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Article

Biochemical Analyses of Ten Cyanobacterial and Microalgal Strains Isolated from Egyptian Habitats, and Screening for Their Potential against Some Selected Phytopathogenic Fungal Strains

by
Hoda H. Senousy
1,*,
Mostafa M. El-Sheekh
2,*,
Abdullah A. Saber
3,
Hanan M. Khairy
4,
Hanan A. Said
5,
Wardah. A. Alhoqail
6 and
Abdelghafar M. Abu-Elsaoud
7
1
Botany and Microbiology Department, Faculty of Science, Cairo University, Giza 12613, Egypt
2
Botany Department, Faculty of Science, Tanta University, Tanta 31527, Egypt
3
Botany Department, Faculty of Science, Ain Shams University, Abbassia, Cairo 11566, Egypt
4
National Institute of Oceanography and Fisheries (NIOF), Cairo 11516, Egypt
5
Botany Department, Faculty of Science, Fayoum University, Fayoum 63514, Egypt
6
Department of Biology, College of Education, Majmaah University, Al Majma’ah 15365, Saudi Arabia
7
Department of Botany and Microbiology, Faculty of Science, Suez Canal University, Ismailia 41522, Egypt
*
Authors to whom correspondence should be addressed.
Agronomy 2022, 12(6), 1340; https://doi.org/10.3390/agronomy12061340
Submission received: 16 April 2022 / Revised: 24 May 2022 / Accepted: 28 May 2022 / Published: 31 May 2022
Browse Figures
Versions Notes

Abstract

:
Microalgae and cyanobacteria are rich sources of numerous phytochemical compounds with intrinsic antifungal potential. This research aimed to screen the phytochemical compounds and contents, as well as the antioxidant profiles, in eight cyanobacterial and two microalgal strains isolated from soil and brackish water habitats in Egypt. Our study also evaluated their antifungal activities against three phytopathogenic fungi—namely, Pythium ultimum, Fusarium solani, and Botryodiplodia theobromae, which are known to cause severe plant loss. The biochemical compounds were obtained from the cyanobacterial and algal methanolic extracts, and were identified through comparative phytochemical analyses related to the inhibition of the fungal pathogens. Comparative qualitative analyses of alkaloids, steroids, glycosides, and saponins were also carried out. The quantitative phytochemical screening of the cyanobacterial and algal strains investigated revealed the presence of xylanase, glucanase, and chitinase enzymes, along with some bioactive compounds, such as phenolics, flavonoids, proteins, neutral sugars, and carotenoids, which were species-dependent and detected in variable amounts in the extracts. The unicellular green microalgal strain Dunaliella sp. HSSASE13 displayed the highest level of antioxidant activity. However, the highest antifungal activities were shown by the heterocystous cyanobacterial strain Anabaena sp. HSSASE11 (83.94%), followed by Dunaliella sp. HSSASE13 (81.94%) and the non-heterocystous cyanobacterial strain Oscillatoria nigro-viridis HSSASE 15 (63.42%), against the three fungal pathogens B. theobromae, F. solani, and P. ultimum, respectively. Our results indicate that the highest significant and positive correlations of flavonoids (r = 0.854), phenolics (r = 0.785), DPPH scavenging activity (r = 0.876), total proteins (r = 0.808), xylanase activity (r = 0.876), glucanase activity (r = 0.746), and total neutral sugars (r = 0.764), in terms of their antifungal activities, were recorded against F. solani. Conclusively, the cyanobacterial and algal strains tested in the present study can be useful agents for the management and biocontrol of plant-infecting fungal pathogens.

1. Introduction

Synthetic fungicides for plant pathogenic fungi have been used for several years. However, the overuse of synthetic fungicides pollutes the environment and increases the risk of harmful substances in nature [1]. In recent years, the bioactive compounds formed by cyanobacteria and green algae have revealed antifungal activity against plant pathogenic fungi [2,3]. Therefore, the potential use of secondary antimicrobial metabolites from algae for disease control in agriculture has become increasingly attractive [4]. Because of their colossal biodiversity, occurrence in a range of habitats, and fast growth rate, microalgae and cyanobacteria offer several benefits to such investigations [5].
The antimycotic activity of some macroalgae collected from the Egyptian coast has been examined against Fusarium solani, F. oxysporum, and Aspergillus flavipes [6]. The marine algae extracts were examined for their antifungal activity against some fungi [7,8]. Nostoc muscorum cell extracts prevented the growth of damping agents such as Sclerotinia sclerotiorum and Rhizoctonia solani [3,9]. Cunninghamella blakesleeana (soil-borne fungus) and damping-off were inhibited by Anabaena spp., Scytonema spp., and Nostoc spp. [10].
The interest in natural active compounds as alternatives to synthetic substances has recently increased. In other words, new and safe biological products with synthetic-like properties—particularly antimicrobial, antifungal, and antioxidant compounds—must be developed. Recently, microbial cells have been shown to play an important role in a wide range of biotechnological applications, including the generation of renewable energy [11,12,13] and biocontrol of plant pathogens [14,15,16]. The extracts of algae and cyanobacteria contain biomolecules such as proteins, carbohydrates, fats, and polyunsaturated fatty acids. In addition to bioactive compounds, antioxidants such as (poly) phenols, amino acids, tocopherols, vitamin E, and vitamin C, and pigments such as phycocyanin, chlorophylls, and carotenoids, which have antiviral, antibacterial, antioxidant, and antifungal properties, have also been studied [17]. Polyphenols constitute the majority of these compounds [8]. The inhibitory effects are due to saponins, flavonoids, tannins, and cardiac glycosides [18], or the presence of secondary metabolites such as phenol and carotenoid compounds [19]. The effect on Trichophyton concentricum and T. interdigitale fungi was efficient in alcoholic and alkaloid extracts from Spirulina platensis [20]. Antifungal activity has previously been detected in Chlorococcum humicola algal extract consisting of alkaloids, carotenoids, saponins, flavonoids, and carbohydrates [21,22]. Extracts of six Tanzanian green algae have been confirmed to have antimicrobial activity. Terpenoids, phlorotannins, and steroids were the observed extract components [23,24].
Cyanobacteria and microalgae produce secondary metabolites, and various hydrolytic enzymes may exhibit antifungal activity [25]. Chitinolytic enzymes are important in their biotechnological applications—particularly chitinases used to control pathogenic fungi in agricultural fields [26]. An earlier study also showed that chitinases inhibit the growth of some phytopathogenic fungi; this is why this enzyme has gained much importance due to its numerous applications [27].
One of the essential properties of cyanobacteria and microalgae is the production of exopolysaccharides (EPSs), which perform protective activities against biotic and abiotic stress [3,28]. To understand the exopolysaccharides’ composition, monosaccharide composition analysis is one of the most important approaches for profiling the composition of complex polysaccharides [29]. An earlier study reported that the chemical structure of the polysaccharides was associated with their antimicrobial activity [30]. EPSs from cyanobacteria are heteropolysaccharides soaked in neutral sugars [31]. Cyanobacterial exopolysaccharide comprises several monosaccharides, including pentoses, which are typically missing in other prokaryotic polysaccharides [32].
Only a few studies have shown how different cyanobacteria produce a variety of metabolites and hydrolytic enzymes, and how those play a role in various biocontrol strains’ fungicidal activity. This research aims to highlight and compare the roles of some metabolites and hydrolytic enzymes that could be related to the fungicidal activity of eight strains of cyanobacteria and two strains of green microalgae, collected from soil and brackish water biomes in Egypt, against three selected phytopathogenic fungi (Pythium ultimum, Fusarium solani, and Botryodiplodia theobromae). This work also aimed at algal biocontrol agents against plant pathogenic fungi by exploiting the isolates with the most effective fungicidal activity.

