Moderate levels of dissolved iron stimulate cellular growth and increase lipid storage in Symbiodinium sp.

doi:10.21203/rs.3.rs-5160718/v1

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Moderate levels of dissolved iron stimulate cellular growth and increase lipid storage in Symbiodinium sp.

https://doi.org/10.21203/rs.3.rs-5160718/v1

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Dinoflagellates in the family Symbiodiniaceae are fundamental in coral reef ecosystems and facilitate essential processes such as photosynthesis, nutrient cycling, and calcium carbonate production. Iron (Fe) is an essential element for the physiological processes of Symbiodiniaceae, yet its role remains poorly understood in the context of cellular development and metabolic health. Here, we investigated the effect of iron availability (0 to 100 nM Fe(III)) on Symbiodiniumsp. ITS2 type A1 cultures and quantified cellular content using flow cytometry and holotomography. Moderate levels of dissolved Fe (50 nM) enhanced growth rates and cellular content development in Symbiodinium sp., including lipids and proteins. We observed distinct growth patterns, pigment concentrations, and cellular morphology under increasing Fe concentrations, indicating the influence of iron availability on cellular physiology. Non-destructive, label-free holotomographic microscopy enabled single cell in vivo revealing higher intracellular lipid accumulation (+57%) in response to 50 nM Fe(III) enrichment. Our findings contribute to a deeper understanding of the relationship between iron availability and Symbiodiniumsp. growth and cellular development, with potential implications for coral health and reef resilience in the face of environmental stressors.

*Walter Dellisanti and Swathi Murthy contributed equally to this manuscript.

Marine and Freshwater Biology

symbiodinium

cell development

in vivo

iron enrichment

Symbiotic dinoflagellates belonging to the family Symbiodiniaceae (LaJaunesse et al., 2018) are of crucial significance to coral reef ecosystems. They have a fundamental role in facilitating key processes to corals through photosynthesis, supporting the macro- and micronutrient cycle, and the production of calcium carbonate as the foundation of the reefs (Frommlet et al., 2015; Coffroth and Santos, 2005). However, the current global environmental changes, including ocean warming, nutrient pollution, and deoxygenation, affect the cellular dynamics of the coral-dinoflagellate symbiosis by altering, among other processes, nutrient exchange (Morris et al., 2019; Johnson et al., 2021; Rädecker et al., 2021). Disruption of nutrient exchange can lead to the breakdown of symbiosis, i.e., bleaching, ultimately compromising coral survival (Pernice 2014).

Among the essential nutrients, iron (Fe) plays a fundamental role in the physiology of Symbiodiniaceae and other microalgae (Reich et al., 2020). Iron is typically present in seawater in nanomolar concentrations, and it is considered a trace metal (Entsch et al., 1983) essential for metabolic processes such as photosynthesis, phagocytosis, and prey digestion in mixotrophic dinoflagellates (Rodriguez et al., 2016; Reich et al., 2020). While iron concentration refers to the total amount of iron present, its bioavailability refers to the fraction of iron that is accessible and usable by the organism. The balance between iron concentration and its bioavailability directly influences the homeostasis of photosynthetic organisms, as insufficient iron availability can limit growth, while excess iron can induce toxicity (Romero et al., 2022; Reich et al., 2020). Iron is an enzyme cofactor in electron transfer and catalysis (Balk & Schaedler, 2014; Müller, 2023), and its limitation can lead to reduced chlorophyll synthesis resulting in decreased pigment content and reduced photosynthetic efficiency in Symbiodiniaceae (Iglic, 2011), phytoplankton (Koch & Trimborn, 2019), and freshwater green microalgae (Yadavalli et al., 2012). Iron limitation can also induce the expression of iron transporters and siderophore production to enhance iron acquisition from the environment (Sandy & Butler, 2009). Recent observations suggest that the photochemical performance of Symbiodiniaceae is enhanced in association with Marinobacter sp. and L. alexandrii bacteria, which may support nutrient exchange and siderophore production to bind Fe into bioavailable forms (Amin et al., 2009; Matthews et al., 2023a, b). On the other hand, excess iron can lead to stressful conditions in Symbiodinium spp. potentially leading to the production of reactive oxygen species (ROS) through Fenton chemistry, and causing oxidative stress (Wietheger et al., 2018; Deleja et al., 2022). This in turn can disrupt cellular homeostasis, damage cellular components, such as proteins and lipids, and inhibit the photosynthetic electron transport chain (Rai et al., 2021; Reich et al., 2023). Despite its importance, only a few Symbiodiniaceae species have been extensively studied regarding their iron requirements (Rodriguez et al., 2016; Reich et al., 2020, 2021).

