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Influence of physical and chemical properties of HTSXT-FTIR samples on the quality of prediction models developed to determine absolute concentrations of total proteins, carbohydrates and triglycerides: a preliminary study on the determination of their absolute concentrations in fresh microalgal biomass

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Abstract

Absolute concentrations of total macromolecules (triglycerides, proteins and carbohydrates) in microorganisms can be rapidly measured by FTIR spectroscopy, but caution is needed to avoid non-specific experimental bias. Here, we assess the limits within which this approach can be used on model solutions of macromolecules of interest. We used the Bruker HTSXT-FTIR system. Our results show that the solid deposits obtained after the sampling procedure present physical and chemical properties that influence the quality of the absolute concentration prediction models (univariate and multivariate). The accuracy of the models was degraded by a factor of 2 or 3 outside the recommended concentration interval of 0.5–35 µg spot−1. Change occurred notably in the sample hydrogen bond network, which could, however, be controlled using an internal probe (pseudohalide anion). We also demonstrate that for aqueous solutions, accurate prediction of total carbohydrate quantities (in glucose equivalent) could not be made unless a constant amount of protein was added to the model solution (BSA). The results of the prediction model for more complex solutions, here with two components: glucose and BSA, were very encouraging, suggesting that this FTIR approach could be used as a rapid quantification method for mixtures of molecules of interest, provided the limits of use of the HTSXT-FTIR method are precisely known and respected. This last finding opens the way to direct quantification of total molecules of interest in more complex matrices.

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Abbreviations

ATR:

Attenuated total reflectance

FTIR:

Fourier-transform infrared spectroscopy

HTSXT:

High-throughput screening extension

PLS-R:

Partial least square regression

PCA:

Principal component analysis

CA:

Correspondence analysis

HCPC:

Hierarchical clustering on principal components

HCCA:

Hierarchical clustering on correspondence analysis

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Acknowledgments

Part of this work was funded by the French National Research Agency project DIESALG (ANR-12-BIME-0001). The authors thank undergraduate student Véronique Airiau for her preliminary work performed on ATR-FTIR.

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Authors and Affiliations

  1. Université de Nantes, GEPEA UMR CNRS 6144, Bât. CRTT, 37 bd de l’Université, BP 406, 44602, Saint-Nazaire Cedex, France

    Esteban Serrano León, Rémy Coat, Benjamin Moutel, Jérémy Pruvost, Jack Legrand & Olivier Gonçalves

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  1. Esteban Serrano León
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  2. Rémy Coat
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  3. Benjamin Moutel
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  4. Jérémy Pruvost
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  5. Jack Legrand
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  6. Olivier Gonçalves
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Corresponding author

Correspondence to Olivier Gonçalves.

Additional information

E. Serrano León and R. Coat contributed equally to this work.

Electronic supplementary material

Below is the link to the electronic supplementary material.

449_2014_1215_MOESM1_ESM.pdf

Fig. S1. Microscopic observations of the spots formed after drying the deposits of solutions of model molecules. Frist line corresponds to three amounts of BSA, second line to three amounts of tripalmitate, third line to three amounts of glucose, and fourth line to three amounts of the mixture of glucose plus BSA (20 µg). (PDF 2758 kb)

449_2014_1215_MOESM2_ESM.pdf

Fig. S2. FTIR raw spectra shape variation observed according to the amount of deposited quantity of matter. Left panel corresponds to several amounts of BSA mixed with 1 µg of KSCN (internal standard), right panel to the glucose mixed with 1 µg of KSCN (internal standard) and 20 µg of BSA (stabilizer). The amounts of deposited matter are indicated on each panel on the spectra, and range from 1 µg to 150 µg of tested compound. On the x axis are wave numbers (cm−1) and on the y axis absorbance values. (PDF 285 kb)

449_2014_1215_MOESM3_ESM.xls

Table S1. Characteristics of the linear models obtained for the determination of the limit of linearity of the FTIR analytical approach according to the different rupture points. The points surrounding the strong shifts observed in the solvatochromic study were also taken into account, i.e., 0.5, 30, 35, 40, 95, 100, 150 µg.spot−1. The reference data obtained in [9] are also indicated. (XLS 35 kb)

449_2014_1215_MOESM4_ESM.xls

Table S2. Quality parameters for cross and test set validation of the PLS-R selected for the quantitative prediction of the model macromolecules. RMSECV stands for root mean square error of cross-validation. RMSEP stands for root mean square error of prediction. R² is the coefficient of determination (predicted vs. actual concentration in the calibration (CV) or validation set (EP)). Rank corresponds to the number of latent factors in the selected PLS-R model (calibration (CV) or validation set (EP)). The models were generated in the range 1,900–950 cm−1. The median and average values of the statistical parameters are indicated at the bottom of the table. (XLS 34 kb)

449_2014_1215_MOESM5_ESM.xls

Table S3. Quality parameters for cross and test set validation of the PLS-R selected for the quantitative prediction of a mixture of model macromolecules. BSA (BSA + Glc) refers to the specific prediction of BSA amount in the mixture of glucose + BSA. Glc (BSA + Glc) refers to the specific prediction of glucose amount in the mixture of glucose + BSA. RMSECV stands for root mean square error of cross-validation. RMSEP stands for root mean square error of prediction. R² is the coefficient of determination (predicted vs. actual concentration in the calibration (CV) or validation set (EP)). Rank corresponds to the number of latent factors in the selected PLS-R model (calibration (CV) or validation set (EP)). The models were generated in the range 1,900–950 cm−1. The median and average values of the statistical parameters are indicated at the bottom of the table. (XLS 28 kb)

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Serrano León, E., Coat, R., Moutel, B. et al. Influence of physical and chemical properties of HTSXT-FTIR samples on the quality of prediction models developed to determine absolute concentrations of total proteins, carbohydrates and triglycerides: a preliminary study on the determination of their absolute concentrations in fresh microalgal biomass. Bioprocess Biosyst Eng 37, 2371–2380 (2014). https://doi.org/10.1007/s00449-014-1215-4

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  • DOI: https://doi.org/10.1007/s00449-014-1215-4

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