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Journal of Applied Phycology

, Volume 31, Issue 1, pp 97–107 | Cite as

Effectiveness of Parachlorella kessleri cell disruption evaluated with the use of laser light scattering methods

  • Agata Piasecka
  • Jolanta Cieśla
  • Magdalena Koczańska
  • Izabela KrzemińskaEmail author
Open Access
Article

Abstract

The main objective of this study is to demonstrate the possibilities of using laser light scattering methods, dynamic light scattering and laser Doppler electrophoresis, as suitable methods in investigations of algal production biosystems and biotechnology. This paper highlights the innovative use of the dynamic light scattering (DLS) methods for monitoring the destruction of Parachlorella kessleri cells. Additionally, these results indicate electrophoretic mobility as a new parameter to investigate the effectiveness of cell disruption prior to extraction conducted to optimise the biotechnological processes of recovery of microalgal intracellular metabolites. The efficacy of P. kessleri cell disintegration by ultrasound was determined by measurements of the number of cells with the algal cell reduction (CRns), relative mean hydrodynamic diameter (Rdt) and electrophoretic mobility after applying different lengths of ultrasound exposure to a cell suspension. It was found that stationary-phase cells were the most resistant to the ultrasound treatment, especially at low values of the optical density. Both the relative hydrodynamic diameter and the electrophoretic mobility of cells were correlated statistically significantly with the time of sonication (t) and the algal cell reduction. The relationships allowed estimation of the sonication time needed for total cell disruption.

Keywords

Parachlorella kessleri Laser light scattering methods Cell disruption Sonication 

Introduction

Laser light scattering methods can be used for particle characterisation. Light scattering has a broad spectrum of applications, e.g. in cosmology, meteorology, oceanography and nanotechnology, as evidenced in the large number of scientific papers. Laser light scattering methods are applied in biomolecules studies, especially in characterisation of physical and physicochemical properties of bacteria and viruses (Xu 2015; Cieśla et al. 2018).

Algal bioproduction processes are expanded in response to the rapidly increasing demand for medicines, dietary supplements and biofuels. Thus, the research efforts have focused especially on improving the biomass production and extraction of metabolites (Piasecka et al. 2014; García-Galán et al. 2018). Microalgae synthesise many valuable metabolites, e.g. pigments, carbohydrates, amino acids and fatty acids, which are attractive for commercial exploitation (Krzemińska et al. 2015a; Grudziński et al. 2016). Since these compounds are usually intracellularly located, cell disintegration prior to extraction thereof must be carried out (Postma et al. 2017). An effective process of microalgal cell disruption is one of the major challenges for the commercialisation of bioproducts from microalgae.

One of the more recent achievements in algal extraction technology has been the use of physical cell disruption method—ultrasonication; in many studies published today, it is one of the most effective cell disruption methods improving the extraction process (Prabakaran and Ravindran 2011; Zheng et al. 2011; Piasecka et al. 2014).

The destruction of cell walls and cell membranes contributes to the inactivation of the microorganisms and is the basis for the release of cellular contents to the environment. The method employed for cell disruption determines the quality and yields of the intracellular metabolites. The efficiencies of the cell wall disruption methods depend on cell wall strength (Joyce et al. 2014). The composition and structure of the microalgal cell wall varies among strains. The structure of the cell wall varies in the organisation with thickness depending on cell growth and cell division (Yamamoto et al. 2005). The construction of microalgal cell wall makes microalgae less permeable and resistant to extraction.

Parachlorella kessleri is a unicellular freshwater alga (Chlorophyta), which is extensively used for physiological and biochemical studies due to its ability to accumulate starch, lipid and protein and its biotechnological importance (Magierek and Krzemińska, 2017; Piasecka et al. 2017; Lv et al. 2018; Taleb et al. 2018). Depending on the sugar composition of the rigid cell wall, Chlorophyta species are divided into two groups: glucosamine type and glucose-mannose type. Parachlorella kessleri has glucosamine as the main sugar component of the rigid cell wall (Takeda 1991). Investigations conducted by Yamamoto et al. (2005) have shown that P. kessleri has an electron-transparent thick wall.

Many investigators have used different methods to measure cell disintegration after ultrasonication. These include the diffusion behaviour of proteins and pigments of Chlorella vulgaris in the aqueous phase (Safi et al. 2015), reductions in intact cell counts and reductions in average colony diameters (Halim et al. 2012), counting only intact cells with a haemocytometer (Greenly and Tester 2015), changes in the algal cell concentration, cell size, chlorophyll a fluorescence and Nile Red-stained lipid fluorescence (Wang et al. 2014) and cell disruption efficiency and lipid release (Natarajan et al. 2014).

Development of the method for measurement of algal cell lysis plays a key role in algal cell disruption and metabolites acquiring. Optical microscopy techniques are commonly used to evaluate the degree of cell disintegration. However, there have been no reports so far on the use of laser light scattering measurements in assessing the degree of algal cell degradation in a solution in laboratory practice.

The main objective of this study was to apply laser light scattering techniques in investigations of cell wall disruption to determine the efficacy of ultrasonic cell disruption. Additionally, the aim of this work was to assess the impact of sonication treatment on disruption of P. kessleri cells depending on the different physiological states of cells at different optical densities.

