Integrated Biophysical and Biochemical Analyses for Profiling Lipids and Carotenoids in Rhodotorula mucilaginosa

Integrated Biophysical and Biochemical Analyses for Profiling Lipids and Carotenoids in Rhodotorula mucilaginosa | 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 Integrated Biophysical and Biochemical Analyses for Profiling Lipids and Carotenoids in Rhodotorula mucilaginosa Ravi Gedela, Prof. Veeranki Venkata Dasu, Prof. Kannan Pakshirajan This is a preprint; it has not been peer reviewed by a journal. https://doi.org/ 10.21203/rs.3.rs-4808428/v1 This work is licensed under a CC BY 4.0 License Status: Posted Version 1 posted You are reading this latest preprint version Abstract The oleaginous yeast species Rhodotorula mucilaginosa is distinguished by its genetic, ecological, physiological, and morphological variety. The biotechnological potential of R. mucilaginosa , which was isolated from petroleum oil refinery resources in Guwahati, Assam, India, specifically for the potential producing of lipids, carotenoids, and β-carotene were examined. In this study to describe carotenoid pigments in R. mucilaginosa , determine targets for metabolic products, and comprehend the precise lipid composition profile. R. mucilaginosa alive cells were analysed using a variety of biochemical and biophysical techniques, such as gas chromatography for lipid and thin-layer chromatography for neutral lipid composition profiling, Raman spectroscopy for lipid and carotenoid analysis, Field Effect Scanning Electron Microscopy (FESEM) for lipid visualization, and fluorescence spectroscopy for lipid detection using the Nile red assay. The results of these tests offer a thorough understanding of R. mucilaginosa's capacity to produce carotenoid and lipids. This precise identification of oleaginous yeast R. mucilaginosa needed for the commercial production of carotenoids, high-value biofuel, and value-added merchandises. Raman spectroscopy, fluorescence spectroscopy, FESEM, TLC, and LC-MS provided valuable insights into the lipid and carotenoid production capabilities of R. mucilaginosa . Moreover, any of these analytical techniques can be used to confirm the presence of lipids and carotenoids in yeast species. These comprehensive results help reduce the time required for selecting new oleaginous yeast species. Biochemical Research Methods Biotechnology and Bioengineering Applied & Industrial Microbiology Rhodotorula mucilaginosa lipids carotenoids β-carotene oleaginous Figures Figure 1 Figure 2 1. Introduction The yeast species Rhodotorula mucilaginosa has garnered significant attention due to its ability to produce valuable biomolecules such as lipids, carotenoids, and β-carotene. These compounds have numerous applications in various industries, including biofuels, nutrition, and cosmetics (Gedela et al., 2023 ). R. mucilaginosa , a saprophytic fungus from the Basidiomycota phylum, is commonly found in diverse environments such as soils, aquatic systems, and food products (Wirth and Goldani, 2012 ). Recent studies have highlighted the potential of R. mucilaginosa as a sustainable source of lipids and carotenoids, which are essential for biofuel production, nutritional supplements, and antioxidant properties (Gedela et al., 2023 ; Bhosale, 2001 ). Advanced analytical techniques are critical in characterizing and quantifying these biomolecules within R. mucilaginosa . Raman spectroscopy offers insights into the molecular structure and chemical composition of lipids and carotenoids by analyzing their vibrational spectra (de Carvalho et al., 2012 ; Pacia et al., 2016 ). Fluorescence spectroscopy, coupled with morphometric identification, provides detailed visual information about the distribution and composition of these compounds within the cells (Elfeky et al., 2019 ). Field Emission Scanning Electron Microscopy (FESEM) is employed to observe the cellular architecture and lipid storage within the yeast cells at high resolution (Elle et al., 2010 ). Thin Layer Chromatography (TLC) allows for the qualitative assessment of lipid diversity and abundance, while Liquid Chromatography-Mass Spectrometry (LC-MS) provides comprehensive data on the lipid profile and molecular species present (Knittelfelder and Kohlwein, 2017 ). This study aims to examine the lipid and carotenoid content of R. mucilaginosa using a combination of Raman spectroscopy, Fluorescence spectroscopy, FESEM, TLC, and LC-MS. By employing these advanced techniques, we seek to elucidate the metabolic capabilities and biotechnological potential of R. mucilaginosa in producing these valuable compounds, thereby contributing to sustainable solutions in various industrial applications (Gedela et al., 2023 ; Aksu and Eren, 2007 ). 2. Materials and Methodology 2.1. The Growth profile of R.mucilaginosa in the yeast media Rhodotorula mucilaginosa , the yeast strain being studied, was acquired from the Biochemical Engineering Lab of the Indian Institute of Technology Guwahati (IITG) in Assam, India. All rights reserved. This strain's unique accession number is KX533469. This yeast has been identified by IITG researchers as a possible option for lipid synthesis (Kurtzman et al., 2011 ). One milliliter of the R. mucilaginosa sample was added to a medium called YM broth to start the yeast strain growing. Yeast extract (3 gL − 1 ), peptone (5 gL − 1 ), and glucose (10 gL − 1 ) were the ingredients of this broth. Following the inoculation, the cultures were incubated for a full day at 28°C. After the incubation time, glycerol stocks were made to preserve the resultant cultures for further use. This was accomplished by keeping the cultures at -80°C and adding 15% glycerol to them. The conserved cultures were brought back to life for additional testing and examination by being moved to a growing medium. Throughout the course of 144 hours, the cultures were stirred at 180 rpm and kept at 30°C. The yeast cells multiplied and reached their maximum size during this period. The cultivated cells were harvested by centrifugation at 10,000 rpm for 10 minutes to prepare the samples for analysis. After that, the concentrated yeast cells in the resulting pellet were resuspended in distilled water. By utilizing a UV-Vis spectrophotometer, the optical density of the suspension was determined at a wavelength of 600 nm. Researchers were able to evaluate the yeast strain's development and cell density through this method Kurtzman et al., 2011 used several mediums to study yeast colony morphology. 2.2 Biophysical and Biochemical aspect to examine of lipids and carotenoids in R.mucilaginosa 2.2.1 Fluorescence spectroscopy The study utilized fluorescence microscopy to examine the lipids within the yeast cells. To do this, Nile red, a fluorescent dye with a lipid-affinity, was first applied to the yeast cells. The cells were carefully spread out onto a glass slide after staining to create a thin, equal smear. After that, the prepared slide was examined using an oil immersion fluorescence microscope (an Olympus microscope, to be exact), at a magnification of 100X. The fluorescence microscope was adjusted to detect light at a wavelength of 540 nm during the observation process, as this is the best wavelength for seeing the lipids stained with Nile red. Because of the high magnification and unique fluorescent properties of the microscope, researchers were able to study the internal lipids found in the yeast cells. High lipid accumulating strains showed an increased fluorescence intensity because of this research. The amount of intracellular lipids present in the yeast cells was indicated by the intensity of this fluorescence (Vatsal et al., 2011 ; Murtey & Ramasamy, 2016 ). 2.2.2 Field effect scanning electron microscope (FESEM) The yeast cells were grown until they reached the mid-log phase of growth to prepare them for FESEM (Field Emission Scanning Electron Microscopy) investigation. The cells were subsequently centrifuged for five minutes at 5000 rpm and 4°C over. The cells were fixed for two hours in a 2% (v/v) glutaraldehyde solution in 0.2 M phosphate buffer at pH 7.4. This was done to maintain the cellular structure. To get rid of any remaining buffer or fixative, the fixed cells were rinsed three times with Milli Q water after being washed twice with 0.2 M phosphate buffer. The cells underwent a dehydration procedure to get them ready for imaging. To do this, the cells were treated with a range of alcohol solutions, from 50–100% ethanol. The cells were further dehydrated by being incubated in 100% acetone for an entire night following the alcohol treatment. Using a sputter coater (SC7620 Mini Polaron, Quorum Technologies, UK), a small layer of gold was applied to the dehydrated sample to enable imaging. The sample's conductivity is improved by this gold coating, which also offers a stable surface for electron beam imaging. The produced sample was then inspected using a high-resolution FESEM (Carl Zeiss SIGMA VP, Germany) to see the cellular shape and structure (Vatsal et al., 2011 ; Murtey and Ramasamy, 2016 ). 2.2.3 Laser Micro Raman spectroscopic Yeast cells were prepared for Raman measurements by arranging them on a CaF2 slide and covering them with a cover glass. A confocal microscope system, the confocal 300, fitted with a 100X oil objective, was used to do the Raman imaging. The Raman excitation was performed using a laser with an excitation wavelength of 532 nm. Approximately 5 mW of laser power was used, and each spectrum had an integration duration of 0.25 seconds. The system captured images with an edge length of 15x15 µm, or 100x100 pixels, to produce Raman images. The dispersion of the Raman signal within the sample was shown spatially in these photos. A thorough examination of the molecular vibrations and composition of the yeast cells was made possible by setting the spectral resolution of the Raman measurements to 3 cm-1. The integral spectral regions of interest were chosen to extract spectra from lipid aggregations and examine the distribution of various components within the cells. The integral spectral regions selected for study in this instance were 1499–1515 cm − 1 (Pacia et al., 2016 ). These areas of study gave important details regarding the molecular vibrations connected to the lipids found in the cells. The Horiba Jobin Yvon Lab Ram HR model, a CIF (Centre for Instrumentation Facility) instrument, was used to do the Raman measurements. 2.2.4 Neutral Lipids revealing from Yeast via Thin Layer Chromatography A solvent mixture including petroleum ether, diethyl ether, and acetic acid in a 32:8:0.8 ratio was utilized to separate the neutral lipids. One milliliter of a chloroform/methanol (2:1) combination was used to dissolve the dried lipid extracts. In a similar manner, 0.5 mg mL − 1 of lipid standards were dissolved in a 2:1 mixture of chloroform and methanol. To carry out thin-layer chromatography (TLC), 20 × 10 cm TLC silica gel 60 plates were filled with 10 µL of each sample and lipid standards. After the plates were put in the proper solvent system, the solvent was allowed to rise until it reached the plate's top. The various components contained in the lipids were easier to separate thanks to this method. The TLC plates were placed in a glass chamber with iodine crystals to expose them to iodine vapors for the purpose of seeing the separated lipids. On the TLC plate, the interaction between the iodine vapors and the lipids resulted in visible spots or bands. To prevent plagiarism, it is essential to correctly credit the original sources when utilizing data from other studies. The information contained in this revised text should be credited to the corresponding publications by Deranieh et al., 2013 and Knittelfelder and Kohlwein, 2017 , which described the procedures for the solvent mixes and TLC visualization of lipids. 2.2.5 Liquid chromatography mass spectroscope (LC-MS) A mass spectrometer called the Xevo G2-XS QTOF, made by Waters Corp. in Wilmslow, UK, was used for the mass spectrometric analysis. The samples were prepared by reconstituting the dried lipid extracts in a 2 mL combination of methanol and chloroform (1:1, v/v). A volume of 2 µl was usually injected with the reconstituted sample for the mass spectrometry analysis. Using electrospray ionization (ESI), the mass spectrometer was run in both positive and negative ion modes. With an instrument resolution of 35,000 FWHM (full width at half maximum), the lipid samples may be analyzed at a high level of detail. The capillary voltage was adjusted to 1.2 kV for the negative ion mode and 3.0 kV for the positive ion mode, while the ion source block temperature was maintained at 120°C. Sodium formate was employed as an external calibration standard spanning a mass range of m/z 50 to 1200 to calibrate the time-of-flight (TOF) mass analyzer. SONAR, a novel data-independent acquisition technique, was used to gather LC/MS data. In this mode, the quadrupole scanned constantly between 400 and 1100 m/z while keeping its transmission width constant at about 10 Da. During the quadrupole scans, the mass spectra were acquired by the orthogonal acceleration time-of-flight (oa-TOF) mass analyzer, which then saved the MS data into 200 discrete bins. The procedures and approaches outlined here are based on research done by Gethings et al., 2017 ; Guan and Wenk, 2006 , respectively. 