Introduction

Microalgae encompass a varied array of self-sustaining organisms that hold considerable importance within the aquatic food web. They have been used as larval diet in shellfish and finfish hatcheries across the world due to their size (suitable for small-sized larvae), high nutritional composition, high multiplication rate, antioxidant properties and disease resistance. Microalgae synthesize a variety of compounds, mainly biomolecules, which have nutraceutical properties. Nutraceuticals refer to food or food products that provide health and medical benefits, including the prevention and treatment of diseases. These products often contain bioactive compounds such as vitamins, minerals, antioxidants, and other dietary supplements that have potential health benefits beyond basic nutritional value. The bioactive molecules in microalgae have the potential for upscaling at industrial scale. It includes astaxanthin, chlorophyll, phycobiliprotein, beta carotene, lutein and polyunsaturated fatty acids, and they offer significant health and developmental benefits for both humans and animals (Paniagua-Michel 2015). Microalgae, generally inhabit highly competitive and dynamically changing ecosystems. As a result, they synthesize an extensive array of compounds from diverse metabolic pathways. Most of these compounds have been demonstrated to possess various beneficial characteristics, such as antibacterial, antifungal, antiviral, enzyme-inhibiting, immunostimulant, cytotoxic, and anti-plasmodial properties (Ghasemi et al. 2004; Sandeep et al. 2022). For instance, the extracts from Chlorella vulgaris and Chlamydomonas pyrenoidosa exhibit in-vitro antibacterial activities against selected bacteria. Furthermore, in-vitro antibacterial activity has been observed in extracts from green algae, diatoms, and dinoflagellates (Borowitzka and Borowitzka 1988; Sandeep et al. 2023). The ability of Thalassiosira sp to control pathogenic Vibrio sp in shrimp hatcheries has been widely recognized (Sandeep et al. 2021). Quin et al (2013) and Sandeep et al (2021) have demonstrated the capability of this species to inhibit specific pathogenic bacteria. Further, marine microalgae are acknowledged as a valuable, bioactive lipids, particularly those rich in polyunsaturated fatty acids (PUFA), which are effective in preventing and treating various diseases. Notably, n-3 PUFA, such as α-linolenic acid (ALA, C18:3n-3), eicosapentaenoic acid (EPA, C20:5n-3), docosapentaenoic acid (DPA, C22:5n-3), and docosahexaenoic acid (DHA, C22:6n-3), have demonstrated their efficacy in disease prevention and treatment (Abdel-Baky et al. 2002).

Cyanobacteria, one of the most ancient life forms, offer great potential as a class of organisms from which novel bioactive natural compounds can be derived. For example, Spirulina, a well-known nutritional supplement due to its high protein content, contains a primary pigment called phycocyanin (PC). In particular, C-Phycocyanin (Phycocyanin from cyanobacteria, CPC), a water-soluble pigment, is a significant component of spirulina (Boussiba and Richmond 1980). In a recent study, Sandeep et al (2022) demonstrated the positive effects of dietary phycocyanin on the health and growth of Penaeus vannamei, and this finding is particularly relevant in regions where bacterial infections in the shrimps are more prevalent.

The diversity of microalgae in estuarine and coastal marine ecosystems is vast. Applications of microalgae have been extensively studied in different fields (Muller-Feuga 2000; Spolaore et al. 2006; Gupta and Bux 2019; Sandeep et al. 2022). To tap this extensive biosynthetic diversity, researchers have isolated microalgae, and there are several institutions and repositories across the world (Duong et al. 2012). Although almost 50,000 species have been identified and preserved in these collections (Richmond and Qiang 2013), they represent only a fraction of the vast biodiversity of microalgae. To date, only a few microalgal species have been thoroughly studied for their nutraceutical properties and potential applications in aquaculture (Sandeep et al. 2019). To ensure ecological sustainability, it is recommended to utilize native strains for production, as these are better suited to the climatic and environmental conditions of their local habitat. The most suitable local strains for large-scale production are typically those isolated from their natural environments and collected across various seasons, as they are expected to be optimally adapted to specific local conditions. Therefore, a rigorous process of screening and selection is essential to identify the most suitable local strains for efficient microalgae biomass production (Lee et al. 2014). It has been widely acknowledged that native strains exhibit better adaptability to the environmental conditions of their isolation area, particularly when compared to other commercially used species (Abdelaziz et al. 2014; Sandeep et al. 2019).

In this study, the primary objective was to investigate the isolation of promising microalgae species from an estuarine ecosystem. The subsequent steps involve characterizing these isolated microalgae and comprehensively understanding their nutraceutical properties. The significance of this research lies in the scarcity of studies specifically focused on isolating microalgae to evaluate their nutraceutical properties and potential application in marine and brackishwater aquaculture. By doing so, it seeks to contribute foundational information that can be pivotal for the future utilization of various microalgae species to enhance aquaculture production. This research not only addresses the knowledge gap in the isolation and assessment of microalgae with nutraceutical potential but also lays the groundwork for potential advancements in the field of aquaculture through the incorporation of diverse microalgae species.

Materials and methods

Location of the study

Microalgae species isolated in the present study were from the Muttukadu estuarine system in the Chengalpattu District of Tamil Nadu, a Southern state of India (Latitude: 12°48′30.1"N Longitude: 80°14′44.5"E). The Muttukadu estuarine ecosystem is the place where the freshwater Buckingham Canal meets the Bay of Bengal (Fig. 1).

