Linking Cultivation Conditions to the Fatty Acid Profile and Nutritional Value of Chlorella sorokiniana Lipids

Abstract

Microalgae are a promising alternative source of PUFAs, with Chlorella being one of the few microalgae widely available in the nutraceuticals market authorized for human consumption. This study explores the fatty acid (FA) profiles of nine C. sorokiniana biomass feedstocks produced under different combinations of light intensity and nitrogen and inorganic carbon loadings, derived via a Taguchi L9 (3³⁻¹) orthogonal array design. Additionally, the nutritional and medical value of Chlorella lipids using several nutritional indices is assessed. PUFAs were maximized under low light intensity and high nitrogen loading; however, these conditions favored the overaccumulation of omega-6 FAs. For omega-3 FA maximization, high light intensity must be applied, suggesting that high illumination induces the desaturation of linoleic acid to alpha-linolenic acid (ALA) in C. sorokiniana cells. Additionally, nitrogen-depleted conditions significantly downgraded its quality due to the overaccumulation of saturated FAs. Despite lacking EPA and DHA, C. sorokiniana lipids are an excellent source of ALA, surpassing concentrations met in plant-based oils. Thus, Chlorella lipids can be included in humans’ diet, satisfying daily ALA requirements; however, accurately labeling the FA profile of Chlorella products, prior to any nutritional claims, is indispensable, considering the sizeable variations in their profile under the impact of cultivation conditions.

1. Introduction

Polyunsaturated fatty acids (PUFAs), particularly ω-3 fatty acids (FAs), are crucial for human nutrition due to their numerous health benefits, including anti-thrombotic, antiarrythmic, antiatherosclerotic, anti-inflammatory, and antibiotic properties [1,2]. Furthermore, ω-3 FAs are essential for the development of the central nervous system in adults and to support the regular operation of the retina and brain [3,4,5]. Primary ω-3 fatty acids are alpha-linolenic acid (ALA), eicosapentaenoic acid (EPA), and docosahexaenoic acid (DHA). Traditional sources of ALA are plant oils, while oily fish have been the primary source of EPA and DHA [2]. However, plant oils usually exhibit an unbalanced ratio of ω-3 to ω-6 FAs, with overaccumulated amounts of ω-6 FA [6,7], which at large concentrations promote inflammation that in turn has been associated with cancer and autoimmune diseases [7]. Complementary to this weakness, the depletion of fish stocks due to overfishing, concerns about heavy metal contamination in fish, and the rise of veganism [8] necessitate alternative sources of ω-3 FAs.

Microalgae have emerged as a valuable source of ω-3 FAs [1,9] and have begun to take share of ω-3 PUFA market [10]. Various microalgae species can accumulate significant amounts of ALA, EPA, and DHA. Despite extensive research on numerous microalgae species, only a few have been approved by the European Food Safety Authority (EFSA) for food applications, while currently the microalgae-based market is dominated by Spirulina—the brand name of the cyanobacterial genus Arthrospira [11]—and the oleaginous microalga Chlorella. Although Chlorella typically lacks EPA and DHA, it is rich in ALA [12,13], a precursor to EPA and DHA synthesis in the human body through the elongase and desaturase pathways [14]. Furthermore, the proportion of ω-3 to ω-6 FAs, commonly being around 1:1 in Chlorella lipids [12], significantly contributes to a lifelong healthy status and cardiovascular safety [13].

Cultivation conditions could orient definite quantitative changes in FA composition. These changes could act either as an improving promoter or downgrade agent of the nutritional quality of Chlorella lipids. Nutrient limitations, particularly in terms of nitrogen, are key cultivation strategies to promote lipid overaccumulation in microalgae cells [15]. However, this well-established cultivation approach usually increases the formation of saturated fatty acids (SFAs) and monounsaturated fatty acids (MUFAs) [16], which, although favoring biodiesel applications [17,18], is a nutritional and functional downgrade for applications related to food and nutraceutical products. Light intensity also plays a crucial role in the composition of FAs. Typically, higher light intensities are associated with an increase in the production of SFAs and MUFAs, while the level of PUFAs tends to decrease or remain stable under this condition [19,20]. However, this response is not consistent across all microalgae species, suggesting different light acclimation strategies among microalgae taxa [20]. Additionally, the interaction between light intensity and other cultivation conditions, such as nitrogen supply or temperature, may play a more critical role in determining the overall FA profile in microalgae cells, rather than light intensity alone [21,22]. Inorganic carbon supply, particularly in the form of bicarbonate salts, can also cause significant changes in the FA profiles of various microalgae. However, its effect is not universal, and high loading (i.e., ≥2–10 g NaHCO₃ L⁻¹) is typically required to induce measurable differences, generally resulting in an increase in SFAs and a reduction in PUFAs [23,24].

Several indices have been proposed for the assessment of the nutritional and/or medicinal value of dietary lipids. Among them, the most frequently used are the Atherogenic Index (AI) and Thrombogenic Index (TI). These indices provide notable implications and perspicuous evidence for lipid evaluation [25] regarding their association with cardiovascular diseases. The AI assesses the ratio of specific SFAs most closely linked with elevated LDL cholesterol (LDL-C) levels—namely, lauric (C12:0), myristic (C14:0), and palmitic (C16:0) acids—relative to unsaturated fatty acids (UFAs). These SFAs are considered pro-atherogenic as they promote the adhesion of lipids to cells within the circulatory and immunological systems [26,27,28]. In contrast, UFAs are deemed antiatherogenic because they inhibit plaque formation and reduce the levels of phospholipids, cholesterol, and esterified fatty acids in the bloodstream [27,28]. Therefore, consumption of foods or nutraceutical products with a lower AI can reduce the levels of total cholesterol and LDL-C in human blood plasma [29]. The Thrombogenic Index (TI) is another crucial measure that evaluates the tendency of dietary fats to promote thrombosis, i.e., the formation of clots in blood vessels. Similar to the AI, the TI is the ratio of selected pro-thrombogenic SFAs (i.e., C14:0, C16:0, and C18:0) over anti-thrombogenic UFAs (MUFAs, ω-3, and ω-6 FAs) [6]. Lower TI values suggest a reduced potential for clot formation, which is beneficial for cardiovascular health. On the opposite side, the health-promoting aspects of lipids can be assessed based on the Hypocholesterolemic/Hypercholesterolemic ratio (H/H) [25,30]. H/H assesses the overall balance between cholesterol-lowering (unsaturated) and cholesterol-raising (saturated) fatty acids, with a value above 1 considered desirable [31]. A higher H/H ratio indicates a greater potential to lower LDL cholesterol levels, offering cardiovascular benefits.

