Evidencing nickel biosorption capacity of cyanobacteria Chroococcidiopsis sp.: potential metallo-protective agents

Abstract

The increasing prevalence of toxic elements such as nickel (Ni) in the environment poses a significant threat to human health due to its carcinogenic effect. The study investigates the Ni biosorption potential of three cyanobacteria strains: Euhalothece sp., Halospira sp., and Chroococcidiopsis sp. Hence, the physicochemical properties of biomass and extract were assessed through transmission electron microscopy (TEM), Fourier transform infrared spectroscopy (FTIR), and Brunauer-Emmet-Teller (BET). Batch experiments for Ni²⁺ biosorption were conducted and residual nickel (Ni²⁺) levels were quantitatively assessed using Inductively Coupled Plasma-Optical Emission Spectroscopy (ICP-OES). The results evidence interesting Ni²⁺ removal efficiency of Chroococcidiopsis sp. biomass reaching a biosorption capacity of 18.19 mg g⁻¹ under pH 6, and 37 °C. Several functional groups including amide, carbonyl, phosphate, and carboxyl groups were revealed as key players in this process via FTIR. Finally, such findings highlight the significant potential of cyanobacterial biomass and by-products to reduce nickel bioavailability to prevent Ni-induced carcinogenesis.

Graphical Abstract

Introduction

Over the past decade, rapid growth in the global economy, urbanization, agriculture, and population has led to significant environmental challenges, including the extensive distribution of pollutants across air, water, and soil. Heavy metals (HMs), characterized by their high atomic weight and density, are among the most critical pollutants due to their potential toxicity and high environmental stability, posing continuous threats to human health [5, 11].

HMs can promote the onset of numerous disorders; however, their carcinogenic potential is among the most dangerous impacts. Accordingly, the International Agency for Research on Cancer has classified several HMs (Arsenic (As), Cadmium (Cd), Nickel (Ni), Chromium (Cr), and Beryllium (Be)) as group one carcinogens [22]. In addition, a clear correlation between exposure to HMs and cancer-related mortality was determined, including gastric, kidney, colon, nasopharyngeal, and lung [12]. For instance, atmospheric pollution has been related to a 45% raised lung cancer risk, promoting 36% of death [4]. From those HMs, Ni is a naturally occurring metal that is perceived as a significant environmental pollutant, widely used in various industrial processes and consumer products such as alloys, jewelry, batteries, electric objects, and in the fabrication of steel and cigarettes [19].

Ni exposure primarily occurs through inhalation, particularly in occupational settings and among smokers, where it has been found at high levels in lung tissues, contributing to an increased risk of lung and nasal cancer [22]. The carcinogenic properties of Ni underscore the critical need for protective measures to mitigate its cancer risk, highlighting the importance of developing effective agents to counteract Ni-induced carcinogenicity.

Recent research has increasingly focused on natural, human-compatible sources to mitigate the toxicity of HMs. Among these, microalgae have emerged as promising candidates due to their environmental sustainability and economic viability. Microalgae are known for their diverse bioactive compounds, including polysaccharides, pigments, phenolics, and vitamins, which have been utilized in various medicinal applications such as antimicrobial, antiviral, antioxidant, anti-inflammatory, and anticancer therapies [18]. Moreover, microalgae by-products have succeeded commercially as dietary supplements, underscoring their safety and potential for oral consumption [25]. Their versatility extends to pharmaceutical applications, including drug delivery systems, and wastewater treatment, where they have demonstrated significant potential [25, 49].

Microalgal cells possess active surfaces that can adhere to the intestinal wall, thereby extending retention time and facilitating the adsorption of ingested HMs [16]. In this context, microalgal biomass can act as a chelating agent, reducing the bioavailability and gastrointestinal absorption of HMs, while promoting faster excretion through enhanced intestinal motility.

Due to their unicellular structure and photosynthetic capability, microalgae have also been explored as effective biosorbents for HM remediation. Species such as Chlorella salina, C. vulgaris, Scenedesmus abundans, and Arthrospira platensis have received particular attention for their potential to remove HMs from contaminated environments [22].

The biosorption process involves the removal of HMs from aqueous solutions through various mechanisms, which can be either active (metabolism-dependent, involving live biomass) or passive (metabolism-independent, involving dead biomass or bioactive molecules) [47]. Passive biosorption is facilitated by the presence of negatively charged functional groups (e.g., hydroxyl, carboxyl, phosphate, amine, sulfhydryl) on the cell surface, which provide abundant binding sites for HMs adsorption [45]. In addition to adsorption, microalgal cell surfaces employ other attachment mechanisms, including ion exchange, microprecipitation, and chelation/complexation processes [47].

While the biosorption mechanisms of cyanobacterial biomass are well-established, the chelating abilities of specific biomolecules extracted from these cells, such as phycobiliproteins and astaxanthin, are less understood. This limited understanding has restricted their broader application, despite their demonstrated potential to bind heavy metals [7].

This study proposes using cyanobacterial biomass and by-products (aqueous extracts) as effective agents for nickel detoxification, to prevent the carcinogenic effects associated with nickel exposure. Moving beyond the more common use of cyanobacterial biomass in biosorption studies, this research uniquely investigates the application of cyanobacterial extracts—an unconventional approach motivated by their potential in biomedical applications for mitigating nickel-induced carcinogenesis.

While this study does not directly address carcinogenicity, it focuses on two primary aspects: (1) the ability of cyanobacterial biomass to uptake nickel and reduce its bioavailability, thereby preventing its absorption in the gastrointestinal tract, and (2) the potential of cyanobacterial phycobiliproteins to bind ingested nickel, thus preventing its accumulation in body tissues, which could otherwise lead to cancer.

Materials and methods

Chemicals and growth media

The cyanobacteria strains were cultivated in BG11 medium, with the following composition (mg L⁻¹): 1500 NaNO₃, 40 K₂HPO₄−3H₂O, 75 MgSO₄−7H₂O, 36 CaCl₂−2H₂O, 20 Na₂CO₃, 6 citric acid, 6 Ferric ammonium citrate, 1 EDTA, 2.86 H₃BO₃, 1.81 MnCl₂-H₂O, 0.222 ZnSO₄−7H₂O, 0.079 CuSO₄, 0.390 Na₂MoO₄−2H2O, and 0.049 Co(NO₃)2-6H₂O [15]. The phosphate buffer used for extract preparation was prepared at 0.1 M using Na₂HPO₄.12H₂O (4.4 g L⁻¹) and NaH₂PO₄ (10.5 g L⁻¹). All chemicals used were of analytical grade and obtained from Sigma-Aldrich. Nickel chloride (hexahydrate) NiCl₂.6H₂O, which was purchased from Research-Lab Fine Chem Industries, India.

