Introducing 

Prezi AI.

Your new presentation assistant.

Refine, enhance, and tailor your content, source relevant images, and edit visuals quicker than ever before.

Loading…
Transcript

INTRODUCTION

MATERIAL

REFERENCES

Immunochemical methods

Hofmann, Fischer, Mueller, and Babel (1999)

  • Identification: used ELISA kit for gelatin and gelatin-containing products
  • Results: influenced by:

i) gelatin type

ii) gelatin quality

iii) concentration used

iv) led to false negative or positive readings (in some cases)

  • Very high homology between collagen sequences of mammals makes their immunochemical differentiation difficult when polyclonal antibodies raised against the whole molecule are used.
  • To overcome the challenge: highly specific antibodies was produced, immunized rabbits against putative species-specific sequences of the bovine collagen alpha 1(I) chain
  • Disadvantages:

i) antibodies were found to be very sensitive to the alkaline or acidic process used for the gelatin

production

ii) not enough species-specific to allow a sensitive detection of mixture of low concentration of bovine

gelatin in porcine gelatin

Chromatographic methods

Spectroscopy method

Cao & Xu, 2008; Muyonga, Cole,& Duodu, 2004

Nemati, Oveisi, Abdollahi, and Sabzevari (2004)

Determination of gelation and intermolecular cross-linking of collagen and proteins: FTIR spectroscopy with attenuated total reflectance (ATR) or transmission accessories

Hashim et al. (2010)

  • Using HPLC-based separation and determination of amino acids in gelatin using principal component analysis (PCA),
  • Result: good differentiation between bovine and porcine gelatins.
  • Analysis procedure: complete hydrolysis by classic acid hydrolysis.
  • Separation and determination of aminoacids: reversed-phase HPLC (RP-HPLC) following pre-column derivatization.
  • Principal component analysis (PCA) with the MATLAB program was used to differentiate these gelatins.
  • However, due to the large (close) similarity in structure and properties of gelatins from different origins, the methods based on HPLC and calcium phosphate precipitation have not been proved yet to be able to detect bovine and porcine gelatin in their mixture
  • Used Fourier Transform Infrared (FTIR) spectroscopy for differentiation of bovine and porcine gelatins.
  • Determination: used deformation of N–H bonds found in the range 3290–3280 and 1660–1200 cm1 within infrared spectra
  • Analyzed using discriminant analysis. These regions were found to give information about the origin of the gelatin.
  • However, this method was concluded to need repeated results.

Other potential method:

Material

PCR-based methods

Tasara, Schumacher, and Stephan (2005)

  • This method evaluated the performance of published species-specific PCR systems
  • In their study, most of the species-specific PCR systems tested were able to discern species of origin for tissue-derived DNA, but not for gelatin DNA templates.
  • Reason: linked to extensive target DNA degradation in gelatin, they envisaged that the majority of species-specific PCR assays applied to other food samples might not be ideal for use with gelatin.
  • Evaluation: only PCR assays designed to detect short regions of highly abundant sequences seemed suited for determination of the species of origin for gelatin samples.
  • Conclusion: species-level DNA detection could be achieved only with primers targeting short regions (104–134 bp) of 16S rRNA, ATPase 8 subunit, and PRESINE 1 element sequences in the different gelatin samples tested.

Chemisorption method

  • Porcine gelatin type A from porcine skin (G2500) was purchased from Sigma–Aldrich (St. Louis, MO, USA).
  • Halal certified bovine gelatin type B (230 bloom) was purchased from m-haditec GmbH & co. KG (Hermann-Köhl-Str.7, D-28199, Bremen, Germany).
  • Powdered gelatin samples were diluted with 2 fold volume of distilled water and dissolved in boiling water by stirring constantly until completely transparent point before their addition into dairy products.
  • Acetonitrile (LC–MS grade)
  • Water (LC-MS grade)
  • Dithiothreitol (DTT)
  • Trifluoroacetic acid (TFA)
  • Formic acid (FA)
  • Iodoacetamide (IAA),
  • Sequencing grade modified trypsin (proteomic grade) and picric acid were purchased from Sigma–Aldrich.
  • Ammonium bicarbonate (NH4HCO3) was purchased from Fluka.
  • RapiGest, an MS compatible detergent
  • The internal standard (massPREP yeast alcohol dehydrogenase digestion standard, Uniprot Accession # P00330) were provided from Waters Corp., Milford, MA.