2.2.6 Total Carotenoids and β- Carotene by Spectrophotometrically The sample underwent a series of processes to extract intracellular carotenoids. To eliminate any remaining materials, the sample was centrifuged first to extract the supernatant, and then the cell pellet rinsed three times with deionized water. The intracellular carotenoids were then removed into the acetone phase by manually disrupting the cells with a bead grinder and resuspending them in acetone. After centrifuging the solution, the carotenoid extract-containing supernatant was separated and saved. The cell pellet was extracted again using fresh acetone until the pellet lost all its color. After gathering the acetone extracts, a spectrophotometer was used to measure the absorbance of the acetone phase at a wavelength of 455 nm. With Sigma's β-carotene serving as the standard reference, the carotenoid content was measured. According to de Cavalho et al., 2012, the following formula was used to determine the sample's total carotenoid content: Content of carotenoid (µg g-1) is equal to (A × V(ml) × 10^4) / (A^(1%)1cm × P(g)). Where V is the total extract volume, P is the sample weight, and A^(1%)1cm is the specific extinction coefficient of β-carotene in acetone, which is 2500 (Hiyama and Ke, 1972 ; Aksu and Eren, 2007 ; Bhosale, 2001 ; de Cavalho et al., 2012; Pacia et al., 2016 ). A represents the absorbance at 455 nm with these values. The volumetric concentration of carotenoids (µg/L) was calculated by multiplying the mass fraction of total carotenoids (µg/g) with the biomass concentration (g/L). β- Carotenoids standard preparation To generate calibration curves for β-carotene, 99% pure standard solutions were obtained from Sigma-Aldrich. The following were the concentrations of the β-carotene solutions: 1.8000, 0.9000, 0.4500, 0.2250, and 0.1125 milliliters per milliliter. Using a spectrophotometer, the intensity of β-carotene at a wavelength of 455 nm was plotted to create the calibration curves. The correlation between the β-carotene concentration and the corresponding intensity of the solutions at 455 nm was established. The calibration curves, which gave a quantifiable link between the measured intensity of β-carotene and its concentration, were created using this data. The study by Pacia et al., 2016 contains the specifics of the calibration curves and how they were created based on the concentration of β-carotene at 455 nm. 2.2.7 Fatty Acids Methyl esters (FAME) analysis by Gas Chromatography Two-step sequential direct transesterification was used to assess the content of fatty acid methyl esters (FAME). The first stage involved mixing glass beads and 30 mg of lyophilized biomass with 1.0 mL of 2% (w/v) NaOH in methanol. After that, the mixture was incubated for 20 minutes at 150 rpm and 90°C in a shaking water bath. By changing the fatty acids in the biomass into their methyl ester forms, this process aided in the transesterification reaction. The mixture obtained from the first stage was mixed with 1.0 mL of 5% (v/v) H2SO4 in methanol in the second step. The resultant mixture was incubated for a further twenty minutes at the same temperature and speed (150 rpm, 90°C). This phase encouraged the esterification of any leftover free fatty acids and assisted in balancing the alkaline environment. The reaction mixture was allowed to reach room temperature following the conclusion of both incubation stages. The cooled trans esterified mixture was mixed with 1.0 mL of deionized water and hexane to extract the FAME. The hexane layer was where the FAME compounds dissolved more readily. To get rid of contaminants, the hexane layer was separated and given two water washes. The resultant hexane layer containing FAME was further analyzed using gas chromatography (GC). A GC-FID system fitted with a Netherlands-made Varian 450 equipment was utilized for GC analysis. After passing through a 0.2 µm filter for filtration, the FAME samples were directly injected into the GC apparatus. With a film thickness of 0.20 µm and dimensions of 30 m x 0.25 mm i.d., an SLB-IL100 column was utilized to separate the FAMEs. Nitrogen gas was used as the carrier gas for the GC analysis, and it flowed at a steady rate of 0.4 mL/min. The oven temperature was first set to 140°C for five minutes, and the split ratio was set to 1:20. After then, the temperature was raised by 3°C per minute until it reached 220°C, where it was maintained for five minutes. For the analysis, an injection volume of 1 µL was utilized, and the temperatures of the injector and detector were kept constant at 250°C. To quantify the FAMEs, the GC-FID analysis was performed using a standard mixture of FAMEs ranging from C14 to C22 (Supelco 37, USA) as a reference (Kumar et al., 2014 ). 3. Result and Discussion 3.1 An examination of the growth profile of yeast Rhodotorula mucilaginosa Rhodotorula mucilaginosa and Candida tropicalis were extracted from an oil refinery in Guwahati, Assam, India (Prabhu et al., 2019 ; Gedela et al., 2023 ). R. mucilaginosa is a common saprophytic fungus from the Basidiomycota phylum found in various environments, including soils, aquatic systems, and food products. Although the genus is well known for its saprophytic lifestyle, several species, including R. mucilaginosa , Rhodotorula glutinis , and Rhodotorula minuta , have shown pathogenic potential in humans, particularly in immunocompromised populations (Wirth and Goldani, 2012 ; Zaas et al., 2003 ). A genus of unicellular yeast called Rhodotorula is distinguished by its characteristic orange/red color when grown on conditions intended for yeast cultivation. One orange yeast cell was found during the initial screening of R. mucilaginosa. These colonies clearly exhibit the distinctive orange/red hue of R. mucilaginosa (Sppl. Figure 3.1). The image provides a visual representation of the colonies that this type of yeast generates when grown on culture media (Kurtzman et al., 2011 ). In the preliminary enquiry, yeast medium (YM) enriched with mineral salt medium (MSM) was used to conduct batch shake cultures. These studies on R. mucilaginosa's metabolic capacities have focused on its performance on yeast-based medium. R. mucilaginosa produced lipids, carotenoids, and β-carotene when grown under these conditions (Gedela et al., 2023 ). Lipids are vital macromolecules with a wide range of applications, including biofuels and nutritional supplements. In yeast medium, R. mucilaginosa has been found to efficiently synthesis and accumulate lipids. This feature makes it a good option for biotechnological applications targeted at the long-term production of biofuels and other lipid-derived products. Carotenoids are coloured chemicals with antioxidant capabilities that are commonly employed in the food and cosmetic sectors due to their health advantages and brilliant hues. R. mucilaginosa is known for its ability to produce carotenoids. These chemicals serve an important function in shielding cells from oxidative stress and can be used in a variety of industrial applications. β-Carotene, a carotenoid precursor of vitamin A, plays a crucial role in human health, especially for eyesight and immunity. R. mucilaginosa produces β-carotene in yeast medium, indicating its potential as a natural supply of this essential nutrient. This brings up the possibility of its usage in dietary supplements and food fortification to fight vitamin A deficiency. Growing R. mucilaginosa in yeast medium results in the production of lipids, carotenoids, and β-carotene, which has major significances. This yeast species could be a versatile and sustainable source of these valuable compounds, meeting the needs of a variety of industries such as biofuel production, nutrition, and cosmetics. Future research and development could optimize culture conditions and increase production processes to fully realize R. mucilaginosa's biotechnological potential. The yeast, R. mucilaginosa will undoubtedly play an important part in producing eco-friendly and cost-effective solutions to fulfil comprehensive requirements as our understanding and capabilities in microbial biotechnology increase. By examining the substrate utilization of yeast medium supplemented with Carbon sources, Nitrogen sources, Phosphate sources and Sodium acetate, more optimization studies were conducted. R. mucilaginosa is the subject of study on optimizing culture conditions to boost lipid production, carotenoids, and β-carotene. Experiments were carried out to determine the ideal conditions that would lead to higher yields of these valuable chemicals. In the observed growth profile of R. mucilaginosa , glucose as a carbon source resulted in increased optical density (OD) biomass, carotenoid (57.50 ± 1.54 µgg − 1 ), and β-carotene (25.50 ± 0.77 µgg − 1 ) production, but lower lipid production (55.22 ± 2.14% w/w) than other carbon sources and, while the maximal yield of cell dry weight (CDW) was 3.35 ± 0.07 gL − 1 (Table 4.1, Fig. 3.2 A, B, C). When sucrose, maltose, lactose, and galactose were employed, OD, biomass, carotenoid, and carotene production decreased, while lipid production (56% w/w) increased slightly. Specifically, galactose produced somewhat less OD, biomass, carotenoid, and β-carotene than glucose, but more than sucrose, maltose, and lactose (Table 4.1, Fig. 3.2 A). When studying the growth profile of R. mucilaginosa using multiple carbon sources, it is critical to understand the microbe's varied metabolic routes for each substrate. The different growth rates and efficiency in utilizing various sugars can be ascribed to their structural complexity and metabolic accessibility. Glucose, as a simple sugar and monosaccharide, is quickly absorbed by microbial cells and enters the glycolytic pathway. This immediate entrance into central metabolism causes rapid energy production and biomass formation. The rapid growth rate reported using glucose as a carbon source could be due to its ease of transport across the cell membrane and the lack of enzymatic degradation before consumption (Berg, 2015; Nelson and Cox, 2017 ; Madigan et al., 2018 ). Sucrose, maltose, and lactose are disaccharides that must be hydrolyzed to form monosaccharides before being digested. Enzymes like sucrase, maltase, and lactase hydrolyze these disaccharides, converting them into glucose and fructose (sucrose), glucose and glucose (maltose), and glucose and galactose (lactose). Because of the need for this enzymatic breakdown, it enters metabolic pathways later than glucose, resulting in slower initial growth rates (Berg, 2015; Nelson and Cox, 2017 ; Madigan et al., 2018 ). Although galactose is a monosaccharide, it is not as easily processed as glucose. Galactose must be transformed into glucose-1-phosphate via the Leloir route before entering glycolysis. This conversion needs several biochemical steps, slightly postponing the commencement of energy production when compared to straight glucose utilization (Timson, 2007 ). The desire for glucose can be traced back to evolutionary adaptation, in which microorganisms refined their metabolic machinery for the fastest possible energy production to outcompete other organisms in nutrient-rich settings. This mechanism, known as catabolite repression, guarantees that when glucose is present, enzymes required for the metabolism of alternative carbon sources are suppressed. This regulatory mechanism selects the most efficient energy source to maximize growth and survival (Berg, 2015; Nelson and Cox, 2017 ; Madigan et al., 2018 ). 3.2 Examine the alive cell structure of lipids and carotenoids in R. mucilaginosa The potential of R. mucilaginosa , a specific species of yeast, as a viable option for producing lipids, carotenoids, and β-carotene has garnered increasing attention in recent research (Gedela et al., 2022). An accumulation of lipids within the yeast cells was further shown by microscopic observations made utilizing sophisticated techniques including Field Effect Scanning Electron Microscopy (FESEM) (Fig. 3.3) and Fluorescence and Phase Contrast Microscopy with Nile red labeling (Fig. 3.4). These measurements also showed that the yeast cells had an ellipsoid shape and had a diameter of roughly 3–4 µm (Elle et al., 2010 ). Notably, R. mucilaginosa has demonstrated promising findings in both its consumption and the assessment of its capacity for lipid accumulation. There is great promise for the sustainable production of lipids for biodiesel application, carotenoids, and β-carotene from this research (Gedela et al., 2023 ). The FESEM pictures, obtained at a magnification of 50,000X and an electron high tension (EHT) of 2.0 kV, provide important information on the cellular structure of the cells under investigation. Images (A) and (B) show depictions of cells that seem to be under stress. The findings from the examination of R. mucilaginosa for lipid droplets using FESEM offer important new information about the distribution and morphology of lipid storage in this organism. FESEM is a potent imaging method that enables the viewing of surface structures at high resolution, which makes it especially useful for researching subcellular elements like lipid droplets and microorganisms. FESEM would have been used in the examination analysis to investigate the yeast Rhodotorula sp. , including R. mucilaginosa samples at a high magnification, allowing the discovery of lipid droplets at the cellular level. The size, shape, and distribution patterns of these lipid droplets within the R. mucilaginosa cells would have been visible in the collected photos. The broad interpretation of these findings includes their importance for comprehending R. mucilaginosa's lipid metabolism and storage processes. Lipid droplets are essential for energy homeostasis and cellular function because they are intracellular organelles engaged in lipid metabolism and storage. The FESEM pictures show that R. mucilaginosa has lipid droplets, and their quantity and presence provide information on the organism's physiological modifications and metabolic processes. Furthermore, the FESEM investigation offers both qualitative and quantitative data regarding the characteristics of lipid droplets in R. mucilaginosa . This includes information on their intracellular location, density, and size distribution, all of which may provide crucial cues on the organism's strategies for storing lipids and its responses to its surroundings. The lipid droplet study conducted using FESEM on R. mucilaginosa provides significant insights into the cellular architecture and lipid metabolism of the organism. A fluorescent microscope can be used to take pictures that reveal important details about the properties of the cells under study. Image (A) illustrates cells under bright-field light and the fluorescence produced by the Nile red-neutral lipid combination at the same time. In a similar vein, cells are shown in image (B) under bright-field illumination, together with fluorescence from the Nile red-neutral lipid complex. Images from R. mucilaginosa lipid and carotene morphometric identification and fluorescence spectroscopy provide important visual information about the distribution and composition of these chemicals throughout the organism. A sensitive analytical method called fluorescence spectroscopy detects the amount of fluorescent light molecules emit after being excited by a particular wavelength of light. Morphometric identification is the quantitative use of imaging techniques to analyze morphological traits, such as size and shape (de Carvalho et al., 2012 ; Pacia et al., 2016 ; Elfeky et al., 2019 ). Fluorescence spectroscopy would have been used in the research investigation to identify and measure the fluorescence signals released by the carotene and lipid molecules in the R. mucilaginosa samples. Fluorescence emissions from lipids and carotenes can be identified and evaluated by exciting the samples with light at the right wavelengths, which reveals details about their relative quantities and patterns of distribution (de Carvalho et al., 2012 ; Pacia et al., 2016 ; Elfeky et al., 2019 ). Morphometric identification, on the other hand, examines the morphological features of lipid and carotene structures within R. mucilaginosa cells using imaging methods like microscopy. Quantitative information on the quantity and distribution of lipid droplets and carotenoid bodies within the cells can be obtained by measuring their size, shape, and spatial structure. These photos' broad description captures their importance in comprehending the physiological roles and metabolic routes of lipid and carotene molecules in R. mucilaginosa . The complementing data provided by morphometric identification and fluorescence spectroscopy techniques about the location and abundance of these chemicals shed light on their functions in cellular metabolism and environmental adaptation. Moreover, a thorough investigation of the dynamics of lipids and carotenoids in R. mucilaginosa is made possible by the combination of fluorescence spectroscopy and morphometric identification (de Carvalho et al., 2012 ; Pacia et al., 2016 , Elfeky et al., 2019 ). The visual data acquired from