2. Materials and Methods

2.1. Isolation, Identification, Cultivation, and Biomass Production of the Cyanobacterial and Algal Strains

All strains were isolated from rice and wheat field soils in El-Sharkia Governorate and a brackish water draining station in Bahr Hadus in Egypt. Isolation and purification were performed for cyanobacterial isolates using BG-11 medium [33], while chlorophycean strains were isolated with Bold’s basal medium [34]. Cyanobacteria and microalgae strains became axenic following standard procedures using a set of antibiotics. Re-streaking and sub-culturing were repeated multiple times to obtain unialgal cultures via the micropipette washing streak plating technique [35]. Briefly, 200 mL of algal medium was inoculated with 10 mL of axenic culture (average cell density of 7.0 × 105 cells/L), and cultures were grown under a photoperiod cycle of L:D (light: dark cycles) 16:8 h, white light (50–55 µmoL photons m−2 s −1), and 25 ± 1 °C in the growth media. The optical density of microalgae was measured at 540 nm for 2–3 weeks, depending on the optimal growth rates of the different microalgal strains. When the growth curves were determined and the microalgae reached the stationary phase, the cyanobacteria and microalgae were harvested by centrifugation. The maximum value of microalgae density was approximately around 1.2 × 108 cells/L after 2–3 weeks. Each strain was morphologically identified under the microscope. The axenic culture from each microalgal isolate was molecularly assigned a GenBank accession number and put in the database. In the present study, eight isolates taxonomically related to Cyanobacteria—Anabaena sp. HSSASE11 (KT277794), Wollea saccata HSSASE12 (KT277795), Dolichospermum circinale HSSASE14 (KT277797), Oscillatoria nigro-viridis HSSASE15 (KT277798), Aphanizomenon gracile HSSASE16 (KT277799), Dolichospermum spiroides HSSASE18 (KT277801), Oscillatoria sancta HSSASE19 (KT277802), and Dolichospermum crassum HSSASE20 (KT277803)—and two isolates related to Chlorophyta—Dunaliella sp. HSSASE13 (KT277796) and Chlorella sorokiniana HSSASE17 (KT277800)—were identified [36].

2.2. Dry Biomass Estimation

Centrifugation of the cell cultures was conducted for 30 min at 5000 rpm at 4 °C, followed by washing with distilled water. About 20 mL of algal suspension was filtered through pre-weighed filter papers (Whatman filter paper No. 1). Then, filter papers were oven-dried at 105 °C for 2 h before weighing again to determine the dry biomass accumulation per liter of culture medium (g/L).

2.3. Determination of Pigments in the Microalgal Crude Extracts

2.3.1. Phycocyanin Analysis

Phycocyanin pigments were determined according to Silveira’s protocol [37]. Briefly, 1 g of the dried algal/cyanobacterial cells was added to 10 mL of sodium phosphate buffer at 30 °C for 72 h under dark conditions. After centrifugation, a spectrophotometer (Jenway UV/Vis, Tokyo, Japan) was used to measure the absorbance spectra at 615 and 652 nm. Phycocyanin content was estimated using the following formula:
Phycocyanin (mg. mL−1) = A615 − (0.474 × A652)/5.34

2.3.2. Total Carotenoid Contents

The total content of carotenoids was calculated according to a method reported in a prior study [38]. The sample (1 g) was homogenized and saponified in a water bath at 60 °C for 30 min with 1 mL of 12% alcoholic potassium hydroxide. The saponified extract was transferred to a separating funnel and gently mixed with 5 mL of petroleum ether. Then, the upper carotenoid-containing petroleum ether layer was collected. The upper yellow color’s absorbance was determined at 450 and 503 nm, while a blank of petroleum ether was used as a negative control.

2.3.3. Chlorophyll-a Content

The chlorophyll-a concentration was determined as described in [39]. Briefly, a pestle and mortar were used in the dark to homogenize 10 mL of algal cell suspension with 5 mL of hot methanol (99.9%). The chlorophyll-a content was measured spectrophotometrically at 665.2 and 652.4 nm after the extracts had been filtered through a 0.45 µm membrane filter.

2.4. Preparation of the Algal Methanolic Extracts

Methanolic extracts prepared from the isolates were used to screen different phytochemical compounds. First, 100 mL of methanol was used to soak 25 g of algal powder for 24 h on a rotating shaker set at 150 rpm at 25–30 °C. The crude extract was filtered through Whatman filter paper No. 1. The filtrate was separated from the methanol solvent by evaporation under pressure using a rotary evaporator. The resulting crude extract was then dissolved in dimethyl sulfoxide (DMSO) at a concentration of 10% to yield 100 mg/mL. Then, each extract was stored in the dark at 4 °C for further analysis, as described previously [40].

2.5. Qualitative Analyses of Some Phytochemical Constituents in the Algal Extracts

The previous studies’ defined qualitative analysis protocols of some phytochemical constituents—including glycosides, alkaloids, saponins, and steroids—were used in this study, as well as to determine the contents as mentioned [41].

2.5.1. Determination of Glycosides

To determine whether glycosides were present in the crude extract, it was dissolved in bromine water and observed to form a yellow precipitate following the previously described protocol [41].

2.5.2. Determination of Saponins

For a positive result, the crude extract was mixed with water and shaken until foam formed, which remained constant for 15 min following the previously described protocol [41].

2.5.3. Determination of Alkaloids

A few drops of Hager’s reagent (saturated picric acid solution) were added to the crude extract. Alkaloids were detected if a yellow precipitate formed, indicating their presence [41].

2.5.4. Determination of Steroids

A few drops of acetic anhydride were added to the crude extract before it was boiled and cooled. The test tube was then splashed with concentrated sulfuric acid from the sides, and the brown ring formed at the point where the two layers met. The upper layer appeared to be green following the previously described protocol [41].