Hunter, Nyburg,and Pritzker (1986)

Amorphous calcium phosphate (ACP)

promote by

collagen, gelatin, and agarose gels

Hydroxyapatite (HAP)

=HAP is a compound which is formed by chemisorption of gelatin

Hidaka and Liu (2003)

• Using in vitro formation of calcium phosphate precipitates.

• Study on the reaction of calcium phosphate precipitation

• Need further study to clarify these effects.

Mass spectrometric methods

Ocana et al. (2004)

  • Reported: some species specific ions could be detected using mass spectroscopy after bovine gelatin was hydrolyzed with 3 mol/L HCl, which could be used for detection of bovine gelatin.
  • However, the content of target ions might be influenced by the hydrolysis time and temperature.

Zhang et al. (2009)

OBJECTIVES

  • Detection and identification: marker peptides in digested gelatins by trypsin, and the resulting peptides were analyzed by high performance liquid chromatography/tandem mass spectroscopy(HPLC–MS/MS).
  • Successfully detect the marker peptides specific for bovine and porcine in the digested bovine and porcine gelatin
  • Other finding: peptide identification was remarkably influenced by proline hydroxylation.
  • Conclusion: it was necessary to manually verify the sequence for peptides (GPPGSAGSPGK and GPPGSAGAPGK detected in digested bovine and porcine gelatin, respectively) since there might be a risk to confuse the proline hydroxylation with the mass difference between Ser and Ala residues.
  • They concluded that detection of marker peptides in the digested gelatin sample using HPLC–MS/ MS was an effective method to differentiate between bovine and porcine gelatin.
  • However, the method also has some drawbacks.

i) During MS/MS data processing, the threshold for specific peptide identification might be different from

one species to another - very high homology between the collagen sequences of mammals

ii) proline hydroxylation is another challenge making identification of peptide more difficult than most of the

proteins

Alternative

Fish gelatine

Other previous study

in developing method

of source detection on gelatin

To establish proteomics based alternative method that can be applicable to gelatine differentiation in food system

Fact : pig skin and bovine hide-derived gelatins constitute a great majority of yearly gelatin production scale around the world

to develop analytical methods intended to detect the species origin of gelatin

Issue:

Outbreak of BSE

(Bovine Spongiform Encephalopathy)

Religious beliefs and convictions

(Islam ; Judaism ; Hinduism)

on consumption or the use of porcine derived gelatin in food materials

on use of bovine gelatin for human consumption, cosmetic and pharmaceutical products.

(Venien & Levieux, 2005).

Gelatine & Issue related:

Gelatin produced nearly 326,000 tons a year

(46%) pig skin-derived

Challenge

(29.4%) bovine hides

  • It is one of the proteomic methods that are based on data independent acquisition mode.
  • In terms of precursor ion selection, there are two distinct methods.

i) Data dependent acquisition mode, a

precursor ion is selected and fragmented for

sequencing.

ii) Data independent acquisition mode, rather

than selecting a precursor, a nonoverlapping

m/z window is selected and all the precursor

ions within the window are co-fragmented

  • Characterization of complex analytes and mixtures of complex compounds.
  • In this respect, ion mobility and the UPLC/MSE data-independent acquisition mode of the SYNAPT HDMS appears to be a promising solution,
  • It allow to achieve unrivalled analytical selectivity for the most confident and comprehensive characterization of complex analytes and mixtures of complex compounds
  • Unprecedented sensitivity at lower concentrations, which has not been ever achieved by any other high resolution mass spectrometry system (Wallace, 2011)

Fig. 4 shows fragment ion information for three of the peptides identified.

(23.1%) bones

nanoUPLC-ESI-qTOF-MSE analysis of gelatin extracted from the food samples

(1.5%) other sources (Karim & Bhat, 2009).

Fig. 4C. is a good candidate for a specific bovine peptide was IGQPGAVGPAGIR because there were no post translational modifications observed and it was identified with high confidence.

  • Precursor mass error =0.4051 ppm
  • Product mass errors =19.8187 ppm
  • The findings showed that unique peptides from both porcine and bovine gelatin were ionized and detected.
  • The method has the potential for the development of other methods to be employed in triple quadrupole instruments where peptides with similar sequences can be effectively filtered and only unique sequences can be analyzed.
  • The ability to detect multiple species specific peptides from bovine and porcine provides unambiguous identification of gelatin origin.

