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Molecular Soil Biology 2026, Vol.17 http://bioscipublisher.com/index.php/msb © 2026 BioSci Publisher, an online publishing platform of Sophia Publishing Group. All Rights Reserved. Sophia Publishing Group (SPG), founded in British Columbia of Canada, is a multilingual publisher. BioSci Publisher, operated by Sophia Publishing Group (SPG), is an international Open Access publishing platform that publishes scientific journals in the field of life science. Sophia Publishing Group (SPG), founded in British Columbia of Canada, is a multilingual publisher. Publisher Sophia Publishing Group Editedby Editorial Team of Molecular Soil Biology Email: edit@msb.bioscipublisher.com Website: http://bioscipublisher.com/index.php/msb Address: 11388 Stevenston Hwy, PO Box 96016, Richmond, V7A 5J5, British Columbia Canada Molecular Soil Biology (ISSN 1926-2005) is an open access, peer reviewed journal published online by BioSci Publisher. The journal publishes in describing and explaining biological processes in soil in terms of soil micro-structure, soil micro-ecosystems, soil microbiology and molecular interactions among soil, microbes and plants, environmental stress resistances, effects of introduced genetically modified organisms, chemical contamination and soil bioremediation, modeling of soil biological and biochemical processes, application and outcomes on the soil biotechnology, etc. At each level, different disciplinary approaches are welcome: molecular biology, genetics, ecophysiology and soil physiochemical properties. All the articles published in Molecular Soil Biology are Open Access, and are distributed under the terms of the Creative Commons Attribution License, which permits unrestricted use, distribution, and reproduction in any medium, provided the original work is properly cited. BioSci Publisher uses CrossCheck service to identify academic plagiarism through the world’s leading plagiarism prevention tool, iParadigms, and to protect the original authors’ copyrights.
Molecular Soil Biology (online), 2026, Vol. 17, No.1 ISSN 1926-2005 https://bioscipublisher.com/index.php/msb © 2026 BioSci Publisher, an online publishing platform of Sophia Publishing Group. All Rights Reserved. Sophia Publishing Group (SPG), founded in British Columbia of Canada, is a multilingual publisher Latest Content Variation Patterns and Influencing Factors of Microalgal Biomass under Abiotic Stress Xu Liu , Zeyu Jin , Haoda Liu, Yuanyuan Bu Molecular Soil Biology, 2026, Vol. 17, No. 1, 1-11 Effects of Irrigation Patterns on Soil Microbial Network Structure and Methanogenic Pathways in Subtropical Paddy Fields Zhongxian Li, Ruchun Chen, Haiying Huang Molecular Soil Biology, 2026, Vol. 17, No. 1, 12-25 Analysis of the Diversity and Functional Potential of Phosphate-Solubilizing Bacteria in Acidic Tea Garden Soil Lian Chen, Lianming Zhang Molecular Soil Biology, 2026, Vol. 17, No. 1, 26-37 Soil Microbial Community Changes under Continuous Cucumber Cropping in Greenhouse Systems Lingli Shen Molecular Soil Biology, 2026, Vol. 17, No. 1, 38-50 Rhizosphere Microbial Structure in Vineyard Soils under Integrated Nutrient Management Miaoya Weng Molecular Soil Biology, 2026, Vol. 17, No. 1, 51-60
Molecular Soil Biology 2026, Vol.17, No.1, 1-11 http://bioscipublisher.com/index.php/msb 1 Research Article Open Access Variation Patterns and Influencing Factors of Microalgal Biomass under Abiotic Stress Xu Liu*, Zeyu Jin*, Haoda Liu, Yuanyuan Bu Key Laboratory of Saline-Alkali Vegetation Ecology Restoration, Ministry of Education, College of Life Sciences, Northeast Forestry University, Harbin 150040, China * Contributed equally, and were the co-first authors of this paper Corresponding email: yuanyuanbu@nefu.edu.cn Molecular Soil Biology, 2026, Vol.17, No.1 doi: 10.5376/msb.2026.17.0001 Received: 17 Dec., 2025 Accepted: 20 Jan., 2026 Published: 06 Feb., 2026 Copyright © 2026 Liu et al., This is an open access article published under the terms of the Creative Commons Attribution License, which permits unrestricted use, distribution, and reproduction in any medium, provided the original work is properly cited. Preferred citation for this article: Liu X., Jin Z.Y., Liu H.D., and Bu Y.Y., 2026, Variation patterns and influencing factors of microalgal biomass under abiotic stress, Molecular Soil Biology, 17(1): 1-11 (doi: 10.5376/msb.2026.17.0001) Abstract To investigate the effects of EDTA-Ca and EDTA-Fe on microalgal biomass accumulation, this study used the salt-tolerant strain SA-2, isolated and screened from soda-alkali soil in Anda, Heilongjiang Province. SA-2 was treated with different concentrations of EDTA-Ca and EDTA-Fe to explore the effects of metal chelator–mediated micronutrient regulation on its growth and physiological–biochemical characteristics.The results showed that when the concentration of EDTA-Ca was 0.3 mg/L or that of EDTA-Fe was 0.2 mg/L, both the cell density and dry weight of SA-2 reached their highest levels, indicating optimal growth. At these concentrations, the lipid, chlorophyll, carbohydrate, and protein contents of the microalgae also reached their maximum values.This study identifies the optimal concentrations of EDTA-Ca and EDTA-Fe that promote the growth and biomass accumulation of SA-2, providing experimental evidence and theoretical guidance for efficient microalgae cultivation and biomass resource utilization. Keywords Microalgae; EDTA-Ca; EDTA-Fe; Biomass content 1 Introduction Against the backdrop of global ecological change and increasing resource demands, microalgae have received widespread attention as a biomass resource with tremendous potential. Microalgae are a group of algae that are widely distributed on land and in aquatic environments, microscopic in size, and whose morphology can only be distinguished under a microscope. They can utilize light, carbon dioxide, and water to carry