Material and methods

Microalgal strain and culture conditions

The axenic culture of Parachlorella kessleri (No. 250) was obtained from the Culture Collection of Autotrophic Organisms (CCALA) at Charles University in Prague. Cultivation of P. kessleri was carried out in a Kessler medium. The Kessler medium is composed (per litre distilled water) of 0.81 g KNO3, 0.47 g NaCl, 0.47 g NaH2PO4·2H2O, 0.36 g Na2HPO4·12H2O, 0.25 g MgSO4·7H2O, 0.014 g CaCl2·2H2O, 0.006 g FeSO4·7H2O, 0.0005 g MnCl2·4H2O, 0.0005 g H3BO3, 0.0002 g ZnSO4·7H2O, 0.00002 g (NH4)6Mo7O24·4H2O, and 0.008 g EDTA (Piasecka et al. 2017).

Cultivations were conducted in 500 mL Erlenmeyer flasks at 26 °C under continuous illumination (80 μmol photons m−2 s−1) with shaking (100 rpm) without aeration. The experiment was carried out in triplicate (n = 3).

Growth measurements and biomass determination

Growth was daily monitored (for 15 days) by measuring optical density at 650 nm (Krzemińska et al. 2015b). The biomass concentration was estimated by dry weight determination. Dilution series of the cell suspension were made and optical density (OD650) was measured. The cell suspension was filtered through a pre-weighted Whatman GF/C glass-fibre filter and dried at 90 °C for 24 h to constant weight. Based on the calibration curve, which showed the relationship between the optical density at 650 nm and the dry cell weight, the optical values were converted to dry weight by the following Eq. (1):
$$ \mathrm{Dry}\ \mathrm{cell}\ \mathrm{weight}\ \left(\mathrm{DCW}\right)=372.21\times {\mathrm{OD}}_{650}\hbox{--} 9.1591,{R}^2=0.9968. $$
(1)

Preparation for laser light scattering measurements

During the cultivation, 100 mL of culture were collected after 24, 96, 240, and 360 h. Each sample represented a different physiological state of P. kessleri cells (growth phases as follows, 24 h—Lag phase, 96 h—Log phase, 240 h—Decline phase, 360 h—Stationary phase). Sampling points were marked on the growth curve (Fig. 1). Cells were centrifuged (Rotanta 460 RS, centrifuge) and washed twice with filtered (Whatman Anodisc 0.02 μm) and distilled water (η = 1.0031 cP, n = 1.330). The microalgal cells were diluted using the abovementioned water to different cell densities (0.05, 0.075, and 0.15 value of optical density at 650 nm—a measuring range limited by the Zetasizer Nano ZS apparatus). The pH value of distilled water was 6.54 ± 0.02 at the measurement temperature. The microalgal cell suspension (10 mL) in 30-mL glass vials was treated by sonic waves for 10, 20, 30, 40, 50, 60, 90, 180, and 360 s (power 500 W, frequency 20 kHz and amplitude 50%) to disrupt the cells. Sonication was performed using a Sonics vibra cell 500 sonicator. Additionally, a non-sonicated sample was used as a control for each study to enable comparisons.
Fig. 1

Growth curve of P. kessleri (the results are presented as the means of nine measurements from n = 3, error bars represent standard deviation, sampling points are marked with empty dots)

Cell numbers

After each sonication treatment, the cells were counted under an OLIMPUS microscope with a Bürker haemocytometer (BLAUBRAND counting chambers) CE-marked according to IVD-Directive 98/79 EC.

Algal cell reduction

The algal cell reduction exhibited a decrease in cell viability as a percentage. The algal cell reduction was calculated using the following Eq. (2):
$$ {\mathrm{CR}}_{n\mathrm{s}}\ \left(\%\right)=100\hbox{--} \left(\left({\mathrm{CN}}_{n\mathrm{s}}\times 100\right)/{\mathrm{CN}}_{0\mathrm{s}}\right) $$
(2)
where:
CR ns

algal cell reduction after n seconds of sonication

CN ns

number of cells counted after n seconds of sonication

CN 0s

number of cells counted in the control sample without sonication

Determination of the particle size in algal dispersion

The dynamic light scattering (DLS) method was used for evaluation of the changes in the particle size after the application of ultrasounds to the algal dispersion. Measurements were performed using the Zetasizer Nano ZS apparatus (Malvern Ltd., UK) equipped with a He-Ne (633 nm) source of laser light. The non-invasive back scattering (NIBS) technique and phase analysis light scattering (PALS) were employed for determination of the diameter of the particles (Zetasizer Nano Series User Manual, 2004). Time-dependent fluctuations of the signal were the basis for the autocorrelation functionG2(τ), which decreases in the time range τ (Kaszuba et al. 2008; ISO 22412:2017):
$$ {G}_2\left(\tau \right)=A\left[1+B\exp \left(-2\Gamma \tau \right)\right], $$
(3)
where: A—constant, which is time-independent and proportional to the square of the mean intensity of scattered light, B—the apparatus coefficient (B ≤ 1) and Γ—speed of autocorrelation function decay, which for isotropic spherical particles are described by eq. (4):
$$ \Gamma ={Dq}^2, $$
(4)
where:
$$ q=\frac{4\pi n}{\lambda_0}\sin \left(\theta /2\right) $$
(5)
is a modulus of the scattering vector, n—refractive index of the dispersant, λ0—length of the laser beam wave in vacuum and θ—angle of laser light scattering. The relationship between the diffusion coefficient D and the particle hydrodynamic diameter d is defined by the Stokes-Einstein Eq. (6):
$$ D=\frac{kT}{3\pi \eta d}, $$
(6)
where.
k

is Boltzmann constant

T

absolute temperature

η

solvent viscosity

Measurements were done using the “size & zeta potential” folded capillary cells in 12 sub-runs at the temperature of 20oC. The general-purpose model of the analysis was applied. Two repetitions of the measurement were performed for each of the three biological replications of samples with appropriate optical density (OD650 0.050; 0.075 and 0.150).

