Sustainable Valorization of Olive Mill Wastewater via Oleaginous Yeasts: Single-Cell Oil Production and Effluent Detoxification

Sustainable Valorization of Olive Mill Wastewater via Oleaginous Yeasts: Single-Cell Oil Production and Effluent Detoxification | 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 Sustainable Valorization of Olive Mill Wastewater via Oleaginous Yeasts: Single-Cell Oil Production and Effluent Detoxification Ines Ayadi, Ali Gargouri, Mohamed Guerfali This is a preprint; it has not been peer reviewed by a journal. https://doi.org/ 10.21203/rs.3.rs-5965608/v1 This work is licensed under a CC BY 4.0 License Status: Published Journal Publication published 02 Jun, 2025 Read the published version in Waste and Biomass Valorization → Version 1 posted 6 You are reading this latest preprint version Abstract Produced as a residual output of olive oil extraction, olive mill wastewater (OMW) is characterized by a high organic load and significant levels of phenolic compounds, posing notable environmental challenges. While it resists biodegradation, OMW serves as a nutrient-rich resource for microbial growth. In this study, OMW was used as renewable feedstock for microbial lipid production by oleaginous yeasts. Chemical characterization revealed that the OMW sample primarily contained 18 g/L total sugars, 3.4 g/L phenolic compounds, and high organic and mineral content of 85 and 15 g/L, respectively. Among the tested yeasts, Rhodotorula babjevae Y-SL7 stood out with a lipid accumulation yield of approximately 38% and a significant phenolic compound detoxification rate of 53.7%. To enhance lipid yield, the most effective nitrogen source was selected following preliminary evaluation, and culture conditions were then optimized using response surface methodology (RSM) based on the Box-Behnken model, incorporating three independent factors. The lipids produced from OMW showed a fatty acid composition dominated by oleic acid (69%) and palmitic acid (23%). Predictive analyses of biodiesel properties suggest this oil could be advantageous for biodiesel production. Additionally, lipid production was accompanied by carotenoid synthesis, mainly torulene (68.2%) and torularhodin (31.7%), both demonstrating significant antibacterial and antioxidant activities. The capacity of Y-SL7 to detoxify OMW and generate valuable by-products positions this approach as a promising alternative to conventional OMW treatment methods. Rhodotorula babjevae microbial lipids Olive mill wastewater Industrial wastes Carotenoids Biodiesel Figures Figure 1 Figure 2 Figure 3 Figure 4 Introduction The global drive for sustainable and eco-friendly fuel alternatives has gained momentum as fossil fuel reserves dwindle and environmental concerns, particularly atmospheric contamination and climate instability, become more pressing. Biodiesel emerges as a viable contender due to its biodegradable, renewable, and non-toxic properties [ 1 , 2 ]. However, the production of biodiesel from both edible and non-edible agricultural biomass, as well as animal fats, poses significant challenges, including competition for food resources, the large land area required, and concerns over animal feed. On the other hand, oils derived from oleaginous microorganisms, specifically single-cell oils (SCOs), offer a promising and sustainable feedstock for biodiesel production. This conversion process is achieved through a simple transesterification reaction with methanol, using either an acid or alkaline catalyst, resulting in fatty acid methyl esters and glycerol as by-products [ 2 ]. To unlock the full potential of SCOs as a sustainable biofuel source, ongoing research must focus on refining production methods to increase both yield and biodiesel quality. Additionally, cost-effective and scalable techniques for SCO production and extraction are critical to making this technology economically viable. Overall, leveraging oleaginous microorganisms for biodiesel production offers an innovative solution to the limitations of traditional biofuels and plays a key role in advancing toward a more sustainable energy landscape [ 3 ]. Certain microorganisms, including microalgae, bacteria, filamentous fungi, and yeasts, can synthesize and accumulate considerable amounts of intracellular lipids, often exceeding 20% of their dry biomass [ 4 ]. In yeasts, lipid content varies by species and can reach as much as 70% under specific nutrient-limited conditions. Lipid accumulation, particularly the synthesis of TAGs, is triggered when non-carbon nutrients such as magnesium, zinc, iron, phosphorus, and especially nitrogen availability is restricted in the microbial medium [ 5 ]. The predominant lipids synthesized by oleaginous microorganisms are triglycerides (around 80%) and sterol esters (about 20%), with triglycerides acting as the main energy reserve and sterol esters contributing to membrane stability [ 6 ]. Yeasts offer several advantages over other microorganisms: they can grow rapidly to high densities with substantial lipid yields, their cultures are simpler to scale up, and they can be genetically engineered to enhance production and develop tailored lipids. Of the known yeast species, only about 5% are classified as oleaginous, including genera such as Rhodotorula , Yarrowia , Cryptococcus , Candida , Lipomyces , and Trichosporon [ 7 ]. Oleaginous yeasts can utilize various renewable and low-cost resources, including lignocellulosic materials [ 8 ], oily wastes [ 9 ], municipal organic wastes [ 10 ], crude glycerol [ 11 ], and olive mill wastewaters [ 12 – 15 ]. This versatility makes yeasts both economically and environmentally attractive. Furthermore, these microorganisms can simultaneously produce valuable compounds such as enzymes [ 15 ], carotenoids [ 16 ], organic acids [ 17 ] and polyol esters of fatty acids [ 18 ], thereby enhancing their commercial significance. However, the commercialization of microbial lipid production remains limited by high costs, primarily driven by the price of fermentation substrates. Therefore, selecting robust yeast strains capable of thriving under extreme conditions and efficiently converting industrial wastes is crucial for developing lipid production methods for bioenergy applications. Additionally, developing innovative solutions for cost-effective and sustainable feedstocks and optimizing production processes are key to advancing yeast-based lipid production and promoting a sustainable biofuel industry. Mediterranean countries dominate global olive oil production, accounting for approximately 95% of the total output [ 17 ]. Olive mill wastewater (OMW), a by-product of this industry, is generated in varying quantities depending on the extraction method and the maturity of the olives. The three-phase olive oil extraction process, in particular, requires significant water inputs, resulting in a larger volume of wastewater compared to traditional or two-phase methods [ 19 ]. Consequently, OMW constitutes a significant waste output, generating between 1.2 and 1.8 cubic meters of wastewater for every ton of olives processed [ 20 ]. This complex effluent is characterized by a reddish-brown color, cloudy appearance, a strong olive oil scent, and high electrical conductivity due to its mineral content. Its composition is influenced by the olive variety and the extraction technique, consisting mainly of water (83–92%), organic matter such as polysaccharides, proteins, organic acids, phenols, and lipids (4–16%), and minerals (0.4–2.5%) [ 21 ]. OMW presents significant management challenges due to its high concentrations of phenolic compounds, chemical oxygen demand (COD) and biological oxygen demand (BOD), which commonly exceed 80 g/L, 100 g/L and 200 g/L, respectively [ 22 ]. Currently, the disposal and management of OMW remain problematic in many producing regions. Traditional disposal methods, such as land spreading, evaporation ponds, and direct discharge into water bodies or agricultural lands, are still widely practiced despite their environmental drawbacks. These methods can lead to groundwater contamination, soil degradation, and the accumulation of phytotoxic compounds, making them unsustainable over the long term [ 12 , 20 ]. Composting and anaerobic digestion are also explored, but they often require pre-treatment steps and do not always result in complete degradation of recalcitrant molecules, particularly phenolic compounds [ 21 ]. Therefore, the valorization of OMW through biotechnological processes represents an eco-friendly and circular alternative, transforming a pollutant into a resource. Numerous studies have focused on developing treatment methods for OMW, including physicochemical, thermochemical, and biological methods [ 23 – 25 ]. These treatments provide an opportunity to convert OMW into value-added products, including its use as a biopesticide, food supplies, precursor for hydrogen and biogas as well as for microbial enzymes production such as protease and lipase [ 15 , 23 , 26 , 27 ]. A particularly promising avenue is the production of microbial lipids through the cultivation of oleaginous microorganisms on OMW as a raw material [ 13 ]. Few oleaginous yeast strains belong to genera Lipomyces, Candida, Debaryomyces and Yarrowia have shown their effectiveness in OMW bioconversion and lipid production [ 12 , 13 , 14 , 28 ]. Therefore, selecting oleaginous yeasts that can resist and degrade polyphenolic compounds while efficiently bio-converting OMW is a critical step toward establishing an economically viable production process. This study aimed to explore the potential of novel oleaginous yeasts for the bioconversion of OMW into microbial lipids by characterizing this wastewater and evaluating its suitability as a carbon-rich substrate under various culture conditions. Additionally, it sought to optimize lipid accumulation and effluent detoxification through response surface methodology (RSM), providing a cost-effective and eco-friendly valorization strategy. Among the screened strains, Rhodotorula babjevae Y-SL7 was identified as particularly efficient in converting OMW into both lipids and carotenoid pigments. This bioconversion process offers a promising alternative for mitigating the environmental impact of OMW by reducing phenolic compound toxicity while generating valuable microbial products. The findings highlight the potential of oleaginous yeasts to support sustainable waste management and contribute to the development of renewable bioresources. Materials and Methods Raw material and oleaginous yeast strains The liquid by-product of olive oil production, OMW, was obtained from an olive mill in Sfax, Tunisia, which used a three-phase extraction technique. To remove suspended materials, the OMW was filtered and then centrifuged at 6000 rpm for 10 minutes, after which the supernatant was either used immediately as a substrate for oleaginous yeast cultivation or stored at -20°C for future use. The oleaginous yeast strains used in this study, including Candida viswanathii Y-E4, Rodotorula babjevae Y-SL7, Yarrowia lipolytica Y-RC7, and Trichosporon cutaneum CTM-30125, were previously isolated, characterized, and identified in our earlier research [ 29 ]. These strains have been deposited in the National Strains Collection (CTM) of the Center of Biotechnology of Sfax, CBS, Tunisia, under the accession numbers CTM-30136, CTM-30137, CTM-30139, and CTM-30125, respectively. The storage of all yeast strains was carried out at -80°C in a solution enriched with sterilized glycerol, containing 2% (w/v) glucose, 1% (w/v) yeast extract, 1% (w/v) bacto-peptone, and 20% (w/w) glycerol. Culture conditions The oleaginous yeast strains were cultivated in 250 mL Erlenmeyer flasks containing a YPG preculture medium composed of 20 g/L glucose, 10 g/L bacto-peptone, and 10 g/L yeast extract. The flasks were incubated in a rotary shaker set to 30°C and 180 rpm for 24 hours. The resulting precultures were then used to inoculate the lipid production medium at a 5% (v/v) ratio, equivalent to an initial optical density (OD) of 0.2 at 600 nm. The lipid production medium consisted of a synthetic nitrogen-limited formulation containing 0.5 g/L yeast extract, 0.5 g/L (NH 4 ) 2 SO 4 , 7 g/L KH 2 PO 4 , 2.5 g/L Na 2 HPO 4 , 1.5 g/L MgSO 4 ·7H 2 O, 0.2 g/L CaCl 2 ·2H 2 O, 0.07 g/L MnSO 4 ·H 2 O, 0.01 g/L ZnSO 4 ·7H 2 O, 0.01 g/L FeSO 4 ·7H 2 O, and 0.0001 g/L CuSO 4 . Commercial glucose and OMW were used as carbon sources at concentrations of 40 g/L and 50% (v/v), respectively. All cultures were performed under identical conditions: the initial pH was adjusted to 6.0, and incubation was carried out at 30°C with an agitation rate of 180 rpm. After 144 hours of fermentation, the yeast cells were harvested by centrifugation at 3000×g for 10 minutes. The collected cells were then washed with absolute ethanol and water to remove any residual substrate before being subjected to biomass quantification and lipid extraction. All experiments were conducted at least three times to ensure reproducibility. Experimental design and statistical analysis The Box-Behnken model was utilized in this study to optimize the culture parameters for improved lipid production by R. babjevae Y-SL7. The 3 3 Box-Behnken design enables the evaluation of potential quadratic interactions between pairs of factors, thus reducing the number of experiments required [ 30 ]. X 1 ​ (OMW quantity), X 2 (nitrogen concentration), and X 3​ (pH) were chosen as independent variables. Each variable was tested at three coded levels (-1, 0, + 1). Lipid yield was linked to changes in OMW amount (30%, 50%, and 70%), nitrogen concentration (0.5, 1.5, and 2.5 g/L), and pH (4.0, 5.5, and 7.0). The experimental design consisted of 17 experiments, with the five at the center point utilized to assess experimental error and adjust the model. The data obtained from RSM regarding the response ŷ (lipid yield) were subjected to analysis of variance (ANOVA) to check for errors and the significance of each parameter. A multiple regression analysis was also conducted to obtain an empirical model that relates the measured response to the independent variables. The quadratic equation (Eq. 1 ) was utilized to model and interpret the system's behavior, enabling the prediction of optimal conditions: $$\:Y=\:{{\beta\:}}_{0}+\:\sum\:{{\beta\:}}_{i}{\text{X}}_{i}+\:\sum\:{{\beta\:}}_{ij}{\text{X}}_{ij}+\sum\:{{\beta\:}}_{ii}{\text{X}}_{i}^{2}$$ 1 In this equation, Y refers to the predicted lipid yield (response variable), X i represents the independent variables, β 0 is the intercept, β i are the linear term coefficients, β ij indicates interaction terms, and β ii represents quadratic effect terms. The statistical software package Nemrod-W, version 2000-D, was employed to perform regression analysis on the experimental data and to generate the response surface graphs [ 31 ]. The statistical significance of the model was determined by applying Fisher’s F test. Furthermore, the iso-response contour plot was employed to illustrate the individual and combined effects of the variables, along with their potential correlations. Lipids and carotenoids extraction The microbial lipid extraction was carried out using the method of Dey and Maiti [ 7 ], with several modifications. A 100 mL culture sample was subjected to centrifugation at 3000×g for 10 minutes, and the resulting cell pellet was washed twice with 50 mL each of distilled water and absolute ethanol to eliminate any traces of substrate. The washed cell pellet was then dried for 24 hours at 105°C. About 0.3 g of the dried biomass was mixed with 10 mL of HCl (4M) and stirred for 2 hours at 70°C. The acid-hydrolyzed cells were stirred with a chloroform-methanol mixture (1:1) for 3 hours at room temperature and centrifuged at 3000×g for 10 minutes. The organic phase, which contains lipids, was carefully recovered and transferred to a new glass tube. Finally, 20% (v/v) of a 9 g/L NaCl solution was added to eliminate any remaining moisture, and the solvent was evaporated by sparging with nitrogen gas. The total lipid content was determined by the gravimetric method and expressed as the percentage (w/w) of the extracted lipids on the dry cell. Intracellular carotenoids were extracted using dimethyl sulfoxide (DMSO), according to the procedure described by Taskin et al. [ 32 ]. Briefly, washed yeast cells were incubated with DMSO at a 2:1 ratio and incubated at 50°C for 30 minutes, with periodic vortexing to ensure complete homogenization. Acetone was then added to the DMSO-treated cells in a 1:2 (v/v) ratio, followed by additional vortexing and centrifugation until the cells were fully decolorized. The collected supernatants were pooled and diluted with a 0.9% NaCl solution (1:2 v/v). Carotenoids were subsequently extracted by adding petroleum ether at a 1:1 (v/v) ratio, and the colored phase was recovered. To prevent degradation, the solvent was evaporated under an inert atmosphere, and the resulting residue was re-suspended in acetone for analysis. Residual carotenoids were subsequently quantified using spectrophotometric analysis. Analytical methods Physical and chemical characterization of OMW The pH measurement was conducted at room temperature (25 ± 0.5°C) using a Thermo Electron Corporation digital pH meter. The electrical conductivity was also measured at the same temperature using a conductivity meter and expressed in mS/cm. The dry weight of OMW was determined by drying 1 g at 105°C until a constant weight was reached. The ash content, representing the mineral matter, was determined following the ASTM D 1102-84 (Reapproved 1990) standard. This involved incinerating 1 g of dry biomass at 550°C for 3 hours. After that, the sample was cooled to ambient temperature in a desiccator, and the residual material was identified as the total ash, as described by Sluiter et al. [ 33 ]. The COD was determined using the method developed by Knechtel [ 34 ], in which the reagent potassium dichromate was used as a strong oxidizing agent with heating and in an acidic medium. The quantity of reagent consumed during the oxidation of the organic matter present was reported in mg/L of oxygen, which corresponds to the COD value. The biological oxygen demand (BOD) test is a method for determining the amount of biodegradable organic matter in a sample by measuring the oxygen consumption of microorganisms present in the sample. A measurable quantity of the sample is placed in a bottle that is connected to a mercury manometer. The depression in the manometer due to the consumption of oxygen by microorganisms corresponds to the BOD, which is expressed in mg/L. The carbon dioxide (CO 2 ) produced by bacterial respiration is absorbed from the gaseous medium by potassium hydroxide (KOH) placed in the stopper. The BOD value is obtained by multiplying the depression by a correlation factor. The BOD5 value is expressed in mg/L after 5 days of incubation in the dark at a constant temperature of 20 ± 1°C. The fat content in OMW was analyzed using a solvent-based extraction technique involving phase separation. A mixture of 10 mL of OMW and 20 mL of methanol-chloroform (1:1) was slowly stirred for 2 hours at room temperature. The organic phase was then collected and quantified using the same method as microbial lipid extraction. The decolorization of OMW was assessed by recording the absorbance at 525 nm for both inoculated and non-inoculated samples, as described by Aggelis et al. [ 35 ], using a Camspec M508 spectrophotometer (Spectronic Instruments Inc., U.K.). The concentration of total phenols in OMW was determined using the Folin-Ciocalteau reagent, as outlined by Singleton and Rossi [ 36 ]. 