Exploring the nutritional biochemical profiles and biological functions in the green microalga Chlorella fusca

Article information

Algae. 2024;39(3):187-205
Publication date (electronic) : 2024 September 15
doi : https://doi.org/10.4490/algae.2024.39.8.23
1Department of Life Resource Industry, Dong-A University, Busan 49315, Korea
2Department of Plant Medicine and RILS, Gyeongsang National University, Jinju 52828, Korea
3Institute of Agriculture & Life Science, Gyeongsang National University, Jinju 52828, Korea
*Corresponding Author: E-mail: schem72@dau.ac.kr, Tel: +82-51-200-7521, Fax: +82-51-200-7505
Received 2024 April 12; Accepted 2024 August 23.

Abstract

Chlorella species of microalgae are utilized in the crop and food industries. The aim of this research was to investigate the metabolite profiles of Chlorella fusca for the first time and evaluate its biological properties. The two ion modes of UPLC-Q-TOF-MS/MS were used to identify a total of 62 components in the methanol extract of C. fusca, with 26 in the negative and 36 in the positive ion mode, including 10 identical ingredients. Fatty acids (negative mode) and combinations of chlorophyll and fatty acids (positive mode) were the most prevalent chemical structures, constituting over 80 and 70% of the total metabolites, respectively, followed by chlorophyll, polar lipids, carotenoids, and fatty alcohols. Moreover, this extract exhibited potent antioxidant and anti-aging benefits in decreasing order of potency at a concentration of 200 μg mL−1: tyrosinase inhibition (100%), ABTS radical scavenging (90%), elastase inhibition (88%), and DPPH radical scavenging (34%). Notably, this extract protected the mobility of DNA fragments up to 5 μg mL−1 (26%), with potential effects (> 60% at 200 μg mL−1). These findings suggest that C. fusca may be a promising candidate for applications related to its biological functions, owing to the high accumulation of fatty acids and chlorophyll derivatives.

INTRODUCTION

Numerous studies have reported that microalgae (microscopic phytosynthetic organisms) living in both fresh water and sea water are widely used in the food, cosmetic, and pharmaceutical industries, as well as in various commercial applications (Kotrbáček et al. 2015, Safarfar et al. 2015, Habashy et al. 2018, EI-fayoumy et al. 2021, Canelli et al. 2022, Ferdous et al. 2023). This source has attracted attention in the agricultural and biotechnological fields because of its utility in biofuel production and valuable chemicals (Musharraf et al. 2012, Gorgich et al. 2021, Zhou et al. 2022, Kang et al. 2023, Won et al. 2023). Specifically, microalgae are currently used to evaluate green biodiesel production under transesterification conditions (Mata et al. 2010, Musharraf et al. 2012, Kotrbáček et al. 2015, Zhou et al. 2022). Considering the observations stated above, these organisms have evolved from food materials to being an energy feedstock and excellent source of chemical products in the modern age. Currently, microalgae are of increasing interest to the medicinal and functional food industries owing to their diverse benefits. Many researchers have demonstrated that microalgal metabolites are crucial for expanding food and nutraceutical applications (Kotrbáček et al. 2015, Yun et al. 2020, Gorgich et al. 2021, Canelli et al. 2022, Ferdous et al. 2023). Other studies have revealed the presence of various metabolites in microalgae, including polysaccharides, peptides, triterpenoids phenolics, fatty acids, proteins, amino acids, and chlorophyll derivatives (Montes D’Oca et al. 2011, López-Pacheco et al. 2019, Fernandes and Cordeiro 2020, Pantami et al. 2020, Kim et al. 2022, Kang et al. 2023). Furthermore, these constituents are associated with a wide range of human health benefits such as anti-inflammatory, antioxidant, antimicrobial, antitumor, and anti-allergic properties (Habashy et al. 2018, Vello et al. 2018, Gorgich et al. 2021, Kim et al. 2022, Ferdous et al. 2023, Kang et al. 2023, Zhou et al. 2023). It has recently been documented that microalgae have excellent characteristics, including fast growth, high photosynthetic rates in a short time, high protein content, high CO2 capture ability, and the ability to convert solar energy to electrical energy (Vello et al. 2018, Deamici et al. 2019, Fernandes and Cordeiro 2020, Martini et al. 2021, Won et al. 2023). Among the various microalgae, the genus Chlorella is a single-celled organism of the Chlorophyta that is present in both fresh and marine water (Montes D’Oca et al. 2011, Sotoudehniakarani et al. 2019, Yun et al. 2020, Canelli et al. 2022, Chae et al. 2023). This material is used in fortified (or supplementary) foods, such as puffs, bread, pasta, juice, and cookies, to enhance their color and nutritional quality (Kotrbáček et al. 2015, Fernandes and Cordeiro 2020, El-fayoumy et al. 2021, Gorgich et al. 2021). In particular, Chlorella is a well-known rich source of metabolites, including dietary fiber, vitamins, carbohydrates, lipids, chlorophylls, and proteins, with a variety of health benefits (Ando et al. 2004, Kotrbáček et al. 2015, Pantami et al. 2020, Conde et al. 2021, Kim et al. 2022, Ferdous et al. 2023). Additionally, thousands of tons of Chlorella are produced annually in East Asia, Europe, and the United States and are now sold as nutraceutical or functional products (Mata et al. 2010, Musharraf et al. 2012, Safi et al. 2014, Safarfar et al. 2015, Sotoudehniakarani et al. 2019, Martini et al. 2021). It has been commonly established that Chlorella comprises several species, such as C. vulgaris, C. pyrenoidosa, C. zofingiensis, C. ellipsoidea, and C. sorokiniana (Montes D’Oca et al. 2011, Sotoudehniakarani et al. 2019, Yun et al. 2020, Gorgich et al. 2021, Martini et al. 2021, Chae et al. 2023), specifically, C. vulgaris and C. sorokiniana are agents of green healthy food approved by the Food and Agriculture Organization of the United Nations because of their nutrient profiles and widespread human consumption (Kotrbáček et al. 2015). It is well established that C. fusca and C. vulgaris are closely related green microalgae species (Bock et al. 2011, Deamici et al. 2019, Sotoudehniakarani et al. 2019). Although they share many similarities, such as their unicellular structure and autotrophic metabolism, they also exhibit distinct differences in terms of their cell size, growth characteristics, taxonomic positioning, and habit preferences (Bock et al. 2011, Deamici et al. 2019, Chae et al. 2023). In addition, C. fusca has been reported to have a lower food and commercial utilization potential than C. vulgaris (Mata et al. 2010, Safi et al. 2014, Kotrbáček et al. 2015). To date, several researchers have elucidated the distribution and composition of metabolites in Chlorella species, namely, Chlorella sp., C. vulgaris, C. pyrenoidosa, and C. sorokiniana (Montes D’Oca et al. 2011, Safi et al. 2014, Safarfar et al. 2015, Habashy et al. 2018, Fernandes and Cordeiro 2020, Pantami et al. 2020, Canelli et al. 2022, Montoya-Arroyo et al. 2022), however, to the best of our knowledge, there is no comprehensive information available on the characterization of the metabolite profile of C. fusca. Moreover, there are few published studies on the simultaneous determination of individual components to obtain chemical profiles using the ultra-high performance liquid chromatography-quadruple-time of flight-mass spectrometry (UPLC-Q-TOF-MS/MS) method in both negative and positive ion modes. Little information is available on the comparison and demonstration of the biological functions of C. fusca extract. Therefore, our study was designed to obtain information regarding metabolite constituents, as well as their as antioxidant and anti-aging abilities, using the two ion modes of TOF-MS.

The key objective of the current work was to identify the metabolite profiles in the methanol extract of C. fusca. We investigated herein, for the first time, the comparison and characterization of metabolite profiles with the application of negative and positive ion modes using the UPLC-Q-TOF-MS/MS technique to screen as many potential metabolites as possible for an in-depth analysis of this resource. In addition, this study documented the antioxidant activities of radical scavenging and DNA protection, as well as the total phenolic and total flavonoid contents of antioxidative substances. Our research is also the first to assess the inhibitory capacities of anti-aging factors against tyrosinase and elastase.

MATERIALS AND METHODS

Microalgae source and reagents

The freshwater microalgae C. fusca, was used in the present study. The CHK0059 strain of C. fusca was provided by the National Institute of Agricultural Science of the Rural Development Administration, Wanju, Jeonbuk Province, Republic of Korea. The microalgae were cultivated at F&B Nature Co. Ltd. (Chungju, Korea) as follows: initial inoculation, 1 × 106 cells mL−1; temperature, 28°C; period, 6 d; light, 120 μm m−2 s for 24 h in a day; air circulation, 2 L min−1. Cultured microalgae were collected on Mar 10, 2021, and their appearance is shown in the Supplementary Fig. S1. This material was immediately stored at 0°C prior to analysis. The pUC19 super-coiled plasmid DNA was supplied by Thermo Fisher Scientific (Waltham, MA, USA). 2,2-diphenyl-1-picrylhydrazyl (DPPH),2,2′-azino-bis(3-ethylbenzthiazoline-6-sulphonic acid) (ABTS), tyrosinase (EC 1.14.18.1), elastase (EC 3.4.21.36), ascorbic acid, 6-hydroxy-2,5,7,8-tetramethylchroman-2-carboxylic acid (Trolox), ursolic acid, FeCl3, dithiothreitol (DTT), L-tyrosine, p-nitrophenyl-α-D-glucopyranoside, p-nitrophenol, p-nitrophenol-β-D-glucopyranoside, gallic acid (GA), and quercetin (QE) were obtained from Sigma-Aldrich (St. Louis, MO, USA). The total phenolic content (TPC; Folin-Ciocalteu reagent and sodium carbonate) and total flavonoid content (TFC; sodium nitrite, sodium hydroxide, and diethylene glycol) were also provided by Sigma-Aldrich. Other chemicals and solvents, such as UPLC-MS grade water and acetonitrile (J.K. Baker, Phillipsburg, NJ, USA), were used at analytical grade without further purification.

Equipment

To measure the biological properties of the antioxidant, tyrosinase, and elastase, UV-Vis absorption spectra were used on an Agilent BioTeck microplate spectrophotometer (EPOCH2; BioTek Instruments, Winooski, VT, USA). The TPC and TFC analyses were also performed using this spectrometer. Multiple metabolite compositions were confirmed by a UPLC system (UPLC SCL40 Nexera X3 series; Shimadzu, Kyoto, Japan) coupled with a triple quadruple time-of-flight tandem mass spectrometry (LC/MS-Triple TOF X500R; AB SCIEX, Framingham, MA, USA) equipped with an electrospray ionization interface. Data acquisition and processing were performed by a preliminary TOF-MS high-resolution full scan, following the SWATH protocol (AB SCIEX, Foster City, CA, USA).