2.6. Quantitative Analyses of Some Phytochemical Constituents

2.6.1. Total Phenolic Content (TPC)

TPC in the methanolic extract was determined by the Folin–Ciocalteu reagent method described in [42]. First, 5 mL of distilled water and 250 μL of Folin–Ciocalteu reagent were added to 1 mL of the methanolic extract. Incubation at 25 °C for 30 min was followed by adding 1 mL of Na2CO3 (7.5%) and distilled water. It took 90 min at room temperature and complete darkness to incubate the mixture. Gallic acid standard solutions were prepared at 100, 125, 150, 175, and 200 μg/mL concentrations. The sample’s absorbance was measured against the blank at 760 nm. TPC was estimated from the standard curve and expressed in the form of mg GAE/g of the extract.

2.6.2. Total Flavonoid Content (TFC)

Total flavonoid content (TFC) was assessed using a colorimetric method defined by the Chang’s protocol [43]. Briefly, 500 µL of sample extract was added to 1.5 mL of methanol, 2.5 mL of distilled water, 100 µL of 10% (w/v) aluminum chloride, and 100 µL of 1 M potassium acetate in a test tube. Afterward, the samples were kept in the dark for 30 min. The absorbance of the mixture was determined at 415 nm. The total flavonoid content was estimated from the standard curve and expressed as milligrams of quercetin equivalent (Q.C.E.) per g of the extract (mg Q.C.E./g of the extract).

2.7. Determination of Antioxidant Activity by DPPH Assay

The antioxidant potential of algae was assessed by the ability of their bioactive substances to scavenge the free radical α,α-diphenyl-β-picryl hydrazyl (DPPH), as described in [44]. A 20 µg/mL solution of DPPH was mixed with methanol, and 2 mL of the DPPH solution was mixed with 0.78 mL of the sample extract, or butylated hydroxy-toluene (BHT) (as a reference). The mixture was then kept for 30 min in the dark at room temperature. Then, the decrease in absorbance was detected against the methanol blank at 517 nm [45].

2.8. Total Protein Estimation

The total protein contents were estimated by the method described by Lowry et al. [46]. As a reference, we used bovine serum albumin. Following the protocol, 1 mL of the algal culture was hydrolyzed in 10 mL of 1 M NaOH solution for 24 h. When the supernatant was centrifuged, it was used to estimate protein content. For 10 min at room temperature, 5 mL of reagent “A” was added to 1 mL of the hydrolysate supernatant and mixed thoroughly. At room temperature, 1 mL of reagent “B” was added, gently mixed, and incubated for 30 min. At 750 nm, this mixture’s absorption was measured.

2.9. Enzyme Activity Assay

2.9.1. Chitinase Enzyme Activity

The estimation of chitinase activity was carried out via Tonon’s method [47]. Chitin was used as the substrate to determine the chitinase activity. A 200 µL sample of chitin was added to a 300 µL aliquot of crude extract. A rotary shaker was used to incubate the mixture for two hours at 37 °C. The mixture was then centrifuged for 10 min at 7000× g. Then 250 µL of supernatant was transferred to a new tube, and 100 µL of 0.2 M sodium borate buffer was added to the mixture. At 100 °C, the mixture was heated for 10 min before cooling. It was then incubated for 30 min at room temperature with 1 mL of Ehrlich reagent. Finally, the absorbance was measured at 585 nm using a spectrophotometer [48]. The chitinase activity was estimated from the standard curve generated from the simple linear regression model using the standard Trichoderma viride chitinase enzyme [49]. It was expressed in units per mg of fresh weight per hour.

2.9.2. β-1,3-Glucanase Enzyme Activity

Laminarin was used as a substrate for the estimation of β-1,3-glucanase activity at a concentration of 0.75% w/v in 50 mM sodium acetate buffer at pH 6.0; 10 μL of enzyme solution and 20 μL of laminarin solution were used in the assay. After 10 min of incubation at 50 °C, 100 μL of dinitrosalicylic acid (DNS) was added, and the reaction mixture was incubated at 95 °C for 5 min. Spectrophotometrically, the amount of reducing sugar was measured at 540 nm. One unit of β-1,3-glucanase activity was identified as the amount of enzyme required to release 1 μmol of D-glucose per minute per milliliter of culture filtrate [50].

2.9.3. The Activity of the Xylanase Enzyme

Xylanase activity was determined as described by Bailey et al. [51]. The substrate used in this assay was 1% xylan; 0.05 M sodium phosphate buffer was used to dissolve the xylan (pH 5.5), which was followed by incubating 0.1 mL of crude enzyme for 30 min in a water bath at 50 °C in a 0.9 mL xylan mixture. For 5 min, the mixture was incubated at 90 °C with 1.5 mL of DNS reagent. Then, 1.5 mL of DNS reagent was added to the mixture and incubated for 5 min at 90 °C. At 575 nm, the absorbance of xylanase was measured using a xylose standard curve. One µmole of xylose released per minute per milliliter of enzyme extract represents one unit of xylanase activity.

2.10. Extraction of Exopolysaccharides (EPS) from the Cyanobacterial and Microalgal Strains

The exopolysaccharides (EPSs) were recovered as described in [52]. First, the algal culture was shaken in warm water to obtain the loosely bound EPSs (LEPSs); second, 0.1 M EDTA was added to extract the tightly bound EPSs (TEPSs). After centrifugation, the pellet was removed. The dialysis desalting process achieved further purification of crude EPSs. Finally, the EPSs were precipitated with isopropanol (1:1), and then lyophilized and stored at −20 °C [53,54].

Determination of the Total Carbohydrates and Composition of the Purified Exopolysaccharides (EPSs)

The total carbohydrate content (total neutral sugars) of purified EPS samples was determined using an assay of phenol–sulfuric acid, in which glucose was used as a reference standard [55,56]. The monosaccharides found in the EPSs were separated and identified via HPLC analysis [57]. About 2 mg of each lyophilized EPS sample was combined with 2 mL of 0.5 M trifluoroacetic acid and warmed for 4 h at 100 °C. Diethyl ether was used to extract the mixture. The aqueous phase was evaporated to dryness at 60 °C using rotary evaporation. This extract was diluted in 1 mL of distilled water before being examined via HPLC. The chromatographic conditions were as follows: the mobile phase was acetonitrile–H2O (80:20), and the flow rate was 0.8 mL min−1; liquid chromatogram with UV–Vis detector; CD18 column.

2.11. Evaluation of the Antifungal Activity Using the Method of Agar Well Diffusion

The algal extracts of the 10 tested strains were evaluated against Pythium ultimum, Fusarium solani, and Botryodiplodia theobromae. The pathogenic fungi were cultured on modified sterile potato dextrose agar (P.D.A.) medium. The samples were incubated at 28 ± 2 °C for 3–5 days and then stored on P.D.A. slant sub-culture at 4 °C until use. The agar well diffusion method was used to investigate the antifungal activity of the tested strains. A cut (5 mm) was punched into the surface of the agar plates previously inoculated with each of the abovementioned strains. The stock solutions of the extracts were prepared in DMSO at 100 mg mL−1 to evaluate their antifungal activity. DMSO can be used as a solvent for antifungal applications. About 100 µL of the algal extract was transferred into each well. The plates were incubated for 72 h at 28 ± 2 °C in the dark [58,59]. Rhizolex-T standard (20 ppm) served as a positive control, while DMSO was used as a negative control. After the fungal growth in the control treatment had completely covered the Petri dish, the diameter of the colony was measured. Mycelial growth inhibition percentage was determined according to [60] in the following formula:
Inhibition of mycelial growth = [(DC − DT)/DC] × 100.
where DC is the average diameter of the control fungal colony, and DT is the average diameter of the treatment fungal colony. All tests were repeated three times.