50 µL of OMW is mixed with 250 µL of the reagent and 500 µL of 20% sodium carbonate solution. After vortexing, the volume is adjusted to 5 mL with distilled water and the mixture is incubated for 30 minutes at room temperature. The optical density (OD) is measured at 727 nm, with distilled water used as a blank to adjust the zero. Nitrogen concentration in the OMW sample is determined using the Kjeldahl method [ 37 ]. Total sugars are determined by adding 1 mL of the sample, 1 mL of phenol (5%) and 5 mL of concentrated sulfuric acid and then incubating the mixture at room temperature for 10 minutes, followed by incubation at 30°C for 20 minutes. The orange-yellow color formed is measured at 488 nm using a spectrophotometer, and the corresponding glucose concentrations are determined from a calibration curve established earlier by Dubois et al. [ 38 ]. Residual glucose levels are quantified using the 3,5-Dinitrosalicylic acid (DNS) method, as detailed by Ichihara et al. [ 39 ]. Neutral lipid composition and biodiesel characterization To determine the complete fatty acid profile of microbial lipids, gas chromatography-mass spectrometry (GC/MS) was employed. Initially, 100 mg of the extracted lipids were dissolved in 2 mL of hexane and mixed with 0.2 mL of a 2 M methanolic KOH solution to produce fatty acid methyl esters (FAME). The mixture was vortexed thoroughly and incubated at room temperature for 15 minutes. Following this, the upper phase was separated and subjected to analysis using a gas chromatograph coupled to a 5975 B Inert MSD Mass-Selective Detector (Agilent Technologies, France). A 2 µL sample of FAME was introduced into the system through an HP-5MS Phenyl Methyl Siloxane capillary column (30 m × 250 µm × 0.25 µm nominal), with helium serving as the carrier gas at a steady flow rate of 1 mL/min. The injector and detector were set at temperatures of 250°C and 240°C, respectively. The temperature gradient was as follows: 120°C for 5 minutes, then ramped at 3°C/min to 180°C, further increased at 10°C/min to 220°C, and finally held at 220°C for 31 minutes [ 40 ]. The resulting data were analyzed using the NIST Mass Spectral Search program. For biodiesel characterization, the Biodiesel-Analyser software (Version 1.1, 2013) was used, which facilitates the prediction of biodiesel fuel properties based on the FAME profile of any oil feedstock, as determined via gas chromatography [ 41 ]. Carotenoids identification For individual carotenoid analysis, high performance liquid chromatography (HPLC) was employed, with a reversed-phase Eclipse XDB-C18 column (150 mm × 4.6 mm, 5 µm) and a mobile phase consisting of (eluent A) acetonitrile and water (9:1 v/v) and (eluent B) ethyl acetate with 1% formic acid. The UV-visible adsorption spectrum was recorded at 501 nm with a flow rate of 0.8 mL/min, and the injection sample volume was 80 µL with a column temperature of 25°C [ 42 ]. Commercial β-carotene was used as a standard, and torulene and torularhodin standards were obtained after separation by thin layer chromatography (TLC) using silica gel 60 plates (F254, 20 × 20 cm, Merck, Germany) and a solvent system of n-hexane and ethyl acetate (7:1). Chromatographed pigments were identified based on their flow rate (R f ). Antioxidant and antimicrobial activities Color degradation was assessed using two oxidant systems: (i) 2-diphenyl-1-picrylhydrazyl (DPPH) and (ii) 2,2'-azino-bis-(3-ethylbenzothiazoline-6-sulfonic acid) (ABTS). The DPPH method, as outlined by Brand-Williams et al. [ 43 ], was employed to determine the antioxidant activity of the extracted carotenoids, while the ABTS method, following Re et al. [ 44 ], was used for further evaluation. To determine the minimum inhibitory concentrations (MICs) of carotenoids from Y-SL7, the micro-dilution technique was applied against three bacterial strains. After incubation in Muller–Hinton broth (MH) (Oxoid Ltd, UK), the assay was performed using the MTT colorimetric method, based on 3-(4,5-dimethyl-2-thiazolyl)-2,5-diphenyl-2H-tetrazolium bromide, in sterile 96-well microtiter plates [ 45 ]. The bacterial strains used were Staphylococcus aureus ATCC 6538, Salmonella enterica ATCC 14,028, and Escherichia coli ATCC 8739, all obtained from international culture collections (ATCC). Results and discussion OMW characterization OMW is known for its highly variable composition, which is influenced by a variety of factors such as the method of oil extraction, the level of fruit maturity, and the specific olive tree variety [ 17 , 46 ]. OMW is typically characterized by its acidic pH, high electrical conductivity, and significant amounts of sugars, lipids, proteins, and phenolic compounds. Given this variability, it is important to conduct a thorough biochemical characterization of OMW before using it as feedstock for microbial metabolites production. The newly collected OMW in this study had a slightly acidic pH of 5.36 (Table 1 ), which is mainly due to the presence of organic acids such as phenolic acids and free fatty acids [ 46 ]. This finding is consistent with previous studies [ 28 , 47 ]. Additionally, OMW showed a conductivity of 3.71 mS/cm, indicating the presence of minerals in this effluent. Other studies have reported much higher electrical conductivities for OMW collected from different regions of Tunisia (11.1–13.2 mS/cm) [ 46 ]. OMW is a complex mixture containing high levels of organic matter, which can be quantified in terms of BOD5 (3.5 g/L), COD (75.6 g/L), and phenolic compounds (3.44 g/L). The characterization of OMWs collected from the north of Portugal revealed a variation in COD and total phenols, ranging from 36.7 g/L to 108.7 g/L and from 1.8 g/L to 4.83 g/L, respectively [ 15 ]. In contrast, OMWs from different regions of Tunisia showed higher levels of COD (219.34–286.3 g/L), BOD5 (65.87–86.71 g/L), and phenolic compounds (5.23–10.62 g/L) [ 46 ]. The solubility of phenolic compounds in oil is lower compared to OMW, which accounts for their higher concentration in the latter [ 48 ]. These toxic compounds have an inhibitory effect on the growth of microorganisms and are the primary cause of the phytotoxic effect, which can limit the potential use of OMW as a source of nutrients or for irrigation purposes in agriculture. Therefore, proper treatment and management of OMW are crucial to mitigate the negative impacts of these toxic compounds on the environment. On the other hand, OMW contains 0.76% lipids and 18.06 g/L of sugars, values that differ from those reported in the literature [ 12 , 15 ]. According to Sarris et al. [ 49 ], the sugars in OMW are mainly present as glucose, which can be easily assimilated by microorganisms. However, OMW is typically poor in nitrogen, containing only 0.07 g/L, which is insufficient for microorganism’s growth. However, this is considered ideal for the cultivation of oleaginous yeasts, which require a low amount of nitrogen in the substrate to direct the assimilated carbon towards primarily lipid synthesis [ 5 ]. Alternative studies have employed a feeding strategy that involves supplementing OMW with a carbon source, such as glucose or other by-products [ 13 , 50 ]. This approach can enhance the OMW's potential as a growth substrate for microorganisms, thereby aiding in the bioremediation of this waste product. Table 1 Parameters This work Yousuf et al. [ 12 ] Arous et al. [ 28 ] Zaier et al. [ 46 ] Dias et al. [ 15 ] pH 5.36 - 5.3 4.7–5.15 4.83–5.03 Conductivity (mS/cm) 3.71 - - 11.1–13.2 - Total dry matter (g/L) 70 ± 5 47.2 111.2 ± 0.2 48.03–95.1 - Mineral matter (g/L) 15.31 ± 0.35 11 26.4 ± 1.0 6.77–13.57 - Organic matter (g/L) 84.68 ± 0.36 - 84.8 ± 0.4 41.2–71.4 COD (g/L) 75.6 ± 5 - 214.3 ± 14.5 219.34–286.3 36.7-108.7 BOD 5 (g/L) 10.3 ± 1.5 - 66.3 ± 3.8 65.87–86.71 - Lipids (%) 0.76 ± 0.09 0.072 4.0 ± 0.6 - - Total nitrogen (g/L) 0.08 ± 0.01 - 0.1 ± 0.4 - 0.15–0.62 Reducing sugars (g/L) 9.3 ± 1.62 - 17.7 ± 0.5 - 10.1–36.3 Total sugars (g/L) 18.06 ± 0.13 12.79 52.5 ± 0.5 - 15–46 Phenolic compounds (g/L) 3.44 ± 0.08 9.14 11.8 ± 1.7 5.23–10.62 1.8–4.83 Lipid production and OMW detoxification Using OMW as a substrate for lipid production through the cultivation of oleaginous yeasts presents a promising alternative. Despite its low nitrogen content, OMW contains substantial amounts of sugars and organic compounds, making it suitable as a feedstock for microbial growth. To evaluate OMW's potential as a substrate, four oleaginous yeast strains: C. viswanathii Y-E4, R. babjevae Y-SL7, Y. lipolytica Y-RC7, and T. cutaneum CTM-30125 (all previously studied for their lipid-accumulating properties) were tested for their growth and lipid accumulation using OMW (at 50% v/v) as the sole carbon source. A nitrogen supplement (yeast extract/ammonium sulfate) was added to the medium at a concentration of 1 g/L. As shown in Fig. 1 a, all yeast strains were able to grow on OMW; however, biomass production was lower compared to when glucose was used as the carbon source. This difference is likely due to the substrate’s heterogeneity and the high concentration of impurities in OMW, which are known to contribute to its toxicity. Despite the high levels of phenolic compounds, yeasts remain the dominant microorganisms in OMW environments, with concentrations reaching up to 10 6 CFU/mL [ 51 ]. Among the tested strains, R. babjevae Y-SL7 showed substantial lipid production on OMW, reaching up to 38% total lipid content. In a similar vein, research indicates that other oleaginous yeasts, such as L. starkeyi , can efficiently utilize OMW as a substrate, reaching a lipid accumulation of 28.6% when grown on a 50% OMW medium [ 12 ]. However, as observed in research by Arous et al. [ 52 ], higher OMW concentrations can have inhibitory effects on yeast growth. For example, D. etchellsii exhibited optimal biomass production (4.8 g/L, containing 0.8 g/L lipids) when cultured at a lower OMW concentration of 25% after 72 hours [ 52 ]. In some cases, enriching the culture medium with nutritional supplements is essential to improve lipid yield, as demonstrated with Rhodotorula glutinis , which achieved an increase from 11% lipid content on undiluted OMW to 41.4% when supplemented with glycerol [ 53 ]. In parallel, tested oleaginous yeasts were evaluated for their ability to reduce phenolic compounds and decolorize OMW (Fig. 1 b). A significant level of detoxification was achieved by the different yeast strains, with rates ranging from 26.7% for the Y-E4 strain to 64.2% for CTM-30125. The Y-SL7 strain, which produced the highest lipid yield, also displayed effective phenolic compound assimilation (53.7%), a notable rate when compared to literature. This reduction in phenolic compounds suggests that the yeast strain assimilates and metabolizes these compounds, rather than simply adsorbing them. For example, C. tropicalis ATCC 750 degraded 39.6% of phenolic compounds in OMW supplemented with NH4Cl and containing 1.8 g/L initial total phenols [ 15 ]. For example, C. tropicalis ATCC 750 degraded 39.6% of phenolic compounds in OMW supplemented with NH 4 Cl and containing 1.8 g/L initial total phenols [ 15 ]. Research by Yousuf et al. [ 12 ] showed that L. starkeyi removed 47% of phenolic compounds in 50% OMW, alongside 28.6% lipid production under high initial phenol concentrations (9.14 g/L). Phenolic compounds, beyond their cytotoxic effects, also hinder carotenoid production; red yeast R. glutinis Y54 showed better growth and carotenoid production in thermally treated, dephenolized media [ 54 ]. The phytotoxicity and dark color of OMW, primarily caused by phenolic compounds, necessitate bioconversion for its safe application. All tested yeast strains demonstrated the ability to decolorize OMW, with Y-RC7 achieving a maximum reduction of 45.9%. For Y-RC7 and Y-E4, the decolorization rates were comparable to their detoxification rates, while Y-SL7 and CTM-30125 exhibited lower decolorization relative to detoxification. Some studies reveal complex relationships between decolorization and detoxification. For example, C. tropicalis LFMB 16 achieved a decolorization rate of 16% alongside a 58% reduction in phenolic compounds in OMW with an initial phenol concentration of 1.5 g/L [ 13 ]. Conversely, Cryptococcus curvatus ATCC 20509 showed nearly matched rates of decolorization and detoxification at 25% and 28%, respectively [ 14 ]. In another study, Yarrowia lipolytica exhibited a higher decolorization rate (63%) than detoxification (34%) when cultured on OMW with initial phenol levels of 1.5 g/L [ 46 ]. Research by Jarboui et al. [ 47 ] further confirmed that phenolic compounds significantly contribute to the color of OMW, as the removal rates for phenolic content and color followed the same model in treatments with R. mucilaginosa [ 47 ]. Due to its significant lipid production and detoxification rates, R. babjevae Y-SL7 was deemed an ideal candidate for the bioconversion of OMW and the production of valuable metabolites. As a result, it has been selected for further work in this research. Effect of nitrogen source on biomass and lipids production Oleaginous yeasts accumulate lipids when an essential nutrient, typically nitrogen, becomes limited in the growth medium, prompting a shift in cellular carbon flux from biomass production to fatty acid synthesis [ 6 ]. This process, known as de novo lipid accumulation, is primarily influenced by nitrogen availability in yeast cells. Consequently, selecting an optimal nitrogen source is crucial for maximizing SCO accumulation. Furthermore, nitrogen has been shown to play a key role in enhancing the biodegradation of aromatic compounds [ 55 ]. In this study, OMW was utilized as the carbon source, but it contains only minimal nitrogen (0.07 g/L), insufficient for supporting robust yeast growth. In order to boost both biomass and lipid production, the oleaginous yeast R. babjevae Y-SL7 was grown in a medium consisting of 50% OMW, enriched with different combinations of yeast extract and various nitrogen sources in equal amounts. Nitrogen supplementation in the OMW-based medium significantly increased both biomass and lipid production compared to using OMW as the sole carbon and nitrogen source (Table 2 ). Notably, the Y-SL7 strain achieved peak production levels, generating 3.62 g/L of biomass and 1.38 g/L of lipids, when fed a 1:1 mixture of yeast extract and ammonium sulfate ((NH 4 ) 2 SO 4 ) as the nitrogen source. Yeast extract, an organic nitrogen source rich in vitamins and amino acids, has been shown to effectively support yeast growth and lipid synthesis [ 56 ]. Additionally, nitrogen from ammonium salts is readily assimilated by yeast cells, enabling efficient utilization for growth and lipid accumulation [ 57 ]. Likewise, Lopes et al. [ 58 ] found that adding ammonium sulfate to an OMW-based medium significantly enhanced organic matter consumption by Y. lipolytica W29. Comparable findings have been observed in previous studies, such as with C. pararugosa BM24 and Schwanniomyces etchellsii M2 strains cultivated on 75% OMW, which produced lower biomass yields without nitrogen supplementation [ 28 ]. Thus, selecting an appropriate nitrogen source is essential for optimizing SCO accumulation. The combination of yeast extract and (NH 4 ) 2 SO 4 in the cultivation of R. babjevae Y-SL7 not only enhanced biomass and lipid production but also underscores the importance of nutrient management in optimizing bioprocesses for industrial applications. Table 2 Nitrogen source Biomass (g/L) Lipids (g/L) Lipid yield (%) Control 0.83 ± 0.14 0.22 ± 0.07 25.95 ± 5.95 Yeast Extract + Peptone (1:1) 2.49 ± 0.04 0.95 ± 0.01 38.23 ± 1.10 Yeast Extract +(NH 4 ) 3 PO 4 (1:1) 2.61 ± 0.04 1.07 ± 0.1 41.13 ± 4.20 Yeast Extract + NH 4 Cl (1:1) 2.94 ± 0.05 1.12 ± 0.04 37.99 ± 1.47 Yeast Extract +(NH 4 ) 2 SO 4 (1:1) 3.62 ± 0.42 1.38 ± 0.2 38.04 ± 1.17 Response surface model (RSM) for lipid yield enhancement Optimizing fermentation conditions through strategic media formulation is fundamental to establishing efficient and productive bioconversion processes. Traditional optimization approaches, where only one independent variable is adjusted at a time, are typically labor-intensive and time-consuming. Furthermore, they often lack precision in predicting optimal levels and understanding interactions among variables [ 59 ]. To address these limitations, a statistical experimental design methodology offers a more effective alternative, enabling a clearer and more accurate determination of optimal conditions and parameter interactions. To achieve this, the Box-Behnken model was applied to identify the optimal levels of independent variables and to assess the impact of their interactions on lipid production by the oleaginous yeast R. babjevae Y-SL7. The three independent variables were as follows: amount of OMW (X 1 ), nitrogen concentration (X 2 ), and pH (X 3 ). Seventeen experiments were conducted using various combinations of these factors. The design matrix, along with the experimental results, is provided in the supporting information (Table S1 ). Significant differences were observed in the lipid yields produced, with this variation closely linked to the levels of each factor. The lipid yield ranged from 0.37 g/L in run 1 to 2.28 g/L in run 8. Through multiple regression analysis of the experimental data, the following second-degree polynomial equation (Eq. 2 ) was derived to represent the response ( Y ), considering only the most significant terms (Table 3 ). Table 3 Model Term Coefficient F.Inflation St.error a t value P value e Intercept 1.360 0.062 22.08 < 0.01 *** X 1 0.432 1.00 0.049 8.88 < 0.01 *** X 2 0.271 1.00 0.049 5.57 0.0985 *** X 3 0.266 1.00 0.049 5.47 0.109 ** X 1 2 -0.155 1.01 0.067 -2.31 5.3 X 2 2 -0.317 1.01 0.067 -4.73 0.231 ** X 3 2 0.083 1.01 0.067 1.23 25.8 X 1 X 2 0.188 1.00 0.069 2.72 2.90 * X 1 X 3 0.298 1.00 0.069 4.32 0.365 ** X 2 X 3 0.075 1.00 0.069 1.09 31.3 Source SS b Df c MS d F test P value Regression 3.7317 9 0.4146 21.8678 0.0457 *** Residual 0.1327 7 0.0190 Lack of fit 0.1059 3 0.0353 5.2699 7.2 Error 0.0268 4 0.0067 Total 3.8644 16 R 2 = 0.96 a St.error, standard error; b Df, degree of freedom; c SS, sum of squares; d MS, mean square e P value less than 0.05 indicates terms are significant $$\:Y=1.36+0.432\:{X}_{1}+0.271{X}_{2}+0.266{X}_{3}-0.317{X}_{2}^{2}+0.298{X}_{1}{X}_{3}$$ 2 Where Y represents the predicted lipid yield; X 1 , X 2 and X 3 ​ correspond to the coded values of OMW concentration, nitrogen concentration, and pH, respectively. The Student's t-test was employed to determine the significance of the coefficients. The regression coefficients, along with their corresponding P values and parameter estimates, are presented in Table 3 . Based on Equation (Eq. 2 ), we can conclude that lipid yield is primarily influenced by the linear effects of the three variables, the squared effect of nitrogen concentration (X 2 ), and to a lesser extent, by the interactions between X 1 and X 3 . The ANOVA analysis conducted on lipid production revealed that the regression model was significant ( P < 0.05), and the lack of fit was found to be non-significant. Additionally, the model demonstrated a high coefficient of determination (R² = 0.96), indicating that 96% of the variability in the response was attributable to the effects of the independent variables. A model's ability to accurately explain the variability between experimental and predicted outcomes increases as the R 2 value approaches 1 [ 30 ]. Using the second-order equation, the response was expressed as a function of the interaction between the amount of OMW and pH. Three-dimensional response surfaces and their respective contour plots were created from the model equation to identify the ideal factor levels for achieving the highest lipid production by the Y-SL7 strain (Fig. 2 ). This figure illustrates the effects of OMW concentration and pH on lipid yield when the nitrogen concentration is maintained at its midpoint (1.5 g/L). Notably, an increase in OMW concentration, accompanied by a slight increase in pH, is consistently associated with an increase in lipid production. Consequently, the predicted response 𝑌 varies from 0.4 to 2.3 g/L of lipids. Nonetheless, raising the nitrogen concentration at low initial OMW levels does not enhance lipid yield. For lipid accumulation in yeast cells to occur, a high carbon concentration is necessary, resulting in an elevated carbon-to-nitrogen (C/N) ratio. The increase in OMW concentration is inherently associated with higher levels of phenolic compounds, which can be detrimental to microbial growth. Unlike many other microorganisms, yeasts are better suited to tolerate high phenolic compound concentrations and low pH levels found in mill wastes, enabling them to thrive in such challenging environments [ 60 ]. In several cases, increasing the initial OMW concentration does not inhibit microbial growth or lipid synthesis. Arous et al. [ 28 ] showed that bioconversion performance was unaffected even at a 75% OMW concentration with high phenolic compound levels, and the growth of Candida pararugosa BM24 was similar in both 50% diluted and undiluted OMW conditions. Similarly, Dias et al. [ 15 ] demonstrated that C. tropicalis ATCC 750 tolerated all tested OMW concentrations (5–50%). An increase in phenolic compounds to 2.4 g/L, resulting from a 50% (v/v) OMW concentration, did not inhibit yeast growth. Moreover, a 1.6-fold increase in cellular growth was observed when the OMW concentration was raised from 5–15%. In some cases, however, a higher OMW concentration can lead to increased phenolic compounds that negatively affect microbial growth and bioconversion. For instance, the accumulation of phenolic compounds in the medium can reach up to 4.5 g/L with higher OMW volumes, which results in a decrease in the maximum biomass yield of Y. lipolytica strains [ 49 , 50 , 61 ]. On the other hand, pH is a crucial factor in the bioconversion process, particularly when using OMW as a substrate. The pH of the fermentation medium influences not only the solubility of certain nutrients but also the permeability of the cell membrane, thereby affecting cellular development [ 62 ]. Previous studies have shown that slightly acidic pH levels enhance lipid production in oleaginous yeasts cultivated on OMW as a carbon source. In fact, the total reduction of sugars, phenols, and chemical oxygen demand (COD) was statistically improved when the cultures were conducted at a pH range of 5 to 6 [ 13 , 55 ] Additionally, an acidic pH can promote the assimilation of phenolic compounds and increase biomass yield. For example, in a solid acidic medium (pH 5.5), R. mucilaginosa was found to be capable of growing and efficiently assimilating simple aromatic compounds such as protocatechuic acid, p-coumaric acid, tyrosol and vanillic acid [ 47 ]. Furthermore, when OMW was used in the culture media of the same yeast strain, chemical oxygen demand (COD) and phenolic compounds were reduced by 56.9% and 34.8%, respectively [ 47 ]. The optimal levels for the independent variables X1, X2, and X3 (OMW, nitrogen, and pH) were determined to be 62%, 2.2 g/L, and pH 5.9, respectively, through further data analysis using the Nemrod-W software, based on the results from Fig. 2 . The corresponding experiment was conducted in four replicates, and the average lipid yield was calculated. The experimental lipid yield was approximately 2.5 g/L, which represents about 40% of the total lipid yield, while the predicted yield was 2.8 g/L. This outcome highlights the model's accuracy in reflecting the experimental results. Under optimal conditions, the elimination rate of phenolic compounds was 58%. The results demonstrate that optimizing fermentation parameters can lead to improved lipid production while minimizing undesirable compounds, thus improving the overall potential of OMW as a feedstock for bioprocessing applications. Table 4 presents a compilation of oleaginous yeasts cultivated on OMW as the sole carbon source or supplemented with additional substrates such as glycerol, glucose, and xylose. In most cases, cultures were conducted in flasks with various nitrogen sources (mineral, organic, or mixed). When OMW is used as a feedstock, lipid production by oleaginous yeasts remains relatively low, even when the medium is enriched with nutritional supplements. This underscores the recalcitrant nature of this waste and the environmental importance of its treatment. In certain cases, controlled fermentation in a bioreactor enhances lipid and