out photosynthesis, efficiently producing a variety of functional bioactive substances, including proteins, polysaccharides, lipids, and pigments.Microalgae are capable of growing in diverse environments and exhibit rapid growth rates and high biomass accumulation. Owing to their rich nutritional composition and diverse functional components, microalgae show broad application prospects in the field of biological resource development (Fabris et al., 2020). As an important source of natural compounds, microalgae not only efficiently synthesize biofuels and polysaccharides but also possess the potential for producing high-value-added products. Pigments, essential amino acids, and vitamins contained in their cellular matrix form the basis for their application in the food industry, while their abundance of long-chain polyunsaturated fatty acids enhances their value in the development of nutritional supplements (Markou and Nerantzis, 2013).These multidimensional utilization characteristics make microalgae a strategically important raw material in sustainable biomanufacturing systems (Shin et al., 2015). EDTA is a widely used chelating agent that forms stable complexes with heavy metals, thereby reducing the toxic effects of heavy metals on plants. Owing to its chelating properties, EDTA is extensively applied in industries such as textiles, papermaking, food processing, medicine, and agriculture for purposes including water softening, boiler descaling, metal de-rusting, electroplating, and the enhanced remediation of heavy-metal-contaminated soils.However, the widespread use of EDTA has led to its significant accumulation in the environment, posing potential ecological risks. Although EDTA itself is non-toxic at low concentrations, its chemical stability and resistance to biodegradation enable its long-term persistence and accumulation in the environment. Meanwhile,
Molecular Soil Biology 2026, Vol.17, No.1, 1-11 http://bioscipublisher.com/index.php/msb 2 the prolonged environmental presence of EDTA can chelate toxic heavy metal ions already deposited in sediments, allowing these ions to re-enter aquatic systems and migrate freely, leading to environmental pollution (Claudia and Jaime, 2003) and disrupting the balance of essential nutrients required for algal growth. For example, metal ions such as iron, zinc, and magnesium are essential micronutrients in the photosynthetic and metabolic processes of algae. Excessive EDTA reduces the availability of these ions, thereby inhibiting normal algal growth and reproduction, slowing growth rates, and reducing cell division. EDTA also affects essential metabolic processes, including photosynthesis and respiration. It may interfere with chlorophyll synthesis and function, reduce photosynthetic efficiency, and limit the ability of algae to acquire energy, ultimately impairing growth and development. For instance, when the EDTA concentration exceeds 13.5 μmol/L, it significantly inhibits the growth of Microcystis aeruginosa (Chu et al., 2007). At low concentrations, however, EDTA can promote microalgal growth and biomass formation. Some studies have shown that low concentrations of EDTA can significantly alter metal toxicity to algae through chelation (Fawaz et al., 2018). When metals form stable complexes with EDTA, their bioavailability is markedly reduced, primarily through decreased concentrations of free metal ions in water, which are the most biologically accessible forms. This chelating mechanism diminishes the biological toxicity of metals, leading to a substantial reduction in toxicity indicators. Such phenomena have been confirmed in multiple toxicological studies involving metal–EDTA complex systems, verifying that the formation of metal–EDTA complexes is the primary mechanism for toxicity reduction (Geis et al., 2000). Some studies have found that high concentrations of EDTA strongly inhibit the growth of Microcystis aeruginosa but have little effect on Scenedesmus quadricauda (Zeng et al., 2009). Other reports indicate that EDTA supplementation can enhance lipid accumulation in microalgae (Ren et al., 2014). For instance, in Nannochloropsis oculata, both biomass and lipid accumulation increase progressively with rising EDTA concentrations (Xiao et al., 2013). Iron is one of the most important trace mineral elements in living organisms and is an essential component of intracellular redox reactions. It plays critical roles in cellular respiration, photosynthesis, and catalytic reactions involving metalloproteins. As an indispensable micronutrient for the growth and development of photosynthetic organisms, iron’s metabolic functions are mainly reflected in the molecular regulation of enzyme cofactors. Its transition metal properties provide a central role in electron transport chains and redox-catalyzed reactions, participating in metabolism through diverse structural forms, including iron–sulfur clusters, heme, di-iron centers, and mononuclear iron. In higher plants and microalgae, the iron–sulfur cluster biosynthesis systems—evolved from endosymbiotic bacteria—are located in the mitochondria and chloroplasts. Their precise assembly mechanisms support the continuous cofactor demand required for photosynthesis, respiration, and other energy metabolism processes (Balk and Schaedler, 2014). Iron deficiency disrupts electron transport and reduces energy conversion efficiency. Moreover, iron is an essential cofactor for enzymes such as RuBisCO and catalase, participating in carbon fixation and reactive oxygen species detoxification. Iron is also a key element in chlorophyll synthesis, the photosynthetic electron transport chain (e.g., cytochromes, ferredoxin), and enzymatic activities (e.g., catalase). Thus, it plays crucial roles in microalgal growth, metabolism, and biomass formation. Supplementing iron during the nutrient phase positively influences the photosynthetic mechanisms of the microalgae