2.12. Data Analysis

Statistical analysis was performed using SPSS (Statistical Package for Social Science, Chicago, IL, USA), IBM-SPSS version 26.0, for Mac OS. Data were checked for normality using the Shapiro–Wilk at the 0.05 level. Data were described statistically, both graphically and numerically, in terms of mean and standard error. Inferential statistics for evaluating and comparing different species were performed using one-way analysis of variance (ANOVA) at a 0.05 significance level. ANOVA was followed by Duncan’s multiple range test (DMRT) to compare different species [61].

3. Results

Data from different algal species extracted from the samples are given in Table 1, Table 2 and Table 3 and Figure 1, Figure 2, Figure 3, Figure 4, Figure 5, Figure 6 and Figure 7. The algal strains identified were Anabaena sp. HSSASE11, Aphanizomenon gracile HSSASE16, Dolichospermum circinale HSSASE14, Dolichospermum crassum HSSASE20, Dolichospermum spiroides HSSASE18, Oscillatoria nigro-viridis HSSASE15, Oscillatoria sancta HSSASE19, Wollea saccata HSSASE12, Chlorella sorokiniana HSSASE17, and Dunaliella sp. HSSASE13.
The highest chlorophyll-a content among the 10 different algal species was recorded in O. sancta, with an average (±SE) of 171.3 ± 0.32 mg·g−1, followed by 152.98 ± 1.00, 148.86 ± 1.32, and 142.91 ± 0.53 mg·g−1 in A. gracile, W. saccata, and Anabaena sp., respectively. The difference in chlorophyll-a content between the 10 different algal species was highly significant (p < 0.001 ***), as revealed by one-way ANOVA; further multiple comparisons were carried out using DMRT at the 0.05 level. Phycocyanin content in the eight algal species ranged from 22.20 ± 0.17 mg·g−1 in D. crassum to a maximum of 50.22 ± 0.14 mg·g−1 in A. gracile—a highly significant difference between the eight studied cyanobacteria and algal species in terms of phycocyanin content. Furthermore, the carotenoid content in the 10 studied algal species recorded its lowest level of 27.43 ± 0.06 mg·g−1 in W. saccata, and its highest level of 112.05 ± 0.37 in Dunaliella sp., with a significant difference in carotenoid contents between the studied cyanobacteria and algal species (Figure 1).
Agronomy 12 01340 g001 550
Figure 1. (A) Chlorophyll-a, (B) phycocyanin, (C) carotenoids, and (D) dry weight of the different cyanobacterial and algal strains. Bars with different superscript letters were significantly different according to DMRT at the p < 0.05 level. ***: Significant at p < 0.001.
Figure 1. (A) Chlorophyll-a, (B) phycocyanin, (C) carotenoids, and (D) dry weight of the different cyanobacterial and algal strains. Bars with different superscript letters were significantly different according to DMRT at the p < 0.05 level. ***: Significant at p < 0.001.
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The dry weight of the 10 studied cyanobacteria and microalgae showed its lowest average of 0.93 ± 0.002 in D. spiroides and its highest value (±SE) of 1.12 ± 0.001 g/L in C. sorokiniana, with a highly significant difference in dry weight between studied the cyanobacteria and algal species (Figure 1).
Dunaliella sp., Anabaena sp., and O. nigro-viridis showed the highest significant enzyme activities with xylanase, chitinase, and β-1,3 glucanase. Dunaliella sp., Anabaena sp., and O. nigro-viridis recorded an average chitinase activity of 137.57 ± 0.19, 133.49 ± 0.16, and 126.45 ± 0.21 U·mg−1 protein, respectively, with a significant difference (p < 0.05) from the other studied species. Moreover, the three previously mentioned algal species recorded the highest average (±SE) β-1,3-glucanase activities of 24.51 ± 0.18, 23.57 ± 0.20, and 21.53 ± 0.15 U·mg−1 protein in Anabaena sp., Dunaliella sp. and O. nigro-viridis, respectively—significantly different from the β-1,3-glucanase activities of other studied cyanobacteria and algal species (Figure 2). Xylanase activities were the highest in these three algal species, which recorded an average (±SE) xylanase activity of 125.27 ± 2.34, 118.37 ± 2.28, and 110.77 ± 1.91 U·mg−1 protein in Dunaliella sp., O. nigro-viridis, and Anabaena sp., respectively (Figure 2).
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Figure 2. Enzyme activities of the different investigated cyanobacterial and algal strains: (A) chitinase, (B) β-1,3-glucanase, (C) xylanase. Bars with different superscript letters were significantly different according to DMRT at p < 0.05. *** significant at p < 0.001.
Figure 2. Enzyme activities of the different investigated cyanobacterial and algal strains: (A) chitinase, (B) β-1,3-glucanase, (C) xylanase. Bars with different superscript letters were significantly different according to DMRT at p < 0.05. *** significant at p < 0.001.
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Comparative analysis of the production of phenolic compounds, flavonoids, and the antioxidant or scavenging activity of cyanobacteria and microalgae extracts on reducing DPPH as a stable free radical with an odd electron, is given in Figure 3. Differences were assessed by one-way ANOVA and followed by Duncan’s post hoc test. Means followed by different letters are significantly different according to DMRT at the 0.05 level. Dunaliella sp., Anabaena sp., O. nigro-viridis, and D. crassum recorded the highest average phenolic compound contents of 34.80 ± 0.10, 34.39 ± 0.11, 31.71 ± 0.11, and 31.44 ± 0.11 mg GAE/g of the extract, respectively.
Total flavonoid content was also estimated in the 10 screened cyanobacteria and algal species. The highest average flavonoid contents were recorded in Dunaliella sp., O. nigro-viridis, and Anabaena sp., with an average flavonoid level of 4.58 ± 0.17, 4.35 ± 0.19, and 3.74 ± 0.10 mg QCE/g of the extract, respectively. The differences in flavonoid contents were significant between the studied algae and cyanobacteria, according to DMRT (Figure 3).
Agronomy 12 01340 g003 550
Figure 3. Average concentrations of the total phenolics (A), flavonoids (B), and DPPH (C) of the different cyanobacterial and algal strains investigated in the present study. Bars with different superscript letters were significantly different according to DMRT at p < 0.05. *** significant at p < 0.001.
Figure 3. Average concentrations of the total phenolics (A), flavonoids (B), and DPPH (C) of the different cyanobacterial and algal strains investigated in the present study. Bars with different superscript letters were significantly different according to DMRT at p < 0.05. *** significant at p < 0.001.
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A comparison of cyanobacteria and microalgae extracts’ antioxidant activity to the reference standard (BHT) is presented in Figure 3. The data revealed that Dunaliella sp. and Anabaena sp. recorded the highest levels of DPPH activity, with an average DPPH of 62.49 ± 0.23% and 61.53 ± 0.23%, respectively—close to the standard BHT (58.53 ± 0.22%).