biomass production, typically accompanied by a significant reduction in phenolic compounds. When cultivated in bioreactors, Y. lipolytica strains A6 and S11 exhibited high lipid accumulation (25%), particularly when OMW was supplemented with 50 g/L of glycerol. This was also associated with OMW detoxification, reaching levels of up to 30% [ 13 ]. Table 4 Strains Raw material Nitrogen source Biomass (g/L) Lipid (g/L) Phenolic compound remouved (%) Decolorization (%) Reference S. etchellsii M2 C. pararugosa BM24 75% OMW NH 4 Cl 15.11 21.68 0.42 1.08 15.4 19.2 - [ 28 ] C. tropicalis ATCC 750 50% OMW NH 4 Cl - 2.5 39 - [ 15 ] C. curvatus ATCC 20509 60% OMW + xylose (100 g/L) YE + Peptone 20.9–27 1.6–8.4 25–28 25 [ 14 ] L. starkeyi DSM 702096 25–100% OMW Without 3.2–11.1 0.7–3.2 43–53 - [ 12 ] Y. lipolytica ACA-DC 5029 OMW + Crude glycerol (70g/L) Peptone + YE 10 2 10 30 [ 50 ] Y. lipolytica ACA-YC 5033 OMW + glucose (35 g/L) YE + (NH 4 ) 2 SO 4 9.1 1 51 58 [ 61 ] Y. lipolytica L2 KF156787 25% OMW YE + Casein peptone 8 1.5 - 90 [ 1 ] R. glutinis DSM 70398 25–100% OMW Urea 1.97–7.93 0.1–0.64 40-93.5 - [ 53 ] R. babjevae Y-SL7 75% OMW YE + (NH 4 ) 2 SO 4 6.2 2.5 58 12 This work Fatty acid composition and biodiesel characterization The lipid profile of R. babjevae Y-SL7 during OMW fermentation process was determined using GC/MS analysis. Figure 3 illustrates the fatty acid (FA) composition of the extracted lipids from the Y-SL7 strain cultivated on both OMW and glucose. The analysis revealed similarities in the fatty acid composition of lipids produced from OMW compared to those produced from glucose. In both profiles, oleic acid (C18:1) was the most abundant lipid component (69.8% and 66.6%, respectively), followed by palmitic acid (C16:0) (23.1% and 18.9%, respectively). The main difference lies in the fact that lipids produced from OMW contain 3.9% palmitoleic acid (C16:1), while stearic acid (C18:0), accounting for 8.2%, was identified as the third most abundant fatty acid in the lipids produced from glucose. The distribution of FAs in the lipids accumulated by L. starkeyi grown on OMW reveals a similar profile to that of Y-SL7 strain, with the two predominant FAs being oleic acid (C18:1, 49.1%) and palmitic acid (C16:0, 19.1%). However, the lipids produced by L. starkeyi contained a significant amount of linoleic acid (C18:2, 18.8%) [ 12 ]. In a study by Dias et al. [ 15 ], comparable results were observed regarding saturated and unsaturated fatty acids, but a higher quantity of polyunsaturated FAs was noted, reaching 12.9% in lipids produced by C. tropicalis ATCC when cultivated on OMW at pH 5.5. Similar findings [ 28 ] were reported for oleaginous yeast strains, including C. pararugosa BM24 and S. etchellsii M2. Differences in the lipid profiles of yeasts derived from OMW fermentation can be attributed to variations in the physicochemical composition of the OMW used and the nature of its residual fatty acids. It's worth emphasizing that lipid accumulation in oleaginous yeasts generally follows two distinct metabolic pathways: de novo synthesis induced by hydrophilic substrates and ex novo synthesis primarily triggered by the presence of hydrophobic compounds [ 63 ]. Given that OMW contains both hydrophilic (sugars) and hydrophobic (residual fatty acids and olive oil residues) compounds, this suggests that lipid synthesis by yeasts under these conditions may occur via both pathways simultaneously, which could explain the observed differences. For biodiesel production, lipids with a high degree of monounsaturation are advantageous, as they improve the economic viability of the transesterification process by lowering the optimal reaction temperature and enhancing triglyceride conversion [ 64 ]. The theoretical characterization of Y-SL7-OMW biodiesel was performed using Biodiesel Analyser software [ 41 ], with key properties summarized in Table 5 , alongside U.S. standards (ASTM D-6751). Y-SL7-OMW biodiesel has a cetane number of 52.54, meeting the standard minimum of 47. This number indicates the ignition quality of diesel fuel and its ability to self-ignite in an engine [ 65 ]. The iodine index, another important parameter, should be 120 or lower; Y-SL7 biodiesel meets this requirement with a value of 75.71. The iodine value significantly affects biodiesel's cold filter clogging point and oxidation stability [ 66 ]. Kinematic viscosity, which influences the potential for engine deposits, was also examined. This biodiesel aligns with standards, showing a kinematic viscosity of 1.59 mm 2 /s. Both kinematic viscosity and density depend on methyl ester content, the feedstock used, and any contaminants (such as methanol) [ 66 ]. However, the density slightly exceeds the maximum limit of 0.99 g/cm 3 . Overall, the lipids extracted from R. babjevae grown on OMW are considered appropriate for biodiesel production. Table 5 Properties Y-SL7 biodiesel Standard Cetane number 52.54 ≥ 47 Iodine value 75.71 120 max Saponification value 234.51 - Kinematic viscosity (mm2 s − 1 ) 1.59 1.6–6 Density (g cm 3 ) 0.99 0.87–0.89 Carotenoids production and identification Alongside lipid production, R. babjevae Y-SL7 also synthesizes carotenoids, which contribute to the red coloration of the cells and possess antioxidant properties [ 40 ]. The optimal conditions identified for lipid production (62% OMW, 2.2 g/L nitrogen, and a pH of 5.9) were also evaluated for carotenoid synthesis. Under these conditions, the R. babjevae Y-SL7 strain produced 4.8 mg/L of carotenoids. This result demonstrates that OMW-based media could effectively serve as an inducer for carotenoid production. R. babjevae Y-SL7 has previously been shown to produce carotenoids on various substrates such as glucose, xylose, crude glycerol, and even acid wheat bran hydrolysate (AWBH), with yields ranging from 1.8 to 6.2 mg/g [ 40 , 67 ]. These values surpass previous reports for the same species isolated from soil and grown on synthetic media, which yielded 189.2 µg/g [ 68 ]. Nonetheless, the carotenoid production observed is comparable to the values reported by Sharma and Ghoshal [ 69 ] when optimizing R. mucilaginosa growth on various agro-industrial waste substrates. Similarly, Ghilardi et al. [ 70 ] reported that the highest total carotenoid production (7.3 ± 0.6 mg/L) was achieved when R. mucilaginosa was cultivated on OMW, with a carotenoid profile predominantly consisting of torulene and torularhodin. The Rhodotorula genus is recognized for its important carotenoids, such as β-carotene, γ-carotene torulene, and torularhodin. The relative abundance of these carotenoids can fluctuate considerably, depending on the growth conditions and the specific yeast strain used [ 71 ]. In this regard, RP-HPLC analysis was performed to identify and quantify the pigments produced by the Y-SL7 strain during its growth on OMW. The results showed two prominent peaks with retention times of 7.92 and 11.35 min (Fig. 4 a). To identify these peaks, commercial standards of β-carotene, as well as purified torulene and torularhodin, were used (standard preparation is illustrated in Fig. S2 of the supplementary material). The chromatographic results demonstrated that the pigment composition from the Y-SL7 strain primarily included torulene (68.26%) and torularhodin (31.7%). When cultivated on crude glycerol, R. babjevae Y-SL7 exhibited a similar carotenoid profile, primarily consisting of 63.7% torularhodin and 36.3% torulene [ 40 ]. However, when AWBH was used as the sole carbon source, in addition to torulene (51%) and torularhodin (36%), a small amount of β-carotene was detected, accounting for approximately 9.0% [ 67 ]. Carotenoids are recognized for their antioxidant properties, protecting cellular membranes from photo-oxidative damage by neutralizing oxygen and peroxyl radicals [ 72 ]. The total antioxidant activity of carotenoids extracted from the Y-SL7 strain was evaluated through DPPH radical scavenging and ABTS assays. The antioxidant effectiveness (EC50) of these carotenoids was compared to ascorbic acid, used as a control (Fig. 4 b). Y-SL7 carotenoids exhibited significantly higher DPPH scavenging activity ( P < 0.05). However, in the ABTS assay, their activity was lower than that of the control, as ABTS is generally more suitable for assessing hydrophilic compounds [ 73 ]. Torulene and torularhodin both feature a β-ionone ring and the structural framework of vitamin A, which makes them potential vitamin A precursors. Their enhanced antioxidant activity, compared to β-carotene, can be attributed to the presence of additional conjugated double bonds at the C13 position [ 72 ]. On the other hand, the antimicrobial activity of OMW-derived carotenoids was investigated against S. aureus (Gram-positive), as well as S. Enteritidis and E. coli (Gram-negative) bacteria. Figure 4 c shows that these carotenoids exert antiproliferative effects on the tested bacteria, with MIC values ranging from 0.1 mg/mL for S. aureus to 0.7 mg/mL for E. coli (The antibacterial effect of Y-CL7 against S. aureus with increasing concentrations is shown in Fig. S3 of the supplementary material). The antimicrobial potential of carotenoids extracted from the Rhodotorula genus has been previously reported in various studies [ 74 – 76 ]. It has been demonstrated that antibacterial activity is more pronounced in carotenoid extracts rich in torularhodin, which is particularly effective against Gram-positive bacteria [ 76 ]. The biological activities associated with these natural molecules position them as attractive candidates for diverse applications, such as feed additives in the food industry and protective agents in cosmetic and health products. To establish an efficient multi-metabolite production process, it is essential to understand cellular metabolic trade-offs, as achieving the right balance between competing metabolic pathways can significantly enhance both metabolite yield and process stability. Triglycerides and carotenoids, for instance, share several metabolic precursors and pathways. In Rhodotorula species, carotenoid biosynthesis can compete with lipid synthesis for common intermediates such as acetyl-CoA and fatty acids [ 18 ]. Despite this overlap, each class of metabolites is synthesized by distinct enzyme families and regulated through specific biosynthetic mechanisms. For carotenoid biosynthesis, Rhodotorula derives acetyl-CoA primarily through glycolysis, which is subsequently channelled into the mevalonate pathway to produce isopentenyl pyrophosphate (IPP), a key precursor in carotenoid synthesis [ 77 ]. This metabolic competition exemplifies the inherent trade-offs in cellular resource allocation, where carbon flux must be distributed among various biosynthetic demands. Moreover, carotenoid synthesis is closely linked to the cell’s oxidative stress response, as these pigments require fatty acids for their formation. These fatty acids could otherwise be used for other cellular functions such as triglyceride synthesis, which supports energy storage and membrane structure. In a study by Peng et al. [ 78 ], the biosynthesis of carotenoids and triglycerides in R. diobovata and R. babjevae was shown to follow similar kinetic patterns, suggesting coordinated regulation. Carbon balance analysis of R. babjevae cultures revealed that approximately 68% of the substrate carbon was directed toward biomass formation, 23.5% toward triglyceride synthesis, and 4.4% toward carotenoid production. These findings highlight the cell’s metabolic prioritization and underscore the importance of optimizing culture conditions to enable balanced co-production of multiple high-value metabolites. Conclusion This study underscores the significant potential of using OMW as a sustainable and renewable feedstock for bioconversion into microbial lipids through oleaginous yeast fermentation. The selected strain, R. babjevae Y-SL7, demonstrated exceptional lipid accumulation capacity while efficiently detoxifying phenolic compounds in OMW, achieving a notable reduction in these toxic components. The fatty acid profile of the lipids produced, characterized by a high proportion of oleic acid, supports their suitability for biodiesel production, aligning with global efforts to develop greener alternatives to fossil fuels. Beyond lipid production, the bioconversion process also yielded valuable carotenoids, predominantly torulene and torularhodin, which exhibited potent antioxidant and antibacterial properties. This co-production not only enhances the economic feasibility of the process but also positions it as a promising avenue for generating multifunctional bio-based products. Furthermore, this approach addresses the dual challenge of mitigating the environmental impact of OMW, a by-product of the olive oil industry, and creating high-value bioproducts from waste. The ability of Y-SL7 to efficiently utilize OMW underscores its potential as a cornerstone in sustainable biotechnological applications. By integrating waste valorization with biofuel and bioactive compound production, this process offers an eco-friendly alternative to traditional OMW treatment methods, contributing to the advancement of circular economy principles and sustainable industrial practices Declarations Appendix A. Supplementary data Supplementary data associated with this article can be found in e-version of this paper online Acknowledgements We would like to express our gratitude to the entire team at the CBS Unit of Analysis in the Centre of Biotechnology of Sfax, Tunisia, for their assistance with the analytical work. A special thanks to Mr. Slim Loukil, engineer at LBPE-CBS, for his invaluable help in OMW characterization. CRediT authorship contribution statement Ines Ayadi: Achievement of manipulations, Methodology and Writing-Original draft preparation. Ali Gargouri: Validation, Project administration and Supervision. Mohamed Guerfali: Conceptualization, Methodology, Software, Data curation and Writing-Reviewing and Editing. Funding This work was financially supported by the Ministry of Higher Education and Scientific Research, Tunisia, through the Contract Program allocation (2023–2026) granted to the Laboratory of Molecular Biotechnology of Eukaryotes (LR15CBS02). 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Lett. 368, fnab126 (2021). https://doi.org/10.1093/femsle/fnab126 Supplementary Files GA.tif SM.pdf Cite Share Download PDF Status: Published Journal Publication published 02 Jun, 2025 Read the published version in Waste and Biomass Valorization → Version 1 posted Editorial decision: Accept 19 May, 2025 Reviewers agreed at journal 24 Apr, 2025 Reviewers invited by journal 20 Apr, 2025 Editor invited by journal 20 Apr, 2025 Editor assigned by journal 17 Apr, 2025 First submitted to journal 16 Apr, 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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Also discoverable on Platform About Our Team In Review Editorial Policies Advisory Board Help Center Resources Author Services Accessibility API Access RSS feed Manage Cookie Preferences © Research Square 2026 | ISSN 2693-5015 (online) Privacy Policy Terms of Service Do Not Sell My Personal Information {"props":{"pageProps":{"initialData":{"identity":"rs-5965608","acceptedTermsAndConditions":true,"allowDirectSubmit":false,"archivedVersions":[],"articleType":"Research Article","associatedPublications":[],"authors":[{"id":445282639,"identity":"79231cb4-e272-43b0-81cd-f2eacbb0739d","order_by":0,"name":"Ines Ayadi","email":"","orcid":"","institution":"Centre de Biotechnologie de Sfax","correspondingAuthor":false,"prefix":"","firstName":"Ines","middleName":"","lastName":"Ayadi","suffix":""},{"id":445282640,"identity":"607afca4-370f-408c-9e9b-960db644e6f8","order_by":1,"name":"Ali Gargouri","email":"","orcid":"","institution":"Centre de Biotechnologie de Sfax","correspondingAuthor":false,"prefix":"","firstName":"Ali","middleName":"","lastName":"Gargouri","suffix":""},{"id":445282641,"identity":"c5d347e1-37b7-4f07-bfd3-02b9c93b7067","order_by":2,"name":"Mohamed Guerfali","email":"data:image/png;base64,iVBORw0KGgoAAAANSUhEUgAAAZAAAAAyAQMAAABI0h/eAAAABlBMVEX///8AAABVwtN+AAAACXBIWXMAAA7EAAAOxAGVKw4bAAABE0lEQVRIie3RPUvDQBjA8UcO2uWBrCcR8wmEKweHEqFfw7EQaJeLXTt0iEuzVOd8GIcLgXQ5nQM6CELmoOAiFHOUgMNpOhZ6f8Jxubsf5AXA5TrI0AxkN1/AJXq7lX2JBoqnCXYbZD8CTPWQi/Q+/6gWIQQ3UdmoJT3jm6eiOXl8nY/BK98sROjnyJd6BqNqGmWqpCj07ZRCXV+tgQyZjVSS+fGqgFEmOWkGLalQAKiCtQ82oHbCv+OtIfNPUFuKPEPe9BDhx0kBAZUE8hVFZq5/idYilOUMGdYc8geK1LzLxJCCCCvZrPmLXIbnQRq9g/q6Hntp+8WalgzTu9pGupCp37cTM/z1J7uCpOeAy+VyHW8/0wlcpOjU6sMAAAAASUVORK5CYII=","orcid":"https://orcid.org/0000-0002-0594-6343","institution":"Centre of Biotechnology of Sfax: Centre de Biotechnologie de Sfax","correspondingAuthor":true,"prefix":"","firstName":"Mohamed","middleName":"","lastName":"Guerfali","suffix":""}],"badges":[],"createdAt":"2025-02-05 12:16:26","currentVersionCode":1,"declarations":"","doi":"10.21203/rs.3.rs-5965608/v1","doiUrl":"https://doi.org/10.21203/rs.3.rs-5965608/v1","draftVersion":[],"editorialEvents":[{"content":"https://doi.org/10.1007/s12649-025-03131-4","type":"published","date":"2025-06-02T15:57:27+00:00"}],"editorialNote":"","failedWorkflow":false,"files":[{"id":81203550,"identity":"a5308bf6-cd89-4872-a63c-ded1ff611dd2","added_by":"auto","created_at":"2025-04-23 11:47:22","extension":"png","order_by":1,"title":"Figure 1","display":"","copyAsset":false,"role":"figure","size":1807635,"visible":true,"origin":"","legend":"\u003cp\u003e\u003cstrong\u003e(a) \u003c/strong\u003eCell mass, lipid production, and lipid content of different oleaginous yeast strains cultivated for 144 h on glucose (Glc) and OMW-based media. \u003cstrong\u003e(b) \u003c/strong\u003eCorresponding detoxification and decolorization rates (for OMW).\u003c/p\u003e","description":"","filename":"Figure1.png","url":"https://assets-eu.researchsquare.com/files/rs-5965608/v1/7f95f992ecba3f6ab446e200.png"},{"id":81204129,"identity":"9c130475-eee3-485f-8587-1a7c41404f87","added_by":"auto","created_at":"2025-04-23 11:55:22","extension":"png","order_by":2,"title":"Figure 2","display":"","copyAsset":false,"role":"figure","size":5631322,"visible":true,"origin":"","legend":"\u003cp\u003eResponse surface and contour plots illustrating the combined effects of OMW concentration (X\u003csub\u003e1\u003c/sub\u003e) and pH (X\u003csub\u003e3\u003c/sub\u003e) on lipid yield of \u003cem\u003eRhodotorula babjevae\u003c/em\u003e Y-SL7 at constant nitrogen concentration.\u003c/p\u003e","description":"","filename":"Figure2.png","url":"https://assets-eu.researchsquare.com/files/rs-5965608/v1/0b325a0c7a03894d00578aa7.png"},{"id":81203555,"identity":"e6341c98-753f-44b3-83c3-539f9e8c27ad","added_by":"auto","created_at":"2025-04-23 11:47:23","extension":"png","order_by":3,"title":"Figure 3","display":"","copyAsset":false,"role":"figure","size":772500,"visible":true,"origin":"","legend":"\u003cp\u003eFatty acid composition (%) of lipids extracted from \u003cem\u003eRhodotorula babjevae\u003c/em\u003eY-SL7 cultivated on glucose and OMW-based media.\u003c/p\u003e","description":"","filename":"Figure3.png","url":"https://assets-eu.researchsquare.com/files/rs-5965608/v1/6fd92d01a2bdc93a6812c328.png"},{"id":81203552,"identity":"b2ca250c-b9b9-4857-a75a-d7c00830cc6a","added_by":"auto","created_at":"2025-04-23 11:47:22","extension":"png","order_by":4,"title":"Figure 4","display":"","copyAsset":false,"role":"figure","size":4510592,"visible":true,"origin":"","legend":"\u003cp\u003e\u003cstrong\u003e(a) \u003c/strong\u003eRP-HPLC chromatogram displaying carotenoid identification from \u003cem\u003eRhodotorula babjevae\u003c/em\u003e Y-SL7. \u003cstrong\u003e(b)\u003c/strong\u003e antioxidant and antibacterial \u003cstrong\u003e(c) \u003c/strong\u003eproperties of carotenoids obtained from \u003cem\u003eRhodotorula babjevae\u003c/em\u003eY-SL7. For antibacterial and antioxidant activities: ± Standard deviation of three replicates; Values with a different letter are significantly different (\u003cem\u003eP\u003c/em\u003e \u0026lt; 0.05) (Tukey’s test).\u003c/p\u003e","description":"","filename":"Figure4.png","url":"https://assets-eu.researchsquare.com/files/rs-5965608/v1/de2d7c989f964e94562de378.png"},{"id":84242574,"identity":"082c8a37-bcca-4a39-a866-b9ee54482ac9","added_by":"auto","created_at":"2025-06-09 16:09:45","extension":"pdf","order_by":0,"title":"","display":"","copyAsset":false,"role":"manuscript-pdf","size":12785764,"visible":true,"origin":"","legend":"","description":"","filename":"manuscript.pdf","url":"https://assets-eu.researchsquare.com/files/rs-5965608/v1/e0feaebd-c22f-446d-bb03-6b1208c94e57.pdf"},{"id":81203556,"identity":"802d76e8-5a1c-4571-a58e-0f4732e5e93a","added_by":"auto","created_at":"2025-04-23 11:47:23","extension":"tif","order_by":1,"title":"","display":"","copyAsset":false,"role":"supplement","size":11050636,"visible":true,"origin":"","legend":"","description":"","filename":"GA.tif","url":"https://assets-eu.researchsquare.com/files/rs-5965608/v1/70257a0687d19271c8cc5e99.tif"},{"id":81203557,"identity":"be6b2df2-0396-4830-aa47-36a631e6c4d1","added_by":"auto","created_at":"2025-04-23 11:47:23","extension":"pdf","order_by":2,"title":"","display":"","copyAsset":false,"role":"supplement","size":238812,"visible":true,"origin":"","legend":"","description":"","filename":"SM.pdf","url":"https://assets-eu.researchsquare.com/files/rs-5965608/v1/fd65460c31e0617dc304ad06.pdf"}],"financialInterests":"","formattedTitle":"Sustainable Valorization of Olive Mill Wastewater via Oleaginous Yeasts: Single-Cell Oil Production and Effluent Detoxification","fulltext":[{"header":"Introduction","content":"\u003cp\u003eThe global drive for sustainable and eco-friendly fuel alternatives has gained momentum as fossil fuel reserves dwindle and environmental concerns, particularly atmospheric contamination and climate instability, become more pressing. Biodiesel emerges as a viable contender due to its biodegradable, renewable, and non-toxic properties [\u003cspan citationid=\"CR1\" class=\"CitationRef\"\u003e1\u003c/span\u003e, \u003cspan citationid=\"CR2\" class=\"CitationRef\"\u003e2\u003c/span\u003e]. However, the production of biodiesel from both edible and non-edible agricultural biomass, as well as animal fats, poses significant challenges, including competition for food resources, the large land area required, and concerns over animal feed. On the other hand, oils derived from oleaginous microorganisms, specifically single-cell oils (SCOs), offer a promising and sustainable feedstock for biodiesel production. This conversion process is achieved through a simple transesterification reaction with methanol, using either an acid or alkaline catalyst, resulting in fatty acid methyl esters and glycerol as by-products [\u003cspan citationid=\"CR2\" class=\"CitationRef\"\u003e2\u003c/span\u003e]. To unlock the full potential of SCOs as a sustainable biofuel source, ongoing research must focus on refining production methods to increase both yield and biodiesel quality. Additionally, cost-effective and scalable techniques for SCO production and extraction are critical to making this technology economically viable. Overall, leveraging oleaginous microorganisms for biodiesel production offers an innovative solution to the limitations of traditional biofuels and plays a key role in advancing toward a more sustainable energy landscape [\u003cspan citationid=\"CR3\" class=\"CitationRef\"\u003e3\u003c/span\u003e].