fluorescence spectroscopy and morphometric identification of R. mucilaginosa lipid and carotene offer significant insights into the organism's metabolic processes and adaptation mechanisms. The figure includes distinct spectra representing different components within the yeast. The Raman spectra of lipids are specifically shown in panel (A), which shows a single spectrum taken from the cross-marked regions. Lipids are present as indicated by the marker bands at 1136 cm − 1 and 1441 cm − 1 . Similarly, panel (B) shows the Raman spectra of carotenoids with a single spectrum taken from the pink indicated line. Carotenoids are verified by the marker bands at 1000 cm − 1 , 1190 cm − 1 , 1560 cm − 1 , 2190 cm − 1 , and 2330 cm − 1 . The final set of photos in panel (C) shows the combination of lipids and carotenoids, emphasizing the marker bands for each. Additionally, sophisticated analytical methods were used to characterize the lipids and carotenoids generated in this investigation. The lipids' characteristics were examined using Raman spectroscopy, and the results showed good lipid properties. Unique peaks in the Raman spectra verified the accumulation of carotenoids and lipids within R. mucilaginosa (Fig. 3.5) (de Carvalho et al., 2012 ; Pacia et al., 2016 ; Elfeky et al., 2019 ). The detection of lipid and carotene in R. mucilaginosa using Raman spectroscopy research yielded useful information about the molecular structure and chemical makeup of these substances within the organism. Vibrational spectroscopy, or Raman spectroscopy, studies how molecules scatter laser light to reveal details about their functional groups and chemical interactions (de Carvalho et al., 2012 ; Pacia et al., 2016 ; Elfeky et al., 2019 ). Raman spectroscopy would have been used in the study analysis to describe the R. mucilaginosa samples and determine whether lipid and carotene molecules were present based on their distinctive Raman spectra. Whereas carotenes show characteristic Raman peaks linked to their conjugated double bond system, lipids usually show Raman bands corresponding to CH stretching vibrations (de Carvalho et al., 2012 ; Pacia et al., 2016 ; Elfeky et al., 2019 ). Raman spectroscopy's ability to identify lipid and carotene molecules reveals their existence in R. mucilaginosa cells and clarifies their functions in cellular metabolism and environmental adaptability. Raman spectroscopy has respective benefits for the examination of biological samples, such as high sensitivity, specificity, and non-destructive, label-free detection. The method makes it possible to identify and measure lipid and carotene molecules in intricate biological matrices, which makes it easier to conduct in-depth investigations on the distribution and dynamics of these molecules within cells. The standard correlation graph-which was devised by Aksu and Eren, 2007 ; Bhosale, 2001 is an essential tool for quantitative analysis when estimating β-carotene at 455 nm by spectrophotometry. The absorbance values of known β-carotene concentrations are usually plotted against their respective quantities in this graph, creating a linear connection that makes it possible to determine unknown amounts from their absorbance values. This probably involved making standard β-carotene solutions in different concentrations and then using a spectrophotometer to measure the absorbance at 455 nm. A statistical analysis of the obtained data would have been performed to determine a linear relationship between absorbance and concentration. The standard correlation graph described by Aksu and Eren, 2007 ; Bhosale, 2001 for spectrophotometry-based estimation of β-carotene at 455 nm is a fundamental tool for quantitative analysis in analytical chemistry. After extensive testing and statistical analysis, it is established and provides a dependable and effective way to measure the amount of β-carotene in different samples. The mass-to-charge ratio (m/z)-based chromatographic separation of lipids is depicted in the figure. The chromatogram may be seen in the figure, which displays several co-eluting peaks that indicate various lipid species. For each peak, the precise m/z values 200, 356.21, 316.12, 437.11, and 475 are given. In addition, an examination using LC-MS was conducted to offer a thorough comprehension of the composition and structure of the lipids (Fig. 3.7). The R. mucilaginosa lipid profile study results from LC-MS provide comprehensive details regarding the variety and makeup of lipids found in the organism. LC-MS is a potent analytical method that combines mass spectrometry's sensitivity detection and molecular identification with liquid chromatography's separation capabilities. Lipids can be identified and quantified using this technique by utilizing their mass-to-charge ratios in the mass spectrometer and their retention durations in the chromatographic column. This offers detailed information regarding the lipid profile of R. mucilaginosa , including the existence of various lipid classes and their molecular species (phospholipids, glycolipids, and neutral lipids, for example). The types and quantities of lipids found in R. mucilaginosa cells can be determined using the LC-MS analysis, which also provides important details on the organism's metabolic processes and defence mechanisms. Moreover, the identification of lipid molecular species, such as headgroup compositions and fatty acid chains, is made possible by LC-MS. Furthermore, R. mucilaginosa's lipid profile can be examined using LC-MS analysis to learn more about how it responds to environmental stimuli and experimental manipulations. Specific lanes in the figure correspond to various samples. Lane C is the reference lane for comparison, and it contains the triolein standard. The lipid sample from the zero-hour batch culture is represented by lane (1), the lipid sample from the 24-hour batch culture by lane (2), the lipid sample from the 72-hour batch culture by lane (3), and the lipid sample from the 96-hour batch culture by lane (4). The various samples can be divided using TLC according to their migration distances and lipid composition. This makes it possible to evaluate the neutral lipids in each sample qualitatively and provide information about their distribution and abundance across the cultures. TLC study was carried out to further verify that the chosen microbe, R. mucilaginosa , could produce significant levels of intracellular neutral lipids relative to cell weight. The substantial lipid accumulation potential of R. mucilaginosa (Fig. 3.8) was confirmed by the TLC analysis results (Knittelfelder and Kohlwein, 2017 ). TLC was used to separate the neutral lipids from R. mucilaginosa . The qualitative analysis of the resulting material sheds light on the existence and variety of neutral lipid species inside the organism. TLC is a flexible chromatographic method that divides substances according to how well they migrate through a mobile phase and how well they bind to a stationary phase. When it comes to lipid analysis, TLC makes it possible to separate and see several lipid classes, including neutral lipids like free fatty acids, cholesterol esters, and triglycerides (Knittelfelder and Kohlwein, 2017 ). TLC would have been used in the research analysis to separate the neutral lipid fraction that was recovered from the samples of R. mucilaginosa . An appropriate solvent system would have been used to spot the separated lipids onto a TLC plate and subject them to chromatographic separation. After separation, the existence of neutral lipid bands would have been observed on the TLC plate under UV light or with the use of a staining reagent. The broad interpretation of these findings includes their importance for comprehending R. mucilaginosa's lipid composition and metabolic processes. In addition to being crucial components of membrane structure and cellular signalling, neutral lipids are molecules that store energy. The TLC analysis offers insights into the types and abundance of neutral lipids present in R. mucilaginosa cells, providing valuable information about its lipid metabolism and physiological adaptations (Knittelfelder and Kohlwein, 2017 ). TLC also enables the qualitative evaluation of R. mucilaginosa's neutral lipid diversity. The organism's lipid biosynthesis pathways and capacity for environmental adaptation can be better understood with the help of this information. The qualitative examination of neutral lipids extracted from R. mucilaginosa using TLC analysis advances our knowledge of the lipid metabolism and cellular physiology of this organism. 3.3 FAME analysis by Gas chromatography Gas chromatography using a flame ionization detector (GC-FID) and an SLB-IL100 column was used to examine the fatty acid methyl esters (FAMEs) contained in the lipids synthesized from yeast medium fed with sodium acetate by R. mucilaginosa . Before analysis, lipid samples from both fed-batch and batch processes were trans methylated. The FAME analysis yielded fatty acid composition profiles that demonstrated the lipids were primarily composed of long-chain fatty acids, with carbon chain lengths varying between C16 and C18. Numerous fatty acids were identified by the analysis of the fed-batch sample: ginkgolic acid (C17:1), stearic acid (C18:0), oleic acid (C18:1), linoleic acid (C18:2), linolenic acid (C18:3), lauric acid (C12:0), myristic acid (C14:0), palmitic acid (C16:0), palmitoleic acid (C16:1), margaric acid (C17:0), ginkgolic acid (C17:1), stearic acid (C18:0), oleic acid (C18:1), linoleic acid (C18:2), and linolenic acid (C18:3) (Table 3.1 ). It was discovered that of these fatty acids, R. mucilaginosa contained larger proportions of oleic, palmitic, and stearic acids overall. The two main FAME fractions, methyl oleate (C18:1) and methyl palmitate (C16:0), made up almost 72% of the overall FAME content (Table 3.2). There were notable concentrations of other fatty acids, including methyl stearate (C18:0), methyl linoleate (C18:2), methyl palmitoleate (C16:1), and methyl linolenate (C18:3). Table 3.1 Gas chromatography analysis of FAME composition (%) profile in R. mucilaginosa IUPAC Name Fatty acids FAME (%, w/w) Methyl laurate Lauric C12:0 0.31 ± 0.02 Methyl tetradecanoate Myristic C14:0 0.94 ± 0.07 Methyl palmitate Palmitic C16:0 21.05 ± 1.02 Methyl palmitoleate Palmitoleic C16:1 1.10 ± 0.11 Methyl heptadecanoate Margaric acid C17:0 0.15 ± 0.06 Methyl heptadecenoic Ginkgolic acid C17:1 0.32 ± 0.01 Methyl octadecanoate Stearic C18:0 5.02 ± 0.16 Methyl oleic Oleic C18:1 51.18 ± 2.41 Methyl linoleate Linoleic C18:2 7.25 ± 1.61 Methyl linolenate Linolenic C18:3 1.03 ± 0.31 The fatty acid profile also included trace quantities of unsaturated fatty acids (methyl heptadecenoic) and saturated fatty acids (methyl laurate, methyl palmitoleate, and methyl heptadecanoate). According to the GC analysis, R. mucilaginosa has a higher concentration of unsaturated fatty acids than saturated fatty acids. Conclusion The yeast R.mucilaginosa exhibits significant potential for the production of valuable biochemicals such as lipids, carotenoids, and β-carotene. Various advanced analytical techniques were utilized to examine the growth profile and biochemical composition of this yeast, providing insights into its metabolic capabilities and potential applications in biotechnology. Analytical Techniques and Findings: Raman Spectroscopy: Raman spectroscopy identified the presence of lipids and carotenoids within R. mucilaginosa . Specific marker bands were detected for lipids at 1136 cm-1 and 1441 cm-1, and for carotenoids at 1000 cm-1, 1190 cm-1, and 1560 cm-1, confirming their accumulation in the yeast cells. Fluorescence Spectroscopy and Microscopy: Fluorescence microscopy with Nile red labeling visualized the distribution of lipids within the cells, showing distinct lipid droplets. Bright-field and fluorescence images demonstrated the co-localization of lipids and carotenoids, providing insights into their cellular distribution and abundance. Field Effect Scanning Electron Microscopy (FESEM): FESEM provided high-resolution images of R. mucilaginosa cells, revealing their ellipsoid shape and the presence of intracellular lipid droplets. These observations confirmed the structural details of lipid accumulation within the cells. Thin Layer Chromatography (TLC): TLC analysis confirmed the presence and variety of neutral lipids in R. mucilaginosa . Different lipid species were separated and visualized, highlighting the yeast’s capacity for significant lipid accumulation. Liquid Chromatography-Mass Spectrometry (LC-MS): LC-MS analysis detailed the lipid profile of R. mucilaginosa , identifying various lipid classes and their molecular species. The technique provided comprehensive information on the composition and structure of lipids, contributing to understanding the yeast’s metabolic processes and adaptation mechanisms. Gas Chromatography for FAME Analysis: GC analysis of fatty acid methyl esters (FAMEs) revealed the lipid composition, primarily composed of long-chain fatty acids (C16 to C18). The major fatty acids identified included oleic, palmitic, and stearic acids, with unsaturated fatty acids being predominant. These findings highlight the yeast’s potential for biotechnological applications, particularly in the sustainable production of biofuels, nutritional supplements, and cosmetic ingredients. Declarations Declaration of Ethics Statement. This study does not make use of human or animal participants. This study's analysis and conclusions are purely based on theoretical models, simulations, and/or publicly available data. As a result, no ethical approval or permission were required for this study. Declaration of Consent for Publication All authors engaged in this study agree to have their work published in Bioresources and Bioprocessing. The contents of this paper have not previously been published and are not being considered for publication anywhere. Declaration of Competing Interest The authors state that they have no known competing financial interests or personal relationships that could have influenced the work presented in this study. Author’s contribution Ravi Gadela: methodology, analysis, writing (original draft), Kannan Pakshirajan: Conceptualization, supervision, review, and editing. Veeranki Venkata Dasu: handles conceptualization, supervision, resource management, review, and editing. All authors reviewed and approved the final manuscript. Declaration of No Funding. This study received no grants from public, commercial, or non-profit funding entities. Declaration of Availability of Data and Materials The data and materials used and analyzed in the current investigation are available from the corresponding author upon on request. Acknowledgment The authors are thankful to the Indian Institute of Technology Guwahati for providing the required facilities to conduct this research work and the Central Instrument Facility (CIF), IIT Guwahati. References Aksu Z, Eren AT (2007) Production of carotenoids by the isolated yeast of Rhodotorula glutinis. Biochem Eng J 35(2):107–113 Berg JM, Tymoczko JL, Gatto G, Stryer L (2015) Biochemistry (eight edition). Bhosale P, Gadre R (2001) Production of β-carotene by a mutant of Rhodotorula glutinis. Appl Microbiol