Sweet potato cultivars were different and sensitive to potassium (K). Based on the variance of the K sensitivity index, 31 good-quality sweet potato cultivars (lines) were studied under the NP plot (treatment of nitrogen and phosphorus) and NPK plot (treatment of nitrogen, phosphorus, and K) (Tang et al., 2014). Sweet potato cultivars (lines) were clustered into four groups: K-high-sensitive group (typical for Ningzishu 1), K-sensitive group (typical for Beijing 553), K-moderate-sensitive group (typical for Xushu 22), and K-tolerance group (typical for Xushu 32). Therefore, Xushu 32 (low-K-tolerant) and Ningzishu 1 (low-K-sensitive) were used in this study. Furthermore, Gao et al. (2021) found that Ningzishu 1 was more sensitive than Xushu 32 in tuber sucrose-to-starch conversion under different K applications, too (Gao et al., 2021).

The shoots of Xushu 32 were obtained from the laboratory of Tang Zhonghou, Xuzhou Academy of Agricultural Sciences. The shoots of Ningzishu 1 were obtained from the Laboratory of Xie Yizhi at Jiangsu Academy of Agricultural Sciences. Shoots with five leaves were collected from tuberous root (20 days), then arranged into transfer pots (12 plants/plot), and cultivated with 8 L (40 × 23 × 12 cm) of 1/4-strength Hoagland solution (Xia et al., 2020). The solution was renewed every 48 h. After a pretreatment period of 5 days, seedlings were divided into two groups with the following treatments: K deficiency (−K, <0.03 mM of K⁺) and K sufficiency (+K, 5 mM of K⁺). The amount of K⁺ was varied by changing the amount of K₂SO₄. Seedlings were grown under a condition with a photoperiod of 16 h, a photosynthetic flux density of 150 mmol m⁻² s⁻¹, and temperatures at 20°C–25°C. The condition was repeated in every pot, and six pots were grown for each treatment.

At 0, 5, 10, and 15 days of K treatment (DKT), functional leaves (youngest fully expanded main-stem leaf) and fine roots were collected for analysis of N-metabolizing enzymes, AA and protein, NO₃ ⁻–N and NH₄ ⁺–N, N and K contents, and steady-state root K⁺ fluxes.

Oven-dried samples (roots, stems, and leaves) of 0.1 g through a 0.25-mm sieve were digested using 5 mL of H₂SO₄–H₂O₂ to analyze K and N contents. The K content was measured by flame photometry, while N was measured with the automated discrete analyzer (SmartChem 200, AMS Alliance, Rome, Italy) (Gao et al., 2019). The steady-state net K⁺ fluxes in sweet potato roots at 10 DKT were measured non-invasively by the NMT system (NMT-100-SIM-YG, Younger USA LLC, Amherst, MA, USA) according to previously described methods (Sun et al., 2009; Yu et al., 2016; Liu et al., 2019). The K⁺ concentration of K⁺-specific microelectrode followed standard procedures. Fluxes were automatically recorded in the apex region and the mature region.

Oven-dried samples (roots and leaves) of 0.2 g were mixed with distilled water (10 mL) at 100°C for 1 h to analyze NO₃ ⁻–N and NH₄ ⁺–N. NO₃ ⁻–N was measured using a salicylic acid method (Ruiz and Romero, 2002). NH₄ ⁺–N was measured using a colorimetric method (Weatherburn, 1967; Xia et al., 2020). In addition, AA content was measured using the acid ninhydrin (Liu et al., 2015).

NR and NiR in leaves and roots were determined according to previous studies (Yu et al., 2016; Xia et al., 2020). Fresh tissue of leaves and roots (0.3 g) was ground with 4 mL of 0.1 M phosphate buffer (pH 7.5). The activities of NR and NiR were measured by the light absorption of residual NO₂ ⁻ at 540 nm. The protein content was analyzed by G-250 reagent using bovine serum albumin as a standard (Bradford, 1976).

GS and GOGAT were extracted and analyzed in leaves and roots, according to previous studies (Barbosa et al., 2010; Xia et al., 2020). GS activity was analyzed using the formation quantity of γ-glutamylhydroxamate. GOGAT activity was measured using a microplate reader at 340 nm by producing NADH oxidation.