\u003c/p\u003e \u003cp\u003eCertain microorganisms, including microalgae, bacteria, filamentous fungi, and yeasts, can synthesize and accumulate considerable amounts of intracellular lipids, often exceeding 20% of their dry biomass [\u003cspan citationid=\"CR4\" class=\"CitationRef\"\u003e4\u003c/span\u003e]. In yeasts, lipid content varies by species and can reach as much as 70% under specific nutrient-limited conditions. Lipid accumulation, particularly the synthesis of TAGs, is triggered when non-carbon nutrients such as magnesium, zinc, iron, phosphorus, and especially nitrogen availability is restricted in the microbial medium [\u003cspan citationid=\"CR5\" class=\"CitationRef\"\u003e5\u003c/span\u003e]. The predominant lipids synthesized by oleaginous microorganisms are triglycerides (around 80%) and sterol esters (about 20%), with triglycerides acting as the main energy reserve and sterol esters contributing to membrane stability [\u003cspan citationid=\"CR6\" class=\"CitationRef\"\u003e6\u003c/span\u003e]. Yeasts offer several advantages over other microorganisms: they can grow rapidly to high densities with substantial lipid yields, their cultures are simpler to scale up, and they can be genetically engineered to enhance production and develop tailored lipids. Of the known yeast species, only about 5% are classified as oleaginous, including genera such as \u003cem\u003eRhodotorula\u003c/em\u003e, \u003cem\u003eYarrowia\u003c/em\u003e, \u003cem\u003eCryptococcus\u003c/em\u003e, \u003cem\u003eCandida\u003c/em\u003e, \u003cem\u003eLipomyces\u003c/em\u003e, and \u003cem\u003eTrichosporon\u003c/em\u003e [\u003cspan citationid=\"CR7\" class=\"CitationRef\"\u003e7\u003c/span\u003e]. Oleaginous yeasts can utilize various renewable and low-cost resources, including lignocellulosic materials [\u003cspan citationid=\"CR8\" class=\"CitationRef\"\u003e8\u003c/span\u003e], oily wastes [\u003cspan citationid=\"CR9\" class=\"CitationRef\"\u003e9\u003c/span\u003e], municipal organic wastes [\u003cspan citationid=\"CR10\" class=\"CitationRef\"\u003e10\u003c/span\u003e], crude glycerol [\u003cspan citationid=\"CR11\" class=\"CitationRef\"\u003e11\u003c/span\u003e], and olive mill wastewaters [\u003cspan additionalcitationids=\"CR13 CR14\" citationid=\"CR12\" class=\"CitationRef\"\u003e12\u003c/span\u003e\u0026ndash;\u003cspan citationid=\"CR15\" class=\"CitationRef\"\u003e15\u003c/span\u003e]. This versatility makes yeasts both economically and environmentally attractive. Furthermore, these microorganisms can simultaneously produce valuable compounds such as enzymes [\u003cspan citationid=\"CR15\" class=\"CitationRef\"\u003e15\u003c/span\u003e], carotenoids [\u003cspan citationid=\"CR16\" class=\"CitationRef\"\u003e16\u003c/span\u003e], organic acids [\u003cspan citationid=\"CR17\" class=\"CitationRef\"\u003e17\u003c/span\u003e] and polyol esters of fatty acids [\u003cspan citationid=\"CR18\" class=\"CitationRef\"\u003e18\u003c/span\u003e], thereby enhancing their commercial significance. However, the commercialization of microbial lipid production remains limited by high costs, primarily driven by the price of fermentation substrates. Therefore, selecting robust yeast strains capable of thriving under extreme conditions and efficiently converting industrial wastes is crucial for developing lipid production methods for bioenergy applications. Additionally, developing innovative solutions for cost-effective and sustainable feedstocks and optimizing production processes are key to advancing yeast-based lipid production and promoting a sustainable biofuel industry.\u003c/p\u003e \u003cp\u003eMediterranean countries dominate global olive oil production, accounting for approximately 95% of the total output [\u003cspan citationid=\"CR17\" class=\"CitationRef\"\u003e17\u003c/span\u003e]. Olive mill wastewater (OMW), a by-product of this industry, is generated in varying quantities depending on the extraction method and the maturity of the olives. The three-phase olive oil extraction process, in particular, requires significant water inputs, resulting in a larger volume of wastewater compared to traditional or two-phase methods [\u003cspan citationid=\"CR19\" class=\"CitationRef\"\u003e19\u003c/span\u003e]. Consequently, OMW constitutes a significant waste output, generating between 1.2 and 1.8 cubic meters of wastewater for every ton of olives processed [\u003cspan citationid=\"CR20\" class=\"CitationRef\"\u003e20\u003c/span\u003e]. This complex effluent is characterized by a reddish-brown color, cloudy appearance, a strong olive oil scent, and high electrical conductivity due to its mineral content. Its composition is influenced by the olive variety and the extraction technique, consisting mainly of water (83\u0026ndash;92%), organic matter such as polysaccharides, proteins, organic acids, phenols, and lipids (4\u0026ndash;16%), and minerals (0.4\u0026ndash;2.5%) [\u003cspan citationid=\"CR21\" class=\"CitationRef\"\u003e21\u003c/span\u003e]. OMW presents significant management challenges due to its high concentrations of phenolic compounds, chemical oxygen demand (COD) and biological oxygen demand (BOD), which commonly exceed 80 g/L, 100 g/L and 200 g/L, respectively [\u003cspan citationid=\"CR22\" class=\"CitationRef\"\u003e22\u003c/span\u003e]. Currently, the disposal and management of OMW remain problematic in many producing regions. Traditional disposal methods, such as land spreading, evaporation ponds, and direct discharge into water bodies or agricultural lands, are still widely practiced despite their environmental drawbacks. These methods can lead to groundwater contamination, soil degradation, and the accumulation of phytotoxic compounds, making them unsustainable over the long term [\u003cspan citationid=\"CR12\" class=\"CitationRef\"\u003e12\u003c/span\u003e, \u003cspan citationid=\"CR20\" class=\"CitationRef\"\u003e20\u003c/span\u003e]. Composting and anaerobic digestion are also explored, but they often require pre-treatment steps and do not always result in complete degradation of recalcitrant molecules, particularly phenolic compounds [\u003cspan citationid=\"CR21\" class=\"CitationRef\"\u003e21\u003c/span\u003e]. Therefore, the valorization of OMW through biotechnological processes represents an eco-friendly and circular alternative, transforming a pollutant into a resource. Numerous studies have focused on developing treatment methods for OMW, including physicochemical, thermochemical, and biological methods [\u003cspan additionalcitationids=\"CR24\" citationid=\"CR23\" class=\"CitationRef\"\u003e23\u003c/span\u003e\u0026ndash;\u003cspan citationid=\"CR25\" class=\"CitationRef\"\u003e25\u003c/span\u003e]. These treatments provide an opportunity to convert OMW into value-added products, including its use as a biopesticide, food supplies, precursor for hydrogen and biogas as well as for microbial enzymes production such as protease and lipase [\u003cspan citationid=\"CR15\" class=\"CitationRef\"\u003e15\u003c/span\u003e, \u003cspan citationid=\"CR23\" class=\"CitationRef\"\u003e23\u003c/span\u003e, \u003cspan citationid=\"CR26\" class=\"CitationRef\"\u003e26\u003c/span\u003e, \u003cspan citationid=\"CR27\" class=\"CitationRef\"\u003e27\u003c/span\u003e]. A particularly promising avenue is the production of microbial lipids through the cultivation of oleaginous microorganisms on OMW as a raw material [\u003cspan citationid=\"CR13\" class=\"CitationRef\"\u003e13\u003c/span\u003e]. Few oleaginous yeast strains belong to genera \u003cem\u003eLipomyces, Candida, Debaryomyces and Yarrowia\u003c/em\u003e have shown their effectiveness in OMW bioconversion and lipid production [\u003cspan citationid=\"CR12\" class=\"CitationRef\"\u003e12\u003c/span\u003e, \u003cspan citationid=\"CR13\" class=\"CitationRef\"\u003e13\u003c/span\u003e, \u003cspan citationid=\"CR14\" class=\"CitationRef\"\u003e14\u003c/span\u003e, \u003cspan citationid=\"CR28\" class=\"CitationRef\"\u003e28\u003c/span\u003e]. Therefore, selecting oleaginous yeasts that can resist and degrade polyphenolic compounds while efficiently bio-converting OMW is a critical step toward establishing an economically viable production process.\u003c/p\u003e \u003cp\u003eThis study aimed to explore the potential of novel oleaginous yeasts for the bioconversion of OMW into microbial lipids by characterizing this wastewater and evaluating its suitability as a carbon-rich substrate under various culture conditions. Additionally, it sought to optimize lipid accumulation and effluent detoxification through response surface methodology (RSM), providing a cost-effective and eco-friendly valorization strategy. Among the screened strains, \u003cem\u003eRhodotorula babjevae\u003c/em\u003e Y-SL7 was identified as particularly efficient in converting OMW into both lipids and carotenoid pigments. This bioconversion process offers a promising alternative for mitigating the environmental impact of OMW by reducing phenolic compound toxicity while generating valuable microbial products. The findings highlight the potential of oleaginous yeasts to support sustainable waste management and contribute to the development of renewable bioresources.\u003c/p\u003e"},{"header":"Materials and Methods","content":"\u003cdiv id=\"Sec3\" class=\"Section2\"\u003e \u003ch2\u003eRaw material and oleaginous yeast strains\u003c/h2\u003e \u003cp\u003eThe liquid by-product of olive oil production, OMW, was obtained from an olive mill in Sfax, Tunisia, which used a three-phase extraction technique. To remove suspended materials, the OMW was filtered and then centrifuged at 6000 rpm for 10 minutes, after which the supernatant was either used immediately as a substrate for oleaginous yeast cultivation or stored at -20\u0026deg;C for future use. The oleaginous yeast strains used in this study, including \u003cem\u003eCandida viswanathii\u003c/em\u003e Y-E4, \u003cem\u003eRodotorula babjevae\u003c/em\u003e Y-SL7, \u003cem\u003eYarrowia lipolytica\u003c/em\u003e Y-RC7, and \u003cem\u003eTrichosporon cutaneum\u003c/em\u003e CTM-30125, were previously isolated, characterized, and identified in our earlier research [\u003cspan citationid=\"CR29\" class=\"CitationRef\"\u003e29\u003c/span\u003e]. These strains have been deposited in the National Strains Collection (CTM) of the Center of Biotechnology of Sfax, CBS, Tunisia, under the accession numbers CTM-30136, CTM-30137, CTM-30139, and CTM-30125, respectively. The storage of all yeast strains was carried out at -80\u0026deg;C in a solution enriched with sterilized glycerol, containing 2% (w/v) glucose, 1% (w/v) yeast extract, 1% (w/v) bacto-peptone, and 20% (w/w) glycerol.\u003c/p\u003e \u003c/div\u003e\n\u003ch3\u003eCulture conditions\u003c/h3\u003e\n\u003cp\u003eThe oleaginous yeast strains were cultivated in 250 mL Erlenmeyer flasks containing a YPG preculture medium composed of 20 g/L glucose, 10 g/L bacto-peptone, and 10 g/L yeast extract. The flasks were incubated in a rotary shaker set to 30\u0026deg;C and 180 rpm for 24 hours. The resulting precultures were then used to inoculate the lipid production medium at a 5% (v/v) ratio, equivalent to an initial optical density (OD) of 0.2 at 600 nm. The lipid production medium consisted of a synthetic nitrogen-limited formulation containing 0.5 g/L yeast extract, 0.5 g/L (NH\u003csub\u003e4\u003c/sub\u003e)\u003csub\u003e2\u003c/sub\u003eSO\u003csub\u003e4\u003c/sub\u003e, 7 g/L KH\u003csub\u003e2\u003c/sub\u003ePO\u003csub\u003e4\u003c/sub\u003e, 2.5 g/L Na\u003csub\u003e2\u003c/sub\u003eHPO\u003csub\u003e4\u003c/sub\u003e, 1.5 g/L MgSO\u003csub\u003e4\u003c/sub\u003e\u0026middot;7H\u003csub\u003e2\u003c/sub\u003eO, 0.2 g/L CaCl\u003csub\u003e2\u003c/sub\u003e\u0026middot;2H\u003csub\u003e2\u003c/sub\u003eO, 0.07 g/L MnSO\u003csub\u003e4\u003c/sub\u003e\u0026middot;H\u003csub\u003e2\u003c/sub\u003eO, 0.01 g/L ZnSO\u003csub\u003e4\u003c/sub\u003e\u0026middot;7H\u003csub\u003e2\u003c/sub\u003eO, 0.01 g/L FeSO\u003csub\u003e4\u003c/sub\u003e\u0026middot;7H\u003csub\u003e2\u003c/sub\u003eO, and 0.0001 g/L CuSO\u003csub\u003e4\u003c/sub\u003e. Commercial glucose and OMW were used as carbon sources at concentrations of 40 g/L and 50% (v/v), respectively. All cultures were performed under identical conditions: the initial pH was adjusted to 6.0, and incubation was carried out at 30\u0026deg;C with an agitation rate of 180 rpm. After 144 hours of fermentation, the yeast cells were harvested by centrifugation at 3000\u0026times;g for 10 minutes. The collected cells were then washed with absolute ethanol and water to remove any residual substrate before being subjected to biomass quantification and lipid extraction. All experiments were conducted at least three times to ensure reproducibility.\u003c/p\u003e\n\u003ch3\u003eExperimental design and statistical analysis\u003c/h3\u003e\n\u003cp\u003eThe Box-Behnken model was utilized in this study to optimize the culture parameters for improved lipid production by \u003cem\u003eR. babjevae\u003c/em\u003e Y-SL7. The 3\u003csup\u003e3\u003c/sup\u003e Box-Behnken design enables the evaluation of potential quadratic interactions between pairs of factors, thus reducing the number of experiments required [\u003cspan citationid=\"CR30\" class=\"CitationRef\"\u003e30\u003c/span\u003e]. X\u003csub\u003e1\u003c/sub\u003e​ (OMW quantity), X\u003csub\u003e2\u003c/sub\u003e (nitrogen concentration), and X\u003csub\u003e3​\u003c/sub\u003e (pH) were chosen as independent variables. Each variable was tested at three coded levels (-1, 0, +\u0026thinsp;1). Lipid yield was linked to changes in OMW amount (30%, 50%, and 70%), nitrogen concentration (0.5, 1.5, and 2.5 g/L), and pH (4.0, 5.5, and 7.0). The experimental design consisted of 17 experiments, with the five at the center point utilized to assess experimental error and adjust the model. The data obtained from RSM regarding the response \u003cem\u003eŷ\u003c/em\u003e (lipid yield) were subjected to analysis of variance (ANOVA) to check for errors and the significance of each parameter. A multiple regression analysis was also conducted to obtain an empirical model that relates the measured response to the independent variables. The quadratic equation (Eq.\u0026nbsp;\u003cspan refid=\"Equ1\" class=\"InternalRef\"\u003e1\u003c/span\u003e) was utilized to model and interpret the system's behavior, enabling the prediction of optimal conditions:\u003cdiv id=\"Equ1\" class=\"Equation\"\u003e\u003cdiv format=\"TEX\" class=\"mathdisplay\" id=\"FileID_Equ1\" name=\"EquationSource\"\u003e\n$$\\:Y=\\:{{\\beta\\:}}_{0}+\\:\\sum\\:{{\\beta\\:}}_{i}{\\text{X}}_{i}+\\:\\sum\\:{{\\beta\\:}}_{ij}{\\text{X}}_{ij}+\\sum\\:{{\\beta\\:}}_{ii}{\\text{X}}_{i}^{2}$$\u003c/div\u003e\u003cdiv class=\"EquationNumber\"\u003e1\u003c/div\u003e\u003c/div\u003e\u003c/p\u003e \u003cp\u003eIn this equation, \u003cem\u003eY\u003c/em\u003e refers to the predicted lipid yield (response variable), X\u003csub\u003ei\u003c/sub\u003e represents the independent variables, β\u003csub\u003e0\u003c/sub\u003e is the intercept, β\u003csub\u003ei\u003c/sub\u003e are the linear term coefficients, β\u003csub\u003eij\u003c/sub\u003e indicates interaction terms, and β\u003csub\u003eii\u003c/sub\u003e represents quadratic effect terms. The statistical software package Nemrod-W, version 2000-D, was employed to perform regression analysis on the experimental data and to generate the response surface graphs [\u003cspan citationid=\"CR31\" class=\"CitationRef\"\u003e31\u003c/span\u003e]. The statistical significance of the model was determined by applying Fisher\u0026rsquo;s \u003cem\u003eF\u003c/em\u003e test. Furthermore, the iso-response contour plot was employed to illustrate the individual and combined effects of the variables, along with their potential correlations.\u003c/p\u003e\n\u003ch3\u003eLipids and carotenoids extraction\u003c/h3\u003e\n\u003cp\u003eThe microbial lipid extraction was carried out using the method of Dey and Maiti [\u003cspan citationid=\"CR7\" class=\"CitationRef\"\u003e7\u003c/span\u003e], with several modifications. A 100 mL culture sample was subjected to centrifugation at 3000\u0026times;g for 10 minutes, and the resulting cell pellet was washed twice with 50 mL each of distilled water and absolute ethanol to eliminate any traces of substrate. The washed cell pellet was then dried for 24 hours at 105\u0026deg;C. About 0.3 g of the dried biomass was mixed with 10 mL of HCl (4M) and stirred for 2 hours at 70\u0026deg;C. The acid-hydrolyzed cells were stirred with a chloroform-methanol mixture (1:1) for 3 hours at room temperature and centrifuged at 3000\u0026times;g for 10 minutes. The organic phase, which contains lipids, was carefully recovered and transferred to a new glass tube. Finally, 20% (v/v) of a 9 g/L NaCl solution was added to eliminate any remaining moisture, and the solvent was evaporated by sparging with nitrogen gas. The total lipid content was determined by the gravimetric method and expressed as the percentage (w/w) of the extracted lipids on the dry cell.\u003c/p\u003e \u003cp\u003eIntracellular carotenoids were extracted using dimethyl sulfoxide (DMSO), according to the procedure described by Taskin et al. [\u003cspan citationid=\"CR32\" class=\"CitationRef\"\u003e32\u003c/span\u003e]. Briefly, washed yeast cells were incubated with DMSO at a 2:1 ratio and incubated at 50\u0026deg;C for 30 minutes, with periodic vortexing to ensure complete homogenization. Acetone was then added to the DMSO-treated cells in a 1:2 (v/v) ratio, followed by additional vortexing and centrifugation until the cells were fully decolorized. The collected supernatants were pooled and diluted with a 0.9% NaCl solution (1:2 v/v). Carotenoids were subsequently extracted by adding petroleum ether at a 1:1 (v/v) ratio, and the colored phase was recovered. To prevent degradation, the solvent was evaporated under an inert atmosphere, and the resulting residue was re-suspended in acetone for analysis. Residual carotenoids were subsequently quantified using spectrophotometric analysis.\u003c/p\u003e\n\u003ch3\u003eAnalytical methods\u003c/h3\u003e\n\u003cdiv id=\"Sec8\" class=\"Section2\"\u003e \u003ch2\u003ePhysical and chemical characterization of OMW\u003c/h2\u003e \u003cp\u003eThe pH measurement was conducted at room temperature (25\u0026thinsp;\u0026plusmn;\u0026thinsp;0.5\u0026deg;C) using a Thermo Electron Corporation digital pH meter. The electrical conductivity was also measured at the same temperature using a conductivity meter and expressed in mS/cm. The dry weight of OMW was determined by drying 1 g at 105\u0026deg;C until a constant weight was reached. The ash content, representing the mineral matter, was determined following the ASTM D 1102-84 (Reapproved 1990) standard. This involved incinerating 1 g of dry biomass at 550\u0026deg;C for 3 hours. After that, the sample was cooled to ambient temperature in a desiccator, and the residual material was identified as the total ash, as described by Sluiter et al. [\u003cspan citationid=\"CR33\" class=\"CitationRef\"\u003e33\u003c/span\u003e]. The COD was determined using the method developed by Knechtel [\u003cspan citationid=\"CR34\" class=\"CitationRef\"\u003e34\u003c/span\u003e], in which the reagent potassium dichromate was used as a strong oxidizing agent with heating and in an acidic medium. The quantity of reagent consumed during the oxidation of the organic matter present was reported in mg/L of oxygen, which corresponds to the COD value. The biological oxygen demand (BOD) test is a method for determining the amount of biodegradable organic matter in a sample by measuring the oxygen consumption of microorganisms present in the sample. A measurable quantity of the sample is placed in a bottle that is connected to a mercury manometer. The depression in the manometer due to the consumption of oxygen by microorganisms corresponds to the BOD, which is expressed in mg/L. The carbon dioxide (CO\u003csub\u003e2\u003c/sub\u003e) produced by bacterial respiration is absorbed from the gaseous medium by potassium hydroxide (KOH) placed in the stopper. The BOD value is obtained by multiplying the depression by a correlation factor. The BOD5 value is expressed in mg/L after 5 days of incubation in the dark at a constant temperature of 20\u0026thinsp;\u0026plusmn;\u0026thinsp;1\u0026deg;C. The fat content in OMW was analyzed using a solvent-based extraction technique involving phase separation. A mixture of 10 mL of OMW and 20 mL of methanol-chloroform (1:1) was slowly stirred for 2 hours at room temperature. The organic phase was then collected and quantified using the same method as microbial lipid extraction. The decolorization of OMW was assessed by recording the absorbance at 525 nm for both inoculated and non-inoculated samples, as described by Aggelis et al. [\u003cspan citationid=\"CR35\" class=\"CitationRef\"\u003e35\u003c/span\u003e], using a Camspec M508 spectrophotometer (Spectronic Instruments Inc., U.K.). The concentration of total phenols in OMW was determined using the Folin-Ciocalteau reagent, as outlined by Singleton and Rossi [\u003cspan citationid=\"CR36\" class=\"CitationRef\"\u003e36\u003c/span\u003e]. 