While the aforementioned indices focus on the relationship between saturated and unsaturated fatty acids, the ratio of ω-3 to ω-6 FAs introduces another dimension to the evaluation of dietary lipid impacts. Although the EFSA does not recommend a value for the ω3/ω6 FA ratio due to insufficient data on clinical and biochemical outcomes on humans [32], maintaining a proportion of ω-3 to ω-6 FAs in the range of 1 to 0.25 is advisable for overall health benefits [7]. Interestingly, the daily intake recommendations by the EFSA for ALA, EPA, and DHA in total, and ω-6 FAs (mainly linoleic acid—LA), are 2 g, 250 mg, and 10 g, respectively [32], nearly satisfying the lower value of this ratio. Additionally, ratios closer to 1 are particularly beneficial for the prevention and management of chronic diseases, and this was the typical value found in human diets prior to 20th century [7].

This study assesses the main and interactional effects of several cultivation conditions on the FA composition of the microalga C. sorokiniana’s lipids. The FA profiles of nine autotrophically produced C. sorokiniana biomass samples, generated under different combinations of light intensity (2500, 5000, and 7500 lx) and nitrogen (250, 750, and 1250 mg NaNO₃ L⁻¹) and inorganic carbon (0, 750, and 1500 mg NaHCO₃ L⁻¹) loading levels, based on a Taguchi L9 (3 ³⁻¹) orthogonal array design, were analyzed. Additionally, key nutritional indices such as the AI, TI, H/H, and ω3/ω6 ratio were calculated to evaluate the nutritional and medicinal value of this dietary fatty acid source and its variation linked to the applied cultivation conditions. The goal is to thoroughly evaluate how these cultivation conditions influence the FA composition and nutritional quality of C. sorokiniana biomass, aiming to establish optimal conditions that enhance its nutritional benefits and thereby its potential for food and nutraceutical applications.

2. Materials and Methods

2.1. Biomass Samples of Chlorella sorokiniana

Freshly freeze-dried biomass samples of C. sorokiniana (100–200 mg) cultivated under the influence of nine (9) different combinations of light intensity and nitrogen and inorganic carbon loadings levels, based on a Taguchi L9 (3 ³⁻¹) orthogonal array design, were derived from the experiment of Papapanagiotou et al. [33]. This specific fractional factorial experimental design was selected to systematically evaluate three factors at three levels each, using only 9 trials instead of 27. By reducing the number of required trials, the method significantly minimized experimental effort while capturing the main effects, ensuring a balanced representation of factor-level combinations and enabling robust optimization and analysis of cultivation conditions. The autotrophic cultivation experiment was conducted in 500 mL Erlenmeyer flasks (working volume 250 mL) in a shaking incubator (BIOBASE, BJPX-2012R, Jinan, China) equipped with lighting and an aeration system. The combined levels of the studied cultivation factors applied for the production of each C. sorokiniana biomass sample are presented in

Table 1. C. sorokiniana biomass samples cultivated under different levels of light intensity and nitrogen and inorganic carbon loadings. (L), (M), and (H) stand for the low, medium, and high levels of each factor, respectively.

Cultivation Factors	C. sorokiniana Biomass Sample
	A	B	C	D	E	F	G	H	I
Light intensity (lx)	2500	2500	2500	5000	5000	5000	7500	7500	7500
	(L)	(L)	(L)	(M)	(M)	(M)	(H)	(H)	(H)
N-loading (mg NaNO3 L−1)	250	750	1250	250	750	1250	250	750	1250
	(L)	(M)	(H)	(L)	(M)	(H)	(L)	(M)	(H)
C-loading (mg NaHCO3 L−1)	0	750	1500	750	1500	0	1500	0	750
	(L)	(M)	(H)	(M)	(H)	(L)	(H)	(L)	(M)

, while the detailed experimental conditions were as follows: an initial cell density of 85 mg L⁻¹ (expressed as Dry Cell Weight—DCW), a cultivation period of 16 days under a daily 16 h photosynthetic light cycle, a temperature of 25 °C, an agitation rate of 140 rpm, and an atmospheric air supply rate of 0.2 mL min⁻¹. Additionally, every 48 h, the pH of the cultures was adjusted to neutral by adding appropriate microdoses of 2.5 M HCl solution. Significant variation among the trials was observed, with final biomass production ranging from 675 to 1084 mg DCW L⁻¹ and lipid content between 17% and 32.9% wt. Further details regarding the outcomes of this experiment are provided in the study of Papapanagiotou et al. [33]. C. sorokiniana freeze-dried biomass samples were stored in a desiccator under dark conditions at temperatures of 20–25 °C, until the performance of the fatty acid analysis.