Before the start of the DLS experiment, the samples were observed under an optical microscope to be sure that the size of algal cells was in the range of the apparatus scale (i.e. 0.6–6.0 μm). An example of the photos obtained is presented in Fig. 2. Generally, the cells were circular but their size was at the upper limit of the measuring range of the Zetasizer apparatus.
Fig. 2

Photograph of P. kessleri cells in the water suspension (OD650 = 0.150) before the sonication treatment in light microscope

The DLS method is often used for characterisation of colloidal systems (Sood 1987; Metzeler et al. 2011; Nawrocka and Cieśla 2013; Sharifi 2014). However, for soft materials, there may be problems with the sharpness of the particle/dispersant optical interface, which affect the results (Cieśla et al. 2013). Some researchers pointed that, in the case of algal cells, the light is scattered not only by the outside surface but also by the cell interior (Witkowski et al. 1993; Quirantes and Bernard 2004). For concentrated systems, it is possible that the effect of restricted diffusion occurs. This may be the cause of the obtaining of overestimated results (Pecora 1985; ISO 22412:2017). To avoid these interferences, the influence of the sonication time on the algal dispersions was analysed using the relative mean hydrodynamic diameter (Rdt):
$$ {Rd}_t=\frac{d_t}{d_0} $$
(7)
where dt and d0 were the mean hydrodynamic diameters at time t and t = 0 s, respectively.

Electrophoretic mobility of algal cells

Electrophoretic mobility characterises the movement of particles under the influence of an electric field applied:
$$ {U}_e=\frac{v}{E}=\left(\raisebox{1ex}{$\varepsilon \zeta $}\!\left/ \!\raisebox{-1ex}{$\eta $}\right.\right)f\left(\kappa a\right) $$
(8)
where Ue—electrophoretic mobility, v—velocity of dispersed particles, E—electric field strength, ε—permittivity of the dispersing medium, ζ—zeta potential, η—viscosity of the dispersing medium and f(κa)—Henry’s function (Hunter 1988; Zetasizer Nano Series User Manual, 2004; Delgado et al. 2007).

The values of electrophoretic mobility are often used for determination of electrokinetic potential to evaluate the stability of the colloidal systems (Hunter 1988; Delgado et al. 2007; Wu et al. 2012; Ndikubwimana et al. 2015). In these investigations, the electrophoretic mobility was measured using the Zetasizer Nano ZS apparatus (Malvern Ltd., UK) and the laser Doppler electrophoresis (LDE) method (Mayinger 1994; Zetasizer Nano Series User Manual, 2004). Measurements were done using the same cells and conditions as in the DLS method.

Statistical analysis

To determine the influence of the sonication time, physiological stage and OD650 on the cell number, particle size (mean hydrodynamic diameter—d), relative mean hydrodynamic diameter (Rdt) and electrophoretic mobility, the multi-factor ANOVA (at p < 0.05), one-way ANOVA and the post hoc Tukey’s HSD test were used (Statistica v. 10.0, StatSoft Poland). The Statistica software was applied to find the correlations (at p < 0.05) between Rdt and the sonication time (t), Rdt and the algal cell reduction (CRns), electrophoretic mobility and sonication time (t), as well as electrophoretic mobility and the algal cell reduction (CRns).

The particle size, Rdt, and electrophoretic mobility data presented in the figures and tables are arithmetic means of six replicates with the indication of standard deviation. In the case of the dry cell weight and cell number, the mean results and standard deviations were obtained from nine and six replicates, respectively.

Results

The present results show changes in the number of P. kessleri cells during sonication at three different optical densities (OD650) and at four physiological stages (Fig. 3). The effectiveness of ultrasound presented as the number of cells was significantly dependent on the time of exposition to the sonication, OD650 value and growth phase (p < 0.05). In this study, the increase in the sonication exposure time ranging from 10 to 360 s caused a decrease in the number of viable cells in the solution in comparison with the control. The application of ultrasonic waves for 360 s did not result in total cell disintegration: the solution still contained viable cells (Table 1).
Fig. 3

Number of P. kessleri cells during sonication at different optical densities for a 24-h, b 96-h, c 240-h and d 360-h algal cells; the results are presented as the means of six measurements from n = 3; error bars represent standard deviation; the blue lozenges, red squares and green triangles represent OD650 values of 0.05, 0.075 and 0.150, respectively

Table 1

Summary of algal cells reduction (CRns (%)) for different OD values and different growth phases in P. kessleri culture

 

CRns (%)

Time of sonication (s)

OD650 = 0.05

OD650 = 0.075

OD650 = 0.15

Growth phase (h)

Growth phase (h)

Growth phase (h)