50 \u0026micro;L of OMW is mixed with 250 \u0026micro;L of the reagent and 500 \u0026micro;L of 20% sodium carbonate solution. After vortexing, the volume is adjusted to 5 mL with distilled water and the mixture is incubated for 30 minutes at room temperature. The optical density (OD) is measured at 727 nm, with distilled water used as a blank to adjust the zero. Nitrogen concentration in the OMW sample is determined using the Kjeldahl method [\u003cspan citationid=\"CR37\" class=\"CitationRef\"\u003e37\u003c/span\u003e]. Total sugars are determined by adding 1 mL of the sample, 1 mL of phenol (5%) and 5 mL of concentrated sulfuric acid and then incubating the mixture at room temperature for 10 minutes, followed by incubation at 30\u0026deg;C for 20 minutes. The orange-yellow color formed is measured at 488 nm using a spectrophotometer, and the corresponding glucose concentrations are determined from a calibration curve established earlier by Dubois et al. [\u003cspan citationid=\"CR38\" class=\"CitationRef\"\u003e38\u003c/span\u003e]. Residual glucose levels are quantified using the 3,5-Dinitrosalicylic acid (DNS) method, as detailed by Ichihara et al. [\u003cspan citationid=\"CR39\" class=\"CitationRef\"\u003e39\u003c/span\u003e].\u003c/p\u003e \u003c/div\u003e\n\u003ch3\u003eNeutral lipid composition and biodiesel characterization\u003c/h3\u003e\n\u003cp\u003eTo determine the complete fatty acid profile of microbial lipids, gas chromatography-mass spectrometry (GC/MS) was employed. Initially, 100 mg of the extracted lipids were dissolved in 2 mL of hexane and mixed with 0.2 mL of a 2 M methanolic KOH solution to produce fatty acid methyl esters (FAME). The mixture was vortexed thoroughly and incubated at room temperature for 15 minutes. Following this, the upper phase was separated and subjected to analysis using a gas chromatograph coupled to a 5975 B Inert MSD Mass-Selective Detector (Agilent Technologies, France). A 2 \u0026micro;L sample of FAME was introduced into the system through an HP-5MS Phenyl Methyl Siloxane capillary column (30 m \u0026times; 250 \u0026micro;m \u0026times; 0.25 \u0026micro;m nominal), with helium serving as the carrier gas at a steady flow rate of 1 mL/min. The injector and detector were set at temperatures of 250\u0026deg;C and 240\u0026deg;C, respectively. The temperature gradient was as follows: 120\u0026deg;C for 5 minutes, then ramped at 3\u0026deg;C/min to 180\u0026deg;C, further increased at 10\u0026deg;C/min to 220\u0026deg;C, and finally held at 220\u0026deg;C for 31 minutes [\u003cspan citationid=\"CR40\" class=\"CitationRef\"\u003e40\u003c/span\u003e]. The resulting data were analyzed using the NIST Mass Spectral Search program. For biodiesel characterization, the Biodiesel-Analyser software (Version 1.1, 2013) was used, which facilitates the prediction of biodiesel fuel properties based on the FAME profile of any oil feedstock, as determined via gas chromatography [\u003cspan citationid=\"CR41\" class=\"CitationRef\"\u003e41\u003c/span\u003e].\u003c/p\u003e\n\u003ch3\u003eCarotenoids identification\u003c/h3\u003e\n\u003cp\u003eFor individual carotenoid analysis, high performance liquid chromatography (HPLC) was employed, with a reversed-phase Eclipse XDB-C18 column (150 mm \u0026times; 4.6 mm, 5 \u0026micro;m) and a mobile phase consisting of (eluent A) acetonitrile and water (9:1 v/v) and (eluent B) ethyl acetate with 1% formic acid. The UV-visible adsorption spectrum was recorded at 501 nm with a flow rate of 0.8 mL/min, and the injection sample volume was 80 \u0026micro;L with a column temperature of 25\u0026deg;C [\u003cspan citationid=\"CR42\" class=\"CitationRef\"\u003e42\u003c/span\u003e]. Commercial β-carotene was used as a standard, and torulene and torularhodin standards were obtained after separation by thin layer chromatography (TLC) using silica gel 60 plates (F254, 20 \u0026times; 20 cm, Merck, Germany) and a solvent system of n-hexane and ethyl acetate (7:1). Chromatographed pigments were identified based on their flow rate (R\u003csub\u003e\u003cem\u003ef\u003c/em\u003e\u003c/sub\u003e).\u003c/p\u003e \u003cdiv id=\"Sec11\" class=\"Section2\"\u003e \u003ch2\u003eAntioxidant and antimicrobial activities\u003c/h2\u003e \u003cp\u003eColor degradation was assessed using two oxidant systems: (i) 2-diphenyl-1-picrylhydrazyl (DPPH) and (ii) 2,2'-azino-bis-(3-ethylbenzothiazoline-6-sulfonic acid) (ABTS). The DPPH method, as outlined by Brand-Williams et al. [\u003cspan citationid=\"CR43\" class=\"CitationRef\"\u003e43\u003c/span\u003e], was employed to determine the antioxidant activity of the extracted carotenoids, while the ABTS method, following Re et al. [\u003cspan citationid=\"CR44\" class=\"CitationRef\"\u003e44\u003c/span\u003e], was used for further evaluation.\u003c/p\u003e \u003cp\u003eTo determine the minimum inhibitory concentrations (MICs) of carotenoids from Y-SL7, the micro-dilution technique was applied against three bacterial strains. After incubation in Muller\u0026ndash;Hinton broth (MH) (Oxoid Ltd, UK), the assay was performed using the MTT colorimetric method, based on 3-(4,5-dimethyl-2-thiazolyl)-2,5-diphenyl-2H-tetrazolium bromide, in sterile 96-well microtiter plates [\u003cspan citationid=\"CR45\" class=\"CitationRef\"\u003e45\u003c/span\u003e]. The bacterial strains used were \u003cem\u003eStaphylococcus aureus\u003c/em\u003e ATCC 6538, \u003cem\u003eSalmonella enterica\u003c/em\u003e ATCC 14,028, and \u003cem\u003eEscherichia coli\u003c/em\u003e ATCC 8739, all obtained from international culture collections (ATCC).\u003c/p\u003e \u003c/div\u003e"},{"header":"Results and discussion","content":"\u003cdiv id=\"Sec13\" class=\"Section2\"\u003e \u003ch2\u003eOMW characterization\u003c/h2\u003e \u003cp\u003eOMW is known for its highly variable composition, which is influenced by a variety of factors such as the method of oil extraction, the level of fruit maturity, and the specific olive tree variety [\u003cspan citationid=\"CR17\" class=\"CitationRef\"\u003e17\u003c/span\u003e, \u003cspan citationid=\"CR46\" class=\"CitationRef\"\u003e46\u003c/span\u003e]. OMW is typically characterized by its acidic pH, high electrical conductivity, and significant amounts of sugars, lipids, proteins, and phenolic compounds. Given this variability, it is important to conduct a thorough biochemical characterization of OMW before using it as feedstock for microbial metabolites production.\u003c/p\u003e \u003cp\u003eThe newly collected OMW in this study had a slightly acidic pH of 5.36 (Table\u0026nbsp;\u003cspan refid=\"Tab1\" class=\"InternalRef\"\u003e1\u003c/span\u003e), which is mainly due to the presence of organic acids such as phenolic acids and free fatty acids [\u003cspan citationid=\"CR46\" class=\"CitationRef\"\u003e46\u003c/span\u003e]. This finding is consistent with previous studies [\u003cspan citationid=\"CR28\" class=\"CitationRef\"\u003e28\u003c/span\u003e, \u003cspan citationid=\"CR47\" class=\"CitationRef\"\u003e47\u003c/span\u003e]. Additionally, OMW showed a conductivity of 3.71 mS/cm, indicating the presence of minerals in this effluent. Other studies have reported much higher electrical conductivities for OMW collected from different regions of Tunisia (11.1\u0026ndash;13.2 mS/cm) [\u003cspan citationid=\"CR46\" class=\"CitationRef\"\u003e46\u003c/span\u003e]. OMW is a complex mixture containing high levels of organic matter, which can be quantified in terms of BOD5 (3.5 g/L), COD (75.6 g/L), and phenolic compounds (3.44 g/L). The characterization of OMWs collected from the north of Portugal revealed a variation in COD and total phenols, ranging from 36.7 g/L to 108.7 g/L and from 1.8 g/L to 4.83 g/L, respectively [\u003cspan citationid=\"CR15\" class=\"CitationRef\"\u003e15\u003c/span\u003e]. In contrast, OMWs from different regions of Tunisia showed higher levels of COD (219.34\u0026ndash;286.3 g/L), BOD5 (65.87\u0026ndash;86.71 g/L), and phenolic compounds (5.23\u0026ndash;10.62 g/L) [\u003cspan citationid=\"CR46\" class=\"CitationRef\"\u003e46\u003c/span\u003e]. The solubility of phenolic compounds in oil is lower compared to OMW, which accounts for their higher concentration in the latter [\u003cspan citationid=\"CR48\" class=\"CitationRef\"\u003e48\u003c/span\u003e]. These toxic compounds have an inhibitory effect on the growth of microorganisms and are the primary cause of the phytotoxic effect, which can limit the potential use of OMW as a source of nutrients or for irrigation purposes in agriculture. Therefore, proper treatment and management of OMW are crucial to mitigate the negative impacts of these toxic compounds on the environment. On the other hand, OMW contains 0.76% lipids and 18.06 g/L of sugars, values that differ from those reported in the literature [\u003cspan citationid=\"CR12\" class=\"CitationRef\"\u003e12\u003c/span\u003e, \u003cspan citationid=\"CR15\" class=\"CitationRef\"\u003e15\u003c/span\u003e]. According to Sarris et al. [\u003cspan citationid=\"CR49\" class=\"CitationRef\"\u003e49\u003c/span\u003e], the sugars in OMW are mainly present as glucose, which can be easily assimilated by microorganisms. However, OMW is typically poor in nitrogen, containing only 0.07 g/L, which is insufficient for microorganism\u0026rsquo;s growth. However, this is considered ideal for the cultivation of oleaginous yeasts, which require a low amount of nitrogen in the substrate to direct the assimilated carbon towards primarily lipid synthesis [\u003cspan citationid=\"CR5\" class=\"CitationRef\"\u003e5\u003c/span\u003e]. Alternative studies have employed a feeding strategy that involves supplementing OMW with a carbon source, such as glucose or other by-products [\u003cspan citationid=\"CR13\" class=\"CitationRef\"\u003e13\u003c/span\u003e, \u003cspan citationid=\"CR50\" class=\"CitationRef\"\u003e50\u003c/span\u003e]. This approach can enhance the OMW's potential as a growth substrate for microorganisms, thereby aiding in the bioremediation of this waste product.\u003c/p\u003e \u003cp\u003e \u003cdiv class=\"gridtable\"\u003e\u003ctable float=\"Yes\" id=\"Tab1\" border=\"1\"\u003e \u003ccaption language=\"En\"\u003e \u003cdiv class=\"CaptionNumber\"\u003eTable 1\u003c/div\u003e \u003cdiv class=\"CaptionContent\"\u003e\u003c/div\u003e \u003c/caption\u003e \u003ccolgroup cols=\"6\"\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c1\" colnum=\"1\"\u003e\u003c/div\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c2\" colnum=\"2\"\u003e\u003c/div\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c3\" colnum=\"3\"\u003e\u003c/div\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c4\" colnum=\"4\"\u003e\u003c/div\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c5\" colnum=\"5\"\u003e\u003c/div\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c6\" colnum=\"6\"\u003e\u003c/div\u003e \u003cthead\u003e \u003ctr\u003e \u003cth align=\"left\" colname=\"c1\"\u003e \u003cp\u003eParameters\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c2\"\u003e \u003cp\u003eThis work\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c3\"\u003e \u003cp\u003eYousuf et al. [\u003cspan citationid=\"CR12\" class=\"CitationRef\"\u003e12\u003c/span\u003e]\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c4\"\u003e \u003cp\u003eArous et al. [\u003cspan citationid=\"CR28\" class=\"CitationRef\"\u003e28\u003c/span\u003e]\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c5\"\u003e \u003cp\u003eZaier et al. [\u003cspan citationid=\"CR46\" class=\"CitationRef\"\u003e46\u003c/span\u003e]\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c6\"\u003e \u003cp\u003eDias et al. [\u003cspan citationid=\"CR15\" class=\"CitationRef\"\u003e15\u003c/span\u003e]\u003c/p\u003e \u003c/th\u003e \u003c/tr\u003e \u003c/thead\u003e \u003ctbody\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e\u003cb\u003epH\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e5.36\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e-\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e5.3\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e4.7\u0026ndash;5.15\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003e4.83\u0026ndash;5.03\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e\u003cb\u003eConductivity (mS/cm)\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e3.71\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e-\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e-\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e11.1\u0026ndash;13.2\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003e-\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e\u003cb\u003eTotal dry matter (g/L)\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e70\u0026thinsp;\u0026plusmn;\u0026thinsp;5\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e47.2\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e111.2\u0026thinsp;\u0026plusmn;\u0026thinsp;0.2\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e48.03\u0026ndash;95.1\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003e-\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e\u003cb\u003eMineral matter (g/L)\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e15.31\u0026thinsp;\u0026plusmn;\u0026thinsp;0.35\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e11\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e26.4\u0026thinsp;\u0026plusmn;\u0026thinsp;1.0\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e6.77\u0026ndash;13.57\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003e-\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e\u003cb\u003eOrganic matter (g/L)\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e84.68\u0026thinsp;\u0026plusmn;\u0026thinsp;0.36\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e-\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e84.8\u0026thinsp;\u0026plusmn;\u0026thinsp;0.4\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e41.2\u0026ndash;71.4\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e\u0026nbsp;\u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e\u003cb\u003eCOD (g/L)\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e75.6\u0026thinsp;\u0026plusmn;\u0026thinsp;5\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e-\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e214.3\u0026thinsp;\u0026plusmn;\u0026thinsp;14.5\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e219.34\u0026ndash;286.3\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003e36.7-108.7\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e\u003cb\u003eBOD\u003c/b\u003e\u003csub\u003e\u003cb\u003e5\u003c/b\u003e\u003c/sub\u003e \u003cb\u003e(g/L)\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e10.3\u0026thinsp;\u0026plusmn;\u0026thinsp;1.5\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e-\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e66.3\u0026thinsp;\u0026plusmn;\u0026thinsp;3.8\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e65.87\u0026ndash;86.71\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003e-\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e\u003cb\u003eLipids (%)\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e0.76\u0026thinsp;\u0026plusmn;\u0026thinsp;0.09\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e0.072\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e4.0\u0026thinsp;\u0026plusmn;\u0026thinsp;0.6\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e-\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003e-\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e\u003cb\u003eTotal nitrogen (g/L)\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e0.08\u0026thinsp;\u0026plusmn;\u0026thinsp;0.01\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e-\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e0.1\u0026thinsp;\u0026plusmn;\u0026thinsp;0.4\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e-\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003e0.15\u0026ndash;0.62\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e\u003cb\u003eReducing sugars (g/L)\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e9.3\u0026thinsp;\u0026plusmn;\u0026thinsp;1.62\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e-\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e17.7\u0026thinsp;\u0026plusmn;\u0026thinsp;0.5\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e-\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003e10.1\u0026ndash;36.3\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e\u003cb\u003eTotal sugars (g/L)\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e18.06\u0026thinsp;\u0026plusmn;\u0026thinsp;0.13\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e12.79\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e52.5\u0026thinsp;\u0026plusmn;\u0026thinsp;0.5\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e-\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003e15\u0026ndash;46\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e\u003cb\u003ePhenolic compounds (g/L)\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e3.44\u0026thinsp;\u0026plusmn;\u0026thinsp;0.08\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e9.14\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e11.8\u0026thinsp;\u0026plusmn;\u0026thinsp;1.7\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e5.23\u0026ndash;10.62\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003e1.8\u0026ndash;4.83\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003c/tbody\u003e \u003c/colgroup\u003e \u003c/table\u003e\u003c/div\u003e \u003c/p\u003e \u003c/div\u003e \u003cdiv id=\"Sec14\" class=\"Section2\"\u003e \u003ch2\u003eLipid production and OMW detoxification\u003c/h2\u003e \u003cp\u003eUsing OMW as a substrate for lipid production through the cultivation of oleaginous yeasts presents a promising alternative. Despite its low nitrogen content, OMW contains substantial amounts of sugars and organic compounds, making it suitable as a feedstock for microbial growth. To evaluate OMW's potential as a substrate, four oleaginous yeast strains: \u003cem\u003eC. viswanathii\u003c/em\u003e Y-E4, \u003cem\u003eR. babjevae\u003c/em\u003e Y-SL7, \u003cem\u003eY. lipolytica\u003c/em\u003e Y-RC7, and \u003cem\u003eT. cutaneum\u003c/em\u003e CTM-30125 (all previously studied for their lipid-accumulating properties) were tested for their growth and lipid accumulation using OMW (at 50% v/v) as the sole carbon source. A nitrogen supplement (yeast extract/ammonium sulfate) was added to the medium at a concentration of 1 g/L. As shown in Fig.\u0026nbsp;\u003cspan refid=\"Fig1\" class=\"InternalRef\"\u003e1\u003c/span\u003ea, all yeast strains were able to grow on OMW; however, biomass production was lower compared to when glucose was used as the carbon source. This difference is likely due to the substrate\u0026rsquo;s heterogeneity and the high concentration of impurities in OMW, which are known to contribute to its toxicity. Despite the high levels of phenolic compounds, yeasts remain the dominant microorganisms in OMW environments, with concentrations reaching up to 10\u003csup\u003e6\u003c/sup\u003e CFU/mL [\u003cspan citationid=\"CR51\" class=\"CitationRef\"\u003e51\u003c/span\u003e]. Among the tested strains, \u003cem\u003eR. babjevae\u003c/em\u003e Y-SL7 showed substantial lipid production on OMW, reaching up to 38% total lipid content. In a similar vein, research indicates that other oleaginous yeasts, such as \u003cem\u003eL. starkeyi\u003c/em\u003e, can efficiently utilize OMW as a substrate, reaching a lipid accumulation of 28.6% when grown on a 50% OMW medium [\u003cspan citationid=\"CR12\" class=\"CitationRef\"\u003e12\u003c/span\u003e]. However, as observed in research by Arous et al. [\u003cspan citationid=\"CR52\" class=\"CitationRef\"\u003e52\u003c/span\u003e], higher OMW concentrations can have inhibitory effects on yeast growth. For example, \u003cem\u003eD. etchellsii\u003c/em\u003e exhibited optimal biomass production (4.8 g/L, containing 0.8 g/L lipids) when cultured at a lower OMW concentration of 25% after 72 hours [\u003cspan citationid=\"CR52\" class=\"CitationRef\"\u003e52\u003c/span\u003e]. In some cases, enriching the culture medium with nutritional supplements is essential to improve lipid yield, as demonstrated with \u003cem\u003eRhodotorula glutinis\u003c/em\u003e, which achieved an increase from 11% lipid content on undiluted OMW to 41.4% when supplemented with glycerol [\u003cspan citationid=\"CR53\" class=\"CitationRef\"\u003e53\u003c/span\u003e].\u003c/p\u003e \u003cp\u003e \u003c/p\u003e \u003cp\u003eIn parallel, tested oleaginous yeasts were evaluated for their ability to reduce phenolic compounds and decolorize OMW (Fig.