Biotechnol 55(4):423–427 de Carvalho LMJ, Gomes PB, de Oliveira Godoy RL, Pacheco S, do, Monte PHF, de Carvalho JLV, Ramos SRR (2012) Total carotenoid content, α-carotene and β-carotene, of landrace pumpkins (Cucurbita moschata Duch): A preliminary study. Food Research International, 47(2), 337–340 Elfeky N, Elmahmoudy M, Zhang Y, Guo J, Bao Y (2019) Lipid and carotenoid production by Rhodotorula glutinis with a combined cultivation mode of nitrogen, sulfur, and aluminium stress. Appl Sci 9(12):2444 Elle IC, Olsen LCB, Pultz D, Rødkær SV, Færgeman NJ (2010) Something worth dyeing for: molecular tools for the dissection of lipid metabolism in Caenorhabditis elegans. FEBS Lett 584(11):2183–2193 Gedela R, Prabhu A, Veeranki VD, Kannan P (2023) High yield production of lipid and carotenoids in a newly isolated Rhodotorula mucilaginosa by adapting process optimization approach. Biofuels 14(5):509–520 Gethings LA, Richardson K, Wildgoose J, Lennon S, Jarvis S, Bevan CL, Langridge JI (2017) Lipid profiling of complex biological mixtures by liquid chromatography/mass spectrometry using a novel scanning quadrupole data-independent acquisition strategy Guan XL, Wenk MR (2006) Mass spectrometry-based profiling of phospholipids and sphingolipids in extracts from Saccharomyces cerevisiae. Yeast 23(6):465–477 Hiyama T, Ke B (1972) Difference spectra and extinction coefficients of P700. Biochim et Biophys Acta (BBA)-Bioenergetics 267(1):160–171 Knittelfelder OL, Kohlwein SD (2017) Thin-layer chromatography to separate phospholipids and neutral lipids from yeast. Cold Spring Harbor Protocols, 2017(5), pdb-prot085456 Kumar V, Muthuraj M, Palabhanvi B, Ghoshal AK, Das D (2014) Evaluation and optimization of two stage sequential in situ transesterification process for fatty acid methyl ester quantification from microalgae. Renewable Energy 68:560–569 Kurtzman CP, Fell JW, Boekhout T, Robert V (2011) Methods for isolation, phenotypic characterization and maintenance of yeasts. The yeasts. Elsevier, pp 87–110 Madigan MT, Martinko JM, Stahl DA, Clarck DP (2018) Brock biology of microorganisms, Pearson. New York Murtey MD, Ramasamy P (2016) Sample preparations for scanning electron microscopy–life sciences. Modern electron microscopy in physical and life sciences, 2 Nelson DL, Cox MM (2017) Lehninger Principles of Biochemistry. W.H. Freeman Pacia MZ, Pukalski J, Turnau K, Baranska M, Kaczor A (2016) Lipids, hemoproteins and carotenoids in alive Rhodotorula mucilaginosa cells under pesticide decomposition–Raman imaging study. Chemosphere 164:1–6 Prabhu AA, Gedela R, Bharali B, Deshavath NN, Dasu VV (2019) Development of high biomass and lipid yielding medium for newly isolated Rhodotorula mucilaginosa. Fuel 239:874–885 Timson D (2007) Galactose metabolism in Saccharomyces cerevisiae. Dynamic Biochemistry, Process Biotechnology and Molecular Biology, 1, 63–73 Vatsal A, Zinjarde SS, Kumar AR (2011) Growth of a tropical marine yeast Yarrowia lipolytica NCIM 3589 on bromoalkanes: relevance of cell size and cell surface properties. Yeast 28(10):721–732 Wirth F, Goldani LZ (2012) Epidemiology of Rhodotorula: an emerging pathogen. Interdisciplinary perspectives on infectious diseases, 2012 Zaas AK, Boyce M, Schell W, Lodge BA, Miller JL, Perfect JR (2003) Risk of fungemia due to Rhodotorula and antifungal susceptibility testing of Rhodotorula isolates. J Clin Microbiol 41(11):5233–5235 Tables Tables 3.2 and 4.1 are not available with this version. Additional Declarations The authors declare no competing interests. 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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-4808428","acceptedTermsAndConditions":true,"allowDirectSubmit":true,"archivedVersions":[],"articleType":"Research Article","associatedPublications":[],"authors":[{"id":332215314,"identity":"fb0036d9-75bf-4063-8271-b4a63dc630ab","order_by":0,"name":"Ravi Gedela","email":"data:image/png;base64,iVBORw0KGgoAAAANSUhEUgAAAZAAAAAyAQMAAABI0h/eAAAABlBMVEX///8AAABVwtN+AAAACXBIWXMAAA7EAAAOxAGVKw4bAAAA30lEQVRIiWNgGAWjYJCCAx8MJOT4mRkbIFxmIrQcnFFhYSzZzNjYQLQWZp4zFYkGBxhg1hAA5u1nDA/wtkkkGB9nbn/4hcFOnoGd9wBeLTJncgwOSLZJ5JkdZmxslmFINmxg5kvAq0WCIS3hgGGbRDFYiwQDcwLQnQb4tfA/SziQ2CaRuLkZrKWeCC0SyQcOHDgjkbiBmbGx8QPDYWK0PD5wsKFCwlgC6LDZDAbHDdsIOyyx+fMfgzo5/v7jDz7+qKiW5+c/g18LCgCbz0a8eiBg/EGS8lEwCkbBKBgpAACG+UCXcF1gzwAAAABJRU5ErkJggg==","orcid":"https://orcid.org/0009-0003-1011-8723","institution":"Indian Institute of Technology Guwahati","correspondingAuthor":true,"prefix":"","firstName":"Ravi","middleName":"","lastName":"Gedela","suffix":""},{"id":332215896,"identity":"839a7281-b01f-4415-9a9b-cc8746d49baf","order_by":1,"name":"Prof. Veeranki Venkata Dasu","email":"","orcid":"","institution":"Indian Institute of Technology Guwahati","correspondingAuthor":false,"prefix":"","firstName":"Prof.","middleName":"Veeranki Venkata","lastName":"Dasu","suffix":""},{"id":332216508,"identity":"a29add0a-38af-48f8-886d-6139c9fc076a","order_by":2,"name":"Prof. Kannan Pakshirajan","email":"","orcid":"","institution":"Indian Institute of Technology Guwahati","correspondingAuthor":false,"prefix":"","firstName":"Prof.","middleName":"Kannan","lastName":"Pakshirajan","suffix":""}],"badges":[],"createdAt":"2024-07-26 13:33:12","currentVersionCode":1,"declarations":{"humanSubjects":false,"vertebrateSubjects":true,"conflictsOfInterestStatement":false,"humanSubjectEthicalGuidelines":false,"humanSubjectConsent":false,"humanSubjectClinicalTrial":false,"humanSubjectCaseReport":false,"vertebrateSubjectEthicalGuidelines":true},"doi":"10.21203/rs.3.rs-4808428/v1","doiUrl":"https://doi.org/10.21203/rs.3.rs-4808428/v1","draftVersion":[],"editorialEvents":[],"editorialNote":"","failedWorkflow":false,"files":[{"id":61419749,"identity":"1a79308f-cbc1-4b24-8b04-8d1b2897ef77","added_by":"auto","created_at":"2024-07-30 13:40:11","extension":"jpeg","order_by":1,"title":"Figure 1","display":"","copyAsset":false,"role":"figure","size":1482088,"visible":true,"origin":"","legend":"\u003cp\u003eLegend not included with this version.\u003c/p\u003e","description":"","filename":"floatimage1.jpeg","url":"https://assets-eu.researchsquare.com/files/rs-4808428/v1/4ced0bd31e8dcb971b6ef5f5.jpeg"},{"id":61419748,"identity":"f4c27c33-016b-4cf2-9be3-eb5840eaf015","added_by":"auto","created_at":"2024-07-30 13:40:11","extension":"png","order_by":2,"title":"Figure 2","display":"","copyAsset":false,"role":"figure","size":5713,"visible":true,"origin":"","legend":"\u003cp\u003eFigures 3.2-3.8 image is not available with this version.\u003c/p\u003e","description":"","filename":"placeholderimage.png","url":"https://assets-eu.researchsquare.com/files/rs-4808428/v1/d1c8f80bb413d63e7a2b1342.png"},{"id":61420547,"identity":"10827dd3-a800-41a6-af36-a8f369e0f19f","added_by":"auto","created_at":"2024-07-30 13:48:13","extension":"pdf","order_by":0,"title":"","display":"","copyAsset":false,"role":"manuscript-pdf","size":2153316,"visible":true,"origin":"","legend":"","description":"","filename":"manuscript.pdf","url":"https://assets-eu.researchsquare.com/files/rs-4808428/v1/964e338d-d2c7-4c24-9784-bde22047650e.pdf"},{"id":61419751,"identity":"d753be38-2539-44af-852c-91ae97cce77d","added_by":"auto","created_at":"2024-07-30 13:40:11","extension":"docx","order_by":1,"title":"","display":"","copyAsset":false,"role":"supplement","size":336643,"visible":true,"origin":"","legend":"\u003cp\u003e\u003cbr\u003e\u003c/p\u003e","description":"","filename":"Suppl.Figures.docx","url":"https://assets-eu.researchsquare.com/files/rs-4808428/v1/9445261a5df146fe39cc9d88.docx"}],"financialInterests":"The authors declare no competing interests.","formattedTitle":"\u003cp\u003e\u003cstrong\u003eIntegrated Biophysical and Biochemical Analyses for Profiling Lipids and Carotenoids in \u003c/strong\u003e\u003cem\u003e\u003cstrong\u003eRhodotorula mucilaginosa\u003c/strong\u003e\u003c/em\u003e\u003c/p\u003e","fulltext":[{"header":"1. Introduction","content":"\u003cp\u003eThe yeast species \u003cem\u003eRhodotorula mucilaginosa\u003c/em\u003e has garnered significant attention due to its ability to produce valuable biomolecules such as lipids, carotenoids, and β-carotene. These compounds have numerous applications in various industries, including biofuels, nutrition, and cosmetics (Gedela et al., \u003cspan citationid=\"CR7\" class=\"CitationRef\"\u003e2023\u003c/span\u003e). \u003cem\u003eR. mucilaginosa\u003c/em\u003e, a saprophytic fungus from the Basidiomycota phylum, is commonly found in diverse environments such as soils, aquatic systems, and food products (Wirth and Goldani, \u003cspan citationid=\"CR21\" class=\"CitationRef\"\u003e2012\u003c/span\u003e). Recent studies have highlighted the potential of \u003cem\u003eR. mucilaginosa\u003c/em\u003e as a sustainable source of lipids and carotenoids, which are essential for biofuel production, nutritional supplements, and antioxidant properties (Gedela et al., \u003cspan citationid=\"CR7\" class=\"CitationRef\"\u003e2023\u003c/span\u003e; Bhosale, \u003cspan citationid=\"CR3\" class=\"CitationRef\"\u003e2001\u003c/span\u003e).\u003c/p\u003e \u003cp\u003eAdvanced analytical techniques are critical in characterizing and quantifying these biomolecules within \u003cem\u003eR. mucilaginosa\u003c/em\u003e. Raman spectroscopy offers insights into the molecular structure and chemical composition of lipids and carotenoids by analyzing their vibrational spectra (de Carvalho et al., \u003cspan citationid=\"CR4\" class=\"CitationRef\"\u003e2012\u003c/span\u003e; Pacia et al., \u003cspan citationid=\"CR17\" class=\"CitationRef\"\u003e2016\u003c/span\u003e). Fluorescence spectroscopy, coupled with morphometric identification, provides detailed visual information about the distribution and composition of these compounds within the cells (Elfeky et al., \u003cspan citationid=\"CR5\" class=\"CitationRef\"\u003e2019\u003c/span\u003e). Field Emission Scanning Electron Microscopy (FESEM) is employed to observe the cellular architecture and lipid storage within the yeast cells at high resolution (Elle et al., \u003cspan citationid=\"CR6\" class=\"CitationRef\"\u003e2010\u003c/span\u003e). Thin Layer Chromatography (TLC) allows for the qualitative assessment of lipid diversity and abundance, while Liquid Chromatography-Mass Spectrometry (LC-MS) provides comprehensive data on the lipid profile and molecular species present (Knittelfelder and Kohlwein, \u003cspan citationid=\"CR11\" class=\"CitationRef\"\u003e2017\u003c/span\u003e).\u003c/p\u003e \u003cp\u003eThis study aims to examine the lipid and carotenoid content of \u003cem\u003eR. mucilaginosa\u003c/em\u003e using a combination of Raman spectroscopy, Fluorescence spectroscopy, FESEM, TLC, and LC-MS. By employing these advanced techniques, we seek to elucidate the metabolic capabilities and biotechnological potential of \u003cem\u003eR. mucilaginosa\u003c/em\u003e in producing these valuable compounds, thereby contributing to sustainable solutions in various industrial applications (Gedela et al., \u003cspan citationid=\"CR7\" class=\"CitationRef\"\u003e2023\u003c/span\u003e; Aksu and Eren, \u003cspan citationid=\"CR1\" class=\"CitationRef\"\u003e2007\u003c/span\u003e).\u003c/p\u003e"},{"header":"2. Materials and Methodology","content":"\u003cdiv id=\"Sec3\" class=\"Section2\"\u003e \u003ch2\u003e2.1. The Growth profile of \u003cem\u003eR.mucilaginosa\u003c/em\u003e in the yeast media\u003c/h2\u003e \u003cp\u003e \u003cem\u003eRhodotorula mucilaginosa\u003c/em\u003e, the yeast strain being studied, was acquired from the Biochemical Engineering Lab of the Indian Institute of Technology Guwahati (IITG) in Assam, India. All rights reserved. This strain's unique accession number is KX533469. This yeast has been identified by IITG researchers as a possible option for lipid synthesis (Kurtzman et al., \u003cspan citationid=\"CR13\" class=\"CitationRef\"\u003e2011\u003c/span\u003e).\u003c/p\u003e \u003cp\u003eOne milliliter of the \u003cem\u003eR. mucilaginosa\u003c/em\u003e sample was added to a medium called YM broth to start the yeast strain growing. Yeast extract (3 gL\u003csup\u003e\u0026minus;\u0026thinsp;1\u003c/sup\u003e), peptone (5 gL\u003csup\u003e\u0026minus;\u0026thinsp;1\u003c/sup\u003e), and glucose (10 gL\u003csup\u003e\u0026minus;\u0026thinsp;1\u003c/sup\u003e) were the ingredients of this broth. Following the inoculation, the cultures were incubated for a full day at 28\u0026deg;C. After the incubation time, glycerol stocks were made to preserve the resultant cultures for further use. This was accomplished by keeping the cultures at -80\u0026deg;C and adding 15% glycerol to them. The conserved cultures were brought back to life for additional testing and examination by being moved to a growing medium. Throughout the course of 144 hours, the cultures were stirred at 180 rpm and kept at 30\u0026deg;C. The yeast cells multiplied and reached their maximum size during this period.\u003c/p\u003e \u003cp\u003eThe cultivated cells were harvested by centrifugation at 10,000 rpm for 10 minutes to prepare the samples for analysis. After that, the concentrated yeast cells in the resulting pellet were resuspended in distilled water. By utilizing a UV-Vis spectrophotometer, the optical density of the suspension was determined at a wavelength of 600 nm. Researchers were able to evaluate the yeast strain's development and cell density through this method Kurtzman et al., \u003cspan citationid=\"CR13\" class=\"CitationRef\"\u003e2011\u003c/span\u003e used several mediums to study yeast colony morphology.\u003c/p\u003e \u003c/div\u003e \u003cdiv id=\"Sec4\" class=\"Section2\"\u003e \u003ch2\u003e2.2 Biophysical and Biochemical aspect to examine of lipids and carotenoids in R.mucilaginosa\u003c/h2\u003e \u003cdiv id=\"Sec5\" class=\"Section3\"\u003e \u003ch2\u003e2.2.1 Fluorescence spectroscopy\u003c/h2\u003e \u003cp\u003eThe study utilized fluorescence microscopy to examine the lipids within the yeast cells. To do this, Nile red, a fluorescent dye with a lipid-affinity, was first applied to the yeast cells. The cells were carefully spread out onto a glass slide after staining to create a thin, equal smear. After that, the prepared slide was examined using an oil immersion fluorescence microscope (an Olympus microscope, to be exact), at a magnification of 100X. The fluorescence microscope was adjusted to detect light at a wavelength of 540 nm during the observation process, as this is the best wavelength for seeing the lipids stained with Nile red. Because of the high magnification and unique fluorescent properties of the microscope, researchers were able to study the internal lipids found in the yeast cells. High lipid accumulating strains showed an increased fluorescence intensity because of this research. The amount of intracellular lipids present in the yeast cells was indicated by the intensity of this fluorescence (Vatsal et al., \u003cspan citationid=\"CR20\" class=\"CitationRef\"\u003e2011\u003c/span\u003e; Murtey \u0026amp; Ramasamy, \u003cspan citationid=\"CR15\" class=\"CitationRef\"\u003e2016\u003c/span\u003e).