Influence of simulated future climate CO2 scenarios on carbon allocation in keystone Cyanobacterium Synechococcus

Influence of simulated future climate CO2 scenarios on carbon allocation in keystone Cyanobacterium Synechococcus | Research Square window.SnipcartSettings = { analytics: { enabled: false } }; (function() { var accessVector = localStorage.getItem('access_vector') || ''; window.dataLayer = window.dataLayer || []; if (accessVector) { window.dataLayer.push({ user: { profile: { profileInfo: { snid: accessVector } } } }); } })(); (function(w,d,s,l,i){w[l]=w[l]||[];w[l].push({'gtm.start':new Date().getTime(),event:'gtm.js'});var f=d.getElementsByTagName(s)[0],j=d.createElement(s),dl=l!='dataLayer'?'&l='+l:'';j.async=true;j.src='https://www.googletagmanager.com/gtm.js?id='+i+dl;f.parentNode.insertBefore(j,f);})(window,document,'script','dataLayer','GTM-K279D39R'); Browse Preprints In Review Journals COVID-19 Preprints AJE Video Bytes Research Tools Research Promotion AJE Professional Editing AJE Rubriq About Preprint Platform In Review Editorial Policies Our Team Advisory Board Help Center Sign In Submit a Preprint Cite Share Download PDF Research Article Influence of simulated future climate CO 2 scenarios on carbon allocation in keystone Cyanobacterium Synechococcus Yanyan Zhang, Lincheng Huang, Yongxin Liu, Tangcheng Li, Hong Du, and 2 more This is a preprint; it has not been peer reviewed by a journal. https://doi.org/ 10.21203/rs.3.rs-6676455/v1 This work is licensed under a CC BY 4.0 License Status: Under Review Version 1 posted 7 You are reading this latest preprint version Abstract Phytoplankton play a key role in aquatic carbon cycling. The partitioning of algal-derived carbon between particulate organic carbon (POC) and dissolved organic carbon (DOC), and its further fractionation within the DOC pool, determines the fate of fixed carbon. However, the regulatory mechanisms of phytoplankton carbon allocation under climate change remain insufficiently explored. Here, we investigated the carbon-partitioning response of a mode algae, Synechococcus to three carbon dioxide (CO 2 ) conditions in different future climate contexts. It was found that when CO 2 concentration increased to 850 ppm, the carbon allocation patterns did not have significantly changed compared to that under current CO 2 concentration. In contrast, till the end of incubation, the extreme CO 2 concentration of 1370 ppm led to significant decrease of 47.05% in the total organic carbon (TOC) concentration, with an increase of the concentration of extracellular DOC (DOC ex ) and a reduction of POC. Notably, the final proportion of DOC ex increased to 44.32% from 22.66% of the DOC fraction. Our observed changes in carbon allocation of Synechococcus under extreme CO 2 concentrations suggests a reduced contribution of phytoplankton to aquatic carbon sequestration via the biological carbon pump through POC sinking, with a larger proportion of microalgal carbon being directly allocated to the surface DOC pool in the form of potentially recalcitrant DOC. Our study has important implications for accurately evaluating the role of phytoplankton in aquatic carbon sequestration in the context of future climate change. Synechococcus carbon allocation elevated CO2 DOC carbon sequestration Figures Figure 1 Figure 2 Figure 3 Figure 4 Figure 5 Figure 6 1. Introduction Carbon is a fundamental element required by all aquatic organisms, serving both an essential nutrient and a key driver of aquatic metabolic processes, making it an issue of concern in biogeochemical cycling studies on aquatic ecosystems (Anderson et al., 2020 ; Williamson et al., 2009 ). As a primary regulator of carbon dynamics, phytoplankton play a crucial role in regulating carbon cycling of aquatic ecosystems through carbon fixation and allocation (Song et al., 2018 ). The partitioning of the algal-derived carbon between POC and DOC (Conan et al., 2007 ), as well as its further fractionation within the DOC pool, governs the fate of the fixed carbon (Henson et al., 2021 ). This process determines the proportion of POC that sinks to the sediments, the DOC released into the surrounding water, and the fraction assimilated by microbes (Hansell, 2013 ), ultimately shaping the phytoplankton’s contribution to aquatic carbon sequestration (Bressac et al., 2024 ; Jiao et al., 2010 ; Oschlies et al., 2018 ). Therefore, understanding the carbon partitioning helps assess the aquatic ecosystems’ long-term storage capacity and their role in the regional and global carbon balance (Fennel et al., 2022 ). However, the mechanisms underlying phytoplankton carbon allocation and its regulatory mechanisms remain insufficiently explored. The continuous rise in CO 2 , primarily driven by fossil fuel combustion and land-use changes, has increased global CO 2 concentrations to over 420 ppm today, with projections reaching approximately around 850 ppm and 1370 ppm by 2100 under different Representative Concentration Pathways (RCPs) (Riahi et al., 2007 ; van Vuuren et al., 2011 ; Yasuaki Hijioka & Nishimoto, 2008 ). Elevated CO 2 levels significantly regulate the growth-reproduction process of phytoplankton (Low-Décarie et al., 2011 ).There is a trade-off between growth and reproduction, with carbon allocation playing a crucial role in this balance (Herms & Mattson, 1992 ). During growth, carbon is primarily allocated to the synthesis of cellular structures and intracellular components (Isanta-Navarro et al., 2022 ), whereas during reproduction, it is mainly directed toward the biosynthesis of nucleic acids and proteins (Lu et al., 2019 ). Thus, we suggest that changes in CO 2 concentrations would alter phytoplankton carbon allocation by regulating their carbon metabolism. However, under different emission scenarios, how the rising CO 2 levels influences the carbon allocation in phytoplankton remains largely unknown. Previous studies mainly focused on the direct effects of CO₂ concentration on phytoplankton physiological metabolism (Jin et al., 2022 ), community structure (Arrigo et al., 1999 ), and carbon fixation efficiency (Tortell, 2000 ). In the context of existing research, the effects of CO 2 concentration on phytoplankton DOC content and its allocation are currently poorly understood. Due to the effect of carbon dioxide on the physiological metabolism of phytoplankton, phytoplankton are forced to up-or down-regulate their metabolic pathways to adapt to the stress of external conditions, so the composition of DOC will change. There are various types of phytoplankton DOC, including transparent extracellular polymer particles (TEP) with a small amount of proteins and lipids, low molecular weight substances such as organic acids, amino acids and monosaccharides, high molecular weight aromatic compounds, and photoprotection related substances. Their sensitivity to changes in CO 2 concentration varies, so the response of different compositions to elevated CO 2 varies greatly. There are gaps in this knowledge, and it is necessary to study the effects of changes in CO 2 concentration on the content, composition, and distribution of DOC in phytoplankton. The cyanobacterium Synechococcus sp., a ubiquitous picoplankton and key contributor to aquatic primary production (Novotny et al., 2023 ), serves as an ideal model to address this knowledge gap (Ravindran et al., 2024 ). Its rapid growth, well-characterized genomics, physiology and sensitivity to environmental stressors make it a robust indicator of CO 2 -induced biogeochemical shifts (Flombaum et al., 2013 ). Here, we investigate the responses of Synechococcus sp. to three CO 2 regimes (400, 850, and 1370 ppm), simulating different emission scenarios. Using controlled laboratory experiments, we quantify temporal changes in DOC fractions (extracellular and intracellular) and POC contents. We tried to elucidate how CO 2 -driven shifts in DOC production and partitioning. By integrating growth dynamics and carbon fractions, this study advances mechanistic understanding of phytoplankton responses to CO 2 enrichment, providing a framework to refine models of future oceanic carbon cycling. 2. Materials and methods 2.1 Organisms and seed cultivation The studied strain, Synechococcus sp. FACHB-410 was obtained from the National Aquatic Biological Resource Center, Institute of Hydrobiology, Chinese Academy of Sciences. The seeds were maintained in 500 mL flasks with sterilized BG-11 medium at a constant temperature of 25 ± 1°C under 12 h:12 h light cycling with light intensity of 20 ± 5 µmol photons m − 2 s − 1 , provided by cold white fluorescent tubes (Lu et al., 2020 ). The composition of BG-11 medium is detailed in Table S1 (Pandey et al., 2023 ). The seeds were cultivated until the late exponential growth phase with biomass at nearly 1.0 g L − 1 , then harvested by centrifugation in the speed of 4,000 rpm for 5 min and the algal pellets were washed twice by fresh medium for inoculation. 2.2 Experimental design The experiments for exploring the effect of CO 2 concentration on the growth and associated carbon partitioning of Synechococcus sp. FACHB-410 was carried out in flasks with a working volume of 50 mL. The seeds were inoculated into this flask containing 20 mL medium, the composition of which is detailed in Table S1 . The cultivation was carried out under an irradiance of 20 ± 5 µmol photons m − 2 s − 1 for a duration of 31 days, within temperature-controlled incubators set at CO 2 concentration from 400 ppm, 850 ppm to 1370 ppm, with a constant cultivation temperature of 25°C. Three biological replicates were established for each experimental group. Samples were periodically collected on days 0, 3, 10, 17, 24, and 31 to measure optical density and Chlorophyll-a (Chl- a ) content, and to collect samples for DOC fraction analysis. Additionally, algal cell particulate samples were collected on days 10 and 31 for the determination of POC content. 2.3 Growth analysis and calculation of carbon content During the experiment, the OD values of Synechococcus sp. FACHB-410 were measured by ReadMax1900 full-wavelength microplate reader (Shanghai Flash Spectrum Biological Technology Co., Ltd., Shanghai, China). Fresh samples (0.1 g) were homogenized in 10 mL of 90% (v/v) acetone, incubated at 4°C in darkness for 24 h, and centrifuged at 3,000 × g for 10 min (4°C). The supernatant absorbance was measured at 664 nm (Chl- a ) and 750 nm (turbidity background) using a ReadMax1900 microplate reader (Shanghai Flash Spectrum Biological Technology Co., Ltd., Shanghai, China). Chl- a concentration in the extract was calculated as: Chl- a (mg·L⁻¹) = 12.25×(A664 − A750), where A664​ and A750​ are absorbance values at respective wavelengths. The carbon content per unit Chl- a in each fraction was multiplied by the Chl- a concentration to obtain the total amount of carbon of single fraction in the whole culture system. 