Iron availability can also affect the lipid content and lipid profile of microalgae (Liu et al., 2008; Wang et al., 2023). Lipids are fundamental components of cells and serve in the cellular metabolism of microalgae, including Symbiodiniaceae (Garrett et al., 2013; Kneeland et al., 2013; Pasaribu et al., 2024). They contribute to energy reserves and form integral components of cellular membranes (Patton & Burris, 1983; Tchernov et al., 2004). These functions have implications for nutrient stress responses, energy storage, and proliferation rates of Symbiodiniaceae in nitrogen-limited host tissue directly affecting lipid accumulation (Wang et al., 2015). Quantification of lipids and other cellular contents (e.g. protein) in relation to inorganic iron concentration is therefore relevant to understand the potential role of this micronutrient in optimizing Symbiodiniaceae cellular conditions, and its role in influencing the health and resilience of Symbiodiniaceae populations, both free-living and in hospite.

Recently, optical diffraction tomography (also known as holotomography) techniques have emerged, providing quantitative morphological and biochemical information about individual cells and tissues without the need for exogenous labeling agents (Kim et al., 2024). The use of interferometry allows the measurement of complex optical fields of diffracted light from biological samples enabling the mapping of refractive index (RI) (Popescu, 2011; Lee et al., 2013). RI is an optical property that varies with the composition and density of cellular components, enabling the identification and quantification of intracellular structures. Holotomography measurements of phase-distortions of light from various incident angles enable the construction of 3D refractive index distributions in cells and tissues at sub-micron resolution (Choi et al., 2007; Habaza et al., 2017), which can then be segmented to identify particular cellular structures with characteristic RI. For example, lipids typically have a higher RI than other cellular components, and this allows their detection and quantification within live cells (Jung et al., 2018). Holotomography thus provides a rapid, quantitative method for intracellular lipid detection in live cells (Kim et al., 2016; Park et al., 2020). It has been used as an effective imaging technique for studying biological samples including microalgae (Jung et al., 2018), phytoplankton (Lee et al., 2014), bacteria (Kim et al., 2014a; Bennet et al., 2017), yeast (Rappaz et al., 2009; Habaza et al., 2015), and red blood cells (Kim et al., 2014b, c). However, potential applications of this technique as a non-invasive, label-free, in vivo approach to quantify cellular content in Symbiodiniaceae have not yet been explored.

In this study, we investigate the effect of iron enrichment on Symbiodinium sp. cultures and quantify their cellular content using a range of label-free, in vivo techniques such as flow cytometry and holotomography. The objectives of this study are to i) evaluate the impact of varying concentrations of dissolved Fe(III) on the growth rate and cellular content development of Symbiodinium sp., ii) visualize and quantify cellular structures, including proteins and lipids, under different iron enrichment conditions through holotomography techniques, and iii) to investigate the role of inorganic iron in optimizing cellular growth conditions. We hypothesized that controlled iron enrichment could enhance Symbiodinium sp. growth and cellular content.

2.1 Symbiodinium cultures

Symbiodinium sp. cultures (K-1618) were acquired from the Norwegian Culture Collection of Algae (NORCCA, Norway) and maintained in TL-30 medium in 250 mL polycarbonate flask, at 20°C with a photoperiod of 12:12 at 100 µmol photons m^− 2 s^− 1 (400–700 nm), as measured with a Universal Light Meter (ULM-500) equipped with a spherical micro quantum sensor (US-SQS/L, Heinz Walz, Effeltrich, Germany). Subsequently, subcultures were acclimated to standard f/2 medium for one month and maintained under the same conditions prior to the start of experiments. All experimental analyses, except for the flow cytometry assay, were performed during the mid-exponential phase, as determined via cell counts identifying optimal growth and cellular activity (Lee et al., 2015).

At the start of the experimental period, aliquots of Symbiodinium sp. cultures were transferred into each culture flask (20 mL, n = 3 replicates per condition) to reach an initial density of ~ 10,000 cells mL^− 1, and maintained under the same conditions as above until they reached the stationary phase (Fig. 1). Symbiodinium sp. cultures were exposed to increasing iron Fe(III) concentrations (0, 10, 50, and 100 nM total dissolved Fe) at a controlled temperature of 20°C. A dissolved Fe(III) solution (FeCl₃*6H₂O, Sigma-Aldrich) was used to enrich the standard f/2 medium to different iron concentrations (Rodriguez et al., 2016; Reich et al., 2021). Experimental conditions were prepared as follows: modified f/2 medium with depleted dissolved iron, 0 nM Fe(III); standard f/2 medium, 10 nM Fe(III); f/2 media with a concentrated solution of dissolved iron to reach the initial concentrations of 50 nM Fe(III) and 100 nM Fe(III), respectively.