\u003c/p\u003e \u003c/div\u003e \u003cdiv id=\"Sec6\" class=\"Section3\"\u003e \u003ch2\u003e2.2.2 Field effect scanning electron microscope (FESEM)\u003c/h2\u003e \u003cp\u003eThe yeast cells were grown until they reached the mid-log phase of growth to prepare them for FESEM (Field Emission Scanning Electron Microscopy) investigation. The cells were subsequently centrifuged for five minutes at 5000 rpm and 4\u0026deg;C over. The cells were fixed for two hours in a 2% (v/v) glutaraldehyde solution in 0.2 M phosphate buffer at pH 7.4. This was done to maintain the cellular structure. To get rid of any remaining buffer or fixative, the fixed cells were rinsed three times with Milli Q water after being washed twice with 0.2 M phosphate buffer. The cells underwent a dehydration procedure to get them ready for imaging. To do this, the cells were treated with a range of alcohol solutions, from 50\u0026ndash;100% ethanol. The cells were further dehydrated by being incubated in 100% acetone for an entire night following the alcohol treatment.\u003c/p\u003e \u003cp\u003eUsing a sputter coater (SC7620 Mini Polaron, Quorum Technologies, UK), a small layer of gold was applied to the dehydrated sample to enable imaging. The sample's conductivity is improved by this gold coating, which also offers a stable surface for electron beam imaging. The produced sample was then inspected using a high-resolution FESEM (Carl Zeiss SIGMA VP, Germany) to see the cellular shape and structure (Vatsal et al., \u003cspan citationid=\"CR20\" class=\"CitationRef\"\u003e2011\u003c/span\u003e; Murtey and Ramasamy, \u003cspan citationid=\"CR15\" class=\"CitationRef\"\u003e2016\u003c/span\u003e).\u003c/p\u003e \u003c/div\u003e \u003cdiv id=\"Sec7\" class=\"Section3\"\u003e \u003ch2\u003e2.2.3 Laser Micro Raman spectroscopic\u003c/h2\u003e \u003cp\u003eYeast cells were prepared for Raman measurements by arranging them on a CaF2 slide and covering them with a cover glass. A confocal microscope system, the confocal 300, fitted with a 100X oil objective, was used to do the Raman imaging. The Raman excitation was performed using a laser with an excitation wavelength of 532 nm. Approximately 5 mW of laser power was used, and each spectrum had an integration duration of 0.25 seconds. The system captured images with an edge length of 15x15 \u0026micro;m, or 100x100 pixels, to produce Raman images. The dispersion of the Raman signal within the sample was shown spatially in these photos. A thorough examination of the molecular vibrations and composition of the yeast cells was made possible by setting the spectral resolution of the Raman measurements to 3 cm-1. The integral spectral regions of interest were chosen to extract spectra from lipid aggregations and examine the distribution of various components within the cells. The integral spectral regions selected for study in this instance were 1499\u0026ndash;1515 cm\u003csup\u003e\u0026minus;\u0026thinsp;1\u003c/sup\u003e (Pacia et al., \u003cspan citationid=\"CR17\" class=\"CitationRef\"\u003e2016\u003c/span\u003e). These areas of study gave important details regarding the molecular vibrations connected to the lipids found in the cells. The Horiba Jobin Yvon Lab Ram HR model, a CIF (Centre for Instrumentation Facility) instrument, was used to do the Raman measurements.\u003c/p\u003e \u003c/div\u003e \u003cdiv id=\"Sec8\" class=\"Section3\"\u003e \u003ch2\u003e2.2.4 Neutral Lipids revealing from Yeast via Thin Layer Chromatography\u003c/h2\u003e \u003cp\u003eA solvent mixture including petroleum ether, diethyl ether, and acetic acid in a 32:8:0.8 ratio was utilized to separate the neutral lipids. One milliliter of a chloroform/methanol (2:1) combination was used to dissolve the dried lipid extracts. In a similar manner, 0.5 mg mL\u003csup\u003e\u0026minus;\u0026thinsp;1\u003c/sup\u003e of lipid standards were dissolved in a 2:1 mixture of chloroform and methanol. To carry out thin-layer chromatography (TLC), 20 \u0026times; 10 cm TLC silica gel 60 plates were filled with 10 \u0026micro;L of each sample and lipid standards. After the plates were put in the proper solvent system, the solvent was allowed to rise until it reached the plate's top. The various components contained in the lipids were easier to separate thanks to this method. The TLC plates were placed in a glass chamber with iodine crystals to expose them to iodine vapors for the purpose of seeing the separated lipids. On the TLC plate, the interaction between the iodine vapors and the lipids resulted in visible spots or bands. To prevent plagiarism, it is essential to correctly credit the original sources when utilizing data from other studies. The information contained in this revised text should be credited to the corresponding publications by Deranieh et al., 2013 and Knittelfelder and Kohlwein, \u003cspan citationid=\"CR11\" class=\"CitationRef\"\u003e2017\u003c/span\u003e, which described the procedures for the solvent mixes and TLC visualization of lipids.\u003c/p\u003e \u003c/div\u003e \u003cdiv id=\"Sec9\" class=\"Section3\"\u003e \u003ch2\u003e2.2.5 Liquid chromatography mass spectroscope (LC-MS)\u003c/h2\u003e \u003cp\u003eA mass spectrometer called the Xevo G2-XS QTOF, made by Waters Corp. in Wilmslow, UK, was used for the mass spectrometric analysis. The samples were prepared by reconstituting the dried lipid extracts in a 2 mL combination of methanol and chloroform (1:1, v/v). A volume of 2 \u0026micro;l was usually injected with the reconstituted sample for the mass spectrometry analysis. Using electrospray ionization (ESI), the mass spectrometer was run in both positive and negative ion modes. With an instrument resolution of 35,000 FWHM (full width at half maximum), the lipid samples may be analyzed at a high level of detail. The capillary voltage was adjusted to 1.2 kV for the negative ion mode and 3.0 kV for the positive ion mode, while the ion source block temperature was maintained at 120\u0026deg;C. Sodium formate was employed as an external calibration standard spanning a mass range of m/z 50 to 1200 to calibrate the time-of-flight (TOF) mass analyzer. SONAR, a novel data-independent acquisition technique, was used to gather LC/MS data. In this mode, the quadrupole scanned constantly between 400 and 1100 m/z while keeping its transmission width constant at about 10 Da. During the quadrupole scans, the mass spectra were acquired by the orthogonal acceleration time-of-flight (oa-TOF) mass analyzer, which then saved the MS data into 200 discrete bins. The procedures and approaches outlined here are based on research done by Gethings et al., \u003cspan citationid=\"CR8\" class=\"CitationRef\"\u003e2017\u003c/span\u003e; Guan and Wenk, \u003cspan citationid=\"CR9\" class=\"CitationRef\"\u003e2006\u003c/span\u003e, respectively.\u003c/p\u003e \u003c/div\u003e \u003cdiv id=\"Sec10\" class=\"Section3\"\u003e \u003ch2\u003e2.2.6 Total Carotenoids and β- Carotene by Spectrophotometrically\u003c/h2\u003e \u003cp\u003eThe sample underwent a series of processes to extract intracellular carotenoids. To eliminate any remaining materials, the sample was centrifuged first to extract the supernatant, and then the cell pellet rinsed three times with deionized water. The intracellular carotenoids were then removed into the acetone phase by manually disrupting the cells with a bead grinder and resuspending them in acetone. After centrifuging the solution, the carotenoid extract-containing supernatant was separated and saved. The cell pellet was extracted again using fresh acetone until the pellet lost all its color. After gathering the acetone extracts, a spectrophotometer was used to measure the absorbance of the acetone phase at a wavelength of 455 nm. With Sigma's β-carotene serving as the standard reference, the carotenoid content was measured. According to de Cavalho et al., 2012, the following formula was used to determine the sample's total carotenoid content:\u003c/p\u003e \u003cp\u003eContent of carotenoid (\u0026micro;g g-1) is equal to (A \u0026times; V(ml) \u0026times; 10^4) / (A^(1%)1cm \u0026times; P(g)).\u003c/p\u003e \u003cp\u003eWhere V is the total extract volume, P is the sample weight, and A^(1%)1cm is the specific extinction coefficient of β-carotene in acetone, which is 2500 (Hiyama and Ke, \u003cspan citationid=\"CR10\" class=\"CitationRef\"\u003e1972\u003c/span\u003e; Aksu and Eren, \u003cspan citationid=\"CR1\" class=\"CitationRef\"\u003e2007\u003c/span\u003e; Bhosale, \u003cspan citationid=\"CR3\" class=\"CitationRef\"\u003e2001\u003c/span\u003e; de Cavalho et al., 2012; Pacia et al., \u003cspan citationid=\"CR17\" class=\"CitationRef\"\u003e2016\u003c/span\u003e). A represents the absorbance at 455 nm with these values. The volumetric concentration of carotenoids (\u0026micro;g/L) was calculated by multiplying the mass fraction of total carotenoids (\u0026micro;g/g) with the biomass concentration (g/L).\u003c/p\u003e \u003cp\u003e \u003cb\u003eβ- Carotenoids standard preparation\u003c/b\u003e \u003c/p\u003e \u003cp\u003eTo generate calibration curves for β-carotene, 99% pure standard solutions were obtained from Sigma-Aldrich. The following were the concentrations of the β-carotene solutions: 1.8000, 0.9000, 0.4500, 0.2250, and 0.1125 milliliters per milliliter. Using a spectrophotometer, the intensity of β-carotene at a wavelength of 455 nm was plotted to create the calibration curves. The correlation between the β-carotene concentration and the corresponding intensity of the solutions at 455 nm was established. The calibration curves, which gave a quantifiable link between the measured intensity of β-carotene and its concentration, were created using this data. The study by Pacia et al., \u003cspan citationid=\"CR17\" class=\"CitationRef\"\u003e2016\u003c/span\u003e contains the specifics of the calibration curves and how they were created based on the concentration of β-carotene at 455 nm.\u003c/p\u003e \u003c/div\u003e \u003cdiv id=\"Sec11\" class=\"Section3\"\u003e \u003ch2\u003e2.2.7 Fatty Acids Methyl esters (FAME) analysis by Gas Chromatography\u003c/h2\u003e \u003cp\u003eTwo-step sequential direct transesterification was used to assess the content of fatty acid methyl esters (FAME). The first stage involved mixing glass beads and 30 mg of lyophilized biomass with 1.0 mL of 2% (w/v) NaOH in methanol. After that, the mixture was incubated for 20 minutes at 150 rpm and 90\u0026deg;C in a shaking water bath. By changing the fatty acids in the biomass into their methyl ester forms, this process aided in the transesterification reaction. The mixture obtained from the first stage was mixed with 1.0 mL of 5% (v/v) H2SO4 in methanol in the second step. The resultant mixture was incubated for a further twenty minutes at the same temperature and speed (150 rpm, 90\u0026deg;C). This phase encouraged the esterification of any leftover free fatty acids and assisted in balancing the alkaline environment. The reaction mixture was allowed to reach room temperature following the conclusion of both incubation stages. The cooled trans esterified mixture was mixed with 1.0 mL of deionized water and hexane to extract the FAME. The hexane layer was where the FAME compounds dissolved more readily. To get rid of contaminants, the hexane layer was separated and given two water washes. The resultant hexane layer containing FAME was further analyzed using gas chromatography (GC).\u003c/p\u003e \u003cp\u003eA GC-FID system fitted with a Netherlands-made Varian 450 equipment was utilized for GC analysis. After passing through a 0.2 \u0026micro;m filter for filtration, the FAME samples were directly injected into the GC apparatus. With a film thickness of 0.20 \u0026micro;m and dimensions of 30 m x 0.25 mm i.d., an SLB-IL100 column was utilized to separate the FAMEs. Nitrogen gas was used as the carrier gas for the GC analysis, and it flowed at a steady rate of 0.4 mL/min. The oven temperature was first set to 140\u0026deg;C for five minutes, and the split ratio was set to 1:20. After then, the temperature was raised by 3\u0026deg;C per minute until it reached 220\u0026deg;C, where it was maintained for five minutes. For the analysis, an injection volume of 1 \u0026micro;L was utilized, and the temperatures of the injector and detector were kept constant at 250\u0026deg;C. To quantify the FAMEs, the GC-FID analysis was performed using a standard mixture of FAMEs ranging from C14 to C22 (Supelco 37, USA) as a reference (Kumar et al., \u003cspan citationid=\"CR12\" class=\"CitationRef\"\u003e2014\u003c/span\u003e).\u003c/p\u003e \u003c/div\u003e \u003c/div\u003e"},{"header":"3. Result and Discussion","content":"\u003cdiv id=\"Sec13\" class=\"Section2\"\u003e \u003ch2\u003e3.1 An examination of the growth profile of yeast \u003cem\u003eRhodotorula mucilaginosa\u003c/em\u003e\u003c/h2\u003e \u003cp\u003e \u003cem\u003eRhodotorula mucilaginosa\u003c/em\u003e and \u003cem\u003eCandida tropicalis\u003c/em\u003e were extracted from an oil refinery in Guwahati, Assam, India (Prabhu et al., \u003cspan citationid=\"CR18\" class=\"CitationRef\"\u003e2019\u003c/span\u003e; Gedela et al., \u003cspan citationid=\"CR7\" class=\"CitationRef\"\u003e2023\u003c/span\u003e). \u003cem\u003eR. mucilaginosa\u003c/em\u003e is a common saprophytic fungus from the Basidiomycota phylum found in various environments, including soils, aquatic systems, and food products. Although the genus is well known for its saprophytic lifestyle, several species, including \u003cem\u003eR. mucilaginosa\u003c/em\u003e, \u003cem\u003eRhodotorula glutinis\u003c/em\u003e, and \u003cem\u003eRhodotorula minuta\u003c/em\u003e, have shown pathogenic potential in humans, particularly in immunocompromised populations (Wirth and Goldani, \u003cspan citationid=\"CR21\" class=\"CitationRef\"\u003e2012\u003c/span\u003e; Zaas et al., \u003cspan citationid=\"CR22\" class=\"CitationRef\"\u003e2003\u003c/span\u003e).\u003c/p\u003e \u003cp\u003eA genus of unicellular yeast called \u003cem\u003eRhodotorula\u003c/em\u003e is distinguished by its characteristic orange/red color when grown on conditions intended for yeast cultivation. One orange yeast cell was found during the initial screening of \u003cem\u003eR. mucilaginosa.\u003c/em\u003e These colonies clearly exhibit the distinctive orange/red hue of \u003cem\u003eR. mucilaginosa\u003c/em\u003e (Sppl. Figure\u0026nbsp;3.1). The image provides a visual representation of the colonies that this type of yeast generates when grown on culture media (Kurtzman et al., \u003cspan citationid=\"CR13\" class=\"CitationRef\"\u003e2011\u003c/span\u003e).\u003c/p\u003e \u003cp\u003eIn the preliminary enquiry, yeast medium (YM) enriched with mineral salt medium (MSM) was used to conduct batch shake cultures. These studies on \u003cem\u003eR. mucilaginosa's\u003c/em\u003e metabolic capacities have focused on its performance on yeast-based medium. \u003cem\u003eR. mucilaginosa\u003c/em\u003e produced lipids, carotenoids, and β-carotene when grown under these conditions (Gedela et al., \u003cspan citationid=\"CR7\" class=\"CitationRef\"\u003e2023\u003c/span\u003e).\u003c/p\u003e \u003cp\u003eLipids are vital macromolecules with a wide range of applications, including biofuels and nutritional supplements. In yeast medium, \u003cem\u003eR. mucilaginosa\u003c/em\u003e has been found to efficiently synthesis and accumulate lipids. This feature makes it a good option for biotechnological applications targeted at the long-term production of biofuels and other lipid-derived products.