Cyanobacteria cultivation and biomass preparation

Three marine cyanobacteria strain Euhalothece sp. QUCCCM77, Halospira sp. QUCCCM155, and Chroococcidiopsis sp. QUCCCM26 were selected for this study. They were chosen due to their unique physiological and environmental resilience, as well as their demonstrated potential in producing phycobiliproteins and other bioactive compounds that facilitate heavy metal biosorption. Additionally, these strains belong to the Qatar University Culture Collection of Cyanobacteria and Microalgae (QUCCCM) [39], making them regionally relevant for environmental applications. Initial cultivation of the cyanobacteria was performed in 5 mL BG11 culture medium under controlled conditions: 30 °C temperature, 150 rpm agitation, 100 µmol photons m⁻² s⁻¹ photon flux density, and a 12/12 h dark/light cycle. The cultures were maintained in an illuminated incubator shaker (Innova 44^®, New Brunswick Scientific). After 12 days, the cultures were scaled up gradually to 500 mL under the same conditions, with two replicates for each strain. The growth was monitored by measuring optical density at 750 nm (Jenway 73100, Staffordshire, UK), and the growth rate (µ) was calculated using the following formula (1):

$$\mu =\frac{ln{OD}_{2-}ln{OD}_{1 }}{{T}_{2}-{T}_{1}}$$

(1)

where T₁ and T₂ are the starting and the end time of the exponential phase (day) respectively, OD₁ and OD₂ are respectively optical densities at T₁ and T_2.

For enhanced biomass productivity and increased high-value product yields, a photobioreactor cultivation system (DASGIP^®parallel, Eppendorf) was used under specific culture conditions (400 µmol photons m⁻² s⁻¹ of light intensity and 5% CO₂). After 20 days of cultivation, the biomass was collected, washed, and lyophilized, then, used for high-value product extraction [40].

Moreover, dry weight was determined at the beginning and the end of the culture by filtering 10 mL of cyanobacterial aliquots through vacuum filtration using pre-weighed Whatman filters. The filters were then dried in an oven at 60 °C for 24 h and subsequently incubated in a desiccator until constant weight was achieved. Two replicates were performed for each strain. Biomass productivity (p) was calculated using the following formula (2):

$$P= \frac{{(X}_{2}-{X}_{1})}{\left({T}_{2}-{T}_{1}\right)}$$

(2)

where T₁ and T₂ are the starting and the end time of the exponential phase, and X₁ and X₂ are their corresponding biomass concentration (g L⁻¹) respectively.

The morphology of the cyanobacterial strains was examined under a light microscope (100X magnification) using a Primo star HAL microscope with full Kohler illumination (Carl Zeiss, Germany).

Preparation of cyanobacterial crude extracts

Cyanobacterial crude extracts, rich in phycobiliproteins, were prepared using a phosphate buffer, following the method described by Bounnit et al. [10]. The harvested biomass from each of the three cyanobacteria strains was suspended in a phosphate buffer solution at a concentration of 10 mg mL⁻¹. The biomass was thoroughly homogenized using continuous agitation until complete disruption of the cells was achieved. The homogenized samples were stored at − 80 °C for 24 h, then, transferred to 4 °C for another 24 h. The mixture was centrifuged at 4500 rpm for 10 min to separate the cellular debris from the supernatant. The supernatant, containing the crude extract, was collected. This extraction process was repeated three times on the same biomass to maximize the yield of phycobiliproteins. The combined supernatants were then stored at − 80 °C before being freeze-dried for use in subsequent experiments.

Furthermore, the cyanobacterial extracts obtained were analyzed by spectral scan between 300 and 900 nm using a UV–Vis spectrophotometer (Synergy H4 Hybrid Multi-Mode Microplate Reader, Bio-Tek, Winooski, VT, USA) to determine the key components present in the extracts.

Characterization of biosorbent materials

Several analytical techniques were employed to characterize the biosorbent materials derived from the cyanobacteria strains. Transmission Electron Microscopy (TEM) (Quantachrome Corporation, Nova 3000, Oregon, US) was designated to illustrate the morphological structure and elemental composition of the biosorbents, following the protocol outlined by Masmoudi et al. [32]. This provided detailed insights into the surface characteristics and potential interaction sites for nickel ions.

Fourier Transform Infrared Spectroscopy (FTIR) (SHIMADZU-IRSpirit, Germany) was conducted in the range of 400–4000 cm⁻¹ to identify the functional groups present on the biosorbent surfaces, which are likely involved in the biosorption process. Additionally, the specific surface area of the biomass was assessed using the Brunauer–Emmett–Teller (BET) method (Quantachrome Corporation, Nova 3000, Oregon, US), which provided essential information on the surface properties and porosity of the cyanobacterial biomass.

Batch experiment for Ni²⁺ biosorption

Batch adsorption experiments were conducted to evaluate the Ni²⁺ biosorption capacity of the cyanobacterial biomass and extracts. Each experiment was carried out in 25 mL glass bottles containing 20 mL of a 10 mg L⁻¹ nickel chloride hexahydrate (NiCl₂·6H₂O) solution. This concentration has been selected based on previous studies conducted on Ni²⁺ biosorption [6, 21, 31].

To investigate the effect of pH on the biosorption process, the pH of the solution was adjusted to various levels (2, 4, 6, 8, and 10) using 0.1 M NaOH or 0.1 M HCl. A precise amount (0.02 g) of each biosorbent (either cyanobacterial biomass or extract) was added to the solutions, and the mixtures were continuously shaken at 165 rpm for 24 h at room temperature using a Brunswick Innova^® 2100/2150 shaker (New Jersey, USA). The 24-h duration was selected to maximize the biosorption effect and to evaluate the performance of the cyanobacterial biomass and extracts in binding with nickel, ensuring sufficient time for optimal sorption capacity. After the incubation period, the samples were centrifuged at 5000 rpm for 10 min to separate the biosorbent from the solution. The supernatant was analyzed for residual Ni²⁺ ions using Inductively Coupled Plasma-Optical Emission Spectroscopy (ICP-OES).