2.2 Culture identification

To verify the taxonomic assignment of the Symbiodinium sp. strain, we performed Sanger sequencing of the ITS2 region of rDNA. Aliquots of the cultures (500,000 cells mL^− 1) were collected and pelleted by centrifugation during the mid-exponential growth phase and stored at -80°C. DNA was extracted using the DNAEasy PowerBiofilm kit (Qiagen) following manufacturer protocol with slight modifications (all centrifugation steps performed at 8,000G for 90s). The ITS2 region was amplified using primers SYM_VAR_5.8S2 and SYM_VAR_REV (Hume et al. 2018) in the following reaction: 0.5 µL of each 10 µM primer, 1 µL of 2 mg mL^− 1 BSA, 12.5 µL KAPA HiFi HotStart Ready Mix (Roche), 1 µL template DNA (2.65 ng µL^− 1) and water to a total reaction volume of 25 µL. The amplification cycle was: 98 °C for 2 min, followed by 35 cycles of 98 °C for 20 s, 61 °C for 30 s, 72 °C for 30 s, followed by 72 °C for 5 min. Successful amplification, amplicon size, and contamination were visually assessed via agarose gel electrophoresis. PCR products were cleaned on AMPure XP beads (Beckman Coulter) and submitted for Sanger sequencing to a commercial provider (Eurofins). Taxonomy was assigned via blastn to the NCBI nt database, as well as local blastn to the SymPortal RefSeq database (github.com/reefgenomics/SymPortal_framework downloaded on 25/03/2024, Hume et al., 2019).

2.3 Growth measurements

Symbiodinium cell growth was assessed every third day with a CytoFLEX cytometer (Beckman Coulter, USA), which was equipped with a 50-mW laser (excitation = 488 nm, fluorescence channel 690/50 BP). Flow cytometry was performed throughout the light phase of the light: dark cycle until cultures reached the stationary phase. The instrument gain settings were as follows: forward scatter (FSC) = 200, side scatter (SSC) = 83, phycoerythrin-Cy5.5 (PC5.5) = 350 (Galotti et al., 2020). Before each analysis, quality control procedures were implemented, as recommended by the CytoFLEX software. All measurements, including culture media blanks, were conducted using an analyzed 1 mL sample at a slow rate (10 µL min^− 1) with a threshold of 300 seconds or 10,000 events. The gating process relied on FSC and SSC patterns, with only cells displaying a positive signal for photosynthetic pigments (PC5.5) being chosen for downstream analysis, aiming to minimize potential contamination from non-algal particles (Fig. S1). Cell counts, size, and shape were determined in vivo by FSC and SSC on unstained cells using the CytExpert software v2.5.

2.4 Pigment analysis

Quantitative determination of chlorophyll and pigment content was carried out using High-Performance Liquid Chromography (HPLC, 1260 Infinity, Agilent Technologies). Aliquots of 1 mL for each culture were collected during the mid-exponential growth phase and transferred to 1.5 mL tubes, centrifuged at 5000g, and the pellet was kept at − 80°C until analysis. The pigments were extracted by adding 0.4 mL acetone:methanol (7:2 vol:vol) to each tube, which was briefly vortexed, and then kept on ice for a 2 min extraction time in darkness. Subsequently, samples were sonicated in an ice-cooled high-power ultrasonicated bath (Misonix 4000; Qsonica LLC., Newtown, CT) in darkness at 80% power for 60 s consisting of 10 pulses of 2 s ON and 4 s OFF (with an amplitude setting of 100%) and then centrifuged at 12,000 g for 1 min in a mini centrifuge (MiniSpin, Eppendorf AG, Hamburg, Germany). The supernatant was filtered through a 0.2 µm pore size syringe filter (Sartorius Minisart SRP 4 filter; Sartorius AG, Goettingen, Germany). 100 µL of the extract was then immediately injected into the HPLC. Pigment extracts were separated and analyzed in the HPLC by a diode array detector (HPLC-DAD and Agilent 1260 Infinity; Agilent Technologies, Santa Clara, CA) fitted with an Ascentis C18 column (25 cm × 4.6 mm, Sigma-Aldrich cat. no. 581325 U), detecting specific absorption wavelengths of compounds. The extracts were run at a constant column temperature of 30°C for 69 min., and a flow rate of 1.0 mL min^− 1 in a changing gradient of solvent A (methanol:acetonitrile:water, 42:33:25, vol/vol/vol), and solvent B (methanol:acetonitrile:ethylacetate, 50:20:30, vol/vol/vol), where the mobile phase changed linearly from 30% solvent B at the time of injection to 100% at 52 min, staying at 100% for 15 min before returning to 30% within 2 min. Elution profiles from the absorbance detector signal at 664 nm (chlorophyll a), 460 nm (carotenoids), and 387 nm (scytonemin) (Lichtenthaler, 1987), were used to calculate pigment ratios from the derived integrated peak areas for each of the identified pigments of interest, using the manufacturer’s software (OpenLAB CDS ChemStation Edition; Agilent Technologies).