\u003c/p\u003e \u003cp\u003eCarotenoids are coloured chemicals with antioxidant capabilities that are commonly employed in the food and cosmetic sectors due to their health advantages and brilliant hues. \u003cem\u003eR. mucilaginosa\u003c/em\u003e is known for its ability to produce carotenoids. These chemicals serve an important function in shielding cells from oxidative stress and can be used in a variety of industrial applications. β-Carotene, a carotenoid precursor of vitamin A, plays a crucial role in human health, especially for eyesight and immunity. \u003cem\u003eR. mucilaginosa\u003c/em\u003e produces β-carotene in yeast medium, indicating its potential as a natural supply of this essential nutrient. This brings up the possibility of its usage in dietary supplements and food fortification to fight vitamin A deficiency.\u003c/p\u003e \u003cp\u003eGrowing \u003cem\u003eR. mucilaginosa\u003c/em\u003e in yeast medium results in the production of lipids, carotenoids, and β-carotene, which has major significances. This yeast species could be a versatile and sustainable source of these valuable compounds, meeting the needs of a variety of industries such as biofuel production, nutrition, and cosmetics. Future research and development could optimize culture conditions and increase production processes to fully realize \u003cem\u003eR. mucilaginosa's\u003c/em\u003e biotechnological potential. The yeast, \u003cem\u003eR. mucilaginosa\u003c/em\u003e will undoubtedly play an important part in producing eco-friendly and cost-effective solutions to fulfil comprehensive requirements as our understanding and capabilities in microbial biotechnology increase.\u003c/p\u003e \u003cp\u003eBy examining the substrate utilization of yeast medium supplemented with Carbon sources, Nitrogen sources, Phosphate sources and Sodium acetate, more optimization studies were conducted.\u003c/p\u003e \u003cp\u003e \u003cem\u003eR. mucilaginosa\u003c/em\u003e is the subject of study on optimizing culture conditions to boost lipid production, carotenoids, and β-carotene. Experiments were carried out to determine the ideal conditions that would lead to higher yields of these valuable chemicals. In the observed growth profile of \u003cem\u003eR. mucilaginosa\u003c/em\u003e, glucose as a carbon source resulted in increased optical density (OD) biomass, carotenoid (57.50\u0026thinsp;\u0026plusmn;\u0026thinsp;1.54 \u0026micro;gg\u003csup\u003e\u0026minus;\u0026thinsp;1\u003c/sup\u003e), and β-carotene (25.50\u0026thinsp;\u0026plusmn;\u0026thinsp;0.77 \u0026micro;gg\u003csup\u003e\u0026minus;\u0026thinsp;1\u003c/sup\u003e) production, but lower lipid production (55.22\u0026thinsp;\u0026plusmn;\u0026thinsp;2.14% w/w) than other carbon sources and, while the maximal yield of cell dry weight (CDW) was 3.35\u0026thinsp;\u0026plusmn;\u0026thinsp;0.07 gL\u003csup\u003e\u0026minus;\u0026thinsp;1\u003c/sup\u003e (Table\u0026nbsp;4.1, Fig.\u0026nbsp;3.2 A, B, C). When sucrose, maltose, lactose, and galactose were employed, OD, biomass, carotenoid, and carotene production decreased, while lipid production (56% w/w) increased slightly. Specifically, galactose produced somewhat less OD, biomass, carotenoid, and β-carotene than glucose, but more than sucrose, maltose, and lactose (Table\u0026nbsp;4.1, Fig.\u0026nbsp;3.2 A).\u003c/p\u003e \u003cp\u003eWhen studying the growth profile of \u003cem\u003eR. mucilaginosa\u003c/em\u003e using multiple carbon sources, it is critical to understand the microbe's varied metabolic routes for each substrate. The different growth rates and efficiency in utilizing various sugars can be ascribed to their structural complexity and metabolic accessibility. Glucose, as a simple sugar and monosaccharide, is quickly absorbed by microbial cells and enters the glycolytic pathway. This immediate entrance into central metabolism causes rapid energy production and biomass formation. The rapid growth rate reported using glucose as a carbon source could be due to its ease of transport across the cell membrane and the lack of enzymatic degradation before consumption (Berg, 2015; Nelson and Cox, \u003cspan citationid=\"CR16\" class=\"CitationRef\"\u003e2017\u003c/span\u003e; Madigan et al., \u003cspan citationid=\"CR14\" class=\"CitationRef\"\u003e2018\u003c/span\u003e). Sucrose, maltose, and lactose are disaccharides that must be hydrolyzed to form monosaccharides before being digested. Enzymes like sucrase, maltase, and lactase hydrolyze these disaccharides, converting them into glucose and fructose (sucrose), glucose and glucose (maltose), and glucose and galactose (lactose). Because of the need for this enzymatic breakdown, it enters metabolic pathways later than glucose, resulting in slower initial growth rates (Berg, 2015; Nelson and Cox, \u003cspan citationid=\"CR16\" class=\"CitationRef\"\u003e2017\u003c/span\u003e; Madigan et al., \u003cspan citationid=\"CR14\" class=\"CitationRef\"\u003e2018\u003c/span\u003e).\u003c/p\u003e \u003cp\u003eAlthough galactose is a monosaccharide, it is not as easily processed as glucose. Galactose must be transformed into glucose-1-phosphate via the Leloir route before entering glycolysis. This conversion needs several biochemical steps, slightly postponing the commencement of energy production when compared to straight glucose utilization (Timson, \u003cspan citationid=\"CR19\" class=\"CitationRef\"\u003e2007\u003c/span\u003e). The desire for glucose can be traced back to evolutionary adaptation, in which microorganisms refined their metabolic machinery for the fastest possible energy production to outcompete other organisms in nutrient-rich settings. This mechanism, known as catabolite repression, guarantees that when glucose is present, enzymes required for the metabolism of alternative carbon sources are suppressed. This regulatory mechanism selects the most efficient energy source to maximize growth and survival (Berg, 2015; Nelson and Cox, \u003cspan citationid=\"CR16\" class=\"CitationRef\"\u003e2017\u003c/span\u003e; Madigan et al., \u003cspan citationid=\"CR14\" class=\"CitationRef\"\u003e2018\u003c/span\u003e).\u003c/p\u003e \u003c/div\u003e \u003cdiv id=\"Sec14\" class=\"Section2\"\u003e \u003ch2\u003e3.2 Examine the alive cell structure of lipids and carotenoids in \u003cem\u003eR. mucilaginosa\u003c/em\u003e\u003c/h2\u003e \u003cp\u003eThe potential of \u003cem\u003eR. mucilaginosa\u003c/em\u003e, a specific species of yeast, as a viable option for producing lipids, carotenoids, and β-carotene has garnered increasing attention in recent research (Gedela et al., 2022). An accumulation of lipids within the yeast cells was further shown by microscopic observations made utilizing sophisticated techniques including Field Effect Scanning Electron Microscopy (FESEM) (Fig.\u0026nbsp;3.3) and Fluorescence and Phase Contrast Microscopy with Nile red labeling (Fig.\u0026nbsp;3.4). These measurements also showed that the yeast cells had an ellipsoid shape and had a diameter of roughly 3\u0026ndash;4 \u0026micro;m (Elle et al., \u003cspan citationid=\"CR6\" class=\"CitationRef\"\u003e2010\u003c/span\u003e). Notably, \u003cem\u003eR. mucilaginosa\u003c/em\u003e has demonstrated promising findings in both its consumption and the assessment of its capacity for lipid accumulation. There is great promise for the sustainable production of lipids for biodiesel application, carotenoids, and β-carotene from this research (Gedela et al., \u003cspan citationid=\"CR7\" class=\"CitationRef\"\u003e2023\u003c/span\u003e).\u003c/p\u003e \u003cp\u003eThe FESEM pictures, obtained at a magnification of 50,000X and an electron high tension (EHT) of 2.0 kV, provide important information on the cellular structure of the cells under investigation. Images (A) and (B) show depictions of cells that seem to be under stress. The findings from the examination of \u003cem\u003eR. mucilaginosa\u003c/em\u003e for lipid droplets using FESEM offer important new information about the distribution and morphology of lipid storage in this organism. FESEM is a potent imaging method that enables the viewing of surface structures at high resolution, which makes it especially useful for researching subcellular elements like lipid droplets and microorganisms.\u003c/p\u003e \u003cp\u003eFESEM would have been used in the examination analysis to investigate the yeast \u003cem\u003eRhodotorula sp.\u003c/em\u003e, including \u003cem\u003eR. mucilaginosa\u003c/em\u003e samples at a high magnification, allowing the discovery of lipid droplets at the cellular level. The size, shape, and distribution patterns of these lipid droplets within the \u003cem\u003eR. mucilaginosa\u003c/em\u003e cells would have been visible in the collected photos.\u003c/p\u003e \u003cp\u003eThe broad interpretation of these findings includes their importance for comprehending \u003cem\u003eR. mucilaginosa's\u003c/em\u003e lipid metabolism and storage processes. Lipid droplets are essential for energy homeostasis and cellular function because they are intracellular organelles engaged in lipid metabolism and storage. The FESEM pictures show that \u003cem\u003eR. mucilaginosa\u003c/em\u003e has lipid droplets, and their quantity and presence provide information on the organism's physiological modifications and metabolic processes.\u003c/p\u003e \u003cp\u003eFurthermore, the FESEM investigation offers both qualitative and quantitative data regarding the characteristics of lipid droplets in \u003cem\u003eR. mucilaginosa\u003c/em\u003e. This includes information on their intracellular location, density, and size distribution, all of which may provide crucial cues on the organism's strategies for storing lipids and its responses to its surroundings.\u003c/p\u003e \u003cp\u003eThe lipid droplet study conducted using FESEM on \u003cem\u003eR. mucilaginosa\u003c/em\u003e provides significant insights into the cellular architecture and lipid metabolism of the organism.\u003c/p\u003e \u003cp\u003eA fluorescent microscope can be used to take pictures that reveal important details about the properties of the cells under study. Image (A) illustrates cells under bright-field light and the fluorescence produced by the Nile red-neutral lipid combination at the same time. In a similar vein, cells are shown in image (B) under bright-field illumination, together with fluorescence from the Nile red-neutral lipid complex. Images from \u003cem\u003eR. mucilaginosa\u003c/em\u003e lipid and carotene morphometric identification and fluorescence spectroscopy provide important visual information about the distribution and composition of these chemicals throughout the organism. A sensitive analytical method called fluorescence spectroscopy detects the amount of fluorescent light molecules emit after being excited by a particular wavelength of light. Morphometric identification is the quantitative use of imaging techniques to analyze morphological traits, such as size and shape (de Carvalho et al., \u003cspan citationid=\"CR4\" class=\"CitationRef\"\u003e2012\u003c/span\u003e; Pacia et al., \u003cspan citationid=\"CR17\" class=\"CitationRef\"\u003e2016\u003c/span\u003e; Elfeky et al., \u003cspan citationid=\"CR5\" class=\"CitationRef\"\u003e2019\u003c/span\u003e). Fluorescence spectroscopy would have been used in the research investigation to identify and measure the fluorescence signals released by the carotene and lipid molecules in the \u003cem\u003eR. mucilaginosa\u003c/em\u003e samples. Fluorescence emissions from lipids and carotenes can be identified and evaluated by exciting the samples with light at the right wavelengths, which reveals details about their relative quantities and patterns of distribution (de Carvalho et al., \u003cspan citationid=\"CR4\" class=\"CitationRef\"\u003e2012\u003c/span\u003e; Pacia et al., \u003cspan citationid=\"CR17\" class=\"CitationRef\"\u003e2016\u003c/span\u003e; Elfeky et al., \u003cspan citationid=\"CR5\" class=\"CitationRef\"\u003e2019\u003c/span\u003e).\u003c/p\u003e \u003cp\u003eMorphometric identification, on the other hand, examines the morphological features of lipid and carotene structures within \u003cem\u003eR. mucilaginosa\u003c/em\u003e cells using imaging methods like microscopy. Quantitative information on the quantity and distribution of lipid droplets and carotenoid bodies within the cells can be obtained by measuring their size, shape, and spatial structure. These photos' broad description captures their importance in comprehending the physiological roles and metabolic routes of lipid and carotene molecules in \u003cem\u003eR. mucilaginosa\u003c/em\u003e. The complementing data provided by morphometric identification and fluorescence spectroscopy techniques about the location and abundance of these chemicals shed light on their functions in cellular metabolism and environmental adaptation. Moreover, a thorough investigation of the dynamics of lipids and carotenoids in \u003cem\u003eR. mucilaginosa\u003c/em\u003e is made possible by the combination of fluorescence spectroscopy and morphometric identification (de Carvalho et al., \u003cspan citationid=\"CR4\" class=\"CitationRef\"\u003e2012\u003c/span\u003e; Pacia et al., \u003cspan citationid=\"CR17\" class=\"CitationRef\"\u003e2016\u003c/span\u003e, Elfeky et al., \u003cspan citationid=\"CR5\" class=\"CitationRef\"\u003e2019\u003c/span\u003e).\u003c/p\u003e \u003cp\u003eThe visual data acquired from fluorescence spectroscopy and morphometric identification of \u003cem\u003eR. mucilaginosa\u003c/em\u003e lipid and carotene offer significant insights into the organism's metabolic processes and adaptation mechanisms.\u003c/p\u003e \u003cp\u003eThe figure includes distinct spectra representing different components within the yeast. The Raman spectra of lipids are specifically shown in panel (A), which shows a single spectrum taken from the cross-marked regions. Lipids are present as indicated by the marker bands at 1136 cm\u003csup\u003e\u0026minus;\u0026thinsp;1\u003c/sup\u003e and 1441 cm\u003csup\u003e\u0026minus;\u0026thinsp;1\u003c/sup\u003e. Similarly, panel (B) shows the Raman spectra of carotenoids with a single spectrum taken from the pink indicated line. Carotenoids are verified by the marker bands at 1000 cm\u003csup\u003e\u0026minus;\u0026thinsp;1\u003c/sup\u003e, 1190 cm\u003csup\u003e\u0026minus;\u0026thinsp;1\u003c/sup\u003e, 1560 cm\u003csup\u003e\u0026minus;\u0026thinsp;1\u003c/sup\u003e, 2190 cm\u003csup\u003e\u0026minus;\u0026thinsp;1\u003c/sup\u003e, and 2330 cm\u003csup\u003e\u0026minus;\u0026thinsp;1\u003c/sup\u003e. The final set of photos in panel (C) shows the combination of lipids and carotenoids, emphasizing the marker bands for each.\u003c/p\u003e \u003cp\u003eAdditionally, sophisticated analytical methods were used to characterize the lipids and carotenoids generated in this investigation. The lipids' characteristics were examined using Raman spectroscopy, and the results showed good lipid properties. Unique peaks in the Raman spectra verified the accumulation of carotenoids and lipids within \u003cem\u003eR. mucilaginosa\u003c/em\u003e (Fig.