strain SA-2. Under mixotrophic conditions, iron significantly affects biomass, chlorophyll, carbohydrate, protein, and lipid synthesis in microalgae (Xia et al., 2010). Furthermore, relevant studies show that iron plays an essential role in microalgal growth and lipid accumulation. At certain concentrations, iron ions influence biomass, lipid composition, and metabolite synthesis, with high iron concentrations significantly affecting oleic acid accumulation (Zhang et al., 2014). Calcium is recognized as the second essential nutrient element in plants and is an important component of cell membranes. It affects the middle lamella of cell walls and plays a vital role in cell division, growth, and death (Lei et al., 2012). Calcium ions also significantly influence carbohydrate formation and transformation. Some studies indicate that calcium ions promote lipid synthesis in microalgae, and their oxides can catalyze microalgal oil synthesis for biodiesel production (Chen et al., 2016). At low concentrations, calcium ions promote
Molecular Soil Biology 2026, Vol.17, No.1, 1-11 http://bioscipublisher.com/index.php/msb 3 microalgal growth, increase biomass, and enhance lipid accumulation, although the effects are modest (Gao, 2024). High concentrations of calcium ions also promote biofilm formation derived from algal organic matter in the microalgal strain SA-2 (Fan et al., 2025).Currently, most studies regarding microalgae and calcium focus on the role of microalgae in balancing environmental calcium ions, with calcium concentrations negatively correlated with the growth of calcified microalgae (Zhao et al., 2020). Research on the effects of calcium on microalgal growth and biomass accumulation remains limited.However, in certain plants—such as Brassica campestris—supplementing calcium under stress conditions promotes growth and photosynthesis. Foliar calcium application increases flavonoid content, enhances electron transport rates, alleviates photosynthetic inhibition, and improves photosynthetic efficiency. Calcium ions also mitigate excessive acidification of the thylakoid membrane, maintain membrane integrity, and enhance ATPase activity (Cheng, 2020).As calcium ions support thylakoid membrane structure and the oxygen-evolving complex in PSII, appropriate concentrations of calcium may similarly promote microalgal growth and biomass synthesis. Excessive accumulation of EDTA-Ca and EDTA-Fe can elevate calcium and iron concentrations in the environment, potentially causing heavy metal-like stress and impairing normal microalgal growth. However, studies indicate that the exogenous addition of EDTA-Fe and EDTA-Ca complexes can significantly regulate the photosynthetic metabolic system of the microalgae SA-2 under mixotrophic conditions. Iron sources not only enhance biomass production by improving light energy conversion efficiency but also exhibit dose-dependent effects on intracellular chlorophyll, carbohydrate, protein, and macromolecular synthesis. Particularly in lipid metabolic regulation, EDTA-Fe displays concentration-dependent modulation, with oleic acid showing specific enrichment in triacylglycerols when the concentration reaches a threshold level (Kona et al., 2017). 2 Results and Analysis This study aims to investigate in depth the variation patterns and influencing factors of microalgal biomass content under EDTA-Fe and EDTA-Ca treatments. The expected outcomes will provide a theoretical basis for the efficient cultivation of microalgae and the optimized utilization of biomass resources, as well as technical support for further research on biomass accumulation in microalgae. Experimental results showed that supplementing the nutrient phase of microalgae SA-2 with EDTA-Ca at concentrations below 0.3 mg/L and EDTA-Fe at concentrations below 0.2 mg/L could promote the growth of SA-2 to a certain extent and increase its biomass yield. The optimal concentration for EDTA-Ca to promote SA-2 growth was 0.3 mg/L, whereas that for EDTA-Fe was 0.2 mg/L. At their respective optimal concentrations, both EDTA-Ca and EDTA-Fe enhanced cell density, dry weight, cell viability, and the contents of proteins, lipids, pigments, and carbohydrates in SA-2. The addition of EDTA-Ca and EDTA-Fe did not alter the logarithmic growth phase of SA-2, which was consistent with that of the untreated control. The promotive effect of EDTA-Fe at its optimal concentration on the growth and biomass synthesis of SA-2 was greater than that of EDTA-Ca at its optimal concentration. This indicates that iron, compared with calcium, plays a more critical role in the growth, reproduction, and biomass formation of microalgae, and that microalgae have a higher demand for iron. Furthermore, the optimal concentration of EDTA-Fe for SA-2 growth was lower than that of EDTA-Ca, suggesting that microalgae are more sensitive to iron than to calcium and are more susceptible to stress caused by high concentrations of iron ions. 2.1 Effects of EDTA-Fe and EDTA-Ca treatments on microalgal cell density Microalgae SA-2 exhibited the highest cell density and best growth performance when the concentration of EDTA-Ca was 0.3 mg/L. Concentrations of EDTA-Ca above 0.3 mg/L showed an inhibitory effect on SA-2 cell density (Figure 1a). For EDTA-Fe, the optimal concentration for promoting SA-2 growth was 0.2 mg/L, whereas concentrations above 0.2 mg/L began to inhibit microalgal growth (Figure 1b). These results indicate that EDTA-Ca at concentrations below 0.3 mg/L and EDTA-Fe at concentrations below 0.2 mg/L promoted the growth of SA-2, while higher concentrations of EDTA-Ca (>0.3 mg/L) and EDTA-Fe (>0.2 mg/L) inhibited growth. The cell density of SA-2 increased exponentially between days 9 and 10 (Figure 1), indicating that day 10 corresponds to the logarithmic growth phase. The addition of EDTA-Ca and EDTA-Fe did not significantly affect the duration or timing of the logarithmic growth phase of SA-2.