2.5 Optical diffraction tomography

Quantitative 3D imaging of individual Symbiodinium cells was carried out with an optical diffraction tomography (ODT) system (Tomocube HT-2H; Tomocube Inc., South Korea). The system also has an inbuilt ability to perform fluorescence microscopy in parallel with RI mapping. The system is based on Mach-Zehnder interferometry, employing a diode-pumped green solid-state laser (532 nm) as a light source. A spatially modulated hologram of the cell was recorded from the diffracted light by a quantitative phase imaging technique (Popescu, 2011). The 3D refractive index (RI) distribution of individual cells was then reconstructed from multiple 2D images measured at various illumination angles (controlled by a digital micromirror device), using the Fourier diffraction theorem (Choi et al., 2007). The theoretical spatial resolution of the system was 119 nm and 336 nm for lateral and axial directions, respectively (Kim et al., 2016). From the measured 3D RI tomograms, different RI regions were visualized with a unique color and rendered as a 3D image. Maximum intensity projection images of the RI tomograms were also generated to visualize the 3D data set on a 2D plane. Data visualization and rendering were carried out using Tomostudio software (Tomocube Inc., South Korea).

2.6 Wide-field fluorescence imaging.

To determine the presence of chlorophyll in the Symbiodinium cells grown at different Fe concentrations, we used the in-built wide-field fluorescence imaging capability of the HT-2H using the green channel with excitation and emission wavelengths centered around 475 nm and 520 nm, respectively. For every cell imaged, fluorescence images were captured immediately after the ODT images. At least 30 cells were imaged for each Fe concentration. The fluorescence image was overlaid on the rendered RI tomograms. While the system is not equipped with a standard Chl a filter set, these settings still enabled clear detection of a Chl a fluorescence signal due to strong coupling in Symbiodiniaceae with Chl c and peridinin (Zigmantas et al., 2002). To confirm the identification of the high RI regions (RI > 1.46) in the 3D tomograms as neutral lipids (see below), aliquots of Symbiodinium cell cultures were stained with a Nile Red solution (10 µg mL^− 1) mixed in 30% ethanol solution according to Storms et al. (2014). About 20 µL of the cell sample solution was sandwiched between a pair of coverslips. Cells were then imaged on the Tomocube HT-2 using the in-built wide-field fluorescence system using the red channel, with an excitation wavelength centered around 575 nm, and an emission band of 600–800 nm.

2.7 Symbiodinium sp. cellular lipid and protein determination

For single-cell imaging, Symbiodinium cell cultures were diluted with culture medium so that the cell density was low enough to avoid having multiple cells within the imaging field. The regions from the RI tomogram with n > 1.46, were identified as lipid droplets, as verified by Nile red staining and from the reported average RI for vegetable oils (Ullmann, 1985; Firestone, 1999). Then, cell volume and lipid dry mass were calculated for cells grown under different Fe concentrations. The cell volume was calculated from the cell boundary, as determined in the Tomocube software using Otsu thresholding. For further analysis, only mature cells (indicated by a sphericity value > 0.8) were chosen, while dividing cells were disregarded. The lipid and the non-lipid (mostly protein) regions were segmented out based on the RI, i.e., assigning RI < 1.46 as protein and RI > 1.46 as lipid. Here, we assume proteins to be the major non-lipid component inside the cell (Zhou et al., 2022). The dry mass of these two cell components was then calculated, as per Eq. 1, using the parameter RI increment (RII), defined as an increment of RI of the solution per unit increment of the solute concentration (Barer & Joseph, 1954).

$$n(x,y,z)=nm+\sum\limits_{i}^{{}} {\alpha iCi(x,y,z)}$$

Where n_m is the RI of the medium, and $\alpha i$ and $Ci$ are the RII and concentration of protein or lipid, respectively. The typical RII for proteins is 0.19 mL/g (Barer & Joseph, 1954), and that for lipids is 0.135 mL g^− 1 (Mashaghi et al., 2008). Integrating the concentration over the volume of the component yields its mass.

All data were log-transformed and checked for normality using the Shapiro-Wilk test and for homogeneity of variance using Levene’s test. When data did not meet the assumptions of normality, a Kruskal-Wallis test was used to compare differences in cell counts, size, chlorophyll fluorescence, and morphology. Permutational analysis of variance (PERMANOVA) with 999 permutations was used to compare differences in cell size (FSC) and complexity (SSC) between conditions. A principal component analysis (PCA) was used to compare all cellular morphology data from tomography analysis between conditions. The lipid: protein ratio was calculated by subtracting the log-transformed protein concentration from the log-transformed lipid concentration. To indicate the variability of data around the mean, the coefficient of variation (CV%) was used. All statistical analyses were run in R v4.2.3 (R Core Team, 2016) using the dplyr package v1.1.2 (Wickman et al., 2023) and visualized with the ggplot2 package v3.4.4 (Wickman, 2016).

3.1 ITS2 identification

Sanger sequencing of the ITS2 rDNA region returned two sequence variants separated by a single SNP (Table S1), as detected via manual inspection of the chromatogram. Subsequent blastn taxonomic assignment confirmed the identification of the cultures as Symbiodinium sp.. The most closely related sequence (98.64% identity, query cover 100%, e-value 7x10^− 104) available from the NCBI nt database had been previously detected from a symbiont of the coral Montastraea faveolata collected in the Florida Keys, USA (accession: HQ317739; Granados-Cifuentes & Rodriguez-Lanetty, 2011), from a free-living strain collected from Hawaii, USA (accession: AF184948), and from a free-living strain of unspecified origin (accession: EU449053). The same sequence was labeled as Symbiodinium A1dh in the SymPortal RefSeq database (Hume et al., 2019).