The biosorbent material that showed the higher Ni²⁺ removal efficiency and the best biosorption characteristics including surface area, morphological structure, and functional groups (Chroccoccidiopsis sp. QUCCCM26 biomass), was selected to study the effect of initial Ni²⁺ concentration variation. Once the optimal pH was revealed (pH6), the Ni²⁺ concentration variation (5, 10, 20, 25, 30, 35, 40, 45, and 50 mg L⁻¹) was considered at that pH. The temperature was specifically set at 37 °C to mimic human physiological temperatures, thus providing a relevant insight into biosorbent’s potential in biomedical applications. Two replicates for each solution were performed. The percentage of removal efficiency and the sorption capacity per mass unit of the biosorbent were calculated using the following Eqs. (3), and (4) respectively:

$$Removal\, efficiency \left(\%\right)=\frac{{C}_{i-}{C}_{f}}{{C}_{i}}*100$$

(3)

$$Sorption\, Capacity \left(\frac{mg}{g}\right)= \left({C}_{i}-{C}_{f}\right)*\frac{V}{w}$$

(4)

where C_i is Ni²⁺ initial concentration within the solution (mg L⁻¹), C_f is Ni²⁺ final equilibrium concentration in the solution (mg L⁻¹, V is the volume of the solution (L), w is microalgae biomass/extract dry weight (g).

A schematic illustration of the batch experiment procedure is provided in the supplementary material (Fig. 1).

Fig. 1

Growth properties of the three cyanobacterial strains: (a) Growth rate and (b) Biomass productivity (* p < 0.05, ** p < 0.01)

Modeling of Ni²⁺ biosorption at equilibrium

Adsorption isotherms are mathematical models employed to describe the association between the amount of adsorbed substance onto a solid surface in aqueous solution and the concentration of that substance at equilibrium [2]. These isotherms are used to characterize the adsorption process under constant temperature and pH. The commonly adopted models in the context of microalgal biomass as an adsorbent are Langmuir and Freundlich isotherms, which are used mainly in mono-component systems [8]. Furthermore, Dubinin-Radushkevich (D-R) and Temkin isotherms were used to provide a more nuanced understanding of the adsorption characteristics and mechanisms of microalgae, highlighting surface heterogeneity and adsorbate interactions [38].

Freundlich isotherm

This model assumes the heterogeneity of the adsorbent surface, and it is centered around the formation of a multilayer of adsorbate molecules on the adsorbent’s surface (without considering the binding site saturation) [30, 38]. It is written as follows (5):

$$\mathit{Ln}\,{q}_{e}=\mathit{Ln}\,{K}_{f}+\frac{1}{n}Ln{C}_{e }$$

(5)

where q_e is the amount of absorbed substance, C_e is the concentration of the substance in solution (after the adsorption process), K_f value is the Freundlich constant that indicates the absorption capacity result of a biosorbent. n is the degree of non-linearity.

Langmuir isotherm

This model presumes the uniform sorbent surface (homogeneous binding sites); however, it is also used to assess the adsorptive behavior of various adsorbents [30]. It is predicated on the assumption of monolayer adsorption of the adsorbate on the adsorbent’s surface. Its Eq. (6) is as follows:

$$\frac{{C}_{e}}{{q}_{e}}=\frac{1}{{q}_{m }b}+\frac{{C}_{e}}{{q}_{m}}$$

(6)

where C_e is the concentration of adsorbate at equilibrium, q_e is the amount of adsorbate at equilibrium, q_m is the maximum adsorption capacity, and b is the Langmuir constant.

Dubinin-radushkevich isotherm

It is basically a three-parameter extension of the Langmuir model. It reflects the heterogeneity of the binding surface as its value varies from 0 to 1. This model assumes a multilayer character, implicating Van der Waal's forces and it can be utilized to describe the physical adsorption process. It is used to differentiate between the implicated metal adsorption mechanisms whether physical or chemical [2]. Its Eq. (7) is written as follows,

$$Ln{q}_{e }= Ln{q}_{s}-K {\varepsilon }^{2}$$

(7)

where q_e is the amount of adsorbate at equilibrium, q_s represents the isotherm saturation capacity, K is the constant of adsorption energy, and ɛ is a constant of the D-R model.

Temkin isotherm

In contrast to the Langmuir isotherm model, which assumes a constant heat of adsorption, Temkin isotherm suggests that the heat of adsorption of a molecule on the surface decreases linearly with increasing coverage of the biosorbent surface [30]. Its Eq. (8) is given as follows:

$${q}_{e}=BLn{A}_{T}+BLn{C}_{e}$$

(8)

where q_e is the amount of adsorbate adsorbed per unit mass of adsorbent, C_e is the adsorbate’s concentration at equilibrium, B is the isotherm constant of Temkin associated with the adsorption heat, and A_T is the Temkin binding constant at equilibrium.

Chi-square test

The Chi-Square (χ²) statistical test provides a quantitative measure to assess the goodness of fit of theoretical isotherm models to experimental data, ultimately aiding in understanding and optimizing the adsorption process. The model with the lowest χ² value is typically considered the most suitable for describing the adsorption system. χ² Eq. (9) is written as follows [1]:

$${\chi }^{2}= \sum\frac{{\left({q}_{e-}{q}_{mod}\right)}^{2}}{{q}_{mod}}$$

(9)

where q_e is the equilibrium adsorption capacity (mg g⁻¹) from the experimental data, q_mod is the adsorption capacity (mg g⁻¹) calculated from the isotherm models.

Results and discussion

Assessment of the growth properties of the three cyanobacterial strains

The Cyanobacteria strains Euhalothece sp. QUCCCM77, Halospira sp. QUCCCM155, and Chroococcidiopsis sp. QUCCCM26 were assessed in terms of growth rate and biomass productivity (Fig. 1) to understand their potential for large-scale biomass production.

As shown in Fig. 1a, Euhalothece sp. QUCCCM77 presented the highest growth rate of 0.155 ± 0.007 day⁻¹ followed by Halospira sp. QUCCCM155 (0.13 ± 0.03 day⁻¹). While Chroococcidiopsis sp. QUCCCM26 showed a slow growth rate of 0.08 ± 0.01 day⁻¹. However, Euhalothece sp. QUCCCM77 presented an interesting biomass productivity of 122.14 mg L⁻¹ day⁻¹, significantly higher than those recorded for Halospira sp. QUCCCM155 (37.50 mg L⁻¹ day⁻¹) and Chroococcidiopsis sp. QUCCCM26 (36.71 mg L⁻¹ day⁻¹) (Fig. 1b).