Molecular Soil Biology 2026, Vol.17, No.1, 1-11 http://bioscipublisher.com/index.php/msb 4 Figure 1 Changes in cell density of microalga SA-2 under different treatments Note: (a) EDTA-Ca at different concentrations; (b) EDTA-Fe at different concentrations 2.2 Effects of EDTA-Fe and EDTA-Ca treatments on microalgal dry weight The dry weight of microalgae SA-2 was calculated based on the constructed dry weight standard curve (Figure 2a). Changes in dry weight were consistent with changes in cell density. The maximum dry weight of SA-2 was observed at an EDTA-Ca concentration of 0.3 mg/L and an EDTA-Fe concentration of 0.2 mg/L, both reaching 0.9 g/L (Figure 2b; Figure 2c). These results indicate that EDTA-Ca at concentrations below 0.3 mg/L and EDTA-Fe at concentrations below 0.2 mg/L promoted the growth of microalgae. In contrast, EDTA-Ca concentrations above 0.3 mg/L and EDTA-Fe concentrations above 0.2 mg/L inhibited microalgal growth. Figure 2 Changes in dry weight of microalga SA-2 under different treatments Note: (a) Dry weight standard curve; (b) EDTA-Ca at different concentrations; (c) EDTA-Fe at different concentrations 2.3 Effects of EDTA-Fe and EDTA-Ca treatments on microalgal cell viability In this study, the effects of EDTA-Ca and EDTA-Fe treatments on microalgal cell viability were measured on day 12, and micrographs of SA-2 cells under different EDTA-Ca and EDTA-Fe concentration gradients were obtained (Figure 3). The strongest cell viability (96.50%) was observed under 0.3 mg/L EDTA-Ca treatment (Figure 4a), while the highest viability (97.24%) occurred under 0.2 mg/L EDTA-Fe treatment (Figure 4b). These results indicate that EDTA-Ca at concentrations below 0.3 mg/L and EDTA-Fe at concentrations below 0.2 mg/L enhance the cell viability of SA-2. Conversely, EDTA-Ca concentrations above 0.3 mg/L and EDTA-Fe concentrations above 0.2 mg/L inhibit cell viability, leading to increased microalgal cell death. Figure 3 Microscopic images of microalga SA-2 cells under different concentrations of EDTA-Ca and EDTA-Fe treatments
Molecular Soil Biology 2026, Vol.17, No.1, 1-11 http://bioscipublisher.com/index.php/msb 5 Figure 4 Changes in cell viability of microalga SA-2 under different treatments Note: (a) EDTA-Ca at different concentrations; (b) EDTA-Fe at different concentrations. Different lowercase letters indicate a significant difference (P<0.05) 2.4 Effects of EDTA-Fe and EDTA-Ca treatments on microalgal protein content Changes in microalgal protein content on day 12 were measured under different concentrations of EDTA-Ca and EDTA-Fe. The results showed that protein content was highest at an EDTA-Ca concentration of 0.3 mg/L, reaching 0.1 mg/mL (Figure 5a). For EDTA-Fe, the maximum protein synthesis occurred at 0.2 mg/L, with a protein content of 0.14 mg/mL (Figure 5b). These findings indicate that EDTA-Ca at concentrations below 0.3 mg/L and EDTA-Fe at concentrations below 0.2 mg/L promoted protein synthesis in SA-2. Conversely, EDTA-Ca concentrations above 0.3 mg/L and EDTA-Fe concentrations above 0.2 mg/L inhibited protein synthesis. The promotive effect of low-concentration EDTA-Fe (<0.2 mg/L) on protein synthesis was more pronounced than that of low-concentration EDTA-Ca (<0.3 mg/L), whereas the inhibitory effect of high-concentration EDTA-Fe (>0.2 mg/L) was stronger than that of high-concentration EDTA-Ca (>0.3 mg/L). Figure 5 Changes in protein content of microalgae SA-2 Note: (a) treatment groups with different concentrations of EDTA-Ca; (b) treatment groups with different concentrations of EDTA-Fe. Different lowercase letters indicate a significant difference (P<0.05) 2.5 Effects of EDTA-Fe and EDTA-Ca treatments on microalgal lipid content The changes in microalgal lipid content under different concentrations of EDTA-Ca and EDTA-Fe were measured. Lipid content reached its maximum under 0.3 mg/L EDTA-Ca treatment, with a value of 11.83 mg/L (Figure 6b). For EDTA-Fe, the highest lipid content was observed at 0.2 mg/L, reaching 13.45 mg/L (Figure 6c). These results indicate that EDTA-Ca at concentrations below 0.3 mg/L and EDTA-Fe at concentrations below 0.2 mg/L promoted lipid synthesis in SA-2. Conversely, EDTA-Ca concentrations above 0.3 mg/L and EDTA-Fe concentrations above 0.2 mg/L inhibited lipid synthesis. The promotive effect of low-concentration EDTA-Fe (<0.2 mg/L) on lipid accumulation was more pronounced than that of low-concentration EDTA-Ca (<0.3 mg/L), while the inhibitory effect of high-concentration EDTA-Fe (>0.2 mg/L) was stronger than that of high-concentration EDTA-Ca (>0.3 mg/L).