Fig. 4B shows an example for proline side chain hydroxylation, where a unique porcine peptide with the sequence GFP*GSP*GNVGPAGK was detected with two hydroxylations.

Process that causes spectrum processing sequence determination more complex

i) 2 hydroxylation detected;

  • Unmodified mono isotopic mass of the peptide = 1240 m/z;
  • However, two proline hydroxylations added another 32 Da.
  • Resulting, the hydroxylated porcine peptide was identified as 1274 m/z.

ii) Deamidation of asparagine in the peptide.

  • Caused the addition of 1 Da in result of detected m/z.

Therefore, it will be better to pick unmodified peptides, as was observed for the peptide in fig 4C

nanoUPLC-ESI-qTOF-MSE analysis of gelatin extracted from the food samples

Fig. 4A is the MS/MS spectrum for one of the unique porcine peptides with the sequence GETGPAGPAGPVGPVGAR.

  • The peptide was identified as a doubly charged ion.
  • Precursor mass error was 1.3362 ppm (0,0021 Da)
  • Product ion mass error was 12,1878 ppm.
  • Peptide sequence was calculated based on 31-b and -y ions which was a high confident identification for a peptide at this length with almost complete sequential readout.

Previous research reported that:

  • Intra- and extracellular enzymes cause collagen to often undergo several post-translational modifications. (Kagan, 2000)
  • Approximately, 18% of the aminoacids in the collagens is proline, indicating thus, the importance of analyzing the hydroxylation sites of proline for sequence verification (Zhang et al., 2009).
  • Proline hydroxylation is known to play an important role for the collagen properties such as stability, antigenicity and mechanical properties (Arbogast, Gunson, & Kefalides, 1976; Mizuno, Hayashi, & Bächinger, 2003; Vitagliano, Berisio, Mazzarella, & Zagari, 2001).
  • On the other hand, gelatin peptides have many prolines in their amino acid sequences and it is evident that many of the proline side chains can undergo hydroxylation. If not examined carefully, hydroxylated proline side chain can be mistaken as leucine side chain.

Other potential method

Standard gelatin of bovine/porcine

Standard gelatin from bovine and porcine was added to food systems

Extracted (based on the modified method above)

ESI-qTOF-MSE

(electrospray ionization quadrupole time-of-flight)

Gelatin peptides

Analysis

The number of peptides identified in these samples was lower

But still multiple unique peptide Identified for porcine and bovine

For example:

All of sample added with porcine gelatin was identified to had 1 of porcine specific peptides, which have

  • Peptides sequence : GPPGESGAAGPAGPIGSR &
  • Identified with 34-b and -y ions
  • Precursor mass error = 0.29ppm
  • Product mass errors= 20.8 ppm, respectively.

Gelatin

Journal paper:

RESULT

&

DISCUSSION

Advantages

Gelatin is a protein based product

  • derived from the fibrous protein collagen
  • produced by partial denaturation of native collagen extract from skins, bones and connective tissue of animals like bovine and porcine

Proteomics analysis based alternative methods that can be applicable to gelatin differentiation in real food systems.

i. MSE method had advantages on complex mixture analysis

because it based on parallel collision-induced-dissociation of

peptides and provides masses of the precursor and fragment

ions in parallel (Purvine, Eppel, Yi, & Goodlett, 2003).

ii Gives a unique opportunity to the researchers to selectively

and accurately study the shape of molecules, which are

beyond the reach of traditional techniques like NMR, electron

microscopy, and X-ray crystallography.

iii Compared to any other high resolution mass spectrometer,it

can be used to identify and quantify sample analytes at

lower concentrations by ion mobility separations.

  • A significant increase in sensitivity and unrivalled selectivity and analytical peak capacity can be achieved by ion mobility separations.
  • In addition, with this technique, it is possible to easily and routinely reveal details about complex samples that were previously difficult or impossible to obtain.
  • it was conducted using a new high definition mass spectrometer technique; a label-free nanoUPLC-ESI-qTOF-MSE system;
  • nanoUPLC (nano ACQUITY ultra performance liquid chromatography)
  • SYNAPT HDMS (high definition mass spectrometer with nanolockspray ion source)

X-Y is generally

  • proline
  • 4 hydroxyproline
  • The most striking attribute of the collagen molecule is that its amino acid sequence is composed of repeated tripeptide unit indicated by:

Glycine - X - Y

  • Regarding to primer struture of gelatine, it contain
  • Basic amino acid
  • 2.5% lysine
  • 5% arginin
  • Acidic amino acid
  • 7.2% glutamic acid
  • 4.7% aspartic acid

GELATIN

Fig. 3 shows the peptides identified from standard porcine and bovine digests with different m/z values.