In previous study conducted by Bounnit et al. [10], the biomass productivity of four cyanobacteria strains was assessed. Their results were in roughly similar range as our findings, the maximum biomass productivity was recorded at 125 ± 1.1 mg L⁻¹ day⁻¹ for Pleurocapsa sp. at 30 ℃ and 40 ppt. However, under the same conditions, Euhalothece sp. showed a biomass productivity of 45 ± 1 mg L⁻¹ day⁻¹.

In our study Euhalothece sp. QUCCCM77 exhibited the highest growth rate and biomass productivity, indicating its strength and potential for industrial applications. This superior performance could be linked to the strain's adaptability to the provided culture conditions, such as high light intensity and CO₂ concentration, which are known to enhance the growth of phototrophic organisms [10]. In contrast, the lower growth rates observed for Halospira sp. QUCCCM155 and Chroococcidiopsis sp. QUCCCM26 might be attributed to their specific physiological needs and sensitivity to the culture conditions. While Chroococcidiopsis sp. QUCCCM26 exhibited the highest biosorption capacity due to its balanced surface area and porosity, Euhalothece sp. QUCCCM77 demonstrated a superior growth rate and biomass productivity, making it advantageous for large-scale applications. Halospira sp. QUCCCM155, though less efficient in biosorption, possesses unique structural characteristics, such as tubular morphology, which could support targeted pollutant interactions.

The variability in growth rates among the strains highlights the importance of optimizing cultivation parameters to maximize biomass yield, which is crucial for scaling up biosorption applications. These findings align with previous studies, suggesting that the growth environment plays a critical role in determining the biomass yield and, consequently, the biosorption efficiency of cyanobacteria [40].

Investigation of the phycobiliproteins in the cyanobacteria’s aqueous extracts

In Fig. 2, the photos of different cyanobacteria biomass and their corresponding liquid and dried extracts (Fig. 2a–i) were represented. According to Fig. 2j, the spectral scan analysis evidenced distinct differences in the phycobiliproteins content of the three different cyanobacteria strains. The results proved that Euhalothece sp. QUCCCM77, presented phycocyanin and allophycocyanin, with peak absorbance at 620 and 660 nm, respectively. In contrast, the extract from Halospira sp. QUCCCM155 predominantly exhibited only phycocyanin. Furthermore, the analysis of Chroococcidiopsis sp. QUCCCM26 revealed a notable peak corresponding to phycoerythrin at 560 nm and a slight peak of phycocyanin, which gives the purple color of the QUCCCM26 extract. These results align with the absorbance ranges of phycobiliproteins suggested by Kovaleski et al. [29], which attribute the spectral regions of 610–625 nm to Phycocyanin, 650–660 nm to Allophycocyanin, and 490–570 nm to Phycoerythrin.

Fig. 2

a–i Photos of different biomass and their corresponding liquid and dried extracts respectively. (j) Uv–vis Spectra of aqueous extracts obtained from cyanobacteria strains

The presence of these pigments is significant because phycobiliproteins, such as phycoerythrin and phycocyanin, have been reported to exhibit an antioxidant property, which could enhance the biosorption capacity of the cyanobacteria by stabilizing reactive metal ions [29].

Characterization of the cyanobacterial biomass and extracts

TEM characterization

The morphological characterization of the three selected cyanobacteria was performed first using light microscopy (Fig. 3a–c), Euhalothece sp. QUCCCM77 cells presented spherical to ovoid cells, with a 2–3 µm diameter. However, Halospira sp. QUCCCM155 strain is a spiral filamentous cyanobacterium, containing non-separated cells after division. The length of the entire thread could attain 500 µm. Chroococcidiopsis sp. QUCCCM26 are agglomerated spherical cells with a diameter of 4 µm for the single cell.

Fig. 3

Morphological characterization of cyanobacterial strains. a–f before Ni²⁺ biosorption, (a–c) under a light microscope (100X), d–f TEM images. g–i TEM images after Ni²⁺ biosorption at different magnifications

This figure also shows the TEM images of the three cyanobacterial strains (QUCCCM77, QUCCCM155, QUCCCM26) performed before (d, e, f) and after (g, h, i) Ni²⁺ biosorption respectively, permitted the visualization of sample structure changes. QUCCCM77 strain showed a deposit of Ni particles (circled red) on the top of the biomass (Fig. 3g) compared to the unloaded biomass (Fig. 3d). However, the QCCCM155 biomass was demonstrated more organized with tubular-shaped structures (blue arrow) (Fig. 3h) compared to the unloaded one (Fig. 3e). In addition, dark dots designated by the red circle could indicate the presence of Ni²⁺ on the cell surface. Figure 3i, evidenced clear changes in the structure of strain QUCCCM26 after contact with Ni²⁺ compared to the control, (before Ni²⁺ biosorption, Fig. 3f). It illustrates an extreme organization of biomass in thin superimposed layers (green arrow). Moreover, the tube-like morphology is clearly shown (blue arrows), trapping Ni²⁺ in between them (red circles) shown in Fig. 3i.

TEM analysis provided detailed insights into the morphological features of the cyanobacterial strains before and after Ni²⁺ biosorption. The observed deposition of Ni²⁺ particles on the surface of QUCCCM77 suggests that the strain’s cell surface characteristics play a significant role in its biosorption capacity. This finding is consistent with the theory that microalgae with higher surface area and specific surface characteristics, such as tubular or layered structures, exhibit enhanced metal-binding capabilities due to the increased availability of binding sites [41]. These structural features are crucial for understanding the mechanisms of metal uptake and for optimizing the biomass for enhanced biosorption efficiency. For instance, the layered structures observed in QUCCCM26 biomass might contribute to trapping Ni²⁺ ions through physical adsorption and complexation processes, which could provide a high adsorption capacity to this strain.