24

96

240

360

24

96

240

360

24

96

240

360

10

1.65

6.08

3.66

1.22

8.42

20.16

0.87

0.78

8.13

6.55

0.54

5.41

20

0.93

8.78

5.13

0.00

21.29

12.90

2.34

2.02

0.00

7.86

13.26

1.54

30

6.17

1.49

5.13

3.05

20.05

20.97

1.73

6.98

3.25

9.61

10.33

16.99

40

0.49

9.12

3.74

2.74

20.30

16.53

5.45

1.40

6.78

19.21

20.65

21.62

50

35.31

13.85

9.89

1.52

29.70

12.50

8.66

15.66

21.41

16.16

21.74

11.20

60

33.33

15.88

10.62

1.59

31.93

27.82

19.48

7.29

29.54

52.40

23.04

17.76

90

29.01

12.84

23.44

0.00

38.61

31.05

29.00

14.42

32.52

56.77

26.96

15.68

180

60.70

35.47

42.86

2.44

46.53

37.90

35.50

24.84

32.25

53.28

41.85

17.07

360

72.84

46.96

54.21

9.27

58.17

49.60

49.78

28.99

52.85

61.14

44.57

38.61

The effect of the ultrasound treatment on cell disintegration expressed as CRns in the lag, log, decline and stationary phases after 360 s of exposure was 72.84, 46.96, 54.21 and 9.27%, respectively, at 0.05 OD; 58.17, 49.60, 49.78 and 28.99% at 0.075 OD and 52.85, 61.14, 44.57 and 38.61% at 0.15 OD. An important effect was noted wherein the increasing OD value of the cell solution used for measurements had a minor influence on the disintegration efficiency of sonication. Only for the stationary phase, the cell disruption effect was decreased with the increasing cell concentration. In the lag phase, the living cells in the solution, especially at 0.05 OD, were reduced to a greater extent after 360 s of exposure. In contrast, stationary-phase cells were more resistant to the ultrasonic treatment at all OD values.

The size distribution and electrokinetic properties of the un-sonicated P. kessleri cells, which were dispersed in distilled water, were determined in the lag, log, decline and stationary phases of growth. The results are presented in Fig. 4.
Fig. 4

Values of the mean hydrodynamic diameter d (a) and electrophoretic mobility (b) (columns) as well as the number of cells (points) at the different growth phases; error bars represent standard deviation. Values of the mean hydrodynamic (d) and electrophoretic mobility are presented as columns. Colours of the column: white, grey and dotted and colours of the dots: white, grey and black denote values of the parameters for OD 0.05, 0.075 and 0.15, respectively

The size of P. kessleri cells (Fig. 4a) increased with the time of cultivation (p < 0.05). The effect of age of P. kessleri cells on the cell size decreased with an increasing OD650 value (p < 0.05 for OD650 = 0.05, p = 0.05 for OD650 = 0.075, p > 0.05 for OD650 = 0.15).

The mean hydrodynamic diameter of P. kessleri cells increased with the increasing optical density of the suspension (p < 0.05). Generally, there were no differences between values obtained for the 0.05 and 0.075 OD650 (i.e. about 25 and 42 million cells per millilitre, respectively). The mean hydrodynamic diameter was lower than 6000 nm for these samples. After the increase in the cell number to about 85 million per millilitre (OD650 = 0.15), the apparatus recorded large particles. The effect of OD650 on the determined size was the highest for cells in the lag and log phases (p < 0.05), and then it decreased (p < 0.05) to be statistically insignificant for the oldest cells (p > 0.05).

The values of electrophoretic mobility (Fig. 4b) of the P. kessleri cells dispersed in distilled water were negative. The electrophoretic mobility was not affected by the physiological stages of P. kessleri cells (p > 0.05) and the concentration of the cells in the suspension (p > 0.05).

The application of ultrasounds led to changes in the size of single algal cells, which can be seen in Fig. 5. The relative hydrodynamic diameter (Rdt) was dependent on the physiological stage of P. kessleri culture (p < 0.05). The highest values of Rdt, which means the lowest reduction of size, were obtained for the logarithmic phase. The results recorded for these samples were characterised by high values of standard deviations. This was probably connected with the high heterogeneity of cells in the logarithmic phase of growth associated with active proliferation of the cells. The lowest values of Rdt were obtained for the decline and stationary phases. However, it should be remembered that the size of the control cells (without the sonication) was the biggest in this case (Fig. 4a). Generally, the values of Rdt depended on the optical density of the samples (p < 0.05).
Fig. 5

Relationship between the relative mean hydrodynamic diameter (Rdt) and time of sonication for a 24-h, b 96-h, c 240-h and d 360-h algal cells in the suspension at different OD650 values; error bars represent standard deviation; the white, grey and black colours represent OD650 values of 0.05, 0.075 and 0.150, respectively

The relative hydrodynamic diameter (Rdt) was strongly affected by the time of the ultrasound treatment (p < 0.05). Its values decreased with the prolongation of the sonication time. This was observed for all samples.

Additionally, there were statistically significant correlations (p < 0.05) between the relative hydrodynamic diameter (Rdt) and the time of sonication (t) and between the relative hydrodynamic diameter (Rdt) and the algal cell reduction (CRns). The relationships were used for calculation of the sonication time that is required for total disintegration of cells (t100%). The mathematical formulas, values of the correlation coefficient and values of t100% are collected in Table 2. The time needed for the total disintegration of microalgal cells was longer than that applied in this study (410–3665 s). Generally, the effective time of sonication was dependent on the growth phase of P. kessleri cells. The longest t100% was obtained for stationary-phase cells in a suspension at OD650 = 0.05. However, the lowest values of correlation coefficients were determined for these samples (0.42–0.43).
Table 2

The values of sonication time which is needed for total rupture of the P. kessleri cells and the formulas, which were used for its calculation basing on Rdt