3.2 Cellular growth rate and pigment concentration

The effect of Fe(III) on cell abundance and morphology varied with different Fe concentrations in the culture media. Symbiodinium sp. cultures exhibited distinct growth curves when exposed to different iron concentrations (χ² = 36.757, p < 0.01, Fig. 2a, Table S2). Under depleted iron conditions (0 nM), no changes in cell abundance were observed, and fluorescence (PC5.5) was not detected after day 18, indicating the absence of viable cells. Under low (10 nM), moderate (50 nM), and replete (100 nM) Fe(III) concentrations, cultures reached their maximum growth on day 26 (Fig. 2a). The highest abundances were observed in cells growing under 50 nM Fe(III), with a cell density of 1.1 ± 0.04 x 10⁶ cells mL^− 1. Cells growing under 100 nM iron exhibited the second highest density of 0.81 ± 0.08 x 10⁶ cells mL^− 1, followed by those growing under 10 nM iron with a concentration of 0.6 ± 0.09 x 10⁶ cells mL^− 1. Iron concentration also influenced cell size (ANOVA, F = 26.24, p < 0.01), although no differences were observed between 50 and 100 nM (Fig. 2b). Cells growing at 10 nM Fe were on average 4.6% and 9.3% larger than those in the 100 and 50 nM treatment, respectively. The depleted Fe condition did not support cellular growth as the overall cell size at 0 nM Fe was 12.5% smaller than 10 nM Fe. In the chlorophyll fluorescence signal (Fig. 2c), no significant differences were observed among the various Fe concentrations tested. However, in terms of cell size (FSC) and complexity (SSC), significant differences were detected under increasing Fe concentrations (PERMANOVA, F = 47.773, p < 0.01, Fig. 2d, Table S3) indicating small and granular cells at 0 nM Fe, large and relatively smooth cells at 10 nM Fe, medium-size and smooth cells at 50 and 100 nM Fe, respectively.

Fe(III) concentration affected the concentration of Chl a, carotenoids, and scytonemin in Symbiodinium sp. cultures (Table 1, S4). Pigment concentrations of cells grown under depleted Fe concentration (0 nM Fe) were undetectable. Chlorophyll a concentration increased from 11.09 ± 0.48 µg mL^− 1 in cells at 10 nM Fe to 24.87 ± 2.5 µg mL^− 1 at 100 nM Fe (ANOVA, F = 113.3, p < 0.01). Similarly, the concentration of carotenoids increased from 0.24 ± 0.01 to 0.54 ± 0.05 µg mL^− 1 in cells grown in 10 nM Fe and 100 nM Fe, respectively (ANOVA, F = 121.2, p < 0.01). The concentration of scytonemin ranged from 5.39 ± 0.23 µg mL^− 1 in cells at 10 nM Fe, to 12.08 ± 1.23 µg mL^− 1 at 100 nM Fe (ANOVA, F = 114.3, p < 0.01).

Table 1

Photosynthetic pigments analyzed by HPLC: Chlorophyll a; carotenoids; scytonemin per each condition. All data are expressed as pigment mass per mL of culture sample. Mean ± standard deviation is shown.
Condition	Fe conc. nM	Chlorophyll a µg mL^− 1	Carotenoids µg mL^− 1	Scytonemin µg mL^− 1
0 Fe	0	0	0	0
10 Fe	10	11.09 (0.48)	0.24 (0.01)	5.39 (0.23)
50 Fe	50	19.69 (2.46)	0.42 (0.05)	9.56 (1.19)
100 Fe	100	24.87 (2.50)	0.54 (0.05)	12.08 (1.21)

The availability of Fe(III) also had a significant impact on cellular volume and content, including proteins and lipids, and on refractive index (RI) (ANOVA, F = 16.34, p < 0.01, Fig. S2).

3.3 Mapping RI distributions within Symbiodinium cells.

Optical diffraction tomography (ODT) was employed to map the 3D refractive index (RI) distribution of Symbiodinium cells. The reconstructed 3D RI distribution (Fig. 3a-d) and maximum intensity projection images (Fig. 3i-l) of cells grown under different Fe (III) concentrations in the culture medium indicated the presence of high RI (>1.46) regions in many of the cells. Based on previous studies (Kim et al., 2016) these regions were suspected to be lipid droplets.