The total RNA from control and treated roots and leaves at 15 DKT was extracted with the use of a DP441-50T RNAprep pure plant kit from Tiangen Biotech (Beijing, China) according to the manufacturer’s instructions. The total RNA (2 μg) was reverse-transcribed using a PrimeScript RT reagent cDNA kit (Takara). Afterward, the synthetic cDNA was used as a template for real-time PCR amplification. The primers of related genes were synthesized by Sangon Biotechnology (Shanghai, China), and the sequences were shown in Supplementary Table 1 . GAPDH was used as a reference gene, and the relative transcriptional levels of NRT1.1, NR, NiR, GS, and GOGAT were calculated using the 2^−ΔΔCT method (Park et al., 2012).

Data were analyzed with Origin 2018 and SPSS 23.0, and the results in the figures and tables are shown as the average value ± SE (n ≥ 3). Statistical analysis used Tukey’s honestly significant difference (HSD) test (p < 0.05).

Compared with the +K treatment (+K), plant growth inhibition was observed in the −K treatment (−K, Figure 1A ), leading to a significant decline in biomass under K deficiency ( Table 1 ). For Xushu 32 and Ningzishu 1, K deficiency reduced plant biomass by 24% and 35%, respectively. Ningzishu 1 was more drastically affected in the biomass of root and leaf when compared with Xushu 32, the biomass of root and leaf declined by 58% and 33% in −K than that in +K for Ningzishu 1, respectively, and a smaller decrease of 14%–20% was observed for Xushu 32. In addition, K deficiency significantly decreased the root–shoot ratio of Ningzishu 1 by 41% but had no significant effect on that of Xushu 32. Additionally, the K and N accumulation per plant also varied significantly between +K and −K and decreased by 79%–87% and 34%–56% in −K, respectively. The amplitude of variations of Ningzishu 1 for K and N accumulation were greater than those of Xushu 32.

The AA content in leaves and roots declined with DKT ( Figures 4A, B ) in the +K and −K treatments. The difference between −K and +K for AA content increased with DKT, but the significant difference in Ningzishu 1 was bigger than that in Xushu 32. With DKT, the soluble protein content in sweet potato leaves showed a single peak curve, and the peak value appeared at 5 DKT, while the root soluble protein content showed a decreasing trend ( Figures 4C, D ). K deficiency decreased soluble protein content in sweet potato leaves. Compared with +K, in −K, the soluble protein content in Xushu 32 and Ningzishu 1 leaves increased by 32% and 33% at 15 DKT, respectively. Nevertheless, in −K, the soluble protein content in roots showed an opposite trend with an increase of 17%–31% at 15 DKT, which was less than that of the soluble protein in leaves.

NO₃ ⁻–N content and NH₄ ⁺–N content in leaves and roots showed a single-peak curve with DKT, and the peak value appeared at 5 DKT ( Figure 5 ). In Xushu 32, the NO₃ ⁻–N content and NH₄ ⁺–N content in leaves only showed significant levels at 15 DKT (p < 0.05), while the two indexes in roots were not significantly affected by K deficiency (p > 0.05). In Ningzishu 1, the NO₃ ⁻–N content in leaves and NH₄ ⁺–N content in roots decreased significantly under K deficiency (p < 0.05), and the difference between −K and +K increased with DKT; in particular, the NH₄ ⁺–N content in roots was decreased by 8%–60%.

Except for NO₃ ⁻–N in leaves and NH₄ ⁺–N in roots for Xushu 32, the content of soluble protein, NO₃ ⁻–N, and NH₄ ⁺–N in leaves and roots was fitted with quadratic equation (R² = 0.657–0.914*, Figures 6A–F ). With the increase of leaf K content, the protein, NO₃ ⁻–N, and NH₄ ⁺–N in leaves and roots showed downward opening parabolic trends.

K deficiency reduced the activities of NR and NiR in leaves and roots for Ningzishu 1 ( Figure 7 ). In Ningzishu 1, compared with +K, K deficiency significantly decreased NR activity and NiR activity by 35% and 8% in leaves at 15 DKT (p < 0.05), respectively, and by 45% and 30% in roots, respectively. However, for Xushu 32, only the root NR activity was significantly decreased (p < 0.05, Figure 7B ).