Growth phase (h)

OD650

Rdt = f(t)

Rdt = f(CRns)

t100% (s)

Formula

r

Formula

r c

24

0.05

y = 0.4612e−0.003x

0.68

y = 0.4939e−0.013x

0.74

410

0.075

y = 0.3812e−0.004x

0.66

y = 0.6588e−0.031x

0.91

638

0.15

y = 0.3609e−0.005x

0.76

y = 0.4465e−0.033x

0.85

617

96

0.05

y = 0.7244e−0.004x

0.86

y = 0.8072e−0.028x

0.88

673

0.075

y = 0.6252e−0.003x

0.68

y = 0.9264e−0.029x

0.77

835

0.15

y = 0.3440e−0.005x

0.76

y = 0.4856e−0.028x

0.88

491

240

0.05

y = 0.3865e−0.004x

0.71

y = 0.4086e−0.023x

0.75

561

0.075

y = 0.3386e−0.004x

0.67

y = 0.3793e−0.030x

0.78

721

0.15

y = 0.3498e−0.005x

0.76

y = 0.5455e−0.041x

0.92

731

360

0.05

y = 0.1972e−0.003x

0.43

y = 0.1979e−0.110x

0.42

3665

0.075

y = 0.3279e−0.004x

0.70

y = 0.3877e−0.052x

0.79

1258

0.15

y = 0.3123e−0.004x

0.61

y = 0.4307e−0.046x

0.69

1070

Growth phase (h) = growth phase of cells expressed in hours, OD650 = optical density of cell suspension measured at 650 nm, Rdt = f(t) relationship between relative hydrodynamic diameter and the sonication time (s), Rdt = f(CRns) relationship between relative hydrodynamic diameter and algal cell reduction (%), r correlation coefficient (at p < 0.05), t100% the sonication time (s) needed for the total disruption of P. kessleri cells

The reduction of intact cells caused by ultrasounds was strongly correlated with the relative mean hydrodynamic diameter as well as electrophoretic mobility, mainly at the low concentrations of the cells. The relationship between the electrophoretic mobility and the CRns for varied OD650 values at the different physiological stages of P. kessleri cells are presented in Fig. 6. The electrophoretic mobility in the microalgal cell suspensions decreased (the absolute value) with the prolonged time of cultivation and ageing of the P. kessleri culture (p < 0.05) and with the increasing OD650 value (p < 0.05).
Fig. 6

Relationship between the electrophoretic mobility and CRns for a 24-h, b 96-h, c 240-h and d 360-h algal cells at different OD650 values of the suspensions; the symbols: white circle, grey triangle and black rhombus reflect the OD650 of 0.05, 0.075 and 0.150, respectively; (error bars represent standard deviation)

The prolonged exposure to ultrasound and the consequent decrease in intact cells in the solution led to an increase in the electrophoretic mobility (p < 0.05), which can be seen in Fig. 6.

For the low optical densities (OD650 0.05 and 0.075) of P. kessleri cells in the dispersion, there were statistically significant (p < 0.05) correlations between the values of electrophoretic mobility and the time of ultrasound exposure and between the electrophoretic mobility and CRns. The mathematic formulas, correlation coefficients (r) and the calculated values of time needed for the total disintegration of P. kessleri cells (t100%) are collected in Table 3.
Table 3

The values of sonication time which is needed for total destruction of the algae cells and the formulas, which were used for its calculation basing on electrophoretic mobility (Ue)

Growth phase (h)

OD650

Ue = f(t)a

Ue = f(CRns)b

t100%d (s)

Formula

r c

Formula

r c

24

0.05

y =  − 0.0015x − 1.8157

0.72

y =  − 0.0071x − 1.7743

0.81

446

96

0.05

y =  − 0.0010x − 1.6881

0.85

y =  − 0.0070x − 1.6670

0.81

679

0.075

y =  − 0.0014x − 1.5758

0.94

y =  − 0.0107x − 1.4470

0.93

672

240

0.05

y =  − 0.0016x − 1.5591

0.94

y =  − 0.0097x − 1.5415

0.95

595

0.075

y =  − 0.0012x − 1.4526

0.82

y =  − 0.0079x − 1.4338

0.85

643

360

0.05

y =  − 0.0015x − 1.6291

0.86

y =  − 0.0544x − 1.6401

0.76

3634

Growth phase (h) = growth phase of cells expressed in hours, OD650 = optical density of cell suspension measured at 650 nm, Ue = f(t) relationship between electrophoretic mobility (10−8 m2 V−1 s−1) and the sonication time (s), Ue = f(CRns) relationship between electrophoretic mobility (10−8 m2 V−1 s−1) and algal cell reduction (%), r correlation coefficient (at p < 0.05), t100% the sonication time (s) needed for the total destruction of cells

The calculated time that was sufficient for the total disintegration of P. kessleri cells was in the range from 446 to 3634 s and increased with ageing of the P. kessleri culture. This tendency was the same as that observed for t100% which was calculated based on the Rdt values. Although the cell disruption could take up to 60 min, the most intensive changes in the physical (size) and physicochemical (electrophoretic mobility) properties occurred within the first 60 s of sonication. In most cases, the prolongation of the time of the ultrasound action from 90 to 360 s did not cause significant changes in the diameter of the algal cells or the values of electrophoretic mobility (Figs. 5 and 6). Generally, as time progressed, the disruptive effect slowed down. The tendency of the cell diameter to decrease at the simultaneous increase in the electrophoretic mobility indicated that the disintegration still occurred. However, the efficiency of this process was low.