Fig. 1
figure 1

Sampling points at Muttukadu estuary, Tamil Nadu, India

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Water quality parameters

Water samples from the different sampling stations were collected for isolation study between 6:30 AM and 8:30 AM. The collected samples were then analyzed following standard laboratory procedures (APHA 2005) to measure various parameters including water temperature (°C), pH, salinity (ppt), dissolved oxygen (mg/L), total ammonia (mg/L), total alkalinity (mg/L), bicarbonate (mg/L) and total Hardness (mg/L).

Isolation and identification

In this study, three methods were employed to isolate various microalgae species, as illustrated in Fig. 2 (Serial dilution, Agar plate streaking, and Micromanipulation). The water samples from the estuarine ecosystem were filtered through a phytoplankton net (10 micron) and the filtered samples underwent serial dilution using specific media such as f/2 media, Walne’s media, and modified Nallayan Research Centre (NRC) media (NaHCO3: 8 g/l; NaCl: 5 g/l; NaNO3: 2.5 g/l; K2SO4: 0.5 g/l; K2HPO4: 0.5 g/l; MgSO47H2O: 0.16 g/l; FeSO47H2O: 0.01 g/l), with various dilutions. The samples were taken at 07:00–08:00 h to ensure the presence of microalgae. After 2–3 weeks, agar streak plating was conducted. The serially diluted test tubes and agar plates were kept in an indoor microalgae laboratory for 1–3 weeks. Periodic microscopic examinations revealed the presence of specific microalgae species. Agar plates were stored in the indoor laboratory at a constant temperature of 24 ± 1 ˚C and illumination of 3,500 ± 100 lx using cool white fluorescent lamps (Philips, 23 W). Light intensity was measured with a lux meter (LX-103, Taiwan), and the photoperiod was fixed at 12:12 h of light and dark periods. If microalgae growth was observed in the dilutions and plates, the cultures were utilized for streaking or re-streaking in agar plates. These plates were again kept in laboratory conditions for 1–2 weeks and observed for colonies. Single colonies were picked using a sterile inoculation loop and re-streaked on freshly prepared agar plates, undergoing 3–4 re-streaking cycles to achieve unialgal growth. For larger species like Arthrospira sp., micromanipulation was employed. A micropipette/pasture pipette was used to separate a single colony, which was then transferred to test tubes with culture media for further multiplication. Microalgae species were identified based on morphological characteristics using taxonomic keys found in standard literatures (Desikachary 1959, 1989; Krishnamurthy 2000). Scanning Electron Microscopy was utilized to examine cellular details of microalgae cells, specifically in the case of Arthrospira maxima, following the method outlined by Kumar et al. (2022) (JSM IT 300LV, JEOL Ltd., Japan).

Fig. 2
figure 2

Schematic representation of isolation of microalgae and utilization of their nutraceutical properties in aquaculture

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Pure culture and biomass production

The uncontaminated isolates were cultivated in an indoor microalgae laboratory at a temperature of 24 ± 1 ˚C under 3000–4000 lx illumination. Microalgae culture was conducted using filtered and sterilized seawater. Light intensity was measured using a lux meter (LX-103, Taiwan), and the photoperiod was maintained at 12:12 h Light: Dark. The growth cycles of the isolated species in specific culture media were investigated by daily estimation of cell numbers per ml. Microalgae cell counting was performed using the haemocytometer method (LeGresley and McDermott 2010), with microalgae density expressed as the number of cells ml−1. Sub-culturing of pure cultures occurred at intervals of 7–10 days. Contamination checks were conducted periodically under a microscope. Stock cultures of species (100 ml conical flasks) were without aeration, while aeration was introduced in larger conical flasks (500 ml and above) with filters in the aeration line to prevent contamination.

Nutrient composition

During the logarithmic phase of the growth microalgae was harvested and subjected to freeze-drying. The microalgae's proximate compositions (g/100 g) were determined following the standard procedures outlined by AOAC (2005). The micro-Kjeldahl method (Kjelteck, FOSS tecator, India) was utilized for the estimation of crude protein (CP, expressed in g/100 g), while the assessment of lipid content was conducted through solvent extraction using Soxhlet’s apparatus (SOCS Plus, Pelican, India). To determine the total ash (TA, expressed in g/100 g) content, the microalgae biomasses underwent incineration at 550 °C for 5 h in a muffle furnace. The determination of crude fiber (CF, expressed in g/100 g) content involved acid digestion followed by alkaline fluxing, and the digested sample was subsequently incinerated in a muffle furnace at 550 °C for 5 h. The nitrogen-free extract (NFE, expressed in g/100 g) of the microalgae biomass was calculated using the subtraction method. The following formulas were used for calculating the proximate composition.