GS activity showed a trend of increasing initially and then decreasing with DKT ( Figure 8A ). In Ningzishu 1, compared with +K, leaf GS activity in K-deficiency-treated plants decreased significantly from 5 DKT, with a decline of 13%–20%, but root GS activity decreased significantly from 10 DKT, with a decline of 35%–48% (p < 0.05). The GS activity in leaves and roots for Xushu 32 in −K had values similar to those for Ningzishu 1, but the decrements were smaller than those for Ningzishu 1.

With DKT, the changes in GOGAT activity were different from those of GS, presenting a “V” type. Compared with +K, the leaf GOGAT activity treated with −K reduced significantly, while the variation trend of root GOGAT activity was the opposite ( Figure 8C ). At the same DKT, the variation range of Ningzishu 1 under K deficiency was larger than that of Xushu 32.

NRT1 involved in nitrate transport in leaves and roots was downregulated in −K, except in Ningzishu 1 roots ( Figure 9 ). Under K deficiency, for Ningzishu 1, the transcript levels of NR2 in leaves and roots were downregulated by 39% and 53%, respectively. However, gene NR2 in Xushu 32 leaves and roots was not affected by K deficiency. The transcript levels of NiR significantly increased in leaves and roots, except in Xushu 32 roots. The −K induced a 69% upregulation in the transcript abundance of NiR in leaves and a 67% to 1.4-fold increase in the NiR gene transcript abundance in roots. In addition, there were no significant differences in the transcript levels of GS2 and GOGAT in leaves and roots, except in Xushu 32 leaves.

Potassium, as one of the main nutrients, participates in some physiological and biochemical processes in the plant (Wang et al., 2017; Zahoor et al., 2017a). The N content in leaves and roots showed a quadratic response to K content ( Table 1 ; Figure 2 ), suggesting that K deficiency affected N metabolism in sweet potatoes, as previously reported in cotton (Gossypium hirsutum L.) (Hu et al., 2016). Gao et al. (2021) reported that K affected starch-sucrose metabolism in tuberous roots; in this study, K deficiency increased K⁺ efflux from sweet potato roots, resulting in the decline of K content and accumulation in roots, stems, leaves, and the whole plants ( Table 1 ; Figures 1 , 3 ). These results indicated that K deficiency repressed K absorption in the roots of sweet potatoes and abated long-distance K transport from roots to stems to leaves, and similar results were reported in cotton (Hu et al., 2016). Previous studies reported that K deficiency could decrease the yield of sweet potato tuber and potato tuber (Wang et al., 2017; Koch et al., 2019; Gao et al., 2021). In this study, compared with +K, similar results were observed in root biomass and whole plant biomass, resulting in a lower root–shoot ratio ( Table 1 ).

In general, abiotic stress reduced plant biomass, coupled with the downregulated expression of genes, which mediated NO₃ ⁻ transport, such as NRT1 (Huang et al., 2018). In this study, K deficiency significantly inhibited the expression of NRT1 in sweet potatoes, except in Ningzishu 1 roots ( Figure 9 ). It was proved that, under abiotic stress, the transcription of NRT1.1 was mainly repressed in a N-efficient cultivar but was induced in the N-inefficient cultivar (Duan et al., 2016). As is well known, Xushu 32 is tolerant to low K, and Ningzishu 1 is sensitive to low K (Tang et al., 2014; Gao et al., 2021). Therefore, we hypothesized that the difference in NRT1 gene in K-deficient plants had a consistent performance on Xushu 32 and Ningzishu 1, like N-efficient and N-inefficient cultivars. In future work, this speculation needs to be further verified.

Compared with +K, the NO₃ ⁻–N content and NH₄ ⁺–N content in sweet potato leaves and roots were significantly reduced under K deficiency ( Figure 5 ), suggesting that K could significantly affect N metabolism in sweet potato leaves and roots, and leaf K content is necessary to maintain former activities at an optimum level, consistent with previous results (Hu et al., 2016; Ali et al., 2019). In this study, as exhibited in the relationship in NO₃ ⁻–N with leaf K content ( Figure 6 ), leaf K at an optimum level had a positive correlation with NO₃ ⁻–N, probably because K⁺ had a cooperative transport relationship with NO₃ ⁻–N in the xylem from roots to other parts in plants (Xu et al., 2012; Ma et al., 2020), but the excessive leaf K caused the decline of NO₃ ⁻–N and NH₄ ⁺–N in both leaves and roots. Nevertheless, some research found that low K decreased leaf NO₃ ⁻–N content in cotton, and leaf NO₃ ⁻–N had a linear positive relationship with leaf K (Hu et al., 2016), inconsistent with this study. Mainly because the crops are different, their samples were gathered from different parts, and their cotton plants were sown in the soil; however, the sweet potato seedlings in this study were planted under hydroponic conditions.