Discussion

The main determinants of effective disintegration of microalgal cells are the algal type, cell size and shape, cell wall strength and growth phase. Exposure to ultrasound treatment is proportional to damage to cellular biomass (Park et al. 2017). The resistance of stationary-phase cells of P. kessleri and the low reduction of the cellular population after 360 s of exposure generally result from differences in cell morphology (cell wall thickness, size and composition). In our previous report, ultrasonication was demonstrated as an appropriate technique in rupturing microalgal cells during extraction, and treating the sample with ultrasonic waves for 90 s improved lipid recovery from Auxenochlorella protothecoides cells (Piasecka et al. 2014). Joyce et al. (2014) reported that no intact cells of Dunaliella salina remained after a 4-min sonication treatment, but in the case of Chlamydomonas concordia cells, 16-min sonication ruptured cells completely. Chlorococcum cells remained intact even after continuous sonication at the maximum power level (130 W) for 25 min (Halim et al. 2012). Differences among examined green algal species are a direct consequence of cell wall thickness and structure. Generally, species with a thinner cell wall were easier to disrupt (Halim et al. 2013). Parachlorella kessleri cells are characterised by a thicker (54–59 nm) cell wall than that in other ‘Chlorella’ species (Yamamoto et al. 2005). Juárez and Vélez (2011) reported that the thickness of the cell wall could reach up 60 to 80 nm. Additionally, the fibrillar cell wall component of P. kessleri cells was composed of 100% of N-acetylglucosamine (chitin) (Takeda 1991; Juárez and Vélez 2011).

In the un-sonicated P. kessleri samples, the increase in the cell size with the time of cultivation was a result of the growth process, during which the volume of a particular cell and, in consequence, its diameter became bigger. According to Chioccioli et al. (2014), during the growth cycle, the cell size is changing predictably. In some tested species, there was a strong correlation between the size and shape of cells and environmental conditions. Chioccioli et al. (2014) reported that Chlorella vulgaris stationary-phase cells began to increase in size. This tendency was observed in this study, especially at the low concentration of algal cell suspension.

The OD650 affected the measured size of the algal cells due to the restricted diffusion in concentrated samples. The DLS method is based on the analysis of light scattered by particles that are moving due to Brownian motion. The diffusion coefficient of particles is inversely proportional to their size (Eq. (5). In the concentrated system, the diffusion of particles was inhibited. Considering the above, the value of the hydrodynamic diameter obtained by DLS was higher in respect to its real value (Pecora 1985; Zetasizer Nano Series User Manual, 2004; ISO 22412:2017). For the P. kessleri cells in the stationary phase, the effect was masked because the cells were large and their diffusion was slow. To avoid this problem in the analysis of the influence of the sonication treatment on the cell size, the relative values of the mean hydrodynamic diameter (Rdt) were used instead of the apparent ones.

The negative values of electrophoretic mobility of the P. kessleri cells dispersed in distilled water suggest that the external cell envelope is dominated by acidic functional groups, the dissociation of which generates a negative electrical charge of the surface. At the neutral pH (about 7), there are mainly carboxylic (-COOH) and phosphoryl (-POH) groups (Vandamme et al. 2013; Ndikubwimana et al. 2015).

The effective time of sonication, determined on the basis of the relationships between the relative hydrodynamic diameter (Rdt) and the time of sonication (t) as well as between the relative hydrodynamic diameter (Rdt) and the algal cell reduction (CRns), was dependent on the growth phase of P. kessleri cells. The cell walls of the cells from the stationary phase were more resistant to the ultrasound treatment than the cell walls from the preceding physiological stages. This may be a consequence of different thickness of cell walls. Yamamoto et al. (2005) reported that P. kessleri cells from the late growth phase were characterised by a thicker cell wall than that in early growth phase cells.

The mobility of particles in liquid, which is caused by the applied electric field, is higher for small particles possessing a surface electric charge than for big ones (Hunter 1988). Therefore, the disintegration of P. kessleri cells should result in an increase in the absolute value of electrophoretic mobility due to the appearance of small particles in the system. In fact, the fragmented debris appeared among the P. kessleri cells in the cell suspension due to the sonication process. The reduction of intact cells caused by ultrasounds was strongly correlated with the relative mean hydrodynamic diameter as well as electrophoretic mobility, what has not been shown so far. The stationary-phase cells were bigger than the young ones, as discussed earlier, and this resulted in their slower movement. Additionally, the increase in the suspension density caused blocking of the movement by the neighbouring particles, which led to a decrease in the electrophoretic mobility. The action of ultrasounds resulted in an increase in the electrophoretic mobility values. This was caused probably by the release of cellular content to the bulk solution and the high mobility of disintegrated cells as well as dissociation of functional groups, which may be facilitated by the applied ultrasounds.

The analysis of both the cell size and electrophoretic mobility in the sonicated samples allowed estimation of the time of ultrasound action required for efficient and complete algal cell disintegration. This points out the usefulness of the applied laser techniques in the algae studies.

Conclusions

Based on the results, it can be concluded that the laser light scattering methods can be applied in investigations of algal cell wall disruption. The effect of ultrasonic treatment on disruption of P. kessleri cells was determined from the physical and physicochemical properties of algal cells by laser light scattering methods and the algal cell reduction CRns. These results indicate electrophoretic mobility as a new parameter to investigate the effectiveness of cell disruption prior to extraction in algal bioproduction processes. Additionally, these studies enable us to estimate the time required for efficient and complete algal cell lysis.