2.4 Carbon fractionation and determination Cell samples and surrounding waters were collected from the algal cultures. The DOC ex solution was the acidified supernatant obtained after centrifugation (9,000 rpm, 5 min) of 10 mL of algal culture. After acid washing, the algal pellets were passed through a 0.7 µm glass fiber filter membrane of known mass GF/F, dried and weighed, and the filter membrane was cut and shaken by adding NaOH and Zirconia grinding beads for cell fragmentation, and the supernatant obtained after centrifugation was designated as DOC in . The remaining algal pellets were gently re-suspended and filtered through 0.7-µm GF/F pre-combusted (400°C, 4 h) glass microfiber filters (Whatman). The filtrate was stored in pre-combusted 20-mL glass vials with acid-rinsed Teflon caps (Wheaton) (Qian & Mopper, 1996 ). Immediately after filtration, samples were acidified with HCl (25%, analysis grade, Carl Roth) to pH 2, then rinse with ddH 2 O until pH reached 7. The acidified and dried algal pellets were weighed and used for assessing the sum of POC and DOC in . Finally, the POC content (excluding DOC in ) was obtained by subtracting the DOC in from the total (POC and DOC in ) using a difference calculation method. 2.5 Statistical analysis The average of three biological replicates and standard deviation were calculated for all the points given in figures and tables. The statistical significant differences in growth and DOC fractions among treatments were analyzed using one-way analysis of variance with least-significant difference (LSD) multiple comparison test. All the statistical analysis and visualization were performed using Microsoft Excel and R program. 3. Results 3.1 POC and DOC allocation under varying CO 2 conditions The allocation of POC and DOC in Synechococcus sp. FACHB-410 showed differential responses to elevated CO 2 concentrations. In the case of moderate CO 2 rise (850 ppm), no significant changes in DOC (including DOC ex and DOC in ) or POC proportions were observed during the growth and decline phases compared to the control (400 ppm). In contrast, extreme CO 2 levels (1370 ppm) markedly altered carbon partitioning. Facing such high CO 2 concentration, POC content at the decline stage decreased to 28.61 ± 1.59 (mg mg − 1 Chl- a ), which was significantly lower than at 400 ppm ( p < 0.05, Fig. 1). Additionally, DOC in content reduced to 14.07 ± 3.06 (mg mg − 1 Chl- a ), showing significant differences compared with both 400 ppm and 850 ppm ( p < 0.05, Fig. 1). The proportion of DOC ex at 1370 ppm increased significantly, reaching 20.8%, which was significantly higher than the proportion of low concentration of CO 2 (Fig. 2). 3.2 Comparative Analysis of DOC Allocation Dynamics The concentration and proportional allocation of DOC ex and DOC in at three different CO 2 ambient concentrations exhibit significant differences. On day3, the concentration of DOC in at 850 ppm increased to 189.29 ± 6.56 (mg mg − 1 Chl- a ), which was significantly higher than that at 400 ppm ( p < 0.05, Fig. 3). The DOC in concentration at 1370 ppm exhibited a progressive decline starting from day 3, with values at later sampling points (days 17, 24, and 31) reaching 28.56 ± 2.38, 26.42 ± 0.54, and 14.06 ± 3.05 (mg mg⁻¹ Chl a ), respectively. These concentrations were significantly lower than those observed under 400 ppm CO₂ throughout the same period ( p < 0.05, Fig. 3). By analyzing the proportions of the two types of DOC, the proportion of DOC ex at 400 and 850 ppm on day 24 reaches its peak. At 850 and 1370 ppm, the proportion of DOC ex exhibits an increasing trend with the progression of culture time, although the value on day31 at 850 ppm shows a slight decrease. The maximum values of the proportion of DOC ex at concentrations of 400 ppm, 850 ppm, and 1370 ppm are 22.66%, 27.79%, and 44.32%, respectively (Fig. 4). 3.3 Changes in the total organic carbon The concentration of DOC ex increased progressively under all three CO 2 concentrations. The concentration of DOC in reached a maximum at 400 and 850ppm at the end of culture (day31). However, at 1370ppm, the concentration of DOC in varied very little, and the concentration at the end of culture (day 31) was 62.46 ± 13.56 (mg·L⁻¹), which was significantly lower than that at 400ppm and 850 ppm ( p < 0.05, Fig. 5). At 1370ppm, the concentration of POC in the decline period decreased to 127.05 ± 7.06 (mg·L⁻¹), which was significantly lower than that at 400ppm and 850 ppm ( p < 0.05, Fig. 6).In Fig. 6, the sum of the concentrations of the three carbon fractions was lowest at the decline phase of 1370 ppm, compared with 400 ppm and 850ppm, indicating that the extremely high CO 2 concentration significantly reduced the total carbon content of the Synechococcus sp. 4. Discussion 4.1 CO 2 -Driven Shifts in Carbon Allocation: Mechanisms and Implications Our study has, for the first time, elucidated the organic carbon partitioning patterns of microalgae under different CO 2 emission concentrations at current/moderate/extreme levels. We revealed that elevated CO 2 concentrations significantly reshape carbon partitioning in a common freshwater microalgae Synechococcus , with distinct responses observed under extreme CO 2 levels (1370 ppm). Specifically, this extreme CO 2 concentration led to a decrease in the total carbon content by the end of cultivation, with a reduction in the POC proportion and an increase of DOC ex proportion. Elevated CO 2 reshapes carbon allocation in phytoplankton by altering key enzymatic activities in photosynthesis. In Synechococcus , extreme CO 2 levels (1370 ppm) suppress RuBisCO carboxylation efficiency and reduce carbon fixation in the Calvin cycle (Jin et al., 2022 ), leading to a decrease in the organic carbon content fixed, a finding consistent with other studies (Moreno et al, 2024). After carbon is assimilated into the cell, it is channeled into glycolysis and the pentose phosophate pathways (Raven et al., 2014), ultimately determining cellular carbon allocation. Studies have shown that under high CO 2 conditions, more carbon is directed toward extracellular polysaccharide synthesis pathways (Xu et al., 2014), which reasonably explains the observed increase in DOC ex secretion under elevated CO 2 in this study. The dominance of DOC ex and the decline of POC under the influence of extreme CO 2 concentrations are the result of synechococcus altering metabolic action to adapt to environmental change. Under high CO 2 conditions, the marked increase in extracellular metabolite efflux in microalgae arises from a interplay of metabolic overflow, pH homeostasis mechanisms, and physicochemical constraints (Sun et al., 2016 ). Elevated CO 2 influx disrupts carbon flux equilibrium by overactivating the Calvin cycle and glycolysis, leading to intracellular accumulation of intermediates like phosphoenolpyruvate (PEP) and pyruvate (Guo et al., 2017 ; Li et al., 2022 ). When cellular storage capacities (e.g., starch granules or lipid droplets) are saturated, these intermediates passively diffuse across membranes via concentration gradients, as observed in Chlorella strains where PEP leakage correlates with cytosolic carbon overload (Li et al., 2022 ). Concurrently, CO 2 dissolution induces cytosolic acidification, triggering compensatory H⁺-organic acid co-transport systems such as upregulated Bestrophin-like anion channels in thylakoid membranes to extrude acetate and malate, thereby restoring pH balance (Burlacot et al., 2022 ). Additionally, small, lipophilic metabolites (e.g., pyruvate and α-ketoglutarate) generated in glycolysis and the pentose phosphate pathway exhibit inherent membrane permeability, with their diffusion rates increasing by 30–50% under high CO 2 due to enhanced solubility and reduced membrane rigidity (Guo et al., 2017 ; Xu et al., 2019 ). Collectively, this integrated response underscores how microalgae dynamically balance carbon assimilation with extracellular metabolite efflux to mitigate metabolic toxicity while adapting to hypercapnic environments. While our study identifies CO 2 -driven carbon reallocation trends, the molecular mechanisms remain unresolved, and the molecular identification technique Fourier-transform ion cyclotron resonance mass spectrometry (FT-ICR MS) needs to be introduced to broaden the insights (Qi et al., 2022 ; Wen et al., 2022 ). 4.2 Implications of CO 2 -Driven Carbon Allocation Shifts for Aquatic Carbon Cycling The observed CO 2 -induced reduction in POC and DOC in in Synechococcus sp., coupled with an increased proportion of DOC ex , holds critical implications for aquatic carbon cycling. POC serves as a primary driver of the biological carbon pump (BCP), facilitating carbon export to deeper waters via gravitational sinking (Wang et al., 2023 ). A decline in POC under elevated CO 2 may attenuate vertical carbon flux, reducing the efficiency of long-term carbon sequestration in sediments (Kalapurakkal et al., 2025 ). In addition, the decreased POC content could disrupt benthic food webs reliant on sinking POC as a carbon source, potentially altering secondary production and trophic interactions (Molari et al., 2018 ). Furthermore, the reallocation within the DOC pool, specifically the decline in DOC in and dominance of DOC ex , further modulates the fate of dissolved carbon. DOC in primarily composed of labile small-molecule metabolites such as amino acids and sugars, is rapidly assimilated by microbes due to its high bioavailability (Hansell, 2013 ). In contrast, DOC ex often contains larger molecular-weight compounds such as extracellular polysaccharides and protein colloids, which exhibit greater recalcitrance and require enzymatic hydrolysis prior to microbial utilization (Medeiros et al., 2015 ; Thornton, 2014 ). The preferential release of DOC ex under extreme CO 2 suggests a potential shift toward more persistent DOC forms, potentially hindering microbial carbon turnover and reducing the production of refractory DOC (RDOC) via the microbial carbon pump (MCP). The MCP relies on microbial transformation of labile DOC into RDOC, which resists degradation and contributes to centennial-scale carbon storage (Jiao et al., 2024 ). The increase in algal-derived RDOC suggests that the contribution of algal-derived carbon to the surface DOC pool in aquatic ecosystems is likely to be more direct and significant (Jiao et al., 2010 ). These findings suggest that under future extreme climate scenarios, rising CO 2 levels will significantly alter the pathways through which phytoplankton contribute to aquatic carbon sequestration. However, the direction and magnitude of this contribution still require further quantification by analyzing the proportions of bioactive vs. recalcitrant carbon in both POC and DOC fractions (Fennel et al., 2022 ). 