$$\boldsymbol M\boldsymbol o\boldsymbol i\boldsymbol s\boldsymbol t\boldsymbol u\boldsymbol r\boldsymbol e\boldsymbol\;\left(\boldsymbol{\mathit\%}\right)\boldsymbol=\frac{\boldsymbol T\boldsymbol h\boldsymbol e\boldsymbol{\mathit\;}\boldsymbol i\boldsymbol n\boldsymbol i\boldsymbol t\boldsymbol i\boldsymbol a\boldsymbol l\boldsymbol{\mathit\;}\boldsymbol w\boldsymbol e\boldsymbol i\boldsymbol g\boldsymbol h\boldsymbol t\boldsymbol{\mathit\;}\boldsymbol o\boldsymbol f\boldsymbol{\mathit\;}\boldsymbol t\boldsymbol h\boldsymbol e\boldsymbol{\mathit\;}\boldsymbol s\boldsymbol a\boldsymbol m\boldsymbol p\boldsymbol l\boldsymbol e\boldsymbol-\boldsymbol T\boldsymbol h\boldsymbol e\boldsymbol{\mathit\;}\boldsymbol d\boldsymbol r\boldsymbol i\boldsymbol e\boldsymbol d\boldsymbol{\mathit\;}\boldsymbol w\boldsymbol e\boldsymbol i\boldsymbol g\boldsymbol h\boldsymbol t\boldsymbol{\mathit\;}\boldsymbol o\boldsymbol f\boldsymbol{\mathit\;}\boldsymbol t\boldsymbol h\boldsymbol e\boldsymbol{\mathit\;}\boldsymbol s\boldsymbol a\boldsymbol m\boldsymbol p\boldsymbol l\boldsymbol e}{\boldsymbol T\boldsymbol h\boldsymbol e\boldsymbol{\mathit\;}\boldsymbol i\boldsymbol n\boldsymbol i\boldsymbol t\boldsymbol i\boldsymbol a\boldsymbol l\boldsymbol{\mathit\;}\boldsymbol w\boldsymbol e\boldsymbol i\boldsymbol g\boldsymbol h\boldsymbol t\boldsymbol{\mathit\;}\boldsymbol o\boldsymbol f\boldsymbol{\mathit\;}\boldsymbol t\boldsymbol h\boldsymbol e\boldsymbol{\mathit\;}\boldsymbol s\boldsymbol a\boldsymbol m\boldsymbol p\boldsymbol l\boldsymbol e}\boldsymbol\times\mathbf{100}$$
$$\boldsymbol C\boldsymbol r\boldsymbol u\boldsymbol d\boldsymbol e\boldsymbol{\mathit\;}\boldsymbol P\boldsymbol r\boldsymbol o\boldsymbol t\boldsymbol e\boldsymbol i\boldsymbol n\boldsymbol{\mathit\;}\left(\boldsymbol{\%}\right)\boldsymbol{=}\frac{\left\{\left(\boldsymbol S\boldsymbol a\boldsymbol m\boldsymbol p\boldsymbol l\boldsymbol e\boldsymbol{\;}\boldsymbol t\boldsymbol i\boldsymbol t\boldsymbol r\boldsymbol e\boldsymbol{-}\boldsymbol B\boldsymbol l\boldsymbol a\boldsymbol n\boldsymbol k\boldsymbol{\mathit\;}\boldsymbol t\boldsymbol i\boldsymbol t\boldsymbol r\boldsymbol e\right)\boldsymbol{\times}\boldsymbol0\boldsymbol{.}\boldsymbol1\boldsymbol{\times}\boldsymbol0\boldsymbol{.}\boldsymbol{014}\boldsymbol{\times}\boldsymbol6\boldsymbol{.}\boldsymbol{25}\right\}}{\boldsymbol W\boldsymbol e\boldsymbol i\boldsymbol g\boldsymbol h\boldsymbol t\boldsymbol{\;}\boldsymbol o\boldsymbol f\boldsymbol{\;}\boldsymbol t\boldsymbol h\boldsymbol e\boldsymbol{\;}\boldsymbol s\boldsymbol a\boldsymbol m\boldsymbol p\boldsymbol l\boldsymbol e\boldsymbol\;\boldsymbol{(}\boldsymbol g\boldsymbol{)}}\boldsymbol{\times}\boldsymbol{100}$$

(0.1: Normality of acid; 0.014: Molecular mass of N; 6.25: Constant relationship between N and the protein of the sample).

$$\boldsymbol E\boldsymbol E\boldsymbol\;\left(\boldsymbol{\mathit\%}\right)\boldsymbol=\frac{\boldsymbol T\boldsymbol h\boldsymbol e\boldsymbol{\mathit\;}\boldsymbol i\boldsymbol n\boldsymbol i\boldsymbol t\boldsymbol i\boldsymbol a\boldsymbol l\boldsymbol{\mathit\;}\boldsymbol w\boldsymbol e\boldsymbol i\boldsymbol g\boldsymbol h\boldsymbol t\boldsymbol{\mathit\;}\boldsymbol o\boldsymbol f\boldsymbol{\mathit\;}\boldsymbol t\boldsymbol h\boldsymbol e\boldsymbol{\mathit\;}\boldsymbol s\boldsymbol a\boldsymbol m\boldsymbol p\boldsymbol l\boldsymbol e\boldsymbol{\mathit-}\boldsymbol F\boldsymbol i\boldsymbol n\boldsymbol a\boldsymbol l\boldsymbol{\mathit\;}\boldsymbol w\boldsymbol e\boldsymbol i\boldsymbol g\boldsymbol h\boldsymbol t\boldsymbol{\mathit\;}\boldsymbol o\boldsymbol f\boldsymbol{\mathit\;}\boldsymbol t\boldsymbol h\boldsymbol e\boldsymbol{\mathit\;}\boldsymbol s\boldsymbol a\boldsymbol m\boldsymbol p\boldsymbol l\boldsymbol e}{\boldsymbol T\boldsymbol h\boldsymbol e\boldsymbol{\mathit\;}\boldsymbol i\boldsymbol n\boldsymbol i\boldsymbol t\boldsymbol i\boldsymbol a\boldsymbol l\boldsymbol{\mathit\;}\boldsymbol w\boldsymbol e\boldsymbol i\boldsymbol g\boldsymbol h\boldsymbol t\boldsymbol{\mathit\;}\boldsymbol o\boldsymbol f\boldsymbol{\mathit\;}\boldsymbol t\boldsymbol h\boldsymbol e\boldsymbol{\mathit\;}\boldsymbol s\boldsymbol a\boldsymbol m\boldsymbol p\boldsymbol l\boldsymbol e}\boldsymbol{\times}\boldsymbol{100}$$

where EE is Ether extract expressed in g/100 g.