Preparation of Chlorella fusca extract

For metabolite analyses and biological assays, the cultured C. fusca samples were separated from the solution and supernatant by centrifugation (3,000 ×g, SL 40R; Thermo Fisher Scientific). The collected supernatant was air dried at 25°C for 2 d to remove the moisture, and then the dried green powder (1 g) was extracted with 20 mL of methanol in a shaking incubator for 3 d at 25°C. Extraction was performed with slight modifications to previously reported methods (Habashy et al. 2018, Vello et al. 2018). The crude methanol extract was centrifuged at 3,000 ×g for 5 min and filtered through Whatman filter paper (No. 42; Sigma-Aldrich). The filtered solution was examined for antioxidant and anti-aging properties as well as TPC and TFC. Also, this solution was filtered through a syringe filter (0.45 μm; Whatman Inc., Maidstone, UK) prior to UPLC-TOF-MS analysis.

Analyses of TPC and TFC

The material for TPC and TFC (mg g−1) were prepared as described in subsection 2.3 (1 g of dried sample in 20 mL methanol). The TPC analysis was performed using the Folin-Ciocalteu reagent with slight modifications (Safarfar et al. 2015, Ha et al. 2021), and TFC was measured by the colorimetric method as described by Safarfar et al. (2015) and Ha et al. (2021). In brief, the methanol extract (500 μL) of C. fusca was mixed with 2 N Folin-Ciocalteu’s reagent (250 μL) and distilled water (250 μL), and then incubated for 1 h at 25°C. Sodium carbonate solution (20%, 500 μL) was added to the Ciocalteu reaction mixture and incubated for 10 min at 35°C. The absorbance value was measured at 750 nm by a spectrophotometer and compared to a calibration curve (GA, 0.5–500 μg mL−1). The content was expressed as milligrams of gallic acid equivalents (GAE) per g of dried sample. The TFC method was also carried out according to previous research using the colorimetric technique (Safarfar et al. 2015, Ha et al. 2021). The sample extract (250 μL) was added to methanol (2 mL) followed by 90% diethylene glycol (1 mL) and 4 M NaOH (1 mL). After heating at 35°C for 10 min, the absorbance of the reaction mixture was determined using a spectrophotometer at 420 nm and compared with the calibration curve (QE, 0.5–500 mg mL−1). This result was calculated as mg of QE per g of dried sample. The TPC and TFC ratios were determined in three independent experiments (mean values) for each triplicate sample.

Antioxidant abilities against radical sources

The antioxidant properties of DPPH and ABTS radicals in the methanol extract of C. fusca (1 g, 20 mL) were determined as described by Ha et al. (2021) and Lee et al. (2023). A sample or positive control (ascorbic acid) (0.1 mL) of six different concentrations (25–600 μg mL−1) was mixed with methanol (0.49 mL), and then added to a 1 mM DPPH methanolic solution (0.39 mL). The crude solution was vortexed at 25°C for 30 min in the dark, and the absorbance of the reaction mixture was measured at 517 nm. The DPPH radical scavenging effect was evaluated as a percentage by the following equation:

Scavenging activity (%)=[(1-sample absorbance value/control absorbance value)]×100

The ABTS radical scavenging properties were determined on the capacities of different substances to the radical cation scavenge by comparison with the positive control (Trolox) using a spectrophotometer at 734 nm. This radical cation source of 7 mM ethanolic solution was generated by reacting the ABTS•+ stock solution with potassium persulfate (K2S2O8, 2.45 mM), and allowing to stand at 25°C for 12 h in darkness. The crude solution was diluted in EtOH (abs 0.70). A sample extract or positive control (0.1 mL) of four concentrations (25–200 μg mL−1) was added to 0.9 mL of ABTS•+ solution. After vortexing for 1 min at 25°C, the absorbance value was measured using a spectrophotometer. This capacity was calculated as a percentage according to the following formula:

Scavenging activity (%)=[(control absorbance value-sample absorbance value)/control absorbance value]×100

Antioxidant capacities were based on three replicate samples with mean values.

DNA protective effect

A metal-catalyzed oxidation (MCO) DNA cleavage protection assay was conducted as described by Lee et al. (2023). In brief, the methanol extracts of C. fusca at different concentrations were added to 3.3 mM DTT (5 μL) and 15.4 μM FeCl3 (5 μL), and then incubated at 37°C for 2 h. The above reaction solution was mixed with pUC18 super-coiled plasma DNA (1 μg). After incubation for 2 h at 37°C, the mixture solution (5 μL) was added to DNA loading buffer (1 μL), and then loaded onto a 0.8% agarose gel in TAE buffer (1 mM EDTA and 40 mM Tris-acetate). After being electrophoresed (30 min at 85 V), the DNA in the gel was visualized and photographed using the Gel Doc XR+ system (Universal Hood II; Bio-Rad Laboratories, Hercules, CA, USA) equipped with a UV transilluminator and a camera. DNA band intensity and imaging were performed using Image Lab software (Bio-Rad Laboratories). The inhibition rate (%) of DNA damage (mean value of three independent experiments) was calculated by the following equation (Rahman et al. 2018, Seal et al. 2020):

DNA protection rate (%)=(SF DNA band intensity/pUC18plasmid DNA band intensity)×100

Enzyme inhibition effects

The inhibitory abilities against tyrosinase and elastase were measured in earlier studies, with slight modifications (Azmi et al. 2014, Lee et al. 2023), as the mean values of three independent experiments performed in triplicate. To prepare the tyrosinase inhibition assay, the diluted sample (30 μL) or ascorbic acid (positive control, 30 μL) was mixed in methanol with sodium phosphate buffer (NaH2PO4, 0.05 mM, pH 6.8, 970 μL). L-tyrosine solution (1,000 μL) was added and vortexed with tyrosinase (200 units mL−1, 1,000 μL) for 1 min. The reaction solution was placed at 37°C for 30 min, and then monitored by spectrophotometry at a wavelength of 490 nm.

The inhibition rate was expressed as a percentage according to the following formula:

Inhibitory activity (%)=[(control absorbance value-sample absorbance value/control absorbance value)×100

Elastase inhibition ability was also demonstrated using a spectrophotometric method. The sample was dissolved in methanol at 1,000 μg mL−1, and then diluted to various concentrations with 0.2 mM Tris-HCl buffer (pH 8.0). Elastase was dissolved to make a 3.33 mg mL−1 stock solution in Tris-HCl buffer (0.2 mM, pH 8.0) and the substrate N-succinyl-Ala-Ala-Ala-P-nitroanilide (1.6 mM) was diluted with the above buffer. The reaction solution contained Tris-HCl buffer (100 μL), substrate (25 μL), elastase (25 μL), and sample (50 μL) or ursolic acid (positive control, 50 μL) in a 96-well plate, and was incubated for 20 min at room temperature. Absorbance value of the crude solution was recorded at a wavelength of 410 nm. This enzyme inhibition rate was calculated as a percentage using the following equation:

Inhibitory activity (%)=(1-absorbance value of sample extract/absorbance value of buffer)×100

Conditions of UPLC-Q-TOF-MS/MS analysis for metabolite identification

The UPLC separation was performed on a Poroshell 120 Bonus-Rp (100 mm × 2.1 mm, 2.7 m; Agilent Technologies, Santa Clara, CA, USA). The mobile phase consisted of two solvents: (A) acetonitrile and (B) water containing 0.1% acetic acid. The metabolites were separated using the following gradient elution profile: 50% A in 0–5 min; 70% A in 5–15 min; 80% A in 15–25 min; 90% A in 25–30 min; 95% A in 30–40 min; 98% A in 40–45 min. The flow rate was 0.3 mL min−1 with an injection volume of 2 μL and the column temperature was carried out at 25°C. After chromatographic separation, the mobile phase was introduced directly into the Triple TOF X500R instrument. The MS system was operated in both negative and positive ion modes, with the mass range set at m/z 100–1,000 Da at full scan resolution. The operating MS conditions were as follows: (common conditions) ion source, turbolonspray; source temperature, 450°C; curtain gas, 30 psi; ion source gas 1: 50 psi and gas 2: 50 psi; accumulation time, 0.25 s. Nitrogen and argon were used as cone (40 L h−1) and collision (600 L h−1) gases; (other conditions of negative ion mode) ion spray voltage, −4,500 V; declustering potential, −80 V; collision energy, −10 V; declustering potential spred, 0 (other conditions of positive ion mode) ion spray voltage, 5,500 V; declustering potential, 50 V; declustering potential spread, 0; collision energy, 10 V; collision energy spread, 0. The raw data was controlled and acquired by Analyst TF1.7 software (AB SCIEX) with information-dependent acquisition packing. Metabolites were identified by comparison with their retention times, accurate mass, and MS/MS fragments in previous research on Chlorella species as well as elemental analysis (SCIEX OS software version 2.0; AB SCIEX, Foster City, CA, USA) and natural products databases (Massbank, Chemspider, and phytochemical dictionary).

Statistical analysis

All measurements, including TPC, TFC, antioxidant, and enzyme inhibition were expressed as the mean values of three replicates using Sigma Plot 2000 (SPSS Inc., Chicago, IL, USA).

RESULTS AND DISCUSSION

Evaluations of TPC and TFC in Chlorella fusca extract

The total amounts of phenolics and flavonoids were evaluated in the methanol extract of C. fusca by UV-Vis spectrophotometer. Their contents were assessed using linear standard curves of GA (TPC) and QE (TFC). In the current work, the TPC value was found to be 0.84 GAE mg g−1, and the TFC was 1.89 QE mg g−1. Our results differed significantly from prior observations, which stated that TPC and TFC in C. vulgaris were observed with 5.18 GA mg g−1 and 3.46 rutin (Ru) mg g−1 (Habashy et al. 2018). In general, these two factors displayed considerable differences depending on the extraction solvents (Ferdous et al. 2023). Furthermore, compared to earlier studies (MeOH extract: TPC, 13.32 GAE mg g−1; TFC, 40.35 QE mg g−1) (Ferdous et al. 2023), our data showed lower TPC and TFC ratios. Based on the above considerations, we confirmed that the presence of phenolic metabolites in the C. fusca extract was significantly lower than that in other Chlorella species. This phenomenon may be due to diverse environmental conditions affecting Chlorella growth, including growth patterns, genetics, and species, as shown in previous studies (Bock et al. 2011, Habashy et al. 2018, Deamici et al. 2019, Yun et al. 2020, Montoya-Arroyo et al. 2022). However, these two factors may not be key sources or contributors for determining the quality of C. fusca. Our research also demonstrated that phenolic metabolites were not the main components observed in this species using UPLC-Q-TOF-MS/MS analysis.