5. Conclusion This study is the first try to investigate the effects of varying CO 2 concentrations under three climate change scenarios on carbon allocation in the common phytoplankton Synechococcus . We found that elevated CO 2 suppresses POC and DOC in , while stimulating the release of DOC ex . This shift may weaken phytoplankton’s contribution to aquatic carbon sequestration through BCP pathway by limiting the POC sinking through vertical carbon flux. Meanwhile, increased DOC ex release could potentially hinder the formation of recalcitrant DOC via the MCP pathway. These findings carry significant implications for accurately assessing phytoplankton’s role in aquatic carbon sequestration under future climate change. Declarations CRediT authorship contribution statement Yanyan Zhang: Writing – original draft, Methodology, Data curation, Conceptualization. Lincheng Huang: Methodology, Formal analysis, Data curation. Yongxin Liu: Methodology, Formal analysis, Data curation. Tangcheng Li: Writing – review & editing. Hong Du: Writing – review & editing. Faming Wang: Writing – review & editing, Funding acquisition. Zhe Lu: Writing – review & editing, Validation, Supervision, Project administration, Funding acquisition, Conceptualization. Acknowledgements Financial support has been given by National Key R&D Program of China (2023YFE0113102, 2023YFF1304500), the National Natural Science Foundation of China (32301398), Guangdong Basic and Applied Basic Research Foundation (2023A1515010946, 2024A1515030067), Guangdong Science and Technology Plan Project (2023B1212060046), and the MOST Ocean Negative Carbon Emissions project. Conflicts of interest The authors declare no competing financial interests. Data Availability Data will be made available on request. References Anderson, N.J., Heathcote, A.J., Engstrom, D.R., contributors, G.d. 2020. Anthropogenic alteration of nutrient supply increases the global freshwater carbon sink. Science Advances , 6 (16), eaaw2145. Arrigo, K.R., Robinson, D.H., Worthen, D.L., Dunbar, R.B., DiTullio, G.R., VanWoert, M., Lizotte, M.P. 1999. Phytoplankton Community Structure and the Drawdown of Nutrients and CO 2 in the Southern Ocean. Science , 283 (5400), 365–367. Bressac, M., Laurenceau-Cornec, E.C., Kennedy, F., Santoro, A.E., Paul, N.L., Briggs, N., Carvalho, F., Boyd, P.W. 2024. Decoding drivers of carbon flux attenuation in the oceanic biological pump. Nature , 633 (8030), 587–593. Burlacot, A., Dao, O., Auroy, P., Cuiné, S., Li-Beisson, Y., Peltier, G. 2022. Alternative photosynthesis pathways drive the algal CO 2 -concentrating mechanism. Nature , 605 (7909), 366–371. Conan, P., Søndergaard, M., Kragh, T., Thingstad, F., Pujo-Pay, M., Williams, P.J.l.B., Markager, S., Cauwet, G., Borch, N.H., Evans, D. 2007. Partitioning of organic production in marine plankton communities: The effects of inorganic nutrient ratios and community composition on new dissolved organic matter. Limnology and Oceanography , 52 (2), 753–765. Fennel, K., Mattern, J.P., Doney, S.C., Bopp, L., Moore, A.M., Wang, B., Yu, L. 2022. Ocean biogeochemical modelling. Nature Reviews Methods Primers , 2 (1), 76. Flombaum, P., Gallegos, J.L., Gordillo, R.A., Rincón, J., Zabala, L.L., Jiao, N., Karl, D.M., Li, W.K., Lomas, M.W., Veneziano, D., Vera, C.S., Vrugt, J.A., Martiny, A.C. 2013. Present and future global distributions of the marine Cyanobacteria Prochlorococcus and Synechococcus . Proc Natl Acad Sci U S A , 110 (24), 9824–9. Guo, Y., Yuan, Z., Xu, J., Wang, Z., Yuan, T., Zhou, W., Xu, J., Liang, C., Xu, H., Liu, S. 2017. Metabolic acclimation mechanism in microalgae developed for CO 2 capture from industrial flue gas. Algal Research , 26 , 225–233. Hansell, D.A. 2013. Recalcitrant Dissolved Organic Carbon Fractions. Annual Review of Marine Science , 5 (Volume 5, 2013), 421–445. Henson, S.A., Cael, B.B., Allen, S.R., Dutkiewicz, S. 2021. Future phytoplankton diversity in a changing climate. Nature Communications , 12 (1), 5372. Herms, D.A., Mattson, W.J. 1992. The dilemma of plants: to grow or defend. The quarterly review of biology , 67 (3), 283–335. Isanta‐Navarro, J., Prater, C., Peoples, L.M., Loladze, I., Phan, T., Jeyasingh, P.D., Church, M.J., Kuang, Y., Elser, J.J. 2022. Revisiting the growth rate hypothesis: Towards a holistic stoichiometric understanding of growth. Ecology Letters , 25 (10), 2324–2339. Jiao, N., Herndl, G.J., Hansell, D.A., Benner, R., Kattner, G., Wilhelm, S.W., Kirchman, D.L., Weinbauer, M.G., Luo, T., Chen, F., Azam, F. 2010. Microbial production of recalcitrant dissolved organic matter: long-term carbon storage in the global ocean. Nature Reviews Microbiology , 8 (8), 593–599. Jiao, N., Luo, T., Chen, Q., Zhao, Z., Xiao, X., Liu, J., Jian, Z., Xie, S., Thomas, H., Herndl, G.J., Benner, R., Gonsior, M., Chen, F., Cai, W.-J., Robinson, C. 2024. The microbial carbon pump and climate change. Nature Reviews Microbiology , 22 (7), 408–419. Jin, P., Ji, Y., Huang, Q., Li, P., Pan, J., Lu, H., Liang, Z., Guo, Y., Zhong, J., Beardall, J., Xia, J. 2022. A reduction in metabolism explains the tradeoffs associated with the long-term adaptation of phytoplankton to high CO 2 concentrations. New Phytologist , 233 (5), 2155–2167. Kalapurakkal, H.T., Dale, A.W., Schmidt, M., Taubner, H., Scholz, F., Spiegel, T., Fuhr, M., Wallmann, K. 2025. Sediment resuspension in muddy sediments enhances pyrite oxidation and carbon dioxide emissions in Kiel Bight. Communications Earth & Environment , 6 (1), 156. Li, J., Tang, X., Pan, K., Zhu, B., Li, Y., Wang, Z., Zhao, Y. 2022. Energy metabolism and intracellular pH regulation reveal different physiological acclimation mechanisms of Chlorella strains to high concentrations of CO 2 . Science of The Total Environment , 853 , 158627. Low-Décarie, E., Fussmann, G.F., Bell, G. 2011. The effect of elevated CO 2 on growth and competition in experimental phytoplankton communities. Global Change Biology , 17 (8), 2525–2535. Lu, Z., Dai, J., Zheng, L., Teng, Z., Zhang, Q., Qiu, D., Song, L. 2020. Disodium 2-oxoglutarate promotes carbon flux into astaxanthin and fatty acid biosynthesis pathways in Haematococcus . Bioresource Technology , 299 , 122612. Lu, Z., Zheng, L., Liu, J., Dai, J., Song, L. 2019. A novel fed-batch strategy to boost cyst cells production based on the understanding of intracellular carbon and nitrogen metabolism in Haematococcus pluvialis . Bioresource technology , 289 , 121744. Medeiros, P.M., Seidel, M., Powers, L.C., Dittmar, T., Hansell, D.A., Miller, W.L. 2015. Dissolved organic matter composition and photochemical transformations in the northern North Pacific Ocean. Geophysical Research Letters , 42 (3), 863–870. Molari, M., Guilini, K., Lott, C., Weber, M., de Beer, D., Meyer, S., Ramette, A., Wegener, G., Wenzhöfer, F., Martin, D., Cibic, T., De Vittor, C., Vanreusel, A., Boetius, A. 2018. CO(2) leakage alters biogeochemical and ecological functions of submarine sands. Sci Adv , 4 (2), eaao2040. Novotny, A., Serandour, B., Kortsch, S., Gauzens, B., Jan, K.M.G., Winder, M. 2023. DNA metabarcoding highlights cyanobacteria as the main source of primary production in a pelagic food web model. Science Advances , 9 (17), eadg1096. Oschlies, A., Brandt, P., Stramma, L., Schmidtko, S. 2018. Drivers and mechanisms of ocean deoxygenation. Nature Geoscience , 11 (7), 467–473. Pandey, S., Narayanan, I., Vinayagam, R., Selvaraj, R., Varadavenkatesan, T., Pugazhendhi, A. 2023. A review on the effect of blue green 11 medium and its constituents on microalgal growth and lipid production. Journal of Environmental Chemical Engineering , 11 (3), 109984. Qi, Y., Xie, Q., Wang, J.-J., He, D., Bao, H., Fu, Q.-L., Su, S., Sheng, M., Li, S.-L., Volmer, D.A., Wu, F., Jiang, G., Liu, C.-Q., Fu, P. 2022. Deciphering dissolved organic matter by Fourier transform ion cyclotron resonance mass spectrometry (FT-ICR MS): from bulk to fractions and individuals. Carbon Research , 1 (1), 3. Qian, J., Mopper, K.J.A.C. 1996. Automated high-performance, high-temperature combustion total organic carbon analyzer. 68 (18), 3090–3097. Ravindran, S., Hajinajaf, N., Kundu, P., Comes, J., Nielsen, D.R., Varman, A.M., Ghosh, A. 2024. Genome-Scale Metabolic Model Reconstruction and Investigation into the Fluxome of the Fast-Growing Cyanobacterium Synechococcus sp. PCC 11901. ACS Synthetic Biology , 13 (10), 3281–3294. Riahi, K., Grübler, A., Nakicenovic, N. 2007. Scenarios of long-term socio-economic and environmental development under climate stabilization. Technological forecasting and social change , 74 (7), 887–935. Song, C., Dodds, W.K., Rüegg, J., Argerich, A., Baker, C.L., Bowden, W.B., Douglas, M.M., Farrell, K.J., Flinn, M.B., Garcia, E.A. 2018. Continental-scale decrease in net primary productivity in streams due to climate warming. Nature Geoscience , 11 (6), 415–420. Sun, Z., Chen, Y.-F., Du, J. 2016. Elevated CO 2 improves lipid accumulation by increasing carbon metabolism in Chlorella sorokiniana . Plant Biotechnology Journal , 14 (2), 557–566. Thornton, D.C.O. 2014. Dissolved organic matter (DOM) release by phytoplankton in the contemporary and future ocean. European Journal of Phycology , 49 (1), 20–46. Tortell, P.D. 2000. Evolutionary and ecological perspectives on carbon acquisition in phytoplankton. Limnology and Oceanography , 45 (3), 744–750. van Vuuren, D.P., Edmonds, J., Kainuma, M., Riahi, K., Thomson, A., Hibbard, K., Hurtt, G.C., Kram, T., Krey, V., Lamarque, J.-F., Masui, T., Meinshausen, M., Nakicenovic, N., Smith, S.J., Rose, S.K. 2011. The representative concentration pathways: an overview. Climatic Change , 109 (1), 5. Wang, W.-L., Fu, W., Le Moigne, F.A.C., Letscher, R.T., Liu, Y., Tang, J.-M., Primeau, F.W. 2023. Biological carbon pump estimate based on multidecadal hydrographic data. Nature , 624 (7992), 579–585. Wen, Z., Shang, Y., Song, K., Liu, G., Hou, J., Lyu, L., Tao, H., Li, S., He, C., Shi, Q., He, D. 2022. Composition of dissolved organic matter (DOM) in lakes responds to the trophic state and phytoplankton community succession. Water Research , 224 , 119073. Williamson, C.E., Saros, J.E., Vincent, W.F., Smol, J.P. 2009. Lakes and reservoirs as sentinels, integrators, and regulators of climate change. Limnology and oceanography , 54 (6part2), 2273–2282. Xu, X., Martin, G.J.O., Kentish, S.E. 2019. Enhanced CO 2 bio-utilization with a liquid–liquid membrane contactor in a bench-scale microalgae raceway pond. Journal of CO 2 Utilization , 34 , 207–214. Yasuaki Hijioka, Y.M., Nishimoto, H. 2008. Global GHG emission scenarios under GIC; concentration stabilization targets. J. Glob. Environ. Eng , 13 , 97–108. Additional Declarations No competing interests reported. Supplementary Files SupplementaryFiles.docx Cite Share Download PDF Status: Under Review Version 1 posted Editorial decision: Revision requested 16 Jun, 2025 Reviews received at journal 12 Jun, 2025 Reviewers agreed at journal 21 May, 2025 Reviewers invited by journal 21 May, 2025 Editor assigned by journal 20 May, 2025 Submission checks completed at journal 19 May, 2025 First submitted to journal 15 May, 2025 You are reading this latest preprint version Research Square lets you share your work early, gain feedback from the community, and start making changes to your manuscript prior to peer review in a journal. As a division of Research Square Company, we’re committed to making research communication faster, fairer, and more useful. We do this by developing innovative software and high quality services for the global research community. 