$$\boldsymbol A\boldsymbol s\boldsymbol h\boldsymbol\;\left(\boldsymbol{\mathit\%}\right)\boldsymbol=\left(\frac{\boldsymbol W\boldsymbol e\boldsymbol i\boldsymbol g\boldsymbol h\boldsymbol t\boldsymbol{\mathit\;}\boldsymbol o\boldsymbol f\boldsymbol{\mathit\;}\boldsymbol t\boldsymbol h\boldsymbol e\boldsymbol{\mathit\;}\boldsymbol a\boldsymbol s\boldsymbol h}{\boldsymbol W\boldsymbol e\boldsymbol i\boldsymbol g\boldsymbol h\boldsymbol t\boldsymbol{\mathit\;}\boldsymbol o\boldsymbol f\boldsymbol{\mathit\;}\boldsymbol t\boldsymbol h\boldsymbol e\boldsymbol{\mathit\;}\boldsymbol s\boldsymbol a\boldsymbol m\boldsymbol p\boldsymbol l\boldsymbol e}\right)\boldsymbol\times\mathbf{100}$$
$$\boldsymbol N\boldsymbol F\boldsymbol E\boldsymbol{\;}\left(\boldsymbol g\boldsymbol/\boldsymbol{100}\boldsymbol g\right)\boldsymbol{=}\boldsymbol{\{}\boldsymbol{100}\boldsymbol{-}\left(\boldsymbol C\boldsymbol P\boldsymbol+\boldsymbol C\boldsymbol L\boldsymbol+\boldsymbol C\boldsymbol F\boldsymbol+\boldsymbol T\boldsymbol A\right)\boldsymbol{\}}$$

The lipid content was estimated by the Bligh and Dyer method (Bligh and Dyer 1959), and the respective fatty acid methyl esters (FAMEs) were prepared and extracted into petroleum ether. Analysis of methyl esters was performed by a gas chromatograph (GC2014 Shimadzu, Japan) on an RTX wax capillary column (100 m length X 0.25 mm I.D X 0.2 µm film thickness). The quantity of fatty acids (mg kg−1) was calculated according to Aziz et al. (2012).

Total phenolic content, total flavonoid content and antioxidant properties

To assess various characteristics of microalgae species, three crucial properties: total phenolic content, total flavonoid content, and total antioxidant activity were measured.

Total phenolic content (TPC)

The quantification of total phenolic content (TPC) in the sample followed the Folin–Ciocalteau (FC) assay as described by Singleton and Rossi (1985), with minor adjustments according to the protocol outlined by Sivaramakrishnan et al (2017). Gallic acid served as the standard, and the phenolic content was expressed as Gallic Acid Equivalents (mgGAE/g) in the macroalgae extract.

Total flavonoid content (TFC)

The assessment of flavonoid content in the microalgae extract followed the spectrophotometric method outlined by Zishen et al (1999), with minor adaptations detailed by Sivaramakrishnan et al (2017). The flavonoid content was quantified as Rutin equivalents in the extract (mg RE/g).

Total antioxidant activity (TAA)

The evaluation of the overall antioxidant activity in methanolic extracts was conducted using the methodology established by Prieto et al (1999), with slight adjustments following the protocol outlined by Sivaramakrishnan et al (2017). The quantification of total antioxidant activity was expressed in milligrams of ascorbic acid per gram of extract.

Antibacterial properties

Bacterial strains, such as Vibrio harveyi, Vibrio campbellii, and Vibrio parahaemolyticus, were obtained from the Aquatic Animal Health Division's culture collection at ICAR-CIBA in Chennai, India. The turbidity of the bacterial cultures was adjusted to 0.5 McFarland Standards, equivalent to 107 CFU/ml, and verified by spectrophotometric readings at 600 nm. The antibacterial effectiveness of methanolic extracts from microalgae was assessed against the specified bacteria using the agar well diffusion method outlined by Holder and Boyce (1994). Duplicate wells were separately filled with 50 µl of methanol and DMSO-dissolved microalgae extracts. Negative controls (solvent alone) and positive controls (streptomycin) were also prepared in duplicate. The plates containing bacterial inoculums and extracts were then incubated for 24 h at 37 °C, and the resulting zones of inhibition were measured using a Hi Antibiotic Zone Scale from HiMedia Laboratories.

Preparations of microalgae extract

Algal biomass was harvested at the log phase of the culture by centrifugation and the biomass was freeze-dried immediately. Then the freeze-dried samples were ground in a pestle and mortar using methanol as solvent. The extract was centrifuged at 8000 rpm for 5 min and supernatant was collected and filtered through Whatman filter paper in a vial. Then the pellet was re-centrifuged and the supernatant was collected and filtered again. The collected extract was evaporated by a rotary evaporator. The algal crude extract was stored at -20 °C for further analysis (Sivaramakrishnan et al. 2017; Sandeep et al. 2023).

Statistical methods used

R statistical software (version 4.0.4) was utilized for conducting statistical analyses. The data were presented as mean ± SD. One-way analysis of variance (ANOVA) was carried out, followed by Tukey's HSD post hoc tests, to assess the significance (p < 0.05) of differences in the means of various parameters individually. The generation of all plots was accomplished using the 'ggplot2' package (Wickham 2016) within the R statistical software (ver. 4.0.5).

Results

Water quality parameters

Table 1 shows different water quality parameters from 5 different sampling points of the Muttukadu estuarine ecosystem during the study. The parameters except salinity did not show any significant difference among the sampling points.