To confirm the identification of the high RI (> 1.46) regions as lipids, the cells were stained with Nile red dye and imaged using the in-built wide-field fluorescence imaging (see methods section). The Nile red fluorescence images (red channel) were compared with the 3D RI tomograms of the same cell (Fig. 4). The images confirmed that regions with RI > 1.46 corresponded to lipid droplets. This is also in accordance with values found in the literature for vegetable oils (Ullmann, 1985) and for lipid droplets in microalgal cells (Jung et al., 2018). The Nile red and chlorophyll fluorescence signals co-localize in most cells and were difficult to separate, as Nile red could also stain membranes of organelles like chloroplasts (Greenspan et al., 1985; An et al., 2021). However, in cases of large lipid droplets (as shown in Fig. 4, of a dividing cell) it was possible to separate the two signals (to some extent) by appropriate thresholding. The chlorophyll fluorescence (green channel), in Fig. 4, appears as a ring around the lipid droplets. This could again be an artifact due to intense light scattering from intra-cellular components and a possible spillover from Nile red fluorescence.

To assess the effect of Fe(III) concentration in the culture medium on Symbiodinium sp. cell growth, morphology, and biochemical content, the 3D RI images were used to quantify (see methods section) cell size, mean RI, protein, and lipid content (Fig. 5, Table S5).

Cells grown in 0 nM Fe displayed smaller volume and refractive index (RI), lower lipid concentration and dry mass, as well as reduced protein concentration and dry mass (Fig. 3 and Fig. 5). In terms of RI, cells grown in 0 nM Fe had a mean value of 1.37 ± 0.02, while the highest mean RI was measured in cells grown in 50 nM Fe condition at 1.4 ± 0.005, compared to 10 and 100 nM conditions (ANOVA, F = 22.83, p < 0.01, Fig. 5a, Table S5). The cell volume ranged from 262.9 ± 420.6 µm³ in 0 nM Fe to 649.07 ± 298.6 µm³ in 10 nM Fe (ANOVA, F = 23.94, p < 0.01, Fig. 5b, Table S5), with no significant differences observed in 50 and 100 nM Fe conditions. The lowest protein dry mass was recorded in 0 nM Fe 61.04 ± 98.55 pg (ANOVA, F = 29.50, p < 0.01), while the highest was measured in 10 nM Fe 171.58 ± 66.55 pg, with no significant difference among the other conditions (Fig. 5c, Table S5). Protein concentration was lowest in cells grown in 0 nM Fe, at 0.17 ± 0.1 10^− 4 pg µm³ (ANOVA, F = 22.91, p < 0.01), while the highest values were measured in cells grown in 50 nM Fe at 0.3 ± 0.02 10^− 4 pg µm^− 3 (Fig. 5d, Table S5). Lipid dry mass and concentration were higher in cells cultured in 50 nM Fe condition than all other conditions and measured at 1.54 ± 2.2 pg (χ² = 18.619, p < 0.01) and 31.47 ± 46.61 10^− 4 pg µm^− 3 (χ² = 17.178, p < 0.01), respectively (Fig. 5e, f, Table S5). Lipid:protein ratio was higher in cells grown in 50 nM condition at 1.66 ± 0.57 (ANOVA, F = 4.82, p < 0.01, Fig. 5g, Table S5), with no significant difference observed in other conditions.

In this study, we investigated the influence of dissolved Fe concentration on the cellular growth and content of Symbiodinium sp. As hypothesized, Fe enrichment enhanced cellular growth and increased cellular contents. However, this was only true up to an intermediate concentration of 50 nM Fe(III), which seemed to provide the most favorable conditions among the investigated concentrations.

Iron is recognized for its support of the photosynthetic process in coral endosymbionts and its essential role as a cofactor in numerous enzymatic reactions involved in photosynthesis, electron transport, and antioxidant activities (Raven et al., 1999; Reich et al., 2020). Thus, iron limitation can limit the growth of Symbiodinium spp. (Rodriguez and Ho, 2018) as well as marine phytoplankton (Sunda & Huntsman, 1997), as observed in our experiment for cells grown in depleted iron conditions (0 nM). An increase in the volume of Symbiodinium sp. cells was observed at 10 nM Fe condition, which could indicate that lower Fe concentrations may facilitate cellular expansion. However, the large variation in cell volume (46%) suggests that cells were at a different growth stage compared to other conditions. Iron availability can influence the expression and activity of cell cycle regulatory proteins, such as cyclins and cyclin-dependent kinases (CDKs), which control the progression of cell cycle phases in phytoplankton (Peter & Herskowitz, 1994; Smith et al., 2017). The variability of cell volume in the growth stages might be related to differences in the utilization of Fe within the cells, with varying requirements at different stages of growth. The highest cell growth rate was measured at moderate Fe levels (50 nM Fe), resulting in a smaller cell volume compared to 10 nM (-36%) and 100 nM Fe (-13%). Similar patterns of high growth rate and reduced cell volume were observed in S. microadriaticum (ITS2 type A1, Camp et al., 2022), indicating a strict correlation between trace metal availability and cellular growth. However, in hospite symbionts are often nitrogen-limited (Falkowski et al., 1993; Cui et al., 2022), and enriching iron under coral reef-like nutrient conditions may exacerbate nitrogen limitation and further unbalance nutrient exchange, photosynthetic activity, and host-symbiont relationship, which could explain the reduced growth rate we observed at high iron levels (100 nM Fe). At the coral host-endosymbiont level, increasing iron levels may stimulate photosynthetic symbiont proliferation but it could lead to their overgrowth in the coral host tissue, which eventually results in expulsion as a stress-response and bleaching. Moreover, the exposure of corals to high iron levels can in turn lead to decreased rates of photosynthesis and reduced maximum quantum yield of PSII (Brown, 1989; Dellisanti et al., 2024).

