The current study presents the development of a reliable method for the quantification of c-phycocyanin. It was found that the spectrophotometric method commonly used for c-phycocyanin quantification tends to overestimate the actual amount of c-phycocyanin in AFA samples. Thus, the aim of this study was to account for c-phycocyanin variation between cyanobacteria species in order to reliably adapt the spectrophotometric quantification method of c-phycocyanin for Aphanizomenon flos-aquae (AFA). High performance liquid chromatography (HPLC) was used to avoid interference between molecules. The existing spectrophotometric equations for the quantification of AFA c-phycocyanin were adapted using a c-phycocyanin standard. The method was then used to obtain a new set of spectrophotometric quantification equations that were adapted to the strain of interest and ensured the accuracy of c-phycocyanin quantification while continuing to use a rapid, simple, and inexpensive method for pigment quantification. The method developed here could be adapted to improve the quantification methods for other types of phycocyanin, cyanobacteria, or even other compounds of interest that are currently quantified by spectrophotometry.
Research Article
Development of a spectrophotometric method for the quantification of c-phycocyanin in the cyanobacteria Aphanizomenon flos-aquae
https://doi.org/10.21203/rs.3.rs-2760709/v1
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C-phycocyanin
spectrophotometry
HPLC
Aphanizomenon flos-aquae
cyanobacteria
quantification method
Nowadays, health-related issues have increased and there is a growing interest in the consumption of healthy functional foods. In this context, microalgae and cyanobacteria are promising microorganisms to study to potentially fulfill the needs of a constantly growing population in the foreseeable future. Because of their large diversity and their richness in essential biological compounds, microalgae and cyanobacteria are microorganisms that meet all the requirements to serve as functional foods.
The most studied and widespread of cyanobacteria species is Limnospira fusiformis (Nowicka-Krawczyk et al. 2019) also known as spirulina (Seyidoglu et al. 2017). However a wide variety of cyanobacteria exist, and each species offers different characteristics and various benefits for humans.
Like other species of cyanobacteria, Aphanizomenon flos-aquae has the particularity of containing characteristic accessory pigments that give it its blue color. These pigments are phycobiliproteins and are grouped in the phycobilisome, a protein macro-complex composed of 85% phycobiliproteins and 15% non-pigmentary proteins (Thomas 1989). Among the phycobiliprotein groups, we have decided to focus this work on c-phycocyanin. This molecule is particularly interesting as it has demonstrated positive effects on human health and can be found in significant quantities (up to 10% by dry mass) in AFA (Busnel 2018). Indeed, c-phycocyanin has renowned antioxidant (Bhat and Madyastha 2000; Benedetti et al. 2004), anti-inflammatory, anticancer (Safari et al. 2017) properties.
As the spirulina is already well-studied and present on the market it is important to focus on the industrialization and marketing of new strains of cyanobacteria such as Aphanizomenon flos-aquae (AFA), which could become a source of new functional molecules beneficial to human health (Menvielle-Bourg et al. 2011; Cremonte et al. 2017; Merino et al. 2020).
Considering the huge potential of c-phycocyanin, it is essential to characterize and quantify the molecule in the most accurate way possible.
To better understand how to quantify c-phycocyanin, special attention was paid to the molecular structure. Phycobiliproteins (PBPs) are composed of a protein part and a pigment part also referred to as a chromophore. The protein part consists of α and β subunits in trimer (αβ)3 or hexamer (αβ)6 form made up of equimolar monomer (αβ). The chromophore part, also called phycocyanobilin, is a linear tetrapyrole group (Padyana et al. 2001).
Among the phycobiliproteins we found several types of chromophores that differ in the number and arrangement of the double bounds in their tetrapyrol group (Bennett and Bogorad 1971). Those differences result in various spectral properties used to classify phycobiliproteins into four types. The phycoerythrin (PE) with an absorption spectra presenting strong peaks between 480 and 570 nm and a maximal absorption at 580nm, the phycoerythrocyanin (PEC) absorbing at 575 nm, and allophycocyanin (APC) with a sharp absorption maximum at 650 nm and an emission maximum at 660 nm (Glazer 1994). The last group of phycobiliproteins is the c-phycocyanin (C-PC) whose chromophore absorbs at a wavelength of 620 nm.