Measurement of antioxidant properties against DPPH and ABTS radicals in Chlorella fusca extract

For a comprehensive evaluation of the antioxidant properties in C. fusca, the present study demonstrated, for the first time, the scavenging activities on DPPH and ABTS radicals related to simple quality control and strong reproducibility (Safarfar et al. 2015, Rahman et al. 2018, Seal et al. 2020, EI-fayoumy et al. 2021, Ha et al. 2021). The antioxidant capacities at various concentrations compared to those of positive control (ascorbic acid) are shown in Fig. 1. Although extracts of Chlorella species have been studied for various functional factors such as antibacterial, anticancer, and antimicrobial activities (Safarfar et al. 2015, Habashy et al. 2018, EI-fayoumy et al. 2021, Gorgich et al. 2021, Ferdous et al. 2023, Zhou et al. 2023), there are no comprehensive reports on the antioxidant properties in C. fusca and little information is available on the radical scavenging effects of Chlorella extracts. For these reasons, we studied the dose-dependent antioxidant activities of methanol extracts of C. fusca and investigated their capacities by comparing the percentage inhibition patterns under the formation of DPPH and ABTS radicals. The DPPH radical scavenging capacities of the methanol extracts varied remarkably with concentrations. The scavenging activities of the individual samples and the positive control (ascorbic acid) increased with increasing concentrations (600, 400, 200, and 100 μg mL−1) (Fig. 1A). The effects of the Chlorella extracts at different concentrations occurred in the following order: 70% at 600 μg mL−1, 50% at 400 μg mL−1, 34% at 200 μg mL−1, and 27% at 100 μg mL−1. This phenomenon suggests that the antioxidant capacities of C. fusca may be more affected by multiple metabolite constituents and contents, including tocopherols, carotenoids, fatty acids, and phenolics, compared to the results obtained with C. vulgaris in previous studies (Safarfar et al. 2015, Canelli et al. 2022, Kim et al. 2022, Ferdous et al. 2023, Zhou et al. 2023). Furthermore, Chlorella radical scavenging rates may be responsible for diverse factors, such as species, growth conditions, and genetics (Habashy et al. 2018, Yun et al. 2020, Gorgich et al. 2021). Another radical source, the scavenging abilities of ABTS radical also exhibited considerable differences in the individual concentrations (Fig. 1B), similar to the data obtained in the DPPH assay (Fig. 1A). The most potent ABTS radical scavenging ability was found in the Chlorella extract at 200 μg mL−1 (90%), and the remaining effects showed significant differences at each concentration as follows: 62% at 100 μg mL−1, 39% at 50 μg mL−1, and 24% at 25 μg mL−1 (Fig. 1B). In other words, their capacities increased with dose-dependent activation according to the increases of sample concentrations in the following rank order: 200 > 100 > 50 > 25 μg mL−1, similar to those of the DPPH radical. Overall, all Chlorella extracts had higher radical scavenging abilities, approximately four-fold higher than that of the DPPH radical (Fig. 1A & B). These differences may be positively correlated with the reaction ratios between the radical sources and metabolites in the Chlorella extract, as observed in previous research crop studies (Rahman et al. 2018, Seal et al. 2020, Lee et al. 2023). Our results confirm that ABTS radical inhibition can be determined by the chain breaking and hydrogen donating effects of many metabolites (tocopherols, carotenoids, fatty acids, etc.) in the methanol extract by comparison with the hydrogen donating characteristics of the DPPH radical reaction (Safarfar et al. 2015, Canelli et al. 2022, Lee et al. 2023). Moreover, the present data are consistent with earlier results on the antioxidant patterns of other Chlorella species (Canelli et al. 2022, Ferdous et al. 2023). Even though the methanol extract of C. fusca showed slightly lower abilities compared with the positive controls (DPPH: ascorbic acid; 70%, ABTS: Trolox; 92%, 200 μg mL−1), the above findings reveal that C. fusca may serve as an active free radical scavenger and an excellent source of natural antioxidants. We believe that this material may provide several options for the development and utilization of functional agents for improving human health.

Fig. 1

Comparisons of antioxidant and DNA protectant properties in the methanol extract of Chlorella fusca. (A) DPPH (2,2-diphenyl-1-pycrylhydrazyl) radical scavenging activities. (B) ABTS (2,2′-azino-bis(3-ethylbenzthiazoline-6-sulphonic acid)) radical scavenging activities. (C) DNA protectant activities. Lane 1, pUC18 only; lane 2, pUC18 with dithiothreitol (DTT) only; lane 3, pUC18 with FeCl3 only; lane 4, pUC18 with metal-catalyzed oxidation (MCO) system; lanes 5–9, pUC18 with combinant extracts in the MCO system (lane 5: 5, lane 6: 10, lane 7: 25, lane 8: 50, lane 9: 100, lane 10: 250, lane 11: 500, and lane 12: 1,000 μg mL−1). Nicked form (NF) and super-coiled form (SF) of the plasmid DNA are indicated by arrows.

Measurement of DNA protection in Chlorella fusca extract

On the basis of the DPPH and ABTS radical scavenging capacities, to get more meaningful results on the antioxidant effect, we examined the super-coiled DNA protection rates of recombinants in the methanol extract of C. fusca. Briefly, the ability of this source to prevent hydroxyl radical-induced oxidative DNA damage was investigated at different concentrations based on the gel mobility in a MCO system. This assay was prepared by comparing the percentage protections using eight different concentrations (1,000, 500, 250, 100, 50, 25, 10, and 5 μg mL−1) of the methanol extract (Fig. 1C). The defense patterns of DNA oxidation showed remarkable differences in the concentrations of the samples. As indicated in Fig. 1C, the methanol extracts were detected with low DNA damage protection (< 45%) at 50, 25, 10, and 5 μg mL−1 in comparison to those of the protection bands at high concentrations of 1,000, 500, 250, and 100 μg mL−1. In detail, the DNA bands were protected with 86, 73, 63, and 51% after incubating the C. fusca extracts at 1,000, 500, 250, and 100 μg mL−1, respectively, compared to that of the control (1 kb DNA marker pUC18 only) (Fig. 1C). Therefore, the antioxidant patterns showed high DNA protection rates (> 50% at 100 μg mL−1) with markedly increasing activities according to the increases in sample concentrations. Although the potential DNA protection rates exhibited similar patterns as the data obtained from the radical scavenging assays, their activities were in the following order: ABTS > DNA protection > DPPH (ex. 62%; ABTS, 51%; DNA protection, 27%; DPPH at 100 μg mL−1). These findings may be significantly influenced by the metabolite profiles and their contents, as well as the reaction portions, through antioxidant methods, as previously described (Rahman et al. 2018, Seal et al. 2020, Ferdous et al. 2023, Kang et al. 2023). From the current results, the methanol extract of C. fusca may be an excellent source for oxidative DNA damage protection in the nicked DNA through the MCO system. Our data provide valuable evidence that this source is beneficial human health. To the best of our knowledge, this is the first study to reveal that C. fusca extract has potential antioxidant properties related to radical scavenging and DNA cleavage factors.

Measurement of enzymatic inhibitions on tyrosinase and elastase in Chlorella fusca extract

To explore more available information, we measured enzyme inhibitory effects of C. fusca extract against tyrosinase and elastase. These enzymes have been the most prominant targets in the cosmetic industry owing to their skin whitening and anti-wrinkle properties (Ando et al. 2004, Azmi et al. 2014, Lee et al. 2023). Unfortunately, up to now, several literatures have not shown the relationship between the inhibition of these enzymes in Chlorella species. Therefore, we conducted the tyrosinase and elastase inhibitory capacities according to the percentage rates at each concentration of the C. fusca extract. Based on the antioxidant results and the previous experiments, the appropriate tyrosinase inhibition was achieved with high activity (93%) at 140 μg mL−1. As illustrated in Fig. 2A, tyrosinase inhibition effects were observed with significant dose-dependent variations at different methanol extract concentrations. Specifically, the inhibitory rates of this enzyme increased with increased concentrations of the C. fusca extract as follows: 35 μg mL−1; 54% → 70 μg mL−1; 73% → 140 μg mL−1; 93% (Fig. 2A). Moreover, the present data showed similar patterns to the results of DPPH and ABTS radical scavenging assays. These symptoms may be strongly associated with the fatty acid profiles and contents of C. fusca, as reported in previous studies (Ando et al. 2004, Zhou et al. 2022, 2023, Ferdous et al. 2023, Kang et al. 2023). Even though the methanol extracts were detected to have approximately 20% lower inhibition abilities compared to the positive control (ascorbic acid, 96% at 70 μg mL−1), this material may be considered an outstanding natural functional food agent beneficial to humans owing to its diverse metabolites and biological properties. To gather further information on these tyrosinase inhibitory properties, we investigated the inhibition patterns at the reaction times during 30 min. When the reaction time was increased (0 → 30 min, 2 min intervals), the inhibition rates of extracts at different concentrations decreased in a dose-dependent manner (Fig. 2A). To be specific, according to the increases of reaction times at 140 μg mL−1, the tyrosinase inhibitory activities were reduced by 93% (2 min) → 79% (4 min) → 73% (6 min) → 70% (8 min) → 67% (12 min) → 65% (20 min) → 63% (24 min) → 61% (30 min), compared to those of the positive control (96 → 87%, 70 μg mL−1). Furthermore, other concentrations exhibited similar tendencies with 73% (2 min) → 60% (4 min) → 48% (10 min) → 45% (18 min) → 40% (30 min) at 70 μg mL−1 and 54% (2 min) → 46% (4 min) → 41% (10 min) → 40% (18 min) → 36% (30 min) at 35 μg mL−1. Notably, the inhibition effects of this enzyme considerably decreased up to 0 → 10 min, and the reaction times between 10 and 30 min showed mild variations with slight decreases. These findings indicate that C. fusca may be considered an effective agent for skin-whitening in the cosmetic industry (Ando et al. 2004, Safarfar et al. 2015, Ferdous et al. 2023). In addition, it is believed that C. fusca extract will help promote potential applications in crop growth, such as flowering, cultivation, seedling development, resistance to environmental stress, and various human health-promoting abilities, as previously described (Musharraf et al. 2012, Safi et al. 2014, Kotrbácek et al. 2015, Deamici et al. 2019, EI-fayoumy et al. 2021, Martini et al. 2021, Canelli et al. 2022, Ferdous et al. 2023).

Fig. 2

Comparisons of tyrosinase and elastase inhibitory capacities in the methanol extracts of Chlorella fusca through reaction times. (A) Tyrosinase inhibitory effects. (B) Elastase inhibitory effects.

Another study on cosmeceutical functions was conducted on elastase inhibitory activity. According to the precedent experimental results of antioxidant and tyrosinase inhibitory activities, the elastase inhibition patterns were measured with percentage ratios by comparing different concentrations of the sample and the positive control (ursolic acid). Their inhibitory properties increased with increasing concentrations of the sample as follows: 1,000 μg mL−1, 100%; 500 μg mL−1, 100%; 400 μg mL−1, 91%; and 200 μg mL−1, 88%. Although 100% inhibition was detected at 1,000 and 500 μg mL−1, the elastase inhibition rate was evaluated at 400 μg mL−1 owing to dose-dependent variation. Elastase inhibition was 3-fold lower compared to that of tyrosinase (Fig. 2). These observations suggest that the metabolite profiles and contents, such as fatty acids, of the C. fusca extract may lead to higher effective inhibitory capacities for tyrosinase than elastase, as shown in earlier studies (Ando et al. 2004, Zhou et al. 2022). This phenomenon was also similar to that reported in previous research on the anti-elastase and anti-tyrosinase abilities of earthworm extracts (Azmi et al. 2014). As shown in Fig. 2B, considerable differences in the elastase inhibition patterns were observed at three different concentrations of 400, 200, and 100 μg mL−1 with the rank order as follows: 91 > 88 > 66%. Even though the C. fusca extract showed mildly lower inhibitory abilities than the positive control (92% at 100 μg mL−1), this material may be a potent anti-elastase source for improving skin elasticity and resistance. To obtain more information on the variation trends under different reaction times, the methanol extract was examined for elastase inhibitory capacities during 30 min (2 min intervals) at different concentrations (Fig. 2B). Briefly, the elastase inhibitory rates persistently decreased with increasing reaction time, with significant differences depending on concentration. Especially, the inhibition patterns of this enzyme were remarkably different from those of tyrosinase. For example, the C. fusca extract at 400 μg mL−1 was considerably reduced by 92%; 2 min → 53%; 30 min when the increase of reaction times (92%; 2 min → 74%; 10 min → 65%; 20 min → 53%; 30 min) and showed the continuous decrease patterns (88%; 2 min → 67%; 10 min → 55%; 20 min → 39%; 30 min) with dose-dependent capacities at 200 μg mL−1. The positive control (100 μg mL−1) also displayed similar tendencies (92%; 2 min → 85%; 10 min → 81%; 20 min → 71%; 30 min), specifically, their inhibition rates were seen to have an approximately 30% higher effect when compared to the sample extracts (Fig. 2B). These results imply that the inhibitory capacities of the samples against elastase may be positively related to the presence and content of abundant metabolites (Ando et al. 2004, Zhou et al. 2022, 2023, Kang et al. 2023). For the above considerations, C. fusca extract may be used as a potent cosmeceutical agent and an excellent natural source for the anti-aging industry. As far as we know, the present research is the first to evaluate the inhibition activities of C. fusca, including those against tyrosinase and elastase.