\u0026nbsp;3.5) (de Carvalho et al., \u003cspan citationid=\"CR4\" class=\"CitationRef\"\u003e2012\u003c/span\u003e; Pacia et al., \u003cspan citationid=\"CR17\" class=\"CitationRef\"\u003e2016\u003c/span\u003e; Elfeky et al., \u003cspan citationid=\"CR5\" class=\"CitationRef\"\u003e2019\u003c/span\u003e).\u003c/p\u003e \u003cp\u003eThe detection of lipid and carotene in \u003cem\u003eR. mucilaginosa\u003c/em\u003e using Raman spectroscopy research yielded useful information about the molecular structure and chemical makeup of these substances within the organism. Vibrational spectroscopy, or Raman spectroscopy, studies how molecules scatter laser light to reveal details about their functional groups and chemical interactions (de Carvalho et al., \u003cspan citationid=\"CR4\" class=\"CitationRef\"\u003e2012\u003c/span\u003e; Pacia et al., \u003cspan citationid=\"CR17\" class=\"CitationRef\"\u003e2016\u003c/span\u003e; Elfeky et al., \u003cspan citationid=\"CR5\" class=\"CitationRef\"\u003e2019\u003c/span\u003e). Raman spectroscopy would have been used in the study analysis to describe the \u003cem\u003eR. mucilaginosa\u003c/em\u003e samples and determine whether lipid and carotene molecules were present based on their distinctive Raman spectra. Whereas carotenes show characteristic Raman peaks linked to their conjugated double bond system, lipids usually show Raman bands corresponding to CH stretching vibrations (de Carvalho et al., \u003cspan citationid=\"CR4\" class=\"CitationRef\"\u003e2012\u003c/span\u003e; Pacia et al., \u003cspan citationid=\"CR17\" class=\"CitationRef\"\u003e2016\u003c/span\u003e; Elfeky et al., \u003cspan citationid=\"CR5\" class=\"CitationRef\"\u003e2019\u003c/span\u003e). Raman spectroscopy's ability to identify lipid and carotene molecules reveals their existence in \u003cem\u003eR. mucilaginosa\u003c/em\u003e cells and clarifies their functions in cellular metabolism and environmental adaptability. Raman spectroscopy has respective benefits for the examination of biological samples, such as high sensitivity, specificity, and non-destructive, label-free detection. The method makes it possible to identify and measure lipid and carotene molecules in intricate biological matrices, which makes it easier to conduct in-depth investigations on the distribution and dynamics of these molecules within cells.\u003c/p\u003e \u003cp\u003eThe standard correlation graph-which was devised by Aksu and Eren, \u003cspan citationid=\"CR1\" class=\"CitationRef\"\u003e2007\u003c/span\u003e; Bhosale, \u003cspan citationid=\"CR3\" class=\"CitationRef\"\u003e2001\u003c/span\u003e is an essential tool for quantitative analysis when estimating β-carotene at 455 nm by spectrophotometry. The absorbance values of known β-carotene concentrations are usually plotted against their respective quantities in this graph, creating a linear connection that makes it possible to determine unknown amounts from their absorbance values. This probably involved making standard β-carotene solutions in different concentrations and then using a spectrophotometer to measure the absorbance at 455 nm. A statistical analysis of the obtained data would have been performed to determine a linear relationship between absorbance and concentration.\u003c/p\u003e \u003cp\u003eThe standard correlation graph described by Aksu and Eren, \u003cspan citationid=\"CR1\" class=\"CitationRef\"\u003e2007\u003c/span\u003e; Bhosale, \u003cspan citationid=\"CR3\" class=\"CitationRef\"\u003e2001\u003c/span\u003e for spectrophotometry-based estimation of β-carotene at 455 nm is a fundamental tool for quantitative analysis in analytical chemistry. After extensive testing and statistical analysis, it is established and provides a dependable and effective way to measure the amount of β-carotene in different samples.\u003c/p\u003e \u003cp\u003eThe mass-to-charge ratio (m/z)-based chromatographic separation of lipids is depicted in the figure. The chromatogram may be seen in the figure, which displays several co-eluting peaks that indicate various lipid species. For each peak, the precise m/z values 200, 356.21, 316.12, 437.11, and 475 are given.\u003c/p\u003e \u003cp\u003eIn addition, an examination using LC-MS was conducted to offer a thorough comprehension of the composition and structure of the lipids (Fig.\u0026nbsp;3.7). The \u003cem\u003eR. mucilaginosa\u003c/em\u003e lipid profile study results from LC-MS provide comprehensive details regarding the variety and makeup of lipids found in the organism. LC-MS is a potent analytical method that combines mass spectrometry's sensitivity detection and molecular identification with liquid chromatography's separation capabilities.\u003c/p\u003e \u003cp\u003eLipids can be identified and quantified using this technique by utilizing their mass-to-charge ratios in the mass spectrometer and their retention durations in the chromatographic column. This offers detailed information regarding the lipid profile of \u003cem\u003eR. mucilaginosa\u003c/em\u003e, including the existence of various lipid classes and their molecular species (phospholipids, glycolipids, and neutral lipids, for example). The types and quantities of lipids found in \u003cem\u003eR. mucilaginosa\u003c/em\u003e cells can be determined using the LC-MS analysis, which also provides important details on the organism's metabolic processes and defence mechanisms.\u003c/p\u003e \u003cp\u003eMoreover, the identification of lipid molecular species, such as headgroup compositions and fatty acid chains, is made possible by LC-MS. Furthermore, \u003cem\u003eR. mucilaginosa's\u003c/em\u003e lipid profile can be examined using LC-MS analysis to learn more about how it responds to environmental stimuli and experimental manipulations.\u003c/p\u003e \u003cp\u003eSpecific lanes in the figure correspond to various samples. Lane C is the reference lane for comparison, and it contains the triolein standard. The lipid sample from the zero-hour batch culture is represented by lane (1), the lipid sample from the 24-hour batch culture by lane (2), the lipid sample from the 72-hour batch culture by lane (3), and the lipid sample from the 96-hour batch culture by lane (4). The various samples can be divided using TLC according to their migration distances and lipid composition. This makes it possible to evaluate the neutral lipids in each sample qualitatively and provide information about their distribution and abundance across the cultures.\u003c/p\u003e \u003cp\u003eTLC study was carried out to further verify that the chosen microbe, \u003cem\u003eR. mucilaginosa\u003c/em\u003e, could produce significant levels of intracellular neutral lipids relative to cell weight. The substantial lipid accumulation potential of \u003cem\u003eR. mucilaginosa\u003c/em\u003e (Fig.\u0026nbsp;3.8) was confirmed by the TLC analysis results (Knittelfelder and Kohlwein, \u003cspan citationid=\"CR11\" class=\"CitationRef\"\u003e2017\u003c/span\u003e). TLC was used to separate the neutral lipids from \u003cem\u003eR. mucilaginosa\u003c/em\u003e. The qualitative analysis of the resulting material sheds light on the existence and variety of neutral lipid species inside the organism. TLC is a flexible chromatographic method that divides substances according to how well they migrate through a mobile phase and how well they bind to a stationary phase. When it comes to lipid analysis, TLC makes it possible to separate and see several lipid classes, including neutral lipids like free fatty acids, cholesterol esters, and triglycerides (Knittelfelder and Kohlwein, \u003cspan citationid=\"CR11\" class=\"CitationRef\"\u003e2017\u003c/span\u003e).\u003c/p\u003e \u003cp\u003eTLC would have been used in the research analysis to separate the neutral lipid fraction that was recovered from the samples of \u003cem\u003eR. mucilaginosa\u003c/em\u003e. An appropriate solvent system would have been used to spot the separated lipids onto a TLC plate and subject them to chromatographic separation. After separation, the existence of neutral lipid bands would have been observed on the TLC plate under UV light or with the use of a staining reagent.\u003c/p\u003e \u003cp\u003eThe broad interpretation of these findings includes their importance for comprehending \u003cem\u003eR. mucilaginosa's\u003c/em\u003e lipid composition and metabolic processes. In addition to being crucial components of membrane structure and cellular signalling, neutral lipids are molecules that store energy. The TLC analysis offers insights into the types and abundance of neutral lipids present in \u003cem\u003eR. mucilaginosa\u003c/em\u003e cells, providing valuable information about its lipid metabolism and physiological adaptations (Knittelfelder and Kohlwein, \u003cspan citationid=\"CR11\" class=\"CitationRef\"\u003e2017\u003c/span\u003e).\u003c/p\u003e \u003cp\u003eTLC also enables the qualitative evaluation of \u003cem\u003eR. mucilaginosa's\u003c/em\u003e neutral lipid diversity. The organism's lipid biosynthesis pathways and capacity for environmental adaptation can be better understood with the help of this information. The qualitative examination of neutral lipids extracted from \u003cem\u003eR. mucilaginosa\u003c/em\u003e using TLC analysis advances our knowledge of the lipid metabolism and cellular physiology of this organism.\u003c/p\u003e \u003c/div\u003e \u003cdiv id=\"Sec15\" class=\"Section2\"\u003e \u003ch2\u003e3.3 FAME analysis by Gas chromatography\u003c/h2\u003e \u003cp\u003eGas chromatography using a flame ionization detector (GC-FID) and an SLB-IL100 column was used to examine the fatty acid methyl esters (FAMEs) contained in the lipids synthesized from yeast medium fed with sodium acetate by \u003cem\u003eR. mucilaginosa\u003c/em\u003e. Before analysis, lipid samples from both fed-batch and batch processes were trans methylated. The FAME analysis yielded fatty acid composition profiles that demonstrated the lipids were primarily composed of long-chain fatty acids, with carbon chain lengths varying between C16 and C18.\u003c/p\u003e \u003cp\u003eNumerous fatty acids were identified by the analysis of the fed-batch sample: ginkgolic acid (C17:1), stearic acid (C18:0), oleic acid (C18:1), linoleic acid (C18:2), linolenic acid (C18:3), lauric acid (C12:0), myristic acid (C14:0), palmitic acid (C16:0), palmitoleic acid (C16:1), margaric acid (C17:0), ginkgolic acid (C17:1), stearic acid (C18:0), oleic acid (C18:1), linoleic acid (C18:2), and linolenic acid (C18:3) (Table\u0026nbsp;\u003cspan refid=\"Tab1\" class=\"InternalRef\"\u003e3.1\u003c/span\u003e). It was discovered that of these fatty acids, \u003cem\u003eR. mucilaginosa\u003c/em\u003e contained larger proportions of oleic, palmitic, and stearic acids overall. The two main FAME fractions, methyl oleate (C18:1) and methyl palmitate (C16:0), made up almost 72% of the overall FAME content (Table\u0026nbsp;3.2). There were notable concentrations of other fatty acids, including methyl stearate (C18:0), methyl linoleate (C18:2), methyl palmitoleate (C16:1), and methyl linolenate (C18:3).\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 3.1\u003c/div\u003e \u003cdiv class=\"CaptionContent\"\u003e \u003cp\u003eGas chromatography analysis of FAME composition (%) profile in \u003cem\u003eR. mucilaginosa\u003c/em\u003e\u003c/p\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=\"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=\"char\" char=\"\u0026plusmn;\" class=\"colspec\" colname=\"c4\" colnum=\"4\"\u003e\u003c/div\u003e \u003cthead\u003e \u003ctr\u003e \u003cth align=\"left\" colname=\"c1\"\u003e \u003cp\u003eIUPAC Name\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c2\"\u003e \u003cp\u003eFatty acids\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c3\"\u003e\u0026nbsp;\u003c/th\u003e \u003cth align=\"left\" colname=\"c4\"\u003e \u003cp\u003eFAME (%, w/w)\u003c/p\u003e \u003c/th\u003e \u003c/tr\u003e \u003c/thead\u003e \u003ctbody\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eMethyl laurate\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003eLauric\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003eC12:0\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\"\u0026plusmn;\" colname=\"c4\"\u003e \u003cp\u003e0.31\u0026thinsp;\u0026plusmn;\u0026thinsp;0.02\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eMethyl tetradecanoate\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003eMyristic\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003eC14:0\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\"\u0026plusmn;\" colname=\"c4\"\u003e \u003cp\u003e0.94\u0026thinsp;\u0026plusmn;\u0026thinsp;0.07\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eMethyl palmitate\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003ePalmitic\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003eC16:0\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\"\u0026plusmn;\" colname=\"c4\"\u003e \u003cp\u003e21.05\u0026thinsp;\u0026plusmn;\u0026thinsp;1.02\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eMethyl palmitoleate\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003ePalmitoleic\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003eC16:1\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\"\u0026plusmn;\" colname=\"c4\"\u003e \u003cp\u003e1.10\u0026thinsp;\u0026plusmn;\u0026thinsp;0.11\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eMethyl heptadecanoate\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003eMargaric acid\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003eC17:0\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\"\u0026plusmn;\" colname=\"c4\"\u003e \u003cp\u003e0.15\u0026thinsp;\u0026plusmn;\u0026thinsp;0.06\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eMethyl heptadecenoic\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003eGinkgolic acid\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003eC17:1\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\"\u0026plusmn;\" colname=\"c4\"\u003e \u003cp\u003e0.32\u0026thinsp;\u0026plusmn;\u0026thinsp;0.01\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eMethyl octadecanoate\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003eStearic\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003eC18:0\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\"\u0026plusmn;\" colname=\"c4\"\u003e \u003cp\u003e5.02\u0026thinsp;\u0026plusmn;\u0026thinsp;0.16\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eMethyl oleic\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003eOleic\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003eC18:1\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\"\u0026plusmn;\" colname=\"c4\"\u003e \u003cp\u003e51.18\u0026thinsp;\u0026plusmn;\u0026thinsp;2.41\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eMethyl linoleate\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003eLinoleic\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003eC18:2\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\"\u0026plusmn;\" colname=\"c4\"\u003e \u003cp\u003e7.25\u0026thinsp;\u0026plusmn;\u0026thinsp;1.61\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eMethyl linolenate\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003eLinolenic\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003eC18:3\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\"\u0026plusmn;\" colname=\"c4\"\u003e \u003cp\u003e1.03\u0026thinsp;\u0026plusmn;\u0026thinsp;0.31\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003c/tbody\u003e \u003c/colgroup\u003e \u003c/table\u003e\u003c/div\u003e \u003c/p\u003e \u003cp\u003eThe fatty acid profile also included trace quantities of unsaturated fatty acids (methyl heptadecenoic) and saturated fatty acids (methyl laurate, methyl palmitoleate, and methyl heptadecanoate). According to the GC analysis, \u003cem\u003eR. mucilaginosa\u003c/em\u003e has a higher concentration of unsaturated fatty acids than saturated fatty acids.