\u0026nbsp;\u003cspan refid=\"Fig1\" class=\"InternalRef\"\u003e1\u003c/span\u003eb). A significant level of detoxification was achieved by the different yeast strains, with rates ranging from 26.7% for the Y-E4 strain to 64.2% for CTM-30125. The Y-SL7 strain, which produced the highest lipid yield, also displayed effective phenolic compound assimilation (53.7%), a notable rate when compared to literature. This reduction in phenolic compounds suggests that the yeast strain assimilates and metabolizes these compounds, rather than simply adsorbing them. For example, C. tropicalis ATCC 750 degraded 39.6% of phenolic compounds in OMW supplemented with NH4Cl and containing 1.8 g/L initial total phenols [\u003cspan citationid=\"CR15\" class=\"CitationRef\"\u003e15\u003c/span\u003e]. For example, \u003cem\u003eC. tropicalis\u003c/em\u003e ATCC 750 degraded 39.6% of phenolic compounds in OMW supplemented with NH\u003csub\u003e4\u003c/sub\u003eCl and containing 1.8 g/L initial total phenols [\u003cspan citationid=\"CR15\" class=\"CitationRef\"\u003e15\u003c/span\u003e]. Research by Yousuf et al. [\u003cspan citationid=\"CR12\" class=\"CitationRef\"\u003e12\u003c/span\u003e] showed that \u003cem\u003eL. starkeyi\u003c/em\u003e removed 47% of phenolic compounds in 50% OMW, alongside 28.6% lipid production under high initial phenol concentrations (9.14 g/L). Phenolic compounds, beyond their cytotoxic effects, also hinder carotenoid production; red yeast \u003cem\u003eR. glutinis\u003c/em\u003e Y54 showed better growth and carotenoid production in thermally treated, dephenolized media [\u003cspan citationid=\"CR54\" class=\"CitationRef\"\u003e54\u003c/span\u003e]. The phytotoxicity and dark color of OMW, primarily caused by phenolic compounds, necessitate bioconversion for its safe application. All tested yeast strains demonstrated the ability to decolorize OMW, with Y-RC7 achieving a maximum reduction of 45.9%. For Y-RC7 and Y-E4, the decolorization rates were comparable to their detoxification rates, while Y-SL7 and CTM-30125 exhibited lower decolorization relative to detoxification. Some studies reveal complex relationships between decolorization and detoxification. For example, \u003cem\u003eC. tropicalis\u003c/em\u003e LFMB 16 achieved a decolorization rate of 16% alongside a 58% reduction in phenolic compounds in OMW with an initial phenol concentration of 1.5 g/L [\u003cspan citationid=\"CR13\" class=\"CitationRef\"\u003e13\u003c/span\u003e]. Conversely, \u003cem\u003eCryptococcus curvatus\u003c/em\u003e ATCC 20509 showed nearly matched rates of decolorization and detoxification at 25% and 28%, respectively [\u003cspan citationid=\"CR14\" class=\"CitationRef\"\u003e14\u003c/span\u003e]. In another study, \u003cem\u003eYarrowia lipolytica\u003c/em\u003e exhibited a higher decolorization rate (63%) than detoxification (34%) when cultured on OMW with initial phenol levels of 1.5 g/L [\u003cspan citationid=\"CR46\" class=\"CitationRef\"\u003e46\u003c/span\u003e]. Research by Jarboui et al. [\u003cspan citationid=\"CR47\" class=\"CitationRef\"\u003e47\u003c/span\u003e] further confirmed that phenolic compounds significantly contribute to the color of OMW, as the removal rates for phenolic content and color followed the same model in treatments with \u003cem\u003eR. mucilaginosa\u003c/em\u003e [\u003cspan citationid=\"CR47\" class=\"CitationRef\"\u003e47\u003c/span\u003e].\u003c/p\u003e \u003cp\u003eDue to its significant lipid production and detoxification rates, \u003cem\u003eR. babjevae\u003c/em\u003e Y-SL7 was deemed an ideal candidate for the bioconversion of OMW and the production of valuable metabolites. As a result, it has been selected for further work in this research.\u003c/p\u003e \u003c/div\u003e \u003cdiv id=\"Sec15\" class=\"Section2\"\u003e \u003ch2\u003eEffect of nitrogen source on biomass and lipids production\u003c/h2\u003e \u003cp\u003eOleaginous yeasts accumulate lipids when an essential nutrient, typically nitrogen, becomes limited in the growth medium, prompting a shift in cellular carbon flux from biomass production to fatty acid synthesis [\u003cspan citationid=\"CR6\" class=\"CitationRef\"\u003e6\u003c/span\u003e]. This process, known as \u003cem\u003ede novo\u003c/em\u003e lipid accumulation, is primarily influenced by nitrogen availability in yeast cells. Consequently, selecting an optimal nitrogen source is crucial for maximizing SCO accumulation. Furthermore, nitrogen has been shown to play a key role in enhancing the biodegradation of aromatic compounds [\u003cspan citationid=\"CR55\" class=\"CitationRef\"\u003e55\u003c/span\u003e]. In this study, OMW was utilized as the carbon source, but it contains only minimal nitrogen (0.07 g/L), insufficient for supporting robust yeast growth. In order to boost both biomass and lipid production, the oleaginous yeast \u003cem\u003eR. babjevae\u003c/em\u003e Y-SL7 was grown in a medium consisting of 50% OMW, enriched with different combinations of yeast extract and various nitrogen sources in equal amounts. Nitrogen supplementation in the OMW-based medium significantly increased both biomass and lipid production compared to using OMW as the sole carbon and nitrogen source (Table\u0026nbsp;\u003cspan refid=\"Tab2\" class=\"InternalRef\"\u003e2\u003c/span\u003e). Notably, the Y-SL7 strain achieved peak production levels, generating 3.62 g/L of biomass and 1.38 g/L of lipids, when fed a 1:1 mixture of yeast extract and ammonium sulfate ((NH\u003csub\u003e4\u003c/sub\u003e)\u003csub\u003e2\u003c/sub\u003eSO\u003csub\u003e4\u003c/sub\u003e) as the nitrogen source. Yeast extract, an organic nitrogen source rich in vitamins and amino acids, has been shown to effectively support yeast growth and lipid synthesis [\u003cspan citationid=\"CR56\" class=\"CitationRef\"\u003e56\u003c/span\u003e]. Additionally, nitrogen from ammonium salts is readily assimilated by yeast cells, enabling efficient utilization for growth and lipid accumulation [\u003cspan citationid=\"CR57\" class=\"CitationRef\"\u003e57\u003c/span\u003e]. Likewise, Lopes et al. [\u003cspan citationid=\"CR58\" class=\"CitationRef\"\u003e58\u003c/span\u003e] found that adding ammonium sulfate to an OMW-based medium significantly enhanced organic matter consumption by \u003cem\u003eY. lipolytica\u003c/em\u003e W29. Comparable findings have been observed in previous studies, such as with \u003cem\u003eC. pararugosa\u003c/em\u003e BM24 and \u003cem\u003eSchwanniomyces etchellsii\u003c/em\u003e M2 strains cultivated on 75% OMW, which produced lower biomass yields without nitrogen supplementation [\u003cspan citationid=\"CR28\" class=\"CitationRef\"\u003e28\u003c/span\u003e]. Thus, selecting an appropriate nitrogen source is essential for optimizing SCO accumulation. The combination of yeast extract and (NH\u003csub\u003e4\u003c/sub\u003e)\u003csub\u003e2\u003c/sub\u003eSO\u003csub\u003e4\u003c/sub\u003e in the cultivation of \u003cem\u003eR. babjevae\u003c/em\u003e Y-SL7 not only enhanced biomass and lipid production but also underscores the importance of nutrient management in optimizing bioprocesses for industrial applications.\u003c/p\u003e \u003cp\u003e \u003cdiv class=\"gridtable\"\u003e\u003ctable float=\"Yes\" id=\"Tab2\" border=\"1\"\u003e \u003ccaption language=\"En\"\u003e \u003cdiv class=\"CaptionNumber\"\u003eTable 2\u003c/div\u003e \u003cdiv class=\"CaptionContent\"\u003e\u003c/div\u003e \u003c/caption\u003e \u003ccolgroup cols=\"4\"\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c1\" colnum=\"1\"\u003e\u003c/div\u003e \u003cdiv align=\"char\" char=\"\u0026plusmn;\" class=\"colspec\" colname=\"c2\" colnum=\"2\"\u003e\u003c/div\u003e \u003cdiv align=\"char\" char=\"\u0026plusmn;\" class=\"colspec\" colname=\"c3\" colnum=\"3\"\u003e\u003c/div\u003e \u003cdiv align=\"char\" char=\"\u0026plusmn;\" class=\"colspec\" colname=\"c4\" colnum=\"4\"\u003e\u003c/div\u003e \u003cthead\u003e \u003ctr\u003e \u003cth align=\"left\" colname=\"c1\"\u003e \u003cp\u003eNitrogen source\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c2\"\u003e \u003cp\u003eBiomass (g/L)\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c3\"\u003e \u003cp\u003eLipids (g/L)\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c4\"\u003e \u003cp\u003eLipid yield (%)\u003c/p\u003e \u003c/th\u003e \u003c/tr\u003e \u003c/thead\u003e \u003ctbody\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eControl\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\"\u0026plusmn;\" colname=\"c2\"\u003e \u003cp\u003e0.83\u0026thinsp;\u0026plusmn;\u0026thinsp;0.14\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\"\u0026plusmn;\" colname=\"c3\"\u003e \u003cp\u003e0.22\u0026thinsp;\u0026plusmn;\u0026thinsp;0.07\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\"\u0026plusmn;\" colname=\"c4\"\u003e \u003cp\u003e25.95\u0026thinsp;\u0026plusmn;\u0026thinsp;5.95\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eYeast Extract\u0026thinsp;+\u0026thinsp;Peptone (1:1)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\"\u0026plusmn;\" colname=\"c2\"\u003e \u003cp\u003e2.49\u0026thinsp;\u0026plusmn;\u0026thinsp;0.04\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\"\u0026plusmn;\" colname=\"c3\"\u003e \u003cp\u003e0.95\u0026thinsp;\u0026plusmn;\u0026thinsp;0.01\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\"\u0026plusmn;\" colname=\"c4\"\u003e \u003cp\u003e38.23\u0026thinsp;\u0026plusmn;\u0026thinsp;1.10\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eYeast Extract +(NH\u003csub\u003e4\u003c/sub\u003e)\u003csub\u003e3\u003c/sub\u003ePO\u003csub\u003e4\u003c/sub\u003e (1:1)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\"\u0026plusmn;\" colname=\"c2\"\u003e \u003cp\u003e2.61\u0026thinsp;\u0026plusmn;\u0026thinsp;0.04\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\"\u0026plusmn;\" colname=\"c3\"\u003e \u003cp\u003e1.07\u0026thinsp;\u0026plusmn;\u0026thinsp;0.1\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\"\u0026plusmn;\" colname=\"c4\"\u003e \u003cp\u003e41.13\u0026thinsp;\u0026plusmn;\u0026thinsp;4.20\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eYeast Extract\u0026thinsp;+\u0026thinsp;NH\u003csub\u003e4\u003c/sub\u003eCl (1:1)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\"\u0026plusmn;\" colname=\"c2\"\u003e \u003cp\u003e2.94\u0026thinsp;\u0026plusmn;\u0026thinsp;0.05\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\"\u0026plusmn;\" colname=\"c3\"\u003e \u003cp\u003e1.12\u0026thinsp;\u0026plusmn;\u0026thinsp;0.04\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\"\u0026plusmn;\" colname=\"c4\"\u003e \u003cp\u003e37.99\u0026thinsp;\u0026plusmn;\u0026thinsp;1.47\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eYeast Extract +(NH\u003csub\u003e4\u003c/sub\u003e)\u003csub\u003e2\u003c/sub\u003eSO\u003csub\u003e4\u003c/sub\u003e (1:1)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\"\u0026plusmn;\" colname=\"c2\"\u003e \u003cp\u003e3.62\u0026thinsp;\u0026plusmn;\u0026thinsp;0.42\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\"\u0026plusmn;\" colname=\"c3\"\u003e \u003cp\u003e1.38\u0026thinsp;\u0026plusmn;\u0026thinsp;0.2\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\"\u0026plusmn;\" colname=\"c4\"\u003e \u003cp\u003e38.04\u0026thinsp;\u0026plusmn;\u0026thinsp;1.17\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003c/tbody\u003e \u003c/colgroup\u003e \u003c/table\u003e\u003c/div\u003e \u003c/p\u003e \u003c/div\u003e \u003cdiv id=\"Sec16\" class=\"Section2\"\u003e \u003ch2\u003eResponse surface model (RSM) for lipid yield enhancement\u003c/h2\u003e \u003cp\u003eOptimizing fermentation conditions through strategic media formulation is fundamental to establishing efficient and productive bioconversion processes. Traditional optimization approaches, where only one independent variable is adjusted at a time, are typically labor-intensive and time-consuming. Furthermore, they often lack precision in predicting optimal levels and understanding interactions among variables [\u003cspan citationid=\"CR59\" class=\"CitationRef\"\u003e59\u003c/span\u003e]. To address these limitations, a statistical experimental design methodology offers a more effective alternative, enabling a clearer and more accurate determination of optimal conditions and parameter interactions. To achieve this, the Box-Behnken model was applied to identify the optimal levels of independent variables and to assess the impact of their interactions on lipid production by the oleaginous yeast \u003cem\u003eR. babjevae\u003c/em\u003e Y-SL7. The three independent variables were as follows: amount of OMW (X\u003csub\u003e1\u003c/sub\u003e), nitrogen concentration (X\u003csub\u003e2\u003c/sub\u003e), and pH (X\u003csub\u003e3\u003c/sub\u003e). Seventeen experiments were conducted using various combinations of these factors. The design matrix, along with the experimental results, is provided in the supporting information (Table \u003cspan refid=\"MOESM1\" class=\"InternalRef\"\u003eS1\u003c/span\u003e). Significant differences were observed in the lipid yields produced, with this variation closely linked to the levels of each factor. The lipid yield ranged from 0.37 g/L in run 1 to 2.28 g/L in run 8. Through multiple regression analysis of the experimental data, the following second-degree polynomial equation (Eq.\u0026nbsp;\u003cspan refid=\"Equ2\" class=\"InternalRef\"\u003e2\u003c/span\u003e) was derived to represent the response (\u003cem\u003eY\u003c/em\u003e), considering only the most significant terms (Table\u0026nbsp;\u003cspan refid=\"Tab3\" class=\"InternalRef\"\u003e3\u003c/span\u003e).\u003c/p\u003e \u003cp\u003e \u003cdiv class=\"gridtable\"\u003e\u003ctable float=\"Yes\" id=\"Tab3\" border=\"1\"\u003e \u003ccaption language=\"En\"\u003e \u003cdiv class=\"CaptionNumber\"\u003eTable 3\u003c/div\u003e \u003cdiv class=\"CaptionContent\"\u003e\u003c/div\u003e \u003c/caption\u003e \u003ccolgroup cols=\"6\"\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c1\" colnum=\"1\"\u003e\u003c/div\u003e \u003cdiv align=\"char\" char=\".\" class=\"colspec\" colname=\"c2\" colnum=\"2\"\u003e\u003c/div\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c3\" colnum=\"3\"\u003e\u003c/div\u003e \u003cdiv align=\"char\" char=\".\" class=\"colspec\" colname=\"c4\" colnum=\"4\"\u003e\u003c/div\u003e \u003cdiv align=\"char\" char=\".\" class=\"colspec\" colname=\"c5\" colnum=\"5\"\u003e\u003c/div\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c6\" colnum=\"6\"\u003e\u003c/div\u003e \u003cthead\u003e \u003ctr\u003e \u003cth align=\"left\" colname=\"c1\"\u003e \u003cp\u003eModel Term\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c2\"\u003e \u003cp\u003eCoefficient\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c3\"\u003e \u003cp\u003eF.Inflation\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c4\"\u003e \u003cp\u003eSt.error\u003csup\u003ea\u003c/sup\u003e\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c5\"\u003e \u003cp\u003e\u003cem\u003et\u003c/em\u003e value\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c6\"\u003e \u003cp\u003e\u003cem\u003eP\u003c/em\u003e value\u003csup\u003ee\u003c/sup\u003e\u003c/p\u003e \u003c/th\u003e \u003c/tr\u003e \u003c/thead\u003e \u003ctbody\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eIntercept\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e \u003cp\u003e1.360\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e \u003cp\u003e0.062\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c5\"\u003e \u003cp\u003e22.08\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003e\u0026lt;\u0026thinsp;0.01 ***\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e\u003cem\u003eX\u003c/em\u003e\u003csub\u003e1\u003c/sub\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e \u003cp\u003e0.432\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e1.00\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e \u003cp\u003e0.049\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c5\"\u003e \u003cp\u003e8.88\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003e\u0026lt;\u0026thinsp;0.01 ***\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e\u003cem\u003eX\u003c/em\u003e\u003csub\u003e2\u003c/sub\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e \u003cp\u003e0.271\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e1.00\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e \u003cp\u003e0.049\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c5\"\u003e \u003cp\u003e5.57\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003e0.0985 ***\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e\u003cem\u003eX\u003c/em\u003e\u003csub\u003e3\u003c/sub\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e \u003cp\u003e0.266\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e1.00\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e \u003cp\u003e0.049\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c5\"\u003e \u003cp\u003e5.47\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003e0.109 **\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e\u003cem\u003eX\u003c/em\u003e\u003csub\u003e\u003cem\u003e1\u003c/em\u003e\u003c/sub\u003e\u003csup\u003e2\u003c/sup\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e \u003cp\u003e-0.155\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e1.01\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e \u003cp\u003e0.067\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c5\"\u003e \u003cp\u003e-2.31\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003e5.3\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e\u003cem\u003eX\u003c/em\u003e\u003csub\u003e2\u003c/sub\u003e\u003csup\u003e2\u003c/sup\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e \u003cp\u003e-0.317\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e1.01\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e \u003cp\u003e0.067\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c5\"\u003e \u003cp\u003e-4.73\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003e0.231 **\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e\u003cem\u003eX\u003c/em\u003e\u003csub\u003e3\u003c/sub\u003e\u003csup\u003e2\u003c/sup\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e \u003cp\u003e0.083\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e1.01\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e \u003cp\u003e0.067\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c5\"\u003e \u003cp\u003e1.23\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003e25.8\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e\u003cem\u003eX\u003c/em\u003e\u003csub\u003e1\u003c/sub\u003e\u003cem\u003eX\u003c/em\u003e\u003csub\u003e2\u003c/sub\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e \u003cp\u003e0.188\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e1.00\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e \u003cp\u003e0.069\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c5\"\u003e \u003cp\u003e2.72\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003e2.90 *\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e\u003cem\u003eX\u003c/em\u003e\u003csub\u003e1\u003c/sub\u003e\u003cem\u003eX\u003c/em\u003e\u003csub\u003e3\u003c/sub\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e \u003cp\u003e0.298\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e1.00\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e \u003cp\u003e0.069\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c5\"\u003e \u003cp\u003e4.32\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003e0.365 **\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e\u003cem\u003eX\u003c/em\u003e\u003csub\u003e2\u003c/sub\u003e\u003cem\u003eX\u003c/em\u003e\u003csub\u003e3\u003c/sub\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e \u003cp\u003e0.075\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e1.00\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e \u003cp\u003e0.069\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c5\"\u003e \u003cp\u003e1.09\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003e31.3\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eSource\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003eSS\u003csup\u003eb\u003c/sup\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003eDf\u003csup\u003ec\u003c/sup\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003eMS\u003csup\u003ed\u003c/sup\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e\u003cem\u003eF\u003c/em\u003e test\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003e\u003cem\u003eP\u003c/em\u003e value\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eRegression\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e \u003cp\u003e3.7317\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e9\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e \u003cp\u003e0.4146\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c5\"\u003e \u003cp\u003e21.8678\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003e0.0457 ***\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eResidual\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e \u003cp\u003e0.1327\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e7\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e \u003cp\u003e0.0190\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e\u0026nbsp;\u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eLack of fit\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e \u003cp\u003e0.1059\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e3\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e \u003cp\u003e0.0353\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c5\"\u003e \u003cp\u003e5.2699\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003e7.2\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eError\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e \u003cp\u003e0.0268\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e4\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e \u003cp\u003e0.0067\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e\u0026nbsp;\u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eTotal\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e \u003cp\u003e3.8644\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e16\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e\u0026nbsp;\u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003eR\u003csup\u003e2\u003c/sup\u003e\u0026thinsp;=\u0026thinsp;0.96\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003c/tbody\u003e \u003c/colgroup\u003e \u003ctfoot\u003e \u003ctr\u003e\u003ctd colspan=\"6\"\u003e\u003csup\u003ea\u003c/sup\u003eSt.error, standard error; \u003csup\u003eb\u003c/sup\u003eDf, degree of freedom; \u003csup\u003ec\u003c/sup\u003eSS, sum of squares; \u003csup\u003ed\u003c/sup\u003eMS, mean square\u003c/td\u003e\u003c/tr\u003e \u003ctr\u003e\u003ctd colspan=\"6\"\u003e\u003csup\u003ee\u003c/sup\u003e\u003cem\u003eP\u003c/em\u003e value less than 0.05 indicates terms are significant\u003c/td\u003e\u003c/tr\u003e \u003c/tfoot\u003e \u003c/table\u003e\u003c/div\u003e \u003cdiv id=\"Equ2\" class=\"Equation\"\u003e \u003cdiv format=\"TEX\" class=\"mathdisplay\" id=\"FileID_Equ2\" name=\"EquationSource\"\u003e\n$$\\:Y=1.36+0.432\\:{X}_{1}+0.271{X}_{2}+0.266{X}_{3}-0.317{X}_{2}^{2}+0.298{X}_{1}{X}_{3}$$\u003c/div\u003e \u003cdiv class=\"EquationNumber\"\u003e2\u003c/div\u003e\u003c/div\u003e \u003c/p\u003e \u003cp\u003eWhere \u003cem\u003eY\u003c/em\u003e represents the predicted lipid yield; X\u003csub\u003e1\u003c/sub\u003e, X\u003csub\u003e2\u003c/sub\u003e and X\u003csub\u003e3\u003c/sub\u003e​ correspond to the coded values of OMW concentration, nitrogen concentration, and pH, respectively.