Notes

Funding

This work was funded in part by the National Science Centre, Poland (Grant No. 2017/25/N/NZ9/01785) in 2018–2021.

References

  1. Chioccioli M, Hankamer B, Ross IL (2014) Flow cytometry pulse width data enables rapid and sensitive estimation of biomass dry weight in the microalgae Chlamydomonas reinhardtii and Chlorella vulgaris. PLoS One 9(5):e97269CrossRefGoogle Scholar
  2. Cieśla J, Bieganowski A, Narkiewicz-Michałek J, Szymula M (2013) Use of a dynamic light scattering technique for SDS/water/pentanol studies. J Disper Sci Technol 34:566–574CrossRefGoogle Scholar
  3. Cieśla J, Stępień-Pyśniak D, Nawrocka A, Łukowska M, Hauschild T, Wernicki A, Bieganowski A (2018) Surface properties of Enterococcus faecalis cells isolated from chicken hearts determine their low ability to form biofilms. Biofouling 34:149–161CrossRefGoogle Scholar
  4. Delgado AV, Gonzales Caballero F, Hunter RJ, Koopal LK, Lyklema J (2007) Measurement and interpretation of electrokinetic phenomena. J Colloid Interf Sci 309:194–224CrossRefGoogle Scholar
  5. García-Galán MJ, Gutiérrez R, Uggetti E, Matamoros V, García J, Ferrer I (2018) Use of full-scale hybrid horizontal tubular photobioreactors to process agricultural runoff. Biosyst Eng 166:138–149CrossRefGoogle Scholar
  6. Greenly JM, Tester JW (2015) Ultrasonic cavitation for disruption of microalgae. Bioresour Technol 184:276–279CrossRefGoogle Scholar
  7. Grudziński W, Krzemińska I, Luchowski R, Nosalewicz A, Gruszecki WI (2016) Strong-light-induced yellowing of green microalgae Chlorella: a study on molecular mechanisms of the acclimation response. Algal Res 16:245–254CrossRefGoogle Scholar
  8. Halim R, Harun R, Danquah MK, Webley PA (2012) Microalgal cell disruption for biofuel development. Appl Energy 91:116–121CrossRefGoogle Scholar
  9. Halim R, Rupasinghe TWT, Tull DL, Webley PA (2013) Mechanical cell disruption for lipid extraction from microalgal biomass. Bioresour Technol 140:53–63CrossRefGoogle Scholar
  10. Hunter RJ (1988) Zeta potential in colloid science. In: Principles and applications. Academic Press, LondonGoogle Scholar
  11. International Standard ISO 22412:2017. Particle size analysis—dynamic light scattering (DLS)Google Scholar
  12. Joyce EM, King PM, Mason TJ (2014) The effect of ultrasound on the growth and viability of microalgae cells. J Appl Phycol 26:1741–1748CrossRefGoogle Scholar
  13. Juárez AB, Vélez CG, Iñiguez AR, Martínez DE, Rodríguez MC, Vigna MS, De Molina MDCR (2011) A Parachlorella kessleri (Trebouxiophyceae, Chlorophyta) strain from an extremely acidic geothermal pond in Argentina. Phycologia 50:413–421CrossRefGoogle Scholar
  14. Kaszuba M, McKnight D, Connah MT, McNeil-Watson FK, Nobbmann U (2008) Measuring sub-nanometre sizes using dynamic light scattering. J Nanopart Res 10:823–829CrossRefGoogle Scholar
  15. Krzemińska I, Piasecka A, Nosalewicz A, Simionato D, Wawrzykowski J (2015a) Alterations of the lipid content and fatty acid profile of Chlorella protothecoides under different light intensities. Bioresour Technol 196:72–77CrossRefGoogle Scholar
  16. Krzemińska I, Nawrocka A, Piasecka A, Jagielski P, Tys J (2015b) Cultivation of Chlorella protothecoides in photobioreactors: the combined impact of photoperiod and CO2 concentration. Eng Life Sci 15:533–541CrossRefGoogle Scholar
  17. Lv J, Wang X, Feng J, Liu Q, Nan F, Jiao X, Xie S (2018) Comparison of growth characteristics and nitrogen removal capacity of five species of green algae. J Appl Phycol.  https://doi.org/10.1007/s10811-018-1542-y
  18. Magierek E, Krzemińska I (2017) Stimulatory effect of indole-3-acetic acid and continuous illumination on the growth of Parachlorella kessleri. Int Agrophys 31:483–489CrossRefGoogle Scholar
  19. Mayinger F (1994) Optical measurements techniques and applications. Springer, BerlinCrossRefGoogle Scholar
  20. Metzler DM, Li M, Erdem A, Huang CP (2011) Responses of algae to photocatalytic nano-TiO2 particles with an emphasis on the effect of particle size. Chem Eng J 170:538–546CrossRefGoogle Scholar
  21. Natarajan R, Ang WMR, Chen X, Voigtmann M, Lau R (2014) Lipid realising characteristics of microalgae species through continuous ultrasonication. Bioresour Technol 158:7–11CrossRefGoogle Scholar
  22. Nawrocka A, Cieśla J (2013) Influence of silver nanoparticles on food components in wheat. Int Agrophys 27:49–55CrossRefGoogle Scholar
  23. Ndikubwimana T, Zeng X, He N, Xiao Z, Xie Y, Chang JS, Lin L, Lu Y (2015) Microalgae biomass harvesting by bioflocculation-interpretation by classical DLVO theory. Biochem Eng J 101:160–167CrossRefGoogle Scholar