The absorption spectrum of an extract of AFA presented in Fig. 1 demonstrates the different absorption properties explained above. Indeed, the first peak at 280 nm represents the proteins; the major peak at 620 nm is the chromophore part of the C-PC and the shoulder at 652 nm that indicates the presence of allophycocyanin in the extract.
For C-PC, the quantification has been performed for years by spectrophotometric methods using simplified determination equations, mainly derived from the methodology developed by (Bennett and Bogorad 1973).
Currently, there is no standardized quantification method and different equations are used in the literature. Table 1 shows a list of the different equations that can be found for the quantification of C-PC.
| References | Equations used |
|---|---|
| (Bennett and Bogorad 1971) | \(\left[C-PC\right]g.{L}^{-1}= \frac{{A}_{615}-0.474{A}_{652}}{5.34}\) |
| (Horváth et al. 2013) | \(\left[C-PC\right]g.{L}^{-1}= \frac{{A}_{615}-0.474{A}_{652}}{5.34}\) |
| (Soni et al. 2006) ; (Syrpas et al. 2020) | \(\left[C-PC\right]g.{L}^{-1}= \frac{{A}_{620}-0.70{A}_{650}}{7.38}\) |
| (Busnel 2018) | \(\left[C-PC\right]g.{L}^{-1}= \frac{{A}_{620}-0.474{A}_{652}}{5.34}\) |
| (Zavřel et al. 2018) | \(\left[PC\right]g.{L}^{-1}= \frac{\left({A}_{615}-{A}_{750}\right)-0.474({A}_{652}-{A}_{720})}{5.34}\) |
Two types of difference between equations can be revealed. First, some authors have shifted the maximum wavelength absorption of c-phycocyanin chromophore from 615 nm to 620 nm. This shift is not well-explained in the literature but it may be due to the drift of the equation through the time. The second change compared with the initial equation from (Bennett and Bogorad 1973) is the addition of the absorbance at 720 nm to take into account the turbidity of the sample. The extinction coefficients present in the equation has also been modified in some studies. For example, (Soni et al. 2006) used the equations from (Bennett and Bogorad 1973) and the extinction coefficients from (Bryant et al. 1979).
Moreover, the equations were initially developed for spirulina by (Bennett and Bogorad 1971) but it has been shown that there are structural differences in phycocyanins between different species (Menvielle-Bourg et al. 2011). Therefore, working on a new strain of cyanobacteria involves reworking the quantification methods to best adapt them to the strain studied.
High Performance Liquid Chromatography can be used to separate the molecules of a mixture and characterize each one separately in order to avoid interference between molecules in the quantification. Previous studies have already studied the interference effect in molecule quantification. For example, (Lauceri et al. 2018) demonstrated the interference of Chlorophyll a in spectrophotometric quantification of c-phycocyanin and allophycocyanin. They showed that chlorophyll a can cause large errors in phycocyanin and, especially, in allophycocyanin spectrophotometric quantification. However, their work allowed to the development of a pair of equations to correct the absorbance spectrum of phycobiliproteins for their quantification. In light of these differences, it was considered essential to use reference methods such as HPLC or ionic chromatography to correct the initial equations as accurately as possible for the quantification of c-phycocyanin in AFA.
The aim of this study was to develop a reliable method for the spectrophotometric quantification of Aphanizomenon flos-aquae c-phycocyanin. For this purpose, High Performance Liquid Chromatography techniques are useful to avoid interference and to adapt existing spectrophotometric equations to improve the quantification of AFA c-phycocyanin.
Chemical
The c-phycocyanin standard used for analysis has been provided by the company Phycobiotech in France, the identification number is PBT-CPCLyo/001. Lyophilized C-PC has a purity of 53.7%, given by the supplier, due to the addition of polysaccharides to protect the product during freezing conditions. Purity is considered in the theoretical concentration calculations of samples used for the correction of spectrophotometric coefficient by HPLC method.
For HPLC analysis, acetonitrile HPCL grade from Fisher Scientific (CAS 75-05-8) and trifluoroacetic acid (TFA) from thermos scientific (CAS 76-05-1) are used as solvents.
Strain cultivation and sample preparation
The Aphanizomenon flos-aquae strain (from company personal collection) was grown in continuous airlift flat panel system (1L) with the following parameters: Bold’s Basal Medium based culture medium (Nichols and Bold 1965), mixing by bubbling air enriched with 1% CO2 enabling to obtain a constant pH of 9 ± 0.3. A continuous lateral illumination with LED is maintained at various photon flux densities ranging from 60 to 500 µmol.m− 2.s− 1(which enabled the various “physiological states of the biomass” necessary for the validation of the method).