Molecular Soil Biology 2026, Vol.17, No.1, 1-11 http://bioscipublisher.com/index.php/msb 6 Figure 6 Changes in lipid content of microalgae SA-2 Note: (a) Standard curve of lipid content; (b)treatment groups with different concentrations of EDTA-Ca; (c) treatment groups with different concentrations of EDTA-Fe. Different lowercase letters indicate a significant difference (P<0.05) 2.6 Effects of EDTA-Fe and EDTA-Ca treatments on microalgal pigment content Pigment content of microalgae under different concentrations of EDTA-Ca and EDTA-Fe was measured at various wavelengths. Total chlorophyll content reached its maximum under 0.3 mg/L EDTA-Ca, at 12.24 mg/L (Figure 7a), and under 0.2 mg/L EDTA-Fe, at 10.19 mg/L (Figure 7b). Chlorophyll a content peaked at 10.60 mg/L with 0.3 mg/L EDTA-Ca (Figure 7c) and at 16.34 mg/L with 0.2 mg/L EDTA-Fe (Figure 7d). Chlorophyll b content was highest at 2.74 mg/L under 0.3 mg/L EDTA-Ca (Figure 7e) and 13.32 mg/L under 0.2 mg/L EDTA-Fe (Figure 7f). Carotenoid content reached a maximum of 2.74 mg/L under 0.3 mg/L EDTA-Ca (Figure 7g) and 4.47 mg/L under 0.2 mg/L EDTA-Fe (Figure 7h).These results indicate that EDTA-Ca at concentrations below 0.3 mg/L and EDTA-Fe at concentrations below 0.2 mg/L promoted the synthesis of various pigments in SA-2, whereas higher concentrations of EDTA-Ca (>0.3 mg/L) and EDTA-Fe (>0.2 mg/L) inhibited pigment synthesis. The promotive effect of low-concentration EDTA-Fe (<0.2 mg/L) was more pronounced than that of low-concentration EDTA-Ca (<0.3 mg/L), while the inhibitory effect of high-concentration EDTA-Fe (>0.2 mg/L) was stronger than that of high-concentration EDTA-Ca (>0.3 mg/L). This difference may be attributed to the role of iron in multiple aspects of microalgal physiology, including photosynthetic electron transport, chloroplast development, key enzyme activities, and photoprotective mechanisms, suggesting that iron is more critical than calcium for chlorophyll synthesis in microalgae. 2.7 Effects of EDTA-Fe and EDTA-Ca treatments on microalgal carbohydrate content Changes in microalgal carbohydrate content on day 12 were measured under different concentrations of EDTA-Ca and EDTA-Fe (Figure 8). Carbohydrate content reached its maximum at 58.13 mg/L under 0.3 mg/L EDTA-Ca. For EDTA-Fe, the highest carbohydrate content of 80.04 mg/L was observed at 0.2 mg/L. These results indicate that EDTA-Ca at concentrations below 0.3 mg/L and EDTA-Fe at concentrations below 0.2 mg/L promoted carbohydrate synthesis in SA-2. Conversely, EDTA-Ca concentrations above 0.3 mg/L and EDTA-Fe concentrations above 0.2 mg/L inhibited carbohydrate accumulation in the microalgae. 3 Discussion In this study, EDTA-Fe and EDTA-Ca exhibited differential effects on microalgal biomass accumulation. The results indicate that supplementation with appropriate concentrations of EDTA-Fe and EDTA-Ca generally enhanced biomass content, whereas excessive concentrations of either EDTA-Fe or EDTA-Ca exerted inhibitory effects on SA-2. This observation is closely related to the distinct roles of the two elements in microalgal metabolism. Iron ions function as cofactors in enzymatic reactions, particularly those involving iron-containing proteins, and participate in the photosynthetic electron transport chain. Microalgae are rich in iron-binding proteins such as iron–sulfur (Fe-S) proteins, ribonucleotide reductase (RNR), and hemoproteins, with iron serving as a cofactor in DNA replication, DNA repair, cell cycle progression, metabolic catalysis, and iron homeostasis (Zhang, 2014). Iron is also a core element for photosynthetic electron transport, chlorophyll synthesis, and multiple enzymatic reactions, with its sufficient supply directly determining photosynthetic efficiency and organic carbon fixation rates.In contrast, calcium primarily contributes to cellular structure, signal transduction, and physiological regulation rather than directly participating in photosynthesis. Unlike nitrogen or phosphorus, it