Total protein contents also recorded their highest average in Dunaliella sp., Anabaena sp., and O. nigro-viridis, with an average total protein level of 272.33 ± 12.86, 253.33 ± 9.24, and 216.00 ± 9.64 mg/g.
Total neutral sugars (TNS) showed the highest levels of 15.62 ± 0.01, 14.55 ± 0.21, and 13.72 ± 0.01 µg/mL in Anabaena sp., Dunaliella sp., and O. nigro-viridis, respectively, which were significantly different from the other tested species.
Furthermore, the monosaccharide compositions (%) extracted from the hydrolyzed exopolysaccharides (EPSs) in the studied cyanobacteria and algal species are presented in Figure 4 and Figure 5. The data indicate that glucose (Glc) showed its highest levels in Anabaena sp., Dunaliella sp., C. sorokiniana, and D. spiroides, which recorded glucose levels of 33.40 ± 0.01%, 31.10 ± 0.01%, 26.40 ± 0.01%, and 22.10 ± 0.01%, respectively.
Agronomy 12 01340 g004 550
Figure 4. Total proteins, total neutral sugars, and monosaccharide composition (%) were determined from the hydrolyzed exopolysaccharides in the different cyanobacterial and algal strains studied: (A) total proteins, (B) total neutral sugars (TNS), (C) glucose, (D) xylose, (E) rhamnose, and (F) galactose. Bars with different superscript letters were significantly different according to DMRT at p < 0.05. *** significant at p < 0.001.
Figure 4. Total proteins, total neutral sugars, and monosaccharide composition (%) were determined from the hydrolyzed exopolysaccharides in the different cyanobacterial and algal strains studied: (A) total proteins, (B) total neutral sugars (TNS), (C) glucose, (D) xylose, (E) rhamnose, and (F) galactose. Bars with different superscript letters were significantly different according to DMRT at p < 0.05. *** significant at p < 0.001.
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Figure 5. The monosaccharide compositions (%) isolated from the hydrolyzed exopolysaccharides in the different cyanobacterial and algal strains studied: (A) fucose, (B) arabinose, (C) mannose, and (D) ribose. Bars with different superscript letters were significantly different according to DMRT at p < 0.05. *** significant at p < 0.001.
Figure 5. The monosaccharide compositions (%) isolated from the hydrolyzed exopolysaccharides in the different cyanobacterial and algal strains studied: (A) fucose, (B) arabinose, (C) mannose, and (D) ribose. Bars with different superscript letters were significantly different according to DMRT at p < 0.05. *** significant at p < 0.001.
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The xylose (Xyl) contents in the examined cyanobacteria and algae species showed their highest averages of 30.20 ± 0.01%, 24.60 ± 0.03%, and 21.30 ± 0.01% in D. circinale, Dunaliella sp., and O. nigro-viridis, respectively. As revealed by one-way ANOVA, differences between in xylose content the tested species were significant (p < 0.001).
Rhamnose (Rha) levels detected in various studied species recorded their highest averages of 43.10 ± 0.01%, 26.00 ± 0.01%, and 25.00 ± 0.09% in D. circinale, O. nigro-viridis, and D. crassum, respectively. However, Anabaena sp. and Dunaliella sp. showed the lowest significant levels of rhamnose, at 3.00 ± 0.01% and 2.10 ± 0.01%, respectively. As revealed by one-way ANOVA, differences in rhamnose content between the studied species were significant (p < 0.001).
The galactose content showed its highest levels of 30.10 ± 0.01%, 29.10 ± 0.08%, 25.60 ± 0.01%, and 22.50 ± 0.01% in W. saccata, O. sancta, D. circinale, and O. nigro-viridis, respectively. However, the lowest galactose level was recorded in D. spiroides.
Anabaena sp., W. saccata, and D. circinale recorded the highest fucose averages (±SE) of 24.70 ± 0.06%, 22.70 ± 0.03%, and 19.70 ± 0.02%, respectively. However, C. sorokiniana and A. gracile showed the highest arabinose contents, with an average (±SE) of 21.10 ± 0.17% and 20.60 ± 0.06%, respectively.
Mannose content showed its highest significant averages of 24.00 ± 0.06%, 19.70 ± 0.07%, and 13.60 ± 0.03% in C. sorokiniana, D. spiroides, and D. circinale, respectively. However, Dunaliella sp. and A. gracile recorded the highest significant levels of ribose content, at 17.50 ± 0.12% and 9.30 ± 0.08%, respectively.
Results of antifungal activities for the 10 studied cyanobacteria and algal extracts are presented in Figure 6 and Figure 7. Oscillatoria nigro-viridis showed the highest antifungal activity against Pythium ultimum, at 63.42 ± 0.23%—significantly different from the fungicide Rhizolex-T (62.34 ± 0.23%)—followed by Dunaliella sp., with average antifungal activity of 61.39 ± 0.04%, which is close to the fungicide activity of Rhizolex-T, and significantly (p < 0.05) different from the fungicide activity of O. nigro-viridis, as revealed by DMRT.
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Figure 6. Antifungal activities (%) of the different cyanobacterial and algal strains were studied against Pythium ultimum (A), Fusarium solani (B), Botryodiplodia theobromae (C) fungi. Bars with different superscript letters were significantly different according to DMRT at p < 0.05. *** significant at p < 0.001.
Figure 6. Antifungal activities (%) of the different cyanobacterial and algal strains were studied against Pythium ultimum (A), Fusarium solani (B), Botryodiplodia theobromae (C) fungi. Bars with different superscript letters were significantly different according to DMRT at p < 0.05. *** significant at p < 0.001.
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Figure 7. In vitro susceptibility of the three pathogenic fungi investigated in this study to the different cyanobacterial and algal strains using the well diffusion assay. The highest antifungal activities were obtained by Anabaena sp. (a), Oscillatoria nigro-viridis (b), and Dunaliella sp. (c), compared to the standard fungicide Rhizolex-T (d).
Figure 7. In vitro susceptibility of the three pathogenic fungi investigated in this study to the different cyanobacterial and algal strains using the well diffusion assay. The highest antifungal activities were obtained by Anabaena sp. (a), Oscillatoria nigro-viridis (b), and Dunaliella sp. (c), compared to the standard fungicide Rhizolex-T (d).
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Dunaliella sp. showed the highest antifungal activity against Fusarium solani, with an average activity of 81.94 ± 0.03%, which is significantly different from the antifungal activity of the fungicide Rhizolex-T (78.43 ± 0.20%). Furthermore, Anabaena sp. showed the highest antifungal activity against Botryodiplodia theobromae, with an average antifungal activity of 83.95 ± 0.01%, which is significantly different from the antifungal activity of the fungicide Rhizolex-T (79.64 ± 0.37%).