Figure 2 shows the total ion chromatograms for bovine and porcine standard gelatins tryptic digests acquired over 50-1600m/z

  • Tables 1 and 2 listed the unique porcine and bovine specific peptides that were identified from the analysis of the standard gelatin samples.
  • Percentage of peptides identified in standard gelatin sample = around 30%
  • Based on gelatin sequence obtained from literature review and protein database, it was possible to achieve over 90% sequence coverage with the IdentityE approach.
  • The software itself with its ion accounting informatics tools which accounts for 14 different physicochemical attributes increases the calculated sequence coverage that enables better identification.

  • Identified peptides show:
  • their respective ionization states where some peptides were doubly and triply charged, thus leading the actual masses could not be reflected by the m/z values
  • the peptide m/z values are in charge state deconvoluted; but the actual masses are listed in Table 1 and 2.
  • Spectra were recorded in the range of 50–1600 m/z
  • but peptide signal was obtained in the range of 300–900 m/z, causes by multiply charged ionisation states
  • all of the gelatin peptides in the respective ionization states appear in the range of 300– 900 m/z
  • on the other hand, the spectra mostly contained common peptide signals,
  • But this did not affect the identification power of the setup since

- the peptides were separated over 90 min before analyzed in the mass spectrometer

- high mass resolution (>10,000) achieved to increased mass accuracy of the peptide analysis, which, in turn, provided

high confidence in deducing peptide sequence information.

  • The identified peptides were present in different charged states and deconvolution provided the peptide m/z values in their singly charged state.
  • NanoUPLC-ESI-q-TOF-MSE enabled to elute peptides in different samples at similar retention times.
  • Overlay of the triplicate analyses showed excellent reproducibility in elution times (data not shown).
  • Each analysis, around 200 ng of tryptic digest was loaded on the column and chromatographic separation was run for 2 hours at 5–40% 90 min ACN gradient for effective separation of peptides.
  • The ion chromatograms show:

- distinct differences in the elution profiles along with many similar peptide elutions.

- identification of the lower abundant peptides which otherwise might be masked by the abundant peptides in the mixture.

  • After the chromatographic separation, the peptides were infused to into the mass spectrometry source for the analysis.

In the IdentityE approach, an alternate scanning mode was applied, by which

- peptide information was collected at low collision energy

- peptide sequence information was collected at ramped higher collision energy.

In this way, more fragment ions per peptide and more peptides per protein were detected

Presenter:

A novel method to differentiate bovine and porcine gelatins in food products: NanoUPLC-ESI-Q-TOF-MSE based data independent acquisition technique to detect marker peptides in gelatin

Absolute quantification by MSE

  • Absolute quantification without the use of specific internal calibrants is very useful and straight forward.
  • The method is very useful for both simple and complex protein mixture analysis (Silva, Gorenstein, Li, Vissers, & Geromanos, 2006).
  • However, the method is inherently not useful to analyze gelatin mixtures because the three most intense peptides from bovine and porcine might well be the same since both gelatin types share large homology.
  • Sequence variation between bovine and porcine type 1 collagens = 3% (according to result in uniprot database & patented work of Bell, Neff, Polarek, & Seeley, 2001 )
  • Homology sequence analysis shows variation in 30 theoretical gelatin peptide sequences out of around 120 possible peptides (according to Zhang et al., 2009).
  • Therefore, we are working on the method to quantify gelatin mixtures, which will need filtering similar peptides and analyze unique marker peptides.

MAISARAH SHAMSUDIN

Tryptic gelatin peptides

  • nanoUPLC-ESI-qTOF-MSE methodology can be an effective and fast way to identify the gelatin origin.

  • The sequence should be verified manually because the mass shift caused by proline hydroxylation may be confused with the mass difference for example, between Ser and Ala residues

  • According to Zhang et al. (2009) has drawn attention to the fact that the searching results should be further verified, and the number and continuity of the b and y ion series in the MS/MS spectra should be taken into consideration.

