FOOD QUALITY CONTROL USING PEPTIDE BASED GAS SENSOR ARRAYS
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1 FOOD QUALITY CONTROL USING PEPTIDE BASED GAS SENSOR ARRAYS D. Compagnone, P. Pittia, C. Di Natale * Faculty of Biosciences and Technologies for Food Agriculture and Environment, University of Teramo, Italy *Department of Electronic Engineering, University of Rome Tor Vergata, Italy 3 International ISEKI Food Conference, Athens, May 2014, 21-23
2 Quartz crystal micro-balance -Cys-Gly 14 mm AT quartz 7 mm gold Resonant frequency 20 MHz
3 Why peptides? Easy synthesis Easy and fast support derivatization Large number of combination Possibility of biomimetic approach and virtual design GNP to increase sensor surface
4 Measurement system E-Nose N 2 1.Start 2.Cleaning 3.Equilibration 4.Baseline 5.Decrease 6.Stabilizzation Air
5 Measurement system E-Nose N 2 1.Start 2.Cleaning 3.Equilibration 4.Baseline 5.Decrease 6.Stabilizzation N 2
6 Measurement system E-Nose N 2 1.Start 2.Cleaning 3.Equilibration 4.Baseline 5.Decrease 6.Stabilizzation Headspace
7 Measurement system E-Nose N 2 1.Start 2.Cleaning 3.Equilibration 4.Baseline 5.Decrease 6.Stabilizzation Headspace
8 Measurement system E-Nose N 2 1.Start 2.Cleaning 3.Equilibration 4.Baseline 5.Decrease 6.Stabilizzation F Max
9 Measurement system E-Nose N 2 1.Start 2.Cleaning 3.Equilibration 4.Baseline 5.Decrease 6.Stabilization F Max F
10 250 Trimethylammine Ethanol F [Hz] , ppm L-Cys GSH GNP GNP-Cys GNP-Cys-Gly GNP-γ-Glu-Cys GNP-GSH F [Hz] , L-Cys GSH GNP GNP-Cys GNP-Cys-Gly GNP-γ-Glu-Cys GNP-GSH Hexan ppm %RH F [Hz] L-Cys GSH GNP GNP-Cys GNP-Cys-Gly F [Hz] L-Cys GSH GNP GNP-Cys GNP-Cys-Gly 50 GNP-γ-Glu-Cys GNP-GSH 500 GNP-γ-Glu-Cys GNP-GSH 0 593, ppm ppm
11 Model solutions (o.1 % aromas in solvent) D. Compagnone, G.C. Fusella, M. Del Carlo et al Biosensors and Bioelectronics 42, , 2013
![Modified GNPs GNP-Glutathione GNP-Cys-Gly [CG] GNP-Cys GNP-Thioglicolic Acid GNP-Cys-Arg-Gln-Val-Phe [CRQVF] GNP-Cys-Ile-His-Asn-Pro [CIHNP]](/docs-images/92/108172252/images/12-1.jpg "GNP-Cys-Ile-Gln-Pro-Val [CIQPV] GNP CRQVF CIHNP CIQPV Molecular Weight 651.79 582.68 558.7 Iso-electric point 9.01 7.15 5.")
12 Modified GNPs GNP-Glutathione GNP-Cys-Gly [CG] GNP-Cys GNP-Thioglicolic Acid GNP-Cys-Arg-Gln-Val-Phe [CRQVF] GNP-Cys-Ile-His-Asn-Pro [CIHNP] GNP-Cys-Ile-Gln-Pro-Val [CIQPV] GNP CRQVF CIHNP CIQPV Molecular Weight Iso-electric point Net charge at ph Estimated solubility Good Poor Poor
13 Real samples Chocolate Temperature: 40 C Equilibration time: 10 min 15g in 100 ml lab bottle grated and melted 4 L/h Standard Samples VS Off-flavoured samples PLS-DA analysis
14 Off-Flavour 3 methylbutanal Phenylacetaldehyde Acetic Acid Tetramethylpyrazine 2-acetylpyrrole 2-nonenal 2,4-decadienal (t,t) Process Fermentation volatiles Conching process Roasting Process Fat related (oxidation) Off-flavours were preliminarily added in the cocoa butter to achieve the concentration of 125 ppm. One tea spoon of contaminated cocoa butter was then added to 400 g of chocolate to obtain an estimated final concentration in the sample of ~ 6ppm.