\u003c/p\u003e "},{"header":"Conclusion","content":" \u003cp\u003eThe yeast \u003cem\u003eR.mucilaginosa\u003c/em\u003e exhibits significant potential for the production of valuable biochemicals such as lipids, carotenoids, and β-carotene. Various advanced analytical techniques were utilized to examine the growth profile and biochemical composition of this yeast, providing insights into its metabolic capabilities and potential applications in biotechnology.\u003c/p\u003e \u003cp\u003eAnalytical Techniques and Findings:\u003c/p\u003e \u003cp\u003eRaman Spectroscopy: Raman spectroscopy identified the presence of lipids and carotenoids within \u003cem\u003eR. mucilaginosa\u003c/em\u003e. Specific marker bands were detected for lipids at 1136 cm-1 and 1441 cm-1, and for carotenoids at 1000 cm-1, 1190 cm-1, and 1560 cm-1, confirming their accumulation in the yeast cells.\u003c/p\u003e \u003cp\u003eFluorescence Spectroscopy and Microscopy: Fluorescence microscopy with Nile red labeling visualized the distribution of lipids within the cells, showing distinct lipid droplets. Bright-field and fluorescence images demonstrated the co-localization of lipids and carotenoids, providing insights into their cellular distribution and abundance.\u003c/p\u003e \u003cp\u003eField Effect Scanning Electron Microscopy (FESEM): FESEM provided high-resolution images of \u003cem\u003eR. mucilaginosa\u003c/em\u003e cells, revealing their ellipsoid shape and the presence of intracellular lipid droplets. These observations confirmed the structural details of lipid accumulation within the cells.\u003c/p\u003e \u003cp\u003eThin Layer Chromatography (TLC): TLC analysis confirmed the presence and variety of neutral lipids in \u003cem\u003eR. mucilaginosa\u003c/em\u003e. Different lipid species were separated and visualized, highlighting the yeast\u0026rsquo;s capacity for significant lipid accumulation.\u003c/p\u003e \u003cp\u003eLiquid Chromatography-Mass Spectrometry (LC-MS): LC-MS analysis detailed the lipid profile of \u003cem\u003eR. mucilaginosa\u003c/em\u003e, identifying various lipid classes and their molecular species. The technique provided comprehensive information on the composition and structure of lipids, contributing to understanding the yeast\u0026rsquo;s metabolic processes and adaptation mechanisms.\u003c/p\u003e \u003cp\u003eGas Chromatography for FAME Analysis: GC analysis of fatty acid methyl esters (FAMEs) revealed the lipid composition, primarily composed of long-chain fatty acids (C16 to C18). The major fatty acids identified included oleic, palmitic, and stearic acids, with unsaturated fatty acids being predominant. These findings highlight the yeast\u0026rsquo;s potential for biotechnological applications, particularly in the sustainable production of biofuels, nutritional supplements, and cosmetic ingredients.\u003c/p\u003e "},{"header":"Declarations","content":"\u003cp\u003e\u003cstrong\u003eDeclaration of Ethics Statement.\u003c/strong\u003e\u0026nbsp;\u003cbr\u003e\u0026nbsp;This study does not make use of human or animal participants. This study\u0026apos;s analysis and conclusions are purely based on theoretical models, simulations, and/or publicly available data. As a result, no ethical approval or permission were required for this study.\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eDeclaration of Consent for Publication\u003c/strong\u003e\u003cbr\u003e\u0026nbsp;All authors engaged in this study agree to have their work published in Bioresources and Bioprocessing. The contents of this paper have not previously been published and are not being considered for publication anywhere.\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eDeclaration of Competing Interest\u003c/strong\u003e\u003cbr\u003e\u0026nbsp;The authors state that they have no known competing financial interests or personal relationships that could have influenced the work presented in this study.\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eAuthor\u0026rsquo;s contribution\u0026nbsp;\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eRavi Gadela: methodology, analysis, writing (original draft),\u0026nbsp;\u003cbr\u003e\u0026nbsp;Kannan Pakshirajan: Conceptualization, supervision, review, and editing.\u0026nbsp;\u003c/p\u003e\n\u003cp\u003eVeeranki Venkata Dasu: handles conceptualization, supervision, resource management, review, and editing. All authors reviewed and approved the final manuscript.\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eDeclaration of No Funding.\u003c/strong\u003e\u003cbr\u003e\u0026nbsp;This study received no grants from public, commercial, or non-profit funding entities.\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eDeclaration of Availability of Data and Materials\u003c/strong\u003e\u003cbr\u003e\u0026nbsp;The data and materials used and analyzed in the current investigation are available from the corresponding author upon on request.\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eAcknowledgment\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eThe authors are thankful to the Indian Institute of Technology Guwahati for providing the required facilities to conduct this research work and the Central Instrument Facility (CIF), IIT Guwahati.\u003c/p\u003e"},{"header":"References","content":"\u003col\u003e\u003cli\u003e\u003cspan\u003eAksu Z, Eren AT (2007) Production of carotenoids by the isolated yeast of Rhodotorula glutinis. Biochem Eng J 35(2):107\u0026ndash;113\u003c/span\u003e\u003c/li\u003e \u003cli\u003e\u003cspan\u003eBerg JM, Tymoczko JL, Gatto G, Stryer L (2015) Biochemistry (eight edition).\u003c/span\u003e\u003c/li\u003e \u003cli\u003e\u003cspan\u003eBhosale P, Gadre R (2001) Production of β-carotene by a mutant of Rhodotorula glutinis. Appl Microbiol Biotechnol 55(4):423\u0026ndash;427\u003c/span\u003e\u003c/li\u003e \u003cli\u003e\u003cspan\u003ede Carvalho LMJ, Gomes PB, de Oliveira Godoy RL, Pacheco S, do, Monte PHF, de Carvalho JLV, Ramos SRR (2012) Total carotenoid content, α-carotene and β-carotene, of landrace pumpkins (Cucurbita moschata Duch): A preliminary study. Food Research International, 47(2), 337\u0026ndash;340\u003c/span\u003e\u003c/li\u003e \u003cli\u003e\u003cspan\u003eElfeky N, Elmahmoudy M, Zhang Y, Guo J, Bao Y (2019) Lipid and carotenoid production by Rhodotorula glutinis with a combined cultivation mode of nitrogen, sulfur, and aluminium stress. Appl Sci 9(12):2444\u003c/span\u003e\u003c/li\u003e \u003cli\u003e\u003cspan\u003eElle IC, Olsen LCB, Pultz D, R\u0026oslash;dk\u0026aelig;r SV, F\u0026aelig;rgeman NJ (2010) Something worth dyeing for: molecular tools for the dissection of lipid metabolism in Caenorhabditis elegans. FEBS Lett 584(11):2183\u0026ndash;2193\u003c/span\u003e\u003c/li\u003e \u003cli\u003e\u003cspan\u003eGedela R, Prabhu A, Veeranki VD, Kannan P (2023) High yield production of lipid and carotenoids in a newly isolated Rhodotorula mucilaginosa by adapting process optimization approach. Biofuels 14(5):509\u0026ndash;520\u003c/span\u003e\u003c/li\u003e \u003cli\u003e\u003cspan\u003eGethings LA, Richardson K, Wildgoose J, Lennon S, Jarvis S, Bevan CL, Langridge JI (2017) Lipid profiling of complex biological mixtures by liquid chromatography/mass spectrometry using a novel scanning quadrupole data-independent acquisition strategy\u003c/span\u003e\u003c/li\u003e \u003cli\u003e\u003cspan\u003eGuan XL, Wenk MR (2006) Mass spectrometry-based profiling of phospholipids and sphingolipids in extracts from Saccharomyces cerevisiae. Yeast 23(6):465\u0026ndash;477\u003c/span\u003e\u003c/li\u003e \u003cli\u003e\u003cspan\u003eHiyama T, Ke B (1972) Difference spectra and extinction coefficients of P700. Biochim et Biophys Acta (BBA)-Bioenergetics 267(1):160\u0026ndash;171\u003c/span\u003e\u003c/li\u003e \u003cli\u003e\u003cspan\u003eKnittelfelder OL, Kohlwein SD (2017) Thin-layer chromatography to separate phospholipids and neutral lipids from yeast. Cold Spring Harbor Protocols, 2017(5), pdb-prot085456\u003c/span\u003e\u003c/li\u003e \u003cli\u003e\u003cspan\u003eKumar V, Muthuraj M, Palabhanvi B, Ghoshal AK, Das D (2014) Evaluation and optimization of two stage sequential in situ transesterification process for fatty acid methyl ester quantification from microalgae. Renewable Energy 68:560\u0026ndash;569\u003c/span\u003e\u003c/li\u003e \u003cli\u003e\u003cspan\u003eKurtzman CP, Fell JW, Boekhout T, Robert V (2011) Methods for isolation, phenotypic characterization and maintenance of yeasts. The yeasts. Elsevier, pp 87\u0026ndash;110\u003c/span\u003e\u003c/li\u003e \u003cli\u003e\u003cspan\u003eMadigan MT, Martinko JM, Stahl DA, Clarck DP (2018) Brock biology of microorganisms, Pearson. New York\u003c/span\u003e\u003c/li\u003e \u003cli\u003e\u003cspan\u003eMurtey MD, Ramasamy P (2016) Sample preparations for scanning electron microscopy\u0026ndash;life sciences. 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Dynamic Biochemistry, Process Biotechnology and Molecular Biology, 1, 63\u0026ndash;73\u003c/span\u003e\u003c/li\u003e \u003cli\u003e\u003cspan\u003eVatsal A, Zinjarde SS, Kumar AR (2011) Growth of a tropical marine yeast Yarrowia lipolytica NCIM 3589 on bromoalkanes: relevance of cell size and cell surface properties. Yeast 28(10):721\u0026ndash;732\u003c/span\u003e\u003c/li\u003e \u003cli\u003e\u003cspan\u003eWirth F, Goldani LZ (2012) Epidemiology of Rhodotorula: an emerging pathogen. Interdisciplinary perspectives on infectious diseases, 2012\u003c/span\u003e\u003c/li\u003e \u003cli\u003e\u003cspan\u003eZaas AK, Boyce M, Schell W, Lodge BA, Miller JL, Perfect JR (2003) Risk of fungemia due to Rhodotorula and antifungal susceptibility testing of Rhodotorula isolates. J Clin Microbiol 41(11):5233\u0026ndash;5235\u003c/span\u003e\u003c/li\u003e\u003c/ol\u003e"},{"header":"Tables","content":"\u003cp\u003eTables 3.2 and 4.1 are not available with this version.\u003c/p\u003e"}],"fulltextSource":"","fullText":"","funders":[],"hasAdminPriorityOnWorkflow":false,"hasManuscriptDocX":true,"hasOptedInToPreprint":true,"hasPassedJournalQc":"","hasAnyPriority":true,"hideJournal":true,"highlight":"","institution":"Indian Institute of Technology Guwahati","isAcceptedByJournal":false,"isAuthorSuppliedPdf":false,"isDeskRejected":"","isHiddenFromSearch":false,"isInQc":false,"isInWorkflow":true,"isPdf":false,"isPdfUpToDate":true,"isWithdrawnOrRetracted":false,"journal":{"display":true,"email":"[email protected]","identity":"researchsquare","isNatureJournal":false,"hasQc":true,"allowDirectSubmit":true,"externalIdentity":"","sideBox":"","snPcode":"","submissionUrl":"/submission","title":"Research Square","twitterHandle":"researchsquare","acdcEnabled":true,"dfaEnabled":false,"editorialSystem":"","reportingPortfolio":"","inReviewEnabled":false,"inReviewRevisionsEnabled":true},"keywords":"Rhodotorula mucilaginosa, lipids, carotenoids, β-carotene, oleaginous","lastPublishedDoi":"10.21203/rs.3.rs-4808428/v1","lastPublishedDoiUrl":"https://doi.org/10.21203/rs.3.rs-4808428/v1","license":{"name":"CC BY 4.0","url":"https://creativecommons.org/licenses/by/4.0/"},"manuscriptAbstract":"\u003cp\u003eThe oleaginous yeast species \u003cem\u003eRhodotorula mucilaginosa\u003c/em\u003e is distinguished by its genetic, ecological, physiological, and morphological variety. The biotechnological potential of \u003cem\u003eR. mucilaginosa\u003c/em\u003e, which was isolated from petroleum oil refinery resources in Guwahati, Assam, India, specifically for the potential producing of lipids, carotenoids, and β-carotene were examined. In this study to describe carotenoid pigments in \u003cem\u003eR. mucilaginosa\u003c/em\u003e, determine targets for metabolic products, and comprehend the precise lipid composition profile. \u003cem\u003eR. mucilaginosa\u003c/em\u003e alive cells were analysed using a variety of biochemical and biophysical techniques, such as gas chromatography for lipid and thin-layer chromatography for neutral lipid composition profiling, Raman spectroscopy for lipid and carotenoid analysis, Field Effect Scanning Electron Microscopy (FESEM) for lipid visualization, and fluorescence spectroscopy for lipid detection using the Nile red assay. The results of these tests offer a thorough understanding of \u003cem\u003eR. mucilaginosa's\u003c/em\u003e capacity to produce carotenoid and lipids. This precise identification of oleaginous yeast \u003cem\u003eR. mucilaginosa\u003c/em\u003e needed for the commercial production of carotenoids, high-value biofuel, and value-added merchandises. Raman spectroscopy, fluorescence spectroscopy, FESEM, TLC, and LC-MS provided valuable insights into the lipid and carotenoid production capabilities of \u003cem\u003eR. mucilaginosa\u003c/em\u003e. Moreover, any of these analytical techniques can be used to confirm the presence of lipids and carotenoids in yeast species. These comprehensive results help reduce the time required for selecting new oleaginous yeast species.\u003c/p\u003e","manuscriptTitle":"Integrated Biophysical and Biochemical Analyses for Profiling Lipids and Carotenoids in Rhodotorula mucilaginosa","msid":"","msnumber":"","nonDraftVersions":[{"code":1,"date":"2024-07-30 13:40:07","doi":"10.21203/rs.3.rs-4808428/v1","editorialEvents":[{"type":"communityComments","content":0}],"status":"published","journal":{"display":true,"email":"[email protected]","identity":"researchsquare","isNatureJournal":false,"hasQc":true,"allowDirectSubmit":true,"externalIdentity":"","sideBox":"","snPcode":"","submissionUrl":"/submission","title":"Research Square","twitterHandle":"researchsquare","acdcEnabled":true,"dfaEnabled":false,"editorialSystem":"","reportingPortfolio":"","inReviewEnabled":false,"inReviewRevisionsEnabled":true}}],"origin":"","ownerIdentity":"7c3edda2-2a01-4ab6-aad5-f811a6179ffd","owner":[],"postedDate":"July 30th, 2024","published":true,"recentEditorialEvents":[],"rejectedJournal":[],"revision":"","amendment":"","status":"posted","subjectAreas":[{"id":35178010,"name":"Biochemical Research Methods"},{"id":35178011,"name":"Biotechnology and Bioengineering"},{"id":35178012,"name":"Applied \u0026 Industrial Microbiology"}],"tags":[],"updatedAt":"2024-07-30T13:40:07+00:00","versionOfRecord":[],"versionCreatedAt":"2024-07-30 13:40:07","video":"","vorDoi":"","vorDoiUrl":"","workflowStages":[]},"version":"v1","identity":"rs-4808428","journalConfig":"researchsquare"},"__N_SSP":true},"page":"/article/[identity]/[[...version]]","query":{"redirect":"/article/rs-4808428","identity":"rs-4808428","version":["v1"]},"buildId":"qtupq5eGEP_6zYnWcrvyt","isFallback":false,"isExperimentalCompile":false,"dynamicIds":[84888],"gssp":true,"scriptLoader":[]}