BET characterization

BET analysis was performed to determine the surface properties of the biomass, providing essential information related to their surface area and porosity. Results evidenced an interesting surface area ranging from 6.746 to 10.116 m² g⁻¹ (Table 1). Among the analyzed strains, Euhalothece sp. QUCCCM77 showed the highest surface area followed by Chroccoccidiopsis sp. QUCCCM26 then Halospira sp. QUCCCM155. Interestingly, such a surface area range is 5–17 times greater than other cyanobacteria biomass (Aphanothece sp.) studied by Satya et al. [41], revealing a surface area in the range of 0.57–1.84 m² g⁻¹. Regarding the pore volume (Table 1), Euhalothece sp. QUCCCM77 was roughly 1.25 and 1.5 times smaller than Chroccoccidiopsis sp. QUCCCM26 and Halospira sp. QUCCCM155 respectively. Moreover, the size of Chroccoccidiopsis sp. QUCCCM26 and Halospira sp. QUCCCM155 pores were found approximately similar and twice as high as Euhalothece sp. QUCCCM77 pores. According to that finding, Chroccoccidiopsis sp. QUCCCM26 was selected for further biosorption studies due to its balanced surface area and porosity, which are critical for achieving efficient biosorption while maintaining structural integrity during the process [20].

Table 1 Surface area characteristics of cyanobacterial biomass from BET analysis

FTIR characterization

Through the FTIR spectra pattern, different algal biomasses (Euhalothece sp. QUCCCM77, Halospira sp. QUCCCM155, Chroccoccidiopsis sp. QUCCCM26) and their corresponding extracts were characterized for their functional group compositions before and after Ni²⁺ biosorption (Fig. 4).

Fig. 4

FTIR spectra of the biomass and extracts before and after Ni²⁺ sorption. a Euhalothece sp. QUCCC77, b Halospira sp. QUCCCM155, c Chroccoccidiopsis sp. QUCCC26

The biomass of algal origin is composed of carbohydrates including cellulose; hemicellulose; and starch, lipids rich in fatty acids, proteins, minerals, water, and a lot of other compounds possessing diverse and specific functional groups [18]. The utilization of FTIR spectroscopy for the analysis of algal biomass has proven valuable in the assessment and tracking of complex chemical substances of microalgae cells.

The results presented in Fig. 4 showed the presence of nine distinct peaks for each strain, indicating similar organic groups with a slight variation in the contents. The bands at 3259, 3277, and 3282 cm⁻¹ corresponding to the raw biomass and extracts of QUCCCM77 (Fig. 4a), QUCCCM155 (Fig. 4b), and QUCCCM26 (Fig. 4c) respectively are owing to the hydroxyl (O–H) and amine groups (N–H). This outcome aligns with those found in previous studies [42]. The bands at 2872, 2887, and 2922 cm⁻¹ were due to lipid band spectra related to the C–H stretching of hydrocarbons. This association with lipids was more intense in a previous study [43]. The weak peaks positioned at 2327 and 2340 cm⁻¹ could be assigned to adsorbed CO₂ [37]. Moreover, sharp peaks at 1621, 1630, and a stronger band at 1636 cm⁻¹ (strain QUCCCM26) are attributed to the amide I band, associated with C = O stretching vibrations in proteins, as supported by Ss & St, [42].

In addition, other less strong bands at 1529, 1533, and 1523 cm⁻¹ were observed due to the C = C stretching. Similarly, Ss & St, [42] indicated the presence of comparable absorbance bands in their microalgal isolates.

The Stretching vibrations at around 1400 cm⁻¹ could be assigned to N–H bonds of the protein amide group as well as C–H bending vibrations aligning with previous studies [17]. The peaks at 1278, 1268, and 1238 cm⁻¹ were observed respectively in QUCCM77, QUCCCM155, and QUCCM26 biomasses and could be typically associated with the asymmetric stretching vibrations of the phosphate groups (PO-2) found in the backbone of nucleic acids. Similarly, phosphate ester groups in phospholipids might be responsible for peaks in that area. The bands at 1031, 1037, and 1042 cm⁻¹ confirm the presence of C–O–C stretching vibration of polysaccharides (cellulose and starch) from carbohydrates, constituting an important component of microalgae cell composition [42]. Finally, at 867 cm⁻¹, C–H stretching vibrations could be indicative of specific aromatic and phenol structures [48].

The above-mentioned band spectra have illustrated the existence of the key components in microalgal biomass and extracts of the three strains, specifically lipids, proteins, and carbohydrates, which is in agreement with several previous studies [43]. According to Harun et al. [23], the lipid reference absorbance peaks in microalgae are in the range of∼2970–2850 cm⁻¹, which was well shown in our results, however, they were slightly more intense in the raw biomass than in their corresponding extracts. This could be explained by the presence of the phospholipidic membrane in the biomass samples and its absence in the aqueous extracts. The presence of polysaccharides mainly cellulose and starch in algal composition is well indicated at ∼1100–900 cm⁻¹ [43]. Their intensity was more seen in the algal extracts than in the biomass, especially in QUCCCM77 and QUCCCM155 strains, this might be due to the extraction method applied to the biomass. Regarding the carboxylic groups represented by the peaks at ∼3250–3280 cm⁻¹, they were similar in both algal biomass and extracts. The proteins reported in the absorbance range of 1750–1500 cm⁻¹ indicated a very small variation in the intensity of peaks, however, at ∼860 a significant difference in the peak intensity was observed between the biomass and their corresponding extracts for all strains. This could be explained by the extract-richness in phenols and phycobiliproteins such as Phycocyanin in QUCCCM155, induced by the aqueous extraction. Phycobiliproteins are water-soluble proteins found in cyanobacteria strains composed of amino acids like tyrosine, some of which contain aromatic rings [29].

The existence of this variety of functional groups (Hydroxy, carboxyl, carbonyl, amine, and phosphate could be advantageous for nickel ions biosorption [43]. In order to investigate the individual functional groups involved in Ni²⁺ biosorption, FTIR spectra of algal biomass were recorded after exposure to Ni²⁺ ions and compared to the peaks obtained from Ni²⁺-unloaded biomass. It is apparent that the three algal biomasses (QUCCCM77, QUCCCM155, and QUCCCM26) were efficient in Ni²⁺ adsorption.

The FTIR spectra of Ni²⁺-loaded biomass revealed significant shifts in key functional groups, highlighting their role in the biosorption process. For instance, the peak at 1636 cm⁻¹, corresponding to the amide I band (C = O stretching in proteins), exhibited a slight shift and reduction in intensity, indicating its involvement in nickel binding. Similarly, the band at 1400 cm⁻¹, associated with N–H bending and C–H bending vibrations, showed increased intensity after Ni sorption, suggesting strong interactions between nickel ions and protein-related functional groups [27]. Additionally, the broadening of the O–H stretching band at 3282 cm⁻¹ confirmed the participation of hydroxyl groups in complexation. These spectral changes underscore the role of carboxyl, amide, and hydroxyl groups in facilitating the adsorption of Ni²⁺ ions onto the biomass surface.