Iron is a limiting nutrient for primary producers, including symbiotic dinoflagellates (Entsch et al., 1983) and eukaryotic marine algae (Greene et al., 1972). However, the concentration of iron in seawater is affected by mechanisms of scavenging, such as complexation by strong ligands (Johnson et al., 1997). Iron in seawater is present in ferrous Fe(II) and ferric Fe(III) forms, and its speciation depends on oxidation states and thermodynamics (Blain & Tagliabue, 2016). Most of the iron present in seawater is in the form of ferric ion Fe(III) and can undergo inorganic speciation to ferrous ion Fe(II) through hydrolysis and organic speciation with ligands, such as EDTA and siderophores produced by marine cyanobacteria (Sandy & Butler, 2009; Blain & Tagliabue, 2016). When considering the bioavailable amount of Fe (Westall et al., 1976), the Fe levels utilized in this study (0–100 nM Fe) were lower compared to previous studies, which used a range of 0–250 nM Fe, corresponding to 0–1250 pM bioavailable Fe (Rodriguez et al., 2016; Rodriguez & Ho, 2018; Reich et al., 2020, 2021). Moreover, in this study, we did not use EDTA as an inorganic ligand to increase the bioavailability of iron, which might account for a lower bioavailable amount of iron. Despite these methodological differences, previous findings have also highlighted a similar role of Fe(III) in the growth of Symbiodiniaceae, evidenced by higher growth rates when S. microadriaticum is cultured with Fe(III) complexes (Romero et al., 2022). This response is, however, species-specific, with other Symbiodiniaceae species responding faster than S. microadriaticum (Romero et al., 2022). Iron uptake and intracellular content are also enhanced when Symbiodinium spp. are exposed to Fe(III), although high Fe levels reduce the utilization efficiency of this element in S. microadriaticum, with a shift to the utilization of other trace metals such as zinc, nickel, and copper to maintain the enzymatic activities and cellular functioning (Blay-Haas & Merchant, 2012).

In our study, the higher Chl a and carotenoid concentration at 100 nM Fe(III) indicates enhanced pigment production, potentially due to excess Fe stimulating pigment synthesis. Iron is present in almost all the components of the electron transport chain in the chloroplast, including cytochromes, and it is a precursor of chlorophyll synthesis (Pushnik et al., 1984) through hemoproteins in the cytochrome b6f complex (Hogle et al., 2014). The absence of these pigments at 0 nM Fe(III) indicates severe stress or nutritional limitations leading to impaired cellular growth (Rodriguez and Ho, 2018; Romero et al., 2022). However, excessive iron (100 nM Fe(III)) may lead to toxic levels negatively impacting Symbiodiniaceae growth and, in turn, the symbiotic relationships within the coral host (Brown, 1989; Leigh-Smith et al., 2018). Moreover, our findings indicate that Symbiodinium sp. can produce higher levels of scytonemin when cells are grown in 100 nM Fe(III). The biosynthesis of scytonemin in Symbiodinium sp. is influenced by osmotic and oxidative stress (Dillon et al., 2002; Liu et al., 2018), potentially serving as an indicator of stress for cells grown under high Fe conditions. This could explain why moderate levels of 50 nM Fe(III) are more favorable, providing sufficient Fe for pigment production, while supporting the development of cellular content without reaching toxic levels (as observed in this study).

