% compared to SA ( Figure 1c ).

COS-PA significantly increased the photosynthetic rate, chlorophyll fluorescence parameters, and photosynthetic pigments in salt-stressed cotton seedlings compared with CK ( Figure 2 ). The leaf Chl, Chl b, and Chl a contents of the SA treatment reduced (p< 0.05) by 24.78%, 29.23%, and 28.67%, respectively compared to CK. The leaf Chl, Chl b, and Chl a contents of CP treatment increased (p< 0.05) by 46.31%, 55.83%, and 44.53%, respectively compared to SA ( Figure 2a ).

The leaf A, G_H₂O, and E of the COS-P treatment enhanced by 53.51%, 20.81%, and 10.96%, respectively, and the Ci decreased by 27.89%, compared with those of CK. The leaf E, G_H₂O, and A of the SA treatment reduced (p< 0.05) by 48.75%, 58.82%, and 42.51%, respectively compared to CK. The E, G_H₂O, as well as A of the CP treatment increased (p< 0.05) by 96.65%, 168.24%, and 36.63%, respectively compared to SA treatment ( Figure 2b ).

The leaf Fv/Fm as well as Y(II) of COS-P treatment reduced (p< 0.05) by 4.91% and 4.87%, respectively, and the leaf Y(II), Y(NPQ), and Fv/Fm of the SA treatment reduced (p< 0.05) by 24.09%, 10.26%, and 17.21%, respectively, compared to CK. The leaf Fv/Fm, Y(II), and Y(NPQ) of the CP treatment increased by 5.01%, 27.15%, and 18.69%, respectively, and the leaf Y(NO) decreased (p< 0.05) by 14.64%, compared to SA treatment ( Figure 2c ).

Figure 3 shows the quality evaluation of metabolomic data of cotton seedling leaves. PCA results showed that PC1 and PC2 explained 49.96% and 20.90% of the total variation, respectively. The PC1 axis clearly separated the CK and CP treatments from the SA and COS-P treatments, and the PC2 axis clearly separated the CK from the SA and CP treatments ( Figure 3a ). In addition, correlation analysis showed a high degree of similarity between samples within each group and a great variation between groups ( Figure 3b ). There were 1,303 metabolites for the samples, which could be classified in 18 classes. Terpenoids were the most abundant metabolites in cotton seedling leaves, accounting for 15.8%, followed by Flavonoids (10.6%), Sugars and alcohobs (9.9%), Organic acid (8.9%), Lipid (8.6%), Amino acids (8.2%), and Polyphenols (8.1%) ( Figure 3c ).

Figure 4 shows the differentially abundant metabolites (DAMs) in cotton seedling leaves. A total of 882 DAMs were identified in CP vs COS-P (253 up-regulated metabolites; 629 down-regulated metabolites). Seven hundred and eighty-six DAMs were identified in COS-P vs CK (499 up-regulated metabolites; 287 down-regulated metabolites). Seven hundred and eighty-two DAMs were identified in CP vs CK (270 up-regulated metabolites; 512 down-regulated metabolites). Eight hundred and fourteen DAMs were identified in SA vs CK (541 up-regulated metabolites; 273 down-regulated metabolites). Eight hundred and seventy-six DAMs were identified in CP vs SA (221 up-regulated metabolites; 655 down-regulated metabolites) ( Figures 4a, c ). According to the Venn diagram, 453 DAMs were identified in the four treatments ( Figure 4b ).