2.2. Analysis of Fatty Acids

2.2.1. Reagents and Solutions

Methanol (≥99.95%), n-hexane (≥98.0%), hydrochloric acid (≥32%), and chloroform (≥99.8%) were purchased from Merck (Darmstadt, Germany). The following fatty acid methyl ester (FAME) standard was used for calibration (Chem-Lab, Zedelgem, Belgium): Mixture CL-40 (10 mg/mL) solution in dichloromethane (Methyl butyrate (400 μg/mL), Methyl hexanoate (400 μg/mL), Methyl octanoate (400 μg/mL), Methyl decanoate (400 μg/mL), Methyl undecanoate (200 μg/mL), Methyl dodecanoate (400 μg/mL), Methyl tridecanoate (200 μg/mL), Methyl myristate (400 μg/mL), Methyl myristolaeate (200 μg/mL), Methyl pentadecanoate (200 μg/mL), Methyl cis-10-pentadecenoate (200 μg/mL), Methyl palmitate (600 μg/mL), Methyl palmitoleate (200 μg/mL), Methyl heptadecanoate (200 μg/mL), Methyl cis-10-heptadecenoate (200 μg/mL), Methyl stearate (400 μg/mL), Methyl elaidate (200 μg/mL), Methyl oleate (400 μg/mL), Methyl linoelaidate (200 μg/mL), Methyl linoleate (200 μg/mL), Methyl γ-linolenate (200 μg/mL), Methyl linolenate (200 μg/mL), Methyl arachidate (400 μg/mL), cis-11-Eicosenoic acid methyl ester (200 μg/mL), cis-11,14-Eicosadienoic acid methyl ester (200 μg/mL), Methyl heneicosanoate (200 μg/mL), cis-8, 11, 14-Eicosatrienoic acid methyl ester (200 μg/mL), Methyl arachidonate (200 μg/mL), cis-11, 14, 17-Eicosatrienoic acid methyl ester (200 μg/mL), Methyl behenate (400 μg/mL), Methyl erucate (200 μg/mL), cis-5,8, 11,14,17-Eicosapentaenoic acid methyl ester (200 μg/mL), cis-13,16-Docosadienoic acid methyl ester (200 μg/mL), Methyl tricosanoate (200 μg/mL), Methyl tetracosanoate (400 μg/mL), Methyl cis-15-tetracosenoate (200 μg/mL), and cis-4,7,10,13,16,19-Docosahexaenoic acid methyl ester (200 μg/mL)).

2.2.2. Sample Treatment and Derivatization

Sample treatment was performed by direct transesterification, which allows for small biomass samples to be analyzed and does not require multiple steps as the esterification agent is added directly to the biomass [34,35]. A major advantage of direct transesterification is that fatty acids are simultaneously extracted and transesterified. For sample preparation, 100 mg of lyophilized microalgae biomass was weighted and placed in 10 mL screw thread glass vials. Then, 300 μL of HCl–methanol solution 6M and 200 μL of chloroform–methanol (2:1 v/v) were added. The vials were sealed hermetically, vortexed for 10 s, and then heated at 85 °C for 1 h to facilitate transesterification. Then, the vials were cooled under running water and 500 μL of hexane was added. The vials were vortexed again for 10 s and allowed to rest for 1 h to enable separation of the hexane phase. Once separation occurred, 300 μL of the hexane phase, containing fatty acid methyl esters (FAMEs), was removed and transferred to GC-specific amber glass vials. Then, oxygen in the vials was replaced with nitrogen by injection, and the vials were stored at −30 °C.

2.2.3. Analysis by Gas Chromatography

Gas chromatography was performed on a Thermo Focus GC coupled with a flame ionization detector (FID). The GC system was equipped with a DB-FATWAX UI column (30 m × 0.25 mm ID, 0.25 μm film thickness from Agilent J&W Scientific (Santa Clara, CA, USA)). Helium was employed as the carrier gas at a constant flow of 3.0 mL min^–1. The injector temperature was held at 230 °C. Injections were performed in split mode (8:1) with an injection volume of 1 μL. The oven temperature was programmed as follows: initially a temperature of 150 °C was held for 1 min, and then increased to 220°at a rate of 1 °C min^–1 C and held at 220 °C for 10 min. The FAMEs were identified by comparing the retention times of the samples with those of reference standards of known composition (Chem-Lab, Zedelgem, Belgium) [36,37].

2.3. Calculation of Nutritional Indices of Chlorella sorokiniana Biomass Samples

2.3.1. Atherogenic Index (AI) and Thrombogenic Index (TI)

The Atherogenic Index (AI) as developed by Ulbricht et al. [38] was used to determine the atherogenic potential of C. sorokiniana lipids. The AI is calculated using the following formula:

$$\mathrm{A}\mathrm{I}={\displaystyle \frac{w_{C12:0}+4·w_{C14:0}+w_{C16:0}}{w_{MUFA}+w_{PUFA}}}$$

(1)

where $w_{C12:0}$, $w_{C14:0}$, and $w_{C16:0}$ are the mass fractions of each fatty acid and $w_{MUFA}$ and $w_{PUFA}$ are the mass fractions of total mono- and polyunsaturated fatty acids, respectively, within the total fatty acid mixture.

2.3.2. Thrombogenic Index (TI)

For the determination of the thrombogenic potential of C. sorokiniana lipids, the index of thrombogenicity (TI) [38] was used, according to the following formula:

$$\mathrm{T}\mathrm{I}={\displaystyle \frac{w_{C14:0}+w_{C16:0}+w_{C18:0}}{0.5·w_{MUFA}+0.5·w_{\omega -6}+3·w_{\omega -3}+\frac{w_{\omega -3}}{w_{\omega -6}}}}$$

(2)

where $w_{C14:0}$, $w_{C16:0}$, and $w_{C18:0}$ are the mass fractions of each fatty acid; $w_{MUFA}$ denotes the mass fraction of total monounsaturated fatty acids (MUFAs); $w_{\omega -6}$ refers to the mass fraction of total omega-6 FAs; and $w_{\omega -3}$ indicates the mass fraction of total omega-3 FAs within the total fatty acid mixture.

2.3.3. Hypocholesterolemic/Hypercholesterolemic (H/H) Ratio

The Hypocholesterolemic/ Hypercholesterolemic (H/H) ratio, first proposed by Santos-Silva et al. [39] and later optimized by Mierliță [40], was employed in this study to assess the effect of FA composition of Chlorella sorokiniana on cholesterol. The employed formula is as follows:

$$\mathrm{H}/\mathrm{H}={\displaystyle \frac{w_{C18:1-cis}+w_{PUFA}}{w_{C12:0}+w_{C14:0}+w_{C16:0}}}$$

(3)

2.3.4. Omega-3/Omega-6 Fatty Acid (ω3/ω6) Ratio

Omega-3-to-Omega-6 FA ratio is also analyzed in this study, since an unbalanced ω3/ω6 ratio of diet lipids is correlated with pro-thrombosis and pro-inflammation [41]. The employed formula is as follows:

$$\omega 3/\omega 6={\displaystyle \frac{w_{\omega -3}}{w_{\omega -6}}}$$

(4)

2.4. Statistical Analysis

All analyzed C. sorokiniana biomass samples were obtained from duplicate (n = 2) cultures, while FA analysis of each sample was conducted in triplicate (n = 3). MiniTAB Statistical Software (Version 21.1.0) was used for the analysis of variance (ANOVA), Fisher pairwise comparisons, visualization of the main and interaction effects, and response surface plots.