Molecular Soil Biology 2026, Vol.17, No.1, 1-11 http://bioscipublisher.com/index.php/msb 7 does not directly constitute biomass (e.g., proteins or nucleic acids), nor does it directly drive photosynthetic electron transport like iron. Its role is to provide “support” and “stability” within the cell (Thomas et al., 2023), and a stable intracellular environment is a prerequisite for efficient metabolic activities, including protein, lipid, and carbohydrate synthesis. The results of this study are consistent with previous reports highlighting the growth-promoting effects of iron on microalgae. Figure 7 Changes in Pigment Content of Microalga SA-2 Note: (a) Total pigment content of microalgae SA-2 under different EDTA-Ca concentrations; (b) Total pigment content of microalgae SA-2 under different EDTA-Fe concentrations; (c) Chlorophyll a content of microalgae SA-2 under different EDTA-Ca concentrations; (d) Chlorophyll a content of microalgae SA-2 under different EDTA-Fe concentrations; (e) Chlorophyll b content of microalgae SA-2 under different EDTA-Ca concentrations; (f) Chlorophyll b content of microalgae SA-2 under different EDTA-Fe concentrations; (g) Carotenoid content of microalgae SA-2 under different EDTA-Ca concentrations; (h) Carotenoid content of microalgae SA-2 under different EDTA-Fe concentrations. Different lowercase letters indicate a significant difference (P<0.05)
Molecular Soil Biology 2026, Vol.17, No.1, 1-11 http://bioscipublisher.com/index.php/msb 8 Figure 8 Changes in carbohydrate content of microalgae SA-2 Note: (a) Standard curve for carbohydrate content; (b) treatment groups with different concentrations of EDTA-Ca; (c) treatment groups with different concentrations of EDTA-Fe. Different lowercase letters indicate a significant difference(P<0.05) The chelating effect of EDTA plays a key role in microalgal cultivation. By binding Fe3+ andCa2+, EDTA prevents the rapid precipitation of these metal ions in the medium, thereby maintaining their bioavailability and extending their effective period in the culture. EDTA not only facilitates the uptake of metal ions but also indirectly regulates metabolic processes, improving light energy utilization and carbon flux allocation. Chelation of Fe by EDTA ensures the normal synthesis of key cellular components, such as iron–sulfur proteins and cytochromes, enhancing electron transport efficiency and promoting accumulation of photosynthetic products. Proper levels of EDTA-Ca help stabilize cell structure and regulate transmembrane ion channels, thereby improving overall cellular homeostasis. These positive effects synergistically enable higher growth rates and biomass production, with the presence of EDTA being a critical prerequisite for the promotive effects of both elements. EDTA’s chelation satisfies the continuous demand for metal ions during metabolic processes. Microalgae, as microorganisms with high light energy utilization efficiency and short growth cycles (Zhou and Ruan, 2014), hold significant potential in sustainable energy and biofuel production, the production of high-value nutrients and food additives, environmental remediation and carbon neutrality, as well as agriculture and fertilizer applications. Their further potential remains to be explored. This study systematically investigated the differential effects of EDTA-chelated metal ions (Fe and Ca) on microalgal biomass accumulation, providing new insights into strategies for enhancing biomass production. By referring to domestic and international reports on microalgal physiological responses to stress and the role of metal chelators in plants and algae, this study analyzed the effects of EDTA-Fe and EDTA-Ca on microalgal growth characteristics, cell viability, and biomass components including proteins, lipids, pigments, and carbohydrates. It was found that appropriate concentrations of EDTA-Fe and EDTA-Ca promoted the accumulation of various biomasses and cell biomass in SA-2, whereas excessive concentrations inhibited both biomass content and cell growth. These findings provide a theoretical basis for effective micronutrient supplementation strategies in microalgal cultivation. Future studies could further explore the synergistic effects of combined EDTA-Fe and EDTA-Ca supplementation, and, based on the specific metabolic characteristics of target algal species, develop customized chelated micronutrient nutrition schemes. Such approaches could enable integrated strategies for EDTA-Fe and EDTA-Ca supplementation in large-scale algal cultivation systems, improving biomass yield and the concurrent accumulation of high-value products such as lipids, polysaccharides, or pigments. With further process optimization and ecological safety evaluation, these findings are expected to advance the application of microalgae in biofuels, carbon mitigation, and bioproduct development. 4 Materials and Methods 4.1 Materials The microalga Nannochloris sp. SA-2 used in this study was isolated from saline-alkaline soil in Anda City, Heilongjiang Province, and was previously identified and preserved in our laboratory. It was cultured in Bold’s Basal Medium (BBM) under shaking conditions at 100 r/min. The cultivation temperature was maintained at (23±1) ℃, with a light/dark photoperiod of 16 h:8 h and a light intensity of 2 000 lx.