  • Accordingly, this was evident in the number of consecutive b and y ions detected for a peptide and the higher number of sequence coverage obtained for protein identification.

90

Bovine

10

50

Standard gelatin samples were mixed ratios

(analyzed in triplicate)

10

50

90

Porcine

Absolute quantification by MSE

• Although there is a large homology between the two gelatin sources,

nano liquid chromatography was able to separate the unique peptides

which were identified using the IdentityE method.

• Even when bovine gelatin standard was 9-fold in excess, it was still

possible to identify porcine peptides in the mixture.

• Therefore, it is reasonable to speculate that, with some calibration to

the method, it might be possible to detect much lower contamination

of porcine gelatin in bovine or vice versa.

Analysis of mixtures

METHOD

Production of dairy samples

Protein Identification

Electrospray ionization quadrupole time-of-flight mass spectrometry (nanoUPLC-ESI-qTOF-MS) analysis

Production of yogurt

Gelatin extraction from the dairy product

Sample preparation for analysis

Protein identification

It was cooled rapidly to 65oC

Cow milk was heated up to 90oC for 15 second in a boiler

Gelatin solution (either porcine or bovine) was added to the milk at the level of 0.1% (w/v)

Homogenized by stirring and temperature was reduced to 45oC

Raw data for peptide sequences

  • processed with ProteinLynx Global Server v2.4 (Waters Corp., Milford, MA)
  • searched with the IDENTITYE algorithm against a custom gelatin database that has species specific tryptic peptide sequences.

1. The internal standard amino acid sequence (yeast alcohol dehydrogenase, Uniprot accession # P00330) was included in

the FASTA file of the database.

2. The peptide sequences were acquired from the uniprot database and from an earlier published work (Zhang et al., 2009).

3. The Apex3D data preparation parameters were set to

  • chromatographic peak width : 0.2 min
  • TOF resolution : 10,000 MS,
  • low energy threshold : 150 counts
  • elevated energy threshold : 50 counts
  • intensity threshold : 1200 counts

4. Database search query was set to

  • minimum 3 fragment ion matches per peptide
  • minimum 7 fragment ion matches per protein
  • minimum 1 peptide matches per protein
  • 1 missed cleavage

5. Variable modification were set for

  • Carbamidomethyl- cysteine fixed modification and Acetyl N-TERM
  • Deamidation of asparagine and glutamine
  • Oxidation of methionine and proline hydroxylation

6. Absolute quantification of the peptides was calculated with the Hi3 functionality of the IDENTITYE system using the spiked

known amount of the internal standard.

7. The false positive rate (FPR) against the random database was set to 4% (according to ProteinLynxGlobal (PLGS) server

workflow).

8. Baseline for peptide selection for protein identification was based on many peptides, 3 fragments per peptide and 7

fragments per protein

9. Protein identifications were manually checked for almost complete consecutive fragments for sequence accuracy

Mixture was inoculated with 2% commercial yoghurt culture of Lactobacillus delbrueckii subsp. bulgaricus and Streptococcus thermophilus

Then, it was stored at 3oC to cooled down and to terminate acid development.

Mixture was incubated at 43oC until pH decreased to about 4.5

Gelatin extraction from the dairy product

Sample preparation for analysis

Electrospray ionization quadrupole time-of-flight mass spectrometry (nanoUPLC-ESI-qTOF-MS) analysis

2 mg of gelatin standard and the gelatin extracted (yoghurt, cheese or ice cream) were mixed with 1 mL of 50 mM NH4HCO3

  • There was no previous study reported to detect marker protein of food product by using mass spectrometric
  • Proteinaceous material present in food product may affect the accuracy of mass spectrometric
  • To obtain gelatin, all protein must be precipitate to facilitates separation of trypic peptides by reverse phase chromatography and analyzing on the SYNAPT HDMS.
  • In gelatin extraction procedure, picric acid is used to form gelatin–picric acid

Sample was sonicated with an ultrasonic homogenizer (10 s on, 10 s off, 3 cycles).

picric acid

The mixture was centrifuged at 15,000 rpm and filtered through a 0.22 µm syringe filter.

Food product (gelatin present)

gelatin-picric acid precipitation

10 µL of the filtered homogenate was mixed with 40 µL of 50mM NH4HCO3.