The carbohydrate metabolism-related KEGG pathways included Ascorbate and aldarate metabolism, Pyruvate metabolism, C5-Branched dibasic acid metabolism, Propanoate metabolism, and Fructose and mannose metabolism ( Supplementary Figure S1 ). In Pyruvate metabolism pathway, the Succinic Acid abundance was up-regulated in the SA treatment and that of (S)-Malate was down-regulated, compared with those of CK. The Succinic Acid abundance was down-regulated in the CP treatment compared to SA treatment. In Propanoate metabolism pathway, the abundances of Methylmalonic Acid, Methylisocitrate, and 2-Methylcitrate of the SA treatment were up-regulated compared with those of CK. The Methylmalonic acid abundance was down-regulated in the CP treatment and the Methylisocitrate abundance was up-regulated compared with those of the SA treatment. In Fructose and mannose metabolism pathwa, the abundance of α-D-Glucose of the SA treatment was down-regulated and that of L-Fuconate was up-regulated compared with those of CK. The abundances of α-D-Glucose, L-Fucose, and L-Fuconate of the CP treatment were up-regulated, and those of D-Sorbitol, Mannitol, and D-Fructose were down-regulated compared to SA. In C5-Branched dibasic acid metabolism pathway, the Citraconic Acid abundance was up-regulated in the SA treatment but the Aconitic Acid, L-Glutamic Acid, Trans-Aconitic Acid, and 2-Hydroxyparaconate abundances were down-regulated compared with those of CK. The Citraconic Acid abundance was down-regulated in the CP treatment but the L-Glutamic Acid, Trans-Aconitic Acid, and 2-Hydroxyparaconate abundances were up-regulated compared to SA treatment. In Ascorbate and aldarate metabolism pathway, the abundance of D-Glucuronolactone was up-regulated in the SA treatment, but D-Glucuronate, Mucic Acid, Dehydroascorbic acid, and D-Galactaro-1,5-lactone abundances were down-regulated compared with those of CK. The abundances of D-Glucuronate, D-Glucuronolactone, and L-Ascorbic acid of the CP treatment were down-regulated, and the abundances of D-Arabinose, Mucic Acid, Dehydroascorbic acid, and D-Galactaro-1,5-lactone were up-regulated compared to SA treatment ( Figure 5 ).

There was a correlation between the growth indexes of cotton seedlings and the abundances of leaf metabolites (L-Lactic Acid, Succinic Acid, Methylmalonic Acid, Mannitol, Aconitic Acid, and Citraconic Acid) (Mantel’s, p< 0.01) ( Figure 6a ). The plant height and stem fresh weight had a negative correlation (p< 0.01) with L-Lactic Acid and Aconitic Acid abundances. The leaf fresh weight had a positive correlation (p< 0.01) with Succinic Acid, Methylmalonic Acid, Mannitol, as well as Citraconic Acid abundances. The root fresh weight had a positive correlation (p< 0.01) with L-Lactic Acid abundance. The total fresh weight had a positive correlation (p< 0.01) with L-Lactic Acid abundance, and a negative correlation with the abundance of Mannitol ( Figure 6b ). Ion content was correlated with the abundances of L-lactic acid, Succinic acid, (S)-Malate, Methylmalonic acid, 2-methylcitrate, Aconitic acid, Citraconic acid, and Trans-Aconitic acid (Mantel’s, p< 0.01) ( Figure 6a ). Leaf K⁺ and Ca²⁺ contents had a positive correlation (p< 0.01) with L-Lactic Acid, (S)-Malate Aconitic Acid, and Trans-Aconitic Acid abundances, and a negative correlation (p< 0.01) with 2-Methylcitrate abundance. Leaf Na²⁺ content had a positive correlation (p< 0.01) with Succinic Acid, Methylmalonic Acid, as well as Citraconic Acid abundances, and a negative correlation (p< 0.01) with L-Lactic Acid abundance ( Figure 6b ).

Leaf photosynthetic characteristics was correlated (Mantel’s, p< 0.01) with the abundances of L-Lactic Acid, (S)-Malate, as well as 2-Methylcitrate ( Figure 6a ). The leaf Ci had a positive correlation (p< 0.01) with (S)-Malate abundance, and a negative correlation (p< 0.01) with 2-Methylcitrate abundance. Leaf G_H₂O and E had a positive correlation (p< 0.01) with L-Lactic acid. abundance Leaf Y(NO) had a negative correlation (p< 0.01) with L-Lactic acid abundance ( Figure 6b ).