Molecular Soil Biology 2026, Vol.17, No.1, 1-11 http://bioscipublisher.com/index.php/msb 9 4.2 Microalgal cultivation SA-2 was cultured in BBM supplemented with EDTA-Fe and EDTA-Ca at concentrations of 0.1, 0.2, 0.3, 0.4, and 0.5 mg/L. The pH of the BBM medium was adjusted to 8.0 using 1 mol/L NaOH. The culture conditions were maintained at (23±1) ℃, with a light intensity of 2 000 lx and a 16 h:8 h light/dark cycle. 4.3 Monitoring microalgal cell density Samples were collected every 24 h for optical density (OD) measurements. Prior to sampling, the culture was gently mixed to prevent cell sedimentation, then transferred to a cuvette. Absorbance was measured at 682 nm using a spectrophotometer. Each measurement was performed in triplicate and the mean value was calculated to reduce error. 4.4 Monitoring microalgal dry weight Microalgal cells were collected from the culture by centrifugation. The pellet was washed 2~3 times with distilled water, centrifuged again, and transferred to pre-weighed dry filter paper. The samples were dried in an oven at 60 ℃to constant weight. Dry weight was measured using an electronic balance. A dry weight standard curve was constructed based on OD values to convert measured OD values to microalgal dry weight. 4.5 Monitoring microalgal cell viability An appropriate volume of microalgal culture was centrifuged and the cells were stained with trypan blue for 3 min. The samples were decolorized overnight in chloral hydrate solution at room temperature, with the solution replaced 2~3 times. Finally, the samples were stored in 50% (v/v) glycerol and counted using a hemocytometer (Wang, 2020). 4.6 Determination of microalgal protein content Protein content was measured using a BCA assay kit (Qiu, 2021). Two milliliters of culture was centrifuged at 8 000 r for 8 min. The pellet was washed twice with deionized water and resuspended in 1 mol/L NaOH solution, boiled for 10 min, and centrifuged at 8 000 r for 8 min. The supernatant was collected, and the extraction process was repeated three times. Protein content in the algal cells was determined using the BCA assay kit. 4.7 Determination of microalgal lipid content Lipid content was determined using the vanillin–phosphoric acid colorimetric method (Mishra et al., 2014). One hundred microliters of algal culture were placed in a stoppered test tube, 2 mL concentrated sulfuric acid was added, and the mixture was heated in a 100 ℃water bath for 10 min. After cooling to room temperature in an ice bath, 5 mL of vanillin–phosphoric acid reagent was added. The reaction proceeded at 37 ℃and 200 rpm on a shaker for 15 min. Absorbance was measured at 530 nm, and lipid content was calculated using a standard curve. 4.8 Determination of microalgal pigment content Pigment content was determined by extraction (Abrha et al., 2025). Two milliliters of culture were centrifuged, the supernatant discarded, and the pellet washed twice with sterile water. Methanol was added, and the samples were extracted in the dark at 4 ℃for 12 h. Absorbance of the supernatant was measured at 750, 665, 652, and 480 nm using a spectrophotometer. Pigment concentrations were calculated using the corresponding formulas. 4.9 Determination of microalgal carbohydrate content Carbohydrate content was measured using the anthrone method (Brányiková et al., 2011). Microalgal cells were collected by centrifugation (3 000~5 000 r, 5~10 min) and washed with distilled water. Cells were disrupted by vortexing 0.5 mL glass beads in 0.25 mL distilled water for 4 min. To the pellet, 3.3 mL of 30% perchloric acid was added, stirred at 25 ℃for 15 min, and centrifuged to obtain the supernatant. This extraction was repeated three times, the extracts were combined, and the volume adjusted to 10 mL. A 0.5 mL aliquot of the extract was cooled to 0 ℃, mixed with 2.5 mL anthrone reagent, and heated in a 100 ℃water bath for 8 min. After cooling to 20 ℃, absorbance was measured at 625 nm. Carbohydrate content was calculated using a standard curve and a correction factor of 0.9.
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Molecular Soil Biology 2026, Vol.17, No.1, 12-25 http://bioscipublisher.com/index.php/msb 12 Research Insight Open Access Effects of Irrigation Patterns on Soil Microbial Network Structure and Methanogenic Pathways in Subtropical Paddy Fields Zhongxian Li, Ruchun Chen, Haiying Huang Hier Rice Research Center, Hainan Institute of Tropical Agricultural Resources, Sanya, 572025, Hainan, China Corresponding email: haiying.huang@hitar.org Molecular Soil Biology, 2026, Vol.17, No.1 doi: 10.5376/msb.2026.17.0002 Received: 25 Dec., 2025 Accepted: 30 Jan., 2026 Published: 11 Feb., 2026 Copyright © 2026 Li et al., This is an open access article published under the terms of the Creative Commons Attribution License, which permits unrestricted use, distribution, and reproduction in any medium, provided the original work is properly cited. Preferred citation for this article: Li Z.X., Chen R.C., and Huang H.Y., 2026, Effects of irrigation patterns on soil microbial network structure and methanogenic pathways in subtropical paddy fields, Molecular Soil Biology, 17(1): 12-25 (doi: 10.5376/msb.2026.17.0001) Abstract Paddy fields in subtropical regions are constantly submerged in water, which can easily lead to a strong reducing environment, making methane-producing bacteria active and increasing methane emissions. However, in the context of increasingly scarce water resources and the continuous emphasis on the "dual carbon" goals, people have begun to pay more attention to alternate wetting and drying (AWD) irrigation, which is believed to save water and potentially reduce emissions. However, the situation is not that simple: some studies combining field experiments, meta-analyses, and multi-omics results have found that the microbial community, key functional genes, and network structure all change under different irrigation patterns. Generally speaking, compared with continuous flooding, AWD can significantly reduce methane emissions and lower the overall warming potential, but sometimes N₂O emissions increase, and the effect is also influenced by factors such as temperature, precipitation, soil organic carbon, and pH. In field practice, the often-mentioned "safe AWD", such as refilling water when the water level drops to about -15 cm, can generally ensure yield while saving water and reducing methane emissions. From a microbial perspective, the periodic changes in water can alter soil Eh and substrate supply, causing the methane-producing related groups and their connections to readjust. These changes often correspond to the variations in gas fluxes and also provide some references for paddy field water management. Keywords Alternate wetting and drying (AWD); Subtropical paddy fields; Microbial co-occurrence network; mcrA/pmoA; Methane production pathway 1 Introduction Rice paddies can actually be regarded as a kind of long-term managed wetland. Once watered, the oxygen in the soil is quickly consumed, and