  • Precipitate which can be finely divided
  • More liable to remain in suspension
  • Precipitates slowly
  • Adheres tenaciously to the bottom of the container and difficult to rinse it.
  • When kept overnight, precipitate gain sticky deposit adhere to bottom of container

5 mM DTT was added to the mixture and it was incubated at 60oC for 15 min.

10 mM IAA was added to the mixture and then, incubated in the dark at room temperature for 30 min.

picric acid

1) Prior to the injection:

  • columns were equilibrated with
  • 97% mobile phase A (water with 0.1% FA)
  • 3% mobile phase B (acetonitrile with 0.1% FA).
  • column temperature was set to 35oC.

2) 2µl volume of sample (containing 200 ng of tryptic peptide mixture) was loaded on the nanoUPLC-

ESI-qTOF-MSE system;

  • First, peptides were trapped
  • nano-ACQUITY UPLC Symmetry C18 Trap column (5µm particle size, 180 µm i.d x 20mm lenght)
  • 5 µl/min flow rate for 5 min.
  • Peptides were separated from the trap column by gradient elution to an analytical column
  • nanoACQUITY UPLC BEH C18 Column (1.7 µm particle size, 75 µm i.d.x 250 mm length)
  • 300 nl/min flow rate with a linear gradient from 5% to 40% acetonitrile over 90 min.

3) Data independent acquisition mode (MSE) was carried out by

  • operating the instrument at positive ion V mode
  • applying the MS and MS/MS functions with:

- 6V low energy

- 15-40 V high energy collision

- over 1.5 s intervals

  • Capillary voltage was set to 3.2kV
  • Source temperature was set to 80oC

4) The internal mass calibrant Glu-fibrinopeptide was infused at every 45 s through the nanolockspray

ion source at 300 nl/min flow rate.

5) Peptide signal data were collected between 50–1600 m/z values.

Food product (gelatin absent)

picric acid precipitation

Production of cheese

50 µL of 0.4% Rapigest in 50 mM NH4HCO3 and 1 µg of proteomics grade trypsin (50 µl, 20 ng/µl) in 50 mM NH4HCO3 was added to the mixture and it was incubated at 37oC for 16 h.

  • Precipitates that are flocculent
  • Can separate readily
  • Do not adhere to walls of container and can be easily removed by rinsing water.

3 µL of TFA and 2 µL ACN was added to the mixture and was incubated at 60oC with constant shaking at 600 rpm for 2 hour

cooled down to 65oC

cooled down to 40oC

Raw milk was pasteurized at 85oC for 5 min

Gelatin solution (either porcine or bovine) was added at the level 0.1% (w/v)

During Rapigest removal, standard ADH tryptic digest internal calibrant was added to a final concentration of 50 fmol/µL.

  • In relatively high gelatin concentration (1%), picric acid precipitate is voluminous and precipitates more quickly.
  • Therefore, for extraction of the gelatin present in the dairy products in this study, the gelatin-picric acid precipitation technique was used. In this respect, the A.O.A.C. official method (AOAC, 2000) as outlined by Stokes (1897) was modified.

The mixture was made up to 200 µL volume by addition of appropriate amounts of 50 mM NH4- HCO3 buffer.

The resulting mixtures had 100 ng/µLtryptic peptide concentration.

0.02% (w/v) of CaCl2 was added to the mixture

After Rapigest cleavage, the mixture was centrifuged at 15,000 rpm for 15 min and an aliquot was taken into a LC vial for analysis and the rest of the tryptic peptides were stored at -86 oC.

Rennet of microbial origin (Mucormiehei) was added & kept at 32oC for 90 min to complete coagulation.

The coagulum was cut into 1–3 cm3 cubes and the curds rested for 5–10 min.

Finally, the cheese blocks were placed in plastic containers filled with brine (12% w/w NaCl) and stored at 5 oC.

It was pressed, molded and salted in brine (12% (w/w) NaCl) at 15oC for 8 h.

Drained for 25 min

Procedure to extract gelatin

6) Label-free proteomics methodology was successfully used for complex mixture analysis.

Fig. 1 shows the experimental flow chart for the analysis applied in this study.

Mercury (Hg) dissolved in twice its weight of nitric acid and this solution was diluted 25 times to its volume with water

20 g of sample was added to 20 mL of acid Hg(NO3)2 solution to precipitate all proteins except for gelatin.