15 Oxidised white chocolate Pentanal Hexanal Heptenal Nonanal Acetic Acid 2-Butoxyethanol
16 Electronic nose sensor arrays arrays GNP-Peptide based GNP-Glutathione GNP-Cys-Gly GNP-Cys GNP-Thioglicolic Acid GNP-Cys-Arg-Gln-Val-Phe GNP-Cys-Ile-His-Asn-Pro GNP-Cys-Ile-Gln-Pro-Val GNP Porphyrin based Cu-Buti-TPP Co-Buti-TPP Zn-Buti-TPP Mn-Buti-TPP Fe-Buti-TPP Sn-Buti-TPP H 2 -Buti-TPP Mg-Buti-TPP
17 Dark Chocolate White Chocolate Milk Chocolate
18 GNP-Peptide vs. Porphyrin Regular Off % Flavours Correct Regular Off flavours Tot. Correct: 100% Regular Off % Flavours Correct Regular Off flavours Tot. Correct: 100% Regular Off % Flavours Correct Regular Off flavours Tot. Correct: 98% Regular Off % Flavours Correct Regular Off flavours Tot. Correct: 92% Regular Off % Flavours Correct Regular Off flavours Tot. Correct: 81% Regular Off % Flavours Correct Regular Off flavours Tot. Correct: 82% D. Compagnone, M. Faieta, D. Pizzoni, C. Di Natale, T. Van Caelemberg, B. Behyedtc, P. Pittia, Sensors and Actuator B, submitted
![Candies 3 structuring agents Gelatine [Gel] Pectin [Pec] Gum Arabic [G.](/docs-images/92/108172252/images/19-0.jpg "Ar.] 2 aromas Natural [A] Synthetic[B] 2 concentrations 0.15% [1] 0.")
19 Candies 3 structuring agents Gelatine [Gel] Pectin [Pec] Gum Arabic [G.Ar.] 2 aromas Natural [A] Synthetic[B] 2 concentrations 0.15% [1] 0.30% [2]
20 GC-MS Pure Aromas GC Peak area (UA) 29 major compounds (25 identified with MS-spectra database) 4 compounds only in Natural aroma 4 compounds only in Synthethic aroma Strong differences in concentration for most compounds Volatile compunds Natural aroma Natural-identic aroma Ethanol α-methyl-butanal Ethyl-acetate Not identified Not identified Etihyl-propanoate nd Not identified ,2-propandiol Ethyl-isobutirrate Not identified nd Ethyl-butirrate Ethyl-α-methyl-butirrate Ethyl-β-methyl-butirrate Cis-3-hexenol α-pinene β-pinene β-myrcene nd Ethyl-hexanoate nd Octanal nd ,4-cineole nd O-Cymene Limonene Eucalyptol nd γ-terpinene α-terpinolene Nonanal cis-3-hexenil-isobutanoate Ethyl-octanoate nd Decanal
21 GC-MS Candies Compounds G.ar G.Ar Pec Pec Gel Gel A1 A2 A1 A2 A2 A2 Ethanol ethyl-acetate ethyl-butanoate 0,07 0, ethyl-α-methyl-butanoate ethyl-β-methyl-butanoate Cis-3-hexenol Ethyl-hexanoate Nd Nd Limonene 0, cis-3-hexenyl-iso-butanoate Nd Nd Decanal Nd Nd Natural aroma Compound peak area in candy Values = Compound peak area in pure aroma 10 compounds confirmed with analytical standard and monitored in candies as significant Compounds Synthetic aroma G.Ar B1 G.Ar B2 Pec B1 Pec B2 Gel B1 Ethanol Gel B2 ethyl-acetate ethyl-butanoate 0,14 0, ethyl-α-methyl-butanoate Nd Nd Nd Nd Nd Nd ethyl-β-methyl-butanoate Nd Nd Nd Nd Nd Nd Cis-3-hexenol Ethyl-hexanoate Np Np Np Np Np Np Limonene cis-3-hexenyl-iso-butanoate Nd Nd Decanal Nd Nd Nd Nd Nd Nd Nd=not detected; Np=not present in pure aroma
22 GC-MS Candies
23 GC-MS Candies Natural Synthetic
24 GC-MS Candies structuring PLS-DA
25 Electronic nose Structuring GNP-Peptide based Porphyrin based
26 GNP-Peptide based (aroma) Gelatin Arabic gum natural synthetic natural Pep 3 Cys Cys-gly Thioglycolic acid
27 Ongoing work Olive oil Gummy candies (synthethic vs. naturally extracted dyes ) Halal salami Coffee mixtures Cheese process
28 Peptide design Virtual screening 5 peptides studied (CG, Glutathione, CIHNP, CIQPV, CRQVF) VS 14 volatile compounds (different chemical classes, shapes, dimensions, hydrophobicity) Docking box generation 10 conformers for each peptide From 1 to 200 conformers for each volatile compound Binding score: average of all conformers Free software Common laptop Fast elaboration (~3min/peptide conformer)
29 Peptide design Virtual screening Glutathione CIHNP CRQVF CIQPV
30 Peptide design Virtual VS Experimental data Binding scores compared with real samples F data (T-test), after normalization Data having p-value>0.05 were considered statistically equivalent as positive match (marked with + ) 78% good matching
31 Peptide design Virtual VS Experimental data CG only 29% positive match Glut.: 71%. CRQVF: 71% CIHNP: 86% CIQPV: 93% Very bad matching with ethanol and 2-propanol Very good matching with Esters and Aldehydes Best matching with compounds with MW>60g/mol D. Pizzoni, M. Mascini,V. Lanzone, M. Del Carlo, C. Di Natale, Biosensors and Bioelectronics, 52, , 2014
32 Conclusions Development of GNP-peptide-based piezoelectric sensors Application to real samples for discrimination and sensing approach Development of a computational method with good correspondence between virtual and real data Creation of new sensors with peptides designed on specific purposes
33 Funding: Puratos Group, Belgium Gelco, Gruppo Perfetti, Italy
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