Nitrogen-containing compounds in plants, such as proteins and AAs, are the dominant products of NO₃ ⁻ assimilation. In this study, reduced NO₃ ⁻–N content and NH₄ ⁺–N content indicated that N metabolism could be reduced under K deficiency in leaves and roots, with a significant decrease in AA content ( Figures 4A, B ). In Ningzishu 1, K deficiency significantly decreased AA content in leaves and roots by 7%–13%, and the reduction of AAs in roots was similar to that in leaves; in Xushu 32, the reduction of AAs in leaves at 15 DKT was 9% greater than that in roots (6%). It may be that K deficiency decreased the unloading rate of AAs in the phloem for low-K-tolerant cultivars (Wang et al., 2012), which would decrease AA output from roots to leaves (Cakmak et al., 1994; Wang et al., 2012), resulting in higher AA accumulation in roots and plant biomass ( Table 1 ; Figure 4 ). The change trends of soluble protein content in leaves and roots of sweet potatoes were different under K deficiency. K deficiency reduced protein content in leaves by 2%–33% ( Figure 4C ). In accordance with our results, similar results were observed in cotton leaves and faba bean (Vicia faba L.) nodules (Wahab and Abdalla, 1995; Zahoor et al., 2017b). On the contrary, average root protein content increased by 6%–31%, smaller than that in leaves ( Figures 4C, D ), probably because decreased protease activity under K deficiency would lead to a decline in protein degradation rate and a significant increment in protein content (Ali et al., 2019). Reduced AA content and improved protein content in roots indicated that the K deficiency could also change the distribution and conversion of N-containing compounds between AAs and proteins in roots.

NR converts nitrate absorbed by the root into nitrite, which is then combined with NiR and converted into NH₄ ⁺ and is the first step of the NO₃ ⁻ assimilation pathway (Ali et al., 2019). In this study, even if the transcription levels of NR and NiR increased, decreased, or remain unchanged, NR and NiR activities in roots decreased under K deficiency ( Figures 7B, D , 9 ), and NO₃ ⁻–N will be converted into NH₄ ⁺ more quickly in plants, verified by a decrease of NO₃ ⁻/NH₄ ⁺ ratio under K deficiency in roots ( Supplementary Figure S1 ). These results were also demonstrated in Arabidopsis roots (Armengaud et al., 2009). As it is known, NH₄ ⁺–N is absorbed mainly through the pathway of GS/GOGAT. Previous studies have found that low K declined GS activity and GOGAT activity in crop roots. In this study, K deficiency significantly decreased GS activity and the content of NH₄ ⁺ and AA; however, the activity of GOGAT was improved ( Figures 8B, D , 4B ), even if the transcription levels of GS and GOGAT increased or remain unchanged ( Figure 9 ). Higher GOGAT activity under K deficiency did not increase the synthesis of AAs in roots, indicating that the transformation of AAs into proteins in roots and the AA export from roots to leaves were not inhibited. Moreover, K deficiency increased root protein content, and the decreasing amplitude of AA in leaves was larger than that in roots, which fully verified the above viewpoints. In Ningzishu 1 leaves, the contents of NO₃ ⁻–N and NH₄ ⁺–N decreased in K-deficiency-treated plants, but the NO₃ ⁻/NH₄ ⁺ ratio was increased, indicating that more NO₃ ⁻ was stored under K deficiency. Therefore, the resistance of NR and NiR activities to K deficiency may be a dominant factor that ameliorates the growth between Xushu 32 and Ningzishu 1 with different low-K sensitivities, in agreement with sweet potato and Salicornia europaea under abiotic stress conditions, revealing improved NO₃ ⁻ uptake (Nie et al., 2015; Xia et al., 2020).