Elucidation of metabolite profiles in Chlorella fusca extract using negative and positive ion modes of UPLC-Q-TOF-MS/MS

UPLC coupled with mass spectrometric detection has been widely used to investigate metabolite profiles with molecular weights in diverse natural sources, such as crops, foods, and vegetables (Rivera et al. 2014, Pantami et al. 2020, Koch et al. 2021, Feng et al. 2022). This technique offers the most meaningful information for characterization through metabolite assignment, which involves the fragmentation of a selected precursor ion in the product ions from the various peaks of the target sample (Nilsson et al. 2010, Rivera et al. 2014, Koch et al. 2021). For these reasons, to obtain exact information on the metabolite profiles of C. fusca, UPLC-Q-TOF-MS/MS analysis was carried out in both negative and positive ion modes. Moreover, we used a highly polar methanol solvent to achieve an effective metabolite extraction ratio (Safarfar et al. 2015, Zhou et al. 2022, Ferdous et al. 2023, Lee et al. 2023). The metabolite constituents were tentatively elucidated by comparing the product ions and their selected precursor ions to the MS and MS/MS data of the detected peaks in previous studies on Chlorella species as well as the phytochemical dictionary, Massbank (https://www.Massbank.jp), and ChemSpider (https://www.chemspider.com) of the Natural Products Database. In the current study, a complete chromatographic separation of many metabolites, including major and minor peaks was achieved within 45 min (Fig. 3).

Fig. 3

Ultra-high performance liquid chromatography coupled with quadrupole time-of-flight mass spectrometry (UPLC-Q-TOF-MS/MS) base peak intensity chromatograms through different ion modes in the methanol extract of Chlorella fusca. (A) UPLC-Q-TOF-MS chromatogram using negative ion mode. (B) UPLC-Q-TOF/MS chromatogram using positive ion mode.

First, we demonstrated 26 components in diverse peaks by the negative ion mode from the methanol extract of C. fusca (Fig. 3A). Their structures were identified with five chemical skeletons: 4-nonylphenol, diterpene alcohol, fatty alcohol, fatty acid, and chlorophyll groups (Fig. 4A). The TOF-MS and MS/MS analyses of peak 1 (tR = 6.3 min) presented the molecular ion [M–H] at m/z 293.2134 (1A in Supplementary Fig. S2A) and a fragment ion at m/z 195.1378 (1B in Supplementary Fig. S2A), which was formed by the loss of the m/z 98 fragment (cleavage of hydroxybenzene ring: 68 amu; C4H4O and methoxy group: 30 amu; OCH3). Based on the above molecular ions and previous data, this peak was elucidated as 4-nonyl-(1-methyl, 6,8-methoxy)-hydroxybenzene (1) of the 4-nonylphenol group (López-Pacheco et al. 2019). The UPLC-TOF-MS/MS scan of peak 2 (tR = 7.7 min) exhibited an identical molecular ion [M–H] at m/z 295.2283 and the two fragment ions at m/z 167.1076 and m/z 141.1279 (2A and 2B in Supplementary Fig. S2A). These ions were characterized as phytol (2), in agreement with previous work on C. vulgaris axenic culture (El-fayoumy et al. 2021). The product ions mass spectra of peaks 3 (tR = 9.1 min) and 4 (tR = 11.9 min) displayed [M–H] ions at m/z 295.2293 and m/z 297.2439, respectively, and their characteristic fragment ions were observed at m/z 195.1377 and m/z 185.1163 in the MS/MS analysis (3A, 4A, 3B, and 4B in Supplementary Fig. S2A). Especially, these fragment ions were formed by the losses of m/z 100 amu {[M–H]–[-CH-(CH2)5OH]; 195 amu} and m/z 112 amu {[M–H]–[-CH-(CH2)6CH3]; 185 amu}. The above molecular weights and fragmentation patterns were similar to those of fatty acids in the published literature (Nilsson et al. 2010). According to the summarized ions and Chlorella research information, peaks 3 and 4 were identified as 11-eicosenol (3) and 1-eicosanol (4), which are fatty alcohol derivatives (Fernandes and Cordeiro 2020). The abundant metabolite types in the remaining diverse peaks were identified as fatty acids and chlorophyll compositions, based on the characteristics of molecular ions and data from earlier studies. Their peaks were as follows: fatty acids, eight peaks 5, 6, 8, 10–12, 17, and 18; chlorophyll, one peak 13 (Figs 3A & 4A). Peak 5 (tR = 12.1 min) exhibited an identical molecular ion [M–H] at m/z 247.1708 and three major fragment ions at m/z 203.1793, m/z 175.1480, and m/z 149.1328 (5A and 5B in Supplementary Fig. S2A). Three fragment ions were assigned as lipid residues with a loss of m/z 44 {[M–H]–44 amu (–COO); m/z 203}, m/z 72 {([M–H]–72 amu (–CH2-CH2-COO); m/z 175)}, and m/z 98 {([M–H]–98 amu (–CH-CH-CH2-CH2-COOH); m/z 149)} (Stigter et al. 2013). According to the above ion profile, this peak coincides with those of hexadeca-4,7,10,13-tetraenoic acid in high concentrations of algae and fish oil (Stigter et al. 2013). The deprotonated molecular ion [M–H] at m/z 249.1863 was found in the UPLC-TOF-MS spectrum of peak 6 (tR = 14.2 min) and two fragments (m/z 205.1950 and m/z 177.1644) were produced in MS/MS data (6A and 6B in Supplementary Fig. S2A). The precursor ion at m/z 205.1950 resulted from the loss of the carboxylic acid (–COO: 44 amu) moiety, and the fragmentation ion at m/z 177.1644 was formed by the loss of the –CH2-CH2-COO (72 amu) (Stigter et al. 2013). These fragmentation characteristics were consistent with those of peak 5. As a result, peak 6 was tentatively assigned to roughanic acid (6) based on a previous report (Cholewski et al. 2018). The TOF-MS and MS/MS spectra of peak 8 (tR = 15.5 min) displayed a [M–H] ion at m/z 299.2596 and two fragment ions at m/z 185.1168 and m/z 139.1123 (8A and 8B in Supplementary Fig. S2A). In particular, these fragment ions may be related to the typical characteristics of cleavage residues in fatty acid structures, as observed in the patterns of peaks 3–5. Moreover, the ion patterns of this peak were in agreement with those of fatty acid derivatives in microalgae sources (Musharraf et al. 2012). Based on this evidence, peak 8 was assumed to be 10-hydroxyoctadecanoic acid (8) (Musharraf et al. 2012). The negative ion mode of peak 9 (tR = 16.8 min) exhibited a molecular ion at m/z 275.2024 (MS) and a fragment ion at m/z 231.2095 (MS/MS) through the loss of a carboxylic acid moiety (44 amu, –COO) (9A and 9B in Supplementary Fig. S2A). The above ion patterns were similar to those of peak 6 and coincided with the chemical characteristics of fatty lipids in C. pyrenoidosa among Chlorella species (Montes D’Oca et al. 2011). Therefore, peak 9 was tentatively confirmed as stearidonic acid (9). Full mass scan analyses of peaks 10 (tR = 17.6 min) and 14 (tR = 22.6 min) were detected with [M–H] ions at m/z 251.2018 and m/z 279.2327 (10A and 14A in Supplementary Fig. S2A) and their fragment ions at m/z 233.1894 and m/z 261.2211 (10B and 14B in Supplementary Fig. S2A). The precursor ions were attributed to the losses of hydrogen ions (−18 amu), including the hydroxyl moiety, and were in agreement with the patterns of fatty acids in C. sorokiniana and C. vulgaris (Yun et al. 2020, Gorgich et al. 2021). By comparing their mass values with data reported in an earlier study, the two peaks were tentatively demonstrated as 7,10-hexadecadienoic acid (10) and linoleic acid (14) (Pantami et al. 2020). Full TOF-MS in negative ion mode of peak 11 (tR = 19.3 min) exhibited a molecular ion at m/z 277.2174 and the MS/MS spectrum showed two minor fragment ions (m/z 233.2265 and m/z 219.1392) (11A and 11B in Supplementary Fig. S2A). Their fragment ions resulted from the losses of 44 amu (carboxyl moiety: –COO) and 58 amu (methyl carboxyl moiety: –CH2-COO), as indicated by previous results related to the rapid quantification of fatty acids in plants using high-performance liquid chromatography mass spectrometry (Pantami et al. 2020, Koch et al. 2021). On the basis of the above mass patterns and molecular weights of published data, this peak was documented as α-linolenic acid (11) (Shimma et al. 2012, Yun et al. 2020, Koch et al. 2021). Subsequently, 13 peaks, 12 and 15–26, were identified by comparisons with the exact MS and MS/MS values using UPLC coupled with the TOF-mass technique, as well as previous results. Their peaks were also compared with the retention times in the chromatogram, in accordance with an earlier study. In the current work, the deprotonated molecular ions were found as follows: m/z 253.2177 (12), m/z 253.2184 (15), m/z 267.2338 (16), m/z 255.2327 (17), m/z 281.2483 (18), m/z 281.2493 (19), m/z 269.2497 (20), m/z 295.2649 (21), m/z 295.2649 (22), m/z 283.2647 (23), m/z 309.2803 (24), m/z 311.2960 (25), and m/z 339.3269 (26) (12A, 15A–26A, 12B, and 15B–26B in Supplementary Fig. S2A). According to the above investigation, their metabolites were tentatively assigned fatty acid distributions, as detailed below (Table 1): 7-hexadecenoic acid (12) (tR = 21.1 min), palmitoleic acid (15) (tR = 23.3 min), heptadecenoic acid (16) (tR = 23.6 min), palmitic acid (17) (tR = 25.4 min), vaccenic acid (18) (tR = 26.7 min), oleic acid (19) (tR = 27.6 min), heptadecanoic acid (20) (tR = 28.6 min), 10-nonadecenoic acid (21) (tR = 29.7 min), 7-nonadecenoic acid (22) (tR = 30.5 min), stearic acid (23) (tR = 31.8 min), gadoleic acid (24) (tR = 32.4 min), arachidic acid (25) (tR = 36.3 min), and behenic acid (26) (tR = 41.1 min) (Montes D’Oca et al. 2011, Yun et al. 2020, Gorgich et al. 2021, Koch et al. 2021). The remaining minor one major peaks (7 and 13) in the negative ion mode showed deprotonated ions [M–H] at m/z 631.2390 and m/z 625.2603 (7A and 13A in Supplementary Fig. S2A), as well as various fragment ions (peak 7: m/z 553.2063; peak 13: m/z 581.2700, m/z 565.2384, m/z 538.2510, and m/z 521.2497) (7B and 13B in Supplementary Fig. S2A). The MS/MS fragmentation of the ion at m/z 553.2063 in peak 7 may be related to loss of the hydroxymethyl (or methoxy) moiety. Among the diverse fragment ions of peak 13, the distinctive product ion at m/z 581.2700 ([M–H]–44 amu) corresponded to the loss of a carboxylic acid moiety, and the fragment ion at m/z 565.2384 resulted from the loss of an acetate moiety ([M–H]–CH3COO: 60 amu). Also, the fragmentation at m/z 521.2497 ([M–H]–104 amu) exhibited losses of carboxylic (44 amu) and acetate (60 amu) moieties. These two peaks were achieved by comparing the molecular weights obtained in the current work with previously reported data concerning chlorophyll derivatives in grapevine and basil leaves (Li et al. 2018, Moser et al. 2020). In particular, a previous study documented that peak 13 is converted to peak 7 via the pheophorbide oxygenase / phyllobilin pathway for chlorophyll breakdown (Moser et al. 2020). Based on the above considerations, their chemical structures were determined to chlorophyll catabolite (phyllobilin) (7) and 10,22-dihydro-4,5-dioxo-4,5-secopheophorbide a (13). Although two compositions have been previously identified in other natural materials, we demonstrated for the first time their presence in Chlorella source. Overall, we revealed 26 metabolites, including one 4-nonylphenol (1), one diterpene alcohol (2), two fatty alcohols (3 and 4), two chlorophylls (7 and 13), and 20 fatty acids (5, 6, 8–12, and 14–26) in the negative ion mode using the UPLC-TOF-MS/MS technique from the methanol extract of C. fusca (Fig. 4A).