3. Results and Discussion

3.1. Fatty Acid Composition of C. sorokiniana Biomass

The fatty acid composition of C. sorokiniana biomass feedstocks is presented in

Table 2. Fatty acid composition (wt. %) of C. sorokiniana lipids for A-I biomass samples. n.d. denotes that this FA was not identified in the FA profile.

Fatty Acid	C. sorokiniana Biomass Samples
	A	B	C	D	E	F	G	H	I
Palmitic acid—C16:0	26.0 ± 2.4	26.7 ± 0.3	24.8 ± 0.4	29.6 ± 0.8	26.1 ± 0.4	27.9 ± 0.0	30.5 ± 0.3	25.9 ± 0.2	22.3 ± 0.3
Palmitoleic acid—C16:1 cis 9	1.2 ± 0.0	0.8 ± 0.0	0.8 ± 0.0	0.7 ± 0.0	0.8 ± 0.1	1.0 ± 0.1	0.8 ± 0.4	1.3 ± 0.2	1.0 ± 0.2
Stearic acid—C18:0	1.5 ± 1.0	n.d.	0.4 ± 0.2	n.d.	0.6 ± 0.0	0.2 ± 0.2	1.4 ± 0.1	n.d.	n.d.
Oleic acid—C18:1 cis 9	12.2 ± 1.1	19.3 ± 0.9	10.0 ± 0.5	17.3 ± 4.2	12 ± 0.8	19.7 ± 4.0	21.6 ± 5.9	13.1 ± 2.1	10.0 ± 0.4
Elaidic acid— C18:1 trans 9	1.7 ± 0.3	0.5 ± 0.5	1.5 ± 0.1	0.9 ± 0.3	1.6 ± 0.0	0.7 ± 0.7	1.5 ± 0.1	n.d.	1.0 ± 0.1
Linoleic acid—C18:2 cis 9,12	28.7 ± 3.0	29.7 ± 0.0	32.9 ± 0.3	22.3 ± 3.9	35.3 ± 1.8	28.5 ± 0.8	13.8 ± 0.9	26.2 ± 0.8	28.7 ± 2.0
α- Linolenic acid—C18:3 cis 9,12,15	28.9 ± 1.8	23.2 ± 0.0	29.7 ± 0.1	29.3 ± 1.5	23.7 ± 1.4	22.2 ± 2.0	30.6 ± 6.1	33.7 ± 2.9	37.1 ± 1.7
Total SFAs	27.4 ± 3.3	26.7 ± 0.3	25.2 ± 0.5	29.6 ± 0.8	26.7 ± 0.5	28.1 ± 0.2	31.9 ± 0.5	25.9 ± 0.2	22.3 ± 0.3
Total MUFAs	15.1 ± 1.3	20.6 + 0.4	12.3 ± 0.6	19.0 ± 4.5	14.4 ± 0.9	21.3 ± 3.0	23.9 ± 6.4	14.4 ± 2.0	12.0 ± 0.6
Total PUFAs	57.5 ± 4.7	52.8 ± 0.1	62.6 ± 0.2	51.6 ± 5.4	59.0 ± 0.4	50.7 ± 2.8	44.4 ± 7.0	59.9 ± 2.2	65.8 ± 0.3
ω-3	28.9 ± 1.8	23.2 ± 0.0	29.7 ± 0.1	29.3 ± 1.5	23.7 ± 1.4	22.2 ± 2.0	30.6 ± 6.1	33.7 ± 2.9	37.1 ± 1.7
ω-6	28.7 ± 3.0	29.7 ± 0.0	32.9 ± 0.3	22.3 ± 3.9	35.3 ± 1.8	28.5 ± 0.8	13.8 ± 0.9	26.2 ± 0.8	28.7 ± 2.0

. The analysis revealed significant amounts of palmitic acid (C16:0), oleic acid (C18:1 cis 9), linoleic acid (C18:2 cis 9,12), and alpha-linolenic acid (C18:3 cis 9,12,15) in all biomass samples of C. sorokiniana. Additionally, palmitoleic (C16:1 cis 9) and elaidic acid (C18:1 trans 9) at low contents were also detected, except from in biomass sample ‘H’, which lacked elaidic acid, while stearic acid (C18:0) was found in very low concentrations in 5 biomass samples (i.e., A, C, E, F, and G).

According to Petkov and Garcia [12], the typical fatty acid composition of Chlorella species includes myristic acid (C14:0), hexadecadienoic acid (C16:2), and hexadecatrienoic acid (C16:3), in addition to the fatty acids detected in our analysis. However, the lack of myristic acid in the FA composition of Chlorella biomass has been reported in a considerable number of studies [42,43,44,45,46,47,48], while others studies [49,50] have confirmed the presence of myristic acid in only a few biomass samples, which were influenced by varying cultivation conditions. Similarly, hexadecadienoic and hexadecatrienoic acids were also absent in the FA profiles in a significant number of studies [43,44,47,49,51,52,53,54], although some studies [48,50] indicated that the detection of hexadecadienoic acid was associated with the applied cultivation conditions. Furthermore, several studies [43,49,50,51,53,55,56,57] reported the presence of fatty acids with 20 carbon atoms (i.e., C20:0, C20:1, C20:4, and C20:5) as well as very long-chain fatty acids (i.e., C22:0, C22:1, C22:5, C22:6, and C24:0), though in all cases, the concentration of these long- and very long-chain fatty acids was low or extremely low. Additionally, in few studies [48,49,58], the detection of C17:0, C17:1 as well as C15:0 was reported; however, these odd-chain FAs are evidence of bacterial contamination [59,60]. Despite the qualitative differences in the fatty acid profiles of different Chlorella biomass samples, it is indisputable that the FA composition of Chlorella species, as well as other members of the phylum Chlorophyta, is dominated by FAs with 16 and 18 carbon atoms, including saturated, monounsaturated, and polyunsaturated FAs [16].