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Huang","email":"","orcid":"","institution":"South China Agricultural University","correspondingAuthor":false,"prefix":"","firstName":"Lincheng","middleName":"","lastName":"Huang","suffix":""},{"id":460029099,"identity":"906f4aef-d892-4115-80cd-378d5fe01759","order_by":2,"name":"Yongxin Liu","email":"","orcid":"","institution":"South China Agricultural University","correspondingAuthor":false,"prefix":"","firstName":"Yongxin","middleName":"","lastName":"Liu","suffix":""},{"id":460029100,"identity":"939aa404-416e-473e-b2a6-e7beaa6c8053","order_by":3,"name":"Tangcheng Li","email":"","orcid":"","institution":"Shantou University","correspondingAuthor":false,"prefix":"","firstName":"Tangcheng","middleName":"","lastName":"Li","suffix":""},{"id":460029101,"identity":"4c1ff1ce-8b43-4932-bd56-8bd6d1263240","order_by":4,"name":"Hong Du","email":"","orcid":"","institution":"Shantou University","correspondingAuthor":false,"prefix":"","firstName":"Hong","middleName":"","lastName":"Du","suffix":""},{"id":460029102,"identity":"08996caa-ac3a-4555-8da7-25f92d04661a","order_by":5,"name":"Faming Wang","email":"","orcid":"","institution":"Xiaoliang Research Station for Tropical Coastal Ecosystems, Chinese Academy of Sciences","correspondingAuthor":false,"prefix":"","firstName":"Faming","middleName":"","lastName":"Wang","suffix":""},{"id":460029103,"identity":"550971c4-44fd-473f-b359-c42946e27707","order_by":6,"name":"Zhe Lu","email":"data:image/png;base64,iVBORw0KGgoAAAANSUhEUgAAAZAAAAAyAQMAAABI0h/eAAAABlBMVEX///8AAABVwtN+AAAACXBIWXMAAA7EAAAOxAGVKw4bAAAAs0lEQVRIiWNgGAWjYBACPgYGNgaGCgYGA6K1sIHRGZK1MLaRpEUi/dmDj/Pq5M35FzB++MFgl0eEloR0w5nbDhvunPGAWbKHIbmYGC3HpHm3HUgwuHGAQZqB4UBiA2EtiW3Sf+fUgbQw/yZSSzKbNGMDc4LB+QY2Im3hecYm2XMM5BfGNsseg2TCWvjZ059J/KgBhdjhwzd+VNgR1oIAEiDFxMcO2L4DJCkfBaNgFIyCEQQAD7Q3Muq2HnsAAAAASUVORK5CYII=","orcid":"","institution":"Xiaoliang Research Station for Tropical Coastal Ecosystems, Chinese Academy of Sciences","correspondingAuthor":true,"prefix":"","firstName":"Zhe","middleName":"","lastName":"Lu","suffix":""}],"badges":[],"createdAt":"2025-05-16 02:38:18","currentVersionCode":1,"declarations":"","doi":"10.21203/rs.3.rs-6676455/v1","doiUrl":"https://doi.org/10.21203/rs.3.rs-6676455/v1","draftVersion":[],"editorialEvents":[],"editorialNote":"","failedWorkflow":false,"files":[{"id":83362529,"identity":"b508df80-b743-4b0c-ac37-86a3830aaba5","added_by":"auto","created_at":"2025-05-23 17:24:08","extension":"jpg","order_by":1,"title":"Figure 1","display":"","copyAsset":false,"role":"figure","size":130831,"visible":true,"origin":"","legend":"\u003cp\u003eSee image above for figure legend\u003c/p\u003e","description":"","filename":"1.jpg","url":"https://assets-eu.researchsquare.com/files/rs-6676455/v1/40f2e912bc155f65ca990969.jpg"},{"id":83362530,"identity":"c9ebd542-bfcd-40d3-ad5c-aa3eae7f4adf","added_by":"auto","created_at":"2025-05-23 17:24:08","extension":"jpg","order_by":2,"title":"Figure 2","display":"","copyAsset":false,"role":"figure","size":82208,"visible":true,"origin":"","legend":"\u003cp\u003eSee image above for figure legend\u003c/p\u003e","description":"","filename":"2.jpg","url":"https://assets-eu.researchsquare.com/files/rs-6676455/v1/48f43651f6d5314e5e713e97.jpg"},{"id":83362663,"identity":"0f7fc5b1-7836-46eb-b632-85790e3af307","added_by":"auto","created_at":"2025-05-23 17:32:08","extension":"jpg","order_by":3,"title":"Figure 3","display":"","copyAsset":false,"role":"figure","size":178879,"visible":true,"origin":"","legend":"\u003cp\u003eSee image above for figure legend\u003c/p\u003e","description":"","filename":"3.jpg","url":"https://assets-eu.researchsquare.com/files/rs-6676455/v1/2d7f7a2ca2dace183f9e79fd.jpg"},{"id":83362537,"identity":"2135fd64-2480-422a-b796-ce9bdf4bfb4e","added_by":"auto","created_at":"2025-05-23 17:24:08","extension":"jpg","order_by":4,"title":"Figure 4","display":"","copyAsset":false,"role":"figure","size":158592,"visible":true,"origin":"","legend":"\u003cp\u003eSee image above for figure legend\u003c/p\u003e","description":"","filename":"4.jpg","url":"https://assets-eu.researchsquare.com/files/rs-6676455/v1/b17644144ba39df3e0e14f3c.jpg"},{"id":83362662,"identity":"351e6de3-304f-49e5-b966-13c0ea413e47","added_by":"auto","created_at":"2025-05-23 17:32:08","extension":"jpg","order_by":5,"title":"Figure 5","display":"","copyAsset":false,"role":"figure","size":195860,"visible":true,"origin":"","legend":"\u003cp\u003eSee image above for figure legend\u003c/p\u003e","description":"","filename":"5.jpg","url":"https://assets-eu.researchsquare.com/files/rs-6676455/v1/a5ffd3a5f6cd3b2e9c7f4211.jpg"},{"id":83362534,"identity":"782fe089-d06b-48f8-84f2-57ebea80848a","added_by":"auto","created_at":"2025-05-23 17:24:08","extension":"jpg","order_by":6,"title":"Figure 6","display":"","copyAsset":false,"role":"figure","size":161622,"visible":true,"origin":"","legend":"\u003cp\u003eSee image above for figure legend\u003c/p\u003e","description":"","filename":"6.jpg","url":"https://assets-eu.researchsquare.com/files/rs-6676455/v1/610b54f1682bc05262dde382.jpg"},{"id":83362965,"identity":"a7950425-f2a9-409b-a2e0-2e345751067c","added_by":"auto","created_at":"2025-05-23 17:40:08","extension":"pdf","order_by":0,"title":"","display":"","copyAsset":false,"role":"manuscript-pdf","size":1700540,"visible":true,"origin":"","legend":"","description":"","filename":"manuscript.pdf","url":"https://assets-eu.researchsquare.com/files/rs-6676455/v1/002da4d7-6a4d-492f-9112-96ab51a6fcb7.pdf"},{"id":83362536,"identity":"af9b0d4a-6baf-49de-885d-820791cb1cf1","added_by":"auto","created_at":"2025-05-23 17:24:08","extension":"docx","order_by":1,"title":"","display":"","copyAsset":false,"role":"supplement","size":118642,"visible":true,"origin":"","legend":"","description":"","filename":"SupplementaryFiles.docx","url":"https://assets-eu.researchsquare.com/files/rs-6676455/v1/f54c1e2fe5b968617bbbdd0d.docx"}],"financialInterests":"No competing interests reported.","formattedTitle":"\u003cp\u003e\u003cstrong\u003eInfluence of simulated future climate CO\u003c/strong\u003e\u003csub\u003e\u003cstrong\u003e2\u003c/strong\u003e\u003c/sub\u003e\u003cstrong\u003e scenarios on carbon allocation in keystone Cyanobacterium \u003c/strong\u003e\u003cem\u003e\u003cstrong\u003eSynechococcus\u003c/strong\u003e\u003c/em\u003e\u003c/p\u003e","fulltext":[{"header":"1. Introduction","content":"\u003cp\u003eCarbon is a fundamental element required by all aquatic organisms, serving both an essential nutrient and a key driver of aquatic metabolic processes, making it an issue of concern in biogeochemical cycling studies on aquatic ecosystems (Anderson et al., \u003cspan citationid=\"CR1\" class=\"CitationRef\"\u003e2020\u003c/span\u003e; Williamson et al., \u003cspan citationid=\"CR37\" class=\"CitationRef\"\u003e2009\u003c/span\u003e). As a primary regulator of carbon dynamics, phytoplankton play a crucial role in regulating carbon cycling of aquatic ecosystems through carbon fixation and allocation (Song et al., \u003cspan citationid=\"CR30\" class=\"CitationRef\"\u003e2018\u003c/span\u003e). The partitioning of the algal-derived carbon between POC and DOC (Conan et al., \u003cspan citationid=\"CR5\" class=\"CitationRef\"\u003e2007\u003c/span\u003e), as well as its further fractionation within the DOC pool, governs the fate of the fixed carbon (Henson et al., \u003cspan citationid=\"CR10\" class=\"CitationRef\"\u003e2021\u003c/span\u003e). This process determines the proportion of POC that sinks to the sediments, the DOC released into the surrounding water, and the fraction assimilated by microbes (Hansell, \u003cspan citationid=\"CR9\" class=\"CitationRef\"\u003e2013\u003c/span\u003e), ultimately shaping the phytoplankton\u0026rsquo;s contribution to aquatic carbon sequestration (Bressac et al., \u003cspan citationid=\"CR3\" class=\"CitationRef\"\u003e2024\u003c/span\u003e; Jiao et al., \u003cspan citationid=\"CR13\" class=\"CitationRef\"\u003e2010\u003c/span\u003e; Oschlies et al., \u003cspan citationid=\"CR24\" class=\"CitationRef\"\u003e2018\u003c/span\u003e). Therefore, understanding the carbon partitioning helps assess the aquatic ecosystems\u0026rsquo; long-term storage capacity and their role in the regional and global carbon balance (Fennel et al., \u003cspan citationid=\"CR6\" class=\"CitationRef\"\u003e2022\u003c/span\u003e). However, the mechanisms underlying phytoplankton carbon allocation and its regulatory mechanisms remain insufficiently explored.\u003c/p\u003e \u003cp\u003eThe continuous rise in CO\u003csub\u003e2\u003c/sub\u003e, primarily driven by fossil fuel combustion and land-use changes, has increased global CO\u003csub\u003e2\u003c/sub\u003e concentrations to over 420 ppm today, with projections reaching approximately around 850 ppm and 1370 ppm by 2100 under different Representative Concentration Pathways (RCPs) (Riahi et al., \u003cspan citationid=\"CR29\" class=\"CitationRef\"\u003e2007\u003c/span\u003e; van Vuuren et al., \u003cspan citationid=\"CR34\" class=\"CitationRef\"\u003e2011\u003c/span\u003e; Yasuaki Hijioka \u0026amp; Nishimoto, \u003cspan citationid=\"CR39\" class=\"CitationRef\"\u003e2008\u003c/span\u003e). Elevated CO\u003csub\u003e2\u003c/sub\u003e levels significantly regulate the growth-reproduction process of phytoplankton (Low-D\u0026eacute;carie et al., \u003cspan citationid=\"CR18\" class=\"CitationRef\"\u003e2011\u003c/span\u003e).There is a trade-off between growth and reproduction, with carbon allocation playing a crucial role in this balance (Herms \u0026amp; Mattson, \u003cspan citationid=\"CR11\" class=\"CitationRef\"\u003e1992\u003c/span\u003e). During growth, carbon is primarily allocated to the synthesis of cellular structures and intracellular components (Isanta-Navarro et al., \u003cspan citationid=\"CR12\" class=\"CitationRef\"\u003e2022\u003c/span\u003e), whereas during reproduction, it is mainly directed toward the biosynthesis of nucleic acids and proteins (Lu et al., \u003cspan citationid=\"CR20\" class=\"CitationRef\"\u003e2019\u003c/span\u003e). Thus, we suggest that changes in CO\u003csub\u003e2\u003c/sub\u003e concentrations would alter phytoplankton carbon allocation by regulating their carbon metabolism. However, under different emission scenarios, how the rising CO\u003csub\u003e2\u003c/sub\u003e levels influences the carbon allocation in phytoplankton remains largely unknown.\u003c/p\u003e \u003cp\u003ePrevious studies mainly focused on the direct effects of CO₂ concentration on phytoplankton physiological metabolism (Jin et al., \u003cspan citationid=\"CR15\" class=\"CitationRef\"\u003e2022\u003c/span\u003e), community structure (Arrigo et al., \u003cspan citationid=\"CR2\" class=\"CitationRef\"\u003e1999\u003c/span\u003e), and carbon fixation efficiency (Tortell, \u003cspan citationid=\"CR33\" class=\"CitationRef\"\u003e2000\u003c/span\u003e). In the context of existing research, the effects of CO\u003csub\u003e2\u003c/sub\u003e concentration on phytoplankton DOC content and its allocation are currently poorly understood. Due to the effect of carbon dioxide on the physiological metabolism of phytoplankton, phytoplankton are forced to up-or down-regulate their metabolic pathways to adapt to the stress of external conditions, so the composition of DOC will change. There are various types of phytoplankton DOC, including transparent extracellular polymer particles (TEP) with a small amount of proteins and lipids, low molecular weight substances such as organic acids, amino acids and monosaccharides, high molecular weight aromatic compounds, and photoprotection related substances. Their sensitivity to changes in CO\u003csub\u003e2\u003c/sub\u003e concentration varies, so the response of different compositions to elevated CO\u003csub\u003e2\u003c/sub\u003e varies greatly. There are gaps in this knowledge, and it is necessary to study the effects of changes in CO\u003csub\u003e2\u003c/sub\u003e concentration on the content, composition, and distribution of DOC in phytoplankton.