Fig. 4

Chemical structures of the identified metabolite compositions from the methanol extract of Chlorella fusca. (A) Metabolite structures through negative ion mode of ultra-high performance liquid chromatography coupled with quadrupole time-of-flight mass spectrometry (UPLC-Q-TOF-MS/MS). (B) Metabolite structures through positive ion mode of UPLC-Q-TOF-MS.

Identification of metabolite profiles in the methanol extract of Chlorella fusca by the negative and positive ion modes of UPLC-Q-TOF-MS/MS

To obtain more valuable information on the metabolite profiles of C. fusca, we also conducted analyses in the positive ion mode of UPLC-TOF-MS. As illustrated in Fig. 3B, the complete chromatographic separation of various metabolites was achieved within 45 min. A total of 36 metabolites were tentatively identified, and their structures were confirmed to belong to 11 chemical groups: fatty acid, fatty alcohol, chlorophyll, carotenoid, lysophospholipid, lipid, oxaspiro, 4-nonylphenol, diterpene alcohol, ergostane, and tocopherol (Fig. 4B). Among the various metabolites, 10 compositions were identified by the full scan experiment in the negative ion mode (peaks 3–5, 7, 8, 13, 17, 20, 26, and 27) (Table 1). In particular, peaks 4, 13, and 14 exhibited remarkably higher intensities than the other components (Fig. 3B). Peak 1 (tR = 6.3 min) showed a molecular ion [M+H]+ at m/z 277.2153, and the MS/MS fragmentation patterns exhibited three major and three minor fragment ions at m/z 189.1259, m/z 159.1178, m/z 147.1176, and m/z 107.0856 (1A and 1B in Supplementary Fig. S2B). Based on these molecular ions, this compound was tentatively identified as 7,9-di-tert-butyl-1-oxaspiro[4.5]deca-6,9-diene-2,8-dione (1) by comparison with previously reported data on Chlorella species and mass spectra in the NIST Chemistry WebBook. The TOF-MS analysis of peak 2 (tR = 9.1 min) revealed the molecular ion [M+H]+ at m/z 279.2307 (2A in Supplementary Fig. S2B) and fragment ions in the MS/MS spectrum were observed at m/z 149.0247, m/z 121.1024, and m/z 107.0863 (2B in Supplementary Fig. S2B). These ion patterns are similar to those of peaks 5, 6, and 11, due to the losses of various –CH2-COOH moieties (–130 amu, –158 amu, –170 amu, and –172 amu). In addition, their patterns were based on earlier studies of commercial C. vulgaris and cultivated microalgae (Sotoudehniakarani et al. 2019). Thus, this peak was confirmed as α-eleostearic acid (2). Full TOF mass analyses of peaks 6, 10, 28, and 29 were observed for [M+H]+ ions at m/z 601.5371, m/z 567.4166, m/z 551.4199, and m/z 657.4106, and their retention times were 15.5, 21.3, 32.4, and 32.8 min, respectively. Fragment ions were detected in the MS/MS spectra, as illustrated in Table 1. Especially, the characteristic MS/MS fragment ion at m/z 283.2610 of peak 6 resulted from the loss of water (H2O) and C20H27O residue in the protonated parent ions (6A and 6B in Supplementary Fig. S2B). This may indicate an α-cleavage of the molecular following a radical side rearrangement through π-bond dissociation of the molecular ion (Pantami et al. 2020). Based on the above ion patterns and earlier results for carotenoid derivatives, this peak was assigned to neoxanthin (6) (Rivera et al. 2014, Pantami et al. 2020). In the TOF-MS and MS/MS spectra, peak 10 was detected as a protonated ion [M+H]+ at m/z 567.4166 with three signals at m/z 211.1488 ([M+H]+–356 amu), m/z 145.1019 ([M+H]+–422 amu), and m/z 119.0862 ([M+H]+ –448 amu) (10A and 10B in Supplementary Fig. S2B). Three ion peaks indicate the presence of conjugated polyene chains with cleavage of characteristic fragmentations regarding the 3′-keto chromophoric moiety of the β-end group and the 3-hydroxy furanoid moiety of the ɛ-end group (Molnár et al. 2006) in the carotenoid structures, as previously published (Rivera et al. 2014, Pantami et al. 2020). From the mentioned evidence, this peak was characterized as 3′-oxolutein with the C40H54O2 formula. The patterns of fragmentation ions in peaks 28 and 29 were similar to those of the carotenoid derivatives 6 and 10 (28A, 28B and 29A, 29B in Supplementary Fig. S2B). The fragment ions were assigned as residues (peak 28: m/z 211.1487, m/z 145.1020, and m/z 119.0858) through the cleavage of mono keto furanoid and furanoid frameworks (Rivera et al. 2014, Pantami et al. 2020), and two fragment ions at m/z 597.3884 and m/z 581.3959 in peak 29 were characterized as carotenoid residues due to the losses of the acetate ion (CH3COO, 60 amu) and CH3COO+OH, 76 amu) (Stigter et al. 2013). Based on the above molecular weights and previous results, peaks 28 and 29 were identified as echinenone (29) and all-trans fucoxanthin (30). Subsequently, 12 peaks (9, 11, 12, 14–16, 18, 19, 21, 23, 24, and 36) exhibited the molecular ions ([M+H]+) at m/z 549.2484, m/z 609.2676, m/z 625.2603, m/z 607.2563, m/z 609.2665, m/z 593.2723, m/z 593.2720, m/z 535.2668, m/z 639.2766, m/z 623.2815, m/z 587.4315, and m/z 557.4560 (Table 1, Supplementary Fig. S2B). Furthermore, their main product ions in the TOF-MS/MS chromatograms are displayed as follows: m/z 521.2545 (9), m/z 591.2548 (11), m/z 581.2700, 565.2384, 538.2510, and 521.2497 (12), m/z 531.2371 (14), m/z 591.2327, 559.2282, 531.2300, and 515.2406 (15), m/z 533.2506 (16), m/z 533.2500 (18), m/z 507.2716 (19), m/z 621.2643, 579.2553, and 552.2671 (21), m/z 605.2693 and 545.2488 (23), m/z 309.2054 (24), and m/z 279.2312 (36). Most of the fragment ions resulted from the losses of methyl, hydroxyl, acetyl, CO, and their mixed moieties, as earlier studies have determined for chlorophyll derivatives in natural plants (Li et al. 2018, Viera et al. 2018). Additionally, these 12 peaks exhibited similar patterns to those of chlorophyll structures (Chen et al. 2015a, 2015b, Li et al. 2018, Viera et al. 2018). Their chemical structures are listed in Table 1 and shown in Fig. 4. To the best of our knowledge, little information has been obtained previously regarding the exact MS and MS/MS values of chlorophyll profiles in C. fusca by UPLC coupled with TOF-MS skill. To obtain more information on the metabolic components of the remaining peaks, we evaluated five peaks (30–34) within the range of 33.5–39.0 min (Fig. 3B). Previous studies have shown that many polar lipid profiles, such as phospholipids and glycolipids, are present in microalgal sources (Vello et al. 2018, Conde et al. 2021, Canelli et al. 2022). Especially, it is well demonstrated that the polar lipid compositions (phosphatidylcholine [PC], phosphatidylglycerol [PG], phosphatidylinositol [PI], lysophosphatidylethanolamine [LPE], lysophosphatidylcholine, and phosphatidylethanolamine) in Chlorococcum amblystomatic of green microalgae are known to exhibit health benefits of antioxidant and anti-inflammatory properties (Conde et al. 2021). A full TOF mass scan of five peaks (30; tR = 33.6 min, 31; tR = 33.8 min, 32; tR = 34.4 min, 33; tR = 34.9 min, and 34; tR = 38.9 min) displayed the molecular ion [M+H]+ at m/z 803.4916 (30), m/z 762.5092 (31), m/z 573.4508 (32), m/z 478.3853 (33), and m/z 508.5064 (34) (30A–34A in Supplementary Fig. S2B), and their fragment ions were as follows: m/z 513.3036 and m/z 277.2159 (30); m/z 335.2551 (31); m/z 295.2261 and m/z 185.1172 (32); m/z 222.1478 and m/z 140.0712 (33); m/z 146.1181 (34) (30B–34B in Supplementary Fig. S2B). Although the distribution of polar lipids displayed mild differences, our data are similar to those of earlier studies that determined the polar lipid components in microalgal species (Conde et al. 2021). Based on the fragmentation patterns in the published studies and their MS and MS/MS data in the present work, the chemical structures were elucidated as below: PG (16:0/22:2) (30), PC (16:0/18:0) (31), PI (16:0/0:0) (32), LPE (18:2/0:0) (33), and LPE (20:1/0:0) (34) (Shimma et al. 2012, Calvano et al. 2020, Conde et al. 2021). Peak 22 (tR = 28.6 min) presented a molecular ion ([M+H]+) at m/z 269.2497 in the TOF-MS spectrum, and its characteristic fragment ion was m/z 251.2368 (22A and 22B in Supplementary Fig. S2B). This fragmentation pattern may result from the loss of a water or hydroxyl moiety ([M+H–18, –18 amu]+), which is in accordance with an earlier study (Rivera et al. 2014). The fragment pattern of this peak (m/z 269.2497 → m/z 251.2368) was also coincident with it of peak 27 (m/z 283.2647 → m/z 265.2521, oleic acid) through the loss of –18 amu. These ions were verified to have the same patterns as the metabolites in C. stigmatophora based on published data (Fernandes and Cordeiro 2020) and the mass spectrum in the NIST Chemistry WebBook. This component was confirmed to be 9-octadecen-1-ol (22) and has been detected in Chlorella species, such as C. amblystomatis, C. sorokiniana, and C. vulgaris (Yun et al. 2020, Conde et al. 2021). The TOF-MS and MS/MS chromatograms in positive ion mode of peak 25 (tR = 29.0 min) showed an identical molecular ion ([M+H]+) at m/z 395.3280 (25A in Supplementary Fig. S2B) and four fragmentation ions (m/z 377.3202, –18 amu; m/z 251.1794, –144 amu; m/z 211.1479, 184 amu; and m/z 125.1329, –270 amu) (25B in Supplementary Fig. S2B). The precursor ion at m/z 377.3202 resulted from the loss of a dehydrated molecular ion ([M+H–18, –H2O]+) and the fragment ion at m/z 125.1329 was a common pattern formed from the primary cleavage of the C17–C20 bond in the sterol side chain (270 amu). Additionally, the major fragment at m/z 211.1479 was formed by the loss of an m/z 184 fragment (m/z 395.3280 → m/z 211.1479: ([M+H]+–{H2O+(C–D) ring cleavage}) + side chain of sterol) (West and Reid 2021, Feng et al. 2022). The major ion was observed at m/z 251.1794, which was formed by the loss of m/z 144 fragment (m/z 395 → m/z 251; {[M+H]+ – (A ring cleavage: C1;4–C5;10) + (C23–C24 cleavage in side chain)}) (Feng et al. 2022). According to the above observations, this peak was assumed to be 9,11-dehydroergosterol (C28H42O) (25). The TOF-MS and MS/MS profiles of peak 35 (tR = 39.8 min) displayed a molecular ion [M+H]+ at m/z 429.3693, with one main fragment ion at m/z 165.0908 (35A and 35B in Supplementary Fig. S2B). The major ion at m/z 165.0908 was characteristic of a C10H13O2 moiety, and the lost fragment (–264 amu) corresponded to an alkylchain (16-carbonside chain) residue (Montoya-Arroyo et al. 2022). These findings are in agreement with the earlier result that 11′-α-tocomonoenol was present in cultured microalgae (C. sorokiniana, N. limnetica, and T. suecica) (Montoya-Arroyo et al. 2022). On the basis of the UPLC-TOF-MS analysis, we determined the peak number, elemental formula, retention times, and mass spectral values, including the molecular and fragmentation ions of the total metabolite compositions (Table 1). The present research was undertaken to provide information on a rapid and sensitive method for the identification of 26 (negative) and 36 (positive) metabolites in different ion modes by UPLC-TOF-MS analysis of C. fusca (Fig. 3). Moreover, the identified metabolite profiles revealed remarkable differences in the individual and total compositions between the two modes (Fig. 4). These data are useful for evaluating the development of human health agents using C. fusca. To the best of our knowledge, the present results document, for the first time, the metabolite compositions as determined by different ion modes using UPLC-TOF-MS/MS.