\u003c/p\u003e \u003cp\u003eThe Student's t-test was employed to determine the significance of the coefficients. The regression coefficients, along with their corresponding \u003cem\u003eP\u003c/em\u003e values and parameter estimates, are presented in Table\u0026nbsp;\u003cspan refid=\"Tab3\" class=\"InternalRef\"\u003e3\u003c/span\u003e. Based on Equation (Eq.\u0026nbsp;\u003cspan refid=\"Equ2\" class=\"InternalRef\"\u003e2\u003c/span\u003e), we can conclude that lipid yield is primarily influenced by the linear effects of the three variables, the squared effect of nitrogen concentration (X\u003csub\u003e2\u003c/sub\u003e), and to a lesser extent, by the interactions between X\u003csub\u003e1\u003c/sub\u003e and X\u003csub\u003e3\u003c/sub\u003e. The ANOVA analysis conducted on lipid production revealed that the regression model was significant (\u003cem\u003eP\u003c/em\u003e\u0026thinsp;\u0026lt;\u0026thinsp;0.05), and the lack of fit was found to be non-significant. Additionally, the model demonstrated a high coefficient of determination (R\u0026sup2; = 0.96), indicating that 96% of the variability in the response was attributable to the effects of the independent variables. A model's ability to accurately explain the variability between experimental and predicted outcomes increases as the R\u003csup\u003e2\u003c/sup\u003e value approaches 1 [\u003cspan citationid=\"CR30\" class=\"CitationRef\"\u003e30\u003c/span\u003e]. Using the second-order equation, the response was expressed as a function of the interaction between the amount of OMW and pH. Three-dimensional response surfaces and their respective contour plots were created from the model equation to identify the ideal factor levels for achieving the highest lipid production by the Y-SL7 strain (Fig.\u0026nbsp;\u003cspan refid=\"Fig2\" class=\"InternalRef\"\u003e2\u003c/span\u003e). This figure illustrates the effects of OMW concentration and pH on lipid yield when the nitrogen concentration is maintained at its midpoint (1.5 g/L). Notably, an increase in OMW concentration, accompanied by a slight increase in pH, is consistently associated with an increase in lipid production. Consequently, the predicted response \u0026#119884; varies from 0.4 to 2.3 g/L of lipids. Nonetheless, raising the nitrogen concentration at low initial OMW levels does not enhance lipid yield. For lipid accumulation in yeast cells to occur, a high carbon concentration is necessary, resulting in an elevated carbon-to-nitrogen (C/N) ratio. The increase in OMW concentration is inherently associated with higher levels of phenolic compounds, which can be detrimental to microbial growth. Unlike many other microorganisms, yeasts are better suited to tolerate high phenolic compound concentrations and low pH levels found in mill wastes, enabling them to thrive in such challenging environments [\u003cspan citationid=\"CR60\" class=\"CitationRef\"\u003e60\u003c/span\u003e]. In several cases, increasing the initial OMW concentration does not inhibit microbial growth or lipid synthesis. Arous et al. [\u003cspan citationid=\"CR28\" class=\"CitationRef\"\u003e28\u003c/span\u003e] showed that bioconversion performance was unaffected even at a 75% OMW concentration with high phenolic compound levels, and the growth of \u003cem\u003eCandida pararugosa\u003c/em\u003e BM24 was similar in both 50% diluted and undiluted OMW conditions. Similarly, Dias et al. [\u003cspan citationid=\"CR15\" class=\"CitationRef\"\u003e15\u003c/span\u003e] demonstrated that \u003cem\u003eC. tropicalis\u003c/em\u003e ATCC 750 tolerated all tested OMW concentrations (5\u0026ndash;50%). An increase in phenolic compounds to 2.4 g/L, resulting from a 50% (v/v) OMW concentration, did not inhibit yeast growth. Moreover, a 1.6-fold increase in cellular growth was observed when the OMW concentration was raised from 5\u0026ndash;15%. In some cases, however, a higher OMW concentration can lead to increased phenolic compounds that negatively affect microbial growth and bioconversion. For instance, the accumulation of phenolic compounds in the medium can reach up to 4.5 g/L with higher OMW volumes, which results in a decrease in the maximum biomass yield of \u003cem\u003eY. lipolytica\u003c/em\u003e strains [\u003cspan citationid=\"CR49\" class=\"CitationRef\"\u003e49\u003c/span\u003e, \u003cspan citationid=\"CR50\" class=\"CitationRef\"\u003e50\u003c/span\u003e, \u003cspan citationid=\"CR61\" class=\"CitationRef\"\u003e61\u003c/span\u003e]. On the other hand, pH is a crucial factor in the bioconversion process, particularly when using OMW as a substrate. The pH of the fermentation medium influences not only the solubility of certain nutrients but also the permeability of the cell membrane, thereby affecting cellular development [\u003cspan citationid=\"CR62\" class=\"CitationRef\"\u003e62\u003c/span\u003e]. Previous studies have shown that slightly acidic pH levels enhance lipid production in oleaginous yeasts cultivated on OMW as a carbon source. In fact, the total reduction of sugars, phenols, and chemical oxygen demand (COD) was statistically improved when the cultures were conducted at a pH range of 5 to 6 [\u003cspan citationid=\"CR13\" class=\"CitationRef\"\u003e13\u003c/span\u003e, \u003cspan citationid=\"CR55\" class=\"CitationRef\"\u003e55\u003c/span\u003e] Additionally, an acidic pH can promote the assimilation of phenolic compounds and increase biomass yield. For example, in a solid acidic medium (pH 5.5), \u003cem\u003eR. mucilaginosa\u003c/em\u003e was found to be capable of growing and efficiently assimilating simple aromatic compounds such as protocatechuic acid, p-coumaric acid, tyrosol and vanillic acid [\u003cspan citationid=\"CR47\" class=\"CitationRef\"\u003e47\u003c/span\u003e]. Furthermore, when OMW was used in the culture media of the same yeast strain, chemical oxygen demand (COD) and phenolic compounds were reduced by 56.9% and 34.8%, respectively [\u003cspan citationid=\"CR47\" class=\"CitationRef\"\u003e47\u003c/span\u003e].\u003c/p\u003e \u003cp\u003e \u003c/p\u003e \u003cp\u003eThe optimal levels for the independent variables X1, X2, and X3 (OMW, nitrogen, and pH) were determined to be 62%, 2.2 g/L, and pH 5.9, respectively, through further data analysis using the Nemrod-W software, based on the results from Fig.\u0026nbsp;\u003cspan refid=\"Fig2\" class=\"InternalRef\"\u003e2\u003c/span\u003e. The corresponding experiment was conducted in four replicates, and the average lipid yield was calculated. The experimental lipid yield was approximately 2.5 g/L, which represents about 40% of the total lipid yield, while the predicted yield was 2.8 g/L. This outcome highlights the model's accuracy in reflecting the experimental results. Under optimal conditions, the elimination rate of phenolic compounds was 58%. The results demonstrate that optimizing fermentation parameters can lead to improved lipid production while minimizing undesirable compounds, thus improving the overall potential of OMW as a feedstock for bioprocessing applications. Table\u0026nbsp;\u003cspan refid=\"Tab4\" class=\"InternalRef\"\u003e4\u003c/span\u003e presents a compilation of oleaginous yeasts cultivated on OMW as the sole carbon source or supplemented with additional substrates such as glycerol, glucose, and xylose. In most cases, cultures were conducted in flasks with various nitrogen sources (mineral, organic, or mixed). When OMW is used as a feedstock, lipid production by oleaginous yeasts remains relatively low, even when the medium is enriched with nutritional supplements. This underscores the recalcitrant nature of this waste and the environmental importance of its treatment. In certain cases, controlled fermentation in a bioreactor enhances lipid and biomass production, typically accompanied by a significant reduction in phenolic compounds. When cultivated in bioreactors, \u003cem\u003eY. lipolytica\u003c/em\u003e strains A6 and S11 exhibited high lipid accumulation (25%), particularly when OMW was supplemented with 50 g/L of glycerol. This was also associated with OMW detoxification, reaching levels of up to 30% [\u003cspan citationid=\"CR13\" class=\"CitationRef\"\u003e13\u003c/span\u003e].\u003c/p\u003e \u003cp\u003e \u003cdiv class=\"gridtable\"\u003e\u003ctable float=\"Yes\" id=\"Tab4\" border=\"1\"\u003e \u003ccaption language=\"En\"\u003e \u003cdiv class=\"CaptionNumber\"\u003eTable 4\u003c/div\u003e \u003cdiv class=\"CaptionContent\"\u003e\u003c/div\u003e \u003c/caption\u003e \u003ccolgroup cols=\"8\"\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c1\" colnum=\"1\"\u003e\u003c/div\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c2\" colnum=\"2\"\u003e\u003c/div\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c3\" colnum=\"3\"\u003e\u003c/div\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c4\" colnum=\"4\"\u003e\u003c/div\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c5\" colnum=\"5\"\u003e\u003c/div\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c6\" colnum=\"6\"\u003e\u003c/div\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c7\" colnum=\"7\"\u003e\u003c/div\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c8\" colnum=\"8\"\u003e\u003c/div\u003e \u003cthead\u003e \u003ctr\u003e \u003cth align=\"left\" colname=\"c1\"\u003e \u003cp\u003eStrains\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c2\"\u003e \u003cp\u003eRaw material\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c3\"\u003e \u003cp\u003eNitrogen source\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c4\"\u003e \u003cp\u003eBiomass (g/L)\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c5\"\u003e \u003cp\u003eLipid (g/L)\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c6\"\u003e \u003cp\u003ePhenolic compound remouved (%)\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c7\"\u003e \u003cp\u003eDecolorization (%)\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c8\"\u003e \u003cp\u003eReference\u003c/p\u003e \u003c/th\u003e \u003c/tr\u003e \u003c/thead\u003e \u003ctbody\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e\u003cem\u003eS. etchellsii M2\u003c/em\u003e\u003c/p\u003e \u003cp\u003e\u003cem\u003eC. pararugosa\u003c/em\u003e BM24\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e75% OMW\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003eNH\u003csub\u003e4\u003c/sub\u003eCl\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e15.11\u003c/p\u003e \u003cp\u003e21.68\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e0.42\u003c/p\u003e \u003cp\u003e1.08\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003e15.4\u003c/p\u003e \u003cp\u003e19.2\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\"\u003e \u003cp\u003e\u003cb\u003e-\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c8\"\u003e \u003cp\u003e[\u003cspan citationid=\"CR28\" class=\"CitationRef\"\u003e28\u003c/span\u003e]\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e\u003cem\u003eC. tropicalis\u003c/em\u003e ATCC 750\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e50% OMW\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003eNH\u003csub\u003e4\u003c/sub\u003eCl\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e-\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e2.5\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003e39\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\"\u003e \u003cp\u003e-\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c8\"\u003e \u003cp\u003e[\u003cspan citationid=\"CR15\" class=\"CitationRef\"\u003e15\u003c/span\u003e]\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e\u003cem\u003eC. curvatus\u003c/em\u003e ATCC 20509\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e60% OMW\u0026thinsp;+\u0026thinsp;xylose (100 g/L)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003eYE\u0026thinsp;+\u0026thinsp;Peptone\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e20.9\u0026ndash;27\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e1.6\u0026ndash;8.4\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003e25\u0026ndash;28\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\"\u003e \u003cp\u003e25\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c8\"\u003e \u003cp\u003e[\u003cspan citationid=\"CR14\" class=\"CitationRef\"\u003e14\u003c/span\u003e]\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e\u003cem\u003eL. starkeyi\u003c/em\u003e DSM 702096\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e25\u0026ndash;100% OMW\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003eWithout\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e3.2\u0026ndash;11.1\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e0.7\u0026ndash;3.2\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003e43\u0026ndash;53\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\"\u003e \u003cp\u003e-\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c8\"\u003e \u003cp\u003e[\u003cspan citationid=\"CR12\" class=\"CitationRef\"\u003e12\u003c/span\u003e]\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e\u003cem\u003eY. lipolytica\u003c/em\u003e ACA-DC 5029\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003eOMW\u0026thinsp;+\u0026thinsp;Crude glycerol (70g/L)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003ePeptone\u0026thinsp;+\u0026thinsp;YE\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e10\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e2\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003e10\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\"\u003e \u003cp\u003e30\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c8\"\u003e \u003cp\u003e[\u003cspan citationid=\"CR50\" class=\"CitationRef\"\u003e50\u003c/span\u003e]\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e\u003cem\u003eY. lipolytica\u003c/em\u003e ACA-YC 5033\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003eOMW\u0026thinsp;+\u0026thinsp;glucose (35 g/L)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003eYE + (NH\u003csub\u003e4\u003c/sub\u003e)\u003csub\u003e2\u003c/sub\u003eSO\u003csub\u003e4\u003c/sub\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e9.1\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e1\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003e51\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\"\u003e \u003cp\u003e58\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c8\"\u003e \u003cp\u003e[\u003cspan citationid=\"CR61\" class=\"CitationRef\"\u003e61\u003c/span\u003e]\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e\u003cem\u003eY. lipolytica\u003c/em\u003e L2 KF156787\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e25% OMW\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003eYE\u0026thinsp;+\u0026thinsp;Casein peptone\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e8\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e1.5\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003e-\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\"\u003e \u003cp\u003e90\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c8\"\u003e \u003cp\u003e[\u003cspan citationid=\"CR1\" class=\"CitationRef\"\u003e1\u003c/span\u003e]\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e\u003cem\u003eR. glutinis\u003c/em\u003e DSM 70398\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e25\u0026ndash;100% OMW\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003eUrea\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e1.97\u0026ndash;7.93\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e0.1\u0026ndash;0.64\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003e40-93.5\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\"\u003e \u003cp\u003e-\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c8\"\u003e \u003cp\u003e[\u003cspan citationid=\"CR53\" class=\"CitationRef\"\u003e53\u003c/span\u003e]\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e\u003cem\u003eR. babjevae\u003c/em\u003e Y-SL7\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e75% OMW\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003eYE + (NH\u003csub\u003e4\u003c/sub\u003e)\u003csub\u003e2\u003c/sub\u003eSO\u003csub\u003e4\u003c/sub\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e6.2\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e2.5\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003e58\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\"\u003e \u003cp\u003e12\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c8\"\u003e \u003cp\u003eThis work\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003c/tbody\u003e \u003c/colgroup\u003e \u003c/table\u003e\u003c/div\u003e \u003c/p\u003e \u003c/div\u003e \u003cdiv id=\"Sec17\" class=\"Section2\"\u003e \u003ch2\u003eFatty acid composition and biodiesel characterization\u003c/h2\u003e \u003cp\u003eThe lipid profile of \u003cem\u003eR. babjevae\u003c/em\u003e Y-SL7 during OMW fermentation process was determined using GC/MS analysis. Figure\u0026nbsp;\u003cspan refid=\"Fig3\" class=\"InternalRef\"\u003e3\u003c/span\u003e illustrates the fatty acid (FA) composition of the extracted lipids from the Y-SL7 strain cultivated on both OMW and glucose. The analysis revealed similarities in the fatty acid composition of lipids produced from OMW compared to those produced from glucose. In both profiles, oleic acid (C18:1) was the most abundant lipid component (69.8% and 66.6%, respectively), followed by palmitic acid (C16:0) (23.1% and 18.9%, respectively). The main difference lies in the fact that lipids produced from OMW contain 3.9% palmitoleic acid (C16:1), while stearic acid (C18:0), accounting for 8.2%, was identified as the third most abundant fatty acid in the lipids produced from glucose. The distribution of FAs in the lipids accumulated by \u003cem\u003eL. starkeyi\u003c/em\u003e grown on OMW reveals a similar profile to that of Y-SL7 strain, with the two predominant FAs being oleic acid (C18:1, 49.1%) and palmitic acid (C16:0, 19.1%). However, the lipids produced by \u003cem\u003eL. starkeyi\u003c/em\u003e contained a significant amount of linoleic acid (C18:2, 18.8%) [\u003cspan citationid=\"CR12\" class=\"CitationRef\"\u003e12\u003c/span\u003e]. In a study by Dias et al. [\u003cspan citationid=\"CR15\" class=\"CitationRef\"\u003e15\u003c/span\u003e], comparable results were observed regarding saturated and unsaturated fatty acids, but a higher quantity of polyunsaturated FAs was noted, reaching 12.9% in lipids produced by \u003cem\u003eC. tropicalis\u003c/em\u003e ATCC when cultivated on OMW at pH 5.5. Similar findings [\u003cspan citationid=\"CR28\" class=\"CitationRef\"\u003e28\u003c/span\u003e] were reported for oleaginous yeast strains, including \u003cem\u003eC. pararugosa\u003c/em\u003e BM24 and \u003cem\u003eS. etchellsii\u003c/em\u003e M2. Differences in the lipid profiles of yeasts derived from OMW fermentation can be attributed to variations in the physicochemical composition of the OMW used and the nature of its residual fatty acids. It's worth emphasizing that lipid accumulation in oleaginous yeasts generally follows two distinct metabolic pathways: \u003cem\u003ede novo\u003c/em\u003e synthesis induced by hydrophilic substrates and \u003cem\u003eex novo\u003c/em\u003e synthesis primarily triggered by the presence of hydrophobic compounds [\u003cspan citationid=\"CR63\" class=\"CitationRef\"\u003e63\u003c/span\u003e]. Given that OMW contains both hydrophilic (sugars) and hydrophobic (residual fatty acids and olive oil residues) compounds, this suggests that lipid synthesis by yeasts under these conditions may occur via both pathways simultaneously, which could explain the observed differences.\u003c/p\u003e \u003cp\u003e \u003c/p\u003e \u003cp\u003eFor biodiesel production, lipids with a high degree of monounsaturation are advantageous, as they improve the economic viability of the transesterification process by lowering the optimal reaction temperature and enhancing triglyceride conversion [\u003cspan citationid=\"CR64\" class=\"CitationRef\"\u003e64\u003c/span\u003e]. The theoretical characterization of Y-SL7-OMW biodiesel was performed using Biodiesel Analyser software [\u003cspan citationid=\"CR41\" class=\"CitationRef\"\u003e41\u003c/span\u003e], with key properties summarized in Table\u0026nbsp;\u003cspan refid=\"Tab5\" class=\"InternalRef\"\u003e5\u003c/span\u003e, alongside U.S. standards (ASTM D-6751). Y-SL7-OMW biodiesel has a cetane number of 52.54, meeting the standard minimum of 47. This number indicates the ignition quality of diesel fuel and its ability to self-ignite in an engine [\u003cspan citationid=\"CR65\" class=\"CitationRef\"\u003e65\u003c/span\u003e]. The iodine index, another important parameter, should be 120 or lower; Y-SL7 biodiesel meets this requirement with a value of 75.71. The iodine value significantly affects biodiesel's cold filter clogging point and oxidation stability [\u003cspan citationid=\"CR66\" class=\"CitationRef\"\u003e66\u003c/span\u003e]. Kinematic viscosity, which influences the potential for engine deposits, was also examined. This biodiesel aligns with standards, showing a kinematic viscosity of 1.59 mm\u003csup\u003e2\u003c/sup\u003e/s. Both kinematic viscosity and density depend on methyl ester content, the feedstock used, and any contaminants (such as methanol) [\u003cspan citationid=\"CR66\" class=\"CitationRef\"\u003e66\u003c/span\u003e]. However, the density slightly exceeds the maximum limit of 0.99 g/cm\u003csup\u003e3\u003c/sup\u003e. Overall, the lipids extracted from \u003cem\u003eR. babjevae\u003c/em\u003e grown on OMW are considered appropriate for biodiesel production.