The procedure for crude extract preparation consists of an aqueous extraction by centrifuging the culture for 15 minutes at 8000g, then removing the supernatant and replacing by the same volume of distilled water. The cells in the pellet were resuspended by vortex (30 seconds) and the solution was frozen at -20°C. After a week, the extract was thawed under agitation, centrifuged at 8000g for 15 minutes, the supernatant was conserved as “crude extract”.
Analytics
1. Spectrophotometry
C-phycocyanin concentration and purity was determined at first by spectrophotometry as described by (Bennett and Bogorad 1973). The crude extracts spectra were measured between 240 nm and 800 nm with spectrophotometer UV-vis, JASCO V-630 (0.5 nm resolution) and the C-PC concentration was determined by Eq. (1) (Bennett and Bogorad 1973).
2. High Performance Liquid Chromatography
Equipment
HPLC analysis was performed using an Agilent 1260 Infinity II chromatography system. The system consists of a quaternary pump, a vial sampler, a column oven maintaining a temperature of 25°C. As described in the methodology of (Chen et al. 2006), 40µl of the samples were injected into a precolumn Garde Eclipse + C8 4.6x12.5mm, 5µm and associated column Eclipse Plus C 8 (4.6 x 150mm, 5µm), previously equilibrated with a solution composed of 80% buffer A (0.1% TFA in water) and 20% buffer B (0.1% TFA in acetonitrile). PC subunits were eluted from the column according to the following program: 0–60 min, linear gradient to 80% buffer B; 60– 65 min, linear gradient to 95% buffer B; 65–70 min, linear gradient to 20% buffer A; 70–75 min, 20% buffer B. The flowrate was 1.0 mL.min− 1 and effluent was monitored by a UV-vis detector (Agilent 1260 Infinity II G7114A), at two different wavelengths, defined in the dedicated section below. The obtained chromatograms were analysed through the software Open lab Chemstation.
Method development
In order to develop the most accurate method of c-phycocyanin quantification by HPLC, particular attention was paid to the solvent interference. For this purpose, 6 samples were analyzed: samples a, b, c representing the mix of solvents and standards at different points in time during the analysis, the solvent proportion of each sample is summarized in Table 2below. The sample d is the c-phycocyanin standards dissolved in water. The two last samples e and f are the solvents alone: e contained water + 0,1% TFA and f contained acetonitrile + 0,1% TFA.
|
Sample name |
Water + 0,1% TFA |
Acetonitrile + 0,1% TFA |
|---|---|---|
|
a |
80% |
20% |
|
b |
50% |
50% |
|
c |
5% |
95% |
|
e |
100% |
0% |
|
f |
0% |
100% |
Each sample spectrum was in the spectral range from 240 to 800 nm to determine the most suitable wavelengths for the C-PC quantification by HPLC method.
Before performing the analysis of c-phycocyanin by HPLC using the above-described method, an analysis was performed to ensure the stability of the c-phycocyanin standard. For this purpose, three samples were analyzed, each sample (a, b and c) corresponding to the standard dissolved in a mixture of the two solvents in the proportions described in Table 2. The spectrum (240–800 nm) was mesured for each sample just after the dissolution of the c-phycocyanin standard and after 10, 30, and 90 minutes. The experiment time of 90 minutes was decided because it is the overall time of the HPLC method of analyzing a sample. The full spectrum analysis enabled a qualitative assessment of the c-phycocyanin stability. The quantity of C-PC at each time was determined using the Bennett and Bogorad equation described previously. Then the relative standard deviation (RSD), which is defined as the ratio of the standard deviation (σ) to the mean (µ), was calculated:
Equation.2 Equation for the calculation of relative standard deviation (Brian Everitt 1998)
To measure HPLC response to c-phycocyanin concentration, an aqueous solution of c-phycocyanin standard (PBT-CPCLyo/001) was prepared with milliQ water. For this, the c-phycocyanin was weighed on a precision balance (Mettler Toledo XA204DR) and the theorical concentration of the sample was calculated using the known purity of the standard. A dilution range was then performed to obtain samples with different concentrations of c-phycocyanine. Each sample is analyzed with the HPLC method developed and the correlation between the theorical concentration in c-phycocyanin and the area under the curve was established. Five calibration curves were used for the complete calibration at 280nm wavelength while three ranges were used for 600nm.