\u003c/p\u003e \u003cp\u003eThe cyanobacterium \u003cem\u003eSynechococcus\u003c/em\u003e sp., a ubiquitous picoplankton and key contributor to aquatic primary production (Novotny et al., \u003cspan citationid=\"CR23\" class=\"CitationRef\"\u003e2023\u003c/span\u003e), serves as an ideal model to address this knowledge gap (Ravindran et al., \u003cspan citationid=\"CR28\" class=\"CitationRef\"\u003e2024\u003c/span\u003e). Its rapid growth, well-characterized genomics, physiology and sensitivity to environmental stressors make it a robust indicator of CO\u003csub\u003e2\u003c/sub\u003e-induced biogeochemical shifts (Flombaum et al., \u003cspan citationid=\"CR7\" class=\"CitationRef\"\u003e2013\u003c/span\u003e). Here, we investigate the responses of \u003cem\u003eSynechococcus\u003c/em\u003e sp. to three CO\u003csub\u003e2\u003c/sub\u003e regimes (400, 850, and 1370 ppm), simulating different emission scenarios. Using controlled laboratory experiments, we quantify temporal changes in DOC fractions (extracellular and intracellular) and POC contents. We tried to elucidate how CO\u003csub\u003e2\u003c/sub\u003e-driven shifts in DOC production and partitioning. By integrating growth dynamics and carbon fractions, this study advances mechanistic understanding of phytoplankton responses to CO\u003csub\u003e2\u003c/sub\u003e enrichment, providing a framework to refine models of future oceanic carbon cycling.\u003c/p\u003e"},{"header":"2. Materials and methods","content":"\u003cdiv id=\"Sec3\" class=\"Section2\"\u003e \u003ch2\u003e2.1 Organisms and seed cultivation\u003c/h2\u003e \u003cp\u003eThe studied strain, \u003cem\u003eSynechococcus\u003c/em\u003e sp. FACHB-410 was obtained from the National Aquatic Biological Resource Center, Institute of Hydrobiology, Chinese Academy of Sciences. The seeds were maintained in 500 mL flasks with sterilized BG-11 medium at a constant temperature of 25\u0026thinsp;\u0026plusmn;\u0026thinsp;1\u0026deg;C under 12 h:12 h light cycling with light intensity of 20\u0026thinsp;\u0026plusmn;\u0026thinsp;5 \u0026micro;mol photons m\u003csup\u003e\u0026minus;\u0026thinsp;2\u003c/sup\u003e s\u003csup\u003e\u0026minus;\u0026thinsp;1\u003c/sup\u003e, provided by cold white fluorescent tubes (Lu et al., \u003cspan citationid=\"CR19\" class=\"CitationRef\"\u003e2020\u003c/span\u003e). The composition of BG-11 medium is detailed in Table \u003cspan refid=\"MOESM1\" class=\"InternalRef\"\u003eS1\u003c/span\u003e (Pandey et al., \u003cspan citationid=\"CR25\" class=\"CitationRef\"\u003e2023\u003c/span\u003e). The seeds were cultivated until the late exponential growth phase with biomass at nearly 1.0 g L\u003csup\u003e\u0026minus;\u0026thinsp;1\u003c/sup\u003e, then harvested by centrifugation in the speed of 4,000 rpm for 5 min and the algal pellets were washed twice by fresh medium for inoculation.\u003c/p\u003e \u003c/div\u003e \u003cdiv id=\"Sec4\" class=\"Section2\"\u003e \u003ch2\u003e2.2 Experimental design\u003c/h2\u003e \u003cp\u003eThe experiments for exploring the effect of CO\u003csub\u003e2\u003c/sub\u003e concentration on the growth and associated carbon partitioning of \u003cem\u003eSynechococcus\u003c/em\u003e sp. FACHB-410 was carried out in flasks with a working volume of 50 mL. The seeds were inoculated into this flask containing 20 mL medium, the composition of which is detailed in Table \u003cspan refid=\"MOESM1\" class=\"InternalRef\"\u003eS1\u003c/span\u003e. The cultivation was carried out under an irradiance of 20\u0026thinsp;\u0026plusmn;\u0026thinsp;5 \u0026micro;mol photons m\u003csup\u003e\u0026minus;\u0026thinsp;2\u003c/sup\u003e s\u003csup\u003e\u0026minus;\u0026thinsp;1\u003c/sup\u003e for a duration of 31 days, within temperature-controlled incubators set at CO\u003csub\u003e2\u003c/sub\u003e concentration from 400 ppm, 850 ppm to 1370 ppm, with a constant cultivation temperature of 25\u0026deg;C. Three biological replicates were established for each experimental group. Samples were periodically collected on days 0, 3, 10, 17, 24, and 31 to measure optical density and Chlorophyll-a (Chl-\u003cem\u003ea\u003c/em\u003e) content, and to collect samples for DOC fraction analysis. Additionally, algal cell particulate samples were collected on days 10 and 31 for the determination of POC content.\u003c/p\u003e \u003c/div\u003e \u003cdiv id=\"Sec5\" class=\"Section2\"\u003e \u003ch2\u003e2.3 Growth analysis and calculation of carbon content\u003c/h2\u003e \u003cp\u003eDuring the experiment, the OD values of \u003cem\u003eSynechococcus\u003c/em\u003e sp. FACHB-410 were measured by ReadMax1900 full-wavelength microplate reader (Shanghai Flash Spectrum Biological Technology Co., Ltd., Shanghai, China). Fresh samples (0.1 g) were homogenized in 10 mL of 90% (v/v) acetone, incubated at 4\u0026deg;C in darkness for 24 h, and centrifuged at 3,000 \u0026times; g for 10 min (4\u0026deg;C). The supernatant absorbance was measured at 664 nm (Chl-\u003cem\u003ea\u003c/em\u003e) and 750 nm (turbidity background) using a ReadMax1900 microplate reader (Shanghai Flash Spectrum Biological Technology Co., Ltd., Shanghai, China). Chl-\u003cem\u003ea\u003c/em\u003e concentration in the extract was calculated as: Chl-\u003cem\u003ea\u003c/em\u003e (mg\u0026middot;L⁻\u0026sup1;)\u0026thinsp;=\u0026thinsp;12.25\u0026times;(A664\u0026thinsp;\u0026minus;\u0026thinsp;A750), where A664​ and A750​ are absorbance values at respective wavelengths. The carbon content per unit Chl-\u003cem\u003ea\u003c/em\u003e in each fraction was multiplied by the Chl-\u003cem\u003ea\u003c/em\u003e concentration to obtain the total amount of carbon of single fraction in the whole culture system.\u003c/p\u003e \u003c/div\u003e \u003cdiv id=\"Sec6\" class=\"Section2\"\u003e \u003ch2\u003e2.4 Carbon fractionation and determination\u003c/h2\u003e \u003cp\u003eCell samples and surrounding waters were collected from the algal cultures. The DOC\u003csub\u003e\u003cem\u003eex\u003c/em\u003e\u003c/sub\u003e solution was the acidified supernatant obtained after centrifugation (9,000 rpm, 5 min) of 10 mL of algal culture. After acid washing, the algal pellets were passed through a 0.7 \u0026micro;m glass fiber filter membrane of known mass GF/F, dried and weighed, and the filter membrane was cut and shaken by adding NaOH and Zirconia grinding beads for cell fragmentation, and the supernatant obtained after centrifugation was designated as DOC\u003csub\u003e\u003cem\u003ein\u003c/em\u003e\u003c/sub\u003e. The remaining algal pellets were gently re-suspended and filtered through 0.7-\u0026micro;m GF/F pre-combusted (400\u0026deg;C, 4 h) glass microfiber filters (Whatman). The filtrate was stored in pre-combusted 20-mL glass vials with acid-rinsed Teflon caps (Wheaton) (Qian \u0026amp; Mopper, \u003cspan citationid=\"CR27\" class=\"CitationRef\"\u003e1996\u003c/span\u003e). Immediately after filtration, samples were acidified with HCl (25%, analysis grade, Carl Roth) to pH 2, then rinse with ddH\u003csub\u003e2\u003c/sub\u003eO until pH reached 7. The acidified and dried algal pellets were weighed and used for assessing the sum of POC and DOC\u003csub\u003e\u003cem\u003ein\u003c/em\u003e\u003c/sub\u003e. Finally, the POC content (excluding DOC\u003csub\u003e\u003cem\u003ein\u003c/em\u003e\u003c/sub\u003e) was obtained by subtracting the DOC\u003csub\u003e\u003cem\u003ein\u003c/em\u003e\u003c/sub\u003e from the total (POC and DOC\u003csub\u003e\u003cem\u003ein\u003c/em\u003e\u003c/sub\u003e) using a difference calculation method.\u003c/p\u003e \u003c/div\u003e \u003cdiv id=\"Sec7\" class=\"Section2\"\u003e \u003ch2\u003e2.5 Statistical analysis\u003c/h2\u003e \u003cp\u003eThe average of three biological replicates and standard deviation were calculated for all the points given in figures and tables. The statistical significant differences in growth and DOC fractions among treatments were analyzed using one-way analysis of variance with least-significant difference (LSD) multiple comparison test. All the statistical analysis and visualization were performed using Microsoft Excel and R program.\u003c/p\u003e \u003c/div\u003e"},{"header":"3. Results","content":"\u003cdiv id=\"Sec9\" class=\"Section2\"\u003e \u003ch2\u003e3.1 POC and DOC allocation under varying CO\u003csub\u003e2\u003c/sub\u003e conditions\u003c/h2\u003e \u003cp\u003eThe allocation of POC and DOC in \u003cem\u003eSynechococcus\u003c/em\u003e sp. FACHB-410 showed differential responses to elevated CO\u003csub\u003e2\u003c/sub\u003e concentrations. In the case of moderate CO\u003csub\u003e2\u003c/sub\u003e rise (850 ppm), no significant changes in DOC (including DOC\u003csub\u003e\u003cem\u003eex\u003c/em\u003e\u003c/sub\u003e and DOC\u003csub\u003e\u003cem\u003ein\u003c/em\u003e\u003c/sub\u003e) or POC proportions were observed during the growth and decline phases compared to the control (400 ppm). In contrast, extreme CO\u003csub\u003e2\u003c/sub\u003e levels (1370 ppm) markedly altered carbon partitioning. Facing such high CO\u003csub\u003e2\u003c/sub\u003e concentration, POC content at the decline stage decreased to 28.61\u0026thinsp;\u0026plusmn;\u0026thinsp;1.59 (mg mg\u003csup\u003e\u0026minus;\u0026thinsp;1\u003c/sup\u003e Chl-\u003cem\u003ea\u003c/em\u003e), which was significantly lower than at 400 ppm (\u003cem\u003ep\u003c/em\u003e\u0026thinsp;\u0026lt;\u0026thinsp;0.05, Fig.\u0026nbsp;1). Additionally, DOC\u003csub\u003e\u003cem\u003ein\u003c/em\u003e\u003c/sub\u003e content reduced to 14.07\u0026thinsp;\u0026plusmn;\u0026thinsp;3.06 (mg mg\u003csup\u003e\u0026minus;\u0026thinsp;1\u003c/sup\u003e Chl-\u003cem\u003ea\u003c/em\u003e), showing significant differences compared with both 400 ppm and 850 ppm (\u003cem\u003ep\u003c/em\u003e\u0026thinsp;\u0026lt;\u0026thinsp;0.05, Fig.\u0026nbsp;1). The proportion of DOC\u003csub\u003e\u003cem\u003eex\u003c/em\u003e\u003c/sub\u003e at 1370 ppm increased significantly, reaching 20.8%, which was significantly higher than the proportion of low concentration of CO\u003csub\u003e2\u003c/sub\u003e (Fig.\u0026nbsp;2).\u003c/p\u003e \u003c/div\u003e \u003cdiv id=\"Sec10\" class=\"Section2\"\u003e \u003ch2\u003e3.2 Comparative Analysis of DOC Allocation Dynamics\u003c/h2\u003e \u003cp\u003eThe concentration and proportional allocation of DOC\u003csub\u003e\u003cem\u003eex\u003c/em\u003e\u003c/sub\u003e and DOC\u003csub\u003e\u003cem\u003ein\u003c/em\u003e\u003c/sub\u003e at three different CO\u003csub\u003e2\u003c/sub\u003e ambient concentrations exhibit significant differences. On day3, the concentration of DOC\u003csub\u003e\u003cem\u003ein\u003c/em\u003e\u003c/sub\u003e at 850 ppm increased to 189.29\u0026thinsp;\u0026plusmn;\u0026thinsp;6.56 (mg mg\u003csup\u003e\u0026minus;\u0026thinsp;1\u003c/sup\u003e Chl-\u003cem\u003ea\u003c/em\u003e), which was significantly higher than that at 400 ppm (\u003cem\u003ep\u003c/em\u003e\u0026thinsp;\u0026lt;\u0026thinsp;0.05, Fig.