CONCLUSION

Our work represents the first presentation of detailed information concerning various metabolites through UPLC-TOF-MS in both negative and positive ion modes from a methanol extract of C. fusca. A total of 62 components (26 in the negative mode and 36 in the positive mode) were simultaneously identified, and their chemical structures were markedly distinct in the two ion modes, organized as fatty acid > chlorophyll > polar lipid > carotenoid. Moreover, this source exhibited high biological capacities in the rank order of tyrosinase > ABTS > elastase > DPPH; specifically, the ABTS radical was observed to have approximately 3 times higher scavenging activity (90%) than DPPH (34%) at 200 μg mL−1. The enzymatic inhibitions of tyrosinase and elastase also revealed significant differences in ratios greater than 50% (tyrosinase: 93.4 → 61.1% at 140 μg mL−1; elastase: 90.5 → 52.0% at 200 μg mL−1) over 30 min. These findings may be utilized as basic data to maximize the efficiency and industrial applications of C. fusca. Our results provide important information for the practical application of Chlorella in the development of agricultural and nutraceutical agents. Further studies on high-value metabolites and biofuel production will improve the economics of commercial-scale cultivation of Chlorella species.

ACKNOWLEDGEMENTS

This work was carried out with the support of “Cooperative Research Program for Agriculture Science and Technology Development (Project No. PJ015641)” Rural Development Administration, Republic of Korea. Also, this research was supported by the Basic Science Research Program through the National Research Foundation of Korea (NRF) funded by the Ministry of Education (Grant number 2020R1A6A1A03047729), Republic of Korea, and the Biomaterials Specialized Graduate Program through the Korea Environmental Industry & Technology Institute (KEITI) funded by the Ministry of Environment (MOE).

Abbreviations

ABTS

2,2′-azino-bis(3-ethylbenzthiazoline-6-sulphonic acid)

DPPH

2,2-diphenyl-1-pycrylhydrazyl

DTT

dithiothreitol

GA

gallic acid

GAE

gallic acid equivalents

LPE

lysophosphatidylethanolamine

MCO

metal-catalyzed oxidation

PC

phosphatidylcholine

PG

phosphatidylglycerol

PI

phosphatidylinositol

QE

quercetin

TFC

total flavonoid content

TPC

total phenolic content

UPLC-Q-TOF-MS

ultra-high performance liquid chromatography coupled with quadrupole time-of-flight mass spectrometry

Notes

The authors declare that they have no potential conflicts of interest.

SUPPLEMENTARY MATERIALS

Supplementary Fig. S1. Appearance of Chlorella fusca (CHK0059) (https://www.e-algae.org).

algae-2024-39-3-187-Supplementary-Fig-S1.pdf

Supplementary Fig. S2. Ultra-high performance liquid chromatography coupled with quadrupole time-of-flight mass spectrometry (UPLC-Q-TOF-MS/MS) spectra through mass fragmentation patterns of the identified metabolites (https://www.e-algae.org).