Production of ice cream

The mixture was shaken and added with 40 mL distilled water

Ingredients of:

The mixture was shaken again

The ingredients (except for emulsifier and gelatin) were mixed and pasteurized at 85oC for 15 min with constant stirring.

Cooled down rapidly to 50oC

Then, the mixture was let stand for 5 min and filtered into a test tube.

  • milk (75 g/100 g)
  • sucrose (15 g/100 g)
  • cream (7 g/100 g)
  • emulsifier (0.5 g/100 g)
  • stabilizer (including starch 12%, moisture 9%, invert sugar 3.5%, fat 2.3%, protein 4.5 g%, ash 2 g% and mucilage 60.2 g%) (0.5 g/100 g)
  • 0.1% gelatin (either porcine or bovine)

An equal volume of saturated aqueous picric acid solution was added to the portion of filtrate in the test tube. The presence of gelatin was confirmed by formation of yellow precipitate.

Homogenized for 3 min

7) After the gelatin extraction from the food materials, carbamidomethyl-cysteine modification was applied and the peptides were

generated by overnight trypsinization.

8) Tryptic peptides generated were then separated prior to mass spectrometry analysis.

  • There was a great deal of homology when it came to bovine and porcine gelatin sequences so it was expected that most of the tryptic peptides would be similar (hydrophobicities)
  • In order to identify the species specific peptides especially for mixture analysis; therefore, it will be but most important

-to separate most of the peptides

-detect the different among all the similarity.

Test tube was centrifuged for 15 min at 1200g (Nuve, NF400/R model, Turkey) and drained.

The ice cream mix was then stored at 4oC for 24 h for ageing

Gelatin precipitate adhered tenaciously to the bottom and walls of the tube was collected using a spatula and transferred into vials after washed with distilled water.

The emulsifier and gelatin solution were then added and the mixture was beaten in an ice-cream maker at -20oC for 15 min.

It was then cooled down to - 20 oC in a freezer and stored under this condition until analysis.

Pak, H., Pasquarello, C., & Scherl, A. (2011). Label-free protein quantification on tandem mass spectra in an ion trapping device. Journal of Integrated OMICS. http://dx.doi.org/10.5584/jiomics. v2011i2011.45.

Purvine, S., Eppel, J. T., Yi, E. C., & Goodlett, D. R. (2003). Shotgun collision-induced

dissociation of peptides using a time of flight mass analyzer. Proteomics, 3, 847–850.

Schrieber, R., & Gareis, H. (2007). Gelatine handbook. Weinhem: Wiley-VCH GmbH &

Co.

Shadforth, I., Dunkley, T., Lilley, K., Crowther, D., & Bessant, C. (2005). Confident protein identification using the average peptide score method coupled with search specific, ab initio thresholds. Rapid Communications in Mass Spectrometry, 19, 3363–3368.

Silva, J. C., Gorenstein, M. V., Li, G. Z., Vissers, J. P. C., & Geromanos, S. J. (2006). Absolute quantification of proteins by LCMSE. Molecular & Cellular Proteomics, 5, 144–156.

Stokes, A. (1897). The detection of gelatin in cream. Analyst, 22, 320a–320a.

Tasara, T., Schumacher, S., & Stephan, R. (2005). Conventional and real-time PCRbased approaches for molecular detection and quantitation of bovine species material in edible gelatin. Journal of Food Protection, 68, 2420–2426.

Termine, J. D., Peckauskas, R. A., & Posner, A. S. (1970). Calcium phosphate formation in vitro II. Effects of environment on amorphous-crystalline transformation. Archives of Biochemistry and Biophysics, 140, 318–325.

Venien, A., & Levieux, D. (2005). Differentiation of bovine from porcine gelatines using polyclonal anti-peptide antibodies in indirect and competitive indirect ELISA. Journal Pharmaceutical and Biomedical Analysis, 39, 418–424.

Vitagliano, L., Berisio, R., Mazzarella, L., & Zagari, A. (2001). Structural bases of collagen stabilization induced by proline hydroxylation. Biopolymers, 58, 459–464.

Zhang, G., Liu, T., Wang, Q., Chen, L., Lei, J., Luo, J., et al. (2009). Mass spectrometric detection of marker peptides in tryptic digests of gelatin: A new method to differentiate between bovine and porcine gelatin. Food Hydrocolloids, 23, 2001–2007.