The interrelationships between the studied variables—including all biochemicals and antifungal activities—were determined based on Pearson’s correlation, and are presented in a correlation matrix in Table 1 and Figure 8. It is an interesting observation that the antifungal activity against Pythium ultimum was strongly positively and significantly correlated with phenolic compounds (r = 0.757; p < 0.001 ***), flavonoids (r = 0.811; p < 0.001 ***), and DPPH free radical scavenging activity (r = 0.732; p < 0.001 ***); however, it was inversely strongly and significantly correlated with chlorophyll-a content (r = −0.760; p < 0.001 ***).
Table
Table 1. Pearson’s correlation matrix represents the interrelationship between variables. The correlation was followed by a two-tailed significance test at the 0.05 level.
Table 1. Pearson’s correlation matrix represents the interrelationship between variables. The correlation was followed by a two-tailed significance test at the 0.05 level.
VariablesAntifungal Activities
Pythium ultimumFusarium solaniBotryodiplodia theobromae
rprprp
Dry weight−0.537 **0.002−0.499 **0.005−0.3390.067
Phycocyanin−0.1470.439−0.3600.051−0.2190.245
Chl-a−0.760 **0.000−0.573 **0.001−0.0910.633
Carotenoids0.1670.3780.373 *0.0430.2200.243
Chitinase0.363 *0.0490.698 **0.0000.548 **0.002
Glucanase0.3350.0700.746 **0.0000.728 **0.000
Xylanase0.720 **0.0000.876 **0.0000.497 **0.005
Phenolics0.757 **0.0000.785 **0.0000.645 **0.000
Flavonoids0.811 **0.0000.854 **0.0000.3220.083
DPPH0.732 **0.0000.876 **0.0000.3560.054
Total proteins0.498 **0.0050.808 **0.0000.832 **0.000
TNS0.655 **0.0000.764 **0.0000.2970.111
*, **: Significant at p < 0.05, and 0.01, respectively.
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Figure 8. Pearson’s correlation matrix represents the interrelationships between variables. The correlation was followed by a two-tailed significance test at the 0.05 level. Blue indicates a positive correlation, red for negative correlation, and boxed colors for significant correlation. Circle colors correspond to the correlation coefficient.
Figure 8. Pearson’s correlation matrix represents the interrelationships between variables. The correlation was followed by a two-tailed significance test at the 0.05 level. Blue indicates a positive correlation, red for negative correlation, and boxed colors for significant correlation. Circle colors correspond to the correlation coefficient.
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Moreover, the antifungal activity against Fusarium solani was strongly positively and significantly correlated with phenolic compounds (r = 0.785; p < 0.001 ***), flavonoids (r = 0.854; p < 0.001 ***), DPPH free radical scavenging activity (r = 0.876; p < 0.001 ***), xylanase activity (r = 0.876; p < 0.001 ***), glucanase activity (r = 0.746; p < 0.001 ***), TNS (r = 0.764; p < 0.001 ***), and total proteins contents (r = 0.808; p < 0.001 ***). However, it was inversely and significantly correlated with chlorophyll-a content (r = −0.573; p < 0.001 ***).
On the other hand, the antifungal activity against Botryodiplodia theobromae was strongly positively and significantly correlated with total proteins (r = 0.832; p < 0.001 ***), glucanase (r = 0.728; p < 0.001 ***), and phenolic compound contents (r = 0.645; p < 0.001 ***).
The distribution of glycosides, steroids, saponins, and alkaloids among the studied cyanobacterial and algal species is presented in Table 2. Qualitative data present the scoring of production of glycosides, steroids, saponins, and alkaloids in medians and interquartile ranges (IQR; Q1–Q3). Differences between species were assessed using Kruskal–Wallis test statistics. The highest glycoside production was recorded in D. crassum and O. nigro-viridis, with a median (IQR; Q1–Q3) of 3 (3.0–3.0). However, the highest steroid contents were recorded in Anabaena sp., with a 3 (3.0–3.0), followed by D. crassum and Dunaliella sp., with a median of 2 (2.0–2.0). Furthermore, the highest saponin production was recorded in C. sorokiniana, with a median of 3 (3.0–3.0), and the highest alkaloids were recorded in Anabaena sp., O. nigro-viridis, and Dunaliella sp., with a median of 3 (3.0–3.0).
Table
Table 2. Distribution of glycosides, steroids, saponins, and alkaloids among the different cyanobacterial and algal strains studied. Differences were assessed using the Kruskal–Wallis test.
Table 2. Distribution of glycosides, steroids, saponins, and alkaloids among the different cyanobacterial and algal strains studied. Differences were assessed using the Kruskal–Wallis test.
SpeciesMedian (IQR)
GlycosidesSteroidsSaponinsAlkaloids
Anabaena sp.2 (2.0–2.0)3 (3.0–3.0)2 (2.0–2.0)3 (3.0–3.0)
Aphanizomenon gracile0 (0.0–0.0)0 (0.0–0.0)2 (2.0–2.0)0 (0.0–0.0)
Dolichospermum circinale1 (1.0–1.0)0 (0.0–0.0)2 (2.0–2.0)1 (1.0–1.0)
Dolichospermum crassum3 (3.0–3.0)2 (2.0–2.0)2 (2.0–2.0)2 (2.0–2.0)
Dolichospermum spiroides2 (2.0–2.0)0 (0.0–0.0)2 (2.0–2.0)2 (2.0–2.0)
Oscillatoria nigro-viridis3 (3.0–3.0)1 (1.0–1.0)0 (0.0–0.0)3 (3.0–3.0)
Oscillatoria sancta1 (1.0–1.0)0 (0.0–0.0)0 (0.0–0.0)1 (1.0–1.0)
Wollea saccata1 (1.0–1.0)0 (0.0–0.0)0 (0.0–0.0)0 (0.0–0.0)
Chlorella sorokiniana2 (2.0–2.0)0 (0.0–0.0)3 (3.0–3.0)1 (1.0–1.0)
Dunaliella sp.2 (2.0–2.0)2 (2.0–2.0)2 (2.0–2.0)3 (3.0–3.0)
Kruskal–Wallis (p-value)0.001 ***0.001 ***0.001 ***0.001 ***
***: Significant at p < 0.001.
Using nonparametric correlation in terms of Spearman’s rank correlation, the glycosides showed a direct moderate-to-strong significant effect on antifungal activities against Botryodiplodia theobromae (r = 0.684, p < 0.001 ***), Pythium ultimum (r = 0.567, p = 0.001 ***), and Fusarium solani (r = 0.604, p < 0.001 ***) (Table 3). Steroids were positively, strongly, and significantly correlated with antifungal activities against Botryodiplodia theobromae (r = 0.861, p < 0.001 ***), Pythium ultimum (r = 0.641, p < 0.001 ***), and Fusarium solani (r = 0.794, p < 0.001 ***). Alkaloids were the most positively and highly significantly correlated with antifungal activities against Botryodiplodia theobromae (r = 0.841, p < 0.001 ***), Pythium ultimum (r = 0.809, p < 0.001 ***), and Fusarium solani (r = 0.918, p < 0.001 ***).
Table
Table 3. Spearman’s rank correlation between glycosides, steroids, saponins, and alkaloids among the different cyanobacterial and algal strains studied. Differences were assessed using the Kruskal–Wallis test.
Table 3. Spearman’s rank correlation between glycosides, steroids, saponins, and alkaloids among the different cyanobacterial and algal strains studied. Differences were assessed using the Kruskal–Wallis test.
VariablesBotryodiplodia theobromaePythium ultimumFusarium solani
GlycosidesSpearman’s0.6840.5670.604
sign (2-tailed)<0.001 ***0.001 ***<0.001 ***
SteroidsSpearman’s0.8610.6410.794
sign (2-tailed)<0.001 ***<0.001 ***<0.001 ***
SaponinsSpearman’s−0.152−0.069−0.1
sign (2-tailed)0.422 ns0.717 ns0.599 ns
AlkaloidsSpearman’s0.8410.8090.918
sign (2-tailed)<0.001 ***<0.001 ***<0.001 ***
***: Significant at p < 0.001; ns: non-significant at p > 0.05.