\u0026nbsp;3). The DOC\u003csub\u003e\u003cem\u003ein\u003c/em\u003e\u003c/sub\u003e concentration at 1370 ppm exhibited a progressive decline starting from day 3, with values at later sampling points (days 17, 24, and 31) reaching 28.56\u0026thinsp;\u0026plusmn;\u0026thinsp;2.38, 26.42\u0026thinsp;\u0026plusmn;\u0026thinsp;0.54, and 14.06\u0026thinsp;\u0026plusmn;\u0026thinsp;3.05 (mg mg⁻\u0026sup1; Chl \u003cem\u003ea\u003c/em\u003e), respectively. These concentrations were significantly lower than those observed under 400 ppm CO₂ throughout the same period (\u003cem\u003ep\u003c/em\u003e\u0026thinsp;\u0026lt;\u0026thinsp;0.05, Fig.\u0026nbsp;3). By analyzing the proportions of the two types of DOC, the proportion of DOC\u003csub\u003e\u003cem\u003eex\u003c/em\u003e\u003c/sub\u003e at 400 and 850 ppm on day 24 reaches its peak. At 850 and 1370 ppm, the proportion of DOC\u003csub\u003e\u003cem\u003eex\u003c/em\u003e\u003c/sub\u003e exhibits an increasing trend with the progression of culture time, although the value on day31 at 850 ppm shows a slight decrease. The maximum values of the proportion of DOC\u003csub\u003e\u003cem\u003eex\u003c/em\u003e\u003c/sub\u003e at concentrations of 400 ppm, 850 ppm, and 1370 ppm are 22.66%, 27.79%, and 44.32%, respectively (Fig.\u0026nbsp;4).\u003c/p\u003e \u003c/div\u003e \u003cdiv id=\"Sec11\" class=\"Section2\"\u003e \u003ch2\u003e3.3 Changes in the total organic carbon\u003c/h2\u003e \u003cp\u003eThe concentration of DOC\u003csub\u003e\u003cem\u003eex\u003c/em\u003e\u003c/sub\u003e increased progressively under all three CO\u003csub\u003e2\u003c/sub\u003e concentrations. The concentration of DOC\u003csub\u003e\u003cem\u003ein\u003c/em\u003e\u003c/sub\u003e reached a maximum at 400 and 850ppm at the end of culture (day31). However, at 1370ppm, the concentration of DOC\u003csub\u003e\u003cem\u003ein\u003c/em\u003e\u003c/sub\u003e varied very little, and the concentration at the end of culture (day 31) was 62.46\u0026thinsp;\u0026plusmn;\u0026thinsp;13.56 (mg\u0026middot;L⁻\u0026sup1;), which was significantly lower than that at 400ppm and 850 ppm (\u003cem\u003ep\u003c/em\u003e\u0026thinsp;\u0026lt;\u0026thinsp;0.05, Fig.\u0026nbsp;5). At 1370ppm, the concentration of POC in the decline period decreased to 127.05\u0026thinsp;\u0026plusmn;\u0026thinsp;7.06 (mg\u0026middot;L⁻\u0026sup1;), which was significantly lower than that at 400ppm and 850 ppm (\u003cem\u003ep\u003c/em\u003e\u0026thinsp;\u0026lt;\u0026thinsp;0.05, Fig.\u0026nbsp;6).In Fig.\u0026nbsp;6, the sum of the concentrations of the three carbon fractions was lowest at the decline phase of 1370 ppm, compared with 400 ppm and 850ppm, indicating that the extremely high CO\u003csub\u003e2\u003c/sub\u003e concentration significantly reduced the total carbon content of the \u003cem\u003eSynechococcus\u003c/em\u003e sp.\u003c/p\u003e \u003c/div\u003e"},{"header":"4. Discussion","content":"\u003cdiv id=\"Sec13\" class=\"Section2\"\u003e \u003ch2\u003e4.1 CO\u003csub\u003e2\u003c/sub\u003e-Driven Shifts in Carbon Allocation: Mechanisms and Implications\u003c/h2\u003e \u003cp\u003eOur study has, for the first time, elucidated the organic carbon partitioning patterns of microalgae under different CO\u003csub\u003e2\u003c/sub\u003e emission concentrations at current/moderate/extreme levels. We revealed that elevated CO\u003csub\u003e2\u003c/sub\u003e concentrations significantly reshape carbon partitioning in a common freshwater microalgae \u003cem\u003eSynechococcus\u003c/em\u003e, with distinct responses observed under extreme CO\u003csub\u003e2\u003c/sub\u003e levels (1370 ppm). Specifically, this extreme CO\u003csub\u003e2\u003c/sub\u003e concentration led to a decrease in the total carbon content by the end of cultivation, with a reduction in the POC proportion and an increase of DOC\u003csub\u003e\u003cem\u003eex\u003c/em\u003e\u003c/sub\u003e proportion. Elevated CO\u003csub\u003e2\u003c/sub\u003e reshapes carbon allocation in phytoplankton by altering key enzymatic activities in photosynthesis. In \u003cem\u003eSynechococcus\u003c/em\u003e, extreme CO\u003csub\u003e2\u003c/sub\u003e levels (1370 ppm) suppress RuBisCO carboxylation efficiency and reduce carbon fixation in the Calvin cycle (Jin et al., \u003cspan citationid=\"CR15\" class=\"CitationRef\"\u003e2022\u003c/span\u003e), leading to a decrease in the organic carbon content fixed, a finding consistent with other studies (Moreno et al, 2024). After carbon is assimilated into the cell, it is channeled into glycolysis and the pentose phosophate pathways (Raven et al., 2014), ultimately determining cellular carbon allocation. Studies have shown that under high CO\u003csub\u003e2\u003c/sub\u003e conditions, more carbon is directed toward extracellular polysaccharide synthesis pathways (Xu et al., 2014), which reasonably explains the observed increase in DOC\u003csub\u003eex\u003c/sub\u003e secretion under elevated CO\u003csub\u003e2\u003c/sub\u003e in this study.\u003c/p\u003e \u003cp\u003eThe dominance of DOC\u003csub\u003e\u003cem\u003eex\u003c/em\u003e\u003c/sub\u003e and the decline of POC under the influence of extreme CO\u003csub\u003e2\u003c/sub\u003e concentrations are the result of \u003cem\u003esynechococcus\u003c/em\u003e altering metabolic action to adapt to environmental change. Under high CO\u003csub\u003e2\u003c/sub\u003e conditions, the marked increase in extracellular metabolite efflux in microalgae arises from a interplay of metabolic overflow, pH homeostasis mechanisms, and physicochemical constraints (Sun et al., \u003cspan citationid=\"CR31\" class=\"CitationRef\"\u003e2016\u003c/span\u003e). Elevated CO\u003csub\u003e2\u003c/sub\u003e influx disrupts carbon flux equilibrium by overactivating the Calvin cycle and glycolysis, leading to intracellular accumulation of intermediates like phosphoenolpyruvate (PEP) and pyruvate (Guo et al., \u003cspan citationid=\"CR8\" class=\"CitationRef\"\u003e2017\u003c/span\u003e; Li et al., \u003cspan citationid=\"CR17\" class=\"CitationRef\"\u003e2022\u003c/span\u003e). When cellular storage capacities (e.g., starch granules or lipid droplets) are saturated, these intermediates passively diffuse across membranes via concentration gradients, as observed in \u003cem\u003eChlorella\u003c/em\u003e strains where PEP leakage correlates with cytosolic carbon overload (Li et al., \u003cspan citationid=\"CR17\" class=\"CitationRef\"\u003e2022\u003c/span\u003e). Concurrently, CO\u003csub\u003e2\u003c/sub\u003e dissolution induces cytosolic acidification, triggering compensatory H⁺-organic acid co-transport systems such as upregulated Bestrophin-like anion channels in thylakoid membranes to extrude acetate and malate, thereby restoring pH balance (Burlacot et al., \u003cspan citationid=\"CR4\" class=\"CitationRef\"\u003e2022\u003c/span\u003e). Additionally, small, lipophilic metabolites (e.g., pyruvate and α-ketoglutarate) generated in glycolysis and the pentose phosphate pathway exhibit inherent membrane permeability, with their diffusion rates increasing by 30\u0026ndash;50% under high CO\u003csub\u003e2\u003c/sub\u003e due to enhanced solubility and reduced membrane rigidity (Guo et al., \u003cspan citationid=\"CR8\" class=\"CitationRef\"\u003e2017\u003c/span\u003e; Xu et al., \u003cspan citationid=\"CR38\" class=\"CitationRef\"\u003e2019\u003c/span\u003e). Collectively, this integrated response underscores how microalgae dynamically balance carbon assimilation with extracellular metabolite efflux to mitigate metabolic toxicity while adapting to hypercapnic environments. While our study identifies CO\u003csub\u003e2\u003c/sub\u003e-driven carbon reallocation trends, the molecular mechanisms remain unresolved, and the molecular identification technique Fourier-transform ion cyclotron resonance mass spectrometry (FT-ICR MS) needs to be introduced to broaden the insights (Qi et al., \u003cspan citationid=\"CR26\" class=\"CitationRef\"\u003e2022\u003c/span\u003e; Wen et al., \u003cspan citationid=\"CR36\" class=\"CitationRef\"\u003e2022\u003c/span\u003e).\u003c/p\u003e \u003c/div\u003e \u003cdiv id=\"Sec14\" class=\"Section2\"\u003e \u003ch2\u003e4.2 Implications of CO\u003csub\u003e2\u003c/sub\u003e-Driven Carbon Allocation Shifts for Aquatic Carbon Cycling\u003c/h2\u003e \u003cp\u003eThe observed CO\u003csub\u003e2\u003c/sub\u003e-induced reduction in POC and DOC\u003csub\u003e\u003cem\u003ein\u003c/em\u003e\u003c/sub\u003e in \u003cem\u003eSynechococcus\u003c/em\u003e sp., coupled with an increased proportion of DOC\u003csub\u003e\u003cem\u003eex\u003c/em\u003e\u003c/sub\u003e, holds critical implications for aquatic carbon cycling. POC serves as a primary driver of the biological carbon pump (BCP), facilitating carbon export to deeper waters via gravitational sinking (Wang et al., \u003cspan citationid=\"CR35\" class=\"CitationRef\"\u003e2023\u003c/span\u003e). A decline in POC under elevated CO\u003csub\u003e2\u003c/sub\u003e may attenuate vertical carbon flux, reducing the efficiency of long-term carbon sequestration in sediments (Kalapurakkal et al., \u003cspan citationid=\"CR16\" class=\"CitationRef\"\u003e2025\u003c/span\u003e). In addition, the decreased POC content could disrupt benthic food webs reliant on sinking POC as a carbon source, potentially altering secondary production and trophic interactions (Molari et al., \u003cspan citationid=\"CR22\" class=\"CitationRef\"\u003e2018\u003c/span\u003e). Furthermore, the reallocation within the DOC pool, specifically the decline in DOC\u003csub\u003e\u003cem\u003ein\u003c/em\u003e\u003c/sub\u003e and dominance of DOC\u003csub\u003e\u003cem\u003eex\u003c/em\u003e\u003c/sub\u003e, further modulates the fate of dissolved carbon. DOC\u003csub\u003e\u003cem\u003ein\u003c/em\u003e\u003c/sub\u003e primarily composed of labile small-molecule metabolites such as amino acids and sugars, is rapidly assimilated by microbes due to its high bioavailability (Hansell, \u003cspan citationid=\"CR9\" class=\"CitationRef\"\u003e2013\u003c/span\u003e). In contrast, DOC\u003csub\u003e\u003cem\u003eex\u003c/em\u003e\u003c/sub\u003e often contains larger molecular-weight compounds such as extracellular polysaccharides and protein colloids, which exhibit greater recalcitrance and require enzymatic hydrolysis prior to microbial utilization (Medeiros et al., \u003cspan citationid=\"CR21\" class=\"CitationRef\"\u003e2015\u003c/span\u003e; Thornton, \u003cspan citationid=\"CR32\" class=\"CitationRef\"\u003e2014\u003c/span\u003e). The preferential release of DOC\u003csub\u003e\u003cem\u003eex\u003c/em\u003e\u003c/sub\u003e under extreme CO\u003csub\u003e2\u003c/sub\u003e suggests a potential shift toward more persistent DOC forms, potentially hindering microbial carbon turnover and reducing the production of refractory DOC (RDOC) via the microbial carbon pump (MCP). The MCP relies on microbial transformation of labile DOC into RDOC, which resists degradation and contributes to centennial-scale carbon storage (Jiao et al., \u003cspan citationid=\"CR14\" class=\"CitationRef\"\u003e2024\u003c/span\u003e). The increase in algal-derived RDOC suggests that the contribution of algal-derived carbon to the surface DOC pool in aquatic ecosystems is likely to be more direct and significant (Jiao et al., \u003cspan citationid=\"CR13\" class=\"CitationRef\"\u003e2010\u003c/span\u003e). These findings suggest that under future extreme climate scenarios, rising CO\u003csub\u003e2\u003c/sub\u003e levels will significantly alter the pathways through which phytoplankton contribute to aquatic carbon sequestration. However, the direction and magnitude of this contribution still require further quantification by analyzing the proportions of bioactive vs. recalcitrant carbon in both POC and DOC fractions (Fennel et al., \u003cspan citationid=\"CR6\" class=\"CitationRef\"\u003e2022\u003c/span\u003e).