  24. Park J, Church J, Son Y, Kim KT, Lee WH (2017) Recent advances in ultrasonic treatment: challenges and field applications for controlling harmful algal blooms (HABs). Ultrason Sonochem 38:326–334CrossRefGoogle Scholar
  25. Pecora R (1985) Dynamic light scattering application of photon correlation spectroscopy. Plenum Press, New YorkGoogle Scholar
  26. Piasecka A, Krzemińska I, Tys J (2014) Physical methods of microalgal biomass pretreatment. Int Agrophys 28:341–348CrossRefGoogle Scholar
  27. Piasecka A, Krzemińska I, Tys J (2017) Enrichment of Parachlorella kessleri biomass with bioproducts: oil and protein by utilization of beet molasses. J Appl Phycol 29:1735–1743CrossRefGoogle Scholar
  28. Postma PR, Suarez-Garcia E, Safi C, Yonathan K, Olivieri G, Barbosa MJ, Wijffels RH, Eppink MHM (2017) Energy efficient bead milling of microalgae: effect of bead size on disintegration and release of proteins and carbohydrates. Bioresour Technol 224:670–679CrossRefGoogle Scholar
  29. Prabakaran P, Ravindran AD (2011) A comparative study on effective cell disruption methods for lipid extraction from microalgae. Lett Appl Microbiol 53:150–154CrossRefGoogle Scholar
  30. Quirantes A, Bernard S (2004) Light scattering by marine algae: two-layer spherical and nonspherical models. J Quant Spectrosc Radiat Transf 89:311–321CrossRefGoogle Scholar
  31. Safi C, Frances C, Ursu AV, Laroche C, Pouzet C, Vaca -Garcia C, Pontalier PY (2015) Understanding the effect of cell disruption methods on the diffusion of Chlorella vulgaris proteins and pigments in the aqueous phase. Algal Res 8:61–68CrossRefGoogle Scholar
  32. Sharifi S (2014) Quasi-elastic light scattering and small-angle X-ray scattering study of a mixture of a biopolymer with microemulsion. Phys Chem Liq 52:618–626CrossRefGoogle Scholar
  33. Sood AK (1987) Light scattering from colloids. Hyperfine Interact 37:365–384CrossRefGoogle Scholar
  34. Takeda H (1991) Sugar composition of the cell wall and the taxonomy of Chlorella (Chlorophyceae). J Phycol 27:224–232CrossRefGoogle Scholar
  35. Taleb A, Legrand J, Takache H, Taha S, Pruvost J (2018) Investigation of lipid production by nitrogen-starved Parachlorella kessleri under continuous illumination and day/night cycles for biodiesel application. J Appl Phycol 30:761–772CrossRefGoogle Scholar
  36. Vandamme D, Foubert I, Muylaert K (2013) Flocculation as a low-cost method for harvesting microalgae for bulk biomass production. Trends Biotechnol 31:233–239CrossRefGoogle Scholar
  37. Wang M, Yuan W, Jiang X, Jing J, Wang Z (2014) Disruption of microalgal cells using high-frequency focused ultrasound. Bioresour Technol 153:315–321CrossRefGoogle Scholar
  38. Witkowski K, Woliński L, Turzyński Z, Gędziorowska D, Zieliński A (1993) The investigation of kinetic growth of Chlorella vulgaris cells by the method of integral and dynamic light scattering. Limnol Oceanogr 38:1365–1372CrossRefGoogle Scholar
  39. Wu Z, Zhu Y, Huang W, Zhang C, Li T, Zhang Y, Li A (2012) Evaluation of flocculation induced by pH increase for harvesting microalgae and reuse of flocculated medium. Bioresour Technol 110:496–502CrossRefGoogle Scholar
  40. Xu R (2015) Light scattering: a review of particle characterization applications. Particuology 18:11–21CrossRefGoogle Scholar
  41. Yamamoto M, Kurihara I, Kawano S (2005) Late type of daughter cell wall synthesis in one of the Chlorellaceae, Parachlorella kessleri (Chlorophyta, Trebouxiophyceae). Planta 221:766–775CrossRefGoogle Scholar
  42. Zetasizer Nano Series User Manual, 2004. Malvern instruments ltd., UKGoogle Scholar
  43. Zheng H, Yin J, Gao Z, Huang H, Ji X, Dou C (2011) Disruption of Chlorella vulgaris cells for the release of biodiesel-producing lipids: a comparison of grinding, ultrasonication, bead milling, enzymatic lysis, and microwaves. Appl Biochem Biotechnol 164:1215–1224CrossRefGoogle Scholar

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Open Access This article is distributed under the terms of the Creative Commons Attribution 4.0 International License (http://creativecommons.org/licenses/by/4.0/), which permits unrestricted use, distribution, and reproduction in any medium, provided you give appropriate credit to the original author(s) and the source, provide a link to the Creative Commons license, and indicate if changes were made.

Authors and Affiliations

  • Agata Piasecka
    • 1
  • Jolanta Cieśla
    • 1
  • Magdalena Koczańska
    • 1
  • Izabela Krzemińska
    • 1
    Email author
  1. 1.Institute of AgrophysicsPolish Academy of SciencesLublinPoland

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