Table 1 Average water quality parameters from sampling locations during the study
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Isolation and identification of microalgae

Seven species of microalgae were identified and isolated from the Muttukadu estuarine ecosystem in Tamil Nadu, India. These microalgae are now preserved in the microalgae repository located at the Muttukadu Experimental Station of ICAR-CIBA, as depicted in Fig. 3. The species are Thalassiosira sp, Chaetoceros sp, Tetraselmis sp, Isochrysis sp, Nannochloropsis sp, Chlorella sp, and Arthrospira sp (Fig. 4). Tetraselmis sp, Nannochloropsis sp, and Isochrysis sp were isolated by the agar streak plating method, whereas Thalassiosira sp and Chaetoceros sp were isolated by repeated serial dilution method as they did not form colonies in the agar plates. Arthrospira sp was isolated by using the micromanipulation technique. The cell sizes of Arthrospira sp were observed to be 60–100 microns and single cells were taken with the help of a Pasteur pipette under the microscope. Using morphological characteristics, the microalgae species were identified as Thalassiosira weissflogii, Nannochloropsis oculata, Chlorella marina, Chaetoceros gracilis, Tetraselmis sp, Isochrysis galbana, and Arthrospira maxima (Fig. 4).

Fig. 3
figure 3

Pure colonies of microalgae in plates (A) Nannochloropsis oculata, (B) Chlorella marina, (C) Tetraselmis sp, (D) Isochrysis galbana

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Fig. 4
figure 4

Microscopic images of microalgae isolates (A) Thalassiosira weissflogii, (B) Chaetoceros gracilis, (C) Tetraselmis sp, (D) Arthrospira sp, (E) Nannochloropsis oculata, (F) Chlorella marina

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Growth kinetics of the selected microalgae isolates

The growth curve of microalgae showed a significantly higher (P < 0.05) growth rate of Nannochloropsis oculata for about 13 days from the start of the culture as compared to other species followed by Chlorella marina (Fig. 5). Both N. oculata and Chlorella marina showed an extended log phase compared to other species. The growth rate of Isochrysis galbana was followed by N. oculata and C. marina. The growth rates of diatoms Thalassiosira weissflogii and Chaetoceros gracilis were comparable to N. oculata and C. marina up to the 7th day. Starting from the 8th day, cultures of T. weissflogii and C. gracilis entered the stationary phase. Notably, the growth rate of T. weissflogii surpassed that of Tetraselmis and C. gracilis. The growth curves illustrated that Tetraselmis sp is a slow-growing microalgae compared to other species, maintaining an extended log phase until the 13th day, albeit with a slower growth rate (Fig. 5).

Fig. 5
figure 5

Growth curves of selected microalgae in indoor conditions

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The growth curve of Arthrospira maxima showed a long lag phase and log phase in the indoor culture conditions (Fig. 6). The growth was observed in a modified NRC medium.

Fig. 6
figure 6

Growth curve of Arthrospira maxima in indoor culture conditions

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Nutrient composition of microalgae biomass

Proximate composition

A. maxima exhibited the highest protein content at 62.46 ± 3.45%, followed by C. marina (49.48 ± 3.8%), T. weissflogii (43.07 ± 1.78), Tetraselmis sp (42.11 ± 2.55%), N. oculata (38.41 ± 1.85%), I. galbana (34.36 ± 2.86%), and C. gracilis (33.34 ± 2.19%). I. galbana showed significantly higher (P < 0.05) lipid content at 33.08 ± 2.18 compared to others, followed by T. weissflogii (20.11 ± 1.02%), N. oculata (18.35 ± 1.02%), and C. gracilis (14.0 ± 0.97%). The highest nitrogen-free extract (NFE) was observed in C. gracilis (33.35 ± 2.06), followed by Tetraselmis sp (28.43 ± 1.39%), N. oculata and T. weissflogii. No significant difference (P > 0.05) was found in the crude fiber content and total ash content among the various microalgae analyzed (Fig. 7).

Fig. 7
figure 7

Proximate composition of microalgae biomass expresses as % dry matter basis. Data are shown as Mean ± SD (n = 3); Mean values in the same column with different alphabets differ significantly (p < 0.05)

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Fatty acid profiling

The fatty acid composition analysis of selected microalgae (Table 2) revealed A. maxima had the highest percentage (69.51) of polyunsaturated fatty acids (PUFA), primarily linoleic acid, gamma-linolenic acid (GLA), and dihomo-gamma-linolenic acid. Tetraselmis sp ranked second in PUFA content at 56.32%, dominated by linoleic acid and gamma-linolenic acid (GLA). I. galbana exhibited a noteworthy PUFA percentage (45.29), mainly contributed by alpha-linolenic acid and docosahexaenoic acid (DHA). N. oculata and C. marina displayed PUFA percentages of 37.42 and 29.27, respectively, while C. gracilis exhibited the lowest at 15.17. N. oculata presented the highest percentage of eicosapentaenoic acid (EPA) at 25.2, followed by T. weissflogii. T. weissflogii had the highest monounsaturated fatty acids (MUFA) percentage (39.44), followed by C. gracilis (37.52), N. oculata (30.97), and I. galbana (24.38). Tetraselmis sp had the lowest MUFA percentage at 7.59. C. gracilis exhibited the highest saturated fatty acids (SFA) percentage at 42.38, mainly contributed by palmitic and stearic acids. T. weissflogii had an SFA percentage of 34.56, dominated by palmitic and myristic acids, while N. oculata and C. marina had percentages of 31.61 and 18.86, respectively.