\u003c/p\u003e \u003c/div\u003e"},{"header":"5. Conclusion","content":"\u003cp\u003eThis study is the first try to investigate the effects of varying CO\u003csub\u003e2\u003c/sub\u003e concentrations under three climate change scenarios on carbon allocation in the common phytoplankton \u003cem\u003eSynechococcus\u003c/em\u003e. We found that elevated CO\u003csub\u003e2\u003c/sub\u003e suppresses POC and DOC\u003cem\u003e\u003csub\u003ein\u003c/sub\u003e\u003c/em\u003e, while stimulating the release of DOC\u003cem\u003e\u003csub\u003eex\u003c/sub\u003e\u003c/em\u003e. This shift may weaken phytoplankton\u0026rsquo;s contribution to aquatic carbon sequestration through BCP pathway by limiting the POC sinking through vertical carbon flux. Meanwhile, increased DOC\u003cem\u003e\u003csub\u003eex\u003c/sub\u003e\u003c/em\u003e release could potentially hinder the formation of recalcitrant DOC via the MCP pathway. These findings carry significant implications for accurately assessing phytoplankton\u0026rsquo;s role in aquatic carbon sequestration under future climate change.\u003c/p\u003e"},{"header":"Declarations","content":"\u003cp\u003e\u003cstrong\u003eCRediT authorship contribution statement\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eYanyan Zhang: Writing – original draft, Methodology, Data curation, Conceptualization. Lincheng Huang: Methodology, Formal analysis, Data curation. Yongxin Liu: Methodology, Formal analysis, Data curation. Tangcheng Li: \u0026nbsp; Writing – review \u0026amp; editing. Hong Du: \u0026nbsp;Writing – review \u0026amp; editing. Faming Wang: \u0026nbsp;Writing – review \u0026amp; editing, Funding acquisition. Zhe Lu: \u0026nbsp;Writing – review \u0026amp; editing, Validation, Supervision, Project administration, Funding acquisition, Conceptualization.\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eAcknowledgements\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eFinancial support has been given by National Key R\u0026amp;D Program of China (2023YFE0113102, 2023YFF1304500), the National Natural Science Foundation of China (32301398), Guangdong Basic and Applied Basic Research Foundation (2023A1515010946, 2024A1515030067), Guangdong Science and Technology Plan Project (2023B1212060046), and the MOST Ocean Negative Carbon Emissions project.\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eConflicts of interest\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eThe authors declare no competing financial interests.\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eData Availability\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eData will be made available on request.\u003c/p\u003e"},{"header":"References","content":"\u003col\u003e\n\u003cli\u003eAnderson, N.J., Heathcote, A.J., Engstrom, D.R., contributors, G.d. 2020. Anthropogenic alteration of nutrient supply increases the global freshwater carbon sink. \u003cem\u003eScience Advances\u003c/em\u003e, \u003cstrong\u003e6\u003c/strong\u003e(16), eaaw2145.\u003c/li\u003e\n\u003cli\u003eArrigo, K.R., Robinson, D.H., Worthen, D.L., Dunbar, R.B., DiTullio, G.R., VanWoert, M., Lizotte, M.P. 1999. Phytoplankton Community Structure and the Drawdown of Nutrients and CO\u003csub\u003e2\u003c/sub\u003e in the Southern Ocean. \u003cem\u003eScience\u003c/em\u003e, \u003cstrong\u003e283\u003c/strong\u003e(5400), 365\u0026ndash;367.\u003c/li\u003e\n\u003cli\u003eBressac, M., Laurenceau-Cornec, E.C., Kennedy, F., Santoro, A.E., Paul, N.L., Briggs, N., Carvalho, F., Boyd, P.W. 2024. Decoding drivers of carbon flux attenuation in the oceanic biological pump. \u003cem\u003eNature\u003c/em\u003e, \u003cstrong\u003e633\u003c/strong\u003e(8030), 587\u0026ndash;593.\u003c/li\u003e\n\u003cli\u003eBurlacot, A., Dao, O., Auroy, P., Cuin\u0026eacute;, S., Li-Beisson, Y., Peltier, G. 2022. Alternative photosynthesis pathways drive the algal CO\u003csub\u003e2\u003c/sub\u003e-concentrating mechanism. \u003cem\u003eNature\u003c/em\u003e, \u003cstrong\u003e605\u003c/strong\u003e(7909), 366\u0026ndash;371.\u003c/li\u003e\n\u003cli\u003eConan, P., S\u0026oslash;ndergaard, M., Kragh, T., Thingstad, F., Pujo-Pay, M., Williams, P.J.l.B., Markager, S., Cauwet, G., Borch, N.H., Evans, D. 2007. Partitioning of organic production in marine plankton communities: The effects of inorganic nutrient ratios and community composition on new dissolved organic matter. \u003cem\u003eLimnology and Oceanography\u003c/em\u003e, \u003cstrong\u003e52\u003c/strong\u003e(2), 753\u0026ndash;765.\u003c/li\u003e\n\u003cli\u003eFennel, K., Mattern, J.P., Doney, S.C., Bopp, L., Moore, A.M., Wang, B., Yu, L. 2022. Ocean biogeochemical modelling. \u003cem\u003eNature Reviews Methods Primers\u003c/em\u003e, \u003cstrong\u003e2\u003c/strong\u003e(1), 76.\u003c/li\u003e\n\u003cli\u003eFlombaum, P., Gallegos, J.L., Gordillo, R.A., Rinc\u0026oacute;n, J., Zabala, L.L., Jiao, N., Karl, D.M., Li, W.K., Lomas, M.W., Veneziano, D., Vera, C.S., Vrugt, J.A., Martiny, A.C. 2013. Present and future global distributions of the marine Cyanobacteria \u003cem\u003eProchlorococcus\u003c/em\u003e and \u003cem\u003eSynechococcus\u003c/em\u003e. \u003cem\u003eProc Natl Acad Sci U S A\u003c/em\u003e, \u003cstrong\u003e110\u003c/strong\u003e(24), 9824\u0026ndash;9.\u003c/li\u003e\n\u003cli\u003eGuo, Y., Yuan, Z., Xu, J., Wang, Z., Yuan, T., Zhou, W., Xu, J., Liang, C., Xu, H., Liu, S. 2017. Metabolic acclimation mechanism in microalgae developed for CO\u003csub\u003e2\u003c/sub\u003e capture from industrial flue gas. \u003cem\u003eAlgal Research\u003c/em\u003e, \u003cstrong\u003e26\u003c/strong\u003e, 225\u0026ndash;233.\u003c/li\u003e\n\u003cli\u003eHansell, D.A. 2013. Recalcitrant Dissolved Organic Carbon Fractions. \u003cem\u003eAnnual Review of Marine Science\u003c/em\u003e, \u003cstrong\u003e5\u003c/strong\u003e(Volume 5, 2013), 421\u0026ndash;445.\u003c/li\u003e\n\u003cli\u003eHenson, S.A., Cael, B.B., Allen, S.R., Dutkiewicz, S. 2021. Future phytoplankton diversity in a changing climate. \u003cem\u003eNature Communications\u003c/em\u003e, \u003cstrong\u003e12\u003c/strong\u003e(1), 5372.\u003c/li\u003e\n\u003cli\u003eHerms, D.A., Mattson, W.J. 1992. The dilemma of plants: to grow or defend. \u003cem\u003eThe quarterly review of biology\u003c/em\u003e, \u003cstrong\u003e67\u003c/strong\u003e(3), 283\u0026ndash;335.\u003c/li\u003e\n\u003cli\u003eIsanta‐Navarro, J., Prater, C., Peoples, L.M., Loladze, I., Phan, T., Jeyasingh, P.D., Church, M.J., Kuang, Y., Elser, J.J. 2022. Revisiting the growth rate hypothesis: Towards a holistic stoichiometric understanding of growth. \u003cem\u003eEcology Letters\u003c/em\u003e, \u003cstrong\u003e25\u003c/strong\u003e(10), 2324\u0026ndash;2339.\u003c/li\u003e\n\u003cli\u003eJiao, N., Herndl, G.J., Hansell, D.A., Benner, R., Kattner, G., Wilhelm, S.W., Kirchman, D.L., Weinbauer, M.G., Luo, T., Chen, F., Azam, F. 2010. Microbial production of recalcitrant dissolved organic matter: long-term carbon storage in the global ocean. \u003cem\u003eNature Reviews Microbiology\u003c/em\u003e, \u003cstrong\u003e8\u003c/strong\u003e(8), 593\u0026ndash;599.\u003c/li\u003e\n\u003cli\u003eJiao, N., Luo, T., Chen, Q., Zhao, Z., Xiao, X., Liu, J., Jian, Z., Xie, S., Thomas, H., Herndl, G.J., Benner, R., Gonsior, M., Chen, F., Cai, W.-J., Robinson, C. 2024. The microbial carbon pump and climate change. \u003cem\u003eNature Reviews Microbiology\u003c/em\u003e, \u003cstrong\u003e22\u003c/strong\u003e(7), 408\u0026ndash;419.\u003c/li\u003e\n\u003cli\u003eJin, P., Ji, Y., Huang, Q., Li, P., Pan, J., Lu, H., Liang, Z., Guo, Y., Zhong, J., Beardall, J., Xia, J. 2022. A reduction in metabolism explains the tradeoffs associated with the long-term adaptation of phytoplankton to high CO\u003csub\u003e2\u003c/sub\u003e concentrations. \u003cem\u003eNew Phytologist\u003c/em\u003e, \u003cstrong\u003e233\u003c/strong\u003e(5), 2155\u0026ndash;2167.\u003c/li\u003e\n\u003cli\u003eKalapurakkal, H.T., Dale, A.W., Schmidt, M., Taubner, H., Scholz, F., Spiegel, T., Fuhr, M., Wallmann, K. 2025. Sediment resuspension in muddy sediments enhances pyrite oxidation and carbon dioxide emissions in Kiel Bight. \u003cem\u003eCommunications Earth \u0026amp; Environment\u003c/em\u003e, \u003cstrong\u003e6\u003c/strong\u003e(1), 156.\u003c/li\u003e\n\u003cli\u003eLi, J., Tang, X., Pan, K., Zhu, B., Li, Y., Wang, Z., Zhao, Y. 2022. Energy metabolism and intracellular pH regulation reveal different physiological acclimation mechanisms of \u003cem\u003eChlorella\u003c/em\u003e strains to high concentrations of CO\u003csub\u003e2\u003c/sub\u003e. \u003cem\u003eScience of The Total Environment\u003c/em\u003e, \u003cstrong\u003e853\u003c/strong\u003e, 158627.\u003c/li\u003e\n\u003cli\u003eLow-D\u0026eacute;carie, E., Fussmann, G.F., Bell, G. 2011. The effect of elevated CO\u003csub\u003e2\u003c/sub\u003e on growth and competition in experimental phytoplankton communities. \u003cem\u003eGlobal Change Biology\u003c/em\u003e, \u003cstrong\u003e17\u003c/strong\u003e(8), 2525\u0026ndash;2535.\u003c/li\u003e\n\u003cli\u003eLu, Z., Dai, J., Zheng, L., Teng, Z., Zhang, Q., Qiu, D., Song, L. 2020. Disodium 2-oxoglutarate promotes carbon flux into astaxanthin and fatty acid biosynthesis pathways in \u003cem\u003eHaematococcus\u003c/em\u003e. \u003cem\u003eBioresource Technology\u003c/em\u003e, \u003cstrong\u003e299\u003c/strong\u003e, 122612.\u003c/li\u003e\n\u003cli\u003eLu, Z., Zheng, L., Liu, J., Dai, J., Song, L. 2019. A novel fed-batch strategy to boost cyst cells production based on the understanding of intracellular carbon and nitrogen metabolism in \u003cem\u003eHaematococcus pluvialis\u003c/em\u003e. \u003cem\u003eBioresource technology\u003c/em\u003e, \u003cstrong\u003e289\u003c/strong\u003e, 121744.\u003c/li\u003e\n\u003cli\u003eMedeiros, P.M., Seidel, M., Powers, L.C., Dittmar, T., Hansell, D.A., Miller, W.L. 2015. Dissolved organic matter composition and photochemical transformations in the northern North Pacific Ocean. \u003cem\u003eGeophysical Research Letters\u003c/em\u003e, \u003cstrong\u003e42\u003c/strong\u003e(3), 863\u0026ndash;870.\u003c/li\u003e\n\u003cli\u003eMolari, M., Guilini, K., Lott, C., Weber, M., de Beer, D., Meyer, S., Ramette, A., Wegener, G., Wenzh\u0026ouml;fer, F., Martin, D., Cibic, T., De Vittor, C., Vanreusel, A., Boetius, A. 2018. CO(2) leakage alters biogeochemical and ecological functions of submarine sands. \u003cem\u003eSci Adv\u003c/em\u003e, \u003cstrong\u003e4\u003c/strong\u003e(2), eaao2040.