algae-2024-39-3-187-Supplementary-Fig-S2.pdf

References

Ando H., Watabe H., Valencia J. C., et al. 2004;Fatty acid regulate pigmentation via proteasomal degradation of tyrosinase: a new aspect of ubiquitin-proteasome function. J. Biol. Chem 279:15427–15433. doi.org/10.1074/jbc.M313701200.
Azmi N., Hashim P., Hashim D. M., Halimoon N., Majid N. M. N.. 2014;Anti-elastase, anti-tyrosinase and matrix metalloproteinase-1 inhibitory activity of earthworm extracts as potential new anti-aging agent. Asian Pac. J. Trop. Biomed 4(Suppl 1):S348–S352. doi.org/10.12980/APJTB.4.2014C1166.
Bock C., Krienitz L., Pröschold T.. 2011;Taxonomic reassessment of the genus Chlorella (Trebouxiophyceae) using molecular signatures (barcodes), including description of seven new species. Fottea 11:293–312. doi.org/10.5507/fot.2011.028.
Calvano C. D., Bianco M., Ventura G., Losito I., Palmisano F., Cataldi T. R. I.. 2020;Analysis of phospholipids, lysophospholipids, and their linked fatty acyl chains in yellow lupin seeds (Lupinus luteus L.) by liquid chromatography and tandem mass spectrometry. Molecules 25:805. doi.org/10.3390/molecules25040805.
Canelli G., Tevere S., Jaquenod L., et al. 2022;A novel strategy to simultaneously enhance bioaccessible lipids and antioxidants in hetero/mixotrophic Chlorella vulgaris as functional ingredient. Bioresour. Technol 347:126744. doi.org/10.1016/j.biortech.2022.126744.
Chae H., Kim E. J., Kim H. S., Choi H. G., Kim S., Kim J. H.. 2023;Morphology and phylogenetic relationships of two Antarctic strains within the genera Carolibrandtia and Chlorella (Chlorellaceae, Trebouxiophyceae). Algae 38:241–252. doi.org/10.4490/algae.2023.38.11.30.
Chen K., Ríos J. J., Pérez-Gálvez A., Roca M.. 2015a;Development of an accurate and high-through put methodology for structural comprehension of chlorophylls derivatives. (I) Phytylated derivatives. J. Chromatogr. A 1406:99–108. doi.org/10.1016/j.chroma.2015.05.072.
Chen K., Ríos J. J., Roca M., Pérez-Gálvez A.. 2015b;Development of an accurate and high-through put methodology for structural comprehension of chlorophylls derivatives. (II) Dephytylated derivatives. J. Chromatogr. A 1412:90–99. doi.org/10.1016/j.chroma.2015.08.007.
Cholewski M., Tomczykowa M., Tomczyk M.. 2018;A comprehensive review of chemistry, sources and bioavailability of omega-3 fatty acids. Nutrients 10:1662. doi.org/10.3390/nu10111662.
Conde T. A., Couto D., Melo T., et al. 2021;Polar lipidomic profile shows Chlorococcum amblystomatis as a promising source of value-added lipids. Sci. Rep 11:4355. doi.org/10.1038/s41598-021-83455-y.
Deamici K. M., Santos L. O., Costa J. A. V.. 2019;Use of static magnetic fields to increase CO2 biofixation by the microalga Chlorella fusca. Bioresour. Technol 276:103–109. doi.org/10.1016/j.biortech.2018.12.080.
EI-fayoumy E. A., Shanab S. M. M., Gaballa H. S., Tantawy M. A., Shalaby E. A.. 2021;Evaluation of antioxidant and anticancer activity of crude extract and different fractions of Chlorella vulgaris axenic culture grown under various concentrations of copper ions. BMC Complement. Med. Ther 21:51. doi.org/10.1186/s12906-020-03194-x.
Feng M., Jin Y., Yang S., et al. 2022;Sterol profiling of Leishmania parasites using a new HPLC-tandem mass spectrometry-based method and antifungal azoles as chemical probes reveals a key intermediate sterol that supports a branched ergosterol biosynthetic pathway. Int. J. Parasitol. Drugs Drug Resist 20:27–42. doi.org/10.1016/j.ijpddr.2022.07.003.
Ferdous U. T., Nurdin A., Ismail S., Yusof Z. N. B.. 2023;Evaluation of the antioxidant and cytotoxic activities of crude extracts from marine Chlorella sp. Biocatal. Agric. Biotechnol 47:102551. doi.org/10.1016/j.bcab.2022.102551.
Fernandes T., Cordeiro N.. 2020; Hemiselmis andersenii and Chlorella stigmatophora as new sources of high-value compounds: a lipidomic approach. J. Phycol 56:1493–1504. doi.org/10.1111/jpy.13042.
Gorgich M., Martins A. A., Mata T. M., Caetano N. S.. 2021;Composition, cultivation and potential applications Chlorella zofingiensis: a comprehensive review. Algal Res 60:102508. doi.org/10.1016/j.algal.2021.102508.
Ha T. J., Park J. E., Lee K.-S., et al. 2021;Identification of anthocyanin compositions in black seed coated Korean adzuki bean (Vigna angularis) by NMR and UPLC-Q-Orbitrap-MS/MS and screening for their antioxidant properties using different solvent systems. Food Chem 346:128882. doi.org/10.1016/j.foodchem.2020.128882.
Habashy N. H., Abu Serie M. M., Attia W. E., Addelgaleil S. A. M.. 2018;Chemical characterization, antioxidant and anti-inflammatory properties of Greek Thymus vulgaris extracts and their possible synergism with Egyptian Chlorella vulgaris. J. Funct. Foods 40:317–328. doi.org/10.1016/j.jff.2017.11.022.
Kang N., Heo S.-Y., Kim E.-A., Ryu B., Heo S.-J.. 2023;Antiviral effect of fucoxanthin obtained from Sargassum siliquastrum (Fucales, Phaeophyceae) against severe acute respiratory syndrome coronavirus 2. Algae 38:295–306. doi.org/10.4490/algae.2023.38.11.29.
Kim M., Oh H. J., Nguyen K., Jin E.. 2022;Identification and characterization of Dunaliella salina OH214 strain newly isolated from a saltpan in Korea. Algae 37:317–329. doi.org/10.4490/algae.2022.37.9.13.
Koch E., Wiebel M., Hopmann C., Kampschulte N., Schebb N. H.. 2021;Rapid quantification of fatty acids in plant oils and biological samples by LC-MS. Anal. Bioanal. Chem 413:5439–5451. doi.org/10.1007/s00216-021-03525-y.
Kotrbáček V., Doubek J., Doucha J.. 2015;The chlorococcalean alga Chlorella in animal nutrition: a review. J. Appl. Phycol 27:2173–2180. doi.org/10.1007/s10811-014-0516-y.
Lee J. H., Seo E. Y., Lee Y. M.. 2023;Comparative investigation on variations of nutritional components in whole seeds and seed coats of Korean black soybeans for different crop years and screening of their antioxidant and anti-aging properties. Food Chem. X 17:100572. doi.org/10.1016/j.fochx.2023.100572.
Li C., Wurst K., Berghold J., Podewitz M., Liedl K. R., Kräutler B.. 2018;Pyro-phyllobilins: elusive chlorophyll catabolites lacking a critical carboxylate function of the natural chlorophylls. Chem. Eur. J 24:2987–2998. doi.org/10.1002/chem.201705331.
López-Pacheco I. Y., Salinas-Salazar C., Silva-Núñez A., et al. 2019;Removal and biotransformation of 4-nonylphenol by Arthrospira maxima and Chlorella vulgaris consortium. Environ. Res 179:108848. doi.org/10.1016/j.envres.2019.108848.
Martini F., Beghini G., Zanin L., Varanini Z., Zamboni A., Ballottari M.. 2021;The potential use of Chlamydomonas reinhardtii and Chlorella sorokiniana as biostimulants on maize plants. Algal Res 60:102515. doi.org/10.1016/j.algal.2021.102515.
Mata T. M., Martins A. A., Caetano N. S.. 2010;Microalgae for biodiesel production and other applications: a review. Renew. Sust. Energ. Rev 14:217–232. doi.org/10.1016/j.rser.2009.07.020.
Molnár P., Deli J., et al. 2006;Preparation and spectroscopic characterization of 3′-oxolutein. Lett. Org. Chem 3:723–734. doi.org/10.2174/157017806779025933.
Montes D’Oca M. G., Viêgas C. V., Lemões J. S., et al. 2011;Production of FAMEs from several microalgal lipidic extracts and direct transesterification of the Chlorella pyrenoidosa. Biomass Bioenerg 35:1533–1538. doi.org/10.1016/j.biombioe.2010.12.047.
Montoya-Arroyo A., Lehnert K., Muñoz-González A., Schmid-Staiger U., Velter W., Frank J.. 2022;Tocochromanol profiles in Chlorella sorokiniana, Nannochloropsis limnetica, and Tetraselmis suecica confirm the presence of 11′-α-tocomonoenol in cultured microalgae independently of species and origin. Foods 11:396. doi.org/10.3390/foods11030396.
Moser S., Erhart T., Neuhauser S., Kräutler B.. 2020;Phyllobilins from senescence-associated chlorophyll breakdown in the leaves of Basil (Ocimum basilicum) show increased abundance upon herbivore attack. J. Agric. Food Chem 68:7132–7142. doi.org/10.1021/acs.jafc.0c02238.
Musharraf S. G., Ahmed M. A., Zehra N., Kabir N., Choudhary M. I., Rahman A.-U.. 2012;Biodiesel production from microalgal isolates of southern Pakistan and quantification of FAMEs by GC-MS/MS analysis. Chem. Cent. J 6:149. doi.org/10.1186/1752-153X-6-149.
Nilsson T., Martínez E., Manresa A., Oliw E. H.. 2010;Liquid chromatography/tandem mass spectrometric analysis of 7,10-dihydroxyoctadecenoic acid, its isotopomers, and other 7,10-dihydroxy fatty acids formed by Pseudomonas aeruginosa 42A2. Rapid Commun. Mass Spectrom 24:777–783. doi.org/10.1002/rcm.4446.
Pantami H. A., Bustamam M. S. A., Lee S. Y., et al. 2020;Comprehensive GC-MS and LC-MS/MS metabolite profiling of Chlorella vulgaris. Mar. Drugs 18:367. doi.org/10.3390/md18070367.
Rahman M. J., Ambigaipalan P., Shahidi F.. 2018;Biological activities of Camelina and Sophia seeds phenolics: inhibition of LDL oxidation, DNA damage, and pancreatic lipase and α-glucosidase activities. J. Food Sci 83:237–245. doi.org/10.1111/1750-3841.14007.
Rivera S. M., Christou P., Canela-Garayoa R.. 2014;Identification of carotenoids using mass spectrometry. Mass Spectrom. Rev 33:353–372. doi.org/10.1002/mas.21390.
Safarfar H., van Wagenen J., Møller P., Jacobsen C.. 2015;Carotenoids, phenolic compounds and tocopherols contribute to the antioxidative properties of some microalgae species grown on industrial wastewater. Mar. Drugs 13:7339–7356. doi.org/10.3390/md13127069.
Safi C., Zebib B., Merah O., Pontalier P.-Y., Vaca-Garcia C.. 2014;Morphology, composition, production, processing and applications of Chlorella vulgaris: a review. Renew. Sustain. Energy Rev 35:265–278. doi.org/10.1016/j.rser.2014.04.007.
Seal T., Chaudhuri K., Pillai B., Chakrabarti S., Mondal T., Auddy B.. 2020;Evaluation of antioxidant activities, toxicity studies and the DNA damage protective effect of various solvent extracts of Litsea cubeba fruits. Heliyon 6:e03637. doi.org/10.1016/j.heliyon.2020.e03637.
Shimma S., Kubo A., Satoh T., Toyoda M.. 2012;Detailed structural analysis of lipids directly on tissue specimens using a MALDI-spiralTOF-reflectron TOF mass spectrometer. PLoS ONE 7:e37107. doi.org/10.1371/journal.pone.0037107.
Sotoudehniakarani F., Alayat A., McDonald A. G.. 2019;Characterization and comparison of pyrolysis products from fast pyrolysis of commercial Chlorella vulgaris and cultivated microalgae. J. Anal. Appl. Pyrolysis 139:258–273. doi.org/10.1016/j.jaap.2019.02.014.
Stigter E. C. A., Letsiou S., vd Broek N. J. F., et al. 2013;Development and validation of a quantitative LC-tandem MS assay for hexadeca-4,7,10,13-tetraenoic acid in human and mouse plasma. J. Chromatogr. B 925:16–19. doi.org/10.1016/j.jchromb.2013.01.012.
Vello V., Umashankar S., Phang S.-M., et al. 2018;Metabolomic profiles of tropical Chlorella and Parachlorella species in response to physiological changes during exponential and stationary growth phase. Algal Res 35:61–75. doi.org/10.1016/j.algal.2018.08.014.
Viera I., Roca M., Pérez-Gálvez A.. 2018;Mass spectrometry of non-allomerized chlorophylls a and b derivatives from plants. Curr. Org. Chem 22:842–876. doi.org/10.2174/1385272821666170920164836.
West H., Reid G. E.. 2021;Hybrid 213 nm photodissociation of cationized sterol lipid ions yield [M]+: radical products for improved structural characterization using multistage tandem mass spectrometry. Anal. Clim. Acta 1141:100–109. doi.org/10.1016/j.aca.2020.10.013.
Won H., Ro E., Seo S., Kim B.-H., Jin E. S.. 2023;Isolation and cultivation of freshwater diatom Nitzschia palea HY1 for increasing biomass and fucoxanthin production. Algae 38:191–202. doi.org/10.4490/algae.2023.38.9.3.
Yun H.-S., Kim Y.-S., Yoon H.-S.. 2020;Characterization of Chlorella sorokiniana and Chlorella vulgaris fatty acid components under a wide range of light intensity and growth temperature for their use as biological resources. Heliyon 6:e04447. doi.org/10.1016/j.heliyon.2020.e04447.
Zhou J., Wang M., Bäuerl C., et al. 2023;The impact of liquid-pressurized extracts of Spirulina, Chlorella and Phaedactylum tricornutum on in vitro antioxidant, antiinflammatory and bacterial growth effects and gut microbiota modulation. Food Chem 401:134083. doi.org/10.1016/j.foodchem.2022.134083.
Zhou J., Wang M., Saraiva J. A., et al. 2022;Extraction of lipids from microalgae using classical and innovative approaches. Food Chem 384:132236. doi.org/10.1016/j.foodchem.2022.132236.

Article information Continued

Fig. 1

Comparisons of antioxidant and DNA protectant properties in the methanol extract of Chlorella fusca. (A) DPPH (2,2-diphenyl-1-pycrylhydrazyl) radical scavenging activities. (B) ABTS (2,2′-azino-bis(3-ethylbenzthiazoline-6-sulphonic acid)) radical scavenging activities. (C) DNA protectant activities. Lane 1, pUC18 only; lane 2, pUC18 with dithiothreitol (DTT) only; lane 3, pUC18 with FeCl3 only; lane 4, pUC18 with metal-catalyzed oxidation (MCO) system; lanes 5–9, pUC18 with combinant extracts in the MCO system (lane 5: 5, lane 6: 10, lane 7: 25, lane 8: 50, lane 9: 100, lane 10: 250, lane 11: 500, and lane 12: 1,000 μg mL−1). Nicked form (NF) and super-coiled form (SF) of the plasmid DNA are indicated by arrows.

Fig. 2

Comparisons of tyrosinase and elastase inhibitory capacities in the methanol extracts of Chlorella fusca through reaction times. (A) Tyrosinase inhibitory effects. (B) Elastase inhibitory effects.