\u003c/p\u003e \u003cp\u003e \u003cdiv class=\"gridtable\"\u003e\u003ctable float=\"Yes\" id=\"Tab5\" border=\"1\"\u003e \u003ccaption language=\"En\"\u003e \u003cdiv class=\"CaptionNumber\"\u003eTable 5\u003c/div\u003e \u003cdiv class=\"CaptionContent\"\u003e\u003c/div\u003e \u003c/caption\u003e \u003ccolgroup cols=\"3\"\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c1\" colnum=\"1\"\u003e\u003c/div\u003e \u003cdiv align=\"char\" char=\".\" class=\"colspec\" colname=\"c2\" colnum=\"2\"\u003e\u003c/div\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c3\" colnum=\"3\"\u003e\u003c/div\u003e \u003cthead\u003e \u003ctr\u003e \u003cth align=\"left\" colname=\"c1\"\u003e \u003cp\u003eProperties\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c2\"\u003e \u003cp\u003eY-SL7 biodiesel\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c3\"\u003e \u003cp\u003eStandard\u003c/p\u003e \u003c/th\u003e \u003c/tr\u003e \u003c/thead\u003e \u003ctbody\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e\u003cb\u003eCetane number\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e \u003cp\u003e52.54\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e\u0026ge;\u0026thinsp;47\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e\u003cb\u003eIodine value\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e \u003cp\u003e75.71\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e120 max\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e\u003cb\u003eSaponification value\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e \u003cp\u003e234.51\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e-\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e\u003cb\u003eKinematic viscosity (mm2 s\u003c/b\u003e\u003csup\u003e\u003cb\u003e\u0026minus;\u0026thinsp;1\u003c/b\u003e\u003c/sup\u003e\u003cb\u003e)\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e \u003cp\u003e1.59\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e1.6\u0026ndash;6\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e\u003cb\u003eDensity (g cm\u003c/b\u003e\u003csup\u003e\u003cb\u003e3\u003c/b\u003e\u003c/sup\u003e\u003cb\u003e)\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e \u003cp\u003e0.99\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e0.87\u0026ndash;0.89\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003c/tbody\u003e \u003c/colgroup\u003e \u003c/table\u003e\u003c/div\u003e \u003c/p\u003e \u003c/div\u003e \u003cdiv id=\"Sec18\" class=\"Section2\"\u003e \u003ch2\u003eCarotenoids production and identification\u003c/h2\u003e \u003cp\u003eAlongside lipid production, \u003cem\u003eR. babjevae\u003c/em\u003e Y-SL7 also synthesizes carotenoids, which contribute to the red coloration of the cells and possess antioxidant properties [\u003cspan citationid=\"CR40\" class=\"CitationRef\"\u003e40\u003c/span\u003e]. The optimal conditions identified for lipid production (62% OMW, 2.2 g/L nitrogen, and a pH of 5.9) were also evaluated for carotenoid synthesis. Under these conditions, the \u003cem\u003eR. babjevae\u003c/em\u003e Y-SL7 strain produced 4.8 mg/L of carotenoids. This result demonstrates that OMW-based media could effectively serve as an inducer for carotenoid production. \u003cem\u003eR. babjevae\u003c/em\u003e Y-SL7 has previously been shown to produce carotenoids on various substrates such as glucose, xylose, crude glycerol, and even acid wheat bran hydrolysate (AWBH), with yields ranging from 1.8 to 6.2 mg/g [\u003cspan citationid=\"CR40\" class=\"CitationRef\"\u003e40\u003c/span\u003e, \u003cspan citationid=\"CR67\" class=\"CitationRef\"\u003e67\u003c/span\u003e]. These values surpass previous reports for the same species isolated from soil and grown on synthetic media, which yielded 189.2 \u0026micro;g/g [\u003cspan citationid=\"CR68\" class=\"CitationRef\"\u003e68\u003c/span\u003e]. Nonetheless, the carotenoid production observed is comparable to the values reported by Sharma and Ghoshal [\u003cspan citationid=\"CR69\" class=\"CitationRef\"\u003e69\u003c/span\u003e] when optimizing \u003cem\u003eR. mucilaginosa\u003c/em\u003e growth on various agro-industrial waste substrates. Similarly, Ghilardi et al. [\u003cspan citationid=\"CR70\" class=\"CitationRef\"\u003e70\u003c/span\u003e] reported that the highest total carotenoid production (7.3\u0026thinsp;\u0026plusmn;\u0026thinsp;0.6 mg/L) was achieved when \u003cem\u003eR. mucilaginosa\u003c/em\u003e was cultivated on OMW, with a carotenoid profile predominantly consisting of torulene and torularhodin. The \u003cem\u003eRhodotorula\u003c/em\u003e genus is recognized for its important carotenoids, such as β-carotene, γ-carotene torulene, and torularhodin. The relative abundance of these carotenoids can fluctuate considerably, depending on the growth conditions and the specific yeast strain used [\u003cspan citationid=\"CR71\" class=\"CitationRef\"\u003e71\u003c/span\u003e]. In this regard, RP-HPLC analysis was performed to identify and quantify the pigments produced by the Y-SL7 strain during its growth on OMW. The results showed two prominent peaks with retention times of 7.92 and 11.35 min (Fig.\u0026nbsp;\u003cspan refid=\"Fig4\" class=\"InternalRef\"\u003e4\u003c/span\u003ea). To identify these peaks, commercial standards of β-carotene, as well as purified torulene and torularhodin, were used (standard preparation is illustrated in Fig. S2 of the supplementary material). The chromatographic results demonstrated that the pigment composition from the Y-SL7 strain primarily included torulene (68.26%) and torularhodin (31.7%). When cultivated on crude glycerol, \u003cem\u003eR. babjevae\u003c/em\u003e Y-SL7 exhibited a similar carotenoid profile, primarily consisting of 63.7% torularhodin and 36.3% torulene [\u003cspan citationid=\"CR40\" class=\"CitationRef\"\u003e40\u003c/span\u003e]. However, when AWBH was used as the sole carbon source, in addition to torulene (51%) and torularhodin (36%), a small amount of β-carotene was detected, accounting for approximately 9.0% [\u003cspan citationid=\"CR67\" class=\"CitationRef\"\u003e67\u003c/span\u003e].\u003c/p\u003e \u003cp\u003e \u003c/p\u003e \u003cp\u003eCarotenoids are recognized for their antioxidant properties, protecting cellular membranes from photo-oxidative damage by neutralizing oxygen and peroxyl radicals [\u003cspan citationid=\"CR72\" class=\"CitationRef\"\u003e72\u003c/span\u003e]. The total antioxidant activity of carotenoids extracted from the Y-SL7 strain was evaluated through DPPH radical scavenging and ABTS assays. The antioxidant effectiveness (EC50) of these carotenoids was compared to ascorbic acid, used as a control (Fig.\u0026nbsp;\u003cspan refid=\"Fig4\" class=\"InternalRef\"\u003e4\u003c/span\u003eb). Y-SL7 carotenoids exhibited significantly higher DPPH scavenging activity (\u003cem\u003eP\u003c/em\u003e\u0026thinsp;\u0026lt;\u0026thinsp;0.05). However, in the ABTS assay, their activity was lower than that of the control, as ABTS is generally more suitable for assessing hydrophilic compounds [\u003cspan citationid=\"CR73\" class=\"CitationRef\"\u003e73\u003c/span\u003e]. Torulene and torularhodin both feature a β-ionone ring and the structural framework of vitamin A, which makes them potential vitamin A precursors. Their enhanced antioxidant activity, compared to β-carotene, can be attributed to the presence of additional conjugated double bonds at the C13 position [\u003cspan citationid=\"CR72\" class=\"CitationRef\"\u003e72\u003c/span\u003e]. On the other hand, the antimicrobial activity of OMW-derived carotenoids was investigated against \u003cem\u003eS. aureus\u003c/em\u003e (Gram-positive), as well as \u003cem\u003eS. Enteritidis\u003c/em\u003e and \u003cem\u003eE. coli\u003c/em\u003e (Gram-negative) bacteria. Figure\u0026nbsp;\u003cspan refid=\"Fig4\" class=\"InternalRef\"\u003e4\u003c/span\u003ec shows that these carotenoids exert antiproliferative effects on the tested bacteria, with MIC values ranging from 0.1 mg/mL for \u003cem\u003eS. aureus\u003c/em\u003e to 0.7 mg/mL for \u003cem\u003eE. coli\u003c/em\u003e (The antibacterial effect of Y-CL7 against \u003cem\u003eS. aureus\u003c/em\u003e with increasing concentrations is shown in Fig. S3 of the supplementary material). The antimicrobial potential of carotenoids extracted from the \u003cem\u003eRhodotorula\u003c/em\u003e genus has been previously reported in various studies [\u003cspan additionalcitationids=\"CR75\" citationid=\"CR74\" class=\"CitationRef\"\u003e74\u003c/span\u003e\u0026ndash;\u003cspan citationid=\"CR76\" class=\"CitationRef\"\u003e76\u003c/span\u003e]. It has been demonstrated that antibacterial activity is more pronounced in carotenoid extracts rich in torularhodin, which is particularly effective against Gram-positive bacteria [\u003cspan citationid=\"CR76\" class=\"CitationRef\"\u003e76\u003c/span\u003e]. The biological activities associated with these natural molecules position them as attractive candidates for diverse applications, such as feed additives in the food industry and protective agents in cosmetic and health products.\u003c/p\u003e \u003cp\u003eTo establish an efficient multi-metabolite production process, it is essential to understand cellular metabolic trade-offs, as achieving the right balance between competing metabolic pathways can significantly enhance both metabolite yield and process stability. Triglycerides and carotenoids, for instance, share several metabolic precursors and pathways. In \u003cem\u003eRhodotorula\u003c/em\u003e species, carotenoid biosynthesis can compete with lipid synthesis for common intermediates such as acetyl-CoA and fatty acids [\u003cspan citationid=\"CR18\" class=\"CitationRef\"\u003e18\u003c/span\u003e]. Despite this overlap, each class of metabolites is synthesized by distinct enzyme families and regulated through specific biosynthetic mechanisms. For carotenoid biosynthesis, \u003cem\u003eRhodotorula\u003c/em\u003e derives acetyl-CoA primarily through glycolysis, which is subsequently channelled into the mevalonate pathway to produce isopentenyl pyrophosphate (IPP), a key precursor in carotenoid synthesis [\u003cspan citationid=\"CR77\" class=\"CitationRef\"\u003e77\u003c/span\u003e]. This metabolic competition exemplifies the inherent trade-offs in cellular resource allocation, where carbon flux must be distributed among various biosynthetic demands. Moreover, carotenoid synthesis is closely linked to the cell\u0026rsquo;s oxidative stress response, as these pigments require fatty acids for their formation. These fatty acids could otherwise be used for other cellular functions such as triglyceride synthesis, which supports energy storage and membrane structure. In a study by Peng et al. [\u003cspan citationid=\"CR78\" class=\"CitationRef\"\u003e78\u003c/span\u003e], the biosynthesis of carotenoids and triglycerides in \u003cem\u003eR. diobovata\u003c/em\u003e and \u003cem\u003eR. babjevae\u003c/em\u003e was shown to follow similar kinetic patterns, suggesting coordinated regulation. Carbon balance analysis of \u003cem\u003eR. babjevae\u003c/em\u003e cultures revealed that approximately 68% of the substrate carbon was directed toward biomass formation, 23.5% toward triglyceride synthesis, and 4.4% toward carotenoid production. These findings highlight the cell\u0026rsquo;s metabolic prioritization and underscore the importance of optimizing culture conditions to enable balanced co-production of multiple high-value metabolites.\u003c/p\u003e \u003c/div\u003e"},{"header":"Conclusion","content":"\u003cp\u003eThis study underscores the significant potential of using OMW as a sustainable and renewable feedstock for bioconversion into microbial lipids through oleaginous yeast fermentation. The selected strain, \u003cem\u003eR. babjevae\u003c/em\u003e Y-SL7, demonstrated exceptional lipid accumulation capacity while efficiently detoxifying phenolic compounds in OMW, achieving a notable reduction in these toxic components. The fatty acid profile of the lipids produced, characterized by a high proportion of oleic acid, supports their suitability for biodiesel production, aligning with global efforts to develop greener alternatives to fossil fuels. Beyond lipid production, the bioconversion process also yielded valuable carotenoids, predominantly torulene and torularhodin, which exhibited potent antioxidant and antibacterial properties. This co-production not only enhances the economic feasibility of the process but also positions it as a promising avenue for generating multifunctional bio-based products. Furthermore, this approach addresses the dual challenge of mitigating the environmental impact of OMW, a by-product of the olive oil industry, and creating high-value bioproducts from waste. The ability of Y-SL7 to efficiently utilize OMW underscores its potential as a cornerstone in sustainable biotechnological applications. By integrating waste valorization with biofuel and bioactive compound production, this process offers an eco-friendly alternative to traditional OMW treatment methods, contributing to the advancement of circular economy principles and sustainable industrial practices\u003c/p\u003e"},{"header":"Declarations","content":"\u003cp\u003e\u003cstrong\u003eAppendix A. Supplementary data\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eSupplementary data associated with this article can be found in e-version of this paper online\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eAcknowledgements\u003c/strong\u003e\u0026nbsp;\u003c/p\u003e\n\u003cp\u003eWe would like to express our gratitude to the entire team at the CBS Unit of Analysis in the Centre of Biotechnology of Sfax, Tunisia, for their assistance with the analytical work. A special thanks to Mr. Slim Loukil, engineer at LBPE-CBS, for his invaluable help in OMW characterization.\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eCRediT authorship contribution statement\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eInes Ayadi: Achievement of manipulations, Methodology and Writing-Original draft preparation. Ali Gargouri: Validation, Project administration and Supervision. Mohamed Guerfali: Conceptualization, Methodology, Software, Data curation and Writing-Reviewing and Editing.\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eFunding\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eThis work was financially supported by the Ministry of Higher Education and Scientific Research, Tunisia, through the Contract Program allocation (2023\u0026ndash;2026) granted to the Laboratory of Molecular Biotechnology of Eukaryotes (LR15CBS02).\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eData Availability\u003c/strong\u003e\u0026nbsp;\u003c/p\u003e\n\u003cp\u003eAll data mentioned in the manuscript or available on request.\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eCompeting Interests\u0026nbsp;\u003c/strong\u003eThe authors declare that they have no competing interests related to this work. There are no financial, personal, or professional relationships that could be perceived as influencing the research or its findings.\u003c/p\u003e"},{"header":"References","content":"\u003col\u003e\n \u003cli\u003eAl Mualad, W.A.N., Bouchedja, D.N., Selmania, A., Maadadi, R., Ikhlef, A., Kabouche, Z., Elmechta, L., Boudjellal, A.: Recycling pollutants and used oils as substrates for producing useful lipids in the form of single-cell oil by the aerobic yeast \u003cem\u003eYarrowia lipolytica\u003c/em\u003e. Int. J. Environ. Res. 16, 97 (2022). https://doi.org/10.1007/s41742-022-00480-z\u003c/li\u003e\n \u003cli\u003eGufrana, T., Islam, H., Khare, S., Pandey, A., Radha, P.: In-situ transesterification of single-cell oil for biodiesel production: a review. Prep. Biochem. 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Front Microbiol. 13, 1088477 (2023). https://doi.org/10.3389/fmicb.2022.1088477\u003c/li\u003e\n \u003cli\u003eSarfaraz, R.M., Ahmad, M., Mahmood, A., Minhas, M.U., Yaqoob, A.: Development and evaluation of rosuvastatin calcium based microparticles for solubility enhancement: an in vitro study. Adv. Polym. Technol. 36, 433\u0026ndash;441 (2017). https://doi.org/ 10.1002/adv.21625.\u003c/li\u003e\n \u003cli\u003ePeng, T., Fakankun, I., Levin, D.B.: Accumulation of neutral lipids and carotenoids of \u003cem\u003eRhodotorula diobovata\u003c/em\u003e and \u003cem\u003eRhodosporidium babjevae\u003c/em\u003e cultivated under nitrogen-limited conditions with glycerol as a sole carbon source. FEMS Microbiol. Lett. 368, fnab126 (2021). https://doi.org/10.1093/femsle/fnab126\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":"[email protected]","identity":"waste-and-biomass-valorization","isNatureJournal":false,"hasQc":true,"allowDirectSubmit":false,"externalIdentity":"wave","sideBox":"Learn more about [Waste and Biomass Valorization](http://link.springer.com/journal/12649)","snPcode":"12649","submissionUrl":"https://submission.nature.com/new-submission/12649/3","title":"Waste and Biomass Valorization","twitterHandle":"","acdcEnabled":true,"dfaEnabled":true,"editorialSystem":"em","reportingPortfolio":"Springer Hybrid","inReviewEnabled":true,"inReviewRevisionsEnabled":false},"keywords":"Rhodotorula babjevae, microbial lipids, Olive mill wastewater, Industrial wastes, Carotenoids, Biodiesel ","lastPublishedDoi":"10.21203/rs.3.rs-5965608/v1","lastPublishedDoiUrl":"https://doi.org/10.21203/rs.3.rs-5965608/v1","license":{"name":"CC BY 4.0","url":"https://creativecommons.org/licenses/by/4.0/"},"manuscriptAbstract":"\u003cp\u003eProduced as a residual output of olive oil extraction, olive mill wastewater (OMW) is characterized by a high organic load and significant levels of phenolic compounds, posing notable environmental challenges. While it resists biodegradation, OMW serves as a nutrient-rich resource for microbial growth. In this study, OMW was used as renewable feedstock for microbial lipid production by oleaginous yeasts. Chemical characterization revealed that the OMW sample primarily contained 18 g/L total sugars, 3.4 g/L phenolic compounds, and high organic and mineral content of 85 and 15 g/L, respectively. Among the tested yeasts, \u003cem\u003eRhodotorula babjevae\u003c/em\u003eY-SL7 stood out with a lipid accumulation yield of approximately 38% and a significant phenolic compound detoxification rate of 53.7%. To enhance lipid yield, the most effective nitrogen source was selected following preliminary evaluation, and culture conditions were then optimized using response surface methodology (RSM) based on the Box-Behnken model, incorporating three independent factors. The lipids produced from OMW showed a fatty acid composition dominated by oleic acid (69%) and palmitic acid (23%). Predictive analyses of biodiesel properties suggest this oil could be advantageous for biodiesel production. Additionally, lipid production was accompanied by carotenoid synthesis, mainly torulene (68.2%) and torularhodin (31.7%), both demonstrating significant antibacterial and antioxidant activities. The capacity of Y-SL7 to detoxify OMW and generate valuable by-products positions this approach as a promising alternative to conventional OMW treatment methods.\u003c/p\u003e","manuscriptTitle":"Sustainable Valorization of Olive Mill Wastewater via Oleaginous Yeasts: Single-Cell Oil Production and Effluent Detoxification","msid":"","msnumber":"","nonDraftVersions":[{"code":1,"date":"2025-04-23 11:47:18","doi":"10.21203/rs.3.rs-5965608/v1","editorialEvents":[{"type":"communityComments","content":0},{"type":"decision","content":"Accept","date":"2025-05-19T15:50:26+00:00","index":"","fulltext":""},{"type":"reviewerAgreed","content":"","date":"2025-04-24T06:08:35+00:00","index":0,"fulltext":""},{"type":"reviewersInvited","content":"","date":"2025-04-20T06:45:53+00:00","index":"","fulltext":""},{"type":"editorInvited","content":"Waste and Biomass Valorization","date":"2025-04-20T06:37:43+00:00","index":"","fulltext":""},{"type":"editorAssigned","content":"","date":"2025-04-17T17:07:34+00:00","index":"","fulltext":""},{"type":"submitted","content":"Waste and Biomass Valorization","date":"2025-04-16T08:39:08+00:00","index":"","fulltext":""}],"status":"published","journal":{"display":true,"email":"[email protected]","identity":"waste-and-biomass-valorization","isNatureJournal":false,"hasQc":true,"allowDirectSubmit":false,"externalIdentity":"wave","sideBox":"Learn more about [Waste and Biomass Valorization](http://link.springer.com/journal/12649)","snPcode":"12649","submissionUrl":"https://submission.nature.com/new-submission/12649/3","title":"Waste and Biomass Valorization","twitterHandle":"","acdcEnabled":true,"dfaEnabled":true,"editorialSystem":"em","reportingPortfolio":"Springer Hybrid","inReviewEnabled":true,"inReviewRevisionsEnabled":false}}],"origin":"","ownerIdentity":"8433158b-1448-4769-84dc-de2abb2049f9","owner":[],"postedDate":"April 23rd, 2025","published":true,"recentEditorialEvents":[],"rejectedJournal":[],"revision":"","amendment":"","status":"published-in-journal","subjectAreas":[],"tags":[],"updatedAt":"2025-06-09T16:02:02+00:00","versionOfRecord":{"articleIdentity":"rs-5965608","link":"https://doi.org/10.1007/s12649-025-03131-4","journal":{"identity":"waste-and-biomass-valorization","isVorOnly":false,"title":"Waste and Biomass Valorization"},"publishedOn":"2025-06-02 15:57:27","publishedOnDateReadable":"June 2nd, 2025"},"versionCreatedAt":"2025-04-23 11:47:18","video":"","vorDoi":"10.1007/s12649-025-03131-4","vorDoiUrl":"https://doi.org/10.1007/s12649-025-03131-4","workflowStages":[]},"version":"v1","identity":"rs-5965608","journalConfig":"researchsquare"},"__N_SSP":true},"page":"/article/[identity]/[[...version]]","query":{"redirect":"/article/rs-5965608","identity":"rs-5965608","version":["v1"]},"buildId":"8U1c8b4HqxoKbykW_rLl7","isFallback":false,"isExperimentalCompile":false,"dynamicIds":[84888],"gssp":true,"scriptLoader":[]}