3.2. Effect of Cultivation Factors on FA Composition

The results of the ANOVA based on the statistical model that considers only the main effects of all factors, ignoring their interactions, for all the FA classes (SFA, UFA, MUFA, and PUFA) and the two PUFA subclasses (ω-3 and ω-6 FAs) are presented in

Table 3. ANOVA based on the main effects model for the composition of SFAs, UFAs, MUFAs, PUFAs, and omega-3 (ω-3) and omega-6 (ω-6) FAs. p-values < 0.05 are highlighted in bold.

Factor	DF	Adjusted Sum of Squares and p-Values
		SFA	UFA	MUFA	PUFA	ω-3	ω-6
Light intensity	2	9.748	9.568	15.303	48.591	248.47	187.954
p-value for light intensity		(0.436)	(0.443)	(0.779)	(0.650)	(0.009)	(0.029)
Factor contribution		6.89%	6.76%	3.84%	5.50%	52.30%	26.94%
N-source loading	2	62.831	63.341	53.563	233.364	30.630	299.081
p-value for N-source loading		(0.019)	(0.019)	(0.436)	(0.163)	(0.428)	(0.007)
Factor contribution		44.47%	44.76%	13.44%	26.39%	6.45%	42.92%
C-source loading	2	8.874	8.698	0.323	5.741	12.230	2.521
p-value for C-source loading		(0.467)	(0.474)	(0.995)	(0.949)	(0.702)	(0.936)
Factor Contribution		6.28%	6.15%	0.01%	0.65%	2.57%	0.36%
Error	11	59.831	59.909	329.150	596.393	183.78	207.241
Total	17	141.284	141.516	398.340	884.089	475.11	696.798
R-sq		57.65%	57.67%	17.37%	32.54%	61.32%	70.26%

. According to this model, nitrogen was denoted as a statistically significant factor in both SFA and UFA (see also Figure S1) accumulation, whereas no factor was statistically significant for MUFA and PUFA formation. Although the ANOVA did not indicate any cultivation factor as significant for the overall PUFA formation, both their subclasses (ω-3 and ω-6 FAs) were influenced by the applied cultivation conditions. Light intensity emerged as the most impactful factor for the formation of ω-3 FAs (p-value = 0.009), while the respective formation of ω-6 FAs was primarily affected by nitrogen concentration in the cultures (p-value = 0.007) and, to a lesser extent, by light intensity (p-value = 0.029). In contrast, C-loading in the form of sodium bicarbonate was the least impactful factor and was statistically insignificant for all FA classes and subclasses.

Considering that the main effects ANOVA model only partially succeeded in attributing the differentiation of the FA profiles of C. sorokiniana biomass to specific cultivation factors, it was further verified through the derived low R-sq values that a substantial portion of the observed variability was not explained by the pertinent statistical model. This unexplained variability can be attributed to the inability to account for the first-order interaction due to the insufficient degrees of freedom in this model. This became evident when the ANOVA was performed based on the main effects of the two most significant factors (thus ignoring the C-source loading) and their first-order interaction (

Table 4. ANOVA based on interaction effect model of the two most impactful factors for the formation of SFAs, UFAs, MUFAs, PUFAs, and omega-3 (ω-3) and omega-6 (ω-6) FAs. DF denotes degrees of freedom and p-values < 0.05 are highlighted in bold.

Factor		Adjusted Sum of Squares and p-Values
	DF	SFA	UFA	MUFA	PUFA	ω-3	ω-6
Light intensity	2	9.748	9.568	15.303	48.591	248.47	187.95
p-value for light intensity		(0.225)	(0.242)	(0.540)	(0.317)	(0.002)	(0.002)
Factor contribution		6.89%	6.76%	3.84%	5.50%	52.30%	26.94%
N-source loading	2	62.831	63.341	53.56	233.36	30.63	299.08
p-value for N-source loading		(0.003)	(0.004)	(0.155)	(0.020)	(0.226)	(0.000)
Factor contribution		44.47%	44.76	13.44%	26.39%	6.45%	42.92%
First order interaction	4	43.876	42.832	225.24	434.85	117.92	145.75
p-value for first order interaction		(0.040)	(0.047)	(0.023)	(0.013)	(0.059)	(0.020)
Factor contribution		31.06%	30.27%	56.54%	49.19%	24.82%	20.92%
Error	9	24.830	25.775	104.23	167.28	78.09	64.01
Total	17	141.284	141.516	398.34	884.09	475.11	696.80
R-sq		82.43%	81.79%	73.83%	81.08%	83.56%	90.81%

), which significantly increased the R-sq values. The two-factor interaction model revealed the significant role of the interaction between light intensity and nitrogen loading for all the FA classes and the ω-6 FAs subclass. Additionally, in this model, the effect of the two most significant factors was further highlighted, as reflected in the lower p-values, compared to those obtained through the main effects model. The unexplained variation was notably reduced in this model, with R-sq values exceeding 80% for all classes and subclasses, except for MUFAs, where the respective R-sq value was approximately 74%. These R-sq values, although not extremely high, provide a reasonable interpretation of the results, especially considering the dynamic nature of FA synthesis and degradation.

3.2.1. Effect of Cultivation Conditions on SFA Formation

SFAs constituted between 22.3 and 31.9% wt. of the total FAs in C. sorokiniana biomass, depending on the applied cultivation conditions (Table 2). In all biomass samples, C16:0 was the main SFA, accounting for more than 94% of this class, while in several samples, C18:0 was also detected. The accumulation of SFAs in C. sorokiniana cells is primarily affected by nitrogen loading, while its interaction with light intensity also contributes to the formation of SFAs (Table 4). Maximum SFA accumulation occurred under the low level of nitrogen loading (Figure 1a), which according to Papapanagiotou et al. [33] triggers a nitrogen-depletion period. This N-depletion period, which was brief, moderate, or prolonged under low, medium, and high light intensity, respectively [33], seems to govern the formation of SFAs at the expense of the other FAs. Additionally, the duration of the N-depleted state is crucial for the overaccumulation of SFAs, as their proportion increases constantly from low to higher light intensity (at the low level of nitrogen loading), as illustrated in the interaction effect plot (Figure 1b).