As an example, the shifting and changes in the FTIR peaks of QUCCM26 biomass after Ni²⁺ sorption were represented in Table 2.

Table 2 Shifting and changes of FTIR band positions of QUCCC26 biomass before and after Ni²⁺ biosorption

From that table, it is clear that the peaks at 1400 and 1539 cm⁻¹ were more intense after the Ni²⁺ sorption process, which denotes evidence of nickel ions binding onto the cyanobacterial biomass. This shifting in the intensity of the peaks indicates the key role of the corresponding groups (–C = C, –N–H, –C–H) in the binding of Ni²⁺ ions in the liquid–solid phase.

As well, the degree of shifting can further provide valuable insights into the biosorption mechanisms and the functional groups involved in the process. These changes reflect the degree of differential interaction advocated between the functional groups of the biosorbent and the adsorbed Ni²⁺ ions. Among changes, the shift of 469 cm⁻¹ peak to 516 cm⁻¹ suggests the involvement of oxygen in forming a bond with nickel (Ni–O) [20]. The significant shifting (47) in this peak position could describe a chemisorption mechanism, where strong covalent bonds and ionic interactions are formed between the functional group (–O–H) and nickel ions.

A significant shift in the absorption peaks after Ni²⁺ biosorption confirms the important role played by the functional groups on the surface of QUCCCM26 biomass allowing its interaction with Ni²⁺ molecules. These shifts approved the involvement of the functional groups present on the cyanobacterial biomass in the biosorption process of Ni²⁺ ions.

As a result, the key functional groups involved in the process include methyl, amide, carbonyl, phosphate, and carboxyl groups. However, carboxyl groups (-COOH) found in the amino acids of proteins and provided to the metal ions represent a major part of the cyanobacterial cell wall and intracellular structure [27]. The complexation of nickel ions with carboxylic groups can take several patterns, depending on factors such as pH and the initial concentration of Ni²⁺, where the metal ion forms a coordinate covalent bond with a pair of electrons from the oxygen atom [27]. Some specific scenarios, monodentate complexation (a single carboxylic group binds with a nickel ion), and Bidentate chelation (two carboxylic groups from a single molecule can bind to the same nickel ion, creating a ring structure) are illustrated in the supplementary material (Fig. 2).

Effect of pH on Ni²⁺ removal

It is indicated that the pH level is the most critical factor influencing nickel ions removal from the aqueous solutions. This could be due to the modification of the adsorbent’s surface charges as well as changes in the adsorbate chemical speciation [9]. Furthermore, at low pH the surface of the sorbents is able to take up more hydrogen ions (H⁺), decreasing probable Ni²⁺ binding to the cell surface [9]. Conversely, at higher pH (alkaline conditions), nickel compounds tend to precipitate forming complexes with hydroxide ions such as Ni(OH)₂, leading to reduced concentration of free nickel ions. The Ni²⁺ removal efficiencies of the cyanobacterial biomass and extracts according to the pH of the solutions are shown in Fig. 5a.

Fig. 5

a Effect of pH solution on the removal efficiency of Ni²⁺ (0.02 g Biomass/extract; 10 mg L⁻¹ initial NiCl₂ concentration; room temperature; 165 rpm agitation speed; 24 h contact time). b, c Effect of Ni²⁺ initial concentration on the removal efficiency b and adsorption capacities c of QUCCCM26 biomass. Experimental conditions: initial concentrations 5–50 mg L⁻¹; mass of adsorbent 0.02 g; volume of Ni²⁺ solution 20 mL; pH 6; temperature 37 °C and contact time of 24 h

It is clear that all biosorbent materials showed a potential to remove Ni²⁺ in solution, with more elevated values in the biomass than the extracts. This difference could be due to the variations in the availability and ionization of functional groups. Biomass contains a diverse array of surface functional groups, embedded in the cell wall, providing abundant binding sites and structural stability for nickel ions. In contrast, aqueous extracts, composed mainly of soluble biomolecules, offer fewer binding sites, which explains their low performance compared to biomass [43].

At pH 2 there is no removal of Ni²⁺ for all biomass and extracts. On the other hand, at higher pH, the removal efficiency increased showing around 30% of removal in QUCCCM155 and QUCCCM26 biomass at pH range from 4 to 10. Likewise, QUCCCM77 showed the same efficiency removal at pH 6 and less than 25% at pH 10. Nevertheless, at pH 8 and 4, the rate of Ni²⁺ removal of this biomass (QUCCCM77) was very low to nonexistent respectively.

This finding is consistent with the literature, where the optimum sorption of metal ions, such as Pb²⁺, Cd²⁺, Cu²⁺, and Ni²⁺ befall within the pH range of 4 to 6 [43, 48]. This was explained by the fact that in this range of pH the cell’s functional groups, like carboxyl groups, quickly release their protons into the solution, turning into anionic forms, which enhances metal binding [30]. At lower pH levels, the protonation of these functional groups reduces the availability of binding sites for metal ions, leading to decreased adsorption efficiency. The results also align with the observations of other researchers, who have reported similar trends in the pH-dependent biosorption of heavy metals, including nickel [47]. Accordingly, the pH of 6 has been revealed as the optimal value for subsequent experiments, ensuring that the biosorption process operates under conditions that maximize the removal efficiency of Ni²⁺ ions.

Effect of initial Ni²⁺ concentration

The effect of the initial concentration of nickel on the adsorption process was examined in this study. Figure 5b, showed an increase in the removal efficiency with increasing Ni²⁺ concentration, reaching 58.16 ± 0.3% at 20 mg L⁻¹ of initial Ni²⁺ concentration. From 25 mg L⁻¹, the removal efficiency decreased gradually attaining 36.38 ± 0.57% at 50 mg L⁻¹ of initial Ni²⁺ concentration.

The consistent pattern observed was a result of the presence of available sites on the adsorbent’s surface. However, as the concentration of Ni²⁺ increased, the number of available sites on the adsorbent's surface decreased, leading to a corresponding decrease in the Ni²⁺ removal.