Once the calibration was completed, the limits of the method were evaluated using the relative standard deviation of the measurement. For each sample, the variation coefficient was calculated between the theorical concentration of C-PC and the calculated concentration determined by using the dose-response correlation previously established. Then, two parameters were considered: the method detection limit (LOD) and the method quantification limit (LOQ). The detection limit of a method (LOD) is the lowest concentration of an analyzed compound in a real matrix that, after undergoing all the steps of a complete method including chemical extractions and pretreatment, produces a detectable signal with a defined reliability statistically different from that produced by a "blank" under the same conditions. A value of RSD under 30% was considered as the limit for the LOD. The quantification limit of a method (LOQ) is the minimum concentration that can be quantified using an analytical method with defined reliability. For the LOQ, a value of RSD of 20% was chosen as the limit. The method presented here enabled the determination of the analytical error of the HPLC method.
Determination of the spectrophotometric coefficients adapted to AFA c-phycocyanin
For the determination of the spectrophotometry coefficient for AFA strain c-phycocyanin quantification, different samples with a range of C-PC concentration from 0.073 g.L− 1 to 1.74 g.L− 1 were analyzed by spectrophotometry and by the developed HPLC method. The correlation was then established between the results of quantification provided by the HPLC method and those estimated by the spectrophotometric analysis. Finally, this correlation was used to adjust the coefficients of the equations for the spectrophotometric quantification of c-phycocyanin in Aphanizomenon flos-aquae.
Quantitative analysis method development
3. Determination of detection wavelengths
Figure 1 reveals three interesting bands for most of the samples. The first peak was common to all the samples (a, b, c, d, e and f). The average maximum absorption wavelength of the first peak was 219 nm. As this band was present for each sample, regardless of the presence of the c-phycocyanin, it can be considered a solvent band, non-suitable for the quantification method of c-phycocyanin by HPLC method.
The two other interesting bands were only observed in samples containing the standards of c-phycocyanin. The second band, with a maximum absorption wavelength at 277 nm (average of samples a, b, c, d) was considered to be related to the absorption of the protein part of the c-phycocyanin standards. Indeed, as described before, the c-phycocyanin is composed of a chromophore part; the bilin which gives the molecule its blue color and a proteinic part composed of an assembly of motifs of two subunits α and β. The third band, with a maximum absorption at 616nm for the sample d (c-phycocyanin in water) and a maximal absorption around 650 nm for the other three samples (c-phycocyanine in solvents) corresponded to the chromophore part of the molecule. It is important to note the shift (black arrow in Fig. 1) of the absorbance maximum to higher wavelengths for the c-phycocyanin samples in solvents. This redshift phenomenon, also called bathochromic shift, may be due to the difference in pH between the samples. Indeed, samples a, b and c contain 0.1% trifluoroacetic acid which considerably decreased the pH which is around 2 compared to 6 for sample d solubilized in water. This shift of wavelength was only seen in the third band, indicating that only the chromophore was sensitive to the batochrome effect, while the protein part of the molecule was not.
In light of these results, a detection wavelength 277 nm was deemed appropriate for the determination of c-phycocyanine by HPLC in order to visualize the protein part of the molecule, while a detection wavelength of around 650 nm was considered preferable for visualizing the chromophore.
However, the detection system of the HPLC chain used has a maximum detection wavelength of 600 nm. Therefore, we decided to work at the wavelengths of 280 nm and 600 nm.
4. C-phycocyanin stability
Figure 3 shows the absorption spectra of the samples. Samples a, b and c were prepared with different amounts of c-phycocyanine, which explains the difference in peak heights. We note that the profile curve was similar to that shown in the previous section on the evaluation of solvent interferences.
First, all of the curves suggest that, in term of quality, the spectra do not evolve over time. Indeed, for each sample, the spectra obtained at the beginning of the experiment, 30 minutes, 60 minutes and 90 minutes later overlap very well.
The quantity of c-phycocyanin at each time was determined using the Bennett and Bogorad equation described in the section 2.2. For each sample the coefficient of variation during the experiment was calculated and values of 2.01% ; 2.91% and 2.77% were obtained for samples a b and c, respectively. Therefore, during the 90 minutes of the experiment, the amount of c-phycocyanine in each of the samples varied around 2–3%. These values being lower than 5%, it can be considered that c-phycocyanine was stable in each of the proportions of solvents analyzed through samples a, b and c.