the environment gradually becomes anoxic. Various anaerobic decomposition processes become active, and methane becomes one of the important end products. However, the internal environment of the rice paddy is not entirely uniform. Early microbiological studies have found that flooded rice paddies are more like systems divided into several small "compartments": the surface layer often has a little oxygen, the lower layer is mostly anaerobic, and the rhizosphere and rhizoplane of rice form special micro-zones. Oxygen, nitrate, and methane often show obvious micro-scale gradients in these places. Because of this, methane production and methane oxidation often coexist and are significantly influenced by environmental conditions (Kögel-Knabner et al., 2021). From this perspective, rice paddies are not only like a continuously operating biogeochemical reaction field but are also often used to observe the relationship between microbial community structure and ecological function. For subtropical rice-growing areas, the climate is hot and humid, the multiple cropping index is high, and organic matter input and farming activities are relatively frequent. Therefore, methane emissions from rice paddies are not only related to climate change but also to regional ecological security and the transformation of agriculture towards a green approach (Li et al., 2022). Rice production has always been inseparable from irrigation. The traditional approach is continuous flooding (CF), which indeed helps suppress weeds and ensure stable yields, but the cost is also obvious: it consumes a large amount of water and the long-term waterlogging makes the soil more oxygen-deficient, increasing the risk of methane emissions (Zhang et al., 2019). In recent years, under the dual pressure of water resource constraints and emission reduction requirements, alternate wetting and drying (AWD) irrigation has gradually been promoted. Simply put, it involves allowing the field to periodically dry to a certain water level before re-flooding. The
Molecular Soil Biology 2026, Vol.17, No.1, 12-25 http://bioscipublisher.com/index.php/msb 13 International Rice Research Institute commonly uses a reference line of about 15 cm below the field surface and monitors water level changes by inserting perforated tubes. Many field studies have summarized data from 1990 to 2024, and the general results are relatively consistent: compared with continuous flooding, AWD can significantly reduce methane emissions and also lower the combined warming potential of CH4 andN2O (Jiang et al., 2022). However, the situation is not entirely uniform; in some areas, N2O emissions may increase, and the effect is also influenced by many factors, such as soil dryness, the frequency of wetting and drying, local precipitation and temperature, soil organic carbon, pH, and nitrogen application levels. Precisely because of this, when discussing irrigation methods now, the focus has gradually shifted from "whether to dry" to more detailed questions, such as to what water level to dry, at which growth stage to do it, and how to coordinate with nutrient management. In many past studies on greenhouse gas emissions from paddy fields, attention was often focused solely on the changes in the abundance of a certain type of functional microorganism, using it to explain the gas flux. However, in a system like soil where multiple processes occur simultaneously, this perspective is actually a bit simplistic: whether different groups change together and what resources or electron flows they might be linked through are also worthy of attention. Thus, the method of co-occurrence networks has gradually been introduced. Researchers first used high-throughput sequencing data to attempt to reconstruct the association relationships between different groups or genes, and then used indicators such as node degree, clustering coefficient, and modularity to describe the network structure. However, the amplification data itself has a relative abundance limitation, which can easily lead to false correlations. Therefore, some more robust inference methods have been developed later, such as SparCC for compositional data and SPIEC-EASI based on conditional independence relationships. With this network framework, people can not only see the influence of environmental selection but also discuss potential interactions and the position of key groups in the functional process, making paddy field methane research no longer rely solely on scattered indicators but closer to an understanding of the overall structure. 2 Theoretical Foundation and Research Hypotheses 2.1 Microbiological mechanism of methane generation and oxidation in paddy soil The amount of methane emitted from paddy fields is not determined by a single process. It can be roughly regarded as the cumulative result of "generation, oxidation and transport". The lower layer of the soil is anaerobic, where methanogenic archaea produce methane; but in the surface layer or near the rice roots, there is oxygen, and some methane will be consumed by methane-oxidizing bacteria. When these processes occur simultaneously, the remaining methane will enter the atmosphere through the rice ventilation structure, bubbling or diffusion (Nazaries et al., 2017). The stratified structure formed after flooding - the surface layer prefers oxygen, the lower part prefers anaerobic conditions, and the rhizosphere micro-region - precisely allows these processes to occur simultaneously at different locations. In research, some molecular markers are commonly used to track related microorganisms. For example, the mcrA gene encodes the alpha subunit of methanocoumarin reductase and is a key enzyme in the final step of methane production, and is usually regarded as a functional marker for methanogenic archaea; while pmoA is often used to describe the phylogeny and potential functions of aerobic methane-oxidizing bacteria. Some studies have proposed that the abundance of mcrA and pmoA, as well as their ratio, often provide clues for determining the source and sink relationship of soil methane (Tveit et al., 2019). However, it should be noted that simply looking at the gene quantity cannot directly indicate the flux size; it is necessary to combine environmental conditions and actual processes for understanding. 2.2 Mechanism of soil redox environment regulation by irrigation modes Many discussions will mention that when the irrigation method changes, the methane process also changes. The key lies in the fact that the soil's redox state is re-adjusted. During continuous flooding, the soil's Eh often remains at a relatively low level, and there are fewer available electron acceptors. As a result, the anaerobic processes such as fermentation, nutrient synthesis, and methane production tend to be more dominant (Conrad et al., 2020). However, if alternate wetting and drying irrigation is adopted, the situation is quite different: after the field surface
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