4. Discussion

In the present study, cyanobacteria and microalgae represented promising alternatives to biocontrol agents against phytopathogenic fungi, because of their production of different chemical compounds with great effectiveness. In addition, the release of some enzymes that break down fungal cell walls represents a practical approach against fungi in biotechnological applications and agriculture. Anabaena sp. and Dunaliella sp., and Oscillatoria nigro-viridis recorded the highest antifungal activities against the fungal pathogens Botryodiplodia theobromae, Fusarium solani, and Pythium ultimum, respectively. The results of this study were consistent with those of earlier research [62,63,64] that revealed that bioactive metabolites with industrial and agricultural importance are abundant in the Anabaena genus, due to their widespread occurrence in various aquatic and terrestrial habitats. Previously, Anabaena was found to have fungicidal activity against species of Pythium, Fusarium, and Rhizoctonia [65,66]. At least 35 strains from 70 isolates belonging to the genus Anabaena revealed an inhibition zone for at least one phytopathogenic fungus [67]. Previous research [68] reported the antifungal activity of Oscillatoria limosa against Aspergillus flavus. Moreover, acetone, methanol, and ethanol extracts of Dunaliella sp. showed resistance against Rhizopus sp. and Fusarium sp. [69]. Similarly, a mixture of the three solvents methanol, acetone, and diethyl ether with the extract of Dunaliella salina caused the highest decrease in the growth of the fungus F. oxysporum (64.4%) [70].
The examined strains differed significantly in their chitinase, β-1,3-glucanase, and xylanase activities, where Dunaliella sp., Anabaena sp., and Oscillatoria nigro-viridis exhibited the highest enzymes activities, the most elevated DPPH free radical scavenging activity, and the highest production of active phytochemical compounds, including phenolic compounds, flavonoids, total proteins, total neutral sugars, steroids, and alkaloids. The highest antifungal activity against the phytopathogenic fungus Pythium ultimum was recorded by the Oscillatoria nigro-viridis, Dunaliella sp., and Anabaena sp. Comparative analysis of the different phytochemical contents and the antifungal activity indicated a positive and significant relationship with levels of flavonoids (r = 0.811), phenolic compounds (r = 0.757), DPPH free radical scavenging activity (r = 0.732), xylanase activity (r = 0.720), and total neutral sugars (TNS) (r = 0.655). However, antifungal activity against Pythium ultimum had a moderate correlation with total proteins (r = 0.498). On the other hand, our findings reveal that chitinase (r = 0.363) and glucanase activities (r = 0.335) have a positive but weak association with antifungal activity. Previously, different studies have shown that cyanobacteria and microalgae produce various hydrolytic enzymes, which are incredibly effective antifungal agents [71], including chitinase, amylase, protease, lipase, cellulase, urease, and superoxide dismutase [72,73]. A prior study on Anabaena strains also demonstrated the biocidal impact that enzymes such as xylanase could have on some phytopathogenic fungi [67]. In another study, the glucanase enzyme showed antifungal activity and inhibitory action against the growth of phytopathogenic fungi [74]. The structure and function of chitinase from Euglena gracilis were also investigated [75].
In the same way, chitinolytic enzymes demonstrated antifungal potential in the culture supernatants of Chlorella vulgaris and Chlamydomonas reinhardtii [76]. Microalgal exoenzymes—such as alkaline phosphatases, chitinases, β-D-glucosidases, and proteases—can affect the development of microorganisms [77]. Additionally, previous studies reported that the chitinase enzyme produced by Volvox carteri appeared to play a defensive role in protecting the plants from pathogenic fungi [78,79]. Moreover, cyanobacterial strains effectively protected flax from infection by soil-borne fungi due to chitinase and catalase enzymes [80]. Cyanobacteria can synthesize and release enzymes that directly attack the cell walls of pathogens. Antifungal chitinase enzymes produced by Anabaena sp. [81] worked effectively against fungi such as F. solani, F. oxysporum, and R. solani. Enzymes such as chitinase and β-1,3-glucanase extracted from Hypnea musciformis—a red seaweed—were tested for their antifungal properties, and the results were very effective [82].
In the present study, Dunaliella sp. showed the most elevated antifungal activity against the phytopathogenic fungus Fusarium solani, followed by Anabaena sp., and then Oscillatoria nigro-viridis. It is worth mentioning that the levels of phenolic compounds (r = 0.785), flavonoids (r = 0.854), DPPH free radical scavenging activity (r = 0.876), total neutral sugars (r = 0.764), total protein contents (r = 0.808), and xylanase (r = 0.876), glucanase (r = 0.746), and chitinase activities (r = 0.698) were positively and strongly correlated with antifungal activity. However, the carotenoid pigment (r = 0.373) had a positive and weak relationship with antifungal activity. Cyanobacteria, in general, are among the richest sources of known and novel bioactive compounds [1,4]. Their antifungal activity is mostly due to the antioxidant activities of secondary metabolites—especially phenols—that work against plant pathogens. Algal and cyanobacterial extracts contain compounds such as proteins and carbohydrates, and bioactive compounds such as polyphenols and pigments, which have antifungal properties [17]. A prior study found that a Chlorella vulgaris extract suppressed B. cinerea growth, and had antifungal action linked to flavonoids and phenols [3,83]. Previously, methanolic extracts from macroalgae such as Padina and Sargassum inhibited Rhizoctonia and Fusarium solani colonies [84].
Similarly, some macroalgae extracts produce terpenes and phenols that inhibit the growth of Colletotrichum lagenarium [3,85]. Early studies mentioned that the antifungal activities of the ethanol fraction of Dictyopteris membranacea might be due to the high concentration of flavonoids in it [86]. Both Dunaliella and Anabaena were found to have the highest DPPH activity, close to that of the standard BHT, indicating that they could be used as possible antioxidants against free radical damage to the cells of organisms. Dunaliella sp. is expected to have a more prominent antioxidant activity because bioactive its metabolites—such as phenolic compounds, flavonoids, total proteins, and carotenoids—have protective effects [87]. The same bioactive metabolites were examined in Anabaena sp., except for previously known carotenoids [88].
Regarding the phytopathogenic fungus Botryodiplodia theobromae, the most elevated antifungal activity against it in the present study was detected in Anabaena sp., Dunaliella sp., and Oscillatoria nigro-viridis, where antifungal activity was found to be positively and significantly associated with the total protein contents (r = 0.832), glucanase enzyme (r = 0.728), and phenolic compounds (r = 0.645). However, the antifungal efficiency of Anabaena sp., Dunaliella sp., and Oscillatoria nigro-viridis against the Botryodiplodia theobromae fungus was positively and moderately associated with chitinase (r = 0.548) and xylanase activities (r = 0.497), whereas the comparative evaluation of the DPPH free radical scavenging activity (r = 0.356), flavonoids (r = 0.322), TNS (r = 0.297), and carotenoids (r = 0.220) explained the positive and weak connection between antifungal activity and these phytochemical compounds. Algae and cyanobacteria produce exopolysaccharides, which have previously been proven to have defensive effects, and are needed for survival in environments under severe stress, as well as to protect plants from pathogens [28,89]. According to the algae species examined in this study, the carbohydrate content varied, consistent with the results from previous reports [90,91]. The exopolysaccharides of cyanobacteria have a different chemical composition that improves exoenzyme activity [3,92,93]. The exopolysaccharides produced by various cyanobacteria and microalgae are different. Their biological activities depend on the composition of various monosaccharides, which have a definite structure depending on their age and culture conditions [28]. Their structure is closely linked to their biological activity. [94,95,96].
The comparative qualitative analysis revealed a positive, strong, highly significant correlation between alkaloids and antifungal activity against Fusarium solani (r = 0.918), Botryodiplodia theobromae (r = 0.841), and Pythium ultimum (r = 0.809), as well as a strong positive relation of steroids with activity against Pythium ultimum (r = 0.641), Fusarium solani (r = 0.794), and Botryodiplodia theobromae (r = 0.861). Furthermore, a moderate positive association was recorded between the glycosides and antifungal activity. In contrast, saponins showed a negative and insignificant correlation with antifungal activity. In agreement with our results, Nostoc muscorum and Oscillatoria sp. extracellular products have been shown to have large amounts of phenols and alkaloids, which are suitable fungicides according to earlier research [97]. Early studies mentioned that alkaloids in Chlorella vulgaris are the main groups with antifungal activity [98]. According to a recent study, marine macroalgae containing bioactive components such as terpene alcohols, diterpenes, and steroids demonstrated remarkable antifungal potential against many fungal diseases [99]. The antimicrobial activities of brown algae can be attributed to various phytochemical substances, including glycosides, alkaloids, phenols, steroids, terpenoids, flavonoids, oils, and amino acids [100].