Similarly, the experimental adsorption capacity of QUCCCM26 biomass was increased with the increase of the initial concentration of nickel, starting from 2.08 ± 0.1 mg g⁻¹ at 5 mg L⁻¹ of initial Ni²⁺ concentration, reaching its maximum of 18.19 mg g⁻¹ at 50 mg L⁻¹ of initial Ni²⁺ concentration (Fig. 5c). Generally, increased initial concentrations of metal lead to an enhancement in the biosorption capacity. This is due to the improved driving force provided by the greater concentration, which helps to exceed the mass transfer resistance encountered between the biosorbent and the biosorption medium.

The maximum nickel adsorption capacity (Qmax) of QUCCCM26 biomass in our study was determined to be 71.43 mg g⁻¹, as calculated from the Langmuir model. This compares with higher capacities reported in other studies, with results ranging from 81.2 mg g⁻¹ to 133.45 mg g⁻¹ [33, 44, 46]. However, in the other reported studies, the adsorption capacity of Ni²⁺ was found to be lower than the current study result. They showed values ranging from 16.43 mg g⁻¹ to 62.45 mg g⁻¹ [6, 21, 31]. Distinct experimental conditions (temperature settings, pH levels, and the initial concentration of the adsorbate) were employed in every study. These elements collectively influence the ultimate capacity for nickel ion adsorption. Moreover, different types of algal biomass used in those studies present their own intracellular and cell wall composition, which could provide various arrays of ligands and functional groups capable of Ni²⁺ binding. Furthermore, the differences in the adsorption capacity might be related to the mechanisms involved in the binding of the metal ions [46].

Adsorption isotherms

The experimental data (equilibrium concentration of Ni²⁺ and the maximum experimental adsorption capacity) were adjusted to Langmuir, Freundlich, Temkin, and Dubinin-Radushkevich (D-R) models to better understand the adsorption interactions and mechanisms of nickel ions on the surface of QUCCCM26 biomass. In Fig. 6, the biosorption isotherms of Ni²⁺ are represented, whereas Table 3 reports their corresponding parameters.

Fig. 6

Ni²⁺ Adsorption isotherms of Chroococcidiopsis sp. QUCCCM26 biomass

Table 3 Isotherm model parameters of Nickel biosorption on Chroococcidiopsis sp. QUCCCM26 biomass at pH 6 and 37 °C

According to the coefficient of correlation (R²), it can be noted that the best adjustment was following the order below: Freundlich > Langmuir > Temkin > D-R, indicating the R² values of 0.993, 0.956, 0.923, and 0.635, respectively. Thus, the experimental data aligned remarkably well with the Freundlich isotherm model evidenced by R² of 0.993. This fit suggests that the adsorption of nickel ions occurs heterogeneously with varying adsorption energies, onto the active sites of QUCCCM26 biomass distributed in an exponential manner, which supports the notion of multilayer adsorption [38].

Concurrently, the Langmuir isotherm model also demonstrated a strong fit to our results, with an R² of 0.956, indicating that the Langmuir model's assumptions of uniform adsorption sites and monolayer coverage provide a considerable estimate of the adsorption process. The commendable fit of both models suggests complex adsorption mechanisms that can involve both homogenous and heterogeneous interactions. The Freundlich isotherm mainly illustrates the adsorption-complexation reactions during the adsorption process, however, the Langmuir isotherm reports the dominance of the ion exchange mechanism.

Supporting the interpretation of our data, the graphical plots of both Freundlich and Langmuir models, as demonstrated in Fig. 6, can be distinctly divided into two segments, labeled I and II. Segment I suggests the occurrence of monolayer binding, where Ni²⁺ ions adhere directly to the available sites on the biomass surface, which aligns well with the Langmuir model's assumption of uniform adsorption sites, indicating efficient monolayer coverage by Ni²⁺ ions [2]. On the other hand, segment II reveals a layering effect, where additional Ni²⁺ ions transmigrate in the plane of the surface and attach on the top of the initial monolayer absorbate, forming a multilayer as predicted by the Freundlich model [38]. This transition from monolayer to multilayer adsorption highlights the complexity of the Ni²⁺ sorption process on the cyanobacterial biomass, suggesting the simultaneous involvement of different adsorption mechanisms. Accordingly, the distinction of segments (I and II) within the plots not only validates the applicability of both isotherm models but also emphasizes the assumption of a heterogeneous adsorption process.

Based on the Langmuir isotherm parameters, the maximum Ni²⁺ biosorption capacity (Q_max) of algal biomass was found to be 71.43 mg g⁻¹, indicating a large difference compared to the experimental biosorption capacity (18.19 mg g⁻¹). This difference could confirm the best fit to the Freundlich isotherm model enlightening the low value of the Langmuir constant (b). It indicates that the Freundlich model is more appropriate for describing the biosorption process in this case.

The high correlation for the Langmuir model reinforces its relevance in describing certain aspects of the adsorption phenomena we observed, highlighting the versatility and efficacy of our cyanobacterial biomass in nickel ion removal through potentially multiple adsorptive interactions. Similar findings were obtained by Pham et al. [36], indicating that Ni²⁺ sorption using Hizikia fusiformis biomass fitted also to the Freundlich isotherm model.

From Freundlich parameters, a higher value of K_F typically indicates a greater adsorption intensity associated with chemosorption, suggesting that the QUCCCM26 biomass is effective at adsorbing Ni²⁺ from the solution. It was roughly 4 times higher than 0.54 L g⁻¹ found by Tabaraki & Nateghi, [44], which was considered potentially high but less readily sorbed than Zn²⁺. Additionally, the coefficient (n) related to the adsorption favorability or intensity of Ni²⁺ sorption on the biomass surface was superior to 1 (1.65), indicating favorable adsorption conditions [24]. This value was comparable to 1.597 obtained by Guarín-Romero et al. [21] and considered favorable. The value of less than 1 of 1/n confirms the Ni²⁺ adsorption favorability process indicated by the parameter n [9].

From the Temkin model, the binding constant (A_T) and the sorption heat (B) were calculated. A low value of A_T indicates an unconformity to the Temkin model, which suggests the linearity of biosorption energy decrease rather than the exponential and non-uniform distribution of heat as implied by Freundlich isotherm [26, 28]. While B (J mol⁻¹), found lower than 20 kJ mol⁻¹, describes the existence of a physisorption process, which occurs due to weak Van der Waals interactions operating over a long range between Ni²⁺ ions and the biomass surface [44]. The parameters of the D-R model were not analyzed due to the low correlation coefficient of the model which indicates its poor fit with the experimental data.