AOAC (2000). A.O.A.C 17th edn, 2000 Official Method - 920.106 Gelatin in Milk and Milk products.

Arbogast, B. W., Gunson, D. E., & Kefalides, N. A. (1976). The role of hydroxylation of proline in the antigenicity of basement membrane collagen. The Journal Immunology, 117, 2181.

Bell, M. P., Neff, T. B., Polarek, J. W., & Seeley, T. W. (2001). Animal collagen and gelatins. World Patent, PCT/034647.

Cao, H., & Xu, S. (2008). Purification and characterization of type II collagen from chick sterna cartilage. Food Chemistry, 108, 439–445.

Cole, C.G.B. (2001). Gelatine: Its Properties and Its Application in Dairy Products. Presented at the Dairy Symposium.

Hashim, D., Man, Y., Norakasha, R., Shuhaimi, M., Salmah, Y., & Syahariza, Z. (2010). Potential use of Fourier transform infrared spectroscopy for differentiation of bovine and porcine gelatins. Food Chemistry, 118, 856–860.

Hidaka, S., & Liu, S. (2003). Effects of gelatins on calcium phosphate precipitation: A possible application for distinguishing bovine bone gelatin from porcine skin gelatin. Journal of Food Composition and Analysis, 16, 477–483.

Hofmann, K., Fischer, K., Mueller, E., & Babel, W. (1999). ELISA test for cooked meat species identification on gelatine and gelatine products. Food/Nahrung, 43, 406–409.

Hunter, G. K., Nyburg, S. C., & Pritzker, K. P. H. (1986). Hydroxyapatite formation in collagen, gelatin, and agarose. Colloid Related Research, 6, 229–238.

Kagan, H. M. (2000). Intra-and extracellular enzymes of collagen biosynthesis as biological and chemical targets in the control of fibrosis. Acta Tropica, 77, 147–152.

Karim, A. A., & Bhat, R. (2009). Fish gelatin: properties, challenges, and prospects as an alternative to mammalian gelatins. Food Hydrocolloids, 23, 563–576.

Kobayashi, T. (1996). Properties and functions of gelatin. Foods & Food Ingredients Journal of Japan, 170, 82–88.

Li, B., Chen, F., Wang, X., Ji, B., & Wu, Y. (2007). Isolation and identification of antioxidative peptides from porcine collagen hydrolysate by consecutive chromatography and electrospray ionization-mass spectrometry. Food Chemistry, 102, 1135–1143.

Manual of Methods of Analysis of Foods (Milk and Milk Products). (2005). Directorate General of Health Service Ministry of Health and Family Welfare Government of India, New Delhi, 17.

Mizuno, K., Hayashi, T., & Bächinger, H. P. (2003). Hydroxylation-induced stabilization of the collagen triple helix. Journal of Biological Chemistry, 278, 32373.

Muyonga, J. H., Cole, C. G. B., & Duodu, K. G. (2004). Fourier transform infrared (FTIR) spectroscopy study of acid soluble collagen and gelatin from skins and bones of young and adult Nile perch (Lates niloticus). Food Chemistry, 86, 325–332.

Nemati, M., Oveisi, M., Abdollahi, H., & Sabzevari, O. (2004). Differentiation of bovine and porcine gelatins using principal component analysis. Journal of Pharmaceutical and Biomedical Analysis, 34, 485–492.

Ocana, M. F., Neubert, H., Przyborowsk, A., Parker, R., Bramley, P., & Patel, R. (2004). BSE control: detection of gelatin-derived peptides in animal feed by mass spectrometry. Analyst, 129, 111–115.

.conclusion..

  • Considering the fact that there is no-well-established analytical method available to confirm the inclusion or exclusion of certain animal materials in gelatin added in the food products; therefore, it was necessary to develop analytical methods intended to control the species origin of gelatin.

  • Based from the study, it was possible to differentiate porcine and bovine gelatin specific marker peptides using nano- UPLC-ESI-q-TOF-MSE based data independent acquisition technique.

  • The methodology has been proven to be useful in gelatin specification that works even in the case of gelatin mixtures of bovine and porcine origin, but further work is needed to develop a method to quantitative mixture ratios, therefore, we are now working on the method to quantify gelatin mixtures.

  • The species specific gelatin peptides can be used for quantitative purposes, but will require an exclusion list to eliminate common peptides.

Learn more about creating dynamic, engaging presentations with Prezi