5. Conclusions

The present work indicates that the antifungal activities of Dunaliella sp., Anabaena sp., and Oscillatoria nigro-viridis against the tested phytopathogenic fungi could be attributed to the promising antimicrobial compounds produced by these cyanobacterial and green algal strains—especially phenolic and flavonoid compounds, total proteins, total neutral sugars, steroids, and alkaloids. Similarly, hydrolytic enzymes such as xylanase and glucanase most likely played a vital role in this fungicidal activity, where the xylanase enzyme was critical to eradicating Fusarium solani and Pythium ultimum, whereas the glucanase enzyme was essential to get rid of Botryodiplodia theobromae and Pythium ultimum. The data obtained revealed a remarkable relationship between the antioxidant activities of the microalgal and cyanobacterial strains and their antifungal activities. The present study indicated that tested microalgae and cyanobacteria strains have different exopolysaccharide structures, which may explain their variation in antifungal efficacy. Our findings showed that F. solani was the most sensitive fungus to the bioactive compounds produced by the tested microalgal and cyanobacterial strains. It can be concluded that Anabaena sp., Dunaliella sp., and O. nigro-viridis could be used as an alternative to synthetic fungicides to overcome and eliminate plant-infecting pathogenic fungi present in the agricultural system. However, more advanced research is recommended in the future to better understand the antifungal and antimicrobial potential of these extracts, as well as the molecular mechanisms involved.

Author Contributions

M.M.E.-S., H.H.S. and H.M.K. designed the study. H.H.S., A.M.A.-E., A.A.S. and H.A.S. performed the experiments. M.M.E.-S. supervised the experimental work. H.A.S., W.A.A. and A.M.A.-E. analyzed the data. A.A.S. and H.H.S. participated in the data analysis. A.A.S., H.A.S., A.M.A.-E. and W.A.A. drafted the manuscript. M.M.E.-S., H.H.S. and H.M.K. carried out the interpretation of the results and critical revision of the article. All authors approved the manuscript. All authors have read and agreed to the published version of the manuscript.

Funding

This research received no external funding.

Institutional Review Board Statement

This study did not require ethical approval.

Conflicts of Interest

The authors declare no conflict of interest.

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Senousy, H.H.; El-Sheekh, M.M.; Saber, A.A.; Khairy, H.M.; Said, H.A.; Alhoqail, W.A.; Abu-Elsaoud, A.M. Biochemical Analyses of Ten Cyanobacterial and Microalgal Strains Isolated from Egyptian Habitats, and Screening for Their Potential against Some Selected Phytopathogenic Fungal Strains. Agronomy 2022, 12, 1340. https://doi.org/10.3390/agronomy12061340

AMA Style

Senousy HH, El-Sheekh MM, Saber AA, Khairy HM, Said HA, Alhoqail WA, Abu-Elsaoud AM. Biochemical Analyses of Ten Cyanobacterial and Microalgal Strains Isolated from Egyptian Habitats, and Screening for Their Potential against Some Selected Phytopathogenic Fungal Strains. Agronomy. 2022; 12(6):1340. https://doi.org/10.3390/agronomy12061340

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Senousy, Hoda H., Mostafa M. El-Sheekh, Abdullah A. Saber, Hanan M. Khairy, Hanan A. Said, Wardah. A. Alhoqail, and Abdelghafar M. Abu-Elsaoud. 2022. "Biochemical Analyses of Ten Cyanobacterial and Microalgal Strains Isolated from Egyptian Habitats, and Screening for Their Potential against Some Selected Phytopathogenic Fungal Strains" Agronomy 12, no. 6: 1340. https://doi.org/10.3390/agronomy12061340

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