Table 2 Fatty acid profiles of selected microalgae (As the percentage of total fatty acids)
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Total phenolic content, total flavonoid content and antioxidant properties

Figure 8 presents diverse total phenolic content, total flavonoid conetnt and antioxidant properties of microalgae extracts. Methanolic extracts of C. gracilis (48.85 ± 3.18) and T. weissflogii (45.83 ± 1.17) demonstrated significantly elevated (P < 0.05) total phenolic content (expressed as mg GAE g−1). Following closely were A. maxima (38.72 ± 2.06), Tetraselmis sp (36.18 ± 1.94), and N. oculata (35.12 ± 1.82). Methanolic extract of A. maxima (8.92 ± 0.92) exhibited significantly higher (P < 0.05) total flavonoid content (expressed as mg RE g−1) compared to other microalgae extracts, followed by Tetraselmis and T. weissflogii. Regarding total antioxidant activity (expressed as mg g−1), A. maxima displayed the highest activity (5.82 ± 0.6), succeeded by T. weissflogii (4.9 ± 0.02) and C. gracilis (4.45 ± 0.28).

Fig. 8
figure 8

Total phenolic content, total flavonoid content and total antioxidant activity of microalgae extracts. Data are shown as Mean ± SD (n = 3); Mean values with different alphabets differ significantly (p < 0.05)

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Antimicrobial properties

Table 3 outline the antibacterial properties of various microalgae extracts. CPC demonstrated the most substantial zones of inhibition against V. harveyi (20.52 ± 0.35 mm), V. campbellii (18.32 ± 0.52 mm), and V. parahaemolyticus (19.48 ± 0.84), significantly surpassing (P < 0.05) other microalgae extracts. Methanolic extract of T. weissflogii displayed significant inhibitory zones against V. harveyi (15.66 ± 0.18 mm), V. campbellii (14.47 ± 0.78 mm), and V. parahaemolyticus (14.59 ± 0.29 mm), though notably lower (P < 0.05) than CPC. Methanolic extract of Tetraselmis sp exhibited zones of inhibition (13.58 ± 0.26 mm against V. harveyi, 12.40 ± 0.67 mm against V. campbellii, and 12.94 ± 0.73 mm against V. parahaemolyticus) surpassing values for C. gracilis, I. galbana, C. marina, and A. maxima (Table 3). N. oculate showed the lowest inhibition zones against V. harveyi (8.60 ± 0.64 mm), C. marina against V. campbellii (10.50 ± 0.63 mm), and I. galbana against V. parahaemolyticus (12.50 ± 0.56 mm). These findings underscore CPC's significantly superior antibacterial efficacy against the three examined pathogenic bacteria compared to other microalgal extracts.

Table 3 Zones of inhibition of microalgae extracts against pathogenic bacteria
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Discussion

Microalgae, minute photosynthetic organisms, offer a plethora of advantages across diverse industries, including aquaculture (Muller-Feuga 2000; Spolaore et al. 2006; Gupta and Bux 2019; Sandeep et al. 2021). Within the ecosystem, microalgae serve a crucial role as a primary food source for numerous aquatic organisms, contributing significantly to the overall productivity and well-being of aquaculture systems (Hemaiswarya et al. 2011). With an estimated 50,000 or more species of microalgae in existence, only a fraction has been isolated and studied for their chemical composition, with a few hundred receiving attention globally (Duong et al. 2012; Lim et al. 2012). Despite this diversity, the utilization of microalgae species in marine and brackishwater aquaculture remains confined to a limited selection of 10 to 20 species (Muller-Feuga 2000; Sandeep et al. 2019). Microalgae have a rich nutritional profile, containing proteins, lipids, vitamins, and minerals (Hemaiswarya et al. 2011). Different microalgae species may have varying nutritional profiles, and selecting the most suitable ones can enhance the growth, health, and productivity of cultured organisms. Hence the isolation of microalgae strains from various ecosystems has a vital role in aquaculture (Sandeep et al. 2019). Isolating and studying different microalgae species enables the identification of species that have optimal nutritional profiles to meet the dietary requirements of target aquaculture species, thereby promoting balanced and efficient nutrition. Microalgae are often the preferred choice as live feed for larvae due to their small size, high nutritional value, and ability to stimulate natural feeding behaviours in larvae. Isolating and culturing specific microalgae species that are suitable for larval rearing can greatly enhance the survival, growth, and overall success rates of the early life stages of cultured organisms.

Hence the present study was attempted for the isolation of microalgae species from a tropical estuary in southern India. Previous research has focused on the isolation of diverse microalgae from Indian waters, as documented by studies such as those conducted by Dar et al (2019), Sandeep et al (2019), Uma et al (2020) and Raghuraman et al (2021). Several authors have observed that freshly isolated microalgae from a specific region exhibit superior growth performance and biomass production (Duong et al. 2012; Lee et al. 2014; Sandeep et al. 2021). The physicochemical parameters of an ecosystem play a pivotal role in influencing the abundance and growth kinetics of microalgae. Consequently, utilizing local strains of microalgae is advocated for achieving enhanced growth and production. The species isolated in the present study were T. weissflogii, C. gracilis, Tetraselmis sp, I. galbana, N. oculata, C. marina, and A. maxima and earlier studies also reported the presence of similar species in brackishwater ecosystems (Lim et al. 2012; Sandeep et al. 2019; 2022; 2023).

The pure cultures of microalgae are commercially very important for various applications and few culture collections are there in different countries, where the stock cultures are maintained (Duong et al. 2012; Lim et al. 2012). In India, dedicated culture collections of microalgae used in aquaculture are very few (Sandhya et al. 2017; Uma et al. 2020). The present study generated various potential microalgae isolates and they are kept in the microalgal culture repository in pure form for further application.