The chi-square (χ²) test has been introduced to validate the suitability of the best isotherm model in the description of the biosorption process since R² values of Langmuir and Freundlich isotherms were convergent [3]. As can be seen in Table 3, the χ² attributed to the Freundlich model was at 6.476, which was lower than χ² of 55.392 calculated for the Langmuir isotherm. This result supports the R² assumption indicating the fitness of the experimental data to the Freundlich model, which ensures that the biosorption of Ni²⁺ on the surface of the biomass follows a heterogeneous adsorption process with a multilayer behavior. Notably, the Temkin model registers the lowest χ² value (2.756) among the three models. This superior fit to experimental data implies a significant correlation with the actual adsorption behavior, potentially indicating the influence of adsorbate-adsorbent interactions and the heat of adsorption on the sorption process [30]. This advocates indirectly the Freundlich model's assumption of surface heterogeneity, by considering the variability in adsorption energy and interactions in the same way as the Freundlich model. Therefore, the suitability of the Temkin model can be perceived as complementary, providing insights into the energetic aspects of the biosorption process that also emphasize the validity of the Freundlich assumptions regarding the surface heterogeneity of the biomass surface and the potential for multilayer adsorption.

The successful application of the Freundlich model suggests that Chroococcidiopsis sp. QUCCCM26 can effectively adsorb Ni²⁺ ions through a complex process influenced by surface heterogeneity and the presence of multiple binding sites. These findings are significant for the development of biosorption systems able to reduce nickel ions' bioavailability and prevent their lung carcinogenic risk.

Beyond nickel, cyanobacterial biomass has demonstrated significant potential for the biosorption of other toxic heavy metals, such as cadmium, lead, and chromium, as well as organic pollutants including dyes and pharmaceutical residues. The efficiency of cyanobacteria in adsorbing a wide range of toxic pollutants stems from their diverse surface functional groups, such as carboxyl, hydroxyl, and amine groups, which facilitate strong interactions with various contaminants [47].

Adsorption mechanisms

The cyanobacterial cell wall has a specific chemical composition that plays a pivotal role in heavy metal adsorption mechanisms. It is primarily made of polysaccharides, proteins, and lipids, as well as a complex structure of superposed layers with a unique array of molecular functional groups, offering a plethora of active sites for the attachment of metals [25]. These functional groups undergo deprotonation and bind the ionic metals such as nickel, resulting in the formation of a metal–ligand surface complex. Specifically, a thick layer of peptidoglycan polymer containing N-acetylglucosamine and ß 1,4-N-acetylmuramic acid offers primarily carboxylic groups for metal biosorption and displays higher levels of cross-linking among other polysaccharides [27]. Moreover, several cyanobacteria strains are able to produce extracellular polymeric substances (EPS) of which approximately 80% account for polysaccharides and proteins [14]. EPS contains mainly uronic acid, they are strong anions due to their diverse functional groups like hydroxyl, carboxylic, phosphoryl, and sulfhydryl, which contribute significantly to their high affinity to metal ions [35].

Given the complexity of the cyanobacterial cell wall composition, a multitude of mechanisms could be involved in nickel biosorption. Commonly, as a cationic metal ion, Ni²⁺ can bind to the cyanobacterial cell surface via electrostatic attraction force, ion exchange, precipitation, and complexation processes [50]. However, metal ion exchange with calcium, magnesium, potassium, or sodium, as well as complex formation with functional groups existing on the surface of the cell are the major mechanisms implicated in nickel sorption [13]. These mechanisms could occur simultaneously at different rates, they are influenced by various physicochemical factors including the nature of biomass and the surrounding conditions (pH, temperature, the concentration of metal ions…) and represented in a supplementary material (Fig. 3).

The FTIR analysis provided evidence for the involvement of functional groups such as hydroxyl, amine, and carboxyl in binding Ni²⁺ ions, which supports the hypothesis that both physical and chemical adsorption mechanisms are at play [47].

The shifts observed in the FTIR spectra, particularly the formation of Ni–O bonds, suggest that chemisorption plays a significant role in the biosorption process, where strong covalent bonds are formed between the biomass and metal ions [20]. This is further supported by the BET analysis, which indicates that the biomass's specific surface area and porosity contribute to the efficiency of the biosorption process by providing ample binding sites for metal ions.

The multi-faceted nature of the adsorption mechanisms underscores the complexity of the biosorption process and highlights the need for further studies to elucidate the specific interactions between metal ions and the biomass surface. This understanding is critical for optimizing biosorption systems and improving their efficiency for practical applications.

While this study focused on nickel biosorption, some limitations should be addressed in future research. These include the need to explore the biosorption potential of cyanobacterial biomass for a wider range of heavy metals and organic pollutants under varied environmental conditions. Refining biomass extraction methods, such as improving phycobiliprotein recovery, could also enhance biosorption efficiency. Furthermore, employing advanced analytical techniques, such as X-ray photoelectron spectroscopy or Raman spectroscopy, could provide deeper insights into the molecular interactions governing the biosorption process, paving the way for optimized biosorbent designs.

Conclusion

This study highlights the effective use of cyanobacteria, specifically Chroococcidiopsis sp. QUCCCM26, for the biosorption of nickel ions, with the goal of mitigating their carcinogenic impact. The biomass exhibited a higher Ni²⁺ removal efficiency compared to its corresponding extracts, achieving a removal efficiency of 58.16 ± 0.3% at an initial Ni²⁺ concentration of 20 mg L⁻¹ and reaching a maximum adsorption capacity of 18.19 mg g⁻¹ at 50 mg L⁻¹ under conditions mimicking human physiology (pH 6 and 37 °C).

The biosorption process was best described by the Freundlich isotherm model, indicating heterogeneous adsorption-complexation mechanisms. FTIR spectroscopy analysis further reveals that amide, carbonyl, phosphate, and carboxyl groups play crucial roles in nickel binding.

These findings underscore the potential of Chroococcidiopsis sp. QUCCCM26 as a natural and cost-effective biosorbent for reducing nickel bioavailability in the gastrointestinal tract, potentially preventing its accumulation in body tissues and offering a novel approach to nickel detoxification. This study highlights a promising direction for developing environmentally friendly and efficient methods for metal ion detoxification, which could contribute to enhancing public health safety against heavy metals toxicity.