The increase in SFAs under N-depleted conditions has been observed in various Chlorella species [61,62,63]. Furthermore, as highlighted in the review article of Maltsev and Maltseva [16], the rise in SFAs under nitrogen starvation appears to be a common trend in the FA profiles of microalgae. The overproduction of SFAs during nitrogen stress is attributed to metabolic reprogramming, driven by the down- and up-regulation of numerous enzymes and genes [64,65]. Under nitrogen starvation, microalgae metabolism shifts from cell growth to energy storage, forcing cells to channel carbon flux toward biosynthesis of neutral lipids, particularly triacylglycerols, [27,66], which are rich in SFAs and MUFAs [16,67].

In our analysis, light intensity had no significant effect on the selective overaccumulation of SFAs in C. sorokiniana. This finding is consistent with the results of Nzayisenga et al. [68], who also noticed a nearly constant SFA content in C. vulgaris cultivated under three different light intensities (50, 150, and 300 μmol m⁻² s⁻¹) and nitrogen-depleted conditions. Conversely, Amini Khoeyi et al. [54], reported a gradual increase in SFA content with increasing the level of light intensity (37.5, 62.5, and 100 μmol m⁻² s⁻¹). Similarly, in the study of He et al. [69], the content of SFAs remained constant between C. vulgaris biomass samples grown under 40 and 200 μmol m⁻² s⁻¹, but increased significantly at the highest tested illumination intensity of 400 μmol m⁻² s⁻¹. Clarifying the effect of light intensity on the synthesis of SFAs, two more factors must be taken into consideration to avoid misinterpreting its role. First, it is important to co-examine the nitrogen status of the cultures, even if nitrogen is not among the studied factors. This is crucial because variations in SFA content across different light intensities can be indirectly induced by nitrogen depletion, which may occur or be prolonged under higher light intensity levels, as microalgae typically show increased growth and thus faster nitrogen consumption with rising light levels. Second, the levels of illumination tested should be evaluated in relevance to the photoinhibition threshold for the examined microalga. For instance, in the study of He et al. [69], the higher level of illumination intensity that induced a significant increase in SFAs also triggered photoinhibition. It is therefore suggested that the increase in SFA content observed in such cases serves as a cellular mechanism to mitigate the effects of excessive light exposure, in accordance with the conclusions of Maltsev and Maltseva [16].

Inorganic carbon supply, in the form of dissolved sodium bicarbonate, was also denoted as an insignificant factor in the formation of SFAs in C. sorokiniana. However, in the studies of Frumento et al. [70] and Najafabadi et al. [71], the inclusion of sodium bicarbonate in the growth medium appeared to diminish the content of SFAs in C. vulgaris lipids; in contrast, Nayak et al. [72] observed an increase in SFA content in Chlorella sp. biomass samples produced with sodium bicarbonate addition. Thus, a definitive conclusion for the effect of sodium bicarbonate cannot be drawn, suggesting a species-specific response.

3.2.2. Effect of Cultivation Conditions on MUFA Formation

MUFAs constituted between 12.3 and 23.9% wt. of the total FAs in C. sorokiniana biomass, depending on the applied cultivation conditions (Table 2). The predominant MUFA was oleic acid (C18:1 cis 9), with trace amounts of its trans isomer detected nearly in all biomass samples. Additionally, all biomass samples had microquantities of palmitoleic acid (C16:1 cis 9). The main effects plot (Figure 2a) shows that nitrogen loading had the greatest impact on the formation of MUFAs, followed by light intensity, while sodium carbonate had no discernible effect. However, only the interaction between nitrogen loading and light intensity was denoted as a statistically significant source of variance (Table 4).

Several studies have demonstrated that N-depleted conditions lead to the enhanced accumulation of MUFAs in Chlorella species [61,62,63]. This trend is confirmed in our study, as shown by the main effects plots (Figure 2a), which display an almost linear increase in MUFAs with decreasing sodium nitrate concentration in the culture. However, deviations from this trend appeared in the interaction effect plot (Figure 2b) under low and medium light intensities, where conflicting trends may suggest a distinct desaturation process. This conversion likely involves specific FA desaturases for each light intensity level, contributing to ω-6 or ω-3 formation. The specific FA desaturases involved, and their interplay, however, remain poorly understood [73].

Regarding the effect of light intensity οn the accumulation of MUFAs in Chlorella spp., there is not a concrete trend. Some studies report a linear increase in MUFAs with increasing light intensity [68,74,75], while others observe a slight decrease under similar conditions [54,69]. In our study, as in the analysis of Belkoura et al. [76], light intensity did not significantly affect MUFA accumulation.

3.2.3. Effect of Cultivation Conditions on PUFA Formation

PUFAs were the predominant class of FAs in all biomass samples, ranging from 44.4 to 65.8% of the total FAs, depending on the cultivation conditions (Table 2). This class includes the ω-3 and ω-6 FA subclasses. Due to the competing synthesis mechanisms of these two subclasses (particularly in terms of illumination), the main effects model of the ANOVA could not attribute the accumulation of PUFAs in C. sorokiniana microalgal biomass to any specific cultivation factor (Table 3). However, the interaction effects model of the ANOVA (Table 4) revealed that nitrogen and its interaction with light intensity were the primary sources of variance (p-value < 0.05) in the production of total PUFAs. The ω-3 subclass consisted solely of ALA (C18:3 cis 9,12,15), while the ω-6 subclass consisted of LA (C18:2 cis 9,12). Both of these PUFAs are essential for human nutrition, playing a pivotal role in metabolism and being indispensable as they cannot be synthesized by humans [16,18].

The main effects plot (Figure 3a) shows that the accumulation of PUFAs increases with nitrogen supplementation in the growth medium, though this increase is not proportional across the examined levels. A significant rise in PUFA content is observed through the transition from the low to the medium level of nitrogen loading, while this increase is less pronounced from the medium to high nitrogen level. The main effects plots for ω-6 and ω-3 FAs (Figure 3c,e), indicate that the augmentation of PUFAs under N-sufficiency conditions is largely driven by ω-6 FA formation, which remains nearly stable under medium and high nitrogen levels. Although nitrogen loading was identified as the most significant factor for ω-6 FA formation (Table 3 and Table 4), it was not significant for ω-3 FAs (Table 3 and Table 4 and V-shaped response in Figure 3e). The ω-3 accumulation pattern, compared to that of ω-6, contributes mildly to the PUFAs’ development, softening the sharp increase observed in the transition from nitrogen-depleted to nitrogen-sufficient conditions and helping to the further rise in PUFA levels at higher nitrogen loading.