Non-destructive label-free tomographic imaging represents an advanced tool for investigating the morphology and cellular content of live single cells, such as Symbiodinium sp. Previous studies have demonstrated its capability in visualizing lipids within cells and delineating cell morphologies of microalgal cells, showing comparability with traditional staining techniques. Recent advancements in holotomography have further expanded the potential of this approach by enabling the study of subcellular components, such as lipid droplets without the need for fixation or staining methods (Kim et al., 2024). This offers researchers the opportunity to investigate cellular structures and contents in-vivo providing insights into dynamic cellular processes that conventional staining techniques may not cover. Using non-destructive holotomography, we measured higher lipid content (+ 57%), refractive index (+ 0.35%), and protein concentration (+ 9%) when Symbiodinium sp. was exposed to 50 nM Fe(III), indicating a physiological response to moderate iron concentrations by increasing cellular content. We speculate that moderate levels of Fe enhance the metabolic activity of Symbiodinium sp., which leads to increased lipid production to store excess energy as a response mechanism to cellular division. This suggests that there is an optimal Fe(III) concentration in the culture medium, which leads to optimal cellular biochemical content, resulting in the highest growth rates of the Symbiodinium cells. It is important to note that different Symbiodinium species may exhibit distinct strategies for energy storage, reflecting their specific physiological adaptations to their respective ecological niches (Wang et al., 2015). The relatively higher lipid content observed in cells grown at 50 nM Fe(III) may represent a cellular response for energy storage, as observed in Symbiodinium cultures and other microalgae (Roessler, 1990; Jiang et al., 2014; Sun et al., 2018). Lipids generate more energy than carbohydrates upon oxidation and can be efficiently packed into the cell, thus providing the best energy reserve for cells to return to homeostatic conditions, particularly in response to stress conditions like temperature fluctuations (Rosset et al., 2019) and nutrient deprivation, such as nitrogen limitation (Jiang et al., 2014). In conclusion, holotomography allows real-time observation of live Symbiodiniaceae cells, providing insights into their response to environmental stressors. It enables non-invasive monitoring of cellular adaptations, such as lipid droplet formation and protein concentration via tomographic mapping of refractive index. This method can also be applied to compare different Symbiodiniaceae species, potentially revealing strategies for energy storage and environmental adaptation, which might help to explain their evolutionary success in various ecological niches.

Importantly, it should be noted that the Fe levels utilized in our study (0-100 nM) are higher than ranges found in natural environments. Coastal waters typically exhibit Fe levels around 14.5 nM (Sarthou & Jandel, 2001), whereas tropical waters often have Fe concentrations below 5 nM (GEOTRACES IDP, 2021). Moreover, our study primarily examined the short-term responses of cultured Symbiodinium sp. to increasing Fe concentrations, which may not fully capture the long-term implications or acclimation potential of these organisms to fluctuating Fe levels in their natural habitats. Additionally, while specific growth rates provide valuable insights, they offer only a partial understanding of overall fitness and ecological performance. Incorporating additional metrics such as specific growth rate, nutrient uptake rates, photophysiological measurements or gene expression profiles could provide a more comprehensive understanding of the physiological responses of Symbiodinium sp. to Fe availability either in culture or in hospite.

Marine photosynthetic organisms are profoundly influenced by the availability of trace metals, which are fundamental for numerous physiological processes including photosynthesis, cellular homeostasis, and antioxidant enzymatic reactions. Increasing levels of dissolved iron, Fe(III), have been shown to significantly impact the growth of Symbiodinium sp., while also stimulating the production of cellular lipids. However, the observed variation in pigment concentrations versus growth and reproduction at different iron concentrations in Symbiodiniaceae cultures suggests that iron availability and pigment concentration are just one facet of the complex network of factors influencing their physiology. Our study highlights the significance of iron availability as an essential trace metal in regulating the growth of Symbiodinium sp. It emphasizes the necessity of considering potential interactions of trace metals when investigating the response of these organisms to environmental changes. Moreover, it highlights the need for further research to elucidate the specific mechanisms and regulatory pathways involved in Symbiodinium sp. responses to iron availability. For future studies, it would be valuable to incorporate measurements e.g. of cellular scavenging of reactive oxygen species (ROS) levels under environmental stress, such as ocean warming, and under nitrogen and phosphorus limitation. Additionally, exploring the role of inorganic Fe in supporting thermo-tolerance may provide insights into the mechanisms of metal availability in the growth of Symbiodiniaceae.

Acknowledgment

We thank Sofie Jakobsen and Jonathan Wolters for excellent technical assistance, and Dr. Stefano Amalfitano at the Water Research Institute (CNR-Italy) for discussing flow cytometry procedure and data analysis.

Data availability

Data and code for data analysis are available in the Zenodo repository at https://zenodo.org/doi/10.5281/zenodo.13845002.

Funding

This research was supported by the European Union (Grant Agreement no. 101062810, MedCorP; WD), the Villum Foundation (Grant no. VIL57413; MK), the Carlsberg Foundation (Grant no. CF21-0599; MK) and the Gordon and Betty Moore Foundation (Grant no. GBMF9206; https://doi.org/10.37807/GBMF9206; MK). The funders had no role in study design, data collection and analysis, decision to publish, or preparation of the manuscript.

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Walter Dellisanti and Swathi Murthy contributed equally to this manuscript.

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Moderate levels of dissolved iron stimulate cellular growth and increase lipid storage in Symbiodinium sp.

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Abstract

Figures

1. Introduction

2. Materials and Methods

2.1 Symbiodinium cultures

2.2 Culture identification

2.3 Growth measurements

2.4 Pigment analysis

2.5 Optical diffraction tomography

2.6 Wide-field fluorescence imaging.

2.7 Symbiodinium sp. cellular lipid and protein determination

3. Results

3.1 ITS2 identification

3.2 Cellular growth rate and pigment concentration

4. Discussion

5. Conclusions

Declarations

References

Additional Declarations

Supplementary Files

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