5. Calibration curves for HPLC quantification of c-phycocyanin
The c-phycocyanin standard is analyzed by the established HPLC method and then each of the peaks of the obtained chromatograms was integrated as presented in Fig. 4.
Figure 5 presents the correlations established for 280 and 600 nm. We can see that the trend curve is linear with an excellent R2 of 0.9961 for the correlation at 280nm and 0.9855 for the correlation at 600nm.
With these correlations it was possible to establish the following relationships (3) for 280 nm and (4) for 600 nm for the quantification of c-phycocyanin by HPLC.
6. Limits determination of the HPLC method
To determine the limits of the method, as explained in the method section, we try to estimate the detection limit (LOD) and the quantification limit (LOQ). Figure 6A summarizes the dose-response correlation established for the HPLC method at 280 nm and the evolution of the relative standard deviation with the c-phycocyanine concentration in the sample. The same data are shown in Fig. 6B for the HPLC method with 600 nm detection.
An acceptable limit for the detection (LOD) was considered to be a coefficient of variation lower than 40%, which corresponds to c-phycocyanin concentration lower than 0.082 g.L− 1 for HPLC method with 280 nm detection and 0.032 g.L− 1 for the detection at 600 nm.
For quantification, the limit (LOQ) has been fixed at a coefficient of variation lower than 30% which corresponds to c-phycocyanin concentration lower than 0.115 g.L− 1 for HPLC method with 280 nm detection and 0.049 g.L− 1 for the detection at 600 nm.
Determination of the spectrophotometric coefficients adapted to AFA c-phycocyanin
Once the method was defined, a validation on the cyanobacterial strain of interest, Aphanizomenon flos-aquae, was performed. The results of the 24 samples analyzed (Fig. 7) show that typically, the measurements by spectrophotometry using the equation of (Bennett and Bogorad 1971), overestimated the c-phycocyanin content of the samples.
Figure 8 illustrates the difference in concentrations estimated by the two methods of measurement. The higher the concentration of c-phycocyanin in the sample, the lower the coefficient of variation; therefore, the difference between the two methods of measurement was reduced for high concentrations (higher than 1 g.L− 1). The data show the same trend for both the HPLC analysis at 280 nm (A) and the method using 600 nm (B) detection. However, it is important to note that the coefficients of variation were lower when considering the detection at 280 nm. Indeed, while we do not exceed 30% variation for the analysis at 280 nm, we reach 45% variation for low concentrations of c-phycocyanin for the detection at 600 nm. This difference will be discussed in the discussion section.
The main objective of this work was to develop the most reliable method for the determination of c-phycocyanin from Aphanizomenon flos-aquae. The spectrophotometric equations were modified to take into account the difference determined by HPLC. Figure 9 shows the correlation between the two measurement methods (HPLC and spectrophotometry). Then, this correlation can be used to modify the existing c-phycocyanin equation to be better-suited to the quantification of c-phycocyanin in AFA. The corrected equations (5) for 280 nm and (6) for 600 nm are presented below:
C-Phycocyanin subunits characterization
If we analyse the chromatograms obtained and presented in Fig. 4 several points can be discussed. First of all, if we look at the shape of the peaks obtained, we see that the peaks are doubled. As presented by Chen et al ; (Chen et al. 2006), this particular shape is due to the presence of two protein subunits α and β and that make up the c-phycocyanin molecule. Both chromatograms obtained at 280 nm and 600 nm show this characteristic shape. This can be explained by the chromophore part of the molecule which features a covalent bound with the protein subunits and absorbs around 600 nm. To go further in the subunits characterisation, it may be interesting to consider a SDS-PAGE analysis in order to determine the size of each complex. Indeed, the author (Rinalducci et al. 2009), worked on the characterization of the primary structure of AFA c-phycocyanin via de novo sequence analysis and showed that there are isoforms present within cyanobacteria. They discuss the possible use of the c-phycocyanin operon for a correct taxonomic identification of this species. The study of (Benedetti et al. 2006) revealed that the apparent molecular mass of the α subunit was 18,500 Da and the β subunit mass was 21,900 Da. It may be interesting to characterize the sizes of the subunits on the AFA strain used for the current study and compare them with those obtained by Benedetti in order to look for potential isoforms within the same species. Nevertheless, if we consider c-phycocyanin in general, it is clear that differences within species can lead to differences in how the molecule absorbs light and the methods developed for spirulina need to be adapted for each species to better quantify c-phycocyanin.