Interaction effect plots provide important insights into the relationship between the two most impactful factors for PUFA formation. Figure 3b illustrates the critical role of the duration of N-depleted conditions (low level of nitrogen loading), with a lower PUFA content recorded under the high level of illumination (prolonged period of N-depleted conditions), which gradually increases under medium and low light intensities. This trend is mainly attributed to ω-6 FAs synthesis mechanisms (Figure 3d), as ω-3 FAs remain relatively unaffected by the duration of N-depleted conditions (Figure 3f). Interestingly, at the high level of illumination, the content of ω-3 FA increases linearly with nitrogen supplementation, mirroring the pattern of ω-6 FA formation, though with smaller percentage increases. Although both subclasses follow similar trends at higher light intensities, they diverge in their response to nitrogen loadings under lower illumination intensities. The negative impact of nitrogen limitation on the synthesis of PUFAs is well documented in the literature for the genus Chlorella [58,61,63,77,78,79], and our findings are in line with this general trend. Light intensity, while not identified as a statistically significant factor for total PUFA accumulation, was significant in the formation of both ω-3 and ω-6 FAs. The low level of this factor induces the formation of ω6, while the high level was the one that maximized the proportion of ω-3 FAs in C. sorokiniana lipids. Although reports of increased ω-3 FA ratios under high light intensity are scarce in the recent bibliography, the sharp increase in ω-3 FA content observed in our study, along with the attenuation of the ω-6 FA production rate, under high illumination, suggests the occurrence of desaturation. In C. sorokiniana, this involves the desaturation of dienoic acid (C18:2) to produce trienoic acid, C18:3, the most unsaturated FA, in this species [80]. Klyachko-Gurvich et al. [80] stated that this desaturation mechanism toward ω-3 FA synthesis has been repeatedly observed for the genus Chlorella.

3.3. Effect of Cultivation Factors on the Nutritional Indices of C. sorokiniana Lipids

The calculated values of the nutritional indices AI, TI, H/H, and ω3/ω6 ratio for the nine C. sorokiniana feedstocks are presented in

Table 5. Values of the nutritional indices (AI, TI and H/H and ω3/ω6 ratios) of C. sorokiniana biomass samples (A to I).

C. sorokiniana Biomass Sample	Nutritional Index
	AI	TI	H/H Ratio	ω3/ω6 Ratio
A	0.36 ± 0.05	0.25 ± 0.04	2.71 ± 0.39	1.01 ± 0.04
B	0.36 ± 0.01	0.28 ± 0.0	2.70 ± 0.07	0.78 ± 0.00
C	0.33 ± 0.01	0.22 ± 0.01	2.93 ± 0.06	0.90 ± 0.01
D	0.42 ± 0.02	0.27 ± 0.02	2.33 ± 0.11	1.35 ± 0.17
E	0.36 ± 0.01	0.28 ± 0.02	2.73 ± 0.06	0.68 ± 0.07
F	0.39 ± 0.00	0.30 ± 0.01	2.52 ± 0.03	0.78 ± 0.03
G	0.45 ± 0.01	0.29 ± 0.03	2.17 ± 0.04	2.22 ± 0.21
H	0.35 ± 0.00	0.21 ± 0.01	2.82 ± 0.02	1.29 ± 0.15
I	0.29 ± 0.01	0.17 ± 0.01	3.4 ± 0.05	1.31 ± 0.15

, while

Table 6. ANOVA based on the interaction effect model of the two most impactful factors for the nutritional indices AI, TI, H/H, and ω3/ω6. DF denotes degrees of freedom and p-values < 0.05 are highlighted in bold.

Factor	DF	Adjusted Sum of Squares and p-Values
		AΙ	ΤΙ	H/H	ω3/ω6
Light intensity	2	0.004150	0.011402	0.2727	1.9033
p-value for light intensity		(0.095)	(0.018)	(0.078)	(0.000)
Factor contribution		10.00%	30.10%	11.51%	49.51%
N-source loading	2	0.017393	0.004350	0.9161	1.3117
p-value for N-source loading		(0.002)	(0.138)	(0.003)	(0.000)
Factor contribution		41.93%	11.49%	38.67%	34.12%
First order interaction	4	0.013914	0.014234	0.8230	0.3831
p-value for first order interaction		(0.019)	(0.038)	(0.019)	(0.055)
Factor contribution		33.55%	37.59%	34.74%	9.97%
Error	9	0.006022	104.23	167.28	78.09
Total	17	0.041479	0.037872	2.3689	3.8442
R-sq		85.48%	79.18%	84.92%	93.60%

summarizes the ANOVA results for these indices based on the interaction effect model. Additionally, the respective results from the main effects model are presented in Table S1. According to Table 6, light intensity was denoted as a significant factor for the TI and ω3/ω6 ratio, while N-source loading was statistically significant factor for the AI and both the H/H and ω3/ω6 ratios. Additionally, the first order interaction between light intensity and N-source loading was a significant co-factor for all nutritional indices, and a marginal one for the ω3/ω6 ratio.

The main effects plots (Figure 4a,c) indicate that a low nitrogen level significantly increases the AI values of C. sorokiniana lipids, while moderate light intensity notably raises the TI values. Furthermore, the response surface plots (Figure 4b,d) highlight the combined effects of light intensity and nitrogen loading on the AI and TI in C. sorokiniana. For both indices, the highest values were observed under the low level of nitrogen and the high level of light intensity, suggesting that nitrogen depletion, especially under intense light, promotes the accumulation of both atherogenic and thrombogenic lipids. At higher N-loadings, both low and high light intensity levels significantly reduced the AI and TI values, while moderate level of light intensity sustained relatively high TI values. This indicates that although increased nitrogen availability can mitigate the accumulation of harmful lipids, light intensity remains a critical factor, particularly for thrombogenic potential. Overall, the above finding suggests that managing N-loading in relation to an applied (typically uncontrolled in outdoor environments) light intensity is an essential strategy for reducing the accumulation of both atherogenic and thrombogenic lipids in C. sorokiniana cultures.