\u003c/li\u003e\n\u003cli\u003eNovotny, A., Serandour, B., Kortsch, S., Gauzens, B., Jan, K.M.G., Winder, M. 2023. DNA metabarcoding highlights cyanobacteria as the main source of primary production in a pelagic food web model. \u003cem\u003eScience Advances\u003c/em\u003e, \u003cstrong\u003e9\u003c/strong\u003e(17), eadg1096.\u003c/li\u003e\n\u003cli\u003eOschlies, A., Brandt, P., Stramma, L., Schmidtko, S. 2018. Drivers and mechanisms of ocean deoxygenation. \u003cem\u003eNature Geoscience\u003c/em\u003e, \u003cstrong\u003e11\u003c/strong\u003e(7), 467\u0026ndash;473.\u003c/li\u003e\n\u003cli\u003ePandey, S., Narayanan, I., Vinayagam, R., Selvaraj, R., Varadavenkatesan, T., Pugazhendhi, A. 2023. A review on the effect of blue green 11 medium and its constituents on microalgal growth and lipid production. \u003cem\u003eJournal of Environmental Chemical Engineering\u003c/em\u003e, \u003cstrong\u003e11\u003c/strong\u003e(3), 109984.\u003c/li\u003e\n\u003cli\u003eQi, Y., Xie, Q., Wang, J.-J., He, D., Bao, H., Fu, Q.-L., Su, S., Sheng, M., Li, S.-L., Volmer, D.A., Wu, F., Jiang, G., Liu, C.-Q., Fu, P. 2022. Deciphering dissolved organic matter by Fourier transform ion cyclotron resonance mass spectrometry (FT-ICR MS): from bulk to fractions and individuals. \u003cem\u003eCarbon Research\u003c/em\u003e, \u003cstrong\u003e1\u003c/strong\u003e(1), 3.\u003c/li\u003e\n\u003cli\u003eQian, J., Mopper, K.J.A.C. 1996. Automated high-performance, high-temperature combustion total organic carbon analyzer. \u003cstrong\u003e68\u003c/strong\u003e(18), 3090\u0026ndash;3097.\u003c/li\u003e\n\u003cli\u003eRavindran, S., Hajinajaf, N., Kundu, P., Comes, J., Nielsen, D.R., Varman, A.M., Ghosh, A. 2024. Genome-Scale Metabolic Model Reconstruction and Investigation into the Fluxome of the Fast-Growing Cyanobacterium \u003cem\u003eSynechococcus\u003c/em\u003e sp. PCC 11901. \u003cem\u003eACS Synthetic Biology\u003c/em\u003e, \u003cstrong\u003e13\u003c/strong\u003e(10), 3281\u0026ndash;3294.\u003c/li\u003e\n\u003cli\u003eRiahi, K., Gr\u0026uuml;bler, A., Nakicenovic, N. 2007. Scenarios of long-term socio-economic and environmental development under climate stabilization. \u003cem\u003eTechnological forecasting and social change\u003c/em\u003e, \u003cstrong\u003e74\u003c/strong\u003e(7), 887\u0026ndash;935.\u003c/li\u003e\n\u003cli\u003eSong, C., Dodds, W.K., R\u0026uuml;egg, J., Argerich, A., Baker, C.L., Bowden, W.B., Douglas, M.M., Farrell, K.J., Flinn, M.B., Garcia, E.A. 2018. Continental-scale decrease in net primary productivity in streams due to climate warming. \u003cem\u003eNature Geoscience\u003c/em\u003e, \u003cstrong\u003e11\u003c/strong\u003e(6), 415\u0026ndash;420.\u003c/li\u003e\n\u003cli\u003eSun, Z., Chen, Y.-F., Du, J. 2016. Elevated CO\u003csub\u003e2\u003c/sub\u003e improves lipid accumulation by increasing carbon metabolism in \u003cem\u003eChlorella sorokiniana\u003c/em\u003e. \u003cem\u003ePlant Biotechnology Journal\u003c/em\u003e, \u003cstrong\u003e14\u003c/strong\u003e(2), 557\u0026ndash;566.\u003c/li\u003e\n\u003cli\u003eThornton, D.C.O. 2014. Dissolved organic matter (DOM) release by phytoplankton in the contemporary and future ocean. \u003cem\u003eEuropean Journal of Phycology\u003c/em\u003e, \u003cstrong\u003e49\u003c/strong\u003e(1), 20\u0026ndash;46.\u003c/li\u003e\n\u003cli\u003eTortell, P.D. 2000. Evolutionary and ecological perspectives on carbon acquisition in phytoplankton. \u003cem\u003eLimnology and Oceanography\u003c/em\u003e, \u003cstrong\u003e45\u003c/strong\u003e(3), 744\u0026ndash;750.\u003c/li\u003e\n\u003cli\u003evan Vuuren, D.P., Edmonds, J., Kainuma, M., Riahi, K., Thomson, A., Hibbard, K., Hurtt, G.C., Kram, T., Krey, V., Lamarque, J.-F., Masui, T., Meinshausen, M., Nakicenovic, N., Smith, S.J., Rose, S.K. 2011. The representative concentration pathways: an overview. \u003cem\u003eClimatic Change\u003c/em\u003e, \u003cstrong\u003e109\u003c/strong\u003e(1), 5.\u003c/li\u003e\n\u003cli\u003eWang, W.-L., Fu, W., Le Moigne, F.A.C., Letscher, R.T., Liu, Y., Tang, J.-M., Primeau, F.W. 2023. Biological carbon pump estimate based on multidecadal hydrographic data. \u003cem\u003eNature\u003c/em\u003e, \u003cstrong\u003e624\u003c/strong\u003e(7992), 579\u0026ndash;585.\u003c/li\u003e\n\u003cli\u003eWen, Z., Shang, Y., Song, K., Liu, G., Hou, J., Lyu, L., Tao, H., Li, S., He, C., Shi, Q., He, D. 2022. Composition of dissolved organic matter (DOM) in lakes responds to the trophic state and phytoplankton community succession. \u003cem\u003eWater Research\u003c/em\u003e, \u003cstrong\u003e224\u003c/strong\u003e, 119073.\u003c/li\u003e\n\u003cli\u003eWilliamson, C.E., Saros, J.E., Vincent, W.F., Smol, J.P. 2009. Lakes and reservoirs as sentinels, integrators, and regulators of climate change. \u003cem\u003eLimnology and oceanography\u003c/em\u003e, \u003cstrong\u003e54\u003c/strong\u003e(6part2), 2273\u0026ndash;2282.\u003c/li\u003e\n\u003cli\u003eXu, X., Martin, G.J.O., Kentish, S.E. 2019. Enhanced CO\u003csub\u003e2\u003c/sub\u003e bio-utilization with a liquid\u0026ndash;liquid membrane contactor in a bench-scale microalgae raceway pond. \u003cem\u003eJournal of CO\u003csub\u003e2\u003c/sub\u003e Utilization\u003c/em\u003e, \u003cstrong\u003e34\u003c/strong\u003e, 207\u0026ndash;214.\u003c/li\u003e\n\u003cli\u003eYasuaki Hijioka, Y.M., Nishimoto, H. 2008. Global GHG emission scenarios under GIC; concentration stabilization targets. \u003cem\u003eJ. Glob. Environ. Eng\u003c/em\u003e, \u003cstrong\u003e13\u003c/strong\u003e, 97\u0026ndash;108.\u003c/li\u003e\n\u003c/ol\u003e"}],"fulltextSource":"","fullText":"","funders":[],"hasAdminPriorityOnWorkflow":false,"hasManuscriptDocX":true,"hasOptedInToPreprint":true,"hasPassedJournalQc":"","hasAnyPriority":false,"hideJournal":false,"highlight":"","institution":"","isAcceptedByJournal":true,"isAuthorSuppliedPdf":false,"isDeskRejected":"","isHiddenFromSearch":false,"isInQc":false,"isInWorkflow":false,"isPdf":false,"isPdfUpToDate":true,"isWithdrawnOrRetracted":false,"journal":{"display":true,"email":"","identity":"journal-of-applied-phycology","isNatureJournal":false,"hasQc":true,"allowDirectSubmit":false,"externalIdentity":"","sideBox":"","snPcode":"10811","submissionUrl":"https://submission.nature.com/new-submission/10811/3","title":"Journal of Applied Phycology","twitterHandle":"","acdcEnabled":true,"dfaEnabled":true,"editorialSystem":"","reportingPortfolio":"Springer Hybrid","inReviewEnabled":true,"inReviewRevisionsEnabled":false},"keywords":"Synechococcus, carbon allocation, elevated CO2, DOC, carbon sequestration","lastPublishedDoi":"10.21203/rs.3.rs-6676455/v1","lastPublishedDoiUrl":"https://doi.org/10.21203/rs.3.rs-6676455/v1","license":{"name":"CC BY 4.0","url":"https://creativecommons.org/licenses/by/4.0/"},"manuscriptAbstract":"\u003cp\u003ePhytoplankton play a key role in aquatic carbon cycling. The partitioning of algal-derived carbon between particulate organic carbon (POC) and dissolved organic carbon (DOC), and its further fractionation within the DOC pool, determines the fate of fixed carbon. However, the regulatory mechanisms of phytoplankton carbon allocation under climate change remain insufficiently explored. Here, we investigated the carbon-partitioning response of a mode algae, \u003cem\u003eSynechococcus\u003c/em\u003e to three carbon dioxide (CO\u003csub\u003e2\u003c/sub\u003e) conditions in different future climate contexts. It was found that when CO\u003csub\u003e2\u003c/sub\u003e concentration increased to 850 ppm, the carbon allocation patterns did not have significantly changed compared to that under current CO\u003csub\u003e2\u003c/sub\u003e concentration. In contrast, till the end of incubation, the extreme CO\u003csub\u003e2\u003c/sub\u003e concentration of 1370 ppm led to significant decrease of 47.05% in the total organic carbon (TOC) concentration, with an increase of the concentration of extracellular DOC (DOC\u003csub\u003e\u003cem\u003eex\u003c/em\u003e\u003c/sub\u003e) and a reduction of POC. Notably, the final proportion of DOC\u003csub\u003e\u003cem\u003eex\u003c/em\u003e\u003c/sub\u003e increased to 44.32% from 22.66% of the DOC fraction. Our observed changes in carbon allocation of \u003cem\u003eSynechococcus\u003c/em\u003e under extreme CO\u003csub\u003e2\u003c/sub\u003e concentrations suggests a reduced contribution of phytoplankton to aquatic carbon sequestration via the biological carbon pump through POC sinking, with a larger proportion of microalgal carbon being directly allocated to the surface DOC pool in the form of potentially recalcitrant DOC. Our study has important implications for accurately evaluating the role of phytoplankton in aquatic carbon sequestration in the context of future climate change.\u003c/p\u003e","manuscriptTitle":"Influence of simulated future climate CO2 scenarios on carbon allocation in keystone Cyanobacterium Synechococcus","msid":"","msnumber":"","nonDraftVersions":[{"code":1,"date":"2025-05-23 17:24:03","doi":"10.21203/rs.3.rs-6676455/v1","editorialEvents":[{"type":"communityComments","content":0},{"type":"decision","content":"Revision requested","date":"2025-06-16T14:38:02+00:00","index":"","fulltext":""},{"type":"editorInvitedReview","content":"","date":"2025-06-12T17:26:05+00:00","index":"hide","fulltext":""},{"type":"reviewerAgreed","content":"314526801901605291698878999820324050784","date":"2025-05-21T16:47:05+00:00","index":"hide","fulltext":""},{"type":"reviewersInvited","content":"","date":"2025-05-21T15:14:20+00:00","index":"","fulltext":""},{"type":"editorAssigned","content":"","date":"2025-05-20T09:03:02+00:00","index":"","fulltext":""},{"type":"checksComplete","content":"","date":"2025-05-19T08:58:39+00:00","index":"","fulltext":""},{"type":"submitted","content":"Journal of Applied Phycology","date":"2025-05-16T02:27:17+00:00","index":"","fulltext":""}],"status":"published","journal":{"display":true,"email":"","identity":"journal-of-applied-phycology","isNatureJournal":false,"hasQc":true,"allowDirectSubmit":false,"externalIdentity":"","sideBox":"","snPcode":"10811","submissionUrl":"https://submission.nature.com/new-submission/10811/3","title":"Journal of Applied Phycology","twitterHandle":"","acdcEnabled":true,"dfaEnabled":true,"editorialSystem":"","reportingPortfolio":"Springer Hybrid","inReviewEnabled":true,"inReviewRevisionsEnabled":false}}],"origin":"","ownerIdentity":"70a34f33-7c39-4c01-bede-6d8839c5b7e0","owner":[],"postedDate":"May 23rd, 2025","published":true,"recentEditorialEvents":[],"rejectedJournal":[],"revision":"","amendment":"","status":"under-review","subjectAreas":[],"tags":[],"updatedAt":"2025-08-02T01:38:16+00:00","versionOfRecord":[],"versionCreatedAt":"2025-05-23 17:24:03","video":"","vorDoi":"","vorDoiUrl":"","workflowStages":[]},"version":"v1","identity":"rs-6676455","journalConfig":"researchsquare"},"__N_SSP":true},"page":"/article/[identity]/[[...version]]","query":{"redirect":"/article/rs-6676455","identity":"rs-6676455","version":["v1"]},"buildId":"8U1c8b4HqxoKbykW_rLl7","isFallback":false,"isExperimentalCompile":false,"dynamicIds":[84888],"gssp":true,"scriptLoader":[]}