Fig. 3

Ultra-high performance liquid chromatography coupled with quadrupole time-of-flight mass spectrometry (UPLC-Q-TOF-MS/MS) base peak intensity chromatograms through different ion modes in the methanol extract of Chlorella fusca. (A) UPLC-Q-TOF-MS chromatogram using negative ion mode. (B) UPLC-Q-TOF/MS chromatogram using positive ion mode.

Fig. 4

Chemical structures of the identified metabolite compositions from the methanol extract of Chlorella fusca. (A) Metabolite structures through negative ion mode of ultra-high performance liquid chromatography coupled with quadrupole time-of-flight mass spectrometry (UPLC-Q-TOF-MS/MS). (B) Metabolite structures through positive ion mode of UPLC-Q-TOF-MS.

Table 1

Identification of metabolite profiles in the methanol extract of Chlorella fusca by the negative and positive ion modes of UPLC-Q-TOF-MS/MS

Peak tR (min) Formula Calculated mass [M] (m/z) Calculated mass [M-H] (m/z) Observed molecular ion in MS [M-H] (m/z) Observed fragment ions in MS2 (m/z) Error (MS) Error (MS2) Identification
Negative ion mode
1 6.3 C18H30O3 294.2195 293.2117 293.2134 293.2098 / 195.1378 1.6 - 4-Nonyl-(1-methyl, 6,8-metoxy)-hydroxybenzene
2 7.7 C20H40O 296.3079 295.3001 295.2283 295.2254 / 167.1076 / 141.1279 - - Phytol
3 9.1 C20H40O 296.3079 295.3001 295.2293 295.2255 / 195.1377 1.5 4.2 11-Eicosenol
4 11.9 C20H42O 298.3236 297.3157 297.2439 297.2407 / 185.1163 - - 1-Eicosanol
5 12.1 C16H24O2 248.1776 247.1698 247.1708 247.1690 / 203.1793 / 175.1480 / 149.1328 2.8 1.7 Hexadeca-4,7,10,13-tetraenoic acid
6 14.2 C16H26O2 250.1933 249.1855 249.1863 249.1837 / 205.1950 / 177.1644 0.8 1.3 Roughanic acid
7 14.7 C34H40N4O8 632.2846 631.2768 631.2390 613.2270 / 553.2063 1.7 3.8 Chlorophyll catabolites (phyllobilin)
8 15.5 C18H36O3 300.2664 299.2586 299.2596 299.2567 / 185.1168 / 139.1123 1.3 2.4 10-Hydroxyoctadecanoic acid
9 16.8 C18H28O2 276.2089 275.2011 275.2024 275.1994 / 231.2095 0 0.5 Stearidonic acid
10 17.6 C16H28O2 252.2089 251.2011 251.2018 251.1991 / 233.1894 / 106.0425 1.3 3.2 7,10-Hexadecadienoic acid
11 19.3 C18H30O2 278.2246 277.2168 277.2174 277.2150 / 233.2265 / 219.1392 0.1 1.8 Linolenic acid
12 21.1 C16H30O2 254.2246 253.2168 253.2177 253.2143 0.3 3.4 7-Hexadecenoic acid
13 22.4 C35H38N4O7 626.2740 625.2662 625.2603 625.2582 / 581.2700 / 521.2497 1.8 0 10,22-Dihydro-4,5-dioxo-4,5-secopheophorbide a
14 22.6 C18H32O2 280.2402 279.2324 279.2327 279.2307 / 261.2211 1.2 2.4 Linoleic acid
15 23.3 C16H30O2 254.2246 253.2168 253.2184 253.2212 0.7 4.8 Palmitoleic acid
16 23.6 C17H32O2 268.2402 267.2324 267.2338 267.2300 4.4 0 Heptadecenoic acid
17 25.4 C16H32O2 256.2402 255.2324 255.2327 255.2299 0.9 2.7 Palmitic acid
18 26.7 C18H34O2 282.2559 281.2481 281.2483 281.2455 1.1 3.8 Vaccenic acid
19 27.6 C18H34O2 282.2559 281.2481 281.2493 281.2455 2.5 0 Oleic acid
20 28.6 C17H34O2 270.2559 269.2481 269.2497 269.2456 4.0 4.9 Heptadecanoic acid
21 29.7 C19H36O2 296.2715 295.2637 295.2649 295.2612 2.3 0 10-Nonadecenoic acid
22 30.5 C19H36O2 296.2715 295.2637 295.2649 295.2612 2.1 2.7 7-Nonadecenoic acid
23 31.8 C18H36O2 284.2715 283.2637 283.2647 283.2607 1.4 0 Stearic acid
24 32.4 C20H38O2 310.2872 309.2794 309.2803 309.2772 1.2 0 Gadoleic acid
25 36.3 C20H40O2 312.3028 311.2950 311.2960 311.2930 1.4 0 Arachidic acid
26 41.1 C22H44O2 340.3341 339.3263 339.3269 339.3243 0.2 3.7 Behenic acid
Positive ion mode
1 6.3 C17H24O3 276.1725 277.1803 277.2153 189.1259 / 159.1178 / 147.1176 / 107.0856 2.2 2.6 7,9-Di-tert-butyl-1-oxaspiro[4.5]deca-6,9-diene-2,8-dione
2 9.1 C18H30O2 278.2245 279.2324 279.2307 149.0247 / 121.1024 / 109.1018 / 107.0863 1.6 0 α-Eleostearic acid
3 11.0 C18H30O3 294.2194 295.2273 295.2257 163.1139 / 131.0868 / 121.1021 2.8 1.7 4-Nonyl-(1-methyl, 6,8-metoxy)-hydroxybenzene
4 11.9 C20H40O 296.3079 297.3157 297.2439 297.2407 / 279.2312 / 185.1163 - - Phytol
5 14.2 C16H24O2 248.1776 249.2218 249.1863 249.1837 / 231.1748 / 177.1644 / 175.1494 1.2 2.7 Hexadeca-4,7,10,13-tetraenoic acid
6 15.5 C40H56O4 600.4178 601.4256 601.5371 283.2610 / 247.2399 2.5 1.7 Neoxanthin
7 15.6 C20H42O 298.3235 299.3313 299.2596 299.2567 / 281.2467 / 253.2522 / 141.1277 1.3 3.2 1-Eicosanol
8 19.3 C18H28O2 276.2089 277.2167 277.2174 277.2150 / 259.2058 0.3 1.2 Stearidonic acid
9 19.6 C33H32N4O4 548.2423 549.2501 549.2484 549.2471 / 521.2545 0.3 4.5 Pyropheophorbide b
10 21.3 C40H54O2 566.4123 567.4202 567.4166 567.4198 / 211.1488 / 145.1019 / 119.0862 1.2 2.4 3′-Oxolutein
11 21.6 C35H28MgN4O5 608.1910 609.1988 609.2676 609.2638 / 591.2548 0.7 4.8 Chlorophyll c2
12 22.4 C35H36N4O7 624.2584 625.2662 625.2603 625.2582 / 565.2384 / 521.2497 4.2 1.1 151-OH-Lactone-pheo a
13 22.6 C18H30O2 278.2245 279.2324 279.2327 279.2307 / 261.2211 0.1 2.4 Linolenic acid
14 23.1 C35H34N4O6 606.2478 607.2556 607.2563 607.2538 / 575.2272 / 531.2371 / 487.2470 1.1 0.5 Pheophorbide b
15 23.3 C35H36N4O6 608.2634 609.2713 609.2665 609.2622 / 591.2527 1.1 0.6 132-OH-Pheo a
16 24.6 C35H36N4O5 592.2685 593.2764 593.2723 593.2687 / 533.2506 0.9 2.7 Pheide a
17 25.4 C16H30O2 254.2245 255.2324 255.2327 255.2299 / 237.2217 0 1.5 7-Hexadecenoic acid
18 26.0 C35H36N4O5 592.2685 593.2764 593.2720 593.2691 / 533.2500 1.1 3.8 Pheophorbide a
19 26.5 C33H34N4O3 534.2630 535.2709 535.2668 535.2628 / 507.2716 0.8 2.2 Pyro-pheophorbide a
20 26.7 C18H32O2 280.2402 281.2480 281.2483 281.2455 / 263.2370 0.2 2.2 Linoleic acid
21 28.1 C35H34N4O8 638.2376 639.2454 639.2766 639.2724 / 621.2643 / 579.2553 / 552.2671 4.0 4.9 151-OH-Lactone-pheo b
22 28.6 C18H36O 268.2766 269.2844 269.2497 269.2456 / 251.2368 1.0 1.5 9-Octadecen-1-ol
23 28.7 C35H34N4O7 622.2427 623.2505 623.2815 623.2803 / 605.2693 / 545.2488 / 546.2559 0.4 2.3 132-OH-pheo b
24 28.9 C33H38N4O6 586.2791 587.2869 587.4315 587.4295 / 569.4201 / 228.1369 0.2 4.2 Pyro-NCC 3
25 29.0 C28H42O 394.3235 395.3313 395.3280 395.3300 / 377.3202 / 211.1479 / 157.1019 0.7 2.2 9,11-Dehydroergosterol
26 30.1 C16H30O2 254.2245 255.2324 255.2341 255.2317 4.6 5.0 Palmitoleic acid
27 31.8 C18H34O2 282.2558 283.2637 283.2647 283.2607 / 265.2521 1.4 0 Oleic acid
28 32.4 C40H54O 550.4174 551.4252 551.4199 551.4245 / 211.1487 / 145.1020 / 119.0858 1.5 1.7 Echinenone
29 32.8 C43H60O5 656.4440 657.4519 657.4106 657.4068 / 597.3844 0.6 3.0 All-trans fucoxanthin
30 33.6 C44H83O10P 802.5723 803.5802 803.4916 803.5121 / 277.2159 / 179.0590 0.5 3.3 PG (16:0/22:2)
31 33.8 C42H84NO8P 761.5934 762.6012 762.5092 565.4235 / 335.2551 0.4 1.2 PC (16:0/18:0)
32 34.4 C25H49O12P 572.2961 573.3039 573.4508 573.4489 / 296.2290 / 185.1172 1.9 2.9 PI (16:0/0:0)
33 34.9 C23H44NO7P 477.2855 478.2933 478.3853 460.3771 / 222.1478 / 140.0712 1.8 0 LPE (18:2/0:0)
34 38.9 C25H50NO7P 507.3324 508.3403 508.5064 508.5074 / 146.1181 1.7 0 LPE (20:1/0:0)
35 39.8 C29H48O2 428.3654 429.3732 429.3693 429.3169 / 165.0908 / 149.0963 1.3 2.4 11′-α-tocomonoenol
36 44.7 C33H32MgN4O3 556.2324 557.2403 557.4560 557.4531 / 279.2312 2.1 3.2 Pyrochlorophyllide a

UPLC-Q-TOF-MS/MS, ultra-high performance liquid chromatography coupled with quadrupole time-of-flight mass spectrometry; PG, phosphatidylglycerol; PC, phosphatidylglycerol; PI, phosphatidylinositol; LPE, lysophophatidylethanolamine.