Wavelength detection choice: 280 nm vs 600 nm
Another important point of this study is the notable difference in measurements between the spectrophotometry assays and the use of the HPLC method with a detection wavelength of 600 nm (Fig. 8). This difference in the quality of the results according to the detection wavelength may be explained by the fact that a detection wavelength of 600 nm is possibly not ideal. Indeed, the absorption maximum of C-phycocyanin is generally considered to be around 615 nm which is higher than the wavelength used for the study. Moreover, we noted on the spectra in Fig. 2a redshift effect which implies that the wavelength corresponding to this absorption maximum increases when the molecule was dissolved in the solvents studied. With this phenomenon, the wavelength adapted for the detection of the molecule shifts from 600 nm and to around 650 nm. The upper limit of 600 nm of the HPLC chain detector in our laboratory could be the reason for this variation in the quality of the results. However, the method based on the detection of the protein part at 280 nm remains reliable and will be used for the following studies using the adjusted relation (5) for the determination of the C-phycocyanin of AFA.
Allophycocyanin interference elimination
During the HPLC quantification of AFA samples, two main peaks were detected both with 280 nm and 600 nm detection wavelength (Fig. 10). For our study, only the first peak corresponding with the retention time of the c-phycocyanin standard was analysed. The study of (Zolla and Bianchetti 2001) on the separation and identification of the Synechocystis phycobilisome proteins by HPLC coupled with on-line electrospray ionization mass spectrometry shows a similar HPLC profile to that which we measured for AFA. There are 4 major peaks with the first two corresponding to the respective sub-units α and β of c-phycocyanin. They then tried to determine the correspondence of the two following peaks by SDS-PAGE and ESI-MS techniques and were able to show that the secondly eluted compound is allophycocyanin. As for c-phycocyanin, the peaks corresponded to the two different subunits of the allophycocyanin molecule. Even if the absorption maximum of c-phycocyanin occurs at 615 nm and that of allophycocyanin at around 650 nm (Murakami et al. 1981), the similarity of the absorption spectra of these two molecules causes non-negligible interferences during spectrophotometric determination. This is an important result since the separation by HPLC enables the proper differentiation of c-phycocyanin and allophycocyanin whose absorption wavelengths are very close. Thus, the method developed here avoids interference issues and enables very accurate measurements of c-phycocyanin. To further characterize the AFA pigments, it might be wise to repeat the method with an allophycocyanin standard of known purity to obtain an accurate equation for the determination of this second type of phycobiliprotein.
This work developed and demonstrated a reliable approach for AFA c-phycocyanin spectrophotometric quantification. Specific attention was given to quantifying the error in the commonly used spectrophotometric equations for compound quantification. Indeed, the results showed that certain assumptions commonly used for spectrophotometric quantification are too simplistic and are not adapted to variation between species, which can often result in significant differences between assays. Moreover, the correction using HPLC separation enables the proper differentiation of c-phycocyanin and allophycocyanin signals whose absorption wavelengths are very close. The method developed here avoids therefore interference issues and enables very accurate measurements of -phycocyanin. Thus, the correction of the spectrophotometric equations after HPLC method verification will enable further research on Aphanizomenon flos-aquae by improving the accuracy of the quantification system while maintaining speed and low-cost.
This study demonstrated that this spectrophotometric approach promises a great potential in the field of bioprocesses easy and reliable monitoring since it corresponds to the operational limits commonly encountered when driving typical experimental protocol for the cultivation of AFA strains in photobioreactors.
Acknowledgements
I am thankful to Jack HOENIGES for correcting the English of this paper.
Funding
The authors thanks the region Pays de la loire council for the fundings of this work into the scientific framework of the applicative chair “bone health”.
Competing interests
The authors have no competing interests.
Availability of data and material
The datasets generated and analyzed during the current study are available from the corresponding author on reasonable request.
Code availability
Note applicable.
Author contributions
All authors contributed to the study conception and design. Material preparations were performed by Delphine DROUIN and Julie BILLY, data collection and analysis by Julie BILLY. The first draft of the manuscript was written by Julie BILLY and Olivier GONCALVES commented on previous versions of the manuscript. All authors read and approved the final manuscript.
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No competing interests reported.