The growth of the microalgae culture is one of the crucial factors in aquaculture (Brown et al. 1997). The growth rate and ease of culture are significant criteria to be looked upon as a main factor in hatcheries or commercial production units, and all other qualities like nutritional composition are secondary factors for the selection of microalgae. In the present study, the growth of N. oculata, I. galbana, C. marina, T. weissflogii, C. gracilis, Tetraselmis sp, and A. maxima were studied in the indoor culture system (Fig. 5). Earlier studies showed the high growth rates of Chlorella sp and Nannochloropsis sp (Upadhyay et al. 2016). Similarly, the growth rates of N. oculata and C. marina were significantly higher than other microalgae. Among diatoms, T. weissflogii showed a better growth rate (Fig. 5). A similar growth curve of Thalassiosira sp was reported by earlier researchers (Thompson and Harrison 1992; Zhukova 2004). The Tetraselmis sp showed an extended growth curve and slower growth rate than other species. Similar growth kinetics of Tetraselmis sp were reported earlier (D’Souza and Kelly 2000). However, Tetraselmis sp is known for its tolerance toward temperatures and salinities (Raes et al. 2014). To get quality microalgae biomass, it is essential to understand the growth curve of microalgae. The best nutritional composition will be in the log phase, and the nutritional quality reduces considerably when the microalgae reach the stationary phase (Brown et al. 1997). Hence, the harvest time can be determined by understanding the growth curve to get a quality microalgae biomass. The growth curve of A. maxima isolated from the Muttukadu estuary was also estimated (Fig. 6). A similar growth curve was reported earlier in Arthrospira sp (Zhukova 2004; Sandeep et al. 2013; 2019).

Microalgae are rich sources of essential nutrients required for the growth and development of aquatic organisms. They contain high levels of proteins, amino acids, lipids, vitamins, minerals, and pigments that are essential for the health and overall nutritional balance of the organisms being cultured (Spolaore et al. 2006). Proper nutrition is critical for the growth, survival, and overall performance of farmed aquatic organisms. Microalgae provide a natural and highly nutritious food source that can enhance growth rates, improve feed conversion efficiency, and enhance disease resistance in fish, shrimp, and other aquaculture species. The present study evaluated the nutrient profiles of selected microalgae from brackishwater for possible use in brackishwater aquaculture.

Arthrospira sp (spirulina) is a cyanobacterium used as human food for centuries and has been rediscovered recently. Earlier studies revealed the high protein content of spirulina biomass (Hoseini et al. 2013) as 60–70%. The present study revealed the highest percentage of protein in A. maxima (62.46 ± 3.45), followed by C. marina (49.48 ± 3.8). The protein content of Arthrospira sp reported by earlier workers was in a similar range (Sandeep et al. 2013; 2015); however, the protein content in the present study is lower than that reported by Seghiri et al (2019). Earlier researchers (Rani et al. 2018) reported a comparable protein content range of 47–55% in Chlorella sp. In the current study, the protein content in T. weissflogii was determined to be 43.07%. Previous studies (Kiatmetha et al. 2010; Sandeep et al. 2019) have highlighted the superior nutritional quality of T. weissflogii. The protein content in Tetraselmis sp (> 42%) aligns with values reported in prior studies (Abiusi et al. 2014; Kim et al. 2016) and exceeds those documented by D’Souza and Kelly (2000). Nannochloropsis oculata exhibited a protein content of 38.41 ± 1.85% in the present study, consistent with findings from earlier researchers (Hulatt et al. 2017). The protein content of C. gracilis in the present study (> 33%), is similar to the values reported by Pacheco-Vega and Sanchez SaaVedra (2009) in C. muelleri but lower than the values reported by Banerjee et al (2011) in C. calcitrans. In the case of I. galbana, the present study reported a protein content of 34.36 ± 2.86%, aligning with the observations made by Tokuşoglu and Üunal (2003).

The highest lipid content was observed in I. galbana, and these values align with earlier reports (Cañavate et al. 2020). T. weissflogii exhibited a lipid content of 20.11%, consistent with previous findings (Sandeep et al. 2019; 2023). The lipid content of N. oculata in the present study was 18.35 ± 1.02%, and this is higher than the earlier report by Converti et al (2009) and lower than those reported by Huang et al (2013). In the case of C. gracilis, the lipid content in the present study was 14%, surpassing the values reported by Banerjee et al (2011) in C. calcitrans but falling below the levels reported by Pacheco-Vega and Sanchez SaaVedra (2009) in C. muelleri.

The analysis of fatty acid composition in the selected microalgae (Table 2) revealed that Arthrospira maxima exhibited the highest proportion (69.51%) of polyunsaturated fatty acids (PUFA) as a percentage of total fatty acids. This value surpasses those reported by previous researchers (Dibeklioglu et al. 2009), with most studies indicating PUFA percentages in the range of 28.20–55.9%. Earlier investigations suggested the elevated PUFA levels in Arthrospira sp were attributed to increased levels of linoleic acid, gamma-linolenic acid (GLA), and Dihomo-gamma-linolenic acid. The PUFA content of Tetraselmis sp (56.32%) in this study is also higher than that of previous reports (Guzmán et al. 2010; Sandeep et al. 2023). In the case of Isochrysis galbana, the present study observed a PUFA content of 45.29% of total fatty acids, which aligns with values reported by Yoshioka et al (2012). However, the PUFA content in C. gracilis (15.17% of total fatty acids) was lower than that of earlier reports (Bhattacharjya et al. 2020). Fatty acid profiling of T. weissflogii in this study revealed a higher eicosapentaenoic acid (EPA) content (17.77% of total fatty acids), consistent with observations in earlier studies on various Thalassiosira sp species (Thompson and Harrison 1992; Zhukova 2004; Sandeep et al. 2019; 2023). In Tetraselmis sp, the EPA content was 8.39% of total fatty acids, exceeding values reported in some earlier studies (D’Souza and Kelly 2000; Abiusi et al. 2014; Sandeep et al. 2023). The EPA content in C. gracilis in this study is lower than that of earlier reports (Banerjee et al. 2011).