Contrary to the AI and TI, which are desired to be as low as possible, high values of the H/H and ω3/ω6 ratios are key indicators of a healthy lipid source. A higher H/H ratio reflects a lipid composition that is associated with a reduced risk of cardiovascular disease, while a higher ω3/ω6 ratio indicates a lower risk of inflammation. Figure 5 illustrates the main effects of the cultivation conditions and the interaction of the two most impactful factors on the configuration of the H/H and ω3/ω6 ratios.

According to Figure 5a, N-loading predominantly influences the H/H values of C. sorokiniana lipids, followed by light intensity. To maximize the H/H ratio, high N-loading should be combined with either low or high light intensity, along with a moderate level of C-loading. This pattern closely mirrors the respective pattern in the main effects plots for the AI and TI. Although the main effects plot equally ranks the low and high level of light intensity for H/H ratio maximization, the response surface plot (Figure 5b) illustrates that the highest value of the H/H ratio (approximately 3.5) was achieved by combining the high levels of both light intensity and N-loading. In contrast, the value of the H/H ratio induced by the low level of light intensity combined with the high level of N-loading was significantly lower (approximately 3.0).

All C. sorokiniana biomass feedstocks analyzed in this study present a desirable proportion of ω-3 to ω-6 FAs, with values ranging from 0.78 to 2.21 (Table 5). Figure 5c shows that this ratio is strongly influenced by the levels of light intensity and N-loading applied. Among the three light intensity levels tested, the highest intensity resulted in a sharp increase in the ω3/ω6 ratio compared to the lower levels. In contrast, the low level of N-loading was the one that promoted the overaccumulation of ω-3 at the expense of ω-6 FAs, while under N-sufficient conditions (moderate and high levels of N-loading) a balanced ratio of ω-3 to ω-6 FAs was achieved. Although C-loading also played a role in shaping the ω3/ω6 ratio through a linear increasing trend, it was not statistically significant (Table S1). The response surface plot (Figure 5d) illustrates the interaction between light intensity and N-loading in determining the ω3/ω6 ratio. When compared to the corresponding plot for the H/H index (Figure 5b), it is realized that the high level of light intensity promotes both elevated H/H and ω3/ω6 ratios. However, when N-loading is taken into consideration, their interaction appears to be more complex. For maximizing the ω3/ω6 ratio, a combination of low N-loading with high light intensity is required, whereas maximizing the H/H ratio necessitates both high N-loading and high light intensity. Therefore, to effectively enhance both indices simultaneously, a cultivation strategy involving augmented illumination combined with a meticulous fed-batch nitrogen addition maintaining a state of marginal nitrogen sufficiency may be recommended.

Table 7. Nutritional indices of several sources of diet lipids. For C. sorokiniana, the reported values represent the average of all analyzed biomass samples.

Lipid Source	AI	TI	H/H	ω3/ω6	Reference
C. sorokiniana	0.36	0.25	2.71	1.14	Present study
Sunflower oil	0.06	0.18	18.63	0.01	[6,81]
Soybean oil	0.11	0.21	9.28	0.15	[6,81]
Sesame oil	0.11	0.34	8.77	0.01	[6,81]
Olive oil	0.16	0.39	6.01	0.14	[6,81]
Peanut butter	0.17	0.45	6.42	0.01	[6,82]
Cocoa butter	0.67	3.09	1.50	0.02	[6,83]

presents the typical nutritional indices of several plant-based lipid sources and the average values for C. sorokiniana biomass. Based on these values, C. sorokiniana demonstrates a relatively high AI compared to typical plant-based lipid source rankings in the AI. However, it exhibits a low TI, which places it among the lower ranks in this category. Despite these findings, both the AI and TI values of C. sorokiniana biomass feedstocks are still considered adequately low (considering typical thresholds form the literature, for the AI < 0.39 and for the TI < 0.28 [36]) and pose a minimal risk for coronary heart disease [6,38]. This suggests that while C. sorokiniana may have a slightly higher AI than several plant oils, its overall lipid profile remains highly favorable for cardiovascular health. Additionally, its balanced ω3/ω6 ratio (approximately 1:1) is highly favorable compared to many conventional plant-based oils, which tend to have significantly higher ω-6 content. This balanced ratio contributes to reduced inflammation and promotes overall cardiovascular health, making C. sorokiniana a valuable source of lipids for functional food and nutraceutical applications. Furthermore, under well-controlled selected conditions (experiment I), C. sorokiniana can provide values of the AI, TI, H/H and ω3/ω6 indices that can be considered beneficial for human health.

4. Conclusions

This study highlights the critical importance of optimizing cultivation conditions to enhance the nutritional profile of microalgal lipids, particularly in achieving a beneficial balance of ω3/ω6 fatty acids for human health, while minimizing the accumulation of SFAs. Through a systematic experimental approach, this study demonstrated the strategic manipulation of cultivation conditions—primarily light intensity, nitrogen, and inorganic carbon supply—to successfully influence the fatty acid profile of C. sorokiniana. By fine-tuning these factors, principally light intensity and nitrogen loading, the production of key fatty acids such as ω-3 and ω-6 can be optimized to support human health. Low nitrogen loading was shown to promote the overaccumulation of SFAs, while high light intensity increased the production of ω-3 fatty acids, leading to an improved overall lipid quality. Notably, the combination of a low Thrombogenic Index (TI) and Atherogenic Index (AI), along with a favorable ω3/ω6 ratio (>0.25, closer to 1), indicates that C. sorokiniana poses minimal cardiovascular risk and holds strong potential for nutraceutical applications. Specifically, the species is a promising source of alpha-linolenic acid (ALA) for meeting daily intake requirements. In summary, C. sorokiniana biomass presents a significant promise as a sustainable and high-quality source of lipids for functional foods and nutraceutical products. The findings of this study underscore its potential as a valuable ingredient in promoting cardiovascular health and advancing nutraceutical innovation.