Microalgae are recognized for producing bioactive compounds with potential health advantages, encompassing antioxidants, pigments (such as astaxanthin), fatty acids (including omega-3), and polysaccharides. These compounds can positively impact the health and immune systems of aquaculture species, as highlighted in studies by El-Araby et al (2022) and Sandeep et al (2022). Certain microalgae species generate antimicrobial compounds, antioxidants, and immunostimulants that contribute to disease prevention and enhance the overall health and resilience of cultured organisms. Antioxidants, classified as biological macromolecules, play a role in safeguarding living organisms or their biological components against oxidative radicals. Many photosynthetic microorganisms, including microalgae, have recently been identified as highly reproducible strains producing diverse phenolic compounds and antioxidants. Numerous researchers have elucidated the polyphenolic and antioxidant components of microalgae, as discussed by Choochote et al (2014). Understanding the antioxidant properties is crucial for assessing the potential of a microalgae species as a nutraceutical in aquaculture. Key properties such as total phenolic content, total flavonoid content, and total antioxidant activity are vital parameters for screening potential microalgae for application in aquaculture as nutraceuticals. In the current study, methanolic microalgae extracts were utilized to assess these properties, following methodologies outlined in earlier reports (Hemalatha et al. 2013; Widowati et al. 2017).

In the current investigation, the methanolic extracts of Chlorella marina exhibited a total phenolic content of 48.85 ± 3.18 mg GAE g−1, surpassing values reported in prior research by Hemalatha et al (2013). Similarly, the methanolic extract of T. weissflogii in this study recorded a higher total phenolic content compared to earlier findings by Bhattacharjya et al (2020). However, there are reports of microalgae, such as Scenedesmus rubescens, displaying exceptionally high total phenolic content of up to 48.57 ± 3.99 mg GAE g−1 (Morowvat and Ghasemi 2016). The total phenolic content of Tetraselmis sp in the present study was 36.18 ± 1.9 mg GAE g−1, which exceeded values reported earlier by Maadane et al (2015) and Widowati et al (2017). Meanwhile, the total phenolic content of N. oculata in the present study resembles values reported by Maadane et al (2015) in N. gaditana. Numerous studies have indicated that various cyanobacteria and microalgae possess significant free radical scavenging abilities, potentially linked to the presence of phenolic compounds within them, as highlighted in the work of Jerez-Martel et al (2017).

In the current study, the highest reported total flavonoid content was found in the methanolic extract of A. maxima (8.92 ± 0.92 mg RE g−1), surpassing values reported by Seghiri et al (2019) but falling below those reported by Dianursanti et al. (2020). The total flavonoid content of the methanolic extract of Tetraselmis sp in this study was 7.26 ± 0.05 mg RE g−1, which exceeded earlier reported values (Haoujar et al. 2019). Additionally, the total flavonoid content of the methanolic extract of T. weissflogii in this study was 6.56 ± 0.62 mg RE g−1, higher than the values reported by Bhattacharjya et al (2020). It is worth noting that Haoujar et al (2019) reported higher total flavonoid content in the methanolic extract of N. gaditana than observed in the present study.

Microalgae, aside from their nutritional richness, often exhibit antibacterial properties. In this study, the methanolic extract of A. maxima showed the highest zones of inhibition against all three bacteria tested: V. harveyi (20.52 ± 0.35 mm), V. campbellii (18.32 ± 0.52 mm), and V. parahaemolyticus (19.48 ± 0.84 mm). The results suggests that the antibacterial activity is primarily attributed to the compound CPC, and its potential efficacy against specific pathogens warrants further exploration. The methanolic extract of T. weissflogii also demonstrated a zone of inhibition against V. harveyi (15.66 ± 0.18 mm), V. campbellii (14.47 ± 0.78 mm), and V. parahaemolyticus (14.59 ± 0.29 mm). Similarly, the methanolic extract of Tetraselmis sp exhibited inhibition zones of 13.58 ± 0.26 mm against V. harveyi, 12.40 ± 0.67 mm against V. campbellii, and 12.94 ± 0.73 mm against V. parahaemolyticus, indicating significant antibacterial properties against various pathogenic bacteria, in line with findings from prior research (Guzmán et al. 2019; Bhattacharjya et al. 2020 and Widowati et al. 2021).

Conclusion

Exploring the potential isolates of microalgae from our ecosystem is having great importance as the new isolates will provide better nutrition and health to aquaculture species. The applications of microalgae in brackishwater aquaculture as nutraceuticals have immense potential for the improved production and health of shrimp. Future research should utilize nutraceutical compounds extracted from these potential microalgae (Thalassiosira, Tetraselmis, Chaetoceros, and Arthrospira) as feed additives in larval and nursery diets. This should be extensively evaluated for their efficacy and practical utility through multi-location field trials. Moreover, commercial shrimp hatcheries should evolve strategies by using combinations of microalgae as